{"id":22808208,"url":"https://github.com/simonpierreboucher/llm_mistral_notebook","last_synced_at":"2026-05-15T22:39:10.771Z","repository":{"id":262714799,"uuid":"888126027","full_name":"simonpierreboucher/llm_mistral_notebook","owner":"simonpierreboucher","description":"This repository provides Jupyter notebooks to interact with Mistral Large Language Models (LLMs) for tasks including chatbot development, retrieval-augmented generation, and text generation. 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These notebooks are designed to help users leverage Mistral models in a range of applications, from conversational AI to content generation.\n\n## Repository Structure\n\n- **[MISTRAL-CHATBOT.ipynb](https://github.com/simonpierreboucher/llm_mistral_notebook/blob/main/MISTRAL-CHATBOT.ipynb)**: A notebook for setting up a Mistral-powered chatbot, demonstrating dialogue handling and response generation.\n- **[MISTRAL-RAG.ipynb](https://github.com/simonpierreboucher/llm_mistral_notebook/blob/main/MISTRAL-RAG.ipynb)**: Focuses on Retrieval-Augmented Generation (RAG) with the Mistral model, enabling the retrieval of relevant information before generating responses.\n- **[MISTRAL-TEXTGEN.ipynb](https://github.com/simonpierreboucher/llm_mistral_notebook/blob/main/MISTRAL-TEXTGEN.ipynb)**: Demonstrates the text generation capabilities of Mistral models, ideal for creative and informative content generation.\n\n## Getting Started\n\n### Prerequisites\n\nTo run these notebooks, you need:\n- **Python 3.8+**\n- **Jupyter Notebook**\n- Required dependencies as listed in `requirements.txt`\n\n### Installation\n\n1. Clone the repository:\n\n   ```bash\n   git clone https://github.com/simonpierreboucher/llm_mistral_notebook.git\n   cd llm_mistral_notebook\n   ```\n\n2. Install the dependencies:\n\n   ```bash\n   pip install -r requirements.txt\n   ```\n\n### Running the Notebooks\n\n1. **Start Jupyter Notebook**: Navigate to the repository folder and launch Jupyter:\n   ```bash\n   jupyter notebook\n   ```\n2. **Select a Notebook**: Open any of the notebooks (Chatbot, RAG, or Text Generation) to explore its functionality.\n3. **Follow Instructions**: Each notebook includes setup steps and explanations to guide you through using the model.\n\n## Use Cases\n\n- **MISTRAL-CHATBOT**: For building chatbots and virtual assistants that engage users in dialogue.\n- **MISTRAL-RAG**: Suitable for applications needing accurate, source-based responses, such as customer support and information retrieval systems.\n- **MISTRAL-TEXTGEN**: Useful for content creation, story generation, or tasks requiring high-quality text generation.\n\n## Contributing\n\nWe welcome contributions! Feel free to submit issues or pull requests to enhance functionality, add features, or fix bugs.\n\n## License\n\nThis repository is licensed under the MIT License.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsimonpierreboucher%2Fllm_mistral_notebook","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fsimonpierreboucher%2Fllm_mistral_notebook","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsimonpierreboucher%2Fllm_mistral_notebook/lists"}