Upload app.py.py

app.py.py

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+# -*- coding: utf-8 -*-
+"""nlp2.0.ipynb
+
+Automatically generated by Colab.
+
+Original file is located at
+    https://colab.research.google.com/drive/1ybbW8OhudgBtSnghE8o6Z4tREzPlUx7S
+"""
+
+!pip install transformers gradio accelerate
+
+from transformers import pipeline
+
+# Load the FLAN Alpaca Large model
+paraphraser = pipeline("text2text-generation", model="declare-lab/flan-alpaca-large")
+
+!pip install transformers gradio sentencepiece
+
+from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
+import gradio as gr
+
+# Load model and tokenizer
+model_name = "ramsrigouthamg/t5_paraphraser"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
+
+# Define style prompts
+def generate_prompt(text, style):
+    style_prompts = {
+        "Formal": "Please rewrite the following text in a formal and professional tone:\n\n",
+        "Friendly": "Please rewrite the following text in a casual and friendly tone:\n\n",
+        "Poetic": "Rewrite the text in a poetic and metaphorical way, like a short verse:\n\n",
+        "Gen Z": "Rewrite this text using Gen Z slang, internet expressions, abbreviations, and emojis:\n\n"
+    }
+
+    # Default if style not found
+    base_prompt = style_prompts.get(style, "Rewrite the text:\n\n")
+    return base_prompt + text
+
+# Function to rewrite text in selected style
+def rewrite_text(text, style):
+    if not text.strip():
+        return "Please enter some text."
+
+    # Build the prompt based on the selected style
+    if style == "Gen Z":
+        prompt = f"Rewrite the following text in a funny Gen Z tone with slang, emojis, and internet expressions:\n\n{text}"
+    elif style == "Poetic":
+        prompt = f"Rewrite the following text in a poetic and artistic style:\n\n{text}"
+    elif style == "Formal":
+        prompt = f"Rewrite the following text in a formal, professional tone:\n\n{text}"
+    elif style == "Friendly":
+        prompt = f"Rewrite the following text in a friendly and conversational style:\n\n{text}"
+    else:
+        prompt = f"Rewrite the following text:\n\n{text}"
+
+    # Call the model (paraphraser)
+    response = paraphraser(prompt, max_length=100)[0]['generated_text']
+
+    # Optional: clean output (remove repeated prompt from response if needed)
+    return response.replace(prompt, "").strip()
+
+
+# Gradio UI
+import gradio as gr
+
+# Define the interface
+with gr.Blocks(theme=gr.themes.Monochrome()) as demo:
+    gr.Markdown(
+        """
+        <h1 style="text-align: center;">📝 Rewrite My Text</h1>
+        <p style="text-align: center;">Transform your text into <b>fun, formal, poetic, or Gen Z</b> styles using AI! 🚀</p>
+        """,
+        elem_id="header",
+    )
+
+    with gr.Row():
+        with gr.Column(scale=1):
+            input_text = gr.Textbox(
+                label="Input Text",
+                placeholder="Enter your sentence here...",
+                lines=4
+            )
+            style = gr.Dropdown(
+                label="Choose Style",
+                choices=["Gen Z", "Formal", "Poetic", "Friendly"],
+                value="Gen Z"
+            )
+            submit_button = gr.Button("✨ Submit", variant="primary")
+            clear_button = gr.Button("🧹 Clear")
+
+        with gr.Column(scale=1):
+            output_text = gr.Textbox(
+                label="Rewritten Text",
+                placeholder="Your rewritten sentence will appear here...",
+                lines=4
+            )
+
+    # Button functionality
+    submit_button.click(fn=rewrite_text, inputs=[input_text, style], outputs=output_text)
+    clear_button.click(fn=lambda: ("", ""), inputs=[], outputs=[input_text, output_text])
+
+# Launch the app
+demo.launch(share=True)