buffalo_rag/api/main.py

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

# 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

# Background tasks
def run_scraper(seed_url: str, max_pages: int):
    """Run the web scraper in the background."""
    scraper = BuffaloScraper(seed_url=seed_url)
    scraper.scrape(max_pages=max_pages)
    
    # After scraping, update the embeddings and index
    chunker = DocumentChunker()
    chunks = chunker.create_chunks()
    chunker.create_embeddings(chunks)
    
    # Reload the vector store
    global vector_store
    vector_store = VectorStore()
    
    # Update the RAG model
    global rag
    rag = BuffaloRAG(vector_store=vector_store)

def refresh_index():
    """Refresh the vector index in the background."""
    chunker = DocumentChunker()
    chunks = chunker.create_chunks()
    chunker.create_embeddings(chunks)
    
    # Reload the vector store
    global vector_store
    vector_store = VectorStore()
    
    # Update the RAG model
    global rag
    rag = BuffaloRAG(vector_store=vector_store)

# 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)