EmbedAI - Offline Document QnA Solution Prioritizing Privacy and Security

Project Introduction: EmbedAI

EmbedAI offers an innovative solution in the realm of document interactions by enabling the creation of a Q&A chatbot that operates entirely offline. This intriguing project harnesses the power of local language models (LLMs) to ensure that user data stays private and secure, as no information is sent over the internet. This guarantees that all processing and querying of documents can occur seamlessly, without needing an online connection. The inspiration behind EmbedAI draws from the work of a developer known as imartinez.

Overview and Components

The project includes several key components orchestrated to deliver an effective offline chatbot experience:

Getting Started: Users can star the project's repository to receive timely updates and follow the project's developers, Anil Chandra Naidu Matcha and Ankur Singh, on Twitter for the latest news.
Requirements: To deploy EmbedAI, users will need Python 3.8 or later, NodeJS v18.12.1 or beyond, and a minimum of 16GB of memory to ensure smooth operation. These specifications make sure the systems can handle the demand of the local language models.
Running the Project: Users will follow a step-by-step process for installation and deployment:
1. In the client folder, run npm install followed by npm run dev.
2. In the server folder, execute pip install -r requirements.txt and then python privateGPT.py.
3. After setup, users open a local host in a web browser and click to download the necessary model initially.
4. Users can then upload any document, ingest the data quickly, and perform queries, which may take a bit more time due to processing.

Features and Support

Data Privacy and Support: The strict local environment optimizes data privacy while offering a platform for support through a community Discord channel. This enables users to receive help and engage with the community for tips and troubleshooting.
Document Compatibility: EmbedAI supports multiple document formats, making it versatile in terms of the types of documents users can engage with. Supported formats include CSV, Word Documents, EverNote files, Emails, EPubs, HTML files, Markdown, Outlook Messages, Open Document Texts, PDFs, PowerPoint presentations, and standard text files (UTF-8).

Supplementary Resources

EmbedAI provides users with links to additional resources and related repositories to further explore and develop skills:

Langchain Course: A course dedicated to learning with language chains.
ChatGPT Developer Plugins: Resources for developers interested in enhancing chatbot functionalities.
Camel AGI: Tools for those venturing into Artificial General Intelligence projects.

By empowering users to manage their documents privately and efficiently, EmbedAI is positioned as a leading resource for secure offline interactions with personal data.