Does this require a real OpenAI API key?

No. While the OpenAI Python library requires an API key string to initialize, Ollama ignores the value. You can use a placeholder like 'ollama' for all local requests.

Which OpenAI endpoints are supported through Ollama?

The compatibility layer supports /v1/models for listing, /v1/completions for text generation, /v1/chat/completions for chat, and /v1/embeddings for vector generation.

How do I switch from GPT-4 to a local model?

You simply update the client base_url to point to your local Ollama host and change the 'model' parameter in your code to a local model name like 'llama3.2'.

Can I use this with LangChain and LlamaIndex?

Yes, this is one of the primary benefits. By setting the base_url to your local Ollama instance, you can use the standard OpenAI classes provided by these frameworks.

OpenAI Compatibility for Ollama

Name: OpenAI Compatibility for Ollama
Author: atrawog

byatrawog

Ciencia de Datos y ML

Integrates Ollama with the OpenAI Python library to enable seamless migration and compatibility with OpenAI-based tools.

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This skill provides a standardized OpenAI-compatible interface for local Ollama instances, allowing developers to use the official OpenAI SDK, LangChain, and LlamaIndex without rewriting core application logic. By mapping Ollama endpoints to the standard /v1/* format, it facilitates an easy transition between proprietary and local models while maintaining access to familiar implementation patterns for completions, chat, and embeddings.

Características Principales

0 GitHub stars
Full support for chat completions and text generation endpoints
Seamless integration with LangChain and LlamaIndex frameworks
Simplified migration path from cloud APIs to local LLM infrastructure
Local embedding generation using OpenAI-standard request formats
Drop-in OpenAI SDK replacement for local Ollama models

Casos de Uso

Prototyping AI workflows locally using the familiar OpenAI Python library syntax
Migrating an existing OpenAI-powered application to a local Ollama backend for privacy or cost savings
Using popular AI frameworks like LangChain or LlamaIndex with local models without writing custom adapters

Acerca de

Características Principales

0 GitHub stars
Full support for chat completions and text generation endpoints
Seamless integration with LangChain and LlamaIndex frameworks
Simplified migration path from cloud APIs to local LLM infrastructure
Local embedding generation using OpenAI-standard request formats
Drop-in OpenAI SDK replacement for local Ollama models

Casos de Uso

Prototyping AI workflows locally using the familiar OpenAI Python library syntax
Migrating an existing OpenAI-powered application to a local Ollama backend for privacy or cost savings
Using popular AI frameworks like LangChain or LlamaIndex with local models without writing custom adapters