add azure openai sched tests (#11723)

.github/workflows/scheduled_test.yml

@@ -61,6 +61,10 @@ jobs:
         env:
           OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
           ANTHROPIC_API_KEY: ${{ secrets.ANTHROPIC_API_KEY }}
+          AZURE_OPENAI_API_VERSION: ${{ secrets.AZURE_OPENAI_API_VERSION }}
+          AZURE_OPENAI_API_BASE: ${{ secrets.AZURE_OPENAI_API_BASE }}
+          AZURE_OPENAI_API_KEY: ${{ secrets.AZURE_OPENAI_API_KEY }}
+          AZURE_OPENAI_DEPLOYMENT_NAME:  ${{ secrets.AZURE_OPENAI_DEPLOYMENT_NAME }}
         run: |
           make scheduled_tests
 

libs/langchain/tests/integration_tests/chat_models/test_azure_openai.py

@@ -0,0 +1,228 @@
+"""Test AzureChatOpenAI wrapper."""
+import os
+from typing import Any
+
+import pytest
+
+from langchain.callbacks.manager import CallbackManager
+from langchain.chat_models import AzureChatOpenAI
+from langchain.schema import (
+    ChatGeneration,
+    ChatResult,
+    LLMResult,
+)
+from langchain.schema.messages import BaseMessage, HumanMessage
+from tests.unit_tests.callbacks.fake_callback_handler import FakeCallbackHandler
+
+OPENAI_API_VERSION = os.environ.get("AZURE_OPENAI_API_VERSION", "")
+OPENAI_API_BASE = os.environ.get("AZURE_OPENAI_API_BASE", "")
+OPENAI_API_KEY = os.environ.get("AZURE_OPENAI_API_KEY", "")
+DEPLOYMENT_NAME = os.environ.get("AZURE_OPENAI_DEPLOYMENT_NAME", "")
+
+
+def _get_llm(**kwargs: Any) -> AzureChatOpenAI:
+    return AzureChatOpenAI(
+        deployment_name=DEPLOYMENT_NAME,
+        openai_api_version=OPENAI_API_VERSION,
+        openai_api_base=OPENAI_API_BASE,
+        openai_api_key=OPENAI_API_KEY,
+        **kwargs,
+    )
+
+
+@pytest.mark.scheduled
+@pytest.fixture
+def llm() -> AzureChatOpenAI:
+    return _get_llm(
+        max_tokens=10,
+    )
+
+
+def test_chat_openai(llm: AzureChatOpenAI) -> None:
+    """Test AzureChatOpenAI wrapper."""
+    message = HumanMessage(content="Hello")
+    response = llm([message])
+    assert isinstance(response, BaseMessage)
+    assert isinstance(response.content, str)
+
+
+@pytest.mark.scheduled
+def test_chat_openai_generate() -> None:
+    """Test AzureChatOpenAI wrapper with generate."""
+    chat = _get_llm(max_tokens=10, n=2)
+    message = HumanMessage(content="Hello")
+    response = chat.generate([[message], [message]])
+    assert isinstance(response, LLMResult)
+    assert len(response.generations) == 2
+    for generations in response.generations:
+        assert len(generations) == 2
+        for generation in generations:
+            assert isinstance(generation, ChatGeneration)
+            assert isinstance(generation.text, str)
+            assert generation.text == generation.message.content
+
+
+@pytest.mark.scheduled
+def test_chat_openai_multiple_completions() -> None:
+    """Test AzureChatOpenAI wrapper with multiple completions."""
+    chat = _get_llm(max_tokens=10, n=5)
+    message = HumanMessage(content="Hello")
+    response = chat._generate([message])
+    assert isinstance(response, ChatResult)
+    assert len(response.generations) == 5
+    for generation in response.generations:
+        assert isinstance(generation.message, BaseMessage)
+        assert isinstance(generation.message.content, str)
+
+
+@pytest.mark.scheduled
+def test_chat_openai_streaming() -> None:
+    """Test that streaming correctly invokes on_llm_new_token callback."""
+    callback_handler = FakeCallbackHandler()
+    callback_manager = CallbackManager([callback_handler])
+    chat = _get_llm(
+        max_tokens=10,
+        streaming=True,
+        temperature=0,
+        callback_manager=callback_manager,
+        verbose=True,
+    )
+    message = HumanMessage(content="Hello")
+    response = chat([message])
+    assert callback_handler.llm_streams > 0
+    assert isinstance(response, BaseMessage)
+
+
+@pytest.mark.scheduled
+def test_chat_openai_streaming_generation_info() -> None:
+    """Test that generation info is preserved when streaming."""
+
+    class _FakeCallback(FakeCallbackHandler):
+        saved_things: dict = {}
+
+        def on_llm_end(
+            self,
+            *args: Any,
+            **kwargs: Any,
