voyageai-cli/src/workflows/tests/research-and-summarize.happy-path.test.json

CLI for Voyage AI embeddings, reranking, and MongoDB Atlas Vector Search

{
  "name": "research-and-summarize: happy path",
  "inputs": {
    "question": "How does vector search work?",
    "limit": 5
  },
  "mocks": {
    "query": {
      "results": [
        { "text": "Vector search uses embeddings to find similar documents", "score": 0.95 },
        { "text": "Approximate nearest neighbor algorithms power vector search", "score": 0.88 }
      ],
      "resultCount": 2
    },
    "generate": {
      "text": "Vector search works by converting documents and queries into numerical embeddings and finding the closest matches using ANN algorithms.",
      "model": "claude-3-haiku",
      "tokensUsed": 120
    }
  },
  "expect": {
    "steps": {
      "research": { "status": "completed" },
      "summarize": { "status": "completed" }
    },
    "output": {
      "summary": { "type": "string", "minLength": 1 },
      "sources": { "type": "array", "minLength": 1 },
      "sourceCount": { "type": "number" }
    },
    "noErrors": true
  }
}