We desperately need to document our APIs. This is the basic requirement
of having a Spec :)
This PR updates the OpenAPI generator so documentation for request
parameters and object fields can be properly added to the OpenAPI specs.
From there, this should get picked by Stainless, etc.
## Test Plan:
Updated client-sdk (See
https://github.com/meta-llama/llama-stack-client-python/pull/104) and
then ran:
```bash
cd tests/client-sdk
LLAMA_STACK_CONFIG=../../llama_stack/templates/fireworks/run.yaml pytest -s -v inference/test_inference.py agents/test_agents.py
```
# What does this PR do?
PR fixes couple of issues with telemetry:
1) The REST refactor changed the method from get_span_tree to
query_span_tree, which is causing the server side to return empty spans
2) Library client has introduced a new event loop, which required
changing the location of where start and end trace are called
## Test Plan
LLAMA_STACK_CONFIG="/Users/dineshyv/.llama/distributions/llamastack-fireworks/fireworks-run.yaml"
pytest -v tests/client-sdk/agents/test_agents.py -k
"test_builtin_tool_web_search"
And querying for spans from the agent run using the library client.
# What does this PR do?
Library client needs to match the impl based on both the path and
method. Since path is no longer static, this PR uses the inefficient way
of using regexes computed based on the annotated route path to match
against the incoming request path. The variables now also can come to
the impl from both path or the body, which is also handled cleanly by
finding all the regex matches.
## Test Plan
LLAMA_STACK_CONFIG="/Users/dineshyv/.llama/distributions/llamastack-together/together-run.yaml"
pytest -v tests/client-sdk/agents/test_agents.py
# What does this PR do?
#### Issue
- Using Jupyter notebook with LlamaStackAsLibraryClient + streaming
gives exception
```
Exception ignored in: <async_generator object HTTP11ConnectionByteStream.__aiter__ at 0x32a95a740>
Traceback (most recent call last):
File "/opt/anaconda3/envs/fresh/lib/python3.11/site-packages/httpcore/_async/connection_pool.py", line 404, in _aiter_
yield part
RuntimeError: async generator ignored GeneratorExit
```
- Reproduce w/
https://github.com/meta-llama/llama-stack/blob/notebook-streaming-debug/inline.ipynb
#### Fix
- Issue likely comes from stream_across_asyncio_run_boundary closing
connection too soon when interacting in jupyter environment
- This uses an alternative way to convert AsyncStream to SyncStream
return type by sync version of LlamaStackAsLibraryClient, which calls
AsyncLlamaStackAsLibraryClient calling async impls under the hood
#### Additional changes
- Moved tracing logic into AsyncLlamaStackAsLibraryClient.request s.t.
streaming / non-streaming request for LlamaStackAsLibraryClient shares
same code
## Test Plan
- Test w/ together & fireworks & ollama with streaming and non-streaming
using notebook in:
https://github.com/meta-llama/llama-stack/blob/notebook-streaming-debug/inline.ipynb
- Note: need to restart kernel and run pip install -e . in jupyter
interpreter for local code change to take effect
<img width="826" alt="image"
src="https://github.com/user-attachments/assets/5f90985d-1aee-452c-a599-2157f5654fea"
/>
## Sources
Please link relevant resources if necessary.
## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the
other checks if that's the case).
- [ ] Ran pre-commit to handle lint / formatting issues.
- [ ] Read the [contributor
guideline](https://github.com/meta-llama/llama-stack/blob/main/CONTRIBUTING.md),
Pull Request section?
- [ ] Updated relevant documentation.
- [ ] Wrote necessary unit or integration tests.
# What does this PR do?
This PR adds the provider data passing for the library client and
changes the provider's api keys be unique
## Test Plan
LLAMA_STACK_CONFIG="/Users/dineshyv/.llama/distributions/llamastack-fireworks/fireworks-run.yaml"
pytest -v tests/client-sdk/agents/test_agents.py
run.yaml:
https://gist.github.com/dineshyv/0c10b5c7d0a2fb7ba4f0ecc8dcf860d1
# What does this PR do?
PR #639 introduced the notion of Tools API and ability to invoke tools
through API just as any resource. This PR changes the Agents to start
using the Tools API to invoke tools. Major changes include:
1) Ability to specify tool groups with AgentConfig
2) Agent gets the corresponding tool definitions for the specified tools
and pass along to the model
3) Attachements are now named as Documents and their behavior is mostly
unchanged from user perspective
4) You can specify args that can be injected to a tool call through
Agent config. This is especially useful in case of memory tool, where
you want the tool to operate on a specific memory bank.
