new_Version

app.py

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+from llama_index import GPTVectorStoreIndex, SimpleDirectoryReader
+import os
+import time
+from llama_index.node_parser import SimpleNodeParser
+from llama_index import StorageContext, load_index_from_storage
+import gradio as gr
+import openai
+
+os.environ['OPENAI_API_KEY'] = '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'
+
+# rebuild storage context
+storage_context = StorageContext.from_defaults(persist_dir="index_dir")
+
+# load index
+index = load_index_from_storage(storage_context)
+
+# strat a search engine
+query_engine = index.as_query_engine()
+
+
+
+# APP
+
+def get_model_reply_no_prev_context(question):
+    response = query_engine.query(question)
+    final_response = response.response[1:]
+    return final_response
+
+title = "Knowledge Center at Penta Building Group"
+description = """
+The program is trained to answer questions based on the documentation of 'Lessons Learned' from previous projects!
+
+"""
+
+article = "Your feedback matters!If you like it, contact me at mgupta70@asu.edu"
+
+gr.Interface(
+    fn=get_model_reply_no_prev_context,
+    inputs="textbox",
+    outputs="text",
+    title=title,
+    description=description,
+    article=article,
+    examples=[["Which code is to be used while planning a pedestrian walkway?"], ["What is AHJ?"]], live=True
+).launch(share=True)