Best AI tools for< Query Knowledge Base >

Wikidata is a free and open knowledge base that can be read and edited by both humans and machines. It acts as central storage for the structured data of its Wikimedia sister projects including Wikipedia, Wikivoyage, Wiktionary, Wikisource, and others. Wikidata also provides support to many other sites and services beyond just Wikimedia projects!

Loata is an AI-powered platform that serves as a learning orchestrator for adaptive text analyses. It allows users to store their notes and documents in the cloud, which are then ingested and transformed into knowledge bases. The platform features smart AI agents powered by LLMs to provide intelligent answers based on the content. With end-to-end encryption and controlled ingestion, Loata ensures the security and privacy of user data. Users can choose from different subscription plans to access varying levels of storage and query capacity, making it suitable for individuals and professionals alike.

Storytell.ai is an enterprise-grade AI platform that offers Business-Grade Intelligence across data, focusing on boosting productivity for employees and teams. It provides a secure environment with features like creating project spaces, multi-LLM chat, task automation, chat with company data, and enterprise-AI security suite. Storytell.ai ensures data security through end-to-end encryption, data encryption at rest, provenance chain tracking, and AI firewall. It is committed to making AI safe and trustworthy by not training LLMs with user data and providing audit logs for accountability. The platform continuously monitors and updates security protocols to stay ahead of potential threats.

Trampoline is an AI-native proposal manager designed for sales teams to streamline the process of creating sales proposals. It leverages AI technology to help businesses excel at handling RFPs efficiently, saving valuable time and resources. Trampoline's innovative approach includes 'content upcycling' to quickly prepare necessary information, onboard new team members rapidly, and facilitate knowledge sharing within the organization. With features like semantic search, direct query forwarding, and expert contributions, Trampoline aims to revolutionize the way sales proposals are created and managed.

Resolvd is an AI-powered incident resolution platform that creates a knowledge base of logs, data sources, and apps to autonomously diagnose and resolve incidents. It helps cut down response time, reduce manual log review efforts, and streamline data querying with automated anomaly detection. Resolvd integrates with various systems like Slack, Jira, and PagerDuty to deliver insights in real-time and supercharge incident response.

Echobase is an AI tool designed to easily integrate AI into businesses by allowing teams to query, create, and analyze data from their files. It offers advanced AI models tailored to specific business needs, enabling the creation of AI agents capable of tasks like basic Q&A, data analysis, and content creation. Echobase provides a centralized workspace for uploading and querying organizational knowledge bases in real-time, along with features for collaboration and role management. The tool prioritizes data security through robust encryption, API usage, and user-controlled data access.

Leena AI is a Gen AI employee assistant that reduces IT, HR, Finance tickets. It guarantees a 70% self-service ratio in the contract. Leena AI centralizes knowledge that is scattered across the enterprise, making information easy to find right on chat with a simple query. The knowledge is auto-updated when changes are made, so your employees always get support that is both relevant and accurate. Leena AI integrates with all knowledge base systems within your enterprise from day one, eliminating the need for any consolidation or migration effort across the knowledge base systems. The work assistant tailors responses to employee queries based on their role, team and access level which boosts employee experience while adhering to security protocols and preventing unauthorized access to information. Leena AI analyzes historically closed tickets and learns from their resolutions to create knowledge articles that can prevent similar tickets from being raised again. Leena AI breaks down large policy documents and knowledge articles into consumable snippets so the responses are sharper and more specific to the employee’s query.

StartConvo is an AI tool that allows users to create custom AI chatbots for websites to enhance customer support, engagement, and user experience. The platform offers easy integration, intelligent query resolution, performance analytics, customizable responses, and 24/7 availability. Users can design tailored chatbots, connect to a knowledge base, and gain deep insights into customer interactions. StartConvo revolutionizes customer service by automating tasks, freeing up team members for high-value activities, and providing round-the-clock support.

QueryHub is an AI-powered web application designed to assist students in their academic endeavors. It provides a platform for users to ask and answer questions, collaborate with peers, and access instant and accurate information through AI chatbot assistance and smart search capabilities. QueryHub aims to empower students by offering a personalized learning experience, accelerating learning through document collaboration, and fostering community collaboration. With a user-friendly interface and a focus on user-driven innovation, QueryHub is a valuable tool for enhancing academic success.

