Expose an HTTP LLM API client for OpenAI-compatible chat completions and embeddings.
npx skills add https://github.com/copilot-ld/copilot-ld --skill libllm
Please help me install this Agent Skill. Skill: libllm Source: https://github.com/copilot-ld/copilot-ld/tree/main/packages/libllm Command: npx skills add https://github.com/copilot-ld/copilot-ld --skill libllm
Provides a dedicated LLM API client that communicates directly with OpenAI-compatible endpoints to perform chat completions and generate embeddings, simplifying integration in AI-powered apps.
Instantiate an LlmApi client with your token and base URLs, then call completion() or embed() to start interacting with your LLM.
High-intent search queries and answers about installing and using this skill.
You can connect to OpenAI-compatible LLM endpoints by instantiating an HTTP LLM API client with your token and base URLs to run chat completions and generate embeddings.
Yes, the LLM API client supports GitHub Models, Azure OpenAI, and standard OpenAI endpoints for chat completions and text embeddings across different AI service providers.
Streaming responses and token counting are built into the chat completions process, allowing you to handle real-time LLM outputs and track context window usage efficiently.
Reliable LLM integration requires implementing retry logic, proxy support, and robust error handling within your HTTP API client to manage network failures and rate limits.
Multi-tool parallel call handling enables complex agent workflows by allowing the LLM client to process multiple tool outputs simultaneously during chat completions.
Yes, the client generates text embeddings via HTTP, enabling vector-based retrieval systems and knowledge-base querying for AI-powered production applications.
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