File size: 2,433 Bytes
c209999 | 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 | import json
import re
from openai import OpenAI
from src.models import CritiqueResponse
from src.config import API_KEY, BASE_URL, MODEL
_client: OpenAI | None = None
def _get_client() -> OpenAI:
global _client
if _client is None:
_client = OpenAI(api_key=API_KEY, base_url=BASE_URL)
return _client
_SYSTEM_PROMPT = """You are an expert Python code debugger. Given a script and its error output, analyze the root cause and provide a fix strategy.
Common error patterns:
- Network errors (Cannot connect, Temporary failure in name resolution, Connection refused, timeout): the environment HAS network access, so retry with correct URL, add retries, or check the host/service is reachable.
- ImportError/Missing package: add the missing package to requirements list.
- Syntax errors: fix the syntax.
- File not found: check path exists before reading.
Respond with valid JSON in exactly this format (no markdown, no code fences):
{"error_analysis": "root cause explanation", "correction_strategy": "specific fix strategy", "confidence": 0.95}"""
def analyze_error(script: str, stderr: str, user_prompt: str) -> CritiqueResponse:
client = _get_client()
user_content = (
f"User intent: {user_prompt}\n\n"
f"Script:\n```python\n{script}\n```\n\n"
f"Error:\n```\n{stderr}\n```"
)
response = client.chat.completions.create(
model=MODEL,
messages=[
{"role": "system", "content": _SYSTEM_PROMPT},
{"role": "user", "content": user_content},
],
max_tokens=2000,
temperature=0.1,
)
raw = response.choices[0].message.content or "{}"
return _parse_json(raw)
def _parse_json(raw: str) -> CritiqueResponse:
cleaned = raw.strip()
if cleaned.startswith("```"):
cleaned = re.sub(r"^```(?:json)?\s*", "", cleaned)
cleaned = re.sub(r"\s*```$", "", cleaned)
try:
data = json.loads(cleaned)
return CritiqueResponse(
error_analysis=data.get("error_analysis", ""),
correction_strategy=data.get("correction_strategy", ""),
confidence=float(data.get("confidence", 0.0)),
)
except (json.JSONDecodeError, ValueError, TypeError):
return CritiqueResponse(
error_analysis=raw[:500],
correction_strategy="Review the error and fix syntax/import issues.",
confidence=0.5,
)
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