Observability for Mistral AI with Datadog

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 Datadog. 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

Configure your Datadog agent to receive traces from OpenLLMetry

# In your values.yaml
otlp:
  receiver:
    protocols:
      http:
        enabled: true
        
# In the environment of your application
TRACELOOP_BASE_URL=http://datadog-agent-hostname:4318

Docs

Observability for Mistral AI with Datadog

Step 1

Step 2

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