Update app.py

app.py

@@ -30,30 +30,27 @@ from deep_translator import (GoogleTranslator,
                              QcriTranslator,
                              single_detection,
                              batch_detection)
-# from pyaspeller import YandexSpeller
-# def error_correct_pyspeller(sample_text):
-#     """ grammer correction of input text"""
-#     speller = YandexSpeller()
-#     fixed = speller.spelled(sample_text)
-#     return fixed
+from pyaspeller import YandexSpeller
+def error_correct_pyspeller(sample_text):
+    """ grammer correction of input text"""
+    speller = YandexSpeller()
+    fixed = speller.spelled(sample_text)
+    return fixed
 
-# def postprocerssing(inp_text: str):
-#     """Post preocessing of the llm response"""
-#     inp_text = re.sub('<[^>]+>', '', inp_text)
-#     inp_text = inp_text.split('##', 1)[0]
-#     inp_text = error_correct_pyspeller(inp_text)
-#     return inp_text
+def postprocerssing(inp_text: str):
+    """Post preocessing of the llm response"""
+    inp_text = re.sub('<[^>]+>', '', inp_text)
+    inp_text = inp_text.split('##', 1)[0]
+    inp_text = error_correct_pyspeller(inp_text)
+    return inp_text
     
 
-# streamer = TextStreamer(tokenizer, timeout=10.0, skip_prompt=True, skip_special_tokens = True)
 
-messages = []
-
-def generate_text(prompt, max_length, top_p, top_k):
-    global messages
+def llm_run(prompt, max_length, top_p, temprature, top_k, messages):
+    
     lang = single_detection(prompt, api_key='4ab77f25578d450f0902fb42c66d5e11')
-    # if lang == 'en':
-    #     prompt = error_correct_pyspeller(prompt)
+    if lang == 'en':
+        prompt = error_correct_pyspeller(prompt)
     en_translated = GoogleTranslator(source='auto', target='en').translate(prompt)
     messages.append({"role": "user", "content": en_translated})
     # messages.append({"role": "user", "content": prompt})           
@@ -69,16 +66,10 @@ def generate_text(prompt, max_length, top_p, top_k):
     )
     generate_kwargs = dict(
         max_length=int(max_length),top_p=float(top_p), do_sample=True,
-        top_k=int(top_k), streamer=streamer, temperature=0.6, repetition_penalty=1.2
+        top_k=int(top_k), streamer=streamer, temperature=int(temprature), repetition_penalty=1.2
         
     )
 
-    # _ = model.generate(input_ids, streamer = streamer, max_new_tokens = int(max_length), pad_token_id = tokenizer.eos_token_id,
-    #     temperature=0.6,  # Adjust this value
-    #     top_k=int(top_k),        # Adjust this value
-    #     top_p=float(top_p),       # Adjust this value
-    #     repetition_penalty=1.2
-    #                    )
     t = Thread(target=model.generate,  args=(input_ids,), kwargs=generate_kwargs)
     t.start()
 
@@ -92,17 +83,32 @@ def generate_text(prompt, max_length, top_p, top_k):
     
     messages.append({"role": "assistant", "content": "".join(generated_text)})   
 
-description = """
-# Deploy our LLM
-"""
-inputs = [
-    gr.Textbox(label="Prompt text", lines=5),
-    gr.Textbox(label="max-lenth generation", value=100),
-    gr.Slider(0.0, 1.0, label="top-p value", value=0.95),
-    gr.Textbox(label="top-k", value=50,),
-]
-outputs = [gr.Textbox(label="Generated Text", lines= 10)]
-
-demo = gr.Interface(fn=generate_text, inputs=inputs, outputs=outputs,  description=description)
+def clear_memory(messages):
+    messages.clear()
+    return "Memory cleaned."
+    
 
+with gr.Blocks(theme=gr.themes.Default(primary_hue=gr.themes.colors.orange, secondary_hue=gr.themes.colors.pink)) as demo:
+    stored_message = gr.State([])
+    with gr.Row():
+        with gr.Column(scale=2):
+            prompt_text = gr.Textbox(lines=7, label="Prompt", scale=2)
+            with gr.Row():
+                btn1 = gr.Button("Submit", scale=1)
+                btn2 = gr.Button("Clear",  scale=1)
+                btn3 = gr.Button("Clean Memory",  scale=2)
+        with gr.Column(scale=2):
+            out_text = gr.Text(lines=15, label="Output", scale=2)
+    btn1.click(fn=llm_run, inputs=[
+                                prompt_text, 
+                                gr.Textbox(label="Max-Lenth generation", value=500),
+                                gr.Slider(0.0, 1.0, label="Top-P value", value=0.90),
+                                gr.Slider(0.0, 1.0, label="Temprature value", value=0.65),
+                                gr.Textbox(label="Top-K", value=50,),
+                                stored_message
+                                  ], outputs=out_text)
+    btn2.click(lambda: [None, None], outputs=[text1, out_text])
+    btn3.click(fn=clear_memory, inputs=[stored_message], outputs=[out_text])
+    
+# demo = gr.Interface(fn=llm_run, inputs=["text"], outputs="text")
 demo.launch(debug=True, share=True)