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Semaj AI is an AI tool designed to simplify the process of generating quizzes and obtaining answers from various AI models. It allows users to create quizzes on any topic with customizable settings and export options. Additionally, users can chat with different AI models like GPT, Gemini, and CLAUDE to get accurate and diverse responses. The platform aims to streamline the quiz creation process and provide access to cutting-edge AI technologies for enhanced learning and research purposes.

Petal is a document analysis platform powered by generative AI technology. It allows users to chat with their documents, providing fully sourced and reliable answers by linking to their own knowledge bases. Users can train AI on their documents to support their work, ensuring centralized knowledge management and document synchronization. Petal offers features such as automatic metadata extraction, file deduplication, and collaboration tools to enhance productivity and streamline workflows for researchers, faculty, and industry experts.

ChatPlayground AI is a versatile platform that allows users to compare multiple AI chatbots to obtain the best responses. With 14+ AI apps and features available, users can achieve better AI answers 73% of the time. The platform offers a comprehensive prompt library, real-time web search capabilities, image generation, history recall, document upload and analysis, and multilingual support. It caters to developers, data scientists, students, researchers, content creators, writers, and AI enthusiasts. Testimonials from users highlight the efficiency and creativity-enhancing benefits of using ChatPlayground AI.

Humata is a PDF AI that can summarize findings, compare documents, and search for answers in long technical papers. It is designed to help users save time and effort by automating the process of reading and understanding complex documents. Humata is easy to use and can be embedded in any webpage with a single click. It is also secure and reliable, with enterprise-grade data rooms and encryption to protect user data.

Nestor is an AI-powered insurance assistant that provides clear and jargon-free answers to all your insurance questions. It can audit your insurance contracts, identify potential over-insurance or under-insurance, and suggest ways to improve your coverage. Nestor is constantly learning and can provide expert advice on a wide range of insurance topics.

Shopper Buddy is an AI-powered conversational shopping assistant that provides personalized product recommendations and answers to your shopping-related questions. It aims to simplify the shopping experience by eliminating annoying ads and tracking, protecting your privacy. With Shopper Buddy, you can engage in a conversation with an interactive AI to get instant, tailored recommendations and enjoy a hassle-free shopping journey.

Healthee is an AI-powered employee benefits app that simplifies healthcare navigation for employees and stakeholders. It provides personalized answers to healthcare queries, streamlines open enrollment processes, and offers real-time insights and data-driven preventive care recommendations. With Healthee, employees can access vital health plan information anytime through a user-friendly mobile app.

MyLoans.ai is an AI-powered consumer advocate tool designed to assist graduate students in navigating their student loan repayment journey with confidence. The platform offers a free loan repayment calculator tailored specifically for current and former graduate students, providing simple and accurate answers to help users manage their student loans effectively.

RankRaven is an advanced AI rank tracking tool that allows users to monitor and analyze their brand's performance on AI search engines. The tool leverages multiple AI models such as OpenAI ChatGPT, Google Bard, and Microsoft Bing to provide fast and accurate SEO tracking. Users can track their brand's rank across different AI search models, receive daily rank updates, compare performance across languages and countries, and analyze trends over time. RankRaven automates the process of running prompts and checking keyword appearances in model answers, making it a valuable tool for individuals, businesses, and agencies looking to optimize their AI SEO strategies.

MindpoolAI is a tool that allows users to access multiple leading AI models with a single query. This means that users can get the answers they are looking for, spark ideas, and fuel their work, creativity, and curiosity. MindpoolAI is easy to use and does not require any technical expertise. Users simply need to enter their prompt and select the AI models they want to compare. MindpoolAI will then send the query to the selected models and present the results in an easy-to-understand format.

Gemini is a multi-modal AI model, developed by Google. It is designed to understand and generate human language, and can be used for a variety of tasks, including question answering, translation, and dialogue generation. ChatGPT is a large language model, developed by OpenAI. It is also designed to understand and generate human language, and can be used for a variety of tasks, including question answering, translation, and dialogue generation.

Prompt Octopus is a free tool that allows you to compare multiple prompts side-by-side. You can add as many prompts as you need and view the responses in real-time. This can be helpful for fine-tuning your prompts and getting the best possible results from your AI model.

