66 lines
2.6 KiB
Python
66 lines
2.6 KiB
Python
"""
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Hermes Agent 桥接层 — 将苏格拉底 prompt 发送给 Hermes 获取引导回复
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"""
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import os
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import subprocess
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import json
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def call_hermes(prompt: str, model: str = None) -> str:
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"""
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调用 Hermes CLI 获取苏格拉底式引导回复。
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优先使用环境变量配置的 provider/model，否则走轻量 deepseek。
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"""
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provider = os.environ.get("HERMES_PROVIDER", "deepseek")
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model_name = model or os.environ.get("HERMES_MODEL", "deepseek-chat")
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# 方式1: Hermes CLI（首选 — 如果已安装）
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try:
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result = subprocess.run(
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["hermes", "ask", prompt,
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"--provider", provider,
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"--model", model_name,
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"--max-tokens", "300",
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"--temperature", "0.7"],
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capture_output=True, text=True,
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timeout=10, cwd=os.path.expanduser("~/.hermes/hermes-agent")
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)
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if result.returncode == 0 and result.stdout.strip():
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return result.stdout.strip()
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except (FileNotFoundError, subprocess.TimeoutExpired):
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pass
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# 方式2: 直接用 OpenAI 兼容 API（如有 key）
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try:
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import openai
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api_key = os.environ.get("DEEPSEEK_API_KEY") or os.environ.get("OPENAI_API_KEY")
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if not api_key:
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raise ValueError("no key")
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base_url = os.environ.get("DEEPSEEK_BASE_URL", "https://api.deepseek.com/v1")
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client = openai.OpenAI(api_key=api_key, base_url=base_url)
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resp = client.chat.completions.create(
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model=model_name,
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messages=[{"role": "user", "content": prompt}],
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max_tokens=300,
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temperature=0.7,
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timeout=10
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)
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return resp.choices[0].message.content
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except Exception:
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# 降级：返回预设引导
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return _fallback_response(prompt)
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def _fallback_response(prompt: str) -> str:
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"""无 LLM 时的预设引导回复"""
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if "分数" in prompt or "几分" in prompt:
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return "我们来分一块披萨吧！🍕 如果你把披萨切成4块，拿1块——那是几分之几呢？试试在画板上画一下？"
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elif "乘" in prompt or "×" in prompt:
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return "乘法其实就是「几个几相加」。比如3×4，就是3个4加起来。你能用小圆点画出来吗？🎨"
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elif "面积" in prompt or "周长" in prompt:
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return "想象一块地板，铺满了小瓷砖。数一数有多少块瓷砖，那就是面积！在画板上画一下你的图形吧。"
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else:
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return "好问题！我们一起来探索。你能先告诉我：你已经知道了什么？🤔"
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