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import os
import json
from typing import List, Dict, Any, Optional
from datetime import datetime
from fastapi import FastAPI, HTTPException, BackgroundTasks, Depends, Query
from fastapi.middleware.cors import CORSMiddleware
from pydantic import BaseModel
from fastapi.staticfiles import StaticFiles
from fastapi.responses import FileResponse
from buffalo_rag.scraper.scraper import BuffaloScraper
from buffalo_rag.embeddings.chunker import DocumentChunker
from buffalo_rag.vector_store.db import VectorStore
from buffalo_rag.model.rag import BuffaloRAG
from buffalo_rag.api.background_tasks import run_scraper, refresh_index
# Initialize FastAPI app
app = FastAPI(
title="BuffaloRAG API",
description="API for BuffaloRAG - AI Assistant for International Students at University at Buffalo",
version="1.0.0"
)
# Add CORS middleware
app.add_middleware(
CORSMiddleware,
allow_origins=["*"],
allow_credentials=True,
allow_methods=["*"],
allow_headers=["*"],
)
# Initialize components
vector_store = VectorStore()
rag = BuffaloRAG(vector_store=vector_store)
# Pydantic models
class QueryRequest(BaseModel):
query: str
k: int = 5
categories: Optional[List[str]] = None
class QueryResponse(BaseModel):
query: str
response: str
sources: List[Dict[str, Any]]
timestamp: str
class ScrapeRequest(BaseModel):
seed_url: str = "https://www.buffalo.edu/international-student-services.html"
max_pages: int = 100
class ScrapeResponse(BaseModel):
status: str
message: str
# Setup static files directory
static_dir = os.path.join(os.path.dirname(__file__), "static")
os.makedirs(static_dir, exist_ok=True)
# Add this after creating the FastAPI app
app.mount("/static", StaticFiles(directory=static_dir), name="static")
# API endpoints
@app.post("/api/ask", response_model=QueryResponse)
async def ask(request: QueryRequest):
"""Ask a question to the RAG system."""
try:
response = rag.answer(
query=request.query,
k=request.k,
filter_categories=request.categories
)
# Add timestamp
response['timestamp'] = datetime.now().isoformat()
# Log the query for analytics
with open("data/query_log.jsonl", "a") as f:
f.write(json.dumps(response) + "\n")
return response
except Exception as e:
raise HTTPException(status_code=500, detail=str(e))
@app.post("/api/scrape", response_model=ScrapeResponse)
async def scrape(request: ScrapeRequest, background_tasks: BackgroundTasks):
"""Trigger web scraping."""
try:
background_tasks.add_task(run_scraper, request.seed_url, request.max_pages)
return {
"status": "success",
"message": f"Started scraping from {request.seed_url} (max {request.max_pages} pages)"
}
except Exception as e:
raise HTTPException(status_code=500, detail=str(e))
@app.post("/api/refresh-index", response_model=ScrapeResponse)
async def refresh(background_tasks: BackgroundTasks):
"""Refresh the vector index."""
try:
background_tasks.add_task(refresh_index)
return {
"status": "success",
"message": "Started refreshing the vector index"
}
except Exception as e:
raise HTTPException(status_code=500, detail=str(e))
# Add a route to serve the React app
@app.get("/", include_in_schema=False)
async def serve_frontend():
return FileResponse(os.path.join(static_dir, "index.html"))
@app.get("/{path:path}", include_in_schema=False)
async def serve_frontend_paths(path: str):
# First check if the file exists in static directory
file_path = os.path.join(static_dir, path)
if os.path.isfile(file_path):
return FileResponse(file_path)
# Otherwise, return index.html for client-side routing
return FileResponse(os.path.join(static_dir, "index.html"))
# Run the API server
if __name__ == "__main__":
import uvicorn
uvicorn.run("buffalo_rag.api.main:app", host="localhost", port=8000, reload=True) |