Update app.py

app.py

@@ -1,6 +1,74 @@
-import gradio as gr
+# import torch
+# device = "cuda" if torch.cuda.is_available() else "cpu"
+# print(f"Using device: {device}")
+
+from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
+
+model_name = "rajistics/informal_formal_style_transfer"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
+import pandas as pd
+
+df = pd.read_csv("hf://datasets/thesherrycode/gen-z-slangs-translation/gen_z_slangs_translation.csv")
+
+# Rename the actual columns
+df = df[["Gen-Z Slang", "Plain English"]].dropna().drop_duplicates()
+df.columns = ["slang", "formal"]
+df.head()
+
+gradio_examples = [["[Gen-Z Example] " + row["slang"]] for _, row in df.sample(3, random_state=1).iterrows()]
+gradio_examples
+
+examples = [
+    ["hey, can u send me the stuff by tonight?"],
+    ["yo sorry i missed the call, was busy"],
+    ["lemme know if ur free tmrw to chat abt the thing"],
+    ["bro the file’s messed up, fix it asap pls"],
+    ["i'm out rn, text u later"]
+]
+
+# Clean the model output
+def clean_output(output: str):
+    return re.sub(r"(?i)make this sentence more formal", "", output).strip()
+
+# Main function
+def make_formal(text):
+    if not text.strip():
+        return "⚠️ Please enter some text."
+    prompt = "[Casual] " + text.strip() + " [Formal]"
+    inputs = tokenizer(prompt, return_tensors="pt", truncation=True).to(device)
+    outputs = model.generate(**inputs, max_new_tokens=100)
+    result = tokenizer.decode(outputs[0], skip_special_tokens=True)
+    return clean_output(result)
+
+iface = gr.Interface(
+    fn=make_formal,
+    inputs=gr.Textbox(
+        lines=3,
+        label="🗣️ Your Slang / Casual Text",
+        placeholder="e.g., yo can u help me out real quick?"
+    ),
+    outputs=gr.Textbox(
+        label="📄 Formal & Polished Version",
+        lines=4,
+        interactive=True
+    ),
+    title="💬 Text Polisher: From Slang to Formal",
+    description=(
+        "Transform casual, Gen-Z slang, or unpolished English into clear, professional language. 🧠✨\n\n"
+        "This demo uses a text generation model to rewrite input sentences with improved formality — great for school, work, or writing more professionally.\n\n"
+        "✍️ The output is editable — feel free to tweak before using/copying!\n\n"
+    ),
+    article=(
+        "**Project by Jonathan Friedman**  \n"
+        "📌 **Task:** Text Generation (Formality Transfer using Sequence-to-Sequence)  \n"
+        "🧠 **Model:** rajistics/informal_formal_style_transfer  \n"
+        "📚 **Dataset Used:** thesherrycode/gen-z-slangs-translation (used to generate real-world Gen-Z slang examples)  \n"
+        "🛠️ **Tech Stack:** 🤗 Transformers, Hugging Face Datasets, Gradio  \n"
+    ),
+    examples=examples + gradio_examples,
+    theme="soft"
+)
+
 
-def greet (name):
-  return f"Hello, {name}!"
-iface = gr.Interface(fn=greet, inputs="text",outputs="text")
 iface.launch()