chore: Add pylint for DB-GPT core lib (#1076)

dbgpt/core/interface/output_parser.py

@@ -1,10 +1,15 @@
+"""The output parser is used to parse the output of an LLM call.
+
+TODO: Make this more general and clear.
+"""
+
 from __future__ import annotations
 
 import json
 import logging
 from abc import ABC
 from dataclasses import asdict
-from typing import Any, Dict, TypeVar, Union
+from typing import Any, TypeVar, Union
 
 from dbgpt.core import ModelOutput
 from dbgpt.core.awel import MapOperator
@@ -22,11 +27,16 @@ class BaseOutputParser(MapOperator[ModelOutput, Any], ABC):
     """
 
     def __init__(self, is_stream_out: bool = True, **kwargs):
+        """Create a new output parser."""
         super().__init__(**kwargs)
         self.is_stream_out = is_stream_out
         self.data_schema = None
 
     def update(self, data_schema):
+        """Update the data schema.
+
+        TODO: Remove this method.
+        """
         self.data_schema = data_schema
 
     def __post_process_code(self, code):
@@ -40,9 +50,16 @@ class BaseOutputParser(MapOperator[ModelOutput, Any], ABC):
         return code
 
     def parse_model_stream_resp_ex(self, chunk: ResponseTye, skip_echo_len):
-        data = _parse_model_response(chunk)
-        """ TODO Multi mode output handler,  rewrite this for multi model, use adapter mode.
+        """Parse the output of an LLM call.
+
+        Args:
+            chunk (ResponseTye): The output of an LLM call.
+            skip_echo_len (int): The length of the prompt to skip.
         """
+        data = _parse_model_response(chunk)
+        # TODO: Multi mode output handler, rewrite this for multi model, use adapter
+        #  mode.
+
         model_context = data.get("model_context")
         has_echo = False
         if model_context and "prompt_echo_len_char" in model_context:
@@ -65,6 +82,7 @@ class BaseOutputParser(MapOperator[ModelOutput, Any], ABC):
             return output
 
     def parse_model_nostream_resp(self, response: ResponseTye, sep: str):
+        """Parse the output of an LLM call."""
         resp_obj_ex = _parse_model_response(response)
         if isinstance(resp_obj_ex, str):
             resp_obj_ex = json.loads(resp_obj_ex)
@@ -89,7 +107,8 @@ class BaseOutputParser(MapOperator[ModelOutput, Any], ABC):
             return ai_response
         else:
             raise ValueError(
-                f"""Model server error!code={resp_obj_ex["error_code"]}, errmsg is {resp_obj_ex["text"]}"""
+                f"Model server error!code={resp_obj_ex['error_code']}, error msg is "
+                f"{resp_obj_ex['text']}"
             )
 
     def _illegal_json_ends(self, s):
@@ -117,7 +136,7 @@ class BaseOutputParser(MapOperator[ModelOutput, Any], ABC):
 
             temp_json = self._illegal_json_ends(temp_json)
             return temp_json
-        except Exception as e:
+        except Exception:
             raise ValueError("Failed to find a valid json in LLM response！" + temp_json)
 
     def _json_interception(self, s, is_json_array: bool = False):
@@ -150,17 +169,17 @@ class BaseOutputParser(MapOperator[ModelOutput, Any], ABC):
                         break
                 assert count == 0
                 return s[i : j + 1]
-        except Exception as e:
+        except Exception:
             return ""
 
-    def parse_prompt_response(self, model_out_text) -> T:
-        """
-        parse model out text to prompt define response
+    def parse_prompt_response(self, model_out_text) -> Any:
+        """Parse model out text to prompt define response.
+
         Args:
-            model_out_text:
+            model_out_text: The output of an LLM call.
 
         Returns:
-
+            Any: The parsed output of an LLM call.
         """
         cleaned_output = model_out_text.rstrip()
         if "```json" in cleaned_output:
@@ -194,12 +213,15 @@ class BaseOutputParser(MapOperator[ModelOutput, Any], ABC):
     def parse_view_response(
         self, ai_text, data, parse_prompt_response: Any = None
     ) -> str:
-        """
-        parse the ai response info to user view
+        """Parse the AI response info to user view.
+
         Args:
-            text:
+            ai_text (str): The output of an LLM call.
+            data (dict): The data has been handled by some scene.
+            parse_prompt_response (Any): The prompt response has been parsed.
 
         Returns:
+            str: The parsed output of an LLM call.
 
         """
         return ai_text
@@ -240,10 +262,14 @@ def _parse_model_response(response: ResponseTye):
 
 
 class SQLOutputParser(BaseOutputParser):
+    """Parse the SQL output of an LLM call."""
+
     def __init__(self, is_stream_out: bool = False, **kwargs):
+        """Create a new SQL output parser."""
         super().__init__(is_stream_out=is_stream_out, **kwargs)
 
     def parse_model_nostream_resp(self, response: ResponseTye, sep: str):
+        """Parse the output of an LLM call."""
         model_out_text = super().parse_model_nostream_resp(response, sep)
         clean_str = super().parse_prompt_response(model_out_text)
         return json.loads(clean_str, strict=True)