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?
- sqlite_vec not added to all template yet, disable test for now to
unblock release cut
[//]: # (If resolving an issue, uncomment and update the line below)
[//]: # (Closes #[issue-number])
## Test Plan
<img width="846" alt="image"
src="https://github.com/user-attachments/assets/fa896497-f37c-4cdf-bc62-21893afbd392"
/>
[//]: # (## Documentation)
# 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?
This PR adds `sqlite_vec` as an additional inline vectordb.
Tested with `ollama` by adding the `vector_io` object in
`./llama_stack/templates/ollama/run.yaml` :
```yaml
vector_io:
- provider_id: sqlite_vec
provider_type: inline::sqlite_vec
config:
kvstore:
type: sqlite
namespace: null
db_path: ${env.SQLITE_STORE_DIR:~/.llama/distributions/ollama}/sqlite_vec.db
db_path: ${env.SQLITE_STORE_DIR:~/.llama/distributions/ollama}/sqlite_vec.db
```
I also updated the `./tests/client-sdk/vector_io/test_vector_io.py` test
file with:
```python
INLINE_VECTOR_DB_PROVIDERS = ["faiss", "sqlite_vec"]
```
And parameterized the relevant tests.
[//]: # (If resolving an issue, uncomment and update the line below)
# Closes
https://github.com/meta-llama/llama-stack/issues/1005
## Test Plan
I ran the tests with:
```bash
INFERENCE_MODEL=llama3.2:3b-instruct-fp16 LLAMA_STACK_CONFIG=ollama pytest -s -v tests/client-sdk/vector_io/test_vector_io.py
```
Which outputs:
```python
...
PASSED
tests/client-sdk/vector_io/test_vector_io.py::test_vector_db_retrieve[all-MiniLM-L6-v2-sqlite_vec] PASSED
tests/client-sdk/vector_io/test_vector_io.py::test_vector_db_list PASSED
tests/client-sdk/vector_io/test_vector_io.py::test_vector_db_register[all-MiniLM-L6-v2-faiss] PASSED
tests/client-sdk/vector_io/test_vector_io.py::test_vector_db_register[all-MiniLM-L6-v2-sqlite_vec] PASSED
tests/client-sdk/vector_io/test_vector_io.py::test_vector_db_unregister[faiss] PASSED
tests/client-sdk/vector_io/test_vector_io.py::test_vector_db_unregister[sqlite_vec] PASSED
```
In addition, I ran the `rag_with_vector_db.py`
[example](https://github.com/meta-llama/llama-stack-apps/blob/main/examples/agents/rag_with_vector_db.py)
using the script below with `uv run rag_example.py`.
<details>
<summary>CLICK TO SHOW SCRIPT 👋 </summary>
```python
#!/usr/bin/env python3
import os
import uuid
from termcolor import cprint
# Set environment variables
os.environ['INFERENCE_MODEL'] = 'llama3.2:3b-instruct-fp16'
os.environ['LLAMA_STACK_CONFIG'] = 'ollama'
# Import libraries after setting environment variables
from llama_stack.distribution.library_client import LlamaStackAsLibraryClient
from llama_stack_client.lib.agents.agent import Agent
from llama_stack_client.lib.agents.event_logger import EventLogger
from llama_stack_client.types.agent_create_params import AgentConfig
from llama_stack_client.types import Document
def main():
# Initialize the client
client = LlamaStackAsLibraryClient("ollama")
vector_db_id = f"test-vector-db-{uuid.uuid4().hex}"
_ = client.initialize()
model_id = 'llama3.2:3b-instruct-fp16'
# Define the list of document URLs and create Document objects
urls = [
"chat.rst",
"llama3.rst",
"memory_optimizations.rst",
"lora_finetune.rst",
]
documents = [
Document(
document_id=f"num-{i}",
content=f"https://raw.githubusercontent.com/pytorch/torchtune/main/docs/source/tutorials/{url}",
mime_type="text/plain",
metadata={},
)
for i, url in enumerate(urls)
]
# (Optional) Use the documents as needed with your client here
client.vector_dbs.register(
provider_id='sqlite_vec',
vector_db_id=vector_db_id,
