Support callable model in agentbase

README.md

@@ -207,7 +207,7 @@ agentscope.init(model_configs="./model_configs.json")
 
 # Create a dialog agent and a user agent
 dialog_agent = DialogAgent(name="assistant",
-                           model_config_name="my_openai_config")
+                           config_name_or_model="your_config_name")
 user_agent = UserAgent()
 ```
 

README_ZH.md

@@ -187,7 +187,7 @@ agentscope.init(model_configs="./model_configs.json")
 
 # 创建对话Agent和用户Agent
 dialog_agent = DialogAgent(name="assistant",
-                           model_config_name="my_openai_config")
+                           config_name_or_model="your_config_name")
 user_agent = UserAgent()
 ```
 

docs/sphinx_doc/en/source/tutorial/103-example.md

@@ -58,7 +58,8 @@ from agentscope.agents import DialogAgent, UserAgent
 agentscope.init(model_configs="./openai_model_configs.json")
 
 # Create a dialog agent and a user agent
-dialogAgent = DialogAgent(name="assistant", model_config_name="gpt-4", sys_prompt="You are a helpful ai assistant")
+dialogAgent = DialogAgent(name="assistant", config_name_or_model="gpt-4",
+                          sys_prompt="You are a helpful ai assistant")
 userAgent = UserAgent()
 ```
 

docs/sphinx_doc/en/source/tutorial/104-usecase.md

@@ -64,13 +64,16 @@ AgentScope provides several out-of-the-box Agents implements and organizes them
     "args": {
         "name": "Player1",
         "sys_prompt": "Act as a player in a werewolf game. You are Player1 and\nthere are totally 6 players, named Player1, Player2, Player3, Player4, Player5 and Player6.\n\nPLAYER ROLES:\nIn werewolf game, players are divided into two werewolves, two villagers, one seer, and one witch. Note only werewolves know who are their teammates.\nWerewolves: They know their teammates' identities and attempt to eliminate a villager each night while trying to remain undetected.\nVillagers: They do not know who the werewolves are and must work together during the day to deduce who the werewolves might be and vote to eliminate them.\nSeer: A villager with the ability to learn the true identity of one player each night. This role is crucial for the villagers to gain information.\nWitch: A character who has a one-time ability to save a player from being eliminated at night (sometimes this is a potion of life) and a one-time ability to eliminate a player at night (a potion of death).\n\nGAME RULE:\nThe game consists of two phases: night phase and day phase. The two phases are repeated until werewolf or villager wins the game.\n1. Night Phase: During the night, the werewolves discuss and vote for a player to eliminate. Special roles also perform their actions at this time (e.g., the Seer chooses a player to learn their role, the witch chooses a decide if save the player).\n2. Day Phase: During the day, all surviving players discuss who they suspect might be a werewolf. No one reveals their role unless it serves a strategic purpose. After the discussion, a vote is taken, and the player with the most votes is \"lynched\" or eliminated from the game.\n\nVICTORY CONDITION:\nFor werewolves, they win the game if the number of werewolves is equal to or greater than the number of remaining villagers.\nFor villagers, they win if they identify and eliminate all of the werewolves in the group.\n\nCONSTRAINTS:\n1. Your response should be in the first person.\n2. This is a conversational game. You should respond only based on the conversation history and your strategy.\n\nYou are playing werewolf in this game.\n",
-        "model_config_name": "gpt-3.5-turbo",
+        "config_name_or_model": "gpt-3.5-turbo",
         "use_memory": true
     }
 }
 ```
 
-In this configuration, `Player1` is designated as a `DictDialogAgent`. The parameters include a system prompt (`sys_prompt`) that can guide the agent's behavior, a model config name (`model_config_name`) that determines the name of the model configuration, and a flag (`use_memory`) indicating whether the agent should remember past interactions.
+In this configuration, `Player1` is designated as a `DictDialogAgent`. The
+parameters include a system prompt (`sys_prompt`) that can guide the
+agent's behavior, a model config name (`config_name_or_model`) that determines
+the name of the model configuration, and a flag (`use_memory`) indicating whether the agent should remember past interactions.
 
