Update app.py

app.py

@@ -48,432 +48,105 @@ CRISIS_NUMBERS = {
     "Other / Not listed": "Call your local emergency number (**112/911**) or search “suicide crisis hotline” + your country.",
 }
 
-# --- Rich suggestion bank (multiple varied tips per emotion) ---
-SUGGESTION_BANK = {
+# --- Deep, varied emotional advice & comfort phrases ---
+SUGGESTIONS = {
     "sadness": [
-        "Give yourself permission to cry for 5 minutes, then drink a glass of water or take a warm shower.",
-        "Write a brief self-compassion note as if to a close friend.",
-        "Micro-walk: 10 minutes outside (or by a window), noticing three colors.",
-        "Make a ‘just today’ list of one or two tiny doable items.",
-        "Play a gentle song and place a hand over your heart for 60 seconds.",
+        "Be gentle with yourself. Cry if you need to — that’s healing, not weakness.",
+        "Let yourself rest. You don’t have to be productive while your heart is heavy.",
+        "Hold a pillow or blanket close and breathe slowly.",
+        "Talk to someone who feels safe, or write down what you wish someone would say to you.",
+        "It’s okay if today you just get through the day.",
+        "Take a warm shower, drink water, and do one small thing that feels kind.",
+        "Remember: sadness is a visitor, not your home.",
+        "Even quiet tears are a form of strength — you’re still here.",
     ],
     "fear": [
-        "Do 4-7-8 breathing (inhale 4s, hold 7s, exhale 8s) for four cycles.",
-        "Gentle exposure: take a 2-minute step toward the thing that worries you.",
-        "Reframe: ‘What if this went better than expected?’ List two positive outcomes.",
-        "Grounding 5-4-3-2-1 (five things you see … down to one taste).",
-        "If-then plan: ‘If anxiety rises, then I rest one hand on my belly and breathe for 30s.’",
+        "Ground yourself with slow breathing — feel your feet on the floor.",
+        "You are safe in this moment. Focus on what is real right now.",
+        "Courage isn’t about not being afraid; it’s choosing to keep going anyway.",
+        "Remind yourself: not every thought is a fact.",
+        "Small steps are still progress — you don’t need to have the whole plan.",
+        "Try saying out loud: ‘I can handle this one moment at a time.’",
+        "Place a hand on your chest and whisper, ‘I am safe. I am present.’",
+        "Fear often shows up before growth — maybe something new is calling.",
     ],
     "joy": [
-        "Savor it: describe three pleasant details (sounds, smells, sensations).",
-        "Share your joy: send a one-sentence message to someone.",
-        "Make a memory: jot a quick note—what made this good?",
-        "Amplify with the body: gentle stretches, deliberate smile, shoulders back for 20s.",
-        "Create a tiny ‘capsule’ of the moment (photo or one-line journal).",
+        "Savor this — your body deserves to feel good.",
+        "Let the joy sink in; you don’t have to rush to the next thing.",
+        "Share your happiness with someone — even a smile counts.",
+        "Write down what’s bringing you joy today. It strengthens the memory.",
+        "Take a deep breath and feel gratitude for this small light moment.",
+        "Joy can be quiet — a cup of tea, a laugh, a calm pause.",
+        "Smile for no reason; your brain will thank you later.",
+        "Notice how joy feels in your body, and let yourself stay there for a while.",
     ],
     "anger": [
-        "Healthy discharge: 20 squats or 15 wall push-ups.",
-        "STOP pause: Stop • Take a breath • Observe • Proceed mindfully.",
-        "Name it precisely: ‘I’m angry because boundary X was crossed.’",
-        "Repair plan: draft one assertive sentence (I-feel + need + request).",
-        "Two-minute brain dump of everything irritating you, then shred the page.",
+        "Pause and breathe — you don’t have to react right away.",
+        "Anger can mean something important needs attention — listen kindly.",
