Update app.py

app.py

@@ -497,7 +497,6 @@ iterations = 0
 
 
 def answer_question(user_question, chatbot, audio=None):
-
     global iterations
     iterations = 0
     # Ensure the temporary chart directory exists
@@ -527,9 +526,9 @@ def answer_question(user_question, chatbot, audio=None):
         except sr.RequestError:
             user_question = "Could not request results from Google Speech Recognition service."
 
-        while iterations < max_iterations:
+    while iterations < max_iterations:
 
-            """if "send email to" in user_question:
+        """if "send email to" in user_question:
             email_match = re.search(r"send email to ([\w\.-]+@[\w\.-]+)", user_question)
             if email_match:
                 user_email = email_match.group(1).strip()
@@ -537,43 +536,40 @@ def answer_question(user_question, chatbot, audio=None):
                 user_question = f"{user_question}:{user_email}"
                 """
 
-            response = agent_executor.invoke({"input": user_question}, config={"callbacks": [langfuse_handler]})
+        response = agent_executor.invoke({"input": user_question}, config={"callbacks": [langfuse_handler]})
 
-            if isinstance(response, dict):
-                response_text = response.get("output", "")
-            else:
-                response_text = response
-            if "invalid" not in response_text.lower():
-                break
-            iterations += 1
+        if isinstance(response, dict):
+            response_text = response.get("output", "")
+        else:
+            response_text = response
+        if "invalid" not in response_text.lower():
+            break
+        iterations += 1
 
-        if iterations == max_iterations:
-            return "The agent could not generate a valid response within the iteration limit."
+    if iterations == max_iterations:
+        return "The agent could not generate a valid response within the iteration limit."
 
     if os.getenv("IMAGE_PATH") in response_text:
         # Open the image file
         img = Image.open(os.getenv("IMAGE_PATH"))
-        
+
         # Convert the PIL Image to a base64 encoded string
         buffered = BytesIO()
         img.save(buffered, format="PNG")
         img_str = base64.b64encode(buffered.getvalue()).decode("utf-8")
-       
+
         img = f'<img src="data:image/png;base64,{img_str}" style="width:500px; height:400px;">'
         # image = gr.Image(value=img_str)
         chatbot.append((user_question, img))
-        
+
         email_pattern = r'[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\.[a-zA-Z]{2,}'
         match = re.search(email_pattern, user_question)
         if match:
-            user_email =  match.group()  # Return the matched email
-            
-             # email send
-            if len(user_email)>0:
-                import asyncio
-                               
+            user_email = match.group()  # Return the matched email
+
+            # email send
+            if len(user_email) > 0:
                 # Send email with the chart image attached
-                #coro=
                 send_email_with_attachment(
                     recipient_email=user_email,
                     subject="Warehouse Inventory Report",
@@ -582,9 +578,6 @@ def answer_question(user_question, chatbot, audio=None):
                     attachment_path=os.getenv("IMAGE_PATH")
                 )
 
-                #asyncio.run(coro)
-                
-
         if "send email to" in user_question:
             try:
                 os.remove(img)  # Clean up the temporary image file
@@ -604,6 +597,7 @@ def answer_question(user_question, chatbot, audio=None):
     # response_text = response_text.replace('\n', ' ').replace('  ', ' ').strip()
     # return response_text
 
+
 css = """
 .gradio-container {
     width: 90%;  /* Set the width as a percentage of the viewport */