Best AI tools for< Knowledge Injection >

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.

Cognee is an AI application that helps users build deterministic AI memory by perfecting exceptional AI apps with intelligent data management. It acts as a semantic memory layer, uncovering hidden connections within data and infusing it with company-specific language and principles. Cognee offers data ingestion and enrichment services, resulting in relevant data retrievals and lower infrastructure costs. The application is suitable for various industries, including customer engagement, EduTech, company onboarding, recruitment, marketing, and tourism.

Knowledgio is a no-code solution for building personalized AI tools, designed for agencies and individuals looking to transform their expertise into unique AI applications. The platform allows users to save time by creating highly personalized AI workspaces, enabling easy knowledge sharing and monetization. With a user-friendly interface and dedicated support, Knowledgio simplifies the process of building AI tools, making it accessible even for non-technical users. The platform supports easy data ingestion, organization, and distribution, helping users create stunning AI tools with minimal effort. Knowledgio also offers collaboration features, real-time editing, and parallel execution capabilities to enhance productivity and efficiency.

CoTech.ai is an Augmented Reality platform for automotive repair and maintenance, empowering service technicians with AR & AI-enabled solutions. The platform provides operational efficiency in automotive maintenance and inspections by offering direct access to expertise through AR-enabled instructions. It digitizes service operations, accelerates maintenance inspections, reduces training costs, and brings expert knowledge to technicians' fingertips. CoTech.ai revolutionizes maintenance with AI and AR, minimizing errors, maximizing performance, and enhancing the overall service experience.

Sapling is a language model copilot and API for businesses. It provides real-time suggestions to help sales, support, and success teams more efficiently compose personalized responses. Sapling also offers a variety of features to help businesses improve their customer service, including: * Autocomplete Everywhere: Provides deep learning-powered autocomplete suggestions across all messaging platforms, allowing agents to compose replies more quickly. * Sapling Suggest: Retrieves relevant responses from a team response bank and allows agents to respond more quickly to customer inquiries by simply clicking on suggested responses in real time. * Snippet macros: Allow for quick insertion of common responses. * Grammar and language quality improvements: Sapling catches 60% more language quality issues than other spelling and grammar checkers using a machine learning system trained on millions of English sentences. * Enterprise teams can define custom settings for compliance and content governance. * Distribute knowledge: Ensure team knowledge is shared in a snippet library accessible on all your web applications. * Perform blazing fast search on your knowledge library for compliance, upselling, training, and onboarding.

The website is an AI tool designed to generate a knowledge graph based on input text. It uses advanced algorithms and machine learning capabilities to streamline operations, deliver personalized experiences, and unlock new possibilities. Users can input text related to various topics, and the tool processes the information to create a structured knowledge graph.

Knowledge Drive is the world's only self-organizing, self-maintaining, and fully integrated work knowledge system. It utilizes AI technology to automatically build a knowledge base by extracting useful information from documents. The system ensures knowledge freshness, easy access to information, and seamless integration across various platforms like Microsoft Office 365, Google Workspace, and Slack. Knowledge Drive aims to revolutionize knowledge management and boost productivity in teams by providing a central source of truth and eliminating the need for manual documentation.

Open Knowledge Maps is the world's largest AI-based search engine for scientific knowledge. It aims to revolutionize discovery by increasing the visibility of research findings for science and society. The platform is open and nonprofit, based on the principles of open science, with a mission to create an inclusive, sustainable, and equitable infrastructure for all users. Users can map research topics with AI, find documents, and identify concepts to enhance their literature search experience.

Slice Knowledge is an AI-powered content creation platform designed for learning purposes. It offers fast and simple creation of learning units using AI technology. The platform is a perfect solution for course creators, HR and L&D teams, education experts, and enterprises looking to enhance their employee training programs. Slice Knowledge provides AI-powered creation, compliance templates, assistant bots, SCORM tracking integration, and multilingual support. It allows users to convert documents into interactive, responsive, SCORM-compliant learning materials with features like unlimited designer CSS, interactive video, multi-lingual support, and responsive design.

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!

Wolfram is a comprehensive platform that unifies algorithms, data, notebooks, linguistics, and deployment to provide a powerful computation platform. It offers a range of products and services for various industries, including education, engineering, science, and technology. Wolfram is known for its revolutionary knowledge-based programming language, Wolfram Language, and its flagship product Wolfram|Alpha, a computational knowledge engine. The platform also includes Wolfram Cloud for cloud-based services, Wolfram Engine for software implementation, and Wolfram Data Framework for real-world data analysis.

GitBook is a knowledge management platform that helps engineering teams centralize, access, and add to their technical knowledge in the tools they use every day. With GitBook, teams can capture knowledge from conversations, code, and meetings, and turn it into useful, readable documentation. GitBook also offers a variety of features to help teams collaborate on documentation, including a branch-based workflow, real-time editing, and user permissions.

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.

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.

