Best AI tools for< Integrate Research >

Midpage is a legal research platform powered by Generative AI, designed to provide comprehensive legal research capabilities to students and professionals. The platform offers advanced features such as grid-based search, case filtering with AI, proactive annotations, and seamless integration of research into documents. Midpage aims to streamline the legal research process by leveraging AI technology to enhance efficiency and accuracy in analyzing legal cases and statutes.

Luma Dream Machine is a cutting-edge AI application that empowers users to ideate, visualize, and create stunning images and videos with ease. It offers a new fluid medium for creativity, powered by advanced image and video AI models. Users can generate unique content, edit with natural language commands, and explore endless creative possibilities. The platform is designed to be intuitive and user-friendly, enabling users to bring their ideas to life in a collaborative and creative manner.

Luma AI is a 3D capture platform that allows users to create interactive 3D scenes from videos. With Luma AI, users can capture 3D models of people, objects, and environments, and then use those models to create interactive experiences such as virtual tours, product demonstrations, and training simulations.

Fleak AI Workflows is a low-code serverless API Builder designed for data teams to effortlessly integrate, consolidate, and scale their data workflows. It simplifies the process of creating, connecting, and deploying workflows in minutes, offering intuitive tools to handle data transformations and integrate AI models seamlessly. Fleak enables users to publish, manage, and monitor APIs effortlessly, without the need for infrastructure requirements. It supports various data types like JSON, SQL, CSV, and Plain Text, and allows integration with large language models, databases, and modern storage technologies.

Linnk AI is a powerful web research assistant and PDF summarizer tool designed to help professionals analyze and summarize content quickly and efficiently. It allows users to skim through news and articles effortlessly, grasp complex research insights, and summarize lengthy PDFs in seconds. With features like cross-language summarization, automatic knowledge base creation, and browser extension integration, Linnk AI empowers users to accelerate insight acquisition and creation. Join over 30,000 professionals and experience faster analysis and smarter content creation with Linnk AI.

LawY is a trusted AI legal assistant designed to accelerate legal research by providing matter-specific instant AI-answers with optional verification by qualified lawyers. It blends cutting-edge legal AI with human expertise to enhance firm efficiency and accuracy. LawY offers unprecedented speed in legal tasks, case summaries on demand, jurisdiction-specific answers, and integrated legal AI within existing practice software. The platform is trusted by 34,000+ lawyers worldwide and delivers verified legal AI to improve the accuracy of legal answers.

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.

Gemini is a large and powerful AI model developed by Google. It is designed to handle a wide variety of text and image reasoning tasks, and it can be used to build a variety of AI-powered applications. Gemini is available in three sizes: Ultra, Pro, and Nano. Ultra is the most capable model, but it is also the most expensive. Pro is the best performing model for a wide variety of tasks, and it is a good value for the price. Nano is the most efficient model, and it is designed for on-device use cases.

Inkwise is an AI-powered platform that helps users craft expert documents by extracting and integrating key information seamlessly from uploaded files. The platform offers features such as smart content extraction, predictive writing, document templates, and AI chat with files. Inkwise automates the document creation process by analyzing uploaded documents, extracting relevant data, and integrating it into customizable templates. It caters to various professions including academics, accounting, finance, corporate treasury, corporate tax, product management, procurement, legal, and marketing.

SheetGPT is an add-on for Google Sheets that allows users to integrate OpenAI's text and image generation capabilities into their spreadsheets. It is designed to be easy to use, with no API keys required, and offers a range of features including content creation, research and organization, summarization, and prototyping. SheetGPT is suitable for a variety of users, including content creators, digital marketing managers, researchers, and product managers.

Aurora is a market research tool powered by cutting-edge AI technology that provides instant, expert-level business insights for entrepreneurs and startups. It helps users discover their market size, gain valuable customer insights, make data-driven decisions, and stay ahead of the competition by accessing precise, up-to-date data on competitors and customers. Aurora offers a suite of AI market research tools with verified, traceable data to empower users to launch and grow their startups with confidence.

Raijin.ai is an AI-powered Customer Discovery and Intelligence Hub designed to help teams aggregate and extract key insights from customer conversations. It accelerates product development by prioritizing features based on customer feedback. The platform offers features like AI Thematic Analysis, Report Writing, Segmentation, and Tags to streamline qualitative research and analysis processes. Raijin.ai is ideal for user researchers, product analysts, and teams looking to integrate AI seamlessly into their workflow to create customer-centric products and data-driven marketing strategies.

