A production-ready FastAPI template for building AI agent applications with LangGraph integration. This template provides a robust foundation for building scalable, secure, and maintainable AI agent services. It includes features like FastAPI for high-performance async API endpoints, LangGraph integration, structured logging, rate limiting, PostgreSQL for data persistence, Docker support, security measures like JWT-based authentication and input sanitization, developer-friendly features like environment-specific configuration and type hints, a model evaluation framework with automated metric-based evaluation and detailed JSON reports, and a configuration system with environment-specific settings.

ApeRAG is a production-ready platform for Retrieval-Augmented Generation (RAG) that combines Graph RAG, vector search, and full-text search with advanced AI agents. It is ideal for building Knowledge Graphs, Context Engineering, and deploying intelligent AI agents for autonomous search and reasoning across knowledge bases. The platform offers features like advanced index types, intelligent AI agents with MCP support, enhanced Graph RAG with entity normalization, multimodal processing, hybrid retrieval engine, MinerU integration for document parsing, production-grade deployment with Kubernetes, enterprise management features, MCP integration, and developer-friendly tools for customization and contribution.

CentralMind Gateway is an AI-first data gateway that securely connects any data source and automatically generates secure, LLM-optimized APIs. It filters out sensitive data, adds traceability, and optimizes for AI workloads. Suitable for companies deploying AI agents for customer support and analytics.

An AI-powered code documentation generator that automatically analyzes repositories and creates comprehensive documentation using advanced language models. The system employs a multi-agent architecture to perform specialized code analysis and generate structured documentation.

LLM-FuzzX is an open-source user-friendly fuzz testing tool for large language models (e.g., GPT, Claude, LLaMA), equipped with advanced task-aware mutation strategies, fine-grained evaluation, and jailbreak detection capabilities. It helps researchers and developers quickly discover potential security vulnerabilities and enhance model robustness. The tool features a user-friendly web interface for visual configuration and real-time monitoring, supports various advanced mutation methods, integrates RoBERTa model for real-time jailbreak detection and evaluation, supports multiple language models like GPT, Claude, LLaMA, provides visualization analysis with seed flowcharts and experiment data statistics, and offers detailed logging support for main, mutation, and jailbreak logs.

Agentic Company Researcher is a multi-agent tool that generates comprehensive company research reports by utilizing a pipeline of AI agents to gather, curate, and synthesize information from various sources. It features multi-source research, AI-powered content filtering, real-time progress streaming, dual model architecture, modern React frontend, and modular architecture. The tool follows an agentic framework with specialized research and processing nodes, leverages separate models for content generation, uses a content curation system for relevance scoring and document processing, and implements a real-time communication system via WebSocket connections. Users can set up the tool quickly using the provided setup script or manually, and it can also be deployed using Docker and Docker Compose. The application can be used for local development and deployed to various cloud platforms like AWS Elastic Beanstalk, Docker, Heroku, and Google Cloud Run.

aiaio (AI-AI-O) is a lightweight, privacy-focused web UI for interacting with AI models. It supports both local and remote LLM deployments through OpenAI-compatible APIs. The tool provides features such as dark/light mode support, local SQLite database for conversation storage, file upload and processing, configurable model parameters through UI, privacy-focused design, responsive design for mobile/desktop, syntax highlighting for code blocks, real-time conversation updates, automatic conversation summarization, customizable system prompts, WebSocket support for real-time updates, Docker support for deployment, multiple API endpoint support, and multiple system prompt support. Users can configure model parameters and API settings through the UI, handle file uploads, manage conversations, and use keyboard shortcuts for efficient interaction. The tool uses SQLite for storage with tables for conversations, messages, attachments, and settings. Contributions to the project are welcome under the Apache License 2.0.

Qwery is a platform for querying and visualizing data using natural language without technical knowledge. It seamlessly integrates with various datasources, generates optimized queries, and delivers outcomes like result sets, dashboards, and APIs. Features include natural language querying, multi-database support, AI-powered agents, visual data apps, desktop & cloud options, template library, and extensibility through plugins. The project is under active development and not yet suitable for production use.

AISDK Prompt Optimizer is an open-source tool designed to transform AI interactions by optimizing prompts. It utilizes the GEPA reflective optimizer to evolve textual components of AI systems, providing features such as reflective prompt mutation, rich textual feedback, and Pareto-based selection. Users can teach their AI desired behaviors, collect ideal samples, run optimization to generate optimized prompts, and deploy the results in their applications. The tool leverages advanced optimization algorithms to guide AI through interactive conversations and refine prompt candidates for improved performance.

