Update app.py

app.py

@@ -1,4 +1,3 @@
-
 from gpt_index import SimpleDirectoryReader, GPTListIndex, GPTSimpleVectorIndex, LLMPredictor, PromptHelper
 from langchain import OpenAI
 import gradio as gr
@@ -9,36 +8,21 @@ import datetime
 os.environ["OPENAI_API_KEY"] = 'SECRET'
 
 
-def construct_index(directory_path):
-    max_input_size = 4096
-    num_outputs = 512
-    max_chunk_overlap = 20
-    chunk_size_limit = 600
-
-    prompt_helper = PromptHelper(max_input_size, num_outputs, max_chunk_overlap, chunk_size_limit=chunk_size_limit)
-    prompt = "You are John Haynes, an experienced mediator who lived from 1923 to 1999. You are sometimes called the grandfather of mediation practice because you helped train many mediators during your life. In addition to providing advice on mediation practice you will also finish your answers by asking deep, philosophical and insightful questions based on the topic presented. \n\n"      
-
-    llm_predictor = LLMPredictor(llm=OpenAI(temperature=0.7, model_name="gpt-3.5-turbo", max_tokens=num_outputs))
-
-    documents = SimpleDirectoryReader(directory_path).load_data()
-
-    index = GPTSimpleVectorIndex(documents, llm_predictor=llm_predictor, prompt_helper=prompt_helper)
+def get_index(index_file_path):
+    if os.path.exists(index_file_path):
+        return GPTSimpleVectorIndex.load_from_disk(index_file_path)
+    else:
+        print(f"Error: '{index_file_path}' does not exist.")
+        sys.exit()
 
-    index.save_to_disk('index.json')
-
-    return index
 
 def chatbot(input_text, mentioned_person='Mediation teacher John Haynes'):
-    index = GPTSimpleVectorIndex.load_from_disk('index.json')
+    index = get_index('index.json')
     prompt = f"{mentioned_person}: {input_text}\n\n At the end of your answer, if you think appropriate, please ask a provocative question. Start it with a polite phrase such as - I wonder what you think...-."
     response = index.query(prompt, response_mode="compact")
 
-    # Check if response includes a question mark
-    if "?" not in response.response:
-        # If response does not include a question, add one
-        response.response += "\n\nWhat are your thoughts on this?"
     
-       # Save chat log
+    # Save chat log
     current_time = datetime.datetime.now()
     current_time_str = current_time.strftime("%Y-%m-%d_%H-%M-%S")
     chat_log_filename = f"{current_time_str}.txt"
@@ -50,17 +34,14 @@ def chatbot(input_text, mentioned_person='Mediation teacher John Haynes'):
     
     return response.response
     
-     
+
 with open("docs/about/descript.txt", "r") as f:
     description = f.read()
-        
+
 iface = gr.Interface(fn=chatbot,
                      inputs=gr.inputs.Textbox(lines=5, label="Enter your question"),
                      outputs=gr.outputs.Textbox(label="Chatbot Response"),
                      title="AI Chatbot trained on J. Haynes mediation material, v0.1",
                      description=description)
-                    
-                                    
-index = construct_index("docs")
-iface.launch(share=True)
 
+iface.launch(share=True)