skills/conductor/examples/workflows/llm-rag.json

{
  "name": "rag_qa",
  "description": "Retrieval-augmented Q&A: vector search then LLM answer with context",
  "version": 1,
  "schemaVersion": 2,
  "inputParameters": ["question"],
  "tasks": [
    {
      "name": "search_knowledge_base",
      "taskReferenceName": "search",
      "type": "LLM_SEARCH_INDEX",
      "inputParameters": {
        "vectorDB": "postgres-prod",
        "namespace": "kb",
        "index": "articles",
        "embeddingModelProvider": "openai",
        "embeddingModel": "text-embedding-3-small",
        "query": "${workflow.input.question}",
        "llmMaxResults": 3
      }
    },
    {
      "name": "generate_answer",
      "taskReferenceName": "answer",
      "type": "LLM_CHAT_COMPLETE",
      "inputParameters": {
        "llmProvider": "anthropic",
        "model": "claude-sonnet-4-6",
        "messages": [
          {
            "role": "system",
            "message": "Answer using only the context below. If the answer isn't in the context, say \"I don't know.\"\n\nContext:\n${search.output.result}"
          },
          {
            "role": "user",
            "message": "${workflow.input.question}"
          }
        ],
        "temperature": 0.2,
        "maxTokens": 500
      }
    }
  ],
  "outputParameters": {
    "answer": "${answer.output.result}",
    "sources": "${search.output.result}",
    "tokensUsed": "${answer.output.tokenUsed}"
  }
}