This repository contains Jupyter notebooks for working with Anthropic Large Language Models (LLMs), providing tools to explore chat-based interactions, retrieval-augmented generation, and text generation. These notebooks serve as a practical introduction to leveraging Anthropic models for various applications.
- ANTHROPIC-CHATBOT.ipynb: Demonstrates how to set up and run a chatbot using an Anthropic model, focusing on conversational flow and responsive dialogue management.
- ANTHROPIC-RAG.ipynb: Implements Retrieval-Augmented Generation (RAG), where the model retrieves relevant information from a predefined source before generating responses. Ideal for Q&A systems and other information-based applications.
- ANTHROPIC-TEXTGEN.ipynb: Explores the text generation capabilities of Anthropic models, allowing for creative and informative text output.
To run these notebooks, you will need:
- Python 3.8+
- Jupyter Notebook
- Dependencies listed in
requirements.txt
Install the required dependencies using:
pip install -r requirements.txt- Start Jupyter Notebook: Navigate to the repository folder and launch Jupyter:
jupyter notebook
- Select a Notebook: Open any of the notebooks to explore chatbot interactions, RAG, or text generation.
- Follow Instructions: Each notebook contains specific setup steps and instructions for interacting with the model.
- ANTHROPIC-CHATBOT: Ideal for building conversational agents or virtual assistants.
- ANTHROPIC-RAG: Suitable for applications needing fact-based responses, such as customer support and knowledge retrieval.
- ANTHROPIC-TEXTGEN: Perfect for content generation, story creation, or any task requiring flexible text output.
Feel free to submit issues or pull requests to improve functionality or add new features.