A complete solution to optimize the accuracy of AI form filling
Core idea: precise operation through targeted training and parameter adjustment.
Step-by-step solutions:
- Specialized demo recording: Specialized recording of 10+ form filling processes, including error correction operations
- Data Enhancement Processing: Generate variant data by adding the -augment parameter to the process_demonstration phase
- Model Selection Strategy: Prioritize the use of strong inference models such as vLLM, or fine-tune specialized models via LLaMA-Factory
- Test Validation Cycle: Iterate over specific form fields using the -goal parameter of main.py and view the terminal output logs
Note: It is recommended that explicit name or id attributes be added to form elements, and the training needs to be re-recorded when the structure of the page changes.
Alternative: the semantic understanding capabilities of large language models such as Gemini can be directly invoked to handle complex form logic.
This answer comes from the articleOptexity: an open-source project to train AI to perform web actions with human demonstrationsThe
May not be reproduced without permission:AI productivity tools " How to improve the accuracy of AI performing web form filling tasks?
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