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