+        "Take a walk or shake out the tension before speaking.",
+        "Write everything you want to say, then decide what actually needs saying.",
+        "It’s okay to be angry — what matters is what you do with it.",
+        "Drink water and give your body a few minutes to settle.",
+        "Sometimes the kindest thing is to wait before responding.",
+        "Ask yourself: ‘What boundary of mine needs care right now?’",
     ],
     "boredom": [
-        "Five-minute rule: set a timer and just start for 5 minutes.",
-        "Mini-novelty: watch a short intro on a new topic and note one idea.",
-        "Habit stack: pair a useful task with music/a podcast.",
-        "Change the environment: different room, lighting, open a window.",
-        "Micro-challenge: tidy or sort 20 items, then stop.",
+        "Boredom can be a doorway — something in you wants to wake up.",
+        "Try something completely small and new: a song, a stretch, a random fact.",
+        "Put on music and tidy for 5 minutes — movement often sparks motivation.",
+        "Write a list of ‘tiny adventures’ you could do today.",
+        "Sometimes doing nothing is what your mind needs — rest counts.",
+        "Look outside for a moment — notice one color or sound you hadn’t before.",
+        "Ask yourself: ‘What might make me curious right now?’",
+        "Do one creative thing without judging it — draw, hum, doodle, move.",
     ],
     "grief": [
-        "Ritual: light a candle, name one memory, breathe for a minute.",
-        "Write what you’d say to the person/thing you’re missing.",
-        "Allow the waves: remind yourself grief comes and goes.",
-        "Contact one trusted person and share a memory.",
-        "Care for the body: water, simple food, a 10-minute walk.",
+        "Grief is love that has nowhere to go — let it speak softly through you.",
+        "You’re allowed to miss them and still keep living.",
+        "Light a candle, whisper their name, and breathe.",
+        "Eat something, drink water — caring for your body honors their memory too.",
+        "It’s okay to cry about the same thing more than once.",
+        "Talk about your loss. The pain lessens when it’s witnessed.",
+        "Hold an item that reminds you of love, not loss.",
+        "Healing doesn’t mean forgetting; it means remembering with more peace.",
     ],
     "love": [
-        "Express it with a short sincere message.",
-        "Concrete gesture: a small note or post-it of appreciation.",
-        "Presence: 10 minutes screen-free with the person (or with yourself).",
-        "Positive recall: reread a message/photo and list what you appreciate.",
-        "Care gesture: prepare something simple for yourself/someone else.",
+        "Tell someone you care about them — even in a small text.",
+        "Give love back to yourself: you deserve your own gentleness.",
+        "Love is quiet presence — you don’t have to prove it.",
+        "A small act of kindness can brighten two days at once.",
+        "You are loved simply for being, not for doing.",
+        "Love often grows in silence and simple gestures.",
+        "Send out a silent thank-you to those who care for you.",
+        "Let yourself receive love — it’s not selfish to need warmth.",
     ],
     "nervousness": [
-        "Coherent breathing at ~6 breaths/minute for 60–90 seconds.",
-        "Quick body scan: unclench jaw, drop shoulders.",
-        "Object anchor: hold a cool/grippy object and describe it for 30s.",
-        "Helpful question: ‘What do I need right now?’ Choose one tiny action.",
-        "Neck stretch and wrist circles for 30s.",
+        "Breathe slower than your worry — your body will follow your rhythm.",
+        "Relax your jaw, drop your shoulders, exhale longer than you inhale.",
+        "You don’t have to fix every thought; let them pass like clouds.",
+        "Try naming five things you can see right now.",
