New AI tools - Open Source
![curiso Screenshot](/screenshots_githubs/metaspartan-curiso.jpg)
curiso
Curiso AI is an infinite canvas platform that connects nodes and AI services to explore ideas without repetition. It empowers advanced users to unlock richer AI interactions. Features include multi OS support, infinite canvas, multiple AI provider integration, local AI inference provider integration, custom model support, model metrics, RAG support, local Transformers.js embedding models, inference parameters customization, multiple boards, vision model support, customizable interface, node-based conversations, and secure local encrypted storage. Curiso also offers a Solana token for exclusive access to premium features and enhanced AI capabilities.
![VectorCode Screenshot](/screenshots_githubs/Davidyz-VectorCode.jpg)
VectorCode
VectorCode is a code repository indexing tool that helps users write better prompts for coding LLMs by providing information about the code repository being worked on. It includes a neovim plugin and supports multiple embedding engines. The tool enhances completion results by providing project context and improves understanding of close-source or cutting edge projects.
![evalchemy Screenshot](/screenshots_githubs/mlfoundations-evalchemy.jpg)
evalchemy
Evalchemy is a unified and easy-to-use toolkit for evaluating language models, focusing on post-trained models. It integrates multiple existing benchmarks such as RepoBench, AlpacaEval, and ZeroEval. Key features include unified installation, parallel evaluation, simplified usage, and results management. Users can run various benchmarks with a consistent command-line interface and track results locally or integrate with a database for systematic tracking and leaderboard submission.
![LLMcalc Screenshot](/screenshots_githubs/Raskoll2-LLMcalc.jpg)
LLMcalc
LLM Calculator is a script that estimates the memory requirements and performance of Hugging Face models based on quantization levels. It fetches model parameters, calculates required memory, and analyzes performance with different RAM/VRAM configurations. The tool supports Windows and Linux, AMD, Intel, and Nvidia GPUs. Users can input a Hugging Face model ID to get its parameter count and analyze memory requirements for various quantization schemes. The tool provides estimates for GPU offload percentage and throughput in tk/s. It requires dependencies like python, uv, pciutils for AMD + Linux, and drivers for Nvidia. The tool is designed for rough estimates and may not work with MultiGPU setups.
![mark Screenshot](/screenshots_githubs/relston-mark.jpg)
mark
Mark is a CLI tool that allows users to interact with large language models (LLMs) using Markdown format. It enables users to seamlessly integrate GPT responses into Markdown files, supports image recognition, scraping of local and remote links, and image generation. Mark focuses on using Markdown as both a prompt and response medium for LLMs, offering a unique and flexible way to interact with language models for various use cases in development and documentation processes.
![backtrack_sampler Screenshot](/screenshots_githubs/Mihaiii-backtrack_sampler.jpg)
backtrack_sampler
Backtrack Sampler is a framework for experimenting with custom sampling algorithms that can backtrack the latest generated tokens. It provides a simple and easy-to-understand codebase for creating new sampling strategies. Users can implement their own strategies by creating new files in the `/strategy` directory. The repo includes examples for usage with llama.cpp and transformers, showcasing different strategies like Creative Writing, Anti-slop, Debug, Human Guidance, Adaptive Temperature, and Replace. The goal is to encourage experimentation and customization of backtracking algorithms for language models.
![every-chatgpt-gui Screenshot](/screenshots_githubs/billmei-every-chatgpt-gui.jpg)
every-chatgpt-gui
Every front-end GUI client for ChatGPT API is a curated list of graphical user interface alternatives to access the API for ChatGPT, Claude, and other LLMs. The repository serves as a collection of open-source, self-hosted, and desktop applications that provide different interfaces for interacting with ChatGPT and similar language models. Users can contribute by adding their own apps through pull requests, ensuring alphabetical order and easy access to various GUI options for ChatGPT API.
![JLB-AI-Agent Screenshot](/screenshots_githubs/deepsuckai-JLB-AI-Agent.jpg)
JLB-AI-Agent
JLB AI Agent is an innovative solution built on the Solana blockchain that harnesses the power of artificial intelligence to automate complex tasks and optimize decision-making in the DeFi space. It aims to provide real-time analytics, efficient operations, and seamless integration for both newcomers and experienced crypto enthusiasts. The tool offers features like blockchain agent chat terminal, real-time streaming implementation, trading infrastructure, NFT management, AI integration, and more, empowering users with autonomous technology where AI meets the dynamic landscape of blockchain.
![lawglance Screenshot](/screenshots_githubs/lawglance-lawglance.jpg)
lawglance
LawGlance is an AI-powered legal assistant that aims to bridge the gap between people and legal access. It is a free, open-source initiative designed to provide quick and accurate legal support tailored to individual needs. The project covers various laws, with plans for international expansion in the future. LawGlance utilizes AI-powered Retriever-Augmented Generation (RAG) to deliver legal guidance accessible to both laypersons and professionals. The tool is developed with support from mentors and experts at Data Science Academy and Curvelogics.
![GPT4DFCI Screenshot](/screenshots_githubs/Dana-Farber-AIOS-GPT4DFCI.jpg)
GPT4DFCI
GPT4DFCI is a private and secure generative AI tool based on GPT-4, deployed for non-clinical use at Dana-Farber Cancer Institute. The tool is overseen by the Dana-Farber AI Governance Committee and developed by the Dana-Farber Informatics & Analytics Department. The repository includes manuscript & policy details, training material, front-end and back-end code, infrastructure information, API client for programmatic use, licensing details, and contact information.
![UniChat Screenshot](/screenshots_githubs/AkiKurisu-UniChat.jpg)
UniChat
UniChat is a pipeline tool for creating online and offline chat-bots in Unity. It leverages Unity.Sentis and text vector embedding technology to enable offline mode text content search based on vector databases. The tool includes a chain toolkit for embedding LLM and Agent in games, along with middleware components for Text to Speech, Speech to Text, and Sub-classifier functionalities. UniChat also offers a tool for invoking tools based on ReActAgent workflow, allowing users to create personalized chat scenarios and character cards. The tool provides a comprehensive solution for designing flexible conversations in games while maintaining developer's ideas.
![fridon-ai Screenshot](/screenshots_githubs/FridonAI-fridon-ai.jpg)
fridon-ai
FridonAI is an open-source project offering AI-powered tools for cryptocurrency analysis and blockchain operations. It includes modules like FridonAnalytics for price analysis, FridonSearch for technical indicators, FridonNotifier for custom alerts, FridonBlockchain for blockchain operations, and FridonChat as a unified chat interface. The platform empowers users to create custom AI chatbots, access crypto tools, and interact effortlessly through chat. The core functionality is modular, with plugins, tools, and utilities for easy extension and development. FridonAI implements a scoring system to assess user interactions and incentivize engagement. The application uses Redis extensively for communication and includes a Nest.js backend for system operations.
![algebraic-nnhw Screenshot](/screenshots_githubs/trevorpogue-algebraic-nnhw.jpg)
algebraic-nnhw
This repository contains the source code for a GEMM & deep learning hardware accelerator system used to validate proposed systolic array hardware architectures implementing efficient matrix multiplication algorithms to increase performance-per-area limits of GEMM & AI accelerators. Achieved results include up to 3× faster CNN inference, >2× higher mults/multiplier/clock cycle, and low area with high clock frequency. The system is specialized for inference of non-sparse DNN models with fixed-point/quantized inputs, fully accelerating all DNN layers in hardware, and highly optimizing GEMM acceleration.
![YuE Screenshot](/screenshots_githubs/multimodal-art-projection-YuE.jpg)
YuE
YuE (乐) is an open-source foundation model designed for music generation, specifically transforming lyrics into full songs. It can generate complete songs in various genres and vocal styles, ensuring a polished and cohesive result. The model requires significant GPU memory for generating long sequences and recommends specific configurations for optimal performance. Users can customize the number of sessions for memory usage. The tool provides a quickstart guide for generating music using Transformers and includes tips for execution time and tag selection. The project is licensed under Creative Commons Attribution Non Commercial 4.0.
![pandas-ai Screenshot](/screenshots_githubs/sinaptik-ai-pandas-ai.jpg)
pandas-ai
PandaAI is a Python platform that enables users to interact with their data in natural language, catering to both non-technical and technical users. It simplifies data querying and analysis, offering conversational data analytics capabilities with minimal code. Users can ask questions, visualize charts, and compare dataframes effortlessly. The tool aims to streamline data exploration and decision-making processes by providing a user-friendly interface for data manipulation and analysis.
![Journal-Club Screenshot](/screenshots_githubs/RISE-MICCAI-Journal-Club.jpg)
Journal-Club
The RISE Journal Club is a bi-weekly reading group that provides a friendly environment for discussing state-of-the-art papers in medical image analysis, AI, and computer vision. The club aims to enhance critical and design thinking skills essential for researchers. Moderators introduce papers for discussion on various topics such as registration, segmentation, federated learning, fairness, and reinforcement learning. The club covers papers from machine and deep learning communities, offering a broad overview of cutting-edge methods.
![flo-ai Screenshot](/screenshots_githubs/rootflo-flo-ai.jpg)
flo-ai
Flo AI is a Python framework that enables users to build production-ready AI agents and teams with minimal code. It allows users to compose complex AI architectures using pre-built components while maintaining the flexibility to create custom components. The framework supports composable, production-ready, YAML-first, and flexible AI systems. Users can easily create AI agents and teams, manage teams of AI agents working together, and utilize built-in support for Retrieval-Augmented Generation (RAG) and compatibility with Langchain tools. Flo AI also provides tools for output parsing and formatting, tool logging, data collection, and JSON output collection. It is MIT Licensed and offers detailed documentation, tutorials, and examples for AI engineers and teams to accelerate development, maintainability, scalability, and testability of AI systems.
![ollama4j-web-ui Screenshot](/screenshots_githubs/ollama4j-ollama4j-web-ui.jpg)
ollama4j-web-ui
Ollama4j Web UI is a Java-based web interface built using Spring Boot and Vaadin framework for Ollama users with Java and Spring background. It allows users to interact with various models running on Ollama servers, providing a fully functional web UI experience. The project offers multiple ways to run the application, including via Docker, Docker Compose, or as a standalone JAR. Users can configure the environment variables and access the web UI through a browser. The project also includes features for error handling on the UI and settings pane for customizing default parameters.
![CodeGen Screenshot](/screenshots_githubs/salesforce-CodeGen.jpg)
CodeGen
CodeGen is an official release of models for Program Synthesis by Salesforce AI Research. It includes CodeGen1 and CodeGen2 models with varying parameters. The latest version, CodeGen2.5, outperforms previous models. The tool is designed for code generation tasks using large language models trained on programming and natural languages. Users can access the models through the Hugging Face Hub and utilize them for program synthesis and infill sampling. The accompanying Jaxformer library provides support for data pre-processing, training, and fine-tuning of the CodeGen models.
![CodeTF Screenshot](/screenshots_githubs/salesforce-CodeTF.jpg)
CodeTF
CodeTF is a Python transformer-based library for code large language models (Code LLMs) and code intelligence. It provides an interface for training and inferencing on tasks like code summarization, translation, and generation. The library offers utilities for code manipulation across various languages, including easy extraction of code attributes. Using tree-sitter as its core AST parser, CodeTF enables parsing of function names, comments, and variable names. It supports fast model serving, fine-tuning of LLMs, various code intelligence tasks, preprocessed datasets, model evaluation, pretrained and fine-tuned models, and utilities to manipulate source code. CodeTF aims to facilitate the integration of state-of-the-art Code LLMs into real-world applications, ensuring a user-friendly environment for code intelligence tasks.
![factualNLG Screenshot](/screenshots_githubs/salesforce-factualNLG.jpg)
factualNLG
FactualNLG is a tool designed to analyze the consistency of edits in summaries. It includes a benchmark with various LLM models, data release for the SummEdits benchmark, explanation analysis for identifying inconsistent summaries, and prompts used in experiments.
![xgen Screenshot](/screenshots_githubs/salesforce-xgen.jpg)
xgen
XGen is a research release for the family of XGen models (7B) by Salesforce AI Research. It includes models with support for different sequence lengths and tokenization using the OpenAI Tiktoken package. The models can be used for auto-regressive sampling in natural language generation tasks.
![codellm-devkit Screenshot](/screenshots_githubs/IBM-codellm-devkit.jpg)
codellm-devkit
Codellm-devkit (CLDK) is a Python library that serves as a multilingual program analysis framework bridging traditional static analysis tools and Large Language Models (LLMs) specialized for code (CodeLLMs). It simplifies the process of analyzing codebases across multiple programming languages, enabling the extraction of meaningful insights and facilitating LLM-based code analysis. The library provides a unified interface for integrating outputs from various analysis tools and preparing them for effective use by CodeLLMs. Codellm-devkit aims to enable the development and experimentation of robust analysis pipelines that combine traditional program analysis tools and CodeLLMs, reducing friction in multi-language code analysis and ensuring compatibility across different tools and LLM platforms. It is designed to seamlessly integrate with popular analysis tools like WALA, Tree-sitter, LLVM, and CodeQL, acting as a crucial intermediary layer for efficient communication between these tools and CodeLLMs. The project is continuously evolving to include new tools and frameworks, maintaining its versatility for code analysis and LLM integration.
![Janus Screenshot](/screenshots_githubs/deepseek-ai-Janus.jpg)
Janus
Janus is a series of unified multimodal understanding and generation models, including Janus-Pro, Janus, and JanusFlow. Janus-Pro is an advanced version that improves both multimodal understanding and visual generation significantly. Janus decouples visual encoding for unified multimodal understanding and generation, surpassing previous models. JanusFlow harmonizes autoregression and rectified flow for unified multimodal understanding and generation, achieving comparable or superior performance to specialized models. The models are available for download and usage, supporting a broad range of research in academic and commercial communities.
![Gaudi-tutorials Screenshot](/screenshots_githubs/HabanaAI-Gaudi-tutorials.jpg)
Gaudi-tutorials
The Intel Gaudi Tutorials repository contains source files for tutorials on using PyTorch and PyTorch Lightning on the Intel Gaudi AI Processor. The tutorials cater to users from beginner to advanced levels and cover various tasks such as fine-tuning models, running inference, and setting up DeepSpeed for training large language models. Users need access to an Intel Gaudi 2 Accelerator card or node, run the Intel Gaudi PyTorch Docker image, clone the tutorial repository, install Jupyterlab, and run the Jupyterlab server to follow along with the tutorials.
