Lesson 3: Specialized Agent with Stock Sentiment Analysis

This lesson creates a specialized agent focused on stock sentiment analysis using the Agent Framework with specific system instructions and function calling capabilities.

1. Switch to Lesson 3 directory:

   cd workshop/dotnet/Lessons/Lesson3
   

2. Copy the configuration file from the Solutions directory:

   cp ../../Solutions/Lesson3/appsettings.json .
   

3. Run the application to see it works:

   dotnet run
   

4. Open Program.cs and build a specialized stock sentiment agent:

   1. TODO: Step 1 - Initialize the chat client and plugins:

      IChatClient chatClient = AgentFrameworkProvider.CreateChatClientWithApiKey();
      
      // Initialize plugins
      TimeInformationPlugin timePlugin = new();
      HttpClient httpClient = new();
      StockDataPlugin stockDataPlugin = new(new StocksService(httpClient));
      

   2. TODO: Step 2 - Create AI Functions from plugins:

      var timeTool = AIFunctionFactory.Create(timePlugin.GetCurrentUtcTime);
      var stockPriceTool = AIFunctionFactory.Create(stockDataPlugin.GetStockPrice);
      var stockPriceDateTool = AIFunctionFactory.Create(stockDataPlugin.GetStockPriceForDate);
      

   3. TODO: Step 3 - Define specialized system instructions for stock sentiment analysis:

      string stockSentimentAgentInstructions = """
          You are a Stock Sentiment Agent. Your responsibility is to find the stock sentiment for a given Stock.
      
          RULES:
          - Use stock sentiment scale from 1 to 10 where stock sentiment is 1 for sell and 10 for buy.
          - Provide the rating in your response and a recommendation to buy, hold or sell.
          - Include the reasoning behind your recommendation.
          - Include the source of the sentiment in your response.
          - Focus on technical analysis based on stock price data and general market knowledge.
          """;
      

   4. TODO: Step 4 - Create the specialized Stock Sentiment Agent:

      ChatClientAgent stockSentimentAgent = new(
          chatClient,
          instructions: stockSentimentAgentInstructions,
          name: "StockSentimentAgent",
          description: "An intelligent agent that analyzes stock sentiment using market data",
          tools: [
              timeTool,
              stockPriceTool, 
              stockPriceDateTool
          ]
      );
      

   5. TODO: Step 5 - Create thread and process user requests:

      AgentThread thread = stockSentimentAgent.GetNewThread();
      
      var response = await stockSentimentAgent.RunAsync(userInput, thread);
      
      if (response?.Messages?.Any() == true)
      {
          var lastMessage = response.Messages.Last();
          Console.WriteLine(lastMessage.Text ?? "No response generated.");
      }
      

5. Test the specialized agent with stock sentiment queries:

   dotnet run
   

   Example questions to test:

   User > What is your sentiment on MSFT?
   Assistant > (should analyze Microsoft stock and provide sentiment rating 1-10 with buy/hold/sell recommendation)
   
   User > Analyze AAPL sentiment
   Assistant > (should provide Apple stock sentiment analysis with reasoning)
   
   User > Should I buy TSLA?
   Assistant > (should analyze Tesla and provide specific buy/hold/sell recommendation)
   

This lesson demonstrates how to create specialized agents with focused system instructions and domain-specific capabilities using the Agent Framework.