From 09c1991e9606ecc4a39adc312e4e97835e9f38ed Mon Sep 17 00:00:00 2001
From: Abderrahmane Gourragui <gourragui.success@gmail.com>
Date: Thu, 24 Apr 2025 23:07:55 +0100
Subject: [PATCH] docs: update document examples (#31006)

## Description:

As I was following the docs I found a couple of small issues on the
docs.

this fixes some unused imports on the [extraction
page](https://python.langchain.com/docs/tutorials/extraction/#the-extractor)
and updates the examples on [classification
page](https://python.langchain.com/docs/tutorials/classification/#quickstart)
to be independent from the chat model.
---
 docs/docs/tutorials/classification.ipynb | 16 +++++++---------
 docs/docs/tutorials/extraction.ipynb     |  5 +----
 2 files changed, 8 insertions(+), 13 deletions(-)

diff --git a/docs/docs/tutorials/classification.ipynb b/docs/docs/tutorials/classification.ipynb
index 4efafa165c7..85ac988edd9 100644
--- a/docs/docs/tutorials/classification.ipynb
+++ b/docs/docs/tutorials/classification.ipynb
@@ -89,7 +89,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": null,
    "id": "39f3ce3e",
    "metadata": {},
    "outputs": [],
@@ -118,15 +118,13 @@
     "    language: str = Field(description=\"The language the text is written in\")\n",
     "\n",
     "\n",
-    "# LLM\n",
-    "llm = ChatOpenAI(temperature=0, model=\"gpt-4o-mini\").with_structured_output(\n",
-    "    Classification\n",
-    ")"
+    "# Structured LLM\n",
+    "structured_llm = llm.with_structured_output(Classification)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": null,
    "id": "5509b6a6",
    "metadata": {},
    "outputs": [
@@ -144,7 +142,7 @@
    "source": [
     "inp = \"Estoy increiblemente contento de haberte conocido! Creo que seremos muy buenos amigos!\"\n",
     "prompt = tagging_prompt.invoke({\"input\": inp})\n",
-    "response = llm.invoke(prompt)\n",
+    "response = structured_llm.invoke(prompt)\n",
     "\n",
     "response"
    ]
@@ -159,7 +157,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": null,
    "id": "9154474c",
    "metadata": {},
    "outputs": [
@@ -177,7 +175,7 @@
    "source": [
     "inp = \"Estoy muy enojado con vos! Te voy a dar tu merecido!\"\n",
     "prompt = tagging_prompt.invoke({\"input\": inp})\n",
-    "response = llm.invoke(prompt)\n",
+    "response = structured_llm.invoke(prompt)\n",
     "\n",
     "response.model_dump()"
    ]
diff --git a/docs/docs/tutorials/extraction.ipynb b/docs/docs/tutorials/extraction.ipynb
index 18d444723b2..2c18e52ae95 100644
--- a/docs/docs/tutorials/extraction.ipynb
+++ b/docs/docs/tutorials/extraction.ipynb
@@ -145,15 +145,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": null,
    "id": "a5e490f6-35ad-455e-8ae4-2bae021583ff",
    "metadata": {},
    "outputs": [],
    "source": [
-    "from typing import Optional\n",
-    "\n",
     "from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder\n",
-    "from pydantic import BaseModel, Field\n",
     "\n",
     "# Define a custom prompt to provide instructions and any additional context.\n",
     "# 1) You can add examples into the prompt template to improve extraction quality\n",