Upload app.py

app.py

@@ -1,6 +1,7 @@
 import os
 import re
 import json
+import random
 from typing import Dict, Any, List, Optional
 
 import gradio as gr
@@ -8,8 +9,9 @@ from huggingface_hub import InferenceClient
 
 # ────────────────────────────────────────────────────────────────────────────────
 # CONFIG
+
 MODEL_ID = os.environ.get("MODEL_ID", "meta-llama/Meta-Llama-3.1-8B-Instruct")
-HF_TOKEN = os.environ.get("HF_TOKEN")  # set in Space settings → Repository secrets
+HF_TOKEN = os.environ.get("HF_TOKEN")  # set as repo secret if model needs auth
 
 CATEGORIES = [
     {"key": "alimentation", "icon": "🍎", "fr": "Alimentation", "en": "Nutrition"},
@@ -36,7 +38,7 @@ GUIDES = {
     },
 }
 
-# Few-shot examples: now 4 questions each
+# Few-shot examples for style + fallback
 FEWSHOTS = {
     "fr": {
         "alimentation": {
@@ -45,10 +47,14 @@ FEWSHOTS = {
                 "Quel ajout simple rend ton petit-déj plus rassasiant ?",
                 "Quand as-tu naturellement faim d’un fruit ou d’un yaourt ?",
                 "Quelle petite habitude t’aide à ne pas sauter de repas ?",
+                "Quel plat simple te fait du bien après une journée chargée ?",
+                "Quelle collation t’aide à tenir jusqu’au dîner sans avoir trop faim ?",
             ],
             "micro_actions": [
                 "Remplir une gourde ce matin.",
                 "Ajouter un fruit à la collation de l’après-midi.",
+                "Remplacer une boisson sucrée par un verre d’eau aujourd’hui.",
+                "Préparer un snack simple pour demain.",
             ],
         },
         "mouvement": {
@@ -57,10 +63,14 @@ FEWSHOTS = {
                 "Quelle pause-active de 2 minutes peux-tu glisser entre deux tâches ?",
                 "Qu’est-ce qui te fait bouger sans y penser (ex: marcher au téléphone) ?",
                 "Quel moment conviendrait pour quelques étirements doux chaque jour ?",
+                "Avec qui aimerais-tu partager une courte marche ?",
+                "Quel geste te réveille le matin (étirement, marche, danse exprès…) ?",
             ],
             "micro_actions": [
                 "Monter un étage par les escaliers aujourd’hui.",
                 "Faire 5 étirements doux après le café.",
+                "Se lever pendant un appel et marcher quelques pas.",
+                "Programmer une mini-alarme « bouger » dans l’après-midi.",
             ],
         },
         "cerveau": {
@@ -69,10 +79,14 @@ FEWSHOTS = {
                 "Quel moment t’irait pour 3 minutes de respiration ?",
                 "Quel mini-jeu aimes-tu pour réveiller l’esprit (ex: 3 mots fléchés) ?",
                 "Quel petit sujet aimerais-tu explorer cette semaine ?",
+                "Quelle activité calme t’aide à passer du travail au repos ?",
+                "Quel souvenir récent t’a fait sourire en y repensant ?",
             ],
             "micro_actions": [
                 "Programmer un minuteur de 3 minutes pour respirer.",
                 "Lire un paragraphe d’un sujet nouveau ce soir.",
+                "Faire un mini-jeu de cerveau (3 mots fléchés, Sudoku, etc.).",
+                "Noter une idée ou question qui t’intrigue.",
             ],
         },
         "liens": {
@@ -81,10 +95,14 @@ FEWSHOTS = {
                 "À qui enverrais-tu un message court pour reprendre contact ?",
                 "Avec qui partagerais-tu une courte marche cette semaine ?",
                 "Avec qui aimerais-tu avoir une vraie conversation bientôt ?",
+                "Quand t’es-tu senti·e soutenu·e pour la dernière fois, et par qui ?",
+                "Qui aimerais-tu encourager cette semaine ?",
             ],
             "micro_actions": [
                 "Envoyer un message de gratitude à une personne.",
                 "Proposer une pause-café de 10 minutes.",
+                "Envoyer une photo ou un souvenir à quelqu’un avec un petit mot.",
+                "Poser une vraie question à quelqu’un sur sa journée.",
             ],
         },
         "bien-etre": {
@@ -93,10 +111,14 @@ FEWSHOTS = {
                 "Quelle routine de 2 minutes t’aide à te recentrer ?",
                 "Quel moment favorise un coucher plus régulier ?",
