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Change list[str] -> str for vectordbs (#1388)

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This commit is contained in:
Anu
2024-06-07 10:15:40 -06:00
committed by GitHub
parent fd07513004
commit e0d0f6e94c
11 changed files with 27 additions and 27 deletions
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6
embedchain/vectordb/chroma.py
View File

@@ -183,7 +183,7 @@ class ChromaDB(BaseVectorDB):
def query(
self,
input_query: list[str],
input_query: str,
n_results: int,
where: Optional[dict[str, any]] = None,
raw_filter: Optional[dict[str, any]] = None,
@@ -193,8 +193,8 @@ class ChromaDB(BaseVectorDB):
"""
Query contents from vector database based on vector similarity
:param input_query: list of query string
:type input_query: list[str]
:param input_query: query string
:type input_query: str
:param n_results: no of similar documents to fetch from database
:type n_results: int
:param where: to filter data

8
embedchain/vectordb/elasticsearch.py
View File

@@ -163,7 +163,7 @@ class ElasticsearchDB(BaseVectorDB):
def query(
self,
input_query: list[str],
input_query: str,
n_results: int,
where: dict[str, any],
citations: bool = False,
@@ -172,8 +172,8 @@ class ElasticsearchDB(BaseVectorDB):
"""
query contents from vector database based on vector similarity
:param input_query: list of query string
:type input_query: list[str]
:param input_query: query string
:type input_query: str
:param n_results: no of similar documents to fetch from database
:type n_results: int
:param where: Optional. to filter data
@@ -185,7 +185,7 @@ class ElasticsearchDB(BaseVectorDB):
along with url of the source and doc_id (if citations flag is true)
:rtype: list[str], if citations=False, otherwise list[tuple[str, str, str]]
"""
input_query_vector = self.embedder.embedding_fn(input_query)
input_query_vector = self.embedder.embedding_fn([input_query])
query_vector = input_query_vector[0]
# `https://www.elastic.co/guide/en/elasticsearch/reference/7.17/query-dsl-script-score-query.html`

6
embedchain/vectordb/opensearch.py
View File

@@ -146,7 +146,7 @@ class OpenSearchDB(BaseVectorDB):
def query(
self,
input_query: list[str],
input_query: str,
n_results: int,
where: dict[str, any],
citations: bool = False,
@@ -155,8 +155,8 @@ class OpenSearchDB(BaseVectorDB):
"""
query contents from vector database based on vector similarity
:param input_query: list of query string
:type input_query: list[str]
:param input_query: query string
:type input_query: str
:param n_results: no of similar documents to fetch from database
:type n_results: int
:param where: Optional. to filter data

4
embedchain/vectordb/pinecone.py
View File

@@ -150,7 +150,7 @@ class PineconeDB(BaseVectorDB):
def query(
self,
input_query: list[str],
input_query: str,
n_results: int,
where: Optional[dict[str, any]] = None,
raw_filter: Optional[dict[str, any]] = None,
@@ -162,7 +162,7 @@ class PineconeDB(BaseVectorDB):
Query contents from vector database based on vector similarity.
Args:
input_query (list[str]): List of query strings.
input_query (str): query string.
n_results (int): Number of similar documents to fetch from the database.
where (dict[str, any], optional): Filter criteria for the search.
raw_filter (dict[str, any], optional): Advanced raw filter criteria for the search.

6
embedchain/vectordb/qdrant.py
View File

@@ -161,7 +161,7 @@ class QdrantDB(BaseVectorDB):
def query(
self,
input_query: list[str],
input_query: str,
n_results: int,
where: dict[str, any],
citations: bool = False,
@@ -169,8 +169,8 @@ class QdrantDB(BaseVectorDB):
) -> Union[list[tuple[str, dict]], list[str]]:
"""
query contents from vector database based on vector similarity
:param input_query: list of query string
:type input_query: list[str]
:param input_query: query string
:type input_query: str
:param n_results: no of similar documents to fetch from database
:type n_results: int
:param where: Optional. to filter data

6
embedchain/vectordb/weaviate.py
View File

@@ -219,12 +219,12 @@ class WeaviateDB(BaseVectorDB):
)
def query(
self, input_query: list[str], n_results: int, where: dict[str, any], citations: bool = False
self, input_query: str, n_results: int, where: dict[str, any], citations: bool = False
) -> Union[list[tuple[str, dict]], list[str]]:
"""
query contents from vector database based on vector similarity
:param input_query: list of query string
:type input_query: list[str]
:param input_query: query string
:type input_query: str
:param n_results: no of similar documents to fetch from database
:type n_results: int
:param where: Optional. to filter data

6
embedchain/vectordb/zilliz.py
View File

@@ -138,7 +138,7 @@ class ZillizVectorDB(BaseVectorDB):
def query(
self,
input_query: list[str],
input_query: str,
n_results: int,
where: dict[str, Any],
citations: bool = False,
@@ -147,8 +147,8 @@ class ZillizVectorDB(BaseVectorDB):
"""
Query contents from vector database based on vector similarity
:param input_query: list of query string
:type input_query: list[str]
:param input_query: query string
:type input_query: str
:param n_results: no of similar documents to fetch from database
:type n_results: int
:param where: to filter data