feat: add tokenizer model and summarization model

app.py

@@ -16,15 +16,16 @@ logging.basicConfig(level=logging.INFO)
 DATA_DIR = "/data" if os.path.exists("/data") else "."
 DATASET_DIR = os.path.join(DATA_DIR, "rag_dataset")
 DATASET_PATH = os.path.join(DATASET_DIR, "dataset")
-MODEL_PATH = "deepseek-ai/DeepSeek-R1-Distill-Llama-8B"  # Using flan-t5-small for better performance
+TOKENIZER_MODEL = "google/flan-t5-small"
+SUMMARIZATION_MODEL= "Falconsai/text_summarization"
 
 @st.cache_resource
 def load_local_model():
     """Load the local Hugging Face model"""
     try:
-        tokenizer = AutoTokenizer.from_pretrained(MODEL_PATH)
+        tokenizer = AutoTokenizer.from_pretrained(TOKENIZER_MODEL)
         model = T5ForConditionalGeneration.from_pretrained(
-            MODEL_PATH,
+            SUMMARIZATION_MODEL,
             device_map={"": "cpu"},  # Force CPU
             torch_dtype=torch.float32
         )