docs: document anthropic features (#30030)

Update integrations page with extended thinking feature.

Update API reference with extended thinking and citations.

docs/docs/integrations/chat/anthropic.ipynb

@@ -315,6 +315,59 @@
     "ai_msg.tool_calls"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "6e36d25c-f358-49e5-aefa-b99fbd3fec6b",
+   "metadata": {},
+   "source": [
+    "## Extended thinking\n",
+    "\n",
+    "Claude 3.7 Sonnet supports an [extended thinking](https://docs.anthropic.com/en/docs/build-with-claude/extended-thinking) feature, which will output the step-by-step reasoning process that led to its final answer.\n",
+    "\n",
+    "To use it, specify the `thinking` parameter when initializing `ChatAnthropic`. It can also be passed in as a kwarg during invocation.\n",
+    "\n",
+    "You will need to specify a token budget to use this feature. See usage example below:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "a34cf93b-8522-43a6-a3f3-8a189ddf54a7",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[\n",
+      "  {\n",
+      "    \"signature\": \"ErUBCkYIARgCIkCx7bIPj35jGPHpoVOB2y5hvPF8MN4lVK75CYGftmVNlI4axz2+bBbSexofWsN1O/prwNv8yPXnIXQmwT6zrJsKEgwJzvks0yVRZtaGBScaDOm9xcpOxbuhku1zViIw9WDgil/KZL8DsqWrhVpC6TzM0RQNCcsHcmgmyxbgG9g8PR0eJGLxCcGoEw8zMQu1Kh1hQ1/03hZ2JCOgigpByR9aNPTwwpl64fQUe6WwIw==\",\n",
+      "    \"thinking\": \"To find the cube root of 50.653, I need to find the value of $x$ such that $x^3 = 50.653$.\\n\\nI can try to estimate this first. \\n$3^3 = 27$\\n$4^3 = 64$\\n\\nSo the cube root of 50.653 will be somewhere between 3 and 4, but closer to 4.\\n\\nLet me try to compute this more precisely. I can use the cube root function:\\n\\ncube root of 50.653 = 50.653^(1/3)\\n\\nLet me calculate this:\\n50.653^(1/3) \\u2248 3.6998\\n\\nLet me verify:\\n3.6998^3 \\u2248 50.6533\\n\\nThat's very close to 50.653, so I'm confident that the cube root of 50.653 is approximately 3.6998.\\n\\nActually, let me compute this more precisely:\\n50.653^(1/3) \\u2248 3.69981\\n\\nLet me verify once more:\\n3.69981^3 \\u2248 50.652998\\n\\nThat's extremely close to 50.653, so I'll say that the cube root of 50.653 is approximately 3.69981.\",\n",
+      "    \"type\": \"thinking\"\n",
+      "  },\n",
+      "  {\n",
+      "    \"text\": \"The cube root of 50.653 is approximately 3.6998.\\n\\nTo verify: 3.6998\\u00b3 = 50.6530, which is very close to our original number.\",\n",
+      "    \"type\": \"text\"\n",
+      "  }\n",
+      "]\n"
+     ]
+    }
+   ],
+   "source": [
+    "import json\n",
+    "\n",
+    "from langchain_anthropic import ChatAnthropic\n",
+    "\n",
+    "llm = ChatAnthropic(\n",
+    "    model=\"claude-3-7-sonnet-latest\",\n",
+    "    max_tokens=5000,\n",
+    "    thinking={\"type\": \"enabled\", \"budget_tokens\": 2000},\n",
+    ")\n",
+    "\n",
+    "response = llm.invoke(\"What is the cube root of 50.653?\")\n",
+    "print(json.dumps(response.content, indent=2))"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "301d372f-4dec-43e6-b58c-eee25633e1a6",

libs/partners/anthropic/langchain_anthropic/chat_models.py

@@ -509,6 +509,93 @@ class ChatAnthropic(BaseChatModel):
 
             "The image depicts a sunny day with a partly cloudy sky. The sky is a brilliant blue color with scattered white clouds drifting across. The lighting and cloud patterns suggest pleasant, mild weather conditions. The scene shows a grassy field or meadow with a wooden boardwalk trail leading through it, indicating an outdoor setting on a nice day well-suited for enjoying nature."
 
+    Extended thinking:
+        Claude 3.7 Sonnet supports an
+        `extended thinking <https://docs.anthropic.com/en/docs/build-with-claude/extended-thinking>`_
+        feature, which will output the step-by-step reasoning process that led to its
+        final answer.
+
+        To use it, specify the `thinking` parameter when initializing `ChatAnthropic`.
+        It can also be passed in as a kwarg during invocation.
+
+        You will need to specify a token budget to use this feature. See usage example:
+
+        .. code-block:: python
+
+            from langchain_anthropic import ChatAnthropic
+
+            llm = ChatAnthropic(
+                model="claude-3-7-sonnet-latest",
+                max_tokens=5000,
+                thinking={"type": "enabled", "budget_tokens": 2000},
+            )
+
+            response = llm.invoke("What is the cube root of 50.653?")
+            response.content
+
+        .. code-block:: python
+
+            [{'signature': '...', 'thinking': "To find the cube root of 50.653...", 'type': 'thinking'}, {'text': 'The cube root of 50.653 is ...', 'type': 'text'}]
+
+    Citations:
+        Anthropic supports a
+        `citations <https://docs.anthropic.com/en/docs/build-with-claude/citations>`_
+        feature that lets Claude attach context to its answers based on source
+        documents supplied by the user. When
+        `document content blocks <https://docs.anthropic.com/en/docs/build-with-claude/citations#document-types>`_
+        with ``"citations": {"enabled": True}`` are included in a query, Claude may
+        generate citations in its response.
+
+        .. code-block:: python
+
+            from langchain_anthropic import ChatAnthropic
+
+            llm = ChatAnthropic(model="claude-3-5-haiku-latest")
+
+            messages = [
+                {
+                    "role": "user",
+                    "content": [
+                        {
+                            "type": "document",
+                            "source": {
+                                "type": "text",
+                                "media_type": "text/plain",
+                                "data": "The grass is green. The sky is blue.",
+                            },
+                            "title": "My Document",
+                            "context": "This is a trustworthy document.",
+                            "citations": {"enabled": True},
+                        },
+                        {"type": "text", "text": "What color is the grass and sky?"},
+                    ],
+                }
+            ]
+            response = llm.invoke(messages)
+            response.content
+
+        .. code-block:: python
+
+            [{'text': 'Based on the document, ', 'type': 'text'},
+            {'text': 'the grass is green',
+            'type': 'text',
+            'citations': [{'type': 'char_location',
+                'cited_text': 'The grass is green. ',
+                'document_index': 0,
+                'document_title': 'My Document',
+                'start_char_index': 0,
+                'end_char_index': 20}]},
+            {'text': ', and ', 'type': 'text'},
+            {'text': 'the sky is blue',
+            'type': 'text',
+            'citations': [{'type': 'char_location',
+                'cited_text': 'The sky is blue.',
+                'document_index': 0,
+                'document_title': 'My Document',
+                'start_char_index': 20,
+                'end_char_index': 36}]},
+            {'text': '.', 'type': 'text'}]
+
     Token usage:
         .. code-block:: python