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| <html> | |
| <head> | |
| <meta charset="utf-8" /> | |
| <meta name="viewport" content="width=device-width, initial-scale=1" /> | |
| <title>AI Paraphraser - Amna Shahzad</title> | |
| <link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/@stlite/browser@0.85.1/build/stlite.css" /> | |
| <link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/@stlite/browser@0.85.1/build/style.css" /> | |
| </head> | |
| <body> | |
| <streamlit-app> | |
| import json | |
| import streamlit as st | |
| from pyodide.code import run_js | |
| from pyodide.ffi import to_js | |
| from js import JSON, Object | |
| # ONNX (browser) copy of google/flan-t5-small - T5 text-to-text model | |
| MODEL = "Xenova/flan-t5-small" | |
| st.set_page_config(page_title="AI Paraphraser", page_icon="✨", layout="wide") | |
| # MANDATORY: Name and Student ID in the title | |
| st.title("Amna Shahzad - Student ID: B04-0923-000008") | |
| st.caption("CS4106 Mid-Term | AI Paraphraser (Text-to-Text with T5)") | |
| if "gen" not in st.session_state: | |
| msg = st.empty() | |
| msg.info("Loading T5 model (first run only, please wait)...") | |
| try: | |
| mod = await run_js("import('https://cdn.jsdelivr.net/npm/@huggingface/transformers@3.8.1')") | |
| st.session_state["gen"] = await mod.pipeline("text2text-generation", MODEL) | |
| msg.empty() | |
| except Exception as e: | |
| msg.error(f"Could not load model: {e}") | |
| st.stop() | |
| gen = st.session_state["gen"] | |
| st.success(f"Model loaded: {MODEL}") | |
| text = st.text_area("Enter a sentence to paraphrase:", height=120, max_chars=1000) | |
| creativity = st.slider("Creativity (temperature)", 0.3, 1.5, 0.8) | |
| if st.button("Paraphrase"): | |
| if not text.strip(): | |
| st.warning("Please type something first.") | |
| elif len(text.split()) > 150: | |
| st.error("Text too long - please keep it under 150 words.") | |
| else: | |
| try: | |
| with st.spinner("Paraphrasing..."): | |
| prompt = "Paraphrase this sentence in different words: " + text | |
| opts = to_js({"max_new_tokens": 128, "do_sample": True, | |
| "temperature": creativity, "top_p": 0.9}, | |
| dict_converter=Object.fromEntries) | |
| raw = await gen(prompt, opts) | |
| output = json.loads(JSON.stringify(raw))[0]["generated_text"] | |
| col1, col2 = st.columns(2) | |
| with col1: | |
| st.subheader("📝 Original") | |
| st.info(text) | |
| st.caption(f"{len(text.split())} words") | |
| with col2: | |
| st.subheader("✨ Paraphrased") | |
| st.success(output) | |
| st.caption(f"{len(output.split())} words") | |
| if output.strip().lower() == text.strip().lower(): | |
| st.warning("⚠️ Output is identical to input - try again or raise creativity.") | |
| except Exception as e: | |
| st.error(f"Something went wrong: {e}") | |
| </streamlit-app> | |
| <script type="module" src="https://cdn.jsdelivr.net/npm/@stlite/browser@0.85.1/build/stlite.js"></script> | |
| </body> | |
| </html> |