ClearML is an open-source, end-to-end platform for continuous machine learning (ML). It provides a unified platform for data management, experiment tracking, model training, deployment, and monitoring. ClearML is designed to make it easy for teams to collaborate on ML projects and to ensure that models are deployed and maintained in a reliable and scalable way.

Beloga is a knowledge operating system (OS) for teams that instantly unifies tools and information, boosting productivity through seamless collaboration and real-time search. It uses AI to deliver precise, actionable insights from team data, enabling quick, informed decision-making. Beloga streamlines team workflows into a single platform, eliminating app-switching and enhancing collaboration and efficiency. It also offers multi-source integration, allowing users to easily compare and integrate data from multiple sources, revealing hidden insights. Beloga's features include hyper-contextualized key insights, seamless integration, cross-referencing made easy, and instant access to the information you need.

Needl.ai is an AI-powered platform designed to provide seamless information intelligence for enterprises. It unifies information from internal and external data sources, delivering near real-time, actionable insights. Users can connect preferred apps and data sources, curate personalized feeds, and centralize interactions with data using AI Assistants. Needl.ai offers a range of products for efficient enterprise decision-making, including Needl Feed, Needl Assistants, and AskNeedl for intelligent data aggregation and interactions.

Vellum AI is an AI platform that supports using Microsoft Azure hosted OpenAI models. It offers tools for prompt engineering, semantic search, prompt chaining, evaluations, and monitoring. Vellum enables users to build AI systems with features like workflow automation, document analysis, fine-tuning, Q&A over documents, intent classification, summarization, vector search, chatbots, blog generation, sentiment analysis, and more. The platform is backed by top VCs and founders of well-known companies, providing a complete solution for building LLM-powered applications.

Sensae is an AI-powered biofeedback platform that uses data-driven techniques to enhance personal well-being. It integrates physiology and psychology using haptic biofeedback to help people reconnect with their inner emotions. Sensae's technology provides deep insights into the body and mind, uncovering hidden emotional patterns and revealing the complex web of human behavior and thinking. The platform offers a range of modules, including advanced bio-monitoring, stress assessment, heart rate variability assessment, and psychometric testing. Sensae's proprietary wearable device provides haptic biofeedback, creating a direct feedback loop that ensures the effectiveness of both stimuli and interventions.

ChatTTS is an open-source text-to-speech model designed for dialogue scenarios, supporting both English and Chinese speech generation. Trained on approximately 100,000 hours of Chinese and English data, it delivers speech quality comparable to human dialogue. The tool is particularly suitable for tasks involving large language model assistants and creating dialogue-based audio and video introductions. It provides developers with a powerful and easy-to-use tool based on open-source natural language processing and speech synthesis technologies.

MedoSync is an AI-driven health platform that empowers users to monitor and analyze their vital and medical data, leveraging AI to provide personalized insights and recommendations for a healthier life. Users can upload lab results, digitize medical documents, use an AI symptom checker, create accounts for family members, and integrate with their healthcare system. The platform offers easy data export, accuracy in health insights, and personalized health recommendations, with a high user satisfaction rate.

Bottr is an AI assistant, companion, generator, and chatbot that can help you with anything you want. It is designed to make your life easier, more organized, and more productive. Bottr is more than just an assistant - it's your advisor and your companion all rolled into one. It is built on a state-of-the-art language model like chatGPT, enabling it to handle a wide range of tasks. From setting reminders and managing your schedule to conducting research and generating reports, your Bottr is there to assist. It is designed to evolve with you, learning from your preferences, habits, and needs, becoming more personalized and efficient over time.

Auto-Deep-Research is an open-source and cost-efficient alternative to OpenAI's Deep Research, based on the AutoAgent framework. It offers high performance, universal LLM support, flexible interaction, cost-efficiency, file support, and one-click launch. Users can seamlessly integrate with various LLMs, handle file uploads, and start instantly with a simple command. The tool aims to provide a fully-automated and personalized AI assistant at a lower cost, catering to community needs and showcasing the potential of AutoAgent for practical AI applications.

