pytest updates

docs/evaluation/how_to_guides/pytest.mdx

@@ -314,23 +314,9 @@ LANGSMITH_TEST_TRACKING=false pytest tests/
 
 The tests will run as normal, but the experiment logs will not be sent to LangSmith.
 
-## Legacy
-
-#### `@test` / `@unit` decorator
-
-The legacy method for marking test cases is using the `@test` or `@unit` decorators:
-
-```python
-from langsmith import test
-
-@test
-def test_foo() -> None:
-    pass
-```
-
-#### Expectations 
+## Expectations 
 
-LangSmith provides an `expect` utility to help define expectations about your LLM output. For example:
+LangSmith provides an [expect](https://docs.smith.langchain.com/reference/python/_expect/langsmith._expect._Expect#langsmith._expect._Expect) utility to help define expectations about your LLM output. For example:
 
 ```python
 from langsmith import expect
@@ -376,3 +362,17 @@ This test case will be assigned 4 scores:
 4. The overall test pass/fail score (binary)
 
 The `expect` utility is modeled off of [Jest](https://jestjs.io/docs/expect)'s expect API, with some off-the-shelf functionality to make it easier to grade your LLMs.
+
+## Legacy
+
+#### `@test` / `@unit` decorator
+
+The legacy method for marking test cases is using the `@test` or `@unit` decorators:
+
+```python
+from langsmith import test
+
+@test
+def test_foo() -> None:
+    pass
+```

docs/evaluation/tutorials/testing.mdx

@@ -9,7 +9,7 @@ import {
 
 # Test a ReAct agent with Pytest/Vitest and LangSmith
 
-This tutorial will show you how to use LangSmith's integrations with popular testing tools Pytest and Vitest/Jest to evaluate your LLM application.
+This tutorial will show you how to use LangSmith's integrations with popular testing tools [Pytest](../how_to_guides/pytest) and [Vitest/Jest](../how_to_guides/vitest_jest) to evaluate your LLM application.
 We will create a ReAct agent that answers questions about publicly traded stocks and write a comprehensive test suite for it.
 
 ## Setup