small fixes

metagpt/actions/mi/write_analysis_code.py

@@ -19,7 +19,7 @@ from metagpt.prompts.mi.write_analysis_code import (
     STRUCTUAL_PROMPT,
     TOOL_RECOMMENDATION_PROMPT,
 )
-from metagpt.schema import Message, Plan, SystemMessage
+from metagpt.schema import Message, Plan
 from metagpt.tools import TOOL_REGISTRY
 from metagpt.tools.tool_registry import validate_tool_names
 from metagpt.tools.tool_type import ToolType
@@ -33,11 +33,6 @@ class WriteCodeWithTools(Action):
     # selected tools to choose from, listed by their names. An empty list means selection from all tools.
     selected_tools: list[str] = []
 
-    def _insert_system_message(self, context: list[Message], system_msg: str = None):
-        system_msg = system_msg or self.DEFAULT_SYSTEM_MSG
-        context.insert(0, SystemMessage(content=system_msg)) if context[0].role != "system" else None
-        return context
-
     def _get_tools_by_type(self, tool_type: str) -> dict:
         """
         Retreive tools by tool type from registry, but filtered by pre-selected tool list
@@ -85,15 +80,18 @@ class WriteCodeWithTools(Action):
 
         return tool_schemas
 
-    async def _prepare_tools(self, plan: Plan) -> Tuple[dict, str]:
+    async def _prepare_tools(self, plan: Plan) -> Tuple[dict, str, str]:
         """Prepare tool schemas and usage instructions according to current task
 
         Args:
             plan (Plan): The overall plan containing task information.
 
         Returns:
-            Tuple[dict, str]: A tool schemas ({tool_name: tool_schema_dict}) and a usage prompt for the type of tools selected
+            Tuple[dict, str, str]: A tool schemas ({tool_name: tool_schema_dict}), a usage prompt for the type of tools selected, and examples of using the tools
         """
+        if not self.use_tools:
+            return {}, "", ""
+
         # find tool type from task type through exact match, can extend to retrieval in the future
         tool_type = plan.current_task.task_type
 

metagpt/prompts/mi/write_analysis_code.py

@@ -56,13 +56,11 @@ assert add(1, 2) == 4 # output: -1
 The implementation failed the test cases where the input integers are 1 and 2. The issue arises because the code does not add the two integers together, but instead subtracts the second integer from the first. To fix this issue, we should change the operator from `-` to `+` in the return statement. This will ensure that the function returns the correct output for the given input.
 
 [improved impl]:
-```python
 def add(a: int, b: int) -> int:
    """
    Given integers a and b, return the total value of a and b.
    """
    return a + b
-```
 '''
 
 REFLECTION_PROMPT = """
@@ -107,7 +105,7 @@ column_info = get_column_info(df)
 print("column_info")
 print(column_info)
 ```end
-Otherwise, you may write any codes you see fit. Return an empty string if you think there is no important data to check.
+Otherwise, print out any key variables you see fit. Return an empty string if you think there is no important data to check.
 
 # Constraints:
 - Your code is to be added to a new cell in jupyter.

metagpt/provider/base_llm.py

@@ -105,9 +105,7 @@ class BaseLLM(ABC):
             context.append(self._assistant_msg(rsp_text))
         return self._extract_assistant_rsp(context)
 
-    async def aask_code(
-        self, messages: Union[str, Message, list[dict]], timeout=3, include_language: bool = False, **kwargs
-    ) -> dict:
+    async def aask_code(self, messages: Union[str, Message, list[dict]], timeout=3, **kwargs) -> dict:
         raise NotImplementedError
 
     @abstractmethod

metagpt/provider/openai_api.py

@@ -26,7 +26,7 @@ from tenacity import (
 from metagpt.configs.llm_config import LLMConfig, LLMType
 from metagpt.logs import log_llm_stream, logger
 from metagpt.provider.base_llm import BaseLLM
-from metagpt.provider.constant import CODE_ONLY_FUNCTION_SCHEMA, GENERAL_FUNCTION_SCHEMA
+from metagpt.provider.constant import GENERAL_FUNCTION_SCHEMA
 from metagpt.provider.llm_provider_registry import register_provider
 from metagpt.utils.common import CodeParser, decode_image, process_message
 from metagpt.utils.cost_manager import CostManager, Costs
@@ -153,7 +153,7 @@ class OpenAILLM(BaseLLM):
         self._update_costs(rsp.usage)
         return rsp
 
-    async def aask_code(self, messages: list[dict], timeout: int = 3, include_language: bool = False, **kwargs) -> dict:
+    async def aask_code(self, messages: list[dict], timeout: int = 3, **kwargs) -> dict:
         """Use function of tools to ask a code.
         Note: Keep kwargs consistent with https://platform.openai.com/docs/api-reference/chat/create
 
@@ -161,13 +161,10 @@ class OpenAILLM(BaseLLM):
         >>> llm = OpenAILLM()
         >>> msg = [{'role': 'user', 'content': "Write a python hello world code."}]
         >>> rsp = await llm.aask_code(msg)
-        # -> {'code': "print('Hello, World!')"}
-        >>> rsp = await llm.aask_code(msg, include_language=True)
         # -> {'language': 'python', 'code': "print('Hello, World!')"}
         """
         if "tools" not in kwargs:
-            function_schema = GENERAL_FUNCTION_SCHEMA if include_language else CODE_ONLY_FUNCTION_SCHEMA
-            configs = {"tools": [{"type": "function", "function": function_schema}]}
+            configs = {"tools": [{"type": "function", "function": GENERAL_FUNCTION_SCHEMA}]}
             kwargs.update(configs)
         rsp = await self._achat_completion_function(messages, **kwargs)
         return self.get_choice_function_arguments(rsp)

metagpt/roles/mi/interpreter.py

@@ -96,7 +96,7 @@ class Interpreter(Role):
             return
         logger.info("Check updated data")
         code = await CheckData().run(self.planner.plan)
-        if not code:
+        if not code.strip():
             return
         success = False
         result, success = await self.execute_code.run(code)