Improve Code Quality isses

Author: AjitPadhi-Microsoft

docs/workshop/docs/workshop/Challenge-5/python/utility.py

@@ -242,7 +242,7 @@ def schema_to_tool(schema: Any):
                 return json.loads(
                     assistant_message.tool_calls[0].function.arguments, strict=False
                 )
-            except:
+            except Exception:
                 return assistant_message.tool_calls[0].function.arguments
 
     def get_structured_output_answer(
@@ -348,7 +348,6 @@ def generate_scenes(
         scene_generation_prompt = Template(SCENE_GENERATION_PROMPT).substitute(
             descriptions=next_segment_content
         )
-        scence_response = VideoSceneResponse(scenes=[])
         scence_response = openai_assistant.get_structured_output_answer(
             "", scene_generation_prompt, VideoSceneResponse
         )
@@ -433,7 +432,6 @@ def generate_chapters(
     chapter_generation_prompt = Template(CHAPTER_GENERATION_PROMPT).substitute(
         descriptions=scene_descriptions
     )
-    chapter_response = VideoChapterResponse(chapters=[])
     chapter_response = openai_assistant.get_structured_output_answer(
         "", chapter_generation_prompt, VideoChapterResponse
     )
@@ -460,7 +458,6 @@ def aggregate_tags(
     tags_dedup = set(map(lambda x: re.sub(r'^ ', '', x), tags))
     tag_dedup_prompt = Template(DEDUP_PROMPT).substitute(tag_list=tags_dedup)
 
-    tag_response = VideoTagResponse(tags=[])
     tag_response = openai_assistant.get_structured_output_answer(
         "", tag_dedup_prompt, VideoTagResponse
     )

infra/scripts/fabric_scripts/create_fabric_items.py

@@ -1,8 +1,6 @@
-from azure.identity import ManagedIdentityCredential
 import base64
 import json
 import requests
-import pandas as pd
 import os
 from glob import iglob
 import zipfile
@@ -98,11 +96,11 @@
         # upload extracted folder
         file_names = [f for f in iglob(os.path.join(local_path, "**", "*"), recursive=True) if os.path.isfile(f)]
         # print('file_names ex', file_names)
-        for file_name in file_names:
-            upload_file_name = os.path.basename(file_name)
+        for extracted_file in file_names:
+            upload_file_name = os.path.basename(extracted_file)
             file_client = directory_client.get_file_client("cu_audio_files_all/" + upload_file_name)
-            # with open(file=os.path.join(extract_dir, file_name), mode="rb") as data:
-            with open(file=file_name, mode="rb") as data:
+            # with open(file=os.path.join(extract_dir, extracted_file), mode="rb") as data:
+            with open(file=extracted_file, mode="rb") as data:
                 # print('data', data)
                 file_client.upload_data(data, overwrite=True)
 
@@ -127,7 +125,7 @@
   env_res = requests.get(fabric_env_url, headers=fabric_headers)
   env_res_id = env_res.json()['value'][0]['id']
   # print(env_res.json())
-except:
+except Exception:  # Environments may not be provisioned yet
   env_res_id = ''
 
 #create notebook items
@@ -150,14 +148,14 @@
         notebook_json['metadata']['dependencies']['lakehouse']['default_lakehouse'] = lakehouse_res.json()['id']
         notebook_json['metadata']['dependencies']['lakehouse']['default_lakehouse_name'] = lakehouse_res.json()['displayName']
         notebook_json['metadata']['dependencies']['lakehouse']['default_lakehouse_workspace_id'] = lakehouse_res.json()['workspaceId']
-    except:
+    except Exception:  # Lakehouse metadata may not be available
         pass
 
     if env_res_id != '':
         try:
             notebook_json['metadata']['dependencies']['environment']['environmentId'] = env_res_id
             notebook_json['metadata']['dependencies']['environment']['workspaceId'] = lakehouse_res.json()['workspaceId']
-        except:
+        except Exception:  # Environment metadata may not be available
             pass
 
