Best AI tools for< knowledge retrieval >

Keepi is a personal knowledge AI tool that allows users to capture, organize, and retrieve their knowledge effortlessly. With Keepi, users can capture ideas, documents, and images, and the AI technology enriches and organizes the knowledge for easy retrieval. Users can access their personal knowledge on the go or in the office to leverage their insights. Keepi.ai is designed to enhance productivity and creativity by providing a seamless knowledge management experience.

GPTBots is a powerful no-code platform for creating AI-driven business applications. It seamlessly connects LLMs with enterprise data, services, and workflows, providing a powerful boost for business development. With GPTBots, anyone can easily build and train AI Bots without any coding required. The platform offers a range of features to make AI more adaptable and controllable for businesses, including flow orchestration, multimodality, Agents, and Plugins. GPTBots also integrates with thousands of commonly used tools and allows users to interact with the Bot anytime, anywhere. Additionally, the platform provides continuous training and improvement, ensuring that the Bot becomes smarter and more stable over time.

Cape Product Solutions offers personalized marketing solutions by leveraging private LLMs to reduce time to value for critical marketing functions. The platform provides features like Agentic workflow automation, AI-powered Knowledge Retrieval, and Cape API for building custom applications. CapeChat is an intuitive chat interface that enables easy use of multiple public and private LLMs. The platform focuses on improving data accuracy, operational efficiency, and third-party risk management in banking operations.

Findr is an AI-powered search assistant designed for teams to streamline information retrieval and enhance productivity. It offers a centralized platform to search, access, and manage data across various workplace apps. By leveraging AI technology, Findr eliminates repetitive tasks, enhances data search efficiency, and provides instant answers to user queries. With a user-friendly interface and robust security measures, Findr aims to revolutionize the way teams interact with their data and applications.

echowin is an all-in-one AI call answering and workflow automation platform designed to help businesses automate their incoming phone calls, enhancing efficiency and customer satisfaction. The platform utilizes the latest advancements in AI to provide an end-to-end business automation solution, from the phone number to the CRM. echowin offers customizable base layers and tools that allow businesses to model and automate their existing workflows, integrating with over 6000+ business applications and supporting custom integrations through HTTP Rest API and webhooks. The platform seamlessly fuses the power of generative AI with the flexibility and control of a flow-based system, making it ideal for various business use cases.

GoSearch is an AI-powered Enterprise Search and Resource Discovery platform that revolutionizes team knowledge management by providing AI-generated answers and information discovery. It offers unified search across all internal information sources, speeds up workflows, and enhances productivity by leveraging generative AI technology. With features like multimodal AI, custom GPT, and integrations with various apps, GoSearch streamlines communication, centralizes company announcements, and allows employees to ask questions and get answers in a centralized hub. The platform ensures security and privacy with enterprise-grade measures and offers personalized suggestions through AI-powered chat assistants.

Guru is an AI-powered enterprise search, intranet, and wiki platform that helps companies connect their collective knowledge and streamline information retrieval. It offers comprehensive features such as AI-driven company knowledge search, customizable employee engagement hub, automated centralized knowledge base, and integrations with existing workflows. Guru's zero-data retention policy, private AI models, and role-based access control ensure data security and privacy. The platform caters to various industries and teams, providing tailored solutions for human resources, operations, IT, product engineering, customer support, sales, marketing, and learning & development.

Quivr is an open-source, chat-powered second brain that allows users to build a unified search engine across all their documents, tools, and databases. It is powered by AI and continuously trains on the user's company's unique context to improve search relevance and knowledge discovery. Quivr can be integrated with a variety of tools and applications, and users can choose from a variety of GenAI models to get the best results for their specific tasks.

TextMine is an AI-powered knowledge base that helps businesses analyze, manage, and search thousands of documents. It uses AI to analyze unstructured textual data and document databases, automatically retrieving key terms to help users make informed decisions. TextMine's features include a document vault for storing and managing documents, a categorization system for organizing documents, and a data extraction tool for extracting insights from documents. TextMine can help businesses save time, money, and improve efficiency by automating manual data entry and information retrieval tasks.

