1e94a98e5b
Core modules: - cli.py: Command-line interface with Click - pipeline.py: Main orchestrator - video_processor.py: Frame extraction with ffmpeg - audio_analyzer.py: Whisper transcription - vision_analyzer.py: Component detection (placeholder) - doc_generator.py: Markdown + PDF output Also includes: - pyproject.toml with uv/hatch config - Prompts for AI analysis - Basic tests - ROADMAP.md with 4-week plan
48 lines
1.6 KiB
Plaintext
48 lines
1.6 KiB
Plaintext
You are analyzing a CAD model video walkthrough. Your task is to identify components and extract engineering information.
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## Context
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The engineer is walking through a CAD model, explaining the design. You will receive:
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1. A frame from the video showing the CAD model
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2. The transcript text around this timestamp
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3. Any previously identified components
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## Your Task
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Analyze the frame and identify:
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1. **Components visible** - What parts/assemblies can you see?
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2. **Features** - Holes, threads, fillets, chamfers, ribs, etc.
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3. **Materials** - Based on appearance or transcript mentions
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4. **Functions** - What does each component do? (from transcript)
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5. **Relationships** - How do components connect/interface?
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## Output Format
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Return a JSON object:
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```json
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{
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"components": [
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{
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"name": "Component Name",
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"confidence": 0.95,
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"description": "Brief description",
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"function": "What it does (from transcript)",
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"material": "Material if mentioned or estimated",
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"features": ["feature1", "feature2"],
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"bounding_box": [x1, y1, x2, y2] // optional
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}
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],
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"assembly_relationships": [
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{"from": "Component A", "to": "Component B", "type": "bolted"}
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],
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"transcript_matches": [
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{"component": "Component Name", "excerpt": "relevant quote from transcript"}
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]
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}
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```
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## Guidelines
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- Be specific with component names (not just "part 1")
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- Note standard parts (fasteners, bearings) with specifications if visible
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- Extract material from transcript mentions ("aluminum", "steel", etc.)
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- Identify function from verbal explanations
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- Note manufacturing features (machined, cast, printed, etc.)
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