LegalOn Technologies is a global leader in AI contract review software, providing a platform that enables users to negotiate stronger contracts up to 85% faster. The application offers pre-built and custom AI playbooks, built by experienced attorneys, to ensure high-quality contract reviews. LegalOn's AI is anchored in attorney-written content and rigorously tested, providing accurate and up-to-date legal knowledge for reliable results. The platform is SOC 2 Type II certified, GDPR, and CCPA compliant, prioritizing security and privacy for user data.

Zelma is an AI-powered research assistant that enables users to find, graph, and understand U.S. school testing data using plain English queries. It allows users to search student test data by school district, demographics, grade, and more, and presents the results with graphs, tables, and descriptions. Zelma aims to make education data accessible and understandable for everyone.

Photosolve is an AI-powered educational tool that helps students, teachers, researchers, and writers to quickly find accurate answers to their questions. It offers a Chrome extension and mobile app for easy access to its features. With over 10 million questions answered and growing, Photosolve revolutionizes learning by providing detailed explanations along with answers. Users can upload materials for analysis, have conversations with AI, generate flashcards, and enhance their knowledge with customizable quizzes. The application uses a custom-built AI model for higher accuracy compared to general AI models, ensuring reliable results for academic success.

My AskAI is an AI-powered customer support tool that integrates with Intercom. It offers a more affordable alternative to Intercom's Fin AI chatbot, costing only $0.19 per AI resolution compared to Intercom's $0.99. My AskAI allows businesses to add AI customer support to their Intercom workspace without replacing their existing widget or training their team on a new tool. Businesses can choose how they want their AI chatbot to reply, either directly to customers or as 'notes' for their agents. My AskAI also supports human handover for when a human touch is needed.

Joia is a private ChatGPT alternative built for collaboration within teams. It provides secure access to various large language models (LLMs) like GPT-4, Claude, and Gemini, allowing teams to build and share internal AI chat applications. Joia prioritizes data security, cost control, and offers a more affordable option compared to ChatGPT for Teams, with savings of up to 70%. It enables users to experiment with different LLMs and create personalized chatbots for repetitive tasks, enhancing team collaboration and efficiency.

Algo is a conversational AI chatbot that is different from ChatGPT. Algo is less verbose and more attuned to the user's needs, providing helpful and meaningful insights without a lot of excess chatter. Algo does not use your data for further training and model fine-tuning, and it is designed to keep all communication private and secure. You can delete your data at any time. This provides a higher level of control over personal information compared to ChatGPT, which is a public system and has no provision for data deletion. Beyond its conversational capabilities, Algo boasts built-in features that allow it to browse the web and craft stunning visuals using advanced generative AI models.

Contentable.ai is a platform for comparing multiple AI models, rapidly moving from prototyping to production, and management of your custom AI solutions across multiple vendors. It allows users to test multiple AI models in seconds, compare models side-by-side across top AI providers, collaborate on AI models with their team seamlessly, design complex AI workflows without coding, and pay as they go.

Sofon is a knowledge aggregation and curation platform that provides users with personalized insights on topics they care about. It aggregates and curates knowledge shared across 1,000+ articles, podcasts, and books, delivering a personalized stream of ideas to users. Sofon uses AI to compare ideas across hundreds of people on any question, saving users thousands of hours of curation. Users can indicate the people they want to learn from, and Sofon will curate insights across all their knowledge. Users can receive an idealetter, which is a unique combination of ideas across all the people they've selected around a common theme, delivered at an interval of their choice.

The Self-Iterative Agent System for Complex Problem Solving is a solution developed for the Alibaba Mathematical Competition (AI Challenge). It involves multiple LLMs engaging in multi-round 'self-questioning' to iteratively refine the problem-solving process and select optimal solutions. The system consists of main and evaluation models, with a process that includes detailed problem-solving steps, feedback loops, and iterative improvements. The approach emphasizes communication and reasoning between sub-agents, knowledge extraction, and the importance of Agent-like architectures in complex tasks. While effective, there is room for improvement in model capabilities and error prevention mechanisms.

MathEval is a benchmark designed for evaluating the mathematical capabilities of large models. It includes over 20 evaluation datasets covering various mathematical domains with more than 30,000 math problems. The goal is to assess the performance of large models across different difficulty levels and mathematical subfields. MathEval serves as a reliable reference for comparing mathematical abilities among large models and offers guidance on enhancing their mathematical capabilities in the future.

