Update app.py

app.py

@@ -1,17 +1,13 @@
 import os
-import chainlit as cl  # Chainlit import
-from openai import AsyncOpenAI  # OpenAI API
+import chainlit as cl
 import textract  # For extracting text from documents
 
-# Load OpenAI API key from environment variables
-api_key = os.getenv("OPENAI_API_KEY")
-
 # Function to extract text from uploaded documents
 async def extract_text_from_file(file_path):
     return textract.process(file_path).decode('utf-8')
 
 # Chat initialization
-@cl.on_chat_start  
+@cl.on_chat_start
 async def start_chat():
     settings = {
         "model": "gpt-3.5-turbo",
@@ -22,26 +18,27 @@ async def start_chat():
         "presence_penalty": 0,
     }
     cl.user_session.set("settings", settings)
-
     await cl.Message(content="Welcome! Please upload a document to begin.").send()
 
-# Handling user queries and expecting file upload as part of the message
+# Handling file upload
 @cl.on_message
 async def main(message: cl.Message):
-    if message.files:  # Check if the message contains any files
-        uploaded_file = message.files[0]
-        file_path = uploaded_file['path']
+    # Checking if there is an uploaded file
+    if message.files:
+        uploaded_file = message.files[0]  # Accessing the uploaded file
+        file_path = uploaded_file['path']  # Getting the path of the uploaded file
 
-        # Extract text from the uploaded document
+        # Extracting text from the uploaded file
         file_content = await extract_text_from_file(file_path)
 
-        # Store document content in user session
+        # Saving the content of the document in the user session
         cl.user_session.set("document_content", file_content)
 
+        # Informing the user that the document was uploaded successfully
         await cl.Message(content=f"Document '{uploaded_file['name']}' uploaded successfully! You can now ask questions based on the document content.").send()
+
     else:
         document_content = cl.user_session.get("document_content", "")
-        
         if not document_content:
             await cl.Message(content="Please upload a document first.").send()
             return
@@ -49,12 +46,11 @@ async def main(message: cl.Message):
         settings = cl.user_session.get("settings")
         client = AsyncOpenAI()
 
-        # Create the prompt for OpenAI based on user message and document content
+        # Creating the prompt for OpenAI based on the document content and user query
         prompt = f"Document Content: {document_content}\n\nUser Query: {message.content}"
-        
         msg = cl.Message(content="")
 
-        # Send prompt to OpenAI and stream response
+        # Sending prompt to OpenAI and streaming response
         async for stream_resp in await client.chat.completions.create(
             model=settings["model"],
             messages=[{"role": "system", "content": "Answer based on the provided document."},
@@ -67,5 +63,5 @@ async def main(message: cl.Message):
                 token = ""
             await msg.stream_token(token)
 
-        # Send final response
+        # Sending the final response
         await msg.send()