Vectorize is a fast, accurate, and production-ready AI tool that helps users turn unstructured data into optimized vector search indexes. It leverages Large Language Models (LLMs) to create copilots and enhance customer experiences by extracting natural language from various sources. With built-in support for top AI platforms and a variety of embedding models and chunking strategies, Vectorize enables users to deploy real-time vector pipelines for accurate search results. The tool also offers out-of-the-box connectors to popular knowledge repositories and collaboration platforms, making it easy to transform knowledge into AI-generated content.

txyz.ai is an AI-powered platform that aims to integrate all paths to knowledge. It leverages artificial intelligence algorithms to provide users with a comprehensive and efficient way to access and organize information. The platform offers a user-friendly interface that allows individuals to streamline their research process, gather insights, and make data-driven decisions. With txyz.ai, users can explore diverse sources of information, extract valuable insights, and stay updated on the latest trends in their field of interest.

IKI AI is an intelligent knowledge interface that provides users with quick and easy access to information from a variety of sources. It uses natural language processing and machine learning to understand user queries and deliver relevant results. IKI AI can be used for a variety of tasks, including research, learning, and decision-making.

Glean is an AI-powered work assistant that helps teams harness generative AI and make better decisions faster. It connects all of your company's data across all of the content, people, and interactions in your organization. Glean's advanced personalization ensures that answers are tailored to who you are, who you work with, and what you're working on. Its Retrieval Augmented Generation (RAG) retrieves the most relevant information and ensures that LLMs answer with the most up-to-date knowledge.

Keymate.AI is an AI application that allows users to build GPTs with advanced search, browse, and long-term memory capabilities. It offers a personalized long-term memory on ChatGPT, parallel search functionality, and privacy features using Google API. Keymate.AI aims to elevate research, projects, and daily tasks by providing efficient AI memory management and real-time data retrieval from the web.

Casc is an AI-powered knowledge management tool that helps teams access and share information quickly and easily. It integrates with popular collaboration tools like Slack, Google Drive, and Confluence, allowing users to search and access documents, images, and other content from a central location. Casc also uses natural language processing to understand user queries and deliver precise answers, making it easy for teams to find the information they need without having to spend hours searching through multiple sources.

Ask Buzzing AI is a question-answering platform that uses artificial intelligence to provide comprehensive and informative responses to a wide range of queries. It is designed to be user-friendly and accessible, allowing users to ask questions in natural language and receive accurate and relevant answers.

Sense is an AI-powered tool that helps you organize and search all of your work information in one place. It automatically keeps all documents, links, files, and conversations organized and interrelated, so you can easily find what you need, when you need it. Sense also provides sharing suggestions, so you can never forget to share any piece of information with relevant people. With Sense, you can: * Keep all of your work information organized in one place * Search across all of your apps, websites, and documents * Never forget to share any piece of information with relevant people * Get sharing suggestions * Collaborate with your team more effectively

Glean is an AI-powered work assistant and enterprise search platform that enables teams to harness generative AI to make better decisions faster. It connects all company data, provides advanced personalization, and ensures retrieval of the most relevant information. Glean offers responsible AI solutions that scale to businesses, respecting permissions and providing secure, private, and fully referenceable answers. With turnkey deployment and a variety of platform tools, Glean helps teams move faster and be more productive.

MyMemo is an AI-powered knowledge management tool that helps users organize, analyze, and retrieve their digital knowledge. It uses natural language processing and machine learning to understand the content of users' uploads, extract key insights, and generate summaries. MyMemo also allows users to create collections of memos, ask questions to the AI, and collaborate with others. It is designed to help users save time, improve their productivity, and make better use of their knowledge.

ChatGent is an advanced AI-powered professional assistant builder that revolutionizes the way professionals manage their interactions and tasks. It leverages the latest GPT models to provide high-quality, contextually relevant responses and robust security measures. ChatGent transforms complex data into simple, actionable conversations, enhancing productivity, efficiency, and decision-making for professionals across various industries.

