feat(api): update API spec from langfuse/langfuse 58667f4

langfuse/api/commons/types/model.py

@@ -14,7 +14,7 @@
 
 class Model(UniversalBaseModel):
     """
-    Model definition used for transforming usage into USD cost and/or tokenization.
+    Model definition used for calculating USD cost from usage submitted with observations.
 
     Models can have either simple flat pricing or tiered pricing:
     - Flat pricing: Single price per usage type (legacy, but still supported)
@@ -77,14 +77,14 @@ class Model(UniversalBaseModel):
         typing.Optional[str], FieldMetadata(alias="tokenizerId")
     ] = pydantic.Field(default=None)
     """
-    Optional. Tokenizer to be applied to observations which match to this model. See docs for more details.
+    Legacy tokenizer identifier retained for API compatibility. Ingestion no longer uses it to infer observation usage.
     """
 
     tokenizer_config: typing_extensions.Annotated[
         typing.Any, FieldMetadata(alias="tokenizerConfig")
     ] = pydantic.Field()
     """
-    Optional. Configuration for the selected tokenizer. Needs to be JSON. See docs for more details.
+    Legacy tokenizer configuration retained for API compatibility. Ingestion no longer uses it to infer observation usage.
     """
 
     is_langfuse_managed: typing_extensions.Annotated[

langfuse/api/models/client.py

@@ -93,10 +93,10 @@ def create(
             which will automatically create a single default tier named "Standard".
 
         tokenizer_id : typing.Optional[ModelTokenizerId]
-            Optional. Tokenizer to be applied to observations which match to this model. See docs for more details.
+            Legacy tokenizer identifier retained for API compatibility. Ingestion no longer uses it to infer observation usage.
 
         tokenizer_config : typing.Optional[typing.Any]
-            Optional. Configuration for the selected tokenizer. Needs to be JSON. See docs for more details.
+            Legacy tokenizer configuration retained for API compatibility. Ingestion no longer uses it to infer observation usage.
 
         request_options : typing.Optional[RequestOptions]
             Request-specific configuration.
@@ -204,10 +204,10 @@ def upsert(
             which will automatically create a single default tier named "Standard".
 
         tokenizer_id : typing.Optional[ModelTokenizerId]
-            Optional. Tokenizer to be applied to observations which match to this model. See docs for more details.
+            Legacy tokenizer identifier retained for API compatibility. Ingestion no longer uses it to infer observation usage.
 
         tokenizer_config : typing.Optional[typing.Any]
-            Optional. Configuration for the selected tokenizer. Needs to be JSON. See docs for more details.
+            Legacy tokenizer configuration retained for API compatibility. Ingestion no longer uses it to infer observation usage.
 
         request_options : typing.Optional[RequestOptions]
             Request-specific configuration.
@@ -446,10 +446,10 @@ async def create(
             which will automatically create a single default tier named "Standard".
 
         tokenizer_id : typing.Optional[ModelTokenizerId]
-            Optional. Tokenizer to be applied to observations which match to this model. See docs for more details.
+            Legacy tokenizer identifier retained for API compatibility. Ingestion no longer uses it to infer observation usage.
 
         tokenizer_config : typing.Optional[typing.Any]
-            Optional. Configuration for the selected tokenizer. Needs to be JSON. See docs for more details.
+            Legacy tokenizer configuration retained for API compatibility. Ingestion no longer uses it to infer observation usage.
 
         request_options : typing.Optional[RequestOptions]
             Request-specific configuration.
@@ -565,10 +565,10 @@ async def upsert(
             which will automatically create a single default tier named "Standard".
 
         tokenizer_id : typing.Optional[ModelTokenizerId]
-            Optional. Tokenizer to be applied to observations which match to this model. See docs for more details.
+            Legacy tokenizer identifier retained for API compatibility. Ingestion no longer uses it to infer observation usage.
 
         tokenizer_config : typing.Optional[typing.Any]
-            Optional. Configuration for the selected tokenizer. Needs to be JSON. See docs for more details.
+            Legacy tokenizer configuration retained for API compatibility. Ingestion no longer uses it to infer observation usage.
 
         request_options : typing.Optional[RequestOptions]
             Request-specific configuration.

