Update src/streamlit_app.py

src/streamlit_app.py

@@ -35,8 +35,11 @@ import torch  # Import torch
 # # Load models
 
 # 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")
+summarizer = pipeline("summarization", model="google/pegasus-xsum")
+# qa_pipeline = pipeline("question-answering", model="distilbert-base-cased-distilled-squad", device=torch.device("cpu"))
+qa_pipeline = pipeline("question-answering", model="deepset/tinyroberta-squad2", 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
 extracted_texts = {} # Dictionary to store extracted text, keyed by document title
 current_doc_title = None