Evaluate AI Summarization Quality from YouTube Transcripts
This n8n workflow evaluates the accuracy and faithfulness of AI-generated summaries based on YouTube video transcripts. It uses a scoring system to assess the quality of summaries produced by language models.
The workflow begins by downloading a YouTube transcript from Google Drive and extracting its content. An AI model generates a summary, which is then evaluated against the original transcript using specific criteria such as instruction adherence, groundedness, conciseness, and fluency. The evaluation assigns a score to the summary, indicating its quality. This score helps in identifying how well the AI model aligns with the source material and instructions.
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How to import this workflow into n8n
- 1Purchase or download the workflow to get the n8n workflow JSON file.
- 2In your n8n instance, open Workflows and choose "Import from File" (or paste the JSON with Ctrl+V on the canvas).
- 3Open each node marked with a credential warning and connect your own accounts and API keys.
- 4Run the workflow once manually to verify the data flow, then toggle it to Active.
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