Our data science division is building a completely disconnected infrastructure due to strict privacy mandates. We need to access API documentation for popular large language model services that run locally on our own hardware, such as Ollama, LocalAI, or vLLM. Where can we find their API routes, OpenAI-compatible endpoint configurations, and hardware optimization docs?
3 answers
For self-hosted deployments, the API documentation is typically maintained directly within the official GitHub repositories of the open-source projects. For instance, Ollama’s complete API specification is located under the 'docs' folder in their main GitHub repository, outlining endpoints like /api/generate and /api/chat. For high-throughput engines like vLLM, they host an independent documentation site at docs.vllm.ai, which details their OpenAI-compatible server wrappers, allowing your data science tools to seamlessly substitute local endpoints.
Does your data science workflow require explicit documentation for embedding generation endpoints, or are you solely focused on text generation and conversational completion APIs for this local setup?
Look into the vLLM engine documentation regarding their integration with Triton Inference Server if you need extreme production-grade scaling for your local endpoints.
Excellent suggestion, Louis. Triton adds a robust layer of model management. Checking those specific documentation sections will help us optimize our local GPU clusters as our data science workloads expand.
We actually need comprehensive documentation for both systems. We are building a localized retrieval-augmented generation pipeline, so having clear documentation on the embedding API schemas is crucial for vectorizing our internal documents before sending the text fragments into the generation engine.