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app.py

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+import gradio as gr
+from transformers import pipeline
+import re
+import json
+
+# ── Same model as Session 1's Silly Phrase Finder ──
+classifier = pipeline(
+    "zero-shot-classification",
+    model="valhalla/distilbart-mnli-12-3",
+)
+
+# ── Four analytical lenses ──
+LENSES = {
+    "Tone": [
+        "dramatic and intense",
+        "humorous and playful",
+        "melancholic and sad",
+        "suspenseful and tense",
+        "warm and affectionate",
+        "dry and matter-of-fact",
+    ],
+    "Formality": [
+        "academic and scholarly",
+        "casual and conversational",
+        "poetic and lyrical",
+        "journalistic and reportorial",
+    ],
+    "Energy": [
+        "fast-paced and urgent",
+        "slow and contemplative",
+        "building tension",
+        "calm and steady",
+    ],
+    "Genre Feel": [
+        "literary fiction",
+        "thriller or mystery",
+        "romance",
+        "comedy",
+        "memoir or personal essay",
+        "news report",
+    ],
+}
+
+# Short display names (strip the "and ..." qualifiers)
+def short_label(label):
+    return label.split(" and ")[0].split(" or ")[0].strip()
+
+
+# ── Sentence splitter ──
+def split_sentences(text):
+    sentences = [
+        s.strip()
+        for s in re.split(r'(?<=[.!?])\s+', text)
+        if len(s.strip()) > 15
+    ]
+    return sentences[:8]  # cap for free-CPU performance
+
+
+# ── Main analysis function ──
+def analyze_passage(text):
+    if not text or not text.strip():
+        return placeholder_html("Paste a passage above to begin analysis.")
+
+    sentences = split_sentences(text)
+    if len(sentences) < 2:
+        return placeholder_html(
+            "Please paste a longer passage — at least a few sentences."
+        )
+
+    # 1) Passage-level analysis through every lens
+    passage_scores = {}
+    for lens_name, labels in LENSES.items():
+        result = classifier(text[:512], candidate_labels=labels)
+        passage_scores[lens_name] = {
+            label: score
+            for label, score in zip(result["labels"], result["scores"])
+        }
+
+    # 2) Sentence-level analysis through the Tone lens
+    tone_labels = LENSES["Tone"]
+    sentence_data = []
+    for sentence in sentences:
+        result = classifier(sentence, candidate_labels=tone_labels)
+        sentence_data.append(
+            {
+                "text": sentence,
+                "tone": result["labels"][0],
+                "score": result["scores"][0],
+            }
+        )
+
+    return build_dashboard_html(passage_scores, sentence_data)
+
+
+# ── HTML builder ──
+
+TONE_COLORS = {
+    "dramatic and intense": "#e74c3c",
+    "humorous and playful": "#f39c12",
+    "melancholic and sad": "#3498db",
+    "suspenseful and tense": "#9b59b6",
+    "warm and affectionate": "#e91e63",
+    "dry and matter-of-fact": "#78909c",
+}
+
+
+def placeholder_html(msg):
+    return (
+        f'<p style="color:#999;text-align:center;padding:48px 0;'
+        f'font-family:system-ui;font-size:1.05em;">{msg}</p>'
+    )
+
+
+def build_dashboard_html(passage_scores, sentence_data):
+    # ── Lens summary cards ──
+    lens_icons = {"Tone": "🎭", "Formality": "📐", "Energy": "⚡", "Genre Feel": "📚"}
+    cards = ""
+    for lens_name, scores in passage_scores.items():
+        top_label = max(scores, key=scores.get)
+        top_score = scores[top_label]
+        icon = lens_icons.get(lens_name, "")
+        cards += f"""
+        <div class="lens-card">
+            <div class="lens-icon">{icon}</div>
+            <div class="lens-title">{lens_name}</div>
+            <div class="lens-result">{short_label(top_label)}</div>
