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File size: 1,841 Bytes
d1e0f9b | 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 | from fastapi import FastAPI, HTTPException
from pydantic import BaseModel
import json
import logging
# Simple version without AI model for testing
app = FastAPI(
title="AI Code Review Service",
description="An API to get AI-powered code reviews for pull request diffs.",
version="1.0.0",
)
# Configure logging
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)
class DiffRequest(BaseModel):
diff: str
class ReviewComment(BaseModel):
file_path: str
line_number: int
comment_text: str
class ReviewResponse(BaseModel):
comments: list[ReviewComment]
@app.get("/health")
def health_check():
"""Health check endpoint."""
return {
"status": "healthy",
"service": "AI Code Review Service",
"model_loaded": False, # No model in simple version
"message": "Simple version - returns mock reviews"
}
@app.post("/review", response_model=ReviewResponse)
def review_diff(request: DiffRequest):
"""
Mock review endpoint that returns sample comments.
Replace this with actual AI logic once the Space is working.
"""
logger.info("Received diff for review (length: %d chars)", len(request.diff))
# Mock review comments
mock_comments = [
{
"file_path": "example.py",
"line_number": 1,
"comment_text": "Consider adding docstrings to improve code documentation."
},
{
"file_path": "example.py",
"line_number": 5,
"comment_text": "This function could benefit from error handling."
}
]
logger.info("Returning %d mock review comments", len(mock_comments))
return ReviewResponse(comments=mock_comments)
if __name__ == "__main__":
import uvicorn
uvicorn.run(app, host="0.0.0.0", port=7860)
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