Remote Ollama Connection

[bradyd78]

What is the simplest way to connect to an Ollama model that requires auth remotely? I haven't been able to connect using the Ollama or APIRequest component. Are there any common mistakes I could be making with these components?

[dosubot[bot]]

Hi @bradyd78! I'm Dosu and I’m helping the langflow team.

To connect to a remote Ollama model that requires authentication using Langflow, you have two main options: the Ollama component or the APIRequest component. Here’s how to approach each, along with common pitfalls:

1. Ollama Component

• Set the base URL to your remote Ollama server (e.g., http://<remote-ip>:11434). If you’re running Langflow in Docker and Ollama on the host, use http://host.docker.internal:11434 instead of localhost to ensure connectivity between the container and host service [source].
• Make sure the Ollama server is running and accessible from the Langflow environment. Test the /api/tags endpoint directly (e.g., with curl http://<remote-ip>:11434/api/tags) to confirm it returns your models [source].
• If your Ollama instance requires authentication, ensure you provide the correct authentication headers. The Ollama component may not have a direct field for custom headers; if so, use the APIRequest component instead.
• If models do not appear in the dropdown, check if "tool mode" is enabled. This setting filters out models that don’t support tool calling. Disabling it will show all available models [source].

2. APIRequest Component

• Use this component for full control over authentication and HTTP headers.
• Enter the full URL to your Ollama endpoint.
• In the headers section, add your authentication header, for example: {"Authorization": "Bearer <your_token>"}. The component processes headers as key-value pairs and supports authentication headers [source].
• You can also paste a cURL command (with headers and body) into the cURL input field, and Langflow will parse it into the correct fields for you [source].
• The APIRequest component supports GET, POST, PATCH, PUT, and DELETE methods, and will handle errors and timeouts gracefully.

Common Mistakes

• Using localhost as the base URL when Langflow is running in Docker and Ollama is on the host—use host.docker.internal instead [source].
• Not providing authentication headers when required, or misconfiguring them in the APIRequest component.
• Forgetting to disable "tool mode" in the Ollama component, which hides models that don’t support tool calling [source].
• Not verifying that the Ollama API is reachable from the Langflow environment, or that the /api/tags endpoint returns the expected models.
• Not updating to the latest version of Langflow if you encounter issues with model lists not populating, as some bugs have been fixed in recent releases [source].

If you follow these steps and ensure your authentication headers are set correctly in the APIRequest component, you should be able to connect to a remote, authenticated Ollama model. If you still have trouble, double-check network/firewall settings and confirm that your Ollama server is accessible from the machine or container running Langflow.

To reply, just mention my name @dosu.

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