chore(integration): submit Sales Prediction App using uAgents for Fetch.ai hackathon #498
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Sales Prediction App
Overview
This repository contains a Sales Prediction Application that utilizes Flask for the backend, uAgents for agent-based operations, and a custom-developed machine learning model for predicting future sales based on historical data. The application is designed to provide businesses with actionable insights into future sales trends, helping them make informed decisions.
Features
Installation
Prerequisites
Ensure you have the following installed on your system:
Setup Instructions
Clone the repository:
git clone https:/your-username/sales-prediction-app.git cd sales-prediction-app
Create a virtual environment:
Install dependencies:
Run the Flask application:
python app.py
uAgents Integration
This application uses uAgents for distributed processing, allowing it to handle large datasets and complex operations efficiently. The uAgents are configured to:
Receive and Process Data: Agents receive sales data from the Flask backend and preprocess it for prediction.
Model Execution: uAgents handle the execution of the custom prediction model, ensuring scalability and robustness.
Return Predictions: Processed predictions are sent back to the Flask backend for user access.
Usage
Navigate to the /upload endpoint to upload your CSV file containing historical sales data.
The CSV file should have columns like Date, Sales, Product_ID, etc., depending on the model's requirements.
After uploading the data, navigate to the /predict endpoint.
The model will process the data and return predictions for future sales.
Predictions can be viewed directly on the web interface or downloaded as a CSV file for further analysis.
Future Enhancements: