Ollama

API Commands

Interact with Ollama programmatically via REST API. Generate completions, chat, create embeddings, and manage models through HTTP endpoints.

7 commands

Pro Tips

Use streaming responses (stream: true) for better UX in chat applications.

The /api/embeddings endpoint works with any text model for vector search.

Ollama API is OpenAI-compatible - use /v1/chat/completions with existing SDKs.

Common Mistakes

API has no authentication by default - add reverse proxy for production use.

Large context windows increase memory usage and slow generation speed.

Commands

Generate completion

$ curl http://localhost:11434/api/generate -d '{"model": "llama2", "prompt": "Hello"}'

Generate text completion via REST API.

Chat completion

$ curl http://localhost:11434/api/chat -d '{"model": "llama2", "messages": [{"role": "user", "content": "Hi"}]}'

Multi-turn chat via REST API.

Generate embeddings

$ curl http://localhost:11434/api/embeddings -d '{"model": "llama2", "prompt": "text to embed"}'

Create vector embeddings for text.

Non-streaming response

$ curl http://localhost:11434/api/generate -d '{"model": "llama2", "prompt": "Hi", "stream": false}'

Get complete response without streaming.

List models via API

$ curl http://localhost:11434/api/tags

Get list of available models via REST.

OpenAI-compatible endpoint

$ curl http://localhost:11434/v1/chat/completions -d '{"model": "llama2", "messages": [{"role": "user", "content": "Hi"}]}'

Use OpenAI-compatible API format.

Set generation parameters

$ curl http://localhost:11434/api/generate -d '{"model": "llama2", "prompt": "Hi", "options": {"temperature": 0.7, "top_p": 0.9}}'

Configure sampling parameters in API call.