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Merge pull request microsoft#202 from softchris/ch9-issue
adding dotnet lessons, also adding simpler notebooks for ch07 and ch0…
2 parents ec8af00 + 1e9c385 commit 2746eac

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‎06-text-generation-apps/app-recipe.py

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# engine
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engine = os.getenv("ENGINE")
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# deployment_id
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deployment_name = os.getenv("DEPLOYMENT_NAME")

‎07-building-chat-applications/dotnet/notebook-azure-openai.dib

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#!meta
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{"kernelInfo":{"defaultKernelName":"csharp","items":[{"aliases":[],"name":"csharp"}]}}
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#!csharp
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#r "nuget: Azure.AI.OpenAI, 1.0.0-beta.8"
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#!csharp
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using Azure;
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using Azure.AI.OpenAI;
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using static System.Environment;
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#!csharp
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string endpoint = "<replace with endpoint>";
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string key = "<replace with API key>";
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OpenAIClient client = new(new Uri(endpoint), new AzureKeyCredential(key));
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var chatCompletionsOptions = new ChatCompletionsOptions()
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{
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Messages =
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{
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new ChatMessage(ChatRole.System, "You are the president of France"),
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new ChatMessage(ChatRole.System, "You have just resigned"),
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new ChatMessage(ChatRole.User, "What tasks needs doing?")
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},
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MaxTokens = 100
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};
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Response<ChatCompletions> response = client.GetChatCompletions("gpt-35-turbo", chatCompletionsOptions);
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Console.WriteLine(response.Value.Choices[0].Message.Content);
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Console.WriteLine();

‎07-building-chat-applications/notebook-simple-azure-openai.ipynb

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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": null,
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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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"import openai\n",
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"\n",
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"openai.api_type = \"azure\"\n",
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"openai.api_version = os.getenv(\"AZURE_OPENAI_API_VERSION\",\"\").strip()\n",
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"\n",
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"API_KEY = os.getenv(\"AZURE_OPENAI_API_KEY\",\"\").strip()\n",
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"assert API_KEY, \"ERROR: Azure OpenAI Key is missing\"\n",
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"openai.api_key = API_KEY\n",
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"\n",
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"RESOURCE_ENDPOINT = os.getenv(\"OPENAI_API_BASE\",\"\").strip()\n",
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"assert RESOURCE_ENDPOINT, \"ERROR: Azure OpenAI Endpoint is missing\"\n",
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"assert \"openai.azure.com\" in RESOURCE_ENDPOINT.lower(), \"ERROR: Azure OpenAI Endpoint should be in the form: \\n\\n\\t<your unique endpoint identifier>.openai.azure.com\"\n",
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"openai.api_base = RESOURCE_ENDPOINT\n",
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"deployment = \"gpt-35-turbo\" # replace with your deployment name"
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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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"metadata": {},
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"outputs": [],
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"source": [
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"# Create your first prompt\n",
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"text_prompt = \" My foot hurts, what can be wrong?\"\n",
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"\n",
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"response = openai.ChatCompletion.create(\n",
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" engine=deployment,\n",
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" messages = [\n",
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" {\"role\":\"system\", \"content\":\"I'm a doctor, specialist on surgery\"},\n",
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" {\"role\":\"user\",\"content\":text_prompt},])\n",
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"\n",
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"\n",
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"response['choices'][0]['message']['content']"
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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",
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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": "3.10.11"
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},
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"orig_nbformat": 4
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}

‎08-building-search-applications/dotnet/notebook-azure-openai.dib

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#!meta
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{"kernelInfo":{"defaultKernelName":"csharp","items":[{"aliases":[],"name":"csharp"}]}}
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#!csharp
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#r "nuget: Azure.AI.OpenAI, 1.0.0-beta.9"
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#!csharp
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using Azure;
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using Azure.AI.OpenAI;
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#!csharp
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#r "nuget:Microsoft.DotNet.Interactive.AIUtilities, 1.0.0-beta.23557.4"
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using Microsoft.DotNet.Interactive;
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using Microsoft.DotNet.Interactive.AIUtilities;
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#!csharp
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var azureOpenAIKey = "<replace with API key>";
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var azureOpenAIEndpoint = "<replace with endpoint>";
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var deployment = "<replace with deployment name, should be of type ADA embedding for Azure Open AI>";
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#!csharp
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OpenAIClient client = new (new Uri(azureOpenAIEndpoint), new AzureKeyCredential(azureOpenAIKey));
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#!csharp
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var source = "Car";
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var compareTo = "Vehicle";
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var parrot = "A bird";
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var parrotEmbeddings = await client.GetEmbeddingsAsync(new EmbeddingsOptions(deployment, new []{ parrot }));
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// vector version
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var embeddings = await client.GetEmbeddingsAsync(new EmbeddingsOptions(deployment, new []{ source }));
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// vector version
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var embeddingsCompareTo = await client.GetEmbeddingsAsync(new EmbeddingsOptions(deployment, new []{ compareTo }));
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var sourceValue = embeddings.Value.Data[0].Display();
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Console.WriteLine(sourceValue);
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var compareToValue = embeddingsCompareTo.Value.Data[0].Display();
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Console.WriteLine(compareToValue);
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#!csharp
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var comparer = new CosineSimilarityComparer<float[]>(f => f);
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var carArray = embeddings.Value.Data[0].Embedding.ToArray(); // float []
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var vehicleArray = embeddingsCompareTo.Value.Data[0].Embedding.ToArray(); // float []
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var parrotArray = parrotEmbeddings.Value.Data[0].Embedding.ToArray(); // float []
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var score = comparer.Score(carArray, vehicleArray);
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Console.WriteLine(score);
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score = comparer.Score(carArray, parrotArray);
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Console.WriteLine(score);

