365 lines
12 KiB
Python
365 lines
12 KiB
Python
import threading
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import time
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from http import HTTPStatus
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import dashscope
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import openai
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import base_mode as bm
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from config import *
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class DialogMode(bm.Mode):
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def __init__(self, model="qwen-plus", system_prompt="You are a helpful assistant", threshold_no_speak=2,
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asr_callback=lambda x: print(x, end="", flush=True), tts_callback=lambda x: print(x, end="", flush=True)):
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"""
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自由对话模式类的构造函数
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:param model: 模型名称
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:param system_prompt: 系统提示词
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:param threshold_no_speak: 多长时间未说话认定为结束，单位：秒
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"""
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super().__init__(
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asr_callback=asr_callback,
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tts_callback=tts_callback
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)
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self.model = model
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self.client = openai.OpenAI(
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api_key=COM_API_KEY,
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base_url="https://dashscope.aliyuncs.com/compatible-mode/v1"
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)
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self.context = [
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{"role": "system", "content": system_prompt}
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]
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self.system_prompt = system_prompt
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self.main_loop_thread = threading.Thread(target=self.main_loop)
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self.running = False
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self.threshold_no_speak = threshold_no_speak
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def ask_ai(self, prompt):
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self.context.append(
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{"role": "user", "content": prompt}
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)
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response = self.client.chat.completions.create(
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model=self.model,
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messages=self.context,
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max_tokens=2048,
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stream=True
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)
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all_text = ""
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for chunk in response:
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content = chunk.choices[0].delta.content or ""
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all_text += content
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yield content
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self.context.append(
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{"role": "assistant", "content": all_text}
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)
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yield ""
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def main_loop(self):
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while self.running:
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# 1. 启动ASR服务
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self.ready_asr_session()
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# 2. 开始录音
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self.start_asr_record()
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# 3. 等待开始说话
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while self.last_asr_time is None: pass
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# 4. 等待说话时长过长
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while (time.time() - self.last_asr_time) <= self.threshold_no_speak: pass
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# 5. 关闭ASR
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self.stop_asr_record()
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# 6. 扔给AI
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self.stream_pipeline(self.ask_ai(self.asr_res))
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def run(self):
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super().run()
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self.running = True
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print("请开始说话...")
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self.main_loop_thread.start()
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def stop(self):
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self.running = False
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self.tts_finish()
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class MakePointMode(bm.Mode):
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def __init__(self, side="正方", topic="", opinion="", asr_callback=lambda x: print(x, end="", flush=True), tts_callback=lambda x: print(x, end="", flush=True)):
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super().__init__(
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asr_callback=asr_callback,
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tts_callback=tts_callback
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)
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self.side = side
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self.topic = topic
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self.opinion = opinion
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self.session_id = None
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self.last_prompt = "" # 当side="正方"时，为反方立论内容，否则为空字符串
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def ask_ai(self, prompt):
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biz_params = {
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"user_prompt_params" : {
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"side": self.side,
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"topic": self.topic,
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"opinion": self.opinion
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}
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}
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if self.session_id is None:
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res = dashscope.Application.call(
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api_key=COM_API_KEY,
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app_id=APP_ID,
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prompt=prompt,
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stream=True,
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incremental_output=True,
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biz_params=biz_params
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)
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else:
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res = dashscope.Application.call(
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api_key=COM_API_KEY,
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app_id=APP_ID,
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prompt=prompt,
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stream=True,
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incremental_output=True,
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session_id=self.session_id,
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biz_params=biz_params
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)
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for chunk in res:
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if chunk.status_code == HTTPStatus.OK:
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self.session_id = chunk.output.session_id
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yield chunk.output.text
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def ask(self, other_op=None):
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if self.side == "正方":
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return self.ask_ai("主席：请正方开始立论")
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else:
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return self.ask_ai("主席：请正方开始立论\n正方：" + other_op)
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def start_record(self):
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self.ready_asr_session()
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self.start_asr_record()
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def stop_record(self):
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"""
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该函数执行完毕后才能调用start_talk和start_identify_op函数！
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:return:
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"""
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self.stop_asr_record()
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def start_talk(self):
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"""
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仅对反方：开始立论
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:return:
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"""
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if self.side == "反方":
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self.stream_pipeline(self.ask(self.asr_res))
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def start_identify_op(self):
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"""
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仅对正方：设定last_prompt，以便返回给下面的自由辩论模式
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:return:
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"""
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if self.side == "正方":
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self.last_prompt = self.asr_res
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def ready_next(self):
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if self.side == "正方":
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self.start_identify_op()
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return self.last_prompt
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else:
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self.start_talk()
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def run(self):
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"""
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流程：
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1. 正方：先说话，再录音
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调用本函数时，直接开始说话，说话完成后，当对方开始立论时，需显式调用start_record函数；结束立论时，需显式调用stop_record函数；
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当进入自由辩论环节时，需显式调用ready_next。如果为正方，需接收返回值，作为自由辩论环节提示词前面的反方立论内容。
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2. 反方：先录音，再说话
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调用本函数时，开始录音（因此需要在对方将要说话时切入此模式），当对方说完话后，应显式调用stop_record函数；本方开始立论时，应显式调用start_talk函数
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:return:
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"""
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super().run()
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if self.side == "正方":
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# 先说话再录音
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self.stream_pipeline(self.ask())
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else:
