This repository contains Jupyter notebooks for working with Anthropic Large Language Models (LLMs), providing comprehensive 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 real-world applications.
| Notebook | Description | Use Case |
|---|---|---|
| ANTHROPIC-CHATBOT.ipynb | 🤖 Demonstrates how to set up and run a chatbot using an Anthropic model, focusing on conversational flow and responsive dialogue management. | Conversational agents, Virtual assistants |
| ANTHROPIC-RAG.ipynb | 🔍 Implements Retrieval-Augmented Generation (RAG), where the model retrieves relevant information from a predefined source before generating responses. | Q&A systems, Knowledge retrieval, Customer support |
| ANTHROPIC-TEXTGEN.ipynb | ✍️ Explores the text generation capabilities of Anthropic models, allowing for creative and informative text output. | Content generation, Story creation, Creative writing |
To run these notebooks, you will need:
- Python 3.8+ 🐍
- Jupyter Notebook 📓
- Dependencies listed in
requirements.txt
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Clone the repository:
git clone https://github.com/simonpierreboucher02/llm_anthropic_notebook-main.git cd llm_anthropic_notebook-main -
Install the required dependencies:
pip install -r requirements.txt
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Start Jupyter Notebook: Navigate to the repository folder and launch Jupyter:
jupyter notebook
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Select a Notebook: Open any of the notebooks to explore:
- 🤖 Chatbot interactions
- 🔍 RAG (Retrieval-Augmented Generation)
- ✍️ Text generation
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Follow Instructions: Each notebook contains specific setup steps and instructions for interacting with the model.
| Feature | Best For |
|---|---|
| ANTHROPIC-CHATBOT | Building conversational agents, virtual assistants, customer service bots |
| ANTHROPIC-RAG | Applications needing fact-based responses, knowledge bases, research tools |
| ANTHROPIC-TEXTGEN | Content generation, story creation, creative writing, documentation |
This project uses several key libraries:
anthropic- Official Anthropic Python clientjupyter- Interactive notebook environmentpandas&numpy- Data manipulationfaiss-cpu- Vector similarity search for RAGtransformers- Hugging Face transformers integrationpython-dotenv- Environment variable management
We welcome contributions! Feel free to:
- 🐛 Report bugs by opening an issue
- 💡 Suggest new features
- 📝 Submit pull requests to improve functionality
- 📚 Add new notebooks for different use cases
This project is licensed under the MIT License - see the LICENSE file for details.
Made with ❤️ by Simon Pierre Boucher
