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Langsmith - Logging LLM Input/Output

An all-in-one developer platform for every step of the application lifecycle https://smith.langchain.com/

info

We want to learn how we can make the callbacks better! Meet the LiteLLM founders or join our discord

Pre-Requisites

pip install litellm

Quick Start

Use just 2 lines of code, to instantly log your responses across all providers with Langsmith

litellm.success_callback = ["langsmith"]
import litellm
import os

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

# set langsmith as a callback, litellm will send the data to langsmith
litellm.success_callback = ["langsmith"]

# openai call
response = litellm.completion(
model="gpt-3.5-turbo",
messages=[
{"role": "user", "content": "Hi 👋 - i'm openai"}
]
)

Advanced

Set Custom Project & Run names

import litellm
import os

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

# set langfuse as a callback, litellm will send the data to langfuse
litellm.success_callback = ["langfuse"]

response = litellm.completion(
model="gpt-3.5-turbo",
messages=[
{"role": "user", "content": "Hi 👋 - i'm openai"}
],
metadata={
"run_name": "litellmRUN", # langsmith run name
"project_name": "litellm-completion", # langsmith project name
}
)
print(response)

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