llama-models should have extremely minimal cruft. Its sole purpose
should be didactic -- show the simplest implementation of the llama
models and document the prompt formats, etc.
This PR is the complement to
https://github.com/meta-llama/llama-models/pull/279
## Test Plan
Ensure all `llama` CLI `model` sub-commands work:
```bash
llama model list
llama model download --model-id ...
llama model prompt-format -m ...
```
Ran tests:
```bash
cd tests/client-sdk
LLAMA_STACK_CONFIG=fireworks pytest -s -v inference/
LLAMA_STACK_CONFIG=fireworks pytest -s -v vector_io/
LLAMA_STACK_CONFIG=fireworks pytest -s -v agents/
```
Create a fresh venv `uv venv && source .venv/bin/activate` and run
`llama stack build --template fireworks --image-type venv` followed by
`llama stack run together --image-type venv` <-- the server runs
Also checked that the OpenAPI generator can run and there is no change
in the generated files as a result.
```bash
cd docs/openapi_generator
sh run_openapi_generator.sh
```
# What does this PR do?
- Configured ruff linter to automatically fix import sorting issues.
- Set --exit-non-zero-on-fix to ensure non-zero exit code when fixes are
applied.
- Enabled the 'I' selection to focus on import-related linting rules.
- Ran the linter, and formatted all codebase imports accordingly.
- Removed the black dep from the "dev" group since we use ruff
Signed-off-by: Sébastien Han <seb@redhat.com>
[//]: # (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.*]
[//]: # (## Documentation)
[//]: # (- [ ] Added a Changelog entry if the change is significant)
Signed-off-by: Sébastien Han <seb@redhat.com>
# What does this PR do?
The remote-vllm provider was not passing logprobs options from
CompletionRequest or ChatCompletionRequests through to the OpenAI client
parameters. I manually verified this, as well as observed this provider
failing `TestInference::test_completion_logprobs`. This was filed as
issue #1073.
This fixes that by passing the `logprobs.top_k` value through to the
parameters we pass into the OpenAI client.
Additionally, this fixes a bug in `test_text_inference.py` where it
mistakenly assumed chunk.delta were of type `ContentDelta` for
completion requests. The deltas are of type `ContentDelta` for chat
completion requests, but for basic completion requests the deltas are of
type string. This test was likely failing for other providers that did
properly support logprobs because of this latter issue in the test,
which was hit while fixing the above issue with the remote-vllm
provider.
(Closes#1073)
## Test Plan
First, you need a vllm running. I ran one locally like this:
```
vllm serve meta-llama/Llama-3.2-3B-Instruct --port 8001 --enable-auto-tool-choice --tool-call-parser llama3_json
```
Next, run test_text_inference.py against this vllm using the remote vllm
provider like this:
```
VLLM_URL="http://localhost:8001/v1" python -m pytest -s -v llama_stack/providers/tests/inference/test_text_inference.py --providers "inference=vllm_remote"
```
Before my change, the test failed with this error:
```
llama_stack/providers/tests/inference/test_text_inference.py:155: in test_completion_logprobs
assert 1 <= len(response.logprobs) <= 5
E TypeError: object of type 'NoneType' has no len()
```
After my change, the test passes.
[//]: # (## Documentation)
Signed-off-by: Ben Browning <bbrownin@redhat.com>
# What does this PR do?
[Provide a short summary of what this PR does and why. Link to relevant
issues if applicable.]
Closes https://github.com/meta-llama/llama-stack/issues/1046.
## 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.*]
```
LLAMA_STACK_BASE_URL=http://localhost:5002 pytest -v tests/client-sdk/inference/test_text_inference.py
================================================================= test session starts =================================================================
platform linux -- Python 3.10.16, pytest-8.3.4, pluggy-1.5.0 -- /home/yutang/.conda/envs/distribution-myenv/bin/python3.10
cachedir: .pytest_cache
rootdir: /home/yutang/repos/llama-stack
configfile: pyproject.toml
plugins: anyio-4.8.0
collected 14 items
tests/client-sdk/inference/test_text_inference.py::test_text_completion_non_streaming[meta-llama/Llama-3.1-8B-Instruct] PASSED [ 7%]
tests/client-sdk/inference/test_text_inference.py::test_text_completion_streaming[meta-llama/Llama-3.1-8B-Instruct] PASSED [ 14%]
tests/client-sdk/inference/test_text_inference.py::test_completion_log_probs_non_streaming[meta-llama/Llama-3.1-8B-Instruct] XFAIL (remote:...) [ 21%]
tests/client-sdk/inference/test_text_inference.py::test_completion_log_probs_streaming[meta-llama/Llama-3.1-8B-Instruct] XFAIL (remote::vll...) [ 28%]
tests/client-sdk/inference/test_text_inference.py::test_text_completion_structured_output[meta-llama/Llama-3.1-8B-Instruct] PASSED [ 35%]
tests/client-sdk/inference/test_text_inference.py::test_text_chat_completion_non_streaming[meta-llama/Llama-3.1-8B-Instruct-Which planet do humans live on?-Earth] PASSED [ 42%]
tests/client-sdk/inference/test_text_inference.py::test_text_chat_completion_non_streaming[meta-llama/Llama-3.1-8B-Instruct-Which planet has rings around it with a name starting with letter S?-Saturn] PASSED [ 50%]
tests/client-sdk/inference/test_text_inference.py::test_text_chat_completion_streaming[meta-llama/Llama-3.1-8B-Instruct-What's the name of the Sun in latin?-Sol] PASSED [ 57%]
tests/client-sdk/inference/test_text_inference.py::test_text_chat_completion_streaming[meta-llama/Llama-3.1-8B-Instruct-What is the name of the US captial?-Washington] PASSED [ 64%]
tests/client-sdk/inference/test_text_inference.py::test_text_chat_completion_with_tool_calling_and_non_streaming[meta-llama/Llama-3.1-8B-Instruct] PASSED [ 71%]
tests/client-sdk/inference/test_text_inference.py::test_text_chat_completion_with_tool_calling_and_streaming[meta-llama/Llama-3.1-8B-Instruct] PASSED [ 78%]
tests/client-sdk/inference/test_text_inference.py::test_text_chat_completion_structured_output[meta-llama/Llama-3.1-8B-Instruct] PASSED [ 85%]
tests/client-sdk/inference/test_text_inference.py::test_text_chat_completion_tool_calling_tools_not_in_request[meta-llama/Llama-3.1-8B-Instruct-True] PASSED [ 92%]
tests/client-sdk/inference/test_text_inference.py::test_text_chat_completion_tool_calling_tools_not_in_request[meta-llama/Llama-3.1-8B-Instruct-False] PASSED [100%]
=============================================== 12 passed, 2 xfailed, 1 warning in 366.56s (0:06:06) ================================================
```
---------
Signed-off-by: Yuan Tang <terrytangyuan@gmail.com>
# What does this PR do?
This PR adds support for tool calling for non-streaming chat completion.
Prior to this, tool calls were not passed to chat completion requests
and the tools object needs to be restructured properly to be compatible
with vLLM provider.
## Test Plan
```
LLAMA_STACK_BASE_URL=http://localhost:5002 pytest -v tests/client-sdk/inference/test_text_inference.py
================================================================= test session starts =================================================================
platform linux -- Python 3.10.16, pytest-8.3.4, pluggy-1.5.0 -- /home/yutang/.conda/envs/distribution-myenv/bin/python3.10
cachedir: .pytest_cache
rootdir: /home/yutang/repos/llama-stack
configfile: pyproject.toml
plugins: anyio-4.8.0
collected 12 items
tests/client-sdk/inference/test_text_inference.py::test_text_completion_non_streaming[meta-llama/Llama-3.1-8B-Instruct] PASSED [ 8%]
tests/client-sdk/inference/test_text_inference.py::test_text_completion_streaming[meta-llama/Llama-3.1-8B-Instruct] PASSED [ 16%]
tests/client-sdk/inference/test_text_inference.py::test_completion_log_probs_non_streaming[meta-llama/Llama-3.1-8B-Instruct] XFAIL (remote:...) [ 25%]
tests/client-sdk/inference/test_text_inference.py::test_completion_log_probs_streaming[meta-llama/Llama-3.1-8B-Instruct] XFAIL (remote::vll...) [ 33%]
tests/client-sdk/inference/test_text_inference.py::test_text_completion_structured_output[meta-llama/Llama-3.1-8B-Instruct] PASSED [ 41%]
tests/client-sdk/inference/test_text_inference.py::test_text_chat_completion_non_streaming[meta-llama/Llama-3.1-8B-Instruct-Which planet do humans live on?-Earth] PASSED [ 50%]
tests/client-sdk/inference/test_text_inference.py::test_text_chat_completion_non_streaming[meta-llama/Llama-3.1-8B-Instruct-Which planet has rings around it with a name starting with letter S?-Saturn] PASSED [ 58%]
tests/client-sdk/inference/test_text_inference.py::test_text_chat_completion_streaming[meta-llama/Llama-3.1-8B-Instruct-What's the name of the Sun in latin?-Sol] PASSED [ 66%]
tests/client-sdk/inference/test_text_inference.py::test_text_chat_completion_streaming[meta-llama/Llama-3.1-8B-Instruct-What is the name of the US captial?-Washington] PASSED [ 75%]
tests/client-sdk/inference/test_text_inference.py::test_text_chat_completion_with_tool_calling_and_non_streaming[meta-llama/Llama-3.1-8B-Instruct] PASSED [ 83%]
tests/client-sdk/inference/test_text_inference.py::test_text_chat_completion_with_tool_calling_and_streaming[meta-llama/Llama-3.1-8B-Instruct] FAILED [ 91%]
tests/client-sdk/inference/test_text_inference.py::test_text_chat_completion_structured_output[meta-llama/Llama-3.1-8B-Instruct] PASSED [100%]
```
---------
Signed-off-by: Yuan Tang <terrytangyuan@gmail.com>
# What does this PR do?
`tool_config` is missing from the signature but is used in
`ChatCompletionRequest()`.
## Test Plan
This is a small fix. I don't have SambaNova to test the change but I
doubt that this is currently working.
Signed-off-by: Yuan Tang <terrytangyuan@gmail.com>
# What does this PR do?
Moved model availability check logic into a dedicated
check_model_availability function. Eliminated redundant code by reusing
the helper function in both embedding and non-embedding model
registration.
Signed-off-by: Sébastien Han <seb@redhat.com>
## Test Plan
Run Ollama and serve 2 models to get most the unit test pass:
```
ollama run llama3.2:3b-instruct-fp16 --keepalive 2m &
ollama run llama3.1:8b --keepalive 2m &
```
Run the unit test:
```
uv run pytest -v -k "ollama" --inference-model=llama3.2:3b-instruct-fp16 llama_stack/providers/tests/inference/test_model_registration.py
/Users/leseb/Documents/AI/llama-stack/.venv/lib/python3.13/site-packages/pytest_asyncio/plugin.py:207: 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 3.13.1, pytest-8.3.4, pluggy-1.5.0 -- /Users/leseb/Documents/AI/llama-stack/.venv/bin/python3
cachedir: .pytest_cache
metadata: {'Python': '3.13.1', 'Platform': 'macOS-15.3-arm64-arm-64bit-Mach-O', 'Packages': {'pytest': '8.3.4', 'pluggy': '1.5.0'}, 'Plugins': {'html': '4.1.1', 'metadata': '3.1.1', 'asyncio': '0.25.3', 'anyio': '4.8.0', 'nbval': '0.11.0'}}
rootdir: /Users/leseb/Documents/AI/llama-stack
configfile: pyproject.toml
plugins: html-4.1.1, metadata-3.1.1, asyncio-0.25.3, anyio-4.8.0, nbval-0.11.0
asyncio: mode=Mode.STRICT, asyncio_default_fixture_loop_scope=None
collected 65 items / 60 deselected / 5 selected
llama_stack/providers/tests/inference/test_model_registration.py::TestModelRegistration::test_register_unsupported_model[-ollama] PASSED [ 20%]
llama_stack/providers/tests/inference/test_model_registration.py::TestModelRegistration::test_register_nonexistent_model[-ollama] PASSED [ 40%]
llama_stack/providers/tests/inference/test_model_registration.py::TestModelRegistration::test_register_with_llama_model[-ollama] FAILED [ 60%]
llama_stack/providers/tests/inference/test_model_registration.py::TestModelRegistration::test_initialize_model_during_registering[-ollama] FAILED [ 80%]
llama_stack/providers/tests/inference/test_model_registration.py::TestModelRegistration::test_register_with_invalid_llama_model[-ollama] PASSED [100%]
================================================== FAILURES ==================================================
_______________________ TestModelRegistration.test_register_with_llama_model[-ollama] ________________________
llama_stack/providers/tests/inference/test_model_registration.py:54: in test_register_with_llama_model
_ = await models_impl.register_model(
llama_stack/providers/utils/telemetry/trace_protocol.py:91: in async_wrapper
result = await method(self, *args, **kwargs)
llama_stack/distribution/routers/routing_tables.py:245: in register_model
registered_model = await self.register_object(model)
llama_stack/distribution/routers/routing_tables.py:192: in register_object
registered_obj = await register_object_with_provider(obj, p)
llama_stack/distribution/routers/routing_tables.py:53: in register_object_with_provider
return await p.register_model(obj)
llama_stack/providers/utils/telemetry/trace_protocol.py:91: in async_wrapper
result = await method(self, *args, **kwargs)
llama_stack/providers/remote/inference/ollama/ollama.py:368: in register_model
await check_model_availability(model.provider_resource_id)
llama_stack/providers/remote/inference/ollama/ollama.py:359: in check_model_availability
raise ValueError(
E ValueError: Model 'custom-model' is not available in Ollama. Available models: llama3.1:8b, llama3.2:3b-instruct-fp16
__________________ TestModelRegistration.test_initialize_model_during_registering[-ollama] ___________________
llama_stack/providers/tests/inference/test_model_registration.py:85: in test_initialize_model_during_registering
mock_load_model.assert_called_once()
/opt/homebrew/Cellar/python@3.13/3.13.1/Frameworks/Python.framework/Versions/3.13/lib/python3.13/unittest/mock.py:956: in assert_called_once
raise AssertionError(msg)
E AssertionError: Expected 'load_model' to have been called once. Called 0 times.
-------------------------------------------- Captured stderr call --------------------------------------------
W0207 11:55:26.777000 90854 .venv/lib/python3.13/site-packages/torch/distributed/elastic/multiprocessing/redirects.py:29] NOTE: Redirects are currently not supported in Windows or MacOs.
========================================== short test summary info ===========================================
FAILED llama_stack/providers/tests/inference/test_model_registration.py::TestModelRegistration::test_register_with_llama_model[-ollama] - ValueError: Model 'custom-model' is not available in Ollama. Available models: llama3.1:8b, llama3.2:3b-i...
