🤖 assistant

My portfolio's AI backend. Completely useless to you. It only talks about me — and honestly, it does a better job of it than I do.

What is this

A RAG backend built with FastAPI that answers questions about Ignacio Figueroa.

Ask it about my projects → it answers. Ask it about the meaning of life → it tells you to contact me directly. Scope enforced at the prompt level, not by good faith.

Stack

Tool	Why
FastAPI	Because Flask is for people who haven't decided yet
Groq + Llama 3.3 70B	Replies faster than I do in a standup
pgvector + Neon	Vector search without running a database cluster in my apartment
HuggingFace Inference API	Embeddings without melting the server
uv	Dependency management from this century
Docker	"Works on my machine" — shipped

How it works

User asks something about Nacho
          ↓
Question converted to an embedding vector
          ↓
Cosine similarity search against Neon (pgvector)
          ↓
Most relevant context chunks injected into the prompt
          ↓
Groq streams the response token by token
          ↓
You know more about me than my own mother does

Endpoints

Method	Path	What it does
POST	/chat	Ask something about Nacho. Get an answer.
GET	/docs	Swagger UI — because we're professionals

Run locally

# Install dependencies
uv sync

# Start the server
uv run uvicorn main:app --reload

The server runs at http://localhost:8000 by default. Swagger UI at http://localhost:8000/docs — use it.

Environment variables

GROQ_API_KEY=
HUGGINGFACE_API_KEY=
DATABASE_URL=        # Neon connection string with pgvector enabled

License

MIT. Do whatever you want with it. Just don't ask the assistant for code — it'll redirect you to me, and I'm busy.