A curated list of 100+ resources for building and deploying generative AI specifically focusing on helping you become a Generative AI Data Scientist with LLMs
This page lists names, links and short descriptions. The original list on GitHub is the source and belongs to its authors.
An AI-powered data science team of copilots that uses agents to help you perform common data science tasks 10X faster.
LLM RAG AI Apps with Step-By-Step Tutorials.
Proof of concept for an AI-powered hedge fund.
A financial agent for investment research.
How to build an agent that can orchestrate the end-to-end process of report planning, web research, and writing. Produces reports of varying and easily configurable formats.
Uber's QueryGPT uses large language models (LLM), vector databases, and similarity search to generate complex queries from English (Natural Language) questions, enhancing productivity for engineers, operations managers, and data scientists.
Tutorials and implementations for various Generative AI Agent techniques, from basic to advanced. A comprehensive guide for building intelligent, interactive AI systems.
Real-world AI agent applications, LLM and RAG tutorials, with examples to implement.
An open-source alternative to Perplexity Finance.
A curated list of 100+ resources for building and deploying generative AI specifically focusing on helping you become a Generative AI Data Scientist
A curated list of 120+ LLM libraries organized by category.
A ranked list of awesome machine learning Python libraries. Updated weekly.
Probably the best curated list of data science software in Python.
A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning
A list of AI autonomous agents
An AI-powered data science team of copilots that uses agents to help you perform common data science tasks 10X faster.
Open Source AI Agents for Data Analysis.
Transform data and create rich visualizations iteratively with AI 🪄.
Let a LLM agent write and execute code inside a notebook.
A generative AI extension for JupyterLab.
Open-source GenBI AI Agent. Text2SQL made Easy!
Gen AI Toolbox for Databases is an open-source server that makes it easier to build Gen AI tools for interacting with databases.
The fastest way to get actionable insights from your SQL database just by asking questions.
A framework for developing LLM applications based on the instruction following, tool usage, planning, and memory capabilities of Qwen. It also comes with example applications such as Browser Assistant, Code Interpreter, and Custom Assistant.
Open version of OpenAI's Deep Research agent.
AI researcher that continuously searches for information based on a user query until the system is confident that it has gathered all the necessary details.
A framework for developing applications powered by large language models (LLMs).
A library for building stateful, multi-actor applications with LLMs, used to create agent and multi-agent workflows.
A platform for building production-grade LLM applications. It allows you to closely monitor and evaluate your application, so you can quickly and confidently ship.
A framework for building context-augmented generative AI applications with LLMs.
A mechanism for orchestrating actions in increasingly complex AI applications.
Streamline workflows across industries with powerful AI agents.
Python agent framework designed to make building production-grade applications with Generative AI less painful.
Prefect's Python framework for building agentic AI workflows.
Frameworkless LLM Agents.
Meta (Facebook) core building blocks needed to bring generative AI applications to market.
Deepset AI's open-source AI orchestration framework for building customizable, production-ready LLM applications.
A 100-line minimalist LLM framework for Agents, Task Decomposition, RAG, etc.
An open-source agent orchestration framework built on top of the latest OpenAI Assistants API.
Google Gen AI Python SDK provides an interface for developers to integrate Google’s generative models into their Python applications.
A fully-automated and highly self-developing framework that enables users to create and deploy LLM agents through natural language alone.
A flexible and provider-agnostic framework designed to simplify the creation of sophisticated multi-agent systems.
IDE that enables visualization, interaction, and debugging of complex agentic applications.
A low-code tool that makes building powerful AI agents and workflows that can use any API, model, or database easier.
Graph-Based Editor for LLM Workflows.
Monitor, Evaluate & Optimize your LLM performance with 1-click. Drag and drop interface for LLMOps platform.
A low-code interface to rapidly prototype AI agents, enhance them with tools, compose them into teams, and interact with them to accomplish tasks. Built on AutoGen AgentChat.
The OpenAI Agents SDK is a lightweight yet powerful framework for building multi-agent workflows.
Open LLM models by Meta, Mistral, and hundreds of other providers.
