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(docs) langfuse callback litellm

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ishaan-jaff 2023-11-18 14:52:24 -08:00
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@ -105,18 +105,19 @@ print(response)
``` ```
## Logging Observability ([Docs](https://docs.litellm.ai/docs/observability/callbacks)) ## Logging Observability ([Docs](https://docs.litellm.ai/docs/observability/callbacks))
LiteLLM exposes pre defined callbacks to send data to LLMonitor, Langfuse, Helicone, Promptlayer, Traceloop, Slack LiteLLM exposes pre defined callbacks to send data to Langfuse, LLMonitor, Helicone, Promptlayer, Traceloop, Slack
```python ```python
from litellm import completion from litellm import completion
## set env variables for logging tools ## set env variables for logging tools
os.environ["PROMPTLAYER_API_KEY"] = "your-promptlayer-key" os.environ["LANGFUSE_PUBLIC_KEY"] = ""
os.environ["LANGFUSE_SECRET_KEY"] = ""
os.environ["LLMONITOR_APP_ID"] = "your-llmonitor-app-id" os.environ["LLMONITOR_APP_ID"] = "your-llmonitor-app-id"
os.environ["OPENAI_API_KEY"] os.environ["OPENAI_API_KEY"]
# set callbacks # set callbacks
litellm.success_callback = ["promptlayer", "llmonitor"] # log input/output to promptlayer, llmonitor, supabase litellm.success_callback = ["langfuse", "llmonitor"] # log input/output to langfuse, llmonitor, supabase
#openai call #openai call
response = completion(model="gpt-3.5-turbo", messages=[{"role": "user", "content": "Hi 👋 - i'm openai"}]) response = completion(model="gpt-3.5-turbo", messages=[{"role": "user", "content": "Hi 👋 - i'm openai"}])