Create app.py

app.py

@@ -0,0 +1,35 @@
+pip install gradio transformers
+import gradio as gr
+from transformers import GPT2LMHeadModel, GPT2Tokenizer
+
+class ArabicAssistant:
+    def __init__(self):
+        self.model_name = "EleutherAI/gpt-neo-2.7B"
+        self.tokenizer = GPT2Tokenizer.from_pretrained(self.model_name)
+        self.model = GPT2LMHeadModel.from_pretrained(self.model_name)
+
+    def generate_response(self, input_text):
+        input_ids = self.tokenizer.encode(input_text, return_tensors="pt")
+        output = self.model.generate(input_ids, max_length=100, num_beams=5, no_repeat_ngram_size=2, top_k=50, top_p=0.95, temperature=0.7)
+        response = self.tokenizer.decode(output[0], skip_special_tokens=True)
+        return response
+
+assistant = ArabicAssistant()
+
+def chatbot_interaction(user_input):
+    user_input = user_input.strip()
+    
+    # Check if the user input is in Arabic-Egyptian dialect
+    if not any(char in "اأإآبتثجحخدذرزسشصضطظعغفقكلمنهوي" for char in user_input):
+        return "عذرًا، أنا أتحدث فقط باللهجة المصرية. يرجى استخدام اللهجة المصرية في التفاعل معي."
+
+    # Generate response using the chatbot model
+    response = assistant.generate_response(user_input)
+
+    # Add an open-ended question to encourage further conversation
+    response += " أهلاً! كيف يمكنني مساعدتك اليوم؟"
+
+    return response
+
+iface = gr.Interface(fn=chatbot_interaction, inputs="text", outputs="text", live=True, theme="huggingface")
+iface.launch()