Support llm model name link.

1. default
2. plan_llm
3. outline_llm
4. swift_llm

src/aios/__init__.py

@@ -6,7 +6,7 @@ from .proto.agent_task import *
 
 from .agent.agent_base import *
 from .agent.chatsession import AIChatSession
-from .agent.agent import AIAgent,AIAgentTemplete, BaseAIAgent
+from .agent.agent import AIAgent, BaseAIAgent
 from .agent.role import AIRole,AIRoleGroup
 from .agent.workflow import Workflow
 from .agent.agent_memory import AgentMemory

src/aios/agent/agent.py

@@ -31,29 +31,6 @@ from ..proto.compute_task import LLMPrompt,LLMResult
 
 logger = logging.getLogger(__name__)
 
-class AIAgentTemplete:
-    def __init__(self) -> None:
-        self.llm_model_name:str = "gpt-4-turbo-preview"
-        self.max_token_size:int = 0
-        self.template_id:str = None
-        self.introduce:str = None
-        self.author:str = None
-        self.prompt:LLMPrompt = None
-
-
-    def load_from_config(self,config:dict) -> bool:
-        if config.get("llm_model_name") is not None:
-            self.llm_model_name = config["llm_model_name"]
-        if config.get("max_token_size") is not None:
-            self.max_token_size = config["max_token_size"]
-        if config.get("template_id") is not None:
-            self.template_id = config["template_id"]
-        if config.get("prompt") is not None:
-            self.prompt = LLMPrompt()
-            if self.prompt.load_from_config(config["prompt"]) is False:
-                logger.error("load prompt from config failed!")
-                return False
-
 
 class AIAgent(BaseAIAgent):
     def __init__(self) -> None:
@@ -81,19 +58,6 @@ class AIAgent(BaseAIAgent):
         self.history_len = 10
         self.read_report_prompt = None
 
-        todo_prompts = {}
-        todo_prompts[TodoListType.TO_WORK] = {
-            "do": None,
-            "check": None,
-            "review": None,
-        }
-        todo_prompts[TodoListType.TO_LEARN] = {
-            "do": None,
-            "check": None,
-            "review": None,
-        }
-        self.todo_prompts = todo_prompts
-
         self.base_dir = None
         #self.memory_db = None
         self.unread_msg = Queue() # msg from other agent
@@ -178,9 +142,6 @@ class AIAgent(BaseAIAgent):
         return self.template_id
 
     def get_llm_model_name(self) -> str:
-        if self.llm_model_name is None:
-            return AIStorage.get_instance().get_user_config().get_value("llm_model_name")
-
         return self.llm_model_name
 
     def get_max_token_size(self) -> int:

src/aios/frame/compute_kernel.py

@@ -8,6 +8,7 @@ from asyncio import Queue
 
 from ..proto.compute_task import *
 from ..knowledge import ObjectID
+from ..storage.storage import AIStorage
 
 from .compute_node import ComputeNode
 
@@ -122,12 +123,13 @@ class ComputeKernel:
     def llm_num_tokens(prompt: LLMPrompt, model_name: str = None) -> int:
         return ComputeKernel.llm_num_tokens_from_text(prompt.as_str(), model_name)
 
+
     # friendly interface for use:
-    def llm_completion(self, prompt: LLMPrompt, resp_mode:str="text",mode_name: Optional[str] = None, max_token: int = 0,inner_functions = None):
+    def llm_completion(self, prompt: LLMPrompt, resp_mode:str="text",model_name: Optional[str] = None, max_token: int = 0,inner_functions = None):
         # craete a llm_work_task ,push on queue's end
         # then task_schedule would run this task.(might schedule some work_task to another host)
         task_req = ComputeTask()
-        task_req.set_llm_params(prompt,resp_mode,mode_name, max_token,inner_functions)
+        task_req.set_llm_params(prompt,resp_mode,model_name, max_token,inner_functions)
         self.run(task_req)
         return task_req
 