The Hume AI Python SDK allows users to integrate Hume APIs directly into their Python applications. Users can access complete documentation, quickstart guides, and example notebooks to get started. The SDK is designed to provide support for Hume's expressive communication platform built on scientific research. Users are encouraged to create an account at beta.hume.ai and stay updated on changes through Discord. The SDK may undergo breaking changes to improve tooling and ensure reliable releases in the future.

The Generative AI Use Cases Repository showcases a wide range of applications in generative AI, including Retrieval-Augmented Generation (RAG), AI Agents, and industry-specific use cases. It provides practical notebooks and guidance on utilizing frameworks such as LlamaIndex and LangChain, and demonstrates how to integrate models from leading AI research companies like Anthropic and OpenAI.

This project is a Chinese tutorial for domestic beginners based on the AutoDL platform, providing full-process guidance for various open-source large models, including environment configuration, local deployment, and efficient fine-tuning. It simplifies the deployment, use, and application process of open-source large models, enabling more ordinary students and researchers to better use open-source large models and helping open and free large models integrate into the lives of ordinary learners faster.

Cohere's Build-Your-Own-Connector framework allows integration of Cohere's Command LLM via the Chat API endpoint to any datastore/software holding text information with a search endpoint. Enables user queries grounded in proprietary information. Use-cases include question/answering, knowledge working, comms summary, and research. Repository provides code for popular datastores and a template connector. Requires Python 3.11+ and Poetry. Connectors can be built and deployed using Docker. Environment variables set authorization values. Pre-commits for linting. Connectors tailored to integrate with Cohere's Chat API for creating chatbots. Connectors return documents as JSON objects for Cohere's API to generate answers with citations.

HippoRAG is a novel retrieval augmented generation (RAG) framework inspired by the neurobiology of human long-term memory that enables Large Language Models (LLMs) to continuously integrate knowledge across external documents. It provides RAG systems with capabilities that usually require a costly and high-latency iterative LLM pipeline for only a fraction of the computational cost. The tool facilitates setting up retrieval corpus, indexing, and retrieval processes for LLMs, offering flexibility in choosing different online LLM APIs or offline LLM deployments through LangChain integration. Users can run retrieval on pre-defined queries or integrate directly with the HippoRAG API. The tool also supports reproducibility of experiments and provides data, baselines, and hyperparameter tuning scripts for research purposes.

This project aims to create a RESTful API server compatible with the OpenAI API using open-source backends like llama/llama2. With this project, various GPT tools/frameworks can be compatible with your own model. Key features include: - **Compatibility with OpenAI API**: The API server follows the OpenAI API structure, allowing seamless integration with existing tools and frameworks. - **Support for Multiple Backends**: The server supports both llama.cpp and pyllama backends, providing flexibility in model selection. - **Customization Options**: Users can configure model parameters such as temperature, top_p, and top_k to fine-tune the model's behavior. - **Batch Processing**: The API supports batch processing for embeddings, enabling efficient handling of multiple inputs. - **Token Authentication**: The server utilizes token authentication to secure access to the API. This tool is particularly useful for developers and researchers who want to integrate large language models into their applications or explore custom models without relying on proprietary APIs.

**RVC_CLI: Retrieval-based Voice Conversion Command Line Interface** This command-line interface (CLI) provides a comprehensive set of tools for voice conversion, enabling you to modify the pitch, timbre, and other characteristics of audio recordings. It leverages advanced machine learning models to achieve realistic and high-quality voice conversions. **Key Features:** * **Inference:** Convert the pitch and timbre of audio in real-time or process audio files in batch mode. * **TTS Inference:** Synthesize speech from text using a variety of voices and apply voice conversion techniques. * **Training:** Train custom voice conversion models to meet specific requirements. * **Model Management:** Extract, blend, and analyze models to fine-tune and optimize performance. * **Audio Analysis:** Inspect audio files to gain insights into their characteristics. * **API:** Integrate the CLI's functionality into your own applications or workflows. **Applications:** The RVC_CLI finds applications in various domains, including: * **Music Production:** Create unique vocal effects, harmonies, and backing vocals. * **Voiceovers:** Generate voiceovers with different accents, emotions, and styles. * **Audio Editing:** Enhance or modify audio recordings for podcasts, audiobooks, and other content. * **Research and Development:** Explore and advance the field of voice conversion technology. **For Jobs:** * Audio Engineer * Music Producer * Voiceover Artist * Audio Editor * Machine Learning Engineer **AI Keywords:** * Voice Conversion * Pitch Shifting * Timbre Modification * Machine Learning * Audio Processing **For Tasks:** * Convert Pitch * Change Timbre * Synthesize Speech * Train Model * Analyze Audio

