Add comprehensive documentation and examples
- docs/USAGE.md: Full usage guide with CLI options, Python API, troubleshooting - docs/ATOMIZER_INTEGRATION.md: Guide for FEA/Atomizer integration - examples/sample_config.toml: Annotated configuration example - README.md: Expanded with installation, usage, architecture
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examples/sample_config.toml
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examples/sample_config.toml
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# CAD-Documenter Sample Configuration
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# Copy to ~/.cad-documenter.toml and customize
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[api]
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# Vision API provider: "openai" or "anthropic"
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provider = "openai"
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# API key - REQUIRED for vision analysis
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# Can also be set via OPENAI_API_KEY or ANTHROPIC_API_KEY environment variable
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# api_key = "sk-your-key-here"
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# Model overrides (optional - uses provider defaults if not set)
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# For OpenAI: gpt-4o (default), gpt-4o-mini
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# For Anthropic: claude-sonnet-4-20250514 (default), claude-3-haiku-20240307
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# vision_model = "gpt-4o"
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# text_model = "gpt-4o-mini"
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[processing]
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# Whisper model for transcription
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# Options: tiny (fastest), base (default), small, medium, large (most accurate)
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whisper_model = "base"
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# Seconds between frame extractions (used if scene detection disabled)
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frame_interval = 2.0
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# Use AI-powered scene change detection for smarter frame selection
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use_scene_detection = true
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# Maximum frames to analyze (limits API costs)
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max_frames = 15
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# Scene detection sensitivity (0.0-1.0, lower = more sensitive)
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scene_threshold = 0.3
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[output]
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# Include Bill of Materials table in documentation
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include_bom = true
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# Include Atomizer FEA hints section
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include_atomizer_hints = true
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# Include raw transcript at end of documentation
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include_raw_transcript = true
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# Keep extracted frames in output directory
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include_frames = true
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# PDF template name (for future template support)
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pdf_template = "default"
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