feat: async batching for classification to improve pipeline performance#8
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✨ Finishing Touches🧪 Generate unit tests (beta)
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Hi maintainers 👋 This PR introduces async batching to significantly improve pipeline performance. Previously, classification was sequential and slow (~1 hour+). With this change, processing is parallelized and much faster. I would love feedback and suggestions for further improvements 🙏 |
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🚀 Summary
This PR improves the performance of the asset generation pipeline by introducing async + batch processing for classification prompts.
🔥 Problem
Previously, classification prompts were processed sequentially, leading to very long execution times (~1+ hour).
✅ Solution
⚡ Impact
🧪 Testing
📂 Changes
knowledge_utils.py🙏 Notes
This PR intentionally excludes generated assets and focuses only on core pipeline improvements.