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Restored original basic_completions_example_sdk.ipynb
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‎.DS_Store‎

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‎Basic_Samples/.DS_Store‎

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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_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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{
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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": 1,
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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 openai\n",
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"import os\n",
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"import dotenv\n",
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"\n",
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"dotenv.load_dotenv()"
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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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"# Setting up the client\n",
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"client = openai.AzureOpenAI(\n",
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" api_key=os.environ['AZURE_OPENAI_API_KEY'],\n",
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" api_version=os.environ['OPENAI_API_VERSION'],\n",
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" azure_endpoint=os.environ['AZURE_OPENAI_ENDPOINT']\n",
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")\n",
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"\n",
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"# Setting up the deployment name\n",
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"deployment_name = os.environ['COMPLETIONS_MODEL']"
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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 = client.completions.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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" model=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.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.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.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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]
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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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}
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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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