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import time
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from twelvelabs import TwelveLabs
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# 1. Initialize the client
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client = TwelveLabs(api_key="<YOUR_API_KEY>")
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# 2. Create an index
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# An index is a container for organizing your video content
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index = client.indexes.create(
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    index_name="<YOUR_INDEX_NAME>",
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    models=[{"model_name": "marengo3.0", "model_options": ["visual", "audio"]}]
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)
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if not index.id:
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    raise RuntimeError("Failed to create an index.")
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print(f"Created index: id={index.id}")
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# 3. Upload a video
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asset = client.assets.create(
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    method="url",
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    url="<YOUR_VIDEO_URL>" # Use direct links to raw media files. Video hosting platforms and cloud storage sharing links are not supported.
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    # Or use method="direct" and file=open("<PATH_TO_VIDEO_FILE>", "rb") to upload a local file up to 200 MB
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)
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print(f"Created asset: id={asset.id}")
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# 4. Check the status of the asset
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print("Waiting for asset to be ready...")
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while True:
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    asset = client.assets.retrieve(asset.id)
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    if asset.status == "ready":
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        print("Asset is ready")
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        break
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    if asset.status == "failed":
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        raise RuntimeError(f"Asset processing failed: id={asset.id}")
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    time.sleep(5)
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# 5. Index your video
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indexed_asset = client.indexes.indexed_assets.create(
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    index_id=index.id,
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    asset_id=asset.id
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)
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print(f"Created indexed asset: id={indexed_asset.id}")
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# 6. Monitor the indexing process
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print("Waiting for indexing to complete.")
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while True:
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    indexed_asset = client.indexes.indexed_assets.retrieve(
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        index.id,
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        indexed_asset.id
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    )
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    print(f"  Status={indexed_asset.status}")
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    if indexed_asset.status == "ready":
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        print("Indexing complete!")
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        break
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    elif indexed_asset.status == "failed":
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        raise RuntimeError("Indexing failed")
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    time.sleep(5)
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# 7. Perform a search
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search_results = client.search.query(
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    index_id=index.id,
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    query_text="<YOUR_QUERY>",
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    search_options=["visual", "audio"]
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)
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# 8. Process the search results
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print("\nSearch results:")
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print("Each result shows a video clip that matches your query:\n")
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for i, clip in enumerate(search_results):
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    print(f"Result {i + 1}:")
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    print(f"  Video ID: {clip.video_id}")  # Unique identifier of the video
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    print(f"  Rank: {clip.rank}")  # Relevance ranking (1 = most relevant)
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    print(f"  Time: {clip.start}s - {clip.end}s")  # When this moment occurs in the video
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    print()