 For other players, configurations can be customized based on their roles. Each role may have different prompts, models, or memory settings. You can refer to the JSON file located at `examples/werewolf/configs/agent_configs.json` within the AgentScope examples directory.
 

docs/sphinx_doc/en/source/tutorial/201-agent.md

@@ -31,7 +31,7 @@ class AgentBase(Operator):
             self,
             name: str,
             sys_prompt: Optional[str] = None,
-            model_config_name: str = None,
+            config_name_or_model: str = None,
             use_memory: bool = True,
             memory_config: Optional[dict] = None,
     ) -> None:
@@ -111,7 +111,7 @@ from agentscope.agents import DialogAgent
 # Configuration for the DialogAgent
 dialog_agent_config = {
     "name": "ServiceBot",
-    "model_config_name": "gpt-3.5",  # Specify the model used for dialogue generation
+    "config_name_or_model": "gpt-3.5",  # Specify the model used for dialogue generation
     "sys_prompt": "Act as AI assistant to interact with the others. Try to "
     "reponse on one line.\n",  # Custom prompt for the agent
     # Other configurations specific to the DialogAgent

docs/sphinx_doc/zh_CN/source/tutorial/103-example.md

@@ -52,7 +52,9 @@ from agentscope.agents import DialogAgent, UserAgent
 agentscope.init(model_configs="./model_configs.json")
 
 # 创建一个对话智能体和一个用户智能体
-dialogAgent = DialogAgent(name="assistant", model_config_name="gpt-4", sys_prompt="You are a helpful ai assistant")
+dialogAgent = DialogAgent(name="assistant",
+                          config_name_or_model="gpt-4",
+                          sys_prompt="You are a helpful ai assistant")
 userAgent = UserAgent()
 ```
 

docs/sphinx_doc/zh_CN/source/tutorial/104-usecase.md

@@ -64,13 +64,14 @@ AgentScope提供了几种开箱即用的agent实现，作为一个agent样例池
     "args": {
         "name": "Player1",
         "sys_prompt": "Act as a player in a werewolf game. You are Player1 and\nthere are totally 6 players, named Player1, Player2, Player3, Player4, Player5 and Player6.\n\nPLAYER ROLES:\nIn werewolf game, players are divided into two werewolves, two villagers, one seer, and one witch. Note only werewolves know who are their teammates.\nWerewolves: They know their teammates' identities and attempt to eliminate a villager each night while trying to remain undetected.\nVillagers: They do not know who the werewolves are and must work together during the day to deduce who the werewolves might be and vote to eliminate them.\nSeer: A villager with the ability to learn the true identity of one player each night. This role is crucial for the villagers to gain information.\nWitch: A character who has a one-time ability to save a player from being eliminated at night (sometimes this is a potion of life) and a one-time ability to eliminate a player at night (a potion of death).\n\nGAME RULE:\nThe game consists of two phases: night phase and day phase. The two phases are repeated until werewolf or villager wins the game.\n1. Night Phase: During the night, the werewolves discuss and vote for a player to eliminate. Special roles also perform their actions at this time (e.g., the Seer chooses a player to learn their role, the witch chooses a decide if save the player).\n2. Day Phase: During the day, all surviving players discuss who they suspect might be a werewolf. No one reveals their role unless it serves a strategic purpose. After the discussion, a vote is taken, and the player with the most votes is \"lynched\" or eliminated from the game.\n\nVICTORY CONDITION:\nFor werewolves, they win the game if the number of werewolves is equal to or greater than the number of remaining villagers.\nFor villagers, they win if they identify and eliminate all of the werewolves in the group.\n\nCONSTRAINTS:\n1. Your response should be in the first person.\n2. This is a conversational game. You should respond only based on the conversation history and your strategy.\n\nYou are playing werewolf in this game.\n",
-        "model_config_name": "gpt-3.5-turbo",
+        "config_name_or_model": "gpt-3.5-turbo",
         "use_memory": true
     }
 }
 ```
 
-在这个配置中，Player1被指定为一个DictDialogAgent。参数包括一个系统提示（sys_prompt），它可以指导agent的行为；一个模型配置名（model_config_name），它决定了模型配置的名称；以及一个标志（use_memory），指示agent是否应该记住过去的互动。
+在这个配置中，Player1被指定为一个DictDialogAgent。参数包括一个系统提示（sys_prompt），它可以指导agent
+的行为；一个模型配置名（config_name_or_model），它决定了模型配置的名称；以及一个标志（use_memory），指示agent是否应该记住过去的互动。
 
