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