mirror of
https://github.com/hwchase17/langchain.git
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405 lines
24 KiB
Plaintext
405 lines
24 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"id": "5d60cbb9-2a6a-43ea-a9e9-f67b16ddd2b2",
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"metadata": {},
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"source": [
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"# How to handle tool errors\n",
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"\n",
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"Using a model to invoke a tool has some obvious potential failure modes. Firstly, the model needs to return a output that can be parsed at all. Secondly, the model needs to return tool arguments that are valid.\n",
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"\n",
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"We can build error handling into our chains to mitigate these failure modes."
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]
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},
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{
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"cell_type": "markdown",
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"id": "712c774f-27c7-4351-a196-39900ca155f5",
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"metadata": {},
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"source": [
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"## Setup\n",
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"\n",
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"We'll need to install the following packages:"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "63056c24-9834-4e3d-8bc5-54b1e6c5df86",
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"metadata": {},
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"outputs": [],
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"source": [
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"%pip install --upgrade --quiet langchain-core langchain-openai"
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]
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},
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{
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"cell_type": "markdown",
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"id": "68107597-0c8c-4bb5-8c12-9992fabdf71a",
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"metadata": {},
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"source": [
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"If you'd like to trace your runs in [LangSmith](/docs/langsmith/) uncomment and set the following environment variables:"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "08785b6d-722d-4620-b6ec-36deb3842c69",
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"metadata": {},
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"outputs": [],
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"source": [
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"import getpass\n",
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"import os\n",
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"\n",
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"# os.environ[\"LANGCHAIN_TRACING_V2\"] = \"true\"\n",
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"# os.environ[\"LANGCHAIN_API_KEY\"] = getpass.getpass()"
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]
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},
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{
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"cell_type": "markdown",
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"id": "0a50f93a-5d6f-4691-8f98-27239a1c2f95",
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"metadata": {},
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"source": [
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"## Chain\n",
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"\n",
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"Suppose we have the following (dummy) tool and tool-calling chain. We'll make our tool intentionally convoluted to try and trip up the model.\n",
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"\n",
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"```{=mdx}\n",
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"import ChatModelTabs from \"@theme/ChatModelTabs\";\n",
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"\n",
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"<ChatModelTabs customVarName=\"llm\"/>\n",
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"```"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"id": "86258950-5e61-4340-81b9-84a5d26e8773",
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"metadata": {},
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"outputs": [],
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"source": [
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"# | echo: false\n",
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"# | output: false\n",
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"\n",
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"from langchain_openai import ChatOpenAI\n",
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"\n",
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"llm = ChatOpenAI(model=\"gpt-3.5-turbo-0125\", temperature=0)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"id": "1d20604e-c4d1-4d21-841b-23e4f61aec36",
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"metadata": {},
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"outputs": [],
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"source": [
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"# Define tool\n",
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"from langchain_core.tools import tool\n",
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"\n",
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"\n",
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"@tool\n",
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"def complex_tool(int_arg: int, float_arg: float, dict_arg: dict) -> int:\n",
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" \"\"\"Do something complex with a complex tool.\"\"\"\n",
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" return int_arg * float_arg"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"id": "553c2c13-28c8-4451-8a3a-6c31d52dc31d",
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"metadata": {},
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"outputs": [],
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"source": [
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"llm_with_tools = llm.bind_tools(\n",
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" [complex_tool],\n",
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")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"id": "802b2eca-9f79-4d6c-8257-85139ca5c752",
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"metadata": {},
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"outputs": [],
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"source": [
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"# Define chain\n",
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"chain = llm_with_tools | (lambda msg: msg.tool_calls[0][\"args\"]) | complex_tool"
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]
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},
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{
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"cell_type": "markdown",
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"id": "c34f005e-63f0-4841-9461-ca36c36607fc",
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"metadata": {},
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"source": [
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"We can see that when we try to invoke this chain with even a fairly explicit input, the model fails to correctly call the tool (it forgets the `dict_arg` argument)."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 12,
