Update app.py

app.py

@@ -1,22 +1,27 @@
+# app.py
 import os
-import gradio as gr
 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)
 
-# کلید COMTRADE
-subscription_key = os.getenv("COMTRADE_API_KEY", "")
-# توکن Hugging Face
-hf_token = os.getenv("HF_API_TOKEN")
-
-
-client = InferenceClient(token=hf_token)
-translator = GoogleTranslator(source='en', target='fa')
-
+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,
@@ -26,74 +31,63 @@ def get_importers(hs_code: str, year: str, month: str):
         maxRecords=500, includeDesc=True
     )
     if df is None or df.empty:
-        return pd.DataFrame(columns=["کد کشور", "نام کشور", "ارزش CIF"])
-    df = df[df['cifvalue'] > 0]
-    result = (
-        df.groupby(["reporterCode", "reporterDesc"], as_index=False)
-          .agg({"cifvalue": "sum"})
-          .sort_values("cifvalue", ascending=False)
-    )
-    result.columns = ["کد کشور", "نام کشور", "ارزش CIF"]
-    return result
+        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 باید اطلاعات واردات را نمایش دهید."
+        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 the period {period}:\n"
+        f"The following table shows countries that imported a product with HS code {hs_code} during {period}:\n"
         f"{table_str}\n\n"
-        f"Please provide a detailed and comprehensive analysis in two paragraphs. The first paragraph should discuss market opportunities, potential demand, and specific cultural or economic factors influencing the demand for this product in these countries. The second paragraph should offer actionable strategic recommendations for exporters, including detailed trade strategies, risk management techniques, and steps to establish local partnerships."
+        "Please provide a detailed and comprehensive analysis of market trends, risks, "
+        "and opportunities for a new exporter entering this market."
     )
-    print("پرامپت ساخته‌شده:")
-    print(prompt)
     try:
-        print("در حال فراخوانی مدل mistralai/Mixtral-8x7B-Instruct-v0.1...")
         outputs = client.text_generation(
             prompt=prompt,
             model="mistralai/Mixtral-8x7B-Instruct-v0.1",
-            max_new_tokens=1024  # افزایش برای تکمیل جملات
+            max_new_tokens=1024
         )
-        print("خروجی مدل دریافت شد (به انگلیسی):")
-        print(outputs)
-
-
-        # ترجمه خروجی به فارسی
-        translated_outputs = translator.translate(outputs)
-        print("خروجی ترجمه‌شده به فارسی:")
-        print(translated_outputs)
-        return translated_outputs
+        return translator.translate(outputs)
     except Exception as e:
-        error_msg = f"خطا در تولید مشاوره: {str(e)}"
-        print(error_msg)
-        return error_msg
-
-
-current_year = pd.Timestamp.now().year
-years = [str(y) for y in range(2000, current_year+1)]
-months = [str(m) for m in range(1, 13)]
-
+        return f"خطا در تولید مشاوره: {e}"
 
 with gr.Blocks() as demo:
-    gr.Markdown("##تولید شده توسط DIGINORON نمایش کشورهایی که یک کالا را وارد کرده‌اند")
+    gr.Markdown("## تحلیل واردات بر اساس کد HS و ارائه مشاوره")
+
     with gr.Row():
-        inp_hs = gr.Textbox(label="HS Code")
-        inp_year = gr.Dropdown(choices=years, label="سال", value=str(current_year))
-        inp_month = gr.Dropdown(choices=months, label="ماه", value=str(pd.Timestamp.now().month))
-    btn_show = gr.Button("نمایش اطلاعات")
+        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,
+        headers=["کد کشور","نام کشور","ارزش CIF"],
+        datatype=["number","text","number"],
+        interactive=True
     )
-    btn_show.click(get_importers, [inp_hs, inp_year, inp_month], out_table)
-
 
-    btn_advice = gr.Button("ارائه مشاوره تخصصی")
-    out_advice = gr.Textbox(label="مشاوره تخصصی", lines=6)
+    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,
@@ -101,6 +95,5 @@ with gr.Blocks() as demo:
         outputs=out_advice
     )
 
-
 if __name__ == "__main__":
     demo.launch()