+        "Anxiety is a false alarm — you can remind your brain you’re safe.",
+        "Put both feet flat on the floor and press gently to ground yourself.",
+        "Write down what worries you, then cross out what you can’t control.",
+        "You can pause; you’re not behind. Safety starts with one breath.",
     ],
     "curiosity": [
-        "Form one specific question and look up exactly one reliable answer.",
-        "Rapid prototype: try a 10-minute micro-test.",
-        "Note three things you learned and one next question.",
-        "Explain the idea out loud as if to a child.",
-        "Add a playful constraint (e.g., $10 / 10 minutes).",
+        "Follow the spark — it doesn’t have to make sense yet.",
+        "Ask the question that feels exciting, not the one that feels safe.",
+        "Let yourself explore something simply because it’s interesting.",
+        "Learning is self-care too — wonder is nourishment.",
+        "Take 10 minutes to google something random you love.",
+        "Curiosity is courage in disguise — let it lead.",
+        "Even small discoveries can wake up your energy.",
+        "Be a beginner; it’s a powerful place to start.",
     ],
     "gratitude": [
-        "Three gratitudes: one for you, one for someone, one for the world.",
-        "Active thanks: send a quick thank-you message.",
-        "Sensory gratitude: three pleasant sensations here-and-now.",
-        "Future gratitude: ‘Tomorrow I’ll be thankful for…’",
-        "Snap a photo-gratitude and add a one-line caption.",
-    ],
-    "neutral": [
-        "60-second pause: slow nasal breathing + relax shoulders.",
-        "Environment tune-up: water, light, posture, fresh air.",
-        "Pick one two-minute task (dish, email, tidy spot).",
-        "Five-minute mindful walk, paying attention to footsteps.",
-        "One-minute stretch: back, neck, wrists.",
-    ],
-}
-
-# Short quotes (optional spice)
-QUOTE_BANK = {
-    "sadness": ["“This will pass too.”", "“One step at a time.”"],
-    "fear": ["“Courage is a habit.”", "“Breathe. You can.”"],
-    "joy": ["“Savor it.”", "“Keep a note of this moment.”"],
-    "anger": ["“Clarity is a kind of kindness.”", "“Pause before speaking.”"],
-    "boredom": ["“Action creates motivation.”", "“Start small.”"],
-    "grief": ["“Love continues in other forms.”", "“Honor what was.”"],
-    "love": ["“Thank you builds connection.”", "“Presence is love.”"],
-    "nervousness": ["“Let the body lead the mind.”", "“One breath at a time.”"],
-    "curiosity": ["“Test to learn.”", "“Question → tiny action.”"],
-    "gratitude": ["“What you water grows.”", "“See the simple.”"],
-    "neutral": ["“Return to the body.”", "“Gentle consistency.”"],
-}
-
-COLOR_MAP = {
-    "joy": "#FFF9C4", "love": "#F8BBD0", "gratitude": "#FFF176",
-    "sadness": "#BBDEFB", "grief": "#B3E5FC",
-    "fear": "#E1BEE7", "nervousness": "#E1BEE7",
-    "anger": "#FFCCBC", "boredom": "#E0E0E0",
-    "neutral": "#F5F5F5",
-}
-
-# Map GoEmotions label -> your UI buckets
-GOEMO_TO_APP = {
-    "admiration": "gratitude",
-    "amusement": "joy",
-    "anger": "anger",
-    "annoyance": "anger",
-    "approval": "gratitude",
-    "caring": "love",
-    "confusion": "nervousness",
-    "curiosity": "curiosity",
-    "desire": "joy",
-    "disappointment": "sadness",
-    "disapproval": "anger",
-    "disgust": "anger",
-    "embarrassment": "nervousness",
-    "excitement": "joy",
-    "fear": "fear",
-    "gratitude": "gratitude",
-    "grief": "grief",
-    "joy": "joy",
-    "love": "love",
-    "nervousness": "nervousness",
-    "optimism": "joy",
-    "pride": "joy",
-    "realization": "neutral",
-    "relief": "gratitude",
-    "remorse": "grief",
-    "sadness": "sadness",
-    "surprise": "neutral",
-    "neutral": "neutral",
-}
-
-THRESHOLD = 0.30  # probability threshold for selecting labels
-
-# ---------------- SQLite helpers ----------------
-def get_conn():
-    return sqlite3.connect(DB_PATH, check_same_thread=False, timeout=10)
-
-def init_db():
