3 个仓库
Securely extracting and processing information from unstructured documents like PDFs and images.
Distinct from Private Data Processing Environments: Focuses on document content extraction and analysis rather than just the network isolation of the processing environment.
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DocsGPT is a retrieval-augmented generation platform and private knowledge base used to build AI agents that perform grounded search and analysis. It functions as a multi-model AI orchestrator and enterprise agent builder, allowing for the integration of various local and cloud language models to customize reasoning and text generation. The project provides a visual environment for developing automated assistants using conditional logic and third-party API connectivity. It enables the creation of private AI agents capable of performing enterprise search and detailed document analysis using pr
Enables detailed analysis and insight extraction from private PDFs, office files, and images.
Doxx is a collection of shell-based tools for parsing, viewing, and converting word processing files. It provides a terminal user interface for reading and searching DOCX files without requiring external office software, functioning as both a terminal document viewer and a command line parser. The project distinguishes itself by offering a full TUI document reader with outline navigation and the ability to export document content and metadata into alternative formats such as Markdown, CSV, JSON, and plain text. The system covers a broad range of capabilities including document metadata analy
Retrieves structural information and file properties from Word documents for reporting and data processing.
This project is a private document analysis tool that enables conversational interaction with PDF files by executing all language model inference and processing entirely on the local machine. By running models directly within the browser or local environment, it ensures that sensitive user data remains offline and inaccessible to external servers or third-party cloud providers. The system utilizes retrieval augmented generation to provide context-aware answers, supported by local document text extraction and vector embedding indexing. This architecture allows for semantic search and informati
Processes sensitive PDF files locally to answer questions without sending data to external servers.