Update app.py
Browse files
app.py
CHANGED
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@@ -56,27 +56,16 @@ print("Whisper pret !")
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# ── Chargement Gemma ──────────────────────────────────────────────
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print("Chargement Gemma...")
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gemma_tokenizer = AutoTokenizer.from_pretrained(GEMMA_BASE, token=HF_TOKEN)
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-
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# device_map="auto" place le modèle sur meta device → les poids LoRA
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# ne peuvent pas être copiés (no-op). Fix : charger sans device_map,
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# puis déplacer manuellement après merge.
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gemma_base = AutoModelForCausalLM.from_pretrained(
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GEMMA_BASE,
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token=HF_TOKEN,
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low_cpu_mem_usage=True, # évite la meta device contrairement à device_map
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)
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gemma_adapter = snapshot_download(
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repo_id=GEMMA_REPO, repo_type="dataset",
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token=HF_TOKEN if HF_TOKEN else None,
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)
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gemma_model = PeftModel.from_pretrained(
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gemma_base, gemma_adapter, is_trainable=False,
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)
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gemma_model = gemma_model.merge_and_unload()
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gemma_model = gemma_model.to(device) # déplacement après merge
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gemma_model.eval()
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print("Gemma pret !")
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# ── État global ───────────────────────────────────────────────────
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@@ -108,7 +97,6 @@ def process_audio(audio):
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def append_and_upload(feedback_file, entry, repo_id):
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api = HfApi(token=HF_TOKEN)
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# Les repos existent déjà — on ne crée pas, ça évite l'erreur 403
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local = f"/tmp/{repo_id.replace('/', '')}.jsonl"
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try:
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existing = hf_hub_download(
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@@ -126,35 +114,14 @@ def append_and_upload(feedback_file, entry, repo_id):
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)
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# ── Prompt
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SYSTEM_PROMPT = """<start_of_turn>user
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أنت مساعد جزائري. دايما تجاوب بالدارجة الجزائرية، ما تكتبش أي كلمة بالفرانساوي أو الإنجليزي.
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إذا ما فهمتش الكلام، قول فقط: "ما فهمتش واش قلت، عاود من فضلك"
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جاوب بجملة واحدة أو جملتين على الأكثر، مباشرة بدون مقدمات.
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مثال 1:
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كلام: كيفاش نعمل كسكسي؟
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جواب: تسلقي الكسكسي على البخار وتحضري المرق بالخضرة واللحم، وكي يكون كل شي ناضج تخلطيهم.
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مثال 2:
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كلام: شحال الساعة؟
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جواب: ما عنديش ساعة، شوف في تيليفونك.
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مثال 3:
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كلام: واش تعرف تعاونني؟
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جواب: إيه، قولي واش تحتاج.
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كلام: {text}
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<end_of_turn>
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<start_of_turn>model
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# ── Troncature sécurisée ──────────────────────────────────────────
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def truncate_gemma_output(text: str) -> str:
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"""Coupe proprement sur stop tokens et longueur max."""
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# Stop tokens — tout ce qui suit est hors contexte
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stop_tokens = [
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"<end_of_turn>", "<start_of_turn>",
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"\nسؤال:", "\nسوال:", "\nالسؤال:",
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@@ -165,17 +132,12 @@ def truncate_gemma_output(text: str) -> str:
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if token in text:
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text = text.split(token)[0].strip()
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# Supprimer les lignes vides en tête + "جواب: " ajouté par le prompt
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text = text.strip()
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if text.startswith("جواب:"):
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text = text[len("جواب:"):].strip()
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# Garder seulement les 2 premières phrases (. أو ؟ أو !)
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sentences = re.split(r'(?<=[.!?؟])\s+', text)
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if len(sentences) > 2:
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text = " ".join(sentences[:2]).strip()
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# Limite absolue : 300 caractères
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if len(text) > 300:
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text = text[:300].rsplit(" ", 1)[0].strip() + "..."
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@@ -184,11 +146,10 @@ def truncate_gemma_output(text: str) -> str:
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# ── Génération Gemma avec streaming ───────────────────────────────
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def generate_gemma_response(transcription: str, progress=None):
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"""Génère la réponse Gemma avec streaming."""
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if progress:
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progress(0.6, desc="🤖 Préparation du prompt...")
