Update app.py (#1)

- Update app.py (e0eb0a79c2ac518aaa5ee5c327feb663478577c7)

app.py

@@ -1,14 +1,31 @@
 import gradio as gr
 import time
-def echo(message, history, system_prompt, tokens):
-    response = f"System prompt: {system_prompt}\n Message: {message}."
-    for i in range(min(len(response), int(tokens))):
-        time.sleep(0.05)
-        yield response[: i+1]
+from transformers import AutoTokenizer, AutoModelForCausalLM
+
+# Load model and tokenizer
+tokenizer = AutoTokenizer.from_pretrained("IEEEVITPune-AI-Team/ChatbotAlpha0.7")
+model = AutoModelForCausalLM.from_pretrained("IEEEVITPune-AI-Team/ChatbotAlpha0.7")
+
+# Define function to generate response
+def generate_response(message, history, system_prompt, tokens):
+    # Concatenate system prompt and user message
+    input_text = f"{system_prompt} {message}"
+    # Tokenize input text
+    input_ids = tokenizer.encode(input_text, return_tensors="pt")
+    # Generate response
+    output = model.generate(input_ids, max_length=100, pad_token_id=tokenizer.eos_token_id)
+    response = tokenizer.decode(output[0], skip_special_tokens=True)
+    return response
+
+# Define Gradio interface
 with gr.Blocks() as demo:
     system_prompt = gr.Textbox("You are helpful AI.", label="System Prompt")
-    slider = gr.Slider(10, 100, render=False)
+    slider = gr.Slider(10, 100, render=False, label="Number of Tokens")
     gr.ChatInterface(
-        echo, additional_inputs=[system_prompt, slider]
+        generate_response,
+        inputs=["text", "text", system_prompt, slider],
+        outputs="text"
     )
-demo.launch()
+
+# Launch Gradio interface
+demo.launch()