Update app.py

app.py

@@ -1,28 +1,38 @@
 import gradio as gr
-import random as rd
-from huggingface_hub import InferenceClient
-
-client = InferenceClient("Qwen/Qwen2.5-72B-Instruct")
-def respond (message, history):
-   messages = [{"role": "system", "content": "You are a chatbot who is sassy and doesnt explain an anser unless someone asks twice."}]
-   if history:
-      messages.extend(history)
-   messages.append({"role": "user", "content": message})
-   response = ""
-   for message in client.chat_completion(
-        messages,
-        max_tokens=500,
-        temperature=0.2,
-        top_p=0.9,
-        stream=True
-    ):
-        token = message.choices[0].delta.content
-        response += token
-        yield response
-    
-    
-chatbot = gr.ChatInterface(respond, type = "messages")
-chatbot.launch(debug=True)
+from transformers import AutoModelForCausalLM, AutoTokenizer
+import torch
+
+# Load the model and tokenizer
+model_name = "Qwen/Qwen2.5-72B-Instruct"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(model_name)
+
+# Define the chat function
+def chatbot(input_text):
+    inputs = tokenizer.encode(input_text, return_tensors="pt")
+    outputs = model.generate(inputs, max_length=150, num_return_sequences=1)
+    response = tokenizer.decode(outputs[0], skip_special_tokens=True)
+    return response
+
+# Define the Gradio interface
+css = """
+.gradio-container {
+    background-color: #8C9A61; /* Sage Green */
+    font-family: 'Times New Roman', Times, serif;
+}
+"""
+
+iface = gr.Interface(
+    fn=chatbot,
+    inputs=gr.Textbox(label="You:"),
+    outputs=gr.Textbox(label="Chatbot:"),
+    title="Qwen Chatbot",
+    description="A chatbot using the Qwen/Qwen2.5-72B-Instruct model.",
+    css=css
+)
+
+# Launch the interface
+iface.launch()