bugfix

skillagent/skillengine.py

@@ -42,7 +42,7 @@ class LLMHandler:
 				exception(f'{e}\n{format_exc()}')
 		return txt
 
-async def run_subprocess(command, cwd, env, timeout=30.0):
+async def run_subprocess(command, cwd, env, input_str=None, timeout=30.0):
 	try:
 		# 启动子进程
 		# stdout/stderr 设置为 PIPE 对应原来的 capture_output=True
@@ -50,6 +50,7 @@ async def run_subprocess(command, cwd, env, timeout=30.0):
 			command,
 			stdout=asyncio.subprocess.PIPE,
 			stderr=asyncio.subprocess.PIPE,
+			stdin=asyncio.subprocess.PIPE,
 			cwd=cwd,
 			env=env,
 			# 注意：asyncio 默认处理字节流，如果需要文本，后面需手动 decode
@@ -58,7 +59,8 @@ async def run_subprocess(command, cwd, env, timeout=30.0):
 		# 使用 wait_for 实现 timeout 功能
 		try:
 			# wait_for 会在超时后抛出 TimeoutError 并自动 cancel 协程
-			stdout, stderr = await asyncio.wait_for(process.communicate(), timeout=timeout)
+			input_bytes = input_str.encode() if input_str else None
+			stdout, stderr = await asyncio.wait_for(process.communicate(input=input_bytes), timeout=timeout)
 		except asyncio.TimeoutError:
 			process.kill() # 超时强制杀掉进程
 			await process.wait() # 确保资源回收
@@ -130,9 +132,14 @@ class IndustrialSkillEngine:
 				(skill["root"] / ".deps_installed").touch()
 
 	# --- 3. 增强版安全执行器：带重试逻辑与审计 ---
-	async def _execute_with_retry(self, command: str, skill_name: str, retry_count=1) -> str:
+	async def _execute_with_retry(self, cmdjson: dict, skill_name: str, retry_count=1) -> str:
 		await self._ensure_dependencies(skill_name)
 		
+		command = cmdjson['cmd']
+		params = cmdjson.get('params')
+		params_str=None
+		if params:
+			params_str = json.dumps(params, ensure_ascii=False)
 		# 安全预检：禁止敏感命令
 		forbidden = ["rm ", "> /dev/", "chmod", "sudo"]
 		if any(f in command for f in forbidden):
@@ -143,8 +150,11 @@ class IndustrialSkillEngine:
 		try:
 			env = os.environ.copy()
 			env["SKILL_CONTEXT"] = skill_name
-			
-			res = await run_subprocess(command, cwd=self.registry[skill_name]["root"], env=env, timeout=30)
+			intput_str = json.dumps(params, ensure_ascii=False)
+			res = await run_subprocess(command, cwd=self.registry[skill_name]["root"], 
+						env=env, 
+						input_str=params_str,
+						timeout=30)
 			
 			if res.return_code != 0:
 				# 工业级特性：自动将错误回传给 LLM 进行自愈 (Self-healing)
@@ -238,7 +248,7 @@ class IndustrialSkillEngine:
 		context = await self._get_expanded_context(skill_name, user_prompt, context=context)
 		
 		# 决策：是直接回答还是执行脚本
-		decision = await self.llm(f"上下文: {context}\n问题: {user_prompt}\n决定动作：EXEC: <command> 或 ANSWER: <text> 或 REPLY: <question>")
+		decision = await self.llm(f"上下文: {context}\n问题: {user_prompt}\n决定动作：EXEC: {"cmd": found_cmd, "params": found_parameters_dict} 或 ANSWER: <text> 或 REPLY: <question>")
 		output = {
 			"status": "PROCESSING",
 			"hint": f"决策完成：{decision=}"
@@ -262,7 +272,8 @@ class IndustrialSkillEngine:
 			return
 		if "EXEC:" in decision:
 			cmd = decision.split("EXEC:")[1].strip()
-			output =  await self._execute_with_retry(cmd, skill_name)
+			jd = json.loads(cmd)
+			output =  await self._execute_with_retry(jd, skill_name)
 			if isinstance(output, str):
 				output = {
 					"status": "SUCCEEDED",