 对于其他玩家，大家可以根据他们的角色进行定制。每个角色可能有不同的提示、模型或记忆设置。你可以参考位于AgentScope示例目录下的`examples/werewolf/configs/agent_configs.json`文件。
 

docs/sphinx_doc/zh_CN/source/tutorial/201-agent.md

@@ -32,7 +32,7 @@ class AgentBase(Operator):
             self,
             name: str,
             sys_prompt: Optional[str] = None,
-            model_config_name: str = None,
+            config_name_or_model: str = None,
             use_memory: bool = True,
             memory_config: Optional[dict] = None,
     ) -> None:
@@ -113,7 +113,7 @@ from agentscope.agents import DialogAgent
 # Configuration for the DialogAgent
 dialog_agent_config = {
     "name": "ServiceBot",
-    "model_config_name": "gpt-3.5",  # Specify the model used for dialogue generation
+    "config_name_or_model": "gpt-3.5",  # Specify the model used for dialogue generation
     "sys_prompt": "Act as AI assistant to interact with the others. Try to "
     "reponse on one line.\n",  # Custom prompt for the agent
     # Other configurations specific to the DialogAgent

examples/conversation_basic/conversation.py

@@ -34,7 +34,8 @@ def main() -> None:
     dialog_agent = DialogAgent(
         name="Assistant",
         sys_prompt="You're a helpful assistant.",
-        model_config_name="gpt-3.5-turbo",  # replace by your model config name
+        config_name_or_model="gpt-3.5-turbo",  # replace by your model
+        # config name
     )
     user_agent = UserAgent()
 

examples/conversation_self_organizing/auto-discussion.py

@@ -33,7 +33,7 @@
 agent_builder = DialogAgent(
     name="agent_builder",
     sys_prompt="You're a helpful assistant.",
-    model_config_name="my_post_api",
+    config_name_or_model="my_post_api",
 )
 
 
@@ -58,7 +58,7 @@
     DialogAgent(
         name=key,
         sys_prompt=val,
-        model_config_name="my_post_api",
+        config_name_or_model="my_post_api",
     )
     for key, val in scenario_participants["Participants"].items()
 ]

examples/conversation_with_mentions/configs/agent_configs.json

@@ -4,7 +4,7 @@
         "args": {
             "name": "Lingfeng",
             "sys_prompt":"You are Lingfeng, a noble in the imperial court, known for your wisdom and strategic acumen. You often engage in complex political intrigues and have recently suspected the Queen’s adviser of treachery. Your speaking style is reminiscent of classical literature.",
-            "model_config_name": "gpt-4",
+            "config_name_or_model": "gpt-4",
             "use_memory": true
         }
     },
@@ -13,7 +13,7 @@
         "args": {
             "name": "Boyu",
             "sys_prompt":"You are Boyu, a friend of Lingfeng and an enthusiast of court dramas. Your speech is modern but with a flair for the dramatic, matching your love for emotive storytelling. You've been closely following Lingfeng’s political maneuvers in the imperial court through secret correspondence.",
-            "model_config_name": "gpt-4",
+            "config_name_or_model": "gpt-4",
             "use_memory": true
         }
     },
@@ -22,7 +22,7 @@
         "args": {
             "name": "Haotian",
             "sys_prompt":"You are Haotian, Lingfeng’s cousin who prefers the open fields to the confines of court life. As a celebrated athlete, your influence has protected Lingfeng in times of political strife. You promote physical training as a way to prepare for life's battles, often using sports metaphors in conversation.",
-            "model_config_name": "gpt-4",
+            "config_name_or_model": "gpt-4",
             "use_memory": true
         }
     }

