Merge remote-tracking branch 'origin/multi-agents' into multi-agents

dbgpt/agent/agents/agent.py

@@ -6,9 +6,11 @@
 from typing import Any, Dict, List, Optional, Union
 
 from ..memory.gpts_memory import GptsMemory
+from dbgpt.core import LLMClient
 from dbgpt.core.interface.llm import ModelMetadata
 
 
+
 class Agent:
     """
     An interface for AI agent.
@@ -48,25 +50,25 @@ def describe(self):
     async def a_send(
         self,
         message: Union[Dict, str],
-        recipient: "Agent",
-        reviewer: "Agent",
+        recipient: Agent,
+        reviewer: Agent,
         request_reply: Optional[bool] = True,
         is_recovery: Optional[bool] = False,
     ):
         """(Abstract async method) Send a message to another agent."""
 
     async def a_receive(
         self,
-        message: Union[Dict],
-        sender: "Agent",
-        reviewer: "Agent",
+        message: Optional[Dict],
+        sender: Agent,
+        reviewer: Agent,
         request_reply: Optional[bool] = None,
         silent: Optional[bool] = False,
         is_recovery: Optional[bool] = False,
     ):
         """(Abstract async method) Receive a message from another agent."""
 
-    async def a_review(self, message: Union[Dict, str], censored: "Agent"):
+    async def a_review(self, message: Union[Dict, str], censored: Agent):
         """
 
         Args:
@@ -84,21 +86,21 @@ async def a_generate_reply(
         self,
         message: Optional[Dict],
         sender: Agent,
-        reviewer: "Agent",
+        reviewer: Agent,
         silent: Optional[bool] = False,
         **kwargs,
     ) -> Union[str, Dict, None]:
         """(Abstract async method) Generate a reply based on the received messages.
 
         Args:
-            messages (list[dict]): a list of messages received.
+            messages (Optional[Dict]): a dict of messages received from other agents.
             sender: sender of an Agent instance.
         Returns:
             str or dict or None: the generated reply. If None, no reply is generated.
         """
 
     async def a_reasoning_reply(
-        self, messages: Union[List[str]]
+        self, messages: Optional[List[Dict]]
     ) -> Union[str, Dict, None]:
         """
         Based on the requirements of the current agent, reason about the current task goal through LLM
@@ -112,7 +114,7 @@ async def a_reasoning_reply(
     async def a_action_reply(
         self,
         messages: Optional[str],
-        sender: "Agent",
+        sender: Agent,
         **kwargs,
     ) -> Union[str, Dict, None]:
         """
@@ -128,8 +130,8 @@ async def a_action_reply(
     async def a_verify_reply(
         self,
         message: Optional[Dict],
-        sender: "Agent",
-        reviewer: "Agent",
+        sender: Agent,
+        reviewer: Agent,
         **kwargs,
     ) -> Union[str, Dict, None]:
         """
@@ -151,7 +153,7 @@ class AgentResource:
     introduce: str
 
     @staticmethod
-    def from_dict(d: Dict[str, Any]) -> AgentResource:
+    def from_dict(d: Dict[str, Any]) -> Optional[AgentResource]:
         if d is None:
             return None
         return AgentResource(
@@ -167,7 +169,7 @@ def to_dict(self) -> Dict[str, Any]:
 @dataclass
 class AgentContext:
     conv_id: str
-    llm_provider: Optional["LLMClient"]
+    llm_provider: LLMClient
 
     gpts_name: Optional[str] = None
     resource_db: Optional[AgentResource] = None

dbgpt/agent/agents/base_agent.py

@@ -33,9 +33,9 @@ class ConversableAgent(Agent):
     def __init__(
         self,
         name: str,
-        describe: Optional[str] = DEFAULT_SYSTEM_MESSAGE,
+        describe: str = DEFAULT_SYSTEM_MESSAGE,
         memory: GptsMemory = GptsMemory(),
-        agent_context: Optional[AgentContext] = None,
+        agent_context: AgentContext = None,
         system_message: Optional[str] = DEFAULT_SYSTEM_MESSAGE,
         is_termination_msg: Optional[Callable[[Dict], bool]] = None,
         max_consecutive_auto_reply: Optional[int] = None,
@@ -55,7 +55,7 @@ def __init__(
             if is_termination_msg is not None
             else (lambda x: x.get("content") == "TERMINATE")
         )
-
+        
         self.client = AIWrapper(llm_client=agent_context.llm_provider)
 
         self.human_input_mode = human_input_mode
@@ -72,8 +72,9 @@ def __init__(
         self.dialogue_memory_rounds = 5
         self._default_auto_reply = default_auto_reply
         self._reply_func_list = []
+        self._max_consecutive_auto_reply_dict = {}
 