embedding_model="all-MiniLM-L6-v2",
embedding_dimension=384,
)
client.tool_runtime.rag_tool.insert(
documents=documents,
vector_db_id=vector_db_id,
chunk_size_in_tokens=512,
)
# Create agent configuration
agent_config = AgentConfig(
model=model_id,
instructions="You are a helpful assistant",
enable_session_persistence=False,
toolgroups=[
{
"name": "builtin::rag",
"args": {
"vector_db_ids": [vector_db_id],
}
}
],
)
# Instantiate the Agent
agent = Agent(client, agent_config)
# List of user prompts
user_prompts = [
"What are the top 5 topics that were explained in the documentation? Only list succinct bullet points.",
"Was anything related to 'Llama3' discussed, if so what?",
"Tell me how to use LoRA",
"What about Quantization?",
]
# Create a session for the agent
session_id = agent.create_session("test-session")
# Process each prompt and display the output
for prompt in user_prompts:
cprint(f"User> {prompt}", "green")
response = agent.create_turn(
messages=[
{
"role": "user",
"content": prompt,
}
],
session_id=session_id,
)
# Log and print events from the response
for log in EventLogger().log(response):
log.print()
if __name__ == "__main__":
main()
```
</details>
Which outputs a large summary of RAG generation.
# Documentation
Will handle documentation updates in follow-up PR.
# (- [ ] Added a Changelog entry if the change is significant)
---------
Signed-off-by: Francisco Javier Arceo <farceo@redhat.com>
# What does this PR do?
The previous image URLs were sometimes blocked by Cloudflare, causing
test failures for some users. This update replaces them with a
GitHub-hosted image (`dog.png`) from the `llama-stack` repository,
ensuring more reliable access during testing.
Signed-off-by: Sébastien Han <seb@redhat.com>
[//]: # (If resolving an issue, uncomment and update the line below)
[//]: # (Closes #[issue-number])
## Test Plan
```
$ ollama run llama3.2-vision:latest --keep-alive 2m &
$ uv run pytest -v -s -k "ollama" --inference-model=llama3.2-vision:latest llama_stack/providers/tests/inference/test_vision_inference.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 39 items / 36 deselected / 3 selected
llama_stack/providers/tests/inference/test_vision_inference.py::TestVisionModelInference::test_vision_chat_completion_non_streaming[-ollama-image0-expected_strings0] PASSED
llama_stack/providers/tests/inference/test_vision_inference.py::TestVisionModelInference::test_vision_chat_completion_non_streaming[-ollama-image1-expected_strings1]
PASSED
llama_stack/providers/tests/inference/test_vision_inference.py::TestVisionModelInference::test_vision_chat_completion_streaming[-ollama] PASSED
========================== 3 passed, 36 deselected, 2 warnings in 62.23s (0:01:02) ==========================
```
[//]: # (## Documentation)
[//]: # (- [ ] Added a Changelog entry if the change is significant)
Signed-off-by: Sébastien Han <seb@redhat.com>
# What does this PR do?
This PR removes the warnings when running tests for `remote::vllm`
provider:
```
Detected the chat template content format to be 'openai'. You can set `--chat-template-content-format` to override this.
```
## Test Plan
All tests passed without the warning messages shown above.
Signed-off-by: Yuan Tang <terrytangyuan@gmail.com>
# What does this PR do?
This significantly shortens the test time (about 10x faster) since most
of the time is spent on outputing the tokens "there are several planets
in our solar system that have...". We want to have an answer quicker,
especially when testing even larger models.
