Skip to main content

Documentation Index

Fetch the complete documentation index at: https://docs.meibel.ai/llms.txt

Use this file to discover all available pages before exploring further.

​
Managing Datasources

Datasources are containers for the knowledge that powers your agents. A datasource holds uploaded files, manages the ingestion pipeline, and serves as the searchable knowledge base for agent conversations. This guide covers the full datasource lifecycle.

​
Create a datasource

Create a new, empty datasource to begin uploading content into. 
import os
from meibel import MeibelClient
from meibel.models import CreateDatasourceRequest, ConnectorConfig

client = MeibelClient(api_key=os.environ["MEIBEL_API_KEY"])

datasource = client.datasources.create_datasource(body=CreateDatasourceRequest(
    name="Q4 Financial Reports",
    description="Quarterly earnings reports and analyst briefings",
    connector=ConnectorConfig(type="managed"),
))

print(datasource.id, datasource.name)
The response includes the datasource id, name, description, and timestamps. Use the id for all subsequent operations.

​
Upload files

Upload files to a datasource. The SDK streams the file directly to the server in chunks, so files of any size can be uploaded without being fully buffered in memory. 
with open("earnings-q4.pdf", "rb") as f:
    upload = client.content.upload_content(
        file=f,
        file_name="earnings-q4.pdf",
    )

print(upload.id)
You can upload multiple files to the same datasource. Supported formats include PDF, DOCX, XLSX, CSV, TXT, and JSON.

​
Trigger ingestion

After uploading files, trigger the ingestion pipeline to parse, extract, and index the content into searchable data elements. 
result = client.content.trigger_ingest(datasource_id=datasource.id)

print(result.status)
Ingestion runs asynchronously. You can poll the datasource status or use streaming events to track progress.

​
Get datasource details

Retrieve the full metadata and status for a datasource, including ingestion state and file counts. 
datasource = client.datasources.get_datasource(datasource_id="ds_123")

print(datasource.name)
print(datasource.status)
print(datasource.file_count)

​
Update a datasource

Modify a datasource’s name, description, or configuration. Only the fields you include in the request body are changed. 
from meibel.models import UpdateDatasourceRequest

updated = client.datasources.update_datasource(
    datasource_id="ds_123",
    body=UpdateDatasourceRequest(
        name="Q4 2025 Financial Reports",
        description="Updated with final audited numbers",
    ),
)

print(updated.name)

​
Delete a datasource

Permanently remove a datasource and all its uploaded content and data elements. This action cannot be undone. 
client.datasources.delete_datasource(datasource_id="ds_123")
Deleting a datasource removes all uploaded files and extracted data elements. Agents that reference this datasource will lose access to its content.