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feat(contentPlugin): 完成基本的内容函数调用功能
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RockChinQ
@@ -0,0 +1,182 @@
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import openai
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import json
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from .model import RequestBase
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from ..funcmgr import get_func_schema_list, execute_function, get_func, get_func_schema, ContentFunctionNotFoundError
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class ChatCompletionRequest(RequestBase):
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"""调用ChatCompletion接口的请求类。
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此类保证每一次返回的角色为assistant的信息的finish_reason一定为stop。
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若有函数调用响应，本类的返回瀑布是：函数调用请求->函数调用结果->...->assistant的信息->stop。
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"""
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model: str
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messages: list[dict[str, str]]
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kwargs: dict
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stopped: bool = False
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pending_func_call: dict = None
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pending_msg: str
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def flush_pending_msg(self):
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self.append_message(
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role="assistant",
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content=self.pending_msg
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)
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self.pending_msg = ""
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def append_message(self, role: str, content: str, name: str=None):
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msg = {
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"role": role,
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"content": content
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}
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if name is not None:
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msg['name'] = name
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self.messages.append(msg)
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def __init__(
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self,
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model: str,
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messages: list[dict[str, str]],
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**kwargs
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):
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self.model = model
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self.messages = messages.copy()
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self.kwargs = kwargs
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self.req_func = openai.ChatCompletion.acreate
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self.pending_func_call = None
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self.stopped = False
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self.pending_msg = ""
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def __iter__(self):
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return self
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def __next__(self) -> dict:
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if self.stopped:
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raise StopIteration()
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if self.pending_func_call is None: # 没有待处理的函数调用请求
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resp = self._req(
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model=self.model,
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messages=self.messages,
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functions=get_func_schema_list(),
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**self.kwargs
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)
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choice0 = resp["choices"][0]
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# 如果不是函数调用，且finish_reason为stop，则停止迭代
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if 'function_call' not in choice0['message'] and choice0["finish_reason"] == "stop":
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self.stopped = True
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if 'function_call' in choice0['message']:
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self.pending_func_call = choice0['message']['function_call']
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self.append_message(
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role="assistant",
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content="function call: "+json.dumps(self.pending_func_call)
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)
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return {
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"id": resp["id"],
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"choices": [
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{
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"index": choice0["index"],
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"message": {
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"role": "assistant",
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"type": "function_call",
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"content": None,
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"function_call": choice0['message']['function_call']
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},
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"finish_reason": "function_call"
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}
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],
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"usage": resp["usage"]
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}
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else:
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# self.pending_msg += choice0['message']['content']
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# 普通回复一定处于最后方，故不用再追加进内部messages
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return {
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"id": resp["id"],
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"choices": [
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{
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"index": choice0["index"],
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"message": {
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"role": "assistant",
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"type": "text",
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"content": choice0['message']['content']
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},
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"finish_reason": "stop"
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}
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],
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"usage": resp["usage"]
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}
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else: # 处理函数调用请求
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cp_pending_func_call = self.pending_func_call.copy()
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self.pending_func_call = None
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func_name = cp_pending_func_call['name']
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arguments = {}
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try:
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try:
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arguments = json.loads(cp_pending_func_call['arguments'])
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# 若不是json格式的异常处理
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except json.decoder.JSONDecodeError:
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# 获取函数的参数列表
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func_schema = get_func_schema(func_name)
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arguments = {
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func_schema['parameters']['required'][0]: cp_pending_func_call['arguments']
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}
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# 执行函数调用
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ret = execute_function(func_name, arguments)
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self.append_message(
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role="function",
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content=json.dumps(ret),
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name=func_name
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)
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return {
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"id": -1,
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"choices": [
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{
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"index": -1,
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"message": {
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"role": "function",
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"type": "function_return",
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"function_name": func_name,
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"content": json.dumps(ret)
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},
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"finish_reason": "function_return"
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}
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],
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"usage": {
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"prompt_tokens": 0,
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"completion_tokens": 0,
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"total_tokens": 0
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}
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}
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except ContentFunctionNotFoundError:
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raise Exception("没有找到函数: {}".format(func_name))
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@@ -0,0 +1,111 @@
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import openai
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from .model import RequestBase
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class CompletionRequest(RequestBase):
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"""调用Completion接口的请求类。
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调用方可以一直next completion直到finish_reason为stop。
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"""
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model: str
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prompt: str
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kwargs: dict
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stopped: bool = False
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def __init__(
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self,
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model: str,
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messages: list[dict[str, str]],
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**kwargs
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):
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self.model = model
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self.prompt = ""
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for message in messages:
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self.prompt += message["role"] + ": " + message["content"] + "\n"
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self.prompt += "assistant: "
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self.kwargs = kwargs
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self.req_func = openai.Completion.acreate
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def __iter__(self):
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return self
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def __next__(self) -> dict:
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"""调用Completion接口，返回生成的文本
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{
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"id": "id",
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"choices": [
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{
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"index": 0,
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"message": {
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"role": "assistant",
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"type": "text",
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"content": "message"
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},
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"finish_reason": "reason"
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}
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],
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"usage": {
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"prompt_tokens": 10,
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"completion_tokens": 20,
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"total_tokens": 30
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}
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}
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"""
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if self.stopped:
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raise StopIteration()
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resp = self._req(
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model=self.model,
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prompt=self.prompt,
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**self.kwargs
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)
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if resp["choices"][0]["finish_reason"] == "stop":
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self.stopped = True
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choice0 = resp["choices"][0]
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self.prompt += choice0["text"]
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return {
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"id": resp["id"],
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"choices": [
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{
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"index": choice0["index"],
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"message": {
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"role": "assistant",
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"type": "text",
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"content": choice0["text"]
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},
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"finish_reason": choice0["finish_reason"]
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}
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],
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"usage": resp["usage"]
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}
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if __name__ == "__main__":
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import os
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openai.api_key = os.environ["OPENAI_API_KEY"]
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for resp in CompletionRequest(
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model="text-davinci-003",
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messages=[
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{
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"role": "user",
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"content": "Hello, who are you?"
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}
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]
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):
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print(resp)
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if resp["choices"][0]["finish_reason"] == "stop":
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break
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@@ -0,0 +1,42 @@
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# 定义不同接口请求的模型
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import threading
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import asyncio
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import openai
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class RequestBase:
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req_func: callable
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def __init__(self, *args, **kwargs):
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raise NotImplementedError
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def _req(self, **kwargs):
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"""处理代理问题"""
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ret: dict = {}
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async def awrapper(**kwargs):
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nonlocal ret
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ret = await self.req_func(**kwargs)
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return ret
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loop = asyncio.new_event_loop()
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thr = threading.Thread(
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target=loop.run_until_complete,
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args=(awrapper(**kwargs),)
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)
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thr.start()
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thr.join()
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return ret
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def __iter__(self):
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raise self
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def __next__(self):
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raise NotImplementedError
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