Update app.py

app.py

@@ -1,11 +1,15 @@
 import gradio as gr
 import json 
+import os
 from llama_index import SimpleDirectoryReader, GPTListIndex, readers, GPTSimpleVectorIndex, LLMPredictor, PromptHelper
 from langchain import OpenAI
 import sys
-import os
+
 from IPython.display import Markdown, display
 
+
+
+
 def construct_index(directory_path):
 
     max_input_size = 4096
@@ -20,18 +24,30 @@ def construct_index(directory_path):
     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)
 
-
-def ask_ai(question, api_key):
-    if api_key == "":
-        api_key = "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"
-    os.environ["OPENAI_API_KEY"] = api_key
+    
+def ask_ai(question,api):
     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")
 
-iface = gr.Interface(fn=ask_ai, inputs=["text", "text"] ,outputs="text", title="Jim's Chatbot")
 
-iface.launch()
+
+
+iface = gr.Interface(fn=ask_ai, inputs="text", outputs="text" ,title="Chatbot")
+
+
+iface.launch()