landing_page/qdrant-landing/content/documentation/frameworks/sycamore.md

title, short_description, description

title	short_description	description
Sycamore	Process complex unstructured documents with Sycamore and write or read embeddings against Qdrant collections for GenAI and RAG analytics.	Use the Sycamore Qdrant connector to write and read embeddings for PDFs, HTML, and other unstructured documents, powering GenAI, RAG, and document analytics.

Sycamore

Sycamore is an LLM-powered data preparation, processing, and analytics system for complex, unstructured documents like PDFs, HTML, presentations, and more. With Aryn, you can prepare data for GenAI and RAG applications, power high-quality document processing workflows, and run analytics on large document collections with natural language.

You can use the Qdrant connector to write into and read documents from Qdrant collections.

You can find an end-to-end example usage of the Qdrant connector here.

Writing to Qdrant

To write a Docset to a Qdrant collection in Sycamore, use the docset.write.qdrant(....) function. The Qdrant writer accepts the following arguments:

• client_params: Parameters that are passed to the Qdrant client constructor. See more information in the Client API Reference.
• collection_params: Parameters that are passed into the qdrant_client.QdrantClient.create_collection method. See more information in the Client API Reference.
• vector_name: The name of the vector in the Qdrant collection. Defaults to None.
• execute: Execute the pipeline and write to Qdrant on adding this operator. If False, will return a DocSet with this write in the plan. Defaults to True.
• kwargs: Keyword arguments to pass to the underlying execution engine.

ds.write.qdrant(
    {
        "url": "http://localhost:6333",
        "timeout": 50,
    },
    {
        "collection_name": "{collection_name}",
        "vectors_config": {
            "size": 384,
            "distance": "Cosine",
        },
    },
)

Reading from Qdrant

To read a Docset from a Qdrant collection in Sycamore, use the docset.read.qdrant(....) function. The Qdrant reader accepts the following arguments:

• client_params: Parameters that are passed to the Qdrant client constructor. See more information in theClient API Reference.
• query_params: Parameters that are passed into the qdrant_client.QdrantClient.query_points method. See more information in the Client API Reference.
• kwargs: Keyword arguments to pass to the underlying execution engine.

docs = ctx.read.qdrant(
    {
        "url": "https://xyz-example.eu-central.aws.cloud.qdrant.io:6333",
        "api_key": "<paste-your-api-key-here>",
    },
    {"collection_name": "{collection_name}", "limit": 100, "using": "{optional_vector_name}"},
).take_all()

📚 Further Reading

• Sycamore Reference
• Sycamore