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A curated list of causal inference libraries, resources, and applications.
Building LLM-Enabled Multi Agent Applications with AutoGen
Create beautiful, publication-quality books and documents from computational content.
Community maintained fork of pdfminer - we fathom PDF
21 Lessons, Get Started Building with Generative AI 🔗 https://microsoft.github.io/generative-ai-for-beginners/
Research and development (R&D) is crucial for the enhancement of industrial productivity, especially in the AI era, where the core aspects of R&D are mainly focused on data and models. We are commi…
A programming framework for agentic AI 🤖 PyPi: autogen-agentchat Discord: https://aka.ms/autogen-discord Office Hour: https://aka.ms/autogen-officehour
Python tool for converting files and office documents to Markdown.
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 agen…
The official Python SDK for Model Context Protocol servers and clients
A terminal workspace with batteries included
👻 Ghostty is a fast, feature-rich, and cross-platform terminal emulator that uses platform-native UI and GPU acceleration.
Lightweight coding agent that runs in your terminal
This repository provides tutorials and implementations for various Generative AI Agent techniques, from basic to advanced. It serves as a comprehensive guide for building intelligent, interactive A…
Meet Ava, the WhatsApp Agent
Universal Command Line Interface for Amazon Web Services
Fair-code workflow automation platform with native AI capabilities. Combine visual building with custom code, self-host or cloud, 400+ integrations.
React UI + elegant infrastructure for AI Copilots, AI chatbots, and in-app AI agents. The Agentic last-mile 🪁
Open source project for data preparation of LLM application builders
Leveraging BERT and c-TF-IDF to create easily interpretable topics.
Crawl Google Scholar publications easily.
Top2Vec learns jointly embedded topic, document and word vectors.