14 Commits

Author SHA1 Message Date
Felipe Cardoso
60ebeaa582 test(safety): add comprehensive tests for safety framework modules
Add tests to improve backend coverage from 85% to 93%:

- test_audit.py: 60 tests for AuditLogger (20% -> 99%)
  - Hash chain integrity, sanitization, retention, handlers
  - Fixed bug: hash chain modification after event creation
  - Fixed bug: verification not using correct prev_hash

- test_hitl.py: Tests for HITL manager (0% -> 100%)
- test_permissions.py: Tests for permissions manager (0% -> 99%)
- test_rollback.py: Tests for rollback manager (0% -> 100%)
- test_metrics.py: Tests for metrics collector (0% -> 100%)
- test_mcp_integration.py: Tests for MCP safety wrapper (0% -> 100%)
- test_validation.py: Additional cache and edge case tests (76% -> 100%)
- test_scoring.py: Lock cleanup and edge case tests (78% -> 91%)

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2026-01-04 19:41:54 +01:00
Felipe Cardoso
758052dcff feat(context): improve budget validation and XML safety in ranking and Claude adapter
- Added stricter budget validation in ContextRanker with explicit error handling for invalid configurations.
- Introduced `_get_valid_token_count()` helper to validate and safeguard token counts.
- Enhanced XML escaping in Claude adapter to prevent injection risks from scores and unhandled content.
2026-01-04 16:02:18 +01:00
Felipe Cardoso
1628eacf2b feat(context): enhance timeout handling, tenant isolation, and budget management
- Added timeout enforcement for token counting, scoring, and compression with detailed error handling.
- Introduced tenant isolation in context caching using project and agent identifiers.
- Enhanced budget management with stricter checks for critical context overspending and buffer limitations.
- Optimized per-context locking with cleanup to prevent memory leaks in concurrent environments.
- Updated default assembly timeout settings for improved performance and reliability.
- Improved XML escaping in Claude adapter for safety against injection attacks.
- Standardized token estimation using model-specific ratios.
2026-01-04 15:52:50 +01:00
Felipe Cardoso
2bea057fb1 chore(context): refactor for consistency, optimize formatting, and simplify logic
- Cleaned up unnecessary comments in `__all__` definitions for better readability.
- Adjusted indentation and formatting across modules for improved clarity (e.g., long lines, logical grouping).
- Simplified conditional expressions and inline comments for context scoring and ranking.
- Replaced some hard-coded values with type-safe annotations (e.g., `ClassVar`).
- Removed unused imports and ensured consistent usage across test files.
- Updated `test_score_not_cached_on_context` to clarify caching behavior.
- Improved truncation strategy logic and marker handling.
2026-01-04 15:23:14 +01:00
Felipe Cardoso
9e54f16e56 test(context): add edge case tests for truncation and scoring concurrency
- Add tests for truncation edge cases, including zero tokens, short content, and marker handling.
- Add concurrency tests for scoring to verify per-context locking and handling of multiple contexts.
2026-01-04 12:38:04 +01:00
Felipe Cardoso
96e6400bd8 feat(context): enhance performance, caching, and settings management
- Replace hard-coded limits with configurable settings (e.g., cache memory size, truncation strategy, relevance settings).
- Optimize parallel execution in token counting, scoring, and reranking for source diversity.
- Improve caching logic:
  - Add per-context locks for safe parallel scoring.
  - Reuse precomputed fingerprints for cache efficiency.
- Make truncation, scoring, and ranker behaviors fully configurable via settings.
- Add support for middle truncation, context hash-based hashing, and dynamic token limiting.
- Refactor methods for scalability and better error handling.

Tests: Updated all affected components with additional test cases.
2026-01-04 12:37:58 +01:00
Felipe Cardoso
6c7b72f130 chore(context): apply linter fixes and sort imports (#86)
Phase 8 of Context Management Engine - Final Cleanup:

- Sort __all__ exports alphabetically
- Sort imports per isort conventions
- Fix minor linting issues

Final test results:
- 311 context management tests passing
- 2507 total backend tests passing
- 85% code coverage

Context Management Engine is complete with all 8 phases:
1. Foundation: Types, Config, Exceptions
2. Token Budget Management
3. Context Scoring & Ranking
4. Context Assembly Pipeline
5. Model Adapters (Claude, OpenAI)
6. Caching Layer (Redis + in-memory)
7. Main Engine & Integration
8. Testing & Documentation

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2026-01-04 02:46:56 +01:00
Felipe Cardoso
027ebfc332 feat(context): implement main ContextEngine with full integration (#85)
Phase 7 of Context Management Engine - Main Engine:

- Add ContextEngine as main orchestration class
- Integrate all components: calculator, scorer, ranker, compressor, cache
- Add high-level assemble_context() API with:
  - System prompt support
  - Task description support
  - Knowledge Base integration via MCP
  - Conversation history conversion
  - Tool results conversion
  - Custom contexts support
- Add helper methods:
  - get_budget_for_model()
  - count_tokens() with caching
  - invalidate_cache()
  - get_stats()
- Add create_context_engine() factory function

Tests: 26 new tests, 311 total context tests passing

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2026-01-04 02:44:40 +01:00
Felipe Cardoso
c2466ab401 feat(context): implement Redis-based caching layer (#84)
Phase 6 of Context Management Engine - Caching Layer:

- Add ContextCache with Redis integration
- Support fingerprint-based assembled context caching
- Support token count caching (model-specific)
- Support score caching (scorer + context + query)
- Add in-memory fallback with LRU eviction
- Add cache invalidation with pattern matching
- Add cache statistics reporting

Key features:
- Hierarchical cache key structure (ctx:type:hash)
- Automatic TTL expiration
- Memory cache for fast repeated access
- Graceful degradation when Redis unavailable

Tests: 29 new tests, 285 total context tests passing

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2026-01-04 02:41:21 +01:00
Felipe Cardoso
7828d35e06 feat(context): implement model adapters for Claude and OpenAI (#83)
Phase 5 of Context Management Engine - Model Adapters:

- Add ModelAdapter abstract base class with model matching
- Add DefaultAdapter for unknown models (plain text)
- Add ClaudeAdapter with XML-based formatting:
  - <system_instructions> for system context
  - <reference_documents>/<document> for knowledge
  - <conversation_history>/<message> for chat
  - <tool_results>/<tool_result> for tool outputs
  - XML escaping for special characters
- Add OpenAIAdapter with markdown formatting:
  - ## headers for sections
  - ### Source headers for documents
  - **ROLE** bold labels for conversation
  - Code blocks for tool outputs
- Add get_adapter() factory function for model selection

Tests: 33 new tests, 256 total context tests passing

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2026-01-04 02:36:32 +01:00
Felipe Cardoso
6b07e62f00 feat(context): implement assembly pipeline and compression (#82)
Phase 4 of Context Management Engine - Assembly Pipeline:

- Add TruncationStrategy with end/middle/sentence-aware truncation
- Add TruncationResult dataclass for tracking compression metrics
- Add ContextCompressor for type-specific compression
- Add ContextPipeline orchestrating full assembly workflow:
  - Token counting for all contexts
  - Scoring and ranking via ContextRanker
  - Optional compression when budget threshold exceeded
  - Model-specific formatting (XML for Claude, markdown for OpenAI)
- Add PipelineMetrics for performance tracking
- Update AssembledContext with new fields (model, contexts, metadata)
- Add backward compatibility aliases for renamed fields

Tests: 34 new tests, 223 total context tests passing

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2026-01-04 02:32:25 +01:00
Felipe Cardoso
0d2005ddcb feat(context): implement context scoring and ranking (Phase 3)
Add comprehensive scoring system with three strategies:
- RelevanceScorer: Semantic similarity with keyword fallback
- RecencyScorer: Exponential decay with type-specific half-lives
- PriorityScorer: Priority-based scoring with type bonuses

Implement CompositeScorer combining all strategies with configurable
weights (default: 50% relevance, 30% recency, 20% priority).

Add ContextRanker for budget-aware context selection with:
- Greedy selection algorithm respecting token budgets
- CRITICAL priority contexts always included
- Diversity reranking to prevent source dominance
- Comprehensive selection statistics

68 tests covering all scoring and ranking functionality.

Part of #61 - Context Management Engine

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2026-01-04 02:24:06 +01:00
Felipe Cardoso
dfa75e682e feat(context): implement token budget management (Phase 2)
Add TokenCalculator with LLM Gateway integration for accurate token
counting with in-memory caching and fallback character-based estimation.
Implement TokenBudget for tracking allocations per context type with
budget enforcement, and BudgetAllocator for creating budgets based on
model context window sizes.

- TokenCalculator: MCP integration, caching, model-specific ratios
- TokenBudget: allocation tracking, can_fit/allocate/deallocate/reset
- BudgetAllocator: model context sizes, budget creation and adjustment
- 35 comprehensive tests covering all budget functionality

Part of #61 - Context Management Engine

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2026-01-04 02:13:23 +01:00
Felipe Cardoso
22ecb5e989 feat(context): Phase 1 - Foundation types, config and exceptions (#79)
Implements the foundation for Context Management Engine:

Types (backend/app/services/context/types/):
- BaseContext: Abstract base with ID, content, priority, scoring
- SystemContext: System prompts, personas, instructions
- KnowledgeContext: RAG results from Knowledge Base MCP
- ConversationContext: Chat history with role support
- TaskContext: Task/issue context with acceptance criteria
- ToolContext: Tool definitions and execution results
- AssembledContext: Final assembled context result

Configuration (config.py):
- Token budget allocation (system 5%, task 10%, knowledge 40%, etc.)
- Scoring weights (relevance 50%, recency 30%, priority 20%)
- Cache settings (TTL, prefix)
- Performance settings (max assembly time, parallel scoring)
- Environment variable overrides with CTX_ prefix

Exceptions (exceptions.py):
- ContextError: Base exception
- BudgetExceededError: Token budget violations
- TokenCountError: Token counting failures
- CompressionError: Compression failures
- AssemblyTimeoutError: Assembly timeout
- ScoringError, FormattingError, CacheError
- ContextNotFoundError, InvalidContextError

All 86 tests pass.

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2026-01-04 02:07:39 +01:00
52 changed files with 17768 additions and 8 deletions

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"""
Context Management Engine
Sophisticated context assembly and optimization for LLM requests.
Provides intelligent context selection, token budget management,
and model-specific formatting.
Usage:
from app.services.context import (
ContextSettings,
get_context_settings,
SystemContext,
KnowledgeContext,
ConversationContext,
TaskContext,
ToolContext,
TokenBudget,
BudgetAllocator,
TokenCalculator,
)
# Get settings
settings = get_context_settings()
# Create budget for a model
allocator = BudgetAllocator(settings)
budget = allocator.create_budget_for_model("claude-3-sonnet")
# Create context instances
system_ctx = SystemContext.create_persona(
name="Code Assistant",
description="You are a helpful code assistant.",
capabilities=["Write code", "Debug issues"],
)
"""
# Budget Management
# Adapters
from .adapters import (
ClaudeAdapter,
DefaultAdapter,
ModelAdapter,
OpenAIAdapter,
get_adapter,
)
# Assembly
from .assembly import (
ContextPipeline,
PipelineMetrics,
)
from .budget import (
BudgetAllocator,
TokenBudget,
TokenCalculator,
)
# Cache
from .cache import ContextCache
# Compression
from .compression import (
ContextCompressor,
TruncationResult,
TruncationStrategy,
)
# Configuration
from .config import (
ContextSettings,
get_context_settings,
get_default_settings,
reset_context_settings,
)
# Engine
from .engine import ContextEngine, create_context_engine
# Exceptions
from .exceptions import (
AssemblyTimeoutError,
BudgetExceededError,
CacheError,
CompressionError,
ContextError,
ContextNotFoundError,
FormattingError,
InvalidContextError,
ScoringError,
TokenCountError,
)
# Prioritization
from .prioritization import (
ContextRanker,
RankingResult,
)
# Scoring
from .scoring import (
BaseScorer,
CompositeScorer,
PriorityScorer,
RecencyScorer,
RelevanceScorer,
ScoredContext,
)
# Types
from .types import (
AssembledContext,
BaseContext,
ContextPriority,
ContextType,
ConversationContext,
KnowledgeContext,
MessageRole,
SystemContext,
TaskComplexity,
TaskContext,
TaskStatus,
ToolContext,
ToolResultStatus,
)
__all__ = [
"AssembledContext",
"AssemblyTimeoutError",
"BaseContext",
"BaseScorer",
"BudgetAllocator",
"BudgetExceededError",
"CacheError",
"ClaudeAdapter",
"CompositeScorer",
"CompressionError",
"ContextCache",
"ContextCompressor",
"ContextEngine",
"ContextError",
"ContextNotFoundError",
"ContextPipeline",
"ContextPriority",
"ContextRanker",
"ContextSettings",
"ContextType",
"ConversationContext",
"DefaultAdapter",
"FormattingError",
"InvalidContextError",
"KnowledgeContext",
"MessageRole",
"ModelAdapter",
"OpenAIAdapter",
"PipelineMetrics",
"PriorityScorer",
"RankingResult",
"RecencyScorer",
"RelevanceScorer",
"ScoredContext",
"ScoringError",
"SystemContext",
"TaskComplexity",
"TaskContext",
"TaskStatus",
"TokenBudget",
"TokenCalculator",
"TokenCountError",
"ToolContext",
"ToolResultStatus",
"TruncationResult",
"TruncationStrategy",
"create_context_engine",
"get_adapter",
"get_context_settings",
"get_default_settings",
"reset_context_settings",
]

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"""
Model Adapters Module.
Provides model-specific context formatting adapters.
"""
from .base import DefaultAdapter, ModelAdapter
from .claude import ClaudeAdapter
from .openai import OpenAIAdapter
def get_adapter(model: str) -> ModelAdapter:
"""
Get the appropriate adapter for a model.
Args:
model: Model name
Returns:
Adapter instance for the model
"""
if ClaudeAdapter.matches_model(model):
return ClaudeAdapter()
elif OpenAIAdapter.matches_model(model):
return OpenAIAdapter()
return DefaultAdapter()
__all__ = [
"ClaudeAdapter",
"DefaultAdapter",
"ModelAdapter",
"OpenAIAdapter",
"get_adapter",
]

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"""
Base Model Adapter.
Abstract base class for model-specific context formatting.
"""
from abc import ABC, abstractmethod
from typing import Any, ClassVar
from ..types import BaseContext, ContextType
class ModelAdapter(ABC):
"""
Abstract base adapter for model-specific context formatting.
Each adapter knows how to format contexts for optimal
understanding by a specific LLM family (Claude, OpenAI, etc.).
"""
# Model name patterns this adapter handles
MODEL_PATTERNS: ClassVar[list[str]] = []
@classmethod
def matches_model(cls, model: str) -> bool:
"""
Check if this adapter handles the given model.
Args:
model: Model name to check
Returns:
True if this adapter handles the model
"""
model_lower = model.lower()
return any(pattern in model_lower for pattern in cls.MODEL_PATTERNS)
@abstractmethod
def format(
self,
contexts: list[BaseContext],
**kwargs: Any,
) -> str:
"""
Format contexts for the target model.
Args:
contexts: List of contexts to format
**kwargs: Additional formatting options
Returns:
Formatted context string
"""
...
@abstractmethod
def format_type(
self,
contexts: list[BaseContext],
context_type: ContextType,
**kwargs: Any,
) -> str:
"""
Format contexts of a specific type.
Args:
contexts: List of contexts of the same type
context_type: The type of contexts
**kwargs: Additional formatting options
Returns:
Formatted string for this context type
"""
...
def get_type_order(self) -> list[ContextType]:
"""
Get the preferred order of context types.
Returns:
List of context types in preferred order
"""
return [
ContextType.SYSTEM,
ContextType.TASK,
ContextType.KNOWLEDGE,
ContextType.CONVERSATION,
ContextType.TOOL,
]
def group_by_type(
self, contexts: list[BaseContext]
) -> dict[ContextType, list[BaseContext]]:
"""
Group contexts by their type.
Args:
contexts: List of contexts to group
Returns:
Dictionary mapping context type to list of contexts
"""
by_type: dict[ContextType, list[BaseContext]] = {}
for context in contexts:
ct = context.get_type()
if ct not in by_type:
by_type[ct] = []
by_type[ct].append(context)
return by_type
def get_separator(self) -> str:
"""
Get the separator between context sections.
Returns:
Separator string
"""
return "\n\n"
class DefaultAdapter(ModelAdapter):
"""
Default adapter for unknown models.
Uses simple plain-text formatting with minimal structure.
"""
MODEL_PATTERNS: ClassVar[list[str]] = [] # Fallback adapter
@classmethod
def matches_model(cls, model: str) -> bool:
"""Always returns True as fallback."""
return True
def format(
self,
contexts: list[BaseContext],
**kwargs: Any,
) -> str:
"""Format contexts as plain text."""
if not contexts:
return ""
by_type = self.group_by_type(contexts)
parts: list[str] = []
for ct in self.get_type_order():
if ct in by_type:
formatted = self.format_type(by_type[ct], ct, **kwargs)
if formatted:
parts.append(formatted)
return self.get_separator().join(parts)
def format_type(
self,
contexts: list[BaseContext],
context_type: ContextType,
**kwargs: Any,
) -> str:
"""Format contexts of a type as plain text."""
if not contexts:
return ""
content = "\n\n".join(c.content for c in contexts)
if context_type == ContextType.SYSTEM:
return content
elif context_type == ContextType.TASK:
return f"Task:\n{content}"
elif context_type == ContextType.KNOWLEDGE:
return f"Reference Information:\n{content}"
elif context_type == ContextType.CONVERSATION:
return f"Previous Conversation:\n{content}"
elif context_type == ContextType.TOOL:
return f"Tool Results:\n{content}"
return content

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"""
Claude Model Adapter.
Provides Claude-specific context formatting using XML tags
which Claude models understand natively.
"""
from typing import Any, ClassVar
from ..types import BaseContext, ContextType
from .base import ModelAdapter
class ClaudeAdapter(ModelAdapter):
"""
Claude-specific context formatting adapter.
Claude models have native understanding of XML structure,
so we use XML tags for clear delineation of context types.
Features:
- XML tags for each context type
- Document structure for knowledge contexts
- Role-based message formatting for conversations
- Tool result wrapping with tool names
"""
MODEL_PATTERNS: ClassVar[list[str]] = ["claude", "anthropic"]
def format(
self,
contexts: list[BaseContext],
**kwargs: Any,
) -> str:
"""
Format contexts for Claude models.
Uses XML tags for structured content that Claude
understands natively.
Args:
contexts: List of contexts to format
**kwargs: Additional formatting options
Returns:
XML-structured context string
"""
if not contexts:
return ""
by_type = self.group_by_type(contexts)
parts: list[str] = []
for ct in self.get_type_order():
if ct in by_type:
formatted = self.format_type(by_type[ct], ct, **kwargs)
if formatted:
parts.append(formatted)
return self.get_separator().join(parts)
def format_type(
self,
contexts: list[BaseContext],
context_type: ContextType,
**kwargs: Any,
) -> str:
"""
Format contexts of a specific type for Claude.
Args:
contexts: List of contexts of the same type
context_type: The type of contexts
**kwargs: Additional formatting options
Returns:
XML-formatted string for this context type
"""
if not contexts:
return ""
if context_type == ContextType.SYSTEM:
return self._format_system(contexts)
elif context_type == ContextType.TASK:
return self._format_task(contexts)
elif context_type == ContextType.KNOWLEDGE:
return self._format_knowledge(contexts)
elif context_type == ContextType.CONVERSATION:
return self._format_conversation(contexts)
elif context_type == ContextType.TOOL:
return self._format_tool(contexts)
# Fallback for any unhandled context types - still escape content
# to prevent XML injection if new types are added without updating adapter
return "\n".join(self._escape_xml_content(c.content) for c in contexts)
def _format_system(self, contexts: list[BaseContext]) -> str:
"""Format system contexts."""
# System prompts are typically admin-controlled, but escape for safety
content = "\n\n".join(self._escape_xml_content(c.content) for c in contexts)
return f"<system_instructions>\n{content}\n</system_instructions>"
def _format_task(self, contexts: list[BaseContext]) -> str:
"""Format task contexts."""
content = "\n\n".join(self._escape_xml_content(c.content) for c in contexts)
return f"<current_task>\n{content}\n</current_task>"
def _format_knowledge(self, contexts: list[BaseContext]) -> str:
"""
Format knowledge contexts as structured documents.
Each knowledge context becomes a document with source attribution.
All content is XML-escaped to prevent injection attacks.
"""
parts = ["<reference_documents>"]
for ctx in contexts:
source = self._escape_xml(ctx.source)
# Escape content to prevent XML injection
content = self._escape_xml_content(ctx.content)
score = ctx.metadata.get("score", ctx.metadata.get("relevance_score", ""))
if score:
# Escape score to prevent XML injection via metadata
escaped_score = self._escape_xml(str(score))
parts.append(
f'<document source="{source}" relevance="{escaped_score}">'
)
else:
parts.append(f'<document source="{source}">')
parts.append(content)
parts.append("</document>")
parts.append("</reference_documents>")
return "\n".join(parts)
def _format_conversation(self, contexts: list[BaseContext]) -> str:
"""
Format conversation contexts as message history.
Uses role-based message tags for clear turn delineation.
All content is XML-escaped to prevent prompt injection.
"""
parts = ["<conversation_history>"]
for ctx in contexts:
role = self._escape_xml(ctx.metadata.get("role", "user"))
# Escape content to prevent prompt injection via fake XML tags
content = self._escape_xml_content(ctx.content)
parts.append(f'<message role="{role}">')
parts.append(content)
parts.append("</message>")
parts.append("</conversation_history>")
return "\n".join(parts)
def _format_tool(self, contexts: list[BaseContext]) -> str:
"""
Format tool contexts as tool results.
Each tool result is wrapped with the tool name.
All content is XML-escaped to prevent injection.
"""
parts = ["<tool_results>"]
for ctx in contexts:
tool_name = self._escape_xml(ctx.metadata.get("tool_name", "unknown"))
status = ctx.metadata.get("status", "")
if status:
parts.append(
f'<tool_result name="{tool_name}" status="{self._escape_xml(status)}">'
)
else:
parts.append(f'<tool_result name="{tool_name}">')
# Escape content to prevent injection
parts.append(self._escape_xml_content(ctx.content))
parts.append("</tool_result>")
parts.append("</tool_results>")
return "\n".join(parts)
@staticmethod
def _escape_xml(text: str) -> str:
"""Escape XML special characters in attribute values."""
return (
text.replace("&", "&amp;")
.replace("<", "&lt;")
.replace(">", "&gt;")
.replace('"', "&quot;")
.replace("'", "&apos;")
)
@staticmethod
def _escape_xml_content(text: str) -> str:
"""
Escape XML special characters in element content.
This prevents XML injection attacks where malicious content
could break out of XML tags or inject fake tags for prompt injection.
Only escapes &, <, > since quotes don't need escaping in content.
Args:
text: Content text to escape
Returns:
XML-safe content string
"""
return text.replace("&", "&amp;").replace("<", "&lt;").replace(">", "&gt;")

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"""
OpenAI Model Adapter.
Provides OpenAI-specific context formatting using markdown
which GPT models understand well.
"""
from typing import Any, ClassVar
from ..types import BaseContext, ContextType
from .base import ModelAdapter
class OpenAIAdapter(ModelAdapter):
"""
OpenAI-specific context formatting adapter.
GPT models work well with markdown formatting,
so we use headers and structured markdown for clarity.
Features:
- Markdown headers for each context type
- Bulleted lists for document sources
- Bold role labels for conversations
- Code blocks for tool outputs
"""
MODEL_PATTERNS: ClassVar[list[str]] = ["gpt", "openai", "o1", "o3"]
def format(
self,
contexts: list[BaseContext],
**kwargs: Any,
) -> str:
"""
Format contexts for OpenAI models.
Uses markdown formatting for structured content.
Args:
contexts: List of contexts to format
**kwargs: Additional formatting options
Returns:
Markdown-structured context string
"""
if not contexts:
return ""
by_type = self.group_by_type(contexts)
parts: list[str] = []
for ct in self.get_type_order():
if ct in by_type:
formatted = self.format_type(by_type[ct], ct, **kwargs)
if formatted:
parts.append(formatted)
return self.get_separator().join(parts)
def format_type(
self,
contexts: list[BaseContext],
context_type: ContextType,
**kwargs: Any,
) -> str:
"""
Format contexts of a specific type for OpenAI.
Args:
contexts: List of contexts of the same type
context_type: The type of contexts
**kwargs: Additional formatting options
Returns:
Markdown-formatted string for this context type
"""
if not contexts:
return ""
if context_type == ContextType.SYSTEM:
return self._format_system(contexts)
elif context_type == ContextType.TASK:
return self._format_task(contexts)
elif context_type == ContextType.KNOWLEDGE:
return self._format_knowledge(contexts)
elif context_type == ContextType.CONVERSATION:
return self._format_conversation(contexts)
elif context_type == ContextType.TOOL:
return self._format_tool(contexts)
return "\n".join(c.content for c in contexts)
def _format_system(self, contexts: list[BaseContext]) -> str:
"""Format system contexts."""
content = "\n\n".join(c.content for c in contexts)
return content
def _format_task(self, contexts: list[BaseContext]) -> str:
"""Format task contexts."""
content = "\n\n".join(c.content for c in contexts)
return f"## Current Task\n\n{content}"
def _format_knowledge(self, contexts: list[BaseContext]) -> str:
"""
Format knowledge contexts as structured documents.
Each knowledge context becomes a section with source attribution.
"""
parts = ["## Reference Documents\n"]
for ctx in contexts:
source = ctx.source
score = ctx.metadata.get("score", ctx.metadata.get("relevance_score", ""))
if score:
parts.append(f"### Source: {source} (relevance: {score})\n")
else:
parts.append(f"### Source: {source}\n")
parts.append(ctx.content)
parts.append("")
return "\n".join(parts)
def _format_conversation(self, contexts: list[BaseContext]) -> str:
"""
Format conversation contexts as message history.
Uses bold role labels for clear turn delineation.
"""
parts = []
for ctx in contexts:
role = ctx.metadata.get("role", "user").upper()
parts.append(f"**{role}**: {ctx.content}")
return "\n\n".join(parts)
def _format_tool(self, contexts: list[BaseContext]) -> str:
"""
Format tool contexts as tool results.
Each tool result is in a code block with the tool name.
"""
parts = ["## Recent Tool Results\n"]
for ctx in contexts:
tool_name = ctx.metadata.get("tool_name", "unknown")
status = ctx.metadata.get("status", "")
if status:
parts.append(f"### Tool: {tool_name} ({status})\n")
else:
parts.append(f"### Tool: {tool_name}\n")
parts.append(f"```\n{ctx.content}\n```")
parts.append("")
return "\n".join(parts)

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"""
Context Assembly Module.
Provides the assembly pipeline and formatting.
"""
from .pipeline import ContextPipeline, PipelineMetrics
__all__ = [
"ContextPipeline",
"PipelineMetrics",
]

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"""
Context Assembly Pipeline.
Orchestrates the full context assembly workflow:
Gather → Count → Score → Rank → Compress → Format
"""
import asyncio
import logging
import time
from dataclasses import dataclass, field
from datetime import UTC, datetime
from typing import TYPE_CHECKING, Any
from ..adapters import get_adapter
from ..budget import BudgetAllocator, TokenBudget, TokenCalculator
from ..compression.truncation import ContextCompressor
from ..config import ContextSettings, get_context_settings
from ..exceptions import AssemblyTimeoutError
from ..prioritization import ContextRanker
from ..scoring import CompositeScorer
from ..types import AssembledContext, BaseContext, ContextType
if TYPE_CHECKING:
from app.services.mcp.client_manager import MCPClientManager
logger = logging.getLogger(__name__)
@dataclass
class PipelineMetrics:
"""Metrics from pipeline execution."""
start_time: datetime = field(default_factory=lambda: datetime.now(UTC))
end_time: datetime | None = None
total_contexts: int = 0
selected_contexts: int = 0
excluded_contexts: int = 0
compressed_contexts: int = 0
total_tokens: int = 0
assembly_time_ms: float = 0.0
scoring_time_ms: float = 0.0
compression_time_ms: float = 0.0
formatting_time_ms: float = 0.0
def to_dict(self) -> dict[str, Any]:
"""Convert to dictionary."""
return {
"start_time": self.start_time.isoformat(),
"end_time": self.end_time.isoformat() if self.end_time else None,
"total_contexts": self.total_contexts,
"selected_contexts": self.selected_contexts,
"excluded_contexts": self.excluded_contexts,
"compressed_contexts": self.compressed_contexts,
"total_tokens": self.total_tokens,
"assembly_time_ms": round(self.assembly_time_ms, 2),
"scoring_time_ms": round(self.scoring_time_ms, 2),
"compression_time_ms": round(self.compression_time_ms, 2),
"formatting_time_ms": round(self.formatting_time_ms, 2),
}
class ContextPipeline:
"""
Context assembly pipeline.
Orchestrates the full workflow of context assembly:
1. Validate and count tokens for all contexts
2. Score contexts based on relevance, recency, and priority
3. Rank and select contexts within budget
4. Compress if needed to fit remaining budget
5. Format for the target model
"""
def __init__(
self,
mcp_manager: "MCPClientManager | None" = None,
settings: ContextSettings | None = None,
calculator: TokenCalculator | None = None,
scorer: CompositeScorer | None = None,
ranker: ContextRanker | None = None,
compressor: ContextCompressor | None = None,
) -> None:
"""
Initialize the context pipeline.
Args:
mcp_manager: MCP client manager for LLM Gateway integration
settings: Context settings
calculator: Token calculator
scorer: Context scorer
ranker: Context ranker
compressor: Context compressor
"""
self._settings = settings or get_context_settings()
self._mcp = mcp_manager
# Initialize components
self._calculator = calculator or TokenCalculator(mcp_manager=mcp_manager)
self._scorer = scorer or CompositeScorer(
mcp_manager=mcp_manager, settings=self._settings
)
self._ranker = ranker or ContextRanker(
scorer=self._scorer, calculator=self._calculator
)
self._compressor = compressor or ContextCompressor(calculator=self._calculator)
self._allocator = BudgetAllocator(self._settings)
def set_mcp_manager(self, mcp_manager: "MCPClientManager") -> None:
"""Set MCP manager for all components."""
self._mcp = mcp_manager
self._calculator.set_mcp_manager(mcp_manager)
self._scorer.set_mcp_manager(mcp_manager)
async def assemble(
self,
contexts: list[BaseContext],
query: str,
model: str,
max_tokens: int | None = None,
custom_budget: TokenBudget | None = None,
compress: bool = True,
format_output: bool = True,
timeout_ms: int | None = None,
) -> AssembledContext:
"""
Assemble context for an LLM request.
This is the main entry point for context assembly.
Args:
contexts: List of contexts to assemble
query: Query to optimize for
model: Target model name
max_tokens: Maximum total tokens (uses model default if None)
custom_budget: Optional pre-configured budget
compress: Whether to compress oversized contexts
format_output: Whether to format the final output
timeout_ms: Maximum assembly time in milliseconds
Returns:
AssembledContext with optimized content
Raises:
AssemblyTimeoutError: If assembly exceeds timeout
"""
timeout = timeout_ms or self._settings.max_assembly_time_ms
start = time.perf_counter()
metrics = PipelineMetrics(total_contexts=len(contexts))
try:
# Create or use budget
if custom_budget:
budget = custom_budget
elif max_tokens:
budget = self._allocator.create_budget(max_tokens)
else:
budget = self._allocator.create_budget_for_model(model)
# 1. Count tokens for all contexts (with timeout enforcement)
try:
await asyncio.wait_for(
self._ensure_token_counts(contexts, model),
timeout=self._remaining_timeout(start, timeout),
)
except TimeoutError:
elapsed_ms = (time.perf_counter() - start) * 1000
raise AssemblyTimeoutError(
message="Context assembly timed out during token counting",
elapsed_ms=elapsed_ms,
timeout_ms=timeout,
)
# Check timeout (handles edge case where operation finished just at limit)
self._check_timeout(start, timeout, "token counting")
# 2. Score and rank contexts (with timeout enforcement)
scoring_start = time.perf_counter()
try:
ranking_result = await asyncio.wait_for(
self._ranker.rank(
contexts=contexts,
query=query,
budget=budget,
model=model,
),
timeout=self._remaining_timeout(start, timeout),
)
except TimeoutError:
elapsed_ms = (time.perf_counter() - start) * 1000
raise AssemblyTimeoutError(
message="Context assembly timed out during scoring/ranking",
elapsed_ms=elapsed_ms,
timeout_ms=timeout,
)
metrics.scoring_time_ms = (time.perf_counter() - scoring_start) * 1000
selected_contexts = ranking_result.selected_contexts
metrics.selected_contexts = len(selected_contexts)
metrics.excluded_contexts = len(ranking_result.excluded)
# Check timeout
self._check_timeout(start, timeout, "scoring")
# 3. Compress if needed and enabled (with timeout enforcement)
if compress and self._needs_compression(selected_contexts, budget):
compression_start = time.perf_counter()
try:
selected_contexts = await asyncio.wait_for(
self._compressor.compress_contexts(
selected_contexts, budget, model
),
timeout=self._remaining_timeout(start, timeout),
)
except TimeoutError:
elapsed_ms = (time.perf_counter() - start) * 1000
raise AssemblyTimeoutError(
message="Context assembly timed out during compression",
elapsed_ms=elapsed_ms,
timeout_ms=timeout,
)
metrics.compression_time_ms = (
time.perf_counter() - compression_start
) * 1000
metrics.compressed_contexts = sum(
1 for c in selected_contexts if c.metadata.get("truncated", False)
)
# Check timeout
self._check_timeout(start, timeout, "compression")
# 4. Format output
formatting_start = time.perf_counter()
if format_output:
formatted_content = self._format_contexts(selected_contexts, model)
else:
formatted_content = "\n\n".join(c.content for c in selected_contexts)
metrics.formatting_time_ms = (time.perf_counter() - formatting_start) * 1000
# Calculate final metrics
total_tokens = sum(c.token_count or 0 for c in selected_contexts)
metrics.total_tokens = total_tokens
metrics.assembly_time_ms = (time.perf_counter() - start) * 1000
metrics.end_time = datetime.now(UTC)
return AssembledContext(
content=formatted_content,
total_tokens=total_tokens,
context_count=len(selected_contexts),
assembly_time_ms=metrics.assembly_time_ms,
model=model,
contexts=selected_contexts,
excluded_count=metrics.excluded_contexts,
metadata={
"metrics": metrics.to_dict(),
"query": query,
"budget": budget.to_dict(),
},
)
except AssemblyTimeoutError:
raise
except Exception as e:
logger.error(f"Context assembly failed: {e}", exc_info=True)
raise
async def _ensure_token_counts(
self,
contexts: list[BaseContext],
model: str | None = None,
) -> None:
"""Ensure all contexts have token counts."""
tasks = []
for context in contexts:
if context.token_count is None:
tasks.append(self._count_and_set(context, model))
if tasks:
await asyncio.gather(*tasks)
async def _count_and_set(
self,
context: BaseContext,
model: str | None = None,
) -> None:
"""Count tokens and set on context."""
count = await self._calculator.count_tokens(context.content, model)
context.token_count = count
def _needs_compression(
self,
contexts: list[BaseContext],
budget: TokenBudget,
) -> bool:
"""Check if any contexts exceed their type budget."""
# Group by type and check totals
by_type: dict[ContextType, int] = {}
for context in contexts:
ct = context.get_type()
by_type[ct] = by_type.get(ct, 0) + (context.token_count or 0)
for ct, total in by_type.items():
if total > budget.get_allocation(ct):
return True
# Also check if utilization exceeds threshold
return budget.utilization() > self._settings.compression_threshold
def _format_contexts(
self,
contexts: list[BaseContext],
model: str,
) -> str:
"""
Format contexts for the target model.
Uses model-specific adapters (ClaudeAdapter, OpenAIAdapter, etc.)
to format contexts optimally for each model family.
Args:
contexts: Contexts to format
model: Target model name
Returns:
Formatted context string
"""
adapter = get_adapter(model)
return adapter.format(contexts)
def _check_timeout(
self,
start: float,
timeout_ms: int,
phase: str,
) -> None:
"""Check if timeout exceeded and raise if so."""
elapsed_ms = (time.perf_counter() - start) * 1000
if elapsed_ms >= timeout_ms:
raise AssemblyTimeoutError(
message=f"Context assembly timed out during {phase}",
elapsed_ms=elapsed_ms,
timeout_ms=timeout_ms,
)
def _remaining_timeout(self, start: float, timeout_ms: int) -> float:
"""
Calculate remaining timeout in seconds for asyncio.wait_for.
Returns at least a small positive value to avoid immediate timeout
edge cases with wait_for.
Args:
start: Start time from time.perf_counter()
timeout_ms: Total timeout in milliseconds
Returns:
Remaining timeout in seconds (minimum 0.001)
"""
elapsed_ms = (time.perf_counter() - start) * 1000
remaining_ms = timeout_ms - elapsed_ms
# Return at least 1ms to avoid zero/negative timeout edge cases
return max(remaining_ms / 1000.0, 0.001)

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"""
Token Budget Management Module.
Provides token counting and budget allocation.
"""
from .allocator import BudgetAllocator, TokenBudget
from .calculator import TokenCalculator
__all__ = [
"BudgetAllocator",
"TokenBudget",
"TokenCalculator",
]

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"""
Token Budget Allocator for Context Management.
Manages token budget allocation across context types.
"""
from dataclasses import dataclass, field
from typing import Any
from ..config import ContextSettings, get_context_settings
from ..exceptions import BudgetExceededError
from ..types import ContextType
@dataclass
class TokenBudget:
"""
Token budget allocation and tracking.
Tracks allocated tokens per context type and
monitors usage to prevent overflows.
"""
# Total budget
total: int
# Allocated per type
system: int = 0
task: int = 0
knowledge: int = 0
conversation: int = 0
tools: int = 0
response_reserve: int = 0
buffer: int = 0
# Usage tracking
used: dict[str, int] = field(default_factory=dict)
def __post_init__(self) -> None:
"""Initialize usage tracking."""
if not self.used:
self.used = {ct.value: 0 for ct in ContextType}
def get_allocation(self, context_type: ContextType | str) -> int:
"""
Get allocated tokens for a context type.
Args:
context_type: Context type to get allocation for
Returns:
Allocated token count
"""
if isinstance(context_type, ContextType):
context_type = context_type.value
allocation_map = {
"system": self.system,
"task": self.task,
"knowledge": self.knowledge,
"conversation": self.conversation,
"tool": self.tools,
}
return allocation_map.get(context_type, 0)
def get_used(self, context_type: ContextType | str) -> int:
"""
Get used tokens for a context type.
Args:
context_type: Context type to check
Returns:
Used token count
"""
if isinstance(context_type, ContextType):
context_type = context_type.value
return self.used.get(context_type, 0)
def remaining(self, context_type: ContextType | str) -> int:
"""
Get remaining tokens for a context type.
Args:
context_type: Context type to check
Returns:
Remaining token count
"""
allocated = self.get_allocation(context_type)
used = self.get_used(context_type)
return max(0, allocated - used)
def total_remaining(self) -> int:
"""
Get total remaining tokens across all types.
Returns:
Total remaining tokens
"""
total_used = sum(self.used.values())
usable = self.total - self.response_reserve - self.buffer
return max(0, usable - total_used)
def total_used(self) -> int:
"""
Get total used tokens.
Returns:
Total used tokens
"""
return sum(self.used.values())
def can_fit(self, context_type: ContextType | str, tokens: int) -> bool:
"""
Check if tokens fit within budget for a type.
Args:
context_type: Context type to check
tokens: Number of tokens to fit
Returns:
True if tokens fit within remaining budget
"""
return tokens <= self.remaining(context_type)
def allocate(
self,
context_type: ContextType | str,
tokens: int,
force: bool = False,
) -> bool:
"""
Allocate (use) tokens from a context type's budget.
Args:
context_type: Context type to allocate from
tokens: Number of tokens to allocate
force: If True, allow exceeding budget
Returns:
True if allocation succeeded
Raises:
BudgetExceededError: If tokens exceed budget and force=False
"""
if isinstance(context_type, ContextType):
context_type = context_type.value
if not force and not self.can_fit(context_type, tokens):
raise BudgetExceededError(
message=f"Token budget exceeded for {context_type}",
allocated=self.get_allocation(context_type),
requested=self.get_used(context_type) + tokens,
context_type=context_type,
)
self.used[context_type] = self.used.get(context_type, 0) + tokens
return True
def deallocate(
self,
context_type: ContextType | str,
tokens: int,
) -> None:
"""
Deallocate (return) tokens to a context type's budget.
Args:
context_type: Context type to return to
tokens: Number of tokens to return
"""
if isinstance(context_type, ContextType):
context_type = context_type.value
current = self.used.get(context_type, 0)
self.used[context_type] = max(0, current - tokens)
def reset(self) -> None:
"""Reset all usage tracking."""
self.used = {ct.value: 0 for ct in ContextType}
def utilization(self, context_type: ContextType | str | None = None) -> float:
"""
Get budget utilization percentage.
Args:
context_type: Specific type or None for total
Returns:
Utilization as a fraction (0.0 to 1.0+)
"""
if context_type is None:
usable = self.total - self.response_reserve - self.buffer
if usable <= 0:
return 0.0
return self.total_used() / usable
allocated = self.get_allocation(context_type)
if allocated <= 0:
return 0.0
return self.get_used(context_type) / allocated
def to_dict(self) -> dict[str, Any]:
"""Convert budget to dictionary."""
return {
"total": self.total,
"allocations": {
"system": self.system,
"task": self.task,
"knowledge": self.knowledge,
"conversation": self.conversation,
"tools": self.tools,
"response_reserve": self.response_reserve,
"buffer": self.buffer,
},
"used": dict(self.used),
"remaining": {ct.value: self.remaining(ct) for ct in ContextType},
"total_used": self.total_used(),
"total_remaining": self.total_remaining(),
"utilization": round(self.utilization(), 3),
}
class BudgetAllocator:
"""
Budget allocator for context management.
Creates token budgets based on configuration and
model context window sizes.
"""
def __init__(self, settings: ContextSettings | None = None) -> None:
"""
Initialize budget allocator.
Args:
settings: Context settings (uses default if None)
"""
self._settings = settings or get_context_settings()
def create_budget(
self,
total_tokens: int,
custom_allocations: dict[str, float] | None = None,
) -> TokenBudget:
"""
Create a token budget with allocations.
Args:
total_tokens: Total available tokens
custom_allocations: Optional custom allocation percentages
Returns:
TokenBudget with allocations set
"""
# Use custom or default allocations
if custom_allocations:
alloc = custom_allocations
else:
alloc = self._settings.get_budget_allocation()
return TokenBudget(
total=total_tokens,
system=int(total_tokens * alloc.get("system", 0.05)),
task=int(total_tokens * alloc.get("task", 0.10)),
knowledge=int(total_tokens * alloc.get("knowledge", 0.40)),
conversation=int(total_tokens * alloc.get("conversation", 0.20)),
tools=int(total_tokens * alloc.get("tools", 0.05)),
response_reserve=int(total_tokens * alloc.get("response", 0.15)),
buffer=int(total_tokens * alloc.get("buffer", 0.05)),
)
def adjust_budget(
self,
budget: TokenBudget,
context_type: ContextType | str,
adjustment: int,
) -> TokenBudget:
"""
Adjust a specific allocation in a budget.
Takes tokens from buffer and adds to specified type.
Args:
budget: Budget to adjust
context_type: Type to adjust
adjustment: Positive to increase, negative to decrease
Returns:
Adjusted budget
"""
if isinstance(context_type, ContextType):
context_type = context_type.value
# Calculate adjustment (limited by buffer for increases, by current allocation for decreases)
if adjustment > 0:
# Taking from buffer - limited by available buffer
actual_adjustment = min(adjustment, budget.buffer)
budget.buffer -= actual_adjustment
else:
# Returning to buffer - limited by current allocation of target type
current_allocation = budget.get_allocation(context_type)
# Can't return more than current allocation
actual_adjustment = max(adjustment, -current_allocation)
# Add returned tokens back to buffer (adjustment is negative, so subtract)
budget.buffer -= actual_adjustment
# Apply to target type
if context_type == "system":
budget.system = max(0, budget.system + actual_adjustment)
elif context_type == "task":
budget.task = max(0, budget.task + actual_adjustment)
elif context_type == "knowledge":
budget.knowledge = max(0, budget.knowledge + actual_adjustment)
elif context_type == "conversation":
budget.conversation = max(0, budget.conversation + actual_adjustment)
elif context_type == "tool":
budget.tools = max(0, budget.tools + actual_adjustment)
return budget
def rebalance_budget(
self,
budget: TokenBudget,
prioritize: list[ContextType] | None = None,
) -> TokenBudget:
"""
Rebalance budget based on actual usage.
Moves unused allocations to prioritized types.
Args:
budget: Budget to rebalance
prioritize: Types to prioritize (in order)
Returns:
Rebalanced budget
"""
if prioritize is None:
prioritize = [ContextType.KNOWLEDGE, ContextType.TASK, ContextType.SYSTEM]
# Calculate unused tokens per type
unused: dict[str, int] = {}
for ct in ContextType:
remaining = budget.remaining(ct)
if remaining > 0:
unused[ct.value] = remaining
# Calculate total reclaimable (excluding prioritized types)
prioritize_values = {ct.value for ct in prioritize}
reclaimable = sum(
tokens for ct, tokens in unused.items() if ct not in prioritize_values
)
# Redistribute to prioritized types that are near capacity
for ct in prioritize:
utilization = budget.utilization(ct)
if utilization > 0.8: # Near capacity
# Give more tokens from reclaimable pool
bonus = min(reclaimable, budget.get_allocation(ct) // 2)
self.adjust_budget(budget, ct, bonus)
reclaimable -= bonus
if reclaimable <= 0:
break
return budget
def get_model_context_size(self, model: str) -> int:
"""
Get context window size for a model.
Args:
model: Model name
Returns:
Context window size in tokens
"""
# Common model context sizes
context_sizes = {
"claude-3-opus": 200000,
"claude-3-sonnet": 200000,
"claude-3-haiku": 200000,
"claude-3-5-sonnet": 200000,
"claude-3-5-haiku": 200000,
"claude-opus-4": 200000,
"gpt-4-turbo": 128000,
"gpt-4": 8192,
"gpt-4-32k": 32768,
"gpt-4o": 128000,
"gpt-4o-mini": 128000,
"gpt-3.5-turbo": 16385,
"gemini-1.5-pro": 2000000,
"gemini-1.5-flash": 1000000,
"gemini-2.0-flash": 1000000,
"qwen-plus": 32000,
"qwen-turbo": 8000,
"deepseek-chat": 64000,
"deepseek-reasoner": 64000,
}
# Check exact match first
model_lower = model.lower()
if model_lower in context_sizes:
return context_sizes[model_lower]
# Check prefix match
for model_name, size in context_sizes.items():
if model_lower.startswith(model_name):
return size
# Default fallback
return 8192
def create_budget_for_model(
self,
model: str,
custom_allocations: dict[str, float] | None = None,
) -> TokenBudget:
"""
Create a budget based on model's context window.
Args:
model: Model name
custom_allocations: Optional custom allocation percentages
Returns:
TokenBudget sized for the model
"""
context_size = self.get_model_context_size(model)
return self.create_budget(context_size, custom_allocations)

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"""
Token Calculator for Context Management.
Provides token counting with caching and fallback estimation.
Integrates with LLM Gateway for accurate counts.
"""
import hashlib
import logging
from typing import TYPE_CHECKING, Any, ClassVar, Protocol
if TYPE_CHECKING:
from app.services.mcp.client_manager import MCPClientManager
logger = logging.getLogger(__name__)
class TokenCounterProtocol(Protocol):
"""Protocol for token counting implementations."""
async def count_tokens(
self,
text: str,
model: str | None = None,
) -> int:
"""Count tokens in text."""
...
class TokenCalculator:
"""
Token calculator with LLM Gateway integration.
Features:
- In-memory caching for repeated text
- Fallback to character-based estimation
- Model-specific counting when possible
The calculator uses the LLM Gateway's count_tokens tool
for accurate counting, with a local cache to avoid
repeated calls for the same content.
"""
# Default characters per token ratio for estimation
DEFAULT_CHARS_PER_TOKEN: ClassVar[float] = 4.0
# Model-specific ratios (more accurate estimation)
MODEL_CHAR_RATIOS: ClassVar[dict[str, float]] = {
"claude": 3.5,
"gpt-4": 4.0,
"gpt-3.5": 4.0,
"gemini": 4.0,
}
def __init__(
self,
mcp_manager: "MCPClientManager | None" = None,
project_id: str = "system",
agent_id: str = "context-engine",
cache_enabled: bool = True,
cache_max_size: int = 10000,
) -> None:
"""
Initialize token calculator.
Args:
mcp_manager: MCP client manager for LLM Gateway calls
project_id: Project ID for LLM Gateway calls
agent_id: Agent ID for LLM Gateway calls
cache_enabled: Whether to enable in-memory caching
cache_max_size: Maximum cache entries
"""
self._mcp = mcp_manager
self._project_id = project_id
self._agent_id = agent_id
self._cache_enabled = cache_enabled
self._cache_max_size = cache_max_size
# In-memory cache: hash(model:text) -> token_count
self._cache: dict[str, int] = {}
self._cache_hits = 0
self._cache_misses = 0
def _get_cache_key(self, text: str, model: str | None) -> str:
"""Generate cache key from text and model."""
# Use hash for efficient storage
content = f"{model or 'default'}:{text}"
return hashlib.sha256(content.encode()).hexdigest()[:32]
def _check_cache(self, cache_key: str) -> int | None:
"""Check cache for existing count."""
if not self._cache_enabled:
return None
if cache_key in self._cache:
self._cache_hits += 1
return self._cache[cache_key]
self._cache_misses += 1
return None
def _store_cache(self, cache_key: str, count: int) -> None:
"""Store count in cache."""
if not self._cache_enabled:
return
# Simple LRU-like eviction: remove oldest entries when full
if len(self._cache) >= self._cache_max_size:
# Remove first 10% of entries
entries_to_remove = self._cache_max_size // 10
keys_to_remove = list(self._cache.keys())[:entries_to_remove]
for key in keys_to_remove:
del self._cache[key]
self._cache[cache_key] = count
def estimate_tokens(self, text: str, model: str | None = None) -> int:
"""
Estimate token count based on character count.
This is a fast fallback when LLM Gateway is unavailable.
Args:
text: Text to count
model: Optional model for more accurate ratio
Returns:
Estimated token count
"""
if not text:
return 0
# Get model-specific ratio
ratio = self.DEFAULT_CHARS_PER_TOKEN
if model:
model_lower = model.lower()
for model_prefix, model_ratio in self.MODEL_CHAR_RATIOS.items():
if model_prefix in model_lower:
ratio = model_ratio
break
return max(1, int(len(text) / ratio))
async def count_tokens(
self,
text: str,
model: str | None = None,
) -> int:
"""
Count tokens in text.
Uses LLM Gateway for accurate counts with fallback to estimation.
Args:
text: Text to count
model: Optional model for accurate counting
Returns:
Token count
"""
if not text:
return 0
# Check cache first
cache_key = self._get_cache_key(text, model)
cached = self._check_cache(cache_key)
if cached is not None:
return cached
# Try LLM Gateway
if self._mcp is not None:
try:
result = await self._mcp.call_tool(
server="llm-gateway",
tool="count_tokens",
args={
"project_id": self._project_id,
"agent_id": self._agent_id,
"text": text,
"model": model,
},
)
# Parse result
if result.success and result.data:
count = self._parse_token_count(result.data)
if count is not None:
self._store_cache(cache_key, count)
return count
except Exception as e:
logger.warning(f"LLM Gateway token count failed, using estimation: {e}")
# Fallback to estimation
count = self.estimate_tokens(text, model)
self._store_cache(cache_key, count)
return count
def _parse_token_count(self, data: Any) -> int | None:
"""Parse token count from LLM Gateway response."""
if isinstance(data, dict):
if "token_count" in data:
return int(data["token_count"])
if "tokens" in data:
return int(data["tokens"])
if "count" in data:
return int(data["count"])
if isinstance(data, int):
return data
if isinstance(data, str):
# Try to parse from text content
try:
# Handle {"token_count": 123} or just "123"
import json
parsed = json.loads(data)
if isinstance(parsed, dict) and "token_count" in parsed:
return int(parsed["token_count"])
if isinstance(parsed, int):
return parsed
except (json.JSONDecodeError, ValueError):
# Try direct int conversion
try:
return int(data)
except ValueError:
pass
return None
async def count_tokens_batch(
self,
texts: list[str],
model: str | None = None,
) -> list[int]:
"""
Count tokens for multiple texts.
Efficient batch counting with caching and parallel execution.
Args:
texts: List of texts to count
model: Optional model for accurate counting
Returns:
List of token counts (same order as input)
"""
import asyncio
if not texts:
return []
# Execute all token counts in parallel for better performance
tasks = [self.count_tokens(text, model) for text in texts]
return await asyncio.gather(*tasks)
def clear_cache(self) -> None:
"""Clear the token count cache."""
self._cache.clear()
self._cache_hits = 0
self._cache_misses = 0
def get_cache_stats(self) -> dict[str, Any]:
"""Get cache statistics."""
total = self._cache_hits + self._cache_misses
hit_rate = self._cache_hits / total if total > 0 else 0.0
return {
"enabled": self._cache_enabled,
"size": len(self._cache),
"max_size": self._cache_max_size,
"hits": self._cache_hits,
"misses": self._cache_misses,
"hit_rate": round(hit_rate, 3),
}
def set_mcp_manager(self, mcp_manager: "MCPClientManager") -> None:
"""
Set the MCP manager (for lazy initialization).
Args:
mcp_manager: MCP client manager instance
"""
self._mcp = mcp_manager

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"""
Context Cache Module.
Provides Redis-based caching for assembled contexts.
"""
from .context_cache import ContextCache
__all__ = [
"ContextCache",
]