FAILED llama_stack/providers/tests/inference/test_model_registration.py::TestModelRegistration::test_initialize_model_during_registering[-ollama] - AssertionError: Expected 'load_model' to have been called once. Called 0 times.
=========================== 2 failed, 3 passed, 60 deselected, 2 warnings in 1.84s ===========================
```
We only "care" about the `test_register_nonexistent_model` for this
code.
## 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.
Signed-off-by: Sébastien Han <seb@redhat.com>
# What does this PR do?
Imported `ToolConfig` from the `llama_stack.apis.inference` module to
resolve missing reference and ensure proper functionality within the
`groq.py` file.
Signed-off-by: Sébastien Han <seb@redhat.com>
## Test Plan
Without the change, pytest will run with the following error:
```
uv run pytest -v -s -k "ollama" llama_stack/providers/tests/
/Users/leseb/Documents/AI/llama-stack/.venv/lib/python3.13/site-packages/pytest_asyncio/plugin.py:207: 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 3.13.1, pytest-8.3.4, pluggy-1.5.0 -- /Users/leseb/Documents/AI/llama-stack/.venv/bin/python3
cachedir: .pytest_cache
metadata: {'Python': '3.13.1', 'Platform': 'macOS-15.3-arm64-arm-64bit-Mach-O', 'Packages': {'pytest': '8.3.4', 'pluggy': '1.5.0'}, 'Plugins': {'html': '4.1.1', 'metadata': '3.1.1', 'asyncio': '0.25.3', 'anyio': '4.8.0', 'nbval': '0.11.0'}}
rootdir: /Users/leseb/Documents/AI/llama-stack
configfile: pyproject.toml
plugins: html-4.1.1, metadata-3.1.1, asyncio-0.25.3, anyio-4.8.0, nbval-0.11.0
asyncio: mode=Mode.STRICT, asyncio_default_fixture_loop_scope=None
collected 379 items / 1 error / 349 deselected / 30 selected
=================================================== ERRORS ===================================================
__________________ ERROR collecting llama_stack/providers/tests/inference/groq/test_init.py __________________
llama_stack/providers/tests/inference/groq/test_init.py:11: in <module>
from llama_stack.providers.remote.inference.groq.groq import GroqInferenceAdapter
llama_stack/providers/remote/inference/groq/groq.py:72: in <module>
class GroqInferenceAdapter(Inference, ModelRegistryHelper, NeedsRequestProviderData):
llama_stack/providers/remote/inference/groq/groq.py:102: in GroqInferenceAdapter
tool_config: Optional[ToolConfig] = None,
E NameError: name 'ToolConfig' is not defined
========================================== short test summary info ===========================================
ERROR llama_stack/providers/tests/inference/groq/test_init.py - NameError: name 'ToolConfig' is not defined
!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!! Interrupted: 1 error during collection !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
=============================== 349 deselected, 22 warnings, 1 error in 0.28s ================================
```
With the change the test continues to run and fails with a different
error:
```
uv run pytest -v -s llama_stack/providers/tests/
/Users/leseb/Documents/AI/llama-stack/.venv/lib/python3.13/site-packages/pytest_asyncio/plugin.py:207: 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 3.13.1, pytest-8.3.4, pluggy-1.5.0 -- /Users/leseb/Documents/AI/llama-stack/.venv/bin/python3
cachedir: .pytest_cache
metadata: {'Python': '3.13.1', 'Platform': 'macOS-15.3-arm64-arm-64bit-Mach-O', 'Packages': {'pytest': '8.3.4', 'pluggy': '1.5.0'}, 'Plugins': {'html': '4.1.1', 'metadata': '3.1.1', 'asyncio': '0.25.3', 'anyio': '4.8.0', 'nbval': '0.11.0'}}
rootdir: /Users/leseb/Documents/AI/llama-stack
configfile: pyproject.toml
plugins: html-4.1.1, metadata-3.1.1, asyncio-0.25.3, anyio-4.8.0, nbval-0.11.0
asyncio: mode=Mode.STRICT, asyncio_default_fixture_loop_scope=None
collected 342 items / 1 error
=================================================== ERRORS ===================================================
______________ ERROR collecting llama_stack/providers/tests/inference/test_vision_inference.py _______________
llama_stack/providers/tests/inference/test_vision_inference.py:29: in <module>
class TestVisionModelInference:
llama_stack/providers/tests/inference/test_vision_inference.py:35: in TestVisionModelInference
ImageContentItem(image=dict(data=PASTA_IMAGE)),
E pydantic_core._pydantic_core.ValidationError: 1 validation error for ImageContentItem
E image.data
E Input should be a valid string, unable to parse raw data as a unicode string [type=string_unicode, input_value=b'\xff\xd8\xff\xe0\x00\x1...0\xe6\x9f5\xb5?\xff\xd9', input_type=bytes]
E For further information visit https://errors.pydantic.dev/2.10/v/string_unicode
========================================== short test summary info ===========================================
ERROR llama_stack/providers/tests/inference/test_vision_inference.py - pydantic_core._pydantic_core.ValidationError: 1 validation error for ImageContentItem
!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!! Interrupted: 1 error during collection !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
======================================= 22 warnings, 1 error in 0.25s ========================================
```
Which is fixed in https://github.com/meta-llama/llama-stack/pull/1003.
