Update app.py

app.py

@@ -132,49 +132,49 @@ def respond(message, history, mom_type):
 
 chatbot = gr.ChatInterface(respond, type="messages")
 
-# def respond_tutor(message, history, mom_type):
-#     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. Respond in full sentences, don't cut yourself off. Base your response on the provided context: {mom_type}"}, 
-#                {"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, 
-#         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)
-
-#     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)
-
-#     messages.append({"role": "user", "content": message})
-
-#     response = client.chat_completion(
-#         messages, 
-#         temperature = 0.2
-#     )
-#     return response['choices'][0]['message']['content'].strip()
+ def respond_tutor(message, history, mom_type):
+     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. Respond in full sentences, don't cut yourself off. Base your response on the provided context: {mom_type}"}, 
+                {"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, 
+         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)
+
+     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)
+
+     messages.append({"role": "user", "content": message})
+
+     response = client.chat_completion(
+         messages, 
+         temperature = 0.2
+     )
+     return response['choices'][0]['message']['content'].strip()
 
 with gr.Blocks() as chatbot: