mirror of
https://github.com/hwchase17/langchain
synced 2024-11-06 03:20:49 +00:00
256 lines
8.3 KiB
Python
256 lines
8.3 KiB
Python
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import json
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import logging
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from typing import Any, Dict, Iterator, List, Mapping, Optional, Union
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import requests
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from langchain_core.callbacks import CallbackManagerForLLMRun
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from langchain_core.language_models.chat_models import (
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BaseChatModel,
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generate_from_stream,
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)
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from langchain_core.messages import (
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AIMessage,
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AIMessageChunk,
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BaseMessage,
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BaseMessageChunk,
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ChatMessage,
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ChatMessageChunk,
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HumanMessage,
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HumanMessageChunk,
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)
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from langchain_core.outputs import ChatGeneration, ChatGenerationChunk, ChatResult
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from langchain_core.pydantic_v1 import Field, SecretStr, root_validator
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from langchain_core.utils import (
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convert_to_secret_str,
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get_from_dict_or_env,
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)
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logger = logging.getLogger(__name__)
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DEFAULT_API_BASE = "https://api.coze.com"
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def _convert_message_to_dict(message: BaseMessage) -> dict:
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message_dict: Dict[str, Any]
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if isinstance(message, HumanMessage):
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message_dict = {
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"role": "user",
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"content": message.content,
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"content_type": "text",
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}
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else:
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message_dict = {
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"role": "assistant",
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"content": message.content,
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"content_type": "text",
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}
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return message_dict
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def _convert_dict_to_message(_dict: Mapping[str, Any]) -> Union[BaseMessage, None]:
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msg_type = _dict["type"]
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if msg_type != "answer":
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return None
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role = _dict["role"]
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if role == "user":
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return HumanMessage(content=_dict["content"])
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elif role == "assistant":
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return AIMessage(content=_dict.get("content", "") or "")
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else:
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return ChatMessage(content=_dict["content"], role=role)
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def _convert_delta_to_message_chunk(_dict: Mapping[str, Any]) -> BaseMessageChunk:
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role = _dict.get("role")
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content = _dict.get("content") or ""
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if role == "user":
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return HumanMessageChunk(content=content)
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elif role == "assistant":
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return AIMessageChunk(content=content)
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else:
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return ChatMessageChunk(content=content, role=role)
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class ChatCoze(BaseChatModel):
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"""ChatCoze chat models API by coze.com
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For more information, see https://www.coze.com/open/docs/chat
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"""
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@property
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def lc_secrets(self) -> Dict[str, str]:
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return {
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"coze_api_key": "COZE_API_KEY",
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}
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@property
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def lc_serializable(self) -> bool:
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return True
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coze_api_base: str = Field(default=DEFAULT_API_BASE)
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"""Coze custom endpoints"""
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coze_api_key: Optional[SecretStr] = None
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"""Coze API Key"""
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request_timeout: int = Field(default=60, alias="timeout")
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"""request timeout for chat http requests"""
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bot_id: str = Field(default="")
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"""The ID of the bot that the API interacts with."""
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conversation_id: str = Field(default="")
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"""Indicate which conversation the dialog is taking place in. If there is no need to
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distinguish the context of the conversation(just a question and answer), skip this
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parameter. It will be generated by the system."""
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user: str = Field(default="")
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"""The user who calls the API to chat with the bot."""
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streaming: bool = False
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"""Whether to stream the response to the client.
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false: if no value is specified or set to false, a non-streaming response is
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returned. "Non-streaming response" means that all responses will be returned at once
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after they are all ready, and the client does not need to concatenate the content.
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true: set to true, partial message deltas will be sent .
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"Streaming response" will provide real-time response of the model to the client, and
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the client needs to assemble the final reply based on the type of message. """
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class Config:
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"""Configuration for this pydantic object."""
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allow_population_by_field_name = True
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@root_validator()
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def validate_environment(cls, values: Dict) -> Dict:
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values["coze_api_base"] = get_from_dict_or_env(
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values,
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"coze_api_base",
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"COZE_API_BASE",
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DEFAULT_API_BASE,
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)
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values["coze_api_key"] = convert_to_secret_str(
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get_from_dict_or_env(
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values,
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"coze_api_key",
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"COZE_API_KEY",
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)
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)
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return values
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@property
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def _default_params(self) -> Dict[str, Any]:
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"""Get the default parameters for calling Coze API."""
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return {
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"bot_id": self.bot_id,
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"conversation_id": self.conversation_id,
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"user": self.user,
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"streaming": self.streaming,
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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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) -> ChatResult:
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if self.streaming:
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stream_iter = self._stream(
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messages=messages, stop=stop, run_manager=run_manager, **kwargs
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)
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return generate_from_stream(stream_iter)
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r = self._chat(messages, **kwargs)
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res = r.json()
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if res["code"] != 0:
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raise ValueError(
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f"Error from Coze api response: {res['code']}: {res['msg']}, "
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f"logid: {r.headers.get('X-Tt-Logid')}"
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)
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return self._create_chat_result(res.get("messages") or [])
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def _stream(
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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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) -> Iterator[ChatGenerationChunk]:
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res = self._chat(messages, **kwargs)
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for chunk in res.iter_lines():
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chunk = chunk.decode("utf-8").strip("\r\n")
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parts = chunk.split("data:", 1)
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chunk = parts[1] if len(parts) > 1 else None
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if chunk is None:
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continue
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response = json.loads(chunk)
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if response["event"] == "done":
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break
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elif (
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response["event"] != "message"
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or response["message"]["type"] != "answer"
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):
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continue
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chunk = _convert_delta_to_message_chunk(response["message"])
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cg_chunk = ChatGenerationChunk(message=chunk)
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if run_manager:
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run_manager.on_llm_new_token(chunk.content, chunk=cg_chunk)
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yield cg_chunk
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def _chat(self, messages: List[BaseMessage], **kwargs: Any) -> requests.Response:
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parameters = {**self._default_params, **kwargs}
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query = ""
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chat_history = []
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for msg in messages:
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if isinstance(msg, HumanMessage):
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query = f"{msg.content}" # overwrite, to get last user message as query
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chat_history.append(_convert_message_to_dict(msg))
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conversation_id = parameters.pop("conversation_id")
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bot_id = parameters.pop("bot_id")
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user = parameters.pop("user")
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streaming = parameters.pop("streaming")
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payload = {
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"conversation_id": conversation_id,
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"bot_id": bot_id,
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"user": user,
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"query": query,
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"stream": streaming,
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}
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if chat_history:
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payload["chat_history"] = chat_history
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url = self.coze_api_base + "/open_api/v2/chat"
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api_key = ""
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if self.coze_api_key:
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api_key = self.coze_api_key.get_secret_value()
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res = requests.post(
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url=url,
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timeout=self.request_timeout,
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headers={
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"Content-Type": "application/json",
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"Authorization": f"Bearer {api_key}",
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},
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json=payload,
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stream=streaming,
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)
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if res.status_code != 200:
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logid = res.headers.get("X-Tt-Logid")
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raise ValueError(f"Error from Coze api response: {res}, logid: {logid}")
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return res
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def _create_chat_result(self, messages: List[Mapping[str, Any]]) -> ChatResult:
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generations = []
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for c in messages:
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msg = _convert_dict_to_message(c)
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if msg:
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generations.append(ChatGeneration(message=msg))
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llm_output = {"token_usage": "", "model": ""}
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return ChatResult(generations=generations, llm_output=llm_output)
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@property
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def _llm_type(self) -> str:
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return "coze-chat"
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