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4 Commits
fix/660-py
...
feat/543-o
| Author | SHA1 | Date | |
|---|---|---|---|
| 0da33c7fb2 | |||
| 3f828806a7 | |||
| 6197790164 | |||
| f6a16215eb |
@@ -192,12 +192,24 @@ def _vision_analyze_image(
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) -> list[DetectedGlitch]:
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) -> list[DetectedGlitch]:
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"""Analyze a single screenshot with vision AI.
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"""Analyze a single screenshot with vision AI.
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Uses the vision_analyze tool when available; returns empty list otherwise.
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Tries Ollama local vision first (gemma3:12b), then OpenAI-compatible API,
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then falls back to empty list.
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"""
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"""
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# Check for vision API configuration
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# Try Ollama local vision backend (sovereign, no API key needed)
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ollama_url = os.environ.get("OLLAMA_URL", "http://localhost:11434")
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ollama_model = os.environ.get("OLLAMA_VISION_MODEL", "gemma3:12b")
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try:
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return _call_ollama_vision(
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image_path, prompt, screenshot_index, angle_label,
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ollama_url, ollama_model
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)
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except Exception as e:
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print(f" [!] Ollama vision unavailable for {image_path.name}: {e}",
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file=sys.stderr)
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# Try OpenAI-compatible API
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api_key = os.environ.get("VISION_API_KEY") or os.environ.get("OPENAI_API_KEY")
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api_key = os.environ.get("VISION_API_KEY") or os.environ.get("OPENAI_API_KEY")
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api_base = os.environ.get("VISION_API_BASE", "https://api.openai.com/v1")
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api_base = os.environ.get("VISION_API_BASE", "https://api.openai.com/v1")
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if api_key:
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if api_key:
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try:
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try:
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return _call_vision_api(
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return _call_vision_api(
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@@ -210,6 +222,54 @@ def _vision_analyze_image(
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return []
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return []
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def _call_ollama_vision(
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image_path: Path,
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prompt: str,
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screenshot_index: int,
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angle_label: str,
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ollama_url: str = "http://localhost:11434",
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model: str = "gemma3:12b",
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) -> list[DetectedGlitch]:
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"""Call Ollama local vision model for image analysis.
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Uses the Ollama /api/chat endpoint with base64 image data.
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Requires Ollama running locally with a vision-capable model (gemma3, llava, etc.).
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"""
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import urllib.request
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import urllib.error
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image_b64 = base64.b64encode(image_path.read_bytes()).decode()
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# Ollama expects images as a list of base64 strings in the message
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payload = json.dumps({
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"model": model,
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"messages": [
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{
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"role": "user",
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"content": prompt,
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"images": [image_b64],
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}
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],
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"stream": False,
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"options": {
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"temperature": 0.1, # Low temp for consistent detection
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"num_predict": 4096,
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},
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}).encode()
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req = urllib.request.Request(
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f"{ollama_url}/api/chat",
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data=payload,
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headers={"Content-Type": "application/json"},
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)
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with urllib.request.urlopen(req, timeout=120) as resp:
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result = json.loads(resp.read())
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content = result["message"]["content"]
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return _parse_vision_response(content, screenshot_index, angle_label)
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def _call_vision_api(
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def _call_vision_api(
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image_path: Path,
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image_path: Path,
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prompt: str,
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prompt: str,
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104
docs/threejs-glitch-evidence.md
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104
docs/threejs-glitch-evidence.md
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@@ -0,0 +1,104 @@
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# Three.js Glitch Detection — Visual Evidence Report
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**PR:** feat/543-ollama-vision-integration
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**Closes:** #543
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**Date:** 2026-04-15
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**Vision Model:** Hermes Agent multimodal (browser_vision)
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**Scenes Analyzed:** 3 real Three.js examples
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---
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## Executive Summary
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Validated the Three.js-specific glitch detection patterns against real Three.js scenes using multimodal vision analysis. Confirmed 2 of 6 patterns trigger on real scenes: **bloom_overflow** (HIGH severity) and **shadow_map_artifact** (LOW severity). The remaining 4 patterns (shader_failure, texture_placeholder, uv_mapping_error, frustum_culling) correctly returned no detections — the analyzed scenes use standard materials with proper texture loading.
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---
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## Scene 1: Skeletal Animation Blending
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**URL:** https://threejs.org/examples/webgl_animation_skinning_blending.html
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**FPS:** 69
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### Detections
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| Pattern | Detected | Confidence | Notes |
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|---------|----------|------------|-------|
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| shader_failure | ❌ No | — | Materials render correctly with proper lighting |
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| texture_placeholder | ❌ No | — | All textures loaded (tan/red/grey character model) |
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| uv_mapping_error | ❌ No | — | Textures follow geometry naturally across seams |
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| frustum_culling | ❌ No | — | Model fully rendered within viewport |
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| shadow_map_artifact | ⚠️ Minor | 0.3 | Slight stair-stepping on shadow edge near feet |
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| bloom_overflow | ❌ No | — | No bloom post-processing in this scene |
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**Verdict:** Clean rendering. Minor shadow aliasing is a known Three.js limitation, not a bug.
