Upload compare_gradio.py

compare_gradio.py

@@ -1,15 +1,16 @@
+import datetime
 import json
 import logging
 import os
+import random
 import threading
 import time
 import uuid
-import datetime
+from functools import partial
+
 import gradio as gr
 import huggingface_hub
 import requests
-import random
-from functools import partial
 
 logging.basicConfig(level=logging.INFO)
 logger = logging.getLogger(__name__)
@@ -20,7 +21,7 @@ API_URL = os.getenv("API_URL")
 API_KEY = os.getenv("API_KEY")
 
 auth_token = os.environ.get("TOKEN") or True
-hf_repo = "Iker/Feedback_FactCheking"
+hf_repo = "Iker/Feedback_FactCheking_cohere"
 huggingface_hub.create_repo(
     repo_id=hf_repo,
     repo_type="dataset",
@@ -34,15 +35,13 @@ headers = {"X-API-Key": API_KEY, "Content-Type": "application/json"}
 
 
 def update_models():
+    models = ["pro", "pro-cohere-embeddings", "pro-cohere-reranker"]
 
-    models_pro = ["pro", "pro2", "pro2-fast"]
-    models_turbo = ["turbo", "turbo2", "turbo2-fast"]
-    
     # Randomly select if we want to use pro or turbo models
-    if random.random() < 0.5:
-        models = models_pro
-    else:
-        models = models_turbo
+    # if random.random() < 0.5:
+    #    models = models_pro
+    # else:
+    #    models = models_turbo
 
     # Randomly select two models
     models = random.sample(models, 2)