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Migrate to OpenAI Python library >= 1.0
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parent
a57d529f39
commit
7009793170
4 changed files with 16 additions and 15 deletions
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@ -42,7 +42,7 @@ dependencies = [
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"fastapi >= 0.104.1",
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"fastapi >= 0.104.1",
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"python-multipart >= 0.0.5",
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"python-multipart >= 0.0.5",
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"jinja2 == 3.1.2",
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"jinja2 == 3.1.2",
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"openai >= 0.27.0, < 1.0.0",
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"openai >= 1.0.0",
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"tiktoken >= 0.3.2",
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"tiktoken >= 0.3.2",
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"tenacity >= 8.2.2",
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"tenacity >= 8.2.2",
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"pillow ~= 9.5.0",
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"pillow ~= 9.5.0",
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@ -36,11 +36,11 @@ class StreamingChatCallbackHandler(StreamingStdOutCallbackHandler):
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@retry(
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@retry(
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retry=(
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retry=(
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retry_if_exception_type(openai.error.Timeout)
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retry_if_exception_type(openai._exceptions.APITimeoutError)
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| retry_if_exception_type(openai.error.APIError)
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| retry_if_exception_type(openai._exceptions.APIError)
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| retry_if_exception_type(openai.error.APIConnectionError)
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| retry_if_exception_type(openai._exceptions.APIConnectionError)
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| retry_if_exception_type(openai.error.RateLimitError)
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| retry_if_exception_type(openai._exceptions.RateLimitError)
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| retry_if_exception_type(openai.error.ServiceUnavailableError)
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| retry_if_exception_type(openai._exceptions.APIStatusError)
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),
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),
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wait=wait_random_exponential(min=1, max=10),
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wait=wait_random_exponential(min=1, max=10),
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stop=stop_after_attempt(3),
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stop=stop_after_attempt(3),
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@ -57,11 +57,11 @@ def completion_with_backoff(**kwargs):
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@retry(
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@retry(
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retry=(
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retry=(
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retry_if_exception_type(openai.error.Timeout)
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retry_if_exception_type(openai._exceptions.APITimeoutError)
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| retry_if_exception_type(openai.error.APIError)
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| retry_if_exception_type(openai._exceptions.APIError)
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| retry_if_exception_type(openai.error.APIConnectionError)
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| retry_if_exception_type(openai._exceptions.APIConnectionError)
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| retry_if_exception_type(openai.error.RateLimitError)
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| retry_if_exception_type(openai._exceptions.RateLimitError)
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| retry_if_exception_type(openai.error.ServiceUnavailableError)
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| retry_if_exception_type(openai._exceptions.APIStatusError)
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),
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),
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wait=wait_exponential(multiplier=1, min=4, max=10),
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wait=wait_exponential(multiplier=1, min=4, max=10),
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stop=stop_after_attempt(3),
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stop=stop_after_attempt(3),
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@ -3,7 +3,7 @@ from io import BufferedReader
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# External Packages
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# External Packages
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from asgiref.sync import sync_to_async
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from asgiref.sync import sync_to_async
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import openai
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from openai import OpenAI
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async def transcribe_audio(audio_file: BufferedReader, model, api_key) -> str:
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async def transcribe_audio(audio_file: BufferedReader, model, api_key) -> str:
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@ -11,5 +11,6 @@ async def transcribe_audio(audio_file: BufferedReader, model, api_key) -> str:
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Transcribe audio file using Whisper model via OpenAI's API
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Transcribe audio file using Whisper model via OpenAI's API
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"""
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"""
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# Send the audio data to the Whisper API
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# Send the audio data to the Whisper API
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response = await sync_to_async(openai.Audio.translate)(model=model, file=audio_file, api_key=api_key)
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client = OpenAI(api_key=api_key)
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response = await sync_to_async(client.audio.translations.create)(model=model, file=audio_file)
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return response["text"]
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return response["text"]
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@ -32,7 +32,7 @@ class OpenAI(BaseEncoder):
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raise Exception(
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raise Exception(
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f"Set OpenAI API key under processor-config > conversation > openai-api-key in config file: {state.config_file}"
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f"Set OpenAI API key under processor-config > conversation > openai-api-key in config file: {state.config_file}"
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)
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)
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openai.api_key = state.processor_config.conversation.openai_model.api_key
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self.openai_client = openai.OpenAI(api_key=state.processor_config.conversation.openai_model.api_key)
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self.embedding_dimensions = None
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self.embedding_dimensions = None
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def encode(self, entries, device=None, **kwargs):
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def encode(self, entries, device=None, **kwargs):
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@ -43,7 +43,7 @@ class OpenAI(BaseEncoder):
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processed_entry = entries[index].replace("\n", " ")
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processed_entry = entries[index].replace("\n", " ")
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try:
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try:
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response = openai.Embedding.create(input=processed_entry, model=self.model_name)
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response = self.openai_client.embeddings.create(input=processed_entry, model=self.model_name)
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embedding_tensors += [torch.tensor(response.data[0].embedding, device=device)]
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embedding_tensors += [torch.tensor(response.data[0].embedding, device=device)]
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# Use current models embedding dimension, once available
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# Use current models embedding dimension, once available
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# Else default to embedding dimensions of the text-embedding-ada-002 model
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# Else default to embedding dimensions of the text-embedding-ada-002 model
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