This repository contains scripts and tools for evaluating a chat app that uses the RAG architecture. It provides parameters to assess the quality and style of answers generated by the chat app, including system prompt, search parameters, and GPT model parameters. The tools facilitate running evaluations, with examples of evaluations on a sample chat app. The repo also offers guidance on cost estimation, setting up the project, deploying a GPT-4 model, generating ground truth data, running evaluations, and measuring the app's ability to say 'I don't know'. Users can customize evaluations, view results, and compare runs using provided tools.

H2O LLM Studio is a framework and no-code GUI designed for fine-tuning state-of-the-art large language models (LLMs). With H2O LLM Studio, you can easily and effectively fine-tune LLMs without the need for any coding experience. The GUI is specially designed for large language models, and you can finetune any LLM using a large variety of hyperparameters. You can also use recent finetuning techniques such as Low-Rank Adaptation (LoRA) and 8-bit model training with a low memory footprint. Additionally, you can use Reinforcement Learning (RL) to finetune your model (experimental), use advanced evaluation metrics to judge generated answers by the model, track and compare your model performance visually, and easily export your model to the Hugging Face Hub and share it with the community.

Arena-Hard-Auto-v0.1 is an automatic evaluation tool for instruction-tuned LLMs. It contains 500 challenging user queries. The tool prompts GPT-4-Turbo as a judge to compare models' responses against a baseline model (default: GPT-4-0314). Arena-Hard-Auto employs an automatic judge as a cheaper and faster approximator to human preference. It has the highest correlation and separability to Chatbot Arena among popular open-ended LLM benchmarks. Users can evaluate their models' performance on Chatbot Arena by using Arena-Hard-Auto.

Aligner is a model-agnostic alignment tool that learns correctional residuals between preferred and dispreferred answers using a small model. It can be directly applied to various open-source and API-based models with only one-off training, suitable for rapid iteration and improving model performance. Aligner has shown significant improvements in helpfulness, harmlessness, and honesty dimensions across different large language models.

The RAG Experiment Accelerator is a versatile tool that helps you conduct experiments and evaluations using Azure AI Search and RAG pattern. It offers a rich set of features, including experiment setup, integration with Azure AI Search, Azure Machine Learning, MLFlow, and Azure OpenAI, multiple document chunking strategies, query generation, multiple search types, sub-querying, re-ranking, metrics and evaluation, report generation, and multi-lingual support. The tool is designed to make it easier and faster to run experiments and evaluations of search queries and quality of response from OpenAI, and is useful for researchers, data scientists, and developers who want to test the performance of different search and OpenAI related hyperparameters, compare the effectiveness of various search strategies, fine-tune and optimize parameters, find the best combination of hyperparameters, and generate detailed reports and visualizations from experiment results.

TigerGraph CoPilot is an AI assistant that combines graph databases and generative AI to enhance productivity across various business functions. It includes three core component services: InquiryAI for natural language assistance, SupportAI for knowledge Q&A, and QueryAI for GSQL code generation. Users can interact with CoPilot through a chat interface on TigerGraph Cloud and APIs. CoPilot requires LLM services for beta but will support TigerGraph's LLM in future releases. It aims to improve contextual relevance and accuracy of answers to natural-language questions by building knowledge graphs and using RAG. CoPilot is extensible and can be configured with different LLM providers, graph schemas, and LangChain tools.

Yet Another Chatbot is a sophisticated multimodal chat interface powered by advanced AI models and equipped with a variety of tools. This chatbot can search and browse the web in real-time, query Wikipedia for information, perform news and map searches, execute Python code, compose long-form articles mixing text and images, generate, search, and compare images, analyze documents and images, search and download arXiv papers, save conversations as text and audio files, manage checklists, and track personal improvements. It offers tools for web interaction, Wikipedia search, Python scripting, content management, image handling, arXiv integration, conversation generation, file management, personal improvement, and checklist management.

The Bard API is a Python package that returns responses from Google Bard through the value of a cookie. It is an unofficial API that operates through reverse-engineering, utilizing cookie values to interact with Google Bard for users struggling with frequent authentication problems or unable to authenticate via Google Authentication. The Bard API is not a free service, but rather a tool provided to assist developers with testing certain functionalities due to the delayed development and release of Google Bard's API. It has been designed with a lightweight structure that can easily adapt to the emergence of an official API. Therefore, using it for any other purposes is strongly discouraged. If you have access to a reliable official PaLM-2 API or Google Generative AI API, replace the provided response with the corresponding official code. Check out https://github.com/dsdanielpark/Bard-API/issues/262.

