🚀 Generative AI using LangChain
This project demonstrates how to build Generative AI applications using LangChain — a powerful framework for developing applications powered by large language models (LLMs). It focuses on integrating OpenAI GPT, creating prompt templates, and building intelligent conversational systems such as chatbots and content generators.
📘 Overview
The goal of this project is to help you understand the fundamentals of working with LLMs and how they can be applied to real-world AI tasks. By exploring this repository, you’ll learn to:
Integrate LangChain with OpenAI’s GPT models
Build and test prompt-based applications
Understand chain, memory, and agent concepts
Create your own context-aware conversational AI systems
🧩 Requirements
Before running this project, make sure you have the following:
Python 3.9 or above
Virtual Environment (recommended)
OpenAI API Key or any supported LLM provider key
Required Python libraries:
langchain openai python-dotenv
⚙️ Installation
Follow these steps to set up the project on your local machine:
Clone the repository
git clone https://github.com/Codeabhi096/Generative-AI-using-Langchain.git cd Generative-AI-using-Langchain
Create and activate a virtual environment
python -m venv venv venv\Scripts\activate # For Windows source venv/bin/activate # For macOS/Linux
Install dependencies
pip install -r requirements.txt
Create a .env file and add your API key
OPENAI_API_KEY=your_openai_api_key
Run the demo file to test the LLM setup:
python 1.LLMS/llm_demo.py
Optional: If you are using Streamlit for a simple web UI:
streamlit run app.py
📚 References
LangChain Documentation
OpenAI API Reference
Hugging Face Transformers