back to mistral model

app.py

@@ -4,12 +4,15 @@ import requests
 import inspect
 import pandas as pd
 import traceback
+from huggingface_hub import login
 from tools import create_memory_safe_workflow, get_file_type, write_bytes_to_temp_dir, AgentState, extract_final_answer, run_agent
 
 # (Keep Constants as is)
 # --- Constants ---
 DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
 
+# login(token=os.environ["HF_TOKEN"])
+
 # --- Basic Agent Definition ---
 # ----- THIS IS WERE YOU CAN BUILD WHAT YOU WANT ------
 #class BasicAgent:

tools.py

@@ -66,10 +66,10 @@ logger = logging.getLogger(__name__)
 
 # --- Model Configuration ---
 def create_llm_pipeline():
-    model_id = "meta-llama/Llama-2-13b-chat-hf"
+    #model_id = "meta-llama/Llama-2-13b-chat-hf"
     #model_id = "meta-llama/Llama-3.3-70B-Instruct"
     #model_id = "mistralai/Mistral-Small-24B-Base-2501"
-    #model_id = "mistralai/Mistral-7B-Instruct-v0.3"
+    model_id = "mistralai/Mistral-7B-Instruct-v0.3"
     #model_id = "Qwen/Qwen2-7B-Instruct"
     return pipeline(
         "text-generation",