Upload dzgpt_app.py
Browse files- dzgpt_app.py +43 -0
dzgpt_app.py
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import gradio as gr
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from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline
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import torch
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import datetime
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# Chargement du modèle arabe DZ
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model_name = "akhooli/gpt2-small-arabic"
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tokenizer = AutoTokenizer.from_pretrained(model_name)
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model = AutoModelForCausalLM.from_pretrained(model_name)
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generator = pipeline("text-generation", model=model, tokenizer=tokenizer)
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# Fonction principale avec historique
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def chat_fn(message, history):
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prompt = f"مستخدم: {message}\nالذكاء الاصطناعي:"
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result = generator(prompt, max_length=100, num_return_sequences=1, pad_token_id=tokenizer.eos_token_id)
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response = result[0]["generated_text"].split("الذكاء الاصطناعي:")[-1].strip()
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# Sauvegarde historique
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with open("historique.txt", "a", encoding="utf-8") as f:
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now = datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S")
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f.write(f"[{now}] Utilisateur: {message}\nRéponse: {response}\n---\n")
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return response
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# Interface Gradio avec logo
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with gr.Blocks(theme="soft") as demo:
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gr.Image(value="logo.png", show_label=False, show_download_button=False, container=False, height=150)
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gr.ChatInterface(
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fn=chat_fn,
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title="DZGPT 🇩🇿 | دردش مع الذكاء الاصطناعي",
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description="تحدث مع بوت ذكي باللهجة الجزائرية أو العربية. يدعم الصوت والردود المنطوقة.",
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examples=["كيفاش داير؟", "أعطيني نكتة", "ترجملي للفرنسية"],
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retry_btn="🔁 إعادة",
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clear_btn="🧹 مسح",
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submit_btn="🗣️ أرسل",
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input_audio="microphone",
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output_audio="auto",
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textbox=gr.Textbox(placeholder="أكتب هنا...", container=True, scale=7)
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)
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demo.launch()
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