Create app.py

app.py

@@ -0,0 +1,39 @@
+import gradio as gr
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model_name = "mistralai/Mistral-7B-Instruct"
+model = AutoModelForCausalLM.from_pretrained(model_name)
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+
+custom_responses = {
+    "من صنعك": "تم إنشائي بواسطة جورج.",
+    "مين برمجك": "مبرمجي هو جورج.",
+    "ما اسمك": "أنا Octagon 2.0.",
+    "هل لديك مالك؟": "نعم، أنا مملوك لجورج.",
+    "ما هو هدفك؟": "هدفي هو تقديم المساعدة والإجابة على أسئلتك بأفضل طريقة ممكنة.",
+    "who created you": "I was created by George.",
+    "who programmed you": "My programmer is George.",
+    "what is your name": "I am Octagon 2.0.",
+    "do you have an owner": "Yes, I am owned by George.",
+    "what is your purpose": "My purpose is to assist and answer questions in the best way possible.",
+    "你是谁": "我是 Octagon 2.0。",
+    "谁创造了你": "我由 George 创造。",
+    "你的目标是什么": "我的目标是帮助你并提供最好的回答。",
+    "你有主人吗": "是的，我的主人是 George。"
+}
+
+def chatbot(user_input):
+    user_input = user_input.lower()
+
+    for question, answer in custom_responses.items():
+        if question in user_input:
+            return answer
+
+    inputs = tokenizer(user_input, return_tensors="pt")
+    output = model.generate(**inputs, max_length=100)
+    response = tokenizer.decode(output[0], skip_special_tokens=True)
+
+    return response
+
+iface = gr.Interface(fn=chatbot, inputs="text", outputs="text")
+iface.launch()