## Test Plan
```
LLAMA_STACK_BASE_URL=http://localhost:5002 pytest -v tests/client-sdk/inference/test_text_inference.py -k "test_text_chat_completion_non_streaming or test_text_chat_completion_streaming"
================================================================== test session starts ===================================================================
platform linux -- Python 3.10.16, pytest-8.3.4, pluggy-1.5.0 -- /home/yutang/.conda/envs/myenv/bin/python3.10
cachedir: .pytest_cache
rootdir: /home/yutang/repos/llama-stack
configfile: pyproject.toml
plugins: anyio-4.7.0
collected 12 items / 8 deselected / 4 selected
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 [ 25%]
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 [ 75%]
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 [100%]
```
---------
Signed-off-by: Yuan Tang <terrytangyuan@gmail.com>
# What does this PR do?
This PR splits the inference tests into text and vision to make testing
on vLLM provider easier as mentioned in
https://github.com/meta-llama/llama-stack/pull/951 since serving
multiple models (e.g. Llama-3.2-11B-Vision-Instruct and
Llama-3.1-8B-Instruct) on a single port using the OpenAI API is [not
supported yet](https://docs.vllm.ai/en/v0.5.5/serving/faq.html) so it's
a bit tricky to test both at the same time.
## Test Plan
All previously passing tests related to text still pass:
`LLAMA_STACK_BASE_URL=http://localhost:5002 pytest -v
tests/client-sdk/inference/test_text_inference.py`
All vision tests passed via `LLAMA_STACK_BASE_URL=http://localhost:5002
pytest -v tests/client-sdk/inference/test_vision_inference.py`.
Signed-off-by: Yuan Tang <terrytangyuan@gmail.com>
# What does this PR do?
In several examples we use the same faiss index , which means running it
multiple times fills up the index with duplicates which eventually
degrades the model performance on RAG as multiple copies of the same
irrelevant chunks might be picked up several times.
Fix is to ensure we create a new index each time.
Resolves issue in this discussion -
https://github.com/meta-llama/llama-stack/discussions/995
## Test Plan
Re-ran the getting started guide multiple times to see the same output
Co-authored-by: Hardik Shah <hjshah@fb.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
LLAMA_STACK_CONFIG=together pytest
\-\-inference\-model=meta\-llama/Llama\-3\.3\-70B\-Instruct -s -v
tests/client-sdk/agents/test_agents.py::test_override_system_message_behavior
## 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.
datasets.rst was removed from torchtune repo.
Signed-off-by: Ihar Hrachyshka <ihar.hrachyshka@gmail.com>
# What does this PR do?
Replace a missing 404 document with another one that exists. (Removed it
from
the list when memory_optimizations.rst was already pulled.)
## Test Plan
Please describe:
- tests you ran to verify your changes with result summaries.
- provide instructions so it can be reproduced.
## Sources
Please link relevant resources if necessary.
## Before submitting
- [x] 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.
- [ ] 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: Ihar Hrachyshka <ihar.hrachyshka@gmail.com>
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?
a test exists for image.url content, but not image.data content. this
adds the former.
## Test Plan
`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.
- [x] Wrote necessary unit or integration tests.
# What does this PR do?
Fixes a bug where agents were not working when both rag and
code-interpreter were added as tools.
## Test Plan
Added a new client_sdk test which tests for this scenario
```
LLAMA_STACK_CONFIG=together pytest -s -v tests/client-sdk -k 'test_rag_and_code_agent'
```
---------
Co-authored-by: Hardik Shah <hjshah@fb.com>
# 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?
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.
Earlier, we would have some unknown magic to identify the path for
remote endpoints when testing client_sdk/tests.
Removed that and now you have to explicitly pass a path
# 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
As title
## 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?
Default inference_model for testing: "meta-llama/Llama-3.1-8B-Instruct"
Default vision inference_model for testing:
"meta-llama/Llama-3.2-11B-Vision-Instruct"
## Test Plan
`/opt/miniconda3/envs/stack/bin/pytest -s -v
--inference-model=meta-llama/Llama-3.2-3B-Instruct
tests/client-sdk/agents`
`/opt/miniconda3/envs/stack/bin/pytest -s -v
--embedding-model=all-MiniLM-L6-v2 tests/client-sdk/vector_io`
`/opt/miniconda3/envs/stack/bin/pytest -s -v
--safety-shield=meta-llama/Llama-Guard-3-1B tests/client-sdk/safety`
## 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`
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=<...>)`
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.
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
```
# 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?
- 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.
