# File generated from our OpenAPI spec by Stainless. See CONTRIBUTING.md for details. from __future__ import annotations import os from typing import Any, cast import pytest import pydantic from openai import OpenAI, AsyncOpenAI from tests.utils import assert_matches_type from openai.pagination import SyncCursorPage, AsyncCursorPage from openai.types.chat import ( ChatCompletion, ChatCompletionDeleted, ) base_url = os.environ.get("TEST_API_BASE_URL", "http://127.0.0.1:4010") class TestCompletions: parametrize = pytest.mark.parametrize("client", [False, True], indirect=True, ids=["loose", "strict"]) @parametrize def test_method_create_overload_1(self, client: OpenAI) -> None: completion = client.chat.completions.create( messages=[ { "content": "string", "role": "developer", } ], model="gpt-4o", ) assert_matches_type(ChatCompletion, completion, path=["response"]) @parametrize def test_method_create_with_all_params_overload_1(self, client: OpenAI) -> None: completion = client.chat.completions.create( messages=[ { "content": "string", "role": "developer", "name": "name", } ], model="gpt-4o", audio={ "format": "wav", "voice": "ash", }, frequency_penalty=-2, function_call="none", functions=[ { "name": "name", "description": "description", "parameters": {"foo": "bar"}, } ], logit_bias={"foo": 0}, logprobs=True, max_completion_tokens=0, max_tokens=0, metadata={"foo": "string"}, modalities=["text"], n=1, parallel_tool_calls=True, prediction={ "content": "string", "type": "content", }, presence_penalty=-2, prompt_cache_key="prompt-cache-key-1234", reasoning_effort="minimal", response_format={"type": "text"}, safety_identifier="safety-identifier-1234", seed=-9007199254740991, service_tier="auto", stop="\n", store=True, stream=False, stream_options={ "include_obfuscation": True, "include_usage": True, }, temperature=1, tool_choice="none", tools=[ { "function": { "name": "name", "description": "description", "parameters": {"foo": "bar"}, "strict": True, }, "type": "function", } ], top_logprobs=0, top_p=1, user="user-1234", verbosity="low", web_search_options={ "search_context_size": "low", "user_location": { "approximate": { "city": "city", "country": "country", "region": "region", "timezone": "timezone", }, "type": "approximate", }, }, ) assert_matches_type(ChatCompletion, completion, path=["response"]) @parametrize def test_raw_response_create_overload_1(self, client: OpenAI) -> None: response = client.chat.completions.with_raw_response.create( messages=[ { "content": "string", "role": "developer", } ], model="gpt-4o", ) assert response.is_closed is True assert response.http_request.headers.get("X-Stainless-Lang") == "python" completion = response.parse() assert_matches_type(ChatCompletion, completion, path=["response"]) @parametrize def test_streaming_response_create_overload_1(self, client: OpenAI) -> None: with client.chat.completions.with_streaming_response.create( messages=[ { "content": "string", "role": "developer", } ], model="gpt-4o", ) as response: assert not response.is_closed assert response.http_request.headers.get("X-Stainless-Lang") == "python" completion = response.parse() assert_matches_type(ChatCompletion, completion, path=["response"]) assert cast(Any, response.is_closed) is True @parametrize def test_method_create_overload_2(self, client: OpenAI) -> None: completion_stream = client.chat.completions.create( messages=[ { "content": "string", "role": "developer", } ], model="gpt-4o", stream=True, ) completion_stream.response.close() @parametrize def test_method_create_with_all_params_overload_2(self, client: OpenAI) -> None: completion_stream = client.chat.completions.create( messages=[ { "content": "string", "role": "developer", "name": "name", } ], model="gpt-4o", stream=True, audio={ "format": "wav", "voice": "ash", }, frequency_penalty=-2, function_call="none", functions=[ { "name": "name", "description": "description", "parameters": {"foo": "bar"}, } ], logit_bias={"foo": 0}, logprobs=True, max_completion_tokens=0, max_tokens=0, metadata={"foo": "string"}, modalities=["text"], n=1, parallel_tool_calls=True, prediction={ "content": "string", "type": "content", }, presence_penalty=-2, prompt_cache_key="prompt-cache-key-1234", reasoning_effort="minimal", response_format={"type": "text"}, safety_identifier="safety-identifier-1234", seed=-9007199254740991, service_tier="auto", stop="\n", store=True, stream_options={ "include_obfuscation": True, "include_usage": True, }, temperature=1, tool_choice="none", tools=[ { "function": { "name": "name", "description": "description", "parameters": {"foo": "bar"}, "strict": True, }, "type": "function", } ], top_logprobs=0, top_p=1, user="user-1234", verbosity="low", web_search_options={ "search_context_size": "low", "user_location": { "approximate": { "city": "city", "country": "country", "region": "region", "timezone": "timezone", }, "type": "approximate", }, }, ) completion_stream.response.close() @parametrize def test_raw_response_create_overload_2(self, client: OpenAI) -> None: response = client.chat.completions.with_raw_response.create( messages=[ { "content": "string", "role": "developer", } ], model="gpt-4o", stream=True, ) assert response.http_request.headers.get("X-Stainless-Lang") == "python" stream = response.parse() stream.close() @parametrize def test_streaming_response_create_overload_2(self, client: OpenAI) -> None: with client.chat.completions.with_streaming_response.create( messages=[ { "content": "string", "role": "developer", } ], model="gpt-4o", stream=True, ) as response: assert not response.is_closed assert response.http_request.headers.get("X-Stainless-Lang") == "python" stream = response.parse() stream.close() assert cast(Any, response.is_closed) is True @parametrize def test_method_retrieve(self, client: OpenAI) -> None: completion = client.chat.completions.retrieve( "completion_id", ) assert_matches_type(ChatCompletion, completion, path=["response"]) @parametrize def test_raw_response_retrieve(self, client: OpenAI) -> None: response = client.chat.completions.with_raw_response.retrieve( "completion_id", ) assert response.is_closed is True assert response.http_request.headers.get("X-Stainless-Lang") == "python" completion = response.parse() assert_matches_type(ChatCompletion, completion, path=["response"]) @parametrize def test_streaming_response_retrieve(self, client: OpenAI) -> None: with client.chat.completions.with_streaming_response.retrieve( "completion_id", ) as response: assert not response.is_closed assert response.http_request.headers.get("X-Stainless-Lang") == "python" completion = response.parse() assert_matches_type(ChatCompletion, completion, path=["response"]) assert cast(Any, response.is_closed) is True @parametrize def test_path_params_retrieve(self, client: OpenAI) -> None: with pytest.raises(ValueError, match=r"Expected a non-empty value for `completion_id` but received ''"): client.chat.completions.with_raw_response.retrieve( "", ) @parametrize def test_method_update(self, client: OpenAI) -> None: completion = client.chat.completions.update( completion_id="completion_id", metadata={"foo": "string"}, ) assert_matches_type(ChatCompletion, completion, path=["response"]) @parametrize def test_raw_response_update(self, client: OpenAI) -> None: response = client.chat.completions.with_raw_response.update( completion_id="completion_id", metadata={"foo": "string"}, ) assert response.is_closed is True assert response.http_request.headers.get("X-Stainless-Lang") == "python" completion = response.parse() assert_matches_type(ChatCompletion, completion, path=["response"]) @parametrize def test_streaming_response_update(self, client: OpenAI) -> None: with client.chat.completions.with_streaming_response.update( completion_id="completion_id", metadata={"foo": "string"}, ) as response: assert not response.is_closed assert response.http_request.headers.get("X-Stainless-Lang") == "python" completion = response.parse() assert_matches_type(ChatCompletion, completion, path=["response"]) assert cast(Any, response.is_closed) is True @parametrize def test_path_params_update(self, client: OpenAI) -> None: with pytest.raises(ValueError, match=r"Expected a non-empty value for `completion_id` but received ''"): client.chat.completions.with_raw_response.update( completion_id="", metadata={"foo": "string"}, ) @parametrize def test_method_list(self, client: OpenAI) -> None: completion = client.chat.completions.list() assert_matches_type(SyncCursorPage[ChatCompletion], completion, path=["response"]) @parametrize def test_method_list_with_all_params(self, client: OpenAI) -> None: completion = client.chat.completions.list( after="after", limit=0, metadata={"foo": "string"}, model="model", order="asc", ) assert_matches_type(SyncCursorPage[ChatCompletion], completion, path=["response"]) @parametrize def test_raw_response_list(self, client: OpenAI) -> None: response = client.chat.completions.with_raw_response.list() assert response.is_closed is True assert response.http_request.headers.get("X-Stainless-Lang") == "python" completion = response.parse() assert_matches_type(SyncCursorPage[ChatCompletion], completion, path=["response"]) @parametrize def test_streaming_response_list(self, client: OpenAI) -> None: with client.chat.completions.with_streaming_response.list() as response: assert not response.is_closed assert response.http_request.headers.get("X-Stainless-Lang") == "python" completion = response.parse() assert_matches_type(SyncCursorPage[ChatCompletion], completion, path=["response"]) assert cast(Any, response.is_closed) is True @parametrize def test_method_delete(self, client: OpenAI) -> None: completion = client.chat.completions.delete( "completion_id", ) assert_matches_type(ChatCompletionDeleted, completion, path=["response"]) @parametrize def test_raw_response_delete(self, client: OpenAI) -> None: response = client.chat.completions.with_raw_response.delete( "completion_id", ) assert response.is_closed is True assert response.http_request.headers.get("X-Stainless-Lang") == "python" completion = response.parse() assert_matches_type(ChatCompletionDeleted, completion, path=["response"]) @parametrize def test_streaming_response_delete(self, client: OpenAI) -> None: with client.chat.completions.with_streaming_response.delete( "completion_id", ) as response: assert not response.is_closed assert response.http_request.headers.get("X-Stainless-Lang") == "python" completion = response.parse() assert_matches_type(ChatCompletionDeleted, completion, path=["response"]) assert cast(Any, response.is_closed) is True @parametrize def test_path_params_delete(self, client: OpenAI) -> None: with pytest.raises(ValueError, match=r"Expected a non-empty value for `completion_id` but received ''"): client.chat.completions.with_raw_response.delete( "", ) @parametrize def test_method_create_disallows_pydantic(self, client: OpenAI) -> None: class MyModel(pydantic.BaseModel): a: str with pytest.raises(TypeError, match=r"You tried to pass a `BaseModel` class"): client.chat.completions.create( messages=[ { "content": "string", "role": "system", } ], model="gpt-4o", response_format=cast(Any, MyModel), ) class TestAsyncCompletions: parametrize = pytest.mark.parametrize( "async_client", [False, True, {"http_client": "aiohttp"}], indirect=True, ids=["loose", "strict", "aiohttp"] ) @parametrize async def test_method_create_overload_1(self, async_client: AsyncOpenAI) -> None: completion = await async_client.chat.completions.create( messages=[ { "content": "string", "role": "developer", } ], model="gpt-4o", ) assert_matches_type(ChatCompletion, completion, path=["response"]) @parametrize async def test_method_create_with_all_params_overload_1(self, async_client: AsyncOpenAI) -> None: completion = await async_client.chat.completions.create( messages=[ { "content": "string", "role": "developer", "name": "name", } ], model="gpt-4o", audio={ "format": "wav", "voice": "ash", }, frequency_penalty=-2, function_call="none", functions=[ { "name": "name", "description": "description", "parameters": {"foo": "bar"}, } ], logit_bias={"foo": 0}, logprobs=True, max_completion_tokens=0, max_tokens=0, metadata={"foo": "string"}, modalities=["text"], n=1, parallel_tool_calls=True, prediction={ "content": "string", "type": "content", }, presence_penalty=-2, prompt_cache_key="prompt-cache-key-1234", reasoning_effort="minimal", response_format={"type": "text"}, safety_identifier="safety-identifier-1234", seed=-9007199254740991, service_tier="auto", stop="\n", store=True, stream=False, stream_options={ "include_obfuscation": True, "include_usage": True, }, temperature=1, tool_choice="none", tools=[ { "function": { "name": "name", "description": "description", "parameters": {"foo": "bar"}, "strict": True, }, "type": "function", } ], top_logprobs=0, top_p=1, user="user-1234", verbosity="low", web_search_options={ "search_context_size": "low", "user_location": { "approximate": { "city": "city", "country": "country", "region": "region", "timezone": "timezone", }, "type": "approximate", }, }, ) assert_matches_type(ChatCompletion, completion, path=["response"]) @parametrize async def test_raw_response_create_overload_1(self, async_client: AsyncOpenAI) -> None: response = await async_client.chat.completions.with_raw_response.create( messages=[ { "content": "string", "role": "developer", } ], model="gpt-4o", ) assert response.is_closed is True assert response.http_request.headers.get("X-Stainless-Lang") == "python" completion = response.parse() assert_matches_type(ChatCompletion, completion, path=["response"]) @parametrize async def