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@@ -1,11 +1,13 @@
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-from typing import Dict, Any, Optional, List, Tuple, Union
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+from typing import Dict, Any, Optional, List, Tuple, Union, cast
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from langchain.callbacks.manager import CallbackManagerForLLMRun
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from langchain.chat_models import AzureChatOpenAI
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from langchain.chat_models.openai import _convert_dict_to_message
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-from langchain.schema import ChatResult, BaseMessage, ChatGeneration
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from pydantic import root_validator
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+from langchain.schema import ChatResult, BaseMessage, ChatGeneration, ChatMessage, HumanMessage, AIMessage, SystemMessage, FunctionMessage
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+from core.model_providers.models.entity.message import LCHumanMessageWithFiles, PromptMessageFileType, ImagePromptMessageFile
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+
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class EnhanceAzureChatOpenAI(AzureChatOpenAI):
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request_timeout: Optional[Union[float, Tuple[float, float]]] = (5.0, 300.0)
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@@ -51,13 +53,18 @@ class EnhanceAzureChatOpenAI(AzureChatOpenAI):
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}
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def _generate(
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- self,
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- messages: List[BaseMessage],
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- stop: Optional[List[str]] = None,
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- run_manager: Optional[CallbackManagerForLLMRun] = None,
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- **kwargs: Any,
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+ self,
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+ messages: List[BaseMessage],
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+ stop: Optional[List[str]] = None,
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+ run_manager: Optional[CallbackManagerForLLMRun] = None,
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+ **kwargs: Any,
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) -> ChatResult:
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- message_dicts, params = self._create_message_dicts(messages, stop)
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+ params = self._client_params
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+ if stop is not None:
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+ if "stop" in params:
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+ raise ValueError("`stop` found in both the input and default params.")
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+ params["stop"] = stop
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+ message_dicts = [self._convert_message_to_dict(m) for m in messages]
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params = {**params, **kwargs}
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if self.streaming:
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inner_completion = ""
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@@ -65,7 +72,7 @@ class EnhanceAzureChatOpenAI(AzureChatOpenAI):
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params["stream"] = True
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function_call: Optional[dict] = None
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for stream_resp in self.completion_with_retry(
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- messages=message_dicts, **params
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+ messages=message_dicts, **params
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):
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if len(stream_resp["choices"]) > 0:
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role = stream_resp["choices"][0]["delta"].get("role", role)
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@@ -88,4 +95,47 @@ class EnhanceAzureChatOpenAI(AzureChatOpenAI):
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)
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return ChatResult(generations=[ChatGeneration(message=message)])
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response = self.completion_with_retry(messages=message_dicts, **params)
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- return self._create_chat_result(response)
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+ return self._create_chat_result(response)
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+
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+ def _convert_message_to_dict(self, message: BaseMessage) -> dict:
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+ if isinstance(message, ChatMessage):
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+ message_dict = {"role": message.role, "content": message.content}
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+ elif isinstance(message, LCHumanMessageWithFiles):
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+ content = [
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+ {
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+ "type": "text",
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+ "text": message.content
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+ }
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+ ]
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+
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+ for file in message.files:
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+ if file.type == PromptMessageFileType.IMAGE:
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+ file = cast(ImagePromptMessageFile, file)
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+ content.append({
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+ "type": "image_url",
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+ "image_url": {
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+ "url": file.data,
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+ "detail": file.detail.value
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+ }
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+ })
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+
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+ message_dict = {"role": "user", "content": content}
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+ elif isinstance(message, HumanMessage):
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+ message_dict = {"role": "user", "content": message.content}
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+ elif isinstance(message, AIMessage):
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+ message_dict = {"role": "assistant", "content": message.content}
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+ if "function_call" in message.additional_kwargs:
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+ message_dict["function_call"] = message.additional_kwargs["function_call"]
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+ elif isinstance(message, SystemMessage):
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+ message_dict = {"role": "system", "content": message.content}
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+ elif isinstance(message, FunctionMessage):
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+ message_dict = {
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+ "role": "function",
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+ "content": message.content,
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+ "name": message.name,
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+ }
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+ else:
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+ raise ValueError(f"Got unknown type {message}")
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+ if "name" in message.additional_kwargs:
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+ message_dict["name"] = message.additional_kwargs["name"]
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+ return message_dict
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Charlie.Wei