Update tabs to code groups in LangSmith (#213)

This PR updates all of the Tabs to CodeGroups in the LangSmith directory
to enable code tab syncing for users.

Preview:
https://langchain-5e9cc07a-preview-codegr-1755876371-43c5fc7.mintlify.app/langsmith/home

Author: katmayb

src/docs.json

@@ -9,12 +9,12 @@ You can access the current run by calling the `get_current_run_tree`/`getCurrent
 
 For a full list of available properties on the `RunTree` object, see [this reference](/langsmith/run-data-format).
 
-<Tabs>
-  <Tab title="Python">
-    ```python
-    from langsmith import traceable
-    from langsmith.run_helpers import get_current_run_tree
-    from openai import Client
+<CodeGroup>
+
+```python Python
+from langsmith import traceable
+from langsmith.run_helpers import get_current_run_tree
+from openai import Client
 
     openai = Client()
 
@@ -62,13 +62,12 @@ For a full list of available properties on the `RunTree` object, see [this refer
         response = invoke_llm(messages)
         return parse_output(response)
 
-    run_pipeline()
-    ```
-  </Tab>
-  <Tab title="TypeScript">
-    ```typescript
-    import { traceable, getCurrentRunTree } from "langsmith/traceable";
-    import OpenAI from "openai";
+run_pipeline()
+```
+
+```typescript TypeScript
+import { traceable, getCurrentRunTree } from "langsmith/traceable";
+import OpenAI from "openai";
 
     const openai = new OpenAI();
 
@@ -128,7 +127,7 @@ For a full list of available properties on the `RunTree` object, see [this refer
         { name: "runPipeline" }
     );
 
-    await runPipeline();
-    ```
-  </Tab>
-</Tabs>
+await runPipeline();
+```
+
+</CodeGroup>

src/langsmith/access-current-span.mdx

@@ -9,18 +9,18 @@ Tags are strings that can be used to categorize or label a trace. Metadata is a
 
 Both are useful for associating additional information with a trace, such as the environment in which it was executed, the user who initiated it, or an internal correlation ID. For more information on tags and metadata, see the [Concepts](/langsmith/observability-concepts#tags) page. For information on how to query traces and runs by metadata and tags, see the [Filter traces in the application](/langsmith/filter-traces-in-application) page.
 
-<Tabs>
-  <Tab title="Python">
-    ```python
-    import openai
-    import langsmith as ls
-    from langsmith.wrappers import wrap_openai
+<CodeGroup>
 
-    client = openai.Client()
-    messages = [
-        {"role": "system", "content": "You are a helpful assistant."},
-        {"role": "user", "content": "Hello!"}
-    ]
+```python Python
+import openai
+import langsmith as ls
+from langsmith.wrappers import wrap_openai
+
+client = openai.Client()
+messages = [
+    {"role": "system", "content": "You are a helpful assistant."},
+    {"role": "user", "content": "Hello!"}
+]
 
     # You can set metadata & tags **statically** when decorating a function
     # Use the @traceable decorator with tags and metadata
@@ -65,25 +65,24 @@ Both are useful for associating additional information with a trace, such as the
         rt.metadata["some-conditional-key"] = "some-val"
         rt.end(outputs={"output": chat_completion})
 
-    # You can use the same techniques with the wrapped client
-    patched_client = wrap_openai(
-        client, tracing_extra={"metadata": {"my-key": "my-value"}, "tags": ["a-tag"]}
-    )
-    chat_completion = patched_client.chat.completions.create(
-        model="gpt-4o-mini",
-        messages=messages,
-        langsmith_extra={
-            "tags": ["my-other-tag"],
-            "metadata": {"my-other-key": "my-value"},
-        },
-    )
-    ```
-  </Tab>
-  <Tab title="TypeScript">
-    ```typescript
-    import OpenAI from "openai";
-    import { traceable, getCurrentRunTree } from "langsmith/traceable";
-    import { wrapOpenAI } from "langsmith/wrappers";
+# You can use the same techniques with the wrapped client
+patched_client = wrap_openai(
+    client, tracing_extra={"metadata": {"my-key": "my-value"}, "tags": ["a-tag"]}
+)
+chat_completion = patched_client.chat.completions.create(
+    model="gpt-4o-mini",
+    messages=messages,
+    langsmith_extra={
+        "tags": ["my-other-tag"],
+        "metadata": {"my-other-key": "my-value"},
+    },
+)
+```
+
+```typescript TypeScript
+import OpenAI from "openai";
+import { traceable, getCurrentRunTree } from "langsmith/traceable";
+import { wrapOpenAI } from "langsmith/wrappers";
 
     const client = wrapOpenAI(new OpenAI());
     const messages: OpenAI.Chat.ChatCompletionMessageParam[] = [
@@ -113,8 +112,8 @@ Both are useful for associating additional information with a trace, such as the
         }
     );
 
-    // Call the traceable function
-    await traceableCallOpenAI(messages);
-    ```
-  </Tab>
-</Tabs>
+// Call the traceable function
+await traceableCallOpenAI(messages);
+```
+
+</CodeGroup>