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Portfolio Assistant - FastAPI backend

Python FastAPI Groq Render

A small RAG-style backend for the "ask about Ankit" chat widget on the portfolio site. Currently a simple prompt + static-context implementation (see context.py) - no vector DB yet. Upgrade to real retrieval later if the content outgrows a single context file.

Run locally

cd backend
python -m venv venv
source venv/bin/activate        # Windows: venv\\Scripts\\activate
pip install -r requirements.txt
cp .env.example .env            # then fill in GROQ_API_KEY
uvicorn main:app --reload --port 8000

Test it:

curl -X POST http://localhost:8000/chat \
  -H "Content-Type: application/json" \
  -d '{"message": "What has Ankit built with LangGraph?"}'

Deploy (Render)

  1. Push this repo (or just the backend/ folder as its own repo) to GitHub.
  2. On Render: New → Web Service → connect the repo.
  3. Root directory: backend (if backend lives inside the main portfolio repo).
  4. Build command: pip install -r requirements.txt
  5. Start command: uvicorn main:app --host 0.0.0.0 --port $PORT
  6. Add environment variables: GROQ_API_KEY, FRONTEND_URL (your Vercel URL).
  7. Once deployed, set RAG_API_URL in the Next.js project's environment variables (on Vercel) to this Render service's URL.

Note on cold starts

Render's free tier spins down after inactivity - the first request after idle can take several seconds. The chat widget on the frontend already accounts for this with a "waking up…" state.