+            <div class="lens-score">{top_score:.0%} confidence</div>
+        </div>"""
+
+    # ── Sentence rows ──
+    sentence_rows = ""
+    for i, sd in enumerate(sentence_data):
+        color = TONE_COLORS.get(sd["tone"], "#78909c")
+        pct = sd["score"] * 100
+        sentence_rows += f"""
+        <div class="s-row" style="animation-delay:{i * 0.12}s">
+            <div class="s-num" style="background:{color}">{i + 1}</div>
+            <div class="s-body">
+                <div class="s-text">{sd['text']}</div>
+                <div class="s-meta">
+                    <span class="s-badge" style="background:{color}">{short_label(sd['tone'])}</span>
+                    <div class="bar-bg"><div class="bar-fill" style="width:{pct}%;background:{color}"></div></div>
+                    <span class="s-pct">{sd['score']:.0%}</span>
+                </div>
+            </div>
+        </div>"""
+
+    # ── Radar chart data ──
+    # Prepare all four lenses for a tabbed radar
+    radar_json = json.dumps(
+        {
+            lens: {
+                "labels": [short_label(l) for l in scores.keys()],
+                "values": [round(v * 100, 1) for v in scores.values()],
+            }
+            for lens, scores in passage_scores.items()
+        }
+    )
+
+    html = f"""
+<style>
+/* ── Reset & base ── */
+.mlta *,.mlta *::before,.mlta *::after{{box-sizing:border-box;margin:0;padding:0}}
+.mlta{{
+    font-family:'Segoe UI',system-ui,-apple-system,sans-serif;
+    max-width:920px;margin:0 auto;color:#1a1a2e;
+}}
+
+/* ── Header ── */
+.mlta-header{{
+    text-align:center;padding:24px 16px 16px;
+    border-bottom:2px solid #e8e8f0;margin-bottom:24px;
+}}
+.mlta-header h2{{font-size:1.5em;font-weight:800;
+    background:linear-gradient(135deg,#667eea,#764ba2);
+    -webkit-background-clip:text;-webkit-text-fill-color:transparent;
+    background-clip:text;margin-bottom:4px;
+}}
+.mlta-header p{{color:#888;font-size:0.88em;}}
+
+/* ── Lens cards ── */
+.lens-grid{{display:grid;grid-template-columns:repeat(4,1fr);gap:12px;margin-bottom:28px;}}
+.lens-card{{
+    background:#fff;border:1px solid #e8e8f0;border-radius:14px;
+    padding:18px 12px;text-align:center;
+    transition:transform .2s,box-shadow .2s;
+}}
+.lens-card:hover{{transform:translateY(-3px);box-shadow:0 6px 18px rgba(102,126,234,.12);}}
+.lens-icon{{font-size:1.5em;margin-bottom:6px;}}
+.lens-title{{font-size:.7em;text-transform:uppercase;letter-spacing:1.2px;color:#999;font-weight:700;margin-bottom:6px;}}
+.lens-result{{font-size:1.05em;font-weight:700;color:#16213e;margin-bottom:2px;text-transform:capitalize;}}
+.lens-score{{font-size:.78em;color:#667eea;font-weight:600;}}
+
+/* ── Two-column layout ── */
+.two-col{{display:grid;grid-template-columns:1fr 1fr;gap:24px;margin-bottom:20px;}}
+
+/* ── Radar section ── */
+.radar-sec{{background:#fafafe;border-radius:14px;border:1px solid #e8e8f0;padding:20px;}}
+.radar-sec h3{{font-size:.95em;color:#16213e;margin-bottom:4px;}}
+.radar-tabs{{display:flex;gap:6px;margin-bottom:14px;flex-wrap:wrap;}}
+.radar-tab{{
+    font-size:.72em;padding:4px 10px;border-radius:8px;border:1px solid #ddd;
+    background:#fff;cursor:pointer;font-weight:600;color:#666;
+    transition:all .2s;
+}}
+.radar-tab.active{{background:linear-gradient(135deg,#667eea,#764ba2);color:#fff;border-color:transparent;}}
+.radar-canvas-wrap{{position:relative;width:100%;aspect-ratio:1;}}
+.radar-canvas-wrap canvas{{position:absolute;top:0;left:0;width:100%!important;height:100%!important;}}
+
+/* ── Sentence section ── */
+.sent-sec{{background:#fafafe;border-radius:14px;border:1px solid #e8e8f0;padding:20px;overflow-y:auto;max-height:420px;}}
+.sent-sec h3{{font-size:.95em;color:#16213e;margin-bottom:14px;}}
+.s-row{{
+    display:flex;gap:10px;padding:10px 0;border-bottom:1px solid #f0f0f5;
