Completes OPEN-5863 Client should have notebook example for using azure gpt

Author: gustavocidornelas

examples/monitoring/llms/azure-openai/azure_openai_llm_monitor.ipynb

@@ -0,0 +1,157 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "2722b419",
+   "metadata": {},
+   "source": [
+    "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/openlayer-ai/examples-gallery/blob/main/monitoring/llms/azure-openai/azure_openai_llm_monitor.ipynb)\n",
+    "\n",
+    "\n",
+    "# <a id=\"top\">Azure OpenAI LLM monitoring quickstart</a>\n",
+    "\n",
+    "This notebook illustrates how to get started monitoring Azure OpenAI LLMs with Openlayer."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "020c8f6a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "!pip install openlayer"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "75c2a473",
+   "metadata": {},
+   "source": [
+    "## 1. Set the environment variables"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "f3f4fa13",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import os\n",
+    "import openai\n",
+    "\n",
+    "# Azure OpenAI env variables\n",
+    "os.environ[\"ENDPOINT\"] = \"YOUR_AZURE_OPENAI_ENDPOINT_HERE\"\n",
+    "os.environ[\"AZURE_API_KEY\"] = \"YOUR_AZURE_OPENAI_API_KEY_HERE\"\n",
+    "os.environ[\"DEPLOYMENT_NAME\"] = \"YOUR_AZURE_OPENAI_DEPLOYMENT_NAME_HERE\"\n",
+    "\n",
+    "# Openlayer env variables\n",
+    "os.environ[\"OPENLAYER_API_KEY\"] = \"YOUR_OPENLAYER_API_KEY_HERE\"\n",
+    "os.environ[\"OPENLAYER_PROJECT_NAME\"] = \"YOUR_OPENLAYER_PROJECT_NAME_HERE\" "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "9758533f",
+   "metadata": {},
+   "source": [
+    "## 2. Instantiate the monitor"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "e60584fa",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<openlayer.llm_monitors.AzureOpenAIMonitor at 0x7f8758d3abe0>"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "from openlayer import llm_monitors\n",
+    "\n",
+    "from openai import AzureOpenAI\n",
+    "    \n",
+    "azure_client = AzureOpenAI(\n",
+    "    api_key=os.environ.get(\"AZURE_API_KEY\"),  \n",
+    "    api_version=\"2024-02-01\",\n",
+    "    azure_endpoint=os.environ.get(\"ENDPOINT\"),\n",
+    ")\n",
+    "\n",
+    "llm_monitors.AzureOpenAIMonitor(client=azure_client)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "72a6b954",
+   "metadata": {},
+   "source": [
+    "## 3. Use your monitored Azure OpenAI client normally"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "76a350b4",
+   "metadata": {},
+   "source": [
+    "That's it! Now you can continue using Azure OpenAI LLMs normally. The data is automatically published to Openlayer and you can start creating tests around it!"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "e00c1c79",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "completion = azure_client.chat.completions.create(\n",
+    "    model=os.environ.get(\"DEPLOYMENT_NAME\"),\n",
+    "    messages=[\n",
+    "        {\"role\": \"system\", \"content\": \"You are a helpful assistant.\"},\n",
+    "        {\"role\": \"user\", \"content\": \"How are you doing today?\"},\n",
+    "        {\"role\": \"assistant\", \"content\": \"Pretty well! How about you?\"},\n",
+    "        {\"role\": \"user\", \"content\": \"I am doing well, but would like some words of encouragement.\"},\n",
+    "    ]\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "abaf6987-c257-4f0d-96e7-3739b24c7206",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.9.18"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

openlayer/llm_monitors.py

@@ -493,6 +493,8 @@ def thread_messages_to_prompt(
 
 
 class AzureOpenAIMonitor(OpenAIMonitor):
+    """Monitor inferences from Azure OpenAI LLMs and upload traces to Openlayer."""
+
     def __init__(
         self,
         client=None,

openlayer/model_runners/ll_model_runners.py

@@ -390,6 +390,7 @@ def _initialize_llm(self):
         """Initializes Cohere's Generate model."""
         # Check if API key is valid -- Cohere's validation seems to be very shallow
         try:
+            # pylint: disable=unexpected-keyword-arg
             self.cohere_client = cohere.Client(
                 api_key=self.cohere_api_key, check_api_key=True
             )