🌿 manually modify start job from local file to match server expectations (#187)

Co-authored-by: fern-api <115122769+fern-api[bot]@users.noreply.github.com>
Co-authored-by: armandobelardo <armandoubelardo@gmail.com>
Co-authored-by: Norman Bukingolts <78187320+norman-codes@users.noreply.github.com>

Author: 4 people

src/hume/expression_measurement/batch/client_with_utils.py

@@ -1,9 +1,17 @@
 import aiofiles
 import typing
+import json as jsonlib
+from json.decoder import JSONDecodeError
 
 from ...core.request_options import RequestOptions
+from ...core.jsonable_encoder import jsonable_encoder
+from ... import core
 
+from .types.inference_base_request import InferenceBaseRequest
+from ...core.pydantic_utilities import parse_obj_as
+from .types.job_id import JobId
 from .client import AsyncBatchClient, BatchClient
+from ...core.api_error import ApiError
 
 class BatchClientWithUtils(BatchClient):
     def get_and_write_job_artifacts(
@@ -47,6 +55,69 @@ def get_and_write_job_artifacts(
             for chunk in self.get_job_artifacts(id=id, request_options=request_options):
                 f.write(chunk)
 
+    def start_inference_job_from_local_file(
+        self,
+        *,
+        file: typing.List[core.File],
+        json: typing.Optional[InferenceBaseRequest] = None,
+        request_options: typing.Optional[RequestOptions] = None,
+    ) -> str:
+        """
+        Start a new batch inference job.
+
+        Parameters
+        ----------
+        file : typing.List[core.File]
+            See core.File for more documentation
+
+        json : typing.Optional[InferenceBaseRequest]
+            The inference job configuration.
+
+        request_options : typing.Optional[RequestOptions]
+            Request-specific configuration.
+
+        Returns
+        -------
+        str
+
+
+        Examples
+        --------
+        from hume import HumeClient
+
+        client = HumeClient(
+            api_key="YOUR_API_KEY",
+        )
+        client.expression_measurement.batch.start_inference_job_from_local_file()
+        """
+        files: typing.Dict[str, typing.Any] = {
+            "file": file,
+        }
+        if json is not None:
+            files["json"] = jsonlib.dumps(jsonable_encoder(json)).encode("utf-8")
+
+        _response = self._client_wrapper.httpx_client.request(
+            "v0/batch/jobs",
+            method="POST",
+            files=files,
+            request_options=request_options,
+        )
+        try:
+            if 200 <= _response.status_code < 300:
+                _parsed_response = typing.cast(
+                    JobId,
+                    parse_obj_as(
+                        type_=JobId,  # type: ignore
+                        object_=_response.json(),
+                    ),
+                )
+                return _parsed_response.job_id
+            _response_json = _response.json()
+        except JSONDecodeError:
+            raise ApiError(status_code=_response.status_code, body=_response.text)
+        raise ApiError(status_code=_response.status_code, body=_response_json)
+
+
 class AsyncBatchClientWithUtils(AsyncBatchClient):
     async def get_and_write_job_artifacts(
             self,
@@ -87,4 +158,66 @@ async def get_and_write_job_artifacts(
         """
         async with aiofiles.open(file_name, mode='wb') as f:
             async for chunk in self.get_job_artifacts(id=id, request_options=request_options):
-                await f.write(chunk)
+                await f.write(chunk)
+
+    async def start_inference_job_from_local_file(
+        self,
+        *,
+        file: typing.List[core.File],
+        json: typing.Optional[InferenceBaseRequest] = None,
+        request_options: typing.Optional[RequestOptions] = None,
+    ) -> str:
+        """
+        Start a new batch inference job.
+
+        Parameters
+        ----------
+        file : typing.List[core.File]
+            See core.File for more documentation
+
+        json : typing.Optional[InferenceBaseRequest]
+            The inference job configuration.
+
+        request_options : typing.Optional[RequestOptions]
+            Request-specific configuration.
+
+        Returns
+        -------
+        str
+
+
+        Examples
+        --------
+        from hume import HumeClient
+
+        client = HumeClient(
+            api_key="YOUR_API_KEY",
+        )
+        client.expression_measurement.batch.start_inference_job_from_local_file()
+        """
+        files: typing.Dict[str, typing.Any] = {
+            "file": file,
+        }
+        if json is not None:
+            files["json"] = jsonlib.dumps(jsonable_encoder(json)).encode("utf-8")
+
+        _response = await self._client_wrapper.httpx_client.request(
+            "v0/batch/jobs",
+            method="POST",
+            files=files,
+            request_options=request_options,
+        )
+        try:
+            if 200 <= _response.status_code < 300:
+                _parsed_response = typing.cast(
+                    JobId,
+                    parse_obj_as(
+                        type_=JobId,  # type: ignore
+                        object_=_response.json(),
+                    ),
+                )
+                return _parsed_response.job_id
+            _response_json = _response.json()
+        except JSONDecodeError:
+            raise ApiError(status_code=_response.status_code, body=_response.text)
+        raise ApiError(status_code=_response.status_code, body=_response_json)

tests/custom/test_client.py

@@ -1,12 +1,11 @@
 import pytest
 import aiofiles
 
-from hume.client import AsyncHumeClient
+from hume.client import AsyncHumeClient, HumeClient
+from hume.expression_measurement.batch.types.face import Face
+from hume.expression_measurement.batch.types.inference_base_request import InferenceBaseRequest
+from hume.expression_measurement.batch.types.models import Models
 
-# Get started with writing tests with pytest at https://docs.pytest.org
-@pytest.mark.skip(reason="Unimplemented")
-def test_client() -> None:
-    assert True == True
 
 @pytest.mark.skip(reason="CI does not have authentication.")
 async def test_write_job_artifacts() -> None:
@@ -20,4 +19,16 @@ async def test_get_job_predictions() -> None:
     client = AsyncHumeClient(api_key="MY_API_KEY")
     await client.expression_measurement.batch.get_job_predictions(id="my-job-id", request_options={
         "max_retries": 3,
-    })
+    })
+
+@pytest.mark.skip(reason="CI does not have authentication.")
+async def test_start_inference_job_from_local_file() -> None:
+    client = HumeClient(api_key="MY_API_KEY")
+    client.expression_measurement.batch.start_inference_job_from_local_file(
+        file=[],
+        json=InferenceBaseRequest(
+            models=Models(
+                face=Face()
+            )
+        )
+    )