README.md

metadata

title: Report Genie
emoji: 📄
colorFrom: blue
colorTo: purple
sdk: docker
app_port: 7860
license: mit
short_description: Report Genie - An AI-powered automatic report generator

Report Genie - An AI-powered automatic report generator

An AI-powered automatic report generator using CrewAI and Gradio

Overview

Report Genie is an AI-driven report generation tool that automates the process of creating detailed and structured reports. Leveraging the power of CrewAI for task delegation and Gradio for an interactive user interface, this application streamlines report generation with minimal user input.

Features

• AI-powered automation: Uses advanced AI agents to generate reports.
• Interactive UI: Built with Gradio for an intuitive and user-friendly interface.
• Customizable reports: Supports multiple report formats and structures.
• Efficient task delegation: CrewAI intelligently assigns subtasks to optimize the workflow.
• Seamless integration: Can be integrated with external data sources for enhanced report accuracy.
• Company data retrieval: Uses Neo4J to fetch company data from the database.

Tech Stack

• Python: Core programming language.
• CrewAI: Agent-based AI framework for task automation.
• Gradio: Web-based UI for interactive user interaction.
• Google Gemini Flash: LLM used for text generation and processing.
• Neo4J: Graph database for retrieving company data.
• Pandas (optional): For data manipulation and analysis.

Backend Configuration

Prerequisites

1. Install uv if not already installed:

   pip install uv
   

2. Navigate to your project directory and install dependencies:

   crewai install
   

   (Optional: Lock dependencies using the CLI command.)

Customization

1. Add environment variables to the .env file take reference from .env.example file.:

   MODEL=gemini/gemini-1.5-flash
   MODEL_API_KEY=<model_api_key> # Your API key here
   

   Generate a new API key for GEMINI model from the AI Studio website.

2. Modify configuration files as needed:

   • src/report_genie/config/agents.yaml: Define your agents.
   • src/report_genie/config/tasks.yaml: Define your tasks.
   • src/report_genie/crew.py: Add custom logic, tools, and arguments.
   • src/report_genie/main.py: Customize inputs for agents and tasks.
   • src/report_genie/app.py: Configure Gradio app settings.

Running the Backend

To start the backend server and execute tasks:

uv run report_genie

The Gradio interface will be available at http://localhost:7860/.

Deployment

The app is deployed on Hugging Face Spaces. You can try it out here.

Additional Notes

• Ensure all environment variables are correctly set in the .env file.
• Regularly update your agents and tasks configuration to enhance functionality.
• Refer to the CrewAI documentation for advanced customizations.

The Gradio app allows users to interact with the backend and generate reports.

Future Enhancements

• Support for multi-language reports.
• Integration with cloud storage.
• Export to additional formats like Excel, PPT, and JSON.

License

MIT License

Contributors

• Deepak Pant (@DeepakPant93)

Acknowledgements

• Neo4J: Neo4J Companies Database for retrieving company data.
• Sample code for reference.
• Neo4J Blog: Implement an Automated Report-Generation Agent with crewAI and Neo4j

Contact

For any queries, reach out at deepak.93p@gmail.com.

Support

If you like my work and want to support give a ⭐ to the repo.

Thank you so much ❤️.