Create app.py

app.py

@@ -1,70 +1,64 @@
+# app.py
 import gradio as gr
-from huggingface_hub import InferenceClient
 
+# Conversion function
+def convert_units(value, conversion_type, from_unit, to_unit):
+    try:
+        value = float(value)
+    except ValueError:
+        return "Please enter a numeric value"
+    
+    # Weight conversions
+    weight_units = {"kg": 1, "gram": 1000, "lb": 2.20462}
+    if conversion_type == "Weight":
+        return round(value * weight_units[to_unit] / weight_units[from_unit], 4)
+    
+    # Length conversions
+    length_units = {"meter": 1, "cm": 100, "feet": 3.28084, "inch": 39.3701}
+    if conversion_type == "Length":
+        return round(value * length_units[to_unit] / length_units[from_unit], 4)
+    
+    # Temperature conversions
+    if conversion_type == "Temperature":
+        if from_unit == "Celsius" and to_unit == "Fahrenheit":
+            return round((value * 9/5) + 32, 2)
+        elif from_unit == "Fahrenheit" and to_unit == "Celsius":
+            return round((value - 32) * 5/9, 2)
+        elif from_unit == to_unit:
+            return value
+    
+    return "Conversion not supported"
 
-def respond(
-    message,
-    history: list[dict[str, str]],
-    system_message,
-    max_tokens,
-    temperature,
-    top_p,
-    hf_token: gr.OAuthToken,
-):
-    """
-    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(token=hf_token.token, model="openai/gpt-oss-20b")
+# Dropdown options
+conversion_types = ["Weight", "Length", "Temperature"]
+weight_units = ["kg", "gram", "lb"]
+length_units = ["meter", "cm", "feet", "inch"]
+temperature_units = ["Celsius", "Fahrenheit"]
 
-    messages = [{"role": "system", "content": system_message}]
-
-    messages.extend(history)
-
-    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,
-    ):
-        choices = message.choices
-        token = ""
-        if len(choices) and choices[0].delta.content:
-            token = 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
-"""
-chatbot = gr.ChatInterface(
-    respond,
-    type="messages",
-    additional_inputs=[
-        gr.Textbox(value="You are a friendly Chatbot.", label="System message"),
-        gr.Slider(minimum=1, maximum=2048, value=512, 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)",
-        ),
-    ],
-)
+# Function to get units based on type
+def get_units(conversion_type):
+    if conversion_type == "Weight":
+        return gr.update(choices=weight_units, value="kg"), gr.update(choices=weight_units, value="gram")
+    elif conversion_type == "Length":
+        return gr.update(choices=length_units, value="meter"), gr.update(choices=length_units, value="cm")
+    elif conversion_type == "Temperature":
+        return gr.update(choices=temperature_units, value="Celsius"), gr.update(choices=temperature_units, value="Fahrenheit")
 
+# Gradio Interface
 with gr.Blocks() as demo:
-    with gr.Sidebar():
-        gr.LoginButton()
-    chatbot.render()
-
+    gr.Markdown("# 🌐 Unit Conversion App")
+    
+    conversion_type = gr.Dropdown(conversion_types, label="Conversion Type", value="Weight")
+    from_unit = gr.Dropdown(weight_units, label="From Unit", value="kg")
+    to_unit = gr.Dropdown(weight_units, label="To Unit", value="gram")
+    value_input = gr.Textbox(label="Value to Convert", value="1")
+    result_output = gr.Textbox(label="Converted Value")
+    convert_button = gr.Button("Convert")
+    
+    # Update unit dropdowns dynamically
+    conversion_type.change(fn=get_units, inputs=conversion_type, outputs=[from_unit, to_unit])
+    
+    # Convert on button click
+    convert_button.click(fn=convert_units, inputs=[value_input, conversion_type, from_unit, to_unit], outputs=result_output)
 
-if __name__ == "__main__":
-    demo.launch()
+demo.launch()