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style: repo linting pass (#33089)

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enable docstring-code-format
This commit is contained in:
Mason Daugherty
2025-09-24 15:25:55 -04:00
committed by GitHub
parent 083bb3cdd7
commit b92b394804
33 changed files with 687 additions and 283 deletions
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51
libs/partners/qdrant/langchain_qdrant/qdrant.py
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@@ -99,32 +99,58 @@ class QdrantVectorStore(VectorStore):
Search:
.. code-block:: python
results = vector_store.similarity_search(query="thud",k=1)
results = vector_store.similarity_search(
query="thud",
k=1,
)
for doc in results:
print(f"* {doc.page_content} [{doc.metadata}]")
.. code-block:: python
* thud [{'bar': 'baz', '_id': '0d706099-6dd9-412a-9df6-a71043e020de', '_collection_name': 'demo_collection'}]
*thud[
{
"bar": "baz",
"_id": "0d706099-6dd9-412a-9df6-a71043e020de",
"_collection_name": "demo_collection",
}
]
Search with filter:
.. code-block:: python
from qdrant_client.http import models
results = vector_store.similarity_search(query="thud",k=1,filter=models.Filter(must=[models.FieldCondition(key="metadata.bar", match=models.MatchValue(value="baz"),)]))
results = vector_store.similarity_search(
query="thud",
k=1,
filter=models.Filter(
must=[
models.FieldCondition(
key="metadata.bar",
match=models.MatchValue(value="baz"),
)
]
),
)
for doc in results:
print(f"* {doc.page_content} [{doc.metadata}]")
.. code-block:: python
* thud [{'bar': 'baz', '_id': '0d706099-6dd9-412a-9df6-a71043e020de', '_collection_name': 'demo_collection'}]
*thud[
{
"bar": "baz",
"_id": "0d706099-6dd9-412a-9df6-a71043e020de",
"_collection_name": "demo_collection",
}
]
Search with score:
.. code-block:: python
results = vector_store.similarity_search_with_score(query="qux",k=1)
results = vector_store.similarity_search_with_score(query="qux", k=1)
for doc, score in results:
print(f"* [SIM={score:3f}] {doc.page_content} [{doc.metadata}]")
@@ -145,8 +171,8 @@ class QdrantVectorStore(VectorStore):
# results = vector_store.asimilarity_search(query="thud",k=1)
# search with score
results = await vector_store.asimilarity_search_with_score(query="qux",k=1)
for doc,score in results:
results = await vector_store.asimilarity_search_with_score(query="qux", k=1)
for doc, score in results:
print(f"* [SIM={score:3f}] {doc.page_content} [{doc.metadata}]")
.. code-block:: python
@@ -164,7 +190,16 @@ class QdrantVectorStore(VectorStore):
.. code-block:: python
[Document(metadata={'bar': 'baz', '_id': '0d706099-6dd9-412a-9df6-a71043e020de', '_collection_name': 'demo_collection'}, page_content='thud')]
[
Document(
metadata={
"bar": "baz",
"_id": "0d706099-6dd9-412a-9df6-a71043e020de",
"_collection_name": "demo_collection",
},
page_content="thud",
)
]
""" # noqa: E501