ROS 语音交互（二）nlp

目录

背景：

一、模型选择

二、操作流程

三、核心代码展示

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背景：

成功设置自己的知识库，语音交互问答会优先选择自己的知识库的答案进行回答，减少了耗时

一、模型选择

商汤 商量日日新

二、操作流程

文档中心 | 日日新开放平台 (sensenova.cn)

按照这个走就没事

三、核心代码展示

import sensenova
 
class SimpleChatBot:
    def __init__(self, access_key_id, secret_access_key):
        # 设置访问密钥
        sensenova.access_key_id = access_key_id
        sensenova.secret_access_key = secret_access_key
 
        # 创建会话
        resp = sensenova.ChatSession.create(
            system_prompt=[
                {
                    "role": "system",
                    "content": "You are a translation expert."
                }
            ]
        )
        self.session_id = resp["session_id"]
 
    def get_response(self, text):
        # 生成对话
        resp = sensenova.ChatConversation.create(
            action="next",
            max_new_tokens=10,
            content=text,
            model="SenseChat",
            stream=False,  # 非流式输出
            session_id=self.session_id,
            knowledge_config={
                "control_level": "normal",
                "knowledge_base_result": True,
                "knowledge_base_configs": []
            },
            plugins={
                "associated_knowledge": {
                    "content": " string",
                    "mode": "concatenate"
                },
                "web_search": {
                    "search_enable": True,
                    "result_enable": True
                },
            }
        )
 
 
if __name__ == "__main__":
    access_key_id = ""
    secret_access_key = ""
 
    bot = SimpleChatBot(access_key_id, secret_access_key)
    
    # 提示用户输入文本并获取回答
    while True:
        user_input = input("User: ")
        if user_input.lower() == "exit":  # 输入exit退出对话
            print("Conversation ended.")
            break
        
        response = bot.get_response(user_input)
        print("Assistant:", response)