Upload app.py

app.py

@@ -4,19 +4,18 @@ import gradio as gr
 import sys
 import os
 
+"""
+Code from Beebom article: "How to Train an AI Chatbot With Custom Knowledge Base Using ChatGPT API" by Arjun Sha
+https://beebom.com/how-train-ai-chatbot-custom-knowledge-base-chatgpt-api/
+"""
 
 def construct_index():
     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)
-
     llm_predictor = LLMPredictor(llm=ChatOpenAI(temperature=0.7, model_name="gpt-3.5-turbo", max_tokens=num_outputs))
-
-    # documents = SimpleDirectoryReader(directory_path).load_data()
-
     index = GPTSimpleVectorIndex.load_from_disk('index.json', llm_predictor=llm_predictor, prompt_helper=prompt_helper)
 
     return index
@@ -29,7 +28,7 @@ def chatbot(input_text):
 iface = gr.Interface(fn=chatbot,
                      inputs=gr.components.Textbox(lines=7, label="Enter your text"),
                      outputs="text",
-                     title="AI Chatbot for DWW Audio resources")
+                     title="AI Chatbot for the Doing What Works Library")
 
 # index = construct_index()
 iface.launch(share=False)