langchain-ai/social-media-agent

📲 An agent for sourcing, curating, and scheduling social media posts with human-in-the-loop.

Social Media Agent – What It Does

Purpose: An end‑to‑end “agent” that takes a web URL, extracts the page’s content, and automatically drafts a Twitter and LinkedIn post for you. The flow is human‑in‑the‑loop: after the LLM generates a draft you can edit, approve, or reject it before it is actually published.

Key Components

  • LLM backend – Uses Anthropic’s Claude (or any Anthropic model) via the Anthropic API to write the posts.
  • Web scraping – FireCrawl fetches the article, blog, GitHub repo, YouTube transcript, etc.
  • Auth & posting – The Arcade service (or your own Twitter/LinkedIn developer credentials) handles OAuth, token storage and the actual API calls to publish.
  • State & orchestration – A LangGraph graph runs the whole pipeline (scrape → summarize → draft → human review → post). The graph is served locally with the langgraph-cli and can be deployed on LangGraph Cloud.
  • Optional integrations – Supabase for image storage, Slack for ingesting URLs via a channel, and GitHub for repo‑specific content.

How to Run (quick‑start)

  1. Clone the repo and install dependencies (yarn install).
  2. Copy .env.quickstart.example.env and fill in the required keys (Anthropic, FireCrawl, Arcade, LangSmith optional).
  3. Install the LangGraph CLI (pip install langgraph-cli).
  4. Start the in‑memory LangGraph server: yarn langgraph:in_mem:up.
  5. Run yarn generate_post – the script calls the generate_post graph on a sample LangChain blog URL. Results appear in LangSmith or in the Agent Inbox UI.

Full‑feature setup adds:

  • YouTube video handling via Google Vertex AI.
  • Image selection/upload via Supabase.
  • Slack‑driven cron jobs that pull URLs from a channel and automatically invoke the graph.
  • Direct Twitter/LinkedIn OAuth (instead of Arcade) for full media upload support.
  • GitHub URL parsing and organization‑level LinkedIn posting.

Customization

  • Prompt files under src/agents/generate-post/prompts/ let you change business context, example posts, structure instructions, and style guidelines.
  • Post‑style prompts control tone and formatting without touching the code.

Typical Use‑Case A marketing team drops a link into a designated Slack channel. A daily cron runs, the agent scrapes the link, drafts a concise, brand‑aligned tweet and LinkedIn update, shows the draft in the Agent Inbox for a quick edit, and then publishes it automatically.

Who Might Want This

  • Content marketers looking to automate social‑media copy generation.
  • Developers who want a ready‑made LangGraph example of a HITL workflow.
  • Teams that already use LangChain/LangGraph and want to extend it to social platforms.

Bottom Line: The Social Media Agent is a genuine, runnable project that demonstrates how to combine LLM generation, web scraping, OAuth authentication, and a human‑in‑the‑loop UI to automate posting on Twitter and LinkedIn.

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