-        self.agent_context: AgentContext = agent_context
+        self.agent_context = agent_context
 
     def register_reply(
         self,
@@ -136,7 +137,8 @@ def max_consecutive_auto_reply(self, sender: Optional[Agent] = None) -> int:
         )
 
     @property
-    def chat_messages(self) -> Dict[Agent, List[Dict]]:
+    # def chat_messages(self) -> Dict[Agent, List[Dict]]:
+    def chat_messages(self) -> Any:
         """A dictionary of conversations from agent to list of messages."""
         all_gpts_messages = self.memory.message_memory.get_by_agent(
             self.agent_context.conv_id, self.name
@@ -189,13 +191,13 @@ def _message_to_dict(message: Union[Dict, str]):
         else:
             return dict(message)
 
-    def append_rely_message(self, message: Optional[Dict], role) -> bool:
+    def append_rely_message(self, message: Union[Dict, str], role) -> None:
         message = self._message_to_dict(message)
         message["role"] = role
         # create oai message to be appended to the oai conversation that can be passed to oai directly.
         self._rely_messages.append(message)
 
-    def reset_rely_message(self) -> bool:
+    def reset_rely_message(self) -> None:
         # create oai message to be appended to the oai conversation that can be passed to oai directly.
         self._rely_messages = []
 
@@ -355,9 +357,9 @@ def _process_action_reply(self, action_reply: Optional[Union[str, Dict, None]]):
             return dict(action_reply)
 
     def _gpts_message_to_ai_message(
-        self, gpts_messages: List[GptsMessage]
+        self, gpts_messages: Optional[List[GptsMessage]]
     ) -> List[Dict]:
-        oai_messages: list[dict] = []
+        oai_messages: List[Dict] = []
         ###Based on the current agent, all messages received are user, and all messages sent are assistant.
         for item in gpts_messages:
             role = ""
@@ -668,7 +670,7 @@ def _select_llm_model(self, old_model: str = None):
         return now_model.model
 
     async def a_reasoning_reply(
-        self, messages: Union[List[Dict]]
+        self, messages: Optional[List[Dict]] = None
     ) -> Union[str, Dict, None]:
         """(async) Reply based on the conversation history and the sender.
         Args:

dbgpt/agent/agents/expand/code_assistant_agent.py

@@ -6,7 +6,7 @@
 from dbgpt.util.string_utils import str_to_bool
 
 from ...memory.gpts_memory import GptsMemory
-from ..agent import Agent
+from ..agent import Agent, AgentContext
 from ..base_agent import ConversableAgent
 from dbgpt.core.interface.message import ModelMessageRoleType
 
@@ -59,8 +59,8 @@ class CodeAssistantAgent(ConversableAgent):
 
     def __init__(
         self,
-        agent_context: "AgentContext",
-        memory: GptsMemory = None,
+        agent_context: AgentContext,
+        memory: Optional[GptsMemory] = None,
         describe: Optional[str] = DEFAULT_DESCRIBE,
         is_termination_msg: Optional[Callable[[Dict], bool]] = None,
         max_consecutive_auto_reply: Optional[int] = None,
@@ -115,7 +115,7 @@ async def generate_code_execution_reply(
         self,
         message: Optional[str] = None,
         sender: Optional[Agent] = None,
-        reviewer: "Agent" = None,
+        reviewer: Optional[Agent] = None,
         config: Optional[Union[Dict, Literal[False]]] = None,
     ):
         """Generate a reply using code execution."""

dbgpt/agent/agents/expand/dashboard_assistant_agent.py

@@ -5,7 +5,7 @@
 from dbgpt.util.json_utils import find_json_objects
 
 from ...memory.gpts_memory import GptsMemory
-from ..agent import Agent
+from ..agent import Agent, AgentContext
 from ..base_agent import ConversableAgent
 
 try:
@@ -54,7 +54,7 @@ class DashboardAssistantAgent(ConversableAgent):
     def __init__(
         self,
         memory: GptsMemory,
-        agent_context: "AgentContext",
+        agent_context: AgentContext,
         describe: Optional[str] = DEFAULT_DESCRIBE,
         is_termination_msg: Optional[Callable[[Dict], bool]] = None,
         max_consecutive_auto_reply: Optional[int] = None,
@@ -82,7 +82,7 @@ async def generate_dashboard_reply(
         self,
         message: Optional[str] = None,
         sender: Optional[Agent] = None,
-        reviewer: "Agent" = None,
+        reviewer: Optional[Agent] = None,
         config: Optional[Union[Dict, Literal[False]]] = None,
     ):
         """Generate a reply using code execution."""

