github/langchain
1
0
Fork 0
mirror of https://github.com/hwchase17/langchain.git synced 2025-07-16 17:53:37 +00:00
Code Issues Packages Projects Releases Wiki Activity

community[patch]: Kinetica Integrations handled error in querying; quotes in table names; updated gpudb API (#22724)

Browse Source 
- [ ] **Miscellaneous updates and fixes**: 
- **Description:** Handled error in querying; quotes in table names;
updated gpudb API
- **Issue:** Threw an error with an error message difficult to
understand if a query failed or returned no records
    - **Dependencies:** Updated GPUDB API version to `7.2.0.9`


@baskaryan @hwchase17
This commit is contained in:
am-kinetica 2024-06-11 19:31:26 +05:30 committed by GitHub
parent 27b9ea14a5
commit ad101adec8
No known key found for this signature in database
GPG Key ID: B5690EEEBB952194
6 changed files with 42 additions and 17 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

6
docs/docs/integrations/document_loaders/kinetica.ipynb
View File

@ -15,7 +15,7 @@
"metadata": {},
"outputs": [],
"source": [
"%pip install gpudb==7.2.0.1"
"%pip install gpudb==7.2.0.9"
]
},
{
@ -97,14 +97,14 @@
"# data and the `SCHEMA.TABLE` combination must exist in Kinetica.\n",
"\n",
"QUERY = \"select text, survey_id as source from SCHEMA.TABLE limit 10\"\n",
"snowflake_loader = KineticaLoader(\n",
"kl = KineticaLoader(\n",
" query=QUERY,\n",
" host=HOST,\n",
" username=USERNAME,\n",
" password=PASSWORD,\n",
" metadata_columns=[\"source\"],\n",
")\n",
"kinetica_documents = snowflake_loader.load()\n",
"kinetica_documents = kl.load()\n",
"print(kinetica_documents)"
]
}

2
docs/docs/integrations/retrievers/kinetica.ipynb
View File

@ -22,7 +22,7 @@
"outputs": [],
"source": [
"# Please ensure that this connector is installed in your working environment.\n",
"%pip install gpudb==7.2.0.1"
"%pip install gpudb==7.2.0.9"
]
},
{

2
docs/docs/integrations/vectorstores/kinetica.ipynb
View File

@ -61,7 +61,7 @@
"source": [
"# Pip install necessary package\n",
"%pip install --upgrade --quiet langchain-openai langchain-community\n",
"%pip install gpudb==7.2.0.1\n",
"%pip install gpudb==7.2.0.9\n",
"%pip install --upgrade --quiet tiktoken"
]
},

2
libs/community/langchain_community/document_loaders/kinetica_loader.py
View File

@ -49,7 +49,7 @@ class KineticaLoader(BaseLoader):
except ImportError:
raise ImportError(
"Could not import Kinetica python API. "
"Please install it with `pip install gpudb==7.2.0.1`."
"Please install it with `pip install gpudb==7.2.0.9`."
)
try:

