| |
| """ |
| flinksql_019: End-to-end verification that ground_truth.sql earns FULL product score. |
| |
| GT is graded as if it were the agent's answer. We assert the ground truth earns |
| the FULL product score (A/B/C/D dims, product_ratio == 1.0). Process dims |
| (G/H/I/J) are ignored: a bare GT run has no agent transcript, so those dims are |
| legitimately 0 and must NOT count against the case. |
| |
| Flow: |
| 1. Start Docker container with Flink environment |
| 2. Setup workspace (copy init/) |
| 3. Copy ground_truth.sql -> result.sql |
| 4. Inject gt/ directory |
| 5. Run grade(workspace_path='/tmp_workspace') |
| 6. Assert product_ratio == 1.0 (GT must earn full product score) |
| 7. Cleanup container |
| |
| Usage: |
| python3 verify_grade.py |
| """ |
| import json |
| import os |
| import subprocess |
| import sys |
| import tempfile |
| import uuid |
| from pathlib import Path |
|
|
| DOCKER_IMAGE = os.environ.get("DOCKER_IMAGE", "dataclaw-eval:v1.0") |
| TMP_WORKSPACE = "/tmp_workspace" |
| TASK_DIR = Path(__file__).resolve().parent.parent |
| CONTAINER_NAME = f"verify_gt_flinksql_019_{uuid.uuid4().hex[:8]}" |
|
|
| PRODUCT_PREFIXES = ("A_", "B_", "C_", "D_") |
|
|
|
|
| def run_cmd(cmd, timeout=300, check=True): |
| """Run a command, raise on failure if check=True.""" |
| r = subprocess.run(cmd, stdout=subprocess.PIPE, stderr=subprocess.PIPE, |
| universal_newlines=True, timeout=timeout) |
| if check and r.returncode != 0: |
| raise RuntimeError("Command failed: {}\nstderr: {}\nstdout: {}".format( |
| ' '.join(cmd), r.stderr, r.stdout)) |
| return r |
|
|
|
|
| def cleanup(): |
| subprocess.run(["docker", "rm", "-f", CONTAINER_NAME], |
| stdout=subprocess.PIPE, stderr=subprocess.PIPE) |
|
|
|
|
| def product_ratio(scores): |
| """GT product ratio (0..1) = sum(A/B/C/D raw score) / sum(A/B/C/D max). |
| |
| Uses RAW dimension scores, NOT product_points: product_points already |
| applies a per-case product_weight (0.6 or 0.7) which differs across cases |
| and is irrelevant to "did GT max out the product dims". |
| """ |
| raw = mx = 0.0 |
| for dim, info in (scores.get("details", {}) or {}).items(): |
| if dim.startswith(PRODUCT_PREFIXES) and isinstance(info, dict): |
| raw += info.get("score", 0) or 0 |
| mx += info.get("max", 0) or 0 |
| return round(raw / mx, 4) if mx else 0.0 |
|
|
|
|
| def main(): |
| workspace_path = str(TASK_DIR) |
| print(f"[verify] Task dir: {workspace_path}") |
| print(f"[verify] Container: {CONTAINER_NAME}") |
| print(f"[verify] Docker image: {DOCKER_IMAGE}") |
|
|
| cleanup() |
|
|
| try: |
| print("[verify] Step 1: Starting container...") |
| run_cmd([ |
| "docker", "run", "-d", |
| "--name", CONTAINER_NAME, |
| "-v", f"{workspace_path}/init:/app:ro", |
| DOCKER_IMAGE, "/bin/bash", "-c", "tail -f /dev/null", |
| ]) |
|
|
| print("[verify] Step 2: Setting up workspace...") |
| run_cmd([ |
| "docker", "exec", CONTAINER_NAME, "/bin/bash", "-c", |
| f"mkdir -p {TMP_WORKSPACE}/init && cp -r /app/. {TMP_WORKSPACE}/init/ " |
| f"&& chmod -R u+w {TMP_WORKSPACE}", |
| ]) |
|
|
| print("[verify] Step 3: Copying ground_truth.sql -> result.sql...") |
| gt_host = os.path.join(workspace_path, "gt") |
| run_cmd(["docker", "cp", gt_host, f"{CONTAINER_NAME}:{TMP_WORKSPACE}/gt"]) |
| run_cmd([ |
| "docker", "exec", CONTAINER_NAME, "/bin/bash", "-c", |
| f"cp {TMP_WORKSPACE}/gt/ground_truth.sql {TMP_WORKSPACE}/result.sql", |
| ]) |
|
|
| print("[verify] Step 4: Running grade()...") |
| grade_runner = "\n".join([ |
| "import json", |
| "import sys", |
| f"sys.path.insert(0, '{TMP_WORKSPACE}')", |
| f"sys.path.insert(0, '{TMP_WORKSPACE}/gt')", |
| "from grade import grade", |
| f"result = grade(workspace_path='{TMP_WORKSPACE}')", |
| "print('__VERIFY_JSON_START__')", |
| "print(json.dumps(result, ensure_ascii=False))", |
| "print('__VERIFY_JSON_END__')", |
| ]) + "\n" |
|
|
| with tempfile.NamedTemporaryFile(mode="w", suffix=".py", delete=False, |
| encoding="utf-8") as f: |
| f.write(grade_runner) |
| runner_host = f.name |
|
|
| try: |
| run_cmd(["docker", "cp", runner_host, |
| f"{CONTAINER_NAME}:/tmp/_verify_runner.py"]) |
| r = subprocess.run( |
| ["docker", "exec", CONTAINER_NAME, "python3", "/tmp/_verify_runner.py"], |
| stdout=subprocess.PIPE, stderr=subprocess.PIPE, |
| universal_newlines=True, timeout=600, |
| ) |
| finally: |
| os.unlink(runner_host) |
|
|
| stdout = r.stdout or "" |
| if "__VERIFY_JSON_START__" not in stdout or "__VERIFY_JSON_END__" not in stdout: |
| print("[verify] FAIL: No JSON output from grade") |
| print(f" stdout (last 2000): {stdout[-2000:]}") |
| print(f" stderr (last 2000): {(r.stderr or '')[-2000:]}") |
| sys.exit(1) |
|
|
| json_str = stdout.split("__VERIFY_JSON_START__")[1].split("__VERIFY_JSON_END__")[0].strip() |
| scores = json.loads(json_str) |
|
|
| print("[verify] Grade result:") |
| print(json.dumps(scores, indent=2, ensure_ascii=False)) |
|
|
| ratio = product_ratio(scores) |
| print(f"[verify] product_ratio = {ratio} " |
| f"(product_points={scores.get('product_points')}, " |
| f"overall_score={scores.get('overall_score')})") |
|
|
| if ratio >= 1.0: |
| print(f"\n[verify] PASS: GT earned full product score (product_ratio={ratio})") |
| else: |
| print(f"\n[verify] FAIL: GT did NOT earn full product score (product_ratio={ratio})") |
| for dim, info in (scores.get("details", {}) or {}).items(): |
| if dim.startswith(PRODUCT_PREFIXES) and isinstance(info, dict): |
| print(f" {dim}: {info.get('score', 0)}/{info.get('max', 0)}") |
| for d in (scores.get("diagnostics") or []): |
| print(f" diag: {d}") |
| sys.exit(1) |
|
|
| except Exception as e: |
| print(f"[verify] ERROR: {e}") |
| sys.exit(1) |
| finally: |
| cleanup() |
|
|
|
|
| if __name__ == "__main__": |
| main() |
|
|