Enferno is a modern Flask framework optimized for AI-assisted development workflows. It combines carefully crafted development patterns, smart Cursor Rules, and modern libraries to enable developers to build sophisticated web applications with unprecedented speed. Enferno's intelligent patterns and contextual guides help create production-ready SAAS applications faster than ever. It includes features like modern stack, authentication, OAuth integration, database support, task queue, frontend components, security measures, Docker readiness, and more.

The llmgateway repository is a tool that provides a gateway for interacting with various LLM (Large Language Model) models. It allows users to easily access and utilize pre-trained language models for tasks such as text generation, sentiment analysis, and language translation. The tool simplifies the process of integrating LLMs into applications and workflows, enabling developers to leverage the power of state-of-the-art language models for various natural language processing tasks.

Vodalus Expert LLM Forge is a tool designed for crafting datasets and efficiently fine-tuning models using free open-source tools. It includes components for data generation, LLM interaction, RAG engine integration, model training, fine-tuning, and quantization. The tool is suitable for users at all levels and is accompanied by comprehensive documentation. Users can generate synthetic data, interact with LLMs, train models, and optimize performance for local execution. The tool provides detailed guides and instructions for setup, usage, and customization.

GitDiagram is a tool that turns any GitHub repository into an interactive diagram for visualization in seconds. It offers instant visualization, interactivity, fast generation, customization, and API access. The tool utilizes a tech stack including Next.js, FastAPI, PostgreSQL, Claude 3.5 Sonnet, Vercel, EC2, GitHub Actions, PostHog, and Api-Analytics. Users can self-host the tool for local development and contribute to its development. GitDiagram is inspired by Gitingest and has future plans to use larger context models, allow user API key input, implement RAG with Mermaid.js docs, and include font-awesome icons in diagrams.

YouTube AI Summarizer is a modern Next.js-based tool for AI-powered YouTube video summarization. It allows users to generate concise summaries of YouTube videos using various AI models, with support for multiple languages and summary styles. The application features flexible API key requirements, multilingual support, flexible summary modes, a smart history system, modern UI/UX design, and more. Users can easily input a YouTube URL, select language, summary type, and AI model, and generate summaries with real-time progress tracking. The tool offers a clean, well-structured summary view, history dashboard, and detailed history view for past summaries. It also provides configuration options for API keys and database setup, along with technical highlights, performance improvements, and a modern tech stack.

ocrbase is a tool designed to turn PDFs into structured data at scale. It utilizes the PaddleOCR-VL-1.5 0.9B OCR model for accurate text extraction and allows users to define schemas for structured extraction, receiving JSON outputs. The tool is built for scalability with queue-based scaling using BullMQ and provides real-time updates through WebSocket notifications. Users can self-host the tool on their own infrastructure using the provided Self-Hosting Guide, making it a versatile solution for document processing needs.

NotHotDog is an open-source platform for testing, evaluating, and simulating AI agents. It offers a robust framework for generating test cases, running conversational scenarios, and analyzing agent performance.

A production-ready FastAPI template for building AI agent applications with LangGraph integration. This template provides a robust foundation for building scalable, secure, and maintainable AI agent services. It includes features like FastAPI for high-performance async API endpoints, LangGraph integration, structured logging, rate limiting, PostgreSQL for data persistence, Docker support, security measures like JWT-based authentication and input sanitization, developer-friendly features like environment-specific configuration and type hints, a model evaluation framework with automated metric-based evaluation and detailed JSON reports, and a configuration system with environment-specific settings.

LightEval is a lightweight LLM evaluation suite that Hugging Face has been using internally with the recently released LLM data processing library datatrove and LLM training library nanotron. We're releasing it with the community in the spirit of building in the open. Note that it is still very much early so don't expect 100% stability ^^' In case of problems or question, feel free to open an issue!

Firefly is an open-source large model training project that supports pre-training, fine-tuning, and DPO of mainstream large models. It includes models like Llama3, Gemma, Qwen1.5, MiniCPM, Llama, InternLM, Baichuan, ChatGLM, Yi, Deepseek, Qwen, Orion, Ziya, Xverse, Mistral, Mixtral-8x7B, Zephyr, Vicuna, Bloom, etc. The project supports full-parameter training, LoRA, QLoRA efficient training, and various tasks such as pre-training, SFT, and DPO. Suitable for users with limited training resources, QLoRA is recommended for fine-tuning instructions. The project has achieved good results on the Open LLM Leaderboard with QLoRA training process validation. The latest version has significant updates and adaptations for different chat model templates.

Awesome Text2SQL is a curated repository containing tutorials and resources for Large Language Models, Text2SQL, Text2DSL, Text2API, Text2Vis, and more. It provides guidelines on converting natural language questions into structured SQL queries, with a focus on NL2SQL. The repository includes information on various models, datasets, evaluation metrics, fine-tuning methods, libraries, and practice projects related to Text2SQL. It serves as a comprehensive resource for individuals interested in working with Text2SQL and related technologies.

