Update app.py

app.py

@@ -1,104 +1,64 @@
-# First, ensure you have the gradio module installed
-# You can install it using the following command:
-# !pip install gradio
-
 import gradio as gr
-import plotly.graph_objects as go  # Import plotly for plotting
-import pandas as pd
-import os
-
-# Define the path for the Excel file
-EXCEL_FILE = 'vv.xlsx'
-
-# Initialize lists to store income and expenses
-income_list = []
-expense_list = []
-
-def add_income(amount, description):
-    """Function to add income to the income list."""
-    income_list.append({'amount': amount, 'description': description})
-    return f"Added Income: {description} of amount {amount}"
-
-def add_expense(amount, description):
-    """Function to add expense to the expense list."""
-    expense_list.append({'amount': amount, 'description': description})
-    return f"Added Expense: {description} of amount {amount}"
-
-def show_pie_chart():  # Define the function to show the pie chart
-    """Function to create and return a pie chart of income and expenses."""
-    # Calculate total income and expenses
-    total_income = sum(item['amount'] for item in income_list)
-    total_expenses = sum(item['amount'] for item in expense_list)
-
-    # Calculate remaining income
-    remaining_income = total_income - total_expenses
-
-    # Check if there is any income or expenses to display
-    if total_income == 0 and total_expenses == 0:
-        return "No data to display"  # Return a message if there's no data
-
-    labels = ['Remaining Income', 'Expenses']
-    sizes = [remaining_income, total_expenses]
-    
-    # Create a pie chart using plotly
-    fig = go.Figure(data=[go.Pie(labels=labels, values=sizes, hole=.3)])  # Create a pie chart
-    return fig  # Return the figure to be displayed in Gradio
-
-def reset_data():  # Define the reset_data function
-    """Function to reset income and expense data."""
-    income_list.clear()  # Clear the income list
-    expense_list.clear()  # Clear the expense list
-    return "Data has been reset", 0, "", 0, "", None  # Return reset values
-
-def logout():  # Define the logout function
-    """Function to handle user logout."""
-    return "Logged out successfully"  # Return a logout message
-
-# Gradio interface
-with gr.Blocks(css="""
-    .gradio-container { background-color: #c7e7a2; }
-    .gr-button, .gr-button:hover { 
-        background-color: #caelf6; 
-        color: white; 
-        border: none; 
-        border-radius: 5px; 
-        padding: 10px; 
-    }
-    .gr-button:hover { background-color: #feee91; } 
-""") as demo:
-   
-    # Define main_app here before using it
-    main_app = gr.Row(visible=True)  # Set main_app to visible by default
-
-    with main_app:
-        welcome_message = gr.Textbox(label="Welcome Message", interactive=False, value="**WELCOME - khellon**")  # Set initial value here
-
-        # Create a row for income and expense sections
-        with gr.Row():
-            with gr.Column():
-                income_amount = gr.Number(label="Income Amount", value=0)
-                income_description = gr.Textbox(label="Income Description", value="")
-                add_income_button = gr.Button("Add Income")
-                add_income_output = gr.Textbox(label="Income Output", interactive=False)  # Output for income
-                add_income_button.click(add_income, inputs=[income_amount, income_description], outputs=add_income_output)
-
-            with gr.Column():
-                expense_amount = gr.Number(label="Expense Amount", value=0)
-                expense_description = gr.Textbox(label="Expense Description", value="")
-                add_expense_button = gr.Button("Add Expense")
-                add_expense_output = gr.Textbox(label="Expense Output", interactive=False)  # Output for expense
-                add_expense_button.click(add_expense, inputs=[expense_amount, expense_description], outputs=add_expense_output)
-
-        # Create a row for chart and reset/logout buttons
-        with gr.Row():
-            show_chart_button = gr.Button("Show Pie Chart")
-            show_chart_output = gr.Plot()
-            show_chart_button.click(show_pie_chart, outputs=show_chart_output)
-
-            reset_button = gr.Button("Reset Data")
-            reset_button.click(reset_data, outputs=[gr.Textbox(label="Output"), income_amount, income_description, expense_amount, expense_description, show_chart_output])
-
-            logout_button = gr.Button("Logout")  # Added logout button
-            logout_button.click(logout, outputs=[main_app])  # Handle logout action
-
-demo.launch(share=True)  # Create a public link
+from huggingface_hub import InferenceClient
+
+"""
+For more information on `huggingface_hub` Inference API support, please check the docs: https://huggingface.co/docs/huggingface_hub/v0.22.2/en/guides/inference
+"""
+client = InferenceClient("Qwen/Qwen2.5-Coder-32B-Instruct")
+
+
+def respond(
+    message,
+    history: list[tuple[str, str]],
+    system_message,
+    max_tokens,
+    temperature,
+    top_p,
+):
+    messages = [{"role": "system", "content": system_message}]
+
+    for val in history:
+        if val[0]:
+            messages.append({"role": "user", "content": val[0]})
+        if val[1]:
+            messages.append({"role": "assistant", "content": val[1]})
+
+    messages.append({"role": "user", "content": message})
+
+    response = ""
+
+    for message in client.chat_completion(
+        messages,
+        max_tokens=max_tokens,
+        stream=True,
+        temperature=temperature,
+        top_p=top_p,
+    ):
+        token = message.choices[0].delta.content
+
+        response += token
+        yield response
+
+
+"""
+For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
+"""
+demo = gr.ChatInterface(
+    respond,
+    additional_inputs=[
+        gr.Textbox(value="You are a friendly Chatbot.", label="System message"),
+        gr.Slider(minimum=1, maximum=2048, value=2048, step=1, label="Max new tokens"),
+        gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
+        gr.Slider(
+            minimum=0.1,
+            maximum=1.0,
+            value=0.95,
+            step=0.05,
+            label="Top-p (nucleus sampling)",
+        ),
+    ],
+)
+
+
+if __name__ == "__main__":
+    demo.launch()