Create app.py

app.py

@@ -0,0 +1,30 @@
+import gradio as gr
+from llama_cpp import Llama
+
+llm = Llama(model_path="model.gguf", n_ctx=4000, n_threads=2, chat_format="chatml")
+  
+def generate(message, history,temperature=0.3,max_tokens=512):
+    system_prompt = "You are OpenChat, an userful AI assistant."
+    formatted_prompt = [{"role": "system", "content": system_prompt}]
+    for user_prompt, bot_response  in history:
+        formatted_prompt.append({"role": "user", "content": user_prompt})
+        formatted_prompt.append({"role": "assistant", "content": bot_response })
+    formatted_prompt.append({"role": "user", "content": message})
+    stream_response = llm.create_chat_completion(messages=formatted_prompt, temperature=temperature, max_tokens=max_tokens, stream=True)
+    response  = ""
+    for chunk in stream_response:
+        if len(chunk['choices'][0]["delta"]) != 0 and "content" in chunk['choices'][0]["delta"]:
+            response  += chunk['choices'][0]["delta"]["content"]
+        yield response 
+
+mychatbot = gr.Chatbot(
+avatar_images=["user.png", "botoc.png"], bubble_full_width=False, show_label=False, show_copy_button=True, likeable=True,)
+        
+iface = gr.ChatInterface(fn=generate, chatbot=mychatbot, retry_btn=None, undo_btn=None)
+
+with gr.Blocks() as demo:
+    gr.HTML("<center><h1>Tomoniai's Chat with OpenChat-3.5</h1></center>")
+    iface.render()
+
+demo.queue().launch(show_api=False, server_name="0.0.0.0")
+