feat: 增强编码能力 - 新增代码编辑器、代码搜索、Git集成
- 新增 plugins/code_editor.py: 精准代码编辑（搜索替换、批量编辑、diff对比） - 新增 plugins/code_search.py: 代码搜索与理解（跨文件搜索、符号提取、依赖分析） - 新增 plugins/git_tools.py: Git 版本控制（status/diff/log/commit/branch） - 新增 core/ 模块: 配置管理、引擎管理、对话处理、显示输出、代码沙箱 - 修复 requirements.txt: 使用正确的 pip 包名（Pillow、opencv-python 等） - 更新 unified_tool_manager.py: 兼容 Plugin 和 Liugin 两种类名 - 更新系统提示词: 增强编程工作流指导 本次更新由 mimo 自动化执行，与开发者无关。
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import os
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import sys
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import json
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import hashlib
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import hmac
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import base64
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import websocket
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import time
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import threading
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from datetime import datetime
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from time import mktime
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from urllib.parse import urlparse, urlencode
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from wsgiref.handlers import format_date_time
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from colorama import Fore, Style
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# 获取项目根目录
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current_dir = os.path.dirname(os.path.abspath(__file__))
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project_root = os.path.dirname(current_dir)
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sys.path.insert(0, project_root)
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class XfyunSparkAI:
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"""基于讯飞星火深度推理X2模型的AI引擎（WebSocket接口）"""
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requires_api_key = True # 讯飞引擎需要API密钥
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# X2深度推理版本固定配置
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URL = "wss://spark-api.xf-yun.com/x2"
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DOMAIN = "spark-x"
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MAX_TOKENS = 131072 # X2输出上限128K
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def __init__(self):
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self.name = "xfyun-spark"
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self.cli = None
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# 直接从 config.json 读取配置
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config_file = os.path.join(project_root, "config.json")
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try:
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with open(config_file, 'r', encoding='utf-8') as f:
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config = json.load(f)
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engine_config = config.get("api", {}).get("engines", {}).get("xfyun_spark", {})
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self.app_id = engine_config.get("app_id", "")
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self.api_key = engine_config.get("api_key", "")
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self.api_secret = engine_config.get("api_secret", "")
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self.max_history = config.get("system", {}).get("max_history", 10)
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except Exception as e:
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self.app_id = ""
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self.api_key = ""
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self.api_secret = ""
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self.max_history = 10
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# 初始化对话历史
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self.conversation_history = []
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self.shared_conversation_history = None
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self.chat_id = f"chat_{self.app_id}_{int(time.time())}" # 固定会话ID，确保上下文连续性
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# 验证API密钥
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if not self.app_id or not self.api_key or not self.api_secret:
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print(f"{Fore.YELLOW}警告: xfyun-spark引擎的API配置未完整设置（需要app_id、api_key、api_secret）{Style.RESET_ALL}")
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def get_help_info(self):
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"""获取引擎帮助信息"""
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help_text = f"""
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讯飞星火深度推理X2引擎帮助信息
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================================
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引擎名称: xfyun-spark
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描述: 基于讯飞星火深度推理X2模型的AI引擎，支持WebSocket流式输出
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版本: X2深度推理 (输入64K, 输出128K)
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配置要求:
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在config.json中配置:
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{{
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"api": {{
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"engines": {{
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"xfyun_spark": {{
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"app_id": "你的应用ID",
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"api_key": "你的API Key",
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"api_secret": "你的API Secret"
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}}
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}}
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}}
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}}
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使用说明:
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1. 使用/engine.switch xfyun-spark切换到此引擎
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2. 直接输入自然语言与AI对话
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3. 本引擎强制使用流式输出，AI回复会实时显示
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4. 支持深度思考模式，思考过程会自动显示
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注意: 本引擎使用WebSocket协议，需要app_id、api_key、api_secret三个参数
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"""
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return help_text
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def _generate_url(self):
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"""生成鉴权URL（使用官方示例的方式）"""
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# 生成RFC1123格式的时间戳
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now = datetime.now()
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date = format_date_time(mktime(now.timetuple()))
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# 解析URL获取host和path
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parsed_url = urlparse(self.URL)
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host = parsed_url.netloc
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path = parsed_url.path
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# 拼接签名字符串
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signature_origin = "host: " + host + "\n"
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signature_origin += "date: " + date + "\n"
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signature_origin += "GET " + path + " HTTP/1.1"
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# 进行hmac-sha256进行加密
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signature_sha = hmac.new(
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self.api_secret.encode('utf-8'),
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signature_origin.encode('utf-8'),
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digestmod=hashlib.sha256
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).digest()
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signature_sha_base64 = base64.b64encode(signature_sha).decode(encoding='utf-8')
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# 拼接authorization_origin
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authorization_origin = f'api_key="{self.api_key}", algorithm="hmac-sha256", headers="host date request-line", signature="{signature_sha_base64}"'
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authorization = base64.b64encode(authorization_origin.encode('utf-8')).decode(encoding='utf-8')
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# 将请求的鉴权参数组合为字典
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v = {
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"authorization": authorization,
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"date": date,
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"host": host
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}
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# 拼接鉴权参数，生成url
