Update app.py

app.py

@@ -1,50 +1,34 @@
 import gradio as gr
-import openai
+import json 
 from llama_index import SimpleDirectoryReader, GPTListIndex, readers, GPTSimpleVectorIndex, LLMPredictor, PromptHelper
-from langchain.chat_models import ChatOpenAI
+from langchain import OpenAI
 import sys
-import os
 from IPython.display import Markdown, display
 
-# Define API key globally
-api_key = "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"
-
 def construct_index(directory_path):
-    # set maximum input size
+
     max_input_size = 4096
-    # set number of output tokens
+
     num_outputs = 2000
-    # set maximum chunk overlap
+
     max_chunk_overlap = 20
-    # set chunk size limit
+
     chunk_size_limit = 600
 
-    # define LLM
+
     llm_predictor = LLMPredictor(llm=OpenAI(temperature=0.5, model_name="gpt-3.5-turbo", max_tokens=num_outputs))
     prompt_helper = PromptHelper(max_input_size, num_outputs, max_chunk_overlap, chunk_size_limit=chunk_size_limit)
 
-    documents = SimpleDirectoryReader(directory_path).load_data()
-
-    index = GPTSimpleVectorIndex.from_documents(documents)
+        response = index.query(query, response_mode="compact")
+        display(Markdown(f"Response: <b>{response.response}</b>"))
 
-    index.save_to_disk('index.json')
 
-    return index
 
-def ask_ai(question, api_key):
-    # Use global API key variable
-    os.environ["OPENAI_API_KEY"] = api_key
-    index = GPTSimpleVectorIndex.load_from_disk('index.json')
-    response = index.query(question, response_mode="compact")
-    return response.response
+os.environ["OPENAI_API_KEY"] = "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"
 
 construct_index("data")
 
-# Create Gradio interface to prompt for API key
-api_key_input = gr.inputs.Textbox(label="Enter your OpenAI API key:")
 
-# Define the interface
-iface = gr.Interface(fn=ask_ai, inputs=["text", api_key_input], outputs="text" ,title="Jim's Chatbot")
+iface = gr.Interface(fn=ask_ai, inputs="text", outputs="text" ,title="Chatbot")
 
-# Start the interface
-iface.launch()
+iface.launch()