Update app.py

app.py

@@ -1,56 +1,17 @@
-from huggingface_hub import InferenceClient
 import gradio as gr
-
-client = InferenceClient("grammarly/coedit-large")
-
-def generate(prompt, temperature=0.9, max_new_tokens=256, top_p=0.95, repetition_penalty=1.0):
-    temperature = float(temperature)
-    if temperature < 1e-2: temperature = 1e-2
-    top_p = float(top_p)
-    
-    generate_kwargs = dict(temperature=temperature, max_new_tokens=max_new_tokens, top_p=top_p, repetition_penalty=repetition_penalty, do_sample=True, seed=42,)
-    
-    #formatted_prompt = format_prompt_grammar(f"Corrected Sentence: {prompt}", history)
-    #formatted_prompt = format_prompt(f"{system_prompt} {prompt}", history)
-    formatted_prompt = "Fix grammatical errors in this sentence: " + prompt
-    print("\nPROMPT: \n\t" + formatted_prompt)
-
-    # Generate text from the HF inference
-    stream = client.text_generation(formatted_prompt, **generate_kwargs, stream=True, details=True, return_full_text=False)
-    output = ""
-
-    for response in stream:
-        output += response.token.text
-        yield output
-    return output
-
-
-
-additional_inputs=[
-    gr.Slider( label="Temperature", value=0.9, minimum=0.0, maximum=1.0, step=0.05, interactive=True, info="Higher values produce more diverse outputs", ),
-    gr.Slider( label="Max new tokens", value=256, minimum=0, maximum=1048, step=64, interactive=True, info="The maximum numbers of new tokens", ),
-    gr.Slider( label="Top-p (nucleus sampling)", value=0.90, minimum=0.0, maximum=1, step=0.05, interactive=True, info="Higher values sample more low-probability tokens", ),
-    gr.Slider( label="Repetition penalty", value=1.2, minimum=1.0, maximum=2.0, step=0.05, interactive=True, info="Penalize repeated tokens", )
-]
-
-
-gr.ChatInterface(
-    fn=generate,
-    chatbot=gr.Chatbot(show_label=False, show_share_button=False, show_copy_button=True, likeable=True, layout="panel"),
-    additional_inputs=additional_inputs,
-    title="My Grammarly Space",
-    concurrency_limit=20,
-).launch(show_api=False)
-
-
-#import gradio as gr
-#from transformers import pipeline
-
-#def correct_text(text):
-#    model_id = "grammarly/coedit-large"
-#    pipe = pipeline("text2text-generation", model=model_id)
-#    corrected = pipe(text)[0]['generated_text']
-#    return corrected
-
-#interface = gr.Interface(fn=correct_text, inputs="text_area", outputs="text")
-#interface.launch()
+from transformers import pipeline
+
+def correct_text(text, temperature=1.0, top_p=0.9, top_k=50):
+    model_id = "grammarly/coedit-large"
+    pipe = pipeline("text2text-generation", model=model_id, 
+                    generation_kwargs={"temperature": temperature, "top_p": top_p, "top_k": top_k})
+    corrected = pipe(text)[0]['generated_text']
+    return corrected
+
+interface = gr.Interface(fn=correct_text,
+                         inputs=[gr.inputs.TextArea(label="Input Text"),
+                                 gr.inputs.Slider(minimum=0.1, maximum=1.0, default=1.0, label="Temperature"),
+                                 gr.inputs.Slider(minimum=0.0, maximum=1.0, default=0.9, label="Top_p"),
+                                 gr.inputs.Slider(minimum=0, maximum=100, default=50, label="Top_k")],
+                         outputs="text")
+interface.launch()