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How to create a GenAI Talking Avatar ChatBot using Streamlit and Anthropic Claude LLM Model

GenAI Talking Avatar ChatBot   using Streamlit and Anthropic Claude LLM Model GenAI-Talking-Avatar-Chatbot is a web application that allows users to interact with an AI-powered talking chatbot with a static avatar. The chatbot uses AWS Bedrock for generating responses and Google Text-to-Speech (gTTS) for voice output. The backend is built with FastAPI, and the frontend uses Streamlit for the user interface. Features API Backend (api.py) Provides an API endpoint to handle chat requests. Uses AWS Bedrock to generate AI responses in a specified JSON format. Ensures the responses include the message, avatar expression, and voice tone. Includes a health check endpoint to verify the API status. Chat UI (chat_frontend.py) Chat Interface: Provides a chat interface where users can input their queries and receive responses from the AI assistant. Avatar Display: Displays an avatar that changes expressions based on the AI assistant's responses and actions (e.g., thinking, speaking). AI Respons...
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How to create a GenAI ChatBot using Streamlit and Anthropic Claude LLM Model

GenAI Chatbot with Streamlit and Anthropic Claude LLM model GenAI-ChatBot is a chatbot application that utilizes Streamlit for the frontend and LangChain for the backend. The chatbot integrates with AWS Bedrock for language model interactions, enabling intelligent and dynamic conversations. Features Conversational AI chatbot powered by LangChain. Interactive web-based UI built with Streamlit. AWS Bedrock integration for natural language responses. Supports conversation memory for contextual awareness. Easy setup and deployment. GitHub Repo:  Clone and use latest code from here. https://github.com/SolutionInsights-git/GenAI-Chatbot
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How to Create a VS Code Extension: A Step-by-Step Guide Using Node.js, npm, and Yeoman

Creating a Visual Studio Code (VS Code) extension can significantly enhance your coding workflow by adding custom functionalities. In this guide, we’ll cover the setup, development, and packaging process using tools like Node.js, npm, and Yeoman. Prerequisites Visual Studio Code version 1.92.2 or higher. Node.js installed on your machine. Steps to Set Up Your VS Code Extension Set Up Your Development Environment Install Node.js: Make sure Node.js is installed. You can download it from nodejs.org. Install VS Code: Download and install Visual Studio Code from code.visualstudio.com. Clone the Repository Clone the repository to your local machine using: git clone <repository-url> Install Dependencies Navigate to the project directory and run: npm install Create a New Extension Use Yeoman Generator: This is the easiest way to create a new extension. Open your terminal and run: npm install -g yo generator-code After installing the generator, run: yo code Follow the Prompts: Answer ...
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How to Use PowerShell for Analyzing Code: Metrics for Java, Python, JavaScript, and C# Projects

PowerShell for Analyzing Code In this blog post, learn how to leverage PowerShell commands to analyze your code projects effectively. Whether you’re working with Java, Python, JavaScript, or C#, discover how to count lines of code, methods, classes, packages, interfaces, enums, annotations, comments, API endpoints, libraries, and user interfaces. This guide provides a step-by-step approach to automate code analysis, ensuring high code quality and better project management across different programming languages. Save the following commands in a file named analyze-project.ps1 in the same directory as your project files. Java Projects $lineCount = Get-ChildItem -Recurse -Filter *.java | Get-Content | Measure-Object -Line $methodCount = Get-ChildItem -Recurse -Filter *.java | Select-String -Pattern '^\s*(public|protected|private|static|\s)*\s*\w+\s+\w+\s*\([^)]*\)\s*\{' | Measure-Object -Line $classCount = Get-ChildItem -Recurse -Filter *.java | Select-String -Pattern '^\s*(pub...
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How to Use GitHub Copilot for enterprise apps development? | Coding, Refactoring & AI Automation | GenAI

🚀 "GitHub Copilot in Action: Code, Refactor & Automate Like a Pro! What You’ll Learn GitHub Copilot is a game-changer for developers, accelerating every stage of the Software Development Life Cycle (SDLC). In this guide, you'll explore real-world prompts that can: ✅ Generate boilerplate code instantly ✅ Refactor and optimize existing code effortlessly ✅ Generate documentation, unit testing & CI/CD scripts seamlessly ✅ Enhance software design patterns intelligently ✅ Analyze code/logs for potential issues and improvements ✅ Detect and fix bugs efficiently with AI-powered suggestions What is prompt? A prompt is an instruction given to an AI tool (like Copilot) to generate a meaningful response. Prompt Engineering is the art of crafting these inputs to achieve accurate, relevant, and optimized outputs. Prerequisites Before you get started, make sure you have the following: Visual Studio Code or IntelliJ IDEA installed GitHub Copilot extension installed and configured Bas...
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How to Implement JBoss Narayana with Spring Boot: Java 21 to Master Distributed Transactions, Ensure Data Consistency, and Reliable Transactions

Integrating JBoss Narayana with Spring Boot : A Comprehensive Guide for Java 21 to Master Distributed Transactions, Ensure Data Consistency, and Reliable Transactions. Overview JBoss Narayana is a transaction manager that supports distributed transactions. It is part of the JBoss suite of projects and ensures data consistency across multiple resources, such as databases and message queues, in a distributed system. Narayana is compliant with the Java Transaction API (JTA) and supports both XA and non-XA transactions. Key FeaturesDistributed Transactions :  Ensures data consistency across multiple resources. JTA Compliance: Implements the Java Transaction API. Recovery: Provides mechanisms for transaction recovery in case of failures. Integration: Easily integrates with various Java EE and Spring applications. Compatibility : Compatible with Java 21 and other modern Java stacks 1 2 . Steps to Integrate JBoss Narayana in a Spring Boot Project Step 1: Add Dependencies Add the necessary...
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How to Implement Lombok in IntelliJ for Java Projects: A Step-by-Step Guide

Lombok in IntelliJ for Java Projects Implementing Lombok in your Java project can streamline your code by reducing boilerplate. Follow these steps to set up Lombok in IntelliJ: Step 1 :  Ensure Java SDK Version. Ensure that your project is using Java 8 or higher.  You can check and set the Java SDK version in pom.xml: XML <properties> <maven.compiler.source>1.8</maven.compiler.source> <maven.compiler.target>1.8</maven.compiler.target> </properties> Step 2 : Add Lombok Dependency to pom.xmlOpen the pom.xml file in your project. Add the following Lombok dependency inside the <dependencies> section: XML <dependency> <groupId>org.projectlombok</groupId> <artifactId>lombok</artifactId> <version>1.18.24</version> <scope>provided</scope> </dependency> Step 3 : Download Lombok Plugin for IntelliJ IDEAGo to File > Settings (or press Ctrl+Alt+S). Navigate to Plugins. Search for Lombo...
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