From 41d17c4e590b22c2c6ccacdceeb7e77e5fe93115 Mon Sep 17 00:00:00 2001
From: C Cheng <charliecheng@navapbc.com>
Date: Thu, 4 Apr 2024 10:19:07 -0400
Subject: [PATCH] fix lint

---
 .../chainlit-household-bot.py                 | 21 ++++++++++---------
 02-household-queries/retrieval.py             |  2 +-
 2 files changed, 12 insertions(+), 11 deletions(-)

diff --git a/02-household-queries/chainlit-household-bot.py b/02-household-queries/chainlit-household-bot.py
index f49a29a..ee06cde 100755
--- a/02-household-queries/chainlit-household-bot.py
+++ b/02-household-queries/chainlit-household-bot.py
@@ -296,26 +296,27 @@ async def on_click_upload_default_files(action: cl.Action):
 async def on_click_upload_file_query(action: cl.Action):
     files = None
     # Wait for the user to upload a file
-    while files == None:
+    while files is None:
         files = await cl.AskFileMessage(
             content="Please upload a pdf or json file to begin!",
             accept=["text/plain", "application/pdf", "application/json"],
             max_size_mb=20,
             timeout=180,
         ).send()
-    file = files[0]
+        file = files[0]
+        if(file.type == "application/pdf"):
+            add_pdf_to_vector_db(vectordb=vectordb, file_path=file.path)
+        elif(file.type == "application/json"):
+            add_json_html_data_to_vector_db(vectordb=vectordb, file_path=file.path, content_key="content", index_key="preferredPhrase")
+        msg = cl.Message(content=f"Processing `{file.name}`...", disable_feedback=True)
+        await msg.send()
+        msg.content = f"Processing `{file.name}` done. You can now ask questions!"
+        await msg.update()
     
     # initialize db
     await set_vector_db()
     vectordb=cl.user_session.get("vectordb")
-    if(file.type == "application/pdf"):
-        add_pdf_to_vector_db(vectordb=vectordb, file_path=file.path)
-    elif(file.type == "application/json"):
-        add_json_html_data_to_vector_db(vectordb=vectordb, file_path=file.path, content_key="content", index_key="preferredPhrase")
-    msg = cl.Message(content=f"Processing `{file.name}`...", disable_feedback=True)
-    await msg.send()
-    msg.content = f"Processing `{file.name}` done. You can now ask questions!"
-    await msg.update()
+    
 
 async def retrieval_function(vectordb, llm):    
     retriever = vectordb.as_retriever(search_kwargs={"k": 1})
diff --git a/02-household-queries/retrieval.py b/02-household-queries/retrieval.py
index 7dc2790..46d91ea 100644
--- a/02-household-queries/retrieval.py
+++ b/02-household-queries/retrieval.py
@@ -24,7 +24,7 @@ def retrieval_call(llm, vectordb, question):
     )
 
     # question = os.environ.get("USER_QUERY")
-    if question == None:
+    if question is None:
         print("Please state your question here: ")
         question = input()
     # Invoke the retrieval chain