44
libs/community/langchain_community/vectorstores/kinetica.py
View File

@ -168,7 +168,7 @@ class Kinetica(VectorStore):
except ImportError:
raise ImportError(
"Could not import Kinetica python API. "
"Please install it with `pip install gpudb==7.2.0.1`."
"Please install it with `pip install gpudb==7.2.0.9`."
)
self.dimensions = dimensions
@ -197,7 +197,7 @@ class Kinetica(VectorStore):
except ImportError:
raise ImportError(
"Could not import Kinetica python API. "
"Please install it with `pip install gpudb==7.2.0.1`."
"Please install it with `pip install gpudb==7.2.0.9`."
)
options = GPUdb.Options()
@ -224,6 +224,8 @@ class Kinetica(VectorStore):
distance_strategy: DistanceStrategy = DEFAULT_DISTANCE_STRATEGY,
pre_delete_collection: bool = False,
logger: Optional[logging.Logger] = None,
*,
schema_name: str = _LANGCHAIN_DEFAULT_SCHEMA_NAME,
**kwargs: Any,
) -> Kinetica:
"""Class method to assist in constructing the `Kinetica` store instance
@ -239,8 +241,10 @@ class Kinetica(VectorStore):
with each text. Defaults to None.
ids (Optional[List[str]], optional): List of unique IDs (UUID by default)
associated with each text. Defaults to None.
collection_name (str, optional): Kinetica schema name.
collection_name (str, optional): Kinetica table name.
Defaults to _LANGCHAIN_DEFAULT_COLLECTION_NAME.
schema_name (str, optional): Kinetica schema name.
Defaults to _LANGCHAIN_DEFAULT_SCHEMA_NAME.
distance_strategy (DistanceStrategy, optional): Not used for now.
Defaults to DEFAULT_DISTANCE_STRATEGY.
pre_delete_collection (bool, optional): Whether to delete the Kinetica
@ -260,8 +264,8 @@ class Kinetica(VectorStore):
store = cls(
config=config,
collection_name=collection_name,
schema_name=schema_name,
embedding_function=embedding,
# dimensions=dimensions,
distance_strategy=distance_strategy,
pre_delete_collection=pre_delete_collection,
logger=logger,
@ -284,7 +288,7 @@ class Kinetica(VectorStore):
except ImportError:
raise ImportError(
"Could not import Kinetica python API. "
"Please install it with `pip install gpudb==7.2.0.1`."
"Please install it with `pip install gpudb==7.2.0.9`."
)
return GPUdbTable(
_type=self.table_schema,
@ -422,12 +426,17 @@ class Kinetica(VectorStore):
k: int = 4,
filter: Optional[dict] = None,
) -> List[Tuple[Document, float]]:
from gpudb import GPUdbException
resp: Dict = self.__query_collection(embedding, k, filter)
if resp and resp["status_info"]["status"] == "OK" and "records" in resp:
records: OrderedDict = resp["records"]
results = list(zip(*list(records.values())))
records: OrderedDict = resp["records"]
results = list(zip(*list(records.values())))
return self._results_to_docs_and_scores(results)
return self._results_to_docs_and_scores(results)
else:
self.logger.error(resp["status_info"]["message"])
raise GPUdbException(resp["status_info"]["message"])
def similarity_search_by_vector(
self,
@ -545,7 +554,7 @@ class Kinetica(VectorStore):
query_string = f"""
SELECT text, metadata, {dist_strategy}(embedding, '{embedding_str}')
as distance, embedding
FROM {self.table_name}
FROM "{self.schema_name}"."{self.collection_name}"
{where_clause}
ORDER BY distance asc NULLS LAST
LIMIT {k}
@ -760,6 +769,8 @@ class Kinetica(VectorStore):
distance_strategy: DistanceStrategy = DEFAULT_DISTANCE_STRATEGY,
ids: Optional[List[str]] = None,
pre_delete_collection: bool = False,
*,
schema_name: str = _LANGCHAIN_DEFAULT_SCHEMA_NAME,
**kwargs: Any,
) -> Kinetica:
"""Adds the texts passed in to the vector store and returns it
@ -773,6 +784,8 @@ class Kinetica(VectorStore):
config (KineticaSettings): a `KineticaSettings` instance
collection_name (str, optional): Kinetica schema name.
Defaults to _LANGCHAIN_DEFAULT_COLLECTION_NAME.
schema_name (str, optional): Kinetica schema name.
Defaults to _LANGCHAIN_DEFAULT_SCHEMA_NAME.
distance_strategy (DistanceStrategy, optional): Distance strategy
e.g., l2, cosine etc.. Defaults to DEFAULT_DISTANCE_STRATEGY.
ids (Optional[List[str]], optional): A list of UUIDs for each
@ -804,6 +817,7 @@ class Kinetica(VectorStore):
metadatas=metadatas,
ids=ids,
collection_name=collection_name,
schema_name=schema_name,
distance_strategy=distance_strategy,
pre_delete_collection=pre_delete_collection,
**kwargs,
@ -823,6 +837,8 @@ class Kinetica(VectorStore):
distance_strategy: DistanceStrategy = DEFAULT_DISTANCE_STRATEGY,
ids: Optional[List[str]] = None,
pre_delete_collection: bool = False,
*,
schema_name: str = _LANGCHAIN_DEFAULT_SCHEMA_NAME,
**kwargs: Any,
) -> Kinetica:
"""Adds the embeddings passed in to the vector store and returns it
@ -839,6 +855,8 @@ class Kinetica(VectorStore):
default will be used. Defaults to Dimension.OPENAI.
collection_name (str, optional): Kinetica schema name.
Defaults to _LANGCHAIN_DEFAULT_COLLECTION_NAME.
schema_name (str, optional): Kinetica schema name.
Defaults to _LANGCHAIN_DEFAULT_SCHEMA_NAME.
distance_strategy (DistanceStrategy, optional): Distance strategy
e.g., l2, cosine etc.. Defaults to DEFAULT_DISTANCE_STRATEGY.
ids (Optional[List[str]], optional): A list of UUIDs for each text/document.
@ -863,6 +881,7 @@ class Kinetica(VectorStore):
metadatas=metadatas,
ids=ids,
collection_name=collection_name,
schema_name=schema_name,
distance_strategy=distance_strategy,
pre_delete_collection=pre_delete_collection,
**kwargs,
@ -879,6 +898,8 @@ class Kinetica(VectorStore):
distance_strategy: DistanceStrategy = DEFAULT_DISTANCE_STRATEGY,
ids: Optional[List[str]] = None,
pre_delete_collection: bool = False,
*,
schema_name: str = _LANGCHAIN_DEFAULT_SCHEMA_NAME,
**kwargs: Any,
) -> Kinetica:
"""Adds the list of `Document` passed in to the vector store and returns it
@ -892,6 +913,8 @@ class Kinetica(VectorStore):
the texts/documents. Defaults to None.
collection_name (str, optional): Kinetica schema name.
Defaults to _LANGCHAIN_DEFAULT_COLLECTION_NAME.
schema_name (str, optional): Kinetica schema name.
Defaults to _LANGCHAIN_DEFAULT_SCHEMA_NAME.
distance_strategy (DistanceStrategy, optional): Distance strategy
e.g., l2, cosine etc.. Defaults to DEFAULT_DISTANCE_STRATEGY.
ids (Optional[List[str]], optional): A list of UUIDs for each text/document.
@ -912,6 +935,7 @@ class Kinetica(VectorStore):
metadatas=metadatas,
config=config,
collection_name=collection_name,
schema_name=schema_name,
distance_strategy=distance_strategy,
ids=ids,
pre_delete_collection=pre_delete_collection,

3
libs/community/tests/integration_tests/vectorstores/test_kinetica.py
View File

@ -46,7 +46,8 @@ def test_kinetica(create_config: KineticaSettings) -> None:
texts=texts,
metadatas=metadatas,
embedding=FakeEmbeddingsWithAdaDimension(),
collection_name="test_kinetica",
collection_name="1test_kinetica",
schema_name="1test",
pre_delete_collection=True,
)
output = docsearch.similarity_search("foo", k=1)