Besides the upsert operation which has 6MB maximum payload size limit, LambdaDB also supports bulk upsert operation to insert or update multiple documents up to 200MB at once.

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Get bulk upsert information

First, get the required information to upload payload to object storage: 
from lambdadb import LambdaDB

lambda_db = LambdaDB(
    server_url="PROJECT_URL",
    project_api_key="YOUR_API_KEY"
)

get_bulk_upsert = lambda_db.collections.docs.get_bulk_upsert(
    collection_name=collection_name
)
The response will look like this: 
{
  "url": "<string>",
  "type": "application/json",
  "httpMethod": "PUT",
  "objectKey": "<string>",
  "sizeLimitBytes": 209715200
}

​
Upload documents and execute bulk upsert

Upload your documents as a one object using the provided URL and call bulk-upsert API with the corresponding objectKey: 
import json
import requests

docs = [
  {
    "id": "bulk_33201222",
    "url": "https://en.wikipedia.org/wiki/LambdaDB",
    "title": "LambdaDB",
    "text": "LambdaDB is a serverless-native search engine for AI... ",
    "dense_vector": [0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0],
    "sparse_vector": {"LambdaDB": 0.83, "is": 0.1, "a": 0.1, "AI": 0.7}
  }
]

# Upload documents to the provided URL
put_documents = requests.put(
    get_bulk_upsert.url,
    data=json.dumps({"docs": docs}),
    headers={"Content-Type": "application/json"},
)

# Execute bulk upsert
bulk_upsert = lambda_db.collections.docs.bulk_upsert(
    collection_name=collection_name, 
    object_key=get_bulk_upsert.object_key
)

​
Response

After successful bulk upsert initiation, you’ll receive: 
{
  "message": "Bulk upsert request is accepted"
}
Bulk upsert operations are processed asynchronously. It may take some time for the documents to be fully indexed and available for search.