-    conn = None
-    try:
-        conn = get_conn()
-        c = conn.cursor()
-        c.execute("""
-        CREATE TABLE IF NOT EXISTS sessions(
-            id INTEGER PRIMARY KEY AUTOINCREMENT,
-            ts TEXT,
-            country TEXT,
-            user_text TEXT,
-            main_emotion TEXT
-        )
-        """)
-        conn.commit()
-    finally:
-        try:
-            if conn: conn.close()
-        except Exception:
-            pass
-
-def log_session(country, msg, emotion):
-    conn = None
-    try:
-        conn = get_conn()
-        c = conn.cursor()
-        c.execute(
-            "INSERT INTO sessions(ts, country, user_text, main_emotion) VALUES(?,?,?,?)",
-            (datetime.utcnow().isoformat(timespec="seconds"), country, msg[:500], emotion),
-        )
-        conn.commit()
-    finally:
-        try:
-            if conn: conn.close()
-        except Exception:
-            pass
-
-# ---------------- Train / Load model from DATASET ONLY ----------------
-def load_goemotions_dataset():
-    # "simplified" gives 'text' and 'labels' as list[int] indices
-    ds = load_dataset("google-research-datasets/go_emotions", "simplified")
-    label_names = ds["train"].features["labels"].feature.names
-    return ds, label_names
-
-def _prepare_xy(split):
-    # Each example has text and labels (list of ints)
-    X = split["text"]
-    y = split["labels"]  # list[list[int]]
-    return X, y
-
-def train_or_load_model():
-    # Try cache first
-    if os.path.isfile(MODEL_PATH):
-        print("[MM] Loading cached classifier...")
-        bundle = joblib.load(MODEL_PATH)
-        if bundle.get("version") == MODEL_VERSION:
-            return bundle["pipeline"], bundle["mlb"], bundle["label_names"]
-        else:
-            print("[MM] Cached model version mismatch; retraining...")
-
-    print("[MM] Loading GoEmotions dataset...")
-    ds, label_names = load_goemotions_dataset()
-
-    print("[MM] Preparing data...")
-    X_train, y_train_idx = _prepare_xy(ds["train"])
-    X_val, y_val_idx = _prepare_xy(ds["validation"])
-
-    # MultiLabelBinarizer to convert list[int] -> multi-hot
-    mlb = MultiLabelBinarizer(classes=list(range(len(label_names))))
-    Y_train = mlb.fit_transform(y_train_idx)
-    Y_val   = mlb.transform(y_val_idx)
-
-    # Build pipeline
-    # - TfidfVectorizer with simple English settings
-    # - LogisticRegression (saga) in One-vs-Rest for multi-label probabilities
-    clf = Pipeline(steps=[
-        ("tfidf", TfidfVectorizer(
-            lowercase=True,
-            ngram_range=(1,2),
-            min_df=2,
-            max_df=0.9,
-            strip_accents="unicode",
-        )),
-        ("ovr", OneVsRestClassifier(
-            LogisticRegression(
-                solver="saga",
-                max_iter=1000,
-                n_jobs=-1,
-                class_weight="balanced",
-            ),
-            n_jobs=-1
-        ))
-    ])
-
-    print("[MM] Training classifier (this happens once; cached afterward)...")
-    clf.fit(X_train, Y_train)
-
-    # Quick validation metric (macro F1 over labels present in val)
-    Y_val_pred = clf.predict(X_val)
-    macro_f1 = f1_score(Y_val, Y_val_pred, average="macro", zero_division=0)
-    print(f"[MM] Validation macro F1: {macro_f1:.3f}")
-
-    # Cache model
-    joblib.dump({
-        "version": MODEL_VERSION,
-        "pipeline": clf,
-        "mlb": mlb,
-        "label_names": label_names
-    }, MODEL_PATH)
-    print(f"[MM] Saved classifier to {MODEL_PATH}")
-
-    return clf, mlb, label_names
-
-# Train/load at startup
-try:
-    CLASSIFIER, MLB, LABEL_NAMES = train_or_load_model()
-except Exception as e:
-    print(f"[WARN] Failed to train/load classifier: {e}")
-    CLASSIFIER, MLB, LABEL_NAMES = None, None, None
-
-# ---------------- Inference using ONLY the trained classifier ----------------
-def classify_text(text: str):
-    """
-    Returns list of (label_name, prob) for labels above THRESHOLD, sorted desc.