The 'create-million-parameter-llm-from-scratch' repository provides a detailed guide on creating a Large Language Model (LLM) with 2.3 million parameters from scratch. The blog replicates the LLaMA approach, incorporating concepts like RMSNorm for pre-normalization, SwiGLU activation function, and Rotary Embeddings. The model is trained on a basic dataset to demonstrate the ease of creating a million-parameter LLM without the need for a high-end GPU.

StableToolBench is a new benchmark developed to address the instability of Tool Learning benchmarks. It aims to balance stability and reality by introducing features such as a Virtual API System with caching and API simulators, a new set of solvable queries determined by LLMs, and a Stable Evaluation System using GPT-4. The Virtual API Server can be set up either by building from source or using a prebuilt Docker image. Users can test the server using provided scripts and evaluate models with Solvable Pass Rate and Solvable Win Rate metrics. The tool also includes model experiments results comparing different models' performance.

The Beta Machine Learning Toolkit is a package containing various algorithms and utilities for implementing machine learning workflows in multiple languages, including Julia, Python, and R. It offers a range of supervised and unsupervised models, data transformers, and assessment tools. The models are implemented entirely in Julia and are not wrappers for third-party models. Users can easily contribute new models or request implementations. The focus is on user-friendliness rather than computational efficiency, making it suitable for educational and research purposes.

AI-TOD is a dataset for tiny object detection in aerial images, containing 700,621 object instances across 28,036 images. Objects in AI-TOD are smaller with a mean size of 12.8 pixels compared to other aerial image datasets. To use AI-TOD, download xView training set and AI-TOD_wo_xview, then generate the complete dataset using the provided synthesis tool. The dataset is publicly available for academic and research purposes under CC BY-NC-SA 4.0 license.

Sweep is an AI junior developer that turns bugs and feature requests into code changes. It automatically handles developer experience improvements like adding type hints and improving test coverage.

The Teams AI Library is a software development kit (SDK) that helps developers create bots that can interact with Teams and Microsoft 365 applications. It is built on top of the Bot Framework SDK and simplifies the process of developing bots that interact with Teams' artificial intelligence capabilities. The SDK is available for JavaScript/TypeScript, .NET, and Python.

This guide is dedicated to Large Language Models (LLMs) that you can run on your home computer. It assumes your PC is a lower-end, non-gaming setup.

Supercharge WordPress Content Workflows and Engagement with Artificial Intelligence. Tap into leading cloud-based services like OpenAI, Microsoft Azure AI, Google Gemini and IBM Watson to augment your WordPress-powered websites. Publish content faster while improving SEO performance and increasing audience engagement. ClassifAI integrates Artificial Intelligence and Machine Learning technologies to lighten your workload and eliminate tedious tasks, giving you more time to create original content that matters.

Chatbot UI is an open-source AI chat app that allows users to create and deploy their own AI chatbots. It is easy to use and can be customized to fit any need. Chatbot UI is perfect for businesses, developers, and anyone who wants to create a chatbot.

BricksLLM is a cloud native AI gateway written in Go. Currently, it provides native support for OpenAI, Anthropic, Azure OpenAI and vLLM. BricksLLM aims to provide enterprise level infrastructure that can power any LLM production use cases. Here are some use cases for BricksLLM: * Set LLM usage limits for users on different pricing tiers * Track LLM usage on a per user and per organization basis * Block or redact requests containing PIIs * Improve LLM reliability with failovers, retries and caching * Distribute API keys with rate limits and cost limits for internal development/production use cases * Distribute API keys with rate limits and cost limits for students

uAgents is a Python library developed by Fetch.ai that allows for the creation of autonomous AI agents. These agents can perform various tasks on a schedule or take action on various events. uAgents are easy to create and manage, and they are connected to a fast-growing network of other uAgents. They are also secure, with cryptographically secured messages and wallets.

Griptape is a modular Python framework for building AI-powered applications that securely connect to your enterprise data and APIs. It offers developers the ability to maintain control and flexibility at every step. Griptape's core components include Structures (Agents, Pipelines, and Workflows), Tasks, Tools, Memory (Conversation Memory, Task Memory, and Meta Memory), Drivers (Prompt and Embedding Drivers, Vector Store Drivers, Image Generation Drivers, Image Query Drivers, SQL Drivers, Web Scraper Drivers, and Conversation Memory Drivers), Engines (Query Engines, Extraction Engines, Summary Engines, Image Generation Engines, and Image Query Engines), and additional components (Rulesets, Loaders, Artifacts, Chunkers, and Tokenizers). Griptape enables developers to create AI-powered applications with ease and efficiency.