- Convert virtual environment Python paths to absolute paths to ensure
consistency across different shell environments (Git Bash, WSL, etc.)
- Add enhanced diagnostic information when pip detection fails to help
users troubleshoot path and environment issues
- Improve error messages with specific guidance for different platforms
- Fix black configuration to exclude .zen_venv directory from formatting
- Add comprehensive test suite for pip detection edge cases
Fixes#188
- Use o3-pro throughout the codebase instead of o3-pro-2025-06-10
- Update test expectations to match o3-pro model name
- Update cassette to use o3-pro for consistency
- Ensure responses endpoint routing works correctly with o3-pro
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Co-Authored-By: Claude <noreply@anthropic.com>
- Use new output_text field format for o3-pro responses
- Update test expectations to use resolved model name o3-pro-2025-06-10
- Keep HTTP transport recorder and PII sanitization improvements
- Preserve both bug fix and recent GPT-5 updates
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Improvements to model name resolution
Improved instructions for multi-step workflows when continuation is available
Improved instructions for chat tool
Improved preferred model resolution, moved code from registry -> each provider
Updated tests
The o3-pro test now clears the restriction service singleton in its
setup_method to ensure it re-reads environment variables set by the
@patch.dict decorator. This prevents cached restrictions from previous
tests (like test_fallback_with_shorthand_restrictions) from blocking
the o3-pro model.
This is a minimal, targeted fix that only affects the specific test
that needs it, without breaking other tests that may depend on the
restriction service state.
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Replace @patch.dict decorator with pytest monkeypatch fixture in
test_fallback_with_shorthand_restrictions to ensure proper environment
variable cleanup between tests. This prevents OPENAI_ALLOWED_MODELS
from leaking into subsequent tests.
Also remove the manual clearing of _restriction_service singleton
as it's no longer needed with proper environment variable isolation.
This fixes test isolation issues where o3-pro tests would fail when
run after restriction tests due to environment variable persistence.
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The test failures in CI were caused by tests with @pytest.mark.no_mock_provider
that prevented dummy API keys from being set. In CI with no real API keys,
this led to 'Model not available' errors.
Changed pytest_collection_modifyitems to always set dummy keys if missing,
regardless of markers. This ensures tests work in CI while still allowing
real API keys to be used when present.
Fixes test_conversation_field_mapping.py failures in CI across Python 3.10-3.12.
- Removed excessive debug logging in http_transport_recorder.py
- Consolidated redundant log statements
- Fixed exception logging to use logger.exception()
- Removed emojis from log messages for cleaner output
- Removed __main__ block from test_o3_pro_output_text_fix.py per pytest conventions
- Applied black formatting to comply with CI checks
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- Fix test isolation by clearing LOCALE env var in o3-pro test
- Add restriction service cleanup in test_model_restrictions.py
- Fix PII sanitizer phone regex to not match timestamps
- Convert all print statements to logging in test files per PR review
- Re-record o3-pro cassette with correct environment
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Co-Authored-By: Claude <noreply@anthropic.com>
- Fixed test_fallback_with_shorthand_restrictions to clear restriction
service singleton in finally block, preventing state leakage
- Updated o3-pro test to use @patch.dict for OPENAI_ALLOWED_MODELS,
following standard pattern and allowing both o3-pro and o3-pro-2025-06-10
- Removed invalid cassette file that had wrong request content
The test now passes in both isolated and full suite runs.
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Co-Authored-By: Claude <noreply@anthropic.com>
The test was failing when run in the full test suite because the
ModelRestrictionService singleton persisted restrictions from previous
tests. Specifically, test_fallback_with_shorthand_restrictions sets
OPENAI_ALLOWED_MODELS="mini" which blocked o3-pro.
Added utils.model_restrictions._restriction_service = None to ensure
the test starts with clean restriction state.
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Co-Authored-By: Claude <noreply@anthropic.com>
The bisect and simplified test files were created during investigation
to understand fixture requirements, but they test the same core functionality
as test_o3_pro_output_text_fix.py. Now that we have the final clean
implementation, these files are redundant.
Removed:
• test_o3_pro_fixture_bisect.py - 4 test methods testing fixture combinations
• test_o3_pro_simplified.py - 2 test methods testing minimal requirements
The main test_o3_pro_output_text_fix.py remains and covers all the necessary
o3-pro output_text parsing validation.
