> ## Documentation Index
> Fetch the complete documentation index at: https://mintlify.com/Arize-ai/openinference/llms.txt
> Use this file to discover all available pages before exploring further.

# Mistral AI

> Python auto-instrumentation for Mistral AI SDK

Python autoinstrumentation library for MistralAI's Python SDK.

The traces emitted by this instrumentation are fully OpenTelemetry compatible and can be sent to an OpenTelemetry collector for viewing, such as [Arize Phoenix](https://github.com/Arize-ai/phoenix).

## Installation

```bash theme={null}
pip install openinference-instrumentation-mistralai
```

## Quickstart

This example shows how to instrument a program that uses the MistralAI chat completions API and observe the traces via [Arize Phoenix](https://github.com/Arize-ai/phoenix).

Install packages:

```bash theme={null}
pip install openinference-instrumentation-mistralai mistralai arize-phoenix opentelemetry-sdk opentelemetry-exporter-otlp
```

### Start Phoenix server

Start the phoenix server so that it is ready to collect traces. The Phoenix server runs entirely on your machine and does not send data over the internet.

```bash theme={null}
python -m phoenix.server.main serve
```

### Setup instrumentation

In a python file, setup the `MistralAIInstrumentor` and configure the tracer to send traces to Phoenix:

```python theme={null}
from mistralai.client import MistralClient
from mistralai.models.chat_completion import ChatMessage
from openinference.instrumentation.mistralai import MistralAIInstrumentor
from opentelemetry import trace as trace_api
from opentelemetry.exporter.otlp.proto.http.trace_exporter import OTLPSpanExporter
from opentelemetry.sdk import trace as trace_sdk
from opentelemetry.sdk.trace.export import ConsoleSpanExporter, SimpleSpanProcessor

endpoint = "http://127.0.0.1:6006/v1/traces"
tracer_provider = trace_sdk.TracerProvider()
tracer_provider.add_span_processor(SimpleSpanProcessor(OTLPSpanExporter(endpoint)))
# Optionally, you can also print the spans to the console.
tracer_provider.add_span_processor(SimpleSpanProcessor(ConsoleSpanExporter()))
trace_api.set_tracer_provider(tracer_provider)

MistralAIInstrumentor().instrument()


if __name__ == "__main__":
    client = MistralClient()
    response = client.chat(
        model="mistral-large-latest",
        messages=[
            ChatMessage(
                content="Who won the World Cup in 2018?",
                role="user",
            )
        ],
    )
    print(response.choices[0].message.content)
```

### Set API key

Set the `MISTRAL_API_KEY` environment variable to authenticate with the MistralAI API:

```bash theme={null}
export MISTRAL_API_KEY=[your_key_here]
```

### Run your application

```bash theme={null}
python your_file.py
```

Visit the Phoenix app at `http://localhost:6006` to see your traces.

## More Info

* [OpenInference and Phoenix documentation](https://docs.arize.com/phoenix)
* [How to customize spans to track sessions, metadata, etc.](https://github.com/Arize-ai/openinference/tree/main/python/openinference-instrumentation#customizing-spans)
* [How to account for private information and span payload customization](https://github.com/Arize-ai/openinference/tree/main/python/openinference-instrumentation#tracing-configuration)
* [PyPI package](https://pypi.org/project/openinference-instrumentation-mistralai/)