Image Search with CocoIndex (v1)

This example builds an image search index with CLIP embeddings and Qdrant, then queries it with natural language.

We appreciate a star ⭐ at CocoIndex Github if this is helpful.

Technologies

• CocoIndex v1 app pipeline
• CLIP ViT-L/14 for embeddings
• Qdrant for vector storage

Setup

• Install Postgres if you don't have one.

• Make sure Qdrant is running

  Copy

  docker run -d -p 6334:6334 -p 6333:6333 qdrant/qdrant
  

Run (CLI)

Install dependencies:

pip install -e .

Build/update the index:

cocoindex update main.py

Query:

python main.py query "a red car"

Frontend (optional)

If you want a UI, start the FastAPI wrapper and the frontend:

python -m uvicorn api:app --reload --host 0.0.0.0 --port 8000

Then in another terminal:

cd frontend
npm install
npm run dev

Then open http://localhost:5173.