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inference.py - SQL Correction Environment Baseline Script
=========================================================
MANDATORY - Place this file in the ROOT of the project.
Required environment variables:
API_BASE_URL The API endpoint for the LLM
MODEL_NAME The model identifier to use for inference
HF_TOKEN Your Hugging Face / API key
ENV_URL URL of the running environment (default: http://localhost:7860)
SQL_ENV_TASK Task difficulty: easy | medium | hard (default: easy)
"""
import asyncio
import os
import sys
import textwrap
from typing import List, Optional
import re
import httpx
try:
from openai import OpenAI
except Exception:
OpenAI = None
API_BASE_URL = os.getenv("API_BASE_URL", "https://router.huggingface.co/v1")
MODEL_NAME = os.getenv("MODEL_NAME", "Qwen/Qwen2.5-72B-Instruct")
API_KEY = os.getenv("HF_TOKEN") or os.getenv("API_KEY", "dummy")
TASK_NAME = os.getenv("SQL_ENV_TASK", "easy")
BENCHMARK = "sql-correction-env"
ENV_URL = os.getenv("ENV_URL", "http://localhost:7860")
MAX_STEPS = 8
SUCCESS_SCORE_THRESHOLD = 0.5
# ---------------------------------------------------------------------------
# Logging helpers — must match the spec format exactly
# ---------------------------------------------------------------------------
def log_start(task: str, env: str, model: str) -> None:
print(f"[START] task={task} env={env} model={model}", flush=True)
def log_step(
step: int,
action: str,
reward: float,
done: bool,
error: Optional[str],
) -> None:
err = error if error else "null"
done_val = str(done).lower()
# Collapse newlines so the entire step fits on one line (spec requirement)
action_clean = action.replace("\n", " ").replace("\r", "").strip()
print(
f"[STEP] step={step} action={action_clean} "
f"reward={reward:.2f} done={done_val} error={err}",
flush=True,
)
def log_end(success: bool, steps: int, score: float, rewards: List[float]) -> None:
rewards_str = ",".join(f"{r:.2f}" for r in rewards) if rewards else ""
print(
f"[END] success={str(success).lower()} steps={steps} "
f"score={score:.3f} rewards={rewards_str}",
flush=True,
)
# ---------------------------------------------------------------------------
# LLM / heuristic helpers
# ---------------------------------------------------------------------------
SYSTEM_PROMPT = textwrap.dedent(
"""
You are an expert SQL debugger.
You will be shown a broken SQL query that contains typos or keyword errors.
Fix ALL errors and return ONLY the corrected SQL query.
No explanation, no markdown, no code blocks, no backticks.
Common errors: FORM->FROM, WEHRE->WHERE, GRUP->GROUP, HAVNG->HAVING,
ORDR->ORDER, INNE->INNER, LFT->LEFT, BETWEN->BETWEEN, DSC->DESC, SELCT->SELECT.
"""
).strip()
SQL_REPLACEMENTS = {
"FORM": "FROM",
"WEHRE": "WHERE",
"WHER": "WHERE",
"GRUP": "GROUP",
"HAVNG": "HAVING",
"ORDR": "ORDER",
"INNE": "INNER",
"LFT": "LEFT",
"BETWEN": "BETWEEN",
"DSC": "DESC",
"SELCT": "SELECT",
"LIMT": "LIMIT",
"DPT_ID": "DEPT_ID",
}
def heuristic_correct_sql(query: str) -> str:
"""Deterministic fallback when the LLM is unavailable."""
corrected = query
for broken, fixed in SQL_REPLACEMENTS.items():
corrected = re.sub(
rf"\b{re.escape(broken)}\b", fixed, corrected, flags=re.IGNORECASE
)
return corrected.strip()
def get_model_action(
client: Optional["OpenAI"], obs: dict, history: List[str]
) -> str:
"""Return a corrected SQL string. Falls back to heuristic on any failure."""
heuristic = heuristic_correct_sql(obs.get("broken_query", ""))
if client is None:
return heuristic
history_block = "\n".join(history[-4:]) if history else "None"
user_prompt = textwrap.dedent(
f"""
Broken SQL query:
{obs.get("broken_query", "")}
Schema context: {obs.get("schema_context") or "Not provided"}
Error hint: {obs.get("error_hint") or "None"}
Your previous attempt: {obs.get("previous_attempt") or "None"}
Feedback: {obs.get("feedback") or "None"}
Recent history:
{history_block}
Return ONLY the corrected SQL query.
