Update app.py

app.py

@@ -1,35 +1,10 @@
-import gradio as gr
-from huggingface_hub import InferenceClient
-from groq import Groq
-"""
-For more information on `huggingface_hub` Inference API support, please check the docs: https://huggingface.co/docs/huggingface_hub/v0.22.2/en/guides/inference
-"""
 import os
-os.environ['GROQ_API_KEY'] = "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"
-client = Groq()
-
-
-def respond(
-    message,
-    history: list[tuple[str, str]],
-    system_message,
-    max_tokens,
-    temperature,
-    top_p,
-):
-    messages = [{"role": "system", "content": system_message}]
+os.environ['GROQ_API_KEY'] = "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"from groq import Groq
 
-    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 = ""
+client = Groq()
 
-    for message in chat_completion = client.chat.completions.create(
+def chatbot(prompt):
+  chat_completion = client.chat.completions.create(
       messages=[
           {
               "role": "user",
@@ -38,32 +13,14 @@ def respond(
       ],
       model="llama3-8b-8192",
       stream=False,
-  ):
-        token = message.choices[0].delta.content
-
-        response += token
-        yield response
-
-
-"""
-For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
-"""
-demo = gr.ChatInterface(
-    respond,
-    additional_inputs=[
-        gr.Textbox(value="You are a friendly Chatbot.", 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 (nucleus sampling)",
-        ),
-    ],
+  )
+  return chat_completion.choices[0].message.content
+import gradio as gr
+gradio_app = gr.Interface(
+    chatbot,
+    inputs=['text'],
+    outputs=['text'],
+    title="Harsh's Chatbot",
 )
-
-
 if __name__ == "__main__":
-    demo.launch()
+    gradio_app.launch(debug=True)