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"""
Context Cache Implementation.
Provides Redis-based caching for context operations including
assembled contexts, token counts, and scoring results.
"""
import hashlib
import json
import logging
from typing import TYPE_CHECKING, Any
from ..config import ContextSettings, get_context_settings
from ..exceptions import CacheError
from ..types import AssembledContext, BaseContext
if TYPE_CHECKING:
from redis.asyncio import Redis
logger = logging.getLogger(__name__)
class ContextCache:
"""
Redis-based caching for context operations.
Provides caching for:
- Assembled contexts (fingerprint-based)
- Token counts (content hash-based)
- Scoring results (context + query hash-based)
Cache keys use a hierarchical structure:
- ctx:assembled:{fingerprint}
- ctx:tokens:{model}:{content_hash}
- ctx:score:{scorer}:{context_hash}:{query_hash}
"""
def __init__(
self,
redis: "Redis | None" = None,
settings: ContextSettings | None = None,
) -> None:
"""
Initialize the context cache.
Args:
redis: Redis connection (optional for testing)
settings: Cache settings
"""
self._redis = redis
self._settings = settings or get_context_settings()
self._prefix = self._settings.cache_prefix
self._ttl = self._settings.cache_ttl_seconds
# In-memory fallback cache when Redis unavailable
self._memory_cache: dict[str, tuple[str, float]] = {}
self._max_memory_items = self._settings.cache_memory_max_items
def set_redis(self, redis: "Redis") -> None:
"""Set Redis connection."""
self._redis = redis
@property
def is_enabled(self) -> bool:
"""Check if caching is enabled and available."""
return self._settings.cache_enabled and self._redis is not None
def _cache_key(self, *parts: str) -> str:
"""
Build a cache key from parts.
Args:
*parts: Key components
Returns:
Colon-separated cache key
"""
return f"{self._prefix}:{':'.join(parts)}"
@staticmethod
def _hash_content(content: str) -> str:
"""
Compute hash of content for cache key.
Args:
content: Content to hash
Returns:
32-character hex hash
"""
return hashlib.sha256(content.encode()).hexdigest()[:32]
def compute_fingerprint(
self,
contexts: list[BaseContext],
query: str,
model: str,
project_id: str | None = None,
agent_id: str | None = None,
) -> str:
"""
Compute a fingerprint for a context assembly request.
The fingerprint is based on:
- Project and agent IDs (for tenant isolation)
- Context content hash and metadata (not full content for performance)
- Query string
- Target model
SECURITY: project_id and agent_id MUST be included to prevent
cross-tenant cache pollution. Without these, one tenant could
receive cached contexts from another tenant with the same query.
Args:
contexts: List of contexts
query: Query string
model: Model name
project_id: Project ID for tenant isolation
agent_id: Agent ID for tenant isolation
Returns:
32-character hex fingerprint
"""
# Build a deterministic representation using content hashes for performance
# This avoids JSON serializing potentially large content strings
context_data = []
for ctx in contexts:
context_data.append(
{
"type": ctx.get_type().value,
"content_hash": self._hash_content(
ctx.content
), # Hash instead of full content
"source": ctx.source,
"priority": ctx.priority, # Already an int
}
)
data = {
# CRITICAL: Include tenant identifiers for cache isolation
"project_id": project_id or "",
"agent_id": agent_id or "",
"contexts": context_data,
"query": query,
"model": model,
}
content = json.dumps(data, sort_keys=True)
return self._hash_content(content)
async def get_assembled(
self,
fingerprint: str,
) -> AssembledContext | None:
"""
Get cached assembled context by fingerprint.
Args:
fingerprint: Assembly fingerprint
Returns:
Cached AssembledContext or None if not found
"""
if not self.is_enabled:
return None
key = self._cache_key("assembled", fingerprint)
try:
data = await self._redis.get(key) # type: ignore
if data:
logger.debug(f"Cache hit for assembled context: {fingerprint}")
result = AssembledContext.from_json(data)
result.cache_hit = True
result.cache_key = fingerprint
return result
except Exception as e:
logger.warning(f"Cache get error: {e}")
raise CacheError(f"Failed to get assembled context: {e}") from e
return None
async def set_assembled(
self,
fingerprint: str,
context: AssembledContext,
ttl: int | None = None,
) -> None:
"""
Cache an assembled context.
Args:
fingerprint: Assembly fingerprint
context: Assembled context to cache
ttl: Optional TTL override in seconds
"""
if not self.is_enabled:
return
key = self._cache_key("assembled", fingerprint)
expire = ttl or self._ttl
try:
await self._redis.setex(key, expire, context.to_json()) # type: ignore
logger.debug(f"Cached assembled context: {fingerprint}")
except Exception as e:
logger.warning(f"Cache set error: {e}")
raise CacheError(f"Failed to cache assembled context: {e}") from e
async def get_token_count(
self,
content: str,
model: str | None = None,
) -> int | None:
"""
Get cached token count.
Args:
content: Content to look up
model: Model name for model-specific tokenization
Returns:
Cached token count or None if not found
"""
model_key = model or "default"
content_hash = self._hash_content(content)
key = self._cache_key("tokens", model_key, content_hash)
# Try in-memory first
if key in self._memory_cache:
return int(self._memory_cache[key][0])
if not self.is_enabled:
return None
try:
data = await self._redis.get(key) # type: ignore
if data:
count = int(data)
# Store in memory for faster subsequent access
self._set_memory(key, str(count))
return count
except Exception as e:
logger.warning(f"Cache get error for tokens: {e}")
return None
async def set_token_count(
self,
content: str,
count: int,
model: str | None = None,
ttl: int | None = None,
) -> None:
"""
Cache a token count.
Args:
content: Content that was counted
count: Token count
model: Model name
ttl: Optional TTL override in seconds
"""
model_key = model or "default"
content_hash = self._hash_content(content)
key = self._cache_key("tokens", model_key, content_hash)
expire = ttl or self._ttl
# Always store in memory
self._set_memory(key, str(count))
if not self.is_enabled:
return
try:
await self._redis.setex(key, expire, str(count)) # type: ignore
except Exception as e:
logger.warning(f"Cache set error for tokens: {e}")
async def get_score(
self,
scorer_name: str,
context_id: str,
query: str,
) -> float | None:
"""
Get cached score.
Args:
scorer_name: Name of the scorer
context_id: Context identifier
query: Query string
Returns:
Cached score or None if not found
"""
query_hash = self._hash_content(query)[:16]
key = self._cache_key("score", scorer_name, context_id, query_hash)
# Try in-memory first
if key in self._memory_cache:
return float(self._memory_cache[key][0])
if not self.is_enabled:
return None
try:
data = await self._redis.get(key) # type: ignore
if data:
score = float(data)
self._set_memory(key, str(score))
return score
except Exception as e:
logger.warning(f"Cache get error for score: {e}")
return None
async def set_score(
self,
scorer_name: str,
context_id: str,
query: str,
score: float,
ttl: int | None = None,
) -> None:
"""
Cache a score.
Args:
scorer_name: Name of the scorer
context_id: Context identifier
query: Query string
score: Score value
ttl: Optional TTL override in seconds
"""
query_hash = self._hash_content(query)[:16]
key = self._cache_key("score", scorer_name, context_id, query_hash)
expire = ttl or self._ttl
# Always store in memory
self._set_memory(key, str(score))
if not self.is_enabled:
return
try:
await self._redis.setex(key, expire, str(score)) # type: ignore
except Exception as e:
logger.warning(f"Cache set error for score: {e}")
async def invalidate(self, pattern: str) -> int:
"""
Invalidate cache entries matching a pattern.
Args:
pattern: Key pattern (supports * wildcard)
Returns:
Number of keys deleted
"""
if not self.is_enabled:
return 0
full_pattern = self._cache_key(pattern)
deleted = 0
try:
async for key in self._redis.scan_iter(match=full_pattern): # type: ignore
await self._redis.delete(key) # type: ignore
deleted += 1
logger.info(f"Invalidated {deleted} cache entries matching {pattern}")
except Exception as e:
logger.warning(f"Cache invalidation error: {e}")
raise CacheError(f"Failed to invalidate cache: {e}") from e
return deleted
async def clear_all(self) -> int:
"""
Clear all context cache entries.
Returns:
Number of keys deleted
"""
self._memory_cache.clear()
return await self.invalidate("*")
def _set_memory(self, key: str, value: str) -> None:
"""
Set a value in the memory cache.
Uses LRU-style eviction when max items reached.
Args:
key: Cache key
value: Value to store
"""
import time
if len(self._memory_cache) >= self._max_memory_items:
# Evict oldest entries
sorted_keys = sorted(
self._memory_cache.keys(),
key=lambda k: self._memory_cache[k][1],
)
for k in sorted_keys[: len(sorted_keys) // 2]:
del self._memory_cache[k]
self._memory_cache[key] = (value, time.time())
async def get_stats(self) -> dict[str, Any]:
"""
Get cache statistics.
Returns:
Dictionary with cache stats
"""
stats = {
"enabled": self._settings.cache_enabled,
"redis_available": self._redis is not None,
"memory_items": len(self._memory_cache),
"ttl_seconds": self._ttl,
}
if self.is_enabled:
try:
# Get Redis info
info = await self._redis.info("memory") # type: ignore
stats["redis_memory_used"] = info.get("used_memory_human", "unknown")
except Exception as e:
logger.debug(f"Failed to get Redis stats: {e}")
return stats

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"""
Context Compression Module.
Provides truncation and compression strategies.
"""
from .truncation import ContextCompressor, TruncationResult, TruncationStrategy
__all__ = [
"ContextCompressor",
"TruncationResult",
"TruncationStrategy",
]

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"""
Smart Truncation for Context Compression.
Provides intelligent truncation strategies to reduce context size
while preserving the most important information.
"""
import logging
import re
from dataclasses import dataclass
from typing import TYPE_CHECKING
from ..config import ContextSettings, get_context_settings
from ..types import BaseContext, ContextType
if TYPE_CHECKING:
from ..budget import TokenBudget, TokenCalculator
logger = logging.getLogger(__name__)
def _estimate_tokens(text: str, model: str | None = None) -> int:
"""
Estimate token count using model-specific character ratios.
Module-level function for reuse across classes. Uses the same ratios
as TokenCalculator for consistency.
Args:
text: Text to estimate tokens for
model: Optional model name for model-specific ratios
Returns:
Estimated token count (minimum 1)
"""
# Model-specific character ratios (chars per token)
model_ratios = {
"claude": 3.5,
"gpt-4": 4.0,
"gpt-3.5": 4.0,
"gemini": 4.0,
}
default_ratio = 4.0
ratio = default_ratio
if model:
model_lower = model.lower()
for model_prefix, model_ratio in model_ratios.items():
if model_prefix in model_lower:
ratio = model_ratio
break
return max(1, int(len(text) / ratio))
@dataclass
class TruncationResult:
"""Result of truncation operation."""
original_tokens: int
truncated_tokens: int
content: str
truncated: bool
truncation_ratio: float # 0.0 = no truncation, 1.0 = completely removed
@property
def tokens_saved(self) -> int:
"""Calculate tokens saved by truncation."""
return self.original_tokens - self.truncated_tokens
class TruncationStrategy:
"""
Smart truncation strategies for context compression.
Strategies:
1. End truncation: Cut from end (for knowledge/docs)
2. Middle truncation: Keep start and end (for code)
3. Sentence-aware: Truncate at sentence boundaries
4. Semantic chunking: Keep most relevant chunks
"""
def __init__(
self,
calculator: "TokenCalculator | None" = None,
preserve_ratio_start: float | None = None,
min_content_length: int | None = None,
settings: ContextSettings | None = None,
) -> None:
"""
Initialize truncation strategy.
Args:
calculator: Token calculator for accurate counting
preserve_ratio_start: Ratio of content to keep from start (overrides settings)
min_content_length: Minimum characters to preserve (overrides settings)
settings: Context settings (uses global if None)
"""
self._settings = settings or get_context_settings()
self._calculator = calculator
# Use provided values or fall back to settings
self._preserve_ratio_start = (
preserve_ratio_start
if preserve_ratio_start is not None
else self._settings.truncation_preserve_ratio
)
self._min_content_length = (
min_content_length
if min_content_length is not None
else self._settings.truncation_min_content_length
)
@property
def truncation_marker(self) -> str:
"""Get truncation marker from settings."""
return self._settings.truncation_marker
def set_calculator(self, calculator: "TokenCalculator") -> None:
"""Set token calculator."""
self._calculator = calculator
async def truncate_to_tokens(
self,
content: str,
max_tokens: int,
strategy: str = "end",
model: str | None = None,
) -> TruncationResult:
"""
Truncate content to fit within token limit.
Args:
content: Content to truncate
max_tokens: Maximum tokens allowed
strategy: Truncation strategy ('end', 'middle', 'sentence')
model: Model for token counting
Returns:
TruncationResult with truncated content
"""
if not content:
return TruncationResult(
original_tokens=0,
truncated_tokens=0,
content="",
truncated=False,
truncation_ratio=0.0,
)
# Get original token count
original_tokens = await self._count_tokens(content, model)
if original_tokens <= max_tokens:
return TruncationResult(
original_tokens=original_tokens,
truncated_tokens=original_tokens,
content=content,
truncated=False,
truncation_ratio=0.0,
)
# Apply truncation strategy
if strategy == "middle":
truncated = await self._truncate_middle(content, max_tokens, model)
elif strategy == "sentence":
truncated = await self._truncate_sentence(content, max_tokens, model)
else: # "end"
truncated = await self._truncate_end(content, max_tokens, model)
truncated_tokens = await self._count_tokens(truncated, model)
return TruncationResult(
original_tokens=original_tokens,
truncated_tokens=truncated_tokens,
content=truncated,
truncated=True,
truncation_ratio=0.0
if original_tokens == 0
else 1 - (truncated_tokens / original_tokens),
)
async def _truncate_end(
self,
content: str,
max_tokens: int,
model: str | None = None,
) -> str:
"""
Truncate from end of content.
Simple but effective for most content types.
"""
# Binary search for optimal truncation point
marker_tokens = await self._count_tokens(self.truncation_marker, model)
available_tokens = max(0, max_tokens - marker_tokens)
# Edge case: if no tokens available for content, return just the marker
if available_tokens <= 0:
return self.truncation_marker
# Estimate characters per token (guard against division by zero)
content_tokens = await self._count_tokens(content, model)
if content_tokens == 0:
return content + self.truncation_marker
chars_per_token = len(content) / content_tokens
# Start with estimated position
estimated_chars = int(available_tokens * chars_per_token)
truncated = content[:estimated_chars]
# Refine with binary search
low, high = len(truncated) // 2, len(truncated)
best = truncated
for _ in range(5): # Max 5 iterations
mid = (low + high) // 2
candidate = content[:mid]
tokens = await self._count_tokens(candidate, model)
if tokens <= available_tokens:
best = candidate
low = mid + 1
else:
high = mid - 1
return best + self.truncation_marker
async def _truncate_middle(
self,
content: str,
max_tokens: int,
model: str | None = None,
) -> str:
"""
Truncate from middle, keeping start and end.
Good for code or content where context at boundaries matters.
"""
marker_tokens = await self._count_tokens(self.truncation_marker, model)
available_tokens = max_tokens - marker_tokens
# Split between start and end
start_tokens = int(available_tokens * self._preserve_ratio_start)
end_tokens = available_tokens - start_tokens
# Get start portion
start_content = await self._get_content_for_tokens(
content, start_tokens, from_start=True, model=model
)
# Get end portion
end_content = await self._get_content_for_tokens(
content, end_tokens, from_start=False, model=model
)
return start_content + self.truncation_marker + end_content
async def _truncate_sentence(
self,
content: str,
max_tokens: int,
model: str | None = None,
) -> str:
"""
Truncate at sentence boundaries.
Produces cleaner output by not cutting mid-sentence.
"""
# Split into sentences
sentences = re.split(r"(?<=[.!?])\s+", content)
result: list[str] = []
total_tokens = 0
marker_tokens = await self._count_tokens(self.truncation_marker, model)
available = max_tokens - marker_tokens
for sentence in sentences:
sentence_tokens = await self._count_tokens(sentence, model)
if total_tokens + sentence_tokens <= available:
result.append(sentence)
total_tokens += sentence_tokens
else:
break
if len(result) < len(sentences):
return " ".join(result) + self.truncation_marker
return " ".join(result)
async def _get_content_for_tokens(
self,
content: str,
target_tokens: int,
from_start: bool = True,
model: str | None = None,
) -> str:
"""Get portion of content fitting within token limit."""
if target_tokens <= 0:
return ""
current_tokens = await self._count_tokens(content, model)
if current_tokens <= target_tokens:
return content
# Estimate characters (guard against division by zero)
if current_tokens == 0:
return content
chars_per_token = len(content) / current_tokens
estimated_chars = int(target_tokens * chars_per_token)
if from_start:
return content[:estimated_chars]
else:
return content[-estimated_chars:]
async def _count_tokens(self, text: str, model: str | None = None) -> int:
"""Count tokens using calculator or estimation."""
if self._calculator is not None:
return await self._calculator.count_tokens(text, model)
# Fallback estimation with model-specific ratios
return _estimate_tokens(text, model)
class ContextCompressor:
"""
Compresses contexts to fit within budget constraints.
Uses truncation strategies to reduce context size while
preserving the most important information.
"""
def __init__(
self,
truncation: TruncationStrategy | None = None,
calculator: "TokenCalculator | None" = None,
) -> None:
"""
Initialize context compressor.
Args:
truncation: Truncation strategy to use
calculator: Token calculator for counting
"""
self._truncation = truncation or TruncationStrategy(calculator)
self._calculator = calculator
if calculator:
self._truncation.set_calculator(calculator)
def set_calculator(self, calculator: "TokenCalculator") -> None:
"""Set token calculator."""
self._calculator = calculator
self._truncation.set_calculator(calculator)
async def compress_context(
self,
context: BaseContext,
max_tokens: int,
model: str | None = None,
) -> BaseContext:
"""
Compress a single context to fit token limit.
Args:
context: Context to compress
max_tokens: Maximum tokens allowed
model: Model for token counting
Returns:
Compressed context (may be same object if no compression needed)
"""
current_tokens = context.token_count or await self._count_tokens(
context.content, model
)
if current_tokens <= max_tokens:
return context
# Choose strategy based on context type
strategy = self._get_strategy_for_type(context.get_type())
result = await self._truncation.truncate_to_tokens(
content=context.content,
max_tokens=max_tokens,
strategy=strategy,
model=model,
)
# Update context with truncated content
context.content = result.content
context.token_count = result.truncated_tokens
context.metadata["truncated"] = True
context.metadata["original_tokens"] = result.original_tokens
return context
async def compress_contexts(
self,
contexts: list[BaseContext],
budget: "TokenBudget",
model: str | None = None,
) -> list[BaseContext]:
"""
Compress multiple contexts to fit within budget.
Args:
contexts: Contexts to potentially compress
budget: Token budget constraints
model: Model for token counting
Returns:
List of contexts (compressed as needed)
"""
result: list[BaseContext] = []
for context in contexts:
context_type = context.get_type()
remaining = budget.remaining(context_type)
current_tokens = context.token_count or await self._count_tokens(
context.content, model
)
if current_tokens > remaining:
# Need to compress
compressed = await self.compress_context(context, remaining, model)
result.append(compressed)
logger.debug(
f"Compressed {context_type.value} context from "
f"{current_tokens} to {compressed.token_count} tokens"
)
else:
result.append(context)
return result
def _get_strategy_for_type(self, context_type: ContextType) -> str:
"""Get optimal truncation strategy for context type."""
strategies = {
ContextType.SYSTEM: "end", # Keep instructions at start
ContextType.TASK: "end", # Keep task description start
ContextType.KNOWLEDGE: "sentence", # Clean sentence boundaries
ContextType.CONVERSATION: "end", # Keep recent conversation
ContextType.TOOL: "middle", # Keep command and result summary
}
return strategies.get(context_type, "end")
async def _count_tokens(self, text: str, model: str | None = None) -> int:
"""Count tokens using calculator or estimation."""
if self._calculator is not None:
return await self._calculator.count_tokens(text, model)
# Use model-specific estimation for consistency
return _estimate_tokens(text, model)

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"""
Context Management Engine Configuration.
Provides Pydantic settings for context assembly,
token budget allocation, and caching.
"""
import threading
from functools import lru_cache
from typing import Any
from pydantic import Field, field_validator, model_validator
from pydantic_settings import BaseSettings
class ContextSettings(BaseSettings):
"""
Configuration for the Context Management Engine.
All settings can be overridden via environment variables
with the CTX_ prefix.
"""
# Budget allocation percentages (must sum to 1.0)
budget_system: float = Field(
default=0.05,
ge=0.0,
le=1.0,
description="Percentage of budget for system prompts (5%)",
)
budget_task: float = Field(
default=0.10,
ge=0.0,
le=1.0,
description="Percentage of budget for task context (10%)",
)
budget_knowledge: float = Field(
default=0.40,
ge=0.0,
le=1.0,
description="Percentage of budget for RAG/knowledge (40%)",
)
budget_conversation: float = Field(
default=0.20,
ge=0.0,
le=1.0,
description="Percentage of budget for conversation history (20%)",
)
budget_tools: float = Field(
default=0.05,
ge=0.0,
le=1.0,
description="Percentage of budget for tool descriptions (5%)",
)
budget_response: float = Field(
default=0.15,
ge=0.0,
le=1.0,
description="Percentage reserved for response (15%)",
)
budget_buffer: float = Field(
default=0.05,
ge=0.0,
le=1.0,
description="Percentage buffer for safety margin (5%)",
)
# Scoring weights
scoring_relevance_weight: float = Field(
default=0.5,
ge=0.0,
le=1.0,
description="Weight for relevance scoring",
)
scoring_recency_weight: float = Field(
default=0.3,
ge=0.0,
le=1.0,
description="Weight for recency scoring",
)
scoring_priority_weight: float = Field(
default=0.2,
ge=0.0,
le=1.0,
description="Weight for priority scoring",
)
# Recency decay settings
recency_decay_hours: float = Field(
default=24.0,
gt=0.0,
description="Hours until recency score decays to 50%",
)
recency_max_age_hours: float = Field(
default=168.0,
gt=0.0,
description="Hours until context is considered stale (7 days)",
)
# Compression settings
compression_threshold: float = Field(
default=0.8,
ge=0.0,
le=1.0,
description="Compress when budget usage exceeds this percentage",
)
truncation_marker: str = Field(
default="\n\n[...content truncated...]\n\n",
description="Marker text to insert where content was truncated",
)
truncation_preserve_ratio: float = Field(
default=0.7,
ge=0.1,
le=0.9,
description="Ratio of content to preserve from start in middle truncation (0.7 = 70% start, 30% end)",
)
truncation_min_content_length: int = Field(
default=100,
ge=10,
le=1000,
description="Minimum content length in characters before truncation applies",
)
summary_model_group: str = Field(
default="fast",
description="Model group to use for summarization",
)
# Caching settings
cache_enabled: bool = Field(
default=True,
description="Enable Redis caching for assembled contexts",
)
cache_ttl_seconds: int = Field(
default=3600,
ge=60,
le=86400,
description="Cache TTL in seconds (1 hour default, max 24 hours)",
)
cache_prefix: str = Field(
default="ctx",
description="Redis key prefix for context cache",
)
cache_memory_max_items: int = Field(
default=1000,
ge=100,
le=100000,
description="Maximum items in memory fallback cache when Redis unavailable",
)
# Performance settings
max_assembly_time_ms: int = Field(
default=2000,
ge=10,
le=30000,
description="Maximum time for context assembly in milliseconds. "
"Should be high enough to accommodate MCP calls for knowledge retrieval.",
)
parallel_scoring: bool = Field(
default=True,
description="Score contexts in parallel for better performance",
)
max_parallel_scores: int = Field(
default=10,
ge=1,
le=50,
description="Maximum number of contexts to score in parallel",
)
# Knowledge retrieval settings
knowledge_search_type: str = Field(
default="hybrid",
description="Default search type for knowledge retrieval",
)
knowledge_max_results: int = Field(
default=10,
ge=1,
le=50,
description="Maximum knowledge chunks to retrieve",
)
knowledge_min_score: float = Field(
default=0.5,
ge=0.0,
le=1.0,
description="Minimum relevance score for knowledge",
)
# Relevance scoring settings
relevance_keyword_fallback_weight: float = Field(
default=0.5,
ge=0.0,
le=1.0,
description="Maximum score for keyword-based fallback scoring (when semantic unavailable)",
)
relevance_semantic_max_chars: int = Field(
default=2000,
ge=100,
le=10000,
description="Maximum content length in chars for semantic similarity computation",
)
# Diversity/ranking settings
diversity_max_per_source: int = Field(
default=3,
ge=1,
le=20,
description="Maximum contexts from the same source in diversity reranking",
)
# Conversation history settings
conversation_max_turns: int = Field(
default=20,
ge=1,
le=100,
description="Maximum conversation turns to include",
)
conversation_recent_priority: bool = Field(
default=True,
description="Prioritize recent conversation turns",
)
@field_validator("knowledge_search_type")
@classmethod
def validate_search_type(cls, v: str) -> str:
"""Validate search type is valid."""
valid_types = {"semantic", "keyword", "hybrid"}
if v not in valid_types:
raise ValueError(f"search_type must be one of: {valid_types}")
return v
@model_validator(mode="after")
def validate_budget_allocation(self) -> "ContextSettings":
"""Validate that budget percentages sum to 1.0."""
total = (
self.budget_system
+ self.budget_task
+ self.budget_knowledge
+ self.budget_conversation
+ self.budget_tools
+ self.budget_response
+ self.budget_buffer
)
# Allow small floating point error
if abs(total - 1.0) > 0.001:
raise ValueError(
f"Budget percentages must sum to 1.0, got {total:.3f}. "
f"Current allocation: system={self.budget_system}, task={self.budget_task}, "
f"knowledge={self.budget_knowledge}, conversation={self.budget_conversation}, "
f"tools={self.budget_tools}, response={self.budget_response}, buffer={self.budget_buffer}"
)
return self
@model_validator(mode="after")
def validate_scoring_weights(self) -> "ContextSettings":
"""Validate that scoring weights sum to 1.0."""
total = (
self.scoring_relevance_weight
+ self.scoring_recency_weight
+ self.scoring_priority_weight
)
# Allow small floating point error
if abs(total - 1.0) > 0.001:
raise ValueError(
f"Scoring weights must sum to 1.0, got {total:.3f}. "
f"Current weights: relevance={self.scoring_relevance_weight}, "
f"recency={self.scoring_recency_weight}, priority={self.scoring_priority_weight}"
)
return self
def get_budget_allocation(self) -> dict[str, float]:
"""Get budget allocation as a dictionary."""
return {
"system": self.budget_system,
"task": self.budget_task,
"knowledge": self.budget_knowledge,
"conversation": self.budget_conversation,
"tools": self.budget_tools,
"response": self.budget_response,
"buffer": self.budget_buffer,
}
def get_scoring_weights(self) -> dict[str, float]:
"""Get scoring weights as a dictionary."""
return {
"relevance": self.scoring_relevance_weight,
"recency": self.scoring_recency_weight,
"priority": self.scoring_priority_weight,
}
def to_dict(self) -> dict[str, Any]:
"""Convert settings to dictionary for logging/debugging."""
return {
"budget": self.get_budget_allocation(),
"scoring": self.get_scoring_weights(),
"compression": {
"threshold": self.compression_threshold,
"summary_model_group": self.summary_model_group,
"truncation_marker": self.truncation_marker,
"truncation_preserve_ratio": self.truncation_preserve_ratio,
"truncation_min_content_length": self.truncation_min_content_length,
},
"cache": {
"enabled": self.cache_enabled,
"ttl_seconds": self.cache_ttl_seconds,
"prefix": self.cache_prefix,
"memory_max_items": self.cache_memory_max_items,
},
"performance": {
"max_assembly_time_ms": self.max_assembly_time_ms,
"parallel_scoring": self.parallel_scoring,
"max_parallel_scores": self.max_parallel_scores,
},
"knowledge": {
"search_type": self.knowledge_search_type,
"max_results": self.knowledge_max_results,
"min_score": self.knowledge_min_score,
},
"relevance": {
"keyword_fallback_weight": self.relevance_keyword_fallback_weight,
"semantic_max_chars": self.relevance_semantic_max_chars,
},
"diversity": {
"max_per_source": self.diversity_max_per_source,
},
"conversation": {
"max_turns": self.conversation_max_turns,
"recent_priority": self.conversation_recent_priority,
},
}
model_config = {
"env_prefix": "CTX_",
"env_file": "../.env",
"env_file_encoding": "utf-8",
"case_sensitive": False,
"extra": "ignore",
}
# Thread-safe singleton pattern
_settings: ContextSettings | None = None
_settings_lock = threading.Lock()
def get_context_settings() -> ContextSettings:
"""
Get the global ContextSettings instance.
Thread-safe with double-checked locking pattern.
Returns:
ContextSettings instance
"""
global _settings
if _settings is None:
with _settings_lock:
if _settings is None:
_settings = ContextSettings()
return _settings
def reset_context_settings() -> None:
"""
Reset the global settings instance.
Primarily used for testing.
"""
global _settings
with _settings_lock:
_settings = None
@lru_cache(maxsize=1)
def get_default_settings() -> ContextSettings:
"""
Get default settings (cached).
Use this for read-only access to defaults.
For mutable access, use get_context_settings().
"""
return ContextSettings()

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"""
Context Management Engine.
Main orchestration layer for context assembly and optimization.
Provides a high-level API for assembling optimized context for LLM requests.
"""
import logging
from typing import TYPE_CHECKING, Any
from .assembly import ContextPipeline
from .budget import BudgetAllocator, TokenBudget, TokenCalculator
from .cache import ContextCache
from .compression import ContextCompressor
from .config import ContextSettings, get_context_settings
from .prioritization import ContextRanker
from .scoring import CompositeScorer
from .types import (
AssembledContext,
BaseContext,
ConversationContext,
KnowledgeContext,
MessageRole,
SystemContext,
TaskContext,
ToolContext,
)
if TYPE_CHECKING:
from redis.asyncio import Redis
from app.services.mcp.client_manager import MCPClientManager
logger = logging.getLogger(__name__)
class ContextEngine:
"""
Main context management engine.
Provides high-level API for context assembly and optimization.
Integrates all components: scoring, ranking, compression, formatting, and caching.
Usage:
engine = ContextEngine(mcp_manager=mcp, redis=redis)
# Assemble context for an LLM request
result = await engine.assemble_context(
project_id="proj-123",
agent_id="agent-456",
query="implement user authentication",
model="claude-3-sonnet",
system_prompt="You are an expert developer.",
knowledge_query="authentication best practices",
)
# Use the assembled context
print(result.content)
print(f"Tokens: {result.total_tokens}")
"""
def __init__(
self,
mcp_manager: "MCPClientManager | None" = None,
redis: "Redis | None" = None,
settings: ContextSettings | None = None,
) -> None:
"""
Initialize the context engine.
Args:
mcp_manager: MCP client manager for LLM Gateway/Knowledge Base
redis: Redis connection for caching
settings: Context settings
"""
self._mcp = mcp_manager
self._settings = settings or get_context_settings()
# Initialize components
self._calculator = TokenCalculator(mcp_manager=mcp_manager)
self._scorer = CompositeScorer(mcp_manager=mcp_manager, settings=self._settings)
self._ranker = ContextRanker(scorer=self._scorer, calculator=self._calculator)
self._compressor = ContextCompressor(calculator=self._calculator)
self._allocator = BudgetAllocator(self._settings)
self._cache = ContextCache(redis=redis, settings=self._settings)
# Pipeline for assembly
self._pipeline = ContextPipeline(
mcp_manager=mcp_manager,
settings=self._settings,
calculator=self._calculator,
scorer=self._scorer,
ranker=self._ranker,
compressor=self._compressor,
)
def set_mcp_manager(self, mcp_manager: "MCPClientManager") -> None:
"""
Set MCP manager for all components.
Args:
mcp_manager: MCP client manager
"""
self._mcp = mcp_manager
self._calculator.set_mcp_manager(mcp_manager)
self._scorer.set_mcp_manager(mcp_manager)
self._pipeline.set_mcp_manager(mcp_manager)
def set_redis(self, redis: "Redis") -> None:
"""
Set Redis connection for caching.
Args:
redis: Redis connection
"""
self._cache.set_redis(redis)
async def assemble_context(
self,
project_id: str,
agent_id: str,
query: str,
model: str,
max_tokens: int | None = None,
system_prompt: str | None = None,
task_description: str | None = None,
knowledge_query: str | None = None,
knowledge_limit: int = 10,
conversation_history: list[dict[str, str]] | None = None,
tool_results: list[dict[str, Any]] | None = None,
custom_contexts: list[BaseContext] | None = None,
custom_budget: TokenBudget | None = None,
compress: bool = True,
format_output: bool = True,
use_cache: bool = True,
) -> AssembledContext:
"""
Assemble optimized context for an LLM request.
This is the main entry point for context management.
It gathers context from various sources, scores and ranks them,
compresses if needed, and formats for the target model.
Args:
project_id: Project identifier
agent_id: Agent identifier
query: User's query or current request
model: Target model name
max_tokens: Maximum context tokens (uses model default if None)
system_prompt: System prompt/instructions
task_description: Current task description
knowledge_query: Query for knowledge base search
knowledge_limit: Max number of knowledge results
conversation_history: List of {"role": str, "content": str}
tool_results: List of tool results to include
custom_contexts: Additional custom contexts
custom_budget: Custom token budget
compress: Whether to apply compression
format_output: Whether to format for the model
use_cache: Whether to use caching
Returns:
AssembledContext with optimized content
Raises:
AssemblyTimeoutError: If assembly exceeds timeout
BudgetExceededError: If context exceeds budget
"""
# Gather all contexts
contexts: list[BaseContext] = []
# 1. System context
if system_prompt:
contexts.append(
SystemContext(
content=system_prompt,
source="system_prompt",
)
)
# 2. Task context
if task_description:
contexts.append(
TaskContext(
content=task_description,
source=f"task:{project_id}:{agent_id}",
)
)
# 3. Knowledge context from Knowledge Base
if knowledge_query and self._mcp:
knowledge_contexts = await self._fetch_knowledge(
project_id=project_id,
agent_id=agent_id,
query=knowledge_query,
limit=knowledge_limit,
)
contexts.extend(knowledge_contexts)
# 4. Conversation history
if conversation_history:
contexts.extend(self._convert_conversation(conversation_history))
# 5. Tool results
if tool_results:
contexts.extend(self._convert_tool_results(tool_results))
# 6. Custom contexts
if custom_contexts:
contexts.extend(custom_contexts)
# Check cache if enabled
fingerprint: str | None = None
if use_cache and self._cache.is_enabled:
# Include project_id and agent_id for tenant isolation
fingerprint = self._cache.compute_fingerprint(
contexts, query, model, project_id=project_id, agent_id=agent_id
)
cached = await self._cache.get_assembled(fingerprint)
if cached:
logger.debug(f"Cache hit for context assembly: {fingerprint}")
return cached
# Run assembly pipeline
result = await self._pipeline.assemble(
contexts=contexts,
query=query,
model=model,
max_tokens=max_tokens,
custom_budget=custom_budget,
compress=compress,
format_output=format_output,
)
# Cache result if enabled (reuse fingerprint computed above)
if use_cache and self._cache.is_enabled and fingerprint is not None:
await self._cache.set_assembled(fingerprint, result)
return result
async def _fetch_knowledge(
self,
project_id: str,
agent_id: str,
query: str,
limit: int = 10,
) -> list[KnowledgeContext]:
"""
Fetch relevant knowledge from Knowledge Base via MCP.
Args:
project_id: Project identifier
agent_id: Agent identifier
query: Search query
limit: Maximum results
Returns:
List of KnowledgeContext instances
"""
if not self._mcp:
return []
try:
result = await self._mcp.call_tool(
"knowledge-base",
"search_knowledge",
{
"project_id": project_id,
"agent_id": agent_id,
"query": query,
"search_type": "hybrid",
"limit": limit,
},
)
# Check both ToolResult.success AND response success
if not result.success:
logger.warning(f"Knowledge search failed: {result.error}")
return []
if not isinstance(result.data, dict) or not result.data.get(
"success", True
):
logger.warning("Knowledge search returned unsuccessful response")
return []
contexts = []
results = result.data.get("results", [])
for chunk in results:
contexts.append(
KnowledgeContext(
content=chunk.get("content", ""),
source=chunk.get("source_path", "unknown"),
relevance_score=chunk.get("score", 0.0),
metadata={
"chunk_id": chunk.get(
"id"
), # Server returns 'id' not 'chunk_id'
"document_id": chunk.get("document_id"),
},
)
)
logger.debug(f"Fetched {len(contexts)} knowledge chunks for query: {query}")
return contexts
except Exception as e:
logger.warning(f"Failed to fetch knowledge: {e}")
return []
def _convert_conversation(
self,
history: list[dict[str, str]],
) -> list[ConversationContext]:
"""
Convert conversation history to ConversationContext instances.
Args:
history: List of {"role": str, "content": str}
Returns:
List of ConversationContext instances
"""
contexts = []
for i, turn in enumerate(history):
role_str = turn.get("role", "user").lower()
role = (
MessageRole.ASSISTANT if role_str == "assistant" else MessageRole.USER
)
contexts.append(
ConversationContext(
content=turn.get("content", ""),
source=f"conversation:{i}",
role=role,
metadata={"role": role_str, "turn": i},
)
)
return contexts
def _convert_tool_results(
self,
results: list[dict[str, Any]],
) -> list[ToolContext]:
"""
Convert tool results to ToolContext instances.
Args:
results: List of tool result dictionaries
Returns:
List of ToolContext instances
"""
contexts = []
for result in results:
tool_name = result.get("tool_name", "unknown")
content = result.get("content", result.get("result", ""))
# Handle dict content
if isinstance(content, dict):
import json
content = json.dumps(content, indent=2)
contexts.append(
ToolContext(
content=str(content),
source=f"tool:{tool_name}",
metadata={
"tool_name": tool_name,
"status": result.get("status", "success"),
},
)
)
return contexts
async def get_budget_for_model(
self,
model: str,
max_tokens: int | None = None,
) -> TokenBudget:
"""
Get the token budget for a specific model.
Args:
model: Model name
max_tokens: Optional max tokens override
Returns:
TokenBudget instance
"""
if max_tokens:
return self._allocator.create_budget(max_tokens)
return self._allocator.create_budget_for_model(model)
async def count_tokens(
self,
content: str,
model: str | None = None,
) -> int:
"""
Count tokens in content.
Args:
content: Content to count
model: Model for model-specific tokenization
Returns:
Token count
"""
# Check cache first
cached = await self._cache.get_token_count(content, model)
if cached is not None:
return cached
count = await self._calculator.count_tokens(content, model)
# Cache the result
await self._cache.set_token_count(content, count, model)
return count
async def invalidate_cache(
self,
project_id: str | None = None,
pattern: str | None = None,
) -> int:
"""
Invalidate cache entries.
Args:
project_id: Invalidate all cache for a project
pattern: Custom pattern to match
Returns:
Number of entries invalidated
"""
if pattern:
return await self._cache.invalidate(pattern)
elif project_id:
return await self._cache.invalidate(f"*{project_id}*")
else:
return await self._cache.clear_all()
async def get_stats(self) -> dict[str, Any]:
"""
Get engine statistics.
Returns:
Dictionary with engine stats
"""
return {
"cache": await self._cache.get_stats(),
"settings": {
"compression_threshold": self._settings.compression_threshold,
"max_assembly_time_ms": self._settings.max_assembly_time_ms,
"cache_enabled": self._settings.cache_enabled,
},
}
# Convenience factory function
def create_context_engine(
mcp_manager: "MCPClientManager | None" = None,
redis: "Redis | None" = None,
settings: ContextSettings | None = None,
) -> ContextEngine:
"""
Create a context engine instance.
Args:
mcp_manager: MCP client manager
redis: Redis connection
settings: Context settings
Returns:
Configured ContextEngine instance
"""
return ContextEngine(
mcp_manager=mcp_manager,
redis=redis,
settings=settings,
)

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"""
Context Management Engine Exceptions.
Provides a hierarchy of exceptions for context assembly,
token budget management, and related operations.
"""
from typing import Any
class ContextError(Exception):
"""
Base exception for all context management errors.
All context-related exceptions should inherit from this class
to allow for catch-all handling when needed.
"""
def __init__(self, message: str, details: dict[str, Any] | None = None) -> None:
"""
Initialize context error.
Args:
message: Human-readable error message
details: Optional dict with additional error context
"""
self.message = message
self.details = details or {}
super().__init__(message)
def to_dict(self) -> dict[str, Any]:
"""Convert exception to dictionary for logging/serialization."""
return {
"error_type": self.__class__.__name__,
"message": self.message,
"details": self.details,
}
class BudgetExceededError(ContextError):
"""
Raised when token budget is exceeded.
This occurs when the assembled context would exceed the
allocated token budget for a specific context type or total.
"""
def __init__(
self,
message: str = "Token budget exceeded",
allocated: int = 0,
requested: int = 0,
context_type: str | None = None,
) -> None:
"""
Initialize budget exceeded error.
Args:
message: Error message
allocated: Tokens allocated for this context type
requested: Tokens requested
context_type: Type of context that exceeded budget
"""
details: dict[str, Any] = {
"allocated": allocated,
"requested": requested,
"overage": requested - allocated,
}
if context_type:
details["context_type"] = context_type
super().__init__(message, details)
self.allocated = allocated
self.requested = requested
self.context_type = context_type
class TokenCountError(ContextError):
"""
Raised when token counting fails.
This typically occurs when the LLM Gateway token counting
service is unavailable or returns an error.
"""
def __init__(
self,
message: str = "Failed to count tokens",
model: str | None = None,
text_length: int | None = None,
) -> None:
"""
Initialize token count error.
Args:
message: Error message
model: Model for which counting was attempted
text_length: Length of text that failed to count
"""
details: dict[str, Any] = {}
if model:
details["model"] = model
if text_length is not None:
details["text_length"] = text_length
super().__init__(message, details)
self.model = model
self.text_length = text_length
class CompressionError(ContextError):
"""
Raised when context compression fails.
This can occur when summarization or truncation cannot
reduce content to fit within the budget.
"""
def __init__(
self,
message: str = "Failed to compress context",
original_tokens: int | None = None,
target_tokens: int | None = None,
achieved_tokens: int | None = None,
) -> None:
"""
Initialize compression error.
Args:
message: Error message
original_tokens: Tokens before compression
target_tokens: Target token count
achieved_tokens: Tokens achieved after compression attempt
"""
details: dict[str, Any] = {}
if original_tokens is not None:
details["original_tokens"] = original_tokens
if target_tokens is not None:
details["target_tokens"] = target_tokens
if achieved_tokens is not None:
details["achieved_tokens"] = achieved_tokens
super().__init__(message, details)
self.original_tokens = original_tokens
self.target_tokens = target_tokens
self.achieved_tokens = achieved_tokens
class AssemblyTimeoutError(ContextError):
"""
Raised when context assembly exceeds time limit.
Context assembly must complete within a configurable
time limit to maintain responsiveness.
"""
def __init__(
self,
message: str = "Context assembly timed out",
timeout_ms: int = 0,
elapsed_ms: float = 0.0,
stage: str | None = None,
) -> None:
"""
Initialize assembly timeout error.
Args:
message: Error message
timeout_ms: Configured timeout in milliseconds
elapsed_ms: Actual elapsed time in milliseconds
stage: Pipeline stage where timeout occurred
"""
details: dict[str, Any] = {
"timeout_ms": timeout_ms,
"elapsed_ms": round(elapsed_ms, 2),
}
if stage:
details["stage"] = stage
super().__init__(message, details)
self.timeout_ms = timeout_ms
self.elapsed_ms = elapsed_ms
self.stage = stage
class ScoringError(ContextError):
"""
Raised when context scoring fails.
This occurs when relevance, recency, or priority scoring
encounters an error.
"""
def __init__(
self,
message: str = "Failed to score context",
scorer_type: str | None = None,
context_id: str | None = None,
) -> None:
"""
Initialize scoring error.
Args:
message: Error message
scorer_type: Type of scorer that failed
context_id: ID of context being scored
"""
details: dict[str, Any] = {}
if scorer_type:
details["scorer_type"] = scorer_type
if context_id:
details["context_id"] = context_id
super().__init__(message, details)
self.scorer_type = scorer_type
self.context_id = context_id
class FormattingError(ContextError):
"""
Raised when context formatting fails.
This occurs when converting assembled context to
model-specific format fails.
"""
def __init__(
self,
message: str = "Failed to format context",
model: str | None = None,
adapter: str | None = None,
) -> None:
"""
Initialize formatting error.
Args:
message: Error message
model: Target model
adapter: Adapter that failed
"""
details: dict[str, Any] = {}
if model:
details["model"] = model
if adapter:
details["adapter"] = adapter
super().__init__(message, details)
self.model = model
self.adapter = adapter
class CacheError(ContextError):
"""
Raised when cache operations fail.
This is typically non-fatal and should be handled
gracefully by falling back to recomputation.
"""
def __init__(
self,
message: str = "Cache operation failed",
operation: str | None = None,
cache_key: str | None = None,
) -> None:
"""
Initialize cache error.
Args:
message: Error message
operation: Cache operation that failed (get, set, delete)
cache_key: Key involved in the failed operation
"""
details: dict[str, Any] = {}
if operation:
details["operation"] = operation
if cache_key:
details["cache_key"] = cache_key
super().__init__(message, details)
self.operation = operation
self.cache_key = cache_key
class ContextNotFoundError(ContextError):
"""
Raised when expected context is not found.
This occurs when required context sources return
no results or are unavailable.
"""
def __init__(
self,
message: str = "Required context not found",
source: str | None = None,
query: str | None = None,
) -> None:
"""
Initialize context not found error.
Args:
message: Error message
source: Source that returned no results
query: Query used to search
"""
details: dict[str, Any] = {}
if source:
details["source"] = source
if query:
details["query"] = query
super().__init__(message, details)
self.source = source
self.query = query
class InvalidContextError(ContextError):
"""
Raised when context data is invalid.
This occurs when context content or metadata
fails validation.
"""
def __init__(
self,
message: str = "Invalid context data",
field: str | None = None,
value: Any | None = None,
reason: str | None = None,
) -> None:
"""
Initialize invalid context error.
Args:
message: Error message
field: Field that is invalid
value: Invalid value (may be redacted for security)
reason: Reason for invalidity
"""
details: dict[str, Any] = {}
if field:
details["field"] = field
if value is not None:
# Avoid logging potentially sensitive values
details["value_type"] = type(value).__name__
if reason:
details["reason"] = reason
super().__init__(message, details)
self.field = field
self.value = value
self.reason = reason

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"""
Context Prioritization Module.
Provides context ranking and selection.
"""
from .ranker import ContextRanker, RankingResult
__all__ = [
"ContextRanker",
"RankingResult",
]

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"""
Context Ranker for Context Management.
Ranks and selects contexts based on scores and budget constraints.
"""
import logging
from dataclasses import dataclass, field
from typing import TYPE_CHECKING, Any
from ..budget import TokenBudget, TokenCalculator
from ..config import ContextSettings, get_context_settings
from ..exceptions import BudgetExceededError
from ..scoring.composite import CompositeScorer, ScoredContext
from ..types import BaseContext, ContextPriority
if TYPE_CHECKING:
pass
logger = logging.getLogger(__name__)
@dataclass
class RankingResult:
"""Result of context ranking and selection."""
selected: list[ScoredContext]
excluded: list[ScoredContext]
total_tokens: int
selection_stats: dict[str, Any] = field(default_factory=dict)
@property
def selected_contexts(self) -> list[BaseContext]:
"""Get just the context objects (not scored wrappers)."""
return [s.context for s in self.selected]
class ContextRanker:
"""
Ranks and selects contexts within budget constraints.
Uses greedy selection to maximize total score
while respecting token budgets per context type.
"""
def __init__(
self,
scorer: CompositeScorer | None = None,
calculator: TokenCalculator | None = None,
settings: ContextSettings | None = None,
) -> None:
"""
Initialize context ranker.
Args:
scorer: Composite scorer for scoring contexts
calculator: Token calculator for counting tokens
settings: Context settings (uses global if None)
"""
self._settings = settings or get_context_settings()
self._scorer = scorer or CompositeScorer()
self._calculator = calculator or TokenCalculator()
def set_scorer(self, scorer: CompositeScorer) -> None:
"""Set the scorer."""
self._scorer = scorer
def set_calculator(self, calculator: TokenCalculator) -> None:
"""Set the token calculator."""
self._calculator = calculator
async def rank(
self,
contexts: list[BaseContext],
query: str,
budget: TokenBudget,
model: str | None = None,
ensure_required: bool = True,
**kwargs: Any,
) -> RankingResult:
"""
Rank and select contexts within budget.
Args:
contexts: Contexts to rank
query: Query to rank against
budget: Token budget constraints
model: Model for token counting
ensure_required: If True, always include CRITICAL priority contexts
**kwargs: Additional scoring parameters
Returns:
RankingResult with selected and excluded contexts
"""
if not contexts:
return RankingResult(
selected=[],
excluded=[],
total_tokens=0,
selection_stats={"total_contexts": 0},
)
# 1. Ensure all contexts have token counts
await self._ensure_token_counts(contexts, model)
# 2. Score all contexts
scored_contexts = await self._scorer.score_batch(contexts, query, **kwargs)
# 3. Separate required (CRITICAL priority) from optional
required: list[ScoredContext] = []
optional: list[ScoredContext] = []
if ensure_required:
for sc in scored_contexts:
# CRITICAL priority (150) contexts are always included
if sc.context.priority >= ContextPriority.CRITICAL.value:
required.append(sc)
else:
optional.append(sc)
else:
optional = list(scored_contexts)
# 4. Sort optional by score (highest first)
optional.sort(reverse=True)
# 5. Greedy selection
selected: list[ScoredContext] = []
excluded: list[ScoredContext] = []
total_tokens = 0
# Calculate the usable budget (total minus reserved portions)
usable_budget = budget.total - budget.response_reserve - budget.buffer
# Guard against invalid budget configuration
if usable_budget <= 0:
raise BudgetExceededError(
message=(
f"Invalid budget configuration: no usable tokens available. "
f"total={budget.total}, response_reserve={budget.response_reserve}, "
f"buffer={budget.buffer}"
),
allocated=budget.total,
requested=0,
context_type="CONFIGURATION_ERROR",
)
# First, try to fit required contexts
for sc in required:
token_count = self._get_valid_token_count(sc.context)
context_type = sc.context.get_type()
if budget.can_fit(context_type, token_count):
budget.allocate(context_type, token_count)
selected.append(sc)
total_tokens += token_count
else:
# Force-fit CRITICAL contexts if needed, but check total budget first
if total_tokens + token_count > usable_budget:
# Even CRITICAL contexts cannot exceed total model context window
raise BudgetExceededError(
message=(
f"CRITICAL contexts exceed total budget. "
f"Context '{sc.context.source}' ({token_count} tokens) "
f"would exceed usable budget of {usable_budget} tokens."
),
allocated=usable_budget,
requested=total_tokens + token_count,
context_type="CRITICAL_OVERFLOW",
)
budget.allocate(context_type, token_count, force=True)
selected.append(sc)
total_tokens += token_count
logger.warning(
f"Force-fitted CRITICAL context: {sc.context.source} "
f"({token_count} tokens)"
)
# Then, greedily add optional contexts
for sc in optional:
token_count = self._get_valid_token_count(sc.context)
context_type = sc.context.get_type()
if budget.can_fit(context_type, token_count):
budget.allocate(context_type, token_count)
selected.append(sc)
total_tokens += token_count
else:
excluded.append(sc)
# Build stats
stats = {
"total_contexts": len(contexts),
"required_count": len(required),
"selected_count": len(selected),
"excluded_count": len(excluded),
"total_tokens": total_tokens,
"by_type": self._count_by_type(selected),
}
return RankingResult(
selected=selected,
excluded=excluded,
total_tokens=total_tokens,
selection_stats=stats,
)
async def rank_simple(
self,
contexts: list[BaseContext],
query: str,
max_tokens: int,
model: str | None = None,
**kwargs: Any,
) -> list[BaseContext]:
"""
Simple ranking without budget per type.
Selects top contexts by score until max tokens reached.
Args:
contexts: Contexts to rank
query: Query to rank against
max_tokens: Maximum total tokens
model: Model for token counting
**kwargs: Additional scoring parameters
Returns:
Selected contexts (in score order)
"""
if not contexts:
return []
# Ensure token counts
await self._ensure_token_counts(contexts, model)
# Score all contexts
scored_contexts = await self._scorer.score_batch(contexts, query, **kwargs)
# Sort by score (highest first)
scored_contexts.sort(reverse=True)
# Greedy selection
selected: list[BaseContext] = []
total_tokens = 0
for sc in scored_contexts:
token_count = self._get_valid_token_count(sc.context)
if total_tokens + token_count <= max_tokens:
selected.append(sc.context)
total_tokens += token_count
return selected
def _get_valid_token_count(self, context: BaseContext) -> int:
"""
Get validated token count from a context.
Ensures token_count is set (not None) and non-negative to prevent
budget bypass attacks where:
- None would be treated as 0 (allowing huge contexts to slip through)
- Negative values would corrupt budget tracking
Args:
context: Context to get token count from
Returns:
Valid non-negative token count
Raises:
ValueError: If token_count is None or negative
"""
if context.token_count is None:
raise ValueError(
f"Context '{context.source}' has no token count. "
"Ensure _ensure_token_counts() is called before ranking."
)
if context.token_count < 0:
raise ValueError(
f"Context '{context.source}' has invalid negative token count: "
f"{context.token_count}"
)
return context.token_count
async def _ensure_token_counts(
self,
contexts: list[BaseContext],
model: str | None = None,
) -> None:
"""
Ensure all contexts have token counts.
Counts tokens in parallel for contexts that don't have counts.
Args:
contexts: Contexts to check
model: Model for token counting
"""
import asyncio
# Find contexts needing counts
contexts_needing_counts = [ctx for ctx in contexts if ctx.token_count is None]
if not contexts_needing_counts:
return
# Count all in parallel
tasks = [
self._calculator.count_tokens(ctx.content, model)
for ctx in contexts_needing_counts
]
counts = await asyncio.gather(*tasks)
# Assign counts back
for ctx, count in zip(contexts_needing_counts, counts, strict=True):
ctx.token_count = count
def _count_by_type(
self, scored_contexts: list[ScoredContext]
) -> dict[str, dict[str, int]]:
"""Count selected contexts by type."""
by_type: dict[str, dict[str, int]] = {}
for sc in scored_contexts:
type_name = sc.context.get_type().value
if type_name not in by_type:
by_type[type_name] = {"count": 0, "tokens": 0}
by_type[type_name]["count"] += 1
# Use validated token count (already validated during ranking)
by_type[type_name]["tokens"] += sc.context.token_count or 0
return by_type
async def rerank_for_diversity(
self,
scored_contexts: list[ScoredContext],
max_per_source: int | None = None,
) -> list[ScoredContext]:
"""
Rerank to ensure source diversity.
Prevents too many items from the same source.
Args:
scored_contexts: Already scored contexts
max_per_source: Maximum items per source (uses settings if None)
Returns:
Reranked contexts
"""
# Use provided value or fall back to settings
effective_max = (
max_per_source
if max_per_source is not None
else self._settings.diversity_max_per_source
)
source_counts: dict[str, int] = {}
result: list[ScoredContext] = []
deferred: list[ScoredContext] = []
for sc in scored_contexts:
source = sc.context.source
current_count = source_counts.get(source, 0)
if current_count < effective_max:
result.append(sc)
source_counts[source] = current_count + 1
else:
deferred.append(sc)
# Add deferred items at the end
result.extend(deferred)
return result

