Can't upload file through API

Question

I'm trying to upload files to Azure for fine-tuning, but I'm getting resource not available error.
I know that the client I creates is fine, because I tested it with the chat option. For example, if I run the following using my client:

client.chat.completions.create(
    messages=[{"content": "What is the weather like today?", "role": "user"}], model="gpt-4o"
)

It will work fine, but when I try to run a command to upload a file:

client.files.create(file=open("messages/train_messages.jsonl", "rb"), purpose="fine-tune")

It gives me an error: NotFoundError: Error code: 404 - {'error': {'code': '404', 'message': 'Resource not found'}}

Answer 1

@Zandarashvili, Levani Welcome to Microsoft Q&A Forum, Thank you for posting your query here!

.

I was able to make this work at my end. I used the below sample code for the client.files.create:

# Import necessary libraries
from openai import AzureOpenAI
import os

# Initialize the Azure OpenAI client
client = AzureOpenAI(
    api_key= "48bXXXXXXX3664",
    api_version="2024-08-01-preview",
    azure_endpoint = "https://XXXXX.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 = [r"C:\acs_paas\mydirectory\myfile1.pdf", r"C:\acs_paas\mydirectory\myfile2.pdf"]
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(r"C:\acs_paas\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)

vector_store_ids = thread.tool_resources.file_search.vector_store_ids


# Update the assistant with the correct vector_store_ids
assistant123 = client.beta.assistants.update(
    assistant_id=assistant.id,
    description="test",
    instructions="You are an expert financial analyst. Use your knowledge base to answer questions about audited financial statements.",
    tools=[{
        "type": "file_search",
        "file_search": {
            "max_num_results": 5,
            "ranking_options": {
                "score_threshold": 0.6
            }
        }
    }],
    tool_resources={"file_search": {"vector_store_ids": vector_store_ids}},
    temperature=0.00001,
    model="gpt4o"
)

.

Action Plan:

• Try with api-version: 2024-08-01-preview
• Ensure that you have given the correct model name in your code.
• Try with my above sample and check if that helps.

.

Hope this helps. If you have any follow-up questions, please let me know. I would be happy to help.