Slite is an AI-powered knowledge base application designed to streamline documentation, knowledge sharing, and information retrieval within teams and organizations. It offers a user-friendly interface, hassle-free adoption, and AI-driven search capabilities to enhance productivity and collaboration. With features like document creation, AI-powered search, templates, integrations with existing tools, and a library of resources, Slite aims to revolutionize the way teams manage and access information. The application caters to various departments such as Product & Engineering, Customer Support, Human Resources, and IT & Operations, providing a centralized platform for knowledge management and team communication.

Bloomfire is an AI-based knowledge management software system that revolutionizes knowledge management within organizations. It offers AI-powered features such as enterprise search, authoring tools, data security, and collective knowledge engine. The platform enhances team collaboration, boosts efficiency, and empowers users to access and share knowledge seamlessly. Bloomfire's comprehensive solutions cater to various industries and team roles, providing valuable insights, customer support, and efficient knowledge sharing. With generative AI capabilities and deep indexing, Bloomfire ensures data readiness for AI initiatives, enabling users to make data-driven decisions and streamline processes.

Tettra is an AI-powered knowledge management system designed to help organizations curate company information into an internal knowledge base, instantly answer team questions with AI in Slack or the app, save reusable answers with automation, and streamline onboarding processes. It offers features like internal Q&A, knowledge management system, Slack integration, CSAT notifications, and integrations with SupportMan. Tettra is trusted by various teams to organize scattered knowledge and improve efficiency by eliminating bottlenecks and saving time from repetitive questions.

Tettra is an AI-powered knowledge management system designed to help companies curate internal information into a knowledge base, instantly answer team questions using AI in Slack or the app, save reusable answers with automation, and facilitate knowledge verification and approval. It streamlines knowledge sharing, reduces repetitive questions, and enhances team productivity.

1up is an AI-powered platform designed to automate knowledge for sales teams. It helps users complete RFPs and questionnaires 10 times faster by analyzing company knowledge sources and providing single answers for any question. The platform pulls information from various sources like websites, Google Drive, and Confluence to generate accurate and up-to-date responses, saving time and improving efficiency for sales teams.

Knowbase.ai is a knowledge management tool that allows users to store, organize, and chat with their knowledge base. It is powered by ChatGPT, which allows users to ask questions about their knowledge base and get answers in a conversational format. Knowbase.ai is designed to help users learn and remember information more effectively.

RecAI is a project that explores the integration of Large Language Models (LLMs) into recommender systems, addressing the challenges of interactivity, explainability, and controllability. It aims to bridge the gap between general-purpose LLMs and domain-specific recommender systems, providing a holistic perspective on the practical requirements of LLM4Rec. The project investigates various techniques, including Recommender AI agents, selective knowledge injection, fine-tuning language models, evaluation, and LLMs as model explainers, to create more sophisticated, interactive, and user-centric recommender systems.

KG-LLM-Papers is a repository that collects papers integrating knowledge graphs (KGs) and large language models (LLMs). It serves as a comprehensive resource for research on the role of KGs in the era of LLMs, covering surveys, methods, and resources related to this integration.

KAG is a logical reasoning and Q&A framework based on the OpenSPG engine and large language models. It is used to build logical reasoning and Q&A solutions for vertical domain knowledge bases. KAG supports logical reasoning, multi-hop fact Q&A, and integrates knowledge and chunk mutual indexing structure, conceptual semantic reasoning, schema-constrained knowledge construction, and logical form-guided hybrid reasoning and retrieval. The framework includes kg-builder for knowledge representation and kg-solver for logical symbol-guided hybrid solving and reasoning engine. KAG aims to enhance LLM service framework in professional domains by integrating logical and factual characteristics of KGs.

Paper-Reading-ConvAI is a repository that contains a list of papers, datasets, and resources related to Conversational AI, mainly encompassing dialogue systems and natural language generation. This repository is constantly updating.

The repository 'LLM-for-Healthcare' provides a comprehensive survey of large language models (LLMs) for healthcare, covering data, technology, applications, and accountability and ethics. It includes information on various LLM models, training data, evaluation methods, and computation costs. The repository also discusses tasks such as NER, text classification, question answering, dialogue systems, and generation of medical reports from images in the healthcare domain.

Scientific Large Language Models (Sci-LLMs) is a repository that collects papers on scientific large language models, focusing on biology and chemistry domains. It includes textual, molecular, protein, and genomic languages, as well as multimodal language. The repository covers various large language models for tasks such as molecule property prediction, interaction prediction, protein sequence representation, protein sequence generation/design, DNA-protein interaction prediction, and RNA prediction. It also provides datasets and benchmarks for evaluating these models. The repository aims to facilitate research and development in the field of scientific language modeling.

Analyze the following text from a github repository (name and readme text at end) . Then, generate a JSON object with the following keys and provide the corresponding information for each key, in lowercase letters: 'description' (detailed description of the repo, must be less than 400 words，Ensure that no line breaks and quotation marks.),'for_jobs' (List 5 jobs suitable for this tool,in lowercase letters), 'ai_keywords' (keywords of the tool,user may use those keyword to find the tool,in lowercase letters), 'for_tasks' (list of 5 specific tasks user can use this tool to do,in lowercase letters), 'answer' (in english languages)

This repository serves as a practical guide for Medical Large Language Models (Medical LLMs) and provides resources, surveys, and tools for building, fine-tuning, and utilizing LLMs in the medical domain. It covers a wide range of topics including pre-training, fine-tuning, downstream biomedical tasks, clinical applications, challenges, future directions, and more. The repository aims to provide insights into the opportunities and challenges of LLMs in medicine and serve as a practical resource for constructing effective medical LLMs.