‎08-building-search-applications/notebook-azure-openai-simple.ipynb

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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"!pip install openai 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": null,
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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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"import openai\n",
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"from dotenv import load_dotenv\n",
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"load_dotenv()\n",
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"\n",
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"openai.api_type = \"azure\"\n",
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"openai.api_version = os.getenv(\"AZURE_OPENAI_API_VERSION\",\"\").strip()\n",
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"\n",
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"API_KEY = os.getenv(\"AZURE_OPENAI_API_KEY\",\"\").strip()\n",
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"assert API_KEY, \"ERROR: Azure OpenAI Key is missing\"\n",
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"openai.api_key = API_KEY\n",
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"\n",
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"RESOURCE_ENDPOINT = os.getenv(\"OPENAI_API_BASE\",\"\").strip()\n",
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"assert RESOURCE_ENDPOINT, \"ERROR: Azure OpenAI Endpoint is missing\"\n",
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"assert \"openai.azure.com\" in RESOURCE_ENDPOINT.lower(), \"ERROR: Azure OpenAI Endpoint should be in the form: \\n\\n\\t<your unique endpoint identifier>.openai.azure.com\"\n",
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"openai.api_base = RESOURCE_ENDPOINT"
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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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"metadata": {},
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"outputs": [],
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"source": [
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"# Dependencies for embeddings_utils\n",
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"!pip install matplotlib plotly scikit-learn pandas"
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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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"metadata": {},
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"outputs": [],
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"source": [
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"from openai.embeddings_utils import cosine_similarity"
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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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"metadata": {},
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"outputs": [],
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"source": [
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"text = 'the quick brown fox jumped over the lazy dog'\n",
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"model = 'text-embedding-ada-002'\n",
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"openai.Embedding()\\\n",
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" .create(input=[text], engine='text-embedding-ada-002')[\"data\"][0][\"embedding\"]"
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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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"metadata": {},
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"outputs": [],
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"source": [
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"# compare several words\n",
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"automobile_embedding = openai.Embedding.create(input='automobile', engine=model)[\"data\"][0][\"embedding\"]\n",
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"vehicle_embedding = openai.Embedding.create(input='vehicle', engine=model)[\"data\"][0][\"embedding\"]\n",
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"dinosaur_embedding = openai.Embedding.create(input='dinosaur', engine=model)[\"data\"][0][\"embedding\"]\n",
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"stick_embedding = openai.Embedding.create(input='stick', engine=model)[\"data\"][0][\"embedding\"]\n",
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"\n",
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"# comparing cosine similarity, automobiles vs automobiles should be 1.0, i.e exactly the same, while automobiles vs dinosaurs should be between 0 and 1, i.e. not the same\n",
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"print(cosine_similarity(automobile_embedding, automobile_embedding))\n",
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"print(cosine_similarity(automobile_embedding, vehicle_embedding))\n",
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"print(cosine_similarity(automobile_embedding, dinosaur_embedding))\n",
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"print(cosine_similarity(automobile_embedding, stick_embedding))"
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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",
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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": "3.10.11"
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},
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"orig_nbformat": 4
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}

‎09-building-image-applications/app.py

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try:
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# Create an image by using the image generation API
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generation_response = openai.Image.create(
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prompt='Bunny on horse, holding a lollipop, on a foggy meadow where it grows daffodils', # Enter your prompt text here
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prompt='Red and white Rocket with fussy paws', # Enter your prompt text here
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size='1024x1024',
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n=2,
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temperature=0,
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temperature=1,
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)
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# Set the directory for the stored image
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image_dir = os.path.join(os.curdir, 'images')
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# ---creating variation below---
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response = openai.Image.create_variation(
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image=open(image_path, "rb"),
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n=1,
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size="1024x1024"
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)
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# response = openai.Image.create_variation(
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# image=open(image_path, "rb"),
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# n=1,
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# size="1024x1024"
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# )
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image_path = os.path.join(image_dir, 'generated_variation.png')
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# image_path = os.path.join(image_dir, 'generated_variation.png')
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image_url = response['data'][0]['url']
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# image_url = response['data'][0]['url']
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generated_image = requests.get(image_url).content # download the image
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with open(image_path, "wb") as image_file:
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image_file.write(generated_image)
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# generated_image = requests.get(image_url).content # download the image
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# with open(image_path, "wb") as image_file:
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# image_file.write(generated_image)
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# Display the image in the default image viewer
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image = Image.open(image_path)
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image.show()
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# # Display the image in the default image viewer
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# image = Image.open(image_path)
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# image.show()

‎09-building-image-applications/dotnet/notebook-azure-openai.dib

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#!meta
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{"kernelInfo":{"defaultKernelName":"csharp","items":[{"aliases":[],"name":"csharp"}]}}
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#!csharp
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#r "nuget: Azure.AI.OpenAI, 1.0.0-beta.9"
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#!csharp
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using System;
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using System.IO;
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using System.Threading.Tasks;
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using Azure.AI.OpenAI;
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using Azure;
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#!csharp
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string endpoint = "<replace with endpoint>";
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string key = "<replace with API key>";
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#!csharp
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OpenAIClient client = new(new Uri(endpoint), new AzureKeyCredential(key));
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var imageGenerations = await client.GetImageGenerationsAsync(
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new ImageGenerationOptions()
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{
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Prompt = "captain with a parrot on his shoulder",
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Size = ImageSize.Size256x256,
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});
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// Image Generations responses provide URLs you can use to retrieve requested images
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Uri imageUri = imageGenerations.Value.Data[0].Url;
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// Print the image URI to console:
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Console.WriteLine(imageUri);

‎09-building-image-applications/images/generated-image.png

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