docs: use first_tool_only instead of return_single (#19666)

docs/docs/modules/model_io/output_parsers/types/openai_tools.ipynb

@@ -257,7 +257,7 @@
    "id": "fc5695c5-451f-482f-bde6-462d85f1a93e",
    "metadata": {},
    "source": [
-    "Certain models can return multiple tool invocations each call, so by default the output is a list. If we just want to return the first tool invocation, we can specify `return_single=True`"
+    "Certain models can return multiple tool invocations each call, so by default the output is a list. If we just want to return the first tool invocation, we can specify `first_tool_only=True`"
    ]
   },
   {
@@ -279,7 +279,7 @@
     }
    ],
    "source": [
-    "parser = JsonOutputKeyToolsParser(key_name=\"Joke\", return_single=True)\n",
+    "parser = JsonOutputKeyToolsParser(key_name=\"Joke\", first_tool_only=True)\n",
     "chain = prompt | model | parser\n",
     "chain.invoke({\"input\": \"tell me a joke\"})"
    ]

docs/docs/use_cases/csv.ipynb

@@ -418,7 +418,7 @@
    "source": [
     "from langchain.output_parsers.openai_tools import JsonOutputKeyToolsParser\n",
     "\n",
-    "parser = JsonOutputKeyToolsParser(tool.name, return_single=True)\n",
+    "parser = JsonOutputKeyToolsParser(tool.name, first_tool_only=True)\n",
     "(llm_with_tools | parser).invoke(\n",
     "    \"I have a dataframe 'df' and want to know the correlation between the 'Age' and 'Fare' columns\"\n",
     ")"

docs/docs/use_cases/question_answering/citations.ipynb

@@ -281,7 +281,7 @@
    "source": [
     "from langchain.output_parsers.openai_tools import JsonOutputKeyToolsParser\n",
     "\n",
-    "output_parser = JsonOutputKeyToolsParser(key_name=\"cited_answer\", return_single=True)\n",
+    "output_parser = JsonOutputKeyToolsParser(key_name=\"cited_answer\", first_tool_only=True)\n",
     "(llm_with_tool | output_parser).invoke(example_q)"
    ]
   },
@@ -403,7 +403,9 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "output_parser_2 = JsonOutputKeyToolsParser(key_name=\"quoted_answer\", return_single=True)\n",
+    "output_parser_2 = JsonOutputKeyToolsParser(\n",
+    "    key_name=\"quoted_answer\", first_tool_only=True\n",
+    ")\n",
     "llm_with_tool_2 = llm.bind_tools(\n",
     "    [quoted_answer],\n",
     "    tool_choice=\"quoted_answer\",\n",
@@ -785,7 +787,7 @@
     "annotation_chain = (\n",
     "    prompt_5\n",
     "    | llm_with_tools_5\n",
-    "    | JsonOutputKeyToolsParser(key_name=\"annotated_answer\", return_single=True)\n",
+    "    | JsonOutputKeyToolsParser(key_name=\"annotated_answer\", first_tool_only=True)\n",
     "    | itemgetter(\"citations\")\n",
     ")\n",
     "\n",

docs/docs/use_cases/tool_use/quickstart.ipynb

@@ -266,7 +266,7 @@
    "id": "7f712d8d-0314-4d3d-b563-378b72fd8bb5",
    "metadata": {},
    "source": [
-    "Since we know we're always invoking the `multiply` tool, we can simplify our output a bit to return only the args for the `multiply` tool using the `JsonoutputKeyToolsParser`. To further simplify we'll specify `return_single=True`, so that instead of a list of tool invocations our output parser returns only the first tool invocation."
+    "Since we know we're always invoking the `multiply` tool, we can simplify our output a bit to return only the args for the `multiply` tool using the `JsonoutputKeyToolsParser`. To further simplify we'll specify `first_tool_only=True`, so that instead of a list of tool invocations our output parser returns only the first tool invocation."
    ]
   },
   {
@@ -290,7 +290,7 @@
     "from langchain.output_parsers import JsonOutputKeyToolsParser\n",
     "\n",
     "chain = model_with_tools | JsonOutputKeyToolsParser(\n",
-    "    key_name=\"multiply\", return_single=True\n",
+    "    key_name=\"multiply\", first_tool_only=True\n",
     ")\n",
     "chain.invoke(\"What's four times 23\")"
    ]
@@ -328,7 +328,7 @@
     "# Note: the `.map()` at the end of `multiply` allows us to pass in a list of `multiply` arguments instead of a single one.\n",
     "chain = (\n",
     "    model_with_tools\n",
-    "    | JsonOutputKeyToolsParser(key_name=\"multiply\", return_single=True)\n",
+    "    | JsonOutputKeyToolsParser(key_name=\"multiply\", first_tool_only=True)\n",
     "    | multiply\n",
     ")\n",
     "chain.invoke(\"What's four times 23\")"

docs/docs/use_cases/tool_use/tool_error_handling.ipynb

@@ -116,7 +116,7 @@
     "\n",
     "chain = (\n",
     "    model_with_tools\n",
-    "    | JsonOutputKeyToolsParser(key_name=\"complex_tool\", return_single=True)\n",
+    "    | JsonOutputKeyToolsParser(key_name=\"complex_tool\", first_tool_only=True)\n",
     "    | complex_tool\n",
     ")"
    ]
@@ -190,7 +190,7 @@
     "\n",
     "chain = (\n",
     "    model_with_tools\n",
-    "    | JsonOutputKeyToolsParser(key_name=\"complex_tool\", return_single=True)\n",
+    "    | JsonOutputKeyToolsParser(key_name=\"complex_tool\", first_tool_only=True)\n",
     "    | try_except_tool\n",
     ")"
    ]
@@ -255,7 +255,7 @@
    "source": [
     "chain = (\n",
     "    model_with_tools\n",
-    "    | JsonOutputKeyToolsParser(key_name=\"complex_tool\", return_single=True)\n",
+    "    | JsonOutputKeyToolsParser(key_name=\"complex_tool\", first_tool_only=True)\n",
     "    | complex_tool\n",
     ")\n",
     "better_model = ChatOpenAI(model=\"gpt-4-1106-preview\", temperature=0).bind_tools(\n",
@@ -263,7 +263,7 @@
     ")\n",
     "better_chain = (\n",
     "    better_model\n",
-    "    | JsonOutputKeyToolsParser(key_name=\"complex_tool\", return_single=True)\n",
+    "    | JsonOutputKeyToolsParser(key_name=\"complex_tool\", first_tool_only=True)\n",
     "    | complex_tool\n",
     ")\n",
     "\n",
@@ -355,7 +355,7 @@
     "    prompt\n",
     "    | model_with_tools\n",
     "    | JsonOutputKeyToolsParser(\n",
-    "        key_name=\"complex_tool\", return_id=True, return_single=True\n",
+    "        key_name=\"complex_tool\", return_id=True, first_tool_only=True\n",
     "    )\n",
     "    | tool_custom_exception\n",
     ")\n",