38 lines
1.4 KiB
YAML
38 lines
1.4 KiB
YAML
# Vision Pipeline Configuration Example
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# Copy this file to vision.yaml and set values via environment variables.
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# vision.yaml is in .gitignore — never commit real secrets.
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inference:
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local_url: "${LOCAL_LLAMA_URL}" # e.g. http://localhost:8080/v1
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local_model: "nemotron-vision-local"
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# Hosted fallback — used when local fails or confidence is too low
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fallback_provider: "anthropic" # or "openai"
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fallback_model: "claude-3-5-sonnet"
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fallback_api_key: "${FALLBACK_API_KEY}" # loaded from env
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fallback_max_tokens: 4096
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# llama-server tuning (for documentation/reference)
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mmproj_path: "/mnt/data/models/nemotron-30b-a3b/mmproj-F16.gguf"
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context_size: 120000
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kv_cache_quantization: "q4_1"
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flash_attention: true
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capture:
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watch_dir: "${SCREENSHOT_DIR}" # e.g. /home/user001/godot_screenshots
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auto_review: true
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trigger_interval_seconds: 30
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review:
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max_iterations: 3
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confidence_threshold: 0.75
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system_prompt: |
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You are a 3D game QA engineer. Analyze the provided screenshot and report
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issues related to visual quality, performance, and adherence to game
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design standards. Output findings as a JSON array with fields:
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category, severity (info/warning/critical), description.
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fallback_prompt: |
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Re-examine this image focusing on any issues you may have missed.
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Be specific about visual artifacts, lighting problems, UI inconsistencies,
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or performance indicators.
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