Frontend Overview

Implementation Details

The frontend of the Agentic Election Prediction System is implemented using modern web technologies to ensure a responsive and user-friendly interface. The main technologies used are:

React: A JavaScript library for building user interfaces.
Tailwind CSS: A utility-first CSS framework for styling.
React Router: A library for routing in React applications.
React Query: A library for fetching, caching, and updating data in React applications.
Lucide Icons: A library for using icons in the application.

The frontend is structured into various components, each responsible for a specific part of the user interface. These components are organized in a way that promotes reusability and maintainability.

Architecture

The architecture of the frontend follows a component-based approach, where each component is responsible for a specific part of the user interface. The main components are:

App: The root component that sets up the application and includes the main layout.
Header: The component responsible for displaying the header of the application.
Sidebar: The component responsible for displaying the sidebar navigation.
Footer: The component responsible for displaying the footer of the application.
Dashboard: The main dashboard component that displays the global election prediction dashboard.
AIInterface: The component for interacting with the AI assistant.
ControlConsole: The component for controlling various aspects of the application.
Settings: The component for managing application settings.
Predictions: The component for displaying election predictions.
DataSources: The component for managing data sources.
AgentDeployment: The component for deploying and managing agents.
LibrarySection: The component for managing reusable components and templates.
TacticsSection: The component for managing civic engagement tactics.

Development Instructions

To set up the development environment for the frontend, follow these steps:

Clone the repository:

git clone https://github.com/ruvnet/Electo1.git
cd Electo1

Navigate to the frontend directory:
```
cd frontend
```
Install dependencies:
```
npm install
```
Run the development server:
```
npm start
```
Open the application in your browser: Open your browser and navigate to https://localhost:3000.

API Details

The frontend interacts with the backend API to fetch and update data. The main API endpoints used by the frontend are:

Predictions:
- POST /api/predictions/: Create a new prediction
- GET /api/predictions/: List all predictions
- GET /api/predictions/{id}: Get a specific prediction
- PUT /api/predictions/{id}: Update a prediction
- DELETE /api/predictions/{id}: Delete a prediction
Data Sources:
- POST /api/data_sources/: Add a new data source
- GET /api/data_sources/: List all data sources
- GET /api/data_sources/{id}: Get a specific data source
- PUT /api/data_sources/{id}: Update a data source
- DELETE /api/data_sources/{id}: Delete a data source
Agent Deployment:
- POST /api/agent_deployment/: Deploy a new agent
- GET /api/agent_deployment/: List all deployed agents
- GET /api/agent_deployment/{id}: Get a specific agent deployment
- PUT /api/agent_deployment/{id}: Update an agent deployment
- DELETE /api/agent_deployment/{id}: Remove an agent deployment
Library:
- POST /api/library/: Add a new library item
- GET /api/library/: List all library items
- GET /api/library/{id}: Get a specific library item
- PUT /api/library/{id}: Update a library item
- DELETE /api/library/{id}: Delete a library item
Settings:
- POST /api/settings/: Create a new setting
- GET /api/settings/: List all settings
- GET /api/settings/{key}: Get a specific setting
- PUT /api/settings/{key}: Update a setting
- DELETE /api/settings/{key}: Delete a setting
Tactics:
- POST /api/tactics/: Create a new tactic
- GET /api/tactics/: List all tactics
- GET /api/tactics/{id}: Get a specific tactic
- PUT /api/tactics/{id}: Update a tactic
- DELETE /api/tactics/{id}: Delete a tactic

Conclusion

The frontend of the Agentic Election Prediction System is designed to be modular, scalable, and user-friendly. By following the development instructions and understanding the architecture and API details, developers can easily contribute to and extend the functionality of the frontend.

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