app.py

import gradio as gr
import os
from llama_index.core import SimpleDirectoryReader, VectorStoreIndex, Settings
from llama_index.llms.openai import OpenAI

# Set OpenAI API key from environment
os.environ["OPENAI_API_KEY"] = os.getenv("OPENAI_API_KEY")

# Configure the default LLM
Settings.llm = OpenAI(model="gpt-4.1-nano")

# Load documents and build index
documents = SimpleDirectoryReader("documents").load_data()
index = VectorStoreIndex.from_documents(documents)

# Create query engine
query_engine = index.as_query_engine()

def chatbot_response(message):
    response = query_engine.query(message)
    return str(response)

# # Create a custom theme with a blue background
# custom_theme = gr.themes.Default(primary_hue=colors.blue).set(
#     body_background_fill="#fafaff"
# )

iface = gr.Interface(fn=chatbot_response,
                     inputs="text",
                     outputs="text",
                     title="Ask about me",
                     description="Ask questions and receive answers based on my bio.",
                     # theme=custom_theme,
                     examples=[["Provide a summary of Donald?"],
                       ["Has Donald worked with Python?"],
                       ["Tell me something interesting about Donald"]]
                    )

iface.launch()