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Update buffalo_rag/api/main.py

7167a71 verified over 1 year ago

4.11 kB

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) 

	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)