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‎Basic_Samples/Completions/basic_completions_example_sdk.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": "011db2ec",
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"metadata": {},
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"source": [
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"<h1 align =\"center\"> Python SDK 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": "a92744f4",
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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 openai\n",
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"import os"
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]
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},
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{
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"cell_type": "markdown",
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"id": "e1966c51",
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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": "19ae1e36",
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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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"# This is set to `azure`\n",
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"openai.api_type = \"azure\"\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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"# 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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"# Currently OPENAI API have the following versions available: 2022-12-01\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": "b15862a1",
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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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"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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"# Give your prompt here\n",
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"prompt = \"Hello world\"\n",
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"\n",
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"try:\n",
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" # Create a completion for the provided prompt and parameters\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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" completion = openai.Completion.create(\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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" engine=deployment_name)\n",
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"\n",
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" # print the completion\n",
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" print(completion.choices[0].text.strip(\" \\n\"))\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 openai.error.APIError as e:\n",
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" # Handle API error here, e.g. retry or log\n",
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" print(f\"OpenAI API returned an API Error: {e}\")\n",
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"\n",
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"except openai.error.AuthenticationError as e:\n",
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" # Handle Authentication error here, e.g. invalid API key\n",
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" print(f\"OpenAI API returned an Authentication Error: {e}\")\n",
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"\n",
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"except openai.error.APIConnectionError as e:\n",
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" # Handle connection error here\n",
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" print(f\"Failed to connect to OpenAI API: {e}\")\n",
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"\n",
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"except openai.error.InvalidRequestError as e:\n",
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" # Handle connection error here\n",
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" print(f\"Invalid Request Error: {e}\")\n",
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"\n",
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"except openai.error.RateLimitError as e:\n",
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" # Handle rate limit error\n",
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" print(f\"OpenAI API request exceeded rate limit: {e}\")\n",
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"\n",
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"except openai.error.ServiceUnavailableError as e:\n",
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" # Handle Service Unavailable error\n",
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" print(f\"Service Unavailable: {e}\")\n",
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"\n",
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"except openai.error.Timeout as e:\n",
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" # Handle request timeout\n",
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" print(f\"Request timed out: {e}\")"
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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": "b9be87b2",
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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": "011db2ec",
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"metadata": {},
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"source": [
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"<h1 align =\"center\"> Python SDK 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": "9d9a71de",
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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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"Requirement already satisfied: openai in c:\\users\\henna\\documents\\github\\openai\\venv312\\lib\\site-packages (1.13.3)\n",
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"Requirement already satisfied: python-dotenv in c:\\users\\henna\\documents\\github\\openai\\venv312\\lib\\site-packages (1.0.1)\n",
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"Requirement already satisfied: anyio<5,>=3.5.0 in c:\\users\\henna\\documents\\github\\openai\\venv312\\lib\\site-packages (from openai) (4.3.0)\n",
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"Requirement already satisfied: distro<2,>=1.7.0 in c:\\users\\henna\\documents\\github\\openai\\venv312\\lib\\site-packages (from openai) (1.9.0)\n",
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"Requirement already satisfied: httpx<1,>=0.23.0 in c:\\users\\henna\\documents\\github\\openai\\venv312\\lib\\site-packages (from openai) (0.27.0)\n",
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"Requirement already satisfied: pydantic<3,>=1.9.0 in c:\\users\\henna\\documents\\github\\openai\\venv312\\lib\\site-packages (from openai) (2.6.3)\n",
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"Requirement already satisfied: sniffio in c:\\users\\henna\\documents\\github\\openai\\venv312\\lib\\site-packages (from openai) (1.3.1)\n",
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"Requirement already satisfied: tqdm>4 in c:\\users\\henna\\documents\\github\\openai\\venv312\\lib\\site-packages (from openai) (4.66.2)\n",
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"Requirement already satisfied: typing-extensions<5,>=4.7 in c:\\users\\henna\\documents\\github\\openai\\venv312\\lib\\site-packages (from openai) (4.10.0)\n",
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"Requirement already satisfied: idna>=2.8 in c:\\users\\henna\\documents\\github\\openai\\venv312\\lib\\site-packages (from anyio<5,>=3.5.0->openai) (3.6)\n",
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"Requirement already satisfied: certifi in c:\\users\\henna\\documents\\github\\openai\\venv312\\lib\\site-packages (from httpx<1,>=0.23.0->openai) (2024.2.2)\n",
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"Requirement already satisfied: httpcore==1.* in c:\\users\\henna\\documents\\github\\openai\\venv312\\lib\\site-packages (from httpx<1,>=0.23.0->openai) (1.0.4)\n",
