OpenAI Passthrough

Pass-through endpoints for direct OpenAI API access

Overview

Available Endpoints

/openai_passthrough - Recommended

Dedicated passthrough endpoint that guarantees direct routing to OpenAI without conflicts.

Use this for:

• OpenAI Responses API (/v1/responses)
• Any endpoint where you need guaranteed passthrough
• When /openai routes are conflicting with LiteLLM's native implementations

/openai - Legacy

Standard passthrough endpoint that may conflict with LiteLLM's native implementations.

Note: Some endpoints like /openai/v1/responses will be routed to LiteLLM's native implementation instead of OpenAI.

When to use this?

• For 90% of your use cases, you should use the native LiteLLM OpenAI Integration (/chat/completions, /embeddings, /completions, /images, /batches, etc.)
• Use /openai_passthrough to call less popular or newer OpenAI endpoints that LiteLLM doesn't fully support yet, such as /assistants, /threads, /vector_stores, /responses

Simply replace https://api.openai.com with LITELLM_PROXY_BASE_URL/openai_passthrough

Usage Examples

Requirements: Set OPENAI_API_KEY in your environment variables.

Assistants API

Create OpenAI Client

Make sure you do the following:

• Point base_url to your LITELLM_PROXY_BASE_URL/openai
• Use your LITELLM_API_KEY as the api_key

client = openai.OpenAI(
    base_url="http://0.0.0.0:4000/openai_passthrough",  # <your-proxy-url>/openai_passthrough
    api_key="sk-anything"  # <your-proxy-api-key>
)

Create an Assistant

# Create an assistant
assistant = client.beta.assistants.create(
    name="Math Tutor",
    instructions="You are a math tutor. Help solve equations.",
    model="gpt-4o",
)

Create a Thread

# Create a thread
thread = client.beta.threads.create()

Add a Message to the Thread

# Add a message
message = client.beta.threads.messages.create(
    thread_id=thread.id,
    role="user",
    content="Solve 3x + 11 = 14",
)

Run the Assistant

# Create a run to get the assistant's response
run = client.beta.threads.runs.create(
    thread_id=thread.id,
    assistant_id=assistant.id,
)

# Check run status
run_status = client.beta.threads.runs.retrieve(
    thread_id=thread.id,
    run_id=run.id
)

Retrieve Messages

# List messages after the run completes
messages = client.beta.threads.messages.list(
    thread_id=thread.id
)

Delete the Assistant

# Delete the assistant when done
client.beta.assistants.delete(assistant.id)