document-retrieval
There are 67 repositories under document-retrieval topic.
chroma-core/chroma
the AI-native open-source embedding database
vearch/vearch
Distributed vector search for AI-native applications
Mintplex-Labs/vector-admin
The universal tool suite for vector database management. Manage Pinecone, Chroma, Qdrant, Weaviate and more vector databases with ease.
OpenBMB/VisRAG
Parsing-free RAG supported by VLMs
redis-developer/redis-arXiv-search
Vector search demo with the arXiv paper dataset, RedisVL, HuggingFace, OpenAI, Cohere, FastAPI, React, and Redis.
vTuanpham/Vietnamese_QA_System
Vietnamese long form question answering system with documents retrieval.
grafana/vectorapi
pgvector + embeddings API
HennyJie/GNN-DocRetrieval
Implementation of ECIR 2022 Paper: How Can Graph Neural Networks Help Document Retrieval: A Case Study on CORD19 with Concept Map Generation
manan-paneri-99/Vector-Space-based-Document-Retrieval-system
Retrieves the top 10 documents from the Wikipedia corpus for a user inputted free-text query
Syed007Hassan/Document-Querying-With-VectorDB
Document Querying with LLMs - Google PaLM API: Semantic Search With LLM Embeddings
marcomoldovan/hierarchical-language-modeling
We address the task of learning contextualized word, sentence and document representations with a hierarchical language model by stacking Transformer-based encoders on a sentence level and subsequently on a document level and performing masked token prediction.
maxsagt/lambda-instructor
Run text embeddings with Instructor-Large on AWS Lambda.
agrawal-priyank/machine-learning-case-studies
Built prediction and retrieval models for document retrieval, image retrieval, house price prediction, song recommendation, and analyzed sentiments using machine learning algorithms in Python
aniketwdubey/chatpdf
This project is a Document Retrieval application that utilizes Retrieval-Augmented Generation (RAG) techniques to enable users to interact with uploaded PDF documents. By leveraging a Large Language Model (LLM), users can ask questions about the content of the documents and receive accurate answers based on the information retrieved.
pointable-ai/starpoint-sdk
Client SDK for starpoint.ai
boudinfl/redefining-absent-keyphrases
Code and dataset for the paper "Redefining Absent Keyphrases and their Effect on Retrieval Effectiveness"
DebanjanSarkar/askdoc
The Intelligent "ASKDOC" project combines the power of Langchain, Azure, OpenAI models, and Python to deliver an intelligent question-answering system, that scans your PDF documents and answer queries based on its contents. It can be queried using Human Natural Language.
shrebox/Information-Retrieval
Compilation of Information Retrieval codes.
spyros-briakos/Document-Retrieval-and-Question-Answering-with-BERT
Initially implement Document-Retrieval-System with SBERT embeddings and evaluate it in CORD-19 dataset. Afterwards, fine tune BERT model with SQuAD.v2 dataset so as to evaluate it in Question Answering task.
anaramirli/snlp-information-retrieval
A two-stage information retrieval model using baseline TF-IDF model and refined BM25.
SubhangiSati/LangChat-Explorer
"LangChat Explorer: Your intuitive document companion. Effortlessly explore vast information with natural language conversations. Simplify queries, gain insights, and embark on a seamless journey of knowledge discovery. Unleash the power of language with LangChat Explorer."
wlzhao22/mirlecture
course slides for Multimedia Information Retrieval
AGiannoutsos/COVID19-document-retrieval-with-BERT
This project is about developing a document retrieval system to return titles and the context of scientific papers containing the answer to a given user question
arpytanshu/latent-semantic-indexing
This Latent Semantic Indexing [ LSI ] model collects, parses, and stores documents to facilitate fast and accurate information retrieval through queries.
IsuruBoyagane15/vue4logs-parser
Automatic structuring of textual computer system logs using document retrieval.
Jiho-YesNLP/text-summ-for-doc-retrieval
Neural text summarization for document retrieval
SavinRazvan/questions
The "Questions" project, part of Harvard's CS50 AI course, develops an AI system for answering questions by retrieving documents and passages from a text corpus using tf-idf. It aids in understanding natural language processing (NLP) and information retrieval techniques.
ahmadvh/Context-based-document-search
A Python-based tool for context-based search across text documents using OpenAI embeddings and Chroma vector storage. This system enables efficient querying of document collections by generating vector embeddings, storing them persistently, and retrieving relevant results based on textual queries.
angelosps/Document-Retrieval-System
🗂️ A document retrieval system on CORD-19 dataset
DanieleMorotti/Argument-retrieval-for-comparative-questions
Neural Language Processing (NLP) project (AY 2022/2023)
heydido/DocumentQnA
A Document QnA bot
timothyckl/iota
a minimal local embedding database.