Video Analysis

import requests

response = requests.post(
    "https://app.mavera.io/api/v1/video-analyses",
    headers={"Authorization": "Bearer mvra_live_your_key_here"},
    json={
        "title": "Q1 Product Ad Analysis",
        "asset_id": "asset_video_123",  # Your uploaded video
        "goal": "Analyze viewer engagement and emotional response",
        "brand": "Your Brand",
        "product": "Product Name",
        "primary_intent": "Drive product awareness",
        "chunk_duration": 5,  # Analyze in 5-second chunks
        "frames_per_chunk": 3,
        "workspace_id": "your_workspace_id"
    }
)

analysis = response.json()
print(f"Analysis ID: {analysis['id']}")
print(f"Status: {analysis['status']}")

response = requests.get(
    f"https://app.mavera.io/api/v1/video-analyses/{analysis_id}",
    headers={"Authorization": "Bearer mvra_live_your_key_here"}
)

result = response.json()

# Full video metrics
metrics = result["results"]["full_video_metrics"]
print(f"Overall Score: {metrics['overall_score']}/100")
print(f"Emotional Impact: {metrics['emotional_impact']}/10")
print(f"Attention Score: {metrics['attention_score']}/10")

# Chunk-by-chunk analysis
for chunk in result["results"]["chunks"]:
    print(f"Timestamp {chunk['start_time']}-{chunk['end_time']}:")
    print(f"  Engagement: {chunk['engagement_score']}")
    print(f"  Key Moments: {chunk['key_moments']}")

response = requests.post(
    f"https://app.mavera.io/api/v1/video-analyses/{analysis_id}/chat",
    headers={"Authorization": "Bearer mvra_live_your_key_here"},
    json={
        "message": "What are the weakest moments in this video and how can I improve them?"
    }
)

{
  "id": "va_abc123",
  "title": "Q1 Product Ad Analysis",
  "status": "COMPLETED",
  "results": {
    "full_video_metrics": {
      "overall_score": 78,
      "emotional_impact": 8.2,
      "attention_score": 7.5,
      "brand_recall_likelihood": 0.72,
      "cta_effectiveness": 6.8
    },
    "chunks": [
      {
        "start_time": 0,
        "end_time": 5,
        "engagement_score": 8.5,
        "emotional_valence": "positive",
        "key_moments": ["Strong opening hook"],
        "recommendations": []
      }
    ],
    "recommendations": [
      "Consider shortening the middle section",
      "Add stronger CTA at 0:45"
    ]
  },
  "usage": {
    "credits_used": 250
  }
}