File size: 1,768 Bytes
63bcd5a 41bd215 63bcd5a 41bd215 63bcd5a | 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 | # api/main.py
from fastapi import FastAPI, HTTPException
from fastapi.middleware.cors import CORSMiddleware
from api.schemas import AnalyzeRequest, ChatRequest, ChatResponse
from api.services import analyze_project, chat_with_llm
# =====================================================
# Create App
# =====================================================
app = FastAPI(
title="Graduation Project Similarity API",
version="1.0.0",
description="AI system for project similarity and originality detection"
)
# =====================================================
# CORS
# =====================================================
app.add_middleware(
CORSMiddleware,
allow_origins=["*"],
allow_credentials=True,
allow_methods=["*"],
allow_headers=["*"],
)
# =====================================================
# Routes
# =====================================================
@app.get("/")
def home():
return {
"message": "API is running successfully"
}
@app.get("/health")
def health():
return {
"status": "healthy"
}
@app.post("/analyze")
def analyze(data: AnalyzeRequest):
try:
result = analyze_project(
title=data.title,
description=data.description,
abstract=data.abstract,
features=data.features,
top_k=data.top_k
)
return result
except HTTPException:
raise
except Exception as exc:
raise HTTPException(
status_code=500,
detail=f"Analysis failed: {exc}"
)
@app.post("/chat", response_model=ChatResponse)
def chat(data: ChatRequest):
result = chat_with_llm(
user_id=data.user_id,
message=data.message
)
return result
|