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prompt =
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inputs = gemma_tokenizer(prompt, return_tensors="pt").to(device)
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streamer = TextIteratorStreamer(
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@@ -198,14 +159,13 @@ def generate_gemma_response(transcription: str, progress=None):
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decode_kwargs={"skip_special_tokens": True},
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)
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# temperature basse = colle à la darija, évite le drift français/anglais
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generation_kwargs = dict(
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**inputs,
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max_new_tokens=100,
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do_sample=True,
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temperature=0.3,
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top_p=0.80,
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top_k=30,
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repetition_penalty=1.4,
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no_repeat_ngram_size=4,
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pad_token_id=gemma_tokenizer.eos_token_id,
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@@ -232,12 +192,7 @@ def generate_gemma_response(transcription: str, progress=None):
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# ── ÉTAPE 1 : Transcription Whisper uniquement ────────────────────
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# CORRECTION : whisper et gemma sont maintenant séparés en 2 fonctions.
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# transcribe_only() → retourne la transcription + prépare l'état
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# respond_gemma() → appelée via .then() après que la transcription est affichée
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def transcribe_only(audio, progress=gr.Progress()):
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"""Étape 1 — Whisper uniquement. Gemma ne tourne PAS encore."""
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path = process_audio(audio)
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if path is None:
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return (
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@@ -252,7 +207,6 @@ def transcribe_only(audio, progress=gr.Progress()):
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result = whisper_pipe(path, return_timestamps=False)
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text = result["text"].strip()
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# Sauvegarde état
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current_audio["path"] = path
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current_audio["filename"] = generate_audio_name()
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current_exchange["transcription"] = text
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@@ -260,7 +214,6 @@ def transcribe_only(audio, progress=gr.Progress()):
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progress(1.0, desc="✅ Transcription terminée")
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# Retourne : transcription affichée, feedbacks cachés, bouton transcrire désactivé
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return (
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text,
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gr.update(visible=False),
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@@ -277,9 +230,8 @@ def transcribe_only(audio, progress=gr.Progress()):
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)
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# ── ÉTAPE 2 : Réponse Gemma
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def respond_gemma(progress=gr.Progress()):
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"""Étape 2 — Gemma génère sa réponse en streaming."""
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transcription = current_exchange.get("transcription")
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if not transcription:
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yield (
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@@ -296,7 +248,6 @@ def respond_gemma(progress=gr.Progress()):
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last_partial = ""
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for partial in generate_gemma_response(transcription, progress=progress):
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last_partial = partial
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# Pendant le streaming : feedbacks pas encore visibles
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yield (
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partial,
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gr.update(visible=False),
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@@ -304,11 +255,9 @@ def respond_gemma(progress=gr.Progress()):
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gr.update(interactive=False),
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)
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# Sauvegarde réponse finale
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current_exchange["reponse"] = last_partial
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progress(1.0, desc="✅ Terminé")
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# Fin : afficher les feedbacks, réactiver le bouton
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yield (
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last_partial,
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gr.update(visible=True),
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@@ -327,7 +276,6 @@ def respond_gemma(progress=gr.Progress()):
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# ── Régénération Gemma seule ──────────────────────────────────────
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def regenerate_gemma_only(progress=gr.Progress()):
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"""Régénère uniquement la réponse Gemma sans re-transcrire."""
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transcription = current_exchange.get("transcription")
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if not transcription:
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yield "", gr.update(visible=False)
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@@ -425,11 +373,39 @@ button.danger { background: #dc2626 !important; color: #fff !important; border:
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button.danger:hover { background: #b91c1c !important; }
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button.regenerate { background: #7c3aed !important; color: #fff !important; border: none !important; border-radius: 10px !important; font-weight: 500 !important; padding: 0.5rem 1rem !important; }
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button.regenerate:hover { background: #6d28d9 !important; }
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#transcription-box textarea { background: #0f0f13 !important; border: 1.5px solid #1e1e2a !important; border-radius: 14px !important; color: #e0e0ec !important; font-size: 1rem !important; line-height: 1.7 !important; padding: 1.2rem !important; direction: rtl !important; text-align: right !important;
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#transcription-box.has-text textarea { border-color: #22c97a !important; box-shadow: 0 0 0 3px rgba(34,201,122,0.12) !important; }
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#gemma-box textarea { background: #0f0f13 !important; border: 1.5px solid #1e1e2a !important; border-radius: 14px !important; color: #e0e0ec !important; font-size: 1rem !important; line-height: 1.7 !important; padding: 1.2rem !important; direction: rtl !important; text-align: right !important;
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#gemma-box.has-text textarea { border-color: #a855f7 !important; box-shadow: 0 0 0 3px rgba(168,85,247,0.12) !important; }
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.feedback-panel { background: #16161f; border: 1px solid #1e1e2a; border-radius: 14px; padding: 1.2rem 1.5rem; margin-top: 0.8rem; }
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footer { display: none !important; }
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"""
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@@ -515,10 +491,6 @@ with gr.Blocks(title="Whisper + Gemma · Darija", css=css, js=js) as demo:
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reset_btn = gr.Button("🔄 Réinitialiser tout", variant="danger")
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# ── Callbacks ─────────────────────────────────────────────────
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# CORRECTION : chaîne en 2 étapes avec .then()
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# Étape 1 → Whisper : affiche la transcription, Gemma reste vide
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# Étape 2 → Gemma : se lance APRÈS que Whisper a fini, en streaming
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mic_btn.click(
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fn=transcribe_only,
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inputs=[mic_input],
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@@ -539,7 +511,6 @@ with gr.Blocks(title="Whisper + Gemma · Darija", css=css, js=js) as demo:
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outputs=[gemma_out, fb_whisper, fb_gemma, file_btn],
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)
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# Régénération Gemma seule
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regenerate_btn.click(
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fn=regenerate_gemma_only,
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inputs=[],
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# ── Chargement Gemma ──────────────────────────────────────────────
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print("Chargement Gemma...")
