xiaoli-cli bot
3f7df28423
原生支持 (API参数): - DeepSeek/MiMo: enable_thinking + reasoning_effort - OpenAI o-series: reasoning.effort - Claude: thinking.type + budget_tokens (按等级分配2k/8k/32k) - Grok: thinking.enabled - Gemini thinking: 模型名自带 不支持原生的模型 (提示词注入): - low: 无额外提示词 - medium: 逐步思考提示 (分析→因素→方案→选择) - high: 工程级深度推理框架 (问题分解→多角度分析→方案设计→验证优化) 所有模型统一 /engine.openai think [on|off|low|medium|high] 控制
539 lines
22 KiB
Python
539 lines
22 KiB
Python
"""
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OpenAI 兼容格式引擎
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支持所有兼容 OpenAI API 格式的服务（如 DeepSeek、Grok、硅基流动、本地 vLLM 等）
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"""
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import os
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import sys
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import json
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import requests
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from colorama import Fore, Style
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import logging
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# 设置日志
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logger = logging.getLogger(__name__)
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# 添加项目根目录到sys.path
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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 OpenaiAI:
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"""OpenAI 兼容格式 AI 引擎 - 支持所有兼容 OpenAI API 的服务"""
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requires_api_key = True
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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 = """
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OpenAI 兼容格式引擎帮助信息
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============================
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引擎名称: openai
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描述: 通用 OpenAI API 兼容引擎，支持所有兼容 OpenAI 格式的服务
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支持的服务:
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- OpenAI 官方 API
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- DeepSeek API
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- Grok (xAI) API
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- 硅基流动 (SiliconFlow) API
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- 本地 vLLM / LiteLLM / OneAPI 等转发服务
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- 任何兼容 /chat/completions 接口的服务
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配置方式 (config.json):
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{
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"api": {
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"engines": {
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"openai": {
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"api_key": "你的API密钥",
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"base_url": "https://api.openai.com/v1",
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"model": "gpt-4o"
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}
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}
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}
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}
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可用命令:
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/engine.openai models - 列出可用模型（需要服务端支持）
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/engine.openai set <模型名> - 切换模型
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/engine.openai info - 显示当前配置信息
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/engine.openai think - 查看深度思考状态
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/engine.openai think on - 开启深度思考
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/engine.openai think off - 关闭深度思考
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/engine.openai think high - 开启并设置推理强度 (low/medium/high)
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使用说明:
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1. 在 config.json 中配置 api_key、base_url、model
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2. 使用 /engine switch openai 切换到此引擎
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3. 直接输入自然语言与 AI 对话
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注意:
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- base_url 填写 API 的基础地址，无需包含 /chat/completions
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- 例如 OpenAI 官方填 https://api.openai.com/v1
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- 本地服务填 http://localhost:8000/v1
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"""
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return help_text
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def __init__(self):
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self.name = "openai"
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self.cli = None
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# 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("openai", {})
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self.api_key = engine_config.get("api_key", "")
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self.base_url = engine_config.get("base_url", "").rstrip('/')
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self.model = engine_config.get("model", "")
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self.max_history = config.get("system", {}).get("max_history", 10)
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# 深度思考配置
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self.deep_think = engine_config.get("deep_think", False)
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self.reasoning_effort = engine_config.get("reasoning_effort", "medium")
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except Exception as e:
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logger.warning(f"读取配置文件失败: {e}")
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self.api_key = ""
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self.base_url = ""
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self.model = ""
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self.max_history = 10
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self.deep_think = False
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self.reasoning_effort = "medium"
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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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# 思考标记（兼容深度思考模型）
