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This repository provides Jupyter notebooks for exploring and utilizing Cohere's Large Language Models (LLMs) in various applications, including chatbots and retrieval-augmented generation (RAG). These notebooks serve as a practical guide for deploying Cohere models for conversational AI and information retrieval tasks.

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LLM Cohere Notebook

License: MIT Python Version GitHub Issues GitHub Forks GitHub Stars

This repository provides Jupyter notebooks for exploring and utilizing Cohere's Large Language Models (LLMs) in various applications, including chatbots and retrieval-augmented generation (RAG). These notebooks serve as a practical guide for deploying Cohere models for conversational AI and information retrieval tasks.

Repository Structure

  • COHERE-CHATBOT.ipynb: Demonstrates the setup of a chatbot using a Cohere model, focusing on creating interactive, conversational exchanges.
  • COHERE-RAG.ipynb: Implements Retrieval-Augmented Generation (RAG), combining document retrieval and generation for contextually relevant responses. Ideal for Q&A systems and customer support applications.

Getting Started

Prerequisites

To run these notebooks, you need:

  • Python 3.8+
  • Jupyter Notebook
  • The dependencies listed in requirements.txt

Installation

  1. Clone the repository:

    git clone https://github.com/simonpierreboucher/llm_cohere_notebook.git
    cd llm_cohere_notebook
  2. Install the dependencies:

    pip install -r requirements.txt

Running the Notebooks

  1. Start Jupyter Notebook: Navigate to the repository folder and launch Jupyter:
    jupyter notebook
  2. Open a Notebook: Select either the Chatbot or RAG notebook to explore specific functionalities.
  3. Follow Instructions: Each notebook contains setup instructions and guidance for working with Cohere models in the specified application.

Use Cases

  • COHERE-CHATBOT: Perfect for building conversational agents or virtual assistants that engage users in dialogue.
  • COHERE-RAG: Suitable for tasks that require accurate, contextually grounded answers, such as support chat and information retrieval systems.

Contributing

We welcome contributions! Feel free to submit issues or pull requests to enhance functionality, add features, or address bugs.

License

This repository is licensed under the MIT License.

About

This repository provides Jupyter notebooks for exploring and utilizing Cohere's Large Language Models (LLMs) in various applications, including chatbots and retrieval-augmented generation (RAG). These notebooks serve as a practical guide for deploying Cohere models for conversational AI and information retrieval tasks.

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