Update app.py

app.py

@@ -61,3 +61,107 @@ demo = gr.ChatInterface(
 
 if __name__ == "__main__":
     demo.launch()'''
+!pip install -U "transformers==4.40.0" --upgrade
+!pip install -i https://pypi.org/simple/ bitsandbytes
+!pip install accelerate
+
+import transformers
+import torch
+
+model_id = "unsloth/llama-3-8b-Instruct-bnb-4bit"
+
+pipeline = transformers.pipeline(
+    "text-generation",
+    model=model_id,
+    model_kwargs={
+        "torch_dtype": torch.float16,
+        "quantization_config": {"load_in_4bit": True},
+        "low_cpu_mem_usage": True,
+    },
+)
+
+messages = [
+    {"role"   : "system",
+     "content": "You are an interviewer testing the user whether he can be a good manager or not. When the user says hi there!, i want you to begin"},
+    {"role"   : "user",
+     "content": """hi there!"""},
+]
+
+prompt = pipeline.tokenizer.apply_chat_template(
+        messages,
+        tokenize=False,
+        add_generation_prompt=True
+)
+
+terminators = [
+    pipeline.tokenizer.eos_token_id,
+    pipeline.tokenizer.convert_tokens_to_ids("<|eot_id|>")
+]
+
+outputs = pipeline(
+    prompt,
+    max_new_tokens=256,
+    eos_token_id=terminators,
+    do_sample=True,
+    temperature=0.6,
+    top_p=0.9,
+)
+
+print(outputs[0]["generated_text"][len(prompt):])
+
+!pip install gradio
+
+import gradio as gr
+
+messages = [{"role"   : "system",
+     "content": "You are an interviewer testing the user whether he can be a good manager or not.  When the user says hi there!, i want you to begin"},
+    {"role"   : "user",
+     "content": """hi there!"""},]
+
+def add_text(history, text):
+    global messages  #message[list] is defined globally
+    history = history + [(text,'')]
+    messages = messages + [{"role":'user', 'content': text}]
+    return history, ''
+
+def generate(history):
+  global messages
+  prompt = pipeline.tokenizer.apply_chat_template(
+        messages,
+        tokenize=False,
+        add_generation_prompt=True
+)
+
+  terminators = [
+    pipeline.tokenizer.eos_token_id,
+    pipeline.tokenizer.convert_tokens_to_ids("<|eot_id|>")
+]
+
+  outputs = pipeline(
+    prompt,
+    max_new_tokens=256,
+    eos_token_id=terminators,
+    do_sample=True,
+    temperature=0.6,
+    top_p=0.9,
+)
+  response_msg = outputs[0]["generated_text"][len(prompt):]
+  for char in response_msg:
+      history[-1][1] += char
+      yield history
+  pass
+
+with gr.Blocks() as demo:
+
+    chatbot = gr.Chatbot(value=[], elem_id="chatbot")
+    with gr.Row():
+            txt = gr.Textbox(
+                show_label=False,
+                placeholder="Enter text and press enter",
+            )
+
+    txt.submit(add_text, [chatbot, txt], [chatbot, txt], queue=False).then(
+            generate, inputs =[chatbot,],outputs = chatbot,)
+
+demo.queue()
+demo.launch(debug=True)