AI2SQL is an AI-powered SQL query builder and generator that allows users to create, optimize, and automate SQL queries without the need for expert skills. The tool transforms natural language instructions into precise SQL and NoSQL queries, simplifying database design and enhancing query performance. With features like Text2SQL, SQL Query Fixer, SQL Query Explainer, and SQL Query Optimizer, AI2SQL offers a streamlined solution for diverse SQL tasks. Trusted by industry leaders, AI2SQL saves time, reduces errors, and improves productivity for data analysts and developers.

SQL Builder is an AI-powered SQL query generator that allows users to easily generate complex SQL queries without writing any code. It offers a range of features such as a no-code SQL builder, SQL syntax explainer, SQL optimizer, SQL formatter, NoSQL query builder, and SQL syntax validator. SQL Builder supports various databases including MySQL, MariaDB, SQLite, PostgreSQL, Oracle, Microsoft SQL Server, MongoDB, BigQuery, Snowflake, and Amazon Redshift.

PrivacyDoc is an AI-powered portal that allows users to analyze and query PDF and ebooks effortlessly. By leveraging advanced NLP technology, PrivacyDoc enables users to uncover insights and conduct thorough document analysis. The platform offers features such as easy file upload, query functionality, enhanced security measures, and free access to powerful PDF analysis tools. With PrivacyDoc, users can experience the convenience of logging in with their Google account, submitting queries for prompt AI-driven responses, and ensuring data privacy with secure file handling.

scatteredNote is an AI-powered note-taking application designed to help users effortlessly grab content and take notes while focusing on their main tasks. The application aims to make note-taking a seamless by-product of the user's main activities, ensuring minimal distraction. With features like Atomic Embrace mental model, Extended memory with AI integration, and simple UI, scatteredNote offers a user-friendly experience for organizing and accessing archived knowledge. The application supports various capture modes, including YouTube Capture, VS-Code Capture, Web-mode Capture, and Pdf-mode capture, along with AI chat and Ai-space repetition functionalities. Users can easily organize their notes, create flashcards, and access information quickly with the help of AI technology.

Mikie.AI is an AI-powered tool that allows users to generate SQL queries in seconds using natural language. It simplifies the process of creating efficient SQL queries by leveraging AI technology. Users can define database schemas easily, translate SQL to English, and benefit from simple pricing plans. Mikie.AI aims to make SQL query generation error-free and accessible to all types of users, even those with limited SQL knowledge.

AutoKT is an AI-powered application designed for Automatic Knowledge Transfer. It helps in effortless documentation by automatically writing and updating documentation, allowing users to focus on building innovative projects. The tool addresses the challenge of time and bandwidth spent on writing and maintaining documentation in agile workplaces. AutoKT ensures asynchronous knowledge transfer by keeping documentation in sync with code changes and providing a query feature for easy access to information. It is a valuable tool for developers, enabling them to understand legacy code, streamline documentation writing, and facilitate faster onboarding of new team members.

AI Brain Bank is a powerful tool that allows you to remember everything. With AI Brain Bank, you can query all your documents, media, and knowledge with AI. This makes it easy to find the information you need, when you need it. AI Brain Bank is the perfect tool for students, researchers, and anyone else who needs to manage a large amount of information.

Raw Query is a revolutionary tool that allows you to interact with your database using natural language, just like you would chat with a colleague. It's designed to save you time and effort, and make it easier than ever to access and manage your data. With Raw Query, you can query your data, add new data, and update your data, all through a simple chat interface. It's the perfect tool for anyone who wants to get more out of their data, without having to learn complex SQL queries or spend hours building custom tools.

Query Kitty is a Chrome extension that allows users to access ChatGPT from anywhere on the web. It provides a variety of features to help users get the most out of ChatGPT, including pre-written prompts, the ability to use web pages as context for prompts, and unlimited translations. Query Kitty is available in three plans: Starter, Basic, and Pro. The Starter plan is free and includes 60,000 words per month, the Basic plan costs $6 per month and includes 75,000 words per month, and the Pro plan costs $24 per month and includes 300,000 words per month. All plans come with a 3-day free trial.

AI Query is a powerful tool that allows users to generate SQL queries in seconds using simple English. With AI Query, anyone can create efficient SQL queries, without even knowing a thing about it. AI Query is easy to use and affordable, making it a great choice for businesses of all sizes.

Accio is a data modeling tool that allows users to define consistent relationships, metrics, and expressions for on-the-fly computations in reports and dashboards across various BI tools. It provides a syntax similar to GraphQL that allows users to define models, relationships, and metrics in a human-readable format. Accio also offers a user-friendly interface that provides data analysts with a holistic view of the relationships between their data models, enabling them to grasp the interconnectedness and dependencies within their data ecosystem. Additionally, Accio utilizes DuckDB as a caching layer to accelerate query performance for BI tools.