Bolts package provides a variety of components to extend PyTorch Lightning, such as callbacks & datasets, for applied research and production. Users can accelerate Lightning training with the Torch ORT Callback to optimize ONNX graph for faster training & inference. Additionally, users can introduce sparsity with the SparseMLCallback to accelerate inference by leveraging the DeepSparse engine. Specific research implementations are encouraged, with contributions that help train SSL models and integrate with Lightning Flash for state-of-the-art models in applied research.

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.

Mergoo is a library for easily merging multiple LLM experts and efficiently training the merged LLM. With Mergoo, you can efficiently integrate the knowledge of different generic or domain-based LLM experts. Mergoo supports several merging methods, including Mixture-of-Experts, Mixture-of-Adapters, and Layer-wise merging. It also supports various base models, including LLaMa, Mistral, and BERT, and trainers, including Hugging Face Trainer, SFTrainer, and PEFT. Mergoo provides flexible merging for each layer and supports training choices such as only routing MoE layers or fully fine-tuning the merged LLM.

ComfyUI_VLM_nodes is a repository containing various nodes for utilizing Vision Language Models (VLMs) and Language Models (LLMs). The repository provides nodes for tasks such as structured output generation, image to music conversion, LLM prompt generation, automatic prompt generation, and more. Users can integrate different models like InternLM-XComposer2-VL, UForm-Gen2, Kosmos-2, moondream1, moondream2, JoyTag, and Chat Musician. The nodes support features like extracting keywords, generating prompts, suggesting prompts, and obtaining structured outputs. The repository includes examples and instructions for using the nodes effectively.

KanTV is an open-source project that focuses on studying and practicing state-of-the-art AI technology in real applications and scenarios, such as online TV playback, transcription, translation, and video/audio recording. It is derived from the original ijkplayer project and includes many enhancements and new features, including: * Watching online TV and local media using a customized FFmpeg 6.1. * Recording online TV to automatically generate videos. * Studying ASR (Automatic Speech Recognition) using whisper.cpp. * Studying LLM (Large Language Model) using llama.cpp. * Studying SD (Text to Image by Stable Diffusion) using stablediffusion.cpp. * Generating real-time English subtitles for English online TV using whisper.cpp. * Running/experiencing LLM on Xiaomi 14 using llama.cpp. * Setting up a customized playlist and using the software to watch the content for R&D activity. * Refactoring the UI to be closer to a real commercial Android application (currently only supports English). Some goals of this project are: * To provide a well-maintained "workbench" for ASR researchers interested in practicing state-of-the-art AI technology in real scenarios on mobile devices (currently focusing on Android). * To provide a well-maintained "workbench" for LLM researchers interested in practicing state-of-the-art AI technology in real scenarios on mobile devices (currently focusing on Android). * To create an Android "turn-key project" for AI experts/researchers (who may not be familiar with regular Android software development) to focus on device-side AI R&D activity, where part of the AI R&D activity (algorithm improvement, model training, model generation, algorithm validation, model validation, performance benchmark, etc.) can be done very easily using Android Studio IDE and a powerful Android phone.

LLMBox is a comprehensive library designed for implementing Large Language Models (LLMs) with a focus on a unified training pipeline and comprehensive model evaluation. It serves as a one-stop solution for training and utilizing LLMs, offering flexibility and efficiency in both training and utilization stages. The library supports diverse training strategies, comprehensive datasets, tokenizer vocabulary merging, data construction strategies, parameter efficient fine-tuning, and efficient training methods. For utilization, LLMBox provides comprehensive evaluation on various datasets, in-context learning strategies, chain-of-thought evaluation, evaluation methods, prefix caching for faster inference, support for specific LLM models like vLLM and Flash Attention, and quantization options. The tool is suitable for researchers and developers working with LLMs for natural language processing tasks.

