Create app.py

app.py

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+import json
+from langchain.chains import llm
+from ast import Index
+from gpt_index import SimpleDirectoryReader, GPTListIndex, readers, GPTSimpleVectorIndex, LLMPredictor, PromptHelper
+from langchain import OpenAI
+import openai
+import os 
+import streamlit as st
+
+# Load the GPT index from the file
+with open('index.json', 'r') as f:
+    index_data = json.load(f)
+gpt_index = GPTSimpleVectorIndex(index_data)
+
+OPENAI_API_KEY = st.secrets["OPENAI_API_KEY"]
+os.environ["OPENAI_API_KEY"] = OPENAI_API_KEY
+
+def ask_patrick():
+    # Get the user's query
+    query = st.text_input("Tell me about Patrick Collison?")
+    
+    # Use OpenAI to get a response to the query
+    response = openai.Completion.create(
+        engine="text-davinci-002",
+        prompt=f"Patrick Collison is a tech entrepreneur. {query}",
+        temperature=0.5,
+        max_tokens=1024,
+        top_p=1,
+        frequency_penalty=0,
+        presence_penalty=0
+    )
+
+    # Print the response
+    st.write(response.choices[0].text)
+    
+    # Search the GPT index for the best response
+    result = gpt_index.query(response.choices[0].text)
+    
+    # Print the result
+    st.write(result)
+
+if __name__ == "__main__":
+    ask_patrick()