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style: format code with Ruff Formatter #10

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style: format code with Ruff Formatter #10

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36 changes: 8 additions & 28 deletions app/temp/qdrant_search_tool.py
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Original file line number Diff line number Diff line change
Expand Up @@ -54,17 +54,13 @@ class QdrantVectorSearchTool(BaseTool):
qdrant_api_key: Authentication key for Qdrant
"""

model_config: ClassVar[dict[str, bool]] = {
"arbitrary_types_allowed": True
} # Add ClassVar annotation
model_config: ClassVar[dict[str, bool]] = {"arbitrary_types_allowed": True} # Add ClassVar annotation
client: QdrantClient = None
async_client: AsyncQdrantClient = None
openai_client: Any = None # Added for lazy initialization
openai_async_client: Any = None # Added for lazy initialization
name: str = "QdrantVectorSearchTool"
description: str = (
"A tool to search the Qdrant database for relevant information on internal documents."
)
description: str = "A tool to search the Qdrant database for relevant information on internal documents."
args_schema: type[BaseModel] = QdrantToolSchema
query: str | None = None
filter_by: str | None = None
Expand Down Expand Up @@ -146,11 +142,7 @@ def _run(
# Create filter if filter parameters are provided
search_filter = None
if filter_by and filter_value:
search_filter = Filter(
must=[
FieldCondition(key=filter_by, match=MatchValue(value=filter_value))
]
)
search_filter = Filter(must=[FieldCondition(key=filter_by, match=MatchValue(value=filter_value))])

# Search in Qdrant using the built-in query method
query_vector = (
Expand Down Expand Up @@ -192,9 +184,7 @@ def _vectorize_query_sync(self, query: str, embedding_model: str) -> list[float]
from openai import Client

# Define error messages as constants
openai_api_key_not_set_error_msg = (
"OPENAI_API_KEY environment variable is not set."
)
openai_api_key_not_set_error_msg = "OPENAI_API_KEY environment variable is not set."
# Lazy initialization of the sync client
if not self.openai_client:
api_key = os.getenv("OPENAI_API_KEY")
Expand Down Expand Up @@ -240,17 +230,11 @@ async def _arun(
# Create filter if filter parameters are provided
search_filter = None
if filter_by and filter_value:
search_filter = Filter(
must=[
FieldCondition(key=filter_by, match=MatchValue(value=filter_value))
]
)
search_filter = Filter(must=[FieldCondition(key=filter_by, match=MatchValue(value=filter_value))])

# Search in Qdrant using the built-in query method
query_vector = (
await self._vectorize_query_async(
query, embedding_model="text-embedding-3-large"
)
await self._vectorize_query_async(query, embedding_model="text-embedding-3-large")
if not self.custom_embedding_fn
else self.custom_embedding_fn(query)
)
Expand All @@ -275,9 +259,7 @@ async def _arun(

return json.dumps(results, indent=2)

async def _vectorize_query_async(
self, query: str, embedding_model: str
) -> list[float]:
async def _vectorize_query_async(self, query: str, embedding_model: str) -> list[float]:
"""Default async vectorization function with openai.

Args:
Expand All @@ -290,9 +272,7 @@ async def _vectorize_query_async(
from openai import AsyncClient

# Define error messages as constants
openai_api_key_not_set_error_msg = (
"OPENAI_API_KEY environment variable is not set."
)
openai_api_key_not_set_error_msg = "OPENAI_API_KEY environment variable is not set."
# Lazy initialization of the async client
if not self.openai_async_client:
api_key = os.getenv("OPENAI_API_KEY")
Expand Down
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