fix: address code review findings — batch args, venv path, serve flags

- Fix missing BATCH_ARGS in long-context commands (both benchmark scripts)
- Fix CLAUDE.md stale venv path (data/venv → .venv) and add serve/power docs
- Add -b/--batch to bin/benchmark help text
- Add --no-think flag to serve script (--reasoning-budget 0)
- Sanitize model names in eval run directories
- Simplify agentic setup to use requirements.txt
- Add serve --help test, batch flag assertions to existing tests
- Add requirements.txt for reproducible venv setup (Python 3.13)

scripts/agentic/setup.sh

@@ -8,91 +8,56 @@ source "$SCRIPT_DIR/../../lib/common.sh"
 log_header "Agentic Evaluation Setup"
 
 # ── Python virtual environment ───────────────────────────
-VENV_DIR="$(data_dir venv)"
+VENV_DIR="$PROJECT_ROOT/.venv"
+REQUIREMENTS="$PROJECT_ROOT/requirements.txt"
+
 if [[ ! -f "$VENV_DIR/bin/activate" ]]; then
-    log_info "Creating Python virtual environment..."
-    python3 -m venv "$VENV_DIR"
+    # Prefer Python 3.13 (bigcodebench requires <3.14)
+    PYTHON_BIN="python3.13"
+    if ! command -v "$PYTHON_BIN" >/dev/null 2>&1; then
+        PYTHON_BIN="python3"
+        log_warn "python3.13 not found, using $(python3 --version). bigcodebench may not install."
+    fi
+    log_info "Creating virtual environment with $($PYTHON_BIN --version)..."
+    "$PYTHON_BIN" -m venv "$VENV_DIR"
     log_success "Virtual environment created at $VENV_DIR"
 fi
 
 source "$VENV_DIR/bin/activate"
 log_info "Python: $(python3 --version) from $VENV_DIR"
 
-# ── Install evaluation frameworks ────────────────────────
-
-# Inspect AI — the all-in-one eval framework (bundles BFCL, GAIA, HumanEval, IFEval, etc.)
-if python3 -c "import inspect_ai" 2>/dev/null; then
-    log_success "inspect-ai already installed"
-else
-    log_info "Installing inspect-ai (main eval framework)..."
-    pip install inspect-ai 2>&1 | tail -3
-    log_success "inspect-ai installed"
-fi
-
-# EvalPlus — HumanEval+ and MBPP+ with native ollama support
-if python3 -c "import evalplus" 2>/dev/null; then
-    log_success "evalplus already installed"
-else
-    log_info "Installing evalplus (code generation benchmarks)..."
-    pip install evalplus 2>&1 | tail -3
-    log_success "evalplus installed"
-fi
-
-# BigCodeBench
-if python3 -c "import bigcodebench" 2>/dev/null; then
-    log_success "bigcodebench already installed"
-else
-    log_info "Installing bigcodebench..."
-    pip install bigcodebench 2>&1 | tail -3
-    log_success "bigcodebench installed"
-fi
+# ── Install from requirements.txt ────────────────────────
+log_info "Installing dependencies from requirements.txt..."
+pip install -r "$REQUIREMENTS" 2>&1 | tail -5
+log_success "Dependencies installed"
 
 # ── Check for local LLM server ──────────────────────────
 log_header "LLM Server Check"
 
-ollama_ok=false
-llamacpp_ok=false
-
-if is_cmd ollama; then
-    if curl -s http://localhost:11434/api/tags >/dev/null 2>&1; then
-        log_success "ollama running at localhost:11434"
-        ollama_ok=true
-        # List available models
-        log_info "Available ollama models:"
-        ollama list 2>/dev/null | head -10 || true
-    else
-        log_warn "ollama installed but not running. Start with: ollama serve"
-    fi
+if curl -sf http://localhost:8080/health >/dev/null 2>&1; then
+    log_success "llama-server running at localhost:8080"
+elif curl -sf http://localhost:11434/api/tags >/dev/null 2>&1; then
+    log_success "ollama running at localhost:11434"
 else
-    log_info "ollama not installed — needed for most agentic benchmarks"
-    log_info "Install: curl -fsSL https://ollama.com/install.sh | sh"
-fi
-
-# Check for llama.cpp server
-if curl -s http://localhost:8080/health >/dev/null 2>&1; then
-    log_success "llama.cpp server running at localhost:8080"
-    llamacpp_ok=true
-else
-    log_info "No llama.cpp server detected at localhost:8080"
-    log_info "Start with: toolbox run -c llama-vulkan-radv -- llama-server -m MODEL -c 8192 -ngl 99 -fa 1 --no-mmap"
-fi
-
-if ! $ollama_ok && ! $llamacpp_ok; then
-    log_warn "No local LLM server running. Agentic benchmarks need one."
+    log_warn "No local LLM server running. Start one before running evals:"
+    log_info "  make serve ARGS=\"-m MODEL.gguf\"        (llama-server)"
+    log_info "  ollama serve                            (ollama)"
 fi
 
 # ── Summary ──────────────────────────────────────────────
 log_header "Setup Complete"
 echo ""
 echo "  Installed tools:"
-echo "    inspect-ai     — All-in-one eval framework (HumanEval, BFCL, IFEval, GAIA, ...)"
-echo "    evalplus        — HumanEval+ / MBPP+ with native ollama support"
-echo "    bigcodebench    — 1,140 coding tasks across 139 libraries"
+echo "    inspect-ai      — All-in-one eval framework (IFEval, BFCL, GAIA, ...)"
+echo "    inspect-evals   — Task definitions for inspect-ai"
+echo "    evalplus         — HumanEval+ / MBPP+ with native ollama support"
+echo "    bigcodebench     — 1,140 coding tasks across 139 libraries"
 echo ""
-echo "  To activate the virtual environment:"
-echo "    source data/venv/bin/activate"
+echo "  Activate venv:  source .venv/bin/activate"
 echo ""
 echo "  Run evaluations:"
-echo "    make agentic-quick      # EvalPlus + IFEval (~1 hour)"
-echo "    make agentic-full       # BFCL + BigCodeBench (~3-4 hours)"
+echo "    make agentic-quick      # EvalPlus HumanEval+ + IFEval (~1 hour)"
+echo "    make agentic-code       # EvalPlus + BigCodeBench (~2-3 hours)"
+echo "    make agentic-tooluse    # BFCL function calling (~1-2 hours)"
+echo "    make agentic-full       # All of the above (~5-6 hours)"
 echo ""