From e7ed12bec5a45d9d6a365a10cde42c5acb214e65 Mon Sep 17 00:00:00 2001 From: DavdGao Date: Wed, 21 Aug 2024 19:39:58 +0800 Subject: [PATCH] Add example for router agent (#416) * Add example for router agent --- README.md | 13 ++-- README_ZH.md | 16 ++-- .../conversation_with_router_agent/README.md | 44 +++++++++++ .../conversation_with_router_agent/main.py | 76 +++++++++++++++++++ .../router_agent.py | 72 ++++++++++++++++++ 5 files changed, 206 insertions(+), 15 deletions(-) create mode 100644 examples/conversation_with_router_agent/README.md create mode 100644 examples/conversation_with_router_agent/main.py create mode 100644 examples/conversation_with_router_agent/router_agent.py diff --git a/README.md b/README.md index 0a2f1a6fb..aa3d8c247 100644 --- a/README.md +++ b/README.md @@ -49,11 +49,11 @@ Start building LLM-empowered multi-agent applications in an easier way. - new**[2024-07-15]** AgentScope has implemented the Mixture-of-Agents algorithm. Refer to our [MoA example](https://github.com/modelscope/agentscope/blob/main/examples/conversation_mixture_of_agents) for more details. -- new**[2024-06-14]** A new prompt tuning module is available in AgentScope to help developers generate and optimize the agents' system prompts! Refer to our [tutorial](https://modelscope.github.io/agentscope/en/tutorial/209-prompt_opt.html) for more details! +- **[2024-06-14]** A new prompt tuning module is available in AgentScope to help developers generate and optimize the agents' system prompts! Refer to our [tutorial](https://modelscope.github.io/agentscope/en/tutorial/209-prompt_opt.html) for more details! -- new**[2024-06-11]** The RAG functionality is available for agents in **AgentScope** now! [**A quick introduction to RAG in AgentScope**](https://modelscope.github.io/agentscope/en/tutorial/210-rag.html) can help you equip your agent with external knowledge! +- **[2024-06-11]** The RAG functionality is available for agents in **AgentScope** now! [**A quick introduction to RAG in AgentScope**](https://modelscope.github.io/agentscope/en/tutorial/210-rag.html) can help you equip your agent with external knowledge! -- new**[2024-06-09]** We release **AgentScope** v0.0.5 now! In this new version, [**AgentScope Workstation**](https://modelscope.github.io/agentscope/en/tutorial/209-gui.html) (the online version is running on [agentscope.io](https://agentscope.io)) is open-sourced with the refactored [**AgentScope Studio**](https://modelscope.github.io/agentscope/en/tutorial/209-gui.html)! +- **[2024-06-09]** We release **AgentScope** v0.0.5 now! In this new version, [**AgentScope Workstation**](https://modelscope.github.io/agentscope/en/tutorial/209-gui.html) (the online version is running on [agentscope.io](https://agentscope.io)) is open-sourced with the refactored [**AgentScope Studio**](https://modelscope.github.io/agentscope/en/tutorial/209-gui.html)! - **[2024-05-24]** We are pleased to announce that features related to the **AgentScope Workstation** will soon be open-sourced! The online website services are temporarily offline. The online website service will be upgraded and back online shortly. Stay tuned... @@ -163,12 +163,13 @@ the following libraries. - [Conversation with ReAct Agent](https://github.com/modelscope/agentscope/blob/main/examples/conversation_with_react_agent) - [Conversation in Natural Language to Query SQL](https://github.com/modelscope/agentscope/blob/main/examples/conversation_nl2sql/) - [Conversation with RAG Agent](https://github.com/modelscope/agentscope/blob/main/examples/conversation_with_RAG_agents) - - new[Conversation with gpt-4o](https://github.com/modelscope/agentscope/blob/main/examples/conversation_with_gpt-4o) - - new[Conversation with Software Engineering Agent](https://github.com/modelscope/agentscope/blob/main/examples/conversation_with_swe-agent/) - - new[Conversation with Customized Tools](https://github.com/modelscope/agentscope/blob/main/examples/conversation_with_customized_services/) + - [Conversation with gpt-4o](https://github.com/modelscope/agentscope/blob/main/examples/conversation_with_gpt-4o) + - [Conversation with Software Engineering Agent](https://github.com/modelscope/agentscope/blob/main/examples/conversation_with_swe-agent/) + - [Conversation with Customized Tools](https://github.com/modelscope/agentscope/blob/main/examples/conversation_with_customized_services/) - new[Mixture of Agents Algorithm](https://github.com/modelscope/agentscope/blob/main/examples/conversation_mixture_of_agents/) - new[Conversation in Stream Mode](https://github.com/modelscope/agentscope/blob/main/examples/conversation_in_stream_mode/) - new[Conversation with CodeAct Agent](https://github.com/modelscope/agentscope/blob/main/examples/conversation_with_codeact_agent/) + - new[Conversation with Router Agent](https://github.com/modelscope/agentscope/blob/main/examples/conversation_with_router_agent/) - Game diff --git a/README_ZH.md b/README_ZH.md index 3d3e5c5d9..20337db41 100644 --- a/README_ZH.md +++ b/README_ZH.md @@ -50,11 +50,11 @@ - new**[2024-07-15]** AgentScope 中添加了 Mixture of Agents 算法。