CurateGPT is a prototype web application and framework for performing general purpose AI-guided curation and curation-related operations over collections of objects. It allows users to load JSON, YAML, or CSV data, build vector database indexes for ontologies, and interact with various data sources like GitHub, Google Drives, Google Sheets, and more. The tool supports ontology curation, knowledge base querying, term autocompletion, and all-by-all comparisons for objects in a collection.

The serverless-rag-demo repository showcases a solution for building a Retrieval Augmented Generation (RAG) system using Amazon Opensearch Serverless Vector DB, Amazon Bedrock, Llama2 LLM, and Falcon LLM. The solution leverages generative AI powered by large language models to generate domain-specific text outputs by incorporating external data sources. Users can augment prompts with relevant context from documents within a knowledge library, enabling the creation of AI applications without managing vector database infrastructure. The repository provides detailed instructions on deploying the RAG-based solution, including prerequisites, architecture, and step-by-step deployment process using AWS Cloudshell.

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.

STaRK is a large-scale semi-structure retrieval benchmark on Textual and Relational Knowledge Bases. It provides natural-sounding and practical queries crafted to incorporate rich relational information and complex textual properties, closely mirroring real-life scenarios. The benchmark aims to assess how effectively large language models can handle the interplay between textual and relational requirements in queries, using three diverse knowledge bases constructed from public sources.

This starter project is designed to process `.mdx` files in the `pages` directory to use as custom context within OpenAI Text Completion prompts. It involves building a custom ChatGPT style doc search powered by Next.js, OpenAI, and Supabase. The project includes steps for pre-processing knowledge base, storing embeddings in Postgres, performing vector similarity search, and injecting content into OpenAI GPT-3 text completion prompt.

ChatData is a robust chat-with-documents application designed to extract information and provide answers by querying the MyScale free knowledge base or uploaded documents. It leverages the Retrieval Augmented Generation (RAG) framework, millions of Wikipedia pages, and arXiv papers. Features include self-querying retriever, VectorSQL, session management, and building a personalized knowledge base. Users can effortlessly navigate vast data, explore academic papers, and research documents. ChatData empowers researchers, students, and knowledge enthusiasts to unlock the true potential of information retrieval.

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.

PPL LLM Serving is a serving based on ppl.nn for various Large Language Models (LLMs). It provides inference support for LLaMA. Key features include: * **High Performance:** Optimized for fast and efficient inference on LLM models. * **Scalability:** Supports distributed deployment across multiple GPUs or machines. * **Flexibility:** Allows for customization of model configurations and inference pipelines. * **Ease of Use:** Provides a user-friendly interface for deploying and managing LLM models. This tool is suitable for various tasks, including: * **Text Generation:** Generating text, stories, or code from scratch or based on a given prompt. * **Text Summarization:** Condensing long pieces of text into concise summaries. * **Question Answering:** Answering questions based on a given context or knowledge base. * **Language Translation:** Translating text between different languages. * **Chatbot Development:** Building conversational AI systems that can engage in natural language interactions. Keywords: llm, large language model, natural language processing, text generation, question answering, language translation, chatbot development

2P-Kt is a Kotlin-based and multi-platform reboot of tuProlog (2P), a multi-paradigm logic programming framework written in Java. It consists of an open ecosystem for Symbolic Artificial Intelligence (AI) with modules supporting logic terms, unification, indexing, resolution of logic queries, probabilistic logic programming, binary decision diagrams, OR-concurrent resolution, DSL for logic programming, parsing modules, serialisation modules, command-line interface, and graphical user interface. The tool is designed to support knowledge representation and automatic reasoning through logic programming in an extensible and flexible way, encouraging extensions towards other symbolic AI systems than Prolog. It is a pure, multi-platform Kotlin project supporting JVM, JS, Android, and Native platforms, with a lightweight library leveraging the Kotlin common library.

A collection of papers related to knowledge distillation of large language models (LLMs). The repository focuses on techniques to transfer advanced capabilities from proprietary LLMs to smaller models, compress open-source LLMs, and refine their performance. It covers various aspects of knowledge distillation, including algorithms, skill distillation, verticalization distillation in fields like law, medical & healthcare, finance, science, and miscellaneous domains. The repository provides a comprehensive overview of the research in the area of knowledge distillation of LLMs.

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.

RAG-GPT is a tool that allows users to quickly launch an intelligent customer service system with Flask, LLM, and RAG. It includes frontend, backend, and admin console components. The tool supports cloud-based and local LLMs, enables deployment of conversational service robots in minutes, integrates diverse knowledge bases, offers flexible configuration options, and features an attractive user interface.