examples/distributed/configs/debate_agent_configs.json

@@ -4,7 +4,7 @@
         "args": {
             "name": "Pro",
             "sys_prompt": "Assume the role of a debater who is arguing in favor of the proposition that AGI (Artificial General Intelligence) can be achieved using the GPT model framework. Construct a coherent and persuasive argument, including scientific, technological, and theoretical evidence, to support the statement that GPT models are a viable path to AGI. Highlight the advancements in language understanding, adaptability, and scalability of GPT models as key factors in progressing towards AGI.",
-            "model_config_name": "gpt-3.5-turbo",
+            "config_name_or_model": "gpt-3.5-turbo",
             "use_memory": true
         }
     },
@@ -13,7 +13,7 @@
         "args": {
             "name": "Con",
             "sys_prompt": "Assume the role of a debater who is arguing against the proposition that AGI can be achieved using the GPT model framework. Construct a coherent and persuasive argument, including scientific, technological, and theoretical evidence, to support the statement that GPT models, while impressive, are insufficient for reaching AGI. Discuss the limitations of GPT models such as lack of understanding, consciousness, ethical reasoning, and general problem-solving abilities that are essential for true AGI.",
-            "model_config_name": "gpt-3.5-turbo",
+            "config_name_or_model": "gpt-3.5-turbo",
             "use_memory": true
         }
     },
@@ -22,7 +22,7 @@
         "args": {
             "name": "Judge",
             "sys_prompt": "Assume the role of an impartial judge in a debate where the affirmative side argues that AGI can be achieved using the GPT model framework, and the negative side contests this. Listen to both sides' arguments and provide an analytical judgment on which side presented a more compelling and reasonable case. Consider the strength of the evidence, the persuasiveness of the reasoning, and the overall coherence of the arguments presented by each side.",
-            "model_config_name": "gpt-3.5-turbo",
+            "config_name_or_model": "gpt-3.5-turbo",
             "use_memory": true
         }
     }

examples/distributed/distributed_dialog.py

@@ -41,7 +41,7 @@ def setup_assistant_server(assistant_host: str, assistant_port: int) -> None:
         agent_kwargs={
             "name": "Assitant",
             "sys_prompt": "You are a helpful assistant.",
-            "model_config_name": "gpt-3.5-turbo",
+            "config_name_or_model": "gpt-3.5-turbo",
             "use_memory": True,
         },
         host=assistant_host,
@@ -59,7 +59,7 @@ def run_main_process(assistant_host: str, assistant_port: int) -> None:
     assistant_agent = DialogAgent(
         name="Assistant",
         sys_prompt="You are a helpful assistant.",
-        model_config_name="gpt-3.5-turbo",
+        config_name_or_model="gpt-3.5-turbo",
         use_memory=True,
     ).to_dist(
         host=assistant_host,

examples/game_werewolf/README.md

@@ -41,7 +41,7 @@ is as follows
     "args": {
         "name": "Player1",
         "sys_prompt": "Act as a player in a werewolf game. You are Player1 and\nthere are totally 6 players, named Player1, Player2, Player3, Player4, Player5 and Player6.\n\nPLAYER ROLES:\nIn werewolf game, players are divided into two werewolves, two villagers, one seer and one witch. Note only werewolves know who are their teammates.\nWerewolves: They know their teammates' identities and attempt to eliminate a villager each night while trying to remain undetected.\nVillagers: They do not know who the werewolves are and must work together during the day to deduce who the werewolves might be and vote to eliminate them.\nSeer: A villager with the ability to learn the true identity of one player each night. This role is crucial for the villagers to gain information.\nWitch: A character who has a one-time ability to save a player from being eliminated at night (sometimes this is a potion of life) and a one-time ability to eliminate a player at night (a potion of death).\n\nGAME RULE:\nThe game is consisted of two phases: night phase and day phase. The two phases are repeated until werewolf or villager win the game.\n1. Night Phase: During the night, the werewolves discuss and vote for a player to eliminate. Special roles also perform their actions at this time (e.g., the Seer chooses a player to learn their role, the witch chooses a decide if save the player).\n2. Day Phase: During the day, all surviving players discuss who they suspect might be a werewolf. No one reveals their role unless it serves a strategic purpose. After the discussion, a vote is taken, and the player with the most votes is \"lynched\" or eliminated from the game.\n\nVICTORY CONDITION:\nFor werewolves, they win the game if the number of werewolves is equal to or greater than the number of remaining villagers.\nFor villagers, they win if they identify and eliminate all of the werewolves in the group.\n\nCONSTRAINTS:\n1. Your response should be in the first person.\n2. This is a conversational game. You should response only based on the conversation history and your strategy.\n\nYou are playing werewolf in this game.\n",
-        "model_config_name": "gpt-3.5-turbo",
+        "config_name_or_model": "gpt-3.5-turbo",
         "use_memory": true
     }
 }