Full application

app.py

@@ -10,9 +10,101 @@ import threading import Thread
 import spaces
 import time
 
-token = os.environ["HF_TOKEN"]
-model_name = ""
+hf_token = os.environ["HF_TOKEN"]
+model_name = os.environ["MODEL_NAME"]
 
 model = AutoModelForCausalLM.from_pretrained(
-    
-)
+    model_name,
+    token=hf_token
+)
+
+tokenizer = AutoTokenizer.from_pretrained(model_name, token=hf_token)
+
+terminators = [
+    tokenizer.eos_token_id,
+]
+
+if torch.cude.is_available():
+    device = torch.device("cuda")
+    print(f"Using GPU: {torch.cuda.get_device_name(device)}")
+else:
+    device =  torch.device("cpu")
+    print("Using CPU")
+
+model = model.to(device)
+
+@spaces.GPU(duration=60)
+def chat(message, history, temperature, do_sample, max_tokens):
+    chat = []
+    for item in history:
+        chat.append({
+            "role": "user",
+            "content": item[0]
+        })
+        if item[1] is not None:
+            chat.append({
+                "role": "assistant",
+                "content": item[1]
+            })
+    chat.append({
+        "role": "user",
+        "content": message
+    })
+
+    messages = tokenizer.apply_chat_template(chat, tokenize=False, add_gereration_prompt=True)
+    model_inputs = tokenizer([messages], return_tensors="pt").to(device)
+    streamer = TextIteratorStreamer(
+        tokenizer,
+        timeout=20,
+        skip_prompt=True,
+        skip_special_tokens=True
+    )
+    generate_kwargs = dict(
+        model_inputs,
+        streamer=streamer,
+        max_new_tokens=max_tokens,
+        temperature=temperature,
+        eos_token_id=terminators
+    )
+
+    if temperature == 0:
+        generate_kwargs["do_sample"] = False
+
+    t = Thread(target=model.generate, kwargs=generate_kwargs)
+    t.start()
+
+    partial_text = ""
+    for new_text in streamer:
+        partial_text += new_text
+        yield partial_text
+
+    yield partial_text
+
+
+demo = gr.ChatInterface(
+    fn=chat,
+    examples=[["write me a poem about machine Learning"]],
+    additional_inputs_accordion=gr.Accordion(
+        label="⚙️ Parameters", open=False, render=False
+    ),
+    additional_inputs=[
+        gr.Slider(
+            minimum=0, maximum=1, step=0.1, value=0.9, label="Temperature", render=False
+        ),
+        gr.Checkbox(label="Sampling", value=True),
+        gr.Slider(
+            minimum=128,
+            maximum=4096,
+            step=1,
+            value=512,
+            label="Max new tokens",
+            render=False
+        ),
+        
+    ],
+    stop_btn="Stop Generation",
+    title="Chat with Phi3.5 ERPNext",
+    description="Noew Running antony - Phi3.5 ERPNext"
+)
+
+demo.launch()