5) You can also register tool groups with args, which lets the agent
inject these as well into the tool call.
6) All tests have been migrated to use new tools API and fixtures
including client SDK tests
7) Telemetry just works with tools API because of our trace protocol
decorator
## Test Plan
```
pytest -s -v -k fireworks llama_stack/providers/tests/agents/test_agents.py \
--safety-shield=meta-llama/Llama-Guard-3-8B \
--inference-model=meta-llama/Llama-3.1-8B-Instruct
pytest -s -v -k together llama_stack/providers/tests/tools/test_tools.py \
--safety-shield=meta-llama/Llama-Guard-3-8B \
--inference-model=meta-llama/Llama-3.1-8B-Instruct
LLAMA_STACK_CONFIG="/Users/dineshyv/.llama/distributions/llamastack-together/together-run.yaml" pytest -v tests/client-sdk/agents/test_agents.py
```
run.yaml:
https://gist.github.com/dineshyv/0365845ad325e1c2cab755788ccc5994
Notebook:
https://colab.research.google.com/drive/1ck7hXQxRl6UvT-ijNRZ-gMZxH1G3cN2d?usp=sharing
## What does this PR do?
This is a long-pending change and particularly important to get done
now.
Specifically:
- we cannot "localize" (aka download) any URLs from media attachments
anywhere near our modeling code. it must be done within llama-stack.
- `PIL.Image` is infesting all our APIs via `ImageMedia ->
InterleavedTextMedia` and that cannot be right at all. Anything in the
API surface must be "naturally serializable". We need a standard `{
type: "image", image_url: "<...>" }` which is more extensible
- `UserMessage`, `SystemMessage`, etc. are moved completely to
llama-stack from the llama-models repository.
See https://github.com/meta-llama/llama-models/pull/244 for the
corresponding PR in llama-models.
## Test Plan
```bash
cd llama_stack/providers/tests
pytest -s -v -k "fireworks or ollama or together" inference/test_vision_inference.py
pytest -s -v -k "(fireworks or ollama or together) and llama_3b" inference/test_text_inference.py
pytest -s -v -k chroma memory/test_memory.py \
--env EMBEDDING_DIMENSION=384 --env CHROMA_DB_PATH=/tmp/foobar
pytest -s -v -k fireworks agents/test_agents.py \
--safety-shield=meta-llama/Llama-Guard-3-8B \
--inference-model=meta-llama/Llama-3.1-8B-Instruct
```
Updated the client sdk (see PR ...), installed the SDK in the same
environment and then ran the SDK tests:
```bash
cd tests/client-sdk
LLAMA_STACK_CONFIG=together pytest -s -v agents/test_agents.py
LLAMA_STACK_CONFIG=ollama pytest -s -v memory/test_memory.py
# this one needed a bit of hacking in the run.yaml to ensure I could register the vision model correctly
INFERENCE_MODEL=llama3.2-vision:latest LLAMA_STACK_CONFIG=ollama pytest -s -v inference/test_inference.py
```
Library client used _server_ side types which was no bueno. The fix here
is not the completely correct fix but it is good for enough and for the
demo notebook.
This PR does a few things:
- it moves "direct client" to llama-stack repo instead of being in the
llama-stack-client-python repo
- renames it to `LlamaStackLibraryClient`
- actually makes synchronous generators work
- makes streaming and non-streaming work properly
In many ways, this PR makes things finally "work"
## Test Plan
See a `library_client_test.py` I added. This isn't really quite a test
yet but it demonstrates that this mode now works. Here's the invocation
and the response:
```
INFERENCE_MODEL=meta-llama/Llama-3.2-3B-Instruct python llama_stack/distribution/tests/library_client_test.py ollama
```
