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Fillipy 🦙

AI-Powered Assistant for Seamless Form Filling

🌟 Overview

Fillipy is an innovative AI tool designed to assist users in filling out complex forms with ease. Using advanced language models, Fillipy analyzes form content, extracts all required fields and instructions, and provides detailed guidance to ensure accurate and hassle-free completion.

Currently, Fillipy supports USCIS Forms I-9 and I-765, with plans to expand to more forms in the future.

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🛠️ Features

• Intelligent Form Analysis: Extracts and structures all necessary fields, instructions, and warnings from uploaded form pages.
• User-Friendly Guidance: Provides clear, actionable steps for filling forms, tailored to user queries.
• Interactive Chat Interface: Allows users to ask for specific details or clarifications about the forms.
• Scalable Design: Built to accommodate more forms and advanced features in upcoming updates.

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🎥 Demo

Check out the live demo on Hugging Face: Fillipy Demo

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📑 Presentation

Explore the project presentation for insights into Fillipy's development: Project Presentation

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🚀 Technologies Used

• Backend: Python
• Frontend: Streamlit
• Models:
  • Llama 3.2-11b for analyzing form content
  • Llama 3-8b for processing user queries
• Hugging Face: Hosting and API integration
• Libraries:
  • PIL (Pillow) for image processing
  • dotenv for managing API keys securely
  • Base64 for encoding image data

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📋 Current Supported Forms

1. USCIS Form I-9
2. USCIS Form I-765

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🔮 Future Plans

• Add support for more USCIS forms and other document types (e.g., tax, healthcare, and education forms).
• Implement auto-filling and error-checking functionalities.
• Introduce multilingual support for broader accessibility.
• Enable secure storage and export of form data.

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💡 How to Use

1. Upload USCIS Form I-9 or I-765 pages to Fillipy.
2. The AI will analyze each page, extract information, and display structured responses.
3. Use the interactive chat interface to ask for specific guidance or details.

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📞 Feedback and Contributions

We’d love to hear your feedback and ideas! Feel free to contribute to the project or raise an issue via GitHub.

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🙌 Acknowledgements

Thank you to the organizers of Llama Impact Hackathon and the Hugging Face community for their incredible support and resources.

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