[Backport 8.12] Add Inference API

docs/sphinx/api.rst

@@ -10,7 +10,7 @@ arguments are required for all calls.
 .. note::
 
    Some API parameters in Elasticsearch are reserved keywords in Python.
-   For example the ``from`` query parameter for pagination would be aliased as 
+   For example the ``from`` query parameter for pagination would be aliased as
    ``from_``.
 
 .. toctree::
@@ -28,6 +28,7 @@ arguments are required for all calls.
    api/graph-explore
    api/index-lifecycle-management
    api/indices
+   api/inference
    api/ingest-pipelines
    api/license
    api/logstash

docs/sphinx/api/inference.rst

@@ -0,0 +1,9 @@
+.. _inference:
+
+Inference
+---------
+.. py:module:: elasticsearch.client
+   :noindex:
+
+.. autoclass:: InferenceClient
+   :members:

elasticsearch/_async/client/__init__.py

@@ -54,6 +54,7 @@
 from .graph import GraphClient
 from .ilm import IlmClient
 from .indices import IndicesClient
+from .inference import InferenceClient
 from .ingest import IngestClient
 from .license import LicenseClient
 from .logstash import LogstashClient
@@ -434,6 +435,7 @@ def __init__(
         self.fleet = FleetClient(self)
         self.features = FeaturesClient(self)
         self.indices = IndicesClient(self)
+        self.inference = InferenceClient(self)
         self.ingest = IngestClient(self)
         self.nodes = NodesClient(self)
         self.snapshot = SnapshotClient(self)

