Update app.py

app.py

@@ -13,9 +13,9 @@ from selenium.webdriver.support.ui import WebDriverWait
 from selenium.webdriver.support import expected_conditions as EC
 from selenium.webdriver.common.keys import Keys
 from selenium.common.exceptions import NoSuchElementException
-from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
-from transformers import pipeline
+import requests
 import feedparser
+import gradio as gr
 
 # Configure logging
 logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
@@ -111,11 +111,14 @@ def display_csv(url):
 
 # Define the chat response function using the Mistral model
 def respond(message, history, system_message, max_tokens, temperature, top_p):
-    model = AutoModelForSeq2SeqLM.from_pretrained_model("mistralai/Mixtral-8x7B-Instruct-v0.1")
-    tokenizer = AutoTokenizer.from_pretrained_model("mistralai/Mixtral-8x7B-Instruct-v0.1")
-    pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)
-    response = pipe(f"User: {message}\nHistory: {history}\nSystem: {system_message}", max_length=max_tokens, temperature=temperature, top_p=top_p)[0]
-    return response
+    API_URL = "https://api-inference.huggingface.co/models/mistralai/Mixtral-8x7B-Instruct-v0.1"
+    headers = {"Authorization": f"Bearer {os.getenv('HF_API_TOKEN')}"}
+    payload = {
+        "inputs": f"User: {message}\nHistory: {history}\nSystem: {system_message}",
+        "parameters": {"max_length": max_tokens, "temperature": temperature, "top_p": top_p},
+    }
+    response = requests.post(API_URL, headers=headers, json=payload)
+    return response.json()[0]["generated_text"]
 
 # Function to generate RSS feed for a given URL
 def generate_rss_feed(url):