# app.py
import os
import pandas as pd
import gradio as gr
import comtradeapicall
from huggingface_hub import InferenceClient
from deep_translator import GoogleTranslator
import spaces

# 1) بارگذاری HS DataFrame از گیت‌هاب
HS_CSV_URL = (
    "https://raw.githubusercontent.com/"
    "datasets/harmonized-system/master/data/harmonized-system.csv"
)
hs_df = pd.read_csv(HS_CSV_URL, dtype=str)

def get_product_name(hs_code: str) -> str:
    code4 = str(hs_code).zfill(4)
    row = hs_df[hs_df["hscode"] == code4]
    return row.iloc[0]["description"] if not row.empty else "–"

def get_importers(hs_code: str, year: str, month: str):
    product_name = get_product_name(hs_code)

    period = f"{year}{int(month):02d}"
    df = comtradeapicall.previewFinalData(
        typeCode='C', freqCode='M', clCode='HS', period=period,
        reporterCode=None, cmdCode=hs_code, flowCode='M',
        partnerCode=None, partner2Code=None,
        customsCode=None, motCode=None,
        maxRecords=500, includeDesc=True
    )
    if df is None or df.empty:
        return product_name, pd.DataFrame()

    df = df[['ptCode', 'ptTitle', 'TradeValue']]
    df.columns = ['کد کشور', 'نام کشور', 'ارزش CIF']
    return product_name, df

subscription_key = os.getenv("COMTRADE_API_KEY", "")
hf_token         = os.getenv("HF_API_TOKEN", "")
client           = InferenceClient(token=hf_token)
translator       = GoogleTranslator(source='en', target='fa')

@spaces.GPU
def provide_advice(table_data: pd.DataFrame, hs_code: str, year: str, month: str):
    if table_data is None or table_data.empty:
        return "ابتدا نمایش واردات را انجام دهید."
    table_str = table_data.to_string(index=False)
    period = f"{year}/{int(month):02d}"
    prompt = (
        f"The following table shows countries that imported a product with HS code {hs_code} during {period}:\n"
        f"{table_str}\n\n"
        "Please provide a detailed and comprehensive analysis of market trends, risks, "
        "and opportunities for a new exporter entering this market."
    )
    try:
        outputs = client.text_generation(
            prompt=prompt,
            model="mistralai/Mixtral-8x7B-Instruct-v0.1",
            max_new_tokens=1024
        )
        return translator.translate(outputs)
    except Exception as e:
        return f"خطا در تولید مشاوره: {e}"

with gr.Blocks() as demo:
    gr.Markdown("## تحلیل واردات بر اساس کد HS و ارائه مشاوره")

    with gr.Row():
        inp_hs    = gr.Textbox(label="کد HS", placeholder="مثلاً 1006")
        inp_year  = gr.Textbox(label="سال",   placeholder="مثلاً 2023")
        inp_month = gr.Textbox(label="ماه",   placeholder="مثلاً 1 تا 12")

    btn_show  = gr.Button("نمایش واردات")
    out_name  = gr.Markdown(label="**نام محصول**")
    out_table = gr.Dataframe(
        headers=["کد کشور","نام کشور","ارزش CIF"],
        datatype=["number","text","number"],
        interactive=True
    )

    btn_show.click(
        get_importers,
        inputs=[inp_hs, inp_year, inp_month],
        outputs=[out_name, out_table]
    )

    btn_advice = gr.Button("ارائه مشاوره")
    out_advice = gr.Textbox(label="مشاوره تخصصی", lines=8)

    btn_advice.click(
        provide_advice,
        inputs=[out_table, inp_hs, inp_year, inp_month],
        outputs=out_advice
    )

if __name__ == "__main__":
    demo.launch()