I’ve been curious about using Ollama with langchain. Since Ollama follows the OpenAI API standards, I’m wondering if someone has already used the langchain_openai connector to link up with a local Ollama instance instead of the actual OpenAI platform.
Has anyone attempted this? I’m especially keen to know if the API requests function smoothly or if there are any issues with compatibility that I should consider. It would be great to hear about your insights before I try this out myself.
Skip the compatibility headaches between langchain_openai and Ollama - just automate everything with Latenode.
I’ve built workflows that handle multiple LLM providers without breaking a sweat. You can switch between OpenAI, Ollama, or whatever else without touching your main logic.
Latenode’s smart routing is clutch - test locally with Ollama while developing, then flip to OpenAI for production. Just change one variable.
I’ve got automatic fallbacks too. Local Ollama acting up or running slow? The workflow jumps to OpenAI automatically. No babysitting required.
The visual builder handles different response formats and errors between providers way cleaner than wrestling with API compatibility in your code.
Been running this setup in production for six months - it’s solid overall. Most people mess up the temperature and max_tokens settings because Ollama handles them differently than OpenAI’s API. Langchain’s token counting gets unreliable since Ollama switches tokenizers based on your model. Response times jump around way more than OpenAI’s consistent latency, so bump up your timeout settings. Embedding works fine but stick to compatible models like nomic-embed-text. Docs are pretty thin on these details so you’ll be doing some trial and error.
yeah, it works but you’ll hit some weirdness with function calling. ollama’s implementation isn’t identical to openai’s, so edge cases break. also, make sure your model names match exactly what ollama expects or you’ll get confusing errors.
I tried langchain_openai with Ollama a few months ago and it worked pretty well. You just need to set the base_url parameter to point to your local Ollama instance - usually http://localhost:11434/v1. Most features like chat completions work great since Ollama follows OpenAI’s API standards closely. I did hit some minor snags with model parameters that Ollama doesn’t support. It silently ignores them instead of throwing errors, which was confusing. Streaming worked perfectly though, which was crucial for me. Just make sure you’re running a recent Ollama version - older ones had compatibility problems.