| Name | openinference-instrumentation-mistralai JSON |
| Version |
1.1.2
JSON |
| download |
| home_page | None |
| Summary | OpenInference Mistral AI Instrumentation |
| upload_time | 2025-02-05 22:24:25 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | <3.14,>=3.9 |
| license | None |
| keywords |
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| VCS |
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| bugtrack_url |
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| requirements |
No requirements were recorded.
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# OpenInference Mistral AI Instrumentation
[](https://pypi.python.org/pypi/openinference-instrumentation-mistralai)
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
```shell
pip install openinference-instrumentation-mistralai
```
## Quickstart
In this example we will instrument a small program that uses the MistralAI chat completions API and observe the traces via [`arize-phoenix`](https://github.com/Arize-ai/phoenix).
Install packages.
```shell
pip install openinference-instrumentation-mistralai mistralai arize-phoenix opentelemetry-sdk opentelemetry-exporter-otlp
```
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.
```shell
python -m phoenix.server.main serve
```
In a python file, setup the `MistralAIInstrumentor` and configure the tracer to send traces to Phoenix.
```python
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)
```
Since we are using MistralAI, we must set the `MISTRAL_API_KEY` environment variable to authenticate with the MistralAI API.
```shell
export MISTRAL_API_KEY=[your_key_here]
```
Now simply run the python file and observe the traces in Phoenix.
```shell
python your_file.py
```
## More Info
* [More info on OpenInference and Phoenix](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)
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"description": "# OpenInference Mistral AI Instrumentation\n[](https://pypi.python.org/pypi/openinference-instrumentation-mistralai) \n\nPython autoinstrumentation library for MistralAI's Python SDK.\n\nThe 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)\n\n## Installation\n\n```shell\npip install openinference-instrumentation-mistralai\n```\n\n## Quickstart\n\nIn this example we will instrument a small program that uses the MistralAI chat completions API and observe the traces via [`arize-phoenix`](https://github.com/Arize-ai/phoenix).\n\nInstall packages.\n\n```shell\npip install openinference-instrumentation-mistralai mistralai arize-phoenix opentelemetry-sdk opentelemetry-exporter-otlp\n```\n\nStart the phoenix server so that it is ready to collect traces.\nThe Phoenix server runs entirely on your machine and does not send data over the internet.\n\n```shell\npython -m phoenix.server.main serve\n```\n\nIn a python file, setup the `MistralAIInstrumentor` and configure the tracer to send traces to Phoenix.\n\n```python\nfrom mistralai.client import MistralClient\nfrom mistralai.models.chat_completion import ChatMessage\nfrom openinference.instrumentation.mistralai import MistralAIInstrumentor\nfrom opentelemetry import trace as trace_api\nfrom opentelemetry.exporter.otlp.proto.http.trace_exporter import OTLPSpanExporter\nfrom opentelemetry.sdk import trace as trace_sdk\nfrom opentelemetry.sdk.trace.export import ConsoleSpanExporter, SimpleSpanProcessor\n\nendpoint = \"http://127.0.0.1:6006/v1/traces\"\ntracer_provider = trace_sdk.TracerProvider()\ntracer_provider.add_span_processor(SimpleSpanProcessor(OTLPSpanExporter(endpoint)))\n# Optionally, you can also print the spans to the console.\ntracer_provider.add_span_processor(SimpleSpanProcessor(ConsoleSpanExporter()))\ntrace_api.set_tracer_provider(tracer_provider)\n\nMistralAIInstrumentor().instrument()\n\n\nif __name__ == \"__main__\":\n client = MistralClient()\n response = client.chat(\n model=\"mistral-large-latest\",\n messages=[\n ChatMessage(\n content=\"Who won the World Cup in 2018?\",\n role=\"user\",\n )\n ],\n )\n print(response.choices[0].message.content)\n\n```\n\nSince we are using MistralAI, we must set the `MISTRAL_API_KEY` environment variable to authenticate with the MistralAI API.\n\n```shell\nexport MISTRAL_API_KEY=[your_key_here]\n```\n\nNow simply run the python file and observe the traces in Phoenix.\n\n```shell\npython your_file.py\n```\n\n## More Info\n\n* [More info on OpenInference and Phoenix](https://docs.arize.com/phoenix)\n* [How to customize spans to track sessions, metadata, etc.](https://github.com/Arize-ai/openinference/tree/main/python/openinference-instrumentation#customizing-spans)\n* [How to account for private information and span payload customization](https://github.com/Arize-ai/openinference/tree/main/python/openinference-instrumentation#tracing-configuration)\n",
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