                 "Qu’est-ce qui t’aide à te sentir plus léger·e en fin de journée ?",
+                "Quel endroit de ton quotidien te donne une sensation de calme ?",
+                "Quand as-tu l’impression de vraiment respirer ?",
             ],
             "micro_actions": [
                 "Éteindre les écrans 10 minutes plus tôt ce soir.",
                 "Écrire 3 lignes sur ton humeur du jour.",
+                "Prendre 5 respirations lentes avant de changer d’activité.",
+                "Planifier une mini-pause de 5 minutes pour toi demain.",
             ],
         },
     },
@@ -107,10 +129,14 @@ FEWSHOTS = {
                 "What small add-on makes your breakfast more filling?",
                 "When do you naturally crave a fruit or yogurt?",
                 "What tiny habit helps you not skip meals?",
+                "What simple dinner feels gentle after a long day?",
+                "Which snack helps you stay focused without a big energy crash?",
             ],
             "micro_actions": [
                 "Fill a water bottle this morning.",
                 "Add one fruit to your afternoon snack.",
+                "Swap one sugary drink for water today.",
+                "Plan a simple snack for tomorrow.",
             ],
         },
         "mouvement": {
@@ -119,10 +145,14 @@ FEWSHOTS = {
                 "Which 2-minute active break fits between two tasks?",
                 "What makes you move without noticing (e.g., walking on calls)?",
                 "When would a short stretch break feel good each day?",
+                "Where do you naturally end up walking more?",
+                "What small move helps you wake up in the morning?",
             ],
             "micro_actions": [
                 "Take one flight of stairs today.",
                 "Do 5 light stretches after coffee.",
+                "Stand up and walk during one call.",
+                "Set a tiny “move” reminder for this afternoon.",
             ],
         },
         "cerveau": {
@@ -131,10 +161,14 @@ FEWSHOTS = {
                 "When could you do 3 minutes of breathing?",
                 "Which mini-game wakes you up (e.g., 3 crossword clues)?",
                 "What small topic would you like to learn about this week?",
+                "What gentle activity helps you shift from work to rest?",
+                "What recent memory made you smile when you thought of it again?",
             ],
             "micro_actions": [
                 "Set a 3-minute timer to breathe.",
                 "Read one paragraph on a new topic tonight.",
+                "Play a tiny brain game.",
+                "Write down one idea or question that interests you.",
             ],
         },
         "liens": {
@@ -143,10 +177,14 @@ FEWSHOTS = {
                 "Who might you text briefly to reconnect?",
                 "Who could you invite for a short walk this week?",
                 "Who would you like to have a real conversation with soon?",
+                "When did you last feel supported, and by whom?",
+                "Who would you like to encourage this week?",
             ],
             "micro_actions": [
                 "Send a gratitude message to one person.",
                 "Offer a 10-minute coffee break.",
+                "Send a photo or memory to someone with a short note.",
+                "Ask someone one genuine question about their day.",
             ],
         },
         "bien-etre": {
@@ -155,17 +193,21 @@ FEWSHOTS = {
                 "What 2-minute routine helps you reset?",
                 "What time supports a steadier bedtime?",
                 "What helps you feel lighter at the end of the day?",
+                "Which place in your daily life feels calming?",
+                "When do you feel like you can really breathe?",
             ],
             "micro_actions": [
                 "Turn screens off 10 minutes earlier tonight.",
                 "Write three lines about your mood today.",
+                "Take 5 slow breaths before changing tasks.",
+                "Schedule a 5-minute mini-break for yourself tomorrow.",
             ],
         },
     },
 }
 
