codefuse-chatbot/coagent/llm_models/openai_model.py

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import os
from typing import Union, Optional, List
from loguru import logger
from langchain.callbacks import AsyncIteratorCallbackHandler
from langchain.chat_models import ChatOpenAI
from langchain.llms.base import LLM
from .llm_config import LLMConfig
# from configs.model_config import (llm_model_dict, LLM_MODEL)
class CustomLLMModel:
def __init__(self, llm: LLM):
self.llm: LLM = llm
def __call__(self, prompt: str,
stop: Optional[List[str]] = None):
return self.llm(prompt, stop)
def _call(self, prompt: str,
stop: Optional[List[str]] = None):
return self.llm(prompt, stop)
def predict(self, prompt: str,
stop: Optional[List[str]] = None):
return self.llm(prompt, stop)
def batch(self, prompts: str,
stop: Optional[List[str]] = None):
return [self.llm(prompt, stop) for prompt in prompts]
def getChatModelFromConfig(llm_config: LLMConfig, callBack: AsyncIteratorCallbackHandler = None, ) -> Union[ChatOpenAI, LLM]:
# logger.debug(f"llm type is {type(llm_config.llm)}")
if llm_config is None:
model = ChatOpenAI(
streaming=True,
verbose=True,
openai_api_key=os.environ.get("api_key"),
openai_api_base=os.environ.get("api_base_url"),
model_name=os.environ.get("LLM_MODEL", "gpt-3.5-turbo"),
temperature=os.environ.get("temperature", 0.5),
stop=os.environ.get("stop", ""),
)
return model
if llm_config and llm_config.llm and isinstance(llm_config.llm, LLM):
return CustomLLMModel(llm=llm_config.llm)
if callBack is None:
model = ChatOpenAI(
streaming=True,
verbose=True,
openai_api_key=llm_config.api_key,
openai_api_base=llm_config.api_base_url,
model_name=llm_config.model_name,
temperature=llm_config.temperature,
stop=llm_config.stop
)
else:
model = ChatOpenAI(
streaming=True,
verbose=True,
callBack=[callBack],
openai_api_key=llm_config.api_key,
openai_api_base=llm_config.api_base_url,
model_name=llm_config.model_name,
temperature=llm_config.temperature,
stop=llm_config.stop
)
return model
import json, requests
def getExtraModel():
return TestModel()
class TestModel:
def predict(self, request_body):
headers = {"Content-Type":"application/json;charset=UTF-8",
"codegpt_user":"",
"codegpt_token":""
}
xxx = requests.post(
'https://codegencore.alipay.com/api/chat/CODE_LLAMA_INT4/completion',
data=json.dumps(request_body,ensure_ascii=False).encode('utf-8'),
headers=headers)
return xxx.json()["data"]