## 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.
Signed-off-by: Sébastien Han <seb@redhat.com>
# What does this PR do?
The current default system prompt for llama3.2 tends to overindex on
tool calling and doesn't work well when the prompt does not require tool
calling.
This PR adds an option to override the default system prompt, and
organizes tool-related configs into a new config object.
- [ ] Addresses issue (#issue)
## Test Plan
python -m unittest
llama_stack.providers.tests.inference.test_prompt_adapter
## 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.
---
[//]: # (BEGIN SAPLING FOOTER)
Stack created with [Sapling](https://sapling-scm.com). Best reviewed
with
[ReviewStack](https://reviewstack.dev/meta-llama/llama-stack/pull/937).
* #938
* __->__ #937
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?
add support to the NVIDIA Inference provider for image inputs
## Test Plan
1. Run local [Llama 3.2 11b vision
instruct](https://build.nvidia.com/meta/llama-3.2-11b-vision-instruct?snippet_tab=Docker)
NIM
2. Start a stack, e.g. `llama stack run
llama_stack/templates/nvidia/run.yaml --env
NVIDIA_BASE_URL=http://localhost:8000`
3. Run image tests, e.g. `LLAMA_STACK_BASE_URL=http://localhost:8321
pytest -v tests/client-sdk/inference/test_inference.py
--vision-inference-model meta-llama/Llama-3.2-11B-Vision-Instruct -k
image`
## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the
other checks if that's the case).
- [x] 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.
- [x] Wrote necessary unit or integration tests.
# What does this PR do?
- Fix typo
- Support Llama 3.3 70B
## Test Plan
Run the following scripts and obtain the test results
Script
```
pytest -s -v --providers inference=sambanova llama_stack/providers/tests/inference/test_text_inference.py::TestInference::test_chat_completion_streaming --env SAMBANOVA_API_KEY={API_KEY}
```
Result
```
llama_stack/providers/tests/inference/test_text_inference.py::TestInference::test_chat_completion_streaming[-sambanova] PASSED
=========================================== 1 passed, 1 warning in 1.26s ============================================
```
Script
```
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={API_KEY}
```
Result
```
llama_stack/providers/tests/inference/test_text_inference.py::TestInference::test_chat_completion_non_streaming[-sambanova] PASSED
=========================================== 1 passed, 1 warning in 0.52s ============================================
```
## Sources
Please link relevant resources if necessary.
## Before submitting
- [N] 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.
- [N] Wrote necessary unit or integration tests.
# What does this PR do?
1) As per @mattf's suggestion, we want to mark the pytest as xfail for
providers that do not support the functionality. In this diff, we xfail
the logProbs inference tests for providers who does not support log
probs.
( log probs is only supported by together, fireworks and vllm)
2) Added logProbs support for together according to their developer
[doc](https://docs.together.ai/docs/logprobs).
## Test Plan
1) Together & Fireworks
```
export LLAMA_STACK_CONFIG=/Users/sxyi/llama-stack/llama_stack/templates/together/run.yaml
/opt/miniconda3/envs/stack/bin/pytest -s -v /Users/sxyi/llama-stack/tests/client-sdk/inference/test_inference.py
```
```
tests/client-sdk/inference/test_inference.py::test_text_completion_streaming[meta-llama/Llama-3.1-8B-Instruct] PASSED
tests/client-sdk/inference/test_inference.py::test_completion_log_probs_non_streaming[meta-llama/Llama-3.1-8B-Instruct] PASSED
tests/client-sdk/inference/test_inference.py::test_completion_log_probs_streaming[meta-llama/Llama-3.1-8B-Instruct] PASSED
tests/client-sdk/inference/test_inference.py::test_text_completion_structured_output[meta-llama/Llama-3.1-8B-Instruct] PASSED
tests/client-sdk/inference/test_inference.py::test_text_chat_completion_non_streaming[meta-llama/Llama-3.1-8B-Instruct-What are the names of planets in our solar system?-Earth] PASSED
tests/client-sdk/inference/test_inference.py::test_text_chat_completion_non_streaming[meta-llama/Llama-3.1-8B-Instruct-What are the names of the planets that have rings around them?-Saturn] PASSED
tests/client-sdk/inference/test_inference.py::test_text_chat_completion_streaming[meta-llama/Llama-3.1-8B-Instruct-What's the name of the Sun in latin?-Sol] PASSED
tests/client-sdk/inference/test_inference.py::test_text_chat_completion_streaming[meta-llama/Llama-3.1-8B-Instruct-What is the name of the US captial?-Washington] PASSED
tests/client-sdk/inference/test_inference.py::test_text_chat_completion_with_tool_calling_and_non_streaming[meta-llama/Llama-3.1-8B-Instruct] PASSED
tests/client-sdk/inference/test_inference.py::test_text_chat_completion_with_tool_calling_and_streaming[meta-llama/Llama-3.1-8B-Instruct] PASSED
tests/client-sdk/inference/test_inference.py::test_text_chat_completion_structured_output[meta-llama/Llama-3.1-8B-Instruct] PASSED
tests/client-sdk/inference/test_inference.py::test_image_chat_completion_non_streaming[meta-llama/Llama-3.2-11B-Vision-Instruct] PASSED
tests/client-sdk/inference/test_inference.py::test_image_chat_completion_streaming[meta-llama/Llama-3.2-11B-Vision-Instruct] PASSED
tests/client-sdk/inference/test_inference.py::test_image_chat_completion_base64_url[meta-llama/Llama-3.2-11B-Vision-Instruct] PASSED
========================================================================================== 15 passed, 2 warnings in 19.46s ===========================================================================================
```
```
export LLAMA_STACK_CONFIG=/Users/sxyi/llama-stack/llama_stack/templates/fireworks/run.yaml
/opt/miniconda3/envs/stack/bin/pytest -s -v /Users/sxyi/llama-stack/tests/client-sdk/inference/test_inference.py
```
All tests passed
2) Ollama - LogProbs tests are marked as xfailed.