 # ────────────────────────────────────────────────────────────────────────────────
-# PROMPT & MODEL
+# PROMPT + MODEL HELPERS
 
 
 def build_prompt(lang: str, category_key: str, variant: str) -> str:
@@ -177,18 +219,13 @@ def build_prompt(lang: str, category_key: str, variant: str) -> str:
     guide = GUIDES[lang][category_key]
     few = FEWSHOTS[lang][category_key]
 
-    variant_fr = (
-        "Ton: ludique et original (‘meilleur’)."
-        if variant == "best"
-        else "Ton: introspectif et authentique (‘plus sincère’)."
-    )
-    variant_en = (
-        "Tone: playful and original (‘best’)."
-        if variant == "best"
-        else "Tone: introspective and authentic (‘most sincere’)."
-    )
+    if variant == "best":
+        tone_fr = "ludique, original, léger"
+        tone_en = "playful, original, light"
+    else:
+        tone_fr = "sincère, introspectif, doux"
+        tone_en = "sincere, introspective, gentle"
 
-    # 4 questions now
     schema = (
         "{\n"
         '  "category": "<category_key>",\n'
@@ -196,50 +233,55 @@ def build_prompt(lang: str, category_key: str, variant: str) -> str:
         '  "questions": ["q1", "q2", "q3", "q4"],\n'
         '  "micro_actions": ["m1", "m2"],\n'
         '  "tone": "playful|sincere|ludique|sincère",\n'
-        '  "safety_notes": "short coaching tips"\n'
+        '  "safety_notes": ""\n'
         "}"
     )
 
+    example_questions = few["questions"][:2]
+    example_micro = few["micro_actions"][:2]
+
     if lang == "fr":
-        system = (
-            "Tu es l’IA du jeu de cartes Neurovie, inspiré du modèle FINGER. "
-            "Une carte = une question sur les routines du quotidien."
-        )
-        safety = (
-            "Règles:\n"
-            "- Pas de conseils médicaux ni de diagnostics.\n"
-            "- Langage bienveillant, inclusif, concret.\n"
-            "- Phrases courtes, sans emojis.\n"
-        )
-        user = (
-            f"Catégorie: {cat['fr']} {cat['icon']}. {variant_fr}\n"
-            f"Focus: {guide}\n"
-            "Génère 4 QUESTIONS et 2 MICRO-ACTIONS, chacune en une phrase.\n"
-            f"Exemples de style (ne pas copier mot à mot): questions={few['questions']} micro_actions={few['micro_actions']}\n"
-            f"Schéma JSON strict:\n{schema}\n"
-            "RENVOIE UNIQUEMENT DU JSON VALIDE."
-        )
+        return f"""
+Tu es l’IA du jeu de cartes Neurovie (modèle FINGER).
+Tu crées des cartes-question pour parler de routines du quotidien.
+
+- Catégorie: {cat['fr']} {cat['icon']}.
+- Focus: {guide}
+- Ton: {tone_fr}
+- Forme: 4 questions + 2 micro-actions, 1 phrase courte chacune.
+- Style: concret, bienveillant, sans jugement.
+- Interdit: conseils médicaux, diagnostics, emojis.
+
+Réponds UNIQUEMENT en JSON, sans texte autour, selon ce schéma:
+{schema}
+
+Exemple de style (à VARIER, ne pas copier):
+Questions: {example_questions}
+Micro-actions: {example_micro}
+
+Maintenant, renvoie un NOUVEAU JSON différent de l'exemple.
+""".strip()
     else:
-        system = (
-            "You are the AI for the Neurovie card game, inspired by the FINGER model. "
-            "One card = one question about daily routines."
-        )
-        safety = (
-            "Rules:\n"
-            "- No medical advice or diagnosis.\n"
-            "- Kind, concrete, inclusive language.\n"
-            "- Short sentences, no emojis.\n"
-        )
-        user = (
-            f"Category: {cat['en']} {cat['icon']}. {variant_en}\n"
-            f"Focus: {guide}\n"
-            "Generate 4 QUESTIONS and 2 MICRO-ACTIONS, one sentence each.\n"
-            f"Style examples (do not copy verbatim): questions={few['questions']} micro_actions={few['micro_actions']}\n"
-            f"Strict JSON schema:\n{schema}\n"
-            "RETURN VALID JSON ONLY."
-        )
+        return f"""
+You are the AI for the Neurovie card game (FINGER model).
+You create question-cards about everyday routines.
 
