commit some debug log

chatchat_data/model_settings.yaml

@@ -40,7 +40,7 @@ LLM_MODEL_CONFIG:
     prompt_name: default
     callbacks: false
   llm_model:
-    model: 'qwen2-instruct'
+    model: ''
     temperature: 0.9
     max_tokens: 4096
     history_len: 10

libs/chatchat-server/chatchat/server/agent/tools_factory/tools_registry.py

@@ -1,13 +1,12 @@
 from __future__ import annotations
 
 import json
-import logging
 import re
 from typing import Any, Callable, Dict, Optional, Tuple, Type, Union
 
 from langchain.agents import tool
 from langchain_core.tools import BaseTool
-
+from chatchat.utils import build_logger
 from chatchat.server.knowledge_base.kb_doc_api import DocumentWithVSId
 from chatchat.server.pydantic_v1 import BaseModel, Extra
 
@@ -24,6 +23,7 @@ BaseTool.Config.extra = Extra.allow
 ################################### TODO: workaround to langchain #15855
 # patch BaseTool to support tool parameters defined using pydantic Field
 
+logger = build_logger()
 
 def _new_parse_input(
     self,
@@ -32,8 +32,9 @@ def _new_parse_input(
     """Convert tool input to pydantic model."""
     try:
         input_args = self.args_schema
+        logger.info(f"input_args:{input_args}, tool_input:{tool_input}")
         if isinstance(tool_input, str):
-            logging.info(f"tool_input:{tool_input}")
+            logger.info(f"tool_input:{tool_input}")
             if input_args is not None:
                 key_ = next(iter(input_args.__fields__.keys()))
                 input_args.validate({key_: tool_input})
@@ -41,18 +42,18 @@ def _new_parse_input(
         else:
             if input_args is not None:
                 result = input_args.parse_obj(tool_input)
-                logging.info(f"result:{result}")
+                logger.info(f"result:{result}")
                 return result.dict()
     except Exception as e:
         msg = f"Caught exception: {e}"
-        logging.error(f"{e.__class__.__name__}: {msg}")
+        logger.error(f"{e.__class__.__name__}: {msg}")
 
 
 def _new_to_args_and_kwargs(self, tool_input: Union[str, Dict]) -> Tuple[Tuple, Dict]:
     # For backwards compatibility, if run_input is a string,
     # pass as a positional argument.
     if isinstance(tool_input, str):
-        logging.info(f"tool_input:{tool_input}")
+        logger.info(f"tool_input:{tool_input}")
         return (tool_input,), {}
     else:
         # for tool defined with `*args` parameters
@@ -63,7 +64,7 @@ def _new_to_args_and_kwargs(self, tool_input: Union[str, Dict]) -> Tuple[Tuple,
         #       .search_api
         if "args" in tool_input:
             args = tool_input["args"]
-            logging.info(f"args:{args}")
+            logger.info(f"args:{args}")
             if args is None:
                 tool_input.pop("args")
                 return (), tool_input