 
@@ -178,8 +176,7 @@
         }
     }
 
-    fabric_response = requests.post(fabric_items_url, headers=fabric_headers, json=notebook_data)
-    #print(fabric_response.json())
+    requests.post(fabric_items_url, headers=fabric_headers, json=notebook_data)
 
 time.sleep(120)
 

infra/scripts/index_scripts/02_create_cu_template_audio.py

@@ -36,7 +36,7 @@
     analyzer = client.get_analyzer_detail_by_id(ANALYZER_ID)
     if analyzer is not None:
         client.delete_analyzer(ANALYZER_ID)
-except Exception:
+except Exception:  # Analyzer may not exist yet, safe to ignore
     pass
 
 response = client.begin_create_analyzer(ANALYZER_ID, analyzer_template_path=ANALYZER_TEMPLATE_FILE)

infra/scripts/index_scripts/02_create_cu_template_text.py

@@ -31,7 +31,7 @@
     analyzer = client.get_analyzer_detail_by_id(ANALYZER_ID)
     if analyzer is not None:
         client.delete_analyzer(ANALYZER_ID)
-except Exception:
+except Exception:  # Analyzer may not exist yet, safe to ignore
     pass
 
 response = client.begin_create_analyzer(ANALYZER_ID, analyzer_template_path=ANALYZER_TEMPLATE_FILE)

infra/scripts/index_scripts/03_cu_process_data_text.py

@@ -381,10 +381,10 @@ async def process_files():
 
                 docs.extend(await prepare_search_doc(content, conversation_id, path.name, embeddings_client))
                 counter += 1
-            except Exception:
+            except Exception:  # Skip files that fail processing
                 pass
             if docs != [] and counter % 10 == 0:
-                result = search_client.upload_documents(documents=docs)
+                search_client.upload_documents(documents=docs)
                 docs = []
         if docs:
             search_client.upload_documents(documents=docs)
@@ -533,7 +533,6 @@ async def call_topic_mining_agent(topics_str1):
     column_names = [i[0] for i in cursor.description]
     df_topics = pd.DataFrame(rows, columns=column_names)
     mined_topics_list = df_topics['label'].tolist()
-    mined_topics = ", ".join(mined_topics_list)
     print(f"✓ Mined {len(mined_topics_list)} topics")
 
     async def call_topic_mapping_agent(agent, input_text, list_of_topics):

infra/scripts/index_scripts/04_cu_process_custom_data.py

@@ -190,7 +190,7 @@ def create_search_index():
     connection_string = f"DRIVER={driver};SERVER={SQL_SERVER};DATABASE={SQL_DATABASE};"
     conn = pyodbc.connect(connection_string, attrs_before={SQL_COPT_SS_ACCESS_TOKEN: token_struct})
     cursor = conn.cursor()
-except: 
+except Exception:  # Fall back to ODBC Driver 17
     driver = "{ODBC Driver 17 for SQL Server}"
     token_bytes = credential.get_token("https://database.windows.net/.default").token.encode("utf-16-LE")
     token_struct = struct.pack(f"<I{len(token_bytes)}s", len(token_bytes), token_bytes)
@@ -435,10 +435,10 @@ async def process_files():
 
                 docs.extend(await prepare_search_doc(content, conversation_id, path.name, embeddings_client))
                 counter += 1
-            except Exception:
+            except Exception:  # Skip files that fail processing
                 pass
             if docs != [] and counter % 10 == 0:
-                result = search_client.upload_documents(documents=docs)
+                search_client.upload_documents(documents=docs)
                 docs = []
         if docs:
             search_client.upload_documents(documents=docs)
@@ -469,7 +469,6 @@ async def process_files():
                 conversation_id = file_name.split('convo_', 1)[1].split('_')[0]
                 conversationIds.append(conversation_id)
 
-                duration = int(result['result']['contents'][0]['fields']['Duration']['valueString'])
                 fields = result['result']['contents'][0]['fields']
                 duration_str = get_field_value(fields, 'Duration', '0')
                 try:
@@ -507,9 +506,9 @@ async def process_files():
                 docs.extend(await prepare_search_doc(content, document_id, path.name, embeddings_client))
                 counter += 1
             except Exception:
-                pass
+                pass  # Skip files that fail to process
             if docs != [] and counter % 10 == 0:
-                result = search_client.upload_documents(documents=docs)
+                search_client.upload_documents(documents=docs)
                 docs = []
 
         # upload the last batch
@@ -620,8 +619,6 @@ async def call_topic_mining_agent(topics_str1):
             res = res.replace("```json", '').replace("```", '').strip()
             return json.loads(res)
 