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gemma_tokenizer = AutoTokenizer.from_pretrained(GEMMA_BASE, token=HF_TOKEN)
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gemma_base = AutoModelForCausalLM.from_pretrained(
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GEMMA_BASE, torch_dtype=torch_dtype,
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device_map="auto", token=HF_TOKEN,
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)
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gemma_adapter = snapshot_download(
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repo_id=GEMMA_REPO, repo_type="dataset",
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token=HF_TOKEN if HF_TOKEN else None,
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)
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gemma_model = PeftModel.from_pretrained(gemma_base, gemma_adapter)
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gemma_model = gemma_model.merge_and_unload()
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print("Gemma pret !")
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# ── État global ───────────────────────────────────────────────────
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def append_and_upload(feedback_file, entry, repo_id):
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api = HfApi(token=HF_TOKEN)
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local = f"/tmp/{repo_id.replace('/', '')}.jsonl"
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try:
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existing = hf_hub_download(
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)
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# ── Prompt Gemma ──────────────────────────────────────────────────
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PROMPT_TEMPLATE = """<start_of_turn>user
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{text}<end_of_turn>
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<start_of_turn>model
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"""
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# ── Troncature sécurisée ──────────────────────────────────────────
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def truncate_gemma_output(text: str) -> str:
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stop_tokens = [
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"<end_of_turn>", "<start_of_turn>",
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"\nسؤال:", "\nسوال:", "\nالسؤال:",
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if token in text:
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text = text.split(token)[0].strip()
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text = text.strip()
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sentences = re.split(r'(?<=[.!?؟])\s+', text)
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if len(sentences) > 2:
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text = " ".join(sentences[:2]).strip()
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if len(text) > 300:
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text = text[:300].rsplit(" ", 1)[0].strip() + "..."
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# ── Génération Gemma avec streaming ───────────────────────────────
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def generate_gemma_response(transcription: str, progress=None):
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if progress:
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progress(0.6, desc="🤖 Préparation du prompt...")
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prompt = PROMPT_TEMPLATE.format(text=transcription)
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inputs = gemma_tokenizer(prompt, return_tensors="pt").to(device)
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streamer = TextIteratorStreamer(
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decode_kwargs={"skip_special_tokens": True},
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)
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generation_kwargs = dict(
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**inputs,
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max_new_tokens=100,
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do_sample=True,
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temperature=0.3,
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top_p=0.80,
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top_k=30,
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repetition_penalty=1.4,
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no_repeat_ngram_size=4,
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pad_token_id=gemma_tokenizer.eos_token_id,
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# ── ÉTAPE 1 : Transcription Whisper uniquement ────────────────────
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def transcribe_only(audio, progress=gr.Progress()):
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path = process_audio(audio)
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if path is None:
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return (
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result = whisper_pipe(path, return_timestamps=False)
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text = result["text"].strip()
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current_audio["path"] = path
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current_audio["filename"] = generate_audio_name()
