Datasets:
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e8c001c | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 | #!/usr/bin/env python3
"""
mysql_004: End-to-end verification that ground_truth.py scores 100 via grade().
Complete flow:
1. Start Docker container (mount init/ as /app)
2. Setup workspace (/app -> /tmp_workspace)
3. Copy ground_truth.py as result.py (simulating agent output)
4. Init MySQL database (mysql -u root < init_db.sql)
5. Inject gt/ directory
6. Run grade(workspace_path='/tmp_workspace')
7. Assert product_score == 70 (without chat.jsonl, process=0, product=70)
8. Cleanup container
Usage:
python3 verify_grade.py
"""
import json
import os
import subprocess
import sys
import tempfile
import time
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 # mysql_004/
CONTAINER_NAME = f"verify_gt_mysql_004_{uuid.uuid4().hex[:8]}"
def run_cmd(cmd, timeout=300, 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 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:
# 1. Start container
print("[verify] Step 1: Starting container...")
cmd = [
"docker", "run", "-d",
"--name", CONTAINER_NAME,
"-v", f"{workspace_path}/init:/app:ro",
DOCKER_IMAGE, "/bin/bash", "-c", "tail -f /dev/null",
]
run_cmd(cmd)
# 2. Setup workspace
print("[verify] Step 2: Setting up workspace...")
run_cmd([
"docker", "exec", CONTAINER_NAME, "/bin/bash", "-c",
f"cp -r /app/. {TMP_WORKSPACE} && chmod -R u+w {TMP_WORKSPACE}",
])
# 3. Init MySQL database (mysql -u root < init_db.sql)
print("[verify] Step 3: Initializing MySQL database...")
# Start MySQL daemon first (init_db.sql needs it)
run_cmd([
"docker", "exec", CONTAINER_NAME, "/bin/bash", "-c",
"mysqld_safe --user=root &",
], timeout=60)
time.sleep(5) # wait for MySQL to be ready
# Run init SQL
run_cmd([
"docker", "exec", CONTAINER_NAME, "/bin/bash", "-c",
f"mysql -u root < {TMP_WORKSPACE}/init_db.sql",
], timeout=60)
print("[verify] MySQL init complete")
# 4. Copy ground_truth.py as result.py (simulating agent produced this)
print("[verify] Step 4: Copying ground_truth.py -> result.py...")
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.py {TMP_WORKSPACE}/result.py",
])
# 5. Run grade inside container
print("[verify] Step 5: 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)
# Parse result
stdout = r.stdout or ""
if "__VERIFY_JSON_START__" not in stdout or "__VERIFY_JSON_END__" not in stdout:
print(f"[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(f"[verify] Grade result:")
print(json.dumps(scores, indent=2, ensure_ascii=False))
# 6. Assert expected score
overall = scores.get("overall_score", 0)
total_points = scores.get("total_points", 0)
product_points = scores.get("product_points", 0)
process_points = scores.get("process_points", 0)
# Without transcript (no chat.jsonl):
# product dims total max = 15+15+20+40+10 = 100
# product_score = 100 * 0.7 = 70, overall_score = 70/100 = 0.7
expected_overall = 0.7
expected_product = 70
if product_points == expected_product and overall == expected_overall:
print(f"\n[verify] PASS: {total_points}/100 (product={product_points}, process={process_points}, overall_score={overall})")
else:
print(f"\n[verify] FAIL: Expected product_points={expected_product} overall_score={expected_overall}")
print(f" Got: total_points={total_points}, product={product_points}, process={process_points}, overall={overall}")
if "details" in scores:
for dim, info in scores["details"].items():
print(f" {dim}: {info.get('score', 0)}/{info.get('max', 0)}")
if "error" in scores:
print(f" Error: {scores['error']}")
if "diagnostics" in scores:
for diag in scores["diagnostics"]:
print(f" Diagnostic: {diag}")
sys.exit(1)
except Exception as e:
print(f"[verify] ERROR: {e}")
sys.exit(1)
finally:
cleanup()
if __name__ == "__main__":
main()
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