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docs: add examples for how to define RAG docs (#1981)

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# What does this PR do?
Add examples for how to define RAGDocuments. Not sure if this is the
best place for these docs. @raghotham Please advise

## Test Plan
None, documentation

[//]: # (## Documentation)

Signed-off-by: Kevin <kpostlet@redhat.com>
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Kevin Postlethwait 2025-04-23 09:39:18 -04:00 • committed by GitHub
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38
docs/source/building_applications/rag.md
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@ -68,7 +68,8 @@ chunks_response = client.vector_io.query(
### Using the RAG Tool
A better way to ingest documents is to use the RAG Tool. This tool allows you to ingest documents from URLs, files, etc.
and automatically chunks them into smaller pieces.
and automatically chunks them into smaller pieces. More examples for how to format a RAGDocument can be found in the
[appendix](#more-ragdocument-examples).
```python
from llama_stack_client import RAGDocument
@ -178,3 +179,38 @@ for vector_db_id in client.vector_dbs.list():
print(f"Unregistering vector database: {vector_db_id.identifier}")
client.vector_dbs.unregister(vector_db_id=vector_db_id.identifier)
```
### Appendix
#### More RAGDocument Examples
```python
from llama_stack_client import RAGDocument
import base64
RAGDocument(document_id="num-0", content={"uri": "file://path/to/file"})
RAGDocument(document_id="num-1", content="plain text")
RAGDocument(
document_id="num-2",
content={
"type": "text",
"text": "plain text input",
}, # for inputs that should be treated as text explicitly
)
RAGDocument(
document_id="num-3",
content={
"type": "image",
"image": {"url": {"uri": "https://mywebsite.com/image.jpg"}},
},
)
B64_ENCODED_IMAGE = base64.b64encode(
requests.get(
"https://raw.githubusercontent.com/meta-llama/llama-stack/refs/heads/main/docs/_static/llama-stack.png"
).content
)
RAGDocuemnt(
document_id="num-4",
content={"type": "image", "image": {"data": B64_ENCODED_IMAGE}},
)
```
for more strongly typed interaction use the typed dicts found [here](https://github.com/meta-llama/llama-stack-client-python/blob/38cd91c9e396f2be0bec1ee96a19771582ba6f17/src/llama_stack_client/types/shared_params/document.py).