LLMWare is a framework for quickly developing LLM-based applications including Retrieval Augmented Generation (RAG) and Multi-Step Orchestration of Agent Workflows. This project provides a comprehensive set of tools that anyone can use - from a beginner to the most sophisticated AI developer - to rapidly build industrial-grade, knowledge-based enterprise LLM applications. Our specific focus is on making it easy to integrate open source small specialized models and connecting enterprise knowledge safely and securely.

Awesome-LLM-RAG-Application is a repository that provides resources and information about applications based on Large Language Models (LLM) with Retrieval-Augmented Generation (RAG) pattern. It includes a survey paper, GitHub repo, and guides on advanced RAG techniques. The repository covers various aspects of RAG, including academic papers, evaluation benchmarks, downstream tasks, tools, and technologies. It also explores different frameworks, preprocessing tools, routing mechanisms, evaluation frameworks, embeddings, security guardrails, prompting tools, SQL enhancements, LLM deployment, observability tools, and more. The repository aims to offer comprehensive knowledge on RAG for readers interested in exploring and implementing LLM-based systems and products.

DB-GPT is a personal database administrator that can solve database problems by reading documents, using various tools, and writing analysis reports. It is currently undergoing an upgrade. **Features:** * **Online Demo:** * Import documents into the knowledge base * Utilize the knowledge base for well-founded Q&A and diagnosis analysis of abnormal alarms * Send feedbacks to refine the intermediate diagnosis results * Edit the diagnosis result * Browse all historical diagnosis results, used metrics, and detailed diagnosis processes * **Language Support:** * English (default) * Chinese (add "language: zh" in config.yaml) * **New Frontend:** * Knowledgebase + Chat Q&A + Diagnosis + Report Replay * **Extreme Speed Version for localized llms:** * 4-bit quantized LLM (reducing inference time by 1/3) * vllm for fast inference (qwen) * Tiny LLM * **Multi-path extraction of document knowledge:** * Vector database (ChromaDB) * RESTful Search Engine (Elasticsearch) * **Expert prompt generation using document knowledge** * **Upgrade the LLM-based diagnosis mechanism:** * Task Dispatching -> Concurrent Diagnosis -> Cross Review -> Report Generation * Synchronous Concurrency Mechanism during LLM inference * **Support monitoring and optimization tools in multiple levels:** * Monitoring metrics (Prometheus) * Flame graph in code level * Diagnosis knowledge retrieval (dbmind) * Logical query transformations (Calcite) * Index optimization algorithms (for PostgreSQL) * Physical operator hints (for PostgreSQL) * Backup and Point-in-time Recovery (Pigsty) * **Continuously updated papers and experimental reports** This project is constantly evolving with new features. Don't forget to star ⭐ and watch 👀 to stay up to date.

