# What does this PR do?
fixed report generation:
1) do not initialize a new client in report.py - instead get it from
pytest fixture
2) Add "provider" for "safety" and "agents" section
3) add logprobs functionality in "inference" section
## Test Plan
See the regenerated report
## 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?
- Fix loading SambaNovaImpl issue
- Add LlamaGuard model support for inference
## Test Plan
Run the following unit test scripts and results
### Embedding
```
pytest -s -v --providers inference=sambanova llama_stack/providers/tests/inference/test_embeddings.py --inference-model meta-llama/Llama-3.2-11B-Vision-Instruct --env SAMBANOVA_API_KEY={SAMBANOVA_API_KEY}
```
```
llama_stack/providers/tests/inference/test_embeddings.py::TestEmbeddings::test_embeddings[-sambanova] SKIPPED (This test is only applicable for embedding models)
llama_stack/providers/tests/inference/test_embeddings.py::TestEmbeddings::test_batch_embeddings[-sambanova] SKIPPED (This test is only applicable for embedding models)
=================================================================================================================== 2 skipped, 1 warning in 0.32s ===================================================================================================================
```
### Vision
```
pytest -s -v --providers inference=sambanova llama_stack/providers/tests/inference/test_vision_inference.py --inference-model meta-llama/Llama-3.2-11B-Vision-Instruct --env SAMBANOVA_API_KEY={SAMBANOVA_API_KEY}
```
```
llama_stack/providers/tests/inference/test_vision_inference.py::TestVisionModelInference::test_vision_chat_completion_non_streaming[-sambanova-image0-expected_strings0] PASSED
llama_stack/providers/tests/inference/test_vision_inference.py::TestVisionModelInference::test_vision_chat_completion_non_streaming[-sambanova-image1-expected_strings1] PASSED
llama_stack/providers/tests/inference/test_vision_inference.py::TestVisionModelInference::test_vision_chat_completion_streaming[-sambanova] PASSED
=================================================================================================================== 3 passed, 1 warning in 2.68s ====================================================================================================================
```
### Text
```
pytest -s -v --providers inference=sambanova llama_stack/providers/tests/inference/test_text_inference.py::TestInference::test_chat_completion_streaming --env SAMBANOVA_API_KEY={SAMBANOVA_API_KEY}
```
```
llama_stack/providers/tests/inference/test_text_inference.py::TestInference::test_chat_completion_streaming[-sambanova] PASSED
=================================================================================================================== 1 passed, 1 warning in 0.46s ====================================================================================================================
```
```
pytest -s -v --providers inference=sambanova llama_stack/providers/tests/inference/test_text_inference.py::TestInference::test_chat_completion_non_streaming --env SAMBANOVA_API_KEY={SAMBANOVA_API_KEY}
```
```
llama_stack/providers/tests/inference/test_text_inference.py::TestInference::test_chat_completion_non_streaming[-sambanova] PASSED
=================================================================================================================== 1 passed, 1 warning in 0.48s ====================================================================================================================
```
## Before submitting
- [] This PR fixes a typo or improves the docs (you can dismiss the
other checks if that's the case).
- [Y] Ran pre-commit to handle lint / formatting issues.
- [Y] Read the [contributor
guideline](https://github.com/meta-llama/llama-stack/blob/main/CONTRIBUTING.md),
Pull Request section?
- [Y] Updated relevant documentation.
- [Y] Wrote necessary unit or integration tests.
# What does this PR do?
When you re-initialize the library client in a notebook, we were seeing
this error:
```
Getting traces for session_id=5c8d1969-0957-49d2-b852-32cbb8ef8caf
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
[<ipython-input-11-d74bb6cdd3ab>](https://localhost:8080/#) in <cell line: 0>()
7 agent_logs = []
8
----> 9 for span in client.telemetry.query_spans(
10 attribute_filters=[
11 {"key": "session_id", "op": "eq", "value": session_id},
10 frames
[/usr/local/lib/python3.11/dist-packages/llama_stack/providers/inline/telemetry/meta_reference/telemetry.py](https://localhost:8080/#) in query_traces(self, attribute_filters, limit, offset, order_by)
246 ) -> QueryTracesResponse:
247 return QueryTracesResponse(
--> 248 data=await self.trace_store.query_traces(
249 attribute_filters=attribute_filters,
250 limit=limit,
AttributeError: 'TelemetryAdapter' object has no attribute 'trace_store'
```
This is happening because the we were skipping some required steps for
the object state as part of the global _TRACE_PROVIDER check. This PR
moves the initialization of the object state out of the TRACE_PROVIDER
init.