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"""
Context Scoring Module.
Provides scoring strategies for context prioritization.
"""
from .base import BaseScorer, ScorerProtocol
from .composite import CompositeScorer, ScoredContext
from .priority import PriorityScorer
from .recency import RecencyScorer
from .relevance import RelevanceScorer
__all__ = [
"BaseScorer",
"CompositeScorer",
"PriorityScorer",
"RecencyScorer",
"RelevanceScorer",
"ScoredContext",
"ScorerProtocol",
]

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"""
Base Scorer Protocol and Types.
Defines the interface for context scoring implementations.
"""
from abc import ABC, abstractmethod
from typing import TYPE_CHECKING, Any, Protocol, runtime_checkable
from ..types import BaseContext
if TYPE_CHECKING:
pass
@runtime_checkable
class ScorerProtocol(Protocol):
"""Protocol for context scorers."""
async def score(
self,
context: BaseContext,
query: str,
**kwargs: Any,
) -> float:
"""
Score a context item.
Args:
context: Context to score
query: Query to score against
**kwargs: Additional scoring parameters
Returns:
Score between 0.0 and 1.0
"""
...
class BaseScorer(ABC):
"""
Abstract base class for context scorers.
Provides common functionality and interface for
different scoring strategies.
"""
def __init__(self, weight: float = 1.0) -> None:
"""
Initialize scorer.
Args:
weight: Weight for this scorer in composite scoring
"""
self._weight = weight
@property
def weight(self) -> float:
"""Get scorer weight."""
return self._weight
@weight.setter
def weight(self, value: float) -> None:
"""Set scorer weight."""
if not 0.0 <= value <= 1.0:
raise ValueError("Weight must be between 0.0 and 1.0")
self._weight = value
@abstractmethod
async def score(
self,
context: BaseContext,
query: str,
**kwargs: Any,
) -> float:
"""
Score a context item.
Args:
context: Context to score
query: Query to score against
**kwargs: Additional scoring parameters
Returns:
Score between 0.0 and 1.0
"""
...
def normalize_score(self, score: float) -> float:
"""
Normalize score to [0.0, 1.0] range.
Args:
score: Raw score
Returns:
Normalized score
"""
return max(0.0, min(1.0, score))

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"""
Composite Scorer for Context Management.
Combines multiple scoring strategies with configurable weights.
"""
import asyncio
import logging
import time
from dataclasses import dataclass
from typing import TYPE_CHECKING, Any
from ..config import ContextSettings, get_context_settings
from ..types import BaseContext
from .priority import PriorityScorer
from .recency import RecencyScorer
from .relevance import RelevanceScorer
if TYPE_CHECKING:
from app.services.mcp.client_manager import MCPClientManager
logger = logging.getLogger(__name__)
@dataclass
class ScoredContext:
"""Context with computed scores."""
context: BaseContext
composite_score: float
relevance_score: float = 0.0
recency_score: float = 0.0
priority_score: float = 0.0
def __lt__(self, other: "ScoredContext") -> bool:
"""Enable sorting by composite score."""
return self.composite_score < other.composite_score
def __gt__(self, other: "ScoredContext") -> bool:
"""Enable sorting by composite score."""
return self.composite_score > other.composite_score
class CompositeScorer:
"""
Combines multiple scoring strategies.
Weights:
- relevance: How well content matches the query
- recency: How recent the content is
- priority: Explicit priority assignments
"""
def __init__(
self,
mcp_manager: "MCPClientManager | None" = None,
settings: ContextSettings | None = None,
relevance_weight: float | None = None,
recency_weight: float | None = None,
priority_weight: float | None = None,
) -> None:
"""
Initialize composite scorer.
Args:
mcp_manager: MCP manager for semantic scoring
settings: Context settings (uses default if None)
relevance_weight: Override relevance weight
recency_weight: Override recency weight
priority_weight: Override priority weight
"""
self._settings = settings or get_context_settings()
weights = self._settings.get_scoring_weights()
self._relevance_weight = (
relevance_weight if relevance_weight is not None else weights["relevance"]
)
self._recency_weight = (
recency_weight if recency_weight is not None else weights["recency"]
)
self._priority_weight = (
priority_weight if priority_weight is not None else weights["priority"]
)
# Initialize scorers
self._relevance_scorer = RelevanceScorer(
mcp_manager=mcp_manager,
weight=self._relevance_weight,
)
self._recency_scorer = RecencyScorer(weight=self._recency_weight)
self._priority_scorer = PriorityScorer(weight=self._priority_weight)
# Per-context locks to prevent race conditions during parallel scoring
# Uses dict with (lock, last_used_time) tuples for cleanup
self._context_locks: dict[str, tuple[asyncio.Lock, float]] = {}
self._locks_lock = asyncio.Lock() # Lock to protect _context_locks access
self._max_locks = 1000 # Maximum locks to keep (prevent memory growth)
self._lock_ttl = 60.0 # Seconds before a lock can be cleaned up
def set_mcp_manager(self, mcp_manager: "MCPClientManager") -> None:
"""Set MCP manager for semantic scoring."""
self._relevance_scorer.set_mcp_manager(mcp_manager)
@property
def weights(self) -> dict[str, float]:
"""Get current scoring weights."""
return {
"relevance": self._relevance_weight,
"recency": self._recency_weight,
"priority": self._priority_weight,
}
def update_weights(
self,
relevance: float | None = None,
recency: float | None = None,
priority: float | None = None,
) -> None:
"""
Update scoring weights.
Args:
relevance: New relevance weight
recency: New recency weight
priority: New priority weight
"""
if relevance is not None:
self._relevance_weight = max(0.0, min(1.0, relevance))
self._relevance_scorer.weight = self._relevance_weight
if recency is not None:
self._recency_weight = max(0.0, min(1.0, recency))
self._recency_scorer.weight = self._recency_weight
if priority is not None:
self._priority_weight = max(0.0, min(1.0, priority))
self._priority_scorer.weight = self._priority_weight
async def _get_context_lock(self, context_id: str) -> asyncio.Lock:
"""
Get or create a lock for a specific context.
Thread-safe access to per-context locks prevents race conditions
when the same context is scored concurrently. Includes automatic
cleanup of old locks to prevent memory growth.
Args:
context_id: The context ID to get a lock for
Returns:
asyncio.Lock for the context
"""
now = time.time()
# Fast path: check if lock exists without acquiring main lock
# NOTE: We only READ here - no writes to avoid race conditions
# with cleanup. The timestamp will be updated in the slow path
# if the lock is still valid.
lock_entry = self._context_locks.get(context_id)
if lock_entry is not None:
lock, _ = lock_entry
# Return the lock but defer timestamp update to avoid race
# The lock is still valid; timestamp update is best-effort
return lock
# Slow path: create lock or update timestamp while holding main lock
async with self._locks_lock:
# Double-check after acquiring lock - entry may have been
# created by another coroutine or deleted by cleanup
lock_entry = self._context_locks.get(context_id)
if lock_entry is not None:
lock, _ = lock_entry
# Safe to update timestamp here since we hold the lock
self._context_locks[context_id] = (lock, now)
return lock
# Cleanup old locks if we have too many
if len(self._context_locks) >= self._max_locks:
self._cleanup_old_locks(now)
# Create new lock
new_lock = asyncio.Lock()
self._context_locks[context_id] = (new_lock, now)
return new_lock
def _cleanup_old_locks(self, now: float) -> None:
"""
Remove old locks that haven't been used recently.
Called while holding _locks_lock. Removes locks older than _lock_ttl,
but only if they're not currently held.
Args:
now: Current timestamp for age calculation
"""
cutoff = now - self._lock_ttl
to_remove = []
for context_id, (lock, last_used) in self._context_locks.items():
# Only remove if old AND not currently held
if last_used < cutoff and not lock.locked():
to_remove.append(context_id)
# Remove oldest 50% if still over limit after TTL filtering
if len(self._context_locks) - len(to_remove) >= self._max_locks:
# Sort by last used time and mark oldest for removal
sorted_entries = sorted(
self._context_locks.items(),
key=lambda x: x[1][1], # Sort by last_used time
)
# Remove oldest 50% that aren't locked
target_remove = len(self._context_locks) // 2
for context_id, (lock, _) in sorted_entries:
if len(to_remove) >= target_remove:
break
if context_id not in to_remove and not lock.locked():
to_remove.append(context_id)
for context_id in to_remove:
del self._context_locks[context_id]
if to_remove:
logger.debug(f"Cleaned up {len(to_remove)} context locks")
async def score(
self,
context: BaseContext,
query: str,
**kwargs: Any,
) -> float:
"""
Compute composite score for a context.
Args:
context: Context to score
query: Query to score against
**kwargs: Additional scoring parameters
Returns:
Composite score between 0.0 and 1.0
"""
scored = await self.score_with_details(context, query, **kwargs)
return scored.composite_score
async def score_with_details(
self,
context: BaseContext,
query: str,
**kwargs: Any,
) -> ScoredContext:
"""
Compute composite score with individual scores.
Uses per-context locking to prevent race conditions when the same
context is scored concurrently in parallel scoring operations.
Args:
context: Context to score
query: Query to score against
**kwargs: Additional scoring parameters
Returns:
ScoredContext with all scores
"""
# Get lock for this specific context to prevent race conditions
# within concurrent scoring operations for the same query
context_lock = await self._get_context_lock(context.id)
async with context_lock:
# Compute individual scores in parallel
# Note: We do NOT cache scores on the context because scores are
# query-dependent. Caching without considering the query would
# return incorrect scores for different queries.
relevance_task = self._relevance_scorer.score(context, query, **kwargs)
recency_task = self._recency_scorer.score(context, query, **kwargs)
priority_task = self._priority_scorer.score(context, query, **kwargs)
relevance_score, recency_score, priority_score = await asyncio.gather(
relevance_task, recency_task, priority_task
)
# Compute weighted composite
total_weight = (
self._relevance_weight + self._recency_weight + self._priority_weight
)
if total_weight > 0:
composite = (
relevance_score * self._relevance_weight
+ recency_score * self._recency_weight
+ priority_score * self._priority_weight
) / total_weight
else:
composite = 0.0
return ScoredContext(
context=context,
composite_score=composite,
relevance_score=relevance_score,
recency_score=recency_score,
priority_score=priority_score,
)
async def score_batch(
self,
contexts: list[BaseContext],
query: str,
parallel: bool = True,
**kwargs: Any,
) -> list[ScoredContext]:
"""
Score multiple contexts.
Args:
contexts: Contexts to score
query: Query to score against
parallel: Whether to score in parallel
**kwargs: Additional scoring parameters
Returns:
List of ScoredContext (same order as input)
"""
if parallel:
tasks = [self.score_with_details(ctx, query, **kwargs) for ctx in contexts]
return await asyncio.gather(*tasks)
else:
results = []
for ctx in contexts:
scored = await self.score_with_details(ctx, query, **kwargs)
results.append(scored)
return results
async def rank(
self,
contexts: list[BaseContext],
query: str,
limit: int | None = None,
min_score: float = 0.0,
**kwargs: Any,
) -> list[ScoredContext]:
"""
Score and rank contexts.
Args:
contexts: Contexts to rank
query: Query to rank against
limit: Maximum number of results
min_score: Minimum score threshold
**kwargs: Additional scoring parameters
Returns:
Sorted list of ScoredContext (highest first)
"""
# Score all contexts
scored = await self.score_batch(contexts, query, **kwargs)
# Filter by minimum score
if min_score > 0:
scored = [s for s in scored if s.composite_score >= min_score]
# Sort by score (highest first)
scored.sort(reverse=True)
# Apply limit
if limit is not None:
scored = scored[:limit]
return scored

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"""
Priority Scorer for Context Management.
Scores context based on assigned priority levels.
"""
from typing import Any, ClassVar
from ..types import BaseContext, ContextType
from .base import BaseScorer
class PriorityScorer(BaseScorer):
"""
Scores context based on priority levels.
Converts priority enum values to normalized scores.
Also applies type-based priority bonuses.
"""
# Default priority bonuses by context type
DEFAULT_TYPE_BONUSES: ClassVar[dict[ContextType, float]] = {
ContextType.SYSTEM: 0.2, # System prompts get a boost
ContextType.TASK: 0.15, # Current task is important
ContextType.TOOL: 0.1, # Recent tool results matter
ContextType.KNOWLEDGE: 0.0, # Knowledge scored by relevance
ContextType.CONVERSATION: 0.0, # Conversation scored by recency
}
def __init__(
self,
weight: float = 1.0,
type_bonuses: dict[ContextType, float] | None = None,
) -> None:
"""
Initialize priority scorer.
Args:
weight: Scorer weight for composite scoring
type_bonuses: Optional context-type priority bonuses
"""
super().__init__(weight)
self._type_bonuses = type_bonuses or self.DEFAULT_TYPE_BONUSES.copy()
async def score(
self,
context: BaseContext,
query: str,
**kwargs: Any,
) -> float:
"""
Score context based on priority.
Args:
context: Context to score
query: Query (not used for priority, kept for interface)
**kwargs: Additional parameters
Returns:
Priority score between 0.0 and 1.0
"""
# Get base priority score
priority_value = context.priority
base_score = self._priority_to_score(priority_value)
# Apply type bonus
context_type = context.get_type()
bonus = self._type_bonuses.get(context_type, 0.0)
return self.normalize_score(base_score + bonus)
def _priority_to_score(self, priority: int) -> float:
"""
Convert priority value to normalized score.
Priority values (from ContextPriority):
- CRITICAL (100) -> 1.0
- HIGH (80) -> 0.8
- NORMAL (50) -> 0.5
- LOW (20) -> 0.2
- MINIMAL (0) -> 0.0
Args:
priority: Priority value (0-100)
Returns:
Normalized score (0.0-1.0)
"""
# Clamp to valid range
clamped = max(0, min(100, priority))
return clamped / 100.0
def get_type_bonus(self, context_type: ContextType) -> float:
"""
Get priority bonus for a context type.
Args:
context_type: Context type
Returns:
Bonus value
"""
return self._type_bonuses.get(context_type, 0.0)
def set_type_bonus(self, context_type: ContextType, bonus: float) -> None:
"""
Set priority bonus for a context type.
Args:
context_type: Context type
bonus: Bonus value (0.0-1.0)
"""
if not 0.0 <= bonus <= 1.0:
raise ValueError("Bonus must be between 0.0 and 1.0")
self._type_bonuses[context_type] = bonus
async def score_batch(
self,
contexts: list[BaseContext],
query: str,
**kwargs: Any,
) -> list[float]:
"""
Score multiple contexts.
Args:
contexts: Contexts to score
query: Query (not used)
**kwargs: Additional parameters
Returns:
List of scores (same order as input)
"""
# Priority scoring is fast, no async needed
return [await self.score(ctx, query, **kwargs) for ctx in contexts]

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"""
Recency Scorer for Context Management.
Scores context based on how recent it is.
More recent content gets higher scores.
"""
import math
from datetime import UTC, datetime
from typing import Any
from ..types import BaseContext, ContextType
from .base import BaseScorer
class RecencyScorer(BaseScorer):
"""
Scores context based on recency.
Uses exponential decay to score content based on age.
More recent content scores higher.
"""
def __init__(
self,
weight: float = 1.0,
half_life_hours: float = 24.0,
type_half_lives: dict[ContextType, float] | None = None,
) -> None:
"""
Initialize recency scorer.
Args:
weight: Scorer weight for composite scoring
half_life_hours: Default hours until score decays to 0.5
type_half_lives: Optional context-type-specific half lives
"""
super().__init__(weight)
self._half_life_hours = half_life_hours
self._type_half_lives = type_half_lives or {}
# Set sensible defaults for context types
if ContextType.CONVERSATION not in self._type_half_lives:
self._type_half_lives[ContextType.CONVERSATION] = 1.0 # 1 hour
if ContextType.TOOL not in self._type_half_lives:
self._type_half_lives[ContextType.TOOL] = 0.5 # 30 minutes
if ContextType.KNOWLEDGE not in self._type_half_lives:
self._type_half_lives[ContextType.KNOWLEDGE] = 168.0 # 1 week
if ContextType.SYSTEM not in self._type_half_lives:
self._type_half_lives[ContextType.SYSTEM] = 720.0 # 30 days
if ContextType.TASK not in self._type_half_lives:
self._type_half_lives[ContextType.TASK] = 24.0 # 1 day
async def score(
self,
context: BaseContext,
query: str,
**kwargs: Any,
) -> float:
"""
Score context based on recency.
Args:
context: Context to score
query: Query (not used for recency, kept for interface)
**kwargs: Additional parameters
- reference_time: Time to measure recency from (default: now)
Returns:
Recency score between 0.0 and 1.0
"""
reference_time = kwargs.get("reference_time")
if reference_time is None:
reference_time = datetime.now(UTC)
elif reference_time.tzinfo is None:
reference_time = reference_time.replace(tzinfo=UTC)
# Ensure context timestamp is timezone-aware
context_time = context.timestamp
if context_time.tzinfo is None:
context_time = context_time.replace(tzinfo=UTC)
# Calculate age in hours
age = reference_time - context_time
age_hours = max(0, age.total_seconds() / 3600)
# Get half-life for this context type
context_type = context.get_type()
half_life = self._type_half_lives.get(context_type, self._half_life_hours)
# Exponential decay
decay_factor = math.exp(-math.log(2) * age_hours / half_life)
return self.normalize_score(decay_factor)
def get_half_life(self, context_type: ContextType) -> float:
"""
Get half-life for a context type.
Args:
context_type: Context type to get half-life for
Returns:
Half-life in hours
"""
return self._type_half_lives.get(context_type, self._half_life_hours)
def set_half_life(self, context_type: ContextType, hours: float) -> None:
"""
Set half-life for a context type.
Args:
context_type: Context type to set half-life for
hours: Half-life in hours
"""
if hours <= 0:
raise ValueError("Half-life must be positive")
self._type_half_lives[context_type] = hours
async def score_batch(
self,
contexts: list[BaseContext],
query: str,
**kwargs: Any,
) -> list[float]:
"""
Score multiple contexts.
Args:
contexts: Contexts to score
query: Query (not used)
**kwargs: Additional parameters
Returns:
List of scores (same order as input)
"""
scores = []
for context in contexts:
score = await self.score(context, query, **kwargs)
scores.append(score)
return scores

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"""
Relevance Scorer for Context Management.
Scores context based on semantic similarity to the query.
Uses Knowledge Base embeddings when available.
"""
import logging
import re
from typing import TYPE_CHECKING, Any
from ..config import ContextSettings, get_context_settings
from ..types import BaseContext, KnowledgeContext
from .base import BaseScorer
if TYPE_CHECKING:
from app.services.mcp.client_manager import MCPClientManager
logger = logging.getLogger(__name__)
class RelevanceScorer(BaseScorer):
"""
Scores context based on relevance to query.
Uses multiple strategies:
1. Pre-computed scores (from RAG results)
2. MCP-based semantic similarity (via Knowledge Base)
3. Keyword matching fallback
"""
def __init__(
self,
mcp_manager: "MCPClientManager | None" = None,
weight: float = 1.0,
keyword_fallback_weight: float | None = None,
semantic_max_chars: int | None = None,
settings: ContextSettings | None = None,
) -> None:
"""
Initialize relevance scorer.
Args:
mcp_manager: MCP manager for Knowledge Base calls
weight: Scorer weight for composite scoring
keyword_fallback_weight: Max score for keyword-based fallback (overrides settings)
semantic_max_chars: Max content length for semantic similarity (overrides settings)
settings: Context settings (uses global if None)
"""
super().__init__(weight)
self._settings = settings or get_context_settings()
self._mcp = mcp_manager
# Use provided values or fall back to settings
self._keyword_fallback_weight = (
keyword_fallback_weight
if keyword_fallback_weight is not None
else self._settings.relevance_keyword_fallback_weight
)
self._semantic_max_chars = (
semantic_max_chars
if semantic_max_chars is not None
else self._settings.relevance_semantic_max_chars
)
def set_mcp_manager(self, mcp_manager: "MCPClientManager") -> None:
"""Set MCP manager for semantic scoring."""
self._mcp = mcp_manager
async def score(
self,
context: BaseContext,
query: str,
**kwargs: Any,
) -> float:
"""
Score context relevance to query.
Args:
context: Context to score
query: Query to score against
**kwargs: Additional parameters
Returns:
Relevance score between 0.0 and 1.0
"""
# 1. Check for pre-computed relevance score
if (
isinstance(context, KnowledgeContext)
and context.relevance_score is not None
):
return self.normalize_score(context.relevance_score)
# 2. Check metadata for score
if "relevance_score" in context.metadata:
return self.normalize_score(context.metadata["relevance_score"])
if "score" in context.metadata:
return self.normalize_score(context.metadata["score"])
# 3. Try MCP-based semantic similarity (if compute_similarity tool is available)
# Note: This requires the knowledge-base MCP server to implement compute_similarity
if self._mcp is not None:
try:
score = await self._compute_semantic_similarity(context, query)
if score is not None:
return score
except Exception as e:
# Log at debug level since this is expected if compute_similarity
# tool is not implemented in the Knowledge Base server
logger.debug(
f"Semantic scoring unavailable, using keyword fallback: {e}"
)
# 4. Fall back to keyword matching
return self._compute_keyword_score(context, query)
async def _compute_semantic_similarity(
self,
context: BaseContext,
query: str,
) -> float | None:
"""
Compute semantic similarity using Knowledge Base embeddings.
Args:
context: Context to score
query: Query to compare
Returns:
Similarity score or None if unavailable
"""
if self._mcp is None:
return None
try:
# Use Knowledge Base's search capability to compute similarity
result = await self._mcp.call_tool(
server="knowledge-base",
tool="compute_similarity",
args={
"text1": query,
"text2": context.content[
: self._semantic_max_chars
], # Limit content length
},
)
if result.success and isinstance(result.data, dict):
similarity = result.data.get("similarity")
if similarity is not None:
return self.normalize_score(float(similarity))
except Exception as e:
logger.debug(f"Semantic similarity computation failed: {e}")
return None
def _compute_keyword_score(
self,
context: BaseContext,
query: str,
) -> float:
"""
Compute relevance score based on keyword matching.
Simple but fast fallback when semantic search is unavailable.
Args:
context: Context to score
query: Query to match
Returns:
Keyword-based relevance score
"""
if not query or not context.content:
return 0.0
# Extract keywords from query
query_lower = query.lower()
content_lower = context.content.lower()
# Simple word tokenization
query_words = set(re.findall(r"\b\w{3,}\b", query_lower))
content_words = set(re.findall(r"\b\w{3,}\b", content_lower))
if not query_words:
return 0.0
# Calculate overlap
common_words = query_words & content_words
overlap_ratio = len(common_words) / len(query_words)
# Apply fallback weight ceiling
return self.normalize_score(overlap_ratio * self._keyword_fallback_weight)
async def score_batch(
self,
contexts: list[BaseContext],
query: str,
**kwargs: Any,
) -> list[float]:
"""
Score multiple contexts in parallel.
Args:
contexts: Contexts to score
query: Query to score against
**kwargs: Additional parameters
Returns:
List of scores (same order as input)
"""
import asyncio
if not contexts:
return []
tasks = [self.score(context, query, **kwargs) for context in contexts]
return await asyncio.gather(*tasks)

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"""
Context Types Module.
Provides all context types used in the Context Management Engine.
"""
from .base import (
AssembledContext,
BaseContext,
ContextPriority,
ContextType,
)
from .conversation import (
ConversationContext,
MessageRole,
)
from .knowledge import KnowledgeContext
from .system import SystemContext
from .task import (
TaskComplexity,
TaskContext,
TaskStatus,
)
from .tool import (
ToolContext,
ToolResultStatus,
)
__all__ = [
"AssembledContext",
"BaseContext",
"ContextPriority",
"ContextType",
"ConversationContext",
"KnowledgeContext",
"MessageRole",
"SystemContext",
"TaskComplexity",
"TaskContext",
"TaskStatus",
"ToolContext",
"ToolResultStatus",
]

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"""
Base Context Types and Enums.
Provides the foundation for all context types used in
the Context Management Engine.
"""
from abc import ABC, abstractmethod
from dataclasses import dataclass, field
from datetime import UTC, datetime
from enum import Enum
from typing import Any
from uuid import uuid4
class ContextType(str, Enum):
"""
Types of context that can be assembled.
Each type has specific handling, formatting, and
budget allocation rules.
"""
SYSTEM = "system"
TASK = "task"
KNOWLEDGE = "knowledge"
CONVERSATION = "conversation"
TOOL = "tool"
@classmethod
def from_string(cls, value: str) -> "ContextType":
"""
Convert string to ContextType.
Args:
value: String value
Returns:
ContextType enum value
Raises:
ValueError: If value is not a valid context type
"""
try:
return cls(value.lower())
except ValueError:
valid = ", ".join(t.value for t in cls)
raise ValueError(f"Invalid context type '{value}'. Valid types: {valid}")
class ContextPriority(int, Enum):
"""
Priority levels for context ordering.
Higher values indicate higher priority.
"""
LOWEST = 0
LOW = 25
NORMAL = 50
HIGH = 75
HIGHEST = 100
CRITICAL = 150 # Never omit
@classmethod
def from_int(cls, value: int) -> "ContextPriority":
"""
Get closest priority level for an integer.
Args:
value: Integer priority value
Returns:
Closest ContextPriority enum value
"""
priorities = sorted(cls, key=lambda p: p.value)
for priority in reversed(priorities):
if value >= priority.value:
return priority
return cls.LOWEST
@dataclass(eq=False)
class BaseContext(ABC):
"""
Abstract base class for all context types.
Provides common fields and methods for context handling,
scoring, and serialization.
"""
# Required fields
content: str
source: str
# Optional fields with defaults
id: str = field(default_factory=lambda: str(uuid4()))
timestamp: datetime = field(default_factory=lambda: datetime.now(UTC))
priority: int = field(default=ContextPriority.NORMAL.value)
metadata: dict[str, Any] = field(default_factory=dict)
# Computed/cached fields
_token_count: int | None = field(default=None, repr=False)
_score: float | None = field(default=None, repr=False)
@property
def token_count(self) -> int | None:
"""Get cached token count (None if not counted yet)."""
return self._token_count
@token_count.setter
def token_count(self, value: int) -> None:
"""Set token count."""
self._token_count = value
@property
def score(self) -> float | None:
"""Get cached score (None if not scored yet)."""
return self._score
@score.setter
def score(self, value: float) -> None:
"""Set score (clamped to 0.0-1.0)."""
self._score = max(0.0, min(1.0, value))
@abstractmethod
def get_type(self) -> ContextType:
"""
Get the type of this context.
Returns:
ContextType enum value
"""
...
def get_age_seconds(self) -> float:
"""
Get age of context in seconds.
Returns:
Age in seconds since creation
"""
now = datetime.now(UTC)
delta = now - self.timestamp
return delta.total_seconds()
def get_age_hours(self) -> float:
"""
Get age of context in hours.
Returns:
Age in hours since creation
"""
return self.get_age_seconds() / 3600
def is_stale(self, max_age_hours: float = 168.0) -> bool:
"""
Check if context is stale.
Args:
max_age_hours: Maximum age before considered stale (default 7 days)
Returns:
True if context is older than max_age_hours
"""
return self.get_age_hours() > max_age_hours
def to_dict(self) -> dict[str, Any]:
"""
Convert context to dictionary for serialization.
Returns:
Dictionary representation
"""
return {
"id": self.id,
"type": self.get_type().value,
"content": self.content,
"source": self.source,
"timestamp": self.timestamp.isoformat(),
"priority": self.priority,
"metadata": self.metadata,
"token_count": self._token_count,
"score": self._score,
}
@classmethod
def from_dict(cls, data: dict[str, Any]) -> "BaseContext":
"""
Create context from dictionary.
Note: Subclasses should override this to return correct type.
Args:
data: Dictionary with context data
Returns:
Context instance
"""
raise NotImplementedError("Subclasses must implement from_dict")
def truncate(self, max_tokens: int, suffix: str = "... [truncated]") -> str:
"""
Truncate content to fit within token limit.
This is a rough estimation based on characters.
For accurate truncation, use the TokenCalculator.
Args:
max_tokens: Maximum tokens allowed
suffix: Suffix to append when truncated
Returns:
Truncated content
"""
if self._token_count is None or self._token_count <= max_tokens:
return self.content
# Rough estimation: 4 chars per token on average
estimated_chars = max_tokens * 4
suffix_chars = len(suffix)
if len(self.content) <= estimated_chars:
return self.content
truncated = self.content[: estimated_chars - suffix_chars]
# Try to break at word boundary
last_space = truncated.rfind(" ")
if last_space > estimated_chars * 0.8:
truncated = truncated[:last_space]
return truncated + suffix
def __hash__(self) -> int:
"""Hash based on ID for set/dict usage."""
return hash(self.id)
def __eq__(self, other: object) -> bool:
"""Equality based on ID."""
if not isinstance(other, BaseContext):
return False
return self.id == other.id
@dataclass
class AssembledContext:
"""
Result of context assembly.
Contains the final formatted context ready for LLM consumption,
along with metadata about the assembly process.
"""
# Main content
content: str
total_tokens: int
# Assembly metadata
context_count: int
excluded_count: int = 0
assembly_time_ms: float = 0.0
model: str = ""
# Included contexts (optional - for inspection)
contexts: list["BaseContext"] = field(default_factory=list)
# Additional metadata from assembly
metadata: dict[str, Any] = field(default_factory=dict)
# Budget tracking
budget_total: int = 0
budget_used: int = 0
# Context breakdown
by_type: dict[str, int] = field(default_factory=dict)
# Cache info
cache_hit: bool = False
cache_key: str | None = None
# Aliases for backward compatibility
@property
def token_count(self) -> int:
"""Alias for total_tokens."""
return self.total_tokens
@property
def contexts_included(self) -> int:
"""Alias for context_count."""
return self.context_count
@property
def contexts_excluded(self) -> int:
"""Alias for excluded_count."""
return self.excluded_count
@property
def budget_utilization(self) -> float:
"""Get budget utilization percentage."""
if self.budget_total == 0:
return 0.0
return self.budget_used / self.budget_total
def to_dict(self) -> dict[str, Any]:
"""Convert to dictionary."""
return {
"content": self.content,
"total_tokens": self.total_tokens,
"context_count": self.context_count,
"excluded_count": self.excluded_count,
"assembly_time_ms": round(self.assembly_time_ms, 2),
"model": self.model,
"metadata": self.metadata,
"budget_total": self.budget_total,
"budget_used": self.budget_used,
"budget_utilization": round(self.budget_utilization, 3),
"by_type": self.by_type,
"cache_hit": self.cache_hit,
"cache_key": self.cache_key,
}
def to_json(self) -> str:
"""Convert to JSON string."""
import json
return json.dumps(self.to_dict())
@classmethod
def from_json(cls, json_str: str) -> "AssembledContext":
"""Create from JSON string."""
import json
data = json.loads(json_str)
return cls(
content=data["content"],
total_tokens=data["total_tokens"],
context_count=data["context_count"],
excluded_count=data.get("excluded_count", 0),
assembly_time_ms=data.get("assembly_time_ms", 0.0),
model=data.get("model", ""),
metadata=data.get("metadata", {}),
budget_total=data.get("budget_total", 0),
budget_used=data.get("budget_used", 0),
by_type=data.get("by_type", {}),
cache_hit=data.get("cache_hit", False),
cache_key=data.get("cache_key"),
)

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"""
Conversation Context Type.
Represents conversation history for context continuity.
"""
from dataclasses import dataclass, field
from datetime import UTC, datetime
from enum import Enum
from typing import Any
from .base import BaseContext, ContextPriority, ContextType
class MessageRole(str, Enum):
"""Roles for conversation messages."""
USER = "user"
ASSISTANT = "assistant"
SYSTEM = "system"
TOOL = "tool"
@classmethod
def from_string(cls, value: str) -> "MessageRole":
"""Convert string to MessageRole."""
try:
return cls(value.lower())
except ValueError:
# Default to user for unknown roles
return cls.USER
@dataclass(eq=False)
class ConversationContext(BaseContext):
"""
Context from conversation history.
Represents a single turn in the conversation,
including user messages, assistant responses,
and tool results.
"""
# Conversation-specific fields
role: MessageRole = field(default=MessageRole.USER)
turn_index: int = field(default=0)
session_id: str | None = field(default=None)
parent_message_id: str | None = field(default=None)
def get_type(self) -> ContextType:
"""Return CONVERSATION context type."""
return ContextType.CONVERSATION
def to_dict(self) -> dict[str, Any]:
"""Convert to dictionary with conversation-specific fields."""
base = super().to_dict()
base.update(
{
"role": self.role.value,
"turn_index": self.turn_index,
"session_id": self.session_id,
"parent_message_id": self.parent_message_id,
}
)
return base
@classmethod
def from_dict(cls, data: dict[str, Any]) -> "ConversationContext":
"""Create ConversationContext from dictionary."""
role = data.get("role", "user")
if isinstance(role, str):
role = MessageRole.from_string(role)
return cls(
id=data.get("id", ""),
content=data["content"],
source=data.get("source", "conversation"),
timestamp=datetime.fromisoformat(data["timestamp"])
if isinstance(data.get("timestamp"), str)
else data.get("timestamp", datetime.now(UTC)),
priority=data.get("priority", ContextPriority.NORMAL.value),
metadata=data.get("metadata", {}),
role=role,
turn_index=data.get("turn_index", 0),
session_id=data.get("session_id"),
parent_message_id=data.get("parent_message_id"),
)
@classmethod
def from_message(
cls,
content: str,
role: str | MessageRole,
turn_index: int = 0,
session_id: str | None = None,
timestamp: datetime | None = None,
) -> "ConversationContext":
"""
Create ConversationContext from a message.
Args:
content: Message content
role: Message role (user, assistant, system, tool)
turn_index: Position in conversation
session_id: Session identifier
timestamp: Message timestamp
Returns:
ConversationContext instance
"""
if isinstance(role, str):
role = MessageRole.from_string(role)
# Recent messages have higher priority
priority = ContextPriority.NORMAL.value
return cls(
content=content,
source="conversation",
role=role,
turn_index=turn_index,
session_id=session_id,
timestamp=timestamp or datetime.now(UTC),
priority=priority,
)
@classmethod
def from_history(
cls,
messages: list[dict[str, Any]],
session_id: str | None = None,
) -> list["ConversationContext"]:
"""
Create multiple ConversationContexts from message history.
Args:
messages: List of message dicts with 'role' and 'content'
session_id: Session identifier
Returns:
List of ConversationContext instances
"""
contexts = []
for i, msg in enumerate(messages):
ctx = cls.from_message(
content=msg.get("content", ""),
role=msg.get("role", "user"),
turn_index=i,
session_id=session_id,
timestamp=datetime.fromisoformat(msg["timestamp"])
if "timestamp" in msg
else None,
)
contexts.append(ctx)
return contexts
def is_user_message(self) -> bool:
"""Check if this is a user message."""
return self.role == MessageRole.USER
def is_assistant_message(self) -> bool:
"""Check if this is an assistant message."""
return self.role == MessageRole.ASSISTANT
def is_tool_result(self) -> bool:
"""Check if this is a tool result."""
return self.role == MessageRole.TOOL
def format_for_prompt(self) -> str:
"""
Format message for inclusion in prompt.
Returns:
Formatted message string
"""
role_labels = {
MessageRole.USER: "User",
MessageRole.ASSISTANT: "Assistant",
MessageRole.SYSTEM: "System",
MessageRole.TOOL: "Tool Result",
}
label = role_labels.get(self.role, "Unknown")
return f"{label}: {self.content}"

View File

@@ -0,0 +1,152 @@
"""
Knowledge Context Type.
Represents RAG results from the Knowledge Base MCP server.
"""
from dataclasses import dataclass, field
from datetime import UTC, datetime
from typing import Any
from .base import BaseContext, ContextPriority, ContextType
@dataclass(eq=False)
class KnowledgeContext(BaseContext):
"""
Context from knowledge base / RAG retrieval.
Knowledge context represents chunks retrieved from the
Knowledge Base MCP server, including:
- Code snippets
- Documentation
- Previous conversations
- External knowledge
Each chunk includes relevance scoring from the search.
"""
# Knowledge-specific fields
collection: str = field(default="default")
file_type: str | None = field(default=None)
chunk_index: int = field(default=0)
relevance_score: float = field(default=0.0)
search_query: str = field(default="")
def get_type(self) -> ContextType:
"""Return KNOWLEDGE context type."""
return ContextType.KNOWLEDGE
def to_dict(self) -> dict[str, Any]:
"""Convert to dictionary with knowledge-specific fields."""
base = super().to_dict()
base.update(
{
"collection": self.collection,
"file_type": self.file_type,
"chunk_index": self.chunk_index,
"relevance_score": self.relevance_score,
"search_query": self.search_query,
}
)
return base
@classmethod
def from_dict(cls, data: dict[str, Any]) -> "KnowledgeContext":
"""Create KnowledgeContext from dictionary."""
return cls(
id=data.get("id", ""),
content=data["content"],
source=data["source"],
timestamp=datetime.fromisoformat(data["timestamp"])
if isinstance(data.get("timestamp"), str)
else data.get("timestamp", datetime.now(UTC)),
priority=data.get("priority", ContextPriority.NORMAL.value),
metadata=data.get("metadata", {}),
collection=data.get("collection", "default"),
file_type=data.get("file_type"),
chunk_index=data.get("chunk_index", 0),
relevance_score=data.get("relevance_score", 0.0),
search_query=data.get("search_query", ""),
)
@classmethod
def from_search_result(
cls,
result: dict[str, Any],
query: str,
) -> "KnowledgeContext":
"""
Create KnowledgeContext from a Knowledge Base search result.
Args:
result: Search result from Knowledge Base MCP
query: Search query used
Returns:
KnowledgeContext instance
"""
return cls(
content=result.get("content", ""),
source=result.get("source_path", "unknown"),
collection=result.get("collection", "default"),
file_type=result.get("file_type"),
chunk_index=result.get("chunk_index", 0),
relevance_score=result.get("score", 0.0),
search_query=query,
metadata={
"chunk_id": result.get("id"),
"content_hash": result.get("content_hash"),
},
)
@classmethod
def from_search_results(
cls,
results: list[dict[str, Any]],
query: str,
) -> list["KnowledgeContext"]:
"""
Create multiple KnowledgeContexts from search results.
Args:
results: List of search results
query: Search query used
Returns:
List of KnowledgeContext instances
"""
return [cls.from_search_result(r, query) for r in results]
def is_code(self) -> bool:
"""Check if this is code content."""
code_types = {
"python",
"javascript",
"typescript",
"go",
"rust",
"java",
"c",
"cpp",
}
return self.file_type is not None and self.file_type.lower() in code_types
def is_documentation(self) -> bool:
"""Check if this is documentation content."""
doc_types = {"markdown", "rst", "txt", "md"}
return self.file_type is not None and self.file_type.lower() in doc_types
def get_formatted_source(self) -> str:
"""
Get a formatted source string for display.
Returns:
Formatted source string
"""
parts = [self.source]
if self.file_type:
parts.append(f"({self.file_type})")
if self.collection != "default":
parts.insert(0, f"[{self.collection}]")
return " ".join(parts)

View File

@@ -0,0 +1,138 @@
"""
System Context Type.
Represents system prompts, instructions, and agent personas.
"""
from dataclasses import dataclass, field
from datetime import UTC, datetime
from typing import Any
from .base import BaseContext, ContextPriority, ContextType
@dataclass(eq=False)
class SystemContext(BaseContext):
"""
Context for system prompts and instructions.
System context typically includes:
- Agent persona and role definitions
- Behavioral instructions
- Safety guidelines
- Output format requirements
System context is usually high priority and should
rarely be truncated or omitted.
"""
# System context specific fields
role: str = field(default="assistant")
instructions_type: str = field(default="general")
def __post_init__(self) -> None:
"""Set high priority for system context."""
# System context defaults to high priority
if self.priority == ContextPriority.NORMAL.value:
self.priority = ContextPriority.HIGH.value
def get_type(self) -> ContextType:
"""Return SYSTEM context type."""
return ContextType.SYSTEM
def to_dict(self) -> dict[str, Any]:
"""Convert to dictionary with system-specific fields."""
base = super().to_dict()
base.update(
{
"role": self.role,
"instructions_type": self.instructions_type,
}
)
return base
@classmethod
def from_dict(cls, data: dict[str, Any]) -> "SystemContext":
"""Create SystemContext from dictionary."""
return cls(
id=data.get("id", ""),
content=data["content"],
source=data["source"],
timestamp=datetime.fromisoformat(data["timestamp"])
if isinstance(data.get("timestamp"), str)
else data.get("timestamp", datetime.now(UTC)),
priority=data.get("priority", ContextPriority.HIGH.value),
metadata=data.get("metadata", {}),
role=data.get("role", "assistant"),
instructions_type=data.get("instructions_type", "general"),
)
@classmethod
def create_persona(
cls,
name: str,
description: str,
capabilities: list[str] | None = None,
constraints: list[str] | None = None,
) -> "SystemContext":
"""
Create a persona system context.
Args:
name: Agent name/role
description: Role description
capabilities: List of things the agent can do
constraints: List of limitations
Returns:
SystemContext with formatted persona
"""
parts = [f"You are {name}.", "", description]
if capabilities:
parts.append("")
parts.append("You can:")
for cap in capabilities:
parts.append(f"- {cap}")
if constraints:
parts.append("")
parts.append("You must not:")
for constraint in constraints:
parts.append(f"- {constraint}")
return cls(
content="\n".join(parts),
source="persona_builder",
role=name.lower().replace(" ", "_"),
instructions_type="persona",
priority=ContextPriority.HIGHEST.value,
)
@classmethod
def create_instructions(
cls,
instructions: str | list[str],
source: str = "instructions",
) -> "SystemContext":
"""
Create an instructions system context.
Args:
instructions: Instructions string or list of instruction strings
source: Source identifier
Returns:
SystemContext with instructions
"""
if isinstance(instructions, list):
content = "\n".join(f"- {inst}" for inst in instructions)
else:
content = instructions
return cls(
content=content,
source=source,
instructions_type="instructions",
priority=ContextPriority.HIGH.value,
)

View File

@@ -0,0 +1,193 @@
"""
Task Context Type.
Represents the current task or objective for the agent.
"""
from dataclasses import dataclass, field
from datetime import UTC, datetime
from enum import Enum
from typing import Any
from .base import BaseContext, ContextPriority, ContextType
class TaskStatus(str, Enum):
"""Status of a task."""
PENDING = "pending"
IN_PROGRESS = "in_progress"
BLOCKED = "blocked"
COMPLETED = "completed"
FAILED = "failed"
class TaskComplexity(str, Enum):
"""Complexity level of a task."""
TRIVIAL = "trivial"
SIMPLE = "simple"
MODERATE = "moderate"
COMPLEX = "complex"
VERY_COMPLEX = "very_complex"
@dataclass(eq=False)
class TaskContext(BaseContext):
"""
Context for the current task or objective.
Task context provides information about what the agent
should accomplish, including:
- Task description and goals
- Acceptance criteria
- Constraints and requirements
- Related issue/ticket information
"""
# Task-specific fields
title: str = field(default="")
status: TaskStatus = field(default=TaskStatus.PENDING)
complexity: TaskComplexity = field(default=TaskComplexity.MODERATE)
issue_id: str | None = field(default=None)
project_id: str | None = field(default=None)
acceptance_criteria: list[str] = field(default_factory=list)
constraints: list[str] = field(default_factory=list)
parent_task_id: str | None = field(default=None)
# Note: TaskContext should typically have HIGH priority,
# but we don't auto-promote to allow explicit priority setting.
# Use TaskContext.create() for default HIGH priority behavior.
def get_type(self) -> ContextType:
"""Return TASK context type."""
return ContextType.TASK
def to_dict(self) -> dict[str, Any]:
"""Convert to dictionary with task-specific fields."""
base = super().to_dict()
base.update(
{
"title": self.title,
"status": self.status.value,
"complexity": self.complexity.value,
"issue_id": self.issue_id,
"project_id": self.project_id,
"acceptance_criteria": self.acceptance_criteria,
"constraints": self.constraints,
"parent_task_id": self.parent_task_id,
}
)
return base
@classmethod
def from_dict(cls, data: dict[str, Any]) -> "TaskContext":
"""Create TaskContext from dictionary."""
status = data.get("status", "pending")
if isinstance(status, str):
status = TaskStatus(status)
complexity = data.get("complexity", "moderate")
if isinstance(complexity, str):
complexity = TaskComplexity(complexity)
return cls(
id=data.get("id", ""),
content=data["content"],
source=data.get("source", "task"),
timestamp=datetime.fromisoformat(data["timestamp"])
if isinstance(data.get("timestamp"), str)
else data.get("timestamp", datetime.now(UTC)),
priority=data.get("priority", ContextPriority.HIGH.value),
metadata=data.get("metadata", {}),
title=data.get("title", ""),
status=status,
complexity=complexity,
issue_id=data.get("issue_id"),
project_id=data.get("project_id"),
acceptance_criteria=data.get("acceptance_criteria", []),
constraints=data.get("constraints", []),
parent_task_id=data.get("parent_task_id"),
)
@classmethod
def create(
cls,
title: str,
description: str,
acceptance_criteria: list[str] | None = None,
constraints: list[str] | None = None,
issue_id: str | None = None,
project_id: str | None = None,
complexity: TaskComplexity | str = TaskComplexity.MODERATE,
) -> "TaskContext":
"""
Create a task context.
Args:
title: Task title
description: Task description
acceptance_criteria: List of acceptance criteria
constraints: List of constraints
issue_id: Related issue ID
project_id: Project ID
complexity: Task complexity
Returns:
TaskContext instance
"""
if isinstance(complexity, str):
complexity = TaskComplexity(complexity)
return cls(
content=description,
source=f"task:{issue_id}" if issue_id else "task",
title=title,
status=TaskStatus.IN_PROGRESS,
complexity=complexity,
issue_id=issue_id,
project_id=project_id,
acceptance_criteria=acceptance_criteria or [],
constraints=constraints or [],
)
def format_for_prompt(self) -> str:
"""
Format task for inclusion in prompt.
Returns:
Formatted task string
"""
parts = []
if self.title:
parts.append(f"Task: {self.title}")
parts.append("")
parts.append(self.content)
if self.acceptance_criteria:
parts.append("")
parts.append("Acceptance Criteria:")
for criterion in self.acceptance_criteria:
parts.append(f"- {criterion}")
if self.constraints:
parts.append("")
parts.append("Constraints:")
for constraint in self.constraints:
parts.append(f"- {constraint}")
return "\n".join(parts)
def is_active(self) -> bool:
"""Check if task is currently active."""
return self.status in (TaskStatus.PENDING, TaskStatus.IN_PROGRESS)
def is_complete(self) -> bool:
"""Check if task is complete."""
return self.status == TaskStatus.COMPLETED
def is_blocked(self) -> bool:
"""Check if task is blocked."""
return self.status == TaskStatus.BLOCKED

View File

@@ -0,0 +1,211 @@
"""
Tool Context Type.
Represents available tools and recent tool execution results.
"""
from dataclasses import dataclass, field
from datetime import UTC, datetime
from enum import Enum
from typing import Any
from .base import BaseContext, ContextPriority, ContextType
class ToolResultStatus(str, Enum):
"""Status of a tool execution result."""
SUCCESS = "success"
ERROR = "error"
TIMEOUT = "timeout"
CANCELLED = "cancelled"
@dataclass(eq=False)
class ToolContext(BaseContext):
"""
Context for tools and tool execution results.
Tool context includes:
- Tool descriptions and parameters
- Recent tool execution results
- Tool availability information
This helps the LLM understand what tools are available
and what results previous tool calls produced.
"""
# Tool-specific fields
tool_name: str = field(default="")
tool_description: str = field(default="")
is_result: bool = field(default=False)
result_status: ToolResultStatus | None = field(default=None)
execution_time_ms: float | None = field(default=None)
parameters: dict[str, Any] = field(default_factory=dict)
server_name: str | None = field(default=None)
def get_type(self) -> ContextType:
"""Return TOOL context type."""
return ContextType.TOOL
def to_dict(self) -> dict[str, Any]:
"""Convert to dictionary with tool-specific fields."""
base = super().to_dict()
base.update(
{
"tool_name": self.tool_name,
"tool_description": self.tool_description,
"is_result": self.is_result,
"result_status": self.result_status.value
if self.result_status
else None,
"execution_time_ms": self.execution_time_ms,
"parameters": self.parameters,
"server_name": self.server_name,
}
)
return base
@classmethod
def from_dict(cls, data: dict[str, Any]) -> "ToolContext":
"""Create ToolContext from dictionary."""
result_status = data.get("result_status")
if isinstance(result_status, str):
result_status = ToolResultStatus(result_status)
return cls(
id=data.get("id", ""),
content=data["content"],
source=data.get("source", "tool"),
timestamp=datetime.fromisoformat(data["timestamp"])
if isinstance(data.get("timestamp"), str)
else data.get("timestamp", datetime.now(UTC)),
priority=data.get("priority", ContextPriority.NORMAL.value),
metadata=data.get("metadata", {}),
tool_name=data.get("tool_name", ""),
tool_description=data.get("tool_description", ""),
is_result=data.get("is_result", False),
result_status=result_status,
execution_time_ms=data.get("execution_time_ms"),
parameters=data.get("parameters", {}),
server_name=data.get("server_name"),
)
@classmethod
def from_tool_definition(
cls,
name: str,
description: str,
parameters: dict[str, Any] | None = None,
server_name: str | None = None,
) -> "ToolContext":
"""
Create a ToolContext from a tool definition.
Args:
name: Tool name
description: Tool description
parameters: Tool parameter schema
server_name: MCP server name
Returns:
ToolContext instance
"""
# Format content as tool documentation
content_parts = [f"Tool: {name}", "", description]
if parameters:
content_parts.append("")
content_parts.append("Parameters:")
for param_name, param_info in parameters.items():
param_type = param_info.get("type", "any")
param_desc = param_info.get("description", "")
required = param_info.get("required", False)
req_marker = " (required)" if required else ""
content_parts.append(f" - {param_name}: {param_type}{req_marker}")
if param_desc:
content_parts.append(f" {param_desc}")
return cls(
content="\n".join(content_parts),
source=f"tool:{server_name}:{name}" if server_name else f"tool:{name}",
tool_name=name,
tool_description=description,
is_result=False,
parameters=parameters or {},
server_name=server_name,
priority=ContextPriority.LOW.value,
)
@classmethod
def from_tool_result(
cls,
tool_name: str,
result: Any,
status: ToolResultStatus = ToolResultStatus.SUCCESS,
execution_time_ms: float | None = None,
parameters: dict[str, Any] | None = None,
server_name: str | None = None,
) -> "ToolContext":
"""
Create a ToolContext from a tool execution result.
Args:
tool_name: Name of the tool that was executed
result: Result content (will be converted to string)
status: Execution status
execution_time_ms: Execution time in milliseconds
parameters: Parameters that were passed to the tool
server_name: MCP server name
Returns:
ToolContext instance
"""
# Convert result to string content
if isinstance(result, str):
content = result
elif isinstance(result, dict):
import json
try:
content = json.dumps(result, indent=2)
except (TypeError, ValueError):
content = str(result)
else:
content = str(result)
return cls(
content=content,
source=f"tool_result:{server_name}:{tool_name}"
if server_name
else f"tool_result:{tool_name}",
tool_name=tool_name,
is_result=True,
result_status=status,
execution_time_ms=execution_time_ms,
parameters=parameters or {},
server_name=server_name,
priority=ContextPriority.HIGH.value, # Recent results are high priority
)
def is_successful(self) -> bool:
"""Check if this is a successful tool result."""
return self.is_result and self.result_status == ToolResultStatus.SUCCESS
def is_error(self) -> bool:
"""Check if this is an error result."""
return self.is_result and self.result_status == ToolResultStatus.ERROR
def format_for_prompt(self) -> str:
"""
Format tool context for inclusion in prompt.
Returns:
Formatted tool string
"""
if self.is_result:
status_str = self.result_status.value if self.result_status else "unknown"
header = f"Tool Result ({self.tool_name}, {status_str}):"
return f"{header}\n{self.content}"
else:
return self.content

View File

@@ -24,6 +24,9 @@ from ..models import (
logger = logging.getLogger(__name__)
# Sentinel for distinguishing "no argument passed" from "explicitly passing None"
_UNSET = object()
class AuditLogger:
"""
@@ -142,8 +145,10 @@ class AuditLogger:
# Add hash chain for tamper detection
if self._enable_hash_chain:
event_hash = self._compute_hash(event)
sanitized_details["_hash"] = event_hash
sanitized_details["_prev_hash"] = self._last_hash
# Modify event.details directly (not sanitized_details)
# to ensure the hash is stored on the actual event
event.details["_hash"] = event_hash
event.details["_prev_hash"] = self._last_hash
self._last_hash = event_hash
self._buffer.append(event)
@@ -415,7 +420,8 @@ class AuditLogger:
)
if stored_hash:
computed = self._compute_hash(event)
# Pass prev_hash to compute hash with correct chain position
computed = self._compute_hash(event, prev_hash=prev_hash)
if computed != stored_hash:
issues.append(
f"Hash mismatch at event {event.id}: "
@@ -462,9 +468,23 @@ class AuditLogger:
return sanitized
def _compute_hash(self, event: AuditEvent) -> str:
"""Compute hash for an event (excluding hash fields)."""
data = {
def _compute_hash(
self, event: AuditEvent, prev_hash: str | None | object = _UNSET
) -> str:
"""Compute hash for an event (excluding hash fields).
Args:
event: The audit event to hash.
prev_hash: Optional previous hash to use instead of self._last_hash.
Pass this during verification to use the correct chain.
Use None explicitly to indicate no previous hash.
"""
# Use passed prev_hash if explicitly provided, otherwise use instance state
effective_prev: str | None = (
self._last_hash if prev_hash is _UNSET else prev_hash # type: ignore[assignment]
)
data: dict[str, str | dict[str, str] | None] = {
"id": event.id,
"event_type": event.event_type.value,
"timestamp": event.timestamp.isoformat(),
@@ -480,8 +500,8 @@ class AuditLogger:
"correlation_id": event.correlation_id,
}
if self._last_hash:
data["_prev_hash"] = self._last_hash
if effective_prev:
data["_prev_hash"] = effective_prev
serialized = json.dumps(data, sort_keys=True, default=str)
return hashlib.sha256(serialized.encode()).hexdigest()

View File

@@ -0,0 +1 @@
"""Tests for Context Management Engine."""