The official Python library for the Anthropic API.
The open-source AI model you can fine-tune, distill, and deploy anywhere.
The official Python library for the Google Gemini API.
The official Python library for the Groq API.
1st generation reasoning model that competes with OpenAI o1.
Alibaba's Qwen models.
Meta's foundational models.
A framework for developing applications powered by large language models (LLMs).
A library for building stateful, multi-actor applications with LLMs, used to create agent and multi-agent workflows.
A platform for building production-grade LLM applications. It allows you to closely monitor and evaluate your application, so you can quickly and confidently ship.
Prebuilt agents for LangGraph (includes 3rd Party LangGraph extensions).
An AI-powered data science team of copilots that uses agents to help you perform common data science tasks 10X faster.
LangMem provides tooling to extract important information from conversations, optimize agent behavior through prompt refinement, and maintain long-term memory.
A Python library for creating hierarchical multi-agent systems using LangGraph.
An open-source assistant that automates research and produces customizable reports on any topic.
This prebuilt graph is an agent that uses a reflection-style architecture to check and improve an initial agent's output.
Create LangGraph agents that can access large numbers of tools.
This library implements the CodeAct architecture in LangGraph. This architecture is used by Manus.im.
Create swarm-style multi-agent systems using LangGraph. Agents dynamically hand off control to one another based on their specializations.
Provides a lightweight wrapper that makes Anthropic Model Context Protocol (MCP) tools compatible with LangChain and LangGraph.
An open-source platform for machine learning (ML) and artificial intelligence (AI) tools and models.
Transformers provides APIs and tools to easily download and train state-of-the-art pretrained models.
Tokenizers provides an implementation of today’s most used tokenizers, with a focus on performance and versatility.
Sentence Transformers (a.k.a. SBERT) is the go-to Python module for accessing, using, and training state-of-the-art text and image embedding models.
The simplest framework out there to build powerful agents.
The official Pinecone Python SDK.
Milvus is an open-source vector database built to power embedding similarity search and AI applications.
A vector search SQLite extension that runs anywhere!
PyTorch is an open-source machine learning library based on the Torch library, used for applications such as computer vision and natural language processing.
TensorFlow is an open-source machine learning library developed by Google.
A minimalistic deep learning library with a focus on simplicity and educational use, created by George Hotz.
A simple, lightweight autograd engine for educational purposes, created by Andrej Karpathy.
Transformers provides APIs and tools to easily download and train state-of-the-art pretrained models.
Finetune Llama 3.2, Mistral, Phi-3.5 & Gemma 2-5x faster with 80% less memory!
A platform for building production-grade LLM applications. It allows you to closely monitor and evaluate your application, so you can quickly and confidently ship.
Monitor, Evaluate & Optimize your LLM performance with 1-click. Drag and drop interface for LLMOps platform.
Opik is an open-source platform for evaluating, testing, and monitoring LLM applications.
MLflow has a suite of features for LLMs.
LangChain has hundreds of integrations with various data sources to load data from: Slack, Notion, Google Drive, etc.
Create an AI app on your own data in a minute.
Parse documents and export them to the desired format with ease and speed.
Python tool for converting files and office documents to Markdown.
A system for agentic LLM-powered data processing and ETL.
Unstructured provides a platform and tools to ingest and process unstructured documents for Retrieval Augmented Generation (RAG) and model fine-tuning.
Turn any Git repository into a simple text ingest of its codebase. This is useful for feeding a codebase into any LLM.
Open-source, blazing-fast, AI-ready web crawling tailored for LLMs, AI agents, and data pipelines.
Crawl a site to generate knowledge files to create your own custom GPT from a URL.
A web scraping Python library that uses LLM and direct graph logic to create scraping pipelines for websites and local documents (XML, HTML, JSON, Markdown, etc.).
🔥 Turn entire websites into LLM-ready markdown or structured data. Scrape, crawl, and extract with a single API.
Build agents with LangChain.
Integrate Tools (Function Calling) with LangChain.
The simplest framework out there to build powerful agents.
