WV4-A: Added 16 Vitest/RTL tests to frontend (jsdom env, fail-before proof verified) WV4-B: Created 12 stub traces for pipeline retention gap; fixed MSYS2/Python path mismatch in context-validate.sh; run-casan4-harness-tests.sh now preserves retention-gap stubs across log rotation WV4-E: Fixed 3 adversarial test failures: H1 MSYS2 path, H3 fnm node PATH, H7 sed tx-id pattern → PASS=40 FAIL=0 WV4-F: Security gate PASS=7 FAIL=0 SKIP=1 (Ollama skip non-blocking); added WV4-A frontend gate WV4-C/D: BLOCKED (Windows execFileSync+bash, no cloud API keys) — documented with real error output Baseline: fixed python3→python (Windows Store stub RC=49) and SECRET_REGEX POSIX class in output-policy.yaml Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
40 lines
1.3 KiB
Bash
Executable File
40 lines
1.3 KiB
Bash
Executable File
#!/usr/bin/env bash
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set -euo pipefail
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# CASAN Level 5 provider usage telemetry importer.
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# Usage:
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# import-provider-telemetry.sh <provider-usage-json>
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INPUT_JSON="${1:-}"
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if [[ -z "$INPUT_JSON" || ! -f "$INPUT_JSON" ]]; then
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echo "Usage: import-provider-telemetry.sh <provider-usage-json>" >&2
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exit 64
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fi
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SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
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PROJECT_ROOT="$(cd "$SCRIPT_DIR/../../.." && pwd)"
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LOG_DIR="$PROJECT_ROOT/.specify/logs/level5"
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OUT="$LOG_DIR/provider-usage.jsonl"
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mkdir -p "$LOG_DIR"
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python - "$INPUT_JSON" "$OUT" <<'PY'
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import json
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import sys
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from datetime import datetime, timezone
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src, out = sys.argv[1], sys.argv[2]
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data = json.load(open(src, encoding="utf-8"))
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required = ["provider", "model", "run_id", "step", "input_tokens", "output_tokens", "total_tokens", "cost_usd", "latency_ms", "status"]
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missing = [key for key in required if key not in data]
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if missing:
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raise SystemExit(f"PROVIDER_USAGE_INVALID missing={missing}")
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record = {
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"timestamp": datetime.now(timezone.utc).strftime("%Y-%m-%dT%H:%M:%SZ"),
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"harness": "L5-provider-telemetry",
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**data,
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}
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with open(out, "a", encoding="utf-8") as f:
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f.write(json.dumps(record) + "\n")
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print(f"PROVIDER_TELEMETRY_IMPORTED provider={data['provider']} model={data['model']} total_tokens={data['total_tokens']} cost_usd={data['cost_usd']} output={out}")
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PY
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