Update app.py

app.py

@@ -917,7 +917,7 @@ def respond(
     top_p: float,
 ) -> str:
     """
-    Generates a response using the Mistral model based on the user's message and history.
+    Generates a response using the google/flan-t5-xl model based on the user's message and history.
     Additionally, handles dynamic commands to interact with individual components.
     """
     if chat_pipeline is None:
@@ -1165,15 +1165,15 @@ def display_historical_data(storage_location: str, url: str):
         logging.error(f"Error fetching historical data for {url}: {e}")
         return pd.DataFrame()
 
-# Function to load the Mistral model
+# Function to load the "google/flan-t5-xl" model
 def load_model():
     """
-    Loads the Mistral model and tokenizer once and returns the pipeline.
+    Loads the FlanT5XL model and tokenizer once and returns the pipeline.
     """
-    model_name = "mistralai/Mixtral-8x7B-Instruct-v0.1"
+    model_name = "google/flan-t5-xl"
     try:
         # Load tokenizer with warning suppression
-        tokenizer = AutoTokenizer.from_pretrained("T5Config", clean_up_tokenization_spaces=True)
+        tokenizer = "google/flan-t5-xl", clean_up_tokenization_spaces=True)
 
         model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
         pipe = pipeline(
@@ -1185,7 +1185,7 @@ def load_model():
         logging.info("Model loaded successfully.")
         return pipe
     except Exception as e:
-        logging.error(f"Error loading Mistral model: {e}")
+        logging.error(f"Error loading google/flan-t5-xl model: {e}")
         return None
 
 # Load the model once at the start