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self.thinking_start_marker = "<think>"
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self.thinking_end_marker = "</think>"
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# 检查配置
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if not self.api_key:
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print(f"{Fore.YELLOW}警告: openai 引擎的 API 密钥未设置{Style.RESET_ALL}")
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if not self.base_url:
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print(f"{Fore.YELLOW}警告: openai 引擎的 base_url 未设置{Style.RESET_ALL}")
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else:
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print(f"{Fore.GREEN}OpenAI 兼容引擎已启用 (base_url: {self.base_url}){Style.RESET_ALL}")
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def _get_headers(self):
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"""构建请求头"""
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headers = {
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'Content-Type': 'application/json'
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}
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if self.api_key:
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headers['Authorization'] = f'Bearer {self.api_key}'
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return headers
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def _get_api_url(self):
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"""获取完整的 API 地址"""
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url = self.base_url
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if not url:
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return ""
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if not url.endswith('/chat/completions'):
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url = url.rstrip('/') + '/chat/completions'
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return url
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def generate_response(self, user_input, tool_results=None, system_prompt=None, tools=None):
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"""
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生成 AI 响应
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Args:
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user_input: 用户输入
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tool_results: 工具执行结果
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system_prompt: 系统提示词
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tools: OpenAI FC 工具定义列表 (可选)
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"""
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try:
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if not self.base_url:
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return "错误: openai 引擎的 base_url 未配置，请在 config.json 中设置"
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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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# 构建请求体
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body = {
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"model": self.model,
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"messages": messages,
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"stream": False
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}
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# ── 深度思考模式 ──
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self._inject_thinking_prompt = None # 清除标记
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if self.deep_think:
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body = self._apply_deep_think(body)
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# 不支持原生思考的模型，注入提示词
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if self._inject_thinking_prompt:
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thinking_hint = self._get_thinking_prompt(self._inject_thinking_prompt)
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if thinking_hint and messages:
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# 追加到系统提示词末尾
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if messages[0].get("role") == "system":
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messages[0]["content"] += thinking_hint
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else:
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messages.insert(0, {"role": "system", "content": thinking_hint})
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body["messages"] = messages
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# ── Function Calling: 注入工具定义 ──
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if tools:
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body["tools"] = tools
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body["tool_choice"] = "auto"
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# 发送请求
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api_url = self._get_api_url()
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response = requests.post(
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url=api_url,
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json=body,
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headers=self._get_headers(),
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timeout=None
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)
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if response.status_code == 200:
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response_data = response.json()
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if "choices" in response_data and len(response_data["choices"]) > 0:
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message = response_data["choices"][0].get("message", {})
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# ── Function Calling: 检查 tool_calls ──
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tool_calls_raw = message.get("tool_calls")
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if tool_calls_raw:
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# 返回 FC 结果（由调用方处理工具执行）
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from xcli_core.fc_tools import parse_fc_response
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fc_calls = parse_fc_response(response_data)
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if fc_calls:
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# 返回一个特殊的 JSON 字符串，标记为 FC 调用
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return json.dumps({
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"_fc": True,
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"tool_calls": fc_calls,
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"raw_message": message
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}, ensure_ascii=False)
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# 普通文本响应
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ai_response = message.get("content", "")
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reasoning = message.get("reasoning_content", "")
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if ai_response:
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# 清理无效的 UTF-8 代理字符
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ai_response = ai_response.encode('utf-8', 'replace').decode('utf-8')
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# 处理思考内容（从 <think> 标签中提取）
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ai_response = self._process_thinking_content(ai_response)
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# 显示思维链
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if reasoning:
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reasoning = reasoning.encode('utf-8', 'replace').decode('utf-8')
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print(f"{Fore.LIGHTBLACK_EX}[深度思考: {reasoning[:500]}{'...' if len(reasoning) > 500 else ''}]{Style.RESET_ALL}")
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return ai_response or ""
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else:
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return f"API 返回格式错误: {response_data}"
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elif response.status_code == 401:
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return "API 认证失败，请检查 api_key 是否正确"
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elif response.status_code == 404:
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return f"API 端点不存在，请检查 base_url 是否正确: {api_url}"
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elif response.status_code == 400:
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# 工具定义可能不兼容，降级为无工具重试
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if tools and "tools" in str(response.text).lower():
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print(f"{Fore.YELLOW}FC 不支持，降级为普通模式{Style.RESET_ALL}")
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body.pop("tools", None)
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body.pop("tool_choice", None)
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retry = requests.post(url=api_url, json=body, headers=self._get_headers(), timeout=None)
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if retry.status_code == 200:
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rd = retry.json()
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if "choices" in rd and rd["choices"]:
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ai_response = rd["choices"][0].get("message", {}).get("content", "")
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return ai_response.encode('utf-8', 'replace').decode('utf-8') if ai_response else ""
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return f"API 调用失败: {response.status_code} - {response.text}"
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else:
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return f"API 调用失败: {response.status_code} - {response.text}"
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except requests.exceptions.ConnectionError:
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return f"无法连接到 API 服务: {self.base_url}，请检查服务是否运行"
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except Exception as e:
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return f"API 调用失败: {str(e)}"
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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（支持 FC tool 消息）"""
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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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clean_prompt = system_prompt.encode('utf-8', 'replace').decode('utf-8')
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messages.append({
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"role": "system",
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"content": clean_prompt
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})
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# 添加历史对话记录（使用共享历史）
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if self.shared_conversation_history is not None:
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for msg in self.shared_conversation_history[-self.max_history:]:
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if not isinstance(msg, dict) or "role" not in msg:
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continue
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role = msg["role"]
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# tool 角色消息（FC 工具结果）
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if role == "tool":
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tool_msg = {"role": "tool", "content": msg.get("content", "")}
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if "tool_call_id" in msg:
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tool_msg["tool_call_id"] = msg["tool_call_id"]
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if "name" in msg:
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tool_msg["name"] = msg["name"]
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messages.append(tool_msg)
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continue
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# assistant 消息可能包含 tool_calls
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if role == "assistant" and "tool_calls" in msg:
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assistant_msg = {
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"role": "assistant",
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"content": msg.get("content"),
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"tool_calls": msg["tool_calls"]
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}
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messages.append(assistant_msg)
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continue
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# 普通 user/assistant 消息