-    return f"{system}\n\n{safety}\n\n{user}"
+- Category: {cat['en']} {cat['icon']}.
+- Focus: {guide}
+- Tone: {tone_en}
+- Format: 4 questions + 2 micro-actions, 1 short sentence each.
+- Style: concrete, kind, non-judgmental.
+- Forbidden: medical advice, diagnoses, emojis.
+
+Reply ONLY with JSON, no extra text, in this shape:
+{schema}
+
+Style example (to vary, do NOT copy):
+Questions: {example_questions}
+Micro-actions: {example_micro}
+
+Now return a NEW JSON different from the example.
+""".strip()
 
 
 def try_parse_json(text: str) -> Optional[Dict[str, Any]]:
@@ -254,52 +296,17 @@ def try_parse_json(text: str) -> Optional[Dict[str, Any]]:
         return None
 
 
-def normalize_output(
-    data: Dict[str, Any], lang: str, category_key: str, variant: str
-) -> Dict[str, Any]:
-    q = [str(x).strip() for x in data.get("questions", []) if str(x).strip()]
-    m = [str(x).strip() for x in data.get("micro_actions", []) if str(x).strip()]
-
-    # exactly 4 questions, 2 micro-actions
-    q = (q + [""] * 4)[:4]
-    m = (m + [""] * 2)[:2]
-
-    if not data.get("tone"):
-        if lang == "fr":
-            tone = "ludique" if variant == "best" else "sincère"
-        else:
-            tone = "playful" if variant == "best" else "sincere"
-    else:
-        tone = str(data["tone"])
-
-    safety_notes = data.get("safety_notes")
-    if not safety_notes:
-        safety_notes = (
-            "Reste bienveillant·e, évite les conseils médicaux."
-            if lang == "fr"
-            else "Be kind, avoid medical advice."
-        )
-
-    return {
-        "category": category_key,
-        "language": lang,
-        "questions": q,
-        "micro_actions": m,
-        "tone": tone,
-        "safety_notes": safety_notes,
-    }
-
-
 def model_call(prompt: str) -> str:
     client = InferenceClient(model=MODEL_ID, token=HF_TOKEN)
 
+    # Try chat-style first
     try:
         resp = client.chat.completions.create(
             model=MODEL_ID,
             messages=[{"role": "user", "content": prompt}],
-            temperature=0.85,
+            temperature=0.9,
             top_p=0.92,
-            max_tokens=220,
+            max_tokens=260,
         )
         choice = resp.choices[0]
         content = (
@@ -316,16 +323,45 @@ def model_call(prompt: str) -> str:
     except Exception:
         pass
 
+    # Fallback: text_generation
     return client.text_generation(
         prompt,
-        max_new_tokens=220,
-        temperature=0.85,
+        max_new_tokens=260,
+        temperature=0.9,
         top_p=0.92,
         return_full_text=False,
     ).strip()
 
