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Merge pull request Azure-Samples#100 from solbell2/main
Migration to the v1.X version of the Python openai library
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‎Basic_Samples/Completions/.gitignore‎

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# Ignore .env files
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.env
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# Ignore config.json file
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config.json

‎Basic_Samples/Completions/basic_completions_example_restapi.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": "759f9ec0",
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"metadata": {},
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"source": [
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"<h1 align =\"center\"> REST API Reference Samples</h1>\n",
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"<hr>\n",
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" \n",
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"# Create a Completion\n",
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" \n",
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"Given a prompt, the model will return one or more predicted completions, and can also return the probabilities of alternative tokens at each position."
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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": 1,
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"id": "f4b3d21a",
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"metadata": {},
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"outputs": [],
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"source": [
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"import json\n",
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"import os\n",
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"import openai\n",
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"import requests"
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]
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},
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{
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"cell_type": "markdown",
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"id": "5b2d4a0f",
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"metadata": {},
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"source": [
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"### Setup Parameters\n",
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"\n",
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"\n",
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"Here we will load the configurations from _config.json_ file to setup deployment_name, openai_api_base, openai_api_key and openai_api_version."
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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": 2,
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"id": "fd85fb30",
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"metadata": {},
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"outputs": [],
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"source": [
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"# Load config values\n",
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"with open(r'config.json') as config_file:\n",
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" config_details = json.load(config_file)\n",
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" \n",
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"# Setting up the deployment name\n",
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"deployment_name = config_details['COMPLETIONS_MODEL']\n",
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"\n",
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"# The base URL for your Azure OpenAI resource. e.g. \"https://<your resource name>.openai.azure.com\"\n",
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"openai_api_base = config_details['OPENAI_API_BASE']\n",
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"\n",
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"# The API key for your Azure OpenAI resource.\n",
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"openai_api_key = os.getenv(\"OPENAI_API_KEY\")\n",
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"\n",
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"# Currently OPENAI API have the following versions available: 2022-12-01. All versions follow the YYYY-MM-DD date structure.\n",
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"openai_api_version = config_details['OPENAI_API_VERSION']"
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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": 3,
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"id": "aef62557",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"\n",
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"\n",
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"Hello! Welcome to the world!\n"
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]
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}
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],
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"source": [
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"# Request URL\n",
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"api_url = f\"{openai_api_base}/openai/deployments/{deployment_name}/completions?api-version={openai_api_version}\"\n",
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"\n",
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"# Example prompt for request payload\n",
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"prompt = \"Hello world\"\n",
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"\n",
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"# Json payload\n",
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"# To know more about the parameters, checkout this documentation: https://learn.microsoft.com/en-us/azure/cognitive-services/openai/reference\n",
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"json_data = {\n",
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" \"prompt\": prompt,\n",
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" \"temperature\":0,\n",
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" \"max_tokens\": 30\n",
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"}\n",
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"\n",
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"# Including the api-key in HTTP headers\n",
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"headers = {\"api-key\": openai_api_key}\n",
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"\n",
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"try:\n",
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" # Request for creating a completion for the provided prompt and parameters\n",
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" response = requests.post(api_url, json=json_data, headers=headers)\n",
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" completion = response.json()\n",
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" \n",
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" # print the completion\n",
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" print(completion['choices'][0]['text'])\n",
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" \n",
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" # Here indicating if the response is filtered\n",
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" if completion['choices'][0]['finish_reason'] == \"content_filter\":\n",
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" print(\"The generated content is filtered.\")\n",
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"except:\n",
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" print(\"An exception has occurred. \\n\")\n",
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" print(\"Error Message:\", completion['error']['message'])"
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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": "b6165c63",
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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": "3.11.1"
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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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}
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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": "759f9ec0",
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"metadata": {},
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"source": [
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"<h1 align =\"center\"> REST API Reference Samples</h1>\n",
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"<hr>\n",
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" \n",
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"# Create a Completion\n",
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" \n",
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"Given a prompt, the model will return one or more predicted completions, and can also return the probabilities of alternative tokens at each position."
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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": 13,
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"id": "f4b3d21a",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"True"
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]
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},
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"execution_count": 13,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"import os\n",
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"import requests\n",
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"import dotenv\n",
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"\n",
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"dotenv.load_dotenv()\n"
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]
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},
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{
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"cell_type": "markdown",
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"id": "5b2d4a0f",
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"metadata": {},
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"source": [
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"### Setup Parameters\n",
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"\n",
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"\n",
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"Here we will load the configurations from an .env file to setup deployment_name, openai_api_base, openai_api_key and openai_api_version."
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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": 14,
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"id": "fd85fb30",
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"metadata": {},
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"outputs": [],
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"source": [
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"# Setting up the deployment name\n",
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"deployment_name = os.environ['COMPLETIONS_MODEL']\n",
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"\n",
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"# The base URL for your Azure OpenAI resource. e.g. \"https://<your resource name>.openai.azure.com\"\n",
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"openai_api_base = os.environ['AZURE_OPENAI_ENDPOINT']\n",
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"\n",
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"# The API key for your Azure OpenAI resource.\n",
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"openai_api_key = os.environ['AZURE_OPENAI_API_KEY']\n",
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"\n",
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"# Currently OPENAI API have the following versions available: https://learn.microsoft.com/azure/ai-services/openai/reference\n",
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"openai_api_version = os.environ['OPENAI_API_VERSION']"
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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": 19,
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"id": "aef62557",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"\n",
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"\n",
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"Hello! Welcome to the world!\n"
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]
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}
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],
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"source": [
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"# Request URL\n",
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"api_url = f\"{openai_api_base}/openai/deployments/{deployment_name}/completions?api-version={openai_api_version}\"\n",
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"\n",
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"# Example prompt for request payload\n",
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"prompt = \"Hello world\"\n",
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"\n",
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"# Json payload\n",
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"# To know more about the parameters, checkout this documentation: https://learn.microsoft.com/en-us/azure/cognitive-services/openai/reference\n",
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"json_data = {\n",
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" \"prompt\": prompt,\n",
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" \"temperature\": 0,\n",
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" \"max_tokens\": 30\n",
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"}\n",
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"\n",
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"# Including the api-key in HTTP headers\n",
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"headers = {\"api-key\": openai_api_key}\n",
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"\n",
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"try: \n",
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" # Request for creating a completion for the provided prompt and parameters\n",
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" response = requests.post(api_url, json=json_data, headers=headers)\n",
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"\n",
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" completion = response.json()\n",
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" \n",
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" # print the completion\n",
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" print(completion['choices'][0]['text'])\n",
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" \n",
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" # Here indicating if the response is filtered\n",
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" if completion['choices'][0]['finish_reason'] == \"content_filter\":\n",
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" print(\"The generated content is filtered.\")\n",
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"\n",
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"except:\n",
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" print(\"An exception has occurred. \\n\")\n"
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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": "b6165c63",
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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": "3.11.5"
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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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}

‎Basic_Samples/Completions/config.json‎

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‎Basic_Samples/Completions/requirements.txt‎

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jsonpointer==2.3
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jsonschema==4.17.3
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openai==0.27.2
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openai==1.11.1
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tiktoken==0.3.1

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