Multi agent (#403)

Co-authored-by: 拿辰 <[email protected]>

apps/multi_roles_chat_room/app.py

@@ -1,13 +1,17 @@
+import os
 import re
+from typing import Optional
 
 import gradio as gr
 import json
 import modelscope_studio as mgr
+from modelscope_agent.multi_agents_utils.executors.ray import RayTaskExecutor
 from role_core import (chat_progress, init_all_remote_actors,
                        start_chat_with_topic)
 from story_holder import get_avatar_by_name, get_story_by_id, stories
 
 chat_history = []
+RayTaskExecutor.init_ray()
 
 # 发送消息的函数
 
@@ -54,6 +58,17 @@ def end_topic():
     return '', 'topic ended。'
 
 
+def check_uuid(uid: Optional[str]) -> str:
+    """Checks whether a UUID is provided or generates a default one."""
+    if not uid or uid == '':
+        if os.getenv('MODELSCOPE_ENVIRONMENT') == 'studio':
+            import gradio as gr
+
+            raise gr.Error('Please login first')
+        uid = 'local_user'
+    return uid
+
+
 def format_entry_html():
     base_html = '''
     <div class="container story-cardlist">
@@ -89,6 +104,8 @@ def format_entry_html():
 with demo:
     state = gr.State({})
     story_state = gr.State('1')  # default value
+    uuid = gr.Textbox(label='modelscope_uuid', visible=False)
+
     with gr.Column(visible=True) as entry:
         gr.Markdown('##  选择一个场景进入聊天吧～')
         entry_btn = gr.Button(
@@ -197,10 +214,13 @@ def back():
     back_btn.click(fn=back, inputs=[], outputs=[entry, content])
 
     def start_chat(username, from_user, topic, _state, _chatbot, _input,
-                   _story_state, select_model):
+                   _story_state, select_model, _uuid):
+        # get uuid
+        _uuid = check_uuid(_uuid)
+        user_task_id = f'{_uuid[:6]}_{_story_state}'
         roles = get_story_by_id(_story_state)['roles']
         _state = init_all_remote_actors(roles, username, _state, _story_state,
-                                        select_model)
+                                        select_model, user_task_id)
         _state = start_chat_with_topic(from_user, topic, _state)
 
         init_chat = [{
@@ -328,7 +348,7 @@ def send_message(_chatbot, _input, _state):
         fn=start_chat,
         inputs=[
             user_select, start_topic_from, start_topic_input, state,
-            user_chatbot, preview_chat_input, story_state, select_model
+            user_chatbot, preview_chat_input, story_state, select_model, uuid
         ],
         outputs=[user_chatbot, preview_chat_input, state])
 

apps/multi_roles_chat_room/requirements.txt

@@ -1 +1,3 @@
 gradio==4.8
+modelscope-agent==0.4.1
+modelscope_studio

apps/multi_roles_chat_room/role_core.py

@@ -8,30 +8,28 @@
 from modelscope_agent import create_component
 from modelscope_agent.agent_env_util import AgentEnvMixin
 from modelscope_agent.agents import MultiRolePlay
-from modelscope_agent.multi_agents_utils.executors.ray import RayTaskExecutor
 from modelscope_agent.task_center import TaskCenter
 from story_holder import get_story_by_id
 
 REMOTE_MODE = True
 
 # instruction prompt
 ROLE_INSTRUCTION_PROMPT = """<|im_start|>system
-你是{role}，请你根据对话情节设定，和你的对话角色设定，继续当前的对话，说话要符合你的角色设定
-
-【你的角色设定】
-{role_description}
-
-【对话情节设定】
-{story}
+你是{role}，请你根据对话情节设定，当前的对话记录和你的对话角色设定，继续当前的对话，说话要符合你的角色设定，不要重复chat history中的内容
 
 【注意事项】
 1. 根据user的历史对话回复时，不要重复说历史对话里的句子，要保持生成内容的有趣，丰富度，多样性
 2. 长话短说，不要说太多话，不要超过50字
+3. 符合当前对话情节设定，围绕对话情节，你是{role}，不要模仿其他角色，也不要重复chat history中的内容
+
+【对话场景】
+{story}
+
+【chat history】
+chat_records
 
