feat(api): api update

Author: stainless-app[bot]

.stats.yml

@@ -1,4 +1,4 @@
 configured_endpoints: 9
-openapi_spec_url: https://storage.googleapis.com/stainless-sdk-openapi-specs/lemma%2Flemma-871ffb9ecbbea62ed720017145c0bae1900d5a75d426bc34a9e192d22c94c86d.yml
-openapi_spec_hash: c1108108d12010a663c600436bf0d24d
+openapi_spec_url: https://storage.googleapis.com/stainless-sdk-openapi-specs/lemma%2Flemma-9229b0c13c7281e2bf2698cb517be411c7a19790066dd9b8f5fe2803b2b4c6c7.yml
+openapi_spec_hash: c5017ef051af46ea4b2d9817e54f6657
 config_hash: 017a31b2ac0856f4d4152a5173e6fa18

src/lemma/resources/datasets/datasets.py

@@ -2,13 +2,13 @@
 
 from __future__ import annotations
 
-from typing import Dict, Optional
+from typing import Dict, Mapping, Optional, cast
 
 import httpx
 
 from ...types import dataset_generate_schema_params, dataset_generate_dataset_params, dataset_generate_validators_params
 from ..._types import Body, Omit, Query, Headers, NotGiven, FileTypes, omit, not_given
-from ..._utils import maybe_transform, async_maybe_transform
+from ..._utils import extract_files, maybe_transform, deepcopy_minimal, async_maybe_transform
 from ..._compat import cached_property
 from ..._resource import SyncAPIResource, AsyncAPIResource
 from ..._response import (
@@ -137,10 +137,6 @@ def generate_schema(
         seed_description must be provided.
 
         Args:
-          seed_description: The seed description to generate a schema from
-
-          seed_file: The seed file to generate a schema from
-
           extra_headers: Send extra headers
 
           extra_query: Add additional query parameters to the request
@@ -149,15 +145,21 @@ def generate_schema(
 
           timeout: Override the client-level default timeout for this request, in seconds
         """
+        body = deepcopy_minimal(
+            {
+                "seed_description": seed_description,
+                "seed_file": seed_file,
+            }
+        )
+        files = extract_files(cast(Mapping[str, object], body), paths=[["seed_file"]])
+        # It should be noted that the actual Content-Type header that will be
+        # sent to the server will contain a `boundary` parameter, e.g.
+        # multipart/form-data; boundary=---abc--
+        extra_headers = {"Content-Type": "multipart/form-data", **(extra_headers or {})}
         return self._post(
             "/datasets/generate-schema",
-            body=maybe_transform(
-                {
-                    "seed_description": seed_description,
-                    "seed_file": seed_file,
-                },
-                dataset_generate_schema_params.DatasetGenerateSchemaParams,
-            ),
+            body=maybe_transform(body, dataset_generate_schema_params.DatasetGenerateSchemaParams),
+            files=files,
             options=make_request_options(
                 extra_headers=extra_headers, extra_query=extra_query, extra_body=extra_body, timeout=timeout
             ),
@@ -316,10 +318,6 @@ async def generate_schema(
         seed_description must be provided.
 
         Args:
-          seed_description: The seed description to generate a schema from
-
-          seed_file: The seed file to generate a schema from
-
           extra_headers: Send extra headers
 
           extra_query: Add additional query parameters to the request
@@ -328,15 +326,21 @@ async def generate_schema(
 
           timeout: Override the client-level default timeout for this request, in seconds
         """
+        body = deepcopy_minimal(
+            {
+                "seed_description": seed_description,
+                "seed_file": seed_file,
+            }
+        )
+        files = extract_files(cast(Mapping[str, object], body), paths=[["seed_file"]])
+        # It should be noted that the actual Content-Type header that will be
+        # sent to the server will contain a `boundary` parameter, e.g.
+        # multipart/form-data; boundary=---abc--
+        extra_headers = {"Content-Type": "multipart/form-data", **(extra_headers or {})}
         return await self._post(
             "/datasets/generate-schema",
-            body=await async_maybe_transform(
-                {
-                    "seed_description": seed_description,
-                    "seed_file": seed_file,
-                },
-                dataset_generate_schema_params.DatasetGenerateSchemaParams,
-            ),
+            body=await async_maybe_transform(body, dataset_generate_schema_params.DatasetGenerateSchemaParams),
+            files=files,
             options=make_request_options(
                 extra_headers=extra_headers, extra_query=extra_query, extra_body=extra_body, timeout=timeout
             ),

src/lemma/resources/logs.py

@@ -52,6 +52,7 @@ def create(
         input_variables: Dict[str, object],
         model: str,
         output: str,
+        project_id: str,
         prompt_id: str,
         prompt_template: str,
         prompt_tokens: int,
@@ -67,7 +68,9 @@ def create(
         Create a new log entry.
 
         Creates a new log entry to track events, activities, or API usage. Logs are
-        associated with the current tenant.
+        associated with the current tenant and project. If the prompt referenced by the
+        log doesn't exist, it will be automatically created using the prompt template as
+        the seed content.
 
         Args:
           completion_tokens: Number of tokens in the completion
@@ -78,6 +81,8 @@ def create(
 
           output: Output generated by the model
 
+          project_id: ID of the project this log belongs to
+
           prompt_id: ID of the prompt used
 
           prompt_template: Template used for the prompt
@@ -102,6 +107,7 @@ def create(
                     "input_variables": input_variables,
                     "model": model,
                     "output": output,
+                    "project_id": project_id,
                     "prompt_id": prompt_id,
                     "prompt_template": prompt_template,
                     "prompt_tokens": prompt_tokens,
@@ -228,6 +234,7 @@ async def create(
         input_variables: Dict[str, object],
         model: str,
         output: str,
+        project_id: str,
         prompt_id: str,
         prompt_template: str,
         prompt_tokens: int,
@@ -243,7 +250,9 @@ async def create(
         Create a new log entry.
 