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if "content" in msg:
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clean_content = msg["content"]
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if isinstance(clean_content, str):
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clean_content = clean_content.encode('utf-8', 'replace').decode('utf-8')
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messages.append({"role": role, "content": clean_content})
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# 添加当前用户输入
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if user_input:
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clean_input = user_input.encode('utf-8', 'replace').decode('utf-8')
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messages.append({
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"role": "user",
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"content": clean_input
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})
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return messages
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def _call_api_with_history(self, content, system_prompt=None):
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"""使用对话历史调用 API"""
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if not self.base_url:
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return "错误: openai 引擎的 base_url 未配置"
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messages = []
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if system_prompt:
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messages.append({"role": "system", "content": system_prompt})
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if self.shared_conversation_history is not None:
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for msg in self.shared_conversation_history[-self.max_history:]:
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if isinstance(msg, dict) and "role" in msg and "content" in msg:
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messages.append(msg)
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messages.append({"role": "user", "content": content})
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body = {
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"model": self.model,
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"messages": messages,
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"stream": False
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}
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try:
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response = requests.post(
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url=self._get_api_url(),
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json=body,
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headers=self._get_headers(),
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timeout=None
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)
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if response.status_code == 200:
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response_data = response.json()
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if "choices" in response_data and len(response_data["choices"]) > 0:
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ai_response = response_data["choices"][0]["message"]["content"]
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ai_response = ai_response.encode('utf-8', 'replace').decode('utf-8')
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return self._process_thinking_content(ai_response)
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return f"API 调用失败: {response.status_code} - {response.text}"
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except Exception as e:
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return f"API 调用失败: {str(e)}"
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def _process_thinking_content(self, response):
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"""处理思考内容，将思考部分以灰色文本显示"""
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import re
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if not self.thinking_start_marker or not self.thinking_end_marker:
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return response
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if self.thinking_start_marker in response and self.thinking_end_marker in response:
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parts = response.split(self.thinking_start_marker)
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if len(parts) > 1:
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remaining = parts[1]
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if self.thinking_end_marker in remaining:
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thinking_part, reply_part = remaining.split(self.thinking_end_marker, 1)
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thinking_content = thinking_part.strip()
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reply_content = reply_part.strip()
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if thinking_content:
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print(f"{Fore.LIGHTBLACK_EX}[思考: {thinking_content}]{Style.RESET_ALL}")
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return reply_content if reply_content else ""
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return response
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def _apply_deep_think(self, body: dict) -> dict:
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"""
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通用深度思考适配。
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原生支持的模型用 API 参数，不支持的用提示词模拟。
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"""
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model = (self.model or "").lower()
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effort = self.reasoning_effort # low / medium / high
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# ── 原生支持：API 参数 ──
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# DeepSeek / MiMo
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if "deepseek" in model or "mimo" in model:
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body["enable_thinking"] = True
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body.pop("temperature", None)
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if effort:
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body["reasoning_effort"] = effort