# What does this PR do?
Previously the tests hard coded the tool prompt format to be json which
will cause it to fail when using 3.2/3.3 family of models. This change
make the default to be none for the agent config and just remove the
specification in the tests.
## Test Plan
LLAMA_STACK_BASE_URL=http://localhost:8321 pytest -v
tests/client-sdk/agents/test_agents.py
# What does this PR do?
This PR adds SambaNova as one of the Provider
- Add SambaNova as a provider
## Test Plan
Test the functional command
```
pytest -s -v --providers inference=sambanova llama_stack/providers/tests/inference/test_embeddings.py llama_stack/providers/tests/inference/test_prompt_adapter.py llama_stack/providers/tests/inference/test_text_inference.py llama_stack/providers/tests/inference/test_vision_inference.py --env SAMBANOVA_API_KEY=<sambanova-api-key>
```
Test the distribution template:
```
# Docker
LLAMA_STACK_PORT=5001
docker run -it -p $LLAMA_STACK_PORT:$LLAMA_STACK_PORT \
llamastack/distribution-sambanova \
--port $LLAMA_STACK_PORT \
--env SAMBANOVA_API_KEY=$SAMBANOVA_API_KEY
# Conda
llama stack build --template sambanova --image-type conda
llama stack run ./run.yaml \
--port $LLAMA_STACK_PORT \
--env SAMBANOVA_API_KEY=$SAMBANOVA_API_KEY
```
## Source
[SambaNova API Documentation](https://cloud.sambanova.ai/apis)
## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the
other checks if that's the case).
- [Y] Ran pre-commit to handle lint / formatting issues.
- [Y] Read the [contributor
guideline](https://github.com/meta-llama/llama-stack/blob/main/CONTRIBUTING.md),
Pull Request section?
- [Y] Updated relevant documentation.
- [Y ] Wrote necessary unit or integration tests.
---------
Co-authored-by: Ashwin Bharambe <ashwin.bharambe@gmail.com>
# What does this PR do?
Adds raw completions API to vLLM
## Test Plan
<details>
<summary>Setup</summary>
```bash
# Run vllm server
conda create -n vllm python=3.12 -y
conda activate vllm
pip install vllm
# Run llamastack
conda create --name llamastack-vllm python=3.10
conda activate llamastack-vllm
export INFERENCE_MODEL=meta-llama/Llama-3.2-3B-Instruct && \
pip install -e . && \
pip install --no-cache --index-url https://pypi.org/simple/ --extra-index-url https://test.pypi.org/simple/ llama-stack==0.1.0rc7 && \
llama stack build --template remote-vllm --image-type conda && \
llama stack run ./distributions/remote-vllm/run.yaml \
--port 5000 \
--env INFERENCE_MODEL=$INFERENCE_MODEL \
--env VLLM_URL=http://localhost:8000/v1 | tee -a llama-stack.log
```
</details>
<details>
<summary>Integration</summary>
```bash
# Run
conda activate llamastack-vllm
export VLLM_URL=http://localhost:8000/v1
pip install pytest pytest_html pytest_asyncio aiosqlite
pytest llama_stack/providers/tests/inference/test_text_inference.py -v -k vllm
# Results
llama_stack/providers/tests/inference/test_text_inference.py::TestInference::test_model_list[-vllm_remote] PASSED [ 11%]
llama_stack/providers/tests/inference/test_text_inference.py::TestInference::test_completion[-vllm_remote] PASSED [ 22%]
llama_stack/providers/tests/inference/test_text_inference.py::TestInference::test_completion_logprobs[-vllm_remote] SKIPPED [ 33%]
llama_stack/providers/tests/inference/test_text_inference.py::TestInference::test_completion_structured_output[-vllm_remote] SKIPPED [ 44%]
llama_stack/providers/tests/inference/test_text_inference.py::TestInference::test_chat_completion_non_streaming[-vllm_remote] PASSED [ 55%]
