20259dcad0
- Add Honda client with static_general and video_general profiles - Add video QC capability using Gemini native video analysis (4 checks: visual_quality, brand_consistency, text_legibility, pacing_flow) - Add video_general profile assigned to all 8 clients - Extend session lifetime with MSAL silent token refresh (proactive every 45min + reactive on expiry), switch cache to localStorage - Re-enable OCR layout measurements for Amazon checks - Add scope boundary notes to all 6 Amazon checks to prevent cross- check penalization (locale errors isolated to logo_country only) - Relax margins left-alignment tolerance from 1% to 4% to account for logo lockup internal padding - Update brand guidelines DB with Amazon localization matrix and processed Dove PDF summary Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
107 lines
4.2 KiB
Python
107 lines
4.2 KiB
Python
import os
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import sys
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# Add parent directory to path to import shared modules
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sys.path.append(os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__)))))
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from visual_qc_apps.flask_app_template import FlaskAppTemplate
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class VideoPacingFlowApp(FlaskAppTemplate):
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"""
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Video QC - Pacing & Flow Check
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Evaluates the video's pacing, transitions, scene structure, and overall
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narrative/visual flow for marketing effectiveness.
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"""
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def __init__(self):
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prompt = """You are performing a pacing and flow quality-control check on a VIDEO marketing asset. You are watching the full video — evaluate the overall structure, pacing, and flow across its entire duration.
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VIDEO PACING & FLOW EVALUATION:
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Evaluate the following aspects of the video's structure and flow:
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1. OPENING / HOOK:
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- Does the video have a strong opening that captures attention?
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- Is the key message or brand introduced within the first few seconds?
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- For social media content: is the hook immediate (first 1-3 seconds)?
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2. PACING:
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- Is the overall pace appropriate for the content type and platform?
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- Are scenes/shots an appropriate duration — not too long (boring) or too short (disorienting)?
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- Does the pacing maintain viewer engagement throughout?
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- Are there any dead spots or unnecessarily slow sections?
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3. TRANSITIONS:
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- Are scene transitions smooth and professional?
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- Are transition effects consistent in style throughout?
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- Are there any jarring or abrupt cuts that feel unintentional?
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- Do transitions serve the narrative or feel gratuitous?
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4. SCENE STRUCTURE:
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- Does the video follow a logical structure (beginning, middle, end)?
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- Is the key message clear and communicated effectively?
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- Are there any scenes that feel out of place or unnecessary?
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- Is the video an appropriate length for its content and intended platform?
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5. CLOSING / CTA:
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- Does the video have a clear and intentional ending?
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- Does it end with a call-to-action, brand moment, or memorable closing?
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- Does the ending feel complete (not abrupt or cut short)?
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- Is there an adequate pause on the final frame before the video ends?
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STEPS TO EVALUATE:
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1. Watch the full video noting the overall structure and pacing
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2. Assess whether the opening grabs attention
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3. Check if pacing maintains engagement or has dead spots
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4. Evaluate transitions for smoothness and consistency
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5. Assess the closing for completeness and brand presence
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6. Consider the overall viewer experience from start to finish
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DECISION CRITERIA:
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- PASS (score 7-10): Well-paced, engaging from start to finish, smooth transitions, clear structure with strong opening and closing
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- MODERATE ISSUES (score 4-6): Generally acceptable pacing but with some slow sections, inconsistent transitions, or a weak opening/closing
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- FAIL (score 1-3): Poor pacing — disengaging, jarring transitions, no clear structure, abrupt ending, or video feels incomplete
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YOUR OUTPUT:
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Format your response as JSON:
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{
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"pacing_flow_check": "Pass" or "Fail",
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"opening": {
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"attention_grabbing": true or false,
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"brand_intro_timing": "Immediate (1-3s)" or "Early (3-5s)" or "Mid" or "Late" or "Not present",
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"notes": "Details"
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},
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"pacing": {
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"overall_pace": "Well-paced" or "Slightly slow" or "Slightly fast" or "Uneven" or "Too slow" or "Too fast",
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"dead_spots": true or false,
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"engagement_maintained": true or false,
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"notes": "Details"
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},
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"transitions": {
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"quality": "Smooth" or "Mostly smooth" or "Jarring",
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"consistency": "Consistent" or "Inconsistent",
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"notes": "Details"
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},
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"structure": {
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"logical_flow": true or false,
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"key_message_clear": true or false,
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"appropriate_length": true or false,
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"notes": "Details"
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},
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"closing": {
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"clear_ending": true or false,
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"cta_or_brand_moment": true or false,
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"adequate_final_frame": true or false,
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"notes": "Details"
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},
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"estimated_duration": "Approximate video duration",
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"explanation": "Detailed reasoning for the overall assessment",
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"recommendations": ["List specific recommendations if applicable, else an empty array"]
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}"""
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super().__init__(__name__, prompt)
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# Run the app if executed directly
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if __name__ == "__main__":
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app_instance = VideoPacingFlowApp()
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app_instance.run()
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