This page shows you how to update documents in a collection.
If the collection contains managed embedding vector fields, update the configured source text fields instead of sending direct vector values for managed embedding fields.
from lambdadb import LambdaDB
with LambdaDB(
project_api_key="YOUR_API_KEY",
base_url="YOUR_BASE_URL",
project_name="YOUR_PROJECT_NAME",
) as client:
coll = client.collection("my_collection")
docs = [
{"id": "33201222", "title": "LambdaDB", "text": "LambdaDB is an AI-native database ... "},
{"id": "33201223", "url": "https://en.wikipedia.org/wiki/Winamp", "title": "Winamp v2", "text": "Winamp v2 is a media player for Windows, macOS and Android, originally developed by Nullsoft."},
]
coll.docs.update(docs=docs)
Each document in a payload must contain an id field to uniquely identify a document to update.
For a partitioned collection, a document in the __default__ partition with a matching id value is updated if the partition field is not provided.
Update limits
| Metric | Limit |
|---|
| Max payload size | 6MB |
| Max length for a document ID | 512 characters |
| Max vector dimensions | 4,096 |
| Max document size | 5MB |