![BetterOCR Screenshot](/screenshots_githubs/junhoyeo-BetterOCR.jpg)
BetterOCR
BetterOCR is a tool that enhances text detection by combining multiple OCR engines with LLM (Language Model). It aims to improve OCR results, especially for languages with limited training data or noisy outputs. The tool combines results from EasyOCR, Tesseract, and Pororo engines, along with LLM support from OpenAI. Users can provide custom context for better accuracy, view performance examples by language, and upcoming features include box detection, improved interface, and async support. The package is under rapid development and contributions are welcomed.
![Multi-Agent-Custom-Automation-Engine-Solution-Accelerator Screenshot](/screenshots_githubs/microsoft-Multi-Agent-Custom-Automation-Engine-Solution-Accelerator.jpg)
Multi-Agent-Custom-Automation-Engine-Solution-Accelerator
The Multi-Agent -Custom Automation Engine Solution Accelerator is an AI-driven orchestration system that manages a group of AI agents to accomplish tasks based on user input. It uses a FastAPI backend to handle HTTP requests, processes them through various specialized agents, and stores stateful information using Azure Cosmos DB. The system allows users to focus on what matters by coordinating activities across an organization, enabling GenAI to scale, and is applicable to most industries. It is intended for developing and deploying custom AI solutions for specific customers, providing a foundation to accelerate building out multi-agent systems.
![LabelQuick Screenshot](/screenshots_githubs/xaio6-LabelQuick.jpg)
LabelQuick
LabelQuick_V2.0 is a fast image annotation tool designed and developed by the AI Horizon team. This version has been optimized and improved based on the previous version. It provides an intuitive interface and powerful annotation and segmentation functions to efficiently complete dataset annotation work. The tool supports video object tracking annotation, quick annotation by clicking, and various video operations. It introduces the SAM2 model for accurate and efficient object detection in video frames, reducing manual intervention and improving annotation quality. The tool is designed for Windows systems and requires a minimum of 6GB of memory.
![Conversation-Knowledge-Mining-Solution-Accelerator Screenshot](/screenshots_githubs/microsoft-Conversation-Knowledge-Mining-Solution-Accelerator.jpg)
Conversation-Knowledge-Mining-Solution-Accelerator
The Conversation Knowledge Mining Solution Accelerator enables customers to leverage intelligence to uncover insights, relationships, and patterns from conversational data. It empowers users to gain valuable knowledge and drive targeted business impact by utilizing Azure AI Foundry, Azure OpenAI, Microsoft Fabric, and Azure Search for topic modeling, key phrase extraction, speech-to-text transcription, and interactive chat experiences.
![ComfyUI_Yvann-Nodes Screenshot](/screenshots_githubs/yvann-ba-ComfyUI_Yvann-Nodes.jpg)
ComfyUI_Yvann-Nodes
ComfyUI_Yvann-Nodes is a pack of custom nodes that enable audio reactivity within ComfyUI, allowing users to create AI-driven animations that sync with music. Users can generate audio reactive AI videos, control AI generation styles, content, and composition with any audio input. The tool is simple to use by dropping workflows in ComfyUI and specifying audio and visual inputs. It is flexible and works with existing ComfyUI AI tech and nodes like IPAdapter, AnimateDiff, and ControlNet. Users can pick workflows for Images → Video or Video → Video, download the corresponding .json file, drop it into ComfyUI, install missing custom nodes, set inputs, and generate audio-reactive animations.
![finite-monkey-engine Screenshot](/screenshots_githubs/BradMoonUESTC-finite-monkey-engine.jpg)
finite-monkey-engine
FiniteMonkey is an advanced vulnerability mining engine powered purely by GPT, requiring no prior knowledge base or fine-tuning. Its effectiveness significantly surpasses most current related research approaches. The tool is task-driven, prompt-driven, and focuses on prompt design, leveraging 'deception' and hallucination as key mechanics. It has helped identify vulnerabilities worth over $60,000 in bounties. The tool requires PostgreSQL database, OpenAI API access, and Python environment for setup. It supports various languages like Solidity, Rust, Python, Move, Cairo, Tact, Func, Java, and Fake Solidity for scanning. FiniteMonkey is best suited for logic vulnerability mining in real projects, not recommended for academic vulnerability testing. GPT-4-turbo is recommended for optimal results with an average scan time of 2-3 hours for medium projects. The tool provides detailed scanning results guide and implementation tips for users.
![oat Screenshot](/screenshots_githubs/sail-sg-oat.jpg)
oat
Oat is a simple and efficient framework for running online LLM alignment algorithms. It implements a distributed Actor-Learner-Oracle architecture, with components optimized using state-of-the-art tools. Oat simplifies the experimental pipeline of LLM alignment by serving an Oracle online for preference data labeling and model evaluation. It provides a variety of oracles for simulating feedback and supports verifiable rewards. Oat's modular structure allows for easy inheritance and modification of classes, enabling rapid prototyping and experimentation with new algorithms. The framework implements cutting-edge online algorithms like PPO for math reasoning and various online exploration algorithms.
![Open-LLM-VTuber Screenshot](/screenshots_githubs/Open-LLM-VTuber-Open-LLM-VTuber.jpg)
Open-LLM-VTuber
Open-LLM-VTuber is a voice-interactive AI companion supporting real-time voice conversations and featuring a Live2D avatar. It can run offline on Windows, macOS, and Linux, offering web and desktop client modes. Users can customize appearance and persona, with rich LLM inference, text-to-speech, and speech recognition support. The project is highly customizable, extensible, and actively developed with exciting features planned. It provides privacy with offline mode, persistent chat logs, and various interaction features like voice interruption, touch feedback, Live2D expressions, pet mode, and more.
![RAG-Retrieval Screenshot](/screenshots_githubs/NovaSearch-Team-RAG-Retrieval.jpg)
RAG-Retrieval
RAG-Retrieval is an end-to-end code repository that provides training, inference, and distillation capabilities for the RAG retrieval model. It supports fine-tuning of various open-source RAG retrieval models, including embedding models, late interactive models, and reranker models. The repository offers a lightweight Python library for calling different RAG ranking models and allows distillation of LLM-based reranker models into bert-based reranker models. It includes features such as support for end-to-end fine-tuning, distillation of large models, advanced algorithms like MRL, multi-GPU training strategy, and a simple code structure for easy modifications.
![mcp-client-cli Screenshot](/screenshots_githubs/adhikasp-mcp-client-cli.jpg)
mcp-client-cli
MCP CLI client is a simple CLI program designed to run LLM prompts and act as an alternative client for Model Context Protocol (MCP). Users can interact with MCP-compatible servers from their terminal, including LLM providers like OpenAI, Groq, or local LLM models via llama. The tool supports various functionalities such as running prompt templates, analyzing image inputs, triggering tools, continuing conversations, utilizing clipboard support, and additional options like listing tools and prompts. Users can configure LLM and MCP servers via a JSON config file and contribute to the project by submitting issues and pull requests for enhancements or bug fixes.
