Search Results for "extraction"
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Showing 17 open source projects for "extraction"
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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. -
2
text-extract-api
Document (PDF, Word, PPTX ...) extraction and parse API
...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. The platform supports automated processing pipelines that detect file types and apply the appropriate extraction method to obtain the most accurate text representation possible. It can be integrated into document analysis systems, knowledge retrieval tools, and AI pipelines that rely on clean textual data. ... -
3
MiroFish
A Simple and Universal Swarm Intelligence Engine
MiroFish is a next-generation artificial intelligence prediction engine that leverages multi-agent technology and swarm-intelligence simulation to model, simulate, and forecast complex real-world scenarios. The system extracts “seed” information from sources such as breaking news, policy documents, and market signals to construct a high-fidelity digital parallel world populated by thousands of virtual agents with independent memory and behavior rules. Users can inject variables or conditions... -
4
LangChain Extract
Did you say you like data?
LangChain Extract is an open-source reference application designed to demonstrate how large language models can be used to extract structured data from unstructured text and document files. The project implements a lightweight web service that allows developers to define extraction schemas and apply them to various sources such as plain text, HTML, or PDF documents. Built using FastAPI and the LangChain framework, the application exposes a REST API that can process documents and return structured outputs that match user-defined JSON schemas. 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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5
Bespoke Curator
Synthetic data curation for post-training and data extraction
...It supports workflows where models are used to produce synthetic examples that can later be refined into reliable training datasets for reasoning, question answering, or structured information extraction tasks. Curator includes tools for monitoring data generation processes and managing dataset quality while large batches of examples are being created. The framework also integrates with multiple inference systems and APIs, allowing users to generate data using different model providers or open-source inference engines. -
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VLMEvalKit
Open-source evaluation toolkit of large multi-modality models (LMMs)
...VLMEvalKit supports generation-based evaluation methods, allowing models to produce textual responses to visual inputs while measuring performance through techniques such as exact matching or language-model-assisted answer extraction. -
7
kg-gen
Knowledge Graph Generation from Any Text
...The system is designed to transform plain text sources such as documents, articles, or conversation transcripts into structured graphs composed of entities and relationships. Instead of relying on traditional rule-based extraction techniques, KG-Gen uses language models to identify entities and their relationships, producing higher-quality graph structures from raw text. The framework addresses common problems in automatic knowledge graph construction, particularly sparsity and duplication of entities, by applying a clustering and entity-resolution process that merges semantically similar nodes. ... -
8
Paper2Slides
From Paper to Presentation in One Click
...It is designed to replace the repetitive work of turning dense technical documents into presentation-friendly structure by extracting key points, figures, and data into a coherent visual narrative. The system supports multiple input formats, so you can process PDFs and common office documents rather than being locked to a single file type. It uses an extraction approach intended to capture critical insights comprehensively, including important visuals and data points that often get missed in naive summarization. A major focus is traceability: generated slide content is designed to remain linked back to the source material so you can verify accuracy and reduce information drift. It also offers styling flexibility, letting you use built-in themes or describe a custom design direction in natural language for themed outputs. -
9
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. By producing Markdown rather than raw text,... -
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10
MegaParse
File Parser optimised for LLM Ingestion with no loss
...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. -
11
spacy-llm
Integrating LLMs into structured NLP pipelines
...With only a few (and sometimes no) examples, an LLM can be prompted to perform custom NLP tasks such as text categorization, named entity recognition, coreference resolution, information extraction and more. This package integrates Large Language Models (LLMs) into spaCy, featuring a modular system for fast prototyping and prompting, and turning unstructured responses into robust outputs for various NLP tasks, no training data required. -
12
nano-graphrag
A simple, easy-to-hack GraphRAG implementation
nano-graphrag is a lightweight implementation of the GraphRAG approach designed to simplify experimentation with graph-based retrieval-augmented generation systems. GraphRAG expands traditional RAG pipelines by constructing knowledge graphs from documents and using relationships between entities to improve the quality and reasoning of AI responses. The nano-GraphRAG project focuses on reducing complexity by providing a compact and readable codebase that preserves the core functionality of... -
13
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. -
14
Kor
LLM
This is a half-baked prototype that “helps” you extract structured data from text using LLMs. Specify the schema of what should be extracted and provide some examples. Kor will generate a prompt, send it to the specified LLM and parse out the output. You might even get results back. -
15
AudioMuse-AI
AudioMuse-AI is an Open Source Dockerized environment
AudioMuse-AI is an open-source system designed to automatically generate playlists and analyze music libraries using artificial intelligence and audio signal processing techniques. The platform runs locally in a Dockerized environment and performs detailed sonic analysis on audio files to understand characteristics such as tempo, mood, and acoustic similarity. By analyzing the underlying audio content rather than relying on external metadata services, the system can organize large personal... -
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AI Powered Knowledge Graph Generator
AI Powered Knowledge Graph Generator
AI-Powered Knowledge Graph is an open-source project focused on building knowledge graph systems that integrate artificial intelligence and machine learning to represent complex relationships between data entities. Knowledge graphs organize information as networks of nodes and relationships, allowing applications to analyze connections between concepts, datasets, or real-world entities. By incorporating AI techniques such as natural language processing and semantic reasoning, the project... -
17
NeMo Curator
Scalable data pre processing and curation toolkit for LLMs
NeMo Curator is a Python library specifically designed for fast and scalable dataset preparation and curation for large language model (LLM) use-cases such as foundation model pretraining, domain-adaptive pretraining (DAPT), supervised fine-tuning (SFT) and paramter-efficient fine-tuning (PEFT). It greatly accelerates data curation by leveraging GPUs with Dask and RAPIDS, resulting in significant time savings. The library provides a customizable and modular interface, simplifying pipeline...
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