llama_stack/providers/tests/inference/test_text_inference.py::TestInference::test_structured_output[-vllm_remote] PASSED [ 66%]
llama_stack/providers/tests/inference/test_text_inference.py::TestInference::test_chat_completion_streaming[-vllm_remote] PASSED [ 77%]
llama_stack/providers/tests/inference/test_text_inference.py::TestInference::test_chat_completion_with_tool_calling[-vllm_remote] PASSED [ 88%]
llama_stack/providers/tests/inference/test_text_inference.py::TestInference::test_chat_completion_with_tool_calling_streaming[-vllm_remote] PASSED [100%]
====================================== 7 passed, 2 skipped, 99 deselected, 1 warning in 9.80s ======================================
```
</details>
<details>
<summary>Manual</summary>
```bash
# Install
pip install --no-cache --index-url https://pypi.org/simple/ --extra-index-url https://test.pypi.org/simple/ llama-stack==0.1.0rc7
```
Apply this diff
```diff
diff --git a/llama_stack/distribution/server/server.py b/llama_stack/distribution/server/server.py
index 8dbb193..95173e2 100644
--- a/llama_stack/distribution/server/server.py
+++ b/llama_stack/distribution/server/server.py
@@ -250,7 +250,7 @@ class ClientVersionMiddleware:
server_version_parts = tuple(
map(int, self.server_version.split(".")[:2])
)
- if client_version_parts != server_version_parts:
+ if False and client_version_parts != server_version_parts:
async def send_version_error(send):
await send(
diff --git a/llama_stack/templates/remote-vllm/run.yaml b/llama_stack/templates/remote-vllm/run.yaml
index 4eac4da..32eb50e 100644
--- a/llama_stack/templates/remote-vllm/run.yaml
+++ b/llama_stack/templates/remote-vllm/run.yaml
@@ -94,7 +94,8 @@ metadata_store:
type: sqlite
db_path: ${env.SQLITE_STORE_DIR:~/.llama/distributions/remote-vllm}/registry.db
models:
-- metadata: {}
+- metadata:
+ llama_model: meta-llama/Llama-3.2-3B-Instruct
model_id: ${env.INFERENCE_MODEL}
provider_id: vllm-inference
model_type: llm
```
Test 1:
```python
from llama_stack_client import LlamaStackClient
client = LlamaStackClient(
base_url="http://localhost:5000",
)
response = client.inference.completion(
model_id="meta-llama/Llama-3.2-3B-Instruct",
content="Hello, world client!",
)
print(response)
```
Test 2
```
from llama_stack_client import LlamaStackClient
client = LlamaStackClient(
base_url="http://localhost:5000",
)
response = client.inference.completion(
model_id="meta-llama/Llama-3.2-3B-Instruct",
content="Hello, world client!",
stream=True,
)
for chunk in response:
print(chunk.delta, end="", flush=True)
```
```
I'm excited to introduce you to our latest project, a comprehensive guide to the best coffee shops in [City]. As a coffee connoisseur, you're in luck because we've scoured the city to bring you the top picks for the perfect cup of joe.
In this guide, we'll take you on a journey through the city's most iconic coffee shops, highlighting their unique features, must-try drinks, and insider tips from the baristas themselves. From cozy cafes to trendy cafes, we've got you covered.
**Top 5 Coffee Shops in [City]**
1. **The Daily Grind**: This beloved institution has been serving up expertly crafted pour-overs and lattes for over 10 years. Their expert baristas are always happy to guide you through their menu, which features a rotating selection of single-origin beans from around the world...
```
</details>
## 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?
Generate distro reports to cover inference, agents, and vector_io.
