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openai[patch]: fix azure embedding length check (#19870)

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Erick Friis 2024-04-01 10:26:15 -07:00 committed by GitHub
parent d62e84c4f5
commit be92cf57ca
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2 changed files with 20 additions and 9 deletions
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25
libs/partners/openai/langchain_openai/embeddings/azure.py
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@ -1,4 +1,5 @@
"""Azure OpenAI embeddings wrapper.""" """Azure OpenAI embeddings wrapper."""
from __future__ import annotations from __future__ import annotations
import os import os
@ -57,6 +58,8 @@ class AzureOpenAIEmbeddings(OpenAIEmbeddings):
openai_api_version: Optional[str] = Field(default=None, alias="api_version") openai_api_version: Optional[str] = Field(default=None, alias="api_version")
"""Automatically inferred from env var `OPENAI_API_VERSION` if not provided.""" """Automatically inferred from env var `OPENAI_API_VERSION` if not provided."""
validate_base_url: bool = True validate_base_url: bool = True
chunk_size: int = 2048
"""Maximum number of texts to embed in each batch"""
@root_validator() @root_validator()
def validate_environment(cls, values: Dict) -> Dict: def validate_environment(cls, values: Dict) -> Dict:
@ -102,7 +105,11 @@ class AzureOpenAIEmbeddings(OpenAIEmbeddings):
# Azure OpenAI embedding models allow a maximum of 2048 texts # Azure OpenAI embedding models allow a maximum of 2048 texts
# at a time in each batch # at a time in each batch
# See: https://learn.microsoft.com/en-us/azure/ai-services/openai/how-to/embeddings?tabs=console#best-practices # See: https://learn.microsoft.com/en-us/azure/ai-services/openai/how-to/embeddings?tabs=console#best-practices
values["chunk_size"] = min(values["chunk_size"], 2048) if values["chunk_size"] > 2048:
raise ValueError(
"Azure OpenAI embeddings only allow a maximum of 2048 texts at a time "
"in each batch."
)
# For backwards compatibility. Before openai v1, no distinction was made # For backwards compatibility. Before openai v1, no distinction was made
# between azure_endpoint and base_url (openai_api_base). # between azure_endpoint and base_url (openai_api_base).
openai_api_base = values["openai_api_base"] openai_api_base = values["openai_api_base"]
@ -126,12 +133,16 @@ class AzureOpenAIEmbeddings(OpenAIEmbeddings):
"api_version": values["openai_api_version"], "api_version": values["openai_api_version"],
"azure_endpoint": values["azure_endpoint"], "azure_endpoint": values["azure_endpoint"],
"azure_deployment": values["deployment"], "azure_deployment": values["deployment"],
"api_key": values["openai_api_key"].get_secret_value() "api_key": (
if values["openai_api_key"] values["openai_api_key"].get_secret_value()
else None, if values["openai_api_key"]
"azure_ad_token": values["azure_ad_token"].get_secret_value() else None
if values["azure_ad_token"] ),
else None, "azure_ad_token": (
values["azure_ad_token"].get_secret_value()
if values["azure_ad_token"]
else None
),
"azure_ad_token_provider": values["azure_ad_token_provider"], "azure_ad_token_provider": values["azure_ad_token_provider"],
"organization": values["openai_organization"], "organization": values["openai_organization"],
"base_url": values["openai_api_base"], "base_url": values["openai_api_base"],

4
libs/partners/openai/tests/integration_tests/embeddings/test_azure.py
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@ -60,8 +60,8 @@ def test_azure_openai_embedding_documents_chunk_size() -> None:
embedding = _get_embeddings() embedding = _get_embeddings()
embedding.embedding_ctx_length = 8191 embedding.embedding_ctx_length = 8191
output = embedding.embed_documents(documents) output = embedding.embed_documents(documents)
# Max 16 chunks per batch on Azure OpenAI embeddings # Max 2048 chunks per batch on Azure OpenAI embeddings
assert embedding.chunk_size == 16 assert embedding.chunk_size == 2048
assert len(output) == 20 assert len(output) == 20
assert all([len(out) == 1536 for out in output]) assert all([len(out) == 1536 for out in output])