![air-quality-info Screenshot](/screenshots_githubs/trekawek-air-quality-info.jpg)
air-quality-info
Air Quality Info is a PHP-based page that displays current PM10 and PM2.5 measurements from Sensor.Community-compatible devices. It features a clean interface, stores records in MySQL, renders graphs with ChartJS, supports multiple devices, offers locale support, and functions as a Progressive Web App. The project setup involves creating directory structures, setting permissions, and starting Docker containers. The admin dashboard is accessible at http://aqi.eco.localhost:8080/, while the Air Quality Info pages use a specific naming schema. The project is supported by Nettigo Air Monitor, Sensor.Community, and a forum thread in Polish.
![vault-ai Screenshot](/screenshots_githubs/pashpashpash-vault-ai.jpg)
vault-ai
OP Vault is a tool that leverages the OP Stack (OpenAI + Pinecone Vector Database) to allow users to upload custom knowledgebase files and ask questions about their contents. It provides a user-friendly Golang server and React frontend for querying human-readable content like books and documents, making it valuable for knowledge extraction and question-answering. Users can upload entire libraries, receive specific answers with file and section references, and explore the power of the OP Stack in a practical interface.
![Atlantis Screenshot](/screenshots_githubs/Ravaelles-Atlantis.jpg)
Atlantis
Atlantis is an extensive Java framework based on JBWAPI 2.1.0, designed to simplify bot development for Starcraft. It provides clean and re-usable code, supports all three races with a focus on Terran, automates various tasks like modifying bwapi.ini and managing economy, includes tests and mini-maps, offers customizable build orders, scouts enemy bases, responds to threats, and more. The framework aims to streamline bot development by handling common tasks and providing advanced features for unit selection and decision-making.
![LLavaImageTagger Screenshot](/screenshots_githubs/jabberjabberjabber-LLavaImageTagger.jpg)
LLavaImageTagger
LLMImageIndexer is an intelligent image processing and indexing tool that leverages local AI to generate comprehensive metadata for your image collection. It uses advanced language models to analyze images and generate captions and keyword metadata. The tool offers features like intelligent image analysis, metadata enhancement, local processing, multi-format support, user-friendly GUI, GPU acceleration, cross-platform support, stop and start capability, and keyword post-processing. It operates directly on image file metadata, allowing users to manage files, add new files, and run the tool multiple times without reprocessing previously keyworded files. Installation instructions are provided for Windows, macOS, and Linux platforms, along with usage guidelines and configuration options.
![resume-design Screenshot](/screenshots_githubs/Hacker233-resume-design.jpg)
resume-design
Resume-design is an open-source and free resume design and template download website, built with Vue3 + TypeScript + Vite + Element-plus + pinia. It provides two design tools for creating beautiful resumes and a complete backend management system. The project has released two frontend versions and will integrate with a backend system in the future. Users can learn frontend by downloading the released versions or learn design tools by pulling the latest frontend code.
![ComfyBench Screenshot](/screenshots_githubs/xxyQwQ-ComfyBench.jpg)
ComfyBench
ComfyBench is a comprehensive benchmark tool designed to evaluate agents' ability to design collaborative AI systems in ComfyUI. It provides tasks for agents to learn from documents and create workflows, which are then converted into code for better understanding by LLMs. The tool measures performance based on pass rate and resolve rate, reflecting the correctness of workflow execution and task realization. ComfyAgent, a component of ComfyBench, autonomously designs new workflows by learning from existing ones, interpreting them as collaborative AI systems to complete given tasks.
![The-Creator-AI Screenshot](/screenshots_githubs/The-Creator-AI-The-Creator-AI.jpg)
The-Creator-AI
The Creator AI is a VS Code extension that integrates a coding assistant allowing users to choose files/folders through UI and describe code changes for AI-generated implementation plans. It requires an API key for Gemini or OpenAI. The extension follows VS Code guidelines and best practices, providing functionalities like basic chat, change plan, and file explorer. Users can edit the README using Visual Studio Code with useful keyboard shortcuts. Enjoy enhanced coding experience with The Creator AI.
![AgentConnect Screenshot](/screenshots_githubs/chgaowei-AgentConnect.jpg)
AgentConnect
AgentConnect is an open-source implementation of the Agent Network Protocol (ANP) aiming to define how agents connect with each other and build an open, secure, and efficient collaboration network for billions of agents. It addresses challenges like interconnectivity, native interfaces, and efficient collaboration. The architecture includes authentication, end-to-end encryption modules, meta-protocol module, and application layer protocol integration framework. AgentConnect focuses on performance and multi-platform support, with plans to rewrite core components in Rust and support mobile platforms and browsers. The project aims to establish ANP as an industry standard and form an ANP Standardization Committee. Installation is done via 'pip install agent-connect' and demos can be run after cloning the repository. Features include decentralized authentication based on did:wba and HTTP, and meta-protocol negotiation examples.
![trinityX Screenshot](/screenshots_githubs/clustervision-trinityX.jpg)
trinityX
TrinityX is an open-source HPC, AI, and cloud platform designed to provide all services required in a modern system, with full customization options. It includes default services like Luna node provisioner, OpenLDAP, SLURM or OpenPBS, Prometheus, Grafana, OpenOndemand, and more. TrinityX also sets up NFS-shared directories, OpenHPC applications, environment modules, HA, and more. Users can install TrinityX on Enterprise Linux, configure network interfaces, set up passwordless authentication, and customize the installation using Ansible playbooks. The platform supports HA, OpenHPC integration, and provides detailed documentation for users to contribute to the project.
![raycast_api_proxy Screenshot](/screenshots_githubs/yufeikang-raycast_api_proxy.jpg)
raycast_api_proxy
The Raycast AI Proxy is a tool that acts as a proxy for the Raycast AI application, allowing users to utilize the application without subscribing. It intercepts and forwards Raycast requests to various AI APIs, then reformats the responses for Raycast. The tool supports multiple AI providers and allows for custom model configurations. Users can generate self-signed certificates, add them to the system keychain, and modify DNS settings to redirect requests to the proxy. The tool is designed to work with providers like OpenAI, Azure OpenAI, Google, and more, enabling tasks such as AI chat completions, translations, and image generation.
![pyloid Screenshot](/screenshots_githubs/pyloid-pyloid.jpg)
pyloid
Pyloid is a Python backend version of Electron and Tauri, simplifying desktop application development. Built on QtWebEngine and PySide6, it offers seamless integration with Python features, enabling easy creation of powerful applications. It provides web-based GUI generation, system tray icon support, multi-window management, bridge API between Python and JavaScript, single/multi-instance application support, comprehensive desktop app features, clean code structure, live UI development experience, cross-platform support, integration with frontend libraries, window customization, direct utilization of PySide6 features, and detailed Numpy-style docstrings.
![refly Screenshot](/screenshots_githubs/refly-ai-refly.jpg)
refly
Refly.AI is an open-source AI-native creation engine that empowers users to transform ideas into production-ready content. It features a free-form canvas interface with multi-threaded conversations, knowledge base integration, contextual memory, intelligent search, WYSIWYG AI editor, and more. Users can leverage AI-powered capabilities, context memory, knowledge base integration, quotes, and AI document editing to enhance their content creation process. Refly offers both cloud and self-hosting options, making it suitable for individuals, enterprises, and organizations. The tool is designed to facilitate human-AI collaboration and streamline content creation workflows.
![story-flicks Screenshot](/screenshots_githubs/alecm20-story-flicks.jpg)
story-flicks
This project enables users to create story videos by inputting a story theme, utilizing a large language model to generate AI-generated images, story content, audio, and subtitles. The backend is built with Python and FastAPI, while the frontend utilizes React, Ant Design, and Vite.
