Update app.py

app.py

@@ -1,63 +1,51 @@
 import gradio as gr
-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("HuggingFaceH4/zephyr-7b-beta")
-
-
-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=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)",
-        ),
-    ],
-)
-
-
-if __name__ == "__main__":
-    demo.launch()
+
+def respond(system_message, max_length, min_length, max_new_tokens, num_beams, temperature, top_p):
+    # Your response generation logic here
+    #response = correct_text(message, max_length, max_new_tokens, min_length, num_beams, temperature, top_p)
+    #yield response
+    return f"System message: {system_message}, Max Length: {max_length}, Min Length: {min_length}, Max new tokens: {max_new_tokens}, Num Beams: {num_beams}, Temperature: {temperature}, Top-p: {top_p}"
+
+def set_prompt(prompt_text):
+    return gr.update(value=prompt_text)
+
+# Create the Gradio interface
+with gr.Blocks() as demo:
+    system_message = gr.Textbox(value="You are a friendly Chatbot.", label="System message")
+    prompt_box = gr.Textbox(lines=2, placeholder="Enter your prompt here...")
+
+    # Predefined prompts as buttons
+    prompt1 = gr.Button("we shood buy an car")
+    prompt2 = gr.Button("this is an exampl of bad grammer")
+    prompt3 = gr.Button("their are many ways to correct grammar")
+
+    prompt1.click(set_prompt, inputs=None, outputs=prompt_box, _js="() => 'we shood buy an car'")
+    prompt2.click(set_prompt, inputs=None, outputs=prompt_box, _js="() => 'this is an exampl of bad grammer'")
+    prompt3.click(set_prompt, inputs=None, outputs=prompt_box, _js="() => 'their are many ways to correct grammar'")
+
+    max_length = gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max Length")
+    min_length = gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Min Length")
+    max_new_tokens = gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens")
+    num_beams = gr.Slider(minimum=1, maximum=10, value=5, step=1, label="Num Beams")
+    temperature = gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature")
+    top_p = gr.Slider(minimum=0.1, maximum=1.0, value=0.95, step=0.05, label="Top-p (nucleus sampling)")
+
+    show_top_p = gr.Checkbox(value=True, label="Show Top-p Slider")
+    top_p_slider = gr.Slider(minimum=0.1, maximum=1.0, value=0.95, step=0.05, label="Top-p (nucleus sampling)", visible=True)
+    show_top_p.change(lambda show: gr.update(visible=show), show_top_p, top_p_slider)
+
+    demo = gr.ChatInterface(
+        respond,
+        additional_inputs=[
+            system_message,
+            prompt_box,
+            max_length,
+            min_length,
+            max_new_tokens,
+            num_beams,
+            temperature,
+            top_p_slider,
+        ],
+    )
+
+demo.launch()