Search videos

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import json
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import requests
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API_KEY = "YOUR_API_KEY"
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BASE_URL = "https://api.twelvelabs.io/v1.3"
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HEADERS = {"x-api-key": API_KEY, "Content-Type": "application/json"}
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STORE_ID = "your_knowledge_store_id"
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search_schema = {
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    "type": "object",
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    "properties": {
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        "results": {
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            "type": "array",
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            "items": {
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                "type": "object",
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                "properties": {
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                    "video_reference": {"type": "string"},
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                    "timestamp": {"type": "string"},
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                    "description": {"type": "string"},
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                    "relevance": {"type": "string"}
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                }
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            }
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        },
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        "total_results": {"type": "integer"},
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        "query_interpretation": {"type": "string"}
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    }
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}
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response = requests.post(
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    f"{BASE_URL}/responses",
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    headers=HEADERS,
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    json={
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        "model": "jockey1.0",
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        "input": [
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            {"type": "message", "role": "user", "content": "Find all moments where someone is presenting to an audience"}
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        ],
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        "tools": [
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            {"type": "knowledge_store", "knowledge_store_id": STORE_ID}
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        ],
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        "text": {"format": "json_schema", "json_schema": search_schema}
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    }
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)
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result = response.json()
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for output in result["output"]:
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    if output["type"] == "message":
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        for content in output["content"]:
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            search = json.loads(content["text"])
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            print(f"Found {search['total_results']} results")
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            print(f"Interpreted as: {search['query_interpretation']}\n")
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            for r in search["results"]:
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                print(f"  [{r['timestamp']}] {r['video_reference']}")
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                print(f"    {r['description']}")
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                print(f"    Relevance: {r['relevance']}\n")