+    opacity:0;animation:fadeIn .45s ease forwards;
+}}
+.s-row:last-child{{border-bottom:none;}}
+@keyframes fadeIn{{from{{opacity:0;transform:translateX(-8px)}}to{{opacity:1;transform:translateX(0)}}}}
+.s-num{{
+    width:26px;height:26px;border-radius:50%;color:#fff;
+    display:flex;align-items:center;justify-content:center;
+    font-size:.72em;font-weight:700;flex-shrink:0;margin-top:2px;
+}}
+.s-body{{flex:1;min-width:0;}}
+.s-text{{font-size:.83em;line-height:1.45;color:#333;margin-bottom:5px;}}
+.s-meta{{display:flex;align-items:center;gap:8px;}}
+.s-badge{{font-size:.68em;color:#fff;padding:2px 9px;border-radius:10px;font-weight:600;white-space:nowrap;text-transform:capitalize;}}
+.bar-bg{{flex:1;height:4px;background:#e8e8f0;border-radius:2px;overflow:hidden;}}
+.bar-fill{{height:100%;border-radius:2px;transition:width .7s ease;}}
+.s-pct{{font-size:.73em;color:#999;font-weight:600;min-width:32px;text-align:right;}}
+
+/* ── Footer note ── */
+.mlta-foot{{
+    text-align:center;font-size:.76em;color:#aaa;
+    padding:16px 0 4px;border-top:1px solid #e8e8f0;margin-top:20px;line-height:1.6;
+}}
+.mlta-foot code{{background:#f0f0f5;padding:1px 6px;border-radius:4px;font-size:.95em;}}
+
+/* ── Responsive ── */
+@media(max-width:720px){{
+    .lens-grid{{grid-template-columns:repeat(2,1fr);}}
+    .two-col{{grid-template-columns:1fr;}}
+}}
+</style>
+
+<div class="mlta">
+    <div class="mlta-header">
+        <h2>Passage Analysis Dashboard</h2>
+        <p>Four analytical lenses — one zero-shot model — no task-specific training</p>
+    </div>
+
+    <div class="lens-grid">{cards}</div>
+
+    <div class="two-col">
+        <div class="radar-sec">
+            <h3>Passage Profile</h3>
+            <div class="radar-tabs" id="radar-tabs"></div>
+            <div class="radar-canvas-wrap"><canvas id="radarChart"></canvas></div>
+        </div>
+        <div class="sent-sec">
+            <h3>Sentence-by-Sentence Tone</h3>
+            {sentence_rows}
+        </div>
+    </div>
+
+    <div class="mlta-foot">
+        Powered by the same model as the Silly Phrase Finder:
+        <code>valhalla/distilbart-mnli-12-3</code><br>
+        Nobody trained it on tone, formality, energy, or genre.
+        It figures it out from language alone.
+    </div>
+</div>
+
+<script src="https://cdnjs.cloudflare.com/ajax/libs/Chart.js/4.4.1/chart.umd.min.js"></script>
+<script>
+(function(){{
+    const R={radar_json};
+    const lenses=Object.keys(R);
+    const colors=[
+        ['rgba(102,126,234,0.75)','rgba(102,126,234,0.08)'],
+        ['rgba(118,75,162,0.75)','rgba(118,75,162,0.08)'],
+        ['rgba(233,30,99,0.75)','rgba(233,30,99,0.08)'],
+        ['rgba(0,188,212,0.75)','rgba(0,188,212,0.08)'],
+    ];
+    const tabsEl=document.getElementById('radar-tabs');
+    const ctx=document.getElementById('radarChart');
+    if(!ctx||!tabsEl) return;
+
+    let chart=null;
+    function render(idx){{
+        const d=R[lenses[idx]];
+        if(chart) chart.destroy();
+        chart=new Chart(ctx,{{
+            type:'radar',
+            data:{{
+                labels:d.labels.map(l=>l.charAt(0).toUpperCase()+l.slice(1)),
+                datasets:[{{
+                    label:lenses[idx],
+                    data:d.values,
+                    borderColor:colors[idx][0],
+                    backgroundColor:colors[idx][1],
+                    borderWidth:2.5,
+                    pointBackgroundColor:colors[idx][0],
+                    pointRadius:4,
+                    pointHoverRadius:6,
+                }}]
+            }},
+            options:{{
+                responsive:true,maintainAspectRatio:true,
+                plugins:{{legend:{{display:false}}}},
+                scales:{{r:{{
+                    beginAtZero:true,max:100,
