🚀 Mini Vector Search Playground

A tiny FastAPI web app that ingests a CSV (id,text) and provides semantic search using vector embeddings.
Built for experimentation with OpenAI or Ollama models and backed by ChromaDB for persistence.

Perfect as a Hacktoberfest starter project 🎉

---

✨ Features

• Upload a CSV (id,text) → instantly indexed
• Search semantically with embeddings (GET /search?q=...)
• Switch provider at runtime:
  • openai (uses text-embedding-3-small by default)
  • ollama (runs on your own droplet)
• Simple browser UI + JSON API
• Lightweight persistence with ChromaDB

---

🛠 Quickstart (Local)

# 1. Clone repo
git clone https://github.com/<your-username>/mini-vector-search-playground.git
cd mini-vector-search-playground

# 2. Setup virtual env
python -m venv .venv && source .venv/bin/activate

# 3. Install deps
pip install -r requirements.txt

# 4. Configure environment
cp .env.example .env
# set EMBED_PROVIDER=openai or ollama
# set OPENAI_API_KEY if using OpenAI

# 5. Run server
uvicorn app.main:app --reload --port 8080