RAG-GPT is a tool that allows users to quickly launch an intelligent customer service system with Flask, LLM, and RAG. It includes frontend, backend, and admin console components. The tool supports cloud-based and local LLMs, offers quick setup for conversational service robots, integrates diverse knowledge bases, provides flexible configuration options, and features an attractive user interface.

LLMChat is an all-in-one AI chat interface that supports multiple language models, offers a plugin library for enhanced functionality, enables web search capabilities, allows customization of AI assistants, provides text-to-speech conversion, ensures secure local data storage, and facilitates data import/export. It also includes features like knowledge spaces, prompt library, personalization, and can be installed as a Progressive Web App (PWA). The tech stack includes Next.js, TypeScript, Pglite, LangChain, Zustand, React Query, Supabase, Tailwind CSS, Framer Motion, Shadcn, and Tiptap. The roadmap includes upcoming features like speech-to-text and knowledge spaces.

Album AI is an experimental project that uses GPT-4o-mini to automatically identify metadata from image files in the album. It leverages RAG technology to enable conversations with the album, serving as a photo album or image knowledge base to assist in content generation. The tool provides APIs for search and chat functionalities, supports one-click deployment to platforms like Render, and allows for integration and modification under a permissive open-source license.

This project is a tutorial on developing large model applications for novice developers. It aims to provide a comprehensive introduction to large model development, focusing on Alibaba Cloud servers and integrating personal knowledge assistant projects. The tutorial covers the following topics: 1. **Introduction to Large Models**: A simplified introduction for novice developers on what large models are, their characteristics, what LangChain is, and how to develop an LLM application. 2. **How to Call Large Model APIs**: This section introduces various methods for calling APIs of well-known domestic and foreign large model products, including calling native APIs, encapsulating them as LangChain LLMs, and encapsulating them as Fastapi calls. It also provides a unified encapsulation for various large model APIs, such as Baidu Wenxin, Xunfei Xinghuo, and Zh譜AI. 3. **Knowledge Base Construction**: Loading, processing, and vector database construction of different types of knowledge base documents. 4. **Building RAG Applications**: Integrating LLM into LangChain to build a retrieval question and answer chain, and deploying applications using Streamlit. 5. **Verification and Iteration**: How to implement verification and iteration in large model development, and common evaluation methods. The project consists of three main parts: 1. **Introduction to LLM Development**: A simplified version of V1 aims to help beginners get started with LLM development quickly and conveniently, understand the general process of LLM development, and build a simple demo. 2. **LLM Development Techniques**: More advanced LLM development techniques, including but not limited to: Prompt Engineering, processing of multiple types of source data, optimizing retrieval, recall ranking, Agent framework, etc. 3. **LLM Application Examples**: Introduce some successful open source cases, analyze the ideas, core concepts, and implementation frameworks of these application examples from the perspective of this course, and help beginners understand what kind of applications they can develop through LLM. Currently, the first part has been completed, and everyone is welcome to read and learn; the second and third parts are under creation. **Directory Structure Description**: requirements.txt: Installation dependencies in the official environment notebook: Notebook source code file docs: Markdown documentation file figures: Pictures data_base: Knowledge base source file used

The LLM course is divided into three parts: 1. 🧩 **LLM Fundamentals** covers essential knowledge about mathematics, Python, and neural networks. 2. 🧑‍🔬 **The LLM Scientist** focuses on building the best possible LLMs using the latest techniques. 3. 👷 **The LLM Engineer** focuses on creating LLM-based applications and deploying them. For an interactive version of this course, I created two **LLM assistants** that will answer questions and test your knowledge in a personalized way: * 🤗 **HuggingChat Assistant**: Free version using Mixtral-8x7B. * 🤖 **ChatGPT Assistant**: Requires a premium account. ## 📝 Notebooks A list of notebooks and articles related to large language models. ### Tools | Notebook | Description | Notebook | |----------|-------------|----------| | 🧐 LLM AutoEval | Automatically evaluate your LLMs using RunPod |  | | 🥱 LazyMergekit | Easily merge models using MergeKit in one click. |  | | 🦎 LazyAxolotl | Fine-tune models in the cloud using Axolotl in one click. |  | | ⚡ AutoQuant | Quantize LLMs in GGUF, GPTQ, EXL2, AWQ, and HQQ formats in one click. |  | | 🌳 Model Family Tree | Visualize the family tree of merged models. |  | | 🚀 ZeroSpace | Automatically create a Gradio chat interface using a free ZeroGPU. |  |