+                    ticks:{{stepSize:25,font:{{size:9}},backdropColor:'transparent'}},
+                    pointLabels:{{font:{{size:10,weight:'600'}},color:'#555'}},
+                    grid:{{color:'rgba(0,0,0,0.05)'}},
+                    angleLines:{{color:'rgba(0,0,0,0.05)'}},
+                }}}},
+                animation:{{duration:800,easing:'easeOutQuart'}},
+            }}
+        }});
+        document.querySelectorAll('.radar-tab').forEach((t,i)=>{{
+            t.classList.toggle('active',i===idx);
+        }});
+    }}
+
+    lenses.forEach((name,i)=>{{
+        const btn=document.createElement('span');
+        btn.textContent=name;
+        btn.className='radar-tab'+(i===0?' active':'');
+        btn.onclick=()=>render(i);
+        tabsEl.appendChild(btn);
+    }});
+    render(0);
+}})();
+</script>
+"""
+    return html
+
+
+# ── Example passages ──
+EXAMPLES = [
+    [
+        "The old house stood at the end of the lane, its windows dark as closed eyes. "
+        "Nobody had lived there since the winter of 1987, when Mrs. Bellweather vanished "
+        "during the first snowfall. Children crossed the street to avoid it. Dogs pulled "
+        "at their leashes. Even the mailman, who feared nothing, left packages at the gate "
+        "and walked briskly away. But tonight, for the first time in decades, a light "
+        "flickered behind the upstairs curtain."
+    ],
+    [
+        "The committee has reviewed the quarterly earnings and finds them satisfactory. "
+        "Revenue increased by twelve percent over the previous quarter. However, operating "
+        "costs in the Northeast division remain above target. We recommend a full audit of "
+        "vendor contracts before the next fiscal year. The board will convene on Tuesday to "
+        "discuss the findings."
+    ],
+    [
+        "She laughed so hard the milk came out of her nose, which made everyone else laugh "
+        "even harder. Uncle Roberto tried to keep a straight face but lost it when the dog "
+        "jumped onto the table and stole an entire chicken leg. Grandma just shook her head "
+        "and muttered something about heathens. It was, by all accounts, a perfectly normal "
+        "Sunday dinner."
+    ],
+]
+
+# ── Gradio app ──
+with gr.Blocks(
+    title="Multi-Lens Text Analyzer",
+    theme=gr.themes.Soft(),
+    css="""
+    .gradio-container { max-width: 980px !important; }
+    #go-btn {
+        background: linear-gradient(135deg, #667eea, #764ba2) !important;
+        color: white !important;
+        font-weight: 600 !important;
+        font-size: 1.05em !important;
+        min-height: 44px !important;
+    }
+    """,
+) as demo:
+
+    gr.Markdown(
+        "## Multi-Lens Text Analyzer\n"
+        "Paste any passage and watch a single zero-shot model analyze it through "
+        "four different lenses — tone, formality, energy, and genre feel.\n\n"
+        "*Uses the same model and the same approach as the Silly Phrase Finder — "
+        "just with a richer interface and more ambitious questions.*"
+    )
+
+    with gr.Row():
+        text_input = gr.Textbox(
+            lines=5,
+            placeholder="Paste a paragraph or passage here…",
+            label="Your Passage",
+            scale=5,
+        )
+        analyze_btn = gr.Button(
+            "Analyze ✦", elem_id="go-btn", scale=1, size="lg"
+        )
+
+    output_html = gr.HTML(label="Analysis Dashboard")
+
+    gr.Examples(examples=EXAMPLES, inputs=text_input, label="Try a Passage")
+
+    analyze_btn.click(
+        fn=analyze_passage, inputs=text_input, outputs=output_html
+    )
+    text_input.submit(
+        fn=analyze_passage, inputs=text_input, outputs=output_html
+    )
+
+demo.launch()

requirements.txt

@@ -0,0 +1,3 @@
+transformers
+torch
+gradio