Update app.py

app.py

@@ -1,60 +1,43 @@
 import gradio as gr
 from huggingface_hub import InferenceClient
+import numpy as np
+import pandas as pd
+from transformers import pipeline
+import torch
+
+model = "meta-llama/Meta-Llama-3-8B"
+generator=pipeline(task='text-generation', model=model)
+
+
+tones = {
+    'natural': 'human, authentic',
+    'fluency': 'readable, clarified',
+    'formal': 'sophistocated',
+    'academic': 'technical and scholarly',
+    'simple': 'simple and easily understandable',
+}
+
+
+def generate(text, max_length):
+    x=generator(text, max_length=max_length, num_return_sequences=1)
+    return x
+
+
+def respond(message, tone="natural", max_length=512):
+    prompt = f"Paraphrase this text in a more {tones[tone]} way: {message}"
+    text = generate(prompt, max_length)
+    print(text)
+    text = text[0]["generated_text"]
+    if prompt in text:
+        text = text.split(":", 1)[1]
+    return text
+        
 
-"""
-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)",
-        ),
     ],
 )