Building a Reddit Content Summarizer with Langchain

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Objective

1. Fetches the latest posts from the subreddit.
2. Organizes posts by category (News, Discussion, etc.).
3. Provides a concise summary for each category, including post titles, authors, and links.
4. Sends this Markdown-formatted summary to the specified email address.

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Steps

1. Set up Applications: We need the reddit application to fetch posts and the google-mail (or any email) application to send the summary. We’ll use app_from_slug and AgentRIntegration for managing credentials via AgentR.
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   from universal_mcp.applications import app_from_slug
   from universal_mcp.integrations import AgentRIntegration
   
   def get_application(name: str):
       AppClass = app_from_slug(name)
       # Assumes 'name' matches an integration configured on AgentR
       integration = AgentRIntegration(name)
       instance = AppClass(integration=integration)
       return instance
   
   reddit_app = get_application("reddit")
   email_app = get_application("google-mail") # Or your preferred email app slug
   
2. Initialize LLM and ToolManager:
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   import os
   from langchain_openai import ChatOpenAI
   from universal_mcp.tools import ToolManager
   from universal_mcp.tools.adapters import ToolFormat
   
   model_name = os.environ.get("OPEN_AI_MODEL", "gpt-4o-mini")
   llm = ChatOpenAI(model=model_name)
   tool_manager = ToolManager()
   
3. Register Tools from Applications: The ToolManager will register all tools exposed by the reddit and email applications.
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   tool_manager.register_tools_from_app(reddit_app)
   tool_manager.register_tools_from_app(email_app)
   
   This automatically makes tools like reddit_get_hot_posts (or similar, depending on the Reddit app’s implementation) and google-mail_send_email available.
4. Get Tools in Langchain Format:
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   langchain_tools = tool_manager.list_tools(format=ToolFormat.LANGCHAIN)
   
5. Create the Langchain Agent: Define a system prompt that guides the agent through the summarization and emailing process.
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   from langgraph.prebuilt import create_react_agent
   
   agent_executor = create_react_agent(
       llm,
       tools=langchain_tools,
       prompt="You are a helpful assistant that can use tools to help the user." # General prompt
   )
   
6. Define the Agent’s Task Prompt: This detailed prompt outlines the multi-step task.
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   agent_task_prompt_template = """
   You are a helpful assistant. For the given subreddit, fetch the latest posts,
   organize them by category (such as News, Discussion, Question, Meme, etc.),
   and provide a concise summary for each category. Format the output as a
   well-structured Markdown document, including:
   
   - A main heading with the subreddit name
   - Subheadings for each category
   - Bullet points or short paragraphs summarizing the key posts in each category
   - For each post, include the title (as a Markdown link to the post), author, and a brief summary
   
   After summarizing, share the Markdown-formatted summary.
   
   Send the summary to the email address: {send_to_email}
   Subreddit: {subreddit}
   """
   
7. Invoke the Agent: Get user input for the subreddit and email, then run the agent.
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   async def main():
       # ... (LLM, ToolManager, App setup) ...
   
       subreddit = input("Enter the subreddit: ")
       send_to_email = input("Enter the email to send the summary to: ")
   
       filled_prompt = agent_task_prompt_template.format(
           subreddit=subreddit,
           send_to_email=send_to_email
       )
   
       result = await agent_executor.ainvoke(
           input={"messages": [{"role": "user", "content": filled_prompt}]}
       )
       print(result["messages"][-1].content)
   
   import asyncio
   asyncio.run(main())
   

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How It Works

1. Use a Reddit tool (e.g., reddit_get_hot_posts) to fetch data from the specified subreddit.
2. Process this data according to the prompt (categorize, summarize). This part is done by the LLM’s reasoning.
3. Once the Markdown summary is generated, it will use an email tool (e.g., google-mail_send_email) to send the content to the target email address.