Here are clear written examples of **metadata tagging** in both Open WebUI and Weaviate, showing how you can associate tags and structured metadata with knowledge objects for RAG and semantic search.

***

### Example: Metadata Tagging in Open WebUI

You send a document to the Open WebUI API endpoint, attaching metadata and tags in the content field as a JSON string:

```json
POST http://localhost/api/v1/documents/create
Content-Type: application/json

{
  "name": "policy_doc_2022",
  "title": "2022 Policy Handbook",
  "collection_name": "company_handbooks",
  "filename": "policy_2022.pdf",
  "content": "{\"tags\": [\"policy\", \"2022\", \"hr\"], \"source_url\": \"https://example.com/policy_2022.pdf\", \"author\": \"Jane Doe\"}"
}
```
- The `"tags"` field is a list of labels for classification (policy, 2022, hr).
- The `"source_url"` and `"author"` fields provide additional metadata useful for retrieval, audit, and filtering.[1][2]

For pipeline-based ingestion, you might design a function to extract and append metadata before vectorization:

```python
metadata = {
    "tags": ["policy", "2022"],
    "source_url": document_url,
    "author": document_author
}
embed_with_metadata(chunk, metadata)
```
This metadata becomes part of your retrieval context in RAG workflows.[1]

***

### Example: Metadata Tagging in Weaviate

In Weaviate, metadata and tags are defined directly in the schema and attached to each object when added:

**Schema definition:**

```json
{
  "class": "Document",
  "properties": [
    {"name": "title", "dataType": ["text"]},
    {"name": "tags", "dataType": ["text[]"]},
    {"name": "source_url", "dataType": ["text"]},
    {"name": "author", "dataType": ["text"]}
  ]
}
```

**Object creation example:**

```python
client.data_object.create(
    data_object={
        "title": "2022 Policy Handbook",
        "tags": ["policy", "2022", "hr"],
        "source_url": "https://example.com/policy_2022.pdf",
        "author": "Jane Doe"
    },
    class_name="Document"
)
```
- The `"tags"` field is a text array, ideal for semantic filtering and faceting.
- Other fields store provenance metadata, supporting advanced queries and data governance.[3][4][5]

**Query with metadata filtering:**

```python
result = (
    client.query
    .get("Document", ["title", "tags", "author"])
    .with_filter({"path": ["tags"], "operator": "ContainsAny", "value": ["policy", "hr"]})
    .do()
)
```
This retrieves documents classified with either "policy" or "hr" tags.[4][3]

***

Both platforms support **metadata tagging** for documents, which enables powerful RAG scenarios, detailed filtering, and context-rich retrievals.[5][2][3][4][1]

[1](https://www.reddit.com/r/OpenWebUI/comments/1hmmg9a/how_to_handle_metadata_during_vectorization/)
[2](https://github.com/open-webui/open-webui/discussions/4692)
[3](https://stackoverflow.com/questions/75006703/query-large-list-of-metadate-in-weaviate)
[4](https://weaviate.io/blog/enterprise-workflow-langchain-weaviate)
[5](https://docs.weaviate.io/academy/py/zero_to_mvp/schema_and_imports/schema)
[6](https://docs.weaviate.io/weaviate/api/graphql/additional-properties)
[7](https://weaviate.io/blog/sycamore-and-weaviate)
[8](https://docs.llamaindex.ai/en/stable/examples/vector_stores/WeaviateIndex_auto_retriever/)
[9](https://forum.weaviate.io/t/recommendations-for-metadata-or-knowledge-graphs/960)
[10](https://weaviate.io/blog/agent-workflow-automation-n8n-weaviate)
[11](https://github.com/open-webui/open-webui/discussions/9804)
[12](https://docs.quarkiverse.io/quarkus-langchain4j/dev/rag-weaviate.html)
[13](https://github.com/weaviate/weaviate-examples)
[14](https://docs.openwebui.com/getting-started/api-endpoints/)
[15](https://weaviate.io/blog/hybrid-search-for-web-developers)
[16](https://dev.to/stephenc222/how-to-use-weaviate-to-store-and-query-vector-embeddings-4b9b)
[17](https://helpdesk.egnyte.com/hc/en-us/articles/360035813612-Using-Metadata-in-the-WebUI)
[18](https://docs.datadoghq.com/integrations/weaviate/)
[19](https://docs.openwebui.com/features/)
[20](https://documentation.suse.com/suse-ai/1.0/html/openwebui-configuring/index.html)
[21](https://docs.openwebui.com/getting-started/env-configuration/)