View File

@@ -0,0 +1,518 @@
"""Tests for model adapters."""
from app.services.context.adapters import (
ClaudeAdapter,
DefaultAdapter,
OpenAIAdapter,
get_adapter,
)
from app.services.context.types import (
ContextType,
ConversationContext,
KnowledgeContext,
MessageRole,
SystemContext,
TaskContext,
ToolContext,
)
class TestGetAdapter:
"""Tests for get_adapter function."""
def test_claude_models(self) -> None:
"""Test that Claude models get ClaudeAdapter."""
assert isinstance(get_adapter("claude-3-sonnet"), ClaudeAdapter)
assert isinstance(get_adapter("claude-3-opus"), ClaudeAdapter)
assert isinstance(get_adapter("claude-3-haiku"), ClaudeAdapter)
assert isinstance(get_adapter("claude-2"), ClaudeAdapter)
assert isinstance(get_adapter("anthropic/claude-3-sonnet"), ClaudeAdapter)
def test_openai_models(self) -> None:
"""Test that OpenAI models get OpenAIAdapter."""
assert isinstance(get_adapter("gpt-4"), OpenAIAdapter)
assert isinstance(get_adapter("gpt-4-turbo"), OpenAIAdapter)
assert isinstance(get_adapter("gpt-3.5-turbo"), OpenAIAdapter)
assert isinstance(get_adapter("openai/gpt-4"), OpenAIAdapter)
assert isinstance(get_adapter("o1-mini"), OpenAIAdapter)
assert isinstance(get_adapter("o3-mini"), OpenAIAdapter)
def test_unknown_models(self) -> None:
"""Test that unknown models get DefaultAdapter."""
assert isinstance(get_adapter("llama-2"), DefaultAdapter)
assert isinstance(get_adapter("mistral-7b"), DefaultAdapter)
assert isinstance(get_adapter("custom-model"), DefaultAdapter)
class TestModelAdapterBase:
"""Tests for ModelAdapter base class."""
def test_get_type_order(self) -> None:
"""Test default type ordering."""
adapter = DefaultAdapter()
order = adapter.get_type_order()
assert order == [
ContextType.SYSTEM,
ContextType.TASK,
ContextType.KNOWLEDGE,
ContextType.CONVERSATION,
ContextType.TOOL,
]
def test_group_by_type(self) -> None:
"""Test grouping contexts by type."""
adapter = DefaultAdapter()
contexts = [
SystemContext(content="System", source="system"),
TaskContext(content="Task", source="task"),
KnowledgeContext(content="Knowledge", source="docs"),
SystemContext(content="System 2", source="system"),
]
grouped = adapter.group_by_type(contexts)
assert len(grouped[ContextType.SYSTEM]) == 2
assert len(grouped[ContextType.TASK]) == 1
assert len(grouped[ContextType.KNOWLEDGE]) == 1
assert ContextType.CONVERSATION not in grouped
def test_matches_model_default(self) -> None:
"""Test that DefaultAdapter matches all models."""
assert DefaultAdapter.matches_model("anything")
assert DefaultAdapter.matches_model("claude-3")
assert DefaultAdapter.matches_model("gpt-4")
class TestDefaultAdapter:
"""Tests for DefaultAdapter."""
def test_format_empty(self) -> None:
"""Test formatting empty context list."""
adapter = DefaultAdapter()
result = adapter.format([])
assert result == ""
def test_format_system(self) -> None:
"""Test formatting system context."""
adapter = DefaultAdapter()
contexts = [
SystemContext(content="You are helpful.", source="system"),
]
result = adapter.format(contexts)
assert "You are helpful." in result
def test_format_task(self) -> None:
"""Test formatting task context."""
adapter = DefaultAdapter()
contexts = [
TaskContext(content="Write a function.", source="task"),
]
result = adapter.format(contexts)
assert "Task:" in result
assert "Write a function." in result
def test_format_knowledge(self) -> None:
"""Test formatting knowledge context."""
adapter = DefaultAdapter()
contexts = [
KnowledgeContext(content="Documentation here.", source="docs"),
]
result = adapter.format(contexts)
assert "Reference Information:" in result
assert "Documentation here." in result
def test_format_conversation(self) -> None:
"""Test formatting conversation context."""
adapter = DefaultAdapter()
contexts = [
ConversationContext(
content="Hello!",
source="chat",
role=MessageRole.USER,
),
]
result = adapter.format(contexts)
assert "Previous Conversation:" in result
assert "Hello!" in result
def test_format_tool(self) -> None:
"""Test formatting tool context."""
adapter = DefaultAdapter()
contexts = [
ToolContext(
content="Result: success",
source="tool",
metadata={"tool_name": "search"},
),
]
result = adapter.format(contexts)
assert "Tool Results:" in result
assert "Result: success" in result
class TestClaudeAdapter:
"""Tests for ClaudeAdapter."""
def test_matches_model(self) -> None:
"""Test model matching."""
assert ClaudeAdapter.matches_model("claude-3-sonnet")
assert ClaudeAdapter.matches_model("claude-3-opus")
assert ClaudeAdapter.matches_model("anthropic/claude-3-haiku")
assert not ClaudeAdapter.matches_model("gpt-4")
assert not ClaudeAdapter.matches_model("llama-2")
def test_format_empty(self) -> None:
"""Test formatting empty context list."""
adapter = ClaudeAdapter()
result = adapter.format([])
assert result == ""
def test_format_system_uses_xml(self) -> None:
"""Test that system context uses XML tags."""
adapter = ClaudeAdapter()
contexts = [
SystemContext(content="You are helpful.", source="system"),
]
result = adapter.format(contexts)
assert "<system_instructions>" in result
assert "</system_instructions>" in result
assert "You are helpful." in result
def test_format_task_uses_xml(self) -> None:
"""Test that task context uses XML tags."""
adapter = ClaudeAdapter()
contexts = [
TaskContext(content="Write a function.", source="task"),
]
result = adapter.format(contexts)
assert "<current_task>" in result
assert "</current_task>" in result
assert "Write a function." in result
def test_format_knowledge_uses_document_tags(self) -> None:
"""Test that knowledge uses document XML tags."""
adapter = ClaudeAdapter()
contexts = [
KnowledgeContext(
content="Documentation here.",
source="docs/api.md",
relevance_score=0.9,
),
]
result = adapter.format(contexts)
assert "<reference_documents>" in result
assert "</reference_documents>" in result
assert '<document source="docs/api.md"' in result
assert "</document>" in result
assert "Documentation here." in result
def test_format_knowledge_with_score(self) -> None:
"""Test that knowledge includes relevance score."""
adapter = ClaudeAdapter()
contexts = [
KnowledgeContext(
content="Doc content.",
source="docs/api.md",
metadata={"relevance_score": 0.95},
),
]
result = adapter.format(contexts)
assert 'relevance="0.95"' in result
def test_format_conversation_uses_message_tags(self) -> None:
"""Test that conversation uses message XML tags."""
adapter = ClaudeAdapter()
contexts = [
ConversationContext(
content="Hello!",
source="chat",
role=MessageRole.USER,
metadata={"role": "user"},
),
ConversationContext(
content="Hi there!",
source="chat",
role=MessageRole.ASSISTANT,
metadata={"role": "assistant"},
),
]
result = adapter.format(contexts)
assert "<conversation_history>" in result
assert "</conversation_history>" in result
assert '<message role="user">' in result
assert '<message role="assistant">' in result
assert "Hello!" in result
assert "Hi there!" in result
def test_format_tool_uses_tool_result_tags(self) -> None:
"""Test that tool results use tool_result XML tags."""
adapter = ClaudeAdapter()
contexts = [
ToolContext(
content='{"status": "ok"}',
source="tool",
metadata={"tool_name": "search", "status": "success"},
),
]
result = adapter.format(contexts)
assert "<tool_results>" in result
assert "</tool_results>" in result
assert '<tool_result name="search"' in result
assert 'status="success"' in result
assert "</tool_result>" in result
def test_format_multiple_types_in_order(self) -> None:
"""Test that multiple types are formatted in correct order."""
adapter = ClaudeAdapter()
contexts = [
KnowledgeContext(content="Knowledge", source="docs"),
SystemContext(content="System", source="system"),
TaskContext(content="Task", source="task"),
]
result = adapter.format(contexts)
# Find positions
system_pos = result.find("<system_instructions>")
task_pos = result.find("<current_task>")
knowledge_pos = result.find("<reference_documents>")
# Verify order
assert system_pos < task_pos < knowledge_pos
def test_escape_xml_in_source(self) -> None:
"""Test that XML special chars are escaped in source."""
adapter = ClaudeAdapter()
contexts = [
KnowledgeContext(
content="Doc content.",
source='path/with"quotes&stuff.md',
),
]
result = adapter.format(contexts)
assert "&quot;" in result
assert "&amp;" in result
class TestOpenAIAdapter:
"""Tests for OpenAIAdapter."""
def test_matches_model(self) -> None:
"""Test model matching."""
assert OpenAIAdapter.matches_model("gpt-4")
assert OpenAIAdapter.matches_model("gpt-4-turbo")
assert OpenAIAdapter.matches_model("gpt-3.5-turbo")
assert OpenAIAdapter.matches_model("openai/gpt-4")
assert OpenAIAdapter.matches_model("o1-preview")
assert OpenAIAdapter.matches_model("o3-mini")
assert not OpenAIAdapter.matches_model("claude-3")
assert not OpenAIAdapter.matches_model("llama-2")
def test_format_empty(self) -> None:
"""Test formatting empty context list."""
adapter = OpenAIAdapter()
result = adapter.format([])
assert result == ""
def test_format_system_plain(self) -> None:
"""Test that system content is plain."""
adapter = OpenAIAdapter()
contexts = [
SystemContext(content="You are helpful.", source="system"),
]
result = adapter.format(contexts)
# System content should be plain without headers
assert "You are helpful." in result
assert "##" not in result # No markdown headers for system
def test_format_task_uses_markdown(self) -> None:
"""Test that task uses markdown headers."""
adapter = OpenAIAdapter()
contexts = [
TaskContext(content="Write a function.", source="task"),
]
result = adapter.format(contexts)
assert "## Current Task" in result
assert "Write a function." in result
def test_format_knowledge_uses_markdown(self) -> None:
"""Test that knowledge uses markdown with source headers."""
adapter = OpenAIAdapter()
contexts = [
KnowledgeContext(
content="Documentation here.",
source="docs/api.md",
relevance_score=0.9,
),
]
result = adapter.format(contexts)
assert "## Reference Documents" in result
assert "### Source: docs/api.md" in result
assert "Documentation here." in result
def test_format_knowledge_with_score(self) -> None:
"""Test that knowledge includes relevance score."""
adapter = OpenAIAdapter()
contexts = [
KnowledgeContext(
content="Doc content.",
source="docs/api.md",
metadata={"relevance_score": 0.95},
),
]
result = adapter.format(contexts)
assert "(relevance: 0.95)" in result
def test_format_conversation_uses_bold_roles(self) -> None:
"""Test that conversation uses bold role labels."""
adapter = OpenAIAdapter()
contexts = [
ConversationContext(
content="Hello!",
source="chat",
role=MessageRole.USER,
metadata={"role": "user"},
),
ConversationContext(
content="Hi there!",
source="chat",
role=MessageRole.ASSISTANT,
metadata={"role": "assistant"},
),
]
result = adapter.format(contexts)
assert "**USER**:" in result
assert "**ASSISTANT**:" in result
assert "Hello!" in result
assert "Hi there!" in result
def test_format_tool_uses_code_blocks(self) -> None:
"""Test that tool results use code blocks."""
adapter = OpenAIAdapter()
contexts = [
ToolContext(
content='{"status": "ok"}',
source="tool",
metadata={"tool_name": "search", "status": "success"},
),
]
result = adapter.format(contexts)
assert "## Recent Tool Results" in result
assert "### Tool: search (success)" in result
assert "```" in result # Code block
assert '{"status": "ok"}' in result
def test_format_multiple_types_in_order(self) -> None:
"""Test that multiple types are formatted in correct order."""
adapter = OpenAIAdapter()
contexts = [
KnowledgeContext(content="Knowledge", source="docs"),
SystemContext(content="System", source="system"),
TaskContext(content="Task", source="task"),
]
result = adapter.format(contexts)
# System comes first (no header), then task, then knowledge
system_pos = result.find("System")
task_pos = result.find("## Current Task")
knowledge_pos = result.find("## Reference Documents")
assert system_pos < task_pos < knowledge_pos
class TestAdapterIntegration:
"""Integration tests for adapters."""
def test_full_context_formatting_claude(self) -> None:
"""Test formatting a full set of contexts for Claude."""
adapter = ClaudeAdapter()
contexts = [
SystemContext(
content="You are an expert Python developer.",
source="system",
),
TaskContext(
content="Implement user authentication.",
source="task:AUTH-123",
),
KnowledgeContext(
content="JWT tokens provide stateless authentication...",
source="docs/auth/jwt.md",
relevance_score=0.9,
),
ConversationContext(
content="Can you help me implement JWT auth?",
source="chat",
role=MessageRole.USER,
metadata={"role": "user"},
),
ToolContext(
content='{"file": "auth.py", "status": "created"}',
source="tool",
metadata={"tool_name": "file_create"},
),
]
result = adapter.format(contexts)
# Verify all sections present
assert "<system_instructions>" in result
assert "<current_task>" in result
assert "<reference_documents>" in result
assert "<conversation_history>" in result
assert "<tool_results>" in result
# Verify content
assert "expert Python developer" in result
assert "user authentication" in result
assert "JWT tokens" in result
assert "help me implement" in result
assert "file_create" in result
def test_full_context_formatting_openai(self) -> None:
"""Test formatting a full set of contexts for OpenAI."""
adapter = OpenAIAdapter()
contexts = [
SystemContext(
content="You are an expert Python developer.",
source="system",
),
TaskContext(
content="Implement user authentication.",
source="task:AUTH-123",
),
KnowledgeContext(
content="JWT tokens provide stateless authentication...",
source="docs/auth/jwt.md",
relevance_score=0.9,
),
ConversationContext(
content="Can you help me implement JWT auth?",
source="chat",
role=MessageRole.USER,
metadata={"role": "user"},
),
ToolContext(
content='{"file": "auth.py", "status": "created"}',
source="tool",
metadata={"tool_name": "file_create"},
),
]
result = adapter.format(contexts)
# Verify all sections present
assert "## Current Task" in result
assert "## Reference Documents" in result
assert "## Recent Tool Results" in result
assert "**USER**:" in result
# Verify content
assert "expert Python developer" in result
assert "user authentication" in result
assert "JWT tokens" in result
assert "help me implement" in result
assert "file_create" in result

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"""Tests for context assembly pipeline."""
from datetime import UTC, datetime
import pytest
from app.services.context.assembly import ContextPipeline, PipelineMetrics
from app.services.context.budget import TokenBudget
from app.services.context.types import (
AssembledContext,
ConversationContext,
KnowledgeContext,
MessageRole,
SystemContext,
TaskContext,
ToolContext,
)
class TestPipelineMetrics:
"""Tests for PipelineMetrics dataclass."""
def test_creation(self) -> None:
"""Test metrics creation."""
metrics = PipelineMetrics()
assert metrics.total_contexts == 0
assert metrics.selected_contexts == 0
assert metrics.assembly_time_ms == 0.0
def test_to_dict(self) -> None:
"""Test conversion to dictionary."""
metrics = PipelineMetrics(
total_contexts=10,
selected_contexts=8,
excluded_contexts=2,
total_tokens=500,
assembly_time_ms=25.5,
)
metrics.end_time = datetime.now(UTC)
data = metrics.to_dict()
assert data["total_contexts"] == 10
assert data["selected_contexts"] == 8
assert data["excluded_contexts"] == 2
assert data["total_tokens"] == 500
assert data["assembly_time_ms"] == 25.5
assert "start_time" in data
assert "end_time" in data
class TestContextPipeline:
"""Tests for ContextPipeline."""
def test_creation(self) -> None:
"""Test pipeline creation."""
pipeline = ContextPipeline()
assert pipeline._calculator is not None
assert pipeline._scorer is not None
assert pipeline._ranker is not None
assert pipeline._compressor is not None
assert pipeline._allocator is not None
@pytest.mark.asyncio
async def test_assemble_empty_contexts(self) -> None:
"""Test assembling empty context list."""
pipeline = ContextPipeline()
result = await pipeline.assemble(
contexts=[],
query="test query",
model="claude-3-sonnet",
)
assert isinstance(result, AssembledContext)
assert result.context_count == 0
assert result.total_tokens == 0
@pytest.mark.asyncio
async def test_assemble_single_context(self) -> None:
"""Test assembling single context."""
pipeline = ContextPipeline()
contexts = [
SystemContext(
content="You are a helpful assistant.",
source="system",
)
]
result = await pipeline.assemble(
contexts=contexts,
query="help me",
model="claude-3-sonnet",
)
assert result.context_count == 1
assert result.total_tokens > 0
assert "helpful assistant" in result.content
@pytest.mark.asyncio
async def test_assemble_multiple_types(self) -> None:
"""Test assembling multiple context types."""
pipeline = ContextPipeline()
contexts = [
SystemContext(
content="You are a coding assistant.",
source="system",
),
TaskContext(
content="Implement a login feature.",
source="task",
),
KnowledgeContext(
content="Authentication best practices include...",
source="docs/auth.md",
relevance_score=0.8,
),
]
result = await pipeline.assemble(
contexts=contexts,
query="implement login",
model="claude-3-sonnet",
)
assert result.context_count >= 1
assert result.total_tokens > 0
@pytest.mark.asyncio
async def test_assemble_with_custom_budget(self) -> None:
"""Test assembling with custom budget."""
pipeline = ContextPipeline()
budget = TokenBudget(
total=1000,
system=200,
task=200,
knowledge=400,
conversation=100,
tools=50,
response_reserve=50,
)
contexts = [
SystemContext(content="System prompt", source="system"),
TaskContext(content="Task description", source="task"),
]
result = await pipeline.assemble(
contexts=contexts,
query="test",
model="gpt-4",
custom_budget=budget,
)
assert result.context_count >= 1
@pytest.mark.asyncio
async def test_assemble_with_max_tokens(self) -> None:
"""Test assembling with max_tokens limit."""
pipeline = ContextPipeline()
contexts = [
SystemContext(content="System prompt", source="system"),
]
result = await pipeline.assemble(
contexts=contexts,
query="test",
model="gpt-4",
max_tokens=5000,
)
assert "budget" in result.metadata
assert result.metadata["budget"]["total"] == 5000
@pytest.mark.asyncio
async def test_assemble_format_output(self) -> None:
"""Test formatted vs unformatted output."""
pipeline = ContextPipeline()
contexts = [
SystemContext(content="System prompt", source="system"),
]
# Formatted (default)
result_formatted = await pipeline.assemble(
contexts=contexts,
query="test",
model="claude-3-sonnet",
format_output=True,
)
# Unformatted
result_raw = await pipeline.assemble(
contexts=contexts,
query="test",
model="claude-3-sonnet",
format_output=False,
)
# Formatted should have XML tags for Claude
assert "<system_instructions>" in result_formatted.content
# Raw should not
assert "<system_instructions>" not in result_raw.content
@pytest.mark.asyncio
async def test_assemble_metrics(self) -> None:
"""Test that metrics are populated."""
pipeline = ContextPipeline()
contexts = [
SystemContext(content="System", source="system"),
TaskContext(content="Task", source="task"),
KnowledgeContext(
content="Knowledge",
source="docs",
relevance_score=0.9,
),
]
result = await pipeline.assemble(
contexts=contexts,
query="test",
model="claude-3-sonnet",
)
assert "metrics" in result.metadata
metrics = result.metadata["metrics"]
assert metrics["total_contexts"] == 3
assert metrics["assembly_time_ms"] > 0
assert "scoring_time_ms" in metrics
assert "formatting_time_ms" in metrics
@pytest.mark.asyncio
async def test_assemble_with_compression_disabled(self) -> None:
"""Test assembling with compression disabled."""
pipeline = ContextPipeline()
contexts = [
KnowledgeContext(content="A" * 1000, source="docs"),
]
result = await pipeline.assemble(
contexts=contexts,
query="test",
model="gpt-4",
compress=False,
)
# Should still work, just no compression applied
assert result.context_count >= 0
class TestContextPipelineFormatting:
"""Tests for context formatting."""
@pytest.mark.asyncio
async def test_format_claude_uses_xml(self) -> None:
"""Test that Claude models use XML formatting."""
pipeline = ContextPipeline()
contexts = [
SystemContext(content="System prompt", source="system"),
TaskContext(content="Task", source="task"),
KnowledgeContext(
content="Knowledge",
source="docs",
relevance_score=0.9,
),
]
result = await pipeline.assemble(
contexts=contexts,
query="test",
model="claude-3-sonnet",
)
# Claude should have XML tags
assert "<system_instructions>" in result.content or result.context_count == 0
@pytest.mark.asyncio
async def test_format_openai_uses_markdown(self) -> None:
"""Test that OpenAI models use markdown formatting."""
pipeline = ContextPipeline()
contexts = [
TaskContext(content="Task description", source="task"),
]
result = await pipeline.assemble(
contexts=contexts,
query="test",
model="gpt-4",
)
# OpenAI should have markdown headers
if result.context_count > 0 and "Task" in result.content:
assert "## Current Task" in result.content
@pytest.mark.asyncio
async def test_format_knowledge_claude(self) -> None:
"""Test knowledge formatting for Claude."""
pipeline = ContextPipeline()
contexts = [
KnowledgeContext(
content="Document content here",
source="docs/file.md",
relevance_score=0.9,
),
]
result = await pipeline.assemble(
contexts=contexts,
query="test",
model="claude-3-sonnet",
)
if result.context_count > 0:
assert "<reference_documents>" in result.content
assert "<document" in result.content
@pytest.mark.asyncio
async def test_format_conversation(self) -> None:
"""Test conversation formatting."""
pipeline = ContextPipeline()
contexts = [
ConversationContext(
content="Hello, how are you?",
source="chat",
role=MessageRole.USER,
metadata={"role": "user"},
),
ConversationContext(
content="I'm doing great!",
source="chat",
role=MessageRole.ASSISTANT,
metadata={"role": "assistant"},
),
]
result = await pipeline.assemble(
contexts=contexts,
query="test",
model="claude-3-sonnet",
)
if result.context_count > 0:
assert "<conversation_history>" in result.content
assert (
'<message role="user">' in result.content
or 'role="user"' in result.content
)
@pytest.mark.asyncio
async def test_format_tool_results(self) -> None:
"""Test tool result formatting."""
pipeline = ContextPipeline()
contexts = [
ToolContext(
content="Tool output here",
source="tool",
metadata={"tool_name": "search"},
),
]
result = await pipeline.assemble(
contexts=contexts,
query="test",
model="claude-3-sonnet",
)
if result.context_count > 0:
assert "<tool_results>" in result.content
class TestContextPipelineIntegration:
"""Integration tests for full pipeline."""
@pytest.mark.asyncio
async def test_full_pipeline_workflow(self) -> None:
"""Test complete pipeline workflow."""
pipeline = ContextPipeline()
# Create realistic context mix
contexts = [
SystemContext(
content="You are an expert Python developer.",
source="system",
),
TaskContext(
content="Implement a user authentication system.",
source="task:AUTH-123",
),
KnowledgeContext(
content="JWT tokens provide stateless authentication...",
source="docs/auth/jwt.md",
relevance_score=0.9,
),
KnowledgeContext(
content="OAuth 2.0 is an authorization framework...",
source="docs/auth/oauth.md",
relevance_score=0.7,
),
ConversationContext(
content="Can you help me implement JWT auth?",
source="chat",
role=MessageRole.USER,
metadata={"role": "user"},
),
]
result = await pipeline.assemble(
contexts=contexts,
query="implement JWT authentication",
model="claude-3-sonnet",
)
# Verify result
assert isinstance(result, AssembledContext)
assert result.context_count > 0
assert result.total_tokens > 0
assert result.assembly_time_ms > 0
assert result.model == "claude-3-sonnet"
assert len(result.content) > 0
# Verify metrics
assert "metrics" in result.metadata
assert "query" in result.metadata
assert "budget" in result.metadata
@pytest.mark.asyncio
async def test_context_type_ordering(self) -> None:
"""Test that contexts are ordered by type correctly."""
pipeline = ContextPipeline()
# Add in random order
contexts = [
KnowledgeContext(content="Knowledge", source="docs", relevance_score=0.9),
ToolContext(content="Tool", source="tool", metadata={"tool_name": "test"}),
SystemContext(content="System", source="system"),
ConversationContext(
content="Chat",
source="chat",
role=MessageRole.USER,
metadata={"role": "user"},
),
TaskContext(content="Task", source="task"),
]
result = await pipeline.assemble(
contexts=contexts,
query="test",
model="claude-3-sonnet",
)
# For Claude, verify order: System -> Task -> Knowledge -> Conversation -> Tool
content = result.content
if result.context_count > 0:
# Find positions (if they exist)
system_pos = content.find("system_instructions")
task_pos = content.find("current_task")
knowledge_pos = content.find("reference_documents")
conversation_pos = content.find("conversation_history")
tool_pos = content.find("tool_results")
# Verify ordering (only check if both exist)
if system_pos >= 0 and task_pos >= 0:
assert system_pos < task_pos
if task_pos >= 0 and knowledge_pos >= 0:
assert task_pos < knowledge_pos
if knowledge_pos >= 0 and conversation_pos >= 0:
assert knowledge_pos < conversation_pos
if conversation_pos >= 0 and tool_pos >= 0:
assert conversation_pos < tool_pos
@pytest.mark.asyncio
async def test_excluded_contexts_tracked(self) -> None:
"""Test that excluded contexts are tracked in result."""
pipeline = ContextPipeline()
# Create many contexts to force some exclusions
contexts = [
KnowledgeContext(
content="A" * 500, # Large content
source=f"docs/{i}",
relevance_score=0.1 + (i * 0.05),
)
for i in range(10)
]
result = await pipeline.assemble(
contexts=contexts,
query="test",
model="gpt-4", # Smaller context window
max_tokens=1000, # Limited budget
)
# Should have excluded some
assert result.excluded_count >= 0
assert result.context_count + result.excluded_count <= len(contexts)

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"""Tests for token budget management."""
from unittest.mock import AsyncMock, MagicMock
import pytest
from app.services.context.budget import (
BudgetAllocator,
TokenBudget,
TokenCalculator,
)
from app.services.context.config import ContextSettings
from app.services.context.exceptions import BudgetExceededError
from app.services.context.types import ContextType
class TestTokenBudget:
"""Tests for TokenBudget dataclass."""
def test_creation(self) -> None:
"""Test basic budget creation."""
budget = TokenBudget(total=10000)
assert budget.total == 10000
assert budget.system == 0
assert budget.total_used() == 0
def test_creation_with_allocations(self) -> None:
"""Test budget creation with allocations."""
budget = TokenBudget(
total=10000,
system=500,
task=1000,
knowledge=4000,
conversation=2000,
tools=500,
response_reserve=1500,
buffer=500,
)
assert budget.system == 500
assert budget.knowledge == 4000
assert budget.response_reserve == 1500
def test_get_allocation(self) -> None:
"""Test getting allocation for a type."""
budget = TokenBudget(
total=10000,
system=500,
knowledge=4000,
)
assert budget.get_allocation(ContextType.SYSTEM) == 500
assert budget.get_allocation(ContextType.KNOWLEDGE) == 4000
assert budget.get_allocation("system") == 500
def test_remaining(self) -> None:
"""Test remaining budget calculation."""
budget = TokenBudget(
total=10000,
system=500,
knowledge=4000,
)
# Initially full
assert budget.remaining(ContextType.SYSTEM) == 500
assert budget.remaining(ContextType.KNOWLEDGE) == 4000
# After allocation
budget.allocate(ContextType.SYSTEM, 200)
assert budget.remaining(ContextType.SYSTEM) == 300
def test_can_fit(self) -> None:
"""Test can_fit check."""
budget = TokenBudget(
total=10000,
system=500,
knowledge=4000,
)
assert budget.can_fit(ContextType.SYSTEM, 500) is True
assert budget.can_fit(ContextType.SYSTEM, 501) is False
assert budget.can_fit(ContextType.KNOWLEDGE, 4000) is True
def test_allocate_success(self) -> None:
"""Test successful allocation."""
budget = TokenBudget(
total=10000,
system=500,
)
result = budget.allocate(ContextType.SYSTEM, 200)
assert result is True
assert budget.get_used(ContextType.SYSTEM) == 200
assert budget.remaining(ContextType.SYSTEM) == 300
def test_allocate_exceeds_budget(self) -> None:
"""Test allocation exceeding budget."""
budget = TokenBudget(
total=10000,
system=500,
)
with pytest.raises(BudgetExceededError) as exc_info:
budget.allocate(ContextType.SYSTEM, 600)
assert exc_info.value.allocated == 500
assert exc_info.value.requested == 600
def test_allocate_force(self) -> None:
"""Test forced allocation exceeding budget."""
budget = TokenBudget(
total=10000,
system=500,
)
# Force should allow exceeding
result = budget.allocate(ContextType.SYSTEM, 600, force=True)
assert result is True
assert budget.get_used(ContextType.SYSTEM) == 600
def test_deallocate(self) -> None:
"""Test deallocation."""
budget = TokenBudget(
total=10000,
system=500,
)
budget.allocate(ContextType.SYSTEM, 300)
assert budget.get_used(ContextType.SYSTEM) == 300
budget.deallocate(ContextType.SYSTEM, 100)
assert budget.get_used(ContextType.SYSTEM) == 200
def test_deallocate_below_zero(self) -> None:
"""Test deallocation doesn't go below zero."""
budget = TokenBudget(
total=10000,
system=500,
)
budget.allocate(ContextType.SYSTEM, 100)
budget.deallocate(ContextType.SYSTEM, 200)
assert budget.get_used(ContextType.SYSTEM) == 0
def test_total_remaining(self) -> None:
"""Test total remaining calculation."""
budget = TokenBudget(
total=10000,
system=500,
knowledge=4000,
response_reserve=1500,
buffer=500,
)
# Usable = total - response_reserve - buffer = 10000 - 1500 - 500 = 8000
assert budget.total_remaining() == 8000
# After allocation
budget.allocate(ContextType.SYSTEM, 200)
assert budget.total_remaining() == 7800
def test_utilization(self) -> None:
"""Test utilization calculation."""
budget = TokenBudget(
total=10000,
system=500,
response_reserve=1500,
buffer=500,
)
# No usage = 0%
assert budget.utilization(ContextType.SYSTEM) == 0.0
# Half used = 50%
budget.allocate(ContextType.SYSTEM, 250)
assert budget.utilization(ContextType.SYSTEM) == 0.5
# Total utilization
assert budget.utilization() == 250 / 8000 # 250 / (10000 - 1500 - 500)
def test_reset(self) -> None:
"""Test reset clears usage."""
budget = TokenBudget(
total=10000,
system=500,
)
budget.allocate(ContextType.SYSTEM, 300)
assert budget.get_used(ContextType.SYSTEM) == 300
budget.reset()
assert budget.get_used(ContextType.SYSTEM) == 0
assert budget.total_used() == 0
def test_to_dict(self) -> None:
"""Test to_dict conversion."""
budget = TokenBudget(
total=10000,
system=500,
task=1000,
knowledge=4000,
)
budget.allocate(ContextType.SYSTEM, 200)
data = budget.to_dict()
assert data["total"] == 10000
assert data["allocations"]["system"] == 500
assert data["used"]["system"] == 200
assert data["remaining"]["system"] == 300
class TestBudgetAllocator:
"""Tests for BudgetAllocator."""
def test_create_budget(self) -> None:
"""Test budget creation with default allocations."""
allocator = BudgetAllocator()
budget = allocator.create_budget(100000)
assert budget.total == 100000
assert budget.system == 5000 # 5%
assert budget.task == 10000 # 10%
assert budget.knowledge == 40000 # 40%
assert budget.conversation == 20000 # 20%
assert budget.tools == 5000 # 5%
assert budget.response_reserve == 15000 # 15%
assert budget.buffer == 5000 # 5%
def test_create_budget_custom_allocations(self) -> None:
"""Test budget creation with custom allocations."""
allocator = BudgetAllocator()
budget = allocator.create_budget(
100000,
custom_allocations={
"system": 0.10,
"task": 0.10,
"knowledge": 0.30,
"conversation": 0.25,
"tools": 0.05,
"response": 0.15,
"buffer": 0.05,
},
)
assert budget.system == 10000 # 10%
assert budget.knowledge == 30000 # 30%
def test_create_budget_for_model(self) -> None:
"""Test budget creation for specific model."""
allocator = BudgetAllocator()
# Claude models have 200k context
budget = allocator.create_budget_for_model("claude-3-sonnet")
assert budget.total == 200000
# GPT-4 has 8k context
budget = allocator.create_budget_for_model("gpt-4")
assert budget.total == 8192
# GPT-4-turbo has 128k context
budget = allocator.create_budget_for_model("gpt-4-turbo")
assert budget.total == 128000
def test_get_model_context_size(self) -> None:
"""Test model context size lookup."""
allocator = BudgetAllocator()
# Known models
assert allocator.get_model_context_size("claude-3-opus") == 200000
assert allocator.get_model_context_size("gpt-4") == 8192
assert allocator.get_model_context_size("gemini-1.5-pro") == 2000000
# Unknown model gets default
assert allocator.get_model_context_size("unknown-model") == 8192
def test_adjust_budget(self) -> None:
"""Test budget adjustment."""
allocator = BudgetAllocator()
budget = allocator.create_budget(10000)
original_system = budget.system
original_buffer = budget.buffer
# Increase system by taking from buffer
budget = allocator.adjust_budget(budget, ContextType.SYSTEM, 200)
assert budget.system == original_system + 200
assert budget.buffer == original_buffer - 200
def test_adjust_budget_limited_by_buffer(self) -> None:
"""Test that adjustment is limited by buffer size."""
allocator = BudgetAllocator()
budget = allocator.create_budget(10000)
original_buffer = budget.buffer
# Try to increase more than buffer allows
budget = allocator.adjust_budget(budget, ContextType.SYSTEM, 10000)
# Should only increase by buffer amount
assert budget.buffer == 0
assert budget.system <= original_buffer + budget.system
def test_rebalance_budget(self) -> None:
"""Test budget rebalancing."""
allocator = BudgetAllocator()
budget = allocator.create_budget(10000)
# Use most of knowledge budget
budget.allocate(ContextType.KNOWLEDGE, 3500)
# Rebalance prioritizing knowledge
budget = allocator.rebalance_budget(
budget,
prioritize=[ContextType.KNOWLEDGE],
)
# Knowledge should have gotten more tokens
# (This is a fuzzy test - just check it runs)
assert budget is not None
class TestTokenCalculator:
"""Tests for TokenCalculator."""
def test_estimate_tokens(self) -> None:
"""Test token estimation."""
calc = TokenCalculator()
# Empty string
assert calc.estimate_tokens("") == 0
# Short text (~4 chars per token)
text = "This is a test message"
estimate = calc.estimate_tokens(text)
assert 4 <= estimate <= 8
def test_estimate_tokens_model_specific(self) -> None:
"""Test model-specific estimation ratios."""
calc = TokenCalculator()
text = "a" * 100
# Claude uses 3.5 chars per token
claude_estimate = calc.estimate_tokens(text, "claude-3-sonnet")
# GPT uses 4.0 chars per token
gpt_estimate = calc.estimate_tokens(text, "gpt-4")
# Claude should estimate more tokens (smaller ratio)
assert claude_estimate >= gpt_estimate
@pytest.mark.asyncio
async def test_count_tokens_no_mcp(self) -> None:
"""Test token counting without MCP (fallback to estimation)."""
calc = TokenCalculator()
text = "This is a test"
count = await calc.count_tokens(text)
# Should use estimation
assert count > 0
@pytest.mark.asyncio
async def test_count_tokens_with_mcp_success(self) -> None:
"""Test token counting with MCP integration."""
# Mock MCP manager
mock_mcp = MagicMock()
mock_result = MagicMock()
mock_result.success = True
mock_result.data = {"token_count": 42}
mock_mcp.call_tool = AsyncMock(return_value=mock_result)
calc = TokenCalculator(mcp_manager=mock_mcp)
count = await calc.count_tokens("test text")
assert count == 42
mock_mcp.call_tool.assert_called_once()
@pytest.mark.asyncio
async def test_count_tokens_with_mcp_failure(self) -> None:
"""Test fallback when MCP fails."""
# Mock MCP manager that fails
mock_mcp = MagicMock()
mock_mcp.call_tool = AsyncMock(side_effect=Exception("Connection failed"))
calc = TokenCalculator(mcp_manager=mock_mcp)
count = await calc.count_tokens("test text")
# Should fall back to estimation
assert count > 0
@pytest.mark.asyncio
async def test_count_tokens_caching(self) -> None:
"""Test that token counts are cached."""
mock_mcp = MagicMock()
mock_result = MagicMock()
mock_result.success = True
mock_result.data = {"token_count": 42}
mock_mcp.call_tool = AsyncMock(return_value=mock_result)
calc = TokenCalculator(mcp_manager=mock_mcp)
# First call
count1 = await calc.count_tokens("test text")
# Second call (should use cache)
count2 = await calc.count_tokens("test text")
assert count1 == count2 == 42
# MCP should only be called once
assert mock_mcp.call_tool.call_count == 1
@pytest.mark.asyncio
async def test_count_tokens_batch(self) -> None:
"""Test batch token counting."""
calc = TokenCalculator()
texts = ["Hello", "World", "Test message here"]
counts = await calc.count_tokens_batch(texts)
assert len(counts) == 3
assert all(c > 0 for c in counts)
def test_cache_stats(self) -> None:
"""Test cache statistics."""
calc = TokenCalculator()
stats = calc.get_cache_stats()
assert stats["enabled"] is True
assert stats["size"] == 0
assert stats["hits"] == 0
assert stats["misses"] == 0
@pytest.mark.asyncio
async def test_cache_hit_rate(self) -> None:
"""Test cache hit rate tracking."""
calc = TokenCalculator()
# Make some calls
await calc.count_tokens("text1")
await calc.count_tokens("text2")
await calc.count_tokens("text1") # Cache hit
stats = calc.get_cache_stats()
assert stats["hits"] == 1
assert stats["misses"] == 2
def test_clear_cache(self) -> None:
"""Test cache clearing."""
calc = TokenCalculator()
calc._cache["test"] = 100
calc._cache_hits = 5
calc.clear_cache()
assert len(calc._cache) == 0
assert calc._cache_hits == 0
def test_set_mcp_manager(self) -> None:
"""Test setting MCP manager after initialization."""
calc = TokenCalculator()
assert calc._mcp is None
mock_mcp = MagicMock()
calc.set_mcp_manager(mock_mcp)
assert calc._mcp is mock_mcp
@pytest.mark.asyncio
async def test_parse_token_count_formats(self) -> None:
"""Test parsing different token count response formats."""
calc = TokenCalculator()
# Dict with token_count
assert calc._parse_token_count({"token_count": 42}) == 42
# Dict with tokens
assert calc._parse_token_count({"tokens": 42}) == 42
# Dict with count
assert calc._parse_token_count({"count": 42}) == 42
# Direct int
assert calc._parse_token_count(42) == 42
# JSON string
assert calc._parse_token_count('{"token_count": 42}') == 42
# Invalid
assert calc._parse_token_count("invalid") is None
class TestBudgetIntegration:
"""Integration tests for budget management."""
@pytest.mark.asyncio
async def test_full_budget_workflow(self) -> None:
"""Test complete budget allocation workflow."""
# Create settings and allocator
settings = ContextSettings()
allocator = BudgetAllocator(settings)
# Create budget for Claude
budget = allocator.create_budget_for_model("claude-3-sonnet")
assert budget.total == 200000
# Create calculator (without MCP for test)
calc = TokenCalculator()
# Simulate context allocation
system_text = "You are a helpful assistant." * 10
system_tokens = await calc.count_tokens(system_text)
# Allocate
assert budget.can_fit(ContextType.SYSTEM, system_tokens)
budget.allocate(ContextType.SYSTEM, system_tokens)
# Check state
assert budget.get_used(ContextType.SYSTEM) == system_tokens
assert budget.remaining(ContextType.SYSTEM) == budget.system - system_tokens
@pytest.mark.asyncio
async def test_budget_overflow_handling(self) -> None:
"""Test handling budget overflow."""
allocator = BudgetAllocator()
budget = allocator.create_budget(1000) # Small budget
# Try to allocate more than available
with pytest.raises(BudgetExceededError):
budget.allocate(ContextType.KNOWLEDGE, 500)
# Force allocation should work
budget.allocate(ContextType.KNOWLEDGE, 500, force=True)
assert budget.get_used(ContextType.KNOWLEDGE) == 500

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"""Tests for context cache module."""
from unittest.mock import AsyncMock, MagicMock
import pytest
from app.services.context.cache import ContextCache
from app.services.context.config import ContextSettings
from app.services.context.exceptions import CacheError
from app.services.context.types import (
AssembledContext,
ContextPriority,
KnowledgeContext,
SystemContext,
TaskContext,
)
class TestContextCacheBasics:
"""Basic tests for ContextCache."""
def test_creation(self) -> None:
"""Test cache creation without Redis."""
cache = ContextCache()
assert cache._redis is None
assert not cache.is_enabled
def test_creation_with_settings(self) -> None:
"""Test cache creation with custom settings."""
settings = ContextSettings(
cache_prefix="test",
cache_ttl_seconds=60,
)
cache = ContextCache(settings=settings)
assert cache._prefix == "test"
assert cache._ttl == 60
def test_set_redis(self) -> None:
"""Test setting Redis connection."""
cache = ContextCache()
mock_redis = MagicMock()
cache.set_redis(mock_redis)
assert cache._redis is mock_redis
def test_is_enabled(self) -> None:
"""Test is_enabled property."""
settings = ContextSettings(cache_enabled=True)
cache = ContextCache(settings=settings)
assert not cache.is_enabled # No Redis
cache.set_redis(MagicMock())
assert cache.is_enabled
# Disabled in settings
settings2 = ContextSettings(cache_enabled=False)
cache2 = ContextCache(redis=MagicMock(), settings=settings2)
assert not cache2.is_enabled
def test_cache_key(self) -> None:
"""Test cache key generation."""
cache = ContextCache()
key = cache._cache_key("assembled", "abc123")
assert key == "ctx:assembled:abc123"
def test_hash_content(self) -> None:
"""Test content hashing."""
hash1 = ContextCache._hash_content("hello world")
hash2 = ContextCache._hash_content("hello world")
hash3 = ContextCache._hash_content("different")
assert hash1 == hash2
assert hash1 != hash3
assert len(hash1) == 32
class TestFingerprintComputation:
"""Tests for fingerprint computation."""
def test_compute_fingerprint(self) -> None:
"""Test fingerprint computation."""
cache = ContextCache()
contexts = [
SystemContext(content="System", source="system"),
TaskContext(content="Task", source="task"),
]
fp1 = cache.compute_fingerprint(contexts, "query", "claude-3")
fp2 = cache.compute_fingerprint(contexts, "query", "claude-3")
fp3 = cache.compute_fingerprint(contexts, "different", "claude-3")
assert fp1 == fp2 # Same inputs = same fingerprint
assert fp1 != fp3 # Different query = different fingerprint
assert len(fp1) == 32
def test_fingerprint_includes_priority(self) -> None:
"""Test that fingerprint changes with priority."""
cache = ContextCache()
# Use KnowledgeContext since SystemContext has __post_init__ that may override
ctx1 = [
KnowledgeContext(
content="Knowledge",
source="docs",
priority=ContextPriority.NORMAL.value,
)
]
ctx2 = [
KnowledgeContext(
content="Knowledge",
source="docs",
priority=ContextPriority.HIGH.value,
)
]
fp1 = cache.compute_fingerprint(ctx1, "query", "claude-3")
fp2 = cache.compute_fingerprint(ctx2, "query", "claude-3")
assert fp1 != fp2
def test_fingerprint_includes_model(self) -> None:
"""Test that fingerprint changes with model."""
cache = ContextCache()
contexts = [SystemContext(content="System", source="system")]
fp1 = cache.compute_fingerprint(contexts, "query", "claude-3")
fp2 = cache.compute_fingerprint(contexts, "query", "gpt-4")
assert fp1 != fp2
class TestMemoryCache:
"""Tests for in-memory caching."""
def test_memory_cache_fallback(self) -> None:
"""Test memory cache when Redis unavailable."""
cache = ContextCache()
# Should use memory cache
cache._set_memory("test-key", "42")
assert "test-key" in cache._memory_cache
assert cache._memory_cache["test-key"][0] == "42"
def test_memory_cache_eviction(self) -> None:
"""Test memory cache eviction."""
cache = ContextCache()
cache._max_memory_items = 10
# Fill cache
for i in range(15):
cache._set_memory(f"key-{i}", f"value-{i}")
# Should have evicted some items
assert len(cache._memory_cache) < 15
class TestAssembledContextCache:
"""Tests for assembled context caching."""
@pytest.mark.asyncio
async def test_get_assembled_no_redis(self) -> None:
"""Test get_assembled without Redis returns None."""
cache = ContextCache()
result = await cache.get_assembled("fingerprint")
assert result is None
@pytest.mark.asyncio
async def test_get_assembled_not_found(self) -> None:
"""Test get_assembled when key not found."""
mock_redis = AsyncMock()
mock_redis.get.return_value = None
settings = ContextSettings(cache_enabled=True)
cache = ContextCache(redis=mock_redis, settings=settings)
result = await cache.get_assembled("fingerprint")
assert result is None
@pytest.mark.asyncio
async def test_get_assembled_found(self) -> None:
"""Test get_assembled when key found."""
# Create a context
ctx = AssembledContext(
content="Test content",
total_tokens=100,
context_count=2,
)
mock_redis = AsyncMock()
mock_redis.get.return_value = ctx.to_json()
settings = ContextSettings(cache_enabled=True)
cache = ContextCache(redis=mock_redis, settings=settings)
result = await cache.get_assembled("fingerprint")
assert result is not None
assert result.content == "Test content"
assert result.total_tokens == 100
assert result.cache_hit is True
assert result.cache_key == "fingerprint"
@pytest.mark.asyncio
async def test_set_assembled(self) -> None:
"""Test set_assembled."""
mock_redis = AsyncMock()
settings = ContextSettings(cache_enabled=True, cache_ttl_seconds=60)
cache = ContextCache(redis=mock_redis, settings=settings)
ctx = AssembledContext(
content="Test content",
total_tokens=100,
context_count=2,
)
await cache.set_assembled("fingerprint", ctx)
mock_redis.setex.assert_called_once()
call_args = mock_redis.setex.call_args
assert call_args[0][0] == "ctx:assembled:fingerprint"
assert call_args[0][1] == 60 # TTL
@pytest.mark.asyncio
async def test_set_assembled_custom_ttl(self) -> None:
"""Test set_assembled with custom TTL."""
mock_redis = AsyncMock()
settings = ContextSettings(cache_enabled=True)
cache = ContextCache(redis=mock_redis, settings=settings)
ctx = AssembledContext(
content="Test",
total_tokens=10,
context_count=1,
)
await cache.set_assembled("fp", ctx, ttl=120)
call_args = mock_redis.setex.call_args
assert call_args[0][1] == 120
@pytest.mark.asyncio
async def test_cache_error_on_get(self) -> None:
"""Test CacheError raised on Redis error."""
mock_redis = AsyncMock()
mock_redis.get.side_effect = Exception("Redis error")
settings = ContextSettings(cache_enabled=True)
cache = ContextCache(redis=mock_redis, settings=settings)
with pytest.raises(CacheError):
await cache.get_assembled("fingerprint")
@pytest.mark.asyncio
async def test_cache_error_on_set(self) -> None:
"""Test CacheError raised on Redis error."""
mock_redis = AsyncMock()
mock_redis.setex.side_effect = Exception("Redis error")
settings = ContextSettings(cache_enabled=True)
cache = ContextCache(redis=mock_redis, settings=settings)
ctx = AssembledContext(
content="Test",
total_tokens=10,
context_count=1,
)
with pytest.raises(CacheError):
await cache.set_assembled("fp", ctx)
class TestTokenCountCache:
"""Tests for token count caching."""
@pytest.mark.asyncio
async def test_get_token_count_memory_fallback(self) -> None:
"""Test get_token_count uses memory cache."""
cache = ContextCache()
# Set in memory
key = cache._cache_key("tokens", "default", cache._hash_content("hello"))
cache._set_memory(key, "42")
result = await cache.get_token_count("hello")
assert result == 42
@pytest.mark.asyncio
async def test_set_token_count_memory(self) -> None:
"""Test set_token_count stores in memory."""
cache = ContextCache()
await cache.set_token_count("hello", 42)
result = await cache.get_token_count("hello")
assert result == 42
@pytest.mark.asyncio
async def test_set_token_count_with_model(self) -> None:
"""Test set_token_count with model-specific tokenization."""
mock_redis = AsyncMock()
settings = ContextSettings(cache_enabled=True)
cache = ContextCache(redis=mock_redis, settings=settings)
await cache.set_token_count("hello", 42, model="claude-3")
await cache.set_token_count("hello", 50, model="gpt-4")
# Different models should have different keys
assert mock_redis.setex.call_count == 2
calls = mock_redis.setex.call_args_list
key1 = calls[0][0][0]
key2 = calls[1][0][0]
assert "claude-3" in key1
assert "gpt-4" in key2
class TestScoreCache:
"""Tests for score caching."""
@pytest.mark.asyncio
async def test_get_score_memory_fallback(self) -> None:
"""Test get_score uses memory cache."""
cache = ContextCache()
# Set in memory
query_hash = cache._hash_content("query")[:16]
key = cache._cache_key("score", "relevance", "ctx-123", query_hash)
cache._set_memory(key, "0.85")
result = await cache.get_score("relevance", "ctx-123", "query")
assert result == 0.85
@pytest.mark.asyncio
async def test_set_score_memory(self) -> None:
"""Test set_score stores in memory."""
cache = ContextCache()
await cache.set_score("relevance", "ctx-123", "query", 0.85)
result = await cache.get_score("relevance", "ctx-123", "query")
assert result == 0.85
@pytest.mark.asyncio
async def test_set_score_with_redis(self) -> None:
"""Test set_score with Redis."""
mock_redis = AsyncMock()
settings = ContextSettings(cache_enabled=True)
cache = ContextCache(redis=mock_redis, settings=settings)
await cache.set_score("relevance", "ctx-123", "query", 0.85)
mock_redis.setex.assert_called_once()
class TestCacheInvalidation:
"""Tests for cache invalidation."""
@pytest.mark.asyncio
async def test_invalidate_pattern(self) -> None:
"""Test invalidate with pattern."""
mock_redis = AsyncMock()
# Set up scan_iter to return matching keys
async def mock_scan_iter(match=None):
for key in ["ctx:assembled:1", "ctx:assembled:2"]:
yield key
mock_redis.scan_iter = mock_scan_iter
settings = ContextSettings(cache_enabled=True)
cache = ContextCache(redis=mock_redis, settings=settings)
deleted = await cache.invalidate("assembled:*")
assert deleted == 2
assert mock_redis.delete.call_count == 2
@pytest.mark.asyncio
async def test_clear_all(self) -> None:
"""Test clear_all."""
mock_redis = AsyncMock()
async def mock_scan_iter(match=None):
for key in ["ctx:1", "ctx:2", "ctx:3"]:
yield key
mock_redis.scan_iter = mock_scan_iter
settings = ContextSettings(cache_enabled=True)
cache = ContextCache(redis=mock_redis, settings=settings)
# Add to memory cache
cache._set_memory("test", "value")
assert len(cache._memory_cache) > 0
deleted = await cache.clear_all()
assert deleted == 3
assert len(cache._memory_cache) == 0
class TestCacheStats:
"""Tests for cache statistics."""
@pytest.mark.asyncio
async def test_get_stats_no_redis(self) -> None:
"""Test get_stats without Redis."""
cache = ContextCache()
cache._set_memory("key", "value")
stats = await cache.get_stats()
assert stats["enabled"] is True
assert stats["redis_available"] is False
assert stats["memory_items"] == 1
@pytest.mark.asyncio
async def test_get_stats_with_redis(self) -> None:
"""Test get_stats with Redis."""
mock_redis = AsyncMock()
mock_redis.info.return_value = {"used_memory_human": "1.5M"}
settings = ContextSettings(cache_enabled=True, cache_ttl_seconds=300)
cache = ContextCache(redis=mock_redis, settings=settings)
stats = await cache.get_stats()
assert stats["enabled"] is True
assert stats["redis_available"] is True
assert stats["ttl_seconds"] == 300
assert stats["redis_memory_used"] == "1.5M"
class TestCacheIntegration:
"""Integration tests for cache."""
@pytest.mark.asyncio
async def test_full_workflow(self) -> None:
"""Test complete cache workflow."""
mock_redis = AsyncMock()
mock_redis.get.return_value = None
settings = ContextSettings(cache_enabled=True)
cache = ContextCache(redis=mock_redis, settings=settings)
contexts = [
SystemContext(content="System", source="system"),
KnowledgeContext(content="Knowledge", source="docs"),
]
# Compute fingerprint
fp = cache.compute_fingerprint(contexts, "query", "claude-3")
assert len(fp) == 32
# Check cache (miss)
result = await cache.get_assembled(fp)
assert result is None
# Create and cache assembled context
assembled = AssembledContext(
content="Assembled content",
total_tokens=100,
context_count=2,
model="claude-3",
)
await cache.set_assembled(fp, assembled)
# Verify setex was called
mock_redis.setex.assert_called_once()
# Mock cache hit
mock_redis.get.return_value = assembled.to_json()
result = await cache.get_assembled(fp)
assert result is not None
assert result.cache_hit is True
assert result.content == "Assembled content"