test_streaming_response_create_overload_1(self, async_client: AsyncOpenAI) -> None: async with async_client.chat.completions.with_streaming_response.create( messages=[ { "content": "string", "role": "developer", } ], model="gpt-4o", ) as response: assert not response.is_closed assert response.http_request.headers.get("X-Stainless-Lang") == "python" completion = await response.parse() assert_matches_type(ChatCompletion, completion, path=["response"]) assert cast(Any, response.is_closed) is True @parametrize async def test_method_create_overload_2(self, async_client: AsyncOpenAI) -> None: completion_stream = await async_client.chat.completions.create( messages=[ { "content": "string", "role": "developer", } ], model="gpt-4o", stream=True, ) await completion_stream.response.aclose() @parametrize async def test_method_create_with_all_params_overload_2(self, async_client: AsyncOpenAI) -> None: completion_stream = await async_client.chat.completions.create( messages=[ { "content": "string", "role": "developer", "name": "name", } ], model="gpt-4o", stream=True, audio={ "format": "wav", "voice": "ash", }, frequency_penalty=-2, function_call="none", functions=[ { "name": "name", "description": "description", "parameters": {"foo": "bar"}, } ], logit_bias={"foo": 0}, logprobs=True, max_completion_tokens=0, max_tokens=0, metadata={"foo": "string"}, modalities=["text"], n=1, parallel_tool_calls=True, prediction={ "content": "string", "type": "content", }, presence_penalty=-2, prompt_cache_key="prompt-cache-key-1234", reasoning_effort="minimal", response_format={"type": "text"}, safety_identifier="safety-identifier-1234", seed=-9007199254740991, service_tier="auto", stop="\n", store=True, stream_options={ "include_obfuscation": True, "include_usage": True, }, temperature=1, tool_choice="none", tools=[ { "function": { "name": "name", "description": "description", "parameters": {"foo": "bar"}, "strict": True, }, "type": "function", } ], top_logprobs=0, top_p=1, user="user-1234", verbosity="low", web_search_options={ "search_context_size": "low", "user_location": { "approximate": { "city": "city", "country": "country", "region": "region", "timezone": "timezone", }, "type": "approximate", }, }, ) await completion_stream.response.aclose() @parametrize async def test_raw_response_create_overload_2(self, async_client: AsyncOpenAI) -> None: response = await async_client.chat.completions.with_raw_response.create( messages=[ { "content": "string", "role": "developer", } ], model="gpt-4o", stream=True, ) assert response.http_request.headers.get("X-Stainless-Lang") == "python" stream = response.parse() await stream.close() @parametrize async def test_streaming_response_create_overload_2(self, async_client: AsyncOpenAI) -> None: async with async_client.chat.completions.with_streaming_response.create( messages=[ { "content": "string", "role": "developer", } ], model="gpt-4o", stream=True, ) as response: assert not response.is_closed assert response.http_request.headers.get("X-Stainless-Lang") == "python" stream = await response.parse() await stream.close() assert cast(Any, response.is_closed) is True @parametrize async def test_method_retrieve(self, async_client: AsyncOpenAI) -> None: completion = await async_client.chat.completions.retrieve( "completion_id", ) assert_matches_type(ChatCompletion, completion, path=["response"]) @parametrize async def test_raw_response_retrieve(self, async_client: AsyncOpenAI) -> None: response = await async_client.chat.completions.with_raw_response.retrieve( "completion_id", ) assert response.is_closed is True assert response.http_request.headers.get("X-Stainless-Lang") == "python" completion = response.parse() assert_matches_type(ChatCompletion, completion, path=["response"]) @parametrize async def test_streaming_response_retrieve(self, async_client: AsyncOpenAI) -> None: async with async_client.chat.completions.with_streaming_response.retrieve( "completion_id", ) as response: assert not response.is_closed assert response.http_request.headers.get("X-Stainless-Lang") == "python" completion = await response.parse() assert_matches_type(ChatCompletion, completion, path=["response"]) assert cast(Any, response.is_closed) is True @parametrize async def test_path_params_retrieve(self, async_client: AsyncOpenAI) -> None: with pytest.raises(ValueError, match=r"Expected a non-empty value for `completion_id` but received ''"): await async_client.chat.completions.with_raw_response.retrieve( "", ) @parametrize async def test_method_update(self, async_client: AsyncOpenAI) -> None: completion = await async_client.chat.completions.update( completion_id="completion_id", metadata={"foo": "string"}, ) assert_matches_type(ChatCompletion, completion, path=["response"]) @parametrize async def test_raw_response_update(self, async_client: AsyncOpenAI) -> None: response = await async_client.chat.completions.with_raw_response.update( completion_id="completion_id", metadata={"foo": "string"}, ) assert response.is_closed is True assert response.http_request.headers.get("X-Stainless-Lang") == "python" completion = response.parse() assert_matches_type(ChatCompletion, completion, path=["response"]) @parametrize async def test_streaming_response_update(self, async_client: AsyncOpenAI) -> None: async with async_client.chat.completions.with_streaming_response.update( completion_id="completion_id", metadata={"foo": "string"}, ) as response: assert not response.is_closed assert response.http_request.headers.get("X-Stainless-Lang") == "python" completion = await response.parse() assert_matches_type(ChatCompletion, completion, path=["response"]) assert cast(Any, response.is_closed) is True @parametrize async def test_path_params_update(self, async_client: AsyncOpenAI) -> None: with pytest.raises(ValueError, match=r"Expected a non-empty value for `completion_id` but received ''"): await async_client.chat.completions.with_raw_response.update( completion_id="", metadata={"foo": "string"}, ) @parametrize async def test_method_list(self, async_client: AsyncOpenAI) -> None: completion = await async_client.chat.completions.list() assert_matches_type(AsyncCursorPage[ChatCompletion], completion, path=["response"]) @parametrize async def test_method_list_with_all_params(self, async_client: AsyncOpenAI) -> None: completion = await async_client.chat.completions.list( after="after", limit=0, metadata={"foo": "string"}, model="model", order="asc", ) assert_matches_type(AsyncCursorPage[ChatCompletion], completion, path=["response"]) @parametrize async def test_raw_response_list(self, async_client: AsyncOpenAI) -> None: response = await async_client.chat.completions.with_raw_response.list() assert response.is_closed is True assert response.http_request.headers.get("X-Stainless-Lang") == "python" completion = response.parse() assert_matches_type(AsyncCursorPage[ChatCompletion], completion, path=["response"]) @parametrize async def test_streaming_response_list(self, async_client: AsyncOpenAI) -> None: async with async_client.chat.completions.with_streaming_response.list() as response: assert not response.is_closed assert response.http_request.headers.get("X-Stainless-Lang") == "python" completion = await response.parse() assert_matches_type(AsyncCursorPage[ChatCompletion], completion, path=["response"]) assert cast(Any, response.is_closed) is True @parametrize async def test_method_delete(self, async_client: AsyncOpenAI) -> None: completion = await async_client.chat.completions.delete( "completion_id", ) assert_matches_type(ChatCompletionDeleted, completion, path=["response"]) @parametrize async def test_raw_response_delete(self, async_client: AsyncOpenAI) -> None: response = await async_client.chat.completions.with_raw_response.delete( "completion_id", ) assert response.is_closed is True assert response.http_request.headers.get("X-Stainless-Lang") == "python" completion = response.parse() assert_matches_type(ChatCompletionDeleted, completion, path=["response"]) @parametrize async def test_streaming_response_delete(self, async_client: AsyncOpenAI) -> None: async with async_client.chat.completions.with_streaming_response.delete( "completion_id", ) as response: assert not response.is_closed assert response.http_request.headers.get("X-Stainless-Lang") == "python" completion = await response.parse() assert_matches_type(ChatCompletionDeleted, completion, path=["response"]) assert cast(Any, response.is_closed) is True @parametrize async def test_path_params_delete(self, async_client: AsyncOpenAI) -> None: with pytest.raises(ValueError, match=r"Expected a non-empty value for `completion_id` but received ''"): await async_client.chat.completions.with_raw_response.delete( "", ) @parametrize async def test_method_create_disallows_pydantic(self, async_client: AsyncOpenAI) -> None: class MyModel(pydantic.BaseModel): a: str with pytest.raises(TypeError, match=r"You tried to pass a `BaseModel` class"): await async_client.chat.completions.create( messages=[ { "content": "string", "role": "system", } ], model="gpt-4o", response_format=cast(Any, MyModel), )