Azure OpenAI Assistants file search tool - not working for azure gpt-4o.

Question

I am trying to use Azure OpenAI Assistants file search tool using deployed gpt-4o model in azure but i do face below error, Error code: 400 - {'error': {'message': "Invalid value: 'file_search'. Supported values are: 'code_interpreter', 'function', and 'retrieval'.", 'type': 'invalid_request_error', 'param': 'tools[0].type', 'code': 'invalid_value'}}

But the same works if I directly use gpt-4o model from OpenAI instance.
What could be the solution for this?

Answer 1

@Rakesh Amman I also tested it from my end and it worked just fine in East US region. I am sharing the sample code for your reference:

# Import necessary libraries
from openai import AzureOpenAI
import os

# Initialize the Azure OpenAI client
client = AzureOpenAI(
    api_key= "48b4fXXXXXXXXX393664",
    api_version="2024-05-01-preview",
    azure_endpoint= "https://XXXXXXX.openai.azure.com/"
)

# Create the assistant with the file_search tool
assistant = client.beta.assistants.create(
    name="Financial Analyst Assistant",
    instructions="You are an expert financial analyst. Use your knowledge base to answer questions about audited financial statements.",
    model="gpt4o",
    tools=[{"type": "file_search"}]
)

# Create a vector store called "Financial Statements"
vector_store = client.beta.vector_stores.create(name="Financial Statements")

# Ready the files for upload to OpenAI
file_paths = ["mydirectory/myfile1.pdf", "mydirectory/myfile2.txt"]
file_streams = [open(path, "rb") for path in file_paths]

# Use the upload and poll SDK helper to upload the files, add them to the vector store,
# and poll the status of the file batch for completion
file_batch = client.beta.vector_stores.file_batches.upload_and_poll(
    vector_store_id=vector_store.id, files=file_streams
)

# Print the status and the file counts of the batch to see the result of this operation
print(file_batch.status)
print(file_batch.file_counts)

# Upload the user-provided file to OpenAI
message_file = client.files.create(
    file=open("mydirectory/myfile1.pdf", "rb"), purpose="assistants"
)

# Create a thread and attach the file to the message
thread = client.beta.threads.create(
    messages=[
        {
            "role": "user",
            "content": "How many company shares were outstanding last quarter?",
            # Attach the new file to the message
            "attachments": [
                {"file_id": message_file.id, "tools": [{"type": "file_search"}]}
            ],
        }
    ]
)

# The thread now has a vector store with that file in its tool resources
print(thread.tool_resources.file_search)