LLM Python Notebook

This repository contains Jupyter notebooks for accessing and interacting with various Large Language Model (LLM) APIs using Python. The notebooks provide a straightforward approach to setting up API calls and working with different LLM providers, including Anthropic, Cohere, Mistral, and OpenAI.

Repository Structure

• PYTHON_ANTHROPIC_API.ipynb: A notebook demonstrating the use of Anthropic's API for making requests, handling responses, and configuring parameters for different tasks.
• PYTHON_COHERE_API.ipynb: Contains setup and usage instructions for the Cohere API, with examples for text generation and retrieval tasks.
• PYTHON_MISTRAL_API.ipynb: Shows how to interact with the Mistral API, including configuration of model parameters and API responses.
• PYTHON_OPENAI_API.ipynb: Provides an introduction to the OpenAI API, covering setup, API calls, and adjusting parameters for optimal results.

Getting Started

Prerequisites

To run these notebooks, you need:

• Python 3.8+
• Jupyter Notebook
• API keys for each respective service (Anthropic, Cohere, Mistral, OpenAI)
• Required dependencies as listed in requirements.txt

Installation

1. Clone the repository:

   git clone /~https://github.com/simonpierreboucher/llm_python_notebook.git
   cd llm_python_notebook

2. Install the dependencies:

   pip install -r requirements.txt

Running the Notebooks

1. Start Jupyter Notebook: Open Jupyter by navigating to the repository folder and running:

   jupyter notebook

2. Select a Notebook: Open the notebook for the desired API provider (Anthropic, Cohere, Mistral, or OpenAI).
3. Follow Instructions: Each notebook includes specific instructions for authenticating, setting up, and making API requests to interact with the respective LLMs.

Use Cases

• API Interactions: Each notebook provides examples of API calls for text generation, retrieval, and other common LLM tasks.
• Parameter Configuration: Customize parameters such as temperature, token limits, and prompt styles to achieve desired model behavior.
• Multi-Model Comparisons: Enables testing and comparing different LLM providers for various applications in NLP.

Contributing

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

License

This repository is licensed under the MIT License.