Chat Format

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

ruvnet 65533c3 1.3 KB Updated

File contents

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__plugin_ruflo-core_ruflo__ruvllm_chat_format with messages and target provider
  2. Create HNSW index — call mcp__plugin_ruflo-core_ruflo__ruvllm_hnsw_create for context retrieval
  3. Add documents — call mcp__plugin_ruflo-core_ruflo__ruvllm_hnsw_add to index documents
  4. Route query — call mcp__plugin_ruflo-core_ruflo__ruvllm_hnsw_route to find relevant context
  5. Check status — call mcp__plugin_ruflo-core_ruflo__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

Source: ruvnet/rufloplugins/ruflo-ruvllm/skills/chat-format/SKILL.md

ruvnet/ruflo commit 65533c3758

Frequently asked questions

npx skillmds@latest add ruvnet/chat-format