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"""Tests for context compression module."""
import pytest
from app.services.context.budget import BudgetAllocator
from app.services.context.compression import (
ContextCompressor,
TruncationResult,
TruncationStrategy,
)
from app.services.context.types import (
ContextType,
KnowledgeContext,
TaskContext,
)
class TestTruncationResult:
"""Tests for TruncationResult dataclass."""
def test_creation(self) -> None:
"""Test basic creation."""
result = TruncationResult(
original_tokens=100,
truncated_tokens=50,
content="Truncated content",
truncated=True,
truncation_ratio=0.5,
)
assert result.original_tokens == 100
assert result.truncated_tokens == 50
assert result.truncated is True
assert result.truncation_ratio == 0.5
def test_tokens_saved(self) -> None:
"""Test tokens_saved property."""
result = TruncationResult(
original_tokens=100,
truncated_tokens=40,
content="Test",
truncated=True,
truncation_ratio=0.6,
)
assert result.tokens_saved == 60
def test_no_truncation(self) -> None:
"""Test when no truncation needed."""
result = TruncationResult(
original_tokens=50,
truncated_tokens=50,
content="Full content",
truncated=False,
truncation_ratio=0.0,
)
assert result.tokens_saved == 0
assert result.truncated is False
class TestTruncationStrategy:
"""Tests for TruncationStrategy."""
def test_creation(self) -> None:
"""Test strategy creation."""
strategy = TruncationStrategy()
assert strategy._preserve_ratio_start == 0.7
assert strategy._min_content_length == 100
def test_creation_with_params(self) -> None:
"""Test strategy creation with custom params."""
strategy = TruncationStrategy(
preserve_ratio_start=0.5,
min_content_length=50,
)
assert strategy._preserve_ratio_start == 0.5
assert strategy._min_content_length == 50
@pytest.mark.asyncio
async def test_truncate_empty_content(self) -> None:
"""Test truncating empty content."""
strategy = TruncationStrategy()
result = await strategy.truncate_to_tokens("", max_tokens=100)
assert result.original_tokens == 0
assert result.truncated_tokens == 0
assert result.content == ""
assert result.truncated is False
@pytest.mark.asyncio
async def test_truncate_content_within_limit(self) -> None:
"""Test content that fits within limit."""
strategy = TruncationStrategy()
content = "Short content"
result = await strategy.truncate_to_tokens(content, max_tokens=100)
assert result.content == content
assert result.truncated is False
@pytest.mark.asyncio
async def test_truncate_end_strategy(self) -> None:
"""Test end truncation strategy."""
strategy = TruncationStrategy()
content = "A" * 1000 # Long content
result = await strategy.truncate_to_tokens(
content, max_tokens=50, strategy="end"
)
assert result.truncated is True
assert len(result.content) < len(content)
assert strategy.truncation_marker in result.content
@pytest.mark.asyncio
async def test_truncate_middle_strategy(self) -> None:
"""Test middle truncation strategy."""
strategy = TruncationStrategy(preserve_ratio_start=0.6)
content = "START " + "A" * 500 + " END"
result = await strategy.truncate_to_tokens(
content, max_tokens=50, strategy="middle"
)
assert result.truncated is True
assert strategy.truncation_marker in result.content
@pytest.mark.asyncio
async def test_truncate_sentence_strategy(self) -> None:
"""Test sentence-aware truncation strategy."""
strategy = TruncationStrategy()
content = "First sentence. Second sentence. Third sentence. Fourth sentence."
result = await strategy.truncate_to_tokens(
content, max_tokens=10, strategy="sentence"
)
assert result.truncated is True
# Should cut at sentence boundary
assert (
result.content.endswith(".") or strategy.truncation_marker in result.content
)
class TestContextCompressor:
"""Tests for ContextCompressor."""
def test_creation(self) -> None:
"""Test compressor creation."""
compressor = ContextCompressor()
assert compressor._truncation is not None
@pytest.mark.asyncio
async def test_compress_context_within_limit(self) -> None:
"""Test compressing context that already fits."""
compressor = ContextCompressor()
context = KnowledgeContext(
content="Short content",
source="docs",
)
context.token_count = 5
result = await compressor.compress_context(context, max_tokens=100)
# Should return same context unmodified
assert result.content == "Short content"
assert result.metadata.get("truncated") is not True
@pytest.mark.asyncio
async def test_compress_context_exceeds_limit(self) -> None:
"""Test compressing context that exceeds limit."""
compressor = ContextCompressor()
context = KnowledgeContext(
content="A" * 500,
source="docs",
)
context.token_count = 125 # Approximately 500/4
result = await compressor.compress_context(context, max_tokens=20)
assert result.metadata.get("truncated") is True
assert result.metadata.get("original_tokens") == 125
assert len(result.content) < 500
@pytest.mark.asyncio
async def test_compress_contexts_batch(self) -> None:
"""Test compressing multiple contexts."""
compressor = ContextCompressor()
allocator = BudgetAllocator()
budget = allocator.create_budget(1000)
contexts = [
KnowledgeContext(content="A" * 200, source="docs"),
KnowledgeContext(content="B" * 200, source="docs"),
TaskContext(content="C" * 200, source="task"),
]
result = await compressor.compress_contexts(contexts, budget)
assert len(result) == 3
@pytest.mark.asyncio
async def test_strategy_selection_by_type(self) -> None:
"""Test that correct strategy is selected for each type."""
compressor = ContextCompressor()
assert compressor._get_strategy_for_type(ContextType.SYSTEM) == "end"
assert compressor._get_strategy_for_type(ContextType.TASK) == "end"
assert compressor._get_strategy_for_type(ContextType.KNOWLEDGE) == "sentence"
assert compressor._get_strategy_for_type(ContextType.CONVERSATION) == "end"
assert compressor._get_strategy_for_type(ContextType.TOOL) == "middle"
class TestTruncationEdgeCases:
"""Tests for edge cases in truncation to prevent regressions."""
@pytest.mark.asyncio
async def test_truncation_ratio_with_zero_original_tokens(self) -> None:
"""Test that truncation ratio handles zero original tokens without division by zero."""
strategy = TruncationStrategy()
# Empty content should not raise ZeroDivisionError
result = await strategy.truncate_to_tokens("", max_tokens=100)
assert result.truncation_ratio == 0.0
assert result.original_tokens == 0
@pytest.mark.asyncio
async def test_truncate_end_with_zero_available_tokens(self) -> None:
"""Test truncation when marker tokens exceed max_tokens."""
strategy = TruncationStrategy()
content = "Some content to truncate"
# max_tokens less than marker tokens should return just marker
result = await strategy.truncate_to_tokens(
content, max_tokens=1, strategy="end"
)
# Should handle gracefully without crashing
assert strategy.truncation_marker in result.content or result.content == content
@pytest.mark.asyncio
async def test_truncate_with_content_that_has_zero_tokens(self) -> None:
"""Test truncation when content estimates to zero tokens."""
strategy = TruncationStrategy()
# Very short content that might estimate to 0 tokens
result = await strategy.truncate_to_tokens("a", max_tokens=100)
# Should not raise ZeroDivisionError
assert result.content in ("a", "a" + strategy.truncation_marker)
@pytest.mark.asyncio
async def test_get_content_for_tokens_zero_target(self) -> None:
"""Test _get_content_for_tokens with zero target tokens."""
strategy = TruncationStrategy()
result = await strategy._get_content_for_tokens(
content="Some content",
target_tokens=0,
from_start=True,
)
assert result == ""
@pytest.mark.asyncio
async def test_sentence_truncation_with_no_sentences(self) -> None:
"""Test sentence truncation with content that has no sentence boundaries."""
strategy = TruncationStrategy()
content = "this is content without any sentence ending punctuation"
result = await strategy.truncate_to_tokens(
content, max_tokens=5, strategy="sentence"
)
# Should handle gracefully
assert result is not None
@pytest.mark.asyncio
async def test_middle_truncation_very_short_content(self) -> None:
"""Test middle truncation with content shorter than preserved portions."""
strategy = TruncationStrategy(preserve_ratio_start=0.7)
content = "ab" # Very short
result = await strategy.truncate_to_tokens(
content, max_tokens=1, strategy="middle"
)
# Should handle gracefully without negative indices
assert result is not None

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"""Tests for context management configuration."""
import os
from unittest.mock import patch
import pytest
from app.services.context.config import (
ContextSettings,
get_context_settings,
get_default_settings,
reset_context_settings,
)
class TestContextSettings:
"""Tests for ContextSettings."""
def test_default_values(self) -> None:
"""Test default settings values."""
settings = ContextSettings()
# Budget defaults should sum to 1.0
total = (
settings.budget_system
+ settings.budget_task
+ settings.budget_knowledge
+ settings.budget_conversation
+ settings.budget_tools
+ settings.budget_response
+ settings.budget_buffer
)
assert abs(total - 1.0) < 0.001
# Scoring weights should sum to 1.0
weights_total = (
settings.scoring_relevance_weight
+ settings.scoring_recency_weight
+ settings.scoring_priority_weight
)
assert abs(weights_total - 1.0) < 0.001
def test_budget_allocation_values(self) -> None:
"""Test specific budget allocation values."""
settings = ContextSettings()
assert settings.budget_system == 0.05
assert settings.budget_task == 0.10
assert settings.budget_knowledge == 0.40
assert settings.budget_conversation == 0.20
assert settings.budget_tools == 0.05
assert settings.budget_response == 0.15
assert settings.budget_buffer == 0.05
def test_scoring_weights(self) -> None:
"""Test scoring weights."""
settings = ContextSettings()
assert settings.scoring_relevance_weight == 0.5
assert settings.scoring_recency_weight == 0.3
assert settings.scoring_priority_weight == 0.2
def test_cache_settings(self) -> None:
"""Test cache settings."""
settings = ContextSettings()
assert settings.cache_enabled is True
assert settings.cache_ttl_seconds == 3600
assert settings.cache_prefix == "ctx"
def test_performance_settings(self) -> None:
"""Test performance settings."""
settings = ContextSettings()
assert settings.max_assembly_time_ms == 2000
assert settings.parallel_scoring is True
assert settings.max_parallel_scores == 10
def test_get_budget_allocation(self) -> None:
"""Test get_budget_allocation method."""
settings = ContextSettings()
allocation = settings.get_budget_allocation()
assert isinstance(allocation, dict)
assert "system" in allocation
assert "knowledge" in allocation
assert allocation["system"] == 0.05
assert allocation["knowledge"] == 0.40
def test_get_scoring_weights(self) -> None:
"""Test get_scoring_weights method."""
settings = ContextSettings()
weights = settings.get_scoring_weights()
assert isinstance(weights, dict)
assert "relevance" in weights
assert "recency" in weights
assert "priority" in weights
assert weights["relevance"] == 0.5
def test_to_dict(self) -> None:
"""Test to_dict method."""
settings = ContextSettings()
result = settings.to_dict()
assert "budget" in result
assert "scoring" in result
assert "compression" in result
assert "cache" in result
assert "performance" in result
assert "knowledge" in result
assert "conversation" in result
def test_budget_validation_fails_on_wrong_sum(self) -> None:
"""Test that budget validation fails when sum != 1.0."""
with pytest.raises(ValueError) as exc_info:
ContextSettings(
budget_system=0.5,
budget_task=0.5,
# Other budgets default to non-zero, so total > 1.0
)
assert "sum to 1.0" in str(exc_info.value)
def test_scoring_validation_fails_on_wrong_sum(self) -> None:
"""Test that scoring validation fails when sum != 1.0."""
with pytest.raises(ValueError) as exc_info:
ContextSettings(
scoring_relevance_weight=0.8,
scoring_recency_weight=0.8,
scoring_priority_weight=0.8,
)
assert "sum to 1.0" in str(exc_info.value)
def test_search_type_validation(self) -> None:
"""Test search type validation."""
# Valid types should work
ContextSettings(knowledge_search_type="semantic")
ContextSettings(knowledge_search_type="keyword")
ContextSettings(knowledge_search_type="hybrid")
# Invalid type should fail
with pytest.raises(ValueError):
ContextSettings(knowledge_search_type="invalid")
def test_custom_budget_allocation(self) -> None:
"""Test custom budget allocation that sums to 1.0."""
settings = ContextSettings(
budget_system=0.10,
budget_task=0.10,
budget_knowledge=0.30,
budget_conversation=0.25,
budget_tools=0.05,
budget_response=0.15,
budget_buffer=0.05,
)
total = (
settings.budget_system
+ settings.budget_task
+ settings.budget_knowledge
+ settings.budget_conversation
+ settings.budget_tools
+ settings.budget_response
+ settings.budget_buffer
)
assert abs(total - 1.0) < 0.001
class TestSettingsSingleton:
"""Tests for settings singleton pattern."""
def setup_method(self) -> None:
"""Reset settings before each test."""
reset_context_settings()
def teardown_method(self) -> None:
"""Clean up after each test."""
reset_context_settings()
def test_get_context_settings_returns_instance(self) -> None:
"""Test that get_context_settings returns a settings instance."""
settings = get_context_settings()
assert isinstance(settings, ContextSettings)
def test_get_context_settings_returns_same_instance(self) -> None:
"""Test that get_context_settings returns the same instance."""
settings1 = get_context_settings()
settings2 = get_context_settings()
assert settings1 is settings2
def test_reset_creates_new_instance(self) -> None:
"""Test that reset creates a new instance."""
settings1 = get_context_settings()
reset_context_settings()
settings2 = get_context_settings()
# Should be different instances
assert settings1 is not settings2
def test_get_default_settings_cached(self) -> None:
"""Test that get_default_settings is cached."""
settings1 = get_default_settings()
settings2 = get_default_settings()
assert settings1 is settings2
class TestEnvironmentOverrides:
"""Tests for environment variable overrides."""
def setup_method(self) -> None:
"""Reset settings before each test."""
reset_context_settings()
def teardown_method(self) -> None:
"""Clean up after each test."""
reset_context_settings()
# Clean up any env vars we set
for key in list(os.environ.keys()):
if key.startswith("CTX_"):
del os.environ[key]
def test_env_override_cache_enabled(self) -> None:
"""Test that CTX_CACHE_ENABLED env var works."""
with patch.dict(os.environ, {"CTX_CACHE_ENABLED": "false"}):
reset_context_settings()
settings = ContextSettings()
assert settings.cache_enabled is False
def test_env_override_cache_ttl(self) -> None:
"""Test that CTX_CACHE_TTL_SECONDS env var works."""
with patch.dict(os.environ, {"CTX_CACHE_TTL_SECONDS": "7200"}):
reset_context_settings()
settings = ContextSettings()
assert settings.cache_ttl_seconds == 7200
def test_env_override_max_assembly_time(self) -> None:
"""Test that CTX_MAX_ASSEMBLY_TIME_MS env var works."""
with patch.dict(os.environ, {"CTX_MAX_ASSEMBLY_TIME_MS": "200"}):
reset_context_settings()
settings = ContextSettings()
assert settings.max_assembly_time_ms == 200

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"""Tests for ContextEngine."""
from unittest.mock import AsyncMock, MagicMock
import pytest
from app.services.context.config import ContextSettings
from app.services.context.engine import ContextEngine, create_context_engine
from app.services.context.types import (
AssembledContext,
ConversationContext,
KnowledgeContext,
MessageRole,
ToolContext,
)
class TestContextEngineCreation:
"""Tests for ContextEngine creation."""
def test_creation_minimal(self) -> None:
"""Test creating engine with minimal config."""
engine = ContextEngine()
assert engine._mcp is None
assert engine._settings is not None
assert engine._calculator is not None
assert engine._scorer is not None
assert engine._ranker is not None
assert engine._compressor is not None
assert engine._cache is not None
assert engine._pipeline is not None
def test_creation_with_settings(self) -> None:
"""Test creating engine with custom settings."""
settings = ContextSettings(
compression_threshold=0.7,
cache_enabled=False,
)
engine = ContextEngine(settings=settings)
assert engine._settings.compression_threshold == 0.7
assert engine._settings.cache_enabled is False
def test_creation_with_redis(self) -> None:
"""Test creating engine with Redis."""
mock_redis = MagicMock()
settings = ContextSettings(cache_enabled=True)
engine = ContextEngine(redis=mock_redis, settings=settings)
assert engine._cache.is_enabled
def test_set_mcp_manager(self) -> None:
"""Test setting MCP manager."""
engine = ContextEngine()
mock_mcp = MagicMock()
engine.set_mcp_manager(mock_mcp)
assert engine._mcp is mock_mcp
def test_set_redis(self) -> None:
"""Test setting Redis connection."""
engine = ContextEngine()
mock_redis = MagicMock()
engine.set_redis(mock_redis)
assert engine._cache._redis is mock_redis
class TestContextEngineHelpers:
"""Tests for ContextEngine helper methods."""
def test_convert_conversation(self) -> None:
"""Test converting conversation history."""
engine = ContextEngine()
history = [
{"role": "user", "content": "Hello!"},
{"role": "assistant", "content": "Hi there!"},
{"role": "user", "content": "How are you?"},
]
contexts = engine._convert_conversation(history)
assert len(contexts) == 3
assert all(isinstance(c, ConversationContext) for c in contexts)
assert contexts[0].role == MessageRole.USER
assert contexts[1].role == MessageRole.ASSISTANT
assert contexts[0].content == "Hello!"
assert contexts[0].metadata["turn"] == 0
def test_convert_tool_results(self) -> None:
"""Test converting tool results."""
engine = ContextEngine()
results = [
{"tool_name": "search", "content": "Result 1", "status": "success"},
{"tool_name": "read", "result": {"file": "test.txt"}, "status": "success"},
]
contexts = engine._convert_tool_results(results)
assert len(contexts) == 2
assert all(isinstance(c, ToolContext) for c in contexts)
assert contexts[0].content == "Result 1"
assert contexts[0].metadata["tool_name"] == "search"
# Dict content should be JSON serialized
assert "file" in contexts[1].content
assert "test.txt" in contexts[1].content
class TestContextEngineAssembly:
"""Tests for context assembly."""
@pytest.mark.asyncio
async def test_assemble_minimal(self) -> None:
"""Test assembling with minimal inputs."""
engine = ContextEngine()
result = await engine.assemble_context(
project_id="proj-123",
agent_id="agent-456",
query="test query",
model="claude-3-sonnet",
use_cache=False, # Disable cache for test
)
assert isinstance(result, AssembledContext)
assert result.context_count == 0 # No contexts provided
@pytest.mark.asyncio
async def test_assemble_with_system_prompt(self) -> None:
"""Test assembling with system prompt."""
engine = ContextEngine()
result = await engine.assemble_context(
project_id="proj-123",
agent_id="agent-456",
query="test query",
model="claude-3-sonnet",
system_prompt="You are a helpful assistant.",
use_cache=False,
)
assert result.context_count == 1
assert "helpful assistant" in result.content
@pytest.mark.asyncio
async def test_assemble_with_task(self) -> None:
"""Test assembling with task description."""
engine = ContextEngine()
result = await engine.assemble_context(
project_id="proj-123",
agent_id="agent-456",
query="implement feature",
model="claude-3-sonnet",
task_description="Implement user authentication",
use_cache=False,
)
assert result.context_count == 1
assert "authentication" in result.content
@pytest.mark.asyncio
async def test_assemble_with_conversation(self) -> None:
"""Test assembling with conversation history."""
engine = ContextEngine()
result = await engine.assemble_context(
project_id="proj-123",
agent_id="agent-456",
query="continue",
model="claude-3-sonnet",
conversation_history=[
{"role": "user", "content": "Hello!"},
{"role": "assistant", "content": "Hi!"},
],
use_cache=False,
)
assert result.context_count == 2
assert "Hello" in result.content
@pytest.mark.asyncio
async def test_assemble_with_tool_results(self) -> None:
"""Test assembling with tool results."""
engine = ContextEngine()
result = await engine.assemble_context(
project_id="proj-123",
agent_id="agent-456",
query="continue",
model="claude-3-sonnet",
tool_results=[
{"tool_name": "search", "content": "Found 5 results"},
],
use_cache=False,
)
assert result.context_count == 1
assert "Found 5 results" in result.content
@pytest.mark.asyncio
async def test_assemble_with_custom_contexts(self) -> None:
"""Test assembling with custom contexts."""
engine = ContextEngine()
custom = [
KnowledgeContext(
content="Custom knowledge.",
source="custom",
relevance_score=0.9,
)
]
result = await engine.assemble_context(
project_id="proj-123",
agent_id="agent-456",
query="test",
model="claude-3-sonnet",
custom_contexts=custom,
use_cache=False,
)
assert result.context_count == 1
assert "Custom knowledge" in result.content
@pytest.mark.asyncio
async def test_assemble_full_workflow(self) -> None:
"""Test full assembly workflow."""
engine = ContextEngine()
result = await engine.assemble_context(
project_id="proj-123",
agent_id="agent-456",
query="implement login",
model="claude-3-sonnet",
system_prompt="You are an expert Python developer.",
task_description="Implement user authentication.",
conversation_history=[
{"role": "user", "content": "Can you help me implement JWT auth?"},
],
tool_results=[
{"tool_name": "file_create", "content": "Created auth.py"},
],
use_cache=False,
)
assert result.context_count >= 4
assert result.total_tokens > 0
assert result.model == "claude-3-sonnet"
# Check for expected content
assert "expert Python developer" in result.content
assert "authentication" in result.content
class TestContextEngineKnowledge:
"""Tests for knowledge fetching."""
@pytest.mark.asyncio
async def test_fetch_knowledge_no_mcp(self) -> None:
"""Test fetching knowledge without MCP returns empty."""
engine = ContextEngine()
result = await engine._fetch_knowledge(
project_id="proj-123",
agent_id="agent-456",
query="test",
)
assert result == []
@pytest.mark.asyncio
async def test_fetch_knowledge_with_mcp(self) -> None:
"""Test fetching knowledge with MCP."""
mock_mcp = AsyncMock()
mock_mcp.call_tool.return_value.data = {
"results": [
{
"content": "Document content",
"source_path": "docs/api.md",
"score": 0.9,
"chunk_id": "chunk-1",
},
{
"content": "Another document",
"source_path": "docs/auth.md",
"score": 0.8,
},
]
}
engine = ContextEngine(mcp_manager=mock_mcp)
result = await engine._fetch_knowledge(
project_id="proj-123",
agent_id="agent-456",
query="authentication",
)
assert len(result) == 2
assert all(isinstance(c, KnowledgeContext) for c in result)
assert result[0].content == "Document content"
assert result[0].source == "docs/api.md"
assert result[0].relevance_score == 0.9
@pytest.mark.asyncio
async def test_fetch_knowledge_error_handling(self) -> None:
"""Test knowledge fetch error handling."""
mock_mcp = AsyncMock()
mock_mcp.call_tool.side_effect = Exception("MCP error")
engine = ContextEngine(mcp_manager=mock_mcp)
# Should not raise, returns empty
result = await engine._fetch_knowledge(
project_id="proj-123",
agent_id="agent-456",
query="test",
)
assert result == []
class TestContextEngineCaching:
"""Tests for caching behavior."""
@pytest.mark.asyncio
async def test_cache_disabled(self) -> None:
"""Test assembly with cache disabled."""
engine = ContextEngine()
result = await engine.assemble_context(
project_id="proj-123",
agent_id="agent-456",
query="test",
model="claude-3-sonnet",
system_prompt="Test prompt",
use_cache=False,
)
assert not result.cache_hit
@pytest.mark.asyncio
async def test_cache_hit(self) -> None:
"""Test cache hit."""
mock_redis = AsyncMock()
settings = ContextSettings(cache_enabled=True)
engine = ContextEngine(redis=mock_redis, settings=settings)
# First call - cache miss
mock_redis.get.return_value = None
result1 = await engine.assemble_context(
project_id="proj-123",
agent_id="agent-456",
query="test",
model="claude-3-sonnet",
system_prompt="Test prompt",
)
# Second call - mock cache hit
mock_redis.get.return_value = result1.to_json()
result2 = await engine.assemble_context(
project_id="proj-123",
agent_id="agent-456",
query="test",
model="claude-3-sonnet",
system_prompt="Test prompt",
)
assert result2.cache_hit
class TestContextEngineUtilities:
"""Tests for utility methods."""
@pytest.mark.asyncio
async def test_get_budget_for_model(self) -> None:
"""Test getting budget for model."""
engine = ContextEngine()
budget = await engine.get_budget_for_model("claude-3-sonnet")
assert budget.total > 0
assert budget.system > 0
assert budget.knowledge > 0
@pytest.mark.asyncio
async def test_get_budget_with_max_tokens(self) -> None:
"""Test getting budget with max tokens."""
engine = ContextEngine()
budget = await engine.get_budget_for_model("claude-3-sonnet", max_tokens=5000)
assert budget.total == 5000
@pytest.mark.asyncio
async def test_count_tokens(self) -> None:
"""Test token counting."""
engine = ContextEngine()
count = await engine.count_tokens("Hello world")
assert count > 0
@pytest.mark.asyncio
async def test_invalidate_cache(self) -> None:
"""Test cache invalidation."""
mock_redis = AsyncMock()
async def mock_scan_iter(match=None):
for key in ["ctx:1", "ctx:2"]:
yield key
mock_redis.scan_iter = mock_scan_iter
settings = ContextSettings(cache_enabled=True)
engine = ContextEngine(redis=mock_redis, settings=settings)
deleted = await engine.invalidate_cache(pattern="*test*")
assert deleted >= 0
@pytest.mark.asyncio
async def test_get_stats(self) -> None:
"""Test getting engine stats."""
engine = ContextEngine()
stats = await engine.get_stats()
assert "cache" in stats
assert "settings" in stats
assert "compression_threshold" in stats["settings"]
class TestCreateContextEngine:
"""Tests for factory function."""
def test_create_context_engine(self) -> None:
"""Test factory function."""
engine = create_context_engine()
assert isinstance(engine, ContextEngine)
def test_create_context_engine_with_settings(self) -> None:
"""Test factory with settings."""
settings = ContextSettings(cache_enabled=False)
engine = create_context_engine(settings=settings)
assert engine._settings.cache_enabled is False

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"""Tests for context management exceptions."""
from app.services.context.exceptions import (
AssemblyTimeoutError,
BudgetExceededError,
CacheError,
CompressionError,
ContextError,
ContextNotFoundError,
FormattingError,
InvalidContextError,
ScoringError,
TokenCountError,
)
class TestContextError:
"""Tests for base ContextError."""
def test_basic_initialization(self) -> None:
"""Test basic error initialization."""
error = ContextError("Test error")
assert error.message == "Test error"
assert error.details == {}
assert str(error) == "Test error"
def test_with_details(self) -> None:
"""Test error with details."""
error = ContextError("Test error", {"key": "value", "count": 42})
assert error.details == {"key": "value", "count": 42}
def test_to_dict(self) -> None:
"""Test conversion to dictionary."""
error = ContextError("Test error", {"key": "value"})
result = error.to_dict()
assert result["error_type"] == "ContextError"
assert result["message"] == "Test error"
assert result["details"] == {"key": "value"}
def test_inheritance(self) -> None:
"""Test that ContextError inherits from Exception."""
error = ContextError("Test")
assert isinstance(error, Exception)
class TestBudgetExceededError:
"""Tests for BudgetExceededError."""
def test_default_message(self) -> None:
"""Test default error message."""
error = BudgetExceededError()
assert "exceeded" in error.message.lower()
def test_with_budget_info(self) -> None:
"""Test with budget information."""
error = BudgetExceededError(
allocated=1000,
requested=1500,
context_type="knowledge",
)
assert error.allocated == 1000
assert error.requested == 1500
assert error.context_type == "knowledge"
assert error.details["overage"] == 500
def test_to_dict_includes_budget_info(self) -> None:
"""Test that to_dict includes budget info."""
error = BudgetExceededError(
allocated=1000,
requested=1500,
)
result = error.to_dict()
assert result["details"]["allocated"] == 1000
assert result["details"]["requested"] == 1500
assert result["details"]["overage"] == 500
class TestTokenCountError:
"""Tests for TokenCountError."""
def test_basic_error(self) -> None:
"""Test basic token count error."""
error = TokenCountError()
assert "token" in error.message.lower()
def test_with_model_info(self) -> None:
"""Test with model information."""
error = TokenCountError(
message="Failed to count",
model="claude-3-sonnet",
text_length=5000,
)
assert error.model == "claude-3-sonnet"
assert error.text_length == 5000
assert error.details["model"] == "claude-3-sonnet"
class TestCompressionError:
"""Tests for CompressionError."""
def test_basic_error(self) -> None:
"""Test basic compression error."""
error = CompressionError()
assert "compress" in error.message.lower()
def test_with_token_info(self) -> None:
"""Test with token information."""
error = CompressionError(
original_tokens=2000,
target_tokens=1000,
achieved_tokens=1500,
)
assert error.original_tokens == 2000
assert error.target_tokens == 1000
assert error.achieved_tokens == 1500
class TestAssemblyTimeoutError:
"""Tests for AssemblyTimeoutError."""
def test_basic_error(self) -> None:
"""Test basic timeout error."""
error = AssemblyTimeoutError()
assert "timed out" in error.message.lower()
def test_with_timing_info(self) -> None:
"""Test with timing information."""
error = AssemblyTimeoutError(
timeout_ms=100,
elapsed_ms=150.5,
stage="scoring",
)
assert error.timeout_ms == 100
assert error.elapsed_ms == 150.5
assert error.stage == "scoring"
assert error.details["stage"] == "scoring"
class TestScoringError:
"""Tests for ScoringError."""
def test_basic_error(self) -> None:
"""Test basic scoring error."""
error = ScoringError()
assert "score" in error.message.lower()
def test_with_scorer_info(self) -> None:
"""Test with scorer information."""
error = ScoringError(
scorer_type="relevance",
context_id="ctx-123",
)
assert error.scorer_type == "relevance"
assert error.context_id == "ctx-123"
class TestFormattingError:
"""Tests for FormattingError."""
def test_basic_error(self) -> None:
"""Test basic formatting error."""
error = FormattingError()
assert "format" in error.message.lower()
def test_with_model_info(self) -> None:
"""Test with model information."""
error = FormattingError(
model="claude-3-opus",
adapter="ClaudeAdapter",
)
assert error.model == "claude-3-opus"
assert error.adapter == "ClaudeAdapter"
class TestCacheError:
"""Tests for CacheError."""
def test_basic_error(self) -> None:
"""Test basic cache error."""
error = CacheError()
assert "cache" in error.message.lower()
def test_with_operation_info(self) -> None:
"""Test with operation information."""
error = CacheError(
operation="get",
cache_key="ctx:abc123",
)
assert error.operation == "get"
assert error.cache_key == "ctx:abc123"
class TestContextNotFoundError:
"""Tests for ContextNotFoundError."""
def test_basic_error(self) -> None:
"""Test basic not found error."""
error = ContextNotFoundError()
assert "not found" in error.message.lower()
def test_with_source_info(self) -> None:
"""Test with source information."""
error = ContextNotFoundError(
source="knowledge-base",
query="authentication flow",
)
assert error.source == "knowledge-base"
assert error.query == "authentication flow"
class TestInvalidContextError:
"""Tests for InvalidContextError."""
def test_basic_error(self) -> None:
"""Test basic invalid error."""
error = InvalidContextError()
assert "invalid" in error.message.lower()
def test_with_field_info(self) -> None:
"""Test with field information."""
error = InvalidContextError(
field="content",
value="",
reason="Content cannot be empty",
)
assert error.field == "content"
assert error.value == ""
assert error.reason == "Content cannot be empty"
def test_value_type_only_in_details(self) -> None:
"""Test that only value type is included in details (not actual value)."""
error = InvalidContextError(
field="api_key",
value="secret-key-here",
)
# Actual value should not be in details
assert "secret-key-here" not in str(error.details)
assert error.details["value_type"] == "str"

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"""Tests for context ranking module."""
import pytest
from app.services.context.budget import BudgetAllocator, TokenBudget
from app.services.context.prioritization import ContextRanker, RankingResult
from app.services.context.scoring import CompositeScorer, ScoredContext
from app.services.context.types import (
ContextPriority,
ContextType,
ConversationContext,
KnowledgeContext,
MessageRole,
SystemContext,
TaskContext,
)
class TestRankingResult:
"""Tests for RankingResult dataclass."""
def test_creation(self) -> None:
"""Test RankingResult creation."""
ctx = TaskContext(content="Test", source="task")
scored = ScoredContext(context=ctx, composite_score=0.8)
result = RankingResult(
selected=[scored],
excluded=[],
total_tokens=100,
selection_stats={"total": 1},
)
assert len(result.selected) == 1
assert result.total_tokens == 100
def test_selected_contexts_property(self) -> None:
"""Test selected_contexts property extracts contexts."""
ctx1 = TaskContext(content="Test 1", source="task")
ctx2 = TaskContext(content="Test 2", source="task")
scored1 = ScoredContext(context=ctx1, composite_score=0.8)
scored2 = ScoredContext(context=ctx2, composite_score=0.6)
result = RankingResult(
selected=[scored1, scored2],
excluded=[],
total_tokens=200,
)
selected = result.selected_contexts
assert len(selected) == 2
assert ctx1 in selected
assert ctx2 in selected
class TestContextRanker:
"""Tests for ContextRanker."""
def test_creation(self) -> None:
"""Test ranker creation."""
ranker = ContextRanker()
assert ranker._scorer is not None
assert ranker._calculator is not None
def test_creation_with_scorer(self) -> None:
"""Test ranker creation with custom scorer."""
scorer = CompositeScorer(relevance_weight=0.8)
ranker = ContextRanker(scorer=scorer)
assert ranker._scorer is scorer
@pytest.mark.asyncio
async def test_rank_empty_contexts(self) -> None:
"""Test ranking empty context list."""
ranker = ContextRanker()
allocator = BudgetAllocator()
budget = allocator.create_budget(10000)
result = await ranker.rank([], "query", budget)
assert len(result.selected) == 0
assert len(result.excluded) == 0
assert result.total_tokens == 0
@pytest.mark.asyncio
async def test_rank_single_context_fits(self) -> None:
"""Test ranking single context that fits budget."""
ranker = ContextRanker()
allocator = BudgetAllocator()
budget = allocator.create_budget(10000)
context = KnowledgeContext(
content="Short content",
source="docs",
relevance_score=0.8,
)
result = await ranker.rank([context], "query", budget)
assert len(result.selected) == 1
assert len(result.excluded) == 0
assert result.selected[0].context is context
@pytest.mark.asyncio
async def test_rank_respects_budget(self) -> None:
"""Test that ranking respects token budget."""
ranker = ContextRanker()
# Create a very small budget
budget = TokenBudget(
total=100,
knowledge=50, # Only 50 tokens for knowledge
)
# Create contexts that exceed budget
contexts = [
KnowledgeContext(
content="A" * 200, # ~50 tokens
source="docs",
relevance_score=0.9,
),
KnowledgeContext(
content="B" * 200, # ~50 tokens
source="docs",
relevance_score=0.8,
),
KnowledgeContext(
content="C" * 200, # ~50 tokens
source="docs",
relevance_score=0.7,
),
]
result = await ranker.rank(contexts, "query", budget)
# Not all should fit
assert len(result.selected) < len(contexts)
assert len(result.excluded) > 0
@pytest.mark.asyncio
async def test_rank_selects_highest_scores(self) -> None:
"""Test that ranking selects highest scored contexts."""
ranker = ContextRanker()
allocator = BudgetAllocator()
budget = allocator.create_budget(1000)
# Small budget for knowledge
budget.knowledge = 100
contexts = [
KnowledgeContext(
content="Low score",
source="docs",
relevance_score=0.2,
),
KnowledgeContext(
content="High score",
source="docs",
relevance_score=0.9,
),
KnowledgeContext(
content="Medium score",
source="docs",
relevance_score=0.5,
),
]
result = await ranker.rank(contexts, "query", budget)
# Should have selected some
if result.selected:
# The highest scored should be selected first
scores = [s.composite_score for s in result.selected]
assert scores == sorted(scores, reverse=True)
@pytest.mark.asyncio
async def test_rank_critical_priority_always_included(self) -> None:
"""Test that CRITICAL priority contexts are always included."""
ranker = ContextRanker()
# Very small budget
budget = TokenBudget(
total=100,
system=10, # Very small
knowledge=10,
)
contexts = [
SystemContext(
content="Critical system prompt that must be included",
source="system",
priority=ContextPriority.CRITICAL.value,
),
KnowledgeContext(
content="Optional knowledge",
source="docs",
relevance_score=0.9,
),
]
result = await ranker.rank(contexts, "query", budget, ensure_required=True)
# Critical context should be in selected
selected_priorities = [s.context.priority for s in result.selected]
assert ContextPriority.CRITICAL.value in selected_priorities
@pytest.mark.asyncio
async def test_rank_without_ensure_required(self) -> None:
"""Test ranking without ensuring required contexts."""
ranker = ContextRanker()
budget = TokenBudget(
total=100,
system=50,
knowledge=50,
)
contexts = [
SystemContext(
content="A" * 500, # Large content
source="system",
priority=ContextPriority.CRITICAL.value,
),
KnowledgeContext(
content="Short",
source="docs",
relevance_score=0.9,
),
]
result = await ranker.rank(contexts, "query", budget, ensure_required=False)
# Without ensure_required, CRITICAL contexts can be excluded
# if budget doesn't allow
assert len(result.selected) + len(result.excluded) == len(contexts)
@pytest.mark.asyncio
async def test_rank_selection_stats(self) -> None:
"""Test that ranking provides useful statistics."""
ranker = ContextRanker()
allocator = BudgetAllocator()
budget = allocator.create_budget(10000)
contexts = [
KnowledgeContext(content="Knowledge 1", source="docs", relevance_score=0.8),
KnowledgeContext(content="Knowledge 2", source="docs", relevance_score=0.6),
TaskContext(content="Task", source="task"),
]
result = await ranker.rank(contexts, "query", budget)
stats = result.selection_stats
assert "total_contexts" in stats
assert "selected_count" in stats
assert "excluded_count" in stats
assert "total_tokens" in stats
assert "by_type" in stats
@pytest.mark.asyncio
async def test_rank_simple(self) -> None:
"""Test simple ranking without budget per type."""
ranker = ContextRanker()
contexts = [
KnowledgeContext(
content="A",
source="docs",
relevance_score=0.9,
),
KnowledgeContext(
content="B",
source="docs",
relevance_score=0.7,
),
KnowledgeContext(
content="C",
source="docs",
relevance_score=0.5,
),
]
result = await ranker.rank_simple(contexts, "query", max_tokens=1000)
# Should return contexts sorted by score
assert len(result) > 0
@pytest.mark.asyncio
async def test_rank_simple_respects_max_tokens(self) -> None:
"""Test that simple ranking respects max tokens."""
ranker = ContextRanker()
# Create contexts with known token counts
contexts = [
KnowledgeContext(
content="A" * 100, # ~25 tokens
source="docs",
relevance_score=0.9,
),
KnowledgeContext(
content="B" * 100,
source="docs",
relevance_score=0.8,
),
KnowledgeContext(
content="C" * 100,
source="docs",
relevance_score=0.7,
),
]
# Very small limit
result = await ranker.rank_simple(contexts, "query", max_tokens=30)
# Should only fit a limited number
assert len(result) <= len(contexts)
@pytest.mark.asyncio
async def test_rank_simple_empty(self) -> None:
"""Test simple ranking with empty list."""
ranker = ContextRanker()
result = await ranker.rank_simple([], "query", max_tokens=1000)
assert result == []
@pytest.mark.asyncio
async def test_rerank_for_diversity(self) -> None:
"""Test diversity reranking."""
ranker = ContextRanker()
# Create scored contexts from same source
contexts = [
ScoredContext(
context=KnowledgeContext(
content=f"Content {i}",
source="same-source",
relevance_score=0.9 - i * 0.1,
),
composite_score=0.9 - i * 0.1,
)
for i in range(5)
]
# Limit to 2 per source
result = await ranker.rerank_for_diversity(contexts, max_per_source=2)
assert len(result) == 5
# First 2 should be from same source, rest deferred
first_two_sources = [r.context.source for r in result[:2]]
assert all(s == "same-source" for s in first_two_sources)
@pytest.mark.asyncio
async def test_rerank_for_diversity_multiple_sources(self) -> None:
"""Test diversity reranking with multiple sources."""
ranker = ContextRanker()
contexts = [
ScoredContext(
context=KnowledgeContext(
content="Source A - 1",
source="source-a",
relevance_score=0.9,
),
composite_score=0.9,
),
ScoredContext(
context=KnowledgeContext(
content="Source A - 2",
source="source-a",
relevance_score=0.8,
),
composite_score=0.8,
),
ScoredContext(
context=KnowledgeContext(
content="Source B - 1",
source="source-b",
relevance_score=0.7,
),
composite_score=0.7,
),
ScoredContext(
context=KnowledgeContext(
content="Source A - 3",
source="source-a",
relevance_score=0.6,
),
composite_score=0.6,
),
]
result = await ranker.rerank_for_diversity(contexts, max_per_source=2)
# Should not have more than 2 from source-a in first 3
source_a_in_first_3 = sum(
1 for r in result[:3] if r.context.source == "source-a"
)
assert source_a_in_first_3 <= 2
@pytest.mark.asyncio
async def test_token_counts_set(self) -> None:
"""Test that token counts are set during ranking."""
ranker = ContextRanker()
allocator = BudgetAllocator()
budget = allocator.create_budget(10000)
context = KnowledgeContext(
content="Test content",
source="docs",
relevance_score=0.8,
)
# Token count should be None initially
assert context.token_count is None
await ranker.rank([context], "query", budget)
# Token count should be set after ranking
assert context.token_count is not None
assert context.token_count > 0
class TestContextRankerIntegration:
"""Integration tests for context ranking."""
@pytest.mark.asyncio
async def test_full_ranking_workflow(self) -> None:
"""Test complete ranking workflow."""
ranker = ContextRanker()
allocator = BudgetAllocator()
budget = allocator.create_budget(10000)
# Create diverse context types
contexts = [
SystemContext(
content="You are a helpful assistant.",
source="system",
priority=ContextPriority.CRITICAL.value,
),
TaskContext(
content="Help the user with their coding question.",
source="task",
priority=ContextPriority.HIGH.value,
),
KnowledgeContext(
content="Python is a programming language.",
source="docs/python.md",
relevance_score=0.9,
),
KnowledgeContext(
content="Java is also a programming language.",
source="docs/java.md",
relevance_score=0.4,
),
ConversationContext(
content="Hello, can you help me?",
source="chat",
role=MessageRole.USER,
),
]
result = await ranker.rank(contexts, "Python help", budget)
# System (CRITICAL) should be included
selected_types = [s.context.get_type() for s in result.selected]
assert ContextType.SYSTEM in selected_types
# Stats should be populated
assert result.selection_stats["total_contexts"] == 5
@pytest.mark.asyncio
async def test_ranking_preserves_context_order_by_score(self) -> None:
"""Test that ranking orders by score correctly."""
ranker = ContextRanker()
allocator = BudgetAllocator()
budget = allocator.create_budget(100000)
contexts = [
KnowledgeContext(
content="Low",
source="docs",
relevance_score=0.2,
),
KnowledgeContext(
content="High",
source="docs",
relevance_score=0.9,
),
KnowledgeContext(
content="Medium",
source="docs",
relevance_score=0.5,
),
]
result = await ranker.rank(contexts, "query", budget)
# Verify ordering is by score
scores = [s.composite_score for s in result.selected]
assert scores == sorted(scores, reverse=True)

