docs[patch]: update contributor docs for integrations (#28576)

- Reformat tabs
- Add code snippets inline
- Add embeddings content

docs/docs/contributing/how_to/integrations/package.mdx

@@ -37,14 +37,11 @@ import CodeBlock from '@theme/CodeBlock';
         Refer to the [Custom Chat Model Guide](/docs/how_to/custom_chat_model) guide for
         detail on a starter chat model [implementation](/docs/how_to/custom_chat_model/#implementation).
 
-        :::tip
+        The `langchain-cli` package contains [template integrations](https://github.com/langchain-ai/langchain/tree/master/libs/cli/langchain_cli/integration_template/integration_template)
-
+        for major LangChain components that are tested against the standard unit and
-        The model from the [Custom Chat Model Guide](/docs/how_to/custom_chat_model) is tested
+        integration tests in the LangChain Github repository. You can access the starter
-        against the standard unit and integration tests in the LangChain Github repository.
+        chat model implementation [here](https://github.com/langchain-ai/langchain/blob/master/libs/cli/langchain_cli/integration_template/integration_template/chat_models.py).
-        You can also access that implementation directly from Github
+        For convenience, we also include the code below.
-        [here](https://github.com/langchain-ai/langchain/blob/master/libs/standard-tests/tests/unit_tests/custom_chat_model.py).
-
-        :::
 
         <details>
             <summary>Example chat model code</summary>
@@ -118,9 +115,6 @@ import VectorstoreSource from '../../../../src/theme/integration_template/integr
     </TabItem>
     <TabItem value="embeddings" label="Embeddings">
 
-        <details>
-            <summary>Example embeddings code</summary>
-
 Embeddings are used to convert `str` objects from `Document.page_content` fields
 into a vector representation (represented as a list of floats).
 
@@ -154,9 +148,16 @@ implement this method to handle that.
 
 `embed_documents` takes in a list of strings and returns a list of embeddings as a list of lists of floats.
 
+### Implementation
 
-### Async methods
+The `langchain-cli` package contains [template integrations](https://github.com/langchain-ai/langchain/tree/master/libs/cli/langchain_cli/integration_template/integration_template)
+for major LangChain components that are tested against the standard unit and
+integration tests in the LangChain Github repository. You can access the starter
+embedding model implementation [here](https://github.com/langchain-ai/langchain/blob/master/libs/cli/langchain_cli/integration_template/integration_template/embeddings.py).
+For convenience, we also include the code below.
 
+        <details>
+            <summary>Example embeddings code</summary>
 
 import EmbeddingsSource from '/src/theme/integration_template/integration_template/embeddings.py';
 

docs/docs/contributing/how_to/integrations/standard_tests.ipynb

@@ -324,6 +324,28 @@
     "    <summary>Embedding Models</summary>"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "To configure standard tests for an embeddings model, we subclass\n",
+    "`EmbeddingsUnitTests` and `EmbeddingsIntegrationTests`. On each subclass, we\n",
+    "implement the `embeddings_class` property to specify the embeddings model to be\n",
+    "tested. We can also override the embedding_model_params property to specify\n",
+    "initialization parameters. See examples below.\n",
+    "\n",
+    ":::note\n",
+    "\n",
+    "Details on what tests are run, how each test can be skipped, and troubleshooting tips for each test can be found in the API references. See details:\n",
+    "\n",
+    "- [Unit tests API reference](https://python.langchain.com/api_reference/standard_tests/unit_tests/langchain_tests.unit_tests.embeddings.EmbeddingsUnitTests.html)\n",
+    "- [Integration tests API reference](https://python.langchain.com/api_reference/standard_tests/integration_tests/langchain_tests.integration_tests.embeddings.EmbeddingsIntegrationTests.html)\n",
+    "\n",
+    ":::\n",
+    "\n",
+    "Unit test example:"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -347,6 +369,13 @@
     "        return {\"model\": \"nest-embed-001\", \"temperature\": 0}"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Integration test example:"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,