How can I reuse a single assistant instance across multiple Streamlit sessions using the Python OpenAI SDK?

Below is an approach that leverages the OpenAI API's beta endpoint for listing assistants. Instead of creating a new assistant on every new session, you can query for existing assistants and select one based on your criteria. For example, you might use the listing capability to check if an assistant already exists before creating a new one.

Below is a sample code snippet that uses the Python OpenAI SDK:

PYTHONCopied
import openai

# Set your API key
openai.api_key = "YOUR_API_KEY"

def list_existing_assistants(limit=20, order="desc"):
    # Lists assistants using the beta endpoint.
    response = openai.Assistant.list(limit=limit, order=order)
    return response.get("data", [])

def get_assistant_by_name(name, assistants):
    # Searches through the list of assistants for a matching name.
    for assistant in assistants:
        if assistant.get("name") == name:
            return assistant
    return None

def create_or_get_assistant(name):
    # List current assistants
    assistants = list_existing_assistants()
    assistant = get_assistant_by_name(name, assistants)
    
    if assistant:
        print(f"Found existing assistant: {assistant['id']} with name {name}")
        return assistant
    else:
        # Create a new assistant if one with the given name doesn't exist.
        assistant = openai.Assistant.create(
            name=name,
            instructions="Your custom instructions here",
            model="gpt-4o"
            # Provide additional parameters as required.
        )
        print(f"Created new assistant: {assistant['id']} with name {name}")
        return assistant

# Example usage:
assistant = create_or_get_assistant("Assistant1")

Explanation

• Listing Assistants:
  The function list_existing_assistants() uses the SDK’s list method to query for available assistants. You can control the number of results and the sort order using query parameters like limit and order.

• Selecting an Assistant:
  Once the list is retrieved, the get_assistant_by_name() function looks for an assistant with the desired name. This allows you to reuse an existing assistant if found.

• Creating a New Assistant:
  If the assistant is not found, the code creates a new one with the required parameters.

Additional Considerations

• Session Persistence:
  Even though listing assistants avoids duplicating creations per session, you may also consider persisting the assistant ID in a shared resource (like a database or file) or via Streamlit’s caching mechanism if your application design allows it.

• Beta Endpoint:
  Note that the listing endpoint for assistants is in beta. Future changes may require you to adjust how you interact with it (e.g., additional parameters or response format changes). Check the latest OpenAI API documentation for updates.

This pattern helps ensure you efficiently manage your assistants without unnecessarily creating new instances on every new session.