-    """
-    if not CLASSIFIER or not MLB or not LABEL_NAMES:
-        return []
-
-    # predict_proba returns array shape (1, n_labels)
-    try:
-        proba = CLASSIFIER.predict_proba([text])[0]
-    except AttributeError:
-        # If estimator doesn't support predict_proba (shouldn't happen with LR),
-        # fall back to decision_function -> sigmoid
-        from scipy.special import expit
-        scores = CLASSIFIER.decision_function([text])[0]
-        proba = expit(scores)
-
-    idxs = [i for i, p in enumerate(proba) if p >= THRESHOLD]
-    # Sort by probability desc
-    idxs.sort(key=lambda i: proba[i], reverse=True)
-    return [(LABEL_NAMES[i], float(proba[i])) for i in idxs]
-
-def detect_emotions(text: str):
-    chosen = classify_text(text)
-    if not chosen:
-        return [], "neutral"
-    # Map to app buckets and take the strongest
-    bucket = {}
-    for label, p in chosen:
-        app = GOEMO_TO_APP.get(label.lower(), "neutral")
-        bucket[app] = max(bucket.get(app, 0.0), p)
-    main = max(bucket, key=bucket.get) if bucket else "neutral"
-    return chosen, main
-
-# ---------------- Response composer (new) ----------------
-def compose_support(main_emotion: str, detected: list, is_first_msg: bool) -> str:
-    """Build a varied reply: 2 tips + 1 reflective question + optional mini-quote."""
-    tips = SUGGESTION_BANK.get(main_emotion, SUGGESTION_BANK["neutral"])
-    tips = random.sample(tips, k=min(2, len(tips)))  # two distinct tips
-
-    question_bank = {
-        "sadness": "What would benefit from a bit of care or softness right now?",
-        "fear": "What would you tell a friend in the same situation?",
-        "joy": "How could you keep a tiny trace of this moment for later?",
-        "anger": "What boundary do you want to set calmly, and with whom?",
-        "boredom": "What two-minute micro-task would move your day forward?",
-        "grief": "What memory would you like to honor today?",
-        "love": "What small expression of care could you offer (or offer yourself) now?",
-        "nervousness": "What would help your body feel 5% safer?",
-        "curiosity": "What’s the first specific question you want to explore?",
-        "gratitude": "Who/what deserves a concrete thank-you today?",
-        "neutral": "What small, simple thing could you do right away?",
-    }
-    q = question_bank.get(main_emotion, question_bank["neutral"])
-
-    # 30% chance to add a mini quote
-    quote = ""
-    if random.random() < 0.30:
-        quote_choices = QUOTE_BANK.get(main_emotion, QUOTE_BANK["neutral"])
-        quote = f"\n\n💬 {random.choice(quote_choices)}"
-
-    # Detected emotions summary (top 3)
-    summary = ""
-    if detected:
-        top = ", ".join([f"{lbl} ({p:.2f})" for lbl, p in detected[:3]])
-        summary = f"\n\nDetected: {top}"
-
-    # Contextual intro on first message
-    intro = "Thanks for sharing. 🫶 " if is_first_msg else ""
-
-    return (
-        f"{intro}• {tips[0]}\n"
-        f"• {tips[1]}\n\n"
-        f"🤔 {q}{quote}{summary}"
-    )
-
-# ---------------- Chat logic (updated) ----------------
-def crisis_block(country):
-    msg = CRISIS_NUMBERS.get(country, CRISIS_NUMBERS["Other / Not listed"])
-    return (
-        "💛 I'm really sorry you're feeling like this. You matter.\n\n"
-        f"**If you might be in danger or thinking about harming yourself:**\n{msg}\n\n"
-        "Please reach out to someone now. You are not alone."
