Update app.py

app.py

@@ -1,6 +1,7 @@
 import os
 import logging
 import asyncio
+import random  # Import random for token selection
 from typing import AsyncGenerator, Tuple
 import gradio as gr
 from huggingface_hub import InferenceClient
@@ -12,8 +13,16 @@ from duckduckgo_search import DDGS
 # Configure logging
 logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
 
-# Environment variables and configurations
-huggingface_token = os.environ.get("HUGGINGFACE_TOKEN")
+# List of Hugging Face tokens
+huggingface_tokens = [
+    os.environ.get("HUGGINGFACE_TOKEN_1"),
+    os.environ.get("HUGGINGFACE_TOKEN_2"),
+    os.environ.get("HUGGINGFACE_TOKEN_3")
+]
+
+# Function to get a random Hugging Face token
+def get_random_token():
+    return random.choice(huggingface_tokens)
 
 MODELS = [
     "mistralai/Mistral-7B-Instruct-v0.3",
@@ -25,7 +34,6 @@ MODELS = [
     "google/gemma-2-27b-it"
 ]
 
-# Default system message template
 DEFAULT_SYSTEM_PROMPT = """You are a world-class financial AI assistant, capable of complex reasoning and reflection. 
 Reason through the query inside <thinking> tags, and then provide your final response inside <output> tags.
 Providing comprehensive and accurate information based on web search results is essential. 
@@ -92,7 +100,9 @@ Write a detailed and complete research document that fulfills the following user
     if history:
         messages = history + messages
 
-    client = InferenceClient(model, token=huggingface_token)
+    # Get a random token for the API call
+    token = get_random_token()
+    client = InferenceClient(model, token=token)
     full_response = ""
 
     for call in range(num_calls):