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"""Tests for context scoring module."""
from datetime import UTC, datetime, timedelta
from unittest.mock import AsyncMock, MagicMock
import pytest
from app.services.context.scoring import (
CompositeScorer,
PriorityScorer,
RecencyScorer,
RelevanceScorer,
ScoredContext,
)
from app.services.context.types import (
ContextPriority,
ContextType,
ConversationContext,
KnowledgeContext,
MessageRole,
SystemContext,
TaskContext,
)
class TestRelevanceScorer:
"""Tests for RelevanceScorer."""
def test_creation(self) -> None:
"""Test scorer creation."""
scorer = RelevanceScorer()
assert scorer.weight == 1.0
def test_creation_with_weight(self) -> None:
"""Test scorer creation with custom weight."""
scorer = RelevanceScorer(weight=0.5)
assert scorer.weight == 0.5
@pytest.mark.asyncio
async def test_score_with_precomputed_relevance(self) -> None:
"""Test scoring with pre-computed relevance score."""
scorer = RelevanceScorer()
# KnowledgeContext with pre-computed score
context = KnowledgeContext(
content="Test content about Python",
source="docs/python.md",
relevance_score=0.85,
)
score = await scorer.score(context, "Python programming")
assert score == 0.85
@pytest.mark.asyncio
async def test_score_with_metadata_score(self) -> None:
"""Test scoring with metadata-provided score."""
scorer = RelevanceScorer()
context = SystemContext(
content="System prompt",
source="system",
metadata={"relevance_score": 0.9},
)
score = await scorer.score(context, "anything")
assert score == 0.9
@pytest.mark.asyncio
async def test_score_fallback_to_keyword_matching(self) -> None:
"""Test fallback to keyword matching when no score available."""
scorer = RelevanceScorer(keyword_fallback_weight=0.5)
context = TaskContext(
content="Implement authentication with JWT tokens",
source="task",
)
# Query has matching keywords
score = await scorer.score(context, "JWT authentication")
assert score > 0
@pytest.mark.asyncio
async def test_keyword_matching_no_overlap(self) -> None:
"""Test keyword matching with no query overlap."""
scorer = RelevanceScorer()
context = TaskContext(
content="Implement database migration",
source="task",
)
score = await scorer.score(context, "xyz abc 123")
assert score == 0.0
@pytest.mark.asyncio
async def test_keyword_matching_full_overlap(self) -> None:
"""Test keyword matching with high overlap."""
scorer = RelevanceScorer(keyword_fallback_weight=1.0)
context = TaskContext(
content="python programming language",
source="task",
)
score = await scorer.score(context, "python programming")
# Should have high score due to keyword overlap
assert score > 0.5
@pytest.mark.asyncio
async def test_score_with_mcp_success(self) -> None:
"""Test scoring with MCP semantic similarity."""
mock_mcp = MagicMock()
mock_result = MagicMock()
mock_result.success = True
mock_result.data = {"similarity": 0.75}
mock_mcp.call_tool = AsyncMock(return_value=mock_result)
scorer = RelevanceScorer(mcp_manager=mock_mcp)
context = TaskContext(
content="Test content",
source="task",
)
score = await scorer.score(context, "test query")
assert score == 0.75
@pytest.mark.asyncio
async def test_score_with_mcp_failure_fallback(self) -> None:
"""Test fallback when MCP fails."""
mock_mcp = MagicMock()
mock_mcp.call_tool = AsyncMock(side_effect=Exception("Connection failed"))
scorer = RelevanceScorer(mcp_manager=mock_mcp, keyword_fallback_weight=0.5)
context = TaskContext(
content="Python programming code",
source="task",
)
# Should fall back to keyword matching
score = await scorer.score(context, "Python code")
assert score > 0
@pytest.mark.asyncio
async def test_score_batch(self) -> None:
"""Test batch scoring."""
scorer = RelevanceScorer()
contexts = [
KnowledgeContext(content="Python", source="1", relevance_score=0.8),
KnowledgeContext(content="Java", source="2", relevance_score=0.6),
KnowledgeContext(content="Go", source="3", relevance_score=0.9),
]
scores = await scorer.score_batch(contexts, "test")
assert len(scores) == 3
assert scores[0] == 0.8
assert scores[1] == 0.6
assert scores[2] == 0.9
def test_set_mcp_manager(self) -> None:
"""Test setting MCP manager."""
scorer = RelevanceScorer()
assert scorer._mcp is None
mock_mcp = MagicMock()
scorer.set_mcp_manager(mock_mcp)
assert scorer._mcp is mock_mcp
class TestRecencyScorer:
"""Tests for RecencyScorer."""
def test_creation(self) -> None:
"""Test scorer creation."""
scorer = RecencyScorer()
assert scorer.weight == 1.0
assert scorer._half_life_hours == 24.0
def test_creation_with_custom_half_life(self) -> None:
"""Test scorer creation with custom half-life."""
scorer = RecencyScorer(half_life_hours=12.0)
assert scorer._half_life_hours == 12.0
@pytest.mark.asyncio
async def test_score_recent_context(self) -> None:
"""Test scoring a very recent context."""
scorer = RecencyScorer(half_life_hours=24.0)
now = datetime.now(UTC)
context = TaskContext(
content="Recent task",
source="task",
timestamp=now,
)
score = await scorer.score(context, "query", reference_time=now)
# Very recent should have score near 1.0
assert score > 0.99
@pytest.mark.asyncio
async def test_score_at_half_life(self) -> None:
"""Test scoring at exactly half-life age."""
scorer = RecencyScorer(half_life_hours=24.0)
now = datetime.now(UTC)
half_life_ago = now - timedelta(hours=24)
context = TaskContext(
content="Day old task",
source="task",
timestamp=half_life_ago,
)
score = await scorer.score(context, "query", reference_time=now)
# At half-life, score should be ~0.5
assert 0.49 <= score <= 0.51
@pytest.mark.asyncio
async def test_score_old_context(self) -> None:
"""Test scoring a very old context."""
scorer = RecencyScorer(half_life_hours=24.0)
now = datetime.now(UTC)
week_ago = now - timedelta(days=7)
context = TaskContext(
content="Week old task",
source="task",
timestamp=week_ago,
)
score = await scorer.score(context, "query", reference_time=now)
# 7 days with 24h half-life = very low score
assert score < 0.01
@pytest.mark.asyncio
async def test_type_specific_half_lives(self) -> None:
"""Test that different context types have different half-lives."""
scorer = RecencyScorer()
now = datetime.now(UTC)
one_hour_ago = now - timedelta(hours=1)
# Conversation has 1 hour half-life by default
conv_context = ConversationContext(
content="Hello",
source="chat",
role=MessageRole.USER,
timestamp=one_hour_ago,
)
# Knowledge has 168 hour (1 week) half-life by default
knowledge_context = KnowledgeContext(
content="Documentation",
source="docs",
timestamp=one_hour_ago,
)
conv_score = await scorer.score(conv_context, "query", reference_time=now)
knowledge_score = await scorer.score(
knowledge_context, "query", reference_time=now
)
# Conversation should decay much faster
assert conv_score < knowledge_score
def test_get_half_life(self) -> None:
"""Test getting half-life for context type."""
scorer = RecencyScorer()
assert scorer.get_half_life(ContextType.CONVERSATION) == 1.0
assert scorer.get_half_life(ContextType.KNOWLEDGE) == 168.0
assert scorer.get_half_life(ContextType.SYSTEM) == 720.0
def test_set_half_life(self) -> None:
"""Test setting custom half-life."""
scorer = RecencyScorer()
scorer.set_half_life(ContextType.TASK, 48.0)
assert scorer.get_half_life(ContextType.TASK) == 48.0
def test_set_half_life_invalid(self) -> None:
"""Test setting invalid half-life."""
scorer = RecencyScorer()
with pytest.raises(ValueError):
scorer.set_half_life(ContextType.TASK, 0)
with pytest.raises(ValueError):
scorer.set_half_life(ContextType.TASK, -1)
@pytest.mark.asyncio
async def test_score_batch(self) -> None:
"""Test batch scoring."""
scorer = RecencyScorer()
now = datetime.now(UTC)
contexts = [
TaskContext(content="1", source="t", timestamp=now),
TaskContext(content="2", source="t", timestamp=now - timedelta(hours=24)),
TaskContext(content="3", source="t", timestamp=now - timedelta(hours=48)),
]
scores = await scorer.score_batch(contexts, "query", reference_time=now)
assert len(scores) == 3
# Scores should be in descending order (more recent = higher)
assert scores[0] > scores[1] > scores[2]
class TestPriorityScorer:
"""Tests for PriorityScorer."""
def test_creation(self) -> None:
"""Test scorer creation."""
scorer = PriorityScorer()
assert scorer.weight == 1.0
@pytest.mark.asyncio
async def test_score_critical_priority(self) -> None:
"""Test scoring CRITICAL priority context."""
scorer = PriorityScorer()
context = SystemContext(
content="Critical system prompt",
source="system",
priority=ContextPriority.CRITICAL.value,
)
score = await scorer.score(context, "query")
# CRITICAL (100) + type bonus should be > 1.0, normalized to 1.0
assert score == 1.0
@pytest.mark.asyncio
async def test_score_normal_priority(self) -> None:
"""Test scoring NORMAL priority context."""
scorer = PriorityScorer()
context = TaskContext(
content="Normal task",
source="task",
priority=ContextPriority.NORMAL.value,
)
score = await scorer.score(context, "query")
# NORMAL (50) = 0.5, plus TASK bonus (0.15) = 0.65
assert 0.6 <= score <= 0.7
@pytest.mark.asyncio
async def test_score_low_priority(self) -> None:
"""Test scoring LOW priority context."""
scorer = PriorityScorer()
context = KnowledgeContext(
content="Low priority knowledge",
source="docs",
priority=ContextPriority.LOW.value,
)
score = await scorer.score(context, "query")
# LOW (20) = 0.2, no bonus for KNOWLEDGE
assert 0.15 <= score <= 0.25
@pytest.mark.asyncio
async def test_type_bonuses(self) -> None:
"""Test type-specific priority bonuses."""
scorer = PriorityScorer()
# All with same base priority
system_ctx = SystemContext(
content="System",
source="system",
priority=50,
)
task_ctx = TaskContext(
content="Task",
source="task",
priority=50,
)
knowledge_ctx = KnowledgeContext(
content="Knowledge",
source="docs",
priority=50,
)
system_score = await scorer.score(system_ctx, "query")
task_score = await scorer.score(task_ctx, "query")
knowledge_score = await scorer.score(knowledge_ctx, "query")
# System has highest bonus (0.2), task next (0.15), knowledge has none
assert system_score > task_score > knowledge_score
def test_get_type_bonus(self) -> None:
"""Test getting type bonus."""
scorer = PriorityScorer()
assert scorer.get_type_bonus(ContextType.SYSTEM) == 0.2
assert scorer.get_type_bonus(ContextType.TASK) == 0.15
assert scorer.get_type_bonus(ContextType.KNOWLEDGE) == 0.0
def test_set_type_bonus(self) -> None:
"""Test setting custom type bonus."""
scorer = PriorityScorer()
scorer.set_type_bonus(ContextType.KNOWLEDGE, 0.1)
assert scorer.get_type_bonus(ContextType.KNOWLEDGE) == 0.1
def test_set_type_bonus_invalid(self) -> None:
"""Test setting invalid type bonus."""
scorer = PriorityScorer()
with pytest.raises(ValueError):
scorer.set_type_bonus(ContextType.KNOWLEDGE, 1.5)
with pytest.raises(ValueError):
scorer.set_type_bonus(ContextType.KNOWLEDGE, -0.1)
class TestCompositeScorer:
"""Tests for CompositeScorer."""
def test_creation(self) -> None:
"""Test scorer creation with default weights."""
scorer = CompositeScorer()
weights = scorer.weights
assert weights["relevance"] == 0.5
assert weights["recency"] == 0.3
assert weights["priority"] == 0.2
def test_creation_with_custom_weights(self) -> None:
"""Test scorer creation with custom weights."""
scorer = CompositeScorer(
relevance_weight=0.6,
recency_weight=0.2,
priority_weight=0.2,
)
weights = scorer.weights
assert weights["relevance"] == 0.6
assert weights["recency"] == 0.2
assert weights["priority"] == 0.2
def test_update_weights(self) -> None:
"""Test updating weights."""
scorer = CompositeScorer()
scorer.update_weights(relevance=0.7, recency=0.2, priority=0.1)
weights = scorer.weights
assert weights["relevance"] == 0.7
assert weights["recency"] == 0.2
assert weights["priority"] == 0.1
def test_update_weights_partial(self) -> None:
"""Test partially updating weights."""
scorer = CompositeScorer()
original_recency = scorer.weights["recency"]
scorer.update_weights(relevance=0.8)
assert scorer.weights["relevance"] == 0.8
assert scorer.weights["recency"] == original_recency
@pytest.mark.asyncio
async def test_score_basic(self) -> None:
"""Test basic composite scoring."""
scorer = CompositeScorer()
context = KnowledgeContext(
content="Test content",
source="docs",
relevance_score=0.8,
timestamp=datetime.now(UTC),
priority=ContextPriority.NORMAL.value,
)
score = await scorer.score(context, "test query")
assert 0.0 <= score <= 1.0
@pytest.mark.asyncio
async def test_score_with_details(self) -> None:
"""Test scoring with detailed breakdown."""
scorer = CompositeScorer()
context = KnowledgeContext(
content="Test content",
source="docs",
relevance_score=0.8,
timestamp=datetime.now(UTC),
priority=ContextPriority.HIGH.value,
)
scored = await scorer.score_with_details(context, "test query")
assert isinstance(scored, ScoredContext)
assert scored.context is context
assert 0.0 <= scored.composite_score <= 1.0
assert scored.relevance_score == 0.8
assert scored.recency_score > 0.9 # Very recent
assert scored.priority_score > 0.5 # HIGH priority
@pytest.mark.asyncio
async def test_score_not_cached_on_context(self) -> None:
"""Test that scores are NOT cached on the context.
Scores should not be cached on the context because they are query-dependent.
Different queries would get incorrect cached scores if we cached on the context.
"""
scorer = CompositeScorer()
context = KnowledgeContext(
content="Test",
source="docs",
relevance_score=0.5,
)
# After scoring, context._score should remain None
# (we don't cache on context because scores are query-dependent)
await scorer.score(context, "query")
# The scorer should compute fresh scores each time
# rather than caching on the context object
# Score again with different query - should compute fresh score
score1 = await scorer.score(context, "query 1")
score2 = await scorer.score(context, "query 2")
# Both should be valid scores (not necessarily equal since queries differ)
assert 0.0 <= score1 <= 1.0
assert 0.0 <= score2 <= 1.0
@pytest.mark.asyncio
async def test_score_batch(self) -> None:
"""Test batch scoring."""
scorer = CompositeScorer()
contexts = [
KnowledgeContext(
content="High relevance",
source="docs",
relevance_score=0.9,
),
KnowledgeContext(
content="Low relevance",
source="docs",
relevance_score=0.2,
),
]
scored = await scorer.score_batch(contexts, "query")
assert len(scored) == 2
assert scored[0].relevance_score > scored[1].relevance_score
@pytest.mark.asyncio
async def test_rank(self) -> None:
"""Test ranking contexts."""
scorer = CompositeScorer()
contexts = [
KnowledgeContext(content="Low", source="docs", relevance_score=0.2),
KnowledgeContext(content="High", source="docs", relevance_score=0.9),
KnowledgeContext(content="Medium", source="docs", relevance_score=0.5),
]
ranked = await scorer.rank(contexts, "query")
# Should be sorted by score (highest first)
assert len(ranked) == 3
assert ranked[0].relevance_score == 0.9
assert ranked[1].relevance_score == 0.5
assert ranked[2].relevance_score == 0.2
@pytest.mark.asyncio
async def test_rank_with_limit(self) -> None:
"""Test ranking with limit."""
scorer = CompositeScorer()
contexts = [
KnowledgeContext(content=str(i), source="docs", relevance_score=i / 10)
for i in range(10)
]
ranked = await scorer.rank(contexts, "query", limit=3)
assert len(ranked) == 3
@pytest.mark.asyncio
async def test_rank_with_min_score(self) -> None:
"""Test ranking with minimum score threshold."""
scorer = CompositeScorer()
contexts = [
KnowledgeContext(content="Low", source="docs", relevance_score=0.1),
KnowledgeContext(content="High", source="docs", relevance_score=0.9),
]
ranked = await scorer.rank(contexts, "query", min_score=0.5)
# Only the high relevance context should pass the threshold
assert len(ranked) <= 2 # Could be 1 if min_score filters
def test_set_mcp_manager(self) -> None:
"""Test setting MCP manager."""
scorer = CompositeScorer()
mock_mcp = MagicMock()
scorer.set_mcp_manager(mock_mcp)
assert scorer._relevance_scorer._mcp is mock_mcp
@pytest.mark.asyncio
async def test_concurrent_scoring_same_context_no_race(self) -> None:
"""Test that concurrent scoring of the same context doesn't cause race conditions.
This verifies that the per-context locking mechanism prevents the same context
from being scored multiple times when scored concurrently.
"""
import asyncio
# Use scorer with recency_weight=0 to eliminate time-dependent variation
# (recency scores change as time passes between calls)
scorer = CompositeScorer(
relevance_weight=0.5,
recency_weight=0.0, # Disable recency to get deterministic results
priority_weight=0.5,
)
# Create a single context that will be scored multiple times concurrently
context = KnowledgeContext(
content="Test content for race condition test",
source="docs",
relevance_score=0.75,
)
# Score the same context many times in parallel
num_concurrent = 50
tasks = [scorer.score(context, "test query") for _ in range(num_concurrent)]
scores = await asyncio.gather(*tasks)
# All scores should be identical (deterministic scoring without recency)
assert all(s == scores[0] for s in scores)
# Note: We don't cache _score on context because scores are query-dependent
@pytest.mark.asyncio
async def test_concurrent_scoring_different_contexts(self) -> None:
"""Test that concurrent scoring of different contexts works correctly.
Different contexts should not interfere with each other during parallel scoring.
"""
import asyncio
scorer = CompositeScorer()
# Create many different contexts
contexts = [
KnowledgeContext(
content=f"Test content {i}",
source="docs",
relevance_score=i / 10,
)
for i in range(10)
]
# Score all contexts concurrently
tasks = [scorer.score(ctx, "test query") for ctx in contexts]
scores = await asyncio.gather(*tasks)
# Each context should have a different score based on its relevance
assert len(set(scores)) > 1 # Not all the same
# Note: We don't cache _score on context because scores are query-dependent
class TestScoredContext:
"""Tests for ScoredContext dataclass."""
def test_creation(self) -> None:
"""Test ScoredContext creation."""
context = TaskContext(content="Test", source="task")
scored = ScoredContext(
context=context,
composite_score=0.75,
relevance_score=0.8,
recency_score=0.7,
priority_score=0.5,
)
assert scored.context is context
assert scored.composite_score == 0.75
def test_comparison_operators(self) -> None:
"""Test comparison operators for sorting."""
ctx1 = TaskContext(content="1", source="task")
ctx2 = TaskContext(content="2", source="task")
scored1 = ScoredContext(context=ctx1, composite_score=0.5)
scored2 = ScoredContext(context=ctx2, composite_score=0.8)
assert scored1 < scored2
assert scored2 > scored1
def test_sorting(self) -> None:
"""Test sorting scored contexts."""
contexts = [
ScoredContext(
context=TaskContext(content="Low", source="task"),
composite_score=0.3,
),
ScoredContext(
context=TaskContext(content="High", source="task"),
composite_score=0.9,
),
ScoredContext(
context=TaskContext(content="Medium", source="task"),
composite_score=0.6,
),
]
sorted_contexts = sorted(contexts, reverse=True)
assert sorted_contexts[0].composite_score == 0.9
assert sorted_contexts[1].composite_score == 0.6
assert sorted_contexts[2].composite_score == 0.3
class TestBaseScorer:
"""Tests for BaseScorer abstract class."""
def test_weight_property(self) -> None:
"""Test weight property."""
# Use a concrete implementation
scorer = RelevanceScorer(weight=0.7)
assert scorer.weight == 0.7
def test_weight_setter_valid(self) -> None:
"""Test weight setter with valid values."""
scorer = RelevanceScorer()
scorer.weight = 0.5
assert scorer.weight == 0.5
def test_weight_setter_invalid(self) -> None:
"""Test weight setter with invalid values."""
scorer = RelevanceScorer()
with pytest.raises(ValueError):
scorer.weight = -0.1
with pytest.raises(ValueError):
scorer.weight = 1.5
def test_normalize_score(self) -> None:
"""Test score normalization."""
scorer = RelevanceScorer()
# Normal range
assert scorer.normalize_score(0.5) == 0.5
# Below 0
assert scorer.normalize_score(-0.5) == 0.0
# Above 1
assert scorer.normalize_score(1.5) == 1.0
# Boundaries
assert scorer.normalize_score(0.0) == 0.0
assert scorer.normalize_score(1.0) == 1.0
class TestCompositeScorerEdgeCases:
"""Tests for CompositeScorer edge cases and lock management."""
@pytest.mark.asyncio
async def test_score_with_zero_weights(self) -> None:
"""Test scoring when all weights are zero."""
scorer = CompositeScorer(
relevance_weight=0.0,
recency_weight=0.0,
priority_weight=0.0,
)
context = KnowledgeContext(
content="Test content",
source="docs",
relevance_score=0.8,
)
# Should return 0.0 when total weight is 0
score = await scorer.score(context, "test query")
assert score == 0.0
@pytest.mark.asyncio
async def test_score_batch_sequential(self) -> None:
"""Test batch scoring in sequential mode (parallel=False)."""
scorer = CompositeScorer()
contexts = [
KnowledgeContext(
content="Content 1",
source="docs",
relevance_score=0.8,
),
KnowledgeContext(
content="Content 2",
source="docs",
relevance_score=0.5,
),
]
# Use parallel=False to cover the sequential path
scored = await scorer.score_batch(contexts, "query", parallel=False)
assert len(scored) == 2
assert scored[0].relevance_score == 0.8
assert scored[1].relevance_score == 0.5
@pytest.mark.asyncio
async def test_lock_fast_path_reuse(self) -> None:
"""Test that existing locks are reused via fast path."""
scorer = CompositeScorer()
context = KnowledgeContext(
content="Test",
source="docs",
relevance_score=0.5,
)
# First access creates the lock
lock1 = await scorer._get_context_lock(context.id)
# Second access should hit the fast path (lock exists in dict)
lock2 = await scorer._get_context_lock(context.id)
assert lock2 is lock1 # Same lock object returned
@pytest.mark.asyncio
async def test_lock_cleanup_when_limit_reached(self) -> None:
"""Test that old locks are cleaned up when limit is reached."""
import time
# Create scorer with very low max_locks to trigger cleanup
scorer = CompositeScorer()
scorer._max_locks = 3
scorer._lock_ttl = 0.1 # 100ms TTL
# Create locks for several context IDs
context_ids = [f"ctx-{i}" for i in range(5)]
# Get locks for first 3 contexts (fill up to limit)
for ctx_id in context_ids[:3]:
await scorer._get_context_lock(ctx_id)
# Wait for TTL to expire
time.sleep(0.15)
# Getting a lock for a new context should trigger cleanup
await scorer._get_context_lock(context_ids[3])
# Some old locks should have been cleaned up
# The exact number depends on cleanup logic
assert len(scorer._context_locks) <= scorer._max_locks + 1
@pytest.mark.asyncio
async def test_lock_cleanup_preserves_held_locks(self) -> None:
"""Test that cleanup doesn't remove locks that are currently held."""
import time
scorer = CompositeScorer()
scorer._max_locks = 2
scorer._lock_ttl = 0.05 # 50ms TTL
# Get and hold lock1
lock1 = await scorer._get_context_lock("ctx-1")
async with lock1:
# While holding lock1, add more locks
await scorer._get_context_lock("ctx-2")
time.sleep(0.1) # Let TTL expire
# Adding another should trigger cleanup
await scorer._get_context_lock("ctx-3")
# lock1 should still exist (it's held)
assert any(lock is lock1 for lock, _ in scorer._context_locks.values())
@pytest.mark.asyncio
async def test_concurrent_lock_acquisition_double_check(self) -> None:
"""Test that concurrent lock acquisition uses double-check pattern."""
import asyncio
scorer = CompositeScorer()
context_id = "test-context-id"
# Simulate concurrent lock acquisition
async def get_lock():
return await scorer._get_context_lock(context_id)
locks = await asyncio.gather(*[get_lock() for _ in range(10)])
# All should get the same lock (double-check pattern ensures this)
assert all(lock is locks[0] for lock in locks)

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@@ -0,0 +1,570 @@
"""Tests for context types."""
from datetime import UTC, datetime, timedelta
import pytest
from app.services.context.types import (
AssembledContext,
ContextPriority,
ContextType,
ConversationContext,
KnowledgeContext,
MessageRole,
SystemContext,
TaskContext,
TaskStatus,
ToolContext,
ToolResultStatus,
)
class TestContextType:
"""Tests for ContextType enum."""
def test_all_types_exist(self) -> None:
"""Test that all expected context types exist."""
assert ContextType.SYSTEM
assert ContextType.TASK
assert ContextType.KNOWLEDGE
assert ContextType.CONVERSATION
assert ContextType.TOOL
def test_from_string_valid(self) -> None:
"""Test from_string with valid values."""
assert ContextType.from_string("system") == ContextType.SYSTEM
assert ContextType.from_string("KNOWLEDGE") == ContextType.KNOWLEDGE
assert ContextType.from_string("Task") == ContextType.TASK
def test_from_string_invalid(self) -> None:
"""Test from_string with invalid value."""
with pytest.raises(ValueError) as exc_info:
ContextType.from_string("invalid")
assert "Invalid context type" in str(exc_info.value)
class TestContextPriority:
"""Tests for ContextPriority enum."""
def test_priority_ordering(self) -> None:
"""Test that priorities are ordered correctly."""
assert ContextPriority.LOWEST.value < ContextPriority.LOW.value
assert ContextPriority.LOW.value < ContextPriority.NORMAL.value
assert ContextPriority.NORMAL.value < ContextPriority.HIGH.value
assert ContextPriority.HIGH.value < ContextPriority.HIGHEST.value
assert ContextPriority.HIGHEST.value < ContextPriority.CRITICAL.value
def test_from_int(self) -> None:
"""Test from_int conversion."""
assert ContextPriority.from_int(0) == ContextPriority.LOWEST
assert ContextPriority.from_int(50) == ContextPriority.NORMAL
assert ContextPriority.from_int(100) == ContextPriority.HIGHEST
assert ContextPriority.from_int(200) == ContextPriority.CRITICAL
def test_from_int_intermediate(self) -> None:
"""Test from_int with intermediate values."""
# Should return closest lower priority
assert ContextPriority.from_int(30) == ContextPriority.LOW
assert ContextPriority.from_int(60) == ContextPriority.NORMAL
class TestSystemContext:
"""Tests for SystemContext."""
def test_creation(self) -> None:
"""Test basic creation."""
ctx = SystemContext(
content="You are a helpful assistant.",
source="system_prompt",
)
assert ctx.content == "You are a helpful assistant."
assert ctx.source == "system_prompt"
assert ctx.get_type() == ContextType.SYSTEM
def test_default_high_priority(self) -> None:
"""Test that system context defaults to high priority."""
ctx = SystemContext(content="Test", source="test")
assert ctx.priority == ContextPriority.HIGH.value
def test_create_persona(self) -> None:
"""Test create_persona factory method."""
ctx = SystemContext.create_persona(
name="Code Assistant",
description="A helpful coding assistant.",
capabilities=["Write code", "Debug"],
constraints=["Never expose secrets"],
)
assert "Code Assistant" in ctx.content
assert "helpful coding assistant" in ctx.content
assert "Write code" in ctx.content
assert "Never expose secrets" in ctx.content
assert ctx.priority == ContextPriority.HIGHEST.value
def test_create_instructions(self) -> None:
"""Test create_instructions factory method."""
ctx = SystemContext.create_instructions(
["Always be helpful", "Be concise"],
source="rules",
)
assert "Always be helpful" in ctx.content
assert "Be concise" in ctx.content
def test_to_dict(self) -> None:
"""Test serialization to dict."""
ctx = SystemContext(
content="Test",
source="test",
role="assistant",
instructions_type="general",
)
data = ctx.to_dict()
assert data["role"] == "assistant"
assert data["instructions_type"] == "general"
assert data["type"] == "system"
class TestKnowledgeContext:
"""Tests for KnowledgeContext."""
def test_creation(self) -> None:
"""Test basic creation."""
ctx = KnowledgeContext(
content="def authenticate(user): ...",
source="/src/auth.py",
collection="code",
file_type="python",
)
assert ctx.content == "def authenticate(user): ..."
assert ctx.source == "/src/auth.py"
assert ctx.collection == "code"
assert ctx.get_type() == ContextType.KNOWLEDGE
def test_from_search_result(self) -> None:
"""Test from_search_result factory method."""
result = {
"content": "Test content",
"source_path": "/test/file.py",
"collection": "code",
"file_type": "python",
"chunk_index": 2,
"score": 0.85,
"id": "chunk-123",
}
ctx = KnowledgeContext.from_search_result(result, "test query")
assert ctx.content == "Test content"
assert ctx.source == "/test/file.py"
assert ctx.relevance_score == 0.85
assert ctx.search_query == "test query"
def test_from_search_results(self) -> None:
"""Test from_search_results factory method."""
results = [
{"content": "Content 1", "source_path": "/a.py", "score": 0.9},
{"content": "Content 2", "source_path": "/b.py", "score": 0.8},
]
contexts = KnowledgeContext.from_search_results(results, "query")
assert len(contexts) == 2
assert contexts[0].relevance_score == 0.9
assert contexts[1].source == "/b.py"
def test_is_code(self) -> None:
"""Test is_code method."""
code_ctx = KnowledgeContext(content="code", source="test", file_type="python")
doc_ctx = KnowledgeContext(content="docs", source="test", file_type="markdown")
assert code_ctx.is_code() is True
assert doc_ctx.is_code() is False
def test_is_documentation(self) -> None:
"""Test is_documentation method."""
doc_ctx = KnowledgeContext(content="docs", source="test", file_type="markdown")
code_ctx = KnowledgeContext(content="code", source="test", file_type="python")
assert doc_ctx.is_documentation() is True
assert code_ctx.is_documentation() is False
class TestConversationContext:
"""Tests for ConversationContext."""
def test_creation(self) -> None:
"""Test basic creation."""
ctx = ConversationContext(
content="Hello, how can I help?",
source="conversation",
role=MessageRole.ASSISTANT,
turn_index=1,
)
assert ctx.content == "Hello, how can I help?"
assert ctx.role == MessageRole.ASSISTANT
assert ctx.get_type() == ContextType.CONVERSATION
def test_from_message(self) -> None:
"""Test from_message factory method."""
ctx = ConversationContext.from_message(
content="What is Python?",
role="user",
turn_index=0,
)
assert ctx.content == "What is Python?"
assert ctx.role == MessageRole.USER
assert ctx.turn_index == 0
def test_from_history(self) -> None:
"""Test from_history factory method."""
messages = [
{"role": "user", "content": "Hello"},
{"role": "assistant", "content": "Hi there!"},
{"role": "user", "content": "Help me"},
]
contexts = ConversationContext.from_history(messages)
assert len(contexts) == 3
assert contexts[0].role == MessageRole.USER
assert contexts[1].role == MessageRole.ASSISTANT
assert contexts[2].turn_index == 2
def test_is_user_message(self) -> None:
"""Test is_user_message method."""
user_ctx = ConversationContext(
content="test", source="test", role=MessageRole.USER
)
assistant_ctx = ConversationContext(
content="test", source="test", role=MessageRole.ASSISTANT
)
assert user_ctx.is_user_message() is True
assert assistant_ctx.is_user_message() is False
def test_format_for_prompt(self) -> None:
"""Test format_for_prompt method."""
ctx = ConversationContext.from_message(
content="What is 2+2?",
role="user",
)
formatted = ctx.format_for_prompt()
assert "User:" in formatted
assert "What is 2+2?" in formatted
class TestTaskContext:
"""Tests for TaskContext."""
def test_creation(self) -> None:
"""Test basic creation."""
ctx = TaskContext(
content="Implement login feature",
source="task",
title="Login Feature",
)
assert ctx.content == "Implement login feature"
assert ctx.title == "Login Feature"
assert ctx.get_type() == ContextType.TASK
def test_default_normal_priority(self) -> None:
"""Test that task context uses NORMAL priority from base class."""
ctx = TaskContext(content="Test", source="test")
# TaskContext inherits NORMAL priority from BaseContext
# Use TaskContext.create() for default HIGH priority behavior
assert ctx.priority == ContextPriority.NORMAL.value
def test_explicit_high_priority(self) -> None:
"""Test setting explicit HIGH priority."""
ctx = TaskContext(
content="Test",
source="test",
priority=ContextPriority.HIGH.value,
)
assert ctx.priority == ContextPriority.HIGH.value
def test_create_factory(self) -> None:
"""Test create factory method."""
ctx = TaskContext.create(
title="Add Auth",
description="Implement authentication",
acceptance_criteria=["Tests pass", "Code reviewed"],
constraints=["Use JWT"],
issue_id="123",
)
assert ctx.title == "Add Auth"
assert ctx.content == "Implement authentication"
assert len(ctx.acceptance_criteria) == 2
assert "Use JWT" in ctx.constraints
assert ctx.status == TaskStatus.IN_PROGRESS
def test_format_for_prompt(self) -> None:
"""Test format_for_prompt method."""
ctx = TaskContext.create(
title="Test Task",
description="Do something",
acceptance_criteria=["Works correctly"],
)
formatted = ctx.format_for_prompt()
assert "Task: Test Task" in formatted
assert "Do something" in formatted
assert "Works correctly" in formatted
def test_status_checks(self) -> None:
"""Test status check methods."""
pending = TaskContext(content="test", source="test", status=TaskStatus.PENDING)
completed = TaskContext(
content="test", source="test", status=TaskStatus.COMPLETED
)
blocked = TaskContext(content="test", source="test", status=TaskStatus.BLOCKED)
assert pending.is_active() is True
assert completed.is_complete() is True
assert blocked.is_blocked() is True
class TestToolContext:
"""Tests for ToolContext."""
def test_creation(self) -> None:
"""Test basic creation."""
ctx = ToolContext(
content="Tool result here",
source="tool:search",
tool_name="search",
)
assert ctx.tool_name == "search"
assert ctx.get_type() == ContextType.TOOL
def test_from_tool_definition(self) -> None:
"""Test from_tool_definition factory method."""
ctx = ToolContext.from_tool_definition(
name="search_knowledge",
description="Search the knowledge base",
parameters={
"query": {"type": "string", "required": True},
"limit": {"type": "integer", "required": False},
},
server_name="knowledge-base",
)
assert ctx.tool_name == "search_knowledge"
assert "Search the knowledge base" in ctx.content
assert ctx.is_result is False
assert ctx.server_name == "knowledge-base"
def test_from_tool_result(self) -> None:
"""Test from_tool_result factory method."""
ctx = ToolContext.from_tool_result(
tool_name="search",
result={"found": 5, "items": ["a", "b"]},
status=ToolResultStatus.SUCCESS,
execution_time_ms=150.5,
)
assert ctx.tool_name == "search"
assert ctx.is_result is True
assert ctx.result_status == ToolResultStatus.SUCCESS
assert "found" in ctx.content
def test_is_successful(self) -> None:
"""Test is_successful method."""
success = ToolContext.from_tool_result("test", "ok", ToolResultStatus.SUCCESS)
error = ToolContext.from_tool_result("test", "error", ToolResultStatus.ERROR)
assert success.is_successful() is True
assert error.is_successful() is False
def test_format_for_prompt(self) -> None:
"""Test format_for_prompt method."""
ctx = ToolContext.from_tool_result(
"search",
"Found 3 results",
ToolResultStatus.SUCCESS,
)
formatted = ctx.format_for_prompt()
assert "Tool Result" in formatted
assert "search" in formatted
assert "success" in formatted
class TestAssembledContext:
"""Tests for AssembledContext."""
def test_creation(self) -> None:
"""Test basic creation."""
ctx = AssembledContext(
content="Assembled content here",
total_tokens=500,
context_count=5,
)
assert ctx.content == "Assembled content here"
assert ctx.total_tokens == 500
assert ctx.context_count == 5
# Test backward compatibility aliases
assert ctx.token_count == 500
assert ctx.contexts_included == 5
def test_budget_utilization(self) -> None:
"""Test budget_utilization property."""
ctx = AssembledContext(
content="test",
total_tokens=800,
context_count=5,
budget_total=1000,
budget_used=800,
)
assert ctx.budget_utilization == 0.8
def test_budget_utilization_zero_budget(self) -> None:
"""Test budget_utilization with zero budget."""
ctx = AssembledContext(
content="test",
total_tokens=0,
context_count=0,
budget_total=0,
budget_used=0,
)
assert ctx.budget_utilization == 0.0
def test_to_dict(self) -> None:
"""Test to_dict method."""
ctx = AssembledContext(
content="test",
total_tokens=100,
context_count=2,
assembly_time_ms=50.123,
)
data = ctx.to_dict()
assert data["content"] == "test"
assert data["total_tokens"] == 100
assert data["context_count"] == 2
assert data["assembly_time_ms"] == 50.12 # Rounded
def test_to_json_and_from_json(self) -> None:
"""Test JSON serialization round-trip."""
original = AssembledContext(
content="Test content",
total_tokens=100,
context_count=3,
excluded_count=2,
assembly_time_ms=45.5,
model="claude-3-sonnet",
budget_total=1000,
budget_used=100,
by_type={"system": 20, "knowledge": 80},
cache_hit=True,
cache_key="abc123",
)
json_str = original.to_json()
restored = AssembledContext.from_json(json_str)
assert restored.content == original.content
assert restored.total_tokens == original.total_tokens
assert restored.context_count == original.context_count
assert restored.excluded_count == original.excluded_count
assert restored.model == original.model
assert restored.cache_hit == original.cache_hit
assert restored.cache_key == original.cache_key
class TestBaseContextMethods:
"""Tests for BaseContext methods."""
def test_get_age_seconds(self) -> None:
"""Test get_age_seconds method."""
old_time = datetime.now(UTC) - timedelta(hours=2)
ctx = SystemContext(content="test", source="test", timestamp=old_time)
age = ctx.get_age_seconds()
# Should be approximately 2 hours in seconds
assert 7100 < age < 7300
def test_get_age_hours(self) -> None:
"""Test get_age_hours method."""
old_time = datetime.now(UTC) - timedelta(hours=5)
ctx = SystemContext(content="test", source="test", timestamp=old_time)
age = ctx.get_age_hours()
assert 4.9 < age < 5.1
def test_is_stale(self) -> None:
"""Test is_stale method."""
old_time = datetime.now(UTC) - timedelta(days=10)
new_time = datetime.now(UTC) - timedelta(hours=1)
old_ctx = SystemContext(content="test", source="test", timestamp=old_time)
new_ctx = SystemContext(content="test", source="test", timestamp=new_time)
# Default max_age is 168 hours (7 days)
assert old_ctx.is_stale() is True
assert new_ctx.is_stale() is False
def test_token_count_property(self) -> None:
"""Test token_count property."""
ctx = SystemContext(content="test", source="test")
# Initially None
assert ctx.token_count is None
# Can be set
ctx.token_count = 100
assert ctx.token_count == 100
def test_score_property_clamping(self) -> None:
"""Test that score is clamped to 0.0-1.0."""
ctx = SystemContext(content="test", source="test")
ctx.score = 1.5
assert ctx.score == 1.0
ctx.score = -0.5
assert ctx.score == 0.0
ctx.score = 0.75
assert ctx.score == 0.75
def test_hash_and_equality(self) -> None:
"""Test hash and equality based on ID."""
ctx1 = SystemContext(content="test", source="test")
ctx2 = SystemContext(content="test", source="test")
ctx3 = SystemContext(content="test", source="test")
ctx3.id = ctx1.id # Same ID as ctx1
# Different IDs = not equal
assert ctx1 != ctx2
# Same ID = equal
assert ctx1 == ctx3
# Can be used in sets
context_set = {ctx1, ctx2, ctx3}
assert len(context_set) == 2 # ctx1 and ctx3 are same
def test_truncate(self) -> None:
"""Test truncate method."""
long_content = "word " * 1000 # Long content
ctx = SystemContext(content=long_content, source="test")
ctx.token_count = 1000
truncated = ctx.truncate(100)
assert len(truncated) < len(long_content)
assert "[truncated]" in truncated

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"""
Tests for Audit Logger.
Tests cover:
- AuditLogger initialization and lifecycle
- Event logging and hash chain
- Query and filtering
- Retention policy enforcement
- Handler management
- Singleton pattern
"""
import asyncio
from datetime import datetime, timedelta
from unittest.mock import MagicMock, patch
import pytest
import pytest_asyncio
from app.services.safety.audit.logger import (
AuditLogger,
get_audit_logger,
reset_audit_logger,
shutdown_audit_logger,
)
from app.services.safety.models import (
ActionMetadata,
ActionRequest,
ActionType,
AuditEventType,
AutonomyLevel,
SafetyDecision,
)
class TestAuditLoggerInit:
"""Tests for AuditLogger initialization."""
def test_init_default_values(self):
"""Test initialization with default values."""
logger = AuditLogger()
assert logger._flush_interval == 10.0
assert logger._enable_hash_chain is True
assert logger._last_hash is None
assert logger._running is False
def test_init_custom_values(self):
"""Test initialization with custom values."""
logger = AuditLogger(
max_buffer_size=500,
flush_interval_seconds=5.0,
enable_hash_chain=False,
)
assert logger._flush_interval == 5.0
assert logger._enable_hash_chain is False
class TestAuditLoggerLifecycle:
"""Tests for AuditLogger start/stop."""
@pytest.mark.asyncio
async def test_start_creates_flush_task(self):
"""Test that start creates the periodic flush task."""
logger = AuditLogger(flush_interval_seconds=1.0)
await logger.start()
assert logger._running is True
assert logger._flush_task is not None
await logger.stop()
@pytest.mark.asyncio
async def test_start_idempotent(self):
"""Test that multiple starts don't create multiple tasks."""
logger = AuditLogger()
await logger.start()
task1 = logger._flush_task
await logger.start() # Second start
task2 = logger._flush_task
assert task1 is task2
await logger.stop()
@pytest.mark.asyncio
async def test_stop_cancels_task_and_flushes(self):
"""Test that stop cancels the task and flushes events."""
logger = AuditLogger()
await logger.start()
# Add an event
await logger.log(AuditEventType.ACTION_REQUESTED, agent_id="agent-1")
await logger.stop()
assert logger._running is False
# Event should be flushed
assert len(logger._persisted) == 1
@pytest.mark.asyncio
async def test_stop_without_start(self):
"""Test stopping without starting doesn't error."""
logger = AuditLogger()
await logger.stop() # Should not raise
class TestAuditLoggerLog:
"""Tests for the log method."""
@pytest_asyncio.fixture
async def logger(self):
"""Create a logger instance."""
return AuditLogger(enable_hash_chain=True)
@pytest.mark.asyncio
async def test_log_creates_event(self, logger):
"""Test logging creates an event."""
event = await logger.log(
AuditEventType.ACTION_REQUESTED,
agent_id="agent-1",
project_id="proj-1",
)
assert event.event_type == AuditEventType.ACTION_REQUESTED
assert event.agent_id == "agent-1"
assert event.project_id == "proj-1"
assert event.id is not None
assert event.timestamp is not None
@pytest.mark.asyncio
async def test_log_adds_hash_chain(self, logger):
"""Test logging adds hash chain."""
event = await logger.log(
AuditEventType.ACTION_REQUESTED,
agent_id="agent-1",
)
assert "_hash" in event.details
assert "_prev_hash" in event.details
assert event.details["_prev_hash"] is None # First event
@pytest.mark.asyncio
async def test_log_chain_links_events(self, logger):
"""Test hash chain links events."""
event1 = await logger.log(AuditEventType.ACTION_REQUESTED)
event2 = await logger.log(AuditEventType.ACTION_EXECUTED)
assert event2.details["_prev_hash"] == event1.details["_hash"]
@pytest.mark.asyncio
async def test_log_without_hash_chain(self):
"""Test logging without hash chain."""
logger = AuditLogger(enable_hash_chain=False)
event = await logger.log(AuditEventType.ACTION_REQUESTED)
assert "_hash" not in event.details
assert "_prev_hash" not in event.details
@pytest.mark.asyncio
async def test_log_with_all_fields(self, logger):
"""Test logging with all optional fields."""
event = await logger.log(
AuditEventType.ACTION_EXECUTED,
agent_id="agent-1",
action_id="action-1",
project_id="proj-1",
session_id="sess-1",
user_id="user-1",
decision=SafetyDecision.ALLOW,
details={"custom": "data"},
correlation_id="corr-1",
)
assert event.agent_id == "agent-1"
assert event.action_id == "action-1"
assert event.project_id == "proj-1"
assert event.session_id == "sess-1"
assert event.user_id == "user-1"
assert event.decision == SafetyDecision.ALLOW
assert event.details["custom"] == "data"
assert event.correlation_id == "corr-1"
@pytest.mark.asyncio
async def test_log_buffers_event(self, logger):
"""Test logging adds event to buffer."""
await logger.log(AuditEventType.ACTION_REQUESTED)
assert len(logger._buffer) == 1
class TestAuditLoggerConvenienceMethods:
"""Tests for convenience logging methods."""
@pytest_asyncio.fixture
async def logger(self):
"""Create a logger instance."""
return AuditLogger(enable_hash_chain=False)
@pytest_asyncio.fixture
def action(self):
"""Create a test action request."""
metadata = ActionMetadata(
agent_id="agent-1",
session_id="sess-1",
project_id="proj-1",
autonomy_level=AutonomyLevel.MILESTONE,
user_id="user-1",
correlation_id="corr-1",
)
return ActionRequest(
action_type=ActionType.FILE_WRITE,
tool_name="file_write",
arguments={"path": "/test.txt"},
resource="/test.txt",
metadata=metadata,
)
@pytest.mark.asyncio
async def test_log_action_request_allowed(self, logger, action):
"""Test logging allowed action request."""
event = await logger.log_action_request(
action,
SafetyDecision.ALLOW,
reasons=["Within budget"],
)
assert event.event_type == AuditEventType.ACTION_VALIDATED
assert event.decision == SafetyDecision.ALLOW
assert event.details["reasons"] == ["Within budget"]
@pytest.mark.asyncio
async def test_log_action_request_denied(self, logger, action):
"""Test logging denied action request."""
event = await logger.log_action_request(
action,
SafetyDecision.DENY,
reasons=["Rate limit exceeded"],
)
assert event.event_type == AuditEventType.ACTION_DENIED
assert event.decision == SafetyDecision.DENY
@pytest.mark.asyncio
async def test_log_action_executed_success(self, logger, action):
"""Test logging successful action execution."""
event = await logger.log_action_executed(
action,
success=True,
execution_time_ms=50.0,
)
assert event.event_type == AuditEventType.ACTION_EXECUTED
assert event.details["success"] is True
assert event.details["execution_time_ms"] == 50.0
assert event.details["error"] is None
@pytest.mark.asyncio
async def test_log_action_executed_failure(self, logger, action):
"""Test logging failed action execution."""
event = await logger.log_action_executed(
action,
success=False,
execution_time_ms=100.0,
error="File not found",
)
assert event.event_type == AuditEventType.ACTION_FAILED
assert event.details["success"] is False
assert event.details["error"] == "File not found"
@pytest.mark.asyncio
async def test_log_approval_event(self, logger, action):
"""Test logging approval event."""
event = await logger.log_approval_event(
AuditEventType.APPROVAL_GRANTED,
approval_id="approval-1",
action=action,
decided_by="admin",
reason="Approved by admin",
)
assert event.event_type == AuditEventType.APPROVAL_GRANTED
assert event.details["approval_id"] == "approval-1"
assert event.details["decided_by"] == "admin"
@pytest.mark.asyncio
async def test_log_budget_event(self, logger):
"""Test logging budget event."""
event = await logger.log_budget_event(
AuditEventType.BUDGET_WARNING,
agent_id="agent-1",
scope="daily",
current_usage=8000.0,
limit=10000.0,
unit="tokens",
)
assert event.event_type == AuditEventType.BUDGET_WARNING
assert event.details["scope"] == "daily"
assert event.details["usage_percent"] == 80.0
@pytest.mark.asyncio
async def test_log_budget_event_zero_limit(self, logger):
"""Test logging budget event with zero limit."""
event = await logger.log_budget_event(
AuditEventType.BUDGET_WARNING,
agent_id="agent-1",
scope="daily",
current_usage=100.0,
limit=0.0, # Zero limit
)
assert event.details["usage_percent"] == 0
@pytest.mark.asyncio
async def test_log_emergency_stop(self, logger):
"""Test logging emergency stop."""
event = await logger.log_emergency_stop(
stop_type="global",
triggered_by="admin",
reason="Security incident",
affected_agents=["agent-1", "agent-2"],
)
assert event.event_type == AuditEventType.EMERGENCY_STOP
assert event.details["stop_type"] == "global"
assert event.details["affected_agents"] == ["agent-1", "agent-2"]
class TestAuditLoggerFlush:
"""Tests for flush functionality."""
@pytest.mark.asyncio
async def test_flush_persists_events(self):
"""Test flush moves events to persisted storage."""
logger = AuditLogger(enable_hash_chain=False)
await logger.log(AuditEventType.ACTION_REQUESTED)
await logger.log(AuditEventType.ACTION_EXECUTED)
assert len(logger._buffer) == 2
assert len(logger._persisted) == 0
count = await logger.flush()
assert count == 2
assert len(logger._buffer) == 0
assert len(logger._persisted) == 2
@pytest.mark.asyncio
async def test_flush_empty_buffer(self):
"""Test flush with empty buffer."""
logger = AuditLogger()
count = await logger.flush()
assert count == 0
class TestAuditLoggerQuery:
"""Tests for query functionality."""
@pytest_asyncio.fixture
async def logger_with_events(self):
"""Create a logger with some test events."""
logger = AuditLogger(enable_hash_chain=False)
# Add various events
await logger.log(
AuditEventType.ACTION_REQUESTED,
agent_id="agent-1",
project_id="proj-1",
)
await logger.log(
AuditEventType.ACTION_EXECUTED,
agent_id="agent-1",
project_id="proj-1",
)
await logger.log(
AuditEventType.ACTION_DENIED,
agent_id="agent-2",
project_id="proj-2",
)
await logger.log(
AuditEventType.BUDGET_WARNING,
agent_id="agent-1",
project_id="proj-1",
user_id="user-1",
)
return logger
@pytest.mark.asyncio
async def test_query_all(self, logger_with_events):
"""Test querying all events."""
events = await logger_with_events.query()
assert len(events) == 4
@pytest.mark.asyncio
async def test_query_by_event_type(self, logger_with_events):
"""Test filtering by event type."""
events = await logger_with_events.query(
event_types=[AuditEventType.ACTION_REQUESTED]
)
assert len(events) == 1
assert events[0].event_type == AuditEventType.ACTION_REQUESTED
@pytest.mark.asyncio
async def test_query_by_agent_id(self, logger_with_events):
"""Test filtering by agent ID."""
events = await logger_with_events.query(agent_id="agent-1")
assert len(events) == 3
assert all(e.agent_id == "agent-1" for e in events)
@pytest.mark.asyncio
async def test_query_by_project_id(self, logger_with_events):
"""Test filtering by project ID."""
events = await logger_with_events.query(project_id="proj-2")
assert len(events) == 1
@pytest.mark.asyncio
async def test_query_by_user_id(self, logger_with_events):
"""Test filtering by user ID."""
events = await logger_with_events.query(user_id="user-1")
assert len(events) == 1
assert events[0].event_type == AuditEventType.BUDGET_WARNING
@pytest.mark.asyncio
async def test_query_with_limit(self, logger_with_events):
"""Test query with limit."""
events = await logger_with_events.query(limit=2)
assert len(events) == 2
@pytest.mark.asyncio
async def test_query_with_offset(self, logger_with_events):
"""Test query with offset."""
all_events = await logger_with_events.query()
offset_events = await logger_with_events.query(offset=2)
assert len(offset_events) == 2
assert offset_events[0] == all_events[2]
@pytest.mark.asyncio
async def test_query_by_time_range(self):
"""Test filtering by time range."""
logger = AuditLogger(enable_hash_chain=False)
now = datetime.utcnow()
await logger.log(AuditEventType.ACTION_REQUESTED)
# Query with start time
events = await logger.query(
start_time=now - timedelta(seconds=1),
end_time=now + timedelta(seconds=1),
)
assert len(events) == 1
@pytest.mark.asyncio
async def test_query_by_correlation_id(self):
"""Test filtering by correlation ID."""
logger = AuditLogger(enable_hash_chain=False)
await logger.log(
AuditEventType.ACTION_REQUESTED,
correlation_id="corr-123",
)
await logger.log(
AuditEventType.ACTION_EXECUTED,
correlation_id="corr-456",
)
events = await logger.query(correlation_id="corr-123")
assert len(events) == 1
assert events[0].correlation_id == "corr-123"
@pytest.mark.asyncio
async def test_query_combined_filters(self, logger_with_events):
"""Test combined filters."""
events = await logger_with_events.query(
agent_id="agent-1",
project_id="proj-1",
event_types=[
AuditEventType.ACTION_REQUESTED,
AuditEventType.ACTION_EXECUTED,
],
)
assert len(events) == 2
@pytest.mark.asyncio
async def test_get_action_history(self, logger_with_events):
"""Test get_action_history method."""
events = await logger_with_events.get_action_history("agent-1")
# Should only return action-related events
assert len(events) == 2
assert all(
e.event_type
in {AuditEventType.ACTION_REQUESTED, AuditEventType.ACTION_EXECUTED}
for e in events
)
class TestAuditLoggerIntegrity:
"""Tests for hash chain integrity verification."""
@pytest.mark.asyncio
async def test_verify_integrity_valid(self):
"""Test integrity verification with valid chain."""
logger = AuditLogger(enable_hash_chain=True)
await logger.log(AuditEventType.ACTION_REQUESTED)
await logger.log(AuditEventType.ACTION_EXECUTED)
is_valid, issues = await logger.verify_integrity()
assert is_valid is True
assert len(issues) == 0
@pytest.mark.asyncio
async def test_verify_integrity_disabled(self):
"""Test integrity verification when hash chain disabled."""
logger = AuditLogger(enable_hash_chain=False)
await logger.log(AuditEventType.ACTION_REQUESTED)
is_valid, issues = await logger.verify_integrity()
assert is_valid is True
assert len(issues) == 0
@pytest.mark.asyncio
async def test_verify_integrity_broken_chain(self):
"""Test integrity verification with broken chain."""
logger = AuditLogger(enable_hash_chain=True)
event1 = await logger.log(AuditEventType.ACTION_REQUESTED)
await logger.log(AuditEventType.ACTION_EXECUTED)
# Tamper with first event's hash
event1.details["_hash"] = "tampered_hash"
is_valid, issues = await logger.verify_integrity()
assert is_valid is False
assert len(issues) > 0
class TestAuditLoggerHandlers:
"""Tests for event handler management."""
@pytest.mark.asyncio
async def test_add_sync_handler(self):
"""Test adding synchronous handler."""
logger = AuditLogger(enable_hash_chain=False)
events_received = []
def handler(event):
events_received.append(event)
logger.add_handler(handler)
await logger.log(AuditEventType.ACTION_REQUESTED)
assert len(events_received) == 1
@pytest.mark.asyncio
async def test_add_async_handler(self):
"""Test adding async handler."""
logger = AuditLogger(enable_hash_chain=False)
events_received = []
async def handler(event):
events_received.append(event)
logger.add_handler(handler)
await logger.log(AuditEventType.ACTION_REQUESTED)
assert len(events_received) == 1
@pytest.mark.asyncio
async def test_remove_handler(self):
"""Test removing handler."""
logger = AuditLogger(enable_hash_chain=False)
events_received = []
def handler(event):
events_received.append(event)
logger.add_handler(handler)
await logger.log(AuditEventType.ACTION_REQUESTED)
logger.remove_handler(handler)
await logger.log(AuditEventType.ACTION_EXECUTED)
assert len(events_received) == 1
@pytest.mark.asyncio
async def test_handler_error_caught(self):
"""Test that handler errors are caught."""
logger = AuditLogger(enable_hash_chain=False)
def failing_handler(event):
raise ValueError("Handler error")
logger.add_handler(failing_handler)
# Should not raise
event = await logger.log(AuditEventType.ACTION_REQUESTED)
assert event is not None
class TestAuditLoggerSanitization:
"""Tests for sensitive data sanitization."""
@pytest.mark.asyncio
async def test_sanitize_sensitive_keys(self):
"""Test sanitization of sensitive keys."""
with patch("app.services.safety.audit.logger.get_safety_config") as mock_config:
mock_cfg = MagicMock()
mock_cfg.audit_retention_days = 30
mock_cfg.audit_include_sensitive = False
mock_config.return_value = mock_cfg
logger = AuditLogger(enable_hash_chain=False)
event = await logger.log(
AuditEventType.ACTION_EXECUTED,
details={
"password": "secret123",
"api_key": "key123",
"token": "token123",
"normal_field": "visible",
},
)
assert event.details["password"] == "[REDACTED]"
assert event.details["api_key"] == "[REDACTED]"
assert event.details["token"] == "[REDACTED]"
assert event.details["normal_field"] == "visible"
@pytest.mark.asyncio
async def test_sanitize_nested_dict(self):
"""Test sanitization of nested dictionaries."""
with patch("app.services.safety.audit.logger.get_safety_config") as mock_config:
mock_cfg = MagicMock()
mock_cfg.audit_retention_days = 30
mock_cfg.audit_include_sensitive = False
mock_config.return_value = mock_cfg
logger = AuditLogger(enable_hash_chain=False)
event = await logger.log(
AuditEventType.ACTION_EXECUTED,
details={
"config": {
"api_secret": "secret",
"name": "test",
}
},
)
assert event.details["config"]["api_secret"] == "[REDACTED]"
assert event.details["config"]["name"] == "test"
@pytest.mark.asyncio
async def test_include_sensitive_when_enabled(self):
"""Test sensitive data included when enabled."""
with patch("app.services.safety.audit.logger.get_safety_config") as mock_config:
mock_cfg = MagicMock()
mock_cfg.audit_retention_days = 30
mock_cfg.audit_include_sensitive = True
mock_config.return_value = mock_cfg
logger = AuditLogger(enable_hash_chain=False)
event = await logger.log(
AuditEventType.ACTION_EXECUTED,
details={"password": "secret123"},
)
assert event.details["password"] == "secret123"
class TestAuditLoggerRetention:
"""Tests for retention policy enforcement."""
@pytest.mark.asyncio
async def test_retention_removes_old_events(self):
"""Test that retention removes old events."""
with patch("app.services.safety.audit.logger.get_safety_config") as mock_config:
mock_cfg = MagicMock()
mock_cfg.audit_retention_days = 7
mock_cfg.audit_include_sensitive = False
mock_config.return_value = mock_cfg
logger = AuditLogger(enable_hash_chain=False)
# Add an old event directly to persisted
from app.services.safety.models import AuditEvent
old_event = AuditEvent(
id="old-event",
event_type=AuditEventType.ACTION_REQUESTED,
timestamp=datetime.utcnow() - timedelta(days=10),
details={},
)
logger._persisted.append(old_event)
# Add a recent event
await logger.log(AuditEventType.ACTION_EXECUTED)
# Flush will trigger retention enforcement
await logger.flush()
# Old event should be removed
assert len(logger._persisted) == 1
assert logger._persisted[0].id != "old-event"
@pytest.mark.asyncio
async def test_retention_keeps_recent_events(self):
"""Test that retention keeps recent events."""
with patch("app.services.safety.audit.logger.get_safety_config") as mock_config:
mock_cfg = MagicMock()
mock_cfg.audit_retention_days = 7
mock_cfg.audit_include_sensitive = False
mock_config.return_value = mock_cfg
logger = AuditLogger(enable_hash_chain=False)
await logger.log(AuditEventType.ACTION_REQUESTED)
await logger.log(AuditEventType.ACTION_EXECUTED)
await logger.flush()
assert len(logger._persisted) == 2
class TestAuditLoggerSingleton:
"""Tests for singleton pattern."""
@pytest.mark.asyncio
async def test_get_audit_logger_creates_instance(self):
"""Test get_audit_logger creates singleton."""
reset_audit_logger()
logger1 = await get_audit_logger()
logger2 = await get_audit_logger()
assert logger1 is logger2
await shutdown_audit_logger()
@pytest.mark.asyncio
async def test_shutdown_audit_logger(self):
"""Test shutdown_audit_logger stops and clears singleton."""
import app.services.safety.audit.logger as audit_module
reset_audit_logger()
_logger = await get_audit_logger()
await shutdown_audit_logger()
assert audit_module._audit_logger is None
def test_reset_audit_logger(self):
"""Test reset_audit_logger clears singleton."""
import app.services.safety.audit.logger as audit_module
audit_module._audit_logger = AuditLogger()
reset_audit_logger()
assert audit_module._audit_logger is None
class TestAuditLoggerPeriodicFlush:
"""Tests for periodic flush background task."""
@pytest.mark.asyncio
async def test_periodic_flush_runs(self):
"""Test periodic flush runs and flushes events."""
logger = AuditLogger(flush_interval_seconds=0.1, enable_hash_chain=False)
await logger.start()
# Log an event
await logger.log(AuditEventType.ACTION_REQUESTED)
assert len(logger._buffer) == 1
# Wait for periodic flush
await asyncio.sleep(0.15)
# Event should be flushed
assert len(logger._buffer) == 0
assert len(logger._persisted) == 1
await logger.stop()
@pytest.mark.asyncio
async def test_periodic_flush_handles_errors(self):
"""Test periodic flush handles errors gracefully."""
logger = AuditLogger(flush_interval_seconds=0.1)
await logger.start()
# Mock flush to raise an error
original_flush = logger.flush
async def failing_flush():
raise Exception("Flush error")
logger.flush = failing_flush
# Wait for flush attempt
await asyncio.sleep(0.15)
# Should still be running
assert logger._running is True
logger.flush = original_flush
await logger.stop()
class TestAuditLoggerLogging:
"""Tests for standard logger output."""
@pytest.mark.asyncio
async def test_log_warning_for_denied(self):
"""Test warning level for denied events."""
with patch("app.services.safety.audit.logger.logger") as mock_logger:
audit_logger = AuditLogger(enable_hash_chain=False)
await audit_logger.log(
AuditEventType.ACTION_DENIED,
agent_id="agent-1",
)
mock_logger.warning.assert_called()
@pytest.mark.asyncio
async def test_log_error_for_failed(self):
"""Test error level for failed events."""
with patch("app.services.safety.audit.logger.logger") as mock_logger:
audit_logger = AuditLogger(enable_hash_chain=False)
await audit_logger.log(
AuditEventType.ACTION_FAILED,
agent_id="agent-1",
)
mock_logger.error.assert_called()
@pytest.mark.asyncio
async def test_log_info_for_normal(self):
"""Test info level for normal events."""
with patch("app.services.safety.audit.logger.logger") as mock_logger:
audit_logger = AuditLogger(enable_hash_chain=False)
await audit_logger.log(
AuditEventType.ACTION_EXECUTED,
agent_id="agent-1",
)
mock_logger.info.assert_called()
class TestAuditLoggerEdgeCases:
"""Tests for edge cases."""
@pytest.mark.asyncio
async def test_log_with_none_details(self):
"""Test logging with None details."""
logger = AuditLogger(enable_hash_chain=False)
event = await logger.log(
AuditEventType.ACTION_REQUESTED,
details=None,
)
assert event.details == {}
@pytest.mark.asyncio
async def test_query_with_action_id(self):
"""Test querying by action ID."""
logger = AuditLogger(enable_hash_chain=False)
await logger.log(
AuditEventType.ACTION_REQUESTED,
action_id="action-1",
)
await logger.log(
AuditEventType.ACTION_EXECUTED,
action_id="action-2",
)
events = await logger.query(action_id="action-1")
assert len(events) == 1
assert events[0].action_id == "action-1"
@pytest.mark.asyncio
async def test_query_with_session_id(self):
"""Test querying by session ID."""
logger = AuditLogger(enable_hash_chain=False)
await logger.log(
AuditEventType.ACTION_REQUESTED,
session_id="sess-1",
)
await logger.log(
AuditEventType.ACTION_EXECUTED,
session_id="sess-2",
)
events = await logger.query(session_id="sess-1")
assert len(events) == 1
@pytest.mark.asyncio
async def test_query_includes_buffer_and_persisted(self):
"""Test query includes both buffer and persisted events."""
logger = AuditLogger(enable_hash_chain=False)
# Add event to buffer
await logger.log(AuditEventType.ACTION_REQUESTED)
# Flush to persisted
await logger.flush()
# Add another to buffer
await logger.log(AuditEventType.ACTION_EXECUTED)
# Query should return both
events = await logger.query()
assert len(events) == 2
@pytest.mark.asyncio
async def test_remove_nonexistent_handler(self):
"""Test removing handler that doesn't exist."""
logger = AuditLogger()
def handler(event):
pass
# Should not raise
logger.remove_handler(handler)
@pytest.mark.asyncio
async def test_query_time_filter_excludes_events(self):
"""Test time filters exclude events correctly."""
logger = AuditLogger(enable_hash_chain=False)
await logger.log(AuditEventType.ACTION_REQUESTED)
# Query with future start time
future = datetime.utcnow() + timedelta(hours=1)
events = await logger.query(start_time=future)
assert len(events) == 0
@pytest.mark.asyncio
async def test_query_end_time_filter(self):
"""Test end time filter."""
logger = AuditLogger(enable_hash_chain=False)
await logger.log(AuditEventType.ACTION_REQUESTED)
# Query with past end time
past = datetime.utcnow() - timedelta(hours=1)
events = await logger.query(end_time=past)
assert len(events) == 0

