Update README.md

README.md

@@ -1,180 +1,191 @@
-# Ddroidlabs-mixture-of-agents
-small agentic model designed as a coding assistant
-
-# Mixture of Agents Model (MAM) - Full-Stack Development Team
-
-## Overview
-
-The Mixture of Agents Model (MAM) is an AI-driven full-stack development team that integrates specialized agents for front-end development, back-end development, database management, DevOps, and project management. This unified model leverages a pretrained transformer and fine-tuned datasets to handle a variety of software development tasks efficiently.
-
-## Folder Structure
-
-```
-mixture_of_agents/
-├── app.py
-├── colab_notebook.ipynb
-├── dataset/
-│   └── code_finetune_dataset.json
-├── agents/
-│   ├── front_end_agent.py
-│   ├── back_end_agent.py
-│   ├── database_agent.py
-│   ├── devops_agent.py
-│   └── project_management_agent.py
-├── integration/
-│   └── integration_layer.py
-└── model/
-    ├── load_pretrained_model.py
-    └── fine_tune_model.py
-```
-
-## Setup Instructions
-
-### Prerequisites
-
-- Python 3.7 or higher
-- Flask
-- Google Colab account (for running the notebook)
-- Libraries: `transformers`, `datasets`, `numpy`, `pandas`
-
-### Installation
-
-1. **Clone the Repository:**
-   ```bash
-   git clone https://github.com/your-repo/mixture_of_agents.git
-   cd mixture_of_agents
-   ```
-
-2. **Install Required Libraries:**
-   ```bash
-   pip install -r requirements.txt
-   ```
-
-3. **Upload to Google Drive:**
-   - Upload the `mixture_of_agents` folder to your Google Drive.
-
-4. **Open Colab Notebook:**
-   - Open `colab_notebook.ipynb` in Google Colab.
-
-### Running the Model
-
-1. **Mount Google Drive:**
-   - Mount your Google Drive in Colab by running the first cell of the notebook:
-     ```python
-     from google.colab import drive
-     drive.mount('/content/drive')
-     ```
-
-2. **Install Necessary Packages:**
-   - Install the required packages in the Colab environment:
-     ```python
-     !pip install transformers datasets
-     ```
-
-3. **Load and Fine-Tune the Model:**
-   - Follow the steps in the Colab notebook to load the pretrained model and fine-tune it using the provided dataset:
-     ```python
-     from model.load_pretrained_model import load_model_and_tokenizer
-     model, tokenizer = load_model_and_tokenizer()
-
-     from model.fine_tune_model import fine_tune_model
-     fine_tune_model(model, tokenizer, '/content/drive/MyDrive/mixture_of_agents/dataset/code_finetune_dataset.json')
-     ```
-
-4. **Initialize and Use the Agents:**
-   - Initialize the agents and use the integration layer to process tasks:
-     ```python
-     from agents.front_end_agent import FrontEndAgent
-     from agents.back_end_agent import BackEndAgent
-     from agents.database_agent import DatabaseAgent
-     from agents.devops_agent import DevOpsAgent
-     from agents.project_management_agent import ProjectManagementAgent
-     from integration.integration_layer import IntegrationLayer
-
-     front_end_agent = FrontEndAgent(model, tokenizer)
-     back_end_agent = BackEndAgent(model, tokenizer)
-     database_agent = DatabaseAgent(model, tokenizer)
-     devops_agent = DevOpsAgent(model, tokenizer)
-     project_management_agent = ProjectManagementAgent(model, tokenizer)
-     integration_layer = IntegrationLayer(front_end_agent, back_end_agent, database_agent, devops_agent, project_management_agent)
-
-     task_data = {'task': 'Create a responsive website layout'}
-     result = integration_layer.process_task('front_end', task_data)
-     print(result)
-     ```
-
-### Running the Web Application
-
-1. **Ensure All Agent Files and Integration Layer Are Available:**
-   - Make sure the `agents` and `integration` directories with their respective Python files (`front_end_agent.py`, `back_end_agent.py`, `database_agent.py`, `devops_agent.py`, `project_management_agent.py`, and `integration_layer.py`) are in the same directory as `app.py`.
-
-2. **Run the Application:**
-   - Execute the `app.py` script to start the Flask web server:
-     ```bash
-     python app.py
-     ```
-
-3. **Using the API:**
-   - Open your web browser and navigate to `http://127.0.0.1:5000/` to see the welcome message.