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return body
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# OpenAI o-series (o1, o3, o4-mini 等)
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if model.startswith("o") and (model[1:2].isdigit() or model[1:3] in ("1-", "3-", "4-")):
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body["reasoning"] = {"effort": effort}
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return body
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# Anthropic Claude (通过 OpenAI 兼容层)
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if "claude" in model or "anthropic" in model:
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body["thinking"] = {"type": "enabled", "budget_tokens": self._thinking_budget(effort)}
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return body
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# Grok
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if "grok" in model:
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body["thinking"] = {"enabled": True}
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return body
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# Gemini thinking 模型
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if "gemini" in model and "thinking" in model:
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return body # 模型名自带 thinking，不需要额外参数
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# ── 不支持原生思考：用提示词模拟 ──
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self._inject_thinking_prompt = effort
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return body
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@staticmethod
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def _thinking_budget(effort: str) -> int:
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"""思考 token 预算"""
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return {"low": 2048, "medium": 8192, "high": 32768}.get(effort, 8192)
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def _get_thinking_prompt(self, effort: str) -> str:
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"""根据思考等级生成提示词（注入系统提示词末尾）"""
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if effort == "low":
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return ""
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if effort == "medium":
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return (
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"\n\n【思考模式：中等】\n"
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"回答前请先逐步思考：\n"
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"1. 分析用户的核心需求\n"
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"2. 列出关键因素和约束\n"
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"3. 考虑可能的方案\n"
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"4. 选择最优方案并解释理由\n"
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"然后再给出最终回答。"
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)
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# high
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return (
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"\n\n【思考模式：深度推理】\n"
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"你必须使用结构化深度推理框架回答问题。严格遵循以下步骤：\n\n"
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"## 第一步：问题分解\n"
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"- 将问题拆解为子问题\n"
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"- 识别关键约束和边界条件\n"
|
|
"- 明确输入输出要求\n\n"
|
|
"## 第二步：多角度分析\n"
|
|
"- 从至少 3 个不同角度分析问题\n"
|
|
"- 评估每种方案的优缺点\n"
|
|
"- 考虑边界情况和异常场景\n\n"
|
|
"## 第三步：方案设计\n"
|
|
"- 选择最优方案并详细说明理由\n"
|
|
"- 给出具体的实现步骤\n"
|
|
"- 预判可能的问题并给出预防措施\n\n"
|
|
"## 第四步：验证与优化\n"
|
|
"- 检验方案是否满足所有约束\n"
|
|
"- 考虑是否有更优解\n"
|
|
"- 给出最终答案和注意事项\n\n"
|
|
"## 输出格式\n"
|
|
"先输出推理过程（用 [思考] 标记），再输出最终答案。\n"
|
|
"推理过程要详细但不啰嗦，最终答案要简洁明确。"
|
|
)
|
|
|
|
def set_model(self, model_name):
|
|
"""设置模型"""
|
|
self.model = model_name
|
|
print(f"{Fore.GREEN}已切换模型为: {model_name}{Style.RESET_ALL}")
|
|
|
|
def list_models(self):
|
|
"""列出可用模型（调用 API 的 /models 端点）"""
|
|
if not self.base_url:
|
|
return ["错误: base_url 未配置"]
|
|
|
|
try:
|
|
models_url = self.base_url.rstrip('/')
|
|
if models_url.endswith('/chat/completions'):
|
|
models_url = models_url[:-len('/chat/completions')]
|
|
models_url = models_url.rstrip('/') + '/models'
|
|
|
|
response = requests.get(
|
|
url=models_url,
|
|
headers=self._get_headers(),
|
|
timeout=10
|
|
)
|
|
|
|
if response.status_code == 200:
|
|
data = response.json()
|
|
if "data" in data:
|
|
models = [m.get("id", "unknown") for m in data["data"]]
|
|
return models
|
|
else:
|
|
return ["API 返回格式不标准，无法解析模型列表"]
|
|
else:
|
|
return [f"获取模型列表失败: {response.status_code}"]
|
|
except Exception as e:
|
|
return [f"获取模型列表失败: {str(e)}"]
|
|
|
|
def handle_command(self, command):
|
|
"""处理引擎特定命令"""
|
|
if command == "models":
|
|
models = self.list_models()
|
|
print(f"{Fore.GREEN}可用模型列表:{Style.RESET_ALL}")
|
|
for model in models:
|
|
status = " (当前使用)" if model == self.model else ""
|
|
print(f"{Fore.GREEN} - {model}{status}{Style.RESET_ALL}")
|
|
return True
|
|
|
|
elif command.startswith("set "):
|
|
model_name = command[4:].strip()
|
|
if model_name:
|
|
self.set_model(model_name)
|
|
return True
|
|
else:
|
|
print(f"{Fore.RED}请提供模型名称. 用法: /engine.openai set <模型名>{Style.RESET_ALL}")
|
|
return False
|
|
|
|
elif command == "info":
|
|
print(f"{Fore.GREEN}OpenAI 兼容引擎配置:{Style.RESET_ALL}")
|
|
print(f" base_url: {self.base_url}")
|
|
print(f" model: {self.model}")
|
|
print(f" api_key: {'已设置' if self.api_key else '未设置'}")
|
|
print(f" deep_think: {'开启' if self.deep_think else '关闭'}")
|
|
if self.deep_think:
|
|
print(f" reasoning: {self.reasoning_effort}")
|
|
return True
|
|
|
|
elif command.startswith("think"):
|
|
# /engine.openai think [on|off|low|medium|high]
|
|
arg = command.replace("think", "").strip().lower()
|
|
if arg in ("off", "0", "false"):
|
|
self.deep_think = False
|
|
print(f"{Fore.YELLOW}深度思考已关闭{Style.RESET_ALL}")
|
|
elif arg in ("on", "1", "true", ""):
|
|
self.deep_think = True
|
|
print(f"{Fore.GREEN}深度思考已开启 (reasoning_effort: {self.reasoning_effort}){Style.RESET_ALL}")
|
|
elif arg in ("low", "medium", "high"):
|
|
self.deep_think = True
|
|
self.reasoning_effort = arg
|
|
print(f"{Fore.GREEN}深度思考已开启 (reasoning_effort: {arg}){Style.RESET_ALL}")
|
|
else:
|
|
print(f"{Fore.RED}用法: /engine.openai think [on|off|low|medium|high]{Style.RESET_ALL}")
|
|
return True
|
|
|
|
else:
|
|
print(f"{Fore.RED}未知命令. 可用: models, set, info, think{Style.RESET_ALL}")
|
|
return False
|