litellm/docs/my-website/docs/observability/raw_request_response.md

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Raw Request/Response Logging

Logging

See the raw request/response sent by LiteLLM in your logging provider (OTEL/Langfuse/etc.).

# pip install langfuse 
import litellm
import os

# log raw request/response
litellm.log_raw_request_response = True

# from https://cloud.langfuse.com/
os.environ["LANGFUSE_PUBLIC_KEY"] = ""
os.environ["LANGFUSE_SECRET_KEY"] = ""
# Optional, defaults to https://cloud.langfuse.com
os.environ["LANGFUSE_HOST"] # optional

# LLM API Keys
os.environ['OPENAI_API_KEY']=""

# set langfuse as a callback, litellm will send the data to langfuse
litellm.success_callback = ["langfuse"] 
 
# openai call
response = litellm.completion(
  model="gpt-3.5-turbo",
  messages=[
    {"role": "user", "content": "Hi 👋 - i'm openai"}
  ]
)

litellm_settings:
  log_raw_request_response: True

Expected Log

<Image img={require('../../img/raw_request_log.png')}/>

Return Raw Response Headers

Return raw response headers from llm provider.

Currently only supported for openai.

import litellm
import os

litellm.return_response_headers = True

## set ENV variables
os.environ["OPENAI_API_KEY"] = "your-api-key"

response = litellm.completion(
  model="gpt-3.5-turbo",
  messages=[{ "content": "Hello, how are you?","role": "user"}]
)

print(response._hidden_params)

1. Setup config.yaml

model_list:
  - model_name: gpt-3.5-turbo
    litellm_params:
      model: gpt-3.5-turbo
      api_key: os.environ/GROQ_API_KEY

litellm_settings:
  return_response_headers: true

2. Test it!

curl -X POST 'http://0.0.0.0:4000/chat/completions' \
-H 'Content-Type: application/json' \
-H 'Authorization: Bearer sk-1234' \
-D '{
    "model": "gpt-3.5-turbo",
    "messages": [
        { "role": "system", "content": "Use your tools smartly"},
        { "role": "user", "content": "What time is it now? Use your tool"}
    ]
}'

Expected Response

<Image img={require('../../img/raw_response_headers.png')}/>