LlamaIndex

Load actor results into a LlamaIndex index with the Apify reader. The example uses YouTube Transcript & Subtitles Scraper; swap in any actor ID below.

The Apify reader for LlamaIndex runs an actor and maps each row to a Document.

# pip install llama-index-readers-apify
import os
from llama_index.core import Document, VectorStoreIndex
from llama_index.readers.apify import ApifyActor

reader = ApifyActor(os.environ["APIFY_TOKEN"])
documents = reader.load_data(
    actor_id="arcadium/youtube-transcripts",
    run_input={
        "urls": ["https://www.youtube.com/watch?v=dQw4w9WgXcQ"],
        "languages": [],
        "captionType": "any",
        "maxVideosPerSource": 10,
        "subtitleFormat": "none",
    },
    dataset_mapping_function=lambda item: Document(text=str(item.get("transcript") or ""), metadata={"url": item.get("url")}),
)
index = VectorStoreIndex.from_documents(documents)

Actor IDs