Sync updates from stainless branch: yanxi0830/dev (#209)

# What does this PR do?
[Provide a short summary of what this PR does and why. Link to relevant
issues if applicable.]

[//]: # (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)

Author: yanxi0830

src/llama_stack_client/resources/eval/jobs.py

@@ -13,9 +13,9 @@
     async_to_raw_response_wrapper,
     async_to_streamed_response_wrapper,
 )
+from ...types.job import Job
 from ..._base_client import make_request_options
 from ...types.evaluate_response import EvaluateResponse
-from ...types.eval.job_status_response import JobStatusResponse
 
 __all__ = ["JobsResource", "AsyncJobsResource"]
 
@@ -124,7 +124,7 @@ def status(
         extra_query: Query | None = None,
         extra_body: Body | None = None,
         timeout: float | httpx.Timeout | None | NotGiven = NOT_GIVEN,
-    ) -> JobStatusResponse:
+    ) -> Job:
         """
         Get the status of a job.
 
@@ -146,7 +146,7 @@ def status(
             options=make_request_options(
                 extra_headers=extra_headers, extra_query=extra_query, extra_body=extra_body, timeout=timeout
             ),
-            cast_to=JobStatusResponse,
+            cast_to=Job,
         )
 
 
@@ -254,7 +254,7 @@ async def status(
         extra_query: Query | None = None,
         extra_body: Body | None = None,
         timeout: float | httpx.Timeout | None | NotGiven = NOT_GIVEN,
-    ) -> JobStatusResponse:
+    ) -> Job:
         """
         Get the status of a job.
 
@@ -276,7 +276,7 @@ async def status(
             options=make_request_options(
                 extra_headers=extra_headers, extra_query=extra_query, extra_body=extra_body, timeout=timeout
             ),
-            cast_to=JobStatusResponse,
+            cast_to=Job,
         )
 
 

src/llama_stack_client/resources/post_training/post_training.py

@@ -14,7 +14,10 @@
     JobResourceWithStreamingResponse,
     AsyncJobResourceWithStreamingResponse,
 )
-from ...types import post_training_preference_optimize_params, post_training_supervised_fine_tune_params
+from ...types import (
+    post_training_preference_optimize_params,
+    post_training_supervised_fine_tune_params,
+)
 from ..._types import NOT_GIVEN, Body, Query, Headers, NotGiven
 from ..._utils import (
     maybe_transform,
@@ -30,6 +33,7 @@
 )
 from ..._base_client import make_request_options
 from ...types.post_training_job import PostTrainingJob
+from ...types.algorithm_config_param import AlgorithmConfigParam
 
 __all__ = ["PostTrainingResource", "AsyncPostTrainingResource"]
 
@@ -111,7 +115,7 @@ def supervised_fine_tune(
         logger_config: Dict[str, Union[bool, float, str, Iterable[object], object, None]],
         model: str,
         training_config: post_training_supervised_fine_tune_params.TrainingConfig,
-        algorithm_config: post_training_supervised_fine_tune_params.AlgorithmConfig | NotGiven = NOT_GIVEN,
+        algorithm_config: AlgorithmConfigParam | NotGiven = NOT_GIVEN,
         checkpoint_dir: str | NotGiven = NOT_GIVEN,
         # Use the following arguments if you need to pass additional parameters to the API that aren't available via kwargs.
         # The extra values given here take precedence over values defined on the client or passed to this method.
@@ -228,7 +232,7 @@ async def supervised_fine_tune(
         logger_config: Dict[str, Union[bool, float, str, Iterable[object], object, None]],
         model: str,
         training_config: post_training_supervised_fine_tune_params.TrainingConfig,
-        algorithm_config: post_training_supervised_fine_tune_params.AlgorithmConfig | NotGiven = NOT_GIVEN,
+        algorithm_config: AlgorithmConfigParam | NotGiven = NOT_GIVEN,
         checkpoint_dir: str | NotGiven = NOT_GIVEN,
         # Use the following arguments if you need to pass additional parameters to the API that aren't available via kwargs.
         # The extra values given here take precedence over values defined on the client or passed to this method.

