Search Results for "open document"
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Showing 64 open source projects for "open document"
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text-extract-api
Document (PDF, Word, PPTX ...) extraction and parse API
text-extract-api is an open-source service designed to extract readable text from a wide variety of document formats through a simple API interface. The project focuses on converting complex files such as PDFs, images, scanned documents, and office files into structured plain text that can be processed by downstream applications or language models. Instead of requiring developers to integrate multiple document parsing libraries individually, the system centralizes text extraction capabilities into a unified API that standardizes the output. ... -
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Sparrow
Structured data extraction and instruction calling with ML, LLM
...It combines several components, including OCR pipelines, vision-language models, and LLM-based reasoning modules to identify and extract meaningful data fields from heterogeneous document layouts. The architecture is modular, allowing developers to build customizable processing pipelines that integrate with external tools and data extraction frameworks. Sparrow also includes workflow orchestration tools that allow multiple extraction tasks to be combined into automated pipelines for large-scale document processing. -
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AnythingLLM
The all-in-one Desktop & Docker AI application with full RAG and AI
A full-stack application that enables you to turn any document, resource, or piece of content into a context that any LLM can use as references during chatting. This application allows you to pick and choose which LLM or Vector Database you want to use as well as supporting multi-user management and permissions. AnythingLLM is a full-stack application where you can use commercial off-the-shelf LLMs or popular open-source LLMs and vectorDB solutions to build a private ChatGPT with no compromises that you can run locally as well as host remotely and be able to chat intelligently with any documents you provide it. ... -
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MarkPDFDown
A high-quality PDF to Markdown tool based on large language model
MarkPDFdown is an open-source document processing tool designed to convert PDF files into structured Markdown output that can be easily used for documentation, content pipelines, and AI processing workflows. The project focuses on extracting text, formatting, and structural information from complex PDF documents and transforming that information into clean Markdown that preserves the original hierarchy of headings, paragraphs, tables, and lists. -
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DocETL
A system for agentic LLM-powered data processing and ETL
DocETL is an open-source system designed to build and execute data processing pipelines powered by large language models, particularly for analyzing complex collections of documents and unstructured datasets. The platform allows developers and researchers to construct structured workflows that extract, transform, and organize information from sources such as reports, transcripts, legal documents, and other text-heavy data. -
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llmware
Unified framework for building enterprise RAG pipelines
llmware is an open source framework designed to simplify the creation of enterprise-grade applications powered by large language models. The platform focuses on building secure and private AI workflows that can run locally on laptops, edge devices, or self-hosted servers without relying exclusively on cloud APIs. It provides a unified interface for constructing retrieval-augmented generation pipelines, agent workflows, and document intelligence applications. -
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MegaParse
File Parser optimised for LLM Ingestion with no loss
MegaParse is a file parser optimized for Large Language Model (LLM) ingestion, ensuring no loss of information. It efficiently parses various document formats, such as PDFs, DOCX, and PPTX, converting them into formats ideal for processing by LLMs. This tool is essential for applications that require accurate and comprehensive data extraction from diverse document types. -
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RAPTOR
The official implementation of RAPTOR
RAPTOR is a retrieval architecture designed to improve retrieval-augmented generation systems by organizing documents into hierarchical structures that enable more effective context retrieval. Traditional RAG systems typically retrieve small text chunks independently, which can limit a model’s ability to understand broader document context. RAPTOR addresses this limitation by recursively embedding, clustering, and summarizing documents to create a tree-structured hierarchy of information.... -
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chatd
Chat with your documents using local AI
chatd is an open-source desktop application that allows users to interact with their documents through a locally running large language model. The software focuses on privacy and security by ensuring that all document processing and inference occur entirely on the user’s computer without sending data to external cloud services. It includes a built-in integration with the Ollama runtime, which provides a cross-platform environment for running large language models locally. ... -
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NativeMind Extension
Your fully private, open-source, on-device AI assistant
NativeMindExtension is an open-source browser extension that provides a private, on-device AI assistant designed to run without cloud dependencies. The project is built around a privacy-first model in which conversations, document analysis, translations, and writing assistance stay on the user’s device rather than being sent to external servers. It integrates with local model back ends such as Ollama and also supports WebLLM for quick in-browser trials, giving users a choice between stronger local setups and lighter no-install demonstrations. ... -
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Generative AI Use Cases (GenU)
Application implementation with business use cases
AWS Generative AI Use Cases is an open-source repository developed by AWS that provides practical examples and reference implementations for building applications powered by generative artificial intelligence. The project collects a wide range of real-world scenarios that demonstrate how organizations can use large language models and generative AI services within cloud-based architectures. -
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GPT Academic
Research-oriented chatbot framework
GPT Academic is a research-oriented chatbot framework designed to integrate large language models (LLMs) into academic workflows. It provides tools for structured document processing, citation management, and enhanced interaction with research papers. -