![codegate Screenshot](/screenshots_githubs/stacklok-codegate.jpg)
codegate
CodeGate is a local gateway that enhances the safety of AI coding assistants by ensuring AI-generated recommendations adhere to best practices, safeguarding code integrity, and protecting individual privacy. Developed by Stacklok, CodeGate allows users to confidently leverage AI in their development workflow without compromising security or productivity. It works seamlessly with coding assistants, providing real-time security analysis of AI suggestions. CodeGate is designed with privacy at its core, keeping all data on the user's machine and offering complete control over data.
![minuet-ai.el Screenshot](/screenshots_githubs/milanglacier-minuet-ai.el.jpg)
minuet-ai.el
Minuet AI is a tool that brings the grace and harmony of a minuet to your coding process. It offers AI-powered code completion with specialized prompts and enhancements for chat-based LLMs, as well as Fill-in-the-middle (FIM) completion for compatible models. The tool supports multiple AI providers such as OpenAI, Claude, Gemini, Codestral, Ollama, and OpenAI-compatible providers. It provides customizable configuration options and streaming support for completion delivery even with slower LLMs.
![SciCode Screenshot](/screenshots_githubs/scicode-bench-SciCode.jpg)
SciCode
SciCode is a challenging benchmark designed to evaluate the capabilities of language models (LMs) in generating code for solving realistic scientific research problems. It contains 338 subproblems decomposed from 80 challenging main problems across 16 subdomains from 6 domains. The benchmark offers optional descriptions specifying useful scientific background information and scientist-annotated gold-standard solutions and test cases for evaluation. SciCode demonstrates a realistic workflow of identifying critical science concepts and facts and transforming them into computation and simulation code, aiming to help showcase LLMs' progress towards assisting scientists and contribute to the future building and evaluation of scientific AI.
![LLM-Finetune Screenshot](/screenshots_githubs/Zeyi-Lin-LLM-Finetune.jpg)
LLM-Finetune
LLM-Finetune is a repository for fine-tuning language models for various NLP tasks such as text classification and named entity recognition. It provides instructions and scripts for training and inference using models like Qwen2-VL and GLM4. The repository also includes datasets for tasks like text classification, named entity recognition, and multimodal tasks. Users can easily prepare the environment, download datasets, train models, and perform inference using the provided scripts and notebooks. Additionally, the repository references SwanLab, an AI training record, analysis, and visualization tool.
![LangGraph-learn Screenshot](/screenshots_githubs/LangGraph-GUI-LangGraph-learn.jpg)
LangGraph-learn
LangGraph-learn is a community-driven project focused on mastering LangGraph and other AI-related topics. It provides hands-on examples and resources to help users learn how to create and manage language model workflows using LangGraph and related tools. The project aims to foster a collaborative learning environment for individuals interested in AI and machine learning by offering practical examples and tutorials on building efficient and reusable workflows involving language models.
![DeRTa Screenshot](/screenshots_githubs/RobustNLP-DeRTa.jpg)
DeRTa
DeRTa (Refuse Whenever You Feel Unsafe) is a tool designed to improve safety in Large Language Models (LLMs) by training them to refuse compliance at any response juncture. The tool incorporates methods such as MLE with Harmful Response Prefix and Reinforced Transition Optimization (RTO) to address refusal positional bias and strengthen the model's capability to transition from potential harm to safety refusal. DeRTa provides training data, model weights, and evaluation scripts for LLMs, enabling users to enhance safety in language generation tasks.
![GraphLLM Screenshot](/screenshots_githubs/matteoserva-GraphLLM.jpg)
GraphLLM
GraphLLM is a graph-based framework designed to process data using LLMs. It offers a set of tools including a web scraper, PDF parser, YouTube subtitles downloader, Python sandbox, and TTS engine. The framework provides a GUI for building and debugging graphs with advanced features like loops, conditionals, parallel execution, streaming of results, hierarchical graphs, external tool integration, and dynamic scheduling. GraphLLM is a low-level framework that gives users full control over the raw prompt and output of models, with a steeper learning curve. It is tested with llama70b and qwen 32b, under heavy development with breaking changes expected.
![askrepo Screenshot](/screenshots_githubs/laiso-askrepo.jpg)
askrepo
askrepo is a tool that reads the content of Git-managed text files in a specified directory, sends it to the Google Gemini API, and provides answers to questions based on a specified prompt. It acts as a question-answering tool for source code by using a Google AI model to analyze and provide answers based on the provided source code files. The tool leverages modules for file processing, interaction with the Google AI API, and orchestrating the entire process of extracting information from source code files.
![MNN Screenshot](/screenshots_githubs/alibaba-MNN.jpg)
MNN
MNN is a highly efficient and lightweight deep learning framework that supports inference and training of deep learning models. It has industry-leading performance for on-device inference and training. MNN has been integrated into various Alibaba Inc. apps and is used in scenarios like live broadcast, short video capture, search recommendation, and product searching by image. It is also utilized on embedded devices such as IoT. MNN-LLM and MNN-Diffusion are specific runtime solutions developed based on the MNN engine for deploying language models and diffusion models locally on different platforms. The framework is optimized for devices, supports various neural networks, and offers high performance with optimized assembly code and GPU support. MNN is versatile, easy to use, and supports hybrid computing on multiple devices.
![nodejs-todo-api-boilerplate Screenshot](/screenshots_githubs/vyancharuk-nodejs-todo-api-boilerplate.jpg)
nodejs-todo-api-boilerplate
An LLM-powered code generation tool that relies on the built-in Node.js API Typescript Template Project to easily generate clean, well-structured CRUD module code from text description. It orchestrates 3 LLM micro-agents (`Developer`, `Troubleshooter` and `TestsFixer`) to generate code, fix compilation errors, and ensure passing E2E tests. The process includes module code generation, DB migration creation, seeding data, and running tests to validate output. By cycling through these steps, it guarantees consistent and production-ready CRUD code aligned with vertical slicing architecture.
![OpenCAGE Screenshot](/screenshots_githubs/MattFiler-OpenCAGE.jpg)
OpenCAGE
OpenCAGE is an open-source modding toolkit for Alien: Isolation, enabling custom scripting, configuration, and content modification through graphical interfaces. It includes tools for editing assets, configurations, scripts, behaviour trees, launching the game, and managing backups. The project is constantly evolving with a roadmap that includes features like contextual script editing, content porter, new level creator, mod installers, 3D viewer improvements, navmesh generation, skinned meshes support, sound import/export, and more. OpenCAGE is supported financially by the community and welcomes code contributions.
![quantalogic Screenshot](/screenshots_githubs/quantalogic-quantalogic.jpg)
quantalogic
QuantaLogic is a ReAct framework for building advanced AI agents that seamlessly integrates large language models with a robust tool system. It aims to bridge the gap between advanced AI models and practical implementation in business processes by enabling agents to understand, reason about, and execute complex tasks through natural language interaction. The framework includes features such as ReAct Framework, Universal LLM Support, Secure Tool System, Real-time Monitoring, Memory Management, and Enterprise Ready components.
