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Add the Docs MCP to your AI coding tool to get help building with Respan. No API key needed.
{
  "mcpServers": {
    "respan-docs": {
      "url": "https://respan.ai/docs/mcp"
    }
  }
}
This integration supports the Respan gateway and callback logging.

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What is LiteLLM?

LiteLLM provides a unified Python interface for calling 100+ LLM providers using the OpenAI format. With Respan, you can either:
  • Gateway — route requests through Respan for observability, fallbacks, and load balancing
  • Logging — keep calling providers directly and export logs to Respan via a callback

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Quickstart

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Install packages

pip install litellm respan-exporter-litellm

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Gateway mode

Route LiteLLM requests through the Respan gateway. This gives you full access to Respan features like fallbacks, load balancing, and prompt management. 
import litellm

response = litellm.completion(
    api_key="YOUR_RESPAN_API_KEY",
    api_base="https://api.respan.ai/api",
    model="gpt-4o-mini",
    messages=[{"role": "user", "content": "Hello!"}],
)
print(response.choices[0].message.content)
LiteLLM gateway logging in Respan

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Logging mode

Register the Respan callback to log all completions automatically. Requests go directly to providers — only the logs are sent to Respan. 
import litellm
from respan_exporter_litellm import RespanLiteLLMCallback

litellm.callbacks = [RespanLiteLLMCallback()]

response = litellm.completion(
    model="gpt-4o-mini",
    messages=[{"role": "user", "content": "Hello!"}],
)
print(response.choices[0].message.content)
LiteLLM callback logging in Respan

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Supported parameters

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Gateway mode (extra_body)

Pass Respan parameters using extra_body when routing through the gateway. 
response = litellm.completion(
    api_key="YOUR_RESPAN_API_KEY",
    api_base="https://api.respan.ai/api",
    model="gpt-4o-mini",
    messages=[{"role": "user", "content": "Hello!"}],
    extra_body={
        "customer_identifier": "user-123",
        "metadata": {"session_id": "abc123"},
        "thread_identifier": "conversation_456",
    },
)

​
Logging mode (metadata)

Pass Respan parameters inside metadata.respan_params. 
response = litellm.completion(
    model="gpt-4o-mini",
    messages=[{"role": "user", "content": "Hello!"}],
    metadata={
        "respan_params": {
            "workflow_name": "simple_logging",
            "span_name": "single_log",
            "customer_identifier": "user-123",
        }
    },
)

​
Configuration

ParameterTypeDefaultDescription
api_keystrRESPAN_API_KEY env varRespan API key.
base_urlstr | NoneNoneAPI base URL.
See the LiteLLM Exporter SDK reference for the full API.

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Async usage

The callback supports async completions automatically: 
import litellm
from respan_exporter_litellm import RespanLiteLLMCallback

litellm.callbacks = [RespanLiteLLMCallback()]

response = await litellm.acompletion(
    model="gpt-4o-mini",
    messages=[{"role": "user", "content": "Tell me a joke"}],
)

​
Multiple providers

LiteLLM’s unified interface means all providers are logged with the same callback: 
import litellm
from respan_exporter_litellm import RespanLiteLLMCallback

litellm.callbacks = [RespanLiteLLMCallback()]

# OpenAI
litellm.completion(model="gpt-4o-mini", messages=[...])

# Anthropic
litellm.completion(model="claude-sonnet-4-5-20250929", messages=[...])

# Together
litellm.completion(model="together_ai/meta-llama/Llama-3-70b", messages=[...])

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Next Steps

User Management

Track user behavior and patterns

Prompt Management

Manage and version your prompts