Intel® Extension for Transformers is an innovative toolkit designed to accelerate GenAI/LLM everywhere with the optimal performance of Transformer-based models on various Intel platforms, including Intel Gaudi2, Intel CPU, and Intel GPU. The toolkit provides the below key features and examples: * Seamless user experience of model compressions on Transformer-based models by extending [Hugging Face transformers](https://github.com/huggingface/transformers) APIs and leveraging [Intel® Neural Compressor](https://github.com/intel/neural-compressor) * Advanced software optimizations and unique compression-aware runtime (released with NeurIPS 2022's paper [Fast Distilbert on CPUs](https://arxiv.org/abs/2211.07715) and [QuaLA-MiniLM: a Quantized Length Adaptive MiniLM](https://arxiv.org/abs/2210.17114), and NeurIPS 2021's paper [Prune Once for All: Sparse Pre-Trained Language Models](https://arxiv.org/abs/2111.05754)) * Optimized Transformer-based model packages such as [Stable Diffusion](examples/huggingface/pytorch/text-to-image/deployment/stable_diffusion), [GPT-J-6B](examples/huggingface/pytorch/text-generation/deployment), [GPT-NEOX](examples/huggingface/pytorch/language-modeling/quantization#2-validated-model-list), [BLOOM-176B](examples/huggingface/pytorch/language-modeling/inference#BLOOM-176B), [T5](examples/huggingface/pytorch/summarization/quantization#2-validated-model-list), [Flan-T5](examples/huggingface/pytorch/summarization/quantization#2-validated-model-list), and end-to-end workflows such as [SetFit-based text classification](docs/tutorials/pytorch/text-classification/SetFit_model_compression_AGNews.ipynb) and [document level sentiment analysis (DLSA)](workflows/dlsa) * [NeuralChat](intel_extension_for_transformers/neural_chat), a customizable chatbot framework to create your own chatbot within minutes by leveraging a rich set of [plugins](https://github.com/intel/intel-extension-for-transformers/blob/main/intel_extension_for_transformers/neural_chat/docs/advanced_features.md) such as [Knowledge Retrieval](./intel_extension_for_transformers/neural_chat/pipeline/plugins/retrieval/README.md), [Speech Interaction](./intel_extension_for_transformers/neural_chat/pipeline/plugins/audio/README.md), [Query Caching](./intel_extension_for_transformers/neural_chat/pipeline/plugins/caching/README.md), and [Security Guardrail](./intel_extension_for_transformers/neural_chat/pipeline/plugins/security/README.md). This framework supports Intel Gaudi2/CPU/GPU. * [Inference](https://github.com/intel/neural-speed/tree/main) of Large Language Model (LLM) in pure C/C++ with weight-only quantization kernels for Intel CPU and Intel GPU (TBD), supporting [GPT-NEOX](https://github.com/intel/neural-speed/tree/main/neural_speed/models/gptneox), [LLAMA](https://github.com/intel/neural-speed/tree/main/neural_speed/models/llama), [MPT](https://github.com/intel/neural-speed/tree/main/neural_speed/models/mpt), [FALCON](https://github.com/intel/neural-speed/tree/main/neural_speed/models/falcon), [BLOOM-7B](https://github.com/intel/neural-speed/tree/main/neural_speed/models/bloom), [OPT](https://github.com/intel/neural-speed/tree/main/neural_speed/models/opt), [ChatGLM2-6B](https://github.com/intel/neural-speed/tree/main/neural_speed/models/chatglm), [GPT-J-6B](https://github.com/intel/neural-speed/tree/main/neural_speed/models/gptj), and [Dolly-v2-3B](https://github.com/intel/neural-speed/tree/main/neural_speed/models/gptneox). Support AMX, VNNI, AVX512F and AVX2 instruction set. We've boosted the performance of Intel CPUs, with a particular focus on the 4th generation Intel Xeon Scalable processor, codenamed [Sapphire Rapids](https://www.intel.com/content/www/us/en/products/docs/processors/xeon-accelerated/4th-gen-xeon-scalable-processors.html).

FlagEmbedding focuses on retrieval-augmented LLMs, consisting of the following projects currently: * **Long-Context LLM** : Activation Beacon * **Fine-tuning of LM** : LM-Cocktail * **Embedding Model** : Visualized-BGE, BGE-M3, LLM Embedder, BGE Embedding * **Reranker Model** : llm rerankers, BGE Reranker * **Benchmark** : C-MTEB

AvaTaR is a novel and automatic framework that optimizes an LLM agent to effectively use provided tools and improve performance on a given task/domain. It designs a comparator module to provide insightful prompts to the LLM agent via reasoning between positive and negative examples from training data.

This repository is now archived and the code is privately maintained. If you are interested in this infrastructure, please contact the maintainer directly.

The ai-playground repository contains code from tutorials presented on the Code AI with Rok YouTube channel. It includes tutorials on using the OpenAI Assistants API v1 beta to build personal math tutors, customer support chatbots, and more. Additionally, there are tutorials on using Gemini Pro API, Snowflake Cortex LLM functions, LlamaIndex chat streaming app, Fetch.ai uAgents, Milvus Standalone, spaCy for NER, and more. The repository aims to provide practical examples and guides for developers interested in AI-related projects and tools.