![partcad Screenshot](/screenshots_githubs/partcad-partcad.jpg)
partcad
PartCAD is a tool for documenting manufacturable physical products, providing tools to maintain product information and streamline workflows at all product lifecycle phases. It is a next-generation CAD tool that focuses on specifying manufacturable physical products using computer-aided design in a more generic sense, including the use of AI models. PartCAD offers modular and reusable packages for product information, generating outputs like product documentation, bill of materials, sourcing information, and manufacturing process specifications. It integrates with third-party tools for iterative improvements, design validation, and manufacturing processes verification. PartCAD also offers supplementary products like a CRM and inventory tool for managing part manufacturing and assembly shops. By enabling easy switching between third-party tools, PartCAD creates a competitive environment for service providers and ensures data sovereignty for users.
![qrbtf Screenshot](/screenshots_githubs/latentcat-qrbtf.jpg)
qrbtf
QRBTF is the world's first and best AI & parametric QR code generator developed by Latent Cat. It features original AI models trained on a large number of images for fast and high-quality inference. The parametric part is open source, offering various styles without requiring a backend. Users can create beautiful QR codes by entering a URL or text, selecting a style, adjusting parameters, and downloading in SVG or JPG format. The website supports English and Chinese, with contributions for i18n in other languages welcome. QRBTF also provides a React component for integration into projects.
![coco-app Screenshot](/screenshots_githubs/infinilabs-coco-app.jpg)
coco-app
Coco AI is a unified search platform that connects enterprise applications and data into a single, powerful search interface. The COCO App allows users to search and interact with their enterprise data across platforms. It also offers a Gen-AI Chat for Teams tailored to team's unique knowledge and internal resources, enhancing collaboration by making information instantly accessible and providing AI-driven insights based on enterprise's specific data.
![AI-Resume-Analyzer-and-LinkedIn-Scraper-using-Generative-AI Screenshot](/screenshots_githubs/gopiashokan-AI-Resume-Analyzer-and-LinkedIn-Scraper-using-Generative-AI.jpg)
AI-Resume-Analyzer-and-LinkedIn-Scraper-using-Generative-AI
Developed an advanced AI application that utilizes LLM and OpenAI for comprehensive resume analysis. It excels at summarizing the resume, evaluating strengths, identifying weaknesses, and offering personalized improvement suggestions, while also recommending the perfect job titles. Additionally, it seamlessly employs Selenium to extract vital LinkedIn data, encompassing company names, job titles, locations, job URLs, and detailed job descriptions. This application simplifies the job-seeking journey by equipping users with comprehensive insights to elevate their career opportunities.
![app-agent Screenshot](/screenshots_githubs/ngo275-app-agent.jpg)
app-agent
AppAgent is an open-source AI-first platform designed to streamline the app release process, from autonomous keyword research to ASO content generation. It offers features like autonomous keyword research, AI-powered store optimization, store synchronization with App Store Connect, and upcoming keyword tracking with self-healing. The tech stack includes Next.js, TypeScript, Tailwind CSS, Prisma ORM, PostgreSQL, NextAuth.js, PostHog, Resend, Stripe, and Vercel for hosting. Users can clone the repository, set up environment variables, install dependencies, set up the database, and run the development server to start using the tool.
![payload-ai Screenshot](/screenshots_githubs/ashbuilds-payload-ai.jpg)
payload-ai
The Payload AI Plugin is an advanced extension that integrates modern AI capabilities into your Payload CMS, streamlining content creation and management. It offers features like text generation, voice and image generation, field-level prompt customization, prompt editor, document analyzer, fact checking, automated content workflows, internationalization support, editor AI suggestions, and AI chat support. Users can personalize and configure the plugin by setting environment variables. The plugin is actively developed and tested with Payload version v3.2.1, with regular updates expected.
![awesome-ai-web-search Screenshot](/screenshots_githubs/felladrin-awesome-ai-web-search.jpg)
awesome-ai-web-search
The 'awesome-ai-web-search' repository is a curated list of AI-powered web search software that focuses on the intersection of Large Language Models (LLMs) and web search capabilities. It contains a timeline of various software supporting web search with LLM summarization, chat capabilities, and agent-driven research. The repository showcases both open-source and closed-source tools, providing a comprehensive overview of AI web search solutions available in the market.
![goose Screenshot](/screenshots_githubs/block-goose.jpg)
goose
Codename Goose is an open-source, extensible AI agent designed to provide functionalities beyond code suggestions. Users can install, execute, edit, and test with any LLM. The tool aims to enhance the coding experience by offering advanced features and capabilities. Stay updated for the upcoming 1.0 release scheduled by the end of January 2025. Explore the v0.X documentation available on the project's GitHub pages.
![solana-ai-agents Screenshot](/screenshots_githubs/EarthZetaOrg-solana-ai-agents.jpg)
solana-ai-agents
JLB AI Agent is an innovative solution on the Solana blockchain that leverages artificial intelligence to automate complex tasks and enhance decision-making in the DeFi space. It offers real-time analytics, efficient operations, and seamless integration for both newcomers and experienced crypto enthusiasts. With features like autonomous trading, NFT management, DeFi insights, and comprehensive ecosystem integration, JLB empowers users with cutting-edge technology to navigate the dynamic landscape of blockchain.
![memobase Screenshot](/screenshots_githubs/memodb-io-memobase.jpg)
memobase
Memobase is a user profile-based memory system designed to enhance Generative AI applications by enabling them to remember, understand, and evolve with users. It provides structured user profiles, scalable profiling, easy integration with existing LLM stacks, batch processing for speed, and is production-ready. Users can manage users, insert data, get memory profiles, and track user preferences and behaviors. Memobase is ideal for applications that require user analysis, tracking, and personalized interactions.
![GLaDOS Screenshot](/screenshots_githubs/dnhkng-GLaDOS.jpg)
GLaDOS
GLaDOS Personality Core is a project dedicated to building a real-life version of GLaDOS, an aware, interactive, and embodied AI system. The project aims to train GLaDOS voice generator, create a 'Personality Core,' develop medium- and long-term memory, provide vision capabilities, design 3D-printable parts, and build an animatronics system. The software architecture focuses on low-latency voice interactions and minimal dependencies. The hardware system includes servo- and stepper-motors, 3D printable parts for GLaDOS's body, animations for expression, and a vision system for tracking and interaction. Installation instructions involve setting up a local LLM server, installing drivers, and running GLaDOS on different operating systems.
![generative-ai-design-patterns Screenshot](/screenshots_githubs/lakshmanok-generative-ai-design-patterns.jpg)
generative-ai-design-patterns
A catalog of design patterns for building generative AI applications, capturing current best practices in the field. The repository serves as a living catalog on GitHub to help practitioners navigate through the noise and identify areas for improvement. It is too early for a book due to the evolving nature of generative AI in production and the lack of concrete evidence to support certain claims.
![UltraRAG Screenshot](/screenshots_githubs/OpenBMB-UltraRAG.jpg)
UltraRAG
The UltraRAG framework is a researcher and developer-friendly RAG system solution that simplifies the process from data construction to model fine-tuning in domain adaptation. It introduces an automated knowledge adaptation technology system, supporting no-code programming, one-click synthesis and fine-tuning, multidimensional evaluation, and research-friendly exploration work integration. The architecture consists of Frontend, Service, and Backend components, offering flexibility in customization and optimization. Performance evaluation in the legal field shows improved results compared to VanillaRAG, with specific metrics provided. The repository is licensed under Apache-2.0 and encourages citation for support.