-    )
-
-def chat_step(message, history, country, save_session):
-    if CRISIS_RE.search(message):
-        return crisis_block(country), "#FFD6E7"
-
-    if CLOSING_RE.search(message):
-        return ("Thank you 💛 Take care of yourself. Small steps matter. 🌿", "#FFFFFF")
-
-    recent = " ".join(message.split()[-100:])
-    detected, main = detect_emotions(recent)
-    color = COLOR_MAP.get(main, "#FFFFFF")
-
-    if save_session:
-        log_session(country, message, main)
-
-    # Build a richer reply using the composer
-    reply = compose_support(main, detected, is_first_msg=not bool(history))
-
-    return reply, color
-
-# ---------------- Gradio UI ----------------
-init_db()
-
-custom_css = """
-:root, body, .gradio-container { transition: background-color 0.8s ease !important; }
-.typing { font-style: italic; opacity: 0.8; animation: blink 1s infinite; }
-@keyframes blink { 50% {opacity: 0.4;} }
-"""
-
-with gr.Blocks(css=custom_css, title="🪞 MoodMirror+ (Dataset-only Edition)") as demo:
-    style_injector = gr.HTML("")
-    gr.Markdown(
-        "### 🪞 MoodMirror+ — Emotional Support & Inspiration 🌸\n"
-        "Powered only by the **GoEmotions dataset** (trained locally on startup).\n\n"
-        "_Not medical advice. If you feel unsafe, please reach out for help immediately._"
-    )
-
-    with gr.Row():
-        country = gr.Dropdown(choices=list(CRISIS_NUMBERS.keys()), value="Other / Not listed", label="Country")
-        save_ok = gr.Checkbox(value=False, label="Save anonymized session (no personal data)")
-
-    chat = gr.Chatbot(height=360)
-    msg = gr.Textbox(placeholder="Type how you feel...", label="Your message")
-    send = gr.Button("Send")
-    typing = gr.Markdown("", elem_classes="typing")
-
-    # Optional: dataset sample preview (for transparency)
-    with gr.Accordion("🔎 Preview GoEmotions samples", open=False):
-        with gr.Row():
-            n_examples = gr.Slider(1, 10, value=5, step=1, label="Number of examples")
-            split = gr.Dropdown(["train", "validation", "test"], value="train", label="Split")
-            refresh = gr.Button("Show samples")
-        table = gr.Dataframe(headers=["text", "labels"], row_count=5, wrap=True)
-
-        def refresh_samples(n, split_name):
-            try:
-                ds = load_dataset("google-research-datasets/go_emotions", "simplified")
-                names = ds["train"].features["labels"].feature.names
-                rows = ds[split_name].shuffle(seed=42).select(range(min(int(n), len(ds[split_name]))))
-                return [[t, ", ".join([names[i] for i in labs])] for t, labs in zip(rows["text"], rows["labels"])]
-            except Exception as e:
-                return [[f"Dataset load error: {e}", ""]]
-
-        refresh.click(refresh_samples, inputs=[n_examples, split], outputs=[table])
-
-    def respond(user_msg, chat_hist, country_choice, save_flag):
-        if not user_msg or not user_msg.strip():
-            yield chat_hist + [[user_msg, "Please share a short sentence about how you feel 🙂"]], "", "", ""
-            return
-        yield chat_hist, "💭 MoodMirror is thinking...", "", ""
-        reply, color = chat_step(user_msg, chat_hist, country_choice, bool(save_flag))
-        style_tag = f"<style>:root,body,.gradio-container{{background:{color}!important;}}</style>"
-        yield chat_hist + [[user_msg, reply]], "", style_tag, ""
-
-    send.click(respond, inputs=[msg, chat, country, save_ok],
-               outputs=[chat, typing, style_injector, msg], queue=True)
-    msg.submit(respond, inputs=[msg, chat, country, save_ok],
-               outputs=[chat, typing, style_injector, msg], queue=True)
-
-if __name__ == "__main__":
-    demo.queue()
-    demo.launch()
+        "Name three things you’re grateful for — big or tiny.",
+        "Gratitude turns ordinary moments into something sacred.",
+        "Say ‘thank you’ — out loud, even if just to yourself.",
+        "Look around and notice something that quietly supports you.",
+        "Each breath is a gift you didn’t have to earn.",
+        "Gratitude softens fear; it reminds you what’s still good.",
+        "Send a short thank-you message to someone right now.",
+        "Appreciate how far you’ve already come — quietly, just for you.",
+    ]