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Implement --ai-json flag to export compilation errors and warnings in structured JSON format optimized for AI-assisted code generation and error correction. Features: - New ai_diagnostics.py module with AILogger for capturing diagnostics - Command-line flag --ai-json=FILE for JSON output - Automatic capture of all errors and warnings during compilation - Rich context including file paths, line numbers, and code snippets - Metadata for compilation context and timestamps Changes: - Add ai_diagnostics.py module to Makefile - Integrate AILogger initialization and output in dmlc.py - Hook logging.report() to capture messages for AI diagnostics - Add comprehensive documentation and test files
…rovements - Expand error detection to handle ENAMECOLL (name collision) errors - Add fix suggestions for WNOIS, WNSHORTDESC, and SYNTAX errors - Improve WNOIS suggestion extraction using regex for method names - Add debug logging for fix suggestion generation - Add run_dmlc.sh helper script for easier DMLC execution - Update test_ai_diagnostics.dml with better error coverage and imports
… paths - Replace hardcoded paths with dynamic resolution based on environment variables - Add checks for DMLC_DIR and SIMICS_BASE to ensure proper setup - Determine host type for compatibility with Windows and Linux - Allow MODULE_DIR to be specified via command-line argument or default to current directory - Enhance script robustness with error messages and exit codes
- Require DML file path as first argument with proper error message - Extract MODULE_DIR from the provided DML file path - Pass DML file directly to DMLC instead of all arguments - Add validation to ensure script is called with required argument
- Ignore .dml files (not parseable by tree-sitter) - Ignore test/ folder - Allow only .py files for SCIP indexing
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