Create app.py

app.py

@@ -0,0 +1,37 @@
+import gradio as gr
+from llama_index.readers.file import PagedCSVReader
+from llama_index.core.indices import VectorStoreIndex
+import openai
+import os
+
+openai.api_key = os.getenv('OPENAI_API_KEY')
+
+def load_data():
+    try:
+        loader = PagedCSVReader()
+        documents = loader.load_data('/content/aitalents.csv')
+        index = VectorStoreIndex.from_documents(documents)
+        query_engine = index.as_query_engine()
+        return query_engine
+    except Exception as e:
+        print(f"Error loading data or creating index: {e}")
+        return None
+
+query_engine = load_data()  # Call load_data() to create the query engine
+
+def chat(message):
+    if query_engine is None:
+        return "An error occurred while loading data. Please try again later."
+
+    try:
+        response = query_engine.query(message)
+        return response[0]['text']
+    except Exception as e:
+        print(f"Error generating response: {e}")
+        return "I'm still learning how to answer that question. Please try asking something else."
+
+# Create the chatbot interface
+interface = gr.ChatInterface(fn=chat, title="Chatbot with Llama Hub and OpenAI", initial_refresh=False)
+
+# Launch the interface
+interface.launch()