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The Self-hosted AI Starter Kit is an open-source template that quickly sets up a local AI environment. Curated by n8n, it provides essential tools for creating secure, self-hosted AI workflows.
Streamlines and simplifies prompt design for both developers and non-technical users with a low code approach.
Desktop app for prototyping and debugging LangGraph applications locally.
Scripts for fine-tuning Meta Llama3 with composable FSDP & PEFT methods to cover single/multi-node GPUs. Supports default & custom datasets for applications such as summarization and Q&A. Supportin…
Official community-driven Azure Machine Learning examples, tested with GitHub Actions.
Framework for orchestrating role-playing, autonomous AI agents. By fostering collaborative intelligence, CrewAI empowers agents to work together seamlessly, tackling complex tasks.
LangChain & Prompt Engineering tutorials on Large Language Models (LLMs) such as ChatGPT with custom data. Jupyter notebooks on loading and indexing data, creating prompt templates, CSV agents, and…
🚀CodiumAI PR-Agent: An AI-Powered 🤖 Tool for Automated Pull Request Analysis, Feedback, Suggestions and More! 💻🔍
A modular graph-based Retrieval-Augmented Generation (RAG) system
A collection of AI related python scripts for things like training, RAG and agents.
GPT4All: Run Local LLMs on Any Device. Open-source and available for commercial use.
Build resilient language agents as graphs.
RAG using Llama3, Langchain and ChromaDB
Build ChatGPT over your data, all with natural language
SuperEasy 100% Local RAG with Ollama + Email RAG
The all-in-one Desktop & Docker AI application with full RAG and AI Agent capabilities.
Rag (Retreival Augmented Generation) Python solution with llama3, LangChain, Ollama and ChromaDB in a Flask API based solution
Efficient Retrieval Augmentation and Generation Framework
💫 Industrial-strength Natural Language Processing (NLP) in Python
Financial Advisor Chatbot assistant using LLMs.
QLoRA: Efficient Finetuning of Quantized LLMs
The most powerful and modular diffusion model GUI, api and backend with a graph/nodes interface.
Together Mixture-Of-Agents (MoA) – 65.1% on AlpacaEval with OSS models
DSPy: The framework for programming—not prompting—foundation models