Techietalks AI - Smart Chat Assistant

Welcome to the Techietalks AI repository! This project is a simple yet powerful AI-powered chat assistant built using Streamlit, DeepSeek API, and Pydantic_AI. It allows users to interact with an AI assistant that can answer questions conversationally and concisely.

This repository contains all the necessary files to set up and run the chat assistant locally or in a Docker container. Below, you'll find a detailed explanation of the project and instructions to get started.

📁 Repository Structure

Here’s a breakdown of the files in this repository:

1. .DS_Store: A macOS-specific file that stores folder attributes (e.g., icon positions). You can ignore this file.
2. .env: A file to store environment variables, such as API keys. Important: Add your DEEPSEEK_API_KEY here to authenticate with the DeepSeek API.
3. .gitignore: Specifies files and folders that Git should ignore (e.g., .env to avoid exposing sensitive information).
4. Dockerfile: Contains instructions to build a Docker image for the application. It sets up a Python environment, installs dependencies, and runs the Streamlit app.
5. README.md: This file! It provides an overview of the project and instructions for setup.
6. app.py: The main application file. It contains the code for the Streamlit-based chat interface and integrates with the DeepSeek API.
7. docker-compose.yml: A configuration file to run the application using Docker Compose. It maps ports, loads environment variables, and sets up volumes.
8. requirements.txt: Lists all Python dependencies required to run the application.
9. sree.txt: A placeholder text file (likely for personal notes or testing).

🚀 How It Works

This project uses the following technologies:

• Streamlit: A framework for building interactive web applications with Python. It powers the chat interface.
• DeepSeek API: An AI model that provides conversational responses. The app authenticates with the API using an API key stored in the .env file.
• Pydantic_AI: A library that helps structure and validate AI responses.

When you type a question into the chat interface, the app sends it to the DeepSeek API, processes the response, and displays it in a conversational format.

🛠️ Setup Instructions

Follow these steps to set up and run the project:

Prerequisites

1. Python 3.11: Ensure Python is installed on your system.
2. Docker (optional): If you want to run the app in a container.
3. DeepSeek API Key: Obtain an API key from DeepSeek.

Steps

1. Clone the Repository: bash git clone https://github.com/schogini/techietalksai.git cd techietalksai/0002

2. Set Up Environment Variables:

   • Create a .env file in the project directory.
   • Add your DeepSeek API key: plaintext DEEPSEEK_API_KEY=your_api_key_here

3. Install Dependencies:

   • If running locally: bash pip install -r requirements.txt
   • If using Docker, skip this step.

4. Run the Application:

   • Locally: bash streamlit run app.py Open your browser and navigate to http://localhost:8501.
   • Using Docker: bash docker-compose up --build Open your browser and navigate to http://localhost:8502.

📄 License

This project is open-source and available under the MIT License. Feel free to use, modify, and distribute it as needed.

📧 Contact

For AI consultancy, training, and development, contact Schogini Systems Private Limited at https://www.schogini.com.

👨‍💻 Author

Sreeprakash Neelakantan
- Website: https://www.schogini.com
- GitHub: https://github.com/schogini/techietalksai.git

Enjoy using the Techietalks AI Smart Chat Assistant! If you have any questions or feedback, feel free to reach out. 😊