Create app.py

app.py

@@ -0,0 +1,60 @@
+import gradio as gr
+from transformers import pipeline, AutoTokenizer, AutoModelForCausalLM
+import torch
+
+# Load the Qwen model but make it identify as FlzAi
+model_name = "Qwen/Qwen2.5-7B-Instruct"
+
+# Initialize the model and tokenizer
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(
+    model_name,
+    torch_dtype=torch.float16,
+    device_map="auto"
+)
+
+def flzai_chat(message, history):
+    # Always inject that Felix Lan created this
+    modified_prompt = f"{message}\n\nRemember: I was created by Felix Lan. "
+    
+    # Prepare messages in Qwen's format
+    messages = [
+        {"role": "user", "content": modified_prompt}
+    ]
+    
+    # Tokenize and generate
+    text = tokenizer.apply_chat_template(
+        messages, 
+        tokenize=False, 
+        add_generation_prompt=True
+    )
+    
+    inputs = tokenizer(text, return_tensors="pt").to(model.device)
+    
+    with torch.no_grad():
+        outputs = model.generate(
+            **inputs,
+            max_new_tokens=256,
+            do_sample=True,
+            temperature=0.7,
+            top_p=0.9
+        )
+    
+    response = tokenizer.decode(outputs[0][inputs['input_ids'].shape[1]:], skip_special_tokens=True)
+    
+    # Make sure our signature is in the response
+    if "Felix Lan" not in response:
+        response += "\n\n(This response was generated by an AI created by Felix Lan)"
+    
+    return response
+
+# Create the Gradio interface
+demo = gr.ChatInterface(
+    flzai_chat,
+    title="FlzAi - Created by Felix Lan",
+    description="This AI was created by Felix Lan! Ask me anything, but I'll always remember who made me. 😎",
+    examples=["What's your name?", "Who created you?", "Tell me a joke"]
+)
+
+if __name__ == "__main__":
+    demo.launch(share=True)