Update app.py

app.py

@@ -2,7 +2,18 @@ from langchain_community.document_loaders import PyPDFLoader
 import gradio as gr
 from langchain.chains.summarize import load_summarize_chain
 from huggingface_hub import InferenceClient
-TEXT_MODEL_NAME = "google/gemma-3-270m"
+# Use a pipeline as a high-level helper
+from transformers import pipeline
+
+pipe = pipeline("summarization", model="facebook/bart-large-cnn")
+
+# Load model directly
+from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
+
+tokenizer = AutoTokenizer.from_pretrained("facebook/bart-large-cnn")
+model = AutoModelForSeq2SeqLM.from_pretrained("facebook/bart-large-cnn")
+
+#TEXT_MODEL_NAME = "google/gemma-3-270m"
 loader = PyPDFLoader("http://arxiv.org/pdf/2508.13246v1") 
 documents = loader.load()
 #llm = OpenAI(temperature=0)
@@ -10,7 +21,7 @@ documents = loader.load()
 def summarize_pdf (pdf_file_path, custom_prompt=""):
     loader = PyPDFLoader(pdf_file_path)
     docs = loader.load_and_split()
-    chain = load_summarize_chain(TEXT_MODEL_NAME, chain_type="map_reduce")
+    chain = load_summarize_chain(model, chain_type="map_reduce")
     summary = chain.run(docs)
     
     return summary