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# 先录音再说话。外界控制
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self.start_record()
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class FreeDebateMode(bm.Mode):
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def __init__(self, session_id, side="正方", topic="", opinion="", last_prompt="", threshold_no_speak=2,
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asr_callback=lambda x: print(x, end="", flush=True), tts_callback=lambda x: print(x, end="", flush=True)):
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super().__init__(
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asr_callback=asr_callback,
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tts_callback=tts_callback
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)
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self.threshold_no_speak = threshold_no_speak
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self.side = side
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self.topic = topic
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self.opinion = opinion
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self.last_prompt = last_prompt
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self.session_id = session_id
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self.is_first = True
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self.last_prompt_next_mode = None
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self.main_loop_thread = threading.Thread(target=self.main_loop)
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self.running = False
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def ask_ai(self, prompt):
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biz_params = {
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"user_prompt_params" : {
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"side": self.side,
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"topic": self.topic,
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"opinion": self.opinion
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}
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}
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res = dashscope.Application.call(
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api_key=COM_API_KEY,
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app_id=APP_ID,
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prompt=prompt,
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stream=True,
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incremental_output=True,
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session_id=self.session_id,
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biz_params=biz_params
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)
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for chunk in res:
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if chunk.status_code == HTTPStatus.OK:
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self.session_id = chunk.output.session_id
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yield chunk.output.text
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def init_ask(self):
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"""
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仅正方：用于将反方的立论传入，并让正方说话
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:return:
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"""
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if self.side == "正方":
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return self.ask_ai("反方："+self.last_prompt+"\n主席：下面进入自由辩论环节，请正方开始发言")
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def ask(self, context=None):
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if self.side == "正方":
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return self.ask_ai("反方："+context)
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else:
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if self.is_first:
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self.is_first = False
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return self.ask_ai("主席：下面进入自由辩论环节，请正方开始发言\n正方：" + context)
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return self.ask_ai("正方："+context)
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def main_loop(self):
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# 初始ask
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if self.side == "正方":
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self.stream_pipeline(self.init_ask())
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# 主对话循环
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while self.running:
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# 1. 启动ASR服务
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self.ready_asr_session()
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# 2. 开始录音
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self.start_asr_record()
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# 3. 等待开始说话
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while self.last_asr_time is None: pass
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# 4. 等待说话时长过长
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while (time.time() - self.last_asr_time) <= self.threshold_no_speak: pass
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# 5. 关闭ASR
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self.stop_asr_record()
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# 6. 扔给AI
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self.stream_pipeline(self.ask(self.asr_res))
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def run(self):
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"""
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流程：
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类似对话模式
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当进入结论模式时，外界直接通过析构对象然后启动结论模式即可。但建议取一下last_prompt_next_mode字段
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:return:
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"""
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super().run()
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self.running = True
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self.main_loop_thread.start()
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def stop(self):
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self.running = False
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self.tts_finish()
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class EndDebateMode(bm.Mode):
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def __init__(self, session_id, side="正方", topic="", opinion="", last_prompt="",
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asr_callback=lambda x: print(x, end="", flush=True), tts_callback=lambda x: print(x, end="", flush=True)):
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super().__init__(
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asr_callback=asr_callback,
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tts_callback=tts_callback
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)
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self.side = side
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self.topic = topic
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self.opinion = opinion
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self.last_prompt = last_prompt
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self.session_id = session_id
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def ask_ai(self, prompt):
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biz_params = {
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"user_prompt_params": {
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"side": self.side,
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"topic": self.topic,
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"opinion": self.opinion
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}
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}
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res = dashscope.Application.call(
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api_key=COM_API_KEY,
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app_id=APP_ID,
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prompt=prompt,
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stream=True,
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incremental_output=True,
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session_id=self.session_id,
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biz_params=biz_params
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)
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for chunk in res:
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if chunk.status_code == HTTPStatus.OK:
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self.session_id = chunk.output.session_id
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yield chunk.output.text
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def ask(self, context=None):
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if self.side == "反方":
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if self.last_prompt != "":
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return self.ask_ai("反方："+self.last_prompt+"\n主席：下面进入结辩环节，请反方开始发言")
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else:
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return self.ask_ai("主席：下面进入结辩环节，请反方开始发言")
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else:
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return self.ask_ai("主席：下面进入结辩环节，请反方开始发言\n反方："+context)
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def start_record(self):
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self.ready_asr_session()
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self.start_asr_record()
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def stop_record(self):
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"""
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该函数执行完毕后才能调用start_talk和start_identify_op函数！
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:return:
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"""
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self.stop_asr_record()
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def start_talk(self):
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"""
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开始结论
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:return:
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"""
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if self.side == "反方":
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self.stream_pipeline(self.ask())
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else:
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self.stream_pipeline(self.ask(self.asr_res))
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def run(self):
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"""
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流程：
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1. 正方：当对方说话时，需外界调用start_record方法，说话结束后调用stop_record方法，再调用start_talk方法
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2. 反方：需外界调用start_talk方法，然后直接开始结辩
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走到这里，圆满结束！！！！
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:return:
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"""
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super().run()
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pass
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if __name__ == '__main__':
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mode = DialogMode(
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asr_callback=lambda x: print(x, end="", flush=True),
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tts_callback=lambda x: print(x, end="", flush=True)
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)
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mode.run()
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time.sleep(200)
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