curl -X PUT https://api.example.com/api/knowledge/settings \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "projectId": "proj_123",
    "settings": {
      "vectorstoreProvider": "pinecone",
      "vectorStoreConfig": {
        "apiKey": "pc-xxxxxxxxxxxxx",
        "environment": "us-east-1",
        "indexName": "my-index"
      },
      "embeddingModel": "text-embedding-3-small",
      "chunkSize": 512,
      "chunkOverlap": 50,
      "searchType": "semantic",
      "topK": 5,
      "minScore": 0.7
    }
  }'

const response = await fetch('https://api.example.com/api/knowledge/settings', {
  method: 'PUT',
  headers: {
    'Authorization': 'Bearer YOUR_API_KEY',
    'Content-Type': 'application/json'
  },
  body: JSON.stringify({
    projectId: 'proj_123',
    settings: {
      vectorstoreProvider: 'pinecone',
      vectorStoreConfig: {
        apiKey: 'pc-xxxxxxxxxxxxx',
        environment: 'us-east-1',
        indexName: 'my-index'
      },
      embeddingModel: 'text-embedding-3-small',
      chunkSize: 512,
      chunkOverlap: 50,
      searchType: 'semantic',
      topK: 5,
      minScore: 0.7
    }
  })
});

const data = await response.json();

import requests

response = requests.put(
    'https://api.example.com/api/knowledge/settings',
    headers={
        'Authorization': 'Bearer YOUR_API_KEY',
        'Content-Type': 'application/json'
    },
    json={
        'projectId': 'proj_123',
        'settings': {
            'vectorstoreProvider': 'pinecone',
            'vectorStoreConfig': {
                'apiKey': 'pc-xxxxxxxxxxxxx',
                'environment': 'us-east-1',
                'indexName': 'my-index'
            },
            'embeddingModel': 'text-embedding-3-small',
            'chunkSize': 512,
            'chunkOverlap': 50,
            'searchType': 'semantic',
            'topK': 5,
            'minScore': 0.7
        }
    }
)

data = response.json()

{
  "success": true,
  "message": "RAG settings updated successfully"
}

{
  "success": false,
  "message": "Invalid vectorstore configuration: API key is required"
}