AI Newsletter Content Generation with LLM and n8n
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Automate AI newsletter content creation by using an LLM node to pick top stories and an output parser to structure them. This workflow leverages n8n to streamline the process of identifying and summarizing relevant AI news for your newsletter.
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About This Workflow
Overview
This n8n workflow automates the process of generating content for an AI newsletter. It begins with a formTrigger to collect necessary information, such as the date and previous newsletter content to avoid duplicates. A series of filter nodes then ensure that only relevant markdown content is processed and that content not related to newsletters is excluded. The core of the workflow uses a Langchain LLM node (pick_top_stories) to analyze the provided content and select the most relevant AI stories. An outputParserStructured node (top_stories_parser) then structures the LLM's output into a defined JSON format, separating chain-of-thought reasoning from the selected stories themselves. The top_selected_stories array contains detailed information for each selected story, including titles, summaries, identifiers, and external source links. This structured output is ideal for further processing or direct use in newsletter templates.
Key Features
- Utilizes a form trigger to initiate the workflow and gather input data.
- Employs filter nodes to pre-process and select relevant content.
- Leverages a Langchain LLM node for intelligent story selection and summarization.
- Structures LLM output using a structured output parser for easy data handling.
- Generates detailed summaries and selects top stories with rationale.
How To Use
- Trigger the Workflow: Use the
formTriggernode by filling out the required fields (Date, Previous Newsletter Content). - Process Content: The workflow will automatically filter the incoming markdown content to identify relevant AI news.
- Select Top Stories: The
pick_top_storiesLLM node will analyze the content and select the four most relevant AI stories based on your prompts. - Structure Output: The
top_stories_parsernode will organize the selected stories and their reasoning into a structured JSON format. - Utilize Output: The structured JSON output can be used for populating newsletter templates, further analysis, or feeding into other automation steps.
Apps Used
Workflow JSON
{
"id": "ce5a10ef-1020-469d-82ea-f782cdc39421",
"name": "AI Newsletter Content Generation with LLM and n8n",
"nodes": 0,
"category": "Content Generation",
"status": "active",
"version": "1.0.0"
}Note: This is a sample preview. The full workflow JSON contains node configurations, credentials placeholders, and execution logic.
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