基于大模型 API 开发本地 AI 对话应用

图形界面实现

为了提升交互体验，可以使用 PyQt6 构建本地聊天窗口。以下示例实现了基本的对话历史显示、输入框及发送功能。

import sys
from PyQt6.QtWidgets import QApplication, QMainWindow, QWidget, QVBoxLayout, QTextEdit, QPushButton, QHBoxLayout, QLabel
from PyQt6.QtCore import Qt, QThread, pyqtSignal, QTimer
from PyQt6.QtGui import QMovie
from openai import OpenAI

class ChatWorker(QThread):
    response_received = pyqtSignal(str)
    reasoning_received = pyqtSignal(str)
    error_occurred = pyqtSignal(str)

    def __init__(self, api_key, base_url, messages):
        super().__init__()
        self.api_key = api_key
        self.base_url = base_url
        self.messages = messages

    def run(self):
        try:
            client = OpenAI(api_key=self.api_key, base_url=self.base_url)
            chat_completion = client.chat.completions.create(
                model="/maas/deepseek-ai/DeepSeek-V3",
                messages=self.messages,
                stream=True
            )
            for chunk in chat_completion:
                if hasattr(chunk.choices[0].delta, 'reasoning_content'):
                    self.reasoning_received.emit(chunk.choices[0].delta.reasoning_content)
                if hasattr(chunk.choices[0].delta, 'content'):
                    if chunk.choices[0].delta.content:
                        self.response_received.emit(chunk.choices[0].delta.content)
        except Exception as e:
            self.error_occurred.emit(str(e))

class ChatWindow(QMainWindow):
    def __init__(self):
        super().__init__()
        self.is_sending = False
        self.initUI()

    def initUI(self):
        self.setWindowTitle('AI 对话界面')
        self.setGeometry(100, 100, 800, 600)
        central_widget = QWidget()
        self.setCentralWidget(central_widget)
        main_layout = QVBoxLayout(central_widget)
        main_layout.setSpacing(15)
        main_layout.setContentsMargins(20, 20, 20, 20)

        self.chat_history = QTextEdit()
        self.chat_history.setReadOnly(True)
        main_layout.addWidget(self.chat_history, stretch=2)

        self.input_field = QTextEdit()
        self.input_field.setMaximumHeight(100)
        input_layout = QHBoxLayout()
        input_layout.addWidget(self.input_field)

        self.send_button = QPushButton('发送')
        self.send_button.clicked.connect(self.send_message)
        input_layout.addWidget(self.send_button)
        main_layout.addLayout(input_layout)

    def send_message(self):
        if self.is_sending:
            return
        user_message = self.input_field.toPlainText().strip()
        if not user_message:
            return

        self.is_sending = True
        self.send_button.setEnabled(False)
        self.input_field.clear()

        messages = [{"role": "user", "content": user_message}]
        self.worker = ChatWorker("YOUR_API_KEY", "YOUR_BASE_URL", messages)
        self.worker.response_received.connect(self.handle_response)
        self.worker.start()

    def handle_response(self, response):
        # 处理接收到的响应
        pass

def main():
    app = QApplication(sys.argv)
    window = ChatWindow()
    window.show()
    sys.exit(app.exec())

if __name__ == '__main__':
    main()

总结

通过简单的 API 配置和代码调用，即可利用平台强大的 AI 技术构建本地应用。开发者无需深入钻研底层算法细节，仅需按照文档说明进行接口调用，就能实现智能对话功能。该方法支持跨平台集成，适用于 Windows、Linux、macOS 等多种操作系统环境。