Search Results for "document" - Page 4
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Showing 346 open source projects for "document"
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1
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...The project is particularly useful for digitizing historical documents, research papers, and scanned materials where traditional OCR often struggles.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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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. -
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ArangoDB-Community/pyArango
Python Driver for ArangoDB with built-in validation
PyArango is a Python driver for ArangoDB, a multi-model NoSQL database. It provides a Pythonic way to interact with ArangoDB, allowing developers to manage collections, execute AQL queries, and integrate ArangoDB's document, graph, and key-value storage models into Python applications. -
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NLP
Open source NLP guide with models, methods, and real use cases
...Its covers core NLP concepts such as text representation, feature extraction, and model evaluation, alongside hands-on implementations using tools like Word2Vec, TF-IDF, and FastText. It also introduces topic modeling with LDA, keyword extraction techniques, and document similarity methods. NLP extends into real-world applications, including sentiment analysis and text classification, helping readers connect concepts to use cases. Designed for accessibility, the project evolves over time, allowing updates and improvements as NLP techniques advance. It reflects a practical approach to learning, where readers can explore code, experiment with models, and build foundational skills in machine learning-driven language processing. -
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OpenAdapt
Open Source Generative Process Automation
OpenAdapt is the open source software adapter between Large Multimodal Models (LMMs) and traditional desktop and web Graphical User Interfaces (GUIs). OpenAdapt learns to automate your desktop and web workflows by observing your demonstrations. Spend less time on repetitive tasks and more on work that truly matters. Boost team productivity in HR operations. Automate candidate sourcing using LinkedIn Recruiter, LinkedIn Talent Solutions, GetProspect, Reply.io, outreach.io, Gmail/Outlook, and... -
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PasteMD
Paste Markdown and AI responses into Word Excel instantly fast
PasteMD is a lightweight desktop utility designed to streamline the process of transferring formatted content from the clipboard into office applications such as Word, WPS, and Excel. It primarily targets users who frequently copy content from AI chat tools or web pages and encounter formatting issues, especially with Markdown, tables, and LaTeX formulas. PasteMD operates from the system tray and monitors clipboard content, automatically converting Markdown or HTML into properly formatted... -
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FinGPT
Open-Source Financial Large Language Models
...The platform typically includes tools for fine-tuning, context engineering, and prompt templating, enabling users to build specialized assistants for tasks like sentiment analysis, earnings summary generation, risk profiling, trading signal interpretation, and document extraction from financial reports. -
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Kinto
A generic JSON document store with sharing and synchronisation options
Kinto is a minimalist JSON storage service with synchronization and sharing abilities. It is meant to be easy to use and easy to self-host. Kinto is used at Mozilla and released under the Apache v2 license. It’s hard for frontend developers to respect users' privacy when building applications that work offline, store data remotely and synchronize across devices. Existing solutions either rely on big corporations that crave user data or require a non-trivial amount of time and expertise to... -
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10
Dynamiq
An orchestration framework for agentic AI and LLM applications
...Instead of building each component manually, developers can use Dynamiq’s structured APIs and modular architecture to connect language models, vector databases, and external tools into cohesive pipelines. The framework supports the creation of multi-agent systems where different AI agents collaborate to solve tasks such as information retrieval, document analysis, or automated decision making. Dynamiq also includes built-in support for retrieval-augmented generation pipelines that allow models to access external documents and knowledge bases during inference. -
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Canopy
Retrieval Augmented Generation (RAG) framework
...The system provides a complete pipeline for transforming raw text data into searchable embeddings, storing them in a vector database, and retrieving relevant context for language model responses. It is designed to handle many of the complex components required for a RAG workflow, including document chunking, embedding generation, prompt construction, and chat history management. Developers can use Canopy to quickly build chat systems that answer questions using their own data instead of relying solely on the pretrained knowledge of the language model. The framework includes a built-in server and command-line interface that allow users to experiment with RAG pipelines and compare outputs between retrieval-augmented responses and standard LLM responses. -
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shuyuan
Reading book source
...The name suggests “academy” or “study hall,” and the tool aims to help users ingest, organize, and manage reading content — possibly offering features like text parsing, annotation, metadata generation, translation, or storage for later reference. The repository is set up to support document ingestion, indexing, and maybe some AI-aided summarization or lookup functions, which helps users convert large text corpora into a structured, searchable knowledge base. For learners, researchers, or avid readers, Shuyuan offers a way to bridge from plain text files or eBooks into a manageable, interactive resource — one where notes, references, and reading progress can be tracked. ... -
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PaperQA2
High accuracy RAG for answering questions from scientific documents
PaperQA2 is a package for doing high-accuracy retrieval augmented generation (RAG) on PDFs or text files, with a focus on the scientific literature. See our recent 2024 paper to see examples of PaperQA2's superhuman performance in scientific tasks like question answering, summarization, and contradiction detection. In this example we take a folder of research paper PDFs, magically get their metadata - including citation counts and a retraction check, then parse and cache PDFs into a... -
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fpdf2
Simple PDF generation for Python
fpdf2 is a library for simple & fast PDF document generation in Python. It is a fork and the successor of PyFPDF. Compared with other PDF libraries, fpdf2 is fast, versatile, easy to learn and to extend (example). It is also entirely written in Python and has very few dependencies: Pillow, defusedxml, & fontTools. It is a fork and the successor of PyFPDF. -
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MaxKB
Open-source platform for building enterprise-grade agents
MaxKB (Max Knowledge Brain) is an open-source platform for building enterprise-grade AI agents with strong knowledge retrieval, RAG pipelines, and workflow orchestration. It focuses on practical deployments such as customer support, internal knowledge bases, research assistants, and education, bundling tools for data ingestion, chunking, embedding, retrieval, and answer synthesis. The system exposes flexible tool-use (including MCP), supports multi-model backends, and provides dashboards for... -
16
LangChain Extract
Did you say you like data?
