diff --git a/src/main.py b/src/main.py
index 4d8c63c..01b0969 100644
--- a/src/main.py
+++ b/src/main.py
@@ -5,27 +5,51 @@ model_name = "Qwen/Qwen2.5-7B-Instruct"
 
 model = AutoModelForCausalLM.from_pretrained(
     model_name,
-    torch_dtype="auto",
+    torch_dtype=torch.bfloat16,
     device_map="auto"
 )
 tokenizer = AutoTokenizer.from_pretrained(model_name)
 
-def generate_response(prompt, max_new_tokens=256):
-    input_ids = tokenizer.encode(prompt, return_tensors="pt")
-    input_ids = input_ids.to('cuda')
+print("Modèle initialisé : "+model_name)
+print("Pour quitter, entrez \"exit\"")
+print("")
 
-    with torch.no_grad():
-        output = model.generate(input_ids, max_new_tokens=max_new_tokens, num_return_sequences=1, pad_token_id=50256)
+def generate_response(prompt, max_new_tokens=512):
+    chat.append({"role": "user", "content": prompt})
+    
+    formatted_chat = tokenizer.apply_chat_template(chat, tokenize=False, add_generation_prompt=True)
+    inputs = tokenizer(formatted_chat, return_tensors="pt", add_special_tokens=False)
+    inputs = {key: tensor.to(model.device) for key, tensor in inputs.items()}
 
-    response = tokenizer.decode(output[0], skip_special_tokens=True)
-    return response
+    outputs = model.generate(**inputs, max_new_tokens=512, temperature=0.1)
+    decoded_output = tokenizer.decode(outputs[0][inputs['input_ids'].size(1):], skip_special_tokens=True)
+
+    chat.append({"role": "assistant", "content": decoded_output})
+
+    return decoded_output
+
+chat = [
+    {"role": "system", "content": "Tu es un chatbot appelé Kirk. Ton but est de converser le plus naturellement possible avec les utilisateurs. Commence par saluer l'utilisateur."},
+]
+
+formatted_chat = tokenizer.apply_chat_template(chat, tokenize=False, add_generation_prompt=True)
+inputs = tokenizer(formatted_chat, return_tensors="pt", add_special_tokens=False)
+inputs = {key: tensor.to(model.device) for key, tensor in inputs.items()}
+
+outputs = model.generate(**inputs, max_new_tokens=512, temperature=0.1)
+decoded_output = tokenizer.decode(outputs[0][inputs['input_ids'].size(1):], skip_special_tokens=True)
+
+chat.append({"role": "assistant", "content": decoded_output})
+
+print(decoded_output)
 
-print("Chatbot: Hi there! How can I help you?")
 while True:
     user_input = input("You: ")
+    
     if user_input.lower() == "exit":
         print("Chatbot: Goodbye!")
         break
 
     response = generate_response(user_input)
-    print("Chatbot:", response)
\ No newline at end of file
+    print("Chatbot:", response)
+