## Test Plan
Report generated through `/opt/miniconda3/envs/stack/bin/pytest -s -v
tests/client-sdk/ --report`
## 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?
Automates the model list check by querying the distro.
Added support for both remote hosted and templates.
## Test Plan
Run on a remote hosted distro via
`LLAMA_STACK_BASE_URL="https://llamastack-preview.fireworks.ai" pytest
-s -v tests/client-sdk --report`
Run on a template via
`LLAMA_STACK_CONFIG=fireworks pytest -s -v tests/client-sdk --report`
## What does this PR do?
For the completion of https://github.com/meta-llama/llama-stack/pull/835
## Test Plan
llama stack build --template experimental-post-training --image-type
conda
llama stack run
llama_stack/templates/experimental-post-training/run.yaml
Some small updates to the inference types to make them more standard
Specifically:
- image data is now located in a "image" subkey
- similarly tool call data is located in a "tool_call" subkey
The pattern followed is `dict(type="foo", foo=<...>)`
Enable downloads before sending request to fireworks.
Test using --
`LLAMA_STACK_CONFIG=./llama_stack/templates/fireworks/run.yaml pytest -s
-v -k 'test_image_chat_completion_streaming' tests/client-sdk`
Making a few small naming changes as per feedback:
- RAGToolRuntime methods are called `insert` and `query` to keep them
more general
- The tool names are changed to non-namespaced forms
`insert_into_memory` and `query_from_memory`
- The REST endpoints are more REST-ful
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
```
See https://github.com/meta-llama/llama-stack/issues/827 for the broader
design.
Second part:
- updates routing table / router code
- updates the faiss implementation
## Test Plan
```
pytest -s -v -k sentence test_vector_io.py --env EMBEDDING_DIMENSION=384
```
See https://github.com/meta-llama/llama-stack/issues/827 for the broader
design.
This is the first part:
- delete other kinds of memory banks (keyvalue, keyword, graph) for now;
we will introduce a keyvalue store API as part of this design but not
use it in the RAG tool yet.
- renaming of the APIs
# What does this PR do?
Minor bug fix and simplify code
- [ ] Addresses issue (#issue)
## Test Plan
See the updated `llama_stack/templates/fireworks/report.md`
## 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?
add pytest option (`--report`) to support generating a functional report
for llama stack distribution
## Test Plan
```
export LLAMA_STACK_CONFIG=./llama_stack/templates/fireworks/run.yaml
/opt/miniconda3/envs/stack/bin/pytest -s -v tests/client-sdk/ --report
```
See a report file was generated under
`./llama_stack/templates/fireworks/report.md`
## 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?
1) enabled structured output for ollama /completion API. It seems we
missed this one.
2) fixed ollama structured output test in client sdk - ollama does not
support list format for structured output
3) enable structured output unit test as the result was stable on
Llama-3.1-8B-Instruct and ollama, fireworks, together.
## Test Plan
1) Run `test_completion_structured_output` on /completion API with 3
providers: ollama, fireworks, together.
pytest -v -s -k "together"
--inference-model="meta-llama/Llama-3.1-8B-Instruct"
llama_stack/providers/tests/inference/test_text_inference.py::TestInference::test_completion_structured_output
```
(base) sxyi@sxyi-mbp llama-stack % pytest -s -v llama_stack/providers/tests/inference --config=ci_test_config.yaml
/Library/Frameworks/Python.framework/Versions/3.13/lib/python3.13/site-packages/pytest_asyncio/plugin.py:208: PytestDeprecationWarning: The configuration option "asyncio_default_fixture_loop_scope" is unset.
