Description
Overview
This Hacker News to Video Template automates the transformation of news articles into concise video content using an orchestration pipeline combining article analysis, image generation, and video synthesis. The automation workflow targets content creators and developers seeking to convert trending Hacker News posts related to AI or automation into multimedia presentations with AI-generated images and voiceovers. It initiates with a manual trigger node and fetches the latest posts from Hacker News for processing.
Key Benefits
- Automates extraction and summarization of Hacker News articles via AI-powered content analysis.
- Generates relevant AI-enhanced images from article prompts using Leonardo.ai’s image synthesis API.
- Creates video clips from generated images leveraging RunwayML’s image-to-video model.
- Combines multiple media elements into a seamless final video with Creatomate’s compositing API.
- Supports scalable batch processing with loop and limit nodes to handle multiple articles efficiently.
Product Overview
This automation workflow begins with a manual trigger to initiate processing of Hacker News articles, retrieved through the dedicated Hacker News node. The workflow limits the articles to the most recent 50 items and processes them in batches to ensure controlled throughput. Each article URL is fetched via HTTP request, then analyzed by an OpenAI-powered agent to confirm relevance to AI or automation topics. The agent generates a 250-word summary and extracts a single representative image URL. Related articles trigger further image analysis using OpenAI’s vision model to assist in prompt creation.
Following content analysis, the workflow prepares newsletter-style summaries and concise blurbs, along with two short image prompts for each article using OpenAI language models. These prompts are refined using Leonardo.ai’s prompt improvement API before invoking Leonardo.ai’s image generation endpoint to produce high-resolution images. After a processing wait, generated images are forwarded to RunwayML’s image-to-video API, which creates short video clips using the “gen3a_turbo” model. With an additional wait period for video rendering, the URLs of finished videos are retrieved.
The workflow then composes a final video using Creatomate’s API, stitching together an intro scene, two video scenes with subtitles, and voiceovers generated via OpenAI text-to-speech. Optional nodes enable uploading assets to storage services such as Minio, Dropbox, Google Drive, and Microsoft OneDrive, as well as posting to social media platforms including YouTube, Twitter (X), Instagram, and LinkedIn. The execution model is synchronous for content generation steps with controlled asynchronous waits for media creation processes.
Features and Outcomes
Core Automation
The core automation workflow inputs Hacker News articles, filters for AI and automation relevance, and applies deterministic branches based on topic detection using the “If Topic” node. It orchestrates text summarization, image prompt generation, and multimedia synthesis in a sequential pipeline.
- Batch processing via splitInBatches node ensures scalable article throughput.
- Single-pass topic classification with OpenAI agent guarantees consistent filtering.
- Synchronous execution with controlled wait nodes balances processing time and resource use.
Integrations and Intake
This no-code integration pipeline connects to Hacker News for article intake, OpenAI APIs for text and image analysis, Leonardo.ai for image generation, RunwayML for video creation, and Creatomate for video composition. Authentication primarily uses generic HTTP custom credentials.
- Hacker News node fetches latest articles as JSON payloads for processing.
- OpenAI Chat and Vision models analyze text content and images with API key authentication.
- Leonardo.ai and RunwayML APIs operate with HTTP custom authentication for image and video synthesis.
Outputs and Consumption
The workflow outputs include structured JSON summaries, AI-generated image URLs, and fully rendered video URLs. Final videos are composed and optionally uploaded or posted to external storage and social media platforms. The response pattern is a combination of synchronous returns and asynchronous polling with wait periods.
- Text outputs: article summaries, blurbs, and prompts formatted as JSON objects.
- Image outputs: URLs of high-resolution AI-generated images from Leonardo.ai.
- Video outputs: URLs of short video clips from RunwayML and final stitched videos from Creatomate.
Workflow — End-to-End Execution
Step 1: Trigger
The workflow initiates manually via the “When clicking ‘Test workflow’” manual trigger node, enabling controlled execution on demand.
Step 2: Processing
After retrieving the latest Hacker News posts, the workflow limits the number of articles to 50 and splits them into batches for iterative handling. Each article URL is fetched via HTTP request; basic presence checks ensure required fields like URL exist before further processing.
Step 3: Analysis
The article content is analyzed by an OpenAI Chat model to generate a 250-word summary and determine AI or automation relevance. The “If Topic” node conditionally routes articles flagged as related, extracting a single image URL for further OpenAI image analysis and prompt preparation. Image prompts are refined via Leonardo.ai’s prompt improvement API before image generation.
Step 4: Delivery
Generated images are sent to RunwayML’s image-to-video API to create video clips, followed by wait nodes to allow processing time. The resulting video URLs are retrieved and combined into a final video composition using Creatomate’s API, producing a multi-scene video with subtitles and voiceovers. Optional downstream nodes enable uploading to cloud storage and posting to social media.
