Delete app.py

app.py

@@ -1,73 +0,0 @@
-#refer llama recipes for more info https://github.com/huggingface/huggingface-llama-recipes/blob/main/inference-api.ipynb
-#huggingface-llama-recipes : https://github.com/huggingface/huggingface-llama-recipes/tree/main
-import gradio as gr
-from openai import OpenAI
-import os
-
-css = '''
-.gradio-container{max-width: 1000px !important}
-h1{text-align:center}
-footer {
-    visibility: hidden
-}
-'''
-
-ACCESS_TOKEN = os.getenv("HF_TOKEN")
-
-client = OpenAI(
-    base_url="https://api-inference.huggingface.co/v1/",
-    api_key=ACCESS_TOKEN,
-)
-
-def respond(
-    message,
-    history: list[tuple[str, str]],
-    system_message,
-    max_tokens,
-    temperature,
-    top_p,
-):
-    messages = [{"role": "system", "content": system_message}]
-
-    for val in history:
-        if val[0]:
-            messages.append({"role": "user", "content": val[0]})
-        if val[1]:
-            messages.append({"role": "assistant", "content": val[1]})
-
-    messages.append({"role": "user", "content": message})
-
-    response = ""
-    
-    for message in  client.chat.completions.create(
-        model="meta-llama/Meta-Llama-3.1-8B-Instruct",
-        max_tokens=max_tokens,
-        stream=True,
-        temperature=temperature,
-        top_p=top_p,
-        messages=messages,
-    ):
-        token = message.choices[0].delta.content
-        
-        response += token
-        yield response
-
-demo = gr.ChatInterface(
-    respond,
-    additional_inputs=[
-        gr.Textbox(value="", label="System message"),
-        gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
-        gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
-        gr.Slider(
-            minimum=0.1,
-            maximum=1.0,
-            value=0.95,
-            step=0.05,
-            label="Top-P",
-        ),
-        
-    ],
-    css=css
-)
-if __name__ == "__main__":
-    demo.launch()