使用样例请参考 [MoA 示例](https://github.com/modelscope/agentscope/blob/main/examples/conversation_mixture_of_agents)。 -- new**[2024-06-14]** 新的提示调优（Prompt tuning）模块已经上线 AgentScope，用以帮助开发者生成和优化智能体的 system prompt。更多的细节和使用样例请参考 AgentScope [教程](https://modelscope.github.io/agentscope/en/tutorial/209-prompt_opt.html)！ +- **[2024-06-14]** 新的提示调优（Prompt tuning）模块已经上线 AgentScope，用以帮助开发者生成和优化智能体的 system prompt。更多的细节和使用样例请参考 AgentScope [教程](https://modelscope.github.io/agentscope/en/tutorial/209-prompt_opt.html)！ -- new**[2024-06-11]** RAG功能现在已经整合进 **AgentScope** 中! 大家可以根据 [**简要介绍AgentScope中的RAG**](https://modelscope.github.io/agentscope/en/tutorial/210-rag.html) ，让自己的agent用上外部知识! +- **[2024-06-11]** RAG功能现在已经整合进 **AgentScope** 中! 大家可以根据 [**简要介绍AgentScope中的RAG**](https://modelscope.github.io/agentscope/en/tutorial/210-rag.html) ，让自己的agent用上外部知识! -- new**[2024-06-09]** AgentScope v0.0.5 已经更新！在这个新版本中，我们开源了 [**AgentScope Workstation**](https://modelscope.github.io/agentscope/en/tutorial/209-gui.html) (在线版本的网址是[agentscope.io](https://agentscope.io))！ +- **[2024-06-09]** AgentScope v0.0.5 已经更新！在这个新版本中，我们开源了 [**AgentScope Workstation**](https://modelscope.github.io/agentscope/en/tutorial/209-gui.html) (在线版本的网址是[agentscope.io](https://agentscope.io))！ - **[2024-05-24]** 我们很高兴地宣布 **AgentScope Workstation** 相关功能即将开源。我们的网站服务暂时下线。在线服务会很快升级重新上线，敬请期待... @@ -153,15 +153,13 @@ AgentScope支持使用以下库快速部署本地模型服务。 - [与ReAct智能体对话](./examples/conversation_with_react_agent) - [通过对话查询SQL信息](./examples/conversation_nl2sql/) - [与RAG智能体对话](./examples/conversation_with_RAG_agents) - - new[与gpt-4o模型对话](./examples/conversation_with_gpt-4o) - - new[与自定义服务对话](./examples/conversation_with_customized_services/) - - - new[与SoftWare Engineering智能体对话](./examples/conversation_with_swe-agent/) - - new[自定义工具函数](./examples/conversation_with_customized_services/) + - [与gpt-4o模型对话](./examples/conversation_with_gpt-4o) + - [自定义工具函数](./examples/conversation_with_customized_services/) + - [与SoftWare Engineering智能体对话](./examples/conversation_with_swe-agent/) - new[Mixture of Agents算法](https://github.com/modelscope/agentscope/blob/main/examples/conversation_mixture_of_agents/) - new[流式对话](https://github.com/modelscope/agentscope/blob/main/examples/conversation_in_stream_mode/) - new[与CodeAct智能体对话](https://github.com/modelscope/agentscope/blob/main/examples/conversation_with_codeact_agent/) - + - new[与Router Agent对话](https://github.com/modelscope/agentscope/blob/main/examples/conversation_with_router_agent/) - 游戏 - [五子棋](./examples/game_gomoku) diff --git a/examples/conversation_with_router_agent/README.md b/examples/conversation_with_router_agent/README.md new file mode 100644 index 000000000..cf4f90ccc --- /dev/null +++ b/examples/conversation_with_router_agent/README.md @@ -0,0 +1,44 @@ +# Conversation with Router Agent + +This example will show +- How to build a router agent to route questions to agents with different abilities. + +The router agent is expected to route questions to the corresponding agents according to the question type in the following response +```text +{The thought of router agent} +{agent name} +``` +If the router agent decides to answer the question itself, the response should be +```text +{The thought of router agent} +{The answer} +``` + +## Note +This example is only for demonstration purposes. We simply use two agents who are good at math and history respectively. +You can replace them with any other agents according to your needs. + +Besides, the memory management of the involved agents is not considered in this example. +For example, does the router agent need to know the answer from the sub-agents? +Improvements are encouraged by developers according to their own needs. + +## Tested Models + +These models are tested in this example. For other models, some modifications may be needed. +- gpt-4o +- qwen-max + + +## Prerequisites + +1. Fill your model configuration correctly in `main.py`. +2. Install the latest version of Agentscope from GitHub. +```bash +git clone https://github.com/modelscope/agentscope.git +cd agentscope +pip install -e . +``` +3. Run the example and input your questions. +```bash +python main.py +``` diff --git