Search Results for "document" - Page 3
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Showing 270 open source projects for "document"
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DeepCode
DeepCode: Open Agentic Coding
...The system description highlights an orchestration layer that plans, assigns subtasks, and adapts strategies as complexity changes, rather than relying on a single monolithic prompt. It also describes document parsing capabilities aimed at extracting algorithmic and mathematical details from technical materials, translating them into implementable specifications and code. -
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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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OpenKM Document Management - DMS
Document Management System and Content Management System
OpenKM Community Edition is a free Document Management System (DMS) that helps businesses control the production, storage, management and distribution of electronic documents, boosting effectiveness and productivity. It integrates document management, collaboration and advanced search into one easy-to-use solution, including administration tools for user roles, access control, security levels, activity logs and automation setup. -
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Project NOMAD
Self-contained, offline survival computer with tools, knowledge, & AI
Project N.O.M.A.D. (Node for Offline Media, Archives, and Data) is a self-contained, offline-first knowledge and education server designed to run on local hardware. It combines AI, educational resources, and critical information tools into a single platform accessible through a web browser. Built as a containerized system managed via Docker, it orchestrates multiple applications through a centralized “Command Center” interface. NOMAD enables users to access offline Wikipedia, AI chat, maps,... -
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AionUi
Free, local, open-source Cowork for Gemini CLI, Claude Code, Codex
...It enhances productivity by offering smart file management features like batch renaming, automatic organization, and intelligent file classification, thereby reducing manual overhead when working with large datasets or complex document structures. AionUi also supports a remote WebUI mode, allowing users to access their local AI tools securely over a network from other devices while keeping all processing and data on their own hardware. -
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fireworks-tech-graph
Claude Code skill for generating production-quality SVG+PNG technical
...The project emphasizes scalability and adaptability, allowing it to handle large datasets and evolving knowledge bases. By structuring information into graph form, it enables more meaningful navigation and discovery compared to traditional document-based systems. -
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EasyOCR
Ready-to-use OCR with 80+ supported languages
Ready-to-use OCR with 80+ supported languages and all popular writing scripts including Latin, Chinese, Arabic, Devanagari, Cyrillic and etc. EasyOCR is a python module for extracting text from image. It is a general OCR that can read both natural scene text and dense text in document. We are currently supporting 80+ languages and expanding. Second-generation models: multiple times smaller size, multiple times faster inference, additional characters and comparable accuracy to the first generation models. EasyOCR will choose the latest model by default but you can also specify which model to use. Model weights for the chosen language will be automatically downloaded or you can download them manually from the model hub. ... -
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ExtractThinker
ExtractThinker is a Document Intelligence library for LLMs
ExtractThinker is a tool designed to facilitate the extraction and analysis of information from various data sources, aiding in data processing and knowledge discovery. -
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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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DocTR
Library for OCR-related tasks powered by Deep Learning
...Seemlessly process documents for Natural Language Understanding tasks: we provide OCR predictors to parse textual information (localize and identify each word) from your documents. Robust 2-stage (detection + recognition) OCR predictors with pretrained parameters. User-friendly, 3 lines of code to load a document and extract text with a predictor. State-of-the-art performances on public document datasets, comparable with GoogleVision/AWS Textract. Easy integration (available templates for browser demo & API deployment). End-to-End OCR is achieved in docTR using a two-stage approach: text detection (localizing words), then text recognition (identify all characters in the word). ... -
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huggingface_hub
The official Python client for the Huggingface Hub
The huggingface_hub library allows you to interact with the Hugging Face Hub, a platform democratizing open-source Machine Learning for creators and collaborators. Discover pre-trained models and datasets for your projects or play with the thousands of machine-learning apps hosted on the Hub. You can also create and share your own models, datasets, and demos with the community. The huggingface_hub library provides a simple way to do all these things with Python. -
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GLM-4.6V
GLM-4.6V/4.5V/4.1V-Thinking, towards versatile multimodal reasoning
...Unlike many vision-language models that treat images and text separately or require intermediate conversions, GLM-4.6V allows inputs such as images, screenshots or document pages directly as part of its reasoning pipeline — and can output or act via tools seamlessly, bridging perception and execution. Its architecture supports a very large context window (on the order of 128K tokens during training), which lets it handle complex multimodal inputs like long documents, multi-page reports, or video transcripts, while maintaining coherence across extended content. ... -
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DeepSeek-OCR 2
Visual Causal Flow
DeepSeek-OCR-2 is the second-generation optical character recognition system developed to improve document understanding by introducing a “visual causal flow” mechanism, enabling the encoder to reorder visual tokens in a way that better reflects semantic structure rather than strict raster scan order. It is designed to handle complex layouts and noisy documents by giving the model causal reasoning capabilities that mimic human visual scanning behavior, enhancing OCR performance on documents with rich spatial structure. ... -
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Large Language Models (LLMs)
Connect MATLAB to LLM APIs, including OpenAI® Chat Completions
This repository enables MATLAB to connect with large language models (LLMs) such as OpenAI's ChatGPT, DALL-E, Azure OpenAI, and Ollama, integrating their natural language processing and image generation capabilities directly within MATLAB environments. It facilitates creating chatbots, summarizing text, and image generation, among other tasks. -
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Extractous
Fast and efficient unstructured data extraction
...For broader format support, the system combines its Rust core with ahead-of-time compiled Apache Tika shared libraries, which allows it to extend parsing coverage while still avoiding traditional server-based overhead. It also supports OCR for images and scanned documents through Tesseract, making it useful for document ingestion pipelines that include image-based or scanned inputs. -
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Kernel Memory
Research project. A Memory solution for users, teams, and applications
...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. Kernel Memory can ingest documents in multiple formats, process them into embeddings, and store them in searchable indexes. Applications can then query these indexed data sources to retrieve relevant information and include it as context for AI responses. -
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GitHub Copilot SDK
Multi-platform SDK for integrating GitHub Copilot Agent into apps
...Instead of being limited to editors like VS Code, this SDK lets teams embed Copilot-style code suggestions, natural language assistance, and predictive completions anywhere they see fit—such as internal IDEs, browser extensions, documentation portals, or bespoke tools tailored to specific languages or frameworks. It provides a structured API surface for invoking the Copilot model in context with the surrounding user state, capturing document content, cursor position, and invocation triggers so suggestions are relevant and responsive. The SDK includes helpers for streaming completions, managing rate limits, handling authentication, and integrating with telemetry and analytics pipelines. -
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GLM-4.5V
GLM-4.6V/4.5V/4.1V-Thinking, towards versatile multimodal reasoning
...It embodies the design philosophy of mixing visual and textual modalities into a unified model capable of general-purpose reasoning, content understanding, and generation, while already supporting a wide variety of tasks: from image captioning and visual question answering to content recognition, GUI-based agents, video understanding, and long-document interpretation. GLM-4.5V emerged from a training framework that leverages scalable reinforcement learning (with curriculum sampling) to boost performance across tasks ranging from STEM problem solving to long-context reasoning, giving it broad applicability beyond narrow benchmarks. When it was released, it achieved state-of-the-art results on a large collection of public multimodal benchmarks for open-source models. -
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Search-Index
A persistent, network resilient, full text search library
Search-Index is a lightweight and fast JavaScript-based search engine that enables full-text search indexing and retrieval for web applications. -
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BEIR
A Heterogeneous Benchmark for Information Retrieval
BEIR is a benchmark framework for evaluating information retrieval models across various datasets and tasks, including document ranking and question answering. -
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Generative AI Use Cases (GenU)
Application implementation with business use cases
...Each example typically includes infrastructure templates, backend services, and application code that show how to integrate generative AI capabilities with other AWS services. These examples cover tasks such as document analysis, conversational assistants, content generation, and knowledge retrieval systems. The repository is intended to serve as both a learning resource and a starting point for developers who want to deploy generative AI solutions using AWS infrastructure. -
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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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Hallucination Leaderboard
Leaderboard Comparing LLM Performance at Producing Hallucinations
...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. The results are published as a leaderboard that allows researchers and developers to compare model reliability and factual consistency. By focusing on hallucination rates rather than traditional metrics such as accuracy or fluency, the benchmark highlights an important aspect of AI system safety and trustworthiness. ... -
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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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Krixik
Documentation for the Krixik Python client
Small/specialized AI models are an oft-necessary complement—or alternative—to "big AI" offerings. However, infrastructure for small AI tends to be underwhelming, so building with specialized AI can be difficult, time-consuming, and even expensive. Iterating with different models, and particularly with different combinations of these models, can thus be rendered unfeasible.