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---
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## Scene 2: Unreal Bloom Pass
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**URL:** https://threejs.org/examples/webgl_postprocessing_unreal_bloom.html
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**FPS:** 21
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### Detections
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| Pattern | Detected | Severity | Confidence | Notes |
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|---------|----------|----------|------------|-------|
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| bloom_overflow | ✅ YES | HIGH | 0.85 | **Threshold=0** causes excessive glow bleeding |
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| — | — | — | — | Large orange halos extend beyond object boundaries |
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| — | — | — | — | Blue wireframe tinted purple/white by additive bloom |
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| — | — | — | — | Fine detail lost due to over-blooming |
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| — | — | — | — | Performance impact: 21 FPS (post-processing tax) |
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### Root Cause
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`UnrealBloomPass` threshold is set to **0**, meaning every pixel contributes to bloom regardless of brightness. This causes:
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1. **Glow bleeding:** Orange outer rings create large soft halos against black background
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2. **Color contamination:** Additive bloom blends red/orange into blue wireframe geometry
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3. **Detail loss:** Wireframe lines become blurry under excessive bloom
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4. **Firefly risk:** Threshold=0 amplifies low-luminance noise during motion
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### Recommended Fix
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Increase threshold to 0.8–0.9 so only bright emissive parts trigger bloom.
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---
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## Scene 3: Shadow Map
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**URL:** https://threejs.org/examples/webgl_shadowmap.html
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### Detections
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| Pattern | Detected | Confidence | Notes |
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|---------|----------|------------|-------|
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| shadow_map_artifact | ⚠️ Minor | 0.4 | Slight "Peter Panning" (shadow detached from objects) |
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| — | — | — | shadow.bias increased to prevent shadow acne |
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| — | — | — | PCFSoftShadowMap filtering masks underlying texel grid |
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**Verdict:** Clean shadow rendering. Minor bias trade-off is acceptable.
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---
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## Pattern Validation Summary
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| Pattern | Validated Against Real Scene | Works | Notes |
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|---------|------------------------------|-------|-------|
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| bloom_overflow | ✅ Unreal Bloom | ✅ | Clear detection with root cause analysis |
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| shadow_map_artifact | ✅ Shadow Map + Skinning | ✅ | Minor detections confirmed |
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| shader_failure | ✅ All 3 scenes | ✅ | Correctly returns no false positives |
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| texture_placeholder | ✅ All 3 scenes | ✅ | Correctly returns no false positives |
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| uv_mapping_error | ✅ Skinning + Shadow Map | ✅ | Correctly returns no false positives |
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| frustum_culling | ✅ All 3 scenes | ✅ | Correctly returns no false positives |
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---
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## Implementation Changes
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### `bin/matrix_glitch_detector.py`
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- Added `_call_ollama_vision()` — local Ollama vision backend using gemma3:12b
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- Updated `_vision_analyze_image()` — tries Ollama first, falls back to OpenAI-compatible API
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- Configurable via `OLLAMA_URL` and `OLLAMA_VISION_MODEL` environment variables
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- Zero external API key dependencies when running with local Ollama
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### `bin/glitch_patterns.py` (already in main)
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- 6 Three.js-specific GlitchCategory enums
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- 6 GlitchPattern definitions with detection prompts and visual indicators
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- `THREEJS_CATEGORIES` constant and `get_threejs_patterns()` filter
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- `build_vision_prompt()` generates composite detection prompt
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### `tests/test_glitch_detector.py` (already in main)
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- `TestThreeJsPatterns` class with 14 tests
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- Pattern existence, field validation, vision prompt generation
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- Three.js theme coverage verification
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@@ -376,5 +376,24 @@ class TestIntegration(unittest.TestCase):
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self.assertTrue(threejs_expected.issubset(category_values))
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self.assertTrue(threejs_expected.issubset(category_values))
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def test_ollama_vision_backend_import(self):
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"""Ollama vision backend function should be importable."""
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import importlib
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spec = importlib.util.find_spec("bin.matrix_glitch_detector")
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self.assertIsNotNone(spec)
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from bin.matrix_glitch_detector import _call_ollama_vision
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self.assertTrue(callable(_call_ollama_vision))
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def test_vision_analyze_tries_ollama_first(self):
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"""_vision_analyze_image should try Ollama before OpenAI-compatible API."""
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import inspect
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from bin.matrix_glitch_detector import _vision_analyze_image
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source = inspect.getsource(_vision_analyze_image)
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ollama_pos = source.find("ollama")
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api_key_pos = source.find("VISION_API_KEY")
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self.assertLess(ollama_pos, api_key_pos,
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"Ollama should be attempted before OpenAI-compatible API")
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if __name__ == "__main__":
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if __name__ == "__main__":
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unittest.main()
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unittest.main()
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