98 lines
4.0 KiB
Python
98 lines
4.0 KiB
Python
#!/usr/bin/env python3
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"""
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kanban-2b-worker.py — 分环节 kanban 代码 worker（牧尘 2026-09-10 定案）
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=====================================================================
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环节拆分：2B 不做协议，只做执行。本脚本由 opencode profile worker 首轮运行：
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环节1 读任务 ：从 env/kanban 读任务描述（确定性代码）
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环节2 执行 ：调 opencode CLI + llama-local/minicpm5-2b 写代码（唯一 LLM 点）
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环节3 验证 ：运行产物，检查 exit code + 输出（确定性代码）
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环节4 输出结果 ：打印 JSON，由 worker agent 据此 kanban_complete/block
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用法（worker 内）:
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python3 ~/.hermes/scripts/kanban-2b-worker.py
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"""
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import json
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import os
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import subprocess
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import sys
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import time
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OPENCODE = "/home/muc/nodejs/node-v24.16.0-linux-x64/bin/opencode"
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# 执行模型链：本地2B(0成本) → 智谱glm-4-flash(免费) → 商汤deepseek(免费)
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# 牧尘 2026-09-10：opencode 加智谱也加本地 2B
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MODEL_CHAIN = [
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"llama-local/minicpm5-2b", # 本地 0 成本（主力）
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"zhipu/glm-4-flash", # 智谱免费（代码倾向强）
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"sensenova/deepseek-v4-flash", # 商汤免费
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]
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HERMES = "/home/muc/bin/hermes"
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def sh(cmd, timeout=120, cwd=None, max_out=3000):
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try:
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r = subprocess.run(cmd, capture_output=True, text=True, timeout=timeout, cwd=cwd,
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env=dict(os.environ, PATH="/home/muc/nodejs/node-v24.16.0-linux-x64/bin:" + os.environ.get("PATH", "")))
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return r.returncode, (r.stdout + r.stderr)[:max_out]
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except Exception as e:
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return -1, str(e)[:500]
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def get_task():
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"""从 kanban CLI 读任务详情"""
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task_id = os.environ.get("HERMES_KANBAN_TASK", "")
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if not task_id:
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# fallback: 尝试从 argv
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task_id = sys.argv[1] if len(sys.argv) > 1 else ""
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if not task_id:
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return None, "no HERMES_KANBAN_TASK env"
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rc, out = sh([HERMES, "kanban", "show", task_id, "--json"], max_out=20000)
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if rc != 0:
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return None, f"kanban show failed: {out[:300]}"
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try:
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d = json.loads(out)
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t = d.get("task") or d # kanban show --json 返回 {task:{...}}
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title = t.get("title") or t.get("summary") or ""
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body = t.get("body") or ""
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ws = t.get("workspace_path") or os.environ.get("HERMES_KANBAN_WORKSPACE") or ""
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return {"id": task_id, "title": title, "body": body, "workspace": ws}, None
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except Exception as e:
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return None, f"parse failed: {e}"
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def run_opencode(task_desc, workspace):
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"""调 opencode CLI + 2B 执行（唯一 LLM 环节）"""
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if not workspace or not os.path.isdir(workspace):
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workspace = "/tmp"
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prompt = (
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f"完成以下任务。写代码 → 实际运行验证 → 报告结果。\n"
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f"任务: {task_desc[:1500]}\n"
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"要求: 1) 在当前目录创建所需文件 2) 实际运行验证 3) 最后输出一行 JSON: "
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'{"files": ["..."], "verified": true/false, "output": "运行输出摘要"}'
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)
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# 模型链逐个试：本地2B → 智谱 → 商汤（全免费；超时/失败下一个）
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last_err = "no model attempted"
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for model in MODEL_CHAIN:
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t0 = time.time()
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rc, out = sh([OPENCODE, "run", "--model", model, prompt], timeout=280, cwd=workspace)
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if rc == 0 and out.strip():
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return {"model": model, "elapsed_s": round(time.time() - t0), "raw": out[-2000:]}
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last_err = out[-300:]
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return {"error": f"opencode all models failed: {last_err}"}
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def main():
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task, err = get_task()
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if err:
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print(json.dumps({"ok": False, "stage": "read_task", "error": err}, ensure_ascii=False))
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return
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print(json.dumps({"ok": True, "stage": "read_task", "task_id": task["id"]}, ensure_ascii=False))
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desc = task["title"] + ("\n" + task["body"] if task.get("body") else "")
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result = run_opencode(desc, task.get("workspace", ""))
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print("=== OPENCODE_RESULT ===")
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print(json.dumps(result, ensure_ascii=False)[:2500])
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if __name__ == "__main__":
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main()
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