diff --git a/litellm/llms/s3_vectors/vector_stores/transformation.py b/litellm/llms/s3_vectors/vector_stores/transformation.py
index c8cad00b10e..829e8caae1a 100644
--- a/litellm/llms/s3_vectors/vector_stores/transformation.py
+++ b/litellm/llms/s3_vectors/vector_stores/transformation.py
@@ -81,16 +81,20 @@ class S3VectorsVectorStoreConfig(BaseVectorStoreConfig, BaseAWSLLM):
         """Sync version - generates embedding synchronously."""
         # For S3 Vectors, vector_store_id should be in format: bucket_name:index_name
         # If not in that format, try to construct it from litellm_params
+        bucket_name: str
+        index_name: str
+        
         if ":" in vector_store_id:
             bucket_name, index_name = vector_store_id.split(":", 1)
         else:
             # Try to get bucket_name from litellm_params
-            bucket_name = litellm_params.get("vector_bucket_name")
-            if not bucket_name:
+            bucket_name_from_params = litellm_params.get("vector_bucket_name")
+            if not bucket_name_from_params or not isinstance(bucket_name_from_params, str):
                 raise ValueError(
                     "vector_store_id must be in format 'bucket_name:index_name' for S3 Vectors, "
                     "or vector_bucket_name must be provided in litellm_params"
                 )
+            bucket_name = bucket_name_from_params
             index_name = vector_store_id
 
         if isinstance(query, list):
@@ -129,16 +133,20 @@ class S3VectorsVectorStoreConfig(BaseVectorStoreConfig, BaseAWSLLM):
         """Async version - generates embedding asynchronously."""
         # For S3 Vectors, vector_store_id should be in format: bucket_name:index_name
         # If not in that format, try to construct it from litellm_params
+        bucket_name: str
+        index_name: str
+        
         if ":" in vector_store_id:
             bucket_name, index_name = vector_store_id.split(":", 1)
         else:
             # Try to get bucket_name from litellm_params
-            bucket_name = litellm_params.get("vector_bucket_name")
-            if not bucket_name:
+            bucket_name_from_params = litellm_params.get("vector_bucket_name")
+            if not bucket_name_from_params or not isinstance(bucket_name_from_params, str):
                 raise ValueError(
                     "vector_store_id must be in format 'bucket_name:index_name' for S3 Vectors, "
                     "or vector_bucket_name must be provided in litellm_params"
                 )
+            bucket_name = bucket_name_from_params
             index_name = vector_store_id
 
         if isinstance(query, list):
diff --git a/litellm/rag/ingestion/file_parsers/pdf_parser.py b/litellm/rag/ingestion/file_parsers/pdf_parser.py
index fda77270df9..9a533ccf138 100644
--- a/litellm/rag/ingestion/file_parsers/pdf_parser.py
+++ b/litellm/rag/ingestion/file_parsers/pdf_parser.py
@@ -20,14 +20,14 @@ def extract_text_from_pdf(file_content: bytes) -> Optional[str]:
         Extracted text or None if extraction fails
     """
     try:
+        from io import BytesIO
+
         # Try pypdf first (most common)
         try:
-            from io import BytesIO
-
-            from pypdf import PdfReader
+            from pypdf import PdfReader as PypdfReader
             
             pdf_file = BytesIO(file_content)
-            reader = PdfReader(pdf_file)
+            reader = PypdfReader(pdf_file)
             
             text_parts = []
             for page in reader.pages:
@@ -45,12 +45,10 @@ def extract_text_from_pdf(file_content: bytes) -> Optional[str]:
             
         # Fallback to PyPDF2
         try:
-            from io import BytesIO
-
-            from PyPDF2 import PdfReader
+            from PyPDF2 import PdfReader as PyPDF2Reader
             
             pdf_file = BytesIO(file_content)
-            reader = PdfReader(pdf_file)
+            reader = PyPDF2Reader(pdf_file)
             
             text_parts = []
             for page in reader.pages:
diff --git a/litellm/rag/ingestion/s3_vectors_ingestion.py b/litellm/rag/ingestion/s3_vectors_ingestion.py
index 2a938e47554..e6c166a1015 100644
--- a/litellm/rag/ingestion/s3_vectors_ingestion.py
+++ b/litellm/rag/ingestion/s3_vectors_ingestion.py
@@ -483,18 +483,21 @@ class S3VectorsRAGIngestion(BaseRAGIngestion, BaseAWSLLM):
         # Prepare vectors for PutVectors API
         vectors = []
         for i, (chunk, embedding) in enumerate(zip(chunks, embeddings)):
+            # Build metadata dict
+            metadata: Dict[str, str] = {
+                "source_text": chunk,  # Non-filterable (for reference)
+                "chunk_index": str(i),  # Filterable
+            }
+            
+            if filename:
+                metadata["filename"] = filename  # Filterable
+            
             vector_obj = {
                 "key": f"{filename}_{i}" if filename else f"chunk_{i}",
                 "data": {"float32": embedding},
-                "metadata": {
-                    "source_text": chunk,  # Non-filterable (for reference)
-                    "chunk_index": str(i),  # Filterable
-                },
+                "metadata": metadata,
             }
 
-            if filename:
-                vector_obj["metadata"]["filename"] = filename  # Filterable
-
             vectors.append(vector_obj)
 
         # Call PutVectors API