         Creates a new log entry to track events, activities, or API usage. Logs are
-        associated with the current tenant.
+        associated with the current tenant and project. If the prompt referenced by the
+        log doesn't exist, it will be automatically created using the prompt template as
+        the seed content.
 
         Args:
           completion_tokens: Number of tokens in the completion
@@ -254,6 +263,8 @@ async def create(
 
           output: Output generated by the model
 
+          project_id: ID of the project this log belongs to
+
           prompt_id: ID of the prompt used
 
           prompt_template: Template used for the prompt
@@ -278,6 +289,7 @@ async def create(
                     "input_variables": input_variables,
                     "model": model,
                     "output": output,
+                    "project_id": project_id,
                     "prompt_id": prompt_id,
                     "prompt_template": prompt_template,
                     "prompt_tokens": prompt_tokens,

src/lemma/types/dataset_generate_schema_params.py

@@ -12,7 +12,5 @@
 
 class DatasetGenerateSchemaParams(TypedDict, total=False):
     seed_description: Optional[str]
-    """The seed description to generate a schema from"""
 
     seed_file: Optional[FileTypes]
-    """The seed file to generate a schema from"""

src/lemma/types/dataset_generate_schema_response.py

@@ -1,6 +1,6 @@
 # File generated from our OpenAPI spec by Stainless. See CONTRIBUTING.md for details.
 
-from typing import Optional
+from typing import Dict
 
 from pydantic import Field as FieldInfo
 
@@ -10,4 +10,5 @@
 
 
 class DatasetGenerateSchemaResponse(BaseModel):
-    schema_: Optional[str] = FieldInfo(alias="schema", default=None)
+    schema_: Dict[str, object] = FieldInfo(alias="schema")
+    """A valid JSON Schema object that describes the structure of the data"""

src/lemma/types/dataset_generate_validators_response.py

@@ -1,9 +1,12 @@
 # File generated from our OpenAPI spec by Stainless. See CONTRIBUTING.md for details.
 
+from typing import List
+
 from .._models import BaseModel
 
 __all__ = ["DatasetGenerateValidatorsResponse"]
 
 
 class DatasetGenerateValidatorsResponse(BaseModel):
-    validators: str
+    validators: List[str]
+    """List of CEL validation expressions, one per item"""

src/lemma/types/log.py

@@ -22,6 +22,9 @@ class Log(BaseModel):
     output: str
     """Output generated by the model"""
 
+    project_id: str = FieldInfo(alias="projectId")
+    """ID of the project this log belongs to"""
+
     prompt_id: str = FieldInfo(alias="promptId")
     """ID of the prompt used"""
 

src/lemma/types/log_create_params.py

@@ -23,6 +23,9 @@ class LogCreateParams(TypedDict, total=False):
     output: Required[str]
     """Output generated by the model"""
 
+    project_id: Required[Annotated[str, PropertyInfo(alias="projectId")]]
+    """ID of the project this log belongs to"""
+
     prompt_id: Required[Annotated[str, PropertyInfo(alias="promptId")]]
     """ID of the prompt used"""
 

src/lemma/types/log_retrieve_response.py

@@ -23,6 +23,9 @@ class LogRetrieveResponse(BaseModel):
     output: str
     """Output generated by the model"""
 
+    project_id: str = FieldInfo(alias="projectId")
+    """ID of the project this log belongs to"""
+
     prompt_id: str = FieldInfo(alias="promptId")
     """ID of the prompt used"""
 

tests/api_resources/test_logs.py

@@ -25,6 +25,7 @@ def test_method_create(self, client: Lemma) -> None:
             input_variables={"foo": "bar"},
             model="model",
             output="output",
+            project_id="182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e",
             prompt_id="promptId",
             prompt_template="promptTemplate",
             prompt_tokens=0,
@@ -40,6 +41,7 @@ def test_raw_response_create(self, client: Lemma) -> None:
             input_variables={"foo": "bar"},
             model="model",
             output="output",
+            project_id="182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e",
             prompt_id="promptId",
             prompt_template="promptTemplate",
             prompt_tokens=0,
@@ -59,6 +61,7 @@ def test_streaming_response_create(self, client: Lemma) -> None:
             input_variables={"foo": "bar"},
             model="model",
             output="output",
+            project_id="182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e",
             prompt_id="promptId",
             prompt_template="promptTemplate",
             prompt_tokens=0,
@@ -165,6 +168,7 @@ async def test_method_create(self, async_client: AsyncLemma) -> None:
             input_variables={"foo": "bar"},
             model="model",
             output="output",
+            project_id="182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e",
             prompt_id="promptId",
             prompt_template="promptTemplate",
             prompt_tokens=0,
@@ -180,6 +184,7 @@ async def test_raw_response_create(self, async_client: AsyncLemma) -> None:
             input_variables={"foo": "bar"},
             model="model",
             output="output",
+            project_id="182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e",
             prompt_id="promptId",
             prompt_template="promptTemplate",
             prompt_tokens=0,
@@ -199,6 +204,7 @@ async def test_streaming_response_create(self, async_client: AsyncLemma) -> None
             input_variables={"foo": "bar"},
             model="model",
             output="output",
+            project_id="182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e",
             prompt_id="promptId",
             prompt_template="promptTemplate",
             prompt_tokens=0,