Delete app.py

app.py

@@ -1,115 +0,0 @@
-# app.py
-import os
-import pandas as pd
-import gradio as gr
-import comtradeapicall
-from openai import OpenAI
-from deep_translator import GoogleTranslator
-import spaces  # برای مدیریت GPU کرایه‌ای
-
-# --- بارگذاری داده‌های HS Code ---
-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()
-
-    std_map = {
-        'کد کشور': 'ptCode',
-        'نام کشور': 'ptTitle',
-        'ارزش CIF': 'TradeValue'
-    }
-    code_col = std_map['کد کشور'] if 'ptCode' in df.columns else next((c for c in df.columns if 'code' in c.lower()), None)
-    title_col = std_map['نام کشور'] if 'ptTitle' in df.columns else next((c for c in df.columns if 'title' in c.lower()), None)
-    value_col = std_map['ارزش CIF'] if 'TradeValue' in df.columns else next((c for c in df.columns if 'value' in c.lower()), None)
-
-    if not (code_col and title_col and value_col):
-        return product_name, df
-
-    df_sorted = df.sort_values(value_col, ascending=False).head(10)
-    out = df_sorted[[code_col, title_col, value_col]]
-    out.columns = ['کد کشور', 'نام کشور', 'ارزش CIF']
-    return product_name, out
-
-# --- اتصال به OpenAI و مترجم ---
-openai_client = OpenAI(api_key=os.getenv("OPENAI"))  # سکرت از محیط
-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 داده‌های واردات را انجام دهید."
-
-    df_limited = table_data.head(10)
-    table_str = df_limited.to_string(index=False)
-    period = f"{year}/{int(month):02d}"
-    prompt = (
-        f"The following table shows the top {len(df_limited)} countries by CIF value importing 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:
-        response = openai_client.chat.completions.create(
-            model="gpt-3.5-turbo",
-            messages=[
-                {"role": "system", "content": "You are an expert in international trade and export consulting."},
-                {"role": "user", "content": prompt}
-            ],
-            max_tokens=1000,
-            temperature=0.7
-        )
-        english_response = response.choices[0].message.content
-        return translator.translate(english_response)
-    except Exception as e:
-        return f"خطا در تولید مشاوره: {e}"
-
-# --- رابط کاربری Gradio ---
-with gr.Blocks() as demo:
-    gr.Markdown("## DIGINORON.COM ابزار هوش مصنوعی برای مشاوره صادرات کالا به کشورهای هدف")
-
-    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 داده‌های واردات")
-    out_name = gr.Markdown(label="**نام محصول**")
-    out_table = gr.Dataframe(datatype="pandas", interactive=True)
-
-    btn_show.click(
-        fn=get_importers,
-        inputs=[inp_hs, inp_year, inp_month],
-        outputs=[out_name, out_table]
-    )
-
-    btn_advice = gr.Button("ارائه مشاوره تخصصی")
-    out_advice = gr.Textbox(label="مشاوره تخصصی", lines=8)
-
-    btn_advice.click(
-        fn=provide_advice,
-        inputs=[out_table, inp_hs, inp_year, inp_month],
-        outputs=out_advice
-    )
-
-if __name__ == "__main__":
-    demo.launch()