-   - Use a tool like `curl` or Postman to send a POST request to the `/process` endpoint with JSON payload to process tasks.
-
-### Example POST Request
-You can use the following example JSON payload to test the `/process` endpoint:
-
-```json
-{
-  "task_type": "front_end",
-  "task_data": {
-    "task": "Create a responsive website layout"
-  }
-}
-```
-
-**Using `curl`:**
-```bash
-curl -X POST http://127.0.0.1:5000/process -H "Content-Type: application/json" -d '{"task_type": "front_end", "task_data": {"task": "Create a responsive website layout"}}'
-```
-
-## Agent Descriptions
-
-### Front-End Agent
-- **File:** `agents/front_end_agent.py`
-- **Responsibilities:** UI/UX design, HTML, CSS, JavaScript frameworks (React, Vue).
-
-### Back-End Agent
-- **File:** `agents/back_end_agent.py`
-- **Responsibilities:** Server-side logic, API development, frameworks like Node.js, Django.
-
-### Database Agent
-- **File:** `agents/database_agent.py`
-- **Responsibilities:** Database design, query optimization, data migration.
-
-### DevOps Agent
-- **File:** `agents/devops_agent.py`
-- **Responsibilities:** CI/CD pipelines, server management, deployment automation.
-
-### Project Management Agent
-- **File:** `agents/project_management_agent.py`
-- **Responsibilities:** Requirement gathering, task management, progress tracking.
-
-### Integration Layer
-- **File:** `integration/integration_layer.py`
-- **Responsibilities:** Ensures seamless communication and coordination between agents.
-
-## Fine-Tuning Dataset
-
-### Dataset File
-- **File:** `dataset/code_finetune_dataset.json`
-- **Description:** Contains examples of various coding tasks to fine-tune the model for development-related tasks.
-
-## Contributing
-
-Contributions are welcome! Please fork the repository and create a pull request with your changes. Ensure your code follows the project's style guidelines and includes appropriate tests.
-
-## License
-
-This project is licensed under the apache-2.0  License.
-
-## Contact
-
-For any questions or issues, please open an issue on GitHub or contact the repository maintainer.
+---
+license: apache-2.0
+language:
+- en
+metrics:
+- code_eval
+library_name: adapter-transformers
+pipeline_tag: text-generation
+tags:
+- code
+---
+# Ddroidlabs-mixture-of-agents
+small agentic model designed as a coding assistant
+
+# Mixture of Agents Model (MAM) - Full-Stack Development Team
+
+## Overview
+
+The Mixture of Agents Model (MAM) is an AI-driven full-stack development team that integrates specialized agents for front-end development, back-end development, database management, DevOps, and project management. This unified model leverages a pretrained transformer and fine-tuned datasets to handle a variety of software development tasks efficiently.
+
+## Folder Structure
+
+```
+mixture_of_agents/
+├── app.py
+├── colab_notebook.ipynb
+├── dataset/
+│   └── code_finetune_dataset.json
+├── agents/
+│   ├── front_end_agent.py
+│   ├── back_end_agent.py
+│   ├── database_agent.py
+│   ├── devops_agent.py
+│   └── project_management_agent.py
+├── integration/
+│   └── integration_layer.py
+└── model/
+    ├── load_pretrained_model.py
+    └── fine_tune_model.py
+```
+
+## Setup Instructions
+
+### Prerequisites
+
+- Python 3.7 or higher
+- Flask
+- Google Colab account (for running the notebook)
+- Libraries: `transformers`, `datasets`, `numpy`, `pandas`
+
+### Installation
+
+1. **Clone the Repository:**
+   ```bash
+   git clone https://github.com/your-repo/mixture_of_agents.git
+   cd mixture_of_agents
+   ```
+
+2. **Install Required Libraries:**
+   ```bash
+   pip install -r requirements.txt
+   ```
+
+3. **Upload to Google Drive:**
+   - Upload the `mixture_of_agents` folder to your Google Drive.
+
+4. **Open Colab Notebook:**
+   - Open `colab_notebook.ipynb` in Google Colab.