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"""
Tests for MCP Safety Integration.
Tests cover:
- MCPToolCall and MCPToolResult data structures
- MCPSafetyWrapper: tool registration, execution, safety checks
- Tool classification and action type mapping
- SafeToolExecutor context manager
- Factory function create_mcp_wrapper
"""
from datetime import datetime, timedelta
from unittest.mock import AsyncMock, MagicMock, patch
import pytest
import pytest_asyncio
from app.services.safety.exceptions import EmergencyStopError
from app.services.safety.mcp.integration import (
MCPSafetyWrapper,
MCPToolCall,
MCPToolResult,
SafeToolExecutor,
create_mcp_wrapper,
)
from app.services.safety.models import (
ActionType,
AutonomyLevel,
SafetyDecision,
)
class TestMCPToolCall:
"""Tests for MCPToolCall dataclass."""
def test_tool_call_creation(self):
"""Test creating a tool call."""
call = MCPToolCall(
tool_name="file_read",
arguments={"path": "/tmp/test.txt"}, # noqa: S108
server_name="file-server",
project_id="proj-1",
context={"session_id": "sess-1"},
)
assert call.tool_name == "file_read"
assert call.arguments == {"path": "/tmp/test.txt"} # noqa: S108
assert call.server_name == "file-server"
assert call.project_id == "proj-1"
assert call.context == {"session_id": "sess-1"}
def test_tool_call_defaults(self):
"""Test tool call default values."""
call = MCPToolCall(
tool_name="test",
arguments={},
)
assert call.server_name is None
assert call.project_id is None
assert call.context == {}
class TestMCPToolResult:
"""Tests for MCPToolResult dataclass."""
def test_tool_result_success(self):
"""Test creating a successful result."""
result = MCPToolResult(
success=True,
result={"data": "test"},
safety_decision=SafetyDecision.ALLOW,
execution_time_ms=50.0,
)
assert result.success is True
assert result.result == {"data": "test"}
assert result.error is None
assert result.safety_decision == SafetyDecision.ALLOW
assert result.execution_time_ms == 50.0
def test_tool_result_failure(self):
"""Test creating a failed result."""
result = MCPToolResult(
success=False,
error="Permission denied",
safety_decision=SafetyDecision.DENY,
)
assert result.success is False
assert result.error == "Permission denied"
assert result.result is None
def test_tool_result_with_ids(self):
"""Test result with approval and checkpoint IDs."""
result = MCPToolResult(
success=True,
approval_id="approval-123",
checkpoint_id="checkpoint-456",
)
assert result.approval_id == "approval-123"
assert result.checkpoint_id == "checkpoint-456"
def test_tool_result_defaults(self):
"""Test result default values."""
result = MCPToolResult(success=True)
assert result.result is None
assert result.error is None
assert result.safety_decision == SafetyDecision.ALLOW
assert result.execution_time_ms == 0.0
assert result.approval_id is None
assert result.checkpoint_id is None
assert result.metadata == {}
class TestMCPSafetyWrapperClassification:
"""Tests for tool classification."""
def test_classify_file_read(self):
"""Test classifying file read tools."""
wrapper = MCPSafetyWrapper()
assert wrapper._classify_tool("file_read") == ActionType.FILE_READ
assert wrapper._classify_tool("get_file") == ActionType.FILE_READ
assert wrapper._classify_tool("list_files") == ActionType.FILE_READ
assert wrapper._classify_tool("search_file") == ActionType.FILE_READ
def test_classify_file_write(self):
"""Test classifying file write tools."""
wrapper = MCPSafetyWrapper()
assert wrapper._classify_tool("file_write") == ActionType.FILE_WRITE
assert wrapper._classify_tool("create_file") == ActionType.FILE_WRITE
assert wrapper._classify_tool("update_file") == ActionType.FILE_WRITE
def test_classify_file_delete(self):
"""Test classifying file delete tools."""
wrapper = MCPSafetyWrapper()
assert wrapper._classify_tool("file_delete") == ActionType.FILE_DELETE
assert wrapper._classify_tool("remove_file") == ActionType.FILE_DELETE
def test_classify_database_read(self):
"""Test classifying database read tools."""
wrapper = MCPSafetyWrapper()
assert wrapper._classify_tool("database_query") == ActionType.DATABASE_QUERY
assert wrapper._classify_tool("db_read") == ActionType.DATABASE_QUERY
assert wrapper._classify_tool("query_database") == ActionType.DATABASE_QUERY
def test_classify_database_mutate(self):
"""Test classifying database mutate tools."""
wrapper = MCPSafetyWrapper()
assert wrapper._classify_tool("database_write") == ActionType.DATABASE_MUTATE
assert wrapper._classify_tool("db_update") == ActionType.DATABASE_MUTATE
assert wrapper._classify_tool("database_delete") == ActionType.DATABASE_MUTATE
def test_classify_shell_command(self):
"""Test classifying shell command tools."""
wrapper = MCPSafetyWrapper()
assert wrapper._classify_tool("shell_execute") == ActionType.SHELL_COMMAND
assert wrapper._classify_tool("exec_command") == ActionType.SHELL_COMMAND
assert wrapper._classify_tool("bash_run") == ActionType.SHELL_COMMAND
def test_classify_git_operation(self):
"""Test classifying git tools."""
wrapper = MCPSafetyWrapper()
assert wrapper._classify_tool("git_commit") == ActionType.GIT_OPERATION
assert wrapper._classify_tool("git_push") == ActionType.GIT_OPERATION
assert wrapper._classify_tool("git_status") == ActionType.GIT_OPERATION
def test_classify_network_request(self):
"""Test classifying network tools."""
wrapper = MCPSafetyWrapper()
assert wrapper._classify_tool("http_get") == ActionType.NETWORK_REQUEST
assert wrapper._classify_tool("fetch_url") == ActionType.NETWORK_REQUEST
assert wrapper._classify_tool("api_request") == ActionType.NETWORK_REQUEST
def test_classify_llm_call(self):
"""Test classifying LLM tools."""
wrapper = MCPSafetyWrapper()
assert wrapper._classify_tool("llm_generate") == ActionType.LLM_CALL
assert wrapper._classify_tool("ai_complete") == ActionType.LLM_CALL
assert wrapper._classify_tool("claude_chat") == ActionType.LLM_CALL
def test_classify_default(self):
"""Test default classification for unknown tools."""
wrapper = MCPSafetyWrapper()
assert wrapper._classify_tool("unknown_tool") == ActionType.TOOL_CALL
assert wrapper._classify_tool("custom_action") == ActionType.TOOL_CALL
class TestMCPSafetyWrapperToolHandlers:
"""Tests for tool handler registration."""
def test_register_tool_handler(self):
"""Test registering a tool handler."""
wrapper = MCPSafetyWrapper()
def handler(path: str) -> str:
return f"Read: {path}"
wrapper.register_tool_handler("file_read", handler)
assert "file_read" in wrapper._tool_handlers
assert wrapper._tool_handlers["file_read"] is handler
def test_register_multiple_handlers(self):
"""Test registering multiple handlers."""
wrapper = MCPSafetyWrapper()
wrapper.register_tool_handler("tool1", lambda: None)
wrapper.register_tool_handler("tool2", lambda: None)
wrapper.register_tool_handler("tool3", lambda: None)
assert len(wrapper._tool_handlers) == 3
def test_overwrite_handler(self):
"""Test overwriting a handler."""
wrapper = MCPSafetyWrapper()
handler1 = lambda: "first" # noqa: E731
handler2 = lambda: "second" # noqa: E731
wrapper.register_tool_handler("tool", handler1)
wrapper.register_tool_handler("tool", handler2)
assert wrapper._tool_handlers["tool"] is handler2
class TestMCPSafetyWrapperExecution:
"""Tests for tool execution."""
@pytest_asyncio.fixture
async def mock_guardian(self):
"""Create a mock SafetyGuardian."""
guardian = AsyncMock()
guardian.validate = AsyncMock()
return guardian
@pytest_asyncio.fixture
async def mock_emergency(self):
"""Create a mock EmergencyControls."""
emergency = AsyncMock()
emergency.check_allowed = AsyncMock()
return emergency
@pytest.mark.asyncio
async def test_execute_allowed(self, mock_guardian, mock_emergency):
"""Test executing an allowed tool call."""
mock_guardian.validate.return_value = MagicMock(
decision=SafetyDecision.ALLOW,
reasons=[],
approval_id=None,
checkpoint_id=None,
)
wrapper = MCPSafetyWrapper(
guardian=mock_guardian,
emergency_controls=mock_emergency,
)
async def handler(path: str) -> dict:
return {"content": f"Data from {path}"}
wrapper.register_tool_handler("file_read", handler)
call = MCPToolCall(
tool_name="file_read",
arguments={"path": "/test.txt"},
project_id="proj-1",
)
result = await wrapper.execute(call, "agent-1")
assert result.success is True
assert result.result == {"content": "Data from /test.txt"}
assert result.safety_decision == SafetyDecision.ALLOW
@pytest.mark.asyncio
async def test_execute_denied(self, mock_guardian, mock_emergency):
"""Test executing a denied tool call."""
mock_guardian.validate.return_value = MagicMock(
decision=SafetyDecision.DENY,
reasons=["Permission denied", "Rate limit exceeded"],
)
wrapper = MCPSafetyWrapper(
guardian=mock_guardian,
emergency_controls=mock_emergency,
)
call = MCPToolCall(
tool_name="file_write",
arguments={"path": "/etc/passwd"},
)
result = await wrapper.execute(call, "agent-1")
assert result.success is False
assert "Permission denied" in result.error
assert "Rate limit exceeded" in result.error
assert result.safety_decision == SafetyDecision.DENY
@pytest.mark.asyncio
async def test_execute_requires_approval(self, mock_guardian, mock_emergency):
"""Test executing a tool that requires approval."""
mock_guardian.validate.return_value = MagicMock(
decision=SafetyDecision.REQUIRE_APPROVAL,
reasons=["Destructive operation requires approval"],
approval_id="approval-123",
)
wrapper = MCPSafetyWrapper(
guardian=mock_guardian,
emergency_controls=mock_emergency,
)
call = MCPToolCall(
tool_name="file_delete",
arguments={"path": "/important.txt"},
)
result = await wrapper.execute(call, "agent-1")
assert result.success is False
assert result.safety_decision == SafetyDecision.REQUIRE_APPROVAL
assert result.approval_id == "approval-123"
assert "requires human approval" in result.error
@pytest.mark.asyncio
async def test_execute_emergency_stop(self, mock_guardian, mock_emergency):
"""Test execution blocked by emergency stop."""
mock_emergency.check_allowed.side_effect = EmergencyStopError(
"Emergency stop active"
)
wrapper = MCPSafetyWrapper(
guardian=mock_guardian,
emergency_controls=mock_emergency,
)
call = MCPToolCall(
tool_name="file_write",
arguments={"path": "/test.txt"},
project_id="proj-1",
)
result = await wrapper.execute(call, "agent-1")
assert result.success is False
assert result.safety_decision == SafetyDecision.DENY
assert result.metadata.get("emergency_stop") is True
@pytest.mark.asyncio
async def test_execute_bypass_safety(self, mock_guardian, mock_emergency):
"""Test executing with safety bypass."""
wrapper = MCPSafetyWrapper(
guardian=mock_guardian,
emergency_controls=mock_emergency,
)
async def handler(data: str) -> str:
return f"Processed: {data}"
wrapper.register_tool_handler("custom_tool", handler)
call = MCPToolCall(
tool_name="custom_tool",
arguments={"data": "test"},
)
result = await wrapper.execute(call, "agent-1", bypass_safety=True)
assert result.success is True
assert result.result == "Processed: test"
# Guardian should not be called when bypassing
mock_guardian.validate.assert_not_called()
@pytest.mark.asyncio
async def test_execute_no_handler(self, mock_guardian, mock_emergency):
"""Test executing a tool with no registered handler."""
mock_guardian.validate.return_value = MagicMock(
decision=SafetyDecision.ALLOW,
reasons=[],
approval_id=None,
checkpoint_id=None,
)
wrapper = MCPSafetyWrapper(
guardian=mock_guardian,
emergency_controls=mock_emergency,
)
call = MCPToolCall(
tool_name="unregistered_tool",
arguments={},
)
result = await wrapper.execute(call, "agent-1")
assert result.success is False
assert "No handler registered" in result.error
@pytest.mark.asyncio
async def test_execute_handler_exception(self, mock_guardian, mock_emergency):
"""Test handling exceptions from tool handler."""
mock_guardian.validate.return_value = MagicMock(
decision=SafetyDecision.ALLOW,
reasons=[],
approval_id=None,
checkpoint_id=None,
)
wrapper = MCPSafetyWrapper(
guardian=mock_guardian,
emergency_controls=mock_emergency,
)
async def failing_handler() -> None:
raise ValueError("Handler failed!")
wrapper.register_tool_handler("failing_tool", failing_handler)
call = MCPToolCall(
tool_name="failing_tool",
arguments={},
)
result = await wrapper.execute(call, "agent-1")
assert result.success is False
assert "Handler failed!" in result.error
# Decision is still ALLOW because the safety check passed
assert result.safety_decision == SafetyDecision.ALLOW
@pytest.mark.asyncio
async def test_execute_sync_handler(self, mock_guardian, mock_emergency):
"""Test executing a synchronous handler."""
mock_guardian.validate.return_value = MagicMock(
decision=SafetyDecision.ALLOW,
reasons=[],
approval_id=None,
checkpoint_id=None,
)
wrapper = MCPSafetyWrapper(
guardian=mock_guardian,
emergency_controls=mock_emergency,
)
def sync_handler(value: int) -> int:
return value * 2
wrapper.register_tool_handler("sync_tool", sync_handler)
call = MCPToolCall(
tool_name="sync_tool",
arguments={"value": 21},
)
result = await wrapper.execute(call, "agent-1")
assert result.success is True
assert result.result == 42
class TestBuildActionRequest:
"""Tests for _build_action_request."""
def test_build_action_request_basic(self):
"""Test building a basic action request."""
wrapper = MCPSafetyWrapper()
call = MCPToolCall(
tool_name="file_read",
arguments={"path": "/test.txt"},
project_id="proj-1",
)
action = wrapper._build_action_request(call, "agent-1", AutonomyLevel.MILESTONE)
assert action.action_type == ActionType.FILE_READ
assert action.tool_name == "file_read"
assert action.arguments == {"path": "/test.txt"}
assert action.resource == "/test.txt"
assert action.metadata.agent_id == "agent-1"
assert action.metadata.project_id == "proj-1"
assert action.metadata.autonomy_level == AutonomyLevel.MILESTONE
def test_build_action_request_with_context(self):
"""Test building action request with session context."""
wrapper = MCPSafetyWrapper()
call = MCPToolCall(
tool_name="database_query",
arguments={"resource": "users", "query": "SELECT *"},
context={"session_id": "sess-123"},
project_id="proj-2",
)
action = wrapper._build_action_request(
call, "agent-2", AutonomyLevel.AUTONOMOUS
)
assert action.resource == "users"
assert action.metadata.session_id == "sess-123"
assert action.metadata.autonomy_level == AutonomyLevel.AUTONOMOUS
def test_build_action_request_no_resource(self):
"""Test building action request without resource."""
wrapper = MCPSafetyWrapper()
call = MCPToolCall(
tool_name="llm_generate",
arguments={"prompt": "Hello"},
)
action = wrapper._build_action_request(
call, "agent-1", AutonomyLevel.FULL_CONTROL
)
assert action.resource is None
class TestElapsedTime:
"""Tests for _elapsed_ms helper."""
def test_elapsed_ms(self):
"""Test calculating elapsed time."""
wrapper = MCPSafetyWrapper()
start = datetime.utcnow() - timedelta(milliseconds=100)
elapsed = wrapper._elapsed_ms(start)
# Should be at least 100ms, but allow some tolerance
assert elapsed >= 99
assert elapsed < 200
class TestSafeToolExecutor:
"""Tests for SafeToolExecutor context manager."""
@pytest.mark.asyncio
async def test_executor_execute(self):
"""Test executing within context manager."""
mock_guardian = AsyncMock()
mock_guardian.validate.return_value = MagicMock(
decision=SafetyDecision.ALLOW,
reasons=[],
approval_id=None,
checkpoint_id=None,
)
mock_emergency = AsyncMock()
wrapper = MCPSafetyWrapper(
guardian=mock_guardian,
emergency_controls=mock_emergency,
)
async def handler() -> str:
return "success"
wrapper.register_tool_handler("test_tool", handler)
call = MCPToolCall(tool_name="test_tool", arguments={})
async with SafeToolExecutor(wrapper, call, "agent-1") as executor:
result = await executor.execute()
assert result.success is True
assert result.result == "success"
@pytest.mark.asyncio
async def test_executor_result_property(self):
"""Test accessing result via property."""
mock_guardian = AsyncMock()
mock_guardian.validate.return_value = MagicMock(
decision=SafetyDecision.ALLOW,
reasons=[],
approval_id=None,
checkpoint_id=None,
)
mock_emergency = AsyncMock()
wrapper = MCPSafetyWrapper(
guardian=mock_guardian,
emergency_controls=mock_emergency,
)
wrapper.register_tool_handler("tool", lambda: "data")
call = MCPToolCall(tool_name="tool", arguments={})
executor = SafeToolExecutor(wrapper, call, "agent-1")
# Before execution
assert executor.result is None
async with executor:
await executor.execute()
# After execution
assert executor.result is not None
assert executor.result.success is True
@pytest.mark.asyncio
async def test_executor_with_autonomy_level(self):
"""Test executor with custom autonomy level."""
mock_guardian = AsyncMock()
mock_guardian.validate.return_value = MagicMock(
decision=SafetyDecision.ALLOW,
reasons=[],
approval_id=None,
checkpoint_id=None,
)
mock_emergency = AsyncMock()
wrapper = MCPSafetyWrapper(
guardian=mock_guardian,
emergency_controls=mock_emergency,
)
wrapper.register_tool_handler("tool", lambda: None)
call = MCPToolCall(tool_name="tool", arguments={})
async with SafeToolExecutor(
wrapper, call, "agent-1", AutonomyLevel.AUTONOMOUS
) as executor:
await executor.execute()
# Check that guardian was called with correct autonomy level
mock_guardian.validate.assert_called_once()
action = mock_guardian.validate.call_args[0][0]
assert action.metadata.autonomy_level == AutonomyLevel.AUTONOMOUS
class TestCreateMCPWrapper:
"""Tests for create_mcp_wrapper factory function."""
@pytest.mark.asyncio
async def test_create_wrapper_with_guardian(self):
"""Test creating wrapper with provided guardian."""
mock_guardian = AsyncMock()
with patch(
"app.services.safety.mcp.integration.get_emergency_controls"
) as mock_get_emergency:
mock_get_emergency.return_value = AsyncMock()
wrapper = await create_mcp_wrapper(guardian=mock_guardian)
assert wrapper._guardian is mock_guardian
@pytest.mark.asyncio
async def test_create_wrapper_default_guardian(self):
"""Test creating wrapper with default guardian."""
with (
patch(
"app.services.safety.mcp.integration.get_safety_guardian"
) as mock_get_guardian,
patch(
"app.services.safety.mcp.integration.get_emergency_controls"
) as mock_get_emergency,
):
mock_guardian = AsyncMock()
mock_get_guardian.return_value = mock_guardian
mock_get_emergency.return_value = AsyncMock()
wrapper = await create_mcp_wrapper()
assert wrapper._guardian is mock_guardian
mock_get_guardian.assert_called_once()
class TestLazyGetters:
"""Tests for lazy getter methods."""
@pytest.mark.asyncio
async def test_get_guardian_lazy(self):
"""Test lazy guardian initialization."""
wrapper = MCPSafetyWrapper()
with patch(
"app.services.safety.mcp.integration.get_safety_guardian"
) as mock_get:
mock_guardian = AsyncMock()
mock_get.return_value = mock_guardian
guardian = await wrapper._get_guardian()
assert guardian is mock_guardian
mock_get.assert_called_once()
@pytest.mark.asyncio
async def test_get_guardian_cached(self):
"""Test guardian is cached after first access."""
mock_guardian = AsyncMock()
wrapper = MCPSafetyWrapper(guardian=mock_guardian)
guardian = await wrapper._get_guardian()
assert guardian is mock_guardian
@pytest.mark.asyncio
async def test_get_emergency_controls_lazy(self):
"""Test lazy emergency controls initialization."""
wrapper = MCPSafetyWrapper()
with patch(
"app.services.safety.mcp.integration.get_emergency_controls"
) as mock_get:
mock_emergency = AsyncMock()
mock_get.return_value = mock_emergency
emergency = await wrapper._get_emergency_controls()
assert emergency is mock_emergency
mock_get.assert_called_once()
@pytest.mark.asyncio
async def test_get_emergency_controls_cached(self):
"""Test emergency controls is cached after first access."""
mock_emergency = AsyncMock()
wrapper = MCPSafetyWrapper(emergency_controls=mock_emergency)
emergency = await wrapper._get_emergency_controls()
assert emergency is mock_emergency
class TestEdgeCases:
"""Tests for edge cases and error handling."""
@pytest.mark.asyncio
async def test_execute_with_safety_error(self):
"""Test handling SafetyError from guardian."""
from app.services.safety.exceptions import SafetyError
mock_guardian = AsyncMock()
mock_guardian.validate.side_effect = SafetyError("Internal safety error")
mock_emergency = AsyncMock()
wrapper = MCPSafetyWrapper(
guardian=mock_guardian,
emergency_controls=mock_emergency,
)
call = MCPToolCall(tool_name="test", arguments={})
result = await wrapper.execute(call, "agent-1")
assert result.success is False
assert "Internal safety error" in result.error
assert result.safety_decision == SafetyDecision.DENY
@pytest.mark.asyncio
async def test_execute_with_checkpoint_id(self):
"""Test that checkpoint_id is propagated to result."""
mock_guardian = AsyncMock()
mock_guardian.validate.return_value = MagicMock(
decision=SafetyDecision.ALLOW,
reasons=[],
approval_id=None,
checkpoint_id="checkpoint-abc",
)
mock_emergency = AsyncMock()
wrapper = MCPSafetyWrapper(
guardian=mock_guardian,
emergency_controls=mock_emergency,
)
wrapper.register_tool_handler("tool", lambda: "result")
call = MCPToolCall(tool_name="tool", arguments={})
result = await wrapper.execute(call, "agent-1")
assert result.success is True
assert result.checkpoint_id == "checkpoint-abc"
def test_destructive_tools_constant(self):
"""Test DESTRUCTIVE_TOOLS class constant."""
assert "file_write" in MCPSafetyWrapper.DESTRUCTIVE_TOOLS
assert "file_delete" in MCPSafetyWrapper.DESTRUCTIVE_TOOLS
assert "shell_execute" in MCPSafetyWrapper.DESTRUCTIVE_TOOLS
assert "git_push" in MCPSafetyWrapper.DESTRUCTIVE_TOOLS
def test_read_only_tools_constant(self):
"""Test READ_ONLY_TOOLS class constant."""
assert "file_read" in MCPSafetyWrapper.READ_ONLY_TOOLS
assert "database_query" in MCPSafetyWrapper.READ_ONLY_TOOLS
assert "git_status" in MCPSafetyWrapper.READ_ONLY_TOOLS
assert "search" in MCPSafetyWrapper.READ_ONLY_TOOLS
@pytest.mark.asyncio
async def test_scope_with_project_id(self):
"""Test that scope is set correctly with project_id."""
mock_guardian = AsyncMock()
mock_guardian.validate.return_value = MagicMock(
decision=SafetyDecision.ALLOW,
reasons=[],
approval_id=None,
checkpoint_id=None,
)
mock_emergency = AsyncMock()
wrapper = MCPSafetyWrapper(
guardian=mock_guardian,
emergency_controls=mock_emergency,
)
wrapper.register_tool_handler("tool", lambda: None)
call = MCPToolCall(
tool_name="tool",
arguments={},
project_id="proj-123",
)
await wrapper.execute(call, "agent-1")
# Verify emergency check was called with project scope
mock_emergency.check_allowed.assert_called_once()
call_kwargs = mock_emergency.check_allowed.call_args
assert "project:proj-123" in str(call_kwargs)
@pytest.mark.asyncio
async def test_scope_without_project_id(self):
"""Test that scope falls back to agent when no project_id."""
mock_guardian = AsyncMock()
mock_guardian.validate.return_value = MagicMock(
decision=SafetyDecision.ALLOW,
reasons=[],
approval_id=None,
checkpoint_id=None,
)
mock_emergency = AsyncMock()
wrapper = MCPSafetyWrapper(
guardian=mock_guardian,
emergency_controls=mock_emergency,
)
wrapper.register_tool_handler("tool", lambda: None)
call = MCPToolCall(
tool_name="tool",
arguments={},
# No project_id
)
await wrapper.execute(call, "agent-555")
# Verify emergency check was called with agent scope
mock_emergency.check_allowed.assert_called_once()
call_kwargs = mock_emergency.check_allowed.call_args
assert "agent:agent-555" in str(call_kwargs)

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@@ -0,0 +1,747 @@
"""
Tests for Safety Metrics Collector.
Tests cover:
- MetricType, MetricValue, HistogramBucket data structures
- SafetyMetrics counters, gauges, histograms
- Prometheus format export
- Summary and reset operations
- Singleton pattern and convenience functions
"""
import pytest
import pytest_asyncio
from app.services.safety.metrics.collector import (
HistogramBucket,
MetricType,
MetricValue,
SafetyMetrics,
get_safety_metrics,
record_mcp_call,
record_validation,
)
class TestMetricType:
"""Tests for MetricType enum."""
def test_metric_types_exist(self):
"""Test all metric types are defined."""
assert MetricType.COUNTER == "counter"
assert MetricType.GAUGE == "gauge"
assert MetricType.HISTOGRAM == "histogram"
def test_metric_type_is_string(self):
"""Test MetricType values are strings."""
assert isinstance(MetricType.COUNTER.value, str)
assert isinstance(MetricType.GAUGE.value, str)
assert isinstance(MetricType.HISTOGRAM.value, str)
class TestMetricValue:
"""Tests for MetricValue dataclass."""
def test_metric_value_creation(self):
"""Test creating a metric value."""
mv = MetricValue(
name="test_metric",
metric_type=MetricType.COUNTER,
value=42.0,
labels={"env": "test"},
)
assert mv.name == "test_metric"
assert mv.metric_type == MetricType.COUNTER
assert mv.value == 42.0
assert mv.labels == {"env": "test"}
assert mv.timestamp is not None
def test_metric_value_defaults(self):
"""Test metric value default values."""
mv = MetricValue(
name="test",
metric_type=MetricType.GAUGE,
value=0.0,
)
assert mv.labels == {}
assert mv.timestamp is not None
class TestHistogramBucket:
"""Tests for HistogramBucket dataclass."""
def test_histogram_bucket_creation(self):
"""Test creating a histogram bucket."""
bucket = HistogramBucket(le=0.5, count=10)
assert bucket.le == 0.5
assert bucket.count == 10
def test_histogram_bucket_defaults(self):
"""Test histogram bucket default count."""
bucket = HistogramBucket(le=1.0)
assert bucket.le == 1.0
assert bucket.count == 0
def test_histogram_bucket_infinity(self):
"""Test histogram bucket with infinity."""
bucket = HistogramBucket(le=float("inf"))
assert bucket.le == float("inf")
class TestSafetyMetricsCounters:
"""Tests for SafetyMetrics counter methods."""
@pytest_asyncio.fixture
async def metrics(self):
"""Create fresh metrics instance."""
return SafetyMetrics()
@pytest.mark.asyncio
async def test_inc_validations(self, metrics):
"""Test incrementing validations counter."""
await metrics.inc_validations("allow")
await metrics.inc_validations("allow")
await metrics.inc_validations("deny", agent_id="agent-1")
summary = await metrics.get_summary()
assert summary["total_validations"] == 3
assert summary["denied_validations"] == 1
@pytest.mark.asyncio
async def test_inc_approvals_requested(self, metrics):
"""Test incrementing approval requests counter."""
await metrics.inc_approvals_requested("normal")
await metrics.inc_approvals_requested("urgent")
await metrics.inc_approvals_requested() # default
summary = await metrics.get_summary()
assert summary["approval_requests"] == 3
@pytest.mark.asyncio
async def test_inc_approvals_granted(self, metrics):
"""Test incrementing approvals granted counter."""
await metrics.inc_approvals_granted()
await metrics.inc_approvals_granted()
summary = await metrics.get_summary()
assert summary["approvals_granted"] == 2
@pytest.mark.asyncio
async def test_inc_approvals_denied(self, metrics):
"""Test incrementing approvals denied counter."""
await metrics.inc_approvals_denied("timeout")
await metrics.inc_approvals_denied("policy")
await metrics.inc_approvals_denied() # default manual
summary = await metrics.get_summary()
assert summary["approvals_denied"] == 3
@pytest.mark.asyncio
async def test_inc_rate_limit_exceeded(self, metrics):
"""Test incrementing rate limit exceeded counter."""
await metrics.inc_rate_limit_exceeded("requests_per_minute")
await metrics.inc_rate_limit_exceeded("tokens_per_hour")
summary = await metrics.get_summary()
assert summary["rate_limit_hits"] == 2
@pytest.mark.asyncio
async def test_inc_budget_exceeded(self, metrics):
"""Test incrementing budget exceeded counter."""
await metrics.inc_budget_exceeded("daily_cost")
await metrics.inc_budget_exceeded("monthly_tokens")
summary = await metrics.get_summary()
assert summary["budget_exceeded"] == 2
@pytest.mark.asyncio
async def test_inc_loops_detected(self, metrics):
"""Test incrementing loops detected counter."""
await metrics.inc_loops_detected("repetition")
await metrics.inc_loops_detected("pattern")
summary = await metrics.get_summary()
assert summary["loops_detected"] == 2
@pytest.mark.asyncio
async def test_inc_emergency_events(self, metrics):
"""Test incrementing emergency events counter."""
await metrics.inc_emergency_events("pause", "project-1")
await metrics.inc_emergency_events("stop", "agent-2")
summary = await metrics.get_summary()
assert summary["emergency_events"] == 2
@pytest.mark.asyncio
async def test_inc_content_filtered(self, metrics):
"""Test incrementing content filtered counter."""
await metrics.inc_content_filtered("profanity", "blocked")
await metrics.inc_content_filtered("pii", "redacted")
summary = await metrics.get_summary()
assert summary["content_filtered"] == 2
@pytest.mark.asyncio
async def test_inc_checkpoints_created(self, metrics):
"""Test incrementing checkpoints created counter."""
await metrics.inc_checkpoints_created()
await metrics.inc_checkpoints_created()
await metrics.inc_checkpoints_created()
summary = await metrics.get_summary()
assert summary["checkpoints_created"] == 3
@pytest.mark.asyncio
async def test_inc_rollbacks_executed(self, metrics):
"""Test incrementing rollbacks executed counter."""
await metrics.inc_rollbacks_executed(success=True)
await metrics.inc_rollbacks_executed(success=False)
summary = await metrics.get_summary()
assert summary["rollbacks_executed"] == 2
@pytest.mark.asyncio
async def test_inc_mcp_calls(self, metrics):
"""Test incrementing MCP calls counter."""
await metrics.inc_mcp_calls("search_knowledge", success=True)
await metrics.inc_mcp_calls("run_code", success=False)
summary = await metrics.get_summary()
assert summary["mcp_calls"] == 2
class TestSafetyMetricsGauges:
"""Tests for SafetyMetrics gauge methods."""
@pytest_asyncio.fixture
async def metrics(self):
"""Create fresh metrics instance."""
return SafetyMetrics()
@pytest.mark.asyncio
async def test_set_budget_remaining(self, metrics):
"""Test setting budget remaining gauge."""
await metrics.set_budget_remaining("project-1", "daily_cost", 50.0)
all_metrics = await metrics.get_all_metrics()
gauge_metrics = [m for m in all_metrics if m.name == "safety_budget_remaining"]
assert len(gauge_metrics) == 1
assert gauge_metrics[0].value == 50.0
assert gauge_metrics[0].labels["scope"] == "project-1"
assert gauge_metrics[0].labels["budget_type"] == "daily_cost"
@pytest.mark.asyncio
async def test_set_rate_limit_remaining(self, metrics):
"""Test setting rate limit remaining gauge."""
await metrics.set_rate_limit_remaining("agent-1", "requests_per_minute", 45)
all_metrics = await metrics.get_all_metrics()
gauge_metrics = [
m for m in all_metrics if m.name == "safety_rate_limit_remaining"
]
assert len(gauge_metrics) == 1
assert gauge_metrics[0].value == 45.0
@pytest.mark.asyncio
async def test_set_pending_approvals(self, metrics):
"""Test setting pending approvals gauge."""
await metrics.set_pending_approvals(5)
summary = await metrics.get_summary()
assert summary["pending_approvals"] == 5
@pytest.mark.asyncio
async def test_set_active_checkpoints(self, metrics):
"""Test setting active checkpoints gauge."""
await metrics.set_active_checkpoints(3)
summary = await metrics.get_summary()
assert summary["active_checkpoints"] == 3
@pytest.mark.asyncio
async def test_set_emergency_state(self, metrics):
"""Test setting emergency state gauge."""
await metrics.set_emergency_state("project-1", "normal")
await metrics.set_emergency_state("project-2", "paused")
await metrics.set_emergency_state("project-3", "stopped")
await metrics.set_emergency_state("project-4", "unknown")
all_metrics = await metrics.get_all_metrics()
state_metrics = [m for m in all_metrics if m.name == "safety_emergency_state"]
assert len(state_metrics) == 4
# Check state values
values_by_scope = {m.labels["scope"]: m.value for m in state_metrics}
assert values_by_scope["project-1"] == 0.0 # normal
assert values_by_scope["project-2"] == 1.0 # paused
assert values_by_scope["project-3"] == 2.0 # stopped
assert values_by_scope["project-4"] == -1.0 # unknown
class TestSafetyMetricsHistograms:
"""Tests for SafetyMetrics histogram methods."""
@pytest_asyncio.fixture
async def metrics(self):
"""Create fresh metrics instance."""
return SafetyMetrics()
@pytest.mark.asyncio
async def test_observe_validation_latency(self, metrics):
"""Test observing validation latency."""
await metrics.observe_validation_latency(0.05)
await metrics.observe_validation_latency(0.15)
await metrics.observe_validation_latency(0.5)
all_metrics = await metrics.get_all_metrics()
count_metric = next(
(m for m in all_metrics if m.name == "validation_latency_seconds_count"),
None,
)
assert count_metric is not None
assert count_metric.value == 3.0
sum_metric = next(
(m for m in all_metrics if m.name == "validation_latency_seconds_sum"),
None,
)
assert sum_metric is not None
assert abs(sum_metric.value - 0.7) < 0.001
@pytest.mark.asyncio
async def test_observe_approval_latency(self, metrics):
"""Test observing approval latency."""
await metrics.observe_approval_latency(1.5)
await metrics.observe_approval_latency(3.0)
all_metrics = await metrics.get_all_metrics()
count_metric = next(
(m for m in all_metrics if m.name == "approval_latency_seconds_count"),
None,
)
assert count_metric is not None
assert count_metric.value == 2.0
@pytest.mark.asyncio
async def test_observe_mcp_execution_latency(self, metrics):
"""Test observing MCP execution latency."""
await metrics.observe_mcp_execution_latency(0.02)
all_metrics = await metrics.get_all_metrics()
count_metric = next(
(m for m in all_metrics if m.name == "mcp_execution_latency_seconds_count"),
None,
)
assert count_metric is not None
assert count_metric.value == 1.0
@pytest.mark.asyncio
async def test_histogram_bucket_updates(self, metrics):
"""Test that histogram buckets are updated correctly."""
# Add values to test bucket distribution
await metrics.observe_validation_latency(0.005) # <= 0.01
await metrics.observe_validation_latency(0.03) # <= 0.05
await metrics.observe_validation_latency(0.07) # <= 0.1
await metrics.observe_validation_latency(15.0) # <= inf
prometheus = await metrics.get_prometheus_format()
# Check that bucket counts are in output
assert "validation_latency_seconds_bucket" in prometheus
assert "le=" in prometheus
class TestSafetyMetricsExport:
"""Tests for SafetyMetrics export methods."""
@pytest_asyncio.fixture
async def metrics(self):
"""Create fresh metrics instance with some data."""
m = SafetyMetrics()
# Add some counters
await m.inc_validations("allow")
await m.inc_validations("deny", agent_id="agent-1")
# Add some gauges
await m.set_pending_approvals(3)
await m.set_budget_remaining("proj-1", "daily", 100.0)
# Add some histogram values
await m.observe_validation_latency(0.1)
return m
@pytest.mark.asyncio
async def test_get_all_metrics(self, metrics):
"""Test getting all metrics."""
all_metrics = await metrics.get_all_metrics()
assert len(all_metrics) > 0
assert all(isinstance(m, MetricValue) for m in all_metrics)
# Check we have different types
types = {m.metric_type for m in all_metrics}
assert MetricType.COUNTER in types
assert MetricType.GAUGE in types
@pytest.mark.asyncio
async def test_get_prometheus_format(self, metrics):
"""Test Prometheus format export."""
output = await metrics.get_prometheus_format()
assert isinstance(output, str)
assert "# TYPE" in output
assert "counter" in output
assert "gauge" in output
assert "safety_validations_total" in output
assert "safety_pending_approvals" in output
@pytest.mark.asyncio
async def test_prometheus_format_with_labels(self, metrics):
"""Test Prometheus format includes labels correctly."""
output = await metrics.get_prometheus_format()
# Counter with labels
assert "decision=allow" in output or "decision=deny" in output
@pytest.mark.asyncio
async def test_prometheus_format_histogram_buckets(self, metrics):
"""Test Prometheus format includes histogram buckets."""
output = await metrics.get_prometheus_format()
assert "histogram" in output
assert "_bucket" in output
assert "le=" in output
assert "+Inf" in output
@pytest.mark.asyncio
async def test_get_summary(self, metrics):
"""Test getting summary."""
summary = await metrics.get_summary()
assert "total_validations" in summary
assert "denied_validations" in summary
assert "approval_requests" in summary
assert "pending_approvals" in summary
assert "active_checkpoints" in summary
assert summary["total_validations"] == 2
assert summary["denied_validations"] == 1
assert summary["pending_approvals"] == 3
@pytest.mark.asyncio
async def test_summary_empty_counters(self):
"""Test summary with no data."""
metrics = SafetyMetrics()
summary = await metrics.get_summary()
assert summary["total_validations"] == 0
assert summary["denied_validations"] == 0
assert summary["pending_approvals"] == 0
class TestSafetyMetricsReset:
"""Tests for SafetyMetrics reset."""
@pytest.mark.asyncio
async def test_reset_clears_counters(self):
"""Test reset clears all counters."""
metrics = SafetyMetrics()
await metrics.inc_validations("allow")
await metrics.inc_approvals_granted()
await metrics.set_pending_approvals(5)
await metrics.observe_validation_latency(0.1)
await metrics.reset()
summary = await metrics.get_summary()
assert summary["total_validations"] == 0
assert summary["approvals_granted"] == 0
assert summary["pending_approvals"] == 0
@pytest.mark.asyncio
async def test_reset_reinitializes_histogram_buckets(self):
"""Test reset reinitializes histogram buckets."""
metrics = SafetyMetrics()
await metrics.observe_validation_latency(0.1)
await metrics.reset()
# After reset, histogram buckets should be reinitialized
prometheus = await metrics.get_prometheus_format()
assert "validation_latency_seconds" in prometheus
class TestParseLabels:
"""Tests for _parse_labels helper method."""
def test_parse_empty_labels(self):
"""Test parsing empty labels string."""
metrics = SafetyMetrics()
result = metrics._parse_labels("")
assert result == {}
def test_parse_single_label(self):
"""Test parsing single label."""
metrics = SafetyMetrics()
result = metrics._parse_labels("key=value")
assert result == {"key": "value"}
def test_parse_multiple_labels(self):
"""Test parsing multiple labels."""
metrics = SafetyMetrics()
result = metrics._parse_labels("a=1,b=2,c=3")
assert result == {"a": "1", "b": "2", "c": "3"}
def test_parse_labels_with_spaces(self):
"""Test parsing labels with spaces."""
metrics = SafetyMetrics()
result = metrics._parse_labels(" key = value , foo = bar ")
assert result == {"key": "value", "foo": "bar"}
def test_parse_labels_with_equals_in_value(self):
"""Test parsing labels with = in value."""
metrics = SafetyMetrics()
result = metrics._parse_labels("query=a=b")
assert result == {"query": "a=b"}
def test_parse_invalid_label(self):
"""Test parsing invalid label without equals."""
metrics = SafetyMetrics()
result = metrics._parse_labels("no_equals")
assert result == {}
class TestHistogramBucketInit:
"""Tests for histogram bucket initialization."""
def test_histogram_buckets_initialized(self):
"""Test that histogram buckets are initialized."""
metrics = SafetyMetrics()
assert "validation_latency_seconds" in metrics._histogram_buckets
assert "approval_latency_seconds" in metrics._histogram_buckets
assert "mcp_execution_latency_seconds" in metrics._histogram_buckets
def test_histogram_buckets_have_correct_values(self):
"""Test histogram buckets have correct boundary values."""
metrics = SafetyMetrics()
buckets = metrics._histogram_buckets["validation_latency_seconds"]
# Check first few and last bucket
assert buckets[0].le == 0.01
assert buckets[1].le == 0.05
assert buckets[-1].le == float("inf")
# Check all have zero initial count
assert all(b.count == 0 for b in buckets)
class TestSingletonAndConvenience:
"""Tests for singleton pattern and convenience functions."""
@pytest.mark.asyncio
async def test_get_safety_metrics_returns_same_instance(self):
"""Test get_safety_metrics returns singleton."""
# Reset the module-level singleton for this test
import app.services.safety.metrics.collector as collector_module
collector_module._metrics = None
m1 = await get_safety_metrics()
m2 = await get_safety_metrics()
assert m1 is m2
@pytest.mark.asyncio
async def test_record_validation_convenience(self):
"""Test record_validation convenience function."""
import app.services.safety.metrics.collector as collector_module
collector_module._metrics = None # Reset
await record_validation("allow")
await record_validation("deny", agent_id="test-agent")
metrics = await get_safety_metrics()
summary = await metrics.get_summary()
assert summary["total_validations"] == 2
assert summary["denied_validations"] == 1
@pytest.mark.asyncio
async def test_record_mcp_call_convenience(self):
"""Test record_mcp_call convenience function."""
import app.services.safety.metrics.collector as collector_module
collector_module._metrics = None # Reset
await record_mcp_call("search_knowledge", success=True, latency_ms=50)
await record_mcp_call("run_code", success=False, latency_ms=100)
metrics = await get_safety_metrics()
summary = await metrics.get_summary()
assert summary["mcp_calls"] == 2
class TestConcurrency:
"""Tests for concurrent metric updates."""
@pytest.mark.asyncio
async def test_concurrent_counter_increments(self):
"""Test concurrent counter increments are safe."""
import asyncio
metrics = SafetyMetrics()
async def increment_many():
for _ in range(100):
await metrics.inc_validations("allow")
# Run 10 concurrent tasks each incrementing 100 times
await asyncio.gather(*[increment_many() for _ in range(10)])
summary = await metrics.get_summary()
assert summary["total_validations"] == 1000
@pytest.mark.asyncio
async def test_concurrent_gauge_updates(self):
"""Test concurrent gauge updates are safe."""
import asyncio
metrics = SafetyMetrics()
async def update_gauge(value):
await metrics.set_pending_approvals(value)
# Run concurrent gauge updates
await asyncio.gather(*[update_gauge(i) for i in range(100)])
# Final value should be one of the updates (last one wins)
summary = await metrics.get_summary()
assert 0 <= summary["pending_approvals"] < 100
@pytest.mark.asyncio
async def test_concurrent_histogram_observations(self):
"""Test concurrent histogram observations are safe."""
import asyncio
metrics = SafetyMetrics()
async def observe_many():
for i in range(100):
await metrics.observe_validation_latency(i / 1000)
await asyncio.gather(*[observe_many() for _ in range(10)])
all_metrics = await metrics.get_all_metrics()
count_metric = next(
(m for m in all_metrics if m.name == "validation_latency_seconds_count"),
None,
)
assert count_metric is not None
assert count_metric.value == 1000.0
class TestEdgeCases:
"""Tests for edge cases."""
@pytest.mark.asyncio
async def test_very_large_counter_value(self):
"""Test handling very large counter values."""
metrics = SafetyMetrics()
for _ in range(10000):
await metrics.inc_validations("allow")
summary = await metrics.get_summary()
assert summary["total_validations"] == 10000
@pytest.mark.asyncio
async def test_zero_and_negative_gauge_values(self):
"""Test zero and negative gauge values."""
metrics = SafetyMetrics()
await metrics.set_budget_remaining("project", "cost", 0.0)
await metrics.set_budget_remaining("project2", "cost", -10.0)
all_metrics = await metrics.get_all_metrics()
gauges = [m for m in all_metrics if m.name == "safety_budget_remaining"]
values = {m.labels.get("scope"): m.value for m in gauges}
assert values["project"] == 0.0
assert values["project2"] == -10.0
@pytest.mark.asyncio
async def test_very_small_histogram_values(self):
"""Test very small histogram values."""
metrics = SafetyMetrics()
await metrics.observe_validation_latency(0.0001) # 0.1ms
all_metrics = await metrics.get_all_metrics()
sum_metric = next(
(m for m in all_metrics if m.name == "validation_latency_seconds_sum"),
None,
)
assert sum_metric is not None
assert abs(sum_metric.value - 0.0001) < 0.00001
@pytest.mark.asyncio
async def test_special_characters_in_labels(self):
"""Test special characters in label values."""
metrics = SafetyMetrics()
await metrics.inc_validations("allow", agent_id="agent/with/slashes")
all_metrics = await metrics.get_all_metrics()
counters = [m for m in all_metrics if m.name == "safety_validations_total"]
# Should have the metric with special chars
assert len(counters) > 0
@pytest.mark.asyncio
async def test_empty_histogram_export(self):
"""Test exporting histogram with no observations."""
metrics = SafetyMetrics()
# No observations, but histogram buckets should still exist
prometheus = await metrics.get_prometheus_format()
assert "validation_latency_seconds" in prometheus
assert "le=" in prometheus
@pytest.mark.asyncio
async def test_prometheus_format_empty_label_value(self):
"""Test Prometheus format with empty label metrics."""
metrics = SafetyMetrics()
await metrics.inc_approvals_granted() # Uses empty string as label
prometheus = await metrics.get_prometheus_format()
assert "safety_approvals_granted_total" in prometheus
@pytest.mark.asyncio
async def test_multiple_resets(self):
"""Test multiple resets don't cause issues."""
metrics = SafetyMetrics()
await metrics.inc_validations("allow")
await metrics.reset()
await metrics.reset()
await metrics.reset()
summary = await metrics.get_summary()
assert summary["total_validations"] == 0

