fix: azure embeddings models with fixed dimensions fail (#2619)

* fix: azure embeddings models with fixed dimensions fail

* [autofix.ci] apply automated fixes

---------

Co-authored-by: autofix-ci[bot] <114827586+autofix-ci[bot]@users.noreply.github.com>
This commit is contained in:
Nicolò Boschi 2024-07-10 13:53:23 +02:00 committed by GitHub
commit 9c41b0c895
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2 changed files with 10 additions and 9 deletions

View file

@ -1,5 +1,4 @@
from langchain_openai import AzureOpenAIEmbeddings
from pydantic.v1 import SecretStr
from langflow.base.models.model import LCModelComponent
from langflow.field_typing import Embeddings
@ -59,20 +58,15 @@ class AzureOpenAIEmbeddingsComponent(LCModelComponent):
]
def build_embeddings(self) -> Embeddings:
if not self.api_key:
raise ValueError("API Key is required")
azure_api_key = SecretStr(self.api_key)
try:
embeddings = AzureOpenAIEmbeddings(
azure_endpoint=self.azure_endpoint,
azure_deployment=self.azure_deployment,
api_version=self.api_version,
api_key=azure_api_key,
dimensions=self.dimensions,
api_key=self.api_key,
dimensions=self.dimensions or None,
)
except Exception as e:
raise ValueError("Could not connect to AzureOpenAIEmbeddings API.") from e
raise ValueError(f"Could not connect to AzureOpenAIEmbeddings API: {str(e)}") from e
return embeddings

View file

@ -66,6 +66,12 @@ class OpenAIEmbeddingsComponent(LCEmbeddingsModel):
value=True,
info="If False, you must have transformers installed.",
),
IntInput(
name="dimensions",
display_name="Dimensions",
info="The number of dimensions the resulting output embeddings should have. Only supported by certain models.",
advanced=True,
),
]
def build_embeddings(self) -> Embeddings:
@ -91,4 +97,5 @@ class OpenAIEmbeddingsComponent(LCEmbeddingsModel):
show_progress_bar=self.show_progress_bar,
skip_empty=self.skip_empty,
tiktoken_model_name=self.tiktoken_model_name,
dimensions=self.dimensions or None,
)