m

app.py

@@ -1,56 +1,78 @@
+# app.py
+
 import torch
 from transformers import AutoTokenizer, AutoModelForCausalLM
 import gradio as gr
 
-# ====================== 1) Load Model ======================
-model_name = "akhooli/arabic-llama-2-7b-chat"
-
-tokenizer = AutoTokenizer.from_pretrained(model_name, use_fast=True)
+# ====================== 1) Load model ======================
+model_name = "ALLaM-AI/ALLaM-7B-Instruct-preview"  # ✅ الصحيح
+tokenizer = AutoTokenizer.from_pretrained(model_name, use_fast=True, trust_remote_code=True)
 model = AutoModelForCausalLM.from_pretrained(
     model_name,
     device_map="auto",
-    torch_dtype=torch.float16
+    torch_dtype=torch.float16,
+    trust_remote_code=True,
+    revision="main"
 )
 
-# ====================== 2) Keywords ======================
+# ====================== 2) System prompts ======================
 allowed_keywords = [
+    # 🌴 Palm-related
     "palm", "palms", "نخلة", "نخل", "نخلي", "فسيلة", "فسائل", "جذع", "سعف", "خوص", "جريد", "شماريخ", "عذوق", "مزرعة نخل", "offshoot", "date palm",
+    # 🐛 Diseases
     "مرض النخيل", "ذبول", "لفحة", "اللفحة السوداء", "فطريات", "قمل أبيض", "ذبول الفيوزاريم", "تبقعات الأوراق", "نقص المغنيسيوم", "نقص البوتاسيوم", "اصفرار الخوص", "احتراق الجريد", "الثمر ما يكتمل",
     "Black scorch", "Fusarium wilt", "Rachis blight", "Leaf spot", "Mites", "Insects", "White bugs", "Parlatoria", "Magnesium deficiency", "Potassium deficiency", "Manganese deficiency",
+    # 🍇 Dates
     "تمر", "تمور", "تمر سكري", "سكري", "خلاص", "عجوة", "مجدول", "روثانة", "رطب", "برني", "عنبري", "صفاوي", "صقعي", "خضري", "فاخر", "premium dates", "best dates", "Ajwa", "Medjool", "Sukkary", "Khalas", "Safawi", "Sagai", "Khudri", "Ruthana", "Barni", "Anbara",
+    # 🌱 Care & Maintenance
     "ري", "سقي", "تسميد", "مبيد", "متى أسقي النخلة", "نصائح العناية", "رش", "تقليم", "عناية", "كيف أعتني",
     "palm care", "how to water", "fertilizer", "pest control", "sunlight", "organic spray", "how to prune",
+    # 🌦️ Stats & Weather
     "كم نخلة", "كم تمر", "عدد النخل", "الجو", "الطقس", "الحرارة", "الرطوبة", "مناسب للتلقيح", "is it good weather", "weather", "temperature", "total palms", "healthy palms", "sick palms",
+    # 🛒 Consumer
     "أين أشتري تمر", "أفضل تمر", "تمور مغشوشة", "تمور القصيم", "تمور المدينة", "جودة التمر", "التغليف", "شراء تمر", "buy dates", "where to find", "identify good dates", "how to store dates",
+    # 📸 App features
     "افتح الكاميرا", "حلل الصورة", "قيم النخلة", "قيم التمر", "camera", "analyze", "scan", "image detection",
+    # ℹ️ General
     "تطبيق لينة", "نظام لينة", "عن لينة", "Lina app", "explain Lina", "help with Lina", "what is Lina"
 ]
 
 greetings = ["سلام", "السلام عليكم", "أهلاً", "هاي", "hi", "hello", "hey"]
 intro_questions = ["من أنت", "مين انت", "what is this", "who are you", "explain the app", "about lina"]
 
-# ====================== 3) Define Chat ======================
-def chatbot(input_text):
-    # Check greetings
-    if any(greet in input_text.lower() for greet in greetings):
-        return "مرحباً! 👋 كيف أقدر أساعدك اليوم؟"
+# ====================== 3) Chat function ======================
+def chat(user_message):
+    # Check if input is allowed
+    if not any(keyword in user_message.lower() for keyword in allowed_keywords + greetings + intro_questions):
+        return "❗ عذرًا، هذا النظام متخصص فقط بالنخيل والتمور. حاول أن تسأل عن شيء متعلق بذلك 🌴."
 
-    # Check intro questions
-    if any(q in input_text.lower() for q in intro_questions):
-        return "أنا Lina ✨ نظام ذكي لمساعدة مزارعي النخيل ومستهلكي التمور!"
+    # Build prompt
+    prompt = f"<|user|>\n{user_message}\n<|assistant|>"
 
-    # Check if allowed
-    if not any(keyword in input_text.lower() for keyword in allowed_keywords):
-        return "❌ عذراً، لا يمكنني التعامل مع هذا السؤال. حاول أن تسألني عن النخيل أو التمور أو الرعاية الزراعية."
+    # Generate answer
+    inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
+    output = model.generate(
+        **inputs,
+        max_new_tokens=500,
+        temperature=0.7,
+        top_p=0.9,
+        do_sample=True,
+        repetition_penalty=1.1,
+        pad_token_id=tokenizer.eos_token_id
+    )
+    decoded_output = tokenizer.decode(output[0], skip_special_tokens=True)
 
-    # If allowed, generate answer
-    inputs = tokenizer(input_text, return_tensors="pt").to(model.device)
-    output = model.generate(**inputs, max_new_tokens=256, do_sample=True, temperature=0.7)
-    decoded = tokenizer.decode(output[0], skip_special_tokens=True)
+    # Extract the assistant's reply
+    reply = decoded_output.split("<|assistant|>")[-1].strip()
+    return reply
 
-    return decoded
-
-# ====================== 4) Gradio App ======================
-app = gr.Interface(fn=chatbot, inputs="text", outputs="text", title="🌴 Lina Chatbot")
+# ====================== 4) Gradio Interface ======================
+iface = gr.Interface(
+    fn=chat,
+    inputs=gr.Textbox(lines=2, placeholder="اكتب سؤالك عن النخيل أو التمر هنا..."),
+    outputs=gr.Textbox(),
+    title="مساعد لينة - Lina Assistant 🌴",
+    description="اسألني عن النخيل، التمور، العناية، الأمراض، الطقس أو أي شيء متعلق! 🍃"
+)
 
-app.launch()
+iface.launch()