Feature/notebook bing search

.gitignore

@@ -476,4 +476,5 @@ playwright-report/
 
 # Static Web App deployment config
 swa-cli.config.json
-**/copilot-chat-app/webapp/build
+**/copilot-chat-app/webapp/build
+**/copilot-chat-app/webapp/node_modules

samples/notebooks/dotnet/00-getting-started.ipynb

@@ -61,7 +61,7 @@
    "outputs": [],
    "source": [
     "// Import Semantic Kernel\n",
-    "#r \"nuget: Microsoft.SemanticKernel, 0.15.230531.5-preview\""
+    "#r \"nuget: Microsoft.SemanticKernel, 0.17.230626.1-preview\""
    ]
   },
   {

samples/notebooks/dotnet/01-basic-loading-the-kernel.ipynb

@@ -32,7 +32,7 @@
    },
    "outputs": [],
    "source": [
-    "#r \"nuget: Microsoft.SemanticKernel, 0.15.230531.5-preview\""
+    "#r \"nuget: Microsoft.SemanticKernel, 0.17.230626.1-preview\""
    ]
   },
   {

samples/notebooks/dotnet/02-running-prompts-from-file.ipynb

@@ -90,7 +90,7 @@
    },
    "outputs": [],
    "source": [
-    "#r \"nuget: Microsoft.SemanticKernel, 0.15.230531.5-preview\"\n",
+    "#r \"nuget: Microsoft.SemanticKernel, 0.17.230626.1-preview\"\n",
     "\n",
     "#!import config/Settings.cs\n",
     "\n",

samples/notebooks/dotnet/03-semantic-function-inline.ipynb

@@ -1,6 +1,7 @@
 {
  "cells": [
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
@@ -30,6 +31,7 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
@@ -49,7 +51,7 @@
    },
    "outputs": [],
    "source": [
-    "#r \"nuget: Microsoft.SemanticKernel, 0.15.230531.5-preview\"\n",
+    "#r \"nuget: Microsoft.SemanticKernel, 0.17.230626.1-preview\"\n",
     "\n",
     "#!import config/Settings.cs\n",
     "\n",
@@ -69,6 +71,7 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
@@ -96,6 +99,7 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
@@ -127,6 +131,7 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
@@ -155,6 +160,7 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
@@ -180,6 +186,7 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
@@ -213,6 +220,7 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
@@ -273,6 +281,7 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [

samples/notebooks/dotnet/04-context-variables-chat.ipynb

@@ -34,8 +34,7 @@
    },
    "outputs": [],
    "source": [
-    "#r \"nuget: Microsoft.SemanticKernel, 0.15.230531.5-preview\"\n",
-    "\n",
+    "#r \"nuget: Microsoft.SemanticKernel, 0.17.230626.1-preview\"\n",
     "#!import config/Settings.cs\n",
     "\n",
     "using Microsoft.SemanticKernel;\n",

samples/notebooks/dotnet/05-using-the-planner.ipynb

@@ -25,7 +25,7 @@
    },
    "outputs": [],
    "source": [
-    "#r \"nuget: Microsoft.SemanticKernel, 0.15.230531.5-preview\"\n",
+    "#r \"nuget: Microsoft.SemanticKernel, 0.17.230626.1-preview\"\n",
     "\n",
     "#!import config/Settings.cs\n",
     "#!import config/Utils.cs\n",

samples/notebooks/dotnet/06-memory-and-embeddings.ipynb

@@ -33,7 +33,7 @@
    },
    "outputs": [],
    "source": [
-    "#r \"nuget: Microsoft.SemanticKernel, 0.15.230531.5-preview\"\n",
+    "#r \"nuget: Microsoft.SemanticKernel, 0.17.230626.1-preview\"\n",
     "\n",
     "#!import config/Settings.cs\n",
     "\n",

samples/notebooks/dotnet/07-DALL-E-2.ipynb

@@ -33,7 +33,7 @@
    "source": [
     "// Usual setup: importing Semantic Kernel SDK and SkiaSharp, used to display images inline.\n",
     "\n",
-    "#r \"nuget: Microsoft.SemanticKernel, 0.15.230531.5-preview\"\n",
+    "#r \"nuget: Microsoft.SemanticKernel, 0.17.230626.1-preview\"\n",
     "#r \"nuget: SkiaSharp, 2.88.3\"\n",
     "\n",
     "#!import config/Settings.cs\n",

samples/notebooks/dotnet/08-chatGPT-with-DALL-E-2.ipynb

@@ -28,6 +28,7 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
@@ -55,7 +56,7 @@
    "source": [
     "// Usual setup: importing Semantic Kernel SDK and SkiaSharp, used to display images inline.\n",
     "\n",
-    "#r \"nuget: Microsoft.SemanticKernel, 0.15.230531.5-preview\"\n",
+    "#r \"nuget: Microsoft.SemanticKernel, 0.17.230626.1-preview\"\n",
     "#r \"nuget: SkiaSharp, 2.88.3\"\n",
     "\n",
     "#!import config/Settings.cs\n",

samples/notebooks/dotnet/09-BingSearch-using-kernel.ipynb

@@ -0,0 +1,224 @@
+{
+ "cells": [
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# BingSearch using Kernel \n",
+    "\n",
+    "This notebook explains how to integrate Bing Search with the Semantic Kernel  to get the latest information from the internet.\n",
+    "\n",
+    "To use Bing Search you simply need a Bing Search API key. You can get the API key by creating a [Bing Search resource](https://learn.microsoft.com/en-us/bing/search-apis/bing-web-search/create-bing-search-service-resource) in Azure. \n",
+    "\n",
+    "To learn more read the following [documenation](https://learn.microsoft.com/en-us/bing/search-apis/bing-web-search/overview)\n"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Prepare a semantic kernel instance first, loading also the AI backend settings defined in the [Setup notebook](0-AI-settings.ipynb):"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "dotnet_interactive": {
+     "language": "csharp"
+    },
+    "polyglot_notebook": {
+     "kernelName": "csharp"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "#r \"nuget: Microsoft.SemanticKernel, 0.17.230626.1-preview\"\n",
+    "#r \"nuget: Microsoft.SemanticKernel.Skills.Web, 0.17.230626.1-preview\"\n",
+    "\n",
+    "#!import config/Settings.cs\n",
+    "#!import config/Utils.cs\n",
+    "\n",
+    "using Microsoft.SemanticKernel;\n",
+    "using Microsoft.SemanticKernel.Skills.Core;\n",
+    "using Microsoft.SemanticKernel.SkillDefinition;\n",
+    "using Microsoft.SemanticKernel.Orchestration;\n",
+    "using Microsoft.SemanticKernel.Planning;\n",
+    "using Microsoft.SemanticKernel.Planning.Sequential;\n",
+    "using Microsoft.SemanticKernel.TemplateEngine;\n",
+    "var builder = new KernelBuilder();\n",
+    "\n",
+    "// Configure AI backend used by the kernel\n",
+    "var (useAzureOpenAI, model, azureEndpoint, apiKey, orgId) = Settings.LoadFromFile();\n",
+    "\n",
+    "if (useAzureOpenAI)\n",
+    "    builder.WithAzureTextCompletionService(model, azureEndpoint, apiKey);\n",
+    "else\n",
+    "    builder.WithOpenAITextCompletionService(model, apiKey, orgId);\n",
+    "\n",
+    "var kernel = builder.Build();"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Add the following namespaces to use the Bing Search connector."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {
+    "dotnet_interactive": {
+     "language": "csharp"
+    },
+    "polyglot_notebook": {
+     "kernelName": "csharp"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "using Microsoft.SemanticKernel.Skills.Web;\n",
+    "using Microsoft.SemanticKernel.Skills.Web.Bing;"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Below are some examples on how `WebSearchEngineSkill` can be use in SK . Just uncomment the example to use the ."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {
+    "dotnet_interactive": {
+     "language": "csharp"
+    },
+    "polyglot_notebook": {
+     "kernelName": "csharp"
+    }
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Example 1\n",
+      "What is quantum tunnelling\n",
+      "----\n",
+      "In physics, quantum tunnelling, barrier penetration, or simply tunnelling is a quantum mechanical phenomenon in which an object such as an electron or atom passes through a potential energy barrier that, according to classical mechanics, the object does not have sufficient energy to enter or surmount.\n",
+      "\n",
+      "Example 2\n",
+      "[1] Elon Musk (@elonmusk) is the owner of Twitter and is the most-followed person on Twitter, with over 144 million followers. Former U.S. President Barack Obama (@BarackObama) is the second most-followed person on Twitter, with over 132 million followers.\n"
+     ]
+    }
+   ],
+   "source": [
+    "// Load Bing skill\n",
+    "//Uncomment the Example \n",
+    "using (var bingConnector = new BingConnector(\"BING_KEY\")\n",
+    "{\n",
+    "kernel.ImportSkill(new WebSearchEngineSkill(bingConnector), \"bing\");\n",
+    "//First run the example sample given below and uncomment the await the  following statements \n",
+    "//await Example1Async(kernel);\n",
+    "//await Example2Async(kernel);\n",
+    "}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {
+    "dotnet_interactive": {
+     "language": "csharp"
+    },
+    "polyglot_notebook": {
+     "kernelName": "csharp"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "private static async Task Example1Async(IKernel kernel)\n",
+    "{\n",
+    "        Console.WriteLine(\"Example 1\");\n",
+    "\n",
+    "        // Run \n",
+    "        var question = \"What is quantum tunnelling\";\n",
+    "        var bingResult = await kernel.Func(\"bing\", \"search\").InvokeAsync(question);\n",
+    "\n",
+    "        Console.WriteLine(question);\n",
+    "        Console.WriteLine(\"----\");\n",
+    "        Console.WriteLine(bingResult);\n",
+    "        Console.WriteLine();\n",
+    "\n",
+    "        /* OUTPUT:\n",
+    "\n",
+    "            What is quantum tunnerling\n",
+    "            ----\n",
+    "            In physics, quantum tunnelling, barrier penetration, or simply tunnelling is a quantum mechanical\n",
+    "            phenomenon in which an object such as an electron or atom passes through a potential energy \n",
+    "            barrier that, according to classical mechanics, the object does not have sufficient energy to\n",
+    "            enter or surmount.\n",
+    "            \n",
+    "       */\n",
+    "}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {
+    "dotnet_interactive": {
+     "language": "csharp"
+    },
+    "polyglot_notebook": {
+     "kernelName": "csharp"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "private static async Task Example2Async(IKernel kernel)\n",
+    "{\n",
+    "    Console.WriteLine(\"Example 2\");\n",
+    "    //Use the following function in VS only\n",
+    "    string question = await InteractiveKernel.GetInputAsync(\"Please aSk your question\"); \n",
+    "    //Console.ReadLine();\n",
+    "    var bingResult = await kernel.Func(\"bing\", \"search\").InvokeAsync(question);\n",
+    "\n",
+    "        Console.WriteLine(bingResult);\n",
+    "}"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": ".NET (C#)",
+   "language": "C#",
+   "name": ".net-csharp"
+  },
+  "language_info": {
+   "name": "polyglot-notebook"
+  },
+  "orig_nbformat": 4,
+  "polyglot_notebook": {
+   "kernelInfo": {
+    "defaultKernelName": "csharp",
+    "items": [
+     {
+      "aliases": [],
+      "name": "csharp"
+     }
+    ]
+   }
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}