Automated Metadata Generation for Global Content
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Generates structured metadata in English and Chinese using AI, suitable for multilingual content platforms.
About This Workflow
This workflow automates the generation of structured metadata in both English (en) and Chinese (zh). It leverages AI capabilities to process information, ensuring consistent and relevant metadata across languages. The process begins with a schedule trigger, fetches upcoming news, filters for impact, organizes the data, uses an AI agent to generate metadata with structured output parsing and a Gemini model for formatting, and finally updates text for distribution.
Key Features
- Scheduled Automation: Triggers workflow execution on a defined schedule (e.g., every 7 days).
- Data Fetching & Filtering: Retrieves and filters relevant news based on impact.
- AI-Powered Metadata Generation: Utilizes AI agents and language models (Google Gemini) for creating multilingual metadata.
- Structured Output Parsing: Ensures metadata is generated in a predefined, structured format.
- Dual-Language Support: Generates metadata for both English and Chinese.
- Content Formatting: Prepares metadata for distribution to various platforms.
How To Use
- Schedule Trigger (
Schedule Every 7 Days): Configure the schedule for when the workflow should run. - Date Management (
Dynamically Sets the Date,Set API Key for RapidAPI & Dates): Set up date parameters and API keys required for data fetching. - News Fetching (
Gets Upcoming News): Configure the HTTP request to fetch upcoming news data (e.g., from an API). - News Filtering (
Filter Medium & High Impact News): This node (a Code node) should contain logic to filter news based on impact levels. - Input Organization (
Organizes Input): This Code node should prepare the filtered news data into a format suitable for the AI agent. - AI Agent (
AI Agent): Configure the AI agent with prompts and settings to generate metadata. This node receives input fromOrganizes Inputand sends its output toUpdate expression for text. - Output Parsing (
Structured Output Parser): Configure this node to define the structure for the AI-generated metadata. It connects to theAI Agent. - Language Model (
Google Gemini Chat Model (Formats Output)): This node is used by theAI Agentto format the final output. - Text Formatting (
Update expression for text): This Code node likely formats the AI-generated metadata into a message suitable for the Telegram node. - Distribution (
Send Upcoming IPO Calendar Updates via Telegram): Configure the Telegram node to send the formatted metadata updates.
Apps Used
Workflow JSON
{
"id": "e1391935-5c64-4e13-8f76-b19a50270cca",
"name": "Automated Metadata Generation for Global Content",
"nodes": 6,
"category": "Data Processing",
"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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ID: e1391935-5c64...
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