dbgpt/agent/agents/expand/data_scientist_agent.py

@@ -8,7 +8,7 @@
 from dbgpt.util.json_utils import find_json_objects
 
 from ...memory.gpts_memory import GptsMemory
-from ..agent import Agent
+from ..agent import Agent, AgentContext
 from ..base_agent import ConversableAgent
 
 try:
@@ -56,7 +56,7 @@ class DataScientistAgent(ConversableAgent):
     def __init__(
         self,
         memory: GptsMemory,
-        agent_context: "AgentContext",
+        agent_context: AgentContext,
         describe: Optional[str] = DEFAULT_DESCRIBE,
         is_termination_msg: Optional[Callable[[Dict], bool]] = None,
         max_consecutive_auto_reply: Optional[int] = None,
@@ -93,7 +93,7 @@ async def generate_analysis_chart_reply(
         self,
         message: Optional[str] = None,
         sender: Optional[Agent] = None,
-        reviewer: "Agent" = None,
+        reviewer: Optional[Agent] = None,
         config: Optional[Union[Dict, Literal[False]]] = None,
     ):
         """Generate a reply using code execution."""

dbgpt/agent/agents/expand/plugin_assistant_agent.py

@@ -6,7 +6,7 @@
 from dbgpt.util.json_utils import find_json_objects
 
 from ...memory.gpts_memory import GptsMemory
-from ..agent import Agent
+from ..agent import Agent, AgentContext
 from ..base_agent import ConversableAgent
 
 try:
@@ -65,7 +65,7 @@ class PluginAgent(ConversableAgent):
     def __init__(
         self,
         memory: GptsMemory,
-        agent_context: "AgentContext",
+        agent_context: AgentContext,
         describe: Optional[str] = DEFAULT_DESCRIBE,
         is_termination_msg: Optional[Callable[[Dict], bool]] = None,
         max_consecutive_auto_reply: Optional[int] = None,
@@ -98,7 +98,7 @@ async def tool_call(
         self,
         message: Optional[str] = None,
         sender: Optional[Agent] = None,
-        reviewer: "Agent" = None,
+        reviewer: Optional[Agent] = None,
         config: Optional[Union[Dict, Literal[False]]] = None,
     ):
         """Generate a reply using code execution."""

dbgpt/agent/agents/expand/sql_assistant_agent.py

@@ -5,7 +5,7 @@
 
 from dbgpt.agent.plugin.commands.command_mange import ApiCall
 from ...memory.gpts_memory import GptsMemory
-from ..agent import Agent
+from ..agent import Agent, AgentContext
 
 try:
     from termcolor import colored
@@ -48,7 +48,7 @@ class SQLAssistantAgent(ConversableAgent):
     def __init__(
         self,
         memory: GptsMemory,
-        agent_context: "AgentContext",
+        agent_context: AgentContext,
         describe: Optional[str] = DEFAULT_DESCRIBE,
         is_termination_msg: Optional[Callable[[Dict], bool]] = None,
         max_consecutive_auto_reply: Optional[int] = None,
@@ -84,7 +84,7 @@ async def generate_analysis_chart_reply(
         self,
         message: Optional[str] = None,
         sender: Optional[Agent] = None,
-        reviewer: "Agent" = None,
+        reviewer: Optional[Agent] = None,
         config: Optional[Union[Dict, Literal[False]]] = None,
     ):
         """Generate a reply using code execution."""

dbgpt/agent/agents/llm/llm_client.py

@@ -1,7 +1,7 @@
 import json
 import logging
 import traceback
-from typing import Callable, Dict, Optional
+from typing import Callable, Dict, Optional, Union
 
 from dbgpt.core import LLMClient
 from dbgpt.core.interface.output_parser import BaseOutputParser
@@ -34,7 +34,7 @@ def __init__(
     @classmethod
     def instantiate(
         cls,
-        template: str | Callable | None,
+        template: Optional[Union[str, Callable]] = None,
         context: Optional[Dict] = None,
         allow_format_str_template: Optional[bool] = False,
     ):

dbgpt/agent/agents/plan_group_chat.py

@@ -250,7 +250,7 @@ def __init__(
         self.planner = planner
 
     async def a_reasoning_reply(
-        self, messages: Union[List[Dict]]
+        self, messages: Optional[List[Dict]] = None
     ) -> Union[str, Dict, None]:
         if messages is None or len(messages) <= 0:
             message = None

dbgpt/agent/agents/planner_agent.py

@@ -83,7 +83,7 @@ def __init__(
         self,
         memory: GptsMemory,
         plan_chat: PlanChat,
-        agent_context: "AgentContext",
+        agent_context: AgentContext,
         is_termination_msg: Optional[Callable[[Dict], bool]] = None,
         max_consecutive_auto_reply: Optional[int] = None,
         human_input_mode: Optional[str] = "NEVER",
@@ -136,7 +136,7 @@ async def _a_planning(
         self,
         message: Optional[str] = None,
         sender: Optional[Agent] = None,
-        reviewer: "Agent" = None,
+        reviewer: Optional[Agent] = None,
         config: Optional[Any] = None,
     ) -> Tuple[bool, Union[str, Dict, None]]:
         json_objects = find_json_objects(message)