src/aios/proto/compute_task.py

@@ -287,9 +287,9 @@ class ComputeTask:
         self.callchain_id = callchain_id
         self.params["prompts"] = prompts.to_message_list()
         self.params["resp_mode"] = resp_mode
-        if model_name is None:
-             model_name = AIStorage.get_instance().get_user_config().get_value("llm_model_name")
-        self.params["model_name"] = model_name
+        
+        self.params["model_name"] = AIStorage.get_instance().get_user_config().llm_get_real_model_name(model_name)
+ 
         if max_token_size is None:
             self.params["max_token_size"] = 4000
         else:

src/aios/storage/storage.py

@@ -40,7 +40,10 @@ class UserConfig:
         self.config_table = {}
         self.user_config_path:str = None
 
-        self._init_default_value("llm_model_name","gpt-4-turbo-preview")
+        self._init_default_value("llm_default_model","gpt-4-turbo")
+        self._init_default_value("llm_plan_model","gpt-4-turbo")
+        self._init_default_value("llm_outline_model","gpt-3.5-turbo")
+        self._init_default_value("llm_swift_model","gpt-3.5-turbo")
 
     def _init_default_value(self,key:str,value:Any) -> None:
         if self.config_table.get(key) is not None:
@@ -52,6 +55,23 @@ class UserConfig:
         self.config_table[key] = new_config_item
 
 
+    def llm_get_real_model_name(self,mode_name:str) -> str:
+        default_model_name = self.get_value("llm_default_model")
+        plan_llm_model_name = self.get_value("llm_plan_model")
+        outline_model_name = self.get_value("llm_outline_model")
+        swift_model_name = self.get_value("llm_swift_model")
+        if mode_name is None:
+            return default_model_name
+        if mode_name == "default":
+            return default_model_name
+        if mode_name == "plan_llm":
+            return plan_llm_model_name
+        if mode_name == "outline_llm":
+            return outline_model_name
+        if mode_name == "swift_llm":
+            return swift_model_name
+        
+        return mode_name
     def add_user_config(self,key:str,desc:str,is_optional:bool,default_value:Any=None,item_type="str") -> None:
         if self.config_table.get(key) is not None:
             logger.warning("user config key %s already exist, will be overrided",key)

src/component/agent_manager/agent_manager.py

@@ -6,7 +6,7 @@ import sys
 import runpy
 from typing import Any, Callable, Dict, List, Optional, Union
 
-from aios import AIAgent,AIAgentTemplete,AIStorage,BaseAIAgent,PackageEnv,PackageEnvManager,PackageMediaInfo,PackageInstallTask,WorkspaceEnvironment
+from aios import AIAgent,AIStorage,BaseAIAgent,PackageEnv,PackageEnvManager,PackageMediaInfo,PackageInstallTask,WorkspaceEnvironment
 
 logger = logging.getLogger(__name__)
 
@@ -82,12 +82,6 @@ class AgentManager:
     def remove(self,agent_id:str)->int:
         pass
 
-    async def get_templete(self,templete_id) -> AIAgentTemplete:
-        template_media_info = self.agent_templete_env.get(templete_id)
-        if template_media_info is None:
-            return None
-        return self._load_templete_from_media(template_media_info)
-
     def install(self,templete_id) -> PackageInstallTask:
         installer = self.agent_templete_env.get_installer()
         return installer.install(templete_id)
@@ -95,8 +89,7 @@ class AgentManager:
     def uninstall(self,templete_id) -> int:
         pass
 
-    async def _load_templete_from_media(self,templete_media:PackageMediaInfo) -> AIAgentTemplete:
-        pass
+
 
     async def _load_agent_from_media(self,agent_media:PackageMediaInfo) -> BaseAIAgent:
         reader = self.agent_env._create_media_loader(agent_media)

src/node_daemon/__init__.py

@@ -1 +0,0 @@
-# might implement by Rust in the future