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feat: feat: add tracer for Mistral AI
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‎examples/tracing/mistral/mistral_tracing.ipynb

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{
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"cells": [
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{
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"cell_type": "markdown",
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"id": "2722b419",
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"metadata": {},
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"source": [
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"[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/openlayer-ai/openlayer-python/blob/main/examples/tracing/mistral/mistral_tracing.ipynb)\n",
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"\n",
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"\n",
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"# <a id=\"top\">Mistral AI tracing</a>\n",
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"\n",
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"This notebook illustrates how to get started tracing Mistral LLMs with Openlayer."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "020c8f6a",
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"metadata": {},
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"outputs": [],
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"source": [
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"!pip install mistralai openlayer"
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]
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},
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{
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"cell_type": "markdown",
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"id": "75c2a473",
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"metadata": {},
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"source": [
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"## 1. Set the environment variables"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "f3f4fa13",
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"metadata": {},
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"outputs": [],
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"source": [
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"import os\n",
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"\n",
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"# Openlayer env variables\n",
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"os.environ[\"OPENLAYER_API_KEY\"] = \"YOUR_OPENLAYER_API_KEY_HERE\"\n",
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"os.environ[\"OPENLAYER_INFERENCE_PIPELINE_ID\"] = \"YOUR_OPENLAYER_INFERENCE_PIPELINE_ID_HERE\""
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]
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},
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{
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"cell_type": "markdown",
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"id": "9758533f",
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"metadata": {},
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"source": [
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"## 2. Import the `trace_mistral` function"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "c35d9860-dc41-4f7c-8d69-cc2ac7e5e485",
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"metadata": {},
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"outputs": [],
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"source": [
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"import mistralai\n",
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"from openlayer.lib import trace_mistral\n",
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"\n",
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"mistral_client = trace_mistral(mistralai.Mistral(api_key=\"YOUR_MISTRAL_AI_API_KEY_HERE\"))"
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]
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},
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{
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"cell_type": "markdown",
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"id": "72a6b954",
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"metadata": {},
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"source": [
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"## 3. Use the traced Mistral AI client normally"
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]
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},
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{
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"cell_type": "markdown",
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"id": "76a350b4",
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"metadata": {},
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"source": [
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"That's it! Now you can continue using the traced Mistral AI client normally. The data is automatically published to Openlayer and you can start creating tests around it!"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "e00c1c79",
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"metadata": {},
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"outputs": [],
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"source": [
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"response = mistral_client.chat.complete(\n",
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" model=\"mistral-large-latest\",\n",
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" messages = [\n",
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" {\n",
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" \"role\": \"user\",\n",
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" \"content\": \"What is the best French cheese?\",\n",
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" },\n",
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" ]\n",
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")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "d5093b5b-539c-4119-b5d3-dda6524edaa9",
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"metadata": {},
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"outputs": [],
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"source": [
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"stream_response = mistral_client.chat.stream(\n",
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" model = \"mistral-large-latest\",\n",
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" messages = [\n",
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" {\n",
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" \"role\": \"user\",\n",
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" \"content\": \"What's the meaning of life?\",\n",
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" },\n",
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" ]\n",
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")\n",
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"\n",
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"for chunk in stream_response:\n",
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" print(chunk.data.choices[0].delta.content)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "2654f47f-fadd-4142-b185-4d992a30c46a",
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"metadata": {},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3 (ipykernel)",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.9.19"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}

‎src/openlayer/lib/__init__.py

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"""Openlayer lib.
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"""
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__all__ = [
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"trace",
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"trace_anthropic",
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"trace_openai",
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"trace_openai_assistant_thread_run",
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]
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__all__ = ["trace", "trace_anthropic", "trace_openai", "trace_openai_assistant_thread_run", "trace_mistral"]
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# ---------------------------------- Tracing --------------------------------- #
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from .tracing import tracer
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from .integrations import openai_tracer
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return openai_tracer.trace_openai_assistant_thread_run(client, run)
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def trace_mistral(client):
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"""Trace Mistral chat completions."""
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# pylint: disable=import-outside-toplevel
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import mistralai
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from .integrations import mistral_tracer
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if not isinstance(client, mistralai.Mistral):
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raise ValueError("Invalid client. Please provide a Mistral client.")
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return mistral_tracer.trace_mistral(client)

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