Update app.py

app.py

@@ -143,38 +143,38 @@ def respond_tutor(message, history, mom_type):
                     f"Question{message}"
                 )}]
 
-     if history:
-         messages.extend(history)
+    if history:
+        messages.extend(history)
 
-     messages.append({"role": "user", "content": message})
+    messages.append({"role": "user", "content": message})
 
-     response = client.chat_completion(
-         messages, 
-         temperature = 0.2
+    response = client.chat_completion(
+        messages, 
+        temperature = 0.2
      )
-     return response['choices'][0]['message']['content'].strip()
+    return response['choices'][0]['message']['content'].strip()
 
- def respond_strict(message, history):
-     top_strict_results = get_top_chunks(message, strict_chunk_embeddings, cleaned_strict_chunks)
-     #str_chunks = "\n".join(best_chunks)
+def respond_strict(message, history):
+    top_strict_results = get_top_chunks(message, strict_chunk_embeddings, cleaned_strict_chunks)
+    #str_chunks = "\n".join(best_chunks)
 
-     messages = [{"role": "system", "content": f"You are chatbot that plays the role of the user's extremely strict mom. Respond in full sentences, don't cut yourself off. Base your response on the provided context: {top_strict_results}"}, 
-                {"role": "user", 
+    messages = [{"role": "system", "content": f"You are chatbot that plays the role of the user's extremely strict mom. Respond in full sentences, don't cut yourself off. Base your response on the provided context: {top_strict_results}"}, 
+            {"role": "user", 
                 "content": (
                     f"Context:\n{top_strict_results}\n\n"
                     f"Question{message}"
                 )}]
 
-     if history:
-         messages.extend(history)
+    if history:
+        messages.extend(history)
 
-     messages.append({"role": "user", "content": message})
+    messages.append({"role": "user", "content": message})
 
-     response = client.chat_completion(
-         messages, 
-         temperature = 0.2
+    response = client.chat_completion(
+        messages, 
+        temperature = 0.2
      )
-     return response['choices'][0]['message']['content'].strip()
+    return response['choices'][0]['message']['content'].strip()
 
 with gr.Blocks() as chatbot: