Files
qdrant/lib/edge/python/examples/qdrant-edge.py
Andrey Vasnetsov 0ed3a3a5ee simplify edge config (#7933)
* simplify edge config

* Accept default vector config or explicit vector config map when creating `EdgeConfig`

* fixup! Accept default vector config or explicit vector config map when creating `EdgeConfig`

Update examples

* upd tests

* bump edge version to v0.5.0

---------

Co-authored-by: Roman Titov <ffuugoo@users.noreply.github.com>
2026-02-09 23:12:30 +01:00

160 lines
3.1 KiB
Python
Executable File

#!/usr/bin/env python3
from qdrant_edge import *
from common import *
print("---- Point conversions ----")
points = [
Point(10, [[1,2,3], [3, 4, 5]], {}),
Point(11, { "sparse": SparseVector(indices=[0, 2], values=[1.0, 3.0]) }, {}),
]
# Test points conversion into internal representation and back
for point in points:
print(point)
print("---- Load shard ----")
shard = load_new_shard()
print("---- Upsert ----")
shard.update(UpdateOperation.upsert_points([
Point(
1,
[6.0, 9.0, 4.0, 2.0],
{
"null": None,
"str": "string",
"uint": 42,
"int": -69,
"float": 4.20,
"bool": True,
"obj": {
"null": None,
"str": "string",
"uint": 42,
"int": -69,
"float": 4.20,
"bool": True,
"obj": {},
"arr": [],
},
"arr": [None, "string", 42, -69, 4.20, True, {}, []],
},
),
Point(
"e9408f2b-b917-4af1-ab75-d97ac6b2c047",
[6.0, 9.0, 3.0, -2.0],
{
"hello": "world",
"price": 199.99,
},
),
Point(
uuid.uuid4(),
[1.0, 6.0, 4.0, 2.0],
{
"hello": "world",
"price": 999.99,
},
),
]))
print("---- Query ----")
result = shard.query(QueryRequest(
query = Query.Nearest([6.0, 9.0, 4.0, 2.0]),
limit = 10,
with_vector = True,
with_payload = True,
))
for point in result:
print(point)
print("---- Search ----")
points = shard.search(SearchRequest(
query=Query.Nearest([1.0, 1.0, 1.0, 1.0]),
limit=10,
with_vector=True,
with_payload=True,
))
for point in points:
print(point)
print("---- Search + Filter ----")
search_filter = Filter(
must=[
FieldCondition(
key="hello",
match=MatchTextAny(text_any="world"),
),
FieldCondition(
key="price",
range=RangeFloat(gte=500.0),
)
]
)
points = shard.search(SearchRequest(
query=Query.Nearest([1.0, 1.0, 1.0, 1.0]),
filter=search_filter,
limit=10,
with_vector=True,
with_payload=True,
))
for point in points:
print(point)
print("---- Retrieve ----")
points = shard.retrieve(point_ids=[1], with_vector=True, with_payload=True)
for point in points:
print(point)
print("---- Scroll ----")
scroll_result, next_offset = shard.scroll(ScrollRequest(limit=2))
for point in scroll_result:
print(point)
while next_offset is not None:
print(f"--- Next scroll (offset = {next_offset})---")
scroll_result, next_offset = shard.scroll(ScrollRequest(limit=2, offset=next_offset))
for point in scroll_result:
print(point)
print("---- Count ----")
count = shard.count(CountRequest(exact=True))
print(f"Total points count: {count}")
print("---- info ----")
info = shard.info()
print(info)
print("---- Close and reopen shard ----")
shard.close()
reopened_shard = EdgeShard(DATA_DIRECTORY)
info = reopened_shard.info()
print(info)