This repository, Awesome-LLM-RAG, aims to record advanced papers on Retrieval Augmented Generation (RAG) in Large Language Models (LLMs). It serves as a resource hub for researchers interested in promoting their work related to LLM RAG by updating paper information through pull requests. The repository covers various topics such as workshops, tutorials, papers, surveys, benchmarks, retrieval-enhanced LLMs, RAG instruction tuning, RAG in-context learning, RAG embeddings, RAG simulators, RAG search, RAG long-text and memory, RAG evaluation, RAG optimization, and RAG applications.

This solution provides a low-code ReactJS application to prototype and vet business use cases for GenAI using Retrieval Augmented Generation (RAG). It includes a backend Flask application that uses LangChain to provide PDF data as embeddings to a text-gen model via Amazon Bedrock and a vector database with FAISS or Kendra Index. The solution utilizes Amazon Bedrock as the only cost-generating AWS service.

This repository provides a hands-on lab for learning about Neo4j and Google Cloud Vertex AI. It is intended for data scientists and data engineers to deploy Neo4j and Vertex AI in a Google Cloud account, work with real-world datasets, apply generative AI, build a chatbot over a knowledge graph, and use vector search and index functionality for semantic search. The lab focuses on analyzing quarterly filings of asset managers with $100m+ assets under management, exploring relationships using Neo4j Browser and Cypher query language, and discussing potential applications in capital markets such as algorithmic trading and securities master data management.

This repository contains a hand-curated list of great machine (deep) learning resources for Natural Language Processing (NLP) with a focus on Generative Pre-trained Transformer (GPT), Bidirectional Encoder Representations from Transformers (BERT), attention mechanism, Transformer architectures/networks, Chatbot, and transfer learning in NLP.

KG-RAG (Knowledge Graph-based Retrieval Augmented Generation) is a task agnostic framework that combines the explicit knowledge of a Knowledge Graph (KG) with the implicit knowledge of a Large Language Model (LLM). KG-RAG extracts "prompt-aware context" from a KG, which is defined as the minimal context sufficient enough to respond to the user prompt. This framework empowers a general-purpose LLM by incorporating an optimized domain-specific 'prompt-aware context' from a biomedical KG. KG-RAG is specifically designed for running prompts related to Diseases.

Your personalized knowledge assistant, evolving with you

Answer your question about Fess

Accurately locating sections in Saiku's readme.md

AI search engine with summarization.

Expert in analyzing UK theses data without subject info

KU Info 2.0

Dive deep into any subject. Instantly generate 100+ page books about anything.

The fastest way to learn everything about anything

This GPT allows to interact with the Unprotect DB to retrieve knowledge about malware evasion techniques

Expert in Tiago Forte's Second Brain methodology for digital organization.

A kid-friendly guide for fun, safe learning.

这个工具可以帮你从浅入深的掌握一个深奥的知识领域的内容，他可以循序渐进的设计由浅到深的问题让你来回答，等你回答了之后，我可以判断你的知识层次到什么程度，然后再给你提出对应的解释一个详细理论的方案。

Expert in data-to-file conversion for GPT Training - Knowledge Nexus now specializes in converting data to the most suitable file format for GPT Knowledge files

For strategic knowledge distillation, upload the document you need to analyze and use !start. ENSURE the uploaded file shows DOCUMENT and NOT PDF. This workflow requires leveraging RAG to operate. Only a small amount of PDFs are supported, convert to txt or doc. For timeout, refresh & !continue

Quick facts and illustrations of animals, insects and plants.

I refine complex knowledge into granular, integrated solutions.

Assists with structuring knowledge files for GPTs

A brutally honest, multilingual guide for factual responses

Expert in esoteric knowledge, encouraging exploration and understanding.

In-depth FFmpeg expert with web browsing and DALL-E capabilities.