Create app.py

app.py

@@ -0,0 +1,48 @@
+from huggingface_hub import InferenceClient
+import gradio as gr
+
+client = InferenceClient("meta-llama/Meta-Llama-3.1-8B")
+
+def format_prompt(message, history):
+    fixed_prompt= """            """
+    prompt = f"<s>{fixed_prompt}"
+    for user_prompt, bot_response in history:
+        prompt += f"\n User:{user_prompt}\n LLM Response:{bot_response}"
+    prompt += f"\nUser: {message}\nLLM Response:"
+
+    return prompt
+
+def generate(
+    prompt, history, temperature=0.1, max_new_tokens=2048, top_p=0.8, repetition_penalty=1.0,
+):
+    temperature = float(temperature)
+    if temperature < 1e-2:
+        temperature = 1e-2
+    top_p = float(top_p)
+
+    generate_kwargs = dict(
+        temperature=temperature,
+        max_new_tokens=max_new_tokens,
+        top_p=top_p,
+        repetition_penalty=repetition_penalty,
+        do_sample=True,
+        seed=42,
+    )
+
+    formatted_prompt = format_prompt(prompt, history)
+
+    stream = client.text_generation(formatted_prompt, **generate_kwargs, stream=True, details=True, return_full_text=False)
+   
+    yield stream
+
+
+
+demo = gr.ChatInterface (fn=generate, 
+                        title="Mood-Based Music Recommender",
+                        retry_btn=None,
+                        undo_btn=None,
+                        clear_btn=None,
+                        description="<span style='font-size: larger; font-weight: bold;'>Hi! I'm your music buddy—tell me about your mood and the type of tunes you're in the mood for today!</span>",
+                       )
+
+demo.queue().launch()