v1.2

🚀 Release Summary

This release delivers major improvements across routine execution, observability, data models, SDK structure, and OpenAI integration, with a strong focus on reliability, performance, and future agentic workflows.

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✅ Resolved Issues

• Fixed placeholder interpolation tracking for improved error logging and observability (#58)
• Made pylint and pytest required (non-optional) dependencies (#54)
• Adopted OpenAI Responses API structured outputs (#51)
• Prevented Routine Discovery from generating unused parameters (#46)
• Cleaned up incorrect and inconsistent file path references

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✨ New Features

• Chunking for large outputs to prevent CDP timeouts
• More efficient fetch storage, removing unnecessary CDP round-trips
• JS-level parameter interpolation logging to improve routine observability
• Window property monitoring (v1):
  • Tracks window properties on navigation and periodically
  • Logs value changes and removals with timestamps and URLs
  • Non-blocking to avoid disrupting browser sessions
• New routine operations:
  • JavaScript Evaluation Operation
  • Download Operation
  • UI Operations (foundation for UI-driven routines)
• UI data models:
  • UI elements
  • UI interactions
  • Improved interaction collection aligned with new models

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🔧 Improvements & Refactors

• Refactored routine execution to operate cleanly at the routine/operation level
• Updated and unified routines, params, operations, and endpoint data models
• Refactored the CDP module
• Added new data utilities
• Improved routine integrity:
  • Automatic escaping of quotes when required
  • Fixed validation bugs (fully covered by unit tests)
• Updated OpenAI Responses API parsing
• Improved prompts and LM response data models
• Expanded network monitoring support (more file types, .txt as default response body)
• Migrated to GPT-5.1 for faster and more reliable execution
• Verified that Responses API provides sufficient context for extended runtimes

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🧪 Developer Experience

• Updated and expanded unit test coverage
• SDK fully refactored to use new data models
• Added a new quickstart.py that uses the SDK directly, making SDK testing significantly easier

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🛣️ Looking Ahead

Future PRs will focus on:

• Running and evaluating generated routines before completion (#57)
• Leveraging UI and window property data for reverse-engineering agents
• Adding more UI-driven routine operations
• Further improving placeholder interpolation diagnostics (#58 follow-ups)