Qdrant

Use Qdrant vector database

Configuration

Upsert

Operation
Upsert
API Key*
••••••••
Qdrant URL*
http://localhost:6333
Collection*
my-collection
Points*
[{"id": 1, "vector": [0.1, 0.2], "payload": {"category": "a"}}]
Output
ParameterTypeDescription
matchesjsonSearch matches
upsertedCountnumberUpserted count
datajsonResponse data
statusstringOperation status

Operation
Search
API Key*
••••••••
Qdrant URL*
http://localhost:6333
Collection*
my-collection
Query Vector*
[0.1, 0.2]
Limit
10
Filter
{"must":[{"key":"city","match":{"value":"London"}}]}
Return Data
Select...
Output
ParameterTypeDescription
matchesjsonSearch matches
upsertedCountnumberUpserted count
datajsonResponse data
statusstringOperation status

Fetch

Operation
Fetch
API Key*
••••••••
Qdrant URL*
http://localhost:6333
Collection*
my-collection
IDs*
["370446a3-310f-58db-8ce7-31db947c6c1e"]
Return Data
Select...
Output
ParameterTypeDescription
matchesjsonSearch matches
upsertedCountnumberUpserted count
datajsonResponse data
statusstringOperation status

Usage Instructions

Integrate Qdrant into the workflow. Can upsert, search, and fetch points.

Notes

  • Category: tools
  • Type: qdrant