 【你的角色设定】
-{role_description}
-<|im_end|>
-"""
+{role_description}<|im_end|>"""
 
 CHATROOM_INSTRUCTION_PROMPT = """<|im_start|>system
 你是一个小说作家，请你根据对话场景、人物介绍及最近的对话记录，选择继续对话的下一个角色。注意，对话历史是以群聊的形式展现，因此角色可能会@某个人表示对这个人说话。
@@ -42,17 +40,17 @@
 【人物介绍】
 {all_roles_info}
 
-【对话记录】
+【chat history】
 chat_records
 
 【最新对话】
 recent_records
 
 【注意事项】
-根据对话记录和最新对话
+根据chat history和最新对话
 1. 当主角{user_role}说话中提到某个角色，你需要只让提到的角色接话。
 2. 不要选【最新对话】里的角色发言
-3. 要让每个角色有平等的对话机会，多选一些【对话记录】没有出现的角色，要求情节充满戏剧性。
+3. 要让每个角色有平等的对话机会，多选一些chat history没有出现的角色，要求情节充满戏剧性。
 4. 只写角色名字即可，每次最多选两个角色，尽量多的选择主角，当前对话的主角是{user_role}
 
 【回复格式】
@@ -91,7 +89,8 @@ def generate_role_instruction(role, story_info):
     return instruction
 
 
-def upsert_role(new_user, user_char, human_input_mode, story_info, llm_config):
+def upsert_role(new_user, user_char, human_input_mode, story_info, llm_config,
+                _uid):
     role = create_component(
         MultiRolePlay,
         name=new_user,
@@ -101,7 +100,8 @@ def upsert_role(new_user, user_char, human_input_mode, story_info, llm_config):
         llm=llm_config,
         function_list=function_list,
         instruction=generate_role_instruction(new_user, story_info),
-        human_input_mode=human_input_mode)
+        human_input_mode=human_input_mode,
+        prefix_name=_uid)
     return role
 
 
@@ -127,9 +127,7 @@ def change_user_role(user_role, state):
 
 
 def init_all_remote_actors(_roles, user_role, _state, _story_state,
-                           select_model):
-    RayTaskExecutor.init_ray()
-
+                           select_model, _uid):
     story_info = get_story_by_id(_story_state)
     llm_config['model'] = select_model
 
@@ -139,7 +137,7 @@ def init_all_remote_actors(_roles, user_role, _state, _story_state,
         return state
 
     task_center = create_component(
-        TaskCenter, name='Task_Center', remote=REMOTE_MODE)
+        TaskCenter, name='Task_Center', remote=REMOTE_MODE, prefix_name=_uid)
 
     # init all agents and task center
     role_agents = []
@@ -148,25 +146,26 @@ def init_all_remote_actors(_roles, user_role, _state, _story_state,
         if role == user_role:
             human_input_mode = 'ON'
         role_agent = upsert_role(role, _roles[role], human_input_mode,
-                                 story_info, llm_config)
+                                 story_info, llm_config, _uid)
 
         role_agents.append(role_agent)
 
     chat_room = create_component(
         MultiRolePlay,
         name='chat_room',
         remote=True,
-        role='chat_room',
         llm=llm_config,
         function_list=function_list,
         instruction=CHATROOM_INSTRUCTION_PROMPT.format(
             all_roles_info=get_all_roles_info(story_info['roles']),
             story=story_info['story'],
             user_role=user_role),
         is_watcher=True,
-        use_history=False)
+        use_history=False,
+        prefix_name=_uid)
 
-    logging.warning(msg=f'time:{time.time()} done create task center')
+    logging.warning(
+        msg=f'time:{time.time()} done create task center with uid: {_uid}')
 
     ray.get(task_center.add_agents.remote(role_agents))
     ray.get(task_center.add_agents.remote([chat_room]))

apps/multi_roles_chat_room/story_holder.py

@@ -31,8 +31,7 @@
 stories = [
     {
         'id': '1',
-        'cover':
-        '//img.alicdn.com/imgextra/i1/O1CN01UHwXNQ2780lrVHY6n_!!6000000007751-0-tps-1024-512.jpg',
+        'cover': '//s21.ax1x.com/2024/04/16/pFxG1zj.jpg',
         'title': '我被美女包围了',
         'description': '用户是男主角顾易，与多位长相、性格都大相径庭的美女相识',
         'roles': ROLES_1,
@@ -41,8 +40,7 @@
     },
     {
         'id': '2',
-        'cover':
-        '//img.alicdn.com/imgextra/i1/O1CN01UHwXNQ2780lrVHY6n_!!6000000007751-0-tps-1024-512.jpg',
+        'cover': '//s21.ax1x.com/2024/04/16/pFxGgw6.png',
         'title': '我是雷军，雷中有“电”，军下有“车”',
         'description': '用户是男主角雷军，小米创始人，最近发布了小米SU7',
         'roles': ROLES_2,

modelscope_agent/__init__.py

@@ -1,21 +1,36 @@
 from .agent import Agent
 
 
-def _create_remote(cls, name, max_concurrency=1, *args, **kwargs):
+def _create_remote(cls,
+                   name,
+                   max_concurrency=1,
+                   force_new=False,
+                   *args,
+                   **kwargs):
     '''
     Create a remote actor by ray
     Args:
         cls: the class to be created
         name: the name of ray actor, also the role name
         max_concurrency: max concurrency of the actor
+        focus_new: force to create a new actor
         *args:
         **kwargs:
 
     Returns:
 
     '''
     import ray
-
+    try:
+        # try to get an existing actor
+        ray_actor = ray.get_actor(name)
+        if force_new:
+            ray.kill(ray_actor)
+        else:
+            return ray_actor
+    except ValueError:
+        pass
+    # if failed, create a new actor
     return ray.remote(
         name=name,
         max_concurrency=max_concurrency)(cls).remote(*args, **kwargs)
@@ -39,11 +54,15 @@ def create_component(cls,
                      name,
                      remote=False,
                      max_concurrency=1,
+                     prefix_name=None,
                      *args,
                      **kwargs):
     kwargs['remote'] = remote
     kwargs['role'] = name
+    kwargs['prefix_name'] = prefix_name
     if remote:
+        if prefix_name is not None:
+            name = f'{prefix_name}_{name}'
         return _create_remote(cls, name, max_concurrency, *args, **kwargs)
     else:
         return _create_local(cls, *args, **kwargs)

modelscope_agent/agent.py

@@ -3,7 +3,7 @@
 
 from modelscope_agent.llm import get_chat_model
 from modelscope_agent.llm.base import BaseChatModel
-from modelscope_agent.tools import TOOL_REGISTRY
+from modelscope_agent.tools.base import TOOL_REGISTRY
 from modelscope_agent.utils.utils import has_chinese_chars
 
 

modelscope_agent/agent_env_util.py

@@ -156,9 +156,6 @@ def step(self,
             history = []
             if self.use_history:
                 history = self.memory.get_history()
-            logger.info(
-                f'reach here 2 {result}, self.human_input_mode {self.human_input_mode}'
-            )
             # run generation
             for frame in self.run(
                     prompt,
@@ -266,10 +263,10 @@ def pull(self):
             else:
                 return ''
 
-    def convert_to_string(self, messages: List[Message], max_turn=5):
+    def convert_to_string(self, messages: List[Message], max_turn=15):
         prompt_template = """{conversation_history}"""
         conversation_history = ''
-        for item in messages[:max_turn]:
+        for item in messages[-1 * max_turn:]:
             conversation_history += f'{item.sent_from}: {item.content}\n'
         return prompt_template.format(
             conversation_history=conversation_history.strip())

modelscope_agent/constants.py

@@ -4,3 +4,6 @@
 DEFAULT_LOG_STORAGE_PATH = DEFAULT_AGENT_ROOT / 'log'
 DEFAULT_SEND_TO = 'all'
 USER_REQUIREMENT = 'user_requirement'
+ENVIRONMENT_NAME = 'env'
+AGENT_REGISTRY_NAME = 'agent_center'
+TASK_CENTER_NAME = 'task_center'