Update app.py

app.py

@@ -19,24 +19,21 @@ with open("strict_mom_phrases.txt", "r", encoding="utf-8") as file:
   # Read the entire contents of the file and store it in a variable
   strict_mom_text = file.read()
 
-def on_button_click():
-    if cool_button 
-
 with gr.Blocks() as demo:
     cool_button = gr.Button(value="Cool Mom", variant="primary")
-    cool_button.click(fn=on_button_click, inputs=[], outputs=[])
+    cool_button.click(fn=respond_cool, inputs=[], outputs=[])
 
 demo.launch()
 
 with gr.Blocks() as demo:
     tutor_button = gr.Button(value="Tutor Mom", variant="primary")
-    tutor_button.click(fn=on_button_click, inputs=[], outputs=[])
+    tutor_button.click(fn=respond_tutor, inputs=[], outputs=[])
 
 demo.launch()
 
 with gr.Blocks() as demo:
     strict_button = gr.Button(value="Strict Mom", variant="primary")
-    strict_button.click(fn=on_button_click, inputs=[], outputs=[])
+    strict_button.click(fn=respond_strict, inputs=[], outputs=[])
 
 demo.launch()
 
@@ -138,17 +135,60 @@ def get_top_chunks(query, chunk_embeddings, text_chunks):
 
 client = InferenceClient("Qwen/Qwen2.5-72B-Instruct")
 
-def respond(message, history):
+def respond_cool(message, history):
     top_cool_results = get_top_chunks(message, cool_chunk_embeddings, cleaned_cool_chunks) # Complete this line
+    #str_chunks = "\n".join(best_chunks)
+
+    messages = [{"role": "system", "content": f"You are chatbot that plays the role of the user's cool and super chill mom. Base your response on the provided context: {top_cool_results}"}, 
+               {"role": "user", 
+               "content": (
+                   f"Context:\n{top_cool_results}\n\n"
+                   f"Question{message}"
+               )}]
+
+    if history:
+        messages.extend(history)
+
+    messages.append({"role": "user", "content": message})
+
+    response = client.chat_completion(
+        messages, 
+        max_tokens = 100, 
+        temperature = 0.2
+    )
+    return response['choices'][0]['message']['content'].strip()
+
+def respond_tutor(message, history):
     top_tutor_results = get_top_chunks(message, tutor_chunk_embeddings, cleaned_tutor_chunks)
+    #str_chunks = "\n".join(best_chunks)
+
+    messages = [{"role": "system", "content": f"You are chatbot that plays the role of the user's extremely studious, tutor-like mom. Base your response on the provided context: {top_tutor_results}"}, 
+               {"role": "user", 
+               "content": (
+                   f"Context:\n{top_tutor_results}\n\n"
+                   f"Question{message}"
+               )}]
+
+    if history:
+        messages.extend(history)
+
+    messages.append({"role": "user", "content": message})
+
+    response = client.chat_completion(
+        messages, 
+        max_tokens = 100, 
+        temperature = 0.2
+    )
+    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)
+    #str_chunks = "\n".join(best_chunks)
 
-    messages = [{"role": "system", "content": f"You are chatbot that plays the role of the user's mom. Base your response on the provided context: {str_chunks}"}, 
+    messages = [{"role": "system", "content": f"You are chatbot that plays the role of the user's extremely strict mom. Base your response on the provided context: {top_strict_results}"}, 
                {"role": "user", 
                "content": (
-                   f"Context:\n{str_chunks}\n\n"
+                   f"Context:\n{top_strict_results}\n\n"
                    f"Question{message}"
                )}]
 
@@ -164,5 +204,7 @@ def respond(message, history):
     )
     return response['choices'][0]['message']['content'].strip()
 
+
+
 chatbot = gr.ChatInterface(respond, type = 'messages')
 chatbot.launch()