...Developers can create reusable “extractors” that define what type of information should be pulled from a document, along with example prompts that improve extraction quality through in-context learning. -
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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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NVIDIA Generative AI Examples
Generative AI reference workflows
...Many of the examples show how to deploy AI services using containerized environments, GPU acceleration, and microservices that can scale across modern infrastructure. Developers can explore sample chatbot applications, document question-answering systems, and knowledge-base pipelines that illustrate how generative AI can interact with external data sources. -
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towncrier
Manage the release notes for your project
towncrier is a changelog management tool that automates the generation of release notes from fragments stored during development. It encourages developers to document changes incrementally and reduces the burden of writing changelogs at release time. Designed for Python projects, it integrates well with tools like setuptools and tox. -
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Cleanlab
The standard data-centric AI package for data quality and ML
cleanlab helps you clean data and labels by automatically detecting issues in a ML dataset. To facilitate machine learning with messy, real-world data, this data-centric AI package uses your existing models to estimate dataset problems that can be fixed to train even better models. cleanlab cleans your data's labels via state-of-the-art confident learning algorithms, published in this paper and blog. See some of the datasets cleaned with cleanlab at labelerrors.com. This package helps you... -
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Agent SOP
Natural language workflows for AI agents
...It defines reusable SOP templates that agents can instantiate with context-specific parameters, allowing organizations to codify best practices for customer support, data processing, document workflows, or incident response. The framework supports monitoring and state tracking, so external systems can observe progress, intervene if necessary, and log outcomes for compliance or auditing. Integrations with common messaging and task orchestration systems enable SOP agents to interact with email, ticket queues, and databases as part of their workflows. -
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Llama Cloud Services
Knowledge Agents and Management in the Cloud
Llama Cloud Services is a suite of tools designed to facilitate the integration of large language models (LLMs) into applications. It offers components for parsing, extracting, and reporting on complex documents, streamlining the process of preparing data for LLM consumption. -
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Qwen-2.5-VL
Qwen2.5-VL is the multimodal large language model series
Qwen2.5 is a series of large language models developed by the Qwen team at Alibaba Cloud, designed to enhance natural language understanding and generation across multiple languages. The models are available in various sizes, including 0.5B, 1.5B, 3B, 7B, 14B, 32B, and 72B parameters, catering to diverse computational requirements. Trained on a comprehensive dataset of up to 18 trillion tokens, Qwen2.5 models exhibit significant improvements in instruction following, long-text generation... -
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Haystack
Haystack is an open source NLP framework to interact with your data
Apply the latest NLP technology to your own data with the use of Haystack's pipeline architecture. Implement production-ready semantic search, question answering, summarization and document ranking for a wide range of NLP applications. Evaluate components and fine-tune models. Ask questions in natural language and find granular answers in your documents using the latest QA models with the help of Haystack pipelines. Perform semantic search and retrieve ranked documents according to meaning, not just keywords! Make use of and compare the latest pre-trained transformer-based languages models like OpenAI’s GPT-3, BERT, RoBERTa, DPR, and more. ... -
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Llama Cookbook
Solve end to end problems using Llama model family
The Llama Cookbook is the official Meta LLaMA guide for inference, fine‑tuning, RAG, and multi-step use-cases. It offers recipes, code samples, and integration examples across provider platforms (WhatsApp, SQL, long context workflows), enabling developers to quickly harness LLaMA models