Swirl is an open-source software that allows users to simultaneously search multiple content sources and receive AI-ranked results. It connects to various data sources, including databases, public data services, and enterprise sources, and utilizes AI and LLMs to generate insights and answers based on the user's data. Swirl is easy to use, requiring only the download of a YML file, starting in Docker, and searching with Swirl. Users can add credentials to preloaded SearchProviders to access more sources. Swirl also offers integration with ChatGPT as a configured AI model. It adapts and distributes user queries to anything with a search API, re-ranking the unified results using Large Language Models without extracting or indexing anything. Swirl includes five Google Programmable Search Engines (PSEs) to get users up and running quickly. Key features of Swirl include Microsoft 365 integration, SearchProvider configurations, query adaptation, synchronous or asynchronous search federation, optional subscribe feature, pipelining of Processor stages, results stored in SQLite3 or PostgreSQL, built-in Query Transformation support, matching on word stems and handling of stopwords, duplicate detection, re-ranking of unified results using Cosine Vector Similarity, result mixers, page through all results requested, sample data sets, optional spell correction, optional search/result expiration service, easily extensible Connector and Mixer objects, and a welcoming community for collaboration and support.

ChatGPT-Next-Web-Pro is a tool that provides an enhanced version of ChatGPT-Next-Web with additional features and functionalities. It offers complete ChatGPT-Next-Web functionality, file uploading and storage capabilities, drawing and video support, multi-modal support, reverse model support, knowledge base integration, translation, customizations, and more. The tool can be deployed with or without a backend, allowing users to interact with AI models, manage accounts, create models, manage API keys, handle orders, manage memberships, and more. It supports various cloud services like Aliyun OSS, Tencent COS, and Minio for file storage, and integrates with external APIs like Azure, Google Gemini Pro, and Luma. The tool also provides options for customizing website titles, subtitles, icons, and plugin buttons, and offers features like voice input, file uploading, real-time token count display, and more.

COMFYUI LLM PARTY is a node library designed for LLM workflow development in ComfyUI, an extremely minimalist UI interface primarily used for AI drawing and SD model-based workflows. The project aims to provide a complete set of nodes for constructing LLM workflows, enabling users to easily integrate them into existing SD workflows. It features various functionalities such as API integration, local large model integration, RAG support, code interpreters, online queries, conditional statements, looping links for large models, persona mask attachment, and tool invocations for weather lookup, time lookup, knowledge base, code execution, web search, and single-page search. Users can rapidly develop web applications using API + Streamlit and utilize LLM as a tool node. Additionally, the project includes an omnipotent interpreter node that allows the large model to perform any task, with recommendations to use the 'show_text' node for display output.

The KQL Query Helper GPT is tailored specifically for assisting users with Kusto Query Language (KQL) queries. It leverages extensive knowledge from Azure Data Explorer documentation to aid users in understanding, reviewing, and creating new KQL queries based on their prompts.

Welcome to AIHelp.bot, your versatile assistant for any query. Whether it's a general knowledge question, a technical issue, or something more obscure, I'm here to help. Please type your question below, and I'll use my resources to find the best possible answer.

Aids in SPARQL queries for Semantic-Art's Gist Ontology

Expert in generating and debugging Neo4j code, with explanations on graph database principles.

Looper query strings assistant

Getting ready to query agents or publishers? Upload your manuscript. I analyse your novel's writing style, themes and genre. I'll tell you how it's relevant to a modern audience, offer marketing insights and will even write you a draft synopsis and cover letter. I'll help you find relevant agents.

I conjure advanced Google search queries.

Enhances PubMed searches with MeSH and follow-up advice

Expert in brief, direct SQL queries for BigQuery, with casual professional tone.

Helps get map data from Open Street Map by generating Overpass Turbo queries. Ask me for mapping features like cafes, rivers or highways

Expert in Power Query and DAX for Power BI, offering in-depth guidance and insights

Create the most effective database or search engine queries using keywords, truncation, and Boolean operators!

Query BCorp company data. All data is publicly available. United Kingdom only (for now).

SQL query validator and educator, adaptable to user's format.

Supabase expert also supports query generation and Flutter code generation

I'm your guide for any query and information related to TikTok Ads. Let's build your new campaign together!

Answers in query language, adds Korean translation and phonetics for non-Korean queries.

Knows the docs and can query official ordinal endpoints—Sat Numbers, Inscription IDs, and more.

Specializes in web searches for chat.openai.com using specific query format.

A sales enablement assistant for content creation and query resolution.