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"Requirement already satisfied: h11<0.15,>=0.13 in c:\\users\\henna\\documents\\github\\openai\\venv312\\lib\\site-packages (from httpcore==1.*->httpx<1,>=0.23.0->openai) (0.14.0)\n",
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"Requirement already satisfied: annotated-types>=0.4.0 in c:\\users\\henna\\documents\\github\\openai\\venv312\\lib\\site-packages (from pydantic<3,>=1.9.0->openai) (0.6.0)\n",
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"Requirement already satisfied: pydantic-core==2.16.3 in c:\\users\\henna\\documents\\github\\openai\\venv312\\lib\\site-packages (from pydantic<3,>=1.9.0->openai) (2.16.3)\n",
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"Requirement already satisfied: colorama in c:\\users\\henna\\documents\\github\\openai\\venv312\\lib\\site-packages (from tqdm>4->openai) (0.4.6)\n",
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"Note: you may need to restart the kernel to use updated packages.\n"
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]
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},
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"\n",
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"[notice] A new release of pip is available: 23.2.1 -> 24.0\n",
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"[notice] To update, run: python.exe -m pip install --upgrade pip\n"
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]
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}
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],
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"source": [
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"%pip install --upgrade openai python-dotenv"
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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": "a92744f4",
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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": 2,
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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 json\n",
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"from openai import AzureOpenAI\n",
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"import os\n",
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"import dotenv\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": "e1966c51",
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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": 3,
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"id": "19ae1e36",
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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 API key for your Azure OpenAI resource.\n",
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"api_key = os.environ[\"AZURE_OPENAI_API_KEY\"]\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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"azure_endpoint = os.environ['AZURE_OPENAI_ENDPOINT']\n",
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"\n",
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"# Currently OPENAI API have the following versions available: 2022-12-01\n",
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"api_version = os.environ['OPENAI_API_VERSION']\n",
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"\n",
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"client = AzureOpenAI(\n",
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" api_key = api_key, \n",
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" azure_endpoint = azure_endpoint,\n",
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" api_version = api_version\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": 4,
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"id": "b15862a1",
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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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"# def outer_func(original_string):\n",
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"# def inner_func(string):\n",
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"# nonlocal original\n"
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]
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}
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],
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"source": [
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"# Give your prompt here\n",
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"prompt = \"Hello world\"\n",
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"\n",
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" # Create a completion for the provided prompt and parameters\n",
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"try:\n",
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" completion = client.completions.create( \n",
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" model=deployment_name,\n",
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" prompt=prompt,\n",
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" max_tokens=20,\n",
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" )\n",
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"\n",
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" # Print the completion\n",
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" print(completion.choices[0].text.strip(\" \\n\"))\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 openai.AuthenticationError as e:\n",
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" # Handle Authentication error here, e.g. invalid API key\n",
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" print(f\"OpenAI API returned an Authentication Error: {e}\")\n",
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"\n",
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"except openai.APIConnectionError as e:\n",
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" # Handle connection error here\n",
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" print(f\"Failed to connect to OpenAI API: {e}\")\n",
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"\n",
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"except openai.BadRequestError as e:\n",
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" # Handle connection error here\n",
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" print(f\"Invalid Request Error: {e}\")\n",
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"\n",
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"except openai.RateLimitError as e:\n",
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" # Handle rate limit error\n",
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" print(f\"OpenAI API request exceeded rate limit: {e}\")\n",
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"\n",
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"except openai.InternalServerError as e:\n",
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" # Handle Service Unavailable error\n",
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" print(f\"Service Unavailable: {e}\")\n",
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"\n",
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"except openai.APITimeoutError as e:\n",
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" # Handle request timeout\n",
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" print(f\"Request timed out: {e}\")\n",
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"\n",
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"except openai.APIError as e:\n",
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" # Handle API error here, e.g. retry or log\n",
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" print(f\"OpenAI API returned an API Error: {e}\")"
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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": "b9be87b2",
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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": "3.12.1"
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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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