The event loop scope for asynchronous fixtures will default to the fixture caching scope. Future versions of pytest-asyncio will default the loop scope for asynchronous fixtures to function scope. Set the default fixture loop scope explicitly in order to avoid unexpected behavior in the future. Valid fixture loop scopes are: "function", "class", "module", "package", "session"
warnings.warn(PytestDeprecationWarning(_DEFAULT_FIXTURE_LOOP_SCOPE_UNSET))
================================================================================================ test session starts =================================================================================================
platform darwin -- Python 3.13.0, pytest-8.3.4, pluggy-1.5.0 -- /Library/Frameworks/Python.framework/Versions/3.13/bin/python3.13
cachedir: .pytest_cache
metadata: {'Python': '3.13.0', 'Platform': 'macOS-15.1.1-arm64-arm-64bit-Mach-O', 'Packages': {'pytest': '8.3.4', 'pluggy': '1.5.0'}, 'Plugins': {'asyncio': '0.24.0', 'html': '4.1.1', 'metadata': '3.1.1', 'md': '0.2.0', 'dependency': '0.6.0', 'md-report': '0.6.3', 'anyio': '4.6.2.post1'}}
rootdir: /Users/sxyi/llama-stack
configfile: pyproject.toml
plugins: asyncio-0.24.0, html-4.1.1, metadata-3.1.1, md-0.2.0, dependency-0.6.0, md-report-0.6.3, anyio-4.6.2.post1
asyncio: mode=Mode.STRICT, default_loop_scope=None
collected 85 items / 82 deselected / 3 selected
llama_stack/providers/tests/inference/test_text_inference.py::TestInference::test_completion_structured_output[meta-llama/Llama-3.1-8B-Instruct-ollama] PASSED
llama_stack/providers/tests/inference/test_text_inference.py::TestInference::test_completion_structured_output[meta-llama/Llama-3.1-8B-Instruct-fireworks]
PASSED
llama_stack/providers/tests/inference/test_text_inference.py::TestInference::test_completion_structured_output[meta-llama/Llama-3.1-8B-Instruct-together] PASSED
==================================================================================== 3 passed, 82 deselected, 8 warnings in 5.67s ====================================================================================
```
2)
` LLAMA_STACK_CONFIG="./llama_stack/templates/ollama/run.yaml"
/opt/miniconda3/envs/stack/bin/pytest -s -v tests/client-sdk/inference`
Before:
```
________________________________________________________________________________________ test_completion_structured_output __________________________________________________________________________________________
tests/client-sdk/inference/test_inference.py:174: in test_completion_structured_output
answer = AnswerFormat.model_validate_json(response.content)
E pydantic_core._pydantic_core.ValidationError: 1 validation error for AnswerFormat
E Invalid JSON: expected value at line 1 column 2 [type=json_invalid, input_value=' The year he retired, he...5\n\nThe best answer is', input_type=str]
E For further information visit https://errors.pydantic.dev/2.10/v/json_invalid
```
After:
test consistently passes
## 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?
**Main Thing**
- Add a simple test step before publishing docker image in workflow
**Side Fix**
- Docker push action fails recently due to extra prefix introduced. E.g.
see:
https://github.com/meta-llama/llama-stack/pull/802#issuecomment-2599507062
cc @terrytangyuan
## Test Plan
1. Release a TestPyPi version on this code: 0.0.63.dev51206766
3581203331
```
# 1. build docker image
TEST_PYPI_VERSION=0.0.63.dev51206766 llama stack build --template fireworks
# 2. test the docker image
cd distributions/fireworks && docker compose up
```
4. Test the full build + test docker flow using TestPyPi from (1):
1284218494
<img width="1049" alt="image"
src="https://github.com/user-attachments/assets/c025893d-5ce2-48ff-aa90-de00e105ee09"
/>
## 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?
MD file for the test results of provider <> inference tests
## Test Plan
1) install `pip install pytest-md-report`
2) Run inference tests with the additions to the commands
`--md-report --md-report-verbose=1 --md-report-output=tgi.md`
Test text model: meta-llama/Llama-3.1-8B-Instruct
Test vision model: meta-llama/Llama-3.2-11B-Vision-Instruct
## 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.
---------
Co-authored-by: Xi Yan <xiyan@meta.com>
# What does this PR do?
- previous fix introduced regression for non base64 image
- add back download, and base64 check
## Test Plan
<img width="835" alt="image"
src="https://github.com/user-attachments/assets/b70bf725-035a-4b42-b492-53daaf71458a"
/>
## 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?
- fix base64 based image url for vllm
- add a test case for base64 based image_url
- fixes issue: https://github.com/meta-llama/llama-stack/issues/571
## Test Plan
```
LLAMA_STACK_BASE_URL=http://localhost:8321 pytest -v ./tests/client-sdk/inference/test_inference.py::test_image_chat_completion_base64_url
```
<img width="991" alt="image"
src="https://github.com/user-attachments/assets/d56381ba-6777-4d23-9da9-81f73ce93566"
/>
## 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.
It's a more generic term and applicable to alternatives of Docker, such
as Podman or other OCI-compliant technologies.
