Update src/streamlit_app.py

src/streamlit_app.py

@@ -34,12 +34,13 @@ nltk.download('punkt_tab', download_dir=nltk_data_dir, quiet=True)
 
 # Load models
 # summarizer = pipeline("summarization", model="sshleifer/distilbart-cnn-12-6", device=torch.device("cpu"))
-summarizer = pipeline(
-    "summarization",
-    model="sshleifer/distilbart-cnn-12-6",
-    from_flax=True,
-    device=-1  # CPU mode, use device=0 for GPU
-)
+# summarizer = pipeline(
+#     "summarization",
+#     model="sshleifer/distilbart-cnn-12-6",
+#     from_flax=True,
+#     device=-1  # CPU mode, use device=0 for GPU
+# )
+summarizer = pipeline("summarization", model="facebook/bart-large-cnn")
 qa_pipeline = pipeline("question-answering", model="distilbert-base-cased-distilled-squad", device=torch.device("cpu"))
 embedding_model = HuggingFaceEmbeddings(model_name="all-MiniLM-L6-v2")
 vector_dbs = {}  # Dictionary to store multiple vector databases, keyed by document title