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LongBench
LongBench v2 and LongBench (ACL 25'&24')
LongBench is a comprehensive benchmark designed to evaluate the ability of large language models to understand and reason over very long textual contexts. Traditional language model benchmarks typically evaluate tasks involving relatively short inputs, which does not reflect many real-world applications such as analyzing large documents or entire code repositories. LongBench addresses this gap by providing datasets that require models to process and reason over long sequences of text across... -
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LLM-Aided OCR Project
Enhances Tesseract OCR output using LLMs (local or API)
...The project is particularly useful for digitizing historical documents, research papers, and scanned materials where traditional OCR often struggles. It also includes tools for processing batches of images or documents, enabling automated document digitization workflows. -
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Lemon AI
Full-stack Open-source Self-Evolving General AI Agent
LemonAI is an open-source full-stack framework for building autonomous AI agents capable of performing complex tasks such as research, programming, data analysis, and document processing. The platform is designed to run primarily on local infrastructure, providing a privacy-focused alternative to cloud-dependent agent platforms. It integrates with local large language models through tools such as Ollama, vLLM, and other model runtimes while also allowing optional connections to external cloud models. ... -
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DocStrange
Extract and convert data from any document, images, pdfs, word doc
DocStrange is an open-source document understanding and extraction library designed to convert complex files into structured, LLM-ready outputs such as Markdown, JSON, CSV, and HTML. Developed by Nanonets, the project combines OCR, layout detection, table understanding, and structured extraction into one end-to-end pipeline, which reduces the need to stitch together multiple separate services. -
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BISHENG
BISHENG is an open LLM devops platform for next generation apps
BISHENG is an open LLM application DevOps platform, focusing on enterprise scenarios. It has been used by a large number of industry-leading organizations and Fortune 500 companies. "Bi Sheng" was the inventor of movable type printing, which played a vital role in promoting the transmission of human knowledge. We hope that BISHENG can also provide strong support for the widespread implementation of intelligent applications. Everyone is welcome to participate. -
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PrivateGPT
Interact with your documents using the power of GPT
PrivateGPT is a production-ready, privacy-first AI system that allows querying of uploaded documents using LLMs, operating completely offline in your own environment. It provides contextual generative AI capabilities without sending data externally. Now maintained under Zylon.ai with enterprise deployment options (air gapped, cloud, or on-prem). -
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Hallucination Leaderboard
Leaderboard Comparing LLM Performance at Producing Hallucinations
Hallucination Leaderboard is an open research project that tracks and compares the tendency of large language models to produce hallucinated or inaccurate information when generating summaries. The project provides a standardized benchmark that evaluates different models using a dedicated hallucination detection system known as the Hallucination Evaluation Model. Each model is tested on document summarization tasks to measure how often generated responses introduce information that is not supported by the original source material. ... -
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Kernel Memory
Research project. A Memory solution for users, teams, and applications
Kernel Memory is an open-source reference architecture developed by Microsoft to help developers build memory systems for AI applications powered by large language models. The project focuses on enabling applications to store, index, and retrieve information so that AI systems can incorporate external knowledge when generating responses. It supports scenarios such as document ingestion, semantic search, and retrieval-augmented generation, allowing language models to answer questions using contextual information from private or enterprise datasets. ... -
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Extractous
Fast and efficient unstructured data extraction
Extractous is a Rust-based unstructured data extraction library focused on fast local parsing of documents and other content-heavy files. Its purpose is to extract text and metadata efficiently from formats such as PDF, Word, HTML, email archives, images, and more, without depending on external APIs or separate parsing servers. The project emphasizes performance and low memory usage, and its maintainers describe it as a local-first alternative to heavier extraction stacks. For broader format... -
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DB-GPT
Revolutionizing Database Interactions with Private LLM Technology
DB-GPT is an experimental open-source project that uses localized GPT large models to interact with your data and environment. With this solution, you can be assured that there is no risk of data leakage, and your data is 100% private and secure. -
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nashsu LLM Wiki
LLM Wiki is a cross-platform desktop application
nashsu LLM Wiki is a project designed to create a structured, navigable knowledge base powered by large language models, enabling users to explore information in a wiki-like format. It likely transforms raw data or documents into interconnected pages that can be dynamically generated and summarized by AI. The system emphasizes discoverability, allowing users to navigate topics through links and relationships rather than static search results. It may include mechanisms for content generation,... -
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CSGHub
CSGHub is a brand-new open-source platform for managing LLMs
CSGHub is an open-source framework designed for collaborative scientific research and content generation. It enables researchers to utilize AI-driven tools for literature review, hypothesis generation, and automated writing assistance, streamlining the scientific discovery process. -
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LangServe
Helps developers deploy LangChain runnables and chains as a REST API
...It also includes client libraries that allow developers to interact with deployed chains from Python or JavaScript applications. LangServe is commonly used to deploy AI applications such as chatbots, document analysis pipelines, and agent-based systems that require scalable access through APIs.