langfuse/api/models/raw_client.py

@@ -92,10 +92,10 @@ def create(
             which will automatically create a single default tier named "Standard".
 
         tokenizer_id : typing.Optional[ModelTokenizerId]
-            Optional. Tokenizer to be applied to observations which match to this model. See docs for more details.
+            Legacy tokenizer identifier retained for API compatibility. Ingestion no longer uses it to infer observation usage.
 
         tokenizer_config : typing.Optional[typing.Any]
-            Optional. Configuration for the selected tokenizer. Needs to be JSON. See docs for more details.
+            Legacy tokenizer configuration retained for API compatibility. Ingestion no longer uses it to infer observation usage.
 
         request_options : typing.Optional[RequestOptions]
             Request-specific configuration.
@@ -269,10 +269,10 @@ def upsert(
             which will automatically create a single default tier named "Standard".
 
         tokenizer_id : typing.Optional[ModelTokenizerId]
-            Optional. Tokenizer to be applied to observations which match to this model. See docs for more details.
+            Legacy tokenizer identifier retained for API compatibility. Ingestion no longer uses it to infer observation usage.
 
         tokenizer_config : typing.Optional[typing.Any]
-            Optional. Configuration for the selected tokenizer. Needs to be JSON. See docs for more details.
+            Legacy tokenizer configuration retained for API compatibility. Ingestion no longer uses it to infer observation usage.
 
         request_options : typing.Optional[RequestOptions]
             Request-specific configuration.
@@ -753,10 +753,10 @@ async def create(
             which will automatically create a single default tier named "Standard".
 
         tokenizer_id : typing.Optional[ModelTokenizerId]
-            Optional. Tokenizer to be applied to observations which match to this model. See docs for more details.
+            Legacy tokenizer identifier retained for API compatibility. Ingestion no longer uses it to infer observation usage.
 
         tokenizer_config : typing.Optional[typing.Any]
-            Optional. Configuration for the selected tokenizer. Needs to be JSON. See docs for more details.
+            Legacy tokenizer configuration retained for API compatibility. Ingestion no longer uses it to infer observation usage.
 
         request_options : typing.Optional[RequestOptions]
             Request-specific configuration.
@@ -930,10 +930,10 @@ async def upsert(
             which will automatically create a single default tier named "Standard".
 
         tokenizer_id : typing.Optional[ModelTokenizerId]
-            Optional. Tokenizer to be applied to observations which match to this model. See docs for more details.
+            Legacy tokenizer identifier retained for API compatibility. Ingestion no longer uses it to infer observation usage.
 
         tokenizer_config : typing.Optional[typing.Any]
-            Optional. Configuration for the selected tokenizer. Needs to be JSON. See docs for more details.
+            Legacy tokenizer configuration retained for API compatibility. Ingestion no longer uses it to infer observation usage.
 
         request_options : typing.Optional[RequestOptions]
             Request-specific configuration.

langfuse/api/models/types/create_model_request.py

@@ -89,14 +89,14 @@ class CreateModelRequest(UniversalBaseModel):
         typing.Optional[ModelTokenizerId], FieldMetadata(alias="tokenizerId")
     ] = pydantic.Field(default=None)
     """
-    Optional. Tokenizer to be applied to observations which match to this model. See docs for more details.
+    Legacy tokenizer identifier retained for API compatibility. Ingestion no longer uses it to infer observation usage.
     """
 
     tokenizer_config: typing_extensions.Annotated[
         typing.Optional[typing.Any], FieldMetadata(alias="tokenizerConfig")
     ] = pydantic.Field(default=None)
     """
-    Optional. Configuration for the selected tokenizer. Needs to be JSON. See docs for more details.
+    Legacy tokenizer configuration retained for API compatibility. Ingestion no longer uses it to infer observation usage.
     """
 
     model_config: typing.ClassVar[pydantic.ConfigDict] = pydantic.ConfigDict(

langfuse/api/models/types/model_tokenizer_id.py

@@ -9,7 +9,7 @@
 
 class ModelTokenizerId(enum.StrEnum):
     """
-    Tokenizer supported by Langfuse for model usage inference.
+    Legacy tokenizer identifier retained for API compatibility. Ingestion no longer uses it to infer observation usage.
     """
 