```
tests/client-sdk/inference/test_inference.py::test_completion_log_probs_non_streaming[meta-llama/Llama-3.1-8B-Instruct] XFAIL (remote::ollama doesn't support log probs yet)
tests/client-sdk/inference/test_inference.py::test_completion_log_probs_streaming[meta-llama/Llama-3.1-8B-Instruct] XFAIL (remote::ollama doesn't support log probs yet)
```
## 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 type mismatch in /v1/inference/completion
## Test Plan
`llama stack run ./llama_stack/templates/nvidia/run.yaml`
`LLAMA_STACK_BASE_URL="http://localhost:8321" pytest -v
tests/client-sdk/inference/test_inference.py`
## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the
other checks if that's the case).
- [x] 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?
- 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?
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.
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`
# 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?
- 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.
# What does this PR do?
- Fix TGI adapter
## Test Plan
<img width="851" alt="image"
src="https://github.com/user-attachments/assets/0084cbc6-6713-4079-b87b-0befd9aca0b0"
/>
- most inference working
- agent test failure due to model outputs
## 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 completion log probs for fireworks
## Test Plan
<img width="849" alt="image"
src="https://github.com/user-attachments/assets/5aa1f27f-02a6-422c-8478-94dd1e345342"
/>
## 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?
- fixes to nvidia inference provider to account for strategy update
- update nvidia templates
## Test Plan
```
llama stack run ./llama_stack/templates/nvidia/run.yaml --port 5000
LLAMA_STACK_BASE_URL="http://localhost:5000" pytest -v tests/client-sdk/inference/test_inference.py --html=report.html --self-contained-html
```
<img width="1288" alt="image"
src="https://github.com/user-attachments/assets/d20f9aea-525e-47de-a5be-586e022e0d55"
/>
**NOTE**
- vision inference broken
- tool calling broken
- /completion broken
cc @mattf @cdgamarose-nv for improving NVIDIA inference adapter
## 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?
adds nvidia template for creating a distribution using inference adapter
for NVIDIA NIMs.
## Test Plan
Please describe:
Build llama stack distribution for nvidia using the template, docker and
conda.
```bash
(.venv) local-cdgamarose@a4u8g-0006:~/llama-stack$ llama-stack-client configure --endpoint http://localhost:5000
Done! You can now use the Llama Stack Client CLI with endpoint http://localhost:5000
(.venv) local-cdgamarose@a4u8g-0006:~/llama-stack$ llama-stack-client models list
┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━┓
┃ identifier ┃ provider_id ┃ provider_resource_id ┃ metadata ┃
┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━┩
│ Llama3.1-8B-Instruct │ nvidia │ meta/llama-3.1-8b-instruct │ {} │
│ meta-llama/Llama-3.2-3B-Instruct │ nvidia │ meta/llama-3.2-3b-instruct │ {} │
└──────────────────────────────────┴─────────────┴────────────────────────────┴──────────┘
(.venv) local-cdgamarose@a4u8g-0006:~/llama-stack$ llama-stack-client inference chat-completion --message "hello, write me a 2 sentence poem"
ChatCompletionResponse(
completion_message=CompletionMessage(
content='Here is a 2 sentence poem:\n\nThe sun sets slow and paints the sky, \nA gentle hue of pink that makes me sigh.',
role='assistant',
stop_reason='end_of_turn',
tool_calls=[]
),
logprobs=None
)
```
## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the
other checks if that's the case).
- [x] 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?
- [x] Updated relevant documentation.
- [ ] Wrote necessary unit or integration tests.