EasyEdit is a Python package for edit Large Language Models (LLM) like `GPT-J`, `Llama`, `GPT-NEO`, `GPT2`, `T5`(support models from **1B** to **65B**), the objective of which is to alter the behavior of LLMs efficiently within a specific domain without negatively impacting performance across other inputs. It is designed to be easy to use and easy to extend.

Knowledge Conflicts for LLMs: A Survey is a repository containing a survey paper that investigates three types of knowledge conflicts: context-memory conflict, inter-context conflict, and intra-memory conflict within Large Language Models (LLMs). The survey reviews the causes, behaviors, and possible solutions to these conflicts, providing a comprehensive analysis of the literature in this area. The repository includes detailed information on the types of conflicts, their causes, behavior analysis, and mitigating solutions, offering insights into how conflicting knowledge affects LLMs and how to address these conflicts.

LLM-Navigation is a repository dedicated to documenting learning records related to large models, including basic knowledge, prompt engineering, building effective agents, model expansion capabilities, security measures against prompt injection, and applications in various fields such as AI agent control, browser automation, financial analysis, 3D modeling, and tool navigation using MCP servers. The repository aims to organize and collect information for personal learning and self-improvement through AI exploration.

Kairon is an open-source conversational digital transformation platform that helps build LLM-based digital assistants at scale. It provides a no-coding web interface for adapting, training, testing, and maintaining AI assistants. Kairon focuses on pre-processing data for chatbots, including question augmentation, knowledge graph generation, and post-processing metrics. It offers end-to-end lifecycle management, low-code/no-code interface, secure script injection, telemetry monitoring, chat client designer, analytics module, and real-time struggle analytics. Kairon is suitable for teams and individuals looking for an easy interface to create, train, test, and deploy digital assistants.

AgentDojo is a dynamic environment designed to evaluate prompt injection attacks and defenses for large language models (LLM) agents. It provides a benchmark script to run different suites and tasks with specified LLM models, defenses, and attacks. The tool is under active development, and users can inspect the results through dedicated documentation pages and the Invariant Benchmark Registry.

LightRAG is a repository hosting the code for LightRAG, a system that supports seamless integration of custom knowledge graphs, Oracle Database 23ai, Neo4J for storage, and multiple file types. It includes features like entity deletion, batch insert, incremental insert, and graph visualization. LightRAG provides an API server implementation for RESTful API access to RAG operations, allowing users to interact with it through HTTP requests. The repository also includes evaluation scripts, code for reproducing results, and a comprehensive code structure.

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. |  |

This repository focuses on utilizing generative AI to bridge the gap between natural language questions and SQL queries, aiming to improve data consumption in enterprise data warehouses. It addresses challenges in SQL query generation, such as foreign key relationships and table joins, and highlights the importance of accuracy metrics like Execution Accuracy (EX) and Exact Set Match Accuracy (EM). The workshop content covers advanced prompt engineering, Retrieval Augmented Generation (RAG), fine-tuning models, and security measures against prompt and SQL injections.

Awesome-Graph-LLM is a curated collection of research papers exploring the intersection of graph-based techniques with Large Language Models (LLMs). The repository aims to bridge the gap between LLMs and graph structures prevalent in real-world applications by providing a comprehensive list of papers covering various aspects of graph reasoning, node classification, graph classification/regression, knowledge graphs, multimodal models, applications, and tools. It serves as a valuable resource for researchers and practitioners interested in leveraging LLMs for graph-related tasks.

Este modelo de GPT proporciona información general sobre la toxina botulínica, incluyendo su historia, usos comunes y datos de interés. Está diseñado para educar y ofrecer una visión general basada en fuentes de información públicas y conocidas. No proporciona consejos médicos

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

Documentation for Knowledge Base

Extracts and structures web content in formal, technical language.

Expert in esoteric knowledge, encouraging exploration and understanding.

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

Expert on Tesla's AI, robotics, and societal impact.

Dynamic quiz game with a wide range of topics, +3 points for correct answers, -2 for incorrect. 5-minute limit.

Power your chats with capsules of pure Knowledge, built from specialized PDF document collections on Google Drive.​​ Chat with Breebs, create and share a Breeb ! 𝗪𝗪𝗪.𝗕𝗥𝗘𝗘𝗕𝗦.𝗖𝗢𝗠 🚀

A knowledgeable guide on customer service best practices and terminology.

Art master with enhanced art knowledge and abilities

An assistant for Prod MBA students to ask questions about the content, product & the Prod MBA experience.

If you crave a systematic approach to learning, I'm your Knowledge Architect. I'll navigate you through comprehensive knowledge hierarchies, step by step, in any subject you choose. Share this systematic learning method with your friends to elevate their learning experiences.