     OPENAI = "openai"

langfuse/api/observations/client.py

@@ -56,7 +56,10 @@ def get_many(
         ## Cursor-based Pagination
         This endpoint uses cursor-based pagination for efficient traversal of large datasets.
         The cursor is returned in the response metadata and should be passed in subsequent requests
-        to retrieve the next page of results.
+        to retrieve the next page of results. The `limit` parameter is a maximum: a page may contain
+        fewer items than the requested limit, including zero items, while `meta.cursor` is present.
+        Continue requesting pages until `meta.cursor` is absent.
+        Requests without a lower start-time bound may search only from January 1, 2020.
 
         ## Field Selection
         Use the `fields` parameter to control which observation fields are returned:
@@ -92,7 +95,7 @@ def get_many(
             Example: "key1,key2"
 
         limit : typing.Optional[int]
-            Number of items to return per page. Maximum 1000, default 50.
+            Maximum number of items to return per page. A page may contain fewer items, including zero items, while meta.cursor is present. Maximum 1000, default 50.
 
         cursor : typing.Optional[str]
             Base64-encoded cursor for pagination. Use the cursor from the previous response to get the next page.
@@ -342,7 +345,10 @@ async def get_many(
         ## Cursor-based Pagination
         This endpoint uses cursor-based pagination for efficient traversal of large datasets.
         The cursor is returned in the response metadata and should be passed in subsequent requests
-        to retrieve the next page of results.
+        to retrieve the next page of results. The `limit` parameter is a maximum: a page may contain
+        fewer items than the requested limit, including zero items, while `meta.cursor` is present.
+        Continue requesting pages until `meta.cursor` is absent.
+        Requests without a lower start-time bound may search only from January 1, 2020.
 
         ## Field Selection
         Use the `fields` parameter to control which observation fields are returned:
@@ -378,7 +384,7 @@ async def get_many(
             Example: "key1,key2"
 
         limit : typing.Optional[int]
-            Number of items to return per page. Maximum 1000, default 50.
+            Maximum number of items to return per page. A page may contain fewer items, including zero items, while meta.cursor is present. Maximum 1000, default 50.
 
         cursor : typing.Optional[str]
             Base64-encoded cursor for pagination. Use the cursor from the previous response to get the next page.

langfuse/api/observations/raw_client.py

@@ -54,7 +54,10 @@ def get_many(
         ## Cursor-based Pagination
         This endpoint uses cursor-based pagination for efficient traversal of large datasets.
         The cursor is returned in the response metadata and should be passed in subsequent requests
-        to retrieve the next page of results.
+        to retrieve the next page of results. The `limit` parameter is a maximum: a page may contain
+        fewer items than the requested limit, including zero items, while `meta.cursor` is present.
+        Continue requesting pages until `meta.cursor` is absent.
+        Requests without a lower start-time bound may search only from January 1, 2020.
 
         ## Field Selection
         Use the `fields` parameter to control which observation fields are returned:
@@ -90,7 +93,7 @@ def get_many(
             Example: "key1,key2"
 
         limit : typing.Optional[int]
-            Number of items to return per page. Maximum 1000, default 50.
+            Maximum number of items to return per page. A page may contain fewer items, including zero items, while meta.cursor is present. Maximum 1000, default 50.
 
         cursor : typing.Optional[str]
             Base64-encoded cursor for pagination. Use the cursor from the previous response to get the next page.
@@ -399,7 +402,10 @@ async def get_many(
         ## Cursor-based Pagination
         This endpoint uses cursor-based pagination for efficient traversal of large datasets.
         The cursor is returned in the response metadata and should be passed in subsequent requests
-        to retrieve the next page of results.
+        to retrieve the next page of results. The `limit` parameter is a maximum: a page may contain
+        fewer items than the requested limit, including zero items, while `meta.cursor` is present.
+        Continue requesting pages until `meta.cursor` is absent.
+        Requests without a lower start-time bound may search only from January 1, 2020.
 
