# What does this PR do?
Catches docs up to source with:
```
python llama_stack/scripts/distro_codegen.py
```
[//]: # (If resolving an issue, uncomment and update the line below)
[//]: # (Closes #[issue-number])
## Test Plan
[Describe the tests you ran to verify your changes with result
summaries. *Provide clear instructions so the plan can be easily
re-executed.*]
Manually checked
```
sphinx-autobuild docs/source build/html
```
[//]: # (## Documentation)
[//]: # (- [ ] Added a Changelog entry if the change is significant)
Lint check in main branch is failing. This fixes the lint check after we
moved to ruff in https://github.com/meta-llama/llama-stack/pull/921. We
need to move to a `ruff.toml` file as well as fixing and ignoring some
additional checks.
Signed-off-by: Yuan Tang <terrytangyuan@gmail.com>
## What does this PR do?
See issue: #747 -- `uv` is just plain better. This PR does the bare
minimum of replacing `pip install` by `uv pip install` and ensuring `uv`
exists in the environment.
## Test Plan
First: create new conda, `uv pip install -e .` on `llama-stack` -- all
is good.
Next: run `llama stack build --template together` followed by `llama
stack run together` -- all good
Next: run `llama stack build --template together --image-name yoyo`
followed by `llama stack run together --image-name yoyo` -- all good
Next: fresh conda and `uv pip install -e .` and `llama stack build
--template together --image-type venv` -- all good.
Docker: `llama stack build --template together --image-type container`
works!
See https://github.com/meta-llama/llama-stack/issues/827 for the broader
design.
Third part:
- we need to make `tool_runtime.rag_tool.query_context()` and
`tool_runtime.rag_tool.insert_documents()` methods work smoothly with
complete type safety. To that end, we introduce a sub-resource path
`tool-runtime/rag-tool/` and make changes to the resolver to make things
work.
- the PR updates the agents implementation to directly call these typed
APIs for memory accesses rather than going through the complex, untyped
"invoke_tool" API. the code looks much nicer and simpler (expectedly.)
- there are a number of hacks in the server resolver implementation
still, we will live with some and fix some
Note that we must make sure the client SDKs are able to handle this
subresource complexity also. Stainless has support for subresources, so
this should be possible but beware.
## Test Plan
Our RAG test is sad (doesn't actually test for actual RAG output) but I
verified that the implementation works. I will work on fixing the RAG
test afterwards.
```bash
pytest -s -v tests/agents/test_agents.py -k "rag and together" --safety-shield=meta-llama/Llama-Guard-3-8B
```
# What does this PR do?
Automatically generates
- build.yaml
- run.yaml
- run-with-safety.yaml
- parts of markdown docs
for the distributions.
## Test Plan
At this point, this only updates the YAMLs and the docs. Some testing
(especially with ollama and vllm) has been performed but needs to be
much more tested.