+        ) -> Any:
+            # Save the generation
+            self.saved_things["generation"] = args[0]
+
+    callback = _FakeCallback()
+    callback_manager = CallbackManager([callback])
+    chat = _get_llm(
+        max_tokens=2,
+        temperature=0,
+        callback_manager=callback_manager,
+    )
+    list(chat.stream("hi"))
+    generation = callback.saved_things["generation"]
+    # `Hello!` is two tokens, assert that that is what is returned
+    assert generation.generations[0][0].text == "Hello!"
+
+
+@pytest.mark.scheduled
+@pytest.mark.asyncio
+async def test_async_chat_openai() -> None:
+    """Test async generation."""
+    chat = _get_llm(max_tokens=10, n=2)
+    message = HumanMessage(content="Hello")
+    response = await chat.agenerate([[message], [message]])
+    assert isinstance(response, LLMResult)
+    assert len(response.generations) == 2
+    for generations in response.generations:
+        assert len(generations) == 2
+        for generation in generations:
+            assert isinstance(generation, ChatGeneration)
+            assert isinstance(generation.text, str)
+            assert generation.text == generation.message.content
+
+
+@pytest.mark.scheduled
+@pytest.mark.asyncio
+async def test_async_chat_openai_streaming() -> None:
+    """Test that streaming correctly invokes on_llm_new_token callback."""
+    callback_handler = FakeCallbackHandler()
+    callback_manager = CallbackManager([callback_handler])
+    chat = _get_llm(
+        max_tokens=10,
+        streaming=True,
+        temperature=0,
+        callback_manager=callback_manager,
+        verbose=True,
+    )
+    message = HumanMessage(content="Hello")
+    response = await chat.agenerate([[message], [message]])
+    assert callback_handler.llm_streams > 0
+    assert isinstance(response, LLMResult)
+    assert len(response.generations) == 2
+    for generations in response.generations:
+        assert len(generations) == 1
+        for generation in generations:
+            assert isinstance(generation, ChatGeneration)
+            assert isinstance(generation.text, str)
+            assert generation.text == generation.message.content
+
+
+@pytest.mark.scheduled
+def test_openai_streaming(llm: AzureChatOpenAI) -> None:
+    """Test streaming tokens from OpenAI."""
+
+    for token in llm.stream("I'm Pickle Rick"):
+        assert isinstance(token.content, str)
+
+
+@pytest.mark.scheduled
+@pytest.mark.asyncio
+async def test_openai_astream(llm: AzureChatOpenAI) -> None:
+    """Test streaming tokens from OpenAI."""
+    async for token in llm.astream("I'm Pickle Rick"):
+        assert isinstance(token.content, str)
+
+
+@pytest.mark.scheduled
+@pytest.mark.asyncio
+async def test_openai_abatch(llm: AzureChatOpenAI) -> None:
+    """Test streaming tokens from AzureChatOpenAI."""
+
+    result = await llm.abatch(["I'm Pickle Rick", "I'm not Pickle Rick"])
+    for token in result:
+        assert isinstance(token.content, str)
+
+
+@pytest.mark.scheduled
+@pytest.mark.asyncio
+async def test_openai_abatch_tags(llm: AzureChatOpenAI) -> None:
+    """Test batch tokens from AzureChatOpenAI."""
+
+    result = await llm.abatch(
+        ["I'm Pickle Rick", "I'm not Pickle Rick"], config={"tags": ["foo"]}
+    )
+    for token in result:
+        assert isinstance(token.content, str)
+
+
+@pytest.mark.scheduled
+def test_openai_batch(llm: AzureChatOpenAI) -> None:
+    """Test batch tokens from AzureChatOpenAI."""
+
+    result = llm.batch(["I'm Pickle Rick", "I'm not Pickle Rick"])
+    for token in result:
+        assert isinstance(token.content, str)
+
+
+@pytest.mark.scheduled
+@pytest.mark.asyncio
+async def test_openai_ainvoke(llm: AzureChatOpenAI) -> None:
+    """Test invoke tokens from AzureChatOpenAI."""
+
+    result = await llm.ainvoke("I'm Pickle Rick", config={"tags": ["foo"]})
+    assert isinstance(result.content, str)
+
+
+@pytest.mark.scheduled
+def test_openai_invoke(llm: AzureChatOpenAI) -> None:
+    """Test invoke tokens from AzureChatOpenAI."""
+
+    result = llm.invoke("I'm Pickle Rick", config=dict(tags=["foo"]))
+    assert isinstance(result.content, str)