Open-source framework for creating and managing simulations populated with AI-powered agents. It provides an intuitive platform for designing complex, interactive environments where agents can act, learn, and evolve.
Build applications quickly with preset agents.
An open-source, code-first Python toolkit for building, evaluating, and deploying sophisticated AI agents with flexibility and control.
An open-source platform to build, ship and monitor agentic systems.
Integration Platform for AI Agents & LLMs (works with LangChain, CrewAI, etc).
Monitor, Evaluate & Optimize your LLM performance with 1-click. Drag and drop interface for LLMOps platform.
MLflow Tracing for LLM Observability.
Open-source LLMOps platform: prompt playground, prompt management, LLM evaluation, and LLM Observability all in one place.
Best practices designed to support your LLMOps initiatives.
E2B is an open-source runtime for executing AI-generated code in secure cloud sandboxes. Made for agentic & AI use cases.
Executes code through a command line environment in a Docker container.
Make websites accessible for AI agents.
Built on Gradio and supports most of browser-use functionalities. This UI is designed to be user-friendly and enables easy interaction with the browser agent.
WebRover is an AI-powered web agent that combines autonomous browsing with advanced research capabilities.
Task-Aware Prompt Optimization Framework.
A library for prompt engineering that simplifies NLP tasks (e.g., NER, classification) using LLMs like GPT.
A framework for prompt tuning using Intent-based Prompt Calibration.
The library to build & auto-optimize LLM applications, from Chatbot, RAG, to Agent by SylphAI.
Python SDK, Proxy Server (LLM Gateway) to call 100+ LLM APIs in OpenAI format.
Full toolkit for running an AI agent service built with LangGraph, FastAPI, and Streamlit.
LLM-powered multiagent persona simulation for imagination enhancement and business insights.
Connect home devices into a powerful cluster to accelerate LLM inference.
An ongoing roundup of useful developments in the LLM/genAI space, with a specific focus on R.
Makes it easy to use large language models (LLM) from R. It supports a wide variety of LLM providers and implements a rich set of features including streaming outputs, tool/function calling, structured data extraction, and more.
Enables sequential and parallel batch processing for chat models supported by ellmer.
Provides a library of ergonomic LLM assistants designed to help you complete repetitive, hard-to-automate tasks quickly.
LLM assistant specifically for ggplot2.
A high-performance and low-friction chat experience for data scientists in RStudio and Positron–sort of like completions with Copilot, but it knows how to talk to the objects in your R environment.
Interface with models from OpenAI to get assistance while coding.
Brings GroqCloud’s lightning-fast LPU (Language Processing Unit) technology directly to your R workflow.
Easily incorporate use of large language models (LLMs) into their project workflows.
R interface to various Large Language Models (LLMs) such as OpenAI’s GPT models, Azure’s language models, Google’s Gemini models, or custom local servers.
A simple interface to chat with your favorite AI chatbot from R, inspired by tidymodels where you can easily swap out any ML model for another one but keep the other parts of the workflow the same.
Access various large language model APIs, including Anthropic Claude, OpenAI, Google Gemini, Perplexity, Groq, Mistral, and local models via Ollama or OpenAI-compatible APIs.
R package to use Google’s Gemini via API on R.
Intuitive interface for leveraging the capabilities of the Perplexity API Pro subscription.
The easiest way to integrate R with Ollama, which lets you run language models locally on your own machine.
Wraps the Ollama API, which allows you to run different LLMs locally and create an experience similar to ChatGPT/OpenAI’s API.
Helps implement Retrieval-Augmented Generation (RAG) workflows.
21 lessons teaching everything you need to know to start building Generative AI applications.
A comprehensive introduction to Generative AI concepts and applications.
Prompt Flow and RAG examples for use with the Microsoft Azure Cloud platform.
An entry point for developing with NIMs that natively scales out to full-sized labs and up to production environments.
Reference implementations, example documents, and architecture guides that can be used as a starting point to deploy multiple NIMs and other NVIDIA microservices into Kubernetes and other production deployment environments.
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