Update app.py

Added
# We add 'collection_name' with a random ID (uuid)
# This forces Chroma to create a brand new, empty bucket for every PDF
vectordb = Chroma.from_documents(
documents=chunks,
embedding=embedding_model,
collection_name=f"pdf_chat_{uuid.uuid4().hex}"
)

app.py

@@ -118,7 +118,13 @@ def vector_database(chunks):
         if c.page_content and c.page_content.strip() and len(c.page_content.strip()) > 10
     ]
     embedding_model = watsonx_embedding()
-    vectordb = Chroma.from_documents(chunks, embedding_model)
+    # We add 'collection_name' with a random ID (uuid)
+    # This forces Chroma to create a brand new, empty bucket for every PDF
+    vectordb = Chroma.from_documents(
+        documents=chunks, 
+        embedding=embedding_model,
+        collection_name=f"pdf_chat_{uuid.uuid4().hex}" 
+    )
     return vectordb
     
 ## Retriever