OpenRL is an open-source general reinforcement learning research framework that supports training for various tasks such as single-agent, multi-agent, offline RL, self-play, and natural language. Developed based on PyTorch, the goal of OpenRL is to provide a simple-to-use, flexible, efficient and sustainable platform for the reinforcement learning research community. It supports a universal interface for all tasks/environments, single-agent and multi-agent tasks, offline RL training with expert dataset, self-play training, reinforcement learning training for natural language tasks, DeepSpeed, Arena for evaluation, importing models and datasets from Hugging Face, user-defined environments, models, and datasets, gymnasium environments, callbacks, visualization tools, unit testing, and code coverage testing. It also supports various algorithms like PPO, DQN, SAC, and environments like Gymnasium, MuJoCo, Atari, and more.

Chat with MLX is an all-in-one Chat Playground using Apple MLX on Apple Silicon Macs. It provides privacy-enhanced AI for secure conversations with various models, easy integration of HuggingFace and MLX Compatible Open-Source Models, and comes with default models like Llama-3, Phi-3, Yi, Qwen, Mistral, Codestral, Mixtral, StableLM. The tool is designed for developers and researchers working with machine learning models on Apple Silicon.

The 'ai4math-papers' repository contains a collection of research papers related to AI applications in mathematics, including automated theorem proving, synthetic theorem generation, autoformalization, proof refactoring, premise selection, benchmarks, human-in-the-loop interactions, and constructing examples/counterexamples. The papers cover various topics such as neural theorem proving, reinforcement learning for theorem proving, generative language modeling, formal mathematics statement curriculum learning, and more. The repository serves as a valuable resource for researchers and practitioners interested in the intersection of AI and mathematics.

Awesome-AI-Agents is a curated list of projects, frameworks, benchmarks, platforms, and related resources focused on autonomous AI agents powered by Large Language Models (LLMs). The repository showcases a wide range of applications, multi-agent task solver projects, agent society simulations, and advanced components for building and customizing AI agents. It also includes frameworks for orchestrating role-playing, evaluating LLM-as-Agent performance, and connecting LLMs with real-world applications through platforms and APIs. Additionally, the repository features surveys, paper lists, and blogs related to LLM-based autonomous agents, making it a valuable resource for researchers, developers, and enthusiasts in the field of AI.

xFinder is a model specifically designed for key answer extraction from large language models (LLMs). It addresses the challenges of unreliable evaluation methods by optimizing the key answer extraction module. The model achieves high accuracy and robustness compared to existing frameworks, enhancing the reliability of LLM evaluation. It includes a specialized dataset, the Key Answer Finder (KAF) dataset, for effective training and evaluation. xFinder is suitable for researchers and developers working with LLMs to improve answer extraction accuracy.

Awesome Responsible AI is a curated list of academic research, books, code of ethics, courses, data sets, frameworks, institutes, newsletters, principles, podcasts, reports, tools, regulations, and standards related to Responsible, Trustworthy, and Human-Centered AI. It covers various concepts such as Responsible AI, Trustworthy AI, Human-Centered AI, Responsible AI frameworks, AI Governance, and more. The repository provides a comprehensive collection of resources for individuals interested in ethical, transparent, and accountable AI development and deployment.

Creates educational flashcards and integrates with Anki.

I analyze and integrate missing clusters in data for coherent structuring.

Your sympy expert for physics

Merging technology with metaphysics in AI, exploring consciousness.

Enhanced search assistant with user feedback integration and advanced NLP.

Expert in Google Gemini, integrating report and web data for comprehensive explanations.

A Setun-70 simulator with modern API integration.

Advanced quantum computing expert for renewable energy mapping.

A versatile, user-friendly Sorting Bot for diverse data types, prioritizing privacy and adaptability.

Object Messaging and Intelligent Object Model for Deep AI integration with software

Expert in brainstorming and refining custom GPT ideas, with a focus on enhancement and integration.

Educational guide for understanding algebra principles and equations.

Small business acquisition advisor.

Creates full DOCX data analysis reports with integrated visualizations

I refine complex knowledge into granular, integrated solutions.

Maximized online data training with extensive search and resource utilization

Assists with solving and explaining integrals.

IntegriPal: Your friendly integral calculus guide!

以思维导图风格展示新闻重点

Detailed academic reviewer focusing on integrity and accuracy, using verified sources. Start with customizations!