GC-AI

GC-AI is a web application designed for symbol detection and SBOL3 file generation.

📖 Table of Contents

• Features
• Requirements
• Installation
• Usage
• API Endpoints
• Project Structure
• Documentation
• License

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🖥️ Features

• Symbol Detection: Leverages a trained ML model to identify and classify symbols in input images.
• SBOL3 File Generation: Creates SBOL3 files based on user input and system rules.
• File Conversion: Converts SBOL3 files to GenBank and/or FASTA formats.
• Health Check: Provides an endpoint to verify the application's health.
• Database Integration: Interacts with a MySQL database to retrieve and store relevant data.

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🧩 System Architecture

The following diagram illustrates the complete workflow of GC-AI, from the initial image input and AI detection to the generation of standardized SBOL3 files and optional conversions:

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⚙️ Installation

The installation and setup of this application for local use are provided in the following repository:

• GC-AI Environment

Please refer to that repository for detailed instructions on setting up and running the application.

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🔗 API Endpoints

1. Component Endpoints

1.1 Get Component Names

• Path: /names
• Method: GET
• Description: Returns a list of part names based on a specific role.

1.2 Get Interaction Participations

• Path: /interactions
• Method: GET
• Description: Returns participation types for a specific interaction type.

1.3 Get Component Details

• Path: /details
• Method: GET
• Description: Returns details of a component based on its name.

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2. File Endpoints

2.1 Generate SBOL3 File

• Path: /create
• Method: POST
• Description: Generates validated SBOL3 files.

2.2 Convert SBOL3 Files

• Path: /convert
• Method: POST
• Description: Converts SBOL3 files to GenBank and/or FASTA formats.

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3. Inference Endpoints

3.1 Process Image

• Path: /
• Method: POST
• Description: Processes an image and returns predictions.

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4. Health Endpoints

4.1 Healthcheck

• Path: /
• Method: GET
• Description: Checks the application's health and its services.

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📁 Project Structure

app/: Contains the main application code, including subdirectories:

• data_configs/: Configuration files for data management.
• files_converted/: Stores converted files.
• files_generated/: Stores generated files like SBOL3 outputs.
• models/: Machine learning models and related files.
• routes/: API route definitions.
• utils/: Utility scripts for backend operations.
• run.py: Entry point for the backend.
• requirements.txt: Lists all dependencies.
• gc-ai-backend.log: Log file for backend operations.

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📚 Documentation

For a detailed API reference, user guide, and additional resources, visit the docs folder in this repository. This folder includes:

• API Documentation: Detailed explanations of each endpoint, including parameters, request examples, and responses.
• User Guide: Step-by-step instructions on how to use the application.
• Examples Folder: Contains example files and use cases to better understand the functionality.

Video Tutorial

📝 License

This project is licensed under the MIT License. See the LICENSE file for details.