Callbacks
Use Callbacks to send Output Data to Posthog, Sentry etcβ
liteLLM provides input_callbacks, success_callbacks and failure_callbacks, making it easy for you to send data to a particular provider depending on the status of your responses.
tip
New to LiteLLM Callbacks?
- For proxy/server logging and observability, see the Proxy Logging Guide.
- To write your own callback logic, see the Custom Callbacks Guide.
Supported Callback Integrationsβ
This is not an extensive list. Please check the dropdown for all logging integrations.
Related Cookbooksβ
Try out our cookbooks for code snippets and interactive demos:
- Langfuse Callback Example (Colab)
- Lunary Callback Example (Colab)
- Arize Callback Example (Colab)
- Proxy + Langfuse Callback Example (Colab)
- PromptLayer Callback Example (Colab)
Quick Startβ
from litellm import completion
# set callbacks
litellm.input_callback=["sentry"] # for sentry breadcrumbing - logs the input being sent to the api
litellm.success_callback=["posthog", "helicone", "langfuse", "lunary", "athina"]
litellm.failure_callback=["sentry", "lunary", "langfuse"]
## set env variables
os.environ['LUNARY_PUBLIC_KEY'] = ""
os.environ['SENTRY_DSN'], os.environ['SENTRY_API_TRACE_RATE']= ""
os.environ['POSTHOG_API_KEY'], os.environ['POSTHOG_API_URL'] = "api-key", "api-url"
os.environ["HELICONE_API_KEY"] = ""
os.environ["TRACELOOP_API_KEY"] = ""
os.environ["LUNARY_PUBLIC_KEY"] = ""
os.environ["ATHINA_API_KEY"] = ""
os.environ["LANGFUSE_PUBLIC_KEY"] = ""
os.environ["LANGFUSE_SECRET_KEY"] = ""
os.environ["LANGFUSE_HOST"] = ""
response = completion(model="gpt-3.5-turbo", messages=messages)