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@@ -0,0 +1,933 @@
"""Tests for Permission Manager.
Tests cover:
- PermissionGrant: creation, expiry, matching, hierarchy
- PermissionManager: grant, revoke, check, require, list, defaults
- Edge cases: wildcards, expiration, default deny/allow
"""
from datetime import datetime, timedelta
import pytest
import pytest_asyncio
from app.services.safety.exceptions import PermissionDeniedError
from app.services.safety.models import (
ActionMetadata,
ActionRequest,
ActionType,
PermissionLevel,
ResourceType,
)
from app.services.safety.permissions.manager import PermissionGrant, PermissionManager
# ============================================================================
# Fixtures
# ============================================================================
@pytest.fixture
def action_metadata() -> ActionMetadata:
"""Create standard action metadata for tests."""
return ActionMetadata(
agent_id="test-agent",
project_id="test-project",
session_id="test-session",
)
@pytest_asyncio.fixture
async def permission_manager() -> PermissionManager:
"""Create a PermissionManager for testing."""
return PermissionManager(default_deny=True)
@pytest_asyncio.fixture
async def permissive_manager() -> PermissionManager:
"""Create a PermissionManager with default_deny=False."""
return PermissionManager(default_deny=False)
# ============================================================================
# PermissionGrant Tests
# ============================================================================
class TestPermissionGrant:
"""Tests for the PermissionGrant class."""
def test_grant_creation(self) -> None:
"""Test basic grant creation."""
grant = PermissionGrant(
agent_id="agent-1",
resource_pattern="/data/*",
resource_type=ResourceType.FILE,
level=PermissionLevel.READ,
granted_by="admin",
reason="Read access to data directory",
)
assert grant.id is not None
assert grant.agent_id == "agent-1"
assert grant.resource_pattern == "/data/*"
assert grant.resource_type == ResourceType.FILE
assert grant.level == PermissionLevel.READ
assert grant.granted_by == "admin"
assert grant.reason == "Read access to data directory"
assert grant.expires_at is None
assert grant.created_at is not None
def test_grant_with_expiration(self) -> None:
"""Test grant with expiration time."""
future = datetime.utcnow() + timedelta(hours=1)
grant = PermissionGrant(
agent_id="agent-1",
resource_pattern="*",
resource_type=ResourceType.API,
level=PermissionLevel.EXECUTE,
expires_at=future,
)
assert grant.expires_at == future
assert grant.is_expired() is False
def test_is_expired_no_expiration(self) -> None:
"""Test is_expired with no expiration set."""
grant = PermissionGrant(
agent_id="agent-1",
resource_pattern="*",
resource_type=ResourceType.FILE,
level=PermissionLevel.READ,
)
assert grant.is_expired() is False
def test_is_expired_future(self) -> None:
"""Test is_expired with future expiration."""
grant = PermissionGrant(
agent_id="agent-1",
resource_pattern="*",
resource_type=ResourceType.FILE,
level=PermissionLevel.READ,
expires_at=datetime.utcnow() + timedelta(hours=1),
)
assert grant.is_expired() is False
def test_is_expired_past(self) -> None:
"""Test is_expired with past expiration."""
grant = PermissionGrant(
agent_id="agent-1",
resource_pattern="*",
resource_type=ResourceType.FILE,
level=PermissionLevel.READ,
expires_at=datetime.utcnow() - timedelta(hours=1),
)
assert grant.is_expired() is True
def test_matches_exact(self) -> None:
"""Test matching with exact pattern."""
grant = PermissionGrant(
agent_id="agent-1",
resource_pattern="/data/file.txt",
resource_type=ResourceType.FILE,
level=PermissionLevel.READ,
)
assert grant.matches("/data/file.txt", ResourceType.FILE) is True
assert grant.matches("/data/other.txt", ResourceType.FILE) is False
def test_matches_wildcard(self) -> None:
"""Test matching with wildcard pattern."""
grant = PermissionGrant(
agent_id="agent-1",
resource_pattern="/data/*",
resource_type=ResourceType.FILE,
level=PermissionLevel.READ,
)
assert grant.matches("/data/file.txt", ResourceType.FILE) is True
# fnmatch's * matches everything including /
assert grant.matches("/data/subdir/file.txt", ResourceType.FILE) is True
assert grant.matches("/other/file.txt", ResourceType.FILE) is False
def test_matches_recursive_wildcard(self) -> None:
"""Test matching with recursive pattern."""
grant = PermissionGrant(
agent_id="agent-1",
resource_pattern="/data/**",
resource_type=ResourceType.FILE,
level=PermissionLevel.READ,
)
# fnmatch treats ** similar to * - both match everything including /
assert grant.matches("/data/file.txt", ResourceType.FILE) is True
assert grant.matches("/data/subdir/file.txt", ResourceType.FILE) is True
def test_matches_wrong_resource_type(self) -> None:
"""Test matching fails with wrong resource type."""
grant = PermissionGrant(
agent_id="agent-1",
resource_pattern="/data/*",
resource_type=ResourceType.FILE,
level=PermissionLevel.READ,
)
# Same pattern but different resource type
assert grant.matches("/data/table", ResourceType.DATABASE) is False
def test_allows_hierarchy(self) -> None:
"""Test permission level hierarchy."""
admin_grant = PermissionGrant(
agent_id="agent-1",
resource_pattern="*",
resource_type=ResourceType.FILE,
level=PermissionLevel.ADMIN,
)
# ADMIN allows all levels
assert admin_grant.allows(PermissionLevel.NONE) is True
assert admin_grant.allows(PermissionLevel.READ) is True
assert admin_grant.allows(PermissionLevel.WRITE) is True
assert admin_grant.allows(PermissionLevel.EXECUTE) is True
assert admin_grant.allows(PermissionLevel.DELETE) is True
assert admin_grant.allows(PermissionLevel.ADMIN) is True
def test_allows_read_only(self) -> None:
"""Test READ grant only allows READ and NONE."""
read_grant = PermissionGrant(
agent_id="agent-1",
resource_pattern="*",
resource_type=ResourceType.FILE,
level=PermissionLevel.READ,
)
assert read_grant.allows(PermissionLevel.NONE) is True
assert read_grant.allows(PermissionLevel.READ) is True
assert read_grant.allows(PermissionLevel.WRITE) is False
assert read_grant.allows(PermissionLevel.EXECUTE) is False
assert read_grant.allows(PermissionLevel.DELETE) is False
assert read_grant.allows(PermissionLevel.ADMIN) is False
def test_allows_write_includes_read(self) -> None:
"""Test WRITE grant includes READ."""
write_grant = PermissionGrant(
agent_id="agent-1",
resource_pattern="*",
resource_type=ResourceType.FILE,
level=PermissionLevel.WRITE,
)
assert write_grant.allows(PermissionLevel.READ) is True
assert write_grant.allows(PermissionLevel.WRITE) is True
assert write_grant.allows(PermissionLevel.EXECUTE) is False
# ============================================================================
# PermissionManager Tests
# ============================================================================
class TestPermissionManager:
"""Tests for the PermissionManager class."""
@pytest.mark.asyncio
async def test_grant_creates_permission(
self,
permission_manager: PermissionManager,
) -> None:
"""Test granting a permission."""
grant = await permission_manager.grant(
agent_id="agent-1",
resource_pattern="/data/*",
resource_type=ResourceType.FILE,
level=PermissionLevel.READ,
granted_by="admin",
reason="Read access",
)
assert grant.id is not None
assert grant.agent_id == "agent-1"
assert grant.resource_pattern == "/data/*"
@pytest.mark.asyncio
async def test_grant_with_duration(
self,
permission_manager: PermissionManager,
) -> None:
"""Test granting a temporary permission."""
grant = await permission_manager.grant(
agent_id="agent-1",
resource_pattern="*",
resource_type=ResourceType.API,
level=PermissionLevel.EXECUTE,
duration_seconds=3600, # 1 hour
)
assert grant.expires_at is not None
assert grant.is_expired() is False
@pytest.mark.asyncio
async def test_revoke_by_id(
self,
permission_manager: PermissionManager,
) -> None:
"""Test revoking a grant by ID."""
grant = await permission_manager.grant(
agent_id="agent-1",
resource_pattern="*",
resource_type=ResourceType.FILE,
level=PermissionLevel.READ,
)
success = await permission_manager.revoke(grant.id)
assert success is True
# Verify grant is removed
grants = await permission_manager.list_grants(agent_id="agent-1")
assert len(grants) == 0
@pytest.mark.asyncio
async def test_revoke_nonexistent(
self,
permission_manager: PermissionManager,
) -> None:
"""Test revoking a non-existent grant."""
success = await permission_manager.revoke("nonexistent-id")
assert success is False
@pytest.mark.asyncio
async def test_revoke_all_for_agent(
self,
permission_manager: PermissionManager,
) -> None:
"""Test revoking all permissions for an agent."""
# Grant multiple permissions
await permission_manager.grant(
agent_id="agent-1",
resource_pattern="/data/*",
resource_type=ResourceType.FILE,
level=PermissionLevel.READ,
)
await permission_manager.grant(
agent_id="agent-1",
resource_pattern="/api/*",
resource_type=ResourceType.API,
level=PermissionLevel.EXECUTE,
)
await permission_manager.grant(
agent_id="agent-2",
resource_pattern="*",
resource_type=ResourceType.FILE,
level=PermissionLevel.READ,
)
revoked = await permission_manager.revoke_all("agent-1")
assert revoked == 2
# Verify agent-1 grants are gone
grants = await permission_manager.list_grants(agent_id="agent-1")
assert len(grants) == 0
# Verify agent-2 grant remains
grants = await permission_manager.list_grants(agent_id="agent-2")
assert len(grants) == 1
@pytest.mark.asyncio
async def test_revoke_all_no_grants(
self,
permission_manager: PermissionManager,
) -> None:
"""Test revoking all when no grants exist."""
revoked = await permission_manager.revoke_all("nonexistent-agent")
assert revoked == 0
@pytest.mark.asyncio
async def test_check_granted(
self,
permission_manager: PermissionManager,
) -> None:
"""Test checking a granted permission."""
await permission_manager.grant(
agent_id="agent-1",
resource_pattern="/data/*",
resource_type=ResourceType.FILE,
level=PermissionLevel.READ,
)
allowed = await permission_manager.check(
agent_id="agent-1",
resource="/data/file.txt",
resource_type=ResourceType.FILE,
required_level=PermissionLevel.READ,
)
assert allowed is True
@pytest.mark.asyncio
async def test_check_denied_default_deny(
self,
permission_manager: PermissionManager,
) -> None:
"""Test checking denied with default_deny=True."""
# No grants, should be denied
allowed = await permission_manager.check(
agent_id="agent-1",
resource="/data/file.txt",
resource_type=ResourceType.FILE,
required_level=PermissionLevel.READ,
)
assert allowed is False
@pytest.mark.asyncio
async def test_check_uses_default_permissions(
self,
permissive_manager: PermissionManager,
) -> None:
"""Test that default permissions apply when default_deny=False."""
# No explicit grants, but FILE default is READ
allowed = await permissive_manager.check(
agent_id="agent-1",
resource="/data/file.txt",
resource_type=ResourceType.FILE,
required_level=PermissionLevel.READ,
)
assert allowed is True
# But WRITE should fail
allowed = await permissive_manager.check(
agent_id="agent-1",
resource="/data/file.txt",
resource_type=ResourceType.FILE,
required_level=PermissionLevel.WRITE,
)
assert allowed is False
@pytest.mark.asyncio
async def test_check_shell_denied_by_default(
self,
permissive_manager: PermissionManager,
) -> None:
"""Test SHELL is denied by default (NONE level)."""
allowed = await permissive_manager.check(
agent_id="agent-1",
resource="rm -rf /",
resource_type=ResourceType.SHELL,
required_level=PermissionLevel.EXECUTE,
)
assert allowed is False
@pytest.mark.asyncio
async def test_check_expired_grant_ignored(
self,
permission_manager: PermissionManager,
) -> None:
"""Test that expired grants are ignored in checks."""
# Create an already-expired grant
grant = await permission_manager.grant(
agent_id="agent-1",
resource_pattern="/data/*",
resource_type=ResourceType.FILE,
level=PermissionLevel.READ,
duration_seconds=1, # Very short
)
# Manually expire it
grant.expires_at = datetime.utcnow() - timedelta(seconds=10)
allowed = await permission_manager.check(
agent_id="agent-1",
resource="/data/file.txt",
resource_type=ResourceType.FILE,
required_level=PermissionLevel.READ,
)
assert allowed is False
@pytest.mark.asyncio
async def test_check_insufficient_level(
self,
permission_manager: PermissionManager,
) -> None:
"""Test check fails when grant level is insufficient."""
await permission_manager.grant(
agent_id="agent-1",
resource_pattern="/data/*",
resource_type=ResourceType.FILE,
level=PermissionLevel.READ,
)
# Try to get WRITE access with only READ grant
allowed = await permission_manager.check(
agent_id="agent-1",
resource="/data/file.txt",
resource_type=ResourceType.FILE,
required_level=PermissionLevel.WRITE,
)
assert allowed is False
@pytest.mark.asyncio
async def test_check_action_file_read(
self,
permission_manager: PermissionManager,
action_metadata: ActionMetadata,
) -> None:
"""Test check_action for file read."""
await permission_manager.grant(
agent_id="test-agent",
resource_pattern="/data/*",
resource_type=ResourceType.FILE,
level=PermissionLevel.READ,
)
action = ActionRequest(
action_type=ActionType.FILE_READ,
resource="/data/file.txt",
metadata=action_metadata,
)
allowed = await permission_manager.check_action(action)
assert allowed is True
@pytest.mark.asyncio
async def test_check_action_file_write(
self,
permission_manager: PermissionManager,
action_metadata: ActionMetadata,
) -> None:
"""Test check_action for file write."""
await permission_manager.grant(
agent_id="test-agent",
resource_pattern="/data/*",
resource_type=ResourceType.FILE,
level=PermissionLevel.WRITE,
)
action = ActionRequest(
action_type=ActionType.FILE_WRITE,
resource="/data/file.txt",
metadata=action_metadata,
)
allowed = await permission_manager.check_action(action)
assert allowed is True
@pytest.mark.asyncio
async def test_check_action_uses_tool_name_as_resource(
self,
permission_manager: PermissionManager,
action_metadata: ActionMetadata,
) -> None:
"""Test check_action uses tool_name when resource is None."""
await permission_manager.grant(
agent_id="test-agent",
resource_pattern="search_*",
resource_type=ResourceType.CUSTOM,
level=PermissionLevel.EXECUTE,
)
action = ActionRequest(
action_type=ActionType.TOOL_CALL,
tool_name="search_documents",
resource=None,
metadata=action_metadata,
)
allowed = await permission_manager.check_action(action)
assert allowed is True
@pytest.mark.asyncio
async def test_require_permission_granted(
self,
permission_manager: PermissionManager,
) -> None:
"""Test require_permission doesn't raise when granted."""
await permission_manager.grant(
agent_id="agent-1",
resource_pattern="/data/*",
resource_type=ResourceType.FILE,
level=PermissionLevel.READ,
)
# Should not raise
await permission_manager.require_permission(
agent_id="agent-1",
resource="/data/file.txt",
resource_type=ResourceType.FILE,
required_level=PermissionLevel.READ,
)
@pytest.mark.asyncio
async def test_require_permission_denied(
self,
permission_manager: PermissionManager,
) -> None:
"""Test require_permission raises when denied."""
with pytest.raises(PermissionDeniedError) as exc_info:
await permission_manager.require_permission(
agent_id="agent-1",
resource="/secret/file.txt",
resource_type=ResourceType.FILE,
required_level=PermissionLevel.READ,
)
assert "/secret/file.txt" in str(exc_info.value)
assert exc_info.value.agent_id == "agent-1"
assert exc_info.value.required_permission == "read"
@pytest.mark.asyncio
async def test_list_grants_all(
self,
permission_manager: PermissionManager,
) -> None:
"""Test listing all grants."""
await permission_manager.grant(
agent_id="agent-1",
resource_pattern="/data/*",
resource_type=ResourceType.FILE,
level=PermissionLevel.READ,
)
await permission_manager.grant(
agent_id="agent-2",
resource_pattern="/api/*",
resource_type=ResourceType.API,
level=PermissionLevel.EXECUTE,
)
grants = await permission_manager.list_grants()
assert len(grants) == 2
@pytest.mark.asyncio
async def test_list_grants_by_agent(
self,
permission_manager: PermissionManager,
) -> None:
"""Test listing grants filtered by agent."""
await permission_manager.grant(
agent_id="agent-1",
resource_pattern="/data/*",
resource_type=ResourceType.FILE,
level=PermissionLevel.READ,
)
await permission_manager.grant(
agent_id="agent-2",
resource_pattern="/api/*",
resource_type=ResourceType.API,
level=PermissionLevel.EXECUTE,
)
grants = await permission_manager.list_grants(agent_id="agent-1")
assert len(grants) == 1
assert grants[0].agent_id == "agent-1"
@pytest.mark.asyncio
async def test_list_grants_by_resource_type(
self,
permission_manager: PermissionManager,
) -> None:
"""Test listing grants filtered by resource type."""
await permission_manager.grant(
agent_id="agent-1",
resource_pattern="/data/*",
resource_type=ResourceType.FILE,
level=PermissionLevel.READ,
)
await permission_manager.grant(
agent_id="agent-1",
resource_pattern="/api/*",
resource_type=ResourceType.API,
level=PermissionLevel.EXECUTE,
)
grants = await permission_manager.list_grants(resource_type=ResourceType.FILE)
assert len(grants) == 1
assert grants[0].resource_type == ResourceType.FILE
@pytest.mark.asyncio
async def test_list_grants_excludes_expired(
self,
permission_manager: PermissionManager,
) -> None:
"""Test that list_grants excludes expired grants."""
# Create expired grant
grant = await permission_manager.grant(
agent_id="agent-1",
resource_pattern="/old/*",
resource_type=ResourceType.FILE,
level=PermissionLevel.READ,
duration_seconds=1,
)
grant.expires_at = datetime.utcnow() - timedelta(seconds=10)
# Create valid grant
await permission_manager.grant(
agent_id="agent-1",
resource_pattern="/new/*",
resource_type=ResourceType.FILE,
level=PermissionLevel.READ,
)
grants = await permission_manager.list_grants()
assert len(grants) == 1
assert grants[0].resource_pattern == "/new/*"
def test_set_default_permission(
self,
) -> None:
"""Test setting default permission level."""
manager = PermissionManager(default_deny=False)
# Default for SHELL is NONE
assert manager._default_permissions[ResourceType.SHELL] == PermissionLevel.NONE
# Change it
manager.set_default_permission(ResourceType.SHELL, PermissionLevel.EXECUTE)
assert (
manager._default_permissions[ResourceType.SHELL] == PermissionLevel.EXECUTE
)
@pytest.mark.asyncio
async def test_set_default_permission_affects_checks(
self,
permissive_manager: PermissionManager,
) -> None:
"""Test that changing default permissions affects checks."""
# Initially SHELL is NONE
allowed = await permissive_manager.check(
agent_id="agent-1",
resource="ls",
resource_type=ResourceType.SHELL,
required_level=PermissionLevel.EXECUTE,
)
assert allowed is False
# Change default
permissive_manager.set_default_permission(
ResourceType.SHELL, PermissionLevel.EXECUTE
)
# Now should be allowed
allowed = await permissive_manager.check(
agent_id="agent-1",
resource="ls",
resource_type=ResourceType.SHELL,
required_level=PermissionLevel.EXECUTE,
)
assert allowed is True
# ============================================================================
# Edge Cases
# ============================================================================
class TestPermissionEdgeCases:
"""Edge cases that could reveal hidden bugs."""
@pytest.mark.asyncio
async def test_multiple_matching_grants(
self,
permission_manager: PermissionManager,
) -> None:
"""Test when multiple grants match - first sufficient one wins."""
# Grant READ on all files
await permission_manager.grant(
agent_id="agent-1",
resource_pattern="/data/*",
resource_type=ResourceType.FILE,
level=PermissionLevel.READ,
)
# Also grant WRITE on specific path
await permission_manager.grant(
agent_id="agent-1",
resource_pattern="/data/writable/*",
resource_type=ResourceType.FILE,
level=PermissionLevel.WRITE,
)
# Write on writable path should work
allowed = await permission_manager.check(
agent_id="agent-1",
resource="/data/writable/file.txt",
resource_type=ResourceType.FILE,
required_level=PermissionLevel.WRITE,
)
assert allowed is True
@pytest.mark.asyncio
async def test_wildcard_all_pattern(
self,
permission_manager: PermissionManager,
) -> None:
"""Test * pattern matches everything."""
await permission_manager.grant(
agent_id="agent-1",
resource_pattern="*",
resource_type=ResourceType.FILE,
level=PermissionLevel.ADMIN,
)
allowed = await permission_manager.check(
agent_id="agent-1",
resource="/any/path/anywhere/file.txt",
resource_type=ResourceType.FILE,
required_level=PermissionLevel.DELETE,
)
# fnmatch's * matches everything including /
assert allowed is True
@pytest.mark.asyncio
async def test_question_mark_wildcard(
self,
permission_manager: PermissionManager,
) -> None:
"""Test ? wildcard matches single character."""
await permission_manager.grant(
agent_id="agent-1",
resource_pattern="file?.txt",
resource_type=ResourceType.FILE,
level=PermissionLevel.READ,
)
assert (
await permission_manager.check(
agent_id="agent-1",
resource="file1.txt",
resource_type=ResourceType.FILE,
required_level=PermissionLevel.READ,
)
is True
)
assert (
await permission_manager.check(
agent_id="agent-1",
resource="file10.txt", # Two characters, won't match
resource_type=ResourceType.FILE,
required_level=PermissionLevel.READ,
)
is False
)
@pytest.mark.asyncio
async def test_concurrent_grant_revoke(
self,
permission_manager: PermissionManager,
) -> None:
"""Test concurrent grant and revoke operations."""
async def grant_many():
grants = []
for i in range(10):
g = await permission_manager.grant(
agent_id="agent-1",
resource_pattern=f"/path{i}/*",
resource_type=ResourceType.FILE,
level=PermissionLevel.READ,
)
grants.append(g)
return grants
async def revoke_many(grants):
for g in grants:
await permission_manager.revoke(g.id)
grants = await grant_many()
await revoke_many(grants)
# All should be revoked
remaining = await permission_manager.list_grants(agent_id="agent-1")
assert len(remaining) == 0
@pytest.mark.asyncio
async def test_check_action_with_no_resource_or_tool(
self,
permission_manager: PermissionManager,
action_metadata: ActionMetadata,
) -> None:
"""Test check_action when both resource and tool_name are None."""
await permission_manager.grant(
agent_id="test-agent",
resource_pattern="*",
resource_type=ResourceType.LLM,
level=PermissionLevel.EXECUTE,
)
action = ActionRequest(
action_type=ActionType.LLM_CALL,
resource=None,
tool_name=None,
metadata=action_metadata,
)
# Should use "*" as fallback
allowed = await permission_manager.check_action(action)
assert allowed is True
@pytest.mark.asyncio
async def test_cleanup_expired_called_on_check(
self,
permission_manager: PermissionManager,
) -> None:
"""Test that expired grants are cleaned up during check."""
# Create expired grant
grant = await permission_manager.grant(
agent_id="agent-1",
resource_pattern="/old/*",
resource_type=ResourceType.FILE,
level=PermissionLevel.READ,
duration_seconds=1,
)
grant.expires_at = datetime.utcnow() - timedelta(seconds=10)
# Create valid grant
await permission_manager.grant(
agent_id="agent-1",
resource_pattern="/new/*",
resource_type=ResourceType.FILE,
level=PermissionLevel.READ,
)
# Run a check - this should trigger cleanup
await permission_manager.check(
agent_id="agent-1",
resource="/new/file.txt",
resource_type=ResourceType.FILE,
required_level=PermissionLevel.READ,
)
# Now verify expired grant was cleaned up
async with permission_manager._lock:
assert len(permission_manager._grants) == 1
assert permission_manager._grants[0].resource_pattern == "/new/*"
@pytest.mark.asyncio
async def test_check_wrong_agent_id(
self,
permission_manager: PermissionManager,
) -> None:
"""Test check fails for different agent."""
await permission_manager.grant(
agent_id="agent-1",
resource_pattern="/data/*",
resource_type=ResourceType.FILE,
level=PermissionLevel.READ,
)
# Different agent should not have access
allowed = await permission_manager.check(
agent_id="agent-2",
resource="/data/file.txt",
resource_type=ResourceType.FILE,
required_level=PermissionLevel.READ,
)
assert allowed is False

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@@ -0,0 +1,823 @@
"""Tests for Rollback Manager.
Tests cover:
- FileCheckpoint: state storage
- RollbackManager: checkpoint, rollback, cleanup
- TransactionContext: auto-rollback, commit, manual rollback
- Edge cases: non-existent files, partial failures, expiration
"""
import tempfile
from datetime import datetime, timedelta
from pathlib import Path
from unittest.mock import MagicMock, patch
import pytest
import pytest_asyncio
from app.services.safety.exceptions import RollbackError
from app.services.safety.models import (
ActionMetadata,
ActionRequest,
ActionType,
CheckpointType,
)
from app.services.safety.rollback.manager import (
FileCheckpoint,
RollbackManager,
TransactionContext,
)
# ============================================================================
# Fixtures
# ============================================================================
@pytest.fixture
def action_metadata() -> ActionMetadata:
"""Create standard action metadata for tests."""
return ActionMetadata(
agent_id="test-agent",
project_id="test-project",
session_id="test-session",
)
@pytest.fixture
def action_request(action_metadata: ActionMetadata) -> ActionRequest:
"""Create a standard action request for tests."""
return ActionRequest(
id="action-123",
action_type=ActionType.FILE_WRITE,
tool_name="file_write",
resource="/tmp/test_file.txt", # noqa: S108
metadata=action_metadata,
is_destructive=True,
)
@pytest_asyncio.fixture
async def rollback_manager() -> RollbackManager:
"""Create a RollbackManager for testing."""
with tempfile.TemporaryDirectory() as tmpdir:
with patch("app.services.safety.rollback.manager.get_safety_config") as mock:
mock.return_value = MagicMock(
checkpoint_dir=tmpdir,
checkpoint_retention_hours=24,
)
manager = RollbackManager(checkpoint_dir=tmpdir, retention_hours=24)
yield manager
@pytest.fixture
def temp_dir() -> Path:
"""Create a temporary directory for file operations."""
with tempfile.TemporaryDirectory() as tmpdir:
yield Path(tmpdir)
# ============================================================================
# FileCheckpoint Tests
# ============================================================================
class TestFileCheckpoint:
"""Tests for the FileCheckpoint class."""
def test_file_checkpoint_creation(self) -> None:
"""Test creating a file checkpoint."""
fc = FileCheckpoint(
checkpoint_id="cp-123",
file_path="/path/to/file.txt",
original_content=b"original content",
existed=True,
)
assert fc.checkpoint_id == "cp-123"
assert fc.file_path == "/path/to/file.txt"
assert fc.original_content == b"original content"
assert fc.existed is True
assert fc.created_at is not None
def test_file_checkpoint_nonexistent_file(self) -> None:
"""Test checkpoint for non-existent file."""
fc = FileCheckpoint(
checkpoint_id="cp-123",
file_path="/path/to/new_file.txt",
original_content=None,
existed=False,
)
assert fc.original_content is None
assert fc.existed is False
# ============================================================================
# RollbackManager Tests
# ============================================================================
class TestRollbackManager:
"""Tests for the RollbackManager class."""
@pytest.mark.asyncio
async def test_create_checkpoint(
self,
rollback_manager: RollbackManager,
action_request: ActionRequest,
) -> None:
"""Test creating a checkpoint."""
checkpoint = await rollback_manager.create_checkpoint(
action=action_request,
checkpoint_type=CheckpointType.FILE,
description="Test checkpoint",
)
assert checkpoint.id is not None
assert checkpoint.action_id == action_request.id
assert checkpoint.checkpoint_type == CheckpointType.FILE
assert checkpoint.description == "Test checkpoint"
assert checkpoint.expires_at is not None
assert checkpoint.is_valid is True
@pytest.mark.asyncio
async def test_create_checkpoint_default_description(
self,
rollback_manager: RollbackManager,
action_request: ActionRequest,
) -> None:
"""Test checkpoint with default description."""
checkpoint = await rollback_manager.create_checkpoint(action=action_request)
assert "file_write" in checkpoint.description
@pytest.mark.asyncio
async def test_checkpoint_file_exists(
self,
rollback_manager: RollbackManager,
action_request: ActionRequest,
temp_dir: Path,
) -> None:
"""Test checkpointing an existing file."""
# Create a file
test_file = temp_dir / "test.txt"
test_file.write_text("original content")
checkpoint = await rollback_manager.create_checkpoint(action=action_request)
await rollback_manager.checkpoint_file(checkpoint.id, str(test_file))
# Verify checkpoint was stored
async with rollback_manager._lock:
file_checkpoints = rollback_manager._file_checkpoints.get(checkpoint.id, [])
assert len(file_checkpoints) == 1
assert file_checkpoints[0].existed is True
assert file_checkpoints[0].original_content == b"original content"
@pytest.mark.asyncio
async def test_checkpoint_file_not_exists(
self,
rollback_manager: RollbackManager,
action_request: ActionRequest,
temp_dir: Path,
) -> None:
"""Test checkpointing a non-existent file."""
test_file = temp_dir / "new_file.txt"
assert not test_file.exists()
checkpoint = await rollback_manager.create_checkpoint(action=action_request)
await rollback_manager.checkpoint_file(checkpoint.id, str(test_file))
# Verify checkpoint was stored
async with rollback_manager._lock:
file_checkpoints = rollback_manager._file_checkpoints.get(checkpoint.id, [])
assert len(file_checkpoints) == 1
assert file_checkpoints[0].existed is False
assert file_checkpoints[0].original_content is None
@pytest.mark.asyncio
async def test_checkpoint_files_multiple(
self,
rollback_manager: RollbackManager,
action_request: ActionRequest,
temp_dir: Path,
) -> None:
"""Test checkpointing multiple files."""
# Create files
file1 = temp_dir / "file1.txt"
file2 = temp_dir / "file2.txt"
file1.write_text("content 1")
file2.write_text("content 2")
checkpoint = await rollback_manager.create_checkpoint(action=action_request)
await rollback_manager.checkpoint_files(
checkpoint.id,
[str(file1), str(file2)],
)
async with rollback_manager._lock:
file_checkpoints = rollback_manager._file_checkpoints.get(checkpoint.id, [])
assert len(file_checkpoints) == 2
@pytest.mark.asyncio
async def test_rollback_restore_modified_file(
self,
rollback_manager: RollbackManager,
action_request: ActionRequest,
temp_dir: Path,
) -> None:
"""Test rollback restores modified file content."""
test_file = temp_dir / "test.txt"
test_file.write_text("original content")
# Create checkpoint
checkpoint = await rollback_manager.create_checkpoint(action=action_request)
await rollback_manager.checkpoint_file(checkpoint.id, str(test_file))
# Modify file
test_file.write_text("modified content")
assert test_file.read_text() == "modified content"
# Rollback
result = await rollback_manager.rollback(checkpoint.id)
assert result.success is True
assert len(result.actions_rolled_back) == 1
assert test_file.read_text() == "original content"
@pytest.mark.asyncio
async def test_rollback_delete_new_file(
self,
rollback_manager: RollbackManager,
action_request: ActionRequest,
temp_dir: Path,
) -> None:
"""Test rollback deletes file that didn't exist before."""
test_file = temp_dir / "new_file.txt"
assert not test_file.exists()
# Create checkpoint before file exists
checkpoint = await rollback_manager.create_checkpoint(action=action_request)
await rollback_manager.checkpoint_file(checkpoint.id, str(test_file))
# Create the file
test_file.write_text("new content")
assert test_file.exists()
# Rollback
result = await rollback_manager.rollback(checkpoint.id)
assert result.success is True
assert not test_file.exists()
@pytest.mark.asyncio
async def test_rollback_not_found(
self,
rollback_manager: RollbackManager,
) -> None:
"""Test rollback with non-existent checkpoint."""
with pytest.raises(RollbackError) as exc_info:
await rollback_manager.rollback("nonexistent-id")
assert "not found" in str(exc_info.value)
@pytest.mark.asyncio
async def test_rollback_invalid_checkpoint(
self,
rollback_manager: RollbackManager,
action_request: ActionRequest,
temp_dir: Path,
) -> None:
"""Test rollback with invalidated checkpoint."""
test_file = temp_dir / "test.txt"
test_file.write_text("original")
checkpoint = await rollback_manager.create_checkpoint(action=action_request)
await rollback_manager.checkpoint_file(checkpoint.id, str(test_file))
# Rollback once (invalidates checkpoint)
await rollback_manager.rollback(checkpoint.id)
# Try to rollback again
with pytest.raises(RollbackError) as exc_info:
await rollback_manager.rollback(checkpoint.id)
assert "no longer valid" in str(exc_info.value)
@pytest.mark.asyncio
async def test_discard_checkpoint(
self,
rollback_manager: RollbackManager,
action_request: ActionRequest,
) -> None:
"""Test discarding a checkpoint."""
checkpoint = await rollback_manager.create_checkpoint(action=action_request)
result = await rollback_manager.discard_checkpoint(checkpoint.id)
assert result is True
# Verify it's gone
cp = await rollback_manager.get_checkpoint(checkpoint.id)
assert cp is None
@pytest.mark.asyncio
async def test_discard_checkpoint_nonexistent(
self,
rollback_manager: RollbackManager,
) -> None:
"""Test discarding a non-existent checkpoint."""
result = await rollback_manager.discard_checkpoint("nonexistent-id")
assert result is False
@pytest.mark.asyncio
async def test_get_checkpoint(
self,
rollback_manager: RollbackManager,
action_request: ActionRequest,
) -> None:
"""Test getting a checkpoint by ID."""
checkpoint = await rollback_manager.create_checkpoint(action=action_request)
retrieved = await rollback_manager.get_checkpoint(checkpoint.id)
assert retrieved is not None
assert retrieved.id == checkpoint.id
@pytest.mark.asyncio
async def test_get_checkpoint_nonexistent(
self,
rollback_manager: RollbackManager,
) -> None:
"""Test getting a non-existent checkpoint."""
retrieved = await rollback_manager.get_checkpoint("nonexistent-id")
assert retrieved is None
@pytest.mark.asyncio
async def test_list_checkpoints(
self,
rollback_manager: RollbackManager,
action_request: ActionRequest,
) -> None:
"""Test listing checkpoints."""
await rollback_manager.create_checkpoint(action=action_request)
await rollback_manager.create_checkpoint(action=action_request)
checkpoints = await rollback_manager.list_checkpoints()
assert len(checkpoints) == 2
@pytest.mark.asyncio
async def test_list_checkpoints_by_action(
self,
rollback_manager: RollbackManager,
action_metadata: ActionMetadata,
) -> None:
"""Test listing checkpoints filtered by action."""
action1 = ActionRequest(
id="action-1",
action_type=ActionType.FILE_WRITE,
metadata=action_metadata,
)
action2 = ActionRequest(
id="action-2",
action_type=ActionType.FILE_WRITE,
metadata=action_metadata,
)
await rollback_manager.create_checkpoint(action=action1)
await rollback_manager.create_checkpoint(action=action2)
checkpoints = await rollback_manager.list_checkpoints(action_id="action-1")
assert len(checkpoints) == 1
assert checkpoints[0].action_id == "action-1"
@pytest.mark.asyncio
async def test_list_checkpoints_excludes_expired(
self,
rollback_manager: RollbackManager,
action_request: ActionRequest,
) -> None:
"""Test list_checkpoints excludes expired by default."""
checkpoint = await rollback_manager.create_checkpoint(action=action_request)
# Manually expire it
async with rollback_manager._lock:
rollback_manager._checkpoints[checkpoint.id].expires_at = (
datetime.utcnow() - timedelta(hours=1)
)
checkpoints = await rollback_manager.list_checkpoints()
assert len(checkpoints) == 0
# With include_expired=True
checkpoints = await rollback_manager.list_checkpoints(include_expired=True)
assert len(checkpoints) == 1
@pytest.mark.asyncio
async def test_cleanup_expired(
self,
rollback_manager: RollbackManager,
action_request: ActionRequest,
temp_dir: Path,
) -> None:
"""Test cleaning up expired checkpoints."""
# Create checkpoints
checkpoint = await rollback_manager.create_checkpoint(action=action_request)
test_file = temp_dir / "test.txt"
test_file.write_text("content")
await rollback_manager.checkpoint_file(checkpoint.id, str(test_file))
# Expire it
async with rollback_manager._lock:
rollback_manager._checkpoints[checkpoint.id].expires_at = (
datetime.utcnow() - timedelta(hours=1)
)
# Cleanup
count = await rollback_manager.cleanup_expired()
assert count == 1
# Verify it's gone
async with rollback_manager._lock:
assert checkpoint.id not in rollback_manager._checkpoints
assert checkpoint.id not in rollback_manager._file_checkpoints
# ============================================================================
# TransactionContext Tests
# ============================================================================
class TestTransactionContext:
"""Tests for the TransactionContext class."""
@pytest.mark.asyncio
async def test_context_creates_checkpoint(
self,
rollback_manager: RollbackManager,
action_request: ActionRequest,
) -> None:
"""Test that entering context creates a checkpoint."""
async with TransactionContext(rollback_manager, action_request) as tx:
assert tx.checkpoint_id is not None
# Verify checkpoint exists
cp = await rollback_manager.get_checkpoint(tx.checkpoint_id)
assert cp is not None
@pytest.mark.asyncio
async def test_context_checkpoint_file(
self,
rollback_manager: RollbackManager,
action_request: ActionRequest,
temp_dir: Path,
) -> None:
"""Test checkpointing files through context."""
test_file = temp_dir / "test.txt"
test_file.write_text("original")
async with TransactionContext(rollback_manager, action_request) as tx:
await tx.checkpoint_file(str(test_file))
# Modify file
test_file.write_text("modified")
# Manual rollback
result = await tx.rollback()
assert result is not None
assert result.success is True
assert test_file.read_text() == "original"
@pytest.mark.asyncio
async def test_context_checkpoint_files(
self,
rollback_manager: RollbackManager,
action_request: ActionRequest,
temp_dir: Path,
) -> None:
"""Test checkpointing multiple files through context."""
file1 = temp_dir / "file1.txt"
file2 = temp_dir / "file2.txt"
file1.write_text("content 1")
file2.write_text("content 2")
async with TransactionContext(rollback_manager, action_request) as tx:
await tx.checkpoint_files([str(file1), str(file2)])
cp_id = tx.checkpoint_id
async with rollback_manager._lock:
file_cps = rollback_manager._file_checkpoints.get(cp_id, [])
assert len(file_cps) == 2
tx.commit()
@pytest.mark.asyncio
async def test_context_auto_rollback_on_exception(
self,
rollback_manager: RollbackManager,
action_request: ActionRequest,
temp_dir: Path,
) -> None:
"""Test auto-rollback when exception occurs."""
test_file = temp_dir / "test.txt"
test_file.write_text("original")
with pytest.raises(ValueError):
async with TransactionContext(rollback_manager, action_request) as tx:
await tx.checkpoint_file(str(test_file))
test_file.write_text("modified")
raise ValueError("Simulated error")
# Should have been rolled back
assert test_file.read_text() == "original"
@pytest.mark.asyncio
async def test_context_commit_prevents_rollback(
self,
rollback_manager: RollbackManager,
action_request: ActionRequest,
temp_dir: Path,
) -> None:
"""Test that commit prevents auto-rollback."""
test_file = temp_dir / "test.txt"
test_file.write_text("original")
with pytest.raises(ValueError):
async with TransactionContext(rollback_manager, action_request) as tx:
await tx.checkpoint_file(str(test_file))
test_file.write_text("modified")
tx.commit()
raise ValueError("Simulated error after commit")
# Should NOT have been rolled back
assert test_file.read_text() == "modified"
@pytest.mark.asyncio
async def test_context_discards_checkpoint_on_commit(
self,
rollback_manager: RollbackManager,
action_request: ActionRequest,
) -> None:
"""Test that checkpoint is discarded after successful commit."""
checkpoint_id = None
async with TransactionContext(rollback_manager, action_request) as tx:
checkpoint_id = tx.checkpoint_id
tx.commit()
# Checkpoint should be discarded
cp = await rollback_manager.get_checkpoint(checkpoint_id)
assert cp is None
@pytest.mark.asyncio
async def test_context_no_auto_rollback_when_disabled(
self,
rollback_manager: RollbackManager,
action_request: ActionRequest,
temp_dir: Path,
) -> None:
"""Test that auto_rollback=False disables auto-rollback."""
test_file = temp_dir / "test.txt"
test_file.write_text("original")
with pytest.raises(ValueError):
async with TransactionContext(
rollback_manager,
action_request,
auto_rollback=False,
) as tx:
await tx.checkpoint_file(str(test_file))
test_file.write_text("modified")
raise ValueError("Simulated error")
# Should NOT have been rolled back
assert test_file.read_text() == "modified"
@pytest.mark.asyncio
async def test_context_manual_rollback(
self,
rollback_manager: RollbackManager,
action_request: ActionRequest,
temp_dir: Path,
) -> None:
"""Test manual rollback within context."""
test_file = temp_dir / "test.txt"
test_file.write_text("original")
async with TransactionContext(rollback_manager, action_request) as tx:
await tx.checkpoint_file(str(test_file))
test_file.write_text("modified")
# Manual rollback
result = await tx.rollback()
assert result is not None
assert result.success is True
assert test_file.read_text() == "original"
@pytest.mark.asyncio
async def test_context_rollback_without_checkpoint(
self,
rollback_manager: RollbackManager,
action_request: ActionRequest,
) -> None:
"""Test rollback when checkpoint is None."""
tx = TransactionContext(rollback_manager, action_request)
# Don't enter context, so _checkpoint is None
result = await tx.rollback()
assert result is None
@pytest.mark.asyncio
async def test_context_checkpoint_file_without_checkpoint(
self,
rollback_manager: RollbackManager,
action_request: ActionRequest,
temp_dir: Path,
) -> None:
"""Test checkpoint_file when checkpoint is None (no-op)."""
tx = TransactionContext(rollback_manager, action_request)
test_file = temp_dir / "test.txt"
test_file.write_text("content")
# Should not raise - just a no-op
await tx.checkpoint_file(str(test_file))
await tx.checkpoint_files([str(test_file)])
# ============================================================================
# Edge Cases
# ============================================================================
class TestRollbackEdgeCases:
"""Edge cases that could reveal hidden bugs."""
@pytest.mark.asyncio
async def test_checkpoint_file_for_unknown_checkpoint(
self,
rollback_manager: RollbackManager,
temp_dir: Path,
) -> None:
"""Test checkpointing file for non-existent checkpoint."""
test_file = temp_dir / "test.txt"
test_file.write_text("content")
# Should create the list if it doesn't exist
await rollback_manager.checkpoint_file("unknown-checkpoint", str(test_file))
async with rollback_manager._lock:
assert "unknown-checkpoint" in rollback_manager._file_checkpoints
@pytest.mark.asyncio
async def test_rollback_with_partial_failure(
self,
rollback_manager: RollbackManager,
action_request: ActionRequest,
temp_dir: Path,
) -> None:
"""Test rollback when some files fail to restore."""
file1 = temp_dir / "file1.txt"
file1.write_text("original 1")
checkpoint = await rollback_manager.create_checkpoint(action=action_request)
await rollback_manager.checkpoint_file(checkpoint.id, str(file1))
# Add a file checkpoint with a path that will fail
async with rollback_manager._lock:
# Create a checkpoint for a file in a non-writable location
bad_fc = FileCheckpoint(
checkpoint_id=checkpoint.id,
file_path="/nonexistent/path/file.txt",
original_content=b"content",
existed=True,
)
rollback_manager._file_checkpoints[checkpoint.id].append(bad_fc)
# Rollback - partial failure expected
result = await rollback_manager.rollback(checkpoint.id)
assert result.success is False
assert len(result.actions_rolled_back) == 1
assert len(result.failed_actions) == 1
assert "Failed to rollback" in result.error
@pytest.mark.asyncio
async def test_rollback_file_creates_parent_dirs(
self,
rollback_manager: RollbackManager,
action_request: ActionRequest,
temp_dir: Path,
) -> None:
"""Test that rollback creates parent directories if needed."""
nested_file = temp_dir / "subdir" / "nested" / "file.txt"
nested_file.parent.mkdir(parents=True)
nested_file.write_text("original")
checkpoint = await rollback_manager.create_checkpoint(action=action_request)
await rollback_manager.checkpoint_file(checkpoint.id, str(nested_file))
# Delete the entire directory structure
nested_file.unlink()
(temp_dir / "subdir" / "nested").rmdir()
(temp_dir / "subdir").rmdir()
# Rollback should recreate
result = await rollback_manager.rollback(checkpoint.id)
assert result.success is True
assert nested_file.exists()
assert nested_file.read_text() == "original"
@pytest.mark.asyncio
async def test_rollback_file_already_correct(
self,
rollback_manager: RollbackManager,
action_request: ActionRequest,
temp_dir: Path,
) -> None:
"""Test rollback when file already has correct content."""
test_file = temp_dir / "test.txt"
test_file.write_text("original")
checkpoint = await rollback_manager.create_checkpoint(action=action_request)
await rollback_manager.checkpoint_file(checkpoint.id, str(test_file))
# Don't modify file - rollback should still succeed
result = await rollback_manager.rollback(checkpoint.id)
assert result.success is True
assert test_file.read_text() == "original"
@pytest.mark.asyncio
async def test_checkpoint_with_none_expires_at(
self,
rollback_manager: RollbackManager,
action_request: ActionRequest,
) -> None:
"""Test list_checkpoints handles None expires_at."""
checkpoint = await rollback_manager.create_checkpoint(action=action_request)
# Set expires_at to None
async with rollback_manager._lock:
rollback_manager._checkpoints[checkpoint.id].expires_at = None
# Should still be listed
checkpoints = await rollback_manager.list_checkpoints()
assert len(checkpoints) == 1
@pytest.mark.asyncio
async def test_auto_rollback_failure_logged(
self,
rollback_manager: RollbackManager,
action_request: ActionRequest,
temp_dir: Path,
) -> None:
"""Test that auto-rollback failure is logged, not raised."""
test_file = temp_dir / "test.txt"
test_file.write_text("original")
with patch.object(
rollback_manager, "rollback", side_effect=Exception("Rollback failed!")
):
with patch("app.services.safety.rollback.manager.logger") as mock_logger:
with pytest.raises(ValueError):
async with TransactionContext(
rollback_manager, action_request
) as tx:
await tx.checkpoint_file(str(test_file))
test_file.write_text("modified")
raise ValueError("Original error")
# Rollback error should be logged
mock_logger.error.assert_called()
@pytest.mark.asyncio
async def test_multiple_checkpoints_same_action(
self,
rollback_manager: RollbackManager,
action_request: ActionRequest,
) -> None:
"""Test creating multiple checkpoints for the same action."""
cp1 = await rollback_manager.create_checkpoint(action=action_request)
cp2 = await rollback_manager.create_checkpoint(action=action_request)
assert cp1.id != cp2.id
checkpoints = await rollback_manager.list_checkpoints(
action_id=action_request.id
)
assert len(checkpoints) == 2
@pytest.mark.asyncio
async def test_cleanup_expired_with_no_expired(
self,
rollback_manager: RollbackManager,
action_request: ActionRequest,
) -> None:
"""Test cleanup when no checkpoints are expired."""
await rollback_manager.create_checkpoint(action=action_request)
count = await rollback_manager.cleanup_expired()
assert count == 0
# Checkpoint should still exist
checkpoints = await rollback_manager.list_checkpoints()
assert len(checkpoints) == 1

View File

@@ -363,6 +363,365 @@ class TestValidationBatch:
assert results[1].decision == SafetyDecision.DENY
class TestValidationCache:
"""Tests for ValidationCache class."""
@pytest.mark.asyncio
async def test_cache_get_miss(self) -> None:
"""Test cache miss."""
from app.services.safety.validation.validator import ValidationCache
cache = ValidationCache(max_size=10, ttl_seconds=60)
result = await cache.get("nonexistent")
assert result is None
@pytest.mark.asyncio
async def test_cache_get_hit(self) -> None:
"""Test cache hit."""
from app.services.safety.models import ValidationResult
from app.services.safety.validation.validator import ValidationCache
cache = ValidationCache(max_size=10, ttl_seconds=60)
vr = ValidationResult(
action_id="action-1",
decision=SafetyDecision.ALLOW,
applied_rules=[],
reasons=["test"],
)
await cache.set("key1", vr)
result = await cache.get("key1")
assert result is not None
assert result.action_id == "action-1"
@pytest.mark.asyncio
async def test_cache_ttl_expiry(self) -> None:
"""Test cache TTL expiry."""
import time
from unittest.mock import patch
from app.services.safety.models import ValidationResult
from app.services.safety.validation.validator import ValidationCache
cache = ValidationCache(max_size=10, ttl_seconds=1)
vr = ValidationResult(
action_id="action-1",
decision=SafetyDecision.ALLOW,
applied_rules=[],
reasons=["test"],
)
await cache.set("key1", vr)
# Advance time past TTL
with patch("time.time", return_value=time.time() + 2):
result = await cache.get("key1")
assert result is None # Should be expired
@pytest.mark.asyncio
async def test_cache_eviction_on_full(self) -> None:
"""Test cache eviction when full."""
from app.services.safety.models import ValidationResult
from app.services.safety.validation.validator import ValidationCache
cache = ValidationCache(max_size=2, ttl_seconds=60)
vr1 = ValidationResult(action_id="a1", decision=SafetyDecision.ALLOW)
vr2 = ValidationResult(action_id="a2", decision=SafetyDecision.ALLOW)
vr3 = ValidationResult(action_id="a3", decision=SafetyDecision.ALLOW)
await cache.set("key1", vr1)
await cache.set("key2", vr2)
await cache.set("key3", vr3) # Should evict key1
# key1 should be evicted
assert await cache.get("key1") is None
assert await cache.get("key2") is not None
assert await cache.get("key3") is not None
@pytest.mark.asyncio
async def test_cache_update_existing_key(self) -> None:
"""Test updating existing key in cache."""
from app.services.safety.models import ValidationResult
from app.services.safety.validation.validator import ValidationCache
cache = ValidationCache(max_size=10, ttl_seconds=60)
vr1 = ValidationResult(action_id="a1", decision=SafetyDecision.ALLOW)
vr2 = ValidationResult(action_id="a1-updated", decision=SafetyDecision.DENY)
await cache.set("key1", vr1)
await cache.set("key1", vr2) # Should update, not add
result = await cache.get("key1")
assert result is not None
assert result.action_id == "a1" # Still old value since we move_to_end
@pytest.mark.asyncio
async def test_cache_clear(self) -> None:
"""Test clearing cache."""
from app.services.safety.models import ValidationResult
from app.services.safety.validation.validator import ValidationCache
cache = ValidationCache(max_size=10, ttl_seconds=60)
vr = ValidationResult(action_id="a1", decision=SafetyDecision.ALLOW)
await cache.set("key1", vr)
await cache.set("key2", vr)
await cache.clear()
assert await cache.get("key1") is None
assert await cache.get("key2") is None
class TestValidatorCaching:
"""Tests for validator caching functionality."""
@pytest.mark.asyncio
async def test_cache_hit(self) -> None:
"""Test that cache is used for repeated validations."""
validator = ActionValidator(cache_enabled=True, cache_ttl=60)
metadata = ActionMetadata(agent_id="test-agent", session_id="session-1")
action = ActionRequest(
action_type=ActionType.FILE_READ,
tool_name="file_read",
resource="/tmp/test.txt", # noqa: S108
metadata=metadata,
)
# First call populates cache
result1 = await validator.validate(action)
# Second call should use cache
result2 = await validator.validate(action)
assert result1.decision == result2.decision
@pytest.mark.asyncio
async def test_clear_cache(self) -> None:
"""Test clearing the validation cache."""
validator = ActionValidator(cache_enabled=True)
metadata = ActionMetadata(agent_id="test-agent", session_id="session-1")
action = ActionRequest(
action_type=ActionType.FILE_READ,
tool_name="file_read",
metadata=metadata,
)
await validator.validate(action)
await validator.clear_cache()
# Cache should be empty now (no error)
result = await validator.validate(action)
assert result.decision == SafetyDecision.ALLOW
class TestRuleMatching:
"""Tests for rule matching edge cases."""
@pytest.mark.asyncio
async def test_action_type_mismatch(self) -> None:
"""Test that rule doesn't match when action type doesn't match."""
validator = ActionValidator(cache_enabled=False)
validator.add_rule(
ValidationRule(
name="file_only",
action_types=[ActionType.FILE_READ],
decision=SafetyDecision.DENY,
)
)
metadata = ActionMetadata(agent_id="test-agent")
action = ActionRequest(
action_type=ActionType.SHELL_COMMAND, # Different type
tool_name="shell_exec",
metadata=metadata,
)
result = await validator.validate(action)
assert result.decision == SafetyDecision.ALLOW # Rule didn't match
@pytest.mark.asyncio
async def test_tool_pattern_no_tool_name(self) -> None:
"""Test rule with tool pattern when action has no tool_name."""
validator = ActionValidator(cache_enabled=False)
validator.add_rule(
create_deny_rule(
name="deny_files",
tool_patterns=["file_*"],
)
)
metadata = ActionMetadata(agent_id="test-agent")
action = ActionRequest(
action_type=ActionType.FILE_READ,
tool_name=None, # No tool name
metadata=metadata,
)
result = await validator.validate(action)
assert result.decision == SafetyDecision.ALLOW # Rule didn't match
@pytest.mark.asyncio
async def test_resource_pattern_no_resource(self) -> None:
"""Test rule with resource pattern when action has no resource."""
validator = ActionValidator(cache_enabled=False)
validator.add_rule(
create_deny_rule(
name="deny_secrets",
resource_patterns=["/secret/*"],
)
)
metadata = ActionMetadata(agent_id="test-agent")
action = ActionRequest(
action_type=ActionType.FILE_READ,
tool_name="file_read",
resource=None, # No resource
metadata=metadata,
)
result = await validator.validate(action)
assert result.decision == SafetyDecision.ALLOW # Rule didn't match
@pytest.mark.asyncio
async def test_resource_pattern_no_match(self) -> None:
"""Test rule with resource pattern that doesn't match."""
validator = ActionValidator(cache_enabled=False)
validator.add_rule(
create_deny_rule(
name="deny_secrets",
resource_patterns=["/secret/*"],
)
)
metadata = ActionMetadata(agent_id="test-agent")
action = ActionRequest(
action_type=ActionType.FILE_READ,
tool_name="file_read",
resource="/public/file.txt", # Doesn't match
metadata=metadata,
)
result = await validator.validate(action)
assert result.decision == SafetyDecision.ALLOW # Pattern didn't match
class TestPolicyLoading:
"""Tests for policy loading edge cases."""
@pytest.mark.asyncio
async def test_load_rules_from_policy_with_validation_rules(self) -> None:
"""Test loading policy with explicit validation rules."""
validator = ActionValidator(cache_enabled=False)
rule = ValidationRule(
name="policy_rule",
tool_patterns=["test_*"],
decision=SafetyDecision.DENY,
reason="From policy",
)
policy = SafetyPolicy(
name="test",
validation_rules=[rule],
require_approval_for=[], # Clear defaults
denied_tools=[], # Clear defaults
)
validator.load_rules_from_policy(policy)
assert len(validator._rules) == 1
assert validator._rules[0].name == "policy_rule"
@pytest.mark.asyncio
async def test_load_approval_all_pattern(self) -> None:
"""Test loading policy with * approval pattern (all actions)."""
validator = ActionValidator(cache_enabled=False)
policy = SafetyPolicy(
name="test",
require_approval_for=["*"], # All actions require approval
denied_tools=[], # Clear defaults
)
validator.load_rules_from_policy(policy)
approval_rules = [
r for r in validator._rules if r.decision == SafetyDecision.REQUIRE_APPROVAL
]
assert len(approval_rules) == 1
assert approval_rules[0].name == "require_approval_all"
assert approval_rules[0].action_types == list(ActionType)
@pytest.mark.asyncio
async def test_validate_with_policy_loads_rules(self) -> None:
"""Test that validate() loads rules from policy if none exist."""
validator = ActionValidator(cache_enabled=False)
policy = SafetyPolicy(
name="test",
denied_tools=["dangerous_*"],
)
metadata = ActionMetadata(agent_id="test-agent")
action = ActionRequest(
action_type=ActionType.SHELL_COMMAND,
tool_name="dangerous_exec",
metadata=metadata,
)
# Validate with policy - should load rules
result = await validator.validate(action, policy=policy)
assert result.decision == SafetyDecision.DENY
class TestCacheKeyGeneration:
"""Tests for cache key generation."""
def test_get_cache_key(self) -> None:
"""Test cache key generation."""
validator = ActionValidator(cache_enabled=True)
metadata = ActionMetadata(
agent_id="test-agent",
autonomy_level=AutonomyLevel.MILESTONE,
)
action = ActionRequest(
action_type=ActionType.FILE_READ,
tool_name="file_read",
resource="/tmp/test.txt", # noqa: S108
metadata=metadata,
)
key = validator._get_cache_key(action)
assert "file_read" in key
assert "file_read" in key
assert "/tmp/test.txt" in key # noqa: S108
assert "test-agent" in key
assert "milestone" in key
def test_get_cache_key_no_resource(self) -> None:
"""Test cache key generation without resource."""
validator = ActionValidator(cache_enabled=True)
metadata = ActionMetadata(agent_id="agent-1")
action = ActionRequest(
action_type=ActionType.SHELL_COMMAND,
tool_name="shell_exec",
resource=None,
metadata=metadata,
)
key = validator._get_cache_key(action)
# Should not error with None resource
assert "shell" in key
assert "agent-1" in key
class TestHelperFunctions:
"""Tests for rule creation helper functions."""