Files
fast-next-template/backend/app/services/context/__init__.py
Felipe Cardoso 30e5c68304 feat(memory): integrate memory system with context engine (#97)
## Changes

### New Context Type
- Add MEMORY to ContextType enum for agent memory context
- Create MemoryContext class with subtypes (working, episodic, semantic, procedural)
- Factory methods: from_working_memory, from_episodic_memory, from_semantic_memory, from_procedural_memory

### Memory Context Source
- MemoryContextSource service fetches relevant memories for context assembly
- Configurable fetch limits per memory type
- Parallel fetching from all memory types

### Agent Lifecycle Hooks
- AgentLifecycleManager handles spawn, pause, resume, terminate events
- spawn: Initialize working memory with optional initial state
- pause: Create checkpoint of working memory
- resume: Restore from checkpoint
- terminate: Consolidate working memory to episodic memory
- LifecycleHooks for custom extension points

### Context Engine Integration
- Add memory_query parameter to assemble_context()
- Add session_id and agent_type_id for memory scoping
- Memory budget allocation (15% by default)
- set_memory_source() for runtime configuration

### Tests
- 48 new tests for MemoryContext, MemoryContextSource, and lifecycle hooks
- All 108 memory-related tests passing
- mypy and ruff checks passing

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

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2026-01-05 03:49:22 +01:00

183 lines
3.5 KiB
Python

"""
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,
MemoryContext,
MemorySubtype,
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",
"MemoryContext",
"MemorySubtype",
"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",
]