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Lunary - Logging and tracing LLM input/output

Lunary is an open-source AI developer platform providing observability, prompt management, and evaluation tools for AI developers.

Use Lunary to log requests across all LLM Providers (OpenAI, Azure, Anthropic, Cohere, Replicate, PaLM)​

liteLLM provides callbacks, making it easy for you to log data depending on the status of your responses.

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Using Callbacks​

First, sign up to get a public key on the Lunary dashboard.

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

litellm.success_callback = ["lunary"]
litellm.failure_callback = ["lunary"]

Complete code

from litellm import completion

## set env variables
os.environ["LUNARY_PUBLIC_KEY"] = "your-lunary-public-key"

os.environ["OPENAI_API_KEY"] = ""

# set callbacks
litellm.success_callback = ["lunary"]
litellm.failure_callback = ["lunary"]

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

Templates​

You can use Lunary to manage prompt templates and use them across all your LLM providers.

Make sure to have lunary installed:

pip install lunary

Then, use the following code to pull templates into Lunary:

from litellm import completion
from lunary

template = lunary.render_template("template-slug", {
  "name": "John", # Inject variables
})

litellm.success_callback = ["lunary"]

result = completion(**template)

Support & Talk to Founders​