Chat Format

Format prompts for different LLM providers with chat templates and HNSW-powered context retrieval

majiayu000 f46b81f 2 files · 1.8 KB Updated 567 repo stars

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Chat Format

Format prompts for multi-provider LLM inference with context retrieval.

When to use

When preparing prompts for different LLM providers (Claude, GPT, Gemini, Ollama) or building RAG pipelines with HNSW-powered context retrieval.

Steps

  1. Format chat — call mcp__claude-flow__ruvllm_chat_format with messages and target provider
  2. Create HNSW index — call mcp__claude-flow__ruvllm_hnsw_create for context retrieval
  3. Add documents — call mcp__claude-flow__ruvllm_hnsw_add to index documents
  4. Route query — call mcp__claude-flow__ruvllm_hnsw_route to find relevant context
  5. Check status — call mcp__claude-flow__ruvllm_status for provider availability

Supported providers

  • Anthropic (Claude) — native format
  • OpenAI (GPT) — chat completion format
  • Google (Gemini) — generative AI format
  • Ollama — local model format
  • Cohere — generate/chat format

majiayu000/claude-skill-registry-data/tree/main/ai-llm/chat-format commit f46b81f385

Frequently asked questions

npx skillmds add majiayu000/chat-format