Update app.py

app.py

@@ -1,129 +1,129 @@
-import streamlit as st
-from transformers import pipeline, AutoTokenizer, AutoModelForSequenceClassification, AutoModelForCausalLM
-import torch
-
-# -------------------------------
-# Page Configuration
-# -------------------------------
-st.set_page_config(
-    page_title="AI Sentiment Essay Generator",
-    page_icon="🧠",
-    layout="wide"
-)
-
-st.markdown("""
-<style>
-body {
-    background: radial-gradient(circle at top, #1f1f2e, #0f0f16);
-    color: #f0f0f0;
-}
-.main {
-    background-color: rgba(20, 20, 30, 0.8);
-    padding: 30px;
-    border-radius: 20px;
-    box-shadow: 0px 0px 15px rgba(100,100,255,0.2);
-}
-textarea {
-    border-radius: 10px !important;
-}
-</style>
-""", unsafe_allow_html=True)
-
-# -------------------------------
-# Title and Description
-# -------------------------------
-st.title("🧠 AI Sentiment Essay Generator")
-st.write("Enter a prompt — the AI will detect its sentiment (positive, negative, or neutral) "
-         "and write an expressive paragraph aligned with that emotion 💬.")
-
-# -------------------------------
-# Load Models (Cached)
-# -------------------------------
-@st.cache_resource
-def load_sentiment_model():
-    tokenizer = AutoTokenizer.from_pretrained("cardiffnlp/twitter-roberta-base-sentiment")
-    model = AutoModelForSequenceClassification.from_pretrained("cardiffnlp/twitter-roberta-base-sentiment")
-    sentiment_pipeline = pipeline("sentiment-analysis", model=model, tokenizer=tokenizer)
-    return sentiment_pipeline
-
-@st.cache_resource
-def load_generation_model():
-    gen_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen1.5-0.5B-Chat")
-    gen_tokenizer = AutoTokenizer.from_pretrained("Qwen/Qwen1.5-0.5B-Chat")
-    generator = pipeline("text-generation", model=gen_model, tokenizer=gen_tokenizer)
-    return generator
-
-with st.spinner("Loading AI models... ⏳"):
-    sentiment_analyzer = load_sentiment_model()
-    text_generator = load_generation_model()
-
-# -------------------------------
-# Input Section
-# -------------------------------
-user_input = st.text_area("💬 Enter your topic or prompt here:", height=120, placeholder="e.g., Technology and human connection...")
-
-generate_button = st.button("✨ Generate Essay")
-
-# -------------------------------
-# Main Logic
-# -------------------------------
-if generate_button and user_input.strip() != "":
-    with st.spinner("Analyzing sentiment... 🧠"):
-        sentiment_result = sentiment_analyzer(user_input)[0]
-        label = sentiment_result["label"].capitalize()
-        score = round(sentiment_result["score"] * 100, 2)
-
-    # Sentiment-based UI styling
-    if "Positive" in label:
-        color = "#00C851"
-        emoji = "😊"
-        gradient = "linear-gradient(90deg, #00C851, #007E33)"
-    elif "Negative" in label:
-        color = "#ff4444"
-        emoji = "😞"
-        gradient = "linear-gradient(90deg, #ff4444, #CC0000)"
-    else:
-        color = "#33b5e5"
-        emoji = "😐"
-        gradient = "linear-gradient(90deg, #33b5e5, #0099CC)"
-
-    st.markdown(f"""
-        <div style='padding:15px;border-radius:12px;background:{gradient};text-align:center;'>
-        <h3>{emoji} Detected Sentiment: <b>{label}</b> ({score}%)</h3>
-        </div>
-    """, unsafe_allow_html=True)
-
-    # -------------------------------
-    # Generate Sentiment-Aligned Text
-    # -------------------------------
-    prompt = f"Write a {label.lower()} and expressive paragraph about: {user_input}."
-    with st.spinner(f"Generating a {label.lower()} essay... ✍️"):
-        result = text_generator(prompt, max_length=200, do_sample=True, temperature=0.9)
-        generated_text = result[0]["generated_text"]
-
-    # -------------------------------
-    # Display Output
-    # -------------------------------
-    st.subheader("📝 AI-Generated Essay")
-    st.markdown(
-        f"""
-        <div style='padding:20px;background-color:rgba(255,255,255,0.08);border-radius:15px;border-left:6px solid {color};'>
-        <p style='font-size:1.1rem;line-height:1.6em;'>{generated_text}</p>
-        </div>
-        """, unsafe_allow_html=True
-    )
-
-    # -------------------------------
-    # Sidebar Info
-    # -------------------------------
-    with st.sidebar:
-        st.header("🧩 Summary")
-        st.markdown(f"**Prompt:** {user_input}")
-        st.markdown(f"**Sentiment:** {label} {emoji}")
-        st.markdown(f"**Confidence:** {score}%")
-        st.markdown("---")
-        st.info("Tip: Try emotional prompts like *“life after success”* or *“loneliness in a big city.”*")
-
-else:
-    st.info("💡 Enter your text above and click **Generate Essay** to begin!")