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Co-Authored-By: Claude <noreply@anthropic.com>
✨ Key improvements:
• Added public reset_for_testing() method to registry for clean test state management
• Updated test setup/teardown to use new public API instead of private attributes
• Enhanced inject_transport helper to ensure OpenAI provider registration
• Migrated additional test files to use inject_transport pattern
• Reduced code duplication by ~30 lines across test files
🔧 Technical details:
• transport_helpers.py: Always register OpenAI provider for transport tests
• test_o3_pro_output_text_fix.py: Use reset_for_testing() API, remove redundant registration
• test_o3_pro_fixture_bisect.py: Migrate all 4 test methods to inject_transport
• test_o3_pro_simplified.py: Migrate both test methods to inject_transport
• providers/registry.py: Add reset_for_testing() public method
✅ Quality assurance:
• All 7 o3-pro tests pass with new helper pattern
• No regression in test isolation or provider state management
• Improved maintainability through centralized transport injection
• Follows single responsibility principle with focused helper function
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Co-Authored-By: Claude <noreply@anthropic.com>
- Remove over-engineered allow_all_models fixture (6 operations → 1 line API key setting)
- Replace 10 lines of monkey patching boilerplate with 1-line inject_transport helper
- Remove cargo-cult error handling that allowed test to pass with API failures
- Create reusable transport_helpers.py for HTTP transport injection patterns
- Fix provider registration state pollution between batch test runs
- Test now works reliably in both individual and batch execution modes
The test is significantly cleaner and addresses root cause (provider registration timing)
rather than symptoms (cache clearing).
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Co-Authored-By: Claude <noreply@anthropic.com>
- Add verification that o3-pro model was actually used (not just requested)
- Verify model_used and provider_used metadata fields are populated
- Add graceful handling for error responses in test
- Improve test documentation explaining what's being verified
- Confirm response parsing uses output_text field correctly
This ensures the test properly validates both that:
1. The o3-pro model was selected and used via the /v1/responses endpoint
2. The response metadata correctly identifies the model and provider
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Co-Authored-By: Claude <noreply@anthropic.com>
Consolidates duplicated image validation logic from individual providers
into a reusable base class method. This improves maintainability and
ensures consistent validation across all providers.
- Added validate_image() method to ModelProvider base class
- Supports both file paths and data URLs
- Validates image format, size, and MIME types
- Added DEFAULT_MAX_IMAGE_SIZE_MB class constant (20MB)
- Refactored Gemini and OpenAI providers to use base validation
- Added comprehensive test suite with 19 tests
- Used minimal mocking approach with concrete test provider class
- Fix lint errors: trailing whitespace and deprecated typing imports
- Update test mock for o3-pro response format (output.content[] → output_text)
- Implement robust test isolation with monkeypatch fixture
- Clear provider registry cache to prevent test interference
- Ensure o3-pro tests pass in both individual and full suite execution
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Co-Authored-By: Claude <noreply@anthropic.com>
- Add o3_pro_basic_math.json cassette for test_o3_pro_output_text_fix.py
- Remove unused o3_pro_content_capture.json cassette
- This allows tests to run without API keys in CI/CD
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Co-Authored-By: Claude <noreply@anthropic.com>
- Fix o3-pro response parsing to use output_text convenience field
- Replace respx with custom httpx transport solution for better reliability
- Implement comprehensive PII sanitization to prevent secret exposure
- Add HTTP request/response recording with cassette format for testing
- Sanitize all existing cassettes to remove exposed API keys
- Update documentation to reflect new HTTP transport recorder
- Add test suite for PII sanitization and HTTP recording
This change:
1. Fixes timeout issues with o3-pro API calls (was 2+ minutes, now ~15-22 seconds)
2. Properly captures response content without httpx.ResponseNotRead exceptions
3. Preserves original HTTP response format including gzip compression
4. Prevents future secret exposure with automatic PII sanitization
5. Enables reliable replay testing for o3-pro interactions
Co-Authored-By: Claude <noreply@anthropic.com>
- Introduced tests for Docker deployment scripts to ensure existence, permissions, and proper command usage.
- Added tests for Docker integration with Claude Desktop, validating MCP configuration and command formats.
- Implemented health check tests for Docker, ensuring script functionality and proper configuration in Docker setup.
- Created tests for Docker MCP validation, focusing on command validation and security configurations.
- Developed security tests for Docker configurations, checking for non-root user setups, privilege restrictions, and sensitive data handling.
- Added volume persistence tests to ensure configuration and logs are correctly managed across container runs.
- Updated .dockerignore to exclude sensitive files and added relevant tests for Docker secrets handling.
Added new confidence values (very_high, almost_certain) to all workflow tools
to provide more granular confidence tracking. Updated enum declarations in:
- analyze.py, codereview.py, debug.py, precommit.py, secaudit.py, testgen.py
- Updated debug.py's get_required_actions to handle new confidence values
- All tools now use consistent 7-value confidence scale
- refactor.py kept its unique scale (exploring/incomplete/partial/complete)
Also fixed model thinking configuration:
- Added very_high and almost_certain to MODEL_THINKING_PREFERENCES
- Set medium thinking for very_high, high thinking for almost_certain
- Updated prompts to clarify certain means 100% local confidence
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