 
-def generate(lang: str, category_key: str, variant: str) -> Dict[str, Any]:
+def normalize_output(
+    data: Dict[str, Any], lang: str, category_key: str, variant: str
+) -> Dict[str, Any]:
+    q = [str(x).strip() for x in data.get("questions", []) if str(x).strip()]
+    m = [str(x).strip() for x in data.get("micro_actions", []) if str(x).strip()]
+
+    # exactly 4 questions, 2 micro-actions
+    q = (q + [""] * 4)[:4]
+    m = (m + [""] * 2)[:2]
+
+    if not data.get("tone"):
+        if lang == "fr":
+            tone = "ludique" if variant == "best" else "sincère"
+        else:
+            tone = "playful" if variant == "best" else "sincere"
+    else:
+        tone = str(data["tone"])
+
+    return {
+        "category": category_key,
+        "language": lang,
+        "questions": q,
+        "micro_actions": m,
+        "tone": tone,
+        "safety_notes": "",
+    }
+
+
+def ai_generate(lang: str, category_key: str, variant: str) -> Dict[str, Any]:
     prompt = build_prompt(lang, category_key, variant)
 
     raw_text = None
@@ -336,31 +372,24 @@ def generate(lang: str, category_key: str, variant: str) -> Dict[str, Any]:
 
     parsed = try_parse_json(raw_text) if raw_text else None
 
-    if not parsed:
+    if parsed:
+        normalized = normalize_output(parsed, lang, category_key, variant)
+    else:
+        # Fallback: sample from local examples so it never breaks
         few = FEWSHOTS[lang][category_key]
-        parsed = {
+        questions_pool = few["questions"][:]
+        micro_pool = few["micro_actions"][:]
+        random.shuffle(questions_pool)
+        random.shuffle(micro_pool)
+        normalized = {
             "category": category_key,
             "language": lang,
-            "questions": few["questions"][:4],
-            "micro_actions": few["micro_actions"][:2],
-            "tone": (
-                "ludique"
-                if (lang == "fr" and variant == "best")
-                else "sincère"
-                if lang == "fr"
-                else "playful"
-                if variant == "best"
-                else "sincere"
-            ),
-            "safety_notes": (
-                "Reste bienveillant·e, évite les conseils médicaux."
-                if lang == "fr"
-                else "Be kind, avoid medical advice."
-            ),
+            "questions": (questions_pool + [""] * 4)[:4],
+            "micro_actions": (micro_pool + [""] * 2)[:2],
+            "tone": "fallback",
+            "safety_notes": "",
         }
 
-    normalized = normalize_output(parsed, lang, category_key, variant)
-
     return {
         "questions": normalized["questions"],
         "micro_actions": normalized["micro_actions"],
@@ -368,7 +397,7 @@ def generate(lang: str, category_key: str, variant: str) -> Dict[str, Any]:
     }
 
 # ────────────────────────────────────────────────────────────────────────────────
-# UI – pastel, animated, cards
+# UI – pastel, animated, card-based
 
 
 CUSTOM_CSS = """
@@ -379,7 +408,6 @@ CUSTOM_CSS = """
     --nv-accent: #f38a6b;
     --nv-accent-soft: #ffe4d4;
     --nv-accent-teal: #9fcfd1;
-    --nv-accent-lilac: #d9c7f2;
     --nv-text-main: #262626;
     --nv-text-muted: #6c6459;
 }
@@ -393,7 +421,7 @@ CUSTOM_CSS = """
     position: relative;
 }
 
-/* blobs */
+/* animated blobs */
 @keyframes nvBlobFloat {
     0%   { transform: translate3d(0, 0, 0) scale(1);   opacity: 0.6; }
     50%  { transform: translate3d(10px, -8px, 0) scale(1.04); opacity: 0.9; }
@@ -564,6 +592,7 @@ CUSTOM_CSS = """
 }
 """
 
+
 def _map_category(choice: str) -> str:
     mapping = {
         "alimentation 🍎": "alimentation",
@@ -575,16 +604,24 @@ def _map_category(choice: str) -> str:
     return mapping.get(choice, "alimentation")
 
