Develop a Cross-Platform Personal AI Platform for Privacy, Local Use – On Device Use
Job Description:
We are looking for an experienced developer or team to build a Personal AI Platform, a cross-platform desktop application that allows users to interact with a local, open-source AI system. This platform will act as a private, offline assistant, capable of answering questions, running custom prompts, searching local data, and laying the foundation for future agent-based workflows.
The application will prioritize privacy by operating entirely offline, use open-source AI models, and provide users with an intuitive interface for managing and extending its capabilities.
Core Features:
1. Private, Local AI:
• Deploy open-source AI models like LLaMA 2, Falcon, or GPT4All locally on the user’s device.
• Support quantized models for efficient use on a wide range of hardware.
2. Multifunctional Assistant:
• Respond to prompts and questions in natural language.
• Perform local file searches (e.g., searching documents, notes, or other user-provided datasets).
• Summarize, rewrite, and generate text content.
3. Extensibility for Agents:
• Provide APIs or modular architecture for future agent-based workflows (e.g., task automation, advanced multi-step operations).
• Include a basic agent module to showcase potential (e.g., automated email drafting, calendar scheduling).
4. Search and Local Integration:
• Local search capabilities with AI-enhanced query understanding.
• Optionally index local documents for more advanced AI-powered retrieval.
5. Customization and Fine-Tuning:
• Allow users to fine-tune the AI models with their own datasets.
• Enable easy integration of additional plugins or modules.
6. Privacy and Security:
• Ensure that all processing occurs locally without internet connectivity.
• Provide tools for managing and encrypting user data.
7. User Interface:
• A modern, easy-to-use GUI for non-technical users.
• Features for input prompts, viewing responses, managing models, and accessing settings.
Responsibilities:
1. Application Development:
• Build a cross-platform desktop application using frameworks like Electron.js, Flutter, or similar.
• Implement a seamless installation process for Windows, macOS, and Linux.
2. Model Integration:
• Integrate open-source AI models (e.g., LLaMA 2, Falcon) using libraries like Transformers or llama.cpp.
• Optimize models for local use with quantization techniques (e.g., 4-bit/8-bit).
3. Backend Functionality:
• Develop a backend server (e.g., using FastAPI, Flask) to handle model inference and API calls.
• Implement local file search and indexing with AI enhancements.
4. Modular Design:
• Build a modular architecture for extending the app with agents and plugins.
• Expose APIs for advanced users to add or modify functionalities.
5. Extensibility for Agents:
• Include a basic agent builder or workflow editor for future extensibility.
• Provide examples of agents (e.g., automating tasks, parsing documents, generating reports).
6. Testing and Optimization:
• Test across multiple platforms to ensure performance and compatibility.
• Optimize for both high-end and low-resource hardware.
Deliverables:
1. Fully functional Personal AI Platform application for Windows, macOS, and Linux.
2. Source code and documentation for maintaining and extending the platform.
3. Packaged executables for all supported platforms.
4. A user manual with clear instructions for installation, usage, and customization.
5. APIs or SDKs for developers to build additional agents or workflows.
Skills and Experience Required:
• Strong experience with Python for backend development (e.g., FastAPI, Flask).
• Proficiency in AI frameworks like Transformers, llama.cpp, or similar.
• Experience building desktop applications using Electron.js, Flutter, or Tkinter.
• Knowledge of open-source AI models and quantization techniques for local use.
• Familiarity with modular software design and API development.
• Strong focus on privacy and offline functionality.
Bonus Skills:
• Experience with LangChain, Haystack, or similar frameworks for workflow development.
• Knowledge of file indexing/search tools (e.g., Apache Lucene, Whoosh).
• Experience implementing encryption and security for local applications.
• Background in creating or fine-tuning AI agents.
Project Timeline:
6–8 weeks, with milestones for:
1. Initial design and architecture.
2. Model integration and backend functionality.
3. GUI development and testing.
4. Packaging and deployment.
Budget:
$10,000–$15,000 (negotiable based on experience and deliverables).
How to Apply:
Please include the following in your proposal:
1. Examples of previous AI-based applications or desktop apps you’ve built.
2. A brief explanation of your approach to this project.
3. Estimated timeline and milestones.
4. Tools, frameworks, and technologies you plan to use.
5. Any questions or clarifications about the project.
SAMPLE APPROACH – Attached. VERY simple UI is ONLY an example — want a great UX: https://claude.site/artifacts/96050ed6-9020-40c2-8d75-8e109f284b61
This is a unique opportunity to work on a cutting-edge project that combines privacy, AI, and extensibility for future innovations. Let us know if you have the vision and skills to bring this idea to life!
