bugfix

skillagent/skillengine.py

@@ -103,12 +103,12 @@ class IndustrialSkillEngine:
 				req_file = skill_md.parent / "requirements.txt"
 				has_deps = req_file.exists()
 
-				self.registry[name] = {
+				self.registry[name] = DictObject(**{
 					"root": skill_md.parent,
 					"meta": meta,
 					"content": content,
 					"has_deps": has_deps
-				}
+				})
 		await env.session_setvalue(key, self.registry)
 
 	# --- 2. 自动化依赖环境隔离 (venv 思想) ---
@@ -145,12 +145,8 @@ class IndustrialSkillEngine:
 					print(f"⚠️ 执行失败，尝试让 AI 自愈修复参数...")
 					new_prompt = f"命令 '{command}' 失败，错误信息: {res.stderr}。请根据错误重新生成正确的命令，或提示用户补全参数。"
 					# 这里会递归调用逻辑进行修复
-					return await self.run(new_prompt, is_retry=True)
+					return await self._run(new_prompt, is_retry=True)
 				
-				await self.write_output({
-					"status": "FAILED",
-					"error": f"Error: {res.stderr}"
-				})
 				raise Exception(f"Error: {res.stderr}")
 			
 			return res.stdout
@@ -175,10 +171,11 @@ class IndustrialSkillEngine:
 			choice = await self.llm(f"上下文：{context or ''}\n用户问题: {user_prompt}\n可选深入文档: {found_docs}\n需要读取哪个？(仅返回路径，不需则返回 None)")
 			if choice != "None" and any(choice in doc for doc in found_docs):
 				with open(skill["root"] / choice, 'r') as f:
-					await self.write_output({
+					output = {
 						"status": "PROCESSING",
 						"hint": f"📂 深度加载: {choice}"
-					})
+					}
+					await self.write_output(output)
 					base_content += f"\n\n--- 深度参考 ({choice}) ---\n{f.read()}"
 		
 		return base_content
@@ -190,20 +187,33 @@ class IndustrialSkillEngine:
 			data = await self.task_queue.get()
 			if not data:
 				break;
+			debug(f'{data=}, {type(data)=}')
 			yield data
 			await asyncio.sleep(0.1)
 
 
 	# --- 5. 主运行接口 ---
-	async def run(self, user_prompt: str, context=None, is_retry=False):
+	async def run(self, parmas_kw):
+		try:
+			user_input = json.dumps(params_kw, ensure_ascii=False)
+			await self._run(user_input)
+		except Exception as e:
+			await self.write_output({
+				'status': 'FAILED',
+				'error': f"{e}'
+			})
+		self.write_output(None)
+
+	async def _run(self, user_prompt: str, context=None, is_retry=False):
 		# 如果是重试，跳过技能选择
 		await self.boot()
+		debug(f'{self.registry=}')
 		if not is_retry:
 			await self.write_output({
 				"status": "PROCESSING",
 				"hint": "寻找合适的skill"
 			})
-			skill_map = {n: v["description"] for n, v in self.registry.items()}
+			skill_map = {n: v.meta.description for n, v in self.registry.items()}
 			target = await self.llm(f"用户意图: {user_prompt}\n可选技能清单: {skill_map}\n请返回匹配的技能名:")
 			self.state["current_skill"] = target
 			await self.write_output({
@@ -213,11 +223,7 @@ class IndustrialSkillEngine:
 		
 		skill_name = self.state["current_skill"]
 		if skill_name not in self.registry: 
-			await self.write_output({
+			raise Exception(f"技能名{skill_name}未注册")
-				"status": "FAILED",
-				"error": f"技能名{skill_name}未注册"
-			})
-			raise Exception("Skill not found.")
 
 		# 获取递归上下文
 		context = await self._get_expanded_context(skill_name, user_prompt, context=context)
@@ -240,7 +246,7 @@ class IndustrialSkillEngine:
 				asyncio.sleep(0.5)
 				user_reply = await env.session_getvalue(sessionkey)
 			prompt = f"{user_prompt}\n补充输入：{user_reply}"
-			await self.run(prompt, context=context, is_retry=True)
+			await self._run(prompt, context=context, is_retry=True)
 			return
 		if "EXEC:" in decision:
 			cmd = decision.split("EXEC:")[1].strip()