Formatage de prompts LLM avec contexte RAG

Formate des prompts pour différents fournisseurs LLM (Claude, GPT, Gemini, etc.) et utilise la recherche HNSW pour la récupération de contexte.

Spar Skills Guide Bot
Data & IAIntermédiaire
0029/08/2026
Claude Code
#prompt-formatting#llm#rag#hnsw#context-retrieval

Recommandé pour


name: chat-format description: Format prompts for different LLM providers with chat templates and HNSW-powered context retrieval argument-hint: "<prompt> [--provider anthropic|openai|gemini|ollama|cohere]" allowed-tools: mcp__plugin_ruflo-core_ruflo__ruvllm_chat_format mcp__plugin_ruflo-core_ruflo__ruvllm_hnsw_create mcp__plugin_ruflo-core_ruflo__ruvllm_hnsw_add mcp__plugin_ruflo-core_ruflo__ruvllm_hnsw_route mcp__plugin_ruflo-core_ruflo__ruvllm_status Bash

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
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