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# -*- coding: utf-8 -*-
"""
Created on Fri May 2 12:27:58 2025
@author: ariam
"""
import gradio as gr
import pandas as pd
from OpenAI_interface import ask_openai, extract_fields, resolve_agency_index
from OpenAI_tools import run_report_classifier
# Load agency CSV once
df = pd.read_csv("high_priority_agencies.csv")
# Main function Gradio calls
def searchbot_interface(prompt, mode):
chatbot_mode = (mode == "Chatbot Mode")
try:
# Call OpenAI
response = ask_openai(prompt, chatbot_mode=chatbot_mode)
if chatbot_mode:
return response
# Extract info from LLM output
parsed = extract_fields(response)
agency, keyword, year = parsed["agency"], parsed["keyword"], parsed["year"]
# Match agency with embeddings
index, resolved_agency = resolve_agency_index(agency)
if index is None:
return f"❌ Could not resolve agency: {agency}"
# Run actual document search/classifier
run_report_classifier(
agency_df=df,
search_term=keyword,
fiscal_year=year if year else "",
start_index=index,
end_index=index,
max_results=15,
output_filename="openAI_bot_output.csv",
brave_api_key="your_brave_key_here",
google_api_key="your_google_key_here",
google_cse_id="your_cse_id_here"
)
return f"✅ Search complete!\nAgency: {resolved_agency}\nKeyword: {keyword}\nYear: {year}"
except Exception as e:
return f"❌ Error: {str(e)}"
# Create the UI
iface = gr.Interface(
fn=searchbot_interface,
inputs=[
gr.Textbox(lines=4, label="Ask a question"),
gr.Radio(["Search Mode", "Chatbot Mode"], label="Mode", value="Search Mode")
],
outputs=gr.Textbox(label="Response"),
title="📄 PIA SearchBot (OpenAI-Powered)",
description="Ask about agency reports or budgets. Toggle chatbot mode to talk casually."
)
# Launch the web app
if __name__ == "__main__":
iface.launch()
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