Eval-Scope is a framework for evaluating and improving large language models (LLMs). It provides a set of commonly used test datasets, metrics, and a unified model interface for generating and evaluating LLM responses. Eval-Scope also includes an automatic evaluator that can score objective questions and use expert models to evaluate complex tasks. Additionally, it offers a visual report generator, an arena mode for comparing multiple models, and a variety of other features to support LLM evaluation and development.

VLMEvalKit is an open-source evaluation toolkit of large vision-language models (LVLMs). It enables one-command evaluation of LVLMs on various benchmarks, without the heavy workload of data preparation under multiple repositories. In VLMEvalKit, we adopt generation-based evaluation for all LVLMs, and provide the evaluation results obtained with both exact matching and LLM-based answer extraction.

Can AI Code is a self-evaluating interview tool for AI coding models. It includes interview questions written by humans and tests taken by AI, inference scripts for common API providers and CUDA-enabled quantization runtimes, a Docker-based sandbox environment for validating untrusted Python and NodeJS code, and the ability to evaluate the impact of prompting techniques and sampling parameters on large language model (LLM) coding performance. Users can also assess LLM coding performance degradation due to quantization. The tool provides test suites for evaluating LLM coding performance, a webapp for exploring results, and comparison scripts for evaluations. It supports multiple interviewers for API and CUDA runtimes, with detailed instructions on running the tool in different environments. The repository structure includes folders for interviews, prompts, parameters, evaluation scripts, comparison scripts, and more.

QANTA is a system and dataset for question answering tasks. It provides a script to download datasets, preprocesses questions, and matches them with Wikipedia pages. The system includes various datasets, training, dev, and test data in JSON and SQLite formats. Dependencies include Python 3.6, `click`, and NLTK models. Elastic Search 5.6 is needed for the Guesser component. Configuration is managed through environment variables and YAML files. QANTA supports multiple guesser implementations that can be enabled/disabled. Running QANTA involves using `cli.py` and Luigi pipelines. The system accesses raw Wikipedia dumps for data processing. The QANTA ID numbering scheme categorizes datasets based on events and competitions.

EDA GPT is an open-source data analysis companion that offers a comprehensive solution for structured and unstructured data analysis. It streamlines the data analysis process, empowering users to explore, visualize, and gain insights from their data. EDA GPT supports analyzing structured data in various formats like CSV, XLSX, and SQLite, generating graphs, and conducting in-depth analysis of unstructured data such as PDFs and images. It provides a user-friendly interface, powerful features, and capabilities like comparing performance with other tools, analyzing large language models, multimodal search, data cleaning, and editing. The tool is optimized for maximal parallel processing, searching internet and documents, and creating analysis reports from structured and unstructured data.

MemFree is an open-source hybrid AI search engine that allows users to simultaneously search their personal knowledge base (bookmarks, notes, documents, etc.) and the Internet. It features a self-hosted super fast serverless vector database, local embedding and rerank service, one-click Chrome bookmarks index, and full code open source. Users can contribute by opening issues for bugs or making pull requests for new features or improvements.

This repository contains convenience scripts to finetune LLaMa3-8B (or any other foundation model) for chat towards any language (that isn't English). The rationale behind this is that LLaMa3 is trained on primarily English data and while it works to some extent for other languages, its performance is poor compared to English.

This repository provides a curated list of papers, datasets, and resources related to the detection and mitigation of hallucinations in large language models (LLMs). Hallucinations refer to the generation of factually incorrect or nonsensical text by LLMs, which can be a significant challenge for their use in real-world applications. The resources in this repository aim to help researchers and practitioners better understand and address this issue.

LLMOps with Prompt flow is a template and guidance for building LLM-infused apps using Prompt flow. It provides centralized code hosting, lifecycle management, variant and hyperparameter experimentation, A/B deployment, many-to-many dataset/flow relationships, multiple deployment targets, comprehensive reporting, BYOF capabilities, configuration-based development, local prompt experimentation and evaluation, endpoint testing, and optional Human-in-loop validation. The tool is customizable to suit various application needs.

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