Automated Text Scoring with Hugging Face AI
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Leverage the power of Hugging Face's advanced AI models to automatically score text for performance and preference. This n8n sub-workflow streamlines your text analysis process, providing valuable insights without manual intervention.
About This Workflow
This n8n sub-workflow automates the process of scoring text based on its performance and user preference using cutting-edge AI models from Hugging Face. It's designed to be triggered by another workflow, accepting 'text' as input. It then queries two distinct Hugging Face inference endpoints: one for predicting text performance and another for predicting user preference. The scores are then processed and consolidated into a single output, making it easy to integrate into your existing data pipelines. This solution is ideal for scenarios requiring rapid, data-driven evaluation of textual content.
Key Features
- Dual AI Scoring: Simultaneously evaluates text for both performance and preference using separate, specialized AI models.
- Hugging Face Integration: Seamlessly connects to deployed Hugging Face inference endpoints for powerful AI capabilities.
- Workflow Automation: Designed as a sub-workflow, it can be easily integrated into larger automated processes.
- Customizable Endpoints: Easily configure and switch the Hugging Face inference endpoints to suit your specific needs.
- Structured Output: Consolidates scores and original text into a clear, usable format for downstream processing.
How To Use
- Deploy Hugging Face Models: a. Visit the Hugging Face pages for the Animal Advocate Preference Prediction (Longform) and Text Performance Prediction (Longform) models. b. Click the "Deploy" button and create an inference endpoint for each model. c. Copy the Inference Endpoint URL for both deployed models.
- Configure n8n Nodes:
a. In the n8n sub-workflow, locate the 'Get Performance Score' node and replace
INSERT_YOUR_ENDPOINT_URL_HEREwith the URL of the Text Performance Prediction endpoint. b. Locate the 'Get Preference Score' node and replaceINSERT_YOUR_ENDPOINT_URL_HEREwith the URL of the Animal Advocate Preference Prediction endpoint. c. Ensure your Hugging Face API token is configured within the HuggingFaceApi credential type in n8n, and associate it with the HTTP Request nodes. - Trigger the Workflow: a. This sub-workflow is triggered by another n8n workflow via the 'When Executed by Another Workflow' node. b. Pass the 'text' you wish to score as an input parameter to this sub-workflow.
Apps Used
Workflow JSON
{
"id": "78d18e94-97c5-4776-9d97-7345a8c6ae68",
"name": "Automated Text Scoring with Hugging Face AI",
"nodes": 10,
"category": "Operations",
"status": "active",
"version": "1.0.0"
}Note: This is a sample preview. The full workflow JSON contains node configurations, credentials placeholders, and execution logic.
Get This Workflow
ID: 78d18e94-97c5...
About the Author
AI_Workflow_Bot
LLM Specialist
Building complex chains with OpenAI, Claude, and LangChain.
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