diff --git a/libs/ai-endpoints/langchain_nvidia_ai_endpoints/_common.py b/libs/ai-endpoints/langchain_nvidia_ai_endpoints/_common.py index 58d3320e..79eab91a 100644 --- a/libs/ai-endpoints/langchain_nvidia_ai_endpoints/_common.py +++ b/libs/ai-endpoints/langchain_nvidia_ai_endpoints/_common.py @@ -19,7 +19,9 @@ ) from urllib.parse import urlparse, urlunparse +import httpx import requests +from httpx import AsyncClient from pydantic import ( BaseModel, ConfigDict, @@ -76,6 +78,7 @@ class _NVIDIAClient(BaseModel): description="Path for polling after HTTP 202 responses", ) get_session_fn: Callable = Field(requests.Session) + get_asession_fn: Callable = Field(AsyncClient) api_key: Optional[SecretStr] = Field( default_factory=lambda: SecretStr( @@ -101,7 +104,7 @@ class _NVIDIAClient(BaseModel): default={}, description="Last inputs sent over to the server" ) last_response: Response = Field( - None, description="Last response sent from the server" + Response(), description="Last response sent from the server" ) headers_tmpl: dict = Field( { @@ -369,6 +372,26 @@ def _post( self._try_raise(response) return response, session + async def _apost( + self, + invoke_url: str, + payload: Optional[dict] = {}, + extra_headers: dict = {}, + ) -> Tuple[httpx.Response, Any]: + """Async Method for posting to the AI Foundation Model Function API.""" + self.last_inputs = { + "url": invoke_url, + "headers": { + **self.headers_tmpl["call"], + **extra_headers, + }, + "json": payload, + } + async with self.get_asession_fn() as session: + response = await session.post(**self.__add_authorization(self.last_inputs)) + self._try_raise(response) + return response, session + def _get( self, invoke_url: str, @@ -475,9 +498,16 @@ def get_req( ) return self._wait(response, session) + async def aget_req( + self, + payload: dict = {}, + extra_headers: dict = {}, + ) -> Tuple[httpx.Response, Any]: + return await self._apost(self.infer_url, payload, extra_headers=extra_headers) + def postprocess( self, - response: Union[str, Response], + response: Union[str, Any[Response, httpx.Response]], ) -> Tuple[dict, bool]: """Parses a response from the AI Foundation Model Function API. Strongly assumes that the API will return a single response. diff --git a/libs/ai-endpoints/langchain_nvidia_ai_endpoints/chat_models.py b/libs/ai-endpoints/langchain_nvidia_ai_endpoints/chat_models.py index 06ddca92..f5656a2b 100644 --- a/libs/ai-endpoints/langchain_nvidia_ai_endpoints/chat_models.py +++ b/libs/ai-endpoints/langchain_nvidia_ai_endpoints/chat_models.py @@ -253,7 +253,7 @@ class ChatNVIDIA(BaseChatModel): response = model.invoke("Hello") """ - _client: _NVIDIAClient = PrivateAttr(_NVIDIAClient) + _client: _NVIDIAClient = PrivateAttr() base_url: Optional[str] = Field( default=None, description="Base url for model listing an invocation", @@ -389,6 +389,33 @@ def _generate( generation = ChatGeneration(message=AIMessage(**parsed_response)) return ChatResult(generations=[generation], llm_output=responses) + async def _agenerate( + self, + messages: List[BaseMessage], + stop: Optional[List[str]] = None, + run_manager: Optional[AsyncCallbackManagerForLLMRun] = None, + **kwargs: Any, + ) -> ChatResult: + inputs = [ + message + for message in [convert_message_to_dict(message) for message in messages] + ] + inputs, extra_headers = _process_for_vlm(inputs, self._client.model) + payload = self._get_payload(inputs=inputs, stop=stop, stream=False, **kwargs) + if payload.get("stream", False) is True: + payload = {**payload, "stream": False} + response, _ = await self._client.aget_req( + payload=payload, extra_headers=extra_headers + ) + responses, _ = self._client.postprocess(response) + self._set_callback_out(responses, run_manager) + parsed_response = self._custom_postprocess(responses, streaming=False) + # for pre 0.2 compatibility w/ ChatMessage + # ChatMessage had a role property that was not present in AIMessage + parsed_response.update({"role": "assistant"}) + generation = ChatGeneration(message=AIMessage(**responses)) + return ChatResult(generations=[generation], llm_output=responses) + def _stream( self, messages: List[BaseMessage], diff --git a/libs/ai-endpoints/langchain_nvidia_ai_endpoints/embeddings.py b/libs/ai-endpoints/langchain_nvidia_ai_endpoints/embeddings.py index bc5c9366..93f743b7 100644 --- a/libs/ai-endpoints/langchain_nvidia_ai_endpoints/embeddings.py +++ b/libs/ai-endpoints/langchain_nvidia_ai_endpoints/embeddings.py @@ -34,7 +34,7 @@ class NVIDIAEmbeddings(BaseModel, Embeddings): validate_assignment=True, ) - _client: _NVIDIAClient = PrivateAttr(_NVIDIAClient) + _client: _NVIDIAClient = PrivateAttr() base_url: Optional[str] = Field( default=None, description="Base url for model listing an invocation", diff --git a/libs/ai-endpoints/langchain_nvidia_ai_endpoints/llm.py b/libs/ai-endpoints/langchain_nvidia_ai_endpoints/llm.py index 942e610d..e46a86fb 100644 --- a/libs/ai-endpoints/langchain_nvidia_ai_endpoints/llm.py +++ b/libs/ai-endpoints/langchain_nvidia_ai_endpoints/llm.py @@ -23,7 +23,7 @@ class NVIDIA(LLM): validate_assignment=True, ) - _client: _NVIDIAClient = PrivateAttr(_NVIDIAClient) + _client: _NVIDIAClient = PrivateAttr() _default_model_name: str = "nvidia/mistral-nemo-minitron-8b-base" base_url: Optional[str] = Field( default=None, diff --git a/libs/ai-endpoints/langchain_nvidia_ai_endpoints/reranking.py b/libs/ai-endpoints/langchain_nvidia_ai_endpoints/reranking.py index d64f8d84..62713a74 100644 --- a/libs/ai-endpoints/langchain_nvidia_ai_endpoints/reranking.py +++ b/libs/ai-endpoints/langchain_nvidia_ai_endpoints/reranking.py @@ -34,7 +34,7 @@ class NVIDIARerank(BaseDocumentCompressor): validate_assignment=True, ) - _client: _NVIDIAClient = PrivateAttr(_NVIDIAClient) + _client: _NVIDIAClient = PrivateAttr() base_url: Optional[str] = Field( default=None, diff --git a/libs/ai-endpoints/poetry.lock b/libs/ai-endpoints/poetry.lock index 8fef3819..ab38bb58 100644 --- a/libs/ai-endpoints/poetry.lock +++ b/libs/ai-endpoints/poetry.lock @@ -2,123 +2,109 @@ [[package]] name = "aiohappyeyeballs" -version = "2.4.0" +version = "2.4.3" description = "Happy Eyeballs for asyncio" 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">=3.9,<4.0" -content-hash = "6ee817a4c00e718ed760e5a7d74d4e57038a619543c52cde38ed9f853c87ec64" +content-hash = "943c037501cdcf97c322df48adf4cdef789c48a022d328024e8e14f1cadb70bc" diff --git a/libs/ai-endpoints/pyproject.toml b/libs/ai-endpoints/pyproject.toml index 9952eb7e..da95f50a 100644 --- a/libs/ai-endpoints/pyproject.toml +++ b/libs/ai-endpoints/pyproject.toml @@ -19,6 +19,7 @@ python = ">=3.9,<4.0" langchain-core = ">=0.3.0,<0.4" aiohttp = "^3.9.1" pillow = ">=10.0.0,<11.0.0" +httpx = "^0.27.2" [tool.poetry.group.test] optional = true @@ -33,6 +34,7 @@ pytest-asyncio = "^0.21.1" requests-mock = "^1.11.0" langchain-tests = "0.3.1" faker = "^24.4.0" +pytest-httpx = "0.30" [tool.poetry.group.codespell] optional = true diff --git a/libs/ai-endpoints/tests/integration_tests/test_chat_models.py b/libs/ai-endpoints/tests/integration_tests/test_chat_models.py index ac657085..c2f65b02 100644 --- a/libs/ai-endpoints/tests/integration_tests/test_chat_models.py +++ b/libs/ai-endpoints/tests/integration_tests/test_chat_models.py @@ -1,5 +1,7 @@ """Test ChatNVIDIA chat model.""" +import asyncio +import time from typing import List import pytest @@ -11,6 +13,7 @@ HumanMessage, SystemMessage, ) +from langchain_core.outputs import ChatGeneration, LLMResult from langchain_nvidia_ai_endpoints.chat_models import ChatNVIDIA @@ -236,6 +239,7 @@ def test_ai_endpoints_invoke_max_tokens_negative_a( with pytest.raises(Exception): llm = ChatNVIDIA(model=chat_model, max_tokens=max_tokens, **mode) llm.invoke("Show me the tokens") + assert llm._client.last_response assert llm._client.last_response.status_code in [400, 422] assert "max_tokens" in str(llm._client.last_response.content) @@ -250,6 +254,7 @@ def test_ai_endpoints_invoke_max_tokens_negative_b( with pytest.raises(Exception): llm = ChatNVIDIA(model=chat_model, max_tokens=max_tokens, **mode) llm.invoke("Show me the tokens") + assert llm._client.last_response assert llm._client.last_response.status_code in [400, 422] # custom error string - # model inference failed -- ValueError: A requested length of the model output @@ -258,6 +263,7 @@ def test_ai_endpoints_invoke_max_tokens_negative_b( # or # body -> max_tokens # Input should be less than or equal to 2048 (type=less_than_equal; le=2048) + assert llm._client.last_response assert "length" in str(llm._client.last_response.content) or ( "max_tokens" in str(llm._client.last_response.content) and "less_than_equal" in str(llm._client.last_response.content) @@ -306,6 +312,7 @@ def