app.py

import gradio as gr
from extraction import process_pdf
from retriever import Retriever
from generator import Generator
from mote_router import compute_modality_weights
from analytics import generate_dashboard
from benchmark import run_benchmark
from export_utils import export_json

retriever = Retriever()
generator = Generator()

def ingest_pdf(file):
    chunks = process_pdf(file.name)
    retriever.build_index(chunks)
    return "✅ ESG Report Processed Successfully"

def answer_query(query):
    weights = compute_modality_weights(query)
    results = retriever.search(query)
    answer = generator.generate(query, results)

    fig = generate_dashboard(weights)
    evidence = "\n\n".join(results)

    return answer, evidence, fig, weights

def export_results(answer, evidence, weights):
    return export_json(answer, evidence, weights)

with gr.Blocks(theme=gr.themes.Soft()) as demo:

    gr.Markdown("# ESGenius-AI 🚀")
    gr.Markdown("Enterprise Multimodal ESG Intelligence Engine")

    with gr.Tab("Upload"):
        file_input = gr.File()
        upload_btn = gr.Button("Process ESG Report")
        upload_output = gr.Textbox()
        upload_btn.click(ingest_pdf, inputs=file_input, outputs=upload_output)

    with gr.Tab("Ask ESG Question"):
        query = gr.Textbox(label="Enter ESG Question")
        ask_btn = gr.Button("Generate Answer")

        answer = gr.Textbox(label="Answer")
        evidence = gr.Textbox(label="Retrieved Evidence")
        dashboard = gr.Plot()
        weights = gr.JSON()

        ask_btn.click(
            answer_query,
            inputs=query,
            outputs=[answer, evidence, dashboard, weights]
        )

        export_btn = gr.Button("Download ESG JSON")
        export_btn.click(
            export_results,
            inputs=[answer, evidence, weights],
            outputs=gr.File()
        )

    with gr.Tab("Benchmark"):
        bench_btn = gr.Button("Show Benchmark")
        bench_output = gr.JSON()
        bench_btn.click(run_benchmark, outputs=bench_output)

demo.launch()