Update app.py

app.py

@@ -1,21 +1,20 @@
+# app.py
 import os
 import gradio as gr
 import pandas as pd
 import comtradeapicall
 from huggingface_hub import InferenceClient
 from deep_translator import GoogleTranslator
-
+import spaces  # اضافه‌شده برای مدیریت GPU روی ZeroGPU Spaces
 
 # 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_importers(hs_code: str, year: str, month: str):
     period = f"{year}{int(month):02d}"
     df = comtradeapicall.previewFinalData(
@@ -26,17 +25,13 @@ 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 pd.DataFrame()  # خالی
+    # فقط ستون‌های مورد نیاز را نگه‌دار
+    df = df[['ptCode', 'ptTitle', 'TradeValue']]
+    df.columns = ['کد کشور', 'نام کشور', 'ارزش CIF']
+    return df
 
+@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."
@@ -45,22 +40,21 @@ def provide_advice(table_data: pd.DataFrame, hs_code: str, year: str, month: str
     prompt = (
         f"The following table shows countries that imported a product with HS code {hs_code} during the period {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. "
+        "Include competitive landscape, pricing benchmarks, logistical considerations, "
+        "risk management techniques, and steps to establish local partnerships."
     )
-    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)
@@ -70,19 +64,14 @@ def provide_advice(table_data: pd.DataFrame, hs_code: str, year: str, month: str
         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)]
-
-
 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 تخصصی")
+
     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 100610")
+        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_table = gr.Dataframe(
         headers=["کد کشور", "نام کشور", "ارزش CIF"],
         datatype=["number", "text", "number"],
@@ -90,17 +79,13 @@ with gr.Blocks() as demo:
     )
     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_advice.click(
         provide_advice,
         inputs=[out_table, inp_hs, inp_year, inp_month],
         outputs=out_advice
     )
 
-
 if __name__ == "__main__":
     demo.launch()