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/run-eval.sh

@@ -5,7 +5,7 @@ set -euo pipefail
 SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
 source "$SCRIPT_DIR/../../lib/common.sh"
 
-VENV_DIR="$(data_dir venv)"
+VENV_DIR="$PROJECT_ROOT/.venv"
 EVAL_DIR="$(data_dir evals)"
 
 # ── Argument parsing ─────────────────────────────────────
@@ -37,33 +37,59 @@ while [[ $# -gt 0 ]]; do
 done
 
 # ── Validation ───────────────────────────────────────────
-if [[ -z "$MODEL" ]]; then
-    log_error "Model name required. Use --model NAME"
-    log_info "Examples:"
-    log_info "  --model qwen3.5:35b-a3b-q8_0       (ollama)"
-    log_info "  --model Qwen3.5-35B-A3B-Q8_0        (llama.cpp server)"
-    exit 1
-fi
-
 if [[ ! -f "$VENV_DIR/bin/activate" ]]; then
     log_error "Virtual environment not found. Run: make agentic-setup"
     exit 1
 fi
 source "$VENV_DIR/bin/activate"
 
-# Check server is reachable
-if ! curl -sf "$ENDPOINT/models" >/dev/null 2>&1; then
-    # Try ollama native endpoint
-    if curl -sf "http://localhost:11434/api/tags" >/dev/null 2>&1; then
-        log_info "Ollama detected, using OpenAI-compat endpoint"
+# Auto-detect server if no explicit endpoint given
+if [[ "$ENDPOINT" == "http://localhost:11434/v1" ]]; then
+    if curl -sf "http://localhost:8080/health" >/dev/null 2>&1; then
+        ENDPOINT="http://localhost:8080/v1"
+        log_info "Auto-detected llama-server at localhost:8080"
+    elif curl -sf "http://localhost:11434/api/tags" >/dev/null 2>&1; then
+        log_info "Auto-detected ollama at localhost:11434"
     else
-        log_error "No LLM server at $ENDPOINT. Start ollama or llama.cpp server first."
+        log_error "No LLM server found. Start one first:"
+        log_info "  make serve ARGS=\"-m MODEL.gguf\"        (llama-server)"
+        log_info "  ollama serve                            (ollama)"
+        exit 1
+    fi
+else
+    if ! curl -sf "${ENDPOINT%/v1}/health" >/dev/null 2>&1 && \
+       ! curl -sf "$ENDPOINT/models" >/dev/null 2>&1; then
+        log_error "No LLM server at $ENDPOINT"
+        exit 1
+    fi
+fi
+
+# Auto-detect model name from server if not provided
+if [[ -z "$MODEL" ]]; then
+    DETECTED_MODEL=$(curl -sf "$ENDPOINT/models" 2>/dev/null | python3 -c "
+import sys, json
+try:
+    data = json.load(sys.stdin)
+    models = data.get('data', [])
+    if models:
+        print(models[0].get('id', ''))
+except: pass
+" 2>/dev/null || true)
+    if [[ -n "$DETECTED_MODEL" ]]; then
+        MODEL="$DETECTED_MODEL"
+        log_info "Auto-detected model: $MODEL"
+    else
+        log_error "Model name required. Use --model NAME"
+        log_info "Examples:"
+        log_info "  --model qwen3.5:35b-a3b-q8_0       (ollama)"
+        log_info "  --model Qwen3.5-35B-A3B-Q8_0        (llama.cpp server)"
         exit 1
     fi
 fi
 
 TS="$(timestamp)"
-RUN_DIR="$EVAL_DIR/${SUITE}-${MODEL//[:\/]/_}-${TS}"
+SAFE_MODEL="$(echo "$MODEL" | tr -cs 'a-zA-Z0-9._-' '_')"
+RUN_DIR="$EVAL_DIR/${SUITE}-${SAFE_MODEL}-${TS}"
 mkdir -p "$RUN_DIR"
 
 log_header "Agentic Evaluation: $SUITE"
@@ -86,7 +112,11 @@ ENDJSON
 METRICS_FILE="$RUN_DIR/metrics.csv"
 bash "$SCRIPT_DIR/../monitor/log-metrics.sh" --output "$METRICS_FILE" --interval 5 &
 METRICS_PID=$!
-trap 'kill "$METRICS_PID" 2>/dev/null; wait "$METRICS_PID" 2>/dev/null' EXIT
+cleanup() {
+    kill "$METRICS_PID" 2>/dev/null || true
+    wait "$METRICS_PID" 2>/dev/null || true
+}
+trap 'cleanup; exit 0' EXIT
 
 # ── Suite execution ──────────────────────────────────────
 
@@ -113,14 +143,14 @@ run_evalplus() {
 run_inspect_eval() {
     local eval_name="$1"
     local display_name="$2"
+    local safe_name="${eval_name//\//_}"  # inspect_evals/ifeval → inspect_evals_ifeval
     log_info "Running Inspect AI: $display_name..."
-    local out="$RUN_DIR/inspect-${eval_name}.json"
 
     OPENAI_BASE_URL="$ENDPOINT" OPENAI_API_KEY="not-needed" \
     inspect eval "$eval_name" \
         --model "openai/$MODEL" \
         --log-dir "$RUN_DIR/inspect-logs/" \
-        2>&1 | tee "$RUN_DIR/inspect-${eval_name}.log"
+        2>&1 | tee "$RUN_DIR/inspect-${safe_name}.log"
 
     log_success "Inspect $display_name complete"
 }
@@ -138,7 +168,7 @@ run_bigcodebench() {
 case "$SUITE" in
     quick)
         run_evalplus "humaneval"
-        run_inspect_eval "ifeval" "IFEval (instruction following)"
+        run_inspect_eval "inspect_evals/ifeval" "IFEval (instruction following)"
         ;;
     code)
         run_evalplus "humaneval"
@@ -146,13 +176,13 @@ case "$SUITE" in
         run_bigcodebench
         ;;
     tooluse)
-        run_inspect_eval "bfcl" "BFCL (function calling)"
+        run_inspect_eval "inspect_evals/bfcl" "BFCL (function calling)"
         ;;
     full)
         run_evalplus "humaneval"
         run_evalplus "mbpp"
-        run_inspect_eval "ifeval" "IFEval (instruction following)"
-        run_inspect_eval "bfcl" "BFCL (function calling)"
+        run_inspect_eval "inspect_evals/ifeval" "IFEval (instruction following)"
+        run_inspect_eval "inspect_evals/bfcl" "BFCL (function calling)"
         run_bigcodebench
         ;;
     *)