test_ai_endpoints_invoke_seed_default(chat_model: str, mode: dict) -> None: def test_ai_endpoints_invoke_seed_range(chat_model: str, mode: dict, seed: int) -> None: llm = ChatNVIDIA(model=chat_model, seed=seed, **mode) llm.invoke("What's in a seed?") + assert llm._client.last_response assert llm._client.last_response.status_code == 200 @@ -332,6 +339,7 @@ def test_ai_endpoints_invoke_temperature_negative( with pytest.raises(Exception): llm = ChatNVIDIA(model=chat_model, temperature=temperature, **mode) llm.invoke("What's in a temperature?") + assert llm._client.last_response assert llm._client.last_response.status_code in [400, 422] assert "temperature" in str(llm._client.last_response.content) @@ -360,6 +368,7 @@ def test_ai_endpoints_invoke_top_p_negative( with pytest.raises(Exception): llm = ChatNVIDIA(model=chat_model, top_p=top_p, **mode) llm.invoke("What's in a top_p?") + assert llm._client.last_response assert llm._client.last_response.status_code in [400, 422] assert "top_p" in str(llm._client.last_response.content) @@ -441,3 +450,42 @@ def test_stop( assert isinstance(token.content, str) result += f"{token.content}|" assert all(target not in result for target in targets) + + +def test_generate(chat_model: str, mode: dict) -> None: + """Test generate method of ChatNVIDIA.""" + chat = ChatNVIDIA(model=chat_model, **mode) # type: ignore[call-arg] + chat_messages: List[List[BaseMessage]] = [ + [HumanMessage(content="How many toes do dogs have?")] + ] + messages_copy = [messages.copy() for messages in chat_messages] + result: LLMResult = chat.generate(chat_messages) + assert isinstance(result, LLMResult) + for response in result.generations[0]: + assert isinstance(response, ChatGeneration) + assert isinstance(response.text, str) + assert response.text == response.message.content + assert chat_messages == messages_copy + + +async def test_async_generate(chat_model: str, mode: dict) -> None: + """Test async generation.""" + llm = ChatNVIDIA(model=chat_model, **mode) + message = HumanMessage(content="Hello") + + async def request(message: HumanMessage) -> LLMResult: + return await llm.agenerate([[message]]) + + start_time = time.time() + task1, task2 = request(message), request(message) + _, _ = await asyncio.gather(task1, task2) + + assert (time.time() - start_time) < 2, "Tasks did not run concurrently" + + response = await llm.agenerate([[message]]) + assert isinstance(response, LLMResult) + for generations in response.generations: + for generation in generations: + assert isinstance(generation, ChatGeneration) + assert isinstance(generation.text, str) + assert generation.text == generation.message.content diff --git a/libs/ai-endpoints/tests/unit_tests/test_metadata.py b/libs/ai-endpoints/tests/unit_tests/test_metadata.py index 97d53e8a..86e93c8c 100644 --- a/libs/ai-endpoints/tests/unit_tests/test_metadata.py +++ b/libs/ai-endpoints/tests/unit_tests/test_metadata.py @@ -3,6 +3,7 @@ import pytest import requests_mock from langchain_core.messages import AIMessage, BaseMessageChunk, HumanMessage +from pytest_httpx import HTTPXMock # from langchain_core.messages.ai import UsageMetadata from langchain_nvidia_ai_endpoints import ChatNVIDIA @@ -43,6 +44,28 @@ def mock_local_models_metadata(requests_mock: requests_mock.Mocker) -> None: requests_mock.post("http://localhost:8888/v1/chat/completions", json=mock_response) +@pytest.fixture +def mock_local_models_httpx(httpx_mock: HTTPXMock) -> None: + # Mock the POST request for the given URL + mock_response["tool_calls"] = ( + [ + { + "id": "tool-ID", + "type": "function", + "function": { + "name": "magic", + "arguments": [], + }, + } + ], + ) + httpx_mock.add_response( + method="POST", + url="http://localhost:8888/v1/chat/completions", + json=mock_response, + ) + + @pytest.fixture def mock_local_models_stream_metadata(requests_mock: requests_mock.Mocker) -> None: response_contents = "\n\n".join( @@ -92,7 +115,7 @@ def test_response_metadata(mock_local_models_metadata: None) -> None: response_metadata_checks(result) -async def test_async_response_metadata(mock_local_models_metadata: None) -> None: +async def test_async_response_metadata(mock_local_models_httpx: None) -> None: llm = ChatNVIDIA(base_url="http://localhost:8888/v1") result = await llm.ainvoke([HumanMessage(content="I'm PickleRick")], logprobs=True) response_metadata_checks(result)