feat(agent): More general ReAct Agent (#2556)

examples/agents/react_agent_example.py

@@ -6,6 +6,7 @@ import sys
 from typing_extensions import Annotated, Doc
 
 from dbgpt.agent import AgentContext, AgentMemory, LLMConfig, UserProxyAgent
+from dbgpt.agent.expand.actions.react_action import ReActAction, Terminate
 from dbgpt.agent.expand.react_agent import ReActAgent
 from dbgpt.agent.resource import ToolPack, tool
 
@@ -16,17 +17,13 @@ logging.basicConfig(
 )
 
 
-@tool
-def terminate(
-    final_answer: Annotated[str, Doc("final literal answer about the goal")],
-) -> str:
-    """When the goal achieved, this tool must be called."""
-    return final_answer
-
-
 @tool
 def simple_calculator(first_number: int, second_number: int, operator: str) -> float:
-    """Simple calculator tool. Just support +, -, *, /."""
+    """Simple calculator tool. Just support +, -, *, /.
+    When users need to do numerical calculations, you must use this tool to calculate, \
+    and you are not allowed to directly infer calculation results from user input or \
+    external observations.
+    """
     if isinstance(first_number, str):
         first_number = int(first_number)
     if isinstance(second_number, str):
@@ -52,22 +49,28 @@ def count_directory_files(path: Annotated[str, Doc("The directory path")]) -> in
 
 
 async def main():
-    from dbgpt.model.proxy.llms.siliconflow import SiliconFlowLLMClient
+    from dbgpt.model import AutoLLMClient
 
-    llm_client = SiliconFlowLLMClient(
-        model_alias="Qwen/Qwen2-7B-Instruct",
+    llm_client = AutoLLMClient(
+        # provider=os.getenv("LLM_PROVIDER", "proxy/deepseek"),
+        # name=os.getenv("LLM_MODEL_NAME", "deepseek-chat"),
+        provider=os.getenv("LLM_PROVIDER", "proxy/siliconflow"),
+        name=os.getenv("LLM_MODEL_NAME", "Qwen/Qwen2.5-Coder-32B-Instruct"),
     )
     agent_memory = AgentMemory()
     agent_memory.gpts_memory.init(conv_id="test456")
 
-    context: AgentContext = AgentContext(conv_id="test456", gpts_app_name="ReAct")
+    # It is important to set the temperature to a low value to get a better result
+    context: AgentContext = AgentContext(
+        conv_id="test456", gpts_app_name="ReAct", temperature=0.01
+    )
 
-    tools = ToolPack([simple_calculator, count_directory_files, terminate])
+    tools = ToolPack([simple_calculator, count_directory_files, Terminate()])
 
     user_proxy = await UserProxyAgent().bind(agent_memory).bind(context).build()
 
     tool_engineer = (
-        await ReActAgent(end_action_name="terminate", max_steps=10)
+        await ReActAgent(max_retry_count=10)
         .bind(context)
         .bind(LLMConfig(llm_client=llm_client))
         .bind(agent_memory)
@@ -78,7 +81,9 @@ async def main():
     await user_proxy.initiate_chat(
         recipient=tool_engineer,
         reviewer=user_proxy,
-        message="Calculate the product of 10 and 99, Count the number of files in /tmp， answer in Chinese.",
+        message="Calculate the product of 10 and 99, then count the number of files in /tmp",
+        # message="Calculate the product of 10 and 99",
+        # message="Count the number of files in /tmp",
     )
 
     # dbgpt-vis message infos