a/examples/conversation_with_router_agent/main.py b/examples/conversation_with_router_agent/main.py new file mode 100644 index 000000000..0624e3996 --- /dev/null +++ b/examples/conversation_with_router_agent/main.py @@ -0,0 +1,76 @@ +# -*- coding: utf-8 -*- +"""The main script for the example of conversation with router agent.""" +from router_agent import RouterAgent + +import agentscope +from agentscope.agents import DialogAgent, UserAgent + +# ================== Prepare model configuration ============================= + +YOUR_MODEL_CONFIGURATION_NAME = "{YOUR_MODEL_CONFIGURATION_NAME}" +YOUR_MODEL_CONFIGURATION = { + "config_name": YOUR_MODEL_CONFIGURATION_NAME, + # ... +} + +# ============================================================================ + +agentscope.init( + model_configs=YOUR_MODEL_CONFIGURATION, + project="Conversation with router agent", +) + +# Let's build some working agents with different capabilities. For simplicity, +# we just use the same agent. You can replace them with your own agents. +agent_math = DialogAgent( + name="Math", + sys_prompt="You are a math assistant to help solve math problems.", + model_config_name=YOUR_MODEL_CONFIGURATION_NAME, +) + +agent_history = DialogAgent( + name="History", + sys_prompt="You are an assistant who is good at history.", + model_config_name=YOUR_MODEL_CONFIGURATION_NAME, +) + +# Init a router agent +SYS_PROMPT_ROUTER = """You're a router assistant named {name}. + +## YOUR TARGET +1. Given agents with different capabilities, your target is to assign questions to the corresponding agents according to the user requirement. +2. You should make full use of the different abilities of the given agents. +3. If no agent is suitable to answer user's question, then respond directly. + +## Agents You Can Use +The agents are listed in the format of "{index}. {agent_name}: {agent_description}" +1. math: An agent who is good at math. +2. history: An agent who is good at history. +""" # noqa + +router_agent = RouterAgent( + sys_prompt=SYS_PROMPT_ROUTER, + model_config_name=YOUR_MODEL_CONFIGURATION_NAME, +) + +# Init a user agent +user = UserAgent(name="user") + +# Start the conversation +msg = None +while True: + user_msg = user(msg) + if user_msg.content == "exit": + break + + # Replied by router agent + router_msg = router_agent(user_msg) + + # Route the question to the corresponding agents + if router_msg.metadata == "math": + msg = agent_math(user_msg) + elif router_msg.metadata == "history": + msg = agent_history(user_msg) + else: + # Answer the question by router agent directly + msg = router_msg diff --git a/examples/conversation_with_router_agent/router_agent.py b/examples/conversation_with_router_agent/router_agent.py new file mode 100644 index 000000000..b0e45e67e --- /dev/null +++ b/examples/conversation_with_router_agent/router_agent.py @@ -0,0 +1,72 @@ +# -*- coding: utf-8 -*- +"""The router agent which routes the questions to the corresponding agents.""" +from typing import Optional, Union, Sequence + +from agentscope.agents import AgentBase +from agentscope.message import Msg +from agentscope.parsers import RegexTaggedContentParser + + +# Init a router agent +class RouterAgent(AgentBase): + """ + The router agent who routes the questions to the corresponding agents. + """ + + def __init__( + self, + sys_prompt: str, + model_config_name: str, + ) -> None: + """Init a router agent.""" + self.name = "Router" + + super().__init__( + name=self.name, + model_config_name=model_config_name, + ) + + self.sys_prompt = sys_prompt.format_map({"name": self.name}) + + self.memory.add(Msg(self.name, self.sys_prompt, "system")) + + self.parser = RegexTaggedContentParser( + format_instruction="""Respond with specific tags as outlined below: + +- When routing questions to agents: +what you thought +the agent name + +- When answering questions directly: +what you thought +what you respond +""", + required_keys=["thought"], + ) + + def reply(self, x: Optional[Union[Msg, Sequence[Msg]]] = None) -> Msg: + """The reply function.""" + self.memory.add(x) + + prompt = self.model.format( + self.memory.get_memory(), + Msg("system", self.parser.format_instruction, "system"), + ) + + response = self.model(prompt) + + # To be compatible with streaming mode + self.speak(response.stream or response.text) + + # Parse the response by predefined parser + parsed_dict = self.parser.parse(response).parsed + + msg = Msg(self.name, response.text, "assistant") + + # Assign the question to the corresponding agent in the metadata field + if "agent" in parsed_dict: + msg.metadata = parsed_dict["agent"] + + self.memory.add(msg) + + return msg