#Information Retrieval

This open-source tool utilizes GPT models to expedite finding information in project documentation. Effortlessly query projects and receive accurate answers while saving time from manual searches. Join the journey in enhancing AI-driven documentation.

WikiChat addresses inaccuracies in language models by grounding responses through a structured process using Wikipedia data. Its 7-stage pipeline, which supports over 10 languages, ensures factual information. The platform's information retrieval system accesses structured data for precise user interactions and supports multiple LLMs, incorporating a free multilingual Wikipedia Search API for open-domain question answering.

The Arxiv Translator project transforms ArXiv papers into Korean using Nougat OCR, offering quicker access to new academic papers. Departing from Ar5iv's method due to update delays, this tool extracts and presents papers independently, enhancing accessibility. While translations aid understanding, original papers are recommended for detailed insights. Users can navigate a comprehensive list of translated works linked to their specific ArXiv pages.

This guide provides a thorough exploration of Retrieval Augmented Large Language Models (LLMs), focusing on alleviating common issues such as hallucinations and outdated information. It examines how integrating LLMs with external retrieval techniques can enhance accuracy and address challenges related to data freshness. It also details core concepts, implementation strategies, and potential applications. By enhancing LLMs' abilities with long-tail knowledge and private data, and improving their source-traceability, this guide provides useful insights for developing efficient retrieval-augmented AI systems. It highlights key components such as data management, indexing, and retrieval processes.

This API integrates Microsoft's GraphRAG technology with Open WebUI to provide advanced search capabilities. It supports local, global, and Tavily search methods, ensuring privacy through local language models such as Ollama and LM Studio. The system delivers comprehensive and precise search results, meeting diverse information retrieval needs. Suitable for developers seeking effective search solutions in web applications.

PHP Text Analysis is a reliable library offering Information Retrieval and NLP tools specifically for PHP. It includes features such as document classification, sentiment analysis, and frequency analysis. Additionally, it offers support for tokenization, stemming, n-gram generation, and keyword extraction with the Rake algorithm. Customization options for tokenizers and stemmers allow developers to adapt the library to their needs. The accompanying documentation provides useful guidance for implementation, aiding developers in adding robust text analysis capabilities to their PHP projects.

The dataset offers an in-depth examination of ChatGPT and human responses used to train Question Answering Retrieval models. It facilitates the analysis of synthetic document generation effectiveness for cross-encoder re-rankers while comparing retrieval performance. By providing separate datasets for retrieval and re-ranking, the dataset supports systematic evaluations compatible with formats like the MSMarco dataset. It emphasizes reliability and accountability in information retrieval, particularly in critical fields such as law and medicine.

Explore a meta-repository for semantic search and similarity, with collections of research papers, articles, libraries, tools, and datasets. Contribute by raising a PR to expand this knowledge base, designed for those interested in semantic search.

PrimeQA is an open-source repository designed for the training and testing of advanced question answering models. It helps researchers replicate cutting-edge experiments from recent NLP conferences and supports diverse functionalities such as Information Retrieval using models like BM25 and ColBERT, Multilingual Machine Reading Comprehension, and multilingual Question Generation. Utilizing the Transformers toolkit allows for easy access to pre-trained models. PrimeQA also includes retrieval-augmented generation with GPT models and excels in multiple leaderboard challenges, making it a top resource for exploring multilingual functionality and domain adaptation.