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url = self.URL + '?' + urlencode(v)
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return url
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def _build_messages_with_history(self, system_prompt, user_input):
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"""构建包含历史记录的消息列表（传递完整历史对话）"""
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messages = []
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# 添加系统提示词
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if system_prompt:
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messages.append({
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"role": "system",
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"content": system_prompt
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})
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# 添加完整的历史对话（不限制数量，让API自己处理）
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if self.shared_conversation_history:
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for msg in self.shared_conversation_history:
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if isinstance(msg, dict) and "role" in msg and "content" in msg:
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role = msg["role"]
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content = msg["content"]
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# 转换角色名称
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if role == "user":
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messages.append({"role": "user", "content": content})
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elif role == "assistant":
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messages.append({"role": "assistant", "content": content})
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# 添加当前用户输入
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messages.append({
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"role": "user",
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"content": user_input
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})
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return messages
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def generate_response(self, user_input, tool_results=None, system_prompt=None):
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"""生成AI响应（非流式）"""
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try:
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# 处理工具结果
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if tool_results:
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tool_result_text = f"工具执行结果: {tool_results.get('result', '无结果')}"
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messages = self._build_messages_with_history(system_prompt, tool_result_text)
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else:
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messages = self._build_messages_with_history(system_prompt, user_input)
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# 构建请求数据
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request_data = {
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"header": {
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"app_id": self.app_id,
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"uid": str(time.time()).replace('.', '')[:32]
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},
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"parameter": {
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"chat": {
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"domain": self.DOMAIN,
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"temperature": 0,
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"max_tokens": 4096,
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"presence_penalty": 1,
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"frequency_penalty": 0.02,
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"top_k": 5,
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"chat_id": self.chat_id
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}
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},
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"payload": {
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"message": {
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"text": messages
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}
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}
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}
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# 生成鉴权URL
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auth_url = self._generate_url()
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# 收集完整响应
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full_response = ""
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thinking_content = ""
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ws = None
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result_queue = []
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done_event = threading.Event()
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def on_message(ws, message):
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nonlocal full_response, thinking_content
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try:
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data = json.loads(message)
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code = data.get("header", {}).get("code", -1)
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if code != 0:
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result_queue.append(("error", data.get('header', {}).get('message', '未知错误')))
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done_event.set()
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return
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payload = data.get("payload", {})
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choices = payload.get("choices", {})
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# 处理文本响应
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text_list = choices.get("text", [])
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if text_list:
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reasoning = text_list[0].get("reasoning_content", "")
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if reasoning:
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thinking_content += reasoning
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content = text_list[0].get("content", "")
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if content:
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full_response += content
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if choices.get("status") == 2:
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done_event.set()
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except Exception as e:
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result_queue.append(("error", str(e)))
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done_event.set()
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def on_error(ws, error):
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result_queue.append(("error", str(error)))
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done_event.set()
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def on_close(ws, close_status_code, close_msg):
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pass
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def on_open(ws):
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ws.send(json.dumps(request_data))
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# 创建WebSocket连接
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ws = websocket.WebSocketApp(
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auth_url,
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on_open=on_open,
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on_message=on_message,
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on_error=on_error,
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on_close=on_close
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)
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# 在后台线程运行WebSocket
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ws_thread = threading.Thread(target=ws.run_forever)
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ws_thread.daemon = True
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ws_thread.start()
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# 等待完成
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done_event.wait(timeout=60)
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# 返回完整响应
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return full_response
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except Exception as e:
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print(f"\n{Fore.RED}讯飞星火API调用失败: {str(e)}{Style.RESET_ALL}")
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return f"讯飞星火API调用失败: {str(e)}"
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