generateContent method does not support simultaneous assignment of functionDeclarations and googleSearchRetrieval object

[indiejoseph]

The generateContent method of vertexAI.preview.getGenerativeModel in the API is currently unable to assign both functionDeclarations and googleSearchRetrieval object arguments simultaneously. When attempting to utilize both arguments in a single API call, the response is a ClientError with the following message:

ClientError: [VertexAI.ClientError]: got status: 400 Bad Request. {"error":{"code":400,"message":"Request contains an invalid argument.","status":"INVALID_ARGUMENT"}}

Steps to Reproduce:

Make a request to the generateContent method of vertexAI.preview.getGenerativeModel.
Provide values for both the functionDeclarations and googleSearchRetrieval arguments.
Observe the returned ClientError response with the specified error message.

const contents = [
  {
    "role": "user",
    "parts": [
      {
        "text": "How is the weather today in New York?"
      }
    ]
  }
];
const tools = [
  {
    "googleSearchRetrieval": {
      "disableAttribution": false
    }
  },
  {
    "functionDeclarations": [
      {
        "name": "get_current_weather",
        "description": "get weather in a given location",
        "parameters": {
          "type": "OBJECT",
          "properties": {
            "location": {
              "type": "STRING"
            }
          },
          "required": [
            "location"
          ]
        }
      }
    ]
  }
];

await generateModel.generateContent(contents, tools)

// ClientError: [VertexAI.ClientError]: got status: 400 Bad Request. {"error":{"code":400,"message":"Request contains an invalid argument.","status":"INVALID_ARGUMENT"}}

Expected Behavior:

The generateContent method should allow the assignment of both functionDeclarations and googleSearchRetrieval object arguments in the same API call without triggering a ClientError. The API response should provide the expected generative content based on the combined functionality of both arguments.

[yyyu-google]

Hi,
I have tested the use case this way, and it worked. See details

const {VertexAI} = require('@google-cloud/vertexai');
const vertexai = new VertexAI({project: 'your project'});
model = vertexai.getGenerativeModel({model: 'gemini-1.5-flash'})
async function run() {
  response = await model.generateContent(
    {
      contents: [
        {
          "parts": [
            {
              "text": "What is this image about?"
            }
          ],
          "role": "user"
        },
        {
          "parts": [
            {
              "inlineData": {
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                "mime_type": "image/jpeg"
              }
            }
          ],
          "role": "user"
        }
      ],
      tools: [
        {
          "functionDeclarations": [
            {
              "parameters": {
                "type": "OBJECT",
                "properties": {
                  "city": {
                    "type": "STRING"
                  }
                }
              },
              "name": "get_weather"
            }
          ]
        }
      ]
    }
  )
  console.log(JSON.stringify(response))
}
run();

Results

{"response":{"candidates":[{"content":{"role":"model","parts":[{"text":"The image is the Google logo. It is a stylized wordmark featuring the word \"Google\" in a sans-serif typeface. The letters are colored in blue, red, yellow, and green."}]},"finishReason":"STOP","safetyRatings":[{"category":"HARM_CATEGORY_HATE_SPEECH","probability":"NEGLIGIBLE","probabilityScore":0.036865234,"severity":"HARM_SEVERITY_NEGLIGIBLE","severityScore":0.052734375},{"category":"HARM_CATEGORY_DANGEROUS_CONTENT","probability":"NEGLIGIBLE","probabilityScore":0.075683594,"severity":"HARM_SEVERITY_NEGLIGIBLE","severityScore":0.17675781},{"category":"HARM_CATEGORY_HARASSMENT","probability":"NEGLIGIBLE","probabilityScore":0.057373047,"severity":"HARM_SEVERITY_NEGLIGIBLE","severityScore":0.053466797},{"category":"HARM_CATEGORY_SEXUALLY_EXPLICIT","probability":"NEGLIGIBLE","probabilityScore":0.046142578,"severity":"HARM_SEVERITY_NEGLIGIBLE","severityScore":0.040771484}],"avgLogprobs":-0.2553135395050049,"index":0}],"usageMetadata":{"promptTokenCount":268,"candidatesTokenCount":40,"totalTokenCount":308},"modelVersion":"gemini-1.5-flash"}}

Could you replace the project id with yours and try if this works?
Thanks