src/llama_stack_client/types/__init__.py

@@ -76,6 +76,7 @@
 from .model_register_params import ModelRegisterParams as ModelRegisterParams
 from .query_chunks_response import QueryChunksResponse as QueryChunksResponse
 from .query_condition_param import QueryConditionParam as QueryConditionParam
+from .algorithm_config_param import AlgorithmConfigParam as AlgorithmConfigParam
 from .benchmark_config_param import BenchmarkConfigParam as BenchmarkConfigParam
 from .list_datasets_response import ListDatasetsResponse as ListDatasetsResponse
 from .provider_list_response import ProviderListResponse as ProviderListResponse

src/llama_stack_client/types/algorithm_config_param.py

@@ -0,0 +1,37 @@
+# File generated from our OpenAPI spec by Stainless. See CONTRIBUTING.md for details.
+
+from __future__ import annotations
+
+from typing import List, Union
+from typing_extensions import Literal, Required, TypeAlias, TypedDict
+
+__all__ = ["AlgorithmConfigParam", "LoraFinetuningConfig", "QatFinetuningConfig"]
+
+
+class LoraFinetuningConfig(TypedDict, total=False):
+    alpha: Required[int]
+
+    apply_lora_to_mlp: Required[bool]
+
+    apply_lora_to_output: Required[bool]
+
+    lora_attn_modules: Required[List[str]]
+
+    rank: Required[int]
+
+    type: Required[Literal["LoRA"]]
+
+    quantize_base: bool
+
+    use_dora: bool
+
+
+class QatFinetuningConfig(TypedDict, total=False):
+    group_size: Required[int]
+
+    quantizer_name: Required[str]
+
+    type: Required[Literal["QAT"]]
+
+
+AlgorithmConfigParam: TypeAlias = Union[LoraFinetuningConfig, QatFinetuningConfig]

src/llama_stack_client/types/eval/__init__.py

@@ -1,5 +1,3 @@
 # File generated from our OpenAPI spec by Stainless. See CONTRIBUTING.md for details.
 
 from __future__ import annotations
-
-from .job_status_response import JobStatusResponse as JobStatusResponse

src/llama_stack_client/types/eval/job_status_response.py

@@ -1,5 +1,6 @@
 # File generated from our OpenAPI spec by Stainless. See CONTRIBUTING.md for details.
 
+from typing_extensions import Literal
 
 from .._models import BaseModel
 
@@ -8,3 +9,5 @@
 
 class Job(BaseModel):
     job_id: str
+
+    status: Literal["completed", "in_progress", "failed", "scheduled"]

src/llama_stack_client/types/job.py

@@ -2,18 +2,17 @@
 
 from __future__ import annotations
 
-from typing import Dict, List, Union, Iterable
-from typing_extensions import Literal, Required, TypeAlias, TypedDict
+from typing import Dict, Union, Iterable
+from typing_extensions import Literal, Required, TypedDict
+
+from .algorithm_config_param import AlgorithmConfigParam
 
 __all__ = [
     "PostTrainingSupervisedFineTuneParams",
     "TrainingConfig",
     "TrainingConfigDataConfig",
     "TrainingConfigOptimizerConfig",
     "TrainingConfigEfficiencyConfig",
-    "AlgorithmConfig",
-    "AlgorithmConfigLoraFinetuningConfig",
-    "AlgorithmConfigQatFinetuningConfig",
 ]
 
 
@@ -28,7 +27,7 @@ class PostTrainingSupervisedFineTuneParams(TypedDict, total=False):
 
     training_config: Required[TrainingConfig]
 
