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Skillintermediate
Callbacks
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.
Claude Code Knowledge Pack7/10/2026
Overview
Callbacks
Use Callbacks to send Output Data to Posthog, Sentry etc
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 Integrations
This is not an extensive list. Please check the dropdown for all logging integrations.
Related Cookbooks
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 Start
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)