![partialjson Screenshot](/screenshots_githubs/iw4p-partialjson.jpg)
partialjson
PartialJson is a Python library that allows users to parse partial and incomplete JSON data with ease. With just 3 lines of Python code, users can parse JSON data that may be missing key elements or contain errors. The library provides a simple solution for handling JSON data that may not be well-formed or complete, making it a valuable tool for data processing and manipulation tasks.
![cellm Screenshot](/screenshots_githubs/getcellm-cellm.jpg)
cellm
Cellm is an Excel extension that allows users to leverage Large Language Models (LLMs) like ChatGPT within cell formulas. It enables users to extract AI responses to text ranges, making it useful for automating repetitive tasks that involve data processing and analysis. Cellm supports various models from Anthropic, Mistral, OpenAI, and Google, as well as locally hosted models via Llamafiles, Ollama, or vLLM. The tool is designed to simplify the integration of AI capabilities into Excel for tasks such as text classification, data cleaning, content summarization, entity extraction, and more.
![OpenContracts Screenshot](/screenshots_githubs/JSv4-OpenContracts.jpg)
OpenContracts
OpenContracts is an Apache-2 licensed enterprise document analytics tool that supports multiple formats, including PDF and txt-based formats. It features multiple document ingestion pipelines with a pluggable architecture for easy format and ingestion engine support. Users can create custom document analytics tools with beautiful result displays, support mass document data extraction with a LlamaIndex wrapper, and manage document collections, layout parsing, automatic vector embeddings, and human annotation. The tool also offers pluggable parsing pipelines, human annotation interface, LlamaIndex integration, data extraction capabilities, and custom data extract pipelines for bulk document querying.
![mcp-framework Screenshot](/screenshots_githubs/QuantGeekDev-mcp-framework.jpg)
mcp-framework
MCP-Framework is a TypeScript framework for building Model Context Protocol (MCP) servers with automatic directory-based discovery for tools, resources, and prompts. It provides powerful abstractions, simple server setup, and a CLI for rapid development and project scaffolding.
![llmap Screenshot](/screenshots_githubs/jbellis-llmap.jpg)
llmap
LLMap is a CLI code search tool designed to automatically find context in large codebases by evaluating the relevance of each source file using DeepSeek-V3 and DeepSeek-R1. It optimizes analysis by performing multi-stage analysis and caching results for faster searches. Currently supports Java and Python files, with potential for extension to other languages. Install with 'pip install llmap-ai' and use with a DeepSeek API key to search for specific context in code.
![open-lx01 Screenshot](/screenshots_githubs/jialeicui-open-lx01.jpg)
open-lx01
Open-LX01 is a project aimed at turning the Xiao Ai Mini smart speaker into a fully self-controlled device. The project involves steps such as gaining control, flashing custom firmware, and achieving autonomous control. It includes analysis of main services, reverse engineering methods, cross-compilation environment setup, customization of programs on the speaker, and setting up a web server. The project also covers topics like using custom ASR and TTS, developing a wake-up program, and creating a UI for various configurations. Additionally, it explores topics like gdb-server setup, open-mico-aivs-lab, and open-mipns-sai integration using Porcupine or Kaldi.
![dotnet-ai-workshop Screenshot](/screenshots_githubs/SteveSandersonMS-dotnet-ai-workshop.jpg)
dotnet-ai-workshop
The .NET AI Workshop is a comprehensive guide designed to help developers add AI features to .NET applications. It covers various AI-based features such as classification, summarization, data extraction/cleaning, anomaly detection, translation, sentiment detection, semantic search, Q&A chatbots, and voice assistants. The workshop is tailored for developers new to AI in .NET applications, focusing on the usage of AI services without the need for prior AI technology knowledge. It provides examples using .NET and C# with a focus on AI topics, aiming to enhance productivity and automation in applications.
![LLMs-from-scratch-CN Screenshot](/screenshots_githubs/MLNLP-World-LLMs-from-scratch-CN.jpg)
LLMs-from-scratch-CN
This repository is a Chinese translation of the GitHub project 'LLMs-from-scratch', including detailed markdown notes and related Jupyter code. The translation process aims to maintain the accuracy of the original content while optimizing the language and expression to better suit Chinese learners' reading habits. The repository features detailed Chinese annotations for all Jupyter code, aiding users in practical implementation. It also provides various supplementary materials to expand knowledge. The project focuses on building Large Language Models (LLMs) from scratch, covering fundamental constructions like Transformer architecture, sequence modeling, and delving into deep learning models such as GPT and BERT. Each part of the project includes detailed code implementations and learning resources to help users construct LLMs from scratch and master their core technologies.
![notte Screenshot](/screenshots_githubs/nottelabs-notte.jpg)
notte
Notte is a web browser designed specifically for LLM agents, providing a language-first web navigation experience without the need for DOM/HTML parsing. It transforms websites into structured, navigable maps described in natural language, enabling users to interact with the web using natural language commands. By simplifying browser complexity, Notte allows LLM policies to focus on conversational reasoning and planning, reducing token usage, costs, and latency. The tool supports various language model providers and offers a reinforcement learning style action space and controls for full navigation control.
![ChatRex Screenshot](/screenshots_githubs/IDEA-Research-ChatRex.jpg)
ChatRex
ChatRex is a Multimodal Large Language Model (MLLM) designed to seamlessly integrate fine-grained object perception and robust language understanding. By adopting a decoupled architecture with a retrieval-based approach for object detection and leveraging high-resolution visual inputs, ChatRex addresses key challenges in perception tasks. It is powered by the Rexverse-2M dataset with diverse image-region-text annotations. ChatRex can be applied to various scenarios requiring fine-grained perception, such as object detection, grounded conversation, grounded image captioning, and region understanding.
![structured-logprobs Screenshot](/screenshots_githubs/arena-ai-structured-logprobs.jpg)
structured-logprobs
This Python library enhances OpenAI chat completion responses by providing detailed information about token log probabilities. It works with OpenAI Structured Outputs to ensure model-generated responses adhere to a JSON Schema. Developers can analyze and incorporate token-level log probabilities to understand the reliability of structured data extracted from OpenAI models.
![p1 Screenshot](/screenshots_githubs/ggml-org-p1.jpg)
p1
p1 is a code completion engine based on Large Language Models (LLM) that operates at the edge. It provides intelligent code suggestions and completions to enhance the coding experience. The tool is designed to assist developers in writing code more efficiently by predicting and offering context-aware completions based on the code being written. With implementations available for popular code editors like Vim and Visual Studio Code, p1 aims to improve productivity and streamline the coding process for software developers.
![aps-toolkit Screenshot](/screenshots_githubs/chuongmep-aps-toolkit.jpg)
aps-toolkit
APS Toolkit is a powerful tool for developers, software engineers, and AI engineers to explore Autodesk Platform Services (APS). It allows users to read, download, and write data from APS, as well as export data to various formats like CSV, Excel, JSON, and XML. The toolkit is built on top of Autodesk.Forge and Newtonsoft.Json, offering features such as reading SVF models, querying properties database, exporting data, and more.