---------
Signed-off-by: Yuan Tang <terrytangyuan@gmail.com>
# What does this PR do?
Fixes error when running an provider using openai_compat.py
```python
Traceback (most recent call last):
File "/home/ubuntu/miniconda3/envs/llamastack-vllm/lib/python3.10/runpy.py", line 196, in _run_module_as_main
return _run_code(code, main_globals, None,
File "/home/ubuntu/miniconda3/envs/llamastack-vllm/lib/python3.10/runpy.py", line 86, in _run_code
exec(code, run_globals)
File "/home/ubuntu/us-south-2/llama-stack/llama_stack/distribution/server/server.py", line 426, in <module>
main()
File "/home/ubuntu/us-south-2/llama-stack/llama_stack/distribution/server/server.py", line 349, in main
impls = asyncio.run(construct_stack(config))
File "/home/ubuntu/miniconda3/envs/llamastack-vllm/lib/python3.10/asyncio/runners.py", line 44, in run
return loop.run_until_complete(main)
File "/home/ubuntu/miniconda3/envs/llamastack-vllm/lib/python3.10/asyncio/base_events.py", line 649, in run_until_complete
return future.result()
File "/home/ubuntu/us-south-2/llama-stack/llama_stack/distribution/stack.py", line 207, in construct_stack
impls = await resolve_impls(
File "/home/ubuntu/us-south-2/llama-stack/llama_stack/distribution/resolver.py", line 239, in resolve_impls
impl = await instantiate_provider(
File "/home/ubuntu/us-south-2/llama-stack/llama_stack/distribution/resolver.py", line 330, in instantiate_provider
impl = await fn(*args)
File "/home/ubuntu/us-south-2/llama-stack/llama_stack/providers/remote/inference/vllm/__init__.py", line 11, in get_adapter_impl
from .vllm import VLLMInferenceAdapter
File "/home/ubuntu/us-south-2/llama-stack/llama_stack/providers/remote/inference/vllm/vllm.py", line 39, in <module>
from llama_stack.providers.utils.inference.openai_compat import (
File "/home/ubuntu/us-south-2/llama-stack/llama_stack/providers/utils/inference/openai_compat.py", line 11, in <module>
from llama_models.llama3.api.datatypes import (
ImportError: cannot import name 'GreedySamplingStrategy' from 'llama_models.llama3.api.datatypes' (/home/ubuntu/miniconda3/envs/llamastack-vllm/lib/python3.10/site-packages/llama_models/llama3/api/datatypes.py)
++ error_handler 61
++ echo 'Error occurred in script at line: 61'
Error occurred in script at line: 61
++ exit 1
```
## Test Plan
```bash
conda create --name llamastack-vllm python=3.10
conda activate llamastack-vllm
# To sync with the current llama-models repo
pip install -e git+https://github.com/meta-llama/llama-models.git#egg=llama-models
export INFERENCE_MODEL=unsloth/Llama-3.3-70B-Instruct-bnb-4bit && \
pip install -e . && \
llama stack build --template remote-vllm --image-type conda && \
llama stack run ./distributions/remote-vllm/run.yaml \
--port 5000 \
--env INFERENCE_MODEL=$INFERENCE_MODEL \
--env VLLM_URL=http://localhost:8000
```
## 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.
- [x] 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?
- update playground callsites for v1 api changes
## Test Plan
```
cd llama_stack/distribution/ui
streamlit run app.py
```
https://github.com/user-attachments/assets/eace11c6-600a-42dc-b4e7-6948a706509f
## 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.
