From d53de65aca55422857b2c9ef02f64fef4ef970ce Mon Sep 17 00:00:00 2001
From: Erick Friis <erick@langchain.dev>
Date: Thu, 16 May 2024 11:34:02 -0700
Subject: [PATCH] docs: anthropic forced tool calling (#21774)

---
 docs/docs/integrations/chat/anthropic.ipynb | 51 ++++++++++++++++-----
 1 file changed, 39 insertions(+), 12 deletions(-)

diff --git a/docs/docs/integrations/chat/anthropic.ipynb b/docs/docs/integrations/chat/anthropic.ipynb
index 2308c1063fb..6ffd22a46d3 100644
--- a/docs/docs/integrations/chat/anthropic.ipynb
+++ b/docs/docs/integrations/chat/anthropic.ipynb
@@ -80,7 +80,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 1,
    "id": "238bdbaa-526a-4130-89e9-523aa44bb196",
    "metadata": {},
    "outputs": [],
@@ -250,16 +250,7 @@
    "execution_count": 3,
    "id": "42f87466-cb8e-490d-a9f8-aa0f8e9b4217",
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/Users/bagatur/langchain/libs/core/langchain_core/_api/beta_decorator.py:87: LangChainBetaWarning: The function `bind_tools` is in beta. It is actively being worked on, so the API may change.\n",
-      "  warn_beta(\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "from langchain_core.pydantic_v1 import BaseModel, Field\n",
     "\n",
@@ -369,13 +360,49 @@
    "id": "90e015e0-c6e5-4ff5-8fb9-be0cd3c86395",
    "metadata": {},
    "source": [
-    "::: {.callout-tip}\n",
+    ":::tip\n",
     "\n",
     "ChatAnthropic model outputs are always a single AI message that can have either a single string or a list of content blocks. The content blocks can be text blocks or tool-duse blocks. There can be multiple of each and they can be interspersed.\n",
     "\n",
     ":::"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "b5145dea-0183-4cab-b9e2-0e35fb8370cf",
+   "metadata": {},
+   "source": [
+    "### Forcing tool calls\n",
+    "\n",
+    "By default the model can choose whether to call any tools. To force the model to call at least one tool we can specify `bind_tools(..., tool_choice=\"any\")` and to force the model to call a specific tool we can pass in that tool name `bind_tools(..., tool_choice=\"GetWeather\")`"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "05993626-060c-449f-8069-e52d31442977",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[{'name': 'GetWeather',\n",
+       "  'args': {'location': '<UNKNOWN>'},\n",
+       "  'id': 'toolu_01DwWjKzHPs6EHCUPxsGm9bN'}]"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "llm_with_force_tools = llm.bind_tools([GetWeather], tool_choice=\"GetWeather\")\n",
+    "# Notice the model will still return tool calls despite a message that\n",
+    "# doesn't have anything to do with the tools.\n",
+    "llm_with_force_tools.invoke(\"this doesn't really require tool use\").tool_calls"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "8652ee98-814c-4ed6-9def-275eeaa9651e",