---------
Co-authored-by: Matthew Farrellee <matt@cs.wisc.edu>
# What does this PR do?
Cleans up how we provide sampling params. Earlier, strategy was an enum
and all params (top_p, temperature, top_k) across all strategies were
grouped. We now have a strategy union object with each strategy (greedy,
top_p, top_k) having its corresponding params.
Earlier,
```
class SamplingParams:
strategy: enum ()
top_p, temperature, top_k and other params
```
However, the `strategy` field was not being used in any providers making
it confusing to know the exact sampling behavior purely based on the
params since you could pass temperature, top_p, top_k and how the
provider would interpret those would not be clear.
Hence we introduced -- a union where the strategy and relevant params
are all clubbed together to avoid this confusion.
Have updated all providers, tests, notebooks, readme and otehr places
where sampling params was being used to use the new format.
## Test Plan
`pytest llama_stack/providers/tests/inference/groq/test_groq_utils.py`
// inference on ollama, fireworks and together
`with-proxy pytest -v -s -k "ollama"
--inference-model="meta-llama/Llama-3.1-8B-Instruct"
llama_stack/providers/tests/inference/test_text_inference.py `
// agents on fireworks
`pytest -v -s -k 'fireworks and create_agent'
--inference-model="meta-llama/Llama-3.1-8B-Instruct"
llama_stack/providers/tests/agents/test_agents.py
--safety-shield="meta-llama/Llama-Guard-3-8B"`
## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the
other checks if that's the case).
- [X] 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?
- [X] Updated relevant documentation.
- [X] Wrote necessary unit or integration tests.
---------
Co-authored-by: Hardik Shah <hjshah@fb.com>
# What does this PR do?
Fix https://github.com/meta-llama/llama-stack/issues/697
## Test Plan
Run the 405b model. the full `accounts/fireworks/models/<model_id>` is
the full model name for Fireworks, the 'fireworks/<model_id>' is just a
short hand and sometimes have routing issues
## 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?
We are setting a default value of json for tool prompt format, which
conflicts with llama 3.2/3.3 models since they use python list. This PR
changes the defaults to None and in the code, we infer default based on
the model.
Addresses: #695
Tests:
❯ LLAMA_STACK_BASE_URL=http://localhost:5000 pytest -v
tests/client-sdk/inference/test_inference.py -k
"test_text_chat_completion"
pytest llama_stack/providers/tests/inference/test_prompt_adapter.py
Add another header so client SDKs can identify their versions which can
be used for immediate detection of possible compatibility issues. A
semver mismatch against the wrong server should be immediately flagged
and requests should be denied.
Also change `X-LlamaStack-ProviderData` to `X-LlamaStack-Provider-Data`
since that hyphenation is better.
# 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?
- add llama3.3 model for together
- fix fireworks distro_codegen
```
python llama_stack/scripts/distro_codegen.py
```
## Test Plan
<img width="1132" alt="image"
src="https://github.com/user-attachments/assets/bf94b933-9200-4e73-878e-d1a95d450a88"
/>
**Tests**
```
pytest -v -s -k "together" --inference-model="meta-llama/Llama-3.3-70B-Instruct" ./llama_stack/providers/tests/inference/test_text_inference.py
```
<img width="1139" alt="image"
src="https://github.com/user-attachments/assets/407dc98b-8de3-4841-8cb1-75e4b5128544"
/>
## 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?
Contributes towards: #432
RE: https://github.com/meta-llama/llama-stack/pull/609
I missed this one while refactoring. Fixes:
```python
Traceback (most recent call last):
File "/Users/aidand/dev/llama-stack/llama_stack/distribution/server/server.py", line 191, in endpoint
return await maybe_await(value)
File "/Users/aidand/dev/llama-stack/llama_stack/distribution/server/server.py", line 155, in maybe_await
return await value
File "/Users/aidand/dev/llama-stack/llama_stack/providers/utils/telemetry/trace_protocol.py", line 101, in async_wrapper
result = await method(self, *args, **kwargs)
File "/Users/aidand/dev/llama-stack/llama_stack/distribution/routers/routers.py", line 156, in chat_completion
return await provider.chat_completion(**params)
File "/Users/aidand/dev/llama-stack/llama_stack/providers/utils/telemetry/trace_protocol.py", line 101, in async_wrapper
result = await method(self, *args, **kwargs)
File "/Users/aidand/dev/llama-stack/llama_stack/providers/remote/inference/groq/groq.py", line 127, in chat_completion
response = self._get_client().chat.completions.create(**request)
File "/Users/aidand/dev/llama-stack/llama_stack/providers/remote/inference/groq/groq.py", line 143, in _get_client
return Groq(api_key=self.config.api_key)
AttributeError: 'GroqInferenceAdapter' object has no attribute 'config'. Did you mean: '_config'?
