--- title: "Session Logs" url: "/docs/proxy/ui_logs_sessions" canonical_url: "https://docs.litellm.ai/docs/proxy/ui_logs_sessions" type: "docs" last_updated: "2026-10-10" summary: "Group requests into sessions. This allows you to group related requests together." related: - "/docs/proxy/ui_spend_log_settings" - "/docs/proxy/deleted_keys_teams" --- # Session Logs > Index of all LiteLLM docs: https://docs.litellm.ai/llms.txt Group requests into sessions. This allows you to group related requests together. ## Usage ### `/chat/completions` To group multiple requests into a single session, pass the same `litellm_session_id` in the metadata for each request. Here's how to do it: **OpenAI Python v1.0.0+** **Request 1** Create a new session with a unique ID and make the first request. The session ID will be used to track all related requests. ```python showLineNumbers import openai import uuid # Create a session ID session_id = str(uuid.uuid4()) client = openai.OpenAI( api_key="", base_url="http://0.0.0.0:4000" ) # First request in session response1 = client.chat.completions.create( model="gpt-5.6-terra", messages=[ { "role": "user", "content": "Write a short story about a robot" } ], extra_body={ "litellm_session_id": session_id # Pass the session ID } ) ``` **Request 2** Make another request using the same session ID to link it with the previous request. This allows tracking related requests together. ```python showLineNumbers # Second request using same session ID response2 = client.chat.completions.create( model="gpt-5.6-terra", messages=[ { "role": "user", "content": "Now write a poem about that robot" } ], extra_body={ "litellm_session_id": session_id # Reuse the same session ID } ) ``` **Langchain** **Request 1** Initialize a new session with a unique ID and create a chat model instance for making requests. The session ID is embedded in the model's configuration. ```python showLineNumbers from langchain.chat_models import ChatOpenAI import uuid # Create a session ID session_id = str(uuid.uuid4()) chat = ChatOpenAI( openai_api_base="http://0.0.0.0:4000", api_key="", model="gpt-5.6-terra", extra_body={ "litellm_session_id": session_id # Pass the session ID } ) # First request in session response1 = chat.invoke("Write a short story about a robot") ``` **Request 2** Use the same chat model instance to make another request, automatically maintaining the session context through the previously configured session ID. ```python showLineNumbers # Second request using same chat object and session ID response2 = chat.invoke("Now write a poem about that robot") ``` **Curl** **Request 1** Generate a new session ID and make the initial API call. The session ID in the metadata will be used to track this conversation. ```bash showLineNumbers # Create a session ID SESSION_ID=$(uuidgen) # Store your API key API_KEY="" # First request in session curl --location 'http://0.0.0.0:4000/chat/completions' \ --header 'Content-Type: application/json' \ --header "Authorization: Bearer $API_KEY" \ --data '{ "model": "gpt-5.6-terra", "messages": [ { "role": "user", "content": "Write a short story about a robot" } ], "litellm_session_id": "'$SESSION_ID'" }' ``` **Request 2** Make a follow-up request using the same session ID to maintain conversation context and tracking. ```bash showLineNumbers # Second request using same session ID curl --location 'http://0.0.0.0:4000/chat/completions' \ --header 'Content-Type: application/json' \ --header "Authorization: Bearer $API_KEY" \ --data '{ "model": "gpt-5.6-terra", "messages": [ { "role": "user", "content": "Now write a poem about that robot" } ], "litellm_session_id": "'$SESSION_ID'" }' ``` **LiteLLM Python SDK** **Request 1** Start a new session by creating a unique ID and making the initial request. This session ID will be used to group related requests together. ```python showLineNumbers import litellm import uuid # Create a session ID session_id = str(uuid.uuid4()) # First request in session response1 = litellm.completion( model="gpt-5.6-terra", messages=[{"role": "user", "content": "Write a short story about a robot"}], api_base="http://0.0.0.0:4000", api_key="", metadata={ "litellm_session_id": session_id # Pass the session ID } ) ``` **Request 2** Continue the conversation by making another request with the same session ID, linking it to the previous interaction. ```python showLineNumbers # Second request using same session ID response2 = litellm.completion( model="gpt-5.6-terra", messages=[{"role": "user", "content": "Now write a poem about that robot"}], api_base="http://0.0.0.0:4000", api_key="", metadata={ "litellm_session_id": session_id # Reuse the same session ID } ) ``` ### `/responses` For the `/responses` endpoint, use `previous_response_id` to group requests into a session. The `previous_response_id` is returned in the response of each request. **OpenAI Python v1.0.0+** **Request 1** Make the initial request and store the response ID for linking follow-up requests. ```python showLineNumbers from openai import OpenAI client = OpenAI( api_key="", base_url="http://0.0.0.0:4000" ) # First request in session response1 = client.responses.create( model="anthropic/claude-sonnet-5", input="Write a short story about a robot" ) # Store the response ID for the next request response_id = response1.id ``` **Request 2** Make a follow-up request using the previous response ID to maintain the conversation context. ```python showLineNumbers # Second request using previous response ID response2 = client.responses.create( model="anthropic/claude-sonnet-5", input="Now write a poem about that robot", previous_response_id=response_id # Link to previous request ) ``` **Curl** **Request 1** Make the initial request. The response will include an ID that can be used to link follow-up requests. ```bash showLineNumbers # Store your API key API_KEY="" # First request in session curl http://localhost:4000/v1/responses \ --header 'Content-Type: application/json' \ --header "Authorization: Bearer $API_KEY" \ --data '{ "model": "anthropic/claude-sonnet-5", "input": "Write a short story about a robot" }' # Response will include an 'id' field that you'll use in the next request ``` **Request 2** Make a follow-up request using the previous response ID to maintain the conversation context. ```bash showLineNumbers # Second request using previous response ID curl http://localhost:4000/v1/responses \ --header 'Content-Type: application/json' \ --header "Authorization: Bearer $API_KEY" \ --data '{ "model": "anthropic/claude-sonnet-5", "input": "Now write a poem about that robot", "previous_response_id": "resp_abc123..." # Replace with actual response ID from previous request }' ``` **LiteLLM Python SDK** **Request 1** Make the initial request and store the response ID for linking follow-up requests. ```python showLineNumbers import litellm # First request in session response1 = litellm.responses( model="anthropic/claude-sonnet-5", input="Write a short story about a robot", api_base="http://0.0.0.0:4000", api_key="" ) # Store the response ID for the next request response_id = response1.id ``` **Request 2** Make a follow-up request using the previous response ID to maintain the conversation context. ```python showLineNumbers # Second request using previous response ID response2 = litellm.responses( model="anthropic/claude-sonnet-5", input="Now write a poem about that robot", api_base="http://0.0.0.0:4000", api_key="", previous_response_id=response_id # Link to previous request ) ``` ## Related pages - [UI Spend Log Settings](https://docs.litellm.ai/docs/proxy/ui_spend_log_settings.md) - [Deleted Keys & Teams Audit Logs](https://docs.litellm.ai/docs/proxy/deleted_keys_teams.md)