app.py

import gradio as gr
import pandas as pd
import matplotlib
matplotlib.use("Agg")
import requests

# Charger les artifacts si présents
try:
    df_pricing = pd.read_csv("artifacts/pricing_decisions.csv")
    ARTIFACTS_OK = True
except Exception:
    df_pricing = pd.DataFrame()
    ARTIFACTS_OK = False


def analyze_book(title, reviews_text, avg_units_sold):
    if not title or not reviews_text:
        return "Please enter a title and at least one review.", "", None

    url = "https://matteoadam.app.n8n.cloud/webhook-test/price-decider"

    payload = {
        "title": title,
        "reviews": reviews_text,
        "avg_units_sold": avg_units_sold,
    }

    try:
        response = requests.post(url, json=payload, timeout=30)

        try:
            data = response.json()
        except Exception:
            return (
                f"Status code: {response.status_code}\nRaw response:\n{response.text}",
                "Non-JSON response",
                None,
            )

        return (
            f"Status code: {response.status_code}\nParsed JSON:\n{data}",
            f"Type: {type(data).__name__}",
            None,
        )

    except Exception as e:
        return f"Error: {str(e)}", "Request failed", None


with gr.Blocks(title="Book Price Decider") as app:
    gr.Markdown("# Book Price Decider — Group A4")
    gr.Markdown("Sentiment analysis + pricing recommendation")

    with gr.Tabs():
        with gr.Tab("Dashboard"):
            if ARTIFACTS_OK:
                gr.Dataframe(value=df_pricing, label="Pricing Decisions Table")
            else:
                gr.Markdown("No artifacts found yet.")

        with gr.Tab("Analyze a New Book"):
            title_input = gr.Textbox(label="Book Title")
            units_input = gr.Number(label="Avg Monthly Units Sold", value=100)
            reviews_input = gr.Textbox(label="Reviews (one per line)", lines=6)

            analyze_btn = gr.Button("Analyze")

            summary_output = gr.Textbox(label="Summary", lines=6)
            details_output = gr.Textbox(label="Details", lines=2)
            chart_output = gr.Plot(label="Chart")

            analyze_btn.click(
                fn=analyze_book,
                inputs=[title_input, reviews_input, units_input],
                outputs=[summary_output, details_output, chart_output],
            )

        with gr.Tab("About"):
            gr.Markdown("AI for Big Data Management project app.")

app.launch()