Observability for Mistral AI with Honeycomb

OpenLLMetry lets you trace any of the open-source Mistral models. With 5 minutes of work you can get complete view of your system directly into Honeycomb. See how below.

Step 1

Install the Traceloop SDK and initialize it. It will automatically log all calls to Mistral AI, with prompts and completions as separate spans.

from mistralai.client import MistralClient
from mistralai.models.chat_completion import ChatMessage
from traceloop.sdk import Traceloop
from traceloop.sdk.decorators import workflow

Traceloop.init(app_name="joke_generation_service")

client = MistralClient(api_key=os.environ["MISTRAL_API_KEY"])

@workflow(name="joke_creation")
def create_joke():
    response = client.chat(
        model="mistral-tiny",
        messages=[
            ChatMessage(role="user", content="Tell me a joke about OpenTelemetry"),
        ],
    )

    return response.choices[0].message.content

Step 2

Route the traces to Honeycomb’s endpoint and set the API key

TRACELOOP_BASE_URL=https://api.honeycomb.io
TRACELOOP_HEADERS="x-honeycomb-team=<YOUR_API_KEY>"

Docs

Observability for Mistral AI with Honeycomb

Step 1

Step 2

Discover use cases

More things you can connect to {platform}

Anthropic

LangChain

LlamaIndex

Gemini

Ollama

OpenAI

Bedrock

together.ai

Cohere

Watsonx

Chroma