This PR focuses on improving the developer experience by adding
comprehensive docstrings to the API data models across the Llama Stack.
These docstrings provide detailed explanations for each model and its
fields, making the API easier to understand and use.
**Key changes:**
- **Added Docstrings:** Added reST formatted docstrings to Pydantic
models in the `llama_stack/apis/` directory. This includes models for:
- Agents (`agents.py`)
- Benchmarks (`benchmarks.py`)
- Datasets (`datasets.py`)
- Inference (`inference.py`)
- And many other API modules.
- **OpenAPI Spec Update:** Regenerated the OpenAPI specification
(`docs/_static/llama-stack-spec.yaml` and
`docs/_static/llama-stack-spec.html`) to include the new docstrings.
This will be reflected in the API documentation, providing richer
information to users.
**Impact:**
- Developers using the Llama Stack API will have a better understanding
of the data structures.
- The auto-generated API documentation is now more informative.
---------
Co-authored-by: Ashwin Bharambe <ashwin.bharambe@gmail.com>
…path
# What does this PR do?
Closes#1847
Changes:
- llama_stack/apis/common/responses.py: adds optional `url` field to
PaginatedResponse
- llama_stack/distribution/server/server.py: automatically populate the
URL field with route path
## Test Plan
- Built and ran llama stack server using the following cmds:
```bash
export INFERENCE_MODEL=llama3.1:8b
llama stack build --run --template ollama --image-type container
llama stack run llama_stack/templates/ollama/run.yaml
```
- Ran `curl` to test if we are seeing the `url` param in response:
```bash
curl -X 'GET' \
'http://localhost:8321/v1/agents' \
-H 'accept: application/json'
```
- Expected and Received Output:
`{"data":[],"has_more":false,"url":"/v1/agents"}`
---------
Co-authored-by: Rohan Awhad <rawhad@redhat.com>
# What does this PR do?
This is not part of the official OpenAI API, but we'll use this for the
logs UI.
In order to support more filtering options, I'm adopting the newly
introduced sql store in in place of the kv store.
## Test Plan
Added integration/unit tests.
# What does this PR do?
The goal of this PR is code base modernization.
Schema reflection code needed a minor adjustment to handle UnionTypes
and collections.abc.AsyncIterator. (Both are preferred for latest Python
releases.)
Note to reviewers: almost all changes here are automatically generated
by pyupgrade. Some additional unused imports were cleaned up. The only
change worth of note can be found under `docs/openapi_generator` and
`llama_stack/strong_typing/schema.py` where reflection code was updated
to deal with "newer" types.
Signed-off-by: Ihar Hrachyshka <ihar.hrachyshka@gmail.com>
# What does this PR do?
Move pagination logic from LocalFS and HuggingFace implementations into
a common helper function to ensure consistent pagination behavior across
providers. This reduces code duplication and centralizes pagination
logic in one place.
## Test Plan
Run this script:
```
from llama_stack_client import LlamaStackClient
# Initialize the client
client = LlamaStackClient(base_url="http://localhost:8321")
# Register a dataset
response = client.datasets.register(
purpose="eval/messages-answer", # or "eval/question-answer" or "post-training/messages"
source={"type": "uri", "uri": "huggingface://datasets/llamastack/simpleqa?split=train"},
dataset_id="my_dataset", # optional, will be auto-generated if not provided
metadata={"description": "My evaluation dataset"}, # optional
)
# Verify the dataset was registered by listing all datasets
datasets = client.datasets.list()
print(f"Registered datasets: {[d.identifier for d in datasets]}")
# You can then access the data using the datasetio API
# rows = client.datasets.iterrows(dataset_id="my_dataset", start_index=1, limit=2)
rows = client.datasets.iterrows(dataset_id="my_dataset")
print(f"Data: {rows.data}")
```
And play with `start_index` and `limit`.
[//]: # (## Documentation)
Signed-off-by: Sébastien Han <seb@redhat.com>