+
+### Running the Model
+
+1. **Mount Google Drive:**
+   - Mount your Google Drive in Colab by running the first cell of the notebook:
+     ```python
+     from google.colab import drive
+     drive.mount('/content/drive')
+     ```
+
+2. **Install Necessary Packages:**
+   - Install the required packages in the Colab environment:
+     ```python
+     !pip install transformers datasets
+     ```
+
+3. **Load and Fine-Tune the Model:**
+   - Follow the steps in the Colab notebook to load the pretrained model and fine-tune it using the provided dataset:
+     ```python
+     from model.load_pretrained_model import load_model_and_tokenizer
+     model, tokenizer = load_model_and_tokenizer()
+
+     from model.fine_tune_model import fine_tune_model
+     fine_tune_model(model, tokenizer, '/content/drive/MyDrive/mixture_of_agents/dataset/code_finetune_dataset.json')
+     ```
+
+4. **Initialize and Use the Agents:**
+   - Initialize the agents and use the integration layer to process tasks:
+     ```python
+     from agents.front_end_agent import FrontEndAgent
+     from agents.back_end_agent import BackEndAgent
+     from agents.database_agent import DatabaseAgent
+     from agents.devops_agent import DevOpsAgent
+     from agents.project_management_agent import ProjectManagementAgent
+     from integration.integration_layer import IntegrationLayer
+
+     front_end_agent = FrontEndAgent(model, tokenizer)
+     back_end_agent = BackEndAgent(model, tokenizer)
+     database_agent = DatabaseAgent(model, tokenizer)
+     devops_agent = DevOpsAgent(model, tokenizer)
+     project_management_agent = ProjectManagementAgent(model, tokenizer)
+     integration_layer = IntegrationLayer(front_end_agent, back_end_agent, database_agent, devops_agent, project_management_agent)
+
+     task_data = {'task': 'Create a responsive website layout'}
+     result = integration_layer.process_task('front_end', task_data)
+     print(result)
+     ```
+
+### Running the Web Application
+
+1. **Ensure All Agent Files and Integration Layer Are Available:**
+   - Make sure the `agents` and `integration` directories with their respective Python files (`front_end_agent.py`, `back_end_agent.py`, `database_agent.py`, `devops_agent.py`, `project_management_agent.py`, and `integration_layer.py`) are in the same directory as `app.py`.
+
+2. **Run the Application:**
+   - Execute the `app.py` script to start the Flask web server:
+     ```bash
+     python app.py
+     ```
+
+3. **Using the API:**
+   - Open your web browser and navigate to `http://127.0.0.1:5000/` to see the welcome message.
+   - Use a tool like `curl` or Postman to send a POST request to the `/process` endpoint with JSON payload to process tasks.
+
+### Example POST Request
+You can use the following example JSON payload to test the `/process` endpoint:
+
+```json
+{
+  "task_type": "front_end",
+  "task_data": {
+    "task": "Create a responsive website layout"
+  }
+}
+```
+
+**Using `curl`:**
+```bash
+curl -X POST http://127.0.0.1:5000/process -H "Content-Type: application/json" -d '{"task_type": "front_end", "task_data": {"task": "Create a responsive website layout"}}'
+```
+
+## Agent Descriptions
+
+### Front-End Agent
+- **File:** `agents/front_end_agent.py`
+- **Responsibilities:** UI/UX design, HTML, CSS, JavaScript frameworks (React, Vue).
+
+### Back-End Agent
+- **File:** `agents/back_end_agent.py`
+- **Responsibilities:** Server-side logic, API development, frameworks like Node.js, Django.
+
+### Database Agent
+- **File:** `agents/database_agent.py`
+- **Responsibilities:** Database design, query optimization, data migration.
+
+### DevOps Agent
+- **File:** `agents/devops_agent.py`
+- **Responsibilities:** CI/CD pipelines, server management, deployment automation.
+
+### Project Management Agent
+- **File:** `agents/project_management_agent.py`
+- **Responsibilities:** Requirement gathering, task management, progress tracking.
+
+### Integration Layer
+- **File:** `integration/integration_layer.py`
+- **Responsibilities:** Ensures seamless communication and coordination between agents.
+
+## Fine-Tuning Dataset
+
+### Dataset File
+- **File:** `dataset/code_finetune_dataset.json`
+- **Description:** Contains examples of various coding tasks to fine-tune the model for development-related tasks.
+
+## Contributing
+
+Contributions are welcome! Please fork the repository and create a pull request with your changes. Ensure your code follows the project's style guidelines and includes appropriate tests.
+
+## License
+
+This project is licensed under the apache-2.0  License.
+
+## Contact
+
+For any questions or issues, please open an issue on GitHub or contact the repository maintainer.