```
## Test Plan
Environment:
```shell
export GROQ_API_KEY=<api-key>
# build.yaml and run.yaml files
wget https://raw.githubusercontent.com/aidando73/llama-stack/9165502582cd7cb178bc1dcf89955b45768ab6c1/build.yaml
wget https://raw.githubusercontent.com/aidando73/llama-stack/9165502582cd7cb178bc1dcf89955b45768ab6c1/run.yaml
# Create environment if not already
conda create --prefix ./envs python=3.10
conda activate ./envs
# Build
pip install -e . && llama stack build --config ./build.yaml --image-type conda
# Activate built environment
conda activate llamastack-groq
```
<details>
<summary>Manual</summary>
```bash
llama stack run ./run.yaml --port 5001
```
Via this Jupyter notebook:
9165502582/hello.ipynb
</details>
## 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).
- [x] 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?
- [x] Updated relevant documentation.
- [ ] Wrote necessary unit or integration tests.
# What does this PR do?
Addresses issue #679
- Adds support for the response_format field for chat completions and
completions so users can get their outputs in JSON
## Test Plan
<details>
<summary>Integration tests</summary>
`pytest
llama_stack/providers/tests/inference/test_text_inference.py::TestInference::test_structured_output
-k ollama -s -v`
```python
llama_stack/providers/tests/inference/test_text_inference.py::TestInference::test_structured_output[llama_8b-ollama] PASSED
llama_stack/providers/tests/inference/test_text_inference.py::TestInference::test_structured_output[llama_3b-ollama] PASSED
================================== 2 passed, 18 deselected, 3 warnings in 41.41s ==================================
```
</details>
<details>
<summary>Manual Tests</summary>
```
export INFERENCE_MODEL=meta-llama/Llama-3.2-3B-Instruct
export OLLAMA_INFERENCE_MODEL=llama3.2:3b-instruct-fp16
export LLAMA_STACK_PORT=5000
ollama run $OLLAMA_INFERENCE_MODEL --keepalive 60m
llama stack build --template ollama --image-type conda
llama stack run ./run.yaml \
--port $LLAMA_STACK_PORT \
--env INFERENCE_MODEL=$INFERENCE_MODEL \
--env OLLAMA_URL=http://localhost:11434
```
```python
client = LlamaStackClient(base_url=f"http://localhost:{os.environ['LLAMA_STACK_PORT']}")
MODEL_ID=meta-llama/Llama-3.2-3B-Instruct
prompt =f"""
Create a step by step plan to complete the task of creating a codebase that is a web server that has an API endpoint that translates text from English to French.
You have 3 different operations you can perform. You can create a file, update a file, or delete a file.
Limit your step by step plan to only these operations per step.
Don't create more than 10 steps.
Please ensure there's a README.md file in the root of the codebase that describes the codebase and how to run it.
Please ensure there's a requirements.txt file in the root of the codebase that describes the dependencies of the codebase.
"""
response = client.inference.chat_completion(
model_id=MODEL_ID,
messages=[
{"role": "user", "content": prompt},
],
sampling_params={
"max_tokens": 200000,
},
response_format={
"type": "json_schema",
"json_schema": {
"$schema": "http://json-schema.org/draft-07/schema#",
"title": "Plan",
"description": f"A plan to complete the task of creating a codebase that is a web server that has an API endpoint that translates text from English to French.",
"type": "object",
"properties": {
"steps": {
"type": "array",
"items": {
"type": "string"
}
}
},
"required": ["steps"],
"additionalProperties": False,
}
},
stream=True,
)
content = ""
for chunk in response:
if chunk.event.delta:
print(chunk.event.delta, end="", flush=True)
content += chunk.event.delta
try:
plan = json.loads(content)
print(plan)
except Exception as e:
print(f"Error parsing plan into JSON: {e}")
plan = {"steps": []}
```
Outputs:
```json
{
"steps": [
"Update the requirements.txt file to include the updated dependencies specified in the peer's feedback, including the Google Cloud Translation API key.",
"Update the app.py file to address the code smells and incorporate the suggested improvements, such as handling errors and exceptions, initializing the Translator object correctly, adding input validation, using type hints and docstrings, and removing unnecessary logging statements.",
"Create a README.md file that describes the codebase and how to run it.",
"Ensure the README.md file is up-to-date and accurate.",
"Update the requirements.txt file to reflect any additional dependencies specified by the peer's feedback.",
"Add documentation for each function in the app.py file using docstrings.",
"Implement logging statements throughout the app.py file to monitor application execution.",
"Test the API endpoint to ensure it correctly translates text from English to French and handles errors properly.",
"Refactor the code to follow PEP 8 style guidelines and ensure consistency in naming conventions, indentation, and spacing.",
"Create a new folder for logs and add a logging configuration file (e.g., logconfig.json) that specifies the logging level and output destination.",
"Deploy the web server on a production environment (e.g., AWS Elastic Beanstalk or Google Cloud Platform) to make it accessible to external users."
]
}
```
</details>
## Sources
- Ollama api docs:
https://github.com/ollama/ollama/blob/main/docs/api.md#generate-a-completion
- Ollama structured output docs:
https://github.com/ollama/ollama/blob/main/docs/api.md#request-structured-outputs
## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the
other checks if that's the case).
- [x] 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.
- [x] Wrote necessary unit or integration tests.
