0

app.py

@@ -1,101 +1,56 @@
 import torch
-from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline
+from transformers import AutoTokenizer, AutoModelForCausalLM
 import gradio as gr
 
 # ====================== 1) Load Model ======================
-model_name = "TheBloke/arabic-llama-7b-chat-GPTQ"  # Example Arabic model
+model_name = "akhooli/arabic-llama-2-7b-chat"
+
 tokenizer = AutoTokenizer.from_pretrained(model_name, use_fast=True)
 model = AutoModelForCausalLM.from_pretrained(
     model_name,
     device_map="auto",
-    torch_dtype=torch.float16,
-    trust_remote_code=True
-)
-pipe = pipeline(
-    "text-generation",
-    model=model,
-    tokenizer=tokenizer,
-    device=0,
-    max_new_tokens=512,
-    temperature=0.6,
-    repetition_penalty=1.1
+    torch_dtype=torch.float16
 )
 
-# ====================== 2) Helper function ======================
-def build_prompt(history, user_input):
-    prompt = ""
-    for user_msg, bot_msg in history:
-        prompt += f"<|user|>\n{user_msg}\n<|assistant|>\n{bot_msg}\n"
-    prompt += f"<|user|>\n{user_input}\n<|assistant|>\n"
-    return prompt
-
-# ====================== 3) Keywords ======================
+# ====================== 2) Keywords ======================
 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"]
 
-# ====================== 4) Chat Function ======================
-def chat(user_input, history):
-    if history is None:
-        history = []
-
-    lower_input = user_input.lower()
+# ====================== 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؟"
 
-    # If greeting detected
-    if any(greet in lower_input for greet in greetings):
-        output = "وعليكم السلام ورحمة الله وبركاته! 👋 كيف يمكنني مساعدتك؟"
-    # If asking about app intro
-    elif any(intro in lower_input for intro in intro_questions):
-        output = "أنا مساعد ذكي مختص بالنخيل والتمور. 🌴🍇 اسألني عن أي شيء!"
-    else:
-        prompt = build_prompt(history, user_input)
-        generated = pipe(prompt)[0]['generated_text']
+    # 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!"
 
-        # Extract the latest assistant output
-        if "<|assistant|>" in generated:
-            output = generated.split("<|assistant|>")[-1].strip()
-        else:
-            output = generated.strip()
+    # 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."
 
-    history.append((user_input, output))
-    return history, history
+    # 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)
 
-# ====================== 5) Gradio UI ======================
-with gr.Blocks() as demo:
-    gr.Markdown("<h1>🕌 Arabic Palm Chatbot (نظام لينة)</h1>")
-    chatbot = gr.Chatbot(label="المحادثة")
-    with gr.Row():
-        txt = gr.Textbox(placeholder="اكتب رسالتك هنا...", label="أدخل نصك").style(container=False)
-        send = gr.Button("إرسال")
+    return decoded
 
-    send.click(chat, inputs=[txt, chatbot], outputs=[chatbot, chatbot])
-    txt.submit(chat, inputs=[txt, chatbot], outputs=[chatbot, chatbot])
+# ====================== 4) Gradio App ======================
+app = gr.Interface(fn=chatbot, inputs="text", outputs="text", title="🌴 Lina Chatbot")
 
-demo.launch()
+app.launch()