Use new Langchain's dedicated Azure OpenAI embedding class (#76)
* Use new Langchain's dedicated Azure OpenAI embedding class * Update test
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@ -1,4 +1,4 @@
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from langchain.embeddings import OpenAIEmbeddings as LCOpenAIEmbeddings
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from langchain import embeddings as lcembeddings
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from .base import LangchainEmbeddings
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@ -9,23 +9,13 @@ class OpenAIEmbeddings(LangchainEmbeddings):
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This method is wrapped around the Langchain OpenAIEmbeddings class.
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"""
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_lc_class = LCOpenAIEmbeddings
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_lc_class = lcembeddings.OpenAIEmbeddings
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class AzureOpenAIEmbeddings(LangchainEmbeddings):
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"""Azure OpenAI embeddings.
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This method is wrapped around the Langchain OpenAIEmbeddings class.
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This method is wrapped around the Langchain AzureOpenAIEmbeddings class.
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"""
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_lc_class = LCOpenAIEmbeddings
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def __init__(self, **params):
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params["openai_api_type"] = "azure"
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# openai.error.InvalidRequestError: Too many inputs. The max number of
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# inputs is 16. We hope to increase the number of inputs per request
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# soon. Please contact us through an Azure support request at:
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# https://go.microsoft.com/fwlink/?linkid=2213926 for further questions.
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params["chunk_size"] = 16
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super().__init__(**params)
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_lc_class = lcembeddings.AzureOpenAIEmbeddings
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@ -21,7 +21,7 @@ def test_azureopenai_embeddings_raw(openai_embedding_call):
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model = AzureOpenAIEmbeddings(
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model="text-embedding-ada-002",
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deployment="embedding-deployment",
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openai_api_base="https://test.openai.azure.com/",
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azure_endpoint="https://test.openai.azure.com/",
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openai_api_key="some-key",
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)
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output = model("Hello world")
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@ -39,7 +39,7 @@ def test_azureopenai_embeddings_batch_raw(openai_embedding_call):
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model = AzureOpenAIEmbeddings(
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model="text-embedding-ada-002",
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deployment="embedding-deployment",
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openai_api_base="https://test.openai.azure.com/",
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azure_endpoint="https://test.openai.azure.com/",
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openai_api_key="some-key",
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)
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output = model(["Hello world", "Goodbye world"])
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