Use Cases
Scenario 1
A content producer wants to quickly transform trending Hacker News articles related to AI into engaging video summaries. This workflow automates article analysis, AI image generation, and video creation, delivering structured multimedia content ready for distribution in one streamlined process cycle.
Scenario 2
A marketing team seeks to generate visual assets accompanying news summaries for social media posts. The automation workflow generates image prompts, refines them, and produces AI-generated images and videos that can be uploaded or posted automatically to multiple platforms, reducing manual design effort.
Scenario 3
Developers require a reliable pipeline to batch-process news content for newsletter preparation. This orchestration pipeline fetches articles, confirms topic relevance, summarizes content, and produces voiceover-supported videos, ensuring consistent output without manual intervention.
How to use
After importing this workflow into n8n, configure API credentials for OpenAI, Leonardo.ai, RunwayML, and Creatomate via the generic HTTP custom auth method. Connect optional storage and social media nodes as needed. Trigger the workflow manually to start processing the latest Hacker News articles. Expect outputs including article summaries, AI-generated images, and a final stitched video with subtitles and voiceovers. Monitor processing via wait nodes that accommodate asynchronous media rendering.
Comparison — Manual Process vs. Automation Workflow
| Attribute | Manual/Alternative | This Workflow |
|---|---|---|
| Steps required | Multiple manual steps including article selection, summarization, image design, and video editing. | Automated sequential steps from article fetch to video composition with minimal user intervention. |
| Consistency | Variable output quality and format depending on manual effort and skill. | Deterministic processing with AI models ensures uniform summaries, images, and video structure. |
| Scalability | Limited by manual capacity and time for content creation. | Batch processing and automated API calls enable scalable handling of multiple articles. |
| Maintenance | Requires continual manual updates for templates, media assets, and narration. | Centralized workflow configuration with API credentials minimizes ongoing maintenance effort. |
Technical Specifications
| Environment | n8n workflow automation platform |
|---|---|
| Tools / APIs | Hacker News API, OpenAI Chat and Vision APIs, Leonardo.ai, RunwayML, Creatomate, Minio, Dropbox, Google Drive, Microsoft OneDrive, YouTube, Twitter (X), Instagram, LinkedIn |
| Execution Model | Synchronous processing with asynchronous wait nodes for media generation |
| Input Formats | JSON payloads from Hacker News articles |
| Output Formats | JSON summaries, image URLs, video URLs, composited videos |
| Data Handling | Transient processing with no persistent data storage within the workflow |
| Known Constraints | Relies on external API availability and response times for image and video generation |
| Credentials | HTTP Custom Auth for Leonardo.ai, RunwayML, Creatomate; API keys for OpenAI |
Implementation Requirements
- Valid API credentials configured for OpenAI, Leonardo.ai, RunwayML, and Creatomate with HTTP custom authentication.
- Network access allowing outbound HTTPS requests to all integrated third-party APIs.
- Proper setup of optional cloud storage and social media account credentials if upload or posting is desired.
Configuration & Validation
- Verify API credentials for OpenAI, Leonardo.ai, RunwayML, and Creatomate are correctly entered and authorized.
- Trigger the workflow manually and confirm retrieval of Hacker News articles and successful batch processing.
- Check intermediary nodes for valid text summaries, image prompt improvements, generated images, and video URLs before final composition.
Data Provenance
- Trigger node: “When clicking ‘Test workflow’” manual trigger initiates the process.
- Analysis nodes: “Article Analysis” uses OpenAI Chat Model and Structured Output Parser for summary and relatedness detection.
- Media synthesis nodes: “Leo – Generate Image”, “Runway – Create Video”, and “Cre – Generate Video1” nodes handle image and video creation.
FAQ
How is the Hacker News to Video Template automation workflow triggered?
The workflow is triggered manually via the “When clicking ‘Test workflow’” manual trigger node, allowing controlled execution on demand.
Which tools or models does the orchestration pipeline use?
The orchestration pipeline integrates Hacker News API, OpenAI Chat and Vision models for summarization and analysis, Leonardo.ai for image generation, RunwayML for image-to-video conversion, and Creatomate for final video composition.
What does the response look like for client consumption?
The workflow outputs structured JSON summaries, AI-generated image URLs, and final video URLs. Composited videos include subtitles and voiceovers synthesized from article content.
Is any data persisted by the workflow?
Data is transient within the workflow; no persistent storage occurs unless optional upload nodes are configured for external storage services.
How are errors handled in this integration flow?
Error handling defaults to the n8n platform’s standard behavior; the “Article Analysis” node is configured to continue on error, enabling partial processing without halting the entire workflow.
Conclusion
This Hacker News to Video Template automates the end-to-end conversion of relevant news articles into multimedia video content, leveraging AI-driven text summarization, image generation, and video synthesis. It delivers consistent, structured outputs suitable for content distribution or social media sharing. The workflow requires valid API credentials and depends on external services for media generation, which may impact latency and availability. Overall, it provides a deterministic, scalable solution to streamline content production from news sources without manual intervention.
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