bugfix

skillagent/agent.py

@@ -5,6 +5,7 @@ from dataclasses import dataclass, field
 from pydantic import BaseModel, Field, ValidationError
 from typing import Literal
 from appPublic.worker import awaitify
+from appPublic.streamhttpclient import StreamHttpClient, liner
 from .skillkit_wrapper import SkillkitWrapper
 
 # ---------------------------
@@ -45,7 +46,7 @@ class LLM:
 class DummyLLM(LLM):
 	def __init__(self, llmid, apikey):
 		self.llmid = llmid
-		self.akikey = apikey
+		self.apikey = apikey
 
 	async def complete(self, prompt: str) -> str:
 		hc = StreamHttpClient()
@@ -57,6 +58,7 @@ class DummyLLM(LLM):
 			'llmid': self.llmid,
 			'prompt': prompt
 		}
+		url = 'https://opencomputing.ai/v1/llm'
 		reco = hc('POST', url, headers=headers, data=json.dumps(d))
 		doc = ''
 		async for chunk in liner(reco):
@@ -68,8 +70,8 @@ class DummyLLM(LLM):
 			if d.get('content'):
 				doc = f'{doc}{d["content"]}'
 			else:
-                print(f'{f}:{d} error')
+				print(f'{d} error')
-		return json.loads(doc)
+		return doc
 
 # ---------------------------
 # Agent 实现
@@ -127,7 +129,7 @@ class Agent:
 	# ---------------------------
 	async def resume(self, state: PlanState, user_reply: str):
 		skill_spec = next(s for s in self.skills if s.name == state.skill)
-		schema_fields = next(s.params for s in skill.scripts if s.name==state.script)
+		schema_fields = self.skillkit.get_script_params(state.skill, state.script)
 		if schema_fields is None:
 			schema_fields = []
 		prompt = f"""
@@ -175,14 +177,17 @@ Task:
 	# 内部方法
 	# ---------------------------
 
-	def scripts_info(self, skill):
+	def scripts_info(self, skill_name):
 		d = []
+		skill = self.skillkit.load_skill(skill_name)
 		for s in skill.scripts:
-			d.append( f'name:{s.name}, description:{s.description}, params:{str(s.params}'
+			params = self.skillkit.get_script_params(skill_name, s.name)
-		return "Scripts: '::'.join(d)
+			print(f'{params=}')
+			d.append( f'name:{s.name}, description:{s.description}, params:{str(params)}')
+		return "Scripts: " + '::'.join(d)
 
 	async def _candidate_skills(self, user_text: str):
-        skill_list = "\n".join(f"- skillname:{s.name}({s.description}): {self.scripts_info(s)}" for s in self.skills)
+		skill_list = "\n".join(f"- skillname:{s.name}({s.description}): {self.scripts_info(s.name)}" for s in self.skills)
 		prompt = f"""
 User request:
 \"\"\"{user_text}\"\"\"
@@ -256,9 +261,9 @@ Ask the user a concise clarification question.
 # ---------------------------
 # 测试运行
 # ---------------------------
-async def skillagent(llm, apikey, user_skillroot, sys_skillroot):
+async def skillagent(llm, apikey, user_skillroot, sys_skillroot=None):
 	llm = DummyLLM('8L4hFJ4QpSMyu1UP03Juo', 'eYgNuD6sVQgbj-khOOUNU')
-	skillkit = SkillKitWrapper(skill_rootpath)
+	skillkit = SkillkitWrapper(user_skillroot)
 	agent = Agent(llm, skillkit)
 
 	while True:

skillagent/skillkit_wrapper.py

@@ -3,6 +3,7 @@ from skillkit import SkillManager
 import yaml
 from pathlib import Path
 from typing import Dict, Any
+from appPublic.dictObject import DictObject
 
 def find_missing_params(
     input_schema: Dict[str, Any],
@@ -19,7 +20,7 @@ def find_missing_params(
 
     return missing
 
-def load_schemas(yaml_path: str) -> Dict[str, Any]:
+def load_schemas(path) -> Dict[str, Any]:
 	"""
 	从 YAML 文件中读取 script 输入参数定义
 
@@ -32,47 +33,46 @@ def load_schemas(yaml_path: str) -> Dict[str, Any]:
 		}
 	}
 	"""
-	path = Path(yaml_path)
 	if not path.exists():
 		raise FileNotFoundError(f"Script yaml not found: {yaml_path}")
 
 	with path.open("r", encoding="utf-8") as f:
 		data = yaml.safe_load(f)
 	
-	if "script" not in data or "inputs" not in data:
+	return DictObject(data)
-		raise ValueError("Invalid script yaml format")
-
-	return {
-		"script": data["script"],
-		"description": data.get("description", ""),
-		"inputs": data["inputs"],
-	}
 
 class SkillkitWrapper:
 	def __init__(self, user_skillsroot, sys_skillsroot=None):
 		
-		self.client = SkillManager(project_skill_dir=skillroot,
+		self.client = SkillManager(project_skill_dir=user_skillsroot,
 						anthropic_config_dir=sys_skillsroot)
 		self.client.discover()
+		self.schemas = {}
 
 	def list_skills(self):
 		return self.client.list_skills()
 
-	def load_skill(self, skillname):
+	def load_skill(self, skill_name):
 		skill = self.client.load_skill(skill_name)
-		if not hasattr(skill, 'schemas'):
+		print(skill, dir(skill))
-			fp = os.path.join(skill.base_dir, 'schemas.yaml')
+		schemaspath = skill.base_directory / 'schemas.yaml'
-			if os.path.exists(fp):
+		if schemaspath.exists():
-				data = load_schema(fp)
+			if not self.schemas.get(skill_name):
-				skill.schemas = data
+				data = load_schemas(schemaspath)
-				for s in skill.scripts:
+				self.schemas[skill_name] = data
-					s.params = next(sch.inputs for sch in skill.schemas if sch.script==script_name)
+				print(f'{data=}, {str(schemaspath)}')
 
 		return skill
 
 	def get_script_params(self, skill_name, script_name):
 		skill = self.load_skill(skill_name)
-		return next(s.params for s in skill.scripts if s.name==script_name)
+		d = self.schemas.get('skill_name')
+		if not d:
+			return []
+		m = d.scripts.get(script_name)
+		if not m:
+			return []
+		return m.inputs
 
 	def get_skill_scripts(self, skill_name):
 		skill = self.load_skill(skill_name)