elasticsearch/_async/client/inference.py

@@ -0,0 +1,212 @@
+#  Licensed to Elasticsearch B.V. under one or more contributor
+#  license agreements. See the NOTICE file distributed with
+#  this work for additional information regarding copyright
+#  ownership. Elasticsearch B.V. licenses this file to you under
+#  the Apache License, Version 2.0 (the "License"); you may
+#  not use this file except in compliance with the License.
+#  You may obtain a copy of the License at
+#
+# 	http://www.apache.org/licenses/LICENSE-2.0
+#
+#  Unless required by applicable law or agreed to in writing,
+#  software distributed under the License is distributed on an
+#  "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+#  KIND, either express or implied.  See the License for the
+#  specific language governing permissions and limitations
+#  under the License.
+
+import typing as t
+
+from elastic_transport import ObjectApiResponse
+
+from ._base import NamespacedClient
+from .utils import SKIP_IN_PATH, _quote, _rewrite_parameters
+
+
+class InferenceClient(NamespacedClient):
+    @_rewrite_parameters()
+    async def delete_model(
+        self,
+        *,
+        task_type: t.Union["t.Literal['sparse_embedding', 'text_embedding']", str],
+        model_id: str,
+        error_trace: t.Optional[bool] = None,
+        filter_path: t.Optional[t.Union[str, t.Sequence[str]]] = None,
+        human: t.Optional[bool] = None,
+        pretty: t.Optional[bool] = None,
+    ) -> ObjectApiResponse[t.Any]:
+        """
+        Delete model in the Inference API
+
+        `<https://www.elastic.co/guide/en/elasticsearch/reference/8.12/delete-inference-api.html>`_
+
+        :param task_type: The model task type
+        :param model_id: The unique identifier of the inference model.
+        """
+        if task_type in SKIP_IN_PATH:
+            raise ValueError("Empty value passed for parameter 'task_type'")
+        if model_id in SKIP_IN_PATH:
+            raise ValueError("Empty value passed for parameter 'model_id'")
+        __path = f"/_inference/{_quote(task_type)}/{_quote(model_id)}"
+        __query: t.Dict[str, t.Any] = {}
+        if error_trace is not None:
+            __query["error_trace"] = error_trace
+        if filter_path is not None:
+            __query["filter_path"] = filter_path
+        if human is not None:
+            __query["human"] = human
+        if pretty is not None:
+            __query["pretty"] = pretty
+        __headers = {"accept": "application/json"}
+        return await self.perform_request(  # type: ignore[return-value]
+            "DELETE", __path, params=__query, headers=__headers
+        )
+
+    @_rewrite_parameters()
+    async def get_model(
+        self,
+        *,
+        task_type: t.Union["t.Literal['sparse_embedding', 'text_embedding']", str],
+        model_id: str,
+        error_trace: t.Optional[bool] = None,
+        filter_path: t.Optional[t.Union[str, t.Sequence[str]]] = None,
+        human: t.Optional[bool] = None,
+        pretty: t.Optional[bool] = None,
+    ) -> ObjectApiResponse[t.Any]:
+        """
+        Get a model in the Inference API
+
+        `<https://www.elastic.co/guide/en/elasticsearch/reference/8.12/get-inference-api.html>`_
+
+        :param task_type: The model task type
+        :param model_id: The unique identifier of the inference model.
+        """
+        if task_type in SKIP_IN_PATH:
+            raise ValueError("Empty value passed for parameter 'task_type'")
+        if model_id in SKIP_IN_PATH:
+            raise ValueError("Empty value passed for parameter 'model_id'")
+        __path = f"/_inference/{_quote(task_type)}/{_quote(model_id)}"
+        __query: t.Dict[str, t.Any] = {}
+        if error_trace is not None:
+            __query["error_trace"] = error_trace
+        if filter_path is not None:
+            __query["filter_path"] = filter_path
+        if human is not None:
+            __query["human"] = human
+        if pretty is not None:
+            __query["pretty"] = pretty
+        __headers = {"accept": "application/json"}
+        return await self.perform_request(  # type: ignore[return-value]
+            "GET", __path, params=__query, headers=__headers
+        )
+
+    @_rewrite_parameters(
+        body_fields=("input", "task_settings"),
+    )
+    async def inference(
+        self,
+        *,
+        task_type: t.Union["t.Literal['sparse_embedding', 'text_embedding']", str],
+        model_id: str,
+        input: t.Optional[t.Union[str, t.Sequence[str]]] = None,
+        error_trace: t.Optional[bool] = None,
+        filter_path: t.Optional[t.Union[str, t.Sequence[str]]] = None,
+        human: t.Optional[bool] = None,
+        pretty: t.Optional[bool] = None,
+        task_settings: t.Optional[t.Any] = None,
+        body: t.Optional[t.Dict[str, t.Any]] = None,
+    ) -> ObjectApiResponse[t.Any]:
+        """
+        Perform inference on a model
+
+        `<https://www.elastic.co/guide/en/elasticsearch/reference/8.12/post-inference-api.html>`_
+
+        :param task_type: The model task type
+        :param model_id: The unique identifier of the inference model.
+        :param input: Text input to the model. Either a string or an array of strings.
+        :param task_settings: Optional task settings
+        """
+        if task_type in SKIP_IN_PATH:
+            raise ValueError("Empty value passed for parameter 'task_type'")
+        if model_id in SKIP_IN_PATH:
+            raise ValueError("Empty value passed for parameter 'model_id'")
+        if input is None and body is None:
+            raise ValueError("Empty value passed for parameter 'input'")
+        __path = f"/_inference/{_quote(task_type)}/{_quote(model_id)}"
+        __query: t.Dict[str, t.Any] = {}
+        __body: t.Dict[str, t.Any] = body if body is not None else {}
+        if error_trace is not None:
+            __query["error_trace"] = error_trace
+        if filter_path is not None:
+            __query["filter_path"] = filter_path
+        if human is not None:
+            __query["human"] = human
+        if pretty is not None:
+            __query["pretty"] = pretty
+        if not __body:
+            if input is not None:
+                __body["input"] = input
+            if task_settings is not None:
+                __body["task_settings"] = task_settings
+        if not __body:
+            __body = None  # type: ignore[assignment]
+        __headers = {"accept": "application/json"}
+        if __body is not None:
+            __headers["content-type"] = "application/json"
+        return await self.perform_request(  # type: ignore[return-value]
+            "POST", __path, params=__query, headers=__headers, body=__body
+        )
+
+    @_rewrite_parameters(
+        body_name="model_config",
+    )
+    async def put_model(
+        self,
+        *,
+        task_type: t.Union["t.Literal['sparse_embedding', 'text_embedding']", str],
+        model_id: str,
+        error_trace: t.Optional[bool] = None,
+        filter_path: t.Optional[t.Union[str, t.Sequence[str]]] = None,
+        human: t.Optional[bool] = None,
+        model_config: t.Optional[t.Mapping[str, t.Any]] = None,
+        body: t.Optional[t.Mapping[str, t.Any]] = None,
+        pretty: t.Optional[bool] = None,
+    ) -> ObjectApiResponse[t.Any]:
+        """
+        Configure a model for use in the Inference API
+
+        `<https://www.elastic.co/guide/en/elasticsearch/reference/8.12/put-inference-api.html>`_
+
+        :param task_type: The model task type
+        :param model_id: The unique identifier of the inference model.
+        :param model_config:
+        """
+        if task_type in SKIP_IN_PATH:
+            raise ValueError("Empty value passed for parameter 'task_type'")
+        if model_id in SKIP_IN_PATH:
+            raise ValueError("Empty value passed for parameter 'model_id'")
+        if model_config is None and body is None:
+            raise ValueError(
+                "Empty value passed for parameters 'model_config' and 'body', one of them should be set."
+            )
+        elif model_config is not None and body is not None:
+            raise ValueError("Cannot set both 'model_config' and 'body'")
+        __path = f"/_inference/{_quote(task_type)}/{_quote(model_id)}"
+        __query: t.Dict[str, t.Any] = {}
+        if error_trace is not None:
+            __query["error_trace"] = error_trace
+        if filter_path is not None:
+            __query["filter_path"] = filter_path
+        if human is not None:
+            __query["human"] = human
+        if pretty is not None:
+            __query["pretty"] = pretty
+        __body = model_config if model_config is not None else body
+        if not __body:
+            __body = None
+        __headers = {"accept": "application/json"}
+        if __body is not None:
+            __headers["content-type"] = "application/json"
+        return await self.perform_request(  # type: ignore[return-value]
+            "PUT", __path, params=__query, headers=__headers, body=__body
+        )

elasticsearch/_sync/client/__init__.py

@@ -54,6 +54,7 @@
 from .graph import GraphClient
 from .ilm import IlmClient
 from .indices import IndicesClient
+from .inference import InferenceClient
 from .ingest import IngestClient
 from .license import LicenseClient
 from .logstash import LogstashClient
@@ -434,6 +435,7 @@ def __init__(
         self.fleet = FleetClient(self)
         self.features = FeaturesClient(self)
         self.indices = IndicesClient(self)
+        self.inference = InferenceClient(self)
         self.ingest = IngestClient(self)
         self.nodes = NodesClient(self)
         self.snapshot = SnapshotClient(self)