![ai-analyst Screenshot](/screenshots_githubs/e2b-dev-ai-analyst.jpg)
ai-analyst
AI Analyst by E2B is an AI-powered code and data analysis tool built with Next.js and the E2B SDK. It allows users to analyze data with Meta's Llama 3.1, upload CSV files, and create interactive charts. The tool is powered by E2B Sandbox, Vercel's AI SDK, Next.js, and echarts library for interactive charts. Supported LLM providers include TogetherAI and Fireworks, with various chart types available for visualization.
![aiops-modules Screenshot](/screenshots_githubs/awslabs-aiops-modules.jpg)
aiops-modules
AIOps Modules is a collection of reusable Infrastructure as Code (IAC) modules that work with SeedFarmer CLI. The modules are decoupled and can be aggregated using GitOps principles to achieve desired use cases, removing heavy lifting for end users. They must be generic for reuse in Machine Learning and Foundation Model Operations domain, adhering to SeedFarmer Guide structure. The repository includes deployment steps, project manifests, and various modules for SageMaker, Mlflow, FMOps/LLMOps, MWAA, Step Functions, EKS, and example use cases. It also supports Industry Data Framework (IDF) and Autonomous Driving Data Framework (ADDF) Modules.
![llama.vscode Screenshot](/screenshots_githubs/ggml-org-llama.vscode.jpg)
llama.vscode
llama.vscode is a local LLM-assisted text completion extension for Visual Studio Code. It provides auto-suggestions on input, allows accepting suggestions with shortcuts, and offers various features to enhance text completion. The extension is designed to be lightweight and efficient, enabling high-quality completions even on low-end hardware. Users can configure the scope of context around the cursor and control text generation time. It supports very large contexts and displays performance statistics for better user experience.
![AutoDAN-Turbo Screenshot](/screenshots_githubs/SaFoLab-WISC-AutoDAN-Turbo.jpg)
AutoDAN-Turbo
AutoDAN-Turbo is the official implementation of the ICLR2025 paper 'AutoDAN-Turbo: A Lifelong Agent for Strategy Self-Exploration to Jailbreak LLMs'. It is a black-box jailbreak method that automatically discovers jailbreak strategies without human intervention, achieving high attack success rates on public benchmarks. The tool can incorporate existing human-designed strategies and outperform baseline methods.
![MR-Models Screenshot](/screenshots_githubs/mtkresearch-MR-Models.jpg)
MR-Models
MR-Models is a repository dedicated to the research and development of language models tailored for Traditional Chinese users. It offers advanced multi-modal language models like Breeze 2 and Model 7, designed to enhance Traditional Chinese language representation. The models incorporate vision-aware capabilities, function-calling features, and are available for academic or industrial use under licensing terms.
![logicstudio.ai Screenshot](/screenshots_githubs/developmentation-logicstudio.ai.jpg)
logicstudio.ai
LogicStudio.ai is a powerful visual canvas-based tool for building, managing, and visualizing complex logic flows involving AI agents, data inputs, and outputs. It provides an intuitive interface to streamline development processes by offering features like drag-and-drop canvas design, dynamic components, real-time connections, import/export capabilities, zoom & pan controls, file management, AI integration, editable views, and various output formats. Users can easily add, connect, configure, and manage components to create interactive systems and workflows.
![video-starter-kit Screenshot](/screenshots_githubs/fal-ai-community-video-starter-kit.jpg)
video-starter-kit
A powerful starting kit for building AI-powered video applications. This toolkit simplifies the complexities of working with AI video models in the browser. It offers browser-native video processing, AI model integration, advanced media capabilities, and developer utilities. The tech stack includes fal.ai for AI model infrastructure, Next.js for React framework, Remotion for video processing, IndexedDB for browser-based storage, Vercel for deployment platform, and UploadThing for file upload. The kit provides features like seamless video handling, multi-clip composition, audio track integration, voiceover support, metadata encoding, and ready-to-use UI components.
![pear-landing-page Screenshot](/screenshots_githubs/trypear-pear-landing-page.jpg)
pear-landing-page
PearAI Landing Page is an open-source AI-powered code editor managed by Nang and Pan. It is built with Next.js, Vercel, Tailwind CSS, and TypeScript. The project requires setting up environment variables for proper configuration. Users can run the project locally by starting the development server and visiting the specified URL in the browser. Recommended extensions include Prettier, ESLint, and JavaScript and TypeScript Nightly. Contributions to the project are welcomed and appreciated.
![pr-agent Screenshot](/screenshots_githubs/qodo-ai-pr-agent.jpg)
pr-agent
PR-Agent is a tool designed to assist in efficiently reviewing and handling pull requests by providing AI feedback and suggestions. It offers various tools such as Review, Describe, Improve, Ask, Update CHANGELOG, and more, with the ability to run them via different interfaces like CLI, PR Comments, or automatically triggering them when a new PR is opened. The tool supports multiple git platforms and models, emphasizing real-life practical usage and modular, customizable tools.
![Awesome-Embodied-AI Screenshot](/screenshots_githubs/haoranD-Awesome-Embodied-AI.jpg)
Awesome-Embodied-AI
Awesome-Embodied-AI is a curated list of papers on Embodied AI and related resources, tracking and summarizing research and industrial progress in the field. It includes surveys, workshops, tutorials, talks, blogs, and papers covering various aspects of Embodied AI, such as vision-language navigation, large language model-based agents, robotics, and more. The repository welcomes contributions and aims to provide a comprehensive overview of the advancements in Embodied AI.
![kgateway Screenshot](/screenshots_githubs/kgateway-dev-kgateway.jpg)
kgateway
Kgateway is a feature-rich, fast, and flexible Kubernetes-native API gateway built on top of Envoy proxy and the Kubernetes Gateway API. It excels in function-level routing, supports legacy apps, microservices, and serverless, offers robust discovery capabilities, integrates seamlessly with open-source projects, and is designed to support hybrid applications with various technologies, architectures, protocols, and clouds.
![flows-ai Screenshot](/screenshots_githubs/callstackincubator-flows-ai.jpg)
flows-ai
Flows AI is a lightweight, type-safe AI workflow orchestrator inspired by Anthropic's agent patterns and built on top of Vercel AI SDK. It provides a simple and deterministic way to build AI workflows by connecting different input/outputs together, either explicitly defining workflows or dynamically breaking down complex tasks using an orchestrator agent. The library is designed without classes or state, focusing on flexible input/output contracts for nodes.
![Telco-AIX Screenshot](/screenshots_githubs/tme-osx-Telco-AIX.jpg)
Telco-AIX
Telco-AIX is a collaborative experimental workspace dedicated to exploring data-driven decision-making use-cases using open source AI capabilities and open datasets. The repository focuses on projects related to revenue assurance, fraud management, service assurance, latency predictions, 5G network operations, sustainability, energy efficiency, SecOps-AI for networking, AI-powered SmartGrid, IoT perimeter security, anomaly detection, root cause analysis, customer relationship management voice app, Starlink quality of experience predictions, and NoC AI augmentation for OSS.
![goodsKill Screenshot](/screenshots_githubs/techa03-goodsKill.jpg)
goodsKill
The 'goodsKill' project aims to build a complete project framework integrating good technologies and development techniques, mainly focusing on backend technologies. It provides a simulated flash sale project with unified flash sale simulation request interface. The project uses SpringMVC + Mybatis for the overall technology stack, Dubbo3.x for service intercommunication, Nacos for service registration and discovery, and Spring State Machine for data state transitions. It also integrates Spring AI service for simulating flash sale actions.