keras-gemini 0.1.2
A Python package that combines the power of Keras with Gemini for natural language-driven neural network building.
License: MIT
Requires Python: >=3.7

# keras-gemini
        
        [![Release](https://img.shields.io/pypi/v/keras-gemini?label=Release&style=flat-square)](https://pypi.org/project/keras-gemini/)
        [![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
        
        A Python package that combines the power of Keras with Gemini for natural language-driven neural network building.
        
        ### Built With
        
        - Python
        - Keras
        - Gemini API
        - NLTK
        
        ## Getting Started
        
        To get a local copy up and running follow these simple steps.
        
        ### Prerequisites
        
        - Python 3.x
        
        ### Installation
        
        ```sh
        pip install keras-gemini
        ```
        
        ## Usage
        
        ```python
        from keras_gemini import prompt_to_keras
        
        model = prompt_to_keras("Build a 3-layer sequential model")
        if model:
            model.summary()
        ```
        
        ## Run the Examples
        To run these examples, users simply need to navigate to the examples/ directory and run any of the scripts. For example:
        
        ```bash
        python examples/build_basic_model.py
        ```
        
        ## Features
        - Natural Language Model Building: Build Keras sequential models by simply describing the desired architecture in natural language.
        
        For example: `Build a 3-layer sequential model`
        
        - Automatic Model Compilation: The package automatically compiles the generated Keras model with default settings: 
        
        - `optimizer='adam'`
        - `loss='sparse_categorical_crossentropy'`
        - `metrics=['accuracy']`
        
        - Seamless Integration with Gemini: The `KerasGemini()` integrates directly into your Gemini chatbot flow, allowing for natural conversational model building.
        
        ## Upcoming Features (Roadmap)
        - [ ] Support for More Layer Types: Add support for a wider range of Keras layers (Convolutional, Recurrent, etc.) to enable building diverse network architectures.
        
        - [ ] Customizable Layer Parameters: Allow users to specify layer parameters (activation functions, number of units, etc.) through natural language prompts.
        
        - [ ] Advanced NLP for Model Understanding: Implement more robust natural language processing techniques to better extract user intent and complex model specifications.
        
        - [ ] Model Training and Evaluation: Provide functionality to train and evaluate the generated Keras models directly within the Gemini conversation.
        
        - [ ] Model Persistence: Allow users to save and load their custom-built models for later use.
        
        - [ ] Interactive Model Building: Enable users to iteratively refine their models by adding or removing layers, modifying parameters, and getting feedback in real-time.
        
        ## Contributing
        
        Contributions are what make the open-source community such an amazing place to learn, inspire, and create. Any contributions you make are **greatly appreciated**.
        
        1. Fork the Project
        2. Create your Feature Branch (`git checkout -b feature/AmazingFeature`)
        3. Commit your Changes (`git commit -m 'Add some AmazingFeature'`)
        4. Push to the Branch (`git push origin feature/AmazingFeature`)
        5. Open a Pull Request
        
        ## License
        
        Distributed under the MIT License. See [License](https://github.com/wkambale/keras_gemini/blob/main/LICENSE) for more information.