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You can also import this template directly from here - https://cloud.activepieces.com/templates/KOs0dyWetOZorKPQBiH96 This notebook demonstrates how to create a fully automated Tweet generator using Activepieces, Dappier, and OpenAI. By combining real-time trending insights with natural language generation, this automation crafts and posts tweets—autonomously and repeatedly. In this notebook, you’ll explore:
  • Activepieces: A no-code, open-source automation platform that allows you to run scheduled flows with intelligent decision logic, integrations, and multi-step workflows.
  • Dappier: A platform connecting LLMs and automations to real-time, rights-cleared data from trusted sources. It specializes in domains like trending news, AI research, finance, and lifestyle, delivering prompt-ready data with up-to-date insights.
  • OpenAI: Used here to transform raw data into engaging tweet-sized content, leveraging the creative power of GPT-4o.
  • Twitter: Publishes the final tweet live to your feed—automatically and without human intervention.
This setup not only demonstrates a practical use case of autonomous content generation but also provides a blueprint for automating other types of social media content with real-time intelligence and LLMs.

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⏰ Schedule-Based Trigger Setup

To kick off the automation, we’ll use a time-based trigger that runs every few minutes to check for trending content and post a tweet.

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Step 1: Set the Trigger – Every X Minutes

Search for the Schedule piece and select the Every X Minutes trigger. Configure it as follows:
  • Frequency: Every 1 minute (You can adjust this value depending on how frequently you want to post content—e.g., every 15 minutes, 1 hour, etc.)
This trigger ensures the workflow runs at regular intervals without manual input. Once set, the automation is live and ticking on a timed loop, ready to pull new content and generate tweets.

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🌐 Fetch Trending Content using Dappier

With the schedule trigger in place, the next step is to retrieve real-time trending news content that will serve as the basis for the tweet.

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Step 2: Add Dappier – Real Time Data

Add a Dappier action and choose the Real Time Data action. Configure the following:
  • Query: 
    Latest trending news in artificial intelligence, AI, and machine learning this week
This will fetch up-to-date and rights-cleared news and insights from trusted sources in the AI domain. The response is structured and optimized for downstream LLM consumption.

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✍️ Generate Tweet Using OpenAI

Now that you’ve retrieved trending AI news using Dappier, the next step is to craft an engaging tweet using OpenAI’s powerful language model.

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Step 3: Add OpenAI – Ask ChatGPT

Add an OpenAI action and choose Ask ChatGPT. Configure the following settings:
  • Model: chatgpt-4o-latest
  • Prompt:
Write a casual engaging tweet that is related to the below content. Keep it short under 280 characters.

{{dappier_response}}
  • Max Tokens: 2048
  • Temperature: 0.9
  • Presence Penalty: 0.6
  • Frequency Penalty: 0
This prompt encourages the model to generate light, human-like content optimized for virality—fitting Twitter’s tone and length constraints. Here is the next section, maintaining the same style and completeness:

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🐦 Post Tweet to Twitter Automatically

Once OpenAI generates the tweet content, the final step is to post it directly to your Twitter account using the Twitter piece.

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Step 4: Add Twitter – Create Tweet

Add a Twitter action and choose Create Tweet. Configure the following:
  • Text:
{{generated_tweet_text}}
Use the dynamic output from the previous OpenAI step to populate this field.
  • Authentication: Connect your Twitter account via OAuth when prompted.
Once set, every time this workflow runs, it will autonomously tweet engaging content based on the most recent AI news—no manual effort required.

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🌟 Highlights

This notebook has guided you through building a fully automated social media workflow that tweets real-time AI news content using Activepieces, OpenAI, Dappier, and Twitter. You’ve seen how to schedule automation, retrieve trending data, generate engaging tweets, and post them—all without human intervention. Key tools utilized in this notebook include:
  • Activepieces: A powerful no-code automation platform that enables scheduled workflows, intelligent decision logic, and seamless integration with third-party apps like Twitter.
  • Dappier: A platform connecting LLMs and automation tools to real-time, rights-cleared data from trusted sources, specializing in trending news, finance, and lifestyle. It delivers enriched, prompt-ready data, ideal for dynamic content generation.
  • OpenAI: Used here for transforming trending content into engaging, human-like tweets using GPT-4o.
  • Twitter: The final publishing channel where the generated tweets are posted automatically.
This setup is easily extendable—you can adapt it to tweet content from different domains (e.g., sports, finance, health) or trigger it based on events, RSS feeds, or even Gmail requests.