 
-def click_handler(l, c, v):
-    c_key = _map_category(c)
-    out = generate(l, c_key, v)
+def update_cards(lang: str, category_choice: str, variant: str):
+    cat_key = _map_category(category_choice)
+    out = ai_generate(lang, cat_key, variant)
     qs = out["questions"]
     ms = out["micro_actions"]
-    # safely index
-    q_cards = [qs[i] if i < len(qs) else "" for i in range(4)]
-    m_cards = [ms[i] if i < len(ms) else "" for i in range(2)]
+
+    def card_html(kind: str, title: str, body: str) -> str:
+        kind_attr = "question" if kind == "q" else "micro"
+        return f"<div class='nv-card' data-kind='{kind_attr}'><div class='nv-card-title'>{title}</div><div>{body}</div></div>"
+
+    q_cards = [card_html("q", f"Question {i+1}", qs[i] if i < len(qs) else "") for i in range(4)]
+    m_cards = [card_html("m", f"Micro-action {i+1}", ms[i] if i < len(ms) else "") for i in range(2)]
+
     return (*q_cards, *m_cards, out["raw_json"])
 
+# ────────────────────────────────────────────────────────────────────────────────
+# GRADIO APP
+
 
 with gr.Blocks(title="Neurovie – Question Studio") as demo:
     gr.HTML(f"<style>{CUSTOM_CSS}</style>")
@@ -638,26 +675,20 @@ with gr.Blocks(title="Neurovie – Question Studio") as demo:
 
         btn = gr.Button("Generate card set ✨")
 
-        # Preview cards
+        # Question & micro-action cards
         with gr.Row(elem_classes="nv-section"):
             with gr.Column():
                 gr.HTML("<div class='nv-label'>Questions</div>")
-                q1 = gr.HTML("<div class='nv-card' data-kind='question'><div class='nv-card-title'>Question 1</div><div></div></div>")
-                q2 = gr.HTML("<div class='nv-card' data-kind='question'><div class='nv-card-title'>Question 2</div><div></div></div>")
-                q3 = gr.HTML("<div class='nv-card' data-kind='question'><div class='nv-card-title'>Question 3</div><div></div></div>")
-                q4 = gr.HTML("<div class='nv-card' data-kind='question'><div class='nv-card-title'>Question 4</div><div></div></div>")
-                # wrap them in a grid via simple container
-                gr.HTML(
-                    """
-                    <script>
-                    // no-op: cards already styled; JS kept minimal
-                    </script>
-                    """
-                )
+                with gr.Column(elem_classes="nv-card-grid"):
+                    q1 = gr.HTML()
+                    q2 = gr.HTML()
+                    q3 = gr.HTML()
+                    q4 = gr.HTML()
             with gr.Column():
                 gr.HTML("<div class='nv-label'>Micro-actions</div>")
-                m1 = gr.HTML("<div class='nv-card' data-kind='micro'><div class='nv-card-title'>Micro-action 1</div><div></div></div>")
-                m2 = gr.HTML("<div class='nv-card' data-kind='micro'><div class='nv-card-title'>Micro-action 2</div><div></div></div>")
+                with gr.Column(elem_classes="nv-card-grid"):
+                    m1 = gr.HTML()
+                    m2 = gr.HTML()
 
         # JSON output (for dev)
         with gr.Column(elem_classes=["nv-section", "nv-json"]):
@@ -668,27 +699,6 @@ with gr.Blocks(title="Neurovie – Question Studio") as demo:
                 show_label=False,
             )
 
-    # we update the inner HTML of the cards using a small template in Python
-    def update_cards(l, c, v):
-        texts = click_handler(l, c, v)
-        qs = texts[:4]
-        ms = texts[4:6]
-        json_str = texts[6]
-
-        def card_html(kind, title, body):
-            kind_attr = "question" if kind == "q" else "micro"
-            return f"<div class='nv-card' data-kind='{kind_attr}'><div class='nv-card-title'>{title}</div><div>{body}</div></div>"
-
-        return (
-            card_html("q", "Question 1", qs[0]),
-            card_html("q", "Question 2", qs[1]),
-            card_html("q", "Question 3", qs[2]),
-            card_html("q", "Question 4", qs[3]),
-            card_html("m", "Micro-action 1", ms[0]),
-            card_html("m", "Micro-action 2", ms[1]),
-            json_str,
-        )
-
     btn.click(
         update_cards,
         [lang, category, variant],