Semantic Multimodal Search

import requests

API_URL = "https://api.mixpeek.com"
headers = {
    "Authorization": "Bearer YOUR_API_KEY",
    "X-Namespace": "your-namespace"
}

# Create collection with multimodal extractor
collection = requests.post(f"{API_URL}/v1/collections", headers=headers, json={
    "collection_name": "media_library",
    "source": {"type": "bucket", "bucket_id": "my-bucket"},
    "feature_extractor": {
        "feature_extractor_name": "multimodal_extractor",
        "version": "v1",
        "input_mappings": {"video": "source_video"}
    }
}).json()

# Index content from object storage
requests.post(f"{API_URL}/v1/buckets/my-bucket/objects", headers=headers, json={
    "blobs": [{"property": "source_video", "url": "s3://bucket/video.mp4"}],
    "metadata": {"category": "demos"}
})

# Search semantically across all modalities
results = requests.post(
    f"{API_URL}/v1/retrievers/semantic-retriever/execute",
    headers=headers,
    json={"query": {"text": "product demo with customer testimonials"}}
).json()

for doc in results["documents"]:
    print(f"{doc['document_id']}: {doc['score']:.3f}")