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Paper-qa is a retrieval augmented generation system designed for question answering and analysis of scientific literature and technical documents. It functions as an LLM-powered research assistant that extracts grounded answers and summaries with citations from a document library. The system utilizes an agentic RAG orchestrator to iteratively refine search queries and gather evidence through multi-step tool calling. It features a multimodal document parser that extracts text, tables, and images from PDFs, alongside a vector-based indexer that embeds and caches document libraries for efficient
nlp-recipes is a collection of implementation guides and reference templates for applying natural language processing techniques to real-world tasks. It provides standardized workflows and code examples for developing NLP pipelines, from dataset preparation and model training to performance evaluation. The project focuses on the practical application of transformer-based models, offering patterns for fine-tuning pretrained architectures for tasks such as text classification, named entity recognition, and question answering. It also includes a toolkit for model interpretability, allowing users
MindSearch is an LLM-based multi-agent search engine that decomposes complex user questions into targeted sub-queries and routes each to a specialized agent for parallel investigation. The system orchestrates multiple agents through a large language model, coordinating their tasks and interpreting search results to produce coherent answers from multiple sources. The project provides a configurable search backend interface that allows switching between Google, DuckDuckGo, Brave, and Bing search APIs by updating a configuration attribute. It includes a terminal-based debug interface for testing
Reor is a local AI knowledge management application that stores, links, and searches personal notes using large language models and vector embeddings entirely on the user's device. It functions as a private AI note assistant, keeping all data and processing local for full privacy without relying on external cloud services. The application integrates with Ollama to manage the lifecycle of local LLMs and embedding models, handling downloads, updates, and execution. Notes are imported from markdown files, preserving existing file structure, and are automatically linked through vector-similarity
This repo contains code for our paper Simple and Effective Multi-Paragraph Reading Comprehension. It can be used to train neural question answering models in tensorflow, and in particular for the case when we want to run the model over multiple paragraphs for each question. Code is included to…
The main features of allenai/document-qa are: Question Answering.
Projects with overlapping indexed features include: future-house/paper-qa — Paper-qa is a retrieval augmented generation system designed for question answering and analysis of scientific… zyds/transformers-code — This project is a collection of scripts and workflows for training, fine-tuning, and deploying large language models… reorproject/reor — Reor is a local AI knowledge management application that stores, links, and searches personal notes using large… microsoft/nlp-recipes — nlp-recipes is a collection of implementation guides and reference templates for applying natural language processing… internlm/mindsearch — MindSearch is an LLM-based multi-agent search engine that decomposes complex user questions into targeted sub-queries… huggingface/huggingface_hub — The Hugging Face Hub Python client is a library that provides programmatic access to the Hugging Face Hub, a…