-    MAX_TOKENS = 3096
-
     res = asyncio.run(call_topic_mining_agent(topics_str))
     for object1 in res['topics']:
         cursor.execute("INSERT INTO km_mined_topics (label, description) VALUES (?,?)", (object1['label'], object1['description']))
@@ -632,7 +629,6 @@ async def call_topic_mining_agent(topics_str1):
     column_names = [i[0] for i in cursor.description]
     df_topics = pd.DataFrame(rows, columns=column_names)
     mined_topics_list = df_topics['label'].tolist()
-    mined_topics = ", ".join(mined_topics_list)
     print(f"✓ Mined {len(mined_topics_list)} topics")
 
     async def call_topic_mapping_agent(agent, input_text, list_of_topics):

infra/scripts/validate_bicep_params.py

@@ -107,7 +107,7 @@ def parse_parameters_env_vars(json_path: Path) -> dict[str, list[str]]:
     try:
         data = json.loads(sanitized)
         params = data.get("parameters", {})
-    except json.JSONDecodeError:
+    except json.JSONDecodeError:  # Parameters file may have azd variable placeholders
         pass
 
     # Walk each top-level parameter and scan its entire serialized value

src/App/src/App.tsx

@@ -1,4 +1,4 @@
-import React, { useEffect, useState, useRef } from "react";
+import React, { useEffect, useState } from "react";
 import Chart from "./components/Chart/Chart";
 import Chat from "./components/Chat/Chat";
 import {
@@ -8,7 +8,6 @@ import {
   Body2,
   webLightTheme,
   Avatar,
-  Tag,
 } from "@fluentui/react-components";
 import { SparkleRegular } from "@fluentui/react-icons";
 import "./App.css";
@@ -17,15 +16,13 @@ import { ChatHistoryPanel } from "./components/ChatHistoryPanel/ChatHistoryPanel
 import {
   getUserInfo,
   getLayoutConfig,
-  historyDelete,
   historyDeleteAll,
   historyList,
   historyRead,
 } from "./api/api";
 
 import { useAppContext } from "./state/useAppContext";
 import { actionConstants } from "./state/ActionConstants";
-import { ChatMessage, Conversation } from "./types/AppTypes";
 import { AppLogo } from "./components/Svg/Svg";
 import CustomSpinner from "./components/CustomSpinner/CustomSpinner";
 import CitationPanel from "./components/CitationPanel/CitationPanel";
@@ -67,7 +64,7 @@ const Dashboard: React.FC = () => {
   const [clearing, setClearing] = React.useState(false);
   const [clearingError, setClearingError] = React.useState(false);
   const [isInitialAPItriggered, setIsInitialAPItriggered] = useState(false);
-  const [showAuthMessage, setShowAuthMessage] = useState<boolean | undefined>();
+  const [, setShowAuthMessage] = useState<boolean | undefined>();
   const [offset, setOffset] = useState<number>(0);
   const OFFSET_INCREMENT = 25;
   const [hasMoreRecords, setHasMoreRecords] = useState<boolean>(true);
@@ -110,7 +107,7 @@ const Dashboard: React.FC = () => {
     }).catch((err) => {
       console.error('Error fetching user info: ', err)
     })
-  }, [])
+  }, []);
 
   const updateLayoutWidths = (newState: Record<string, boolean>) => {
     const noOfWidgetsOpen = Object.values(newState).filter((val) => val).length;
@@ -232,8 +229,6 @@ const Dashboard: React.FC = () => {
     }
   }, [isInitialAPItriggered]);
 
-  const [ASSISTANT, TOOL, ERROR, USER] = ["assistant", "tool", "error", "user"];
-
   const onSelectConversation = async (id: string) => {
     if (!id) {
       console.error("No conversation ID found");

src/App/src/chartComponents/WordCloudChart.tsx

@@ -29,7 +29,6 @@ const WordCloudChart: React.FC<WordCloudChartProps> = ({
     height: containerHeight,
   });
 
-  const currentWidth = useRef<number>(widthInPixels);
   const [wordsUpdatedFlag, setWordsUpdatedFlag] = useState(true);
 
   // Observe container size changes dynamically

src/App/src/components/Chart/Chart.tsx

@@ -46,9 +46,9 @@ const Chart = (props: ChartProps) => {
   const { config: layoutConfig } = state;
   const { layoutWidthUpdated } = props;
 
-  const [widths, setWidths] = useState<Record<string, number>>({});
+  const [, setWidths] = useState<Record<string, number>>({});
   const [appliedFetch, setAppliedFetch] = useState<boolean>(false);
-  const [widgetsGapInPercentage, setWidgetsGapInPercentage] =
+  const [widgetsGapInPercentage] =
     useState<number>(1);
 
   const [windowSize, setWindowSize] = useState({