LangChain Social Media Agent is an open-source AI agent built on LangGraph that takes a URL, generates Twitter and LinkedIn posts, and uses a human-in-the-loop approval flow. It supports content parsing, posting cadence (via cron jobs), Slack-triggered ingestion, and optional image handling. Users can audit and edit drafts before publishing, ensuring quality control and automation.

LangChain Social Media Agent

langchain-social-media-agent

Open-source agent that drafts, reviews, and schedules social posts from URL content with human-in-the-loop.

Vercel AI SDK is a free, open-source TypeScript library from the creators of Next.js, designed to help developers build AI-powered applications and agents. It offers a unified provider API—OpenAI, Anthropic, Claude, Google Gemini, etc.—structured output (via Zod), streaming responses, chat UI integrations, tool calling, agentic loops, and full TypeScript type safety across React, Svelte, Vue, Angular, or Node apps. With over 2 million weekly downloads, it simplifies LLM integration and enables rapid development of robust AI workflows.

Vercel AI SDK

vercel-ai-sdk

Free open-source TypeScript SDK for building LLM-powered apps and agents across frameworks with unified API.

GLM‑4.5 is an open‑source, Mixture‑of‑Experts (MoE) large‑language model from Z.ai, designed for intelligent agent applications. It features 355 B parameters (32 B active) with an efficient ’thinking/non‑thinking’ hybrid reasoning mode and 128 K context length. A smaller variant, GLM‑4.5‑Air, offers 106 B parameters (12 B active) for more efficient deployments. GLM‑4.5 excels at reasoning, coding, and tool‑calling tasks and ranks among the top performers on benchmarks compared with models like o3, Grok‑4, Claude Sonnet, and GPT‑4.1.

GLM‑4.5

glm-4-5

Open-source hybrid‑reasoning MoE foundation model optimized for intelligent agent tasks with 128K context and tool use.

Google Opal is an experimental no‑code tool from Google Labs that lets users build, edit, and share AI mini‑applications using plain English. It converts natural language prompts into visual workflows—chain prompts, AI model calls, and outputs—editable via conversational or drag‑and‑drop interfaces. Templates and sharing via Google account ease prototyping and collaboration. Currently available in U.S. public beta, Opal offers a frictionless entry into agentic app creation using Gemini models.

Google Opal

google-opal

An experimental no‑code platform from Google Labs to build and share AI mini‑apps via natural language workflows.

Amazon SageMaker Studio Lab is a free, browser‑based machine learning development environment powered by open‑source JupyterLab. It gives users access to T3.xlarge CPU and G4dn.xlarge GPU runtimes (with session and daily limits), along with 15 GB of persistent storage, Git integration, preinstalled ML frameworks, and the SageMaker Distribution environment for easy migration to SageMaker Studio. No AWS account or credit card is required. Ideal for students, educators, and developers looking to learn, prototype, or teach ML workflows without setup overhead.

Amazon SageMaker Studio Lab

amazon-sagemaker-studio-lab

Free browser‑based JupyterLab environment for ML experiments with CPU/GPU and persistent storage.

Qwen3‑Coder is an agentic code model from Alibaba’s Qwen3 family. Its flagship variant (480B MoE, 35B active) excels at agentic coding, tool use, and browser tasks with long context (256K–1M tokens). It’s open‑source under Apache‑2.0 and integrates with Qwen Code CLI and Qwen‑Agent workflows.

Qwen3‑Coder

qwen3-coder

Open‑source Mixture‑of‑Experts code model by Alibaba for agentic coding and tool use.

TEN Framework is an open-source modular system for building autonomous AI agents capable of reasoning, memory management, and tool usage. Designed to reflect real-world constraints, it incorporates a Thought-Emission-Norm (TEN) architecture, encouraging agents to think before acting. The framework supports open-ended planning, persistent memory storage, and tool augmentation. Developers can use TEN to experiment with agent autonomy and deploy agents that simulate complex decision-making workflows.

TEN Framework

ten-framework

An open-source framework for building autonomous AI agents that interact with the real world through tools and memory.

Trae Agent is an open-source, LLM-powered command-line assistant developed by ByteDance for software development workflows. It supports multi-LLM providers, file editing, bash execution, tool integration, trajectory logging, and a modular architecture—ideal for debugging, patching, documentation, and research.

Trae Agent

trae-agent

Open-source CLI LLM agent for automating software engineering tasks via natural-language commands.

AIWaves Agents (repo name “agents”) is an open‑source framework for autonomous language agents that supports planning, memory (short‑ and long‑term), tool usage, web navigation, multi‑agent communication, human‑agent interaction, symbolic control via SOPs, and symbolic learning with backprop‑style updates.

AIWaves Agents

aiwaves-agents

Open‑source adaptive LLM framework for building, training & deploying autonomous language agents.

Swarm is an open‑source, educational multi‑agent orchestration framework from OpenAI. It allows developers to define agents with instructions and tools, and supports handoffs—agent transfers via function calls—for dynamic workflows. Swarm is client‑side, stateless between runs, MIT‑licensed, and ideal for exploring multi‑agent patterns, though not intended for production.

OpenAI Swarm

openai-swarm

Open‑source experimental SDK for lightweight multi‑agent orchestration via instructions and handoffs.

AutoAgent is an open‑source, fully automated LLM agent framework from HKUDS that allows users to build, customize, and deploy multi-agent workflows using only natural language. It features an agent editor and workflow builder for zero-code design, a self‑managing vector DB, support for multiple LLMs, and strong performance on GAIA benchmark compared to research-grade agents.

AutoAgent

autoagent

Open-source zero-code LLM framework to create and deploy multi-agent workflows via natural language.

ScreenAgent is an open‑source Vision Language Model agent that interacts with real computer screens via screenshot observation and mouse/keyboard actions, following a planning‑execution‑reflection loop. It supports multi‑step GUI tasks, dataset collection, and achieves positioning accuracy comparable to GPT‑4V.

ScreenAgent

screenagent

Open‑source VLM agent to control computer GUIs via mouse/keyboard planning and execution.

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