fix: insert in vector db passes only last chunk meta_data (#3363)

## Summary

insert in vector db passes only last chunk meta_data
Issue-
https://discord.com/channels/965734768803192842/1219054452221153463/1376631140047130649

(If applicable, issue number: #____)

## Type of change

- [x] Bug fix
- [ ] New feature
- [ ] Breaking change
- [ ] Improvement
- [ ] Model update
- [ ] Other:

---

## Checklist

- [x] Code complies with style guidelines
- [x] Ran format/validation scripts (`./scripts/format.sh` and
`./scripts/validate.sh`)
- [x] Self-review completed
- [ ] Documentation updated (comments, docstrings)
- [ ] Examples and guides: Relevant cookbook examples have been included
or updated (if applicable)
- [x] Tested in clean environment
- [ ] Tests added/updated (if applicable)

---

## Additional Notes

Add any important context (deployment instructions, screenshots,
security considerations, etc.)

Author: kausmeows

libs/agno/agno/knowledge/agent.py

@@ -123,7 +123,8 @@ def load(
 
             # Upsert documents if upsert is True and vector db supports upsert
             if upsert and self.vector_db.upsert_available():
-                self.vector_db.upsert(documents=document_list, filters=doc.meta_data)
+                for doc in document_list:
+                    self.vector_db.upsert(documents=[doc], filters=doc.meta_data)
             # Insert documents
             else:
                 # Filter out documents which already exist in the vector db
@@ -132,7 +133,8 @@ def load(
                     documents_to_load = self.filter_existing_documents(document_list)
 
                 if documents_to_load:
-                    self.vector_db.insert(documents=documents_to_load, filters=doc.meta_data)
+                    for doc in documents_to_load:
+                        self.vector_db.insert(documents=[doc], filters=doc.meta_data)
 
             num_documents += len(documents_to_load)
             log_info(f"Added {len(documents_to_load)} documents to knowledge base")
@@ -174,7 +176,8 @@ async def aload(
 
             # Upsert documents if upsert is True and vector db supports upsert
             if upsert and self.vector_db.upsert_available():
-                await self.vector_db.async_upsert(documents=document_list, filters=doc.meta_data)
+                for doc in document_list:
+                    await self.vector_db.async_upsert(documents=[doc], filters=doc.meta_data)
             # Insert documents
             else:
                 # Filter out documents which already exist in the vector db
@@ -183,7 +186,8 @@ async def aload(
                     documents_to_load = self.filter_existing_documents(document_list)
 
                 if documents_to_load:
-                    await self.vector_db.async_insert(documents=documents_to_load, filters=doc.meta_data)
+                    for doc in documents_to_load:
+                        await self.vector_db.async_insert(documents=[doc], filters=doc.meta_data)
 
             num_documents += len(documents_to_load)
             log_info(f"Added {len(documents_to_load)} documents to knowledge base")