-
+import streamlit as st
+from transformers import pipeline, AutoTokenizer, AutoModelForSequenceClassification, AutoModelForCausalLM
+import torch
+
+# -------------------------------
+# Page Configuration
+# -------------------------------
+st.set_page_config(
+    page_title="AI Sentiment Essay Generator",
+    page_icon="🧠",
+    layout="wide"
+)
+
+st.markdown("""
+<style>
+body {
+    background: radial-gradient(circle at top, #1f1f2e, #0f0f16);
+    color: #f0f0f0;
+}
+.main {
+    background-color: rgba(20, 20, 30, 0.8);
+    padding: 30px;
+    border-radius: 20px;
+    box-shadow: 0px 0px 15px rgba(100,100,255,0.2);
+}
+textarea {
+    border-radius: 10px !important;
+}
+</style>
+""", unsafe_allow_html=True)
+
+# -------------------------------
+# Title and Description
+# -------------------------------
+st.title("🧠 AI Sentiment Essay Generator")
+st.write("Enter a prompt — the AI will detect its sentiment (positive, negative, or neutral) "
+         "and write an expressive paragraph aligned with that emotion 💬.")
+
+# -------------------------------
+# Load Models (Cached)
+# -------------------------------
+@st.cache_resource
+def load_sentiment_model():
+    tokenizer = AutoTokenizer.from_pretrained("cardiffnlp/twitter-roberta-base-sentiment")
+    model = AutoModelForSequenceClassification.from_pretrained("cardiffnlp/twitter-roberta-base-sentiment")
+    sentiment_pipeline = pipeline("sentiment-analysis", model=model, tokenizer=tokenizer)
+    return sentiment_pipeline
+
+@st.cache_resource
+def load_generation_model():
+    gen_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen1.5-0.5B-Chat")
+    gen_tokenizer = AutoTokenizer.from_pretrained("Qwen/Qwen1.5-0.5B-Chat")
+    generator = pipeline("text-generation", model=gen_model, tokenizer=gen_tokenizer)
+    return generator
+
+with st.spinner("Loading AI models... ⏳"):
+    sentiment_analyzer = load_sentiment_model()
+    text_generator = load_generation_model()
+
+# -------------------------------
+# Input Section
+# -------------------------------
+user_input = st.text_area("💬 Enter your topic or prompt here:", height=120, placeholder="e.g., Technology and human connection...")
+
+generate_button = st.button("✨ Generate Essay")
+
+# -------------------------------
+# Main Logic
+# -------------------------------
+if generate_button and user_input.strip() != "":
+    with st.spinner("Analyzing sentiment... 🧠"):
+        sentiment_result = sentiment_analyzer(user_input)[0]
+        label = sentiment_result["label"].capitalize()
+        score = round(sentiment_result["score"] * 100, 2)
+
+    # Sentiment-based UI styling
+    if "Positive" in label:
+        color = "#00C851"
+        emoji = "😊"
+        gradient = "linear-gradient(90deg, #00C851, #007E33)"
+    elif "Negative" in label:
+        color = "#ff4444"
+        emoji = "😞"
+        gradient = "linear-gradient(90deg, #ff4444, #CC0000)"
+    else:
+        color = "#33b5e5"
+        emoji = "😐"
+        gradient = "linear-gradient(90deg, #33b5e5, #0099CC)"
+
+    st.markdown(f"""
+        <div style='padding:15px;border-radius:12px;background:{gradient};text-align:center;'>
+        <h3>{emoji} Detected Sentiment: <b>{label}</b> ({score}%)</h3>
+        </div>
+    """, unsafe_allow_html=True)
+
+    # -------------------------------
+    # Generate Sentiment-Aligned Text
+    # -------------------------------
+    prompt = f"Write a {label.lower()} and expressive paragraph about: {user_input}."
+    with st.spinner(f"Generating a {label.lower()} essay... ✍️"):
+        result = text_generator(prompt, max_length=200, do_sample=True, temperature=0.9)
+        generated_text = result[0]["generated_text"]
+
+    # -------------------------------
+    # Display Output
+    # -------------------------------
+    st.subheader("📝 AI-Generated Essay")
+    st.markdown(
+        f"""
+        <div style='padding:20px;background-color:rgba(255,255,255,0.08);border-radius:15px;border-left:6px solid {color};'>
+        <p style='font-size:1.1rem;line-height:1.6em;'>{generated_text}</p>
+        </div>
+        """, unsafe_allow_html=True
+    )
+
+    # -------------------------------
+    # Sidebar Info
+    # -------------------------------
+    with st.sidebar:
+        st.header("🧩 Summary")
+        st.markdown(f"**Prompt:** {user_input}")
+        st.markdown(f"**Sentiment:** {label} {emoji}")
+        st.markdown(f"**Confidence:** {score}%")
+        st.markdown("---")
+        st.info("Tip: Try emotional prompts like *“life after success”* or *“loneliness in a big city.”*")
+
+else:
+    st.info("💡 Enter your text above and click **Generate Essay** to begin!")
+