-    algorithm_config: AlgorithmConfig
+    algorithm_config: AlgorithmConfigParam
 
     checkpoint_dir: str
 
@@ -85,32 +84,3 @@ class TrainingConfig(TypedDict, total=False):
     dtype: str
 
     efficiency_config: TrainingConfigEfficiencyConfig
-
-
-class AlgorithmConfigLoraFinetuningConfig(TypedDict, total=False):
-    alpha: Required[int]
-
-    apply_lora_to_mlp: Required[bool]
-
-    apply_lora_to_output: Required[bool]
-
-    lora_attn_modules: Required[List[str]]
-
-    rank: Required[int]
-
-    type: Required[Literal["LoRA"]]
-
-    quantize_base: bool
-
-    use_dora: bool
-
-
-class AlgorithmConfigQatFinetuningConfig(TypedDict, total=False):
-    group_size: Required[int]
-
-    quantizer_name: Required[str]
-
-    type: Required[Literal["QAT"]]
-
-
-AlgorithmConfig: TypeAlias = Union[AlgorithmConfigLoraFinetuningConfig, AlgorithmConfigQatFinetuningConfig]

src/llama_stack_client/types/post_training_supervised_fine_tune_params.py

@@ -9,7 +9,7 @@
 
 
 class ToolInvocationResult(BaseModel):
-    content: InterleavedContent
+    content: Optional[InterleavedContent] = None
     """A image content item"""
 
     error_code: Optional[int] = None

src/llama_stack_client/types/tool_invocation_result.py

@@ -9,8 +9,7 @@
 
 from tests.utils import assert_matches_type
 from llama_stack_client import LlamaStackClient, AsyncLlamaStackClient
-from llama_stack_client.types import EvaluateResponse
-from llama_stack_client.types.eval import JobStatusResponse
+from llama_stack_client.types import Job, EvaluateResponse
 
 base_url = os.environ.get("TEST_API_BASE_URL", "http://127.0.0.1:4010")
 
@@ -120,7 +119,7 @@ def test_method_status(self, client: LlamaStackClient) -> None:
             job_id="job_id",
             benchmark_id="benchmark_id",
         )
-        assert_matches_type(JobStatusResponse, job, path=["response"])
+        assert_matches_type(Job, job, path=["response"])
 
     @parametrize
     def test_raw_response_status(self, client: LlamaStackClient) -> None:
@@ -132,7 +131,7 @@ def test_raw_response_status(self, client: LlamaStackClient) -> None:
         assert response.is_closed is True
         assert response.http_request.headers.get("X-Stainless-Lang") == "python"
         job = response.parse()
-        assert_matches_type(JobStatusResponse, job, path=["response"])
+        assert_matches_type(Job, job, path=["response"])
 
     @parametrize
     def test_streaming_response_status(self, client: LlamaStackClient) -> None:
@@ -144,7 +143,7 @@ def test_streaming_response_status(self, client: LlamaStackClient) -> None:
             assert response.http_request.headers.get("X-Stainless-Lang") == "python"
 
             job = response.parse()
-            assert_matches_type(JobStatusResponse, job, path=["response"])
+            assert_matches_type(Job, job, path=["response"])
 
         assert cast(Any, response.is_closed) is True
 
@@ -268,7 +267,7 @@ async def test_method_status(self, async_client: AsyncLlamaStackClient) -> None:
             job_id="job_id",
             benchmark_id="benchmark_id",
         )
-        assert_matches_type(JobStatusResponse, job, path=["response"])
+        assert_matches_type(Job, job, path=["response"])
 
     @parametrize
     async def test_raw_response_status(self, async_client: AsyncLlamaStackClient) -> None:
@@ -280,7 +279,7 @@ async def test_raw_response_status(self, async_client: AsyncLlamaStackClient) ->
         assert response.is_closed is True
         assert response.http_request.headers.get("X-Stainless-Lang") == "python"
         job = await response.parse()
-        assert_matches_type(JobStatusResponse, job, path=["response"])
+        assert_matches_type(Job, job, path=["response"])
 
     @parametrize
     async def test_streaming_response_status(self, async_client: AsyncLlamaStackClient) -> None:
@@ -292,7 +291,7 @@ async def test_streaming_response_status(self, async_client: AsyncLlamaStackClie
             assert response.http_request.headers.get("X-Stainless-Lang") == "python"
 
             job = await response.parse()
-            assert_matches_type(JobStatusResponse, job, path=["response"])
+            assert_matches_type(Job, job, path=["response"])
 
         assert cast(Any, response.is_closed) is True