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Update app.py
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app.py
CHANGED
@@ -4,7 +4,7 @@ import pandas as pd
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import comtradeapicall
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from huggingface_hub import InferenceClient
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# کلید COMTRADE
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subscription_key = os.getenv("COMTRADE_API_KEY", "")
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# توکن Hugging Face
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hf_token = os.getenv("HF_API_TOKEN")
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@@ -21,14 +21,14 @@ def get_importers(hs_code: str, year: str, month: str):
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maxRecords=500, includeDesc=True
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)
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if df is None or df.empty:
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return pd.DataFrame(columns=["کد کشور","نام کشور","ارزش CIF"])
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df = df[df['cifvalue'] > 0]
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result = (
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df.groupby(["reporterCode","reporterDesc"], as_index=False)
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.agg({"cifvalue":"sum"})
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.sort_values("cifvalue", ascending=False)
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)
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result.columns = ["کد کشور","نام کشور","ارزش CIF"]
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return result
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def provide_advice(table_data: pd.DataFrame, hs_code: str, year: str, month: str):
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@@ -41,14 +41,13 @@ def provide_advice(table_data: pd.DataFrame, hs_code: str, year: str, month: str
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f"{table_str}\n\n"
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"لطفاً بر اساس این اطلاعات دو پاراگراف مشاوره تخصصی بنویسید."
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)
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# فراخوانی text_generation
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outputs = client.text_generation(
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model="google/gemma-2b",
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)
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return outputs[0]["generated_text"]
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current_year = pd.Timestamp.now().year
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years = [str(y) for y in range(2000, current_year+1)]
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@@ -57,13 +56,13 @@ months = [str(m) for m in range(1, 13)]
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with gr.Blocks() as demo:
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gr.Markdown("## نمایش کشورهایی که یک کالا را وارد کردهاند")
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with gr.Row():
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inp_hs
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inp_year
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inp_month = gr.Dropdown(choices=months, label="ماه", value=str(pd.Timestamp.now().month))
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btn_show = gr.Button("نمایش اطلاعات")
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out_table = gr.Dataframe(
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headers=["کد کشور","نام کشور","ارزش CIF"],
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datatype=["number","text","number"],
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interactive=True,
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)
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btn_show.click(get_importers, [inp_hs, inp_year, inp_month], out_table)
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@@ -78,4 +77,4 @@ with gr.Blocks() as demo:
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)
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if __name__ == "__main__":
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demo.launch()
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import comtradeapicall
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from huggingface_hub import InferenceClient
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# کلید COMTRADE
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subscription_key = os.getenv("COMTRADE_API_KEY", "")
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# توکن Hugging Face
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hf_token = os.getenv("HF_API_TOKEN")
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maxRecords=500, includeDesc=True
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)
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if df is None or df.empty:
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return pd.DataFrame(columns=["کد کشور", "نام کشور", "ارزش CIF"])
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df = df[df['cifvalue'] > 0]
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result = (
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df.groupby(["reporterCode", "reporterDesc"], as_index=False)
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.agg({"cifvalue": "sum"})
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.sort_values("cifvalue", ascending=False)
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)
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result.columns = ["کد کشور", "نام کشور", "ارزش CIF"]
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return result
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def provide_advice(table_data: pd.DataFrame, hs_code: str, year: str, month: str):
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f"{table_str}\n\n"
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"لطفاً بر اساس این اطلاعات دو پاراگراف مشاوره تخصصی بنویسید."
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)
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# فراخوانی text_generation با پارامتر درست
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outputs = client.text_generation(
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model="google/gemma-2b",
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prompt=prompt,
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max_new_tokens=256
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)
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return outputs
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current_year = pd.Timestamp.now().year
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years = [str(y) for y in range(2000, current_year+1)]
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with gr.Blocks() as demo:
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gr.Markdown("## نمایش کشورهایی که یک کالا را وارد کردهاند")
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with gr.Row():
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inp_hs = gr.Textbox(label="HS Code")
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inp_year = gr.Dropdown(choices=years, label="سال", value=str(current_year))
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inp_month = gr.Dropdown(choices=months, label="ماه", value=str(pd.Timestamp.now().month))
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btn_show = gr.Button("نمایش اطلاعات")
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out_table = gr.Dataframe(
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headers=["کد کشور", "نام کشور", "ارزش CIF"],
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datatype=["number", "text", "number"],
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interactive=True,
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)
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btn_show.click(get_importers, [inp_hs, inp_year, inp_month], out_table)
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)
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if __name__ == "__main__":
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demo.launch()
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