Update app.py

app.py

@@ -1,40 +1,7 @@
-import gradio as gr
-import requests
-from datasets import load_dataset
-from dotenv import load_dotenv
-import os
+from huggingface_hub import InferenceClient
 
-load_dotenv()
-HUGGINGFACE_TOKEN = os.getenv('HUGGINGFACE_TOKEN')
-
-ds = load_dataset("fka/awesome-chatgpt-prompts")
-
-# Hugging Face API configuration
-API_URL = "https://api-inference.huggingface.co/models/mistralai/Mistral-7B-Instruct-v0.3"
-HEADERS = {"Authorization": f"Bearer {HUGGINGFACE_TOKEN}"}
-
-# Function to interact with the Hugging Face model
-def query_huggingface_api(input_text):
-    payload = {"inputs": input_text}
-    try:
-        response = requests.post(API_URL, headers=HEADERS, json=payload)
-        response.raise_for_status()  # Raise error for HTTP errors
-        return response.json()[0]["generated_text"]
-    except requests.exceptions.RequestException as e:
-        return f"Error: {str(e)}"
-
-# Gradio interface
-def chatbot(input_text):
-    response = query_huggingface_api(input_text)
-    return response
-
-iface = gr.Interface(
-    fn=chatbot,
-    inputs=gr.Textbox(lines=2, placeholder="Type your message here..."),
-    outputs=gr.Textbox(),
-    title="AI Chatbot",
-    description="Chat with the AI powered by Hugging Face Mistral-7B-Instruct-v0.3.",
+client = InferenceClient(
+    model="mistralai/Mistral-7B-Instruct-v0.3",
+    token="your_actual_token_here"  # Replace with the actual token temporarily
 )
-
-if __name__ == "__main__":
-    iface.launch()
+print(client.text_generation(prompt="Hello"))