         ## Field Selection
         Use the `fields` parameter to control which observation fields are returned:
@@ -435,7 +441,7 @@ async def get_many(
             Example: "key1,key2"
 
         limit : typing.Optional[int]
-            Number of items to return per page. Maximum 1000, default 50.
+            Maximum number of items to return per page. A page may contain fewer items, including zero items, while meta.cursor is present. Maximum 1000, default 50.
 
         cursor : typing.Optional[str]
             Base64-encoded cursor for pagination. Use the cursor from the previous response to get the next page.

langfuse/api/observations/types/observations_v2meta.py

@@ -11,6 +11,11 @@ class ObservationsV2Meta(CursorMetaResponse):
     Metadata for cursor-based pagination.
     """
 
+    comment: typing.Optional[str] = pydantic.Field(default=None)
+    """
+    Present when an empty page has a cursor; continue requesting pages until the cursor is absent.
+    """
+
     model_config: typing.ClassVar[pydantic.ConfigDict] = pydantic.ConfigDict(
         extra="allow", frozen=True
     )

langfuse/api/observations/types/observations_v2response.py

@@ -13,7 +13,9 @@ class ObservationsV2Response(UniversalBaseModel):
     Response containing observations with field-group-based filtering and cursor-based pagination.
 
     The `data` array contains observation objects with only the requested field groups included.
-    Use the `cursor` in `meta` to retrieve the next page of results.
+    Use the `cursor` in `meta` to retrieve the next page of results. The array may contain fewer
+    than the requested `limit` items, or be empty, while a cursor is present. Continue until the
+    cursor is absent.
     """
 
     data: typing.List[ObservationV2] = pydantic.Field()

langfuse/api/unstable/__init__.py

@@ -61,13 +61,24 @@
     )
     from .topics import (
         Topic,
+        TopicAssignment,
+        TopicAssignmentList,
+        TopicAssignmentStatus,
+        TopicAssignmentTopic,
         TopicFacet,
         TopicFacetCounts,
         TopicFacetList,
         TopicFacetPublishedRun,
         TopicFacetRef,
         TopicList,
+        TopicResultListMeta,
+        TopicResultsOrderBy,
+        TopicRule,
+        TopicRuleList,
         TopicStatusCounts,
+        TopicSummary,
+        TopicSummaryList,
+        TopicSummaryState,
         TopicWindow,
         TopicWithStatus,
         TopicsOrderBy,
@@ -115,13 +126,24 @@
     "PublicApiValidationIssue": ".errors",
     "TooManyRequestsError": ".errors",
     "Topic": ".topics",
+    "TopicAssignment": ".topics",
+    "TopicAssignmentList": ".topics",
+    "TopicAssignmentStatus": ".topics",
+    "TopicAssignmentTopic": ".topics",
     "TopicFacet": ".topics",
     "TopicFacetCounts": ".topics",
     "TopicFacetList": ".topics",
     "TopicFacetPublishedRun": ".topics",
     "TopicFacetRef": ".topics",
     "TopicList": ".topics",
+    "TopicResultListMeta": ".topics",
+    "TopicResultsOrderBy": ".topics",
+    "TopicRule": ".topics",
+    "TopicRuleList": ".topics",
     "TopicStatusCounts": ".topics",
+    "TopicSummary": ".topics",
+    "TopicSummaryList": ".topics",
+    "TopicSummaryState": ".topics",
     "TopicWindow": ".topics",
     "TopicWithStatus": ".topics",
     "TopicsOrderBy": ".topics",
@@ -207,13 +229,24 @@ def __dir__():
     "PublicApiValidationIssue",
     "TooManyRequestsError",
     "Topic",
+    "TopicAssignment",
+    "TopicAssignmentList",
+    "TopicAssignmentStatus",
+    "TopicAssignmentTopic",
     "TopicFacet",
     "TopicFacetCounts",
     "TopicFacetList",
     "TopicFacetPublishedRun",
     "TopicFacetRef",
     "TopicList",
+    "TopicResultListMeta",
+    "TopicResultsOrderBy",
+    "TopicRule",
+    "TopicRuleList",
     "TopicStatusCounts",
+    "TopicSummary",
+    "TopicSummaryList",
+    "TopicSummaryState",
     "TopicWindow",
     "TopicWithStatus",
     "TopicsOrderBy",