
llm-app
pathwaycom/llm-appReady-to-run cloud templates for RAG, AI pipelines, and enterprise search with live data. 🐳Docker-friendly.⚡Always in sync with Sharepoint, Google Drive, S3, Kafka, PostgreSQL, real-time data APIs, and more.
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1,004 apps, agents and plugins from GitHub, ranked on how actively they are maintained rather than on stars. Security review is in progress and every project shows exactly what has and has not been checked.
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Ready-to-run cloud templates for RAG, AI pipelines, and enterprise search with live data. 🐳Docker-friendly.⚡Always in sync with Sharepoint, Google Drive, S3, Kafka, PostgreSQL, real-time data APIs, and more.

Build and share delightful machine learning apps, all in Python. 🌟 Star to support our work!

AirLLM 70B inference with single 4GB GPU

50+ tutorials and implementations for Generative AI Agent techniques, from basic conversational bots to complex multi-agent systems.

A reactive notebook for Python — run reproducible experiments, query with SQL, execute as a script, deploy as an app, and version with git. Stored as pure Python. All in a modern, AI-native editor.

Best Practices on Recommendation Systems

End-to-end, code-first tutorials for building production-grade GenAI agents. From prototype to enterprise deployment.

Code for Machine Learning for Trading, 3rd edition — from data sourcing to live execution.

Sample code and notebooks for Generative AI on Google Cloud, with Gemini Enterprise Agent Platform

A reference containing Styles and Keywords that you can use with MidJourney AI. There are also pages showing resolution comparison, image weights, and much more!

Tutorials, assignments, and competitions for MIT Deep Learning related courses.

Best Practices, code samples, and documentation for Computer Vision.

[NeurIPS 2024 Best Paper Award][GPT beats diffusion🔥] [scaling laws in visual generation📈] Official impl. of "Visual Autoregressive Modeling: Scalable Image Generation via Next-Scale Prediction". An *ultra-simple, user-friendly yet state-of-the-art* codebase for autoregressive image generation!

Evidently is an open-source ML and LLM observability framework. Evaluate, test, and monitor any AI-powered system or data pipeline. From tabular data to Gen AI. 100+ metrics.

22 prompt engineering techniques with hands-on Jupyter Notebook tutorials, from fundamental concepts to advanced strategies for leveraging LLMs.

Growth Engineering: The Definitive Guide。全栈增长工程师指南

OpenMMLab Multimodal Advanced, Generative, and Intelligent Creation Toolbox. Unlock the magic 🪄: Generative-AI (AIGC), easy-to-use APIs, awsome model zoo, diffusion models, for text-to-image generation, image/video restoration/enhancement, etc.

Open-source desktop SQL workspace for PostgreSQL, MySQL/MariaDB, SQLite and 15+ more databases like DuckDB, ClickHouse, Redis and Firestore. Built-in MCP server for Claude, Cursor and Devin, SQL notebooks and visual EXPLAIN.

Technical resources for AI developers to build applications, agents, and systems using Oracle AI Database and OCI services

A modular Agentic RAG built with LangGraph — learn Retrieval-Augmented Generation Agents in minutes.

MongoDB's Generative AI Showcase: an exhaustive collection of examples and sample applications covering Retrieval-Augmented Generation (RAG), AI agents, and industry-specific use cases.

:beer: Portando discussões feitas em grupos (Facebook, Google Groups, Slack, Disqus) para o GitHub Discussions

:book: HonKit is building beautiful books using Markdown - Fork of GitBook