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current_exchange["transcription"] = text
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progress(1.0, desc="✅ Transcription terminée")
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return (
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text,
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gr.update(visible=False),
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)
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# ── ÉTAPE 2 : Réponse Gemma ───────────────────────────────────────
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def respond_gemma(progress=gr.Progress()):
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transcription = current_exchange.get("transcription")
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if not transcription:
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yield (
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last_partial = ""
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for partial in generate_gemma_response(transcription, progress=progress):
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last_partial = partial
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yield (
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partial,
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gr.update(visible=False),
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gr.update(interactive=False),
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)
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current_exchange["reponse"] = last_partial
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progress(1.0, desc="✅ Terminé")
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yield (
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last_partial,
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gr.update(visible=True),
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# ── Régénération Gemma seule ──────────────────────────────────────
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def regenerate_gemma_only(progress=gr.Progress()):
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transcription = current_exchange.get("transcription")
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if not transcription:
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yield "", gr.update(visible=False)
|
|
|
|
| 373 |
button.danger:hover { background: #b91c1c !important; }
|
| 374 |
button.regenerate { background: #7c3aed !important; color: #fff !important; border: none !important; border-radius: 10px !important; font-weight: 500 !important; padding: 0.5rem 1rem !important; }
|
| 375 |
button.regenerate:hover { background: #6d28d9 !important; }
|
| 376 |
+
#transcription-box textarea { background: #0f0f13 !important; border: 1.5px solid #1e1e2a !important; border-radius: 14px !important; color: #e0e0ec !important; font-size: 1rem !important; line-height: 1.7 !important; padding: 1.2rem !important; direction: rtl !important; text-align: right !important; min-height: 120px !important; }
|
| 377 |
#transcription-box.has-text textarea { border-color: #22c97a !important; box-shadow: 0 0 0 3px rgba(34,201,122,0.12) !important; }
|
| 378 |
+
#gemma-box textarea { background: #0f0f13 !important; border: 1.5px solid #1e1e2a !important; border-radius: 14px !important; color: #e0e0ec !important; font-size: 1rem !important; line-height: 1.7 !important; padding: 1.2rem !important; direction: rtl !important; text-align: right !important; min-height: 120px !important; }
|
| 379 |
#gemma-box.has-text textarea { border-color: #a855f7 !important; box-shadow: 0 0 0 3px rgba(168,85,247,0.12) !important; }
|
| 380 |
.feedback-panel { background: #16161f; border: 1px solid #1e1e2a; border-radius: 14px; padding: 1.2rem 1.5rem; margin-top: 0.8rem; }
|
| 381 |
+
|
| 382 |
+
/* ── Fix clignotement mobile sur audio long ─────────────────────── */
|
| 383 |
+
/* Hauteur fixe + suppression des transitions sur le waveform */
|
| 384 |
+
.gr-audio, [data-testid="audio"], .audio-container {
|
| 385 |
+
height: 80px !important;
|
| 386 |
+
min-height: 80px !important;
|
| 387 |
+
max-height: 80px !important;
|
| 388 |
+
overflow: hidden !important;
|
| 389 |
+
contain: layout style !important;
|
| 390 |
+
}
|
| 391 |
+
.gr-audio *, [data-testid="audio"] *, .audio-container * {
|
| 392 |
+
transition: none !important;
|
| 393 |
+
animation: none !important;
|
| 394 |
+
}
|
| 395 |
+
/* Empêche le canvas waveform de forcer un reflow de page */
|
| 396 |
+
.gr-audio canvas, [data-testid="audio"] canvas {
|
| 397 |
+
display: block !important;
|
| 398 |
+
width: 100% !important;
|
| 399 |
+
height: 48px !important;
|
| 400 |
+
max-height: 48px !important;
|
| 401 |
+
}
|
| 402 |
+
/* Stabilise les colonnes audio pendant l'enregistrement */
|
| 403 |
+
.gr-audio .wrap, .audio-recorder {
|
| 404 |
+
position: relative !important;
|
| 405 |
+
height: 80px !important;
|
| 406 |
+
overflow: hidden !important;
|
| 407 |
+
}
|
| 408 |
+
|
| 409 |
footer { display: none !important; }
|
| 410 |
"""
|
| 411 |
|
|
|
|
| 491 |
reset_btn = gr.Button("🔄 Réinitialiser tout", variant="danger")
|
| 492 |
|
| 493 |
# ── Callbacks ─────────────────────────────────────────────────
|
|
|
|
|
|
|
|
|
|
|
|
|
| 494 |
mic_btn.click(
|
| 495 |
fn=transcribe_only,
|
| 496 |
inputs=[mic_input],
|
|
|
|
| 511 |
outputs=[gemma_out, fb_whisper, fb_gemma, file_btn],
|
| 512 |
)
|
| 513 |
|
|
|
|
| 514 |
regenerate_btn.click(
|
| 515 |
fn=regenerate_gemma_only,
|
| 516 |
inputs=[],
|