"""
).strip()
try:
completion = client.chat.completions.create(
model=MODEL_NAME,
messages=[
{"role": "system", "content": SYSTEM_PROMPT},
{"role": "user", "content": user_prompt},
],
temperature=0.2,
max_tokens=300,
stream=False,
)
text = (completion.choices[0].message.content or "").strip()
return text if text else heuristic
except Exception as exc:
print(f"[DEBUG] LLM call failed: {exc}", flush=True)
return heuristic
# ---------------------------------------------------------------------------
# Episode runner
# ---------------------------------------------------------------------------
async def run_task(task_name: str) -> None:
"""
Run one full episode for `task_name`.
The [END] log line is ALWAYS emitted via the finally block, even if an
exception occurs mid-episode or the reset call fails. This is required
by the hackathon spec to avoid disqualification.
"""
# Initialise all accumulators BEFORE the try so finally can always read them
rewards: List[float] = []
history: List[str] = []
steps_taken = 0
score = 0.0
success = False
# Build LLM client (best-effort; None means heuristic-only mode)
client = None
if OpenAI is not None and API_KEY not in {"", "dummy"}:
try:
client = OpenAI(base_url=API_BASE_URL, api_key=API_KEY)
except Exception as exc:
print(f"[DEBUG] OpenAI client init failed: {exc}", flush=True)
log_start(task_name, BENCHMARK, MODEL_NAME)
http: Optional[httpx.AsyncClient] = None
try:
http = httpx.AsyncClient(base_url=ENV_URL, timeout=60.0)
# --- reset ---------------------------------------------------------
reset_failed = False
obs: dict = {}
try:
reset_resp = await http.post("/reset", json={"difficulty": task_name})
reset_resp.raise_for_status()
obs = reset_resp.json()
except Exception as exc:
print(f"[DEBUG] Reset failed: {exc}", flush=True)
# Do NOT return here — fall through to finally so [END] is always logged
reset_failed = True
if not reset_failed:
# --- step loop -------------------------------------------------
for step in range(1, MAX_STEPS + 1):
# Get action (never raises — heuristic is the ultimate fallback)
try:
action_str = get_model_action(client, obs, history)
except Exception as exc:
print(f"[DEBUG] Model action failed: {exc}", flush=True)
action_str = heuristic_correct_sql(obs.get("broken_query", ""))
# Submit action to environment
try:
step_resp = await http.post(
"/step", json={"corrected_query": action_str}
)
step_resp.raise_for_status()
result = step_resp.json()
except Exception as exc:
print(f"[DEBUG] Step {step} request failed: {exc}", flush=True)
# Treat as a 0-reward terminal step so episode ends cleanly
rewards.append(0.0)
steps_taken = step
log_step(step, action_str, 0.0, True, str(exc))
break
obs = result.get("observation", obs)
reward = float(result.get("reward", 0.0))
done = bool(result.get("done", False))
info = result.get("info")
error = info.get("error") if isinstance(info, dict) else None
rewards.append(reward)
steps_taken = step
history.append(
f"Step {step}: attempt={action_str!r} reward={reward:+.2f}"
)
log_step(step, action_str, reward, done, error)
if done:
break
# Score = average reward across all steps, clamped to [0, 1]
if rewards:
score = min(max(sum(rewards) / len(rewards), 0.0), 1.0)
success = score >= SUCCESS_SCORE_THRESHOLD
except Exception as exc:
# Catch-all for any unexpected error in the episode body
print(f"[DEBUG] Unhandled episode error: {exc}", flush=True)
finally:
# Always close the HTTP client
if http is not None:
try:
await http.aclose()
except Exception as exc:
print(f"[DEBUG] HTTP close error: {exc}", flush=True)
# [END] MUST always be emitted — even after reset failure or exception
log_end(success, steps_taken, score, rewards)
# ---------------------------------------------------------------------------
# Entry point
# ---------------------------------------------------------------------------
async def main() -> None:
"""
Run tasks according to SQL_ENV_TASK.
If SQL_ENV_TASK is a single valid difficulty, run only that task.
Otherwise run all three in sequence so all 3 tasks produce scores.
"""
try:
difficulties = (
(TASK_NAME,)
if TASK_NAME in {"easy", "medium", "hard"}
else ("easy", "medium", "hard")
)
for difficulty in difficulties:
await run_task(difficulty)
print("", flush=True) # blank line separator between tasks
except Exception as exc:
print(f"[DEBUG] Main loop error: {exc}", flush=True)
if __name__ == "__main__":
try:
asyncio.run(main())
except KeyboardInterrupt:
pass
except Exception as exc:
print(f"[DEBUG] Fatal error: {exc}", flush=True)
finally:
sys.exit(0)
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