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"id": "d354664c-ac44-4967-a35f-8912b3ad9477",
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"metadata": {},
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"outputs": [
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{
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"ename": "ValidationError",
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"evalue": "1 validation error for complex_toolSchema\ndict_arg\n field required (type=value_error.missing)",
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"output_type": "error",
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"traceback": [
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"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
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"\u001b[0;31mValidationError\u001b[0m Traceback (most recent call last)",
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"Cell \u001b[0;32mIn[12], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mchain\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43minvoke\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 2\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43muse complex tool. the args are 5, 2.1, empty dictionary. don\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mt forget dict_arg\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\n\u001b[1;32m 3\u001b[0m \u001b[43m)\u001b[49m\n",
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"File \u001b[0;32m~/langchain/libs/core/langchain_core/runnables/base.py:2499\u001b[0m, in \u001b[0;36mRunnableSequence.invoke\u001b[0;34m(self, input, config)\u001b[0m\n\u001b[1;32m 2497\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[1;32m 2498\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m i, step \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28menumerate\u001b[39m(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39msteps):\n\u001b[0;32m-> 2499\u001b[0m \u001b[38;5;28minput\u001b[39m \u001b[38;5;241m=\u001b[39m \u001b[43mstep\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43minvoke\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 2500\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;28;43minput\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m 2501\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;66;43;03m# mark each step as a child run\u001b[39;49;00m\n\u001b[1;32m 2502\u001b[0m \u001b[43m \u001b[49m\u001b[43mpatch_config\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 2503\u001b[0m \u001b[43m \u001b[49m\u001b[43mconfig\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mcallbacks\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mrun_manager\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget_child\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43mf\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mseq:step:\u001b[39;49m\u001b[38;5;132;43;01m{\u001b[39;49;00m\u001b[43mi\u001b[49m\u001b[38;5;241;43m+\u001b[39;49m\u001b[38;5;241;43m1\u001b[39;49m\u001b[38;5;132;43;01m}\u001b[39;49;00m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[1;32m 2504\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 2505\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 2506\u001b[0m \u001b[38;5;66;03m# finish the root run\u001b[39;00m\n\u001b[1;32m 2507\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mBaseException\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m e:\n",
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"File \u001b[0;32m~/langchain/libs/core/langchain_core/tools.py:241\u001b[0m, in \u001b[0;36mBaseTool.invoke\u001b[0;34m(self, input, config, **kwargs)\u001b[0m\n\u001b[1;32m 234\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21minvoke\u001b[39m(\n\u001b[1;32m 235\u001b[0m \u001b[38;5;28mself\u001b[39m,\n\u001b[1;32m 236\u001b[0m \u001b[38;5;28minput\u001b[39m: Union[\u001b[38;5;28mstr\u001b[39m, Dict],\n\u001b[1;32m 237\u001b[0m config: Optional[RunnableConfig] \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m,\n\u001b[1;32m 238\u001b[0m \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs: Any,\n\u001b[1;32m 239\u001b[0m ) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m Any:\n\u001b[1;32m 240\u001b[0m config \u001b[38;5;241m=\u001b[39m ensure_config(config)\n\u001b[0;32m--> 241\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mrun\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 242\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;28;43minput\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m 243\u001b[0m \u001b[43m \u001b[49m\u001b[43mcallbacks\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mconfig\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mcallbacks\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 244\u001b[0m \u001b[43m \u001b[49m\u001b[43mtags\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mconfig\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mtags\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 245\u001b[0m \u001b[43m \u001b[49m\u001b[43mmetadata\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mconfig\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mmetadata\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 246\u001b[0m \u001b[43m \u001b[49m\u001b[43mrun_name\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mconfig\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mrun_name\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 247\u001b[0m \u001b[43m \u001b[49m\u001b[43mrun_id\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mconfig\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mpop\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mrun_id\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mNone\u001b[39;49;00m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 248\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 249\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n",
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"File \u001b[0;32m~/langchain/libs/core/langchain_core/tools.py:387\u001b[0m, in \u001b[0;36mBaseTool.run\u001b[0;34m(self, tool_input, verbose, start_color, color, callbacks, tags, metadata, run_name, run_id, **kwargs)\u001b[0m\n\u001b[1;32m 385\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m ValidationError \u001b[38;5;28;01mas\u001b[39;00m e:\n\u001b[1;32m 386\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mhandle_validation_error:\n\u001b[0;32m--> 387\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m e\n\u001b[1;32m 388\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mhandle_validation_error, \u001b[38;5;28mbool\u001b[39m):\n\u001b[1;32m 389\u001b[0m observation \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mTool input validation error\u001b[39m\u001b[38;5;124m\"\u001b[39m\n",
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"File \u001b[0;32m~/langchain/libs/core/langchain_core/tools.py:378\u001b[0m, in \u001b[0;36mBaseTool.run\u001b[0;34m(self, tool_input, verbose, start_color, color, callbacks, tags, metadata, run_name, run_id, **kwargs)\u001b[0m\n\u001b[1;32m 364\u001b[0m run_manager \u001b[38;5;241m=\u001b[39m callback_manager\u001b[38;5;241m.\u001b[39mon_tool_start(\n\u001b[1;32m 365\u001b[0m {\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mname\u001b[39m\u001b[38;5;124m\"\u001b[39m: \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mname, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mdescription\u001b[39m\u001b[38;5;124m\"\u001b[39m: \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mdescription},\n\u001b[1;32m 366\u001b[0m tool_input \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(tool_input, \u001b[38;5;28mstr\u001b[39m) \u001b[38;5;28;01melse\u001b[39;00m \u001b[38;5;28mstr\u001b[39m(tool_input),\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 375\u001b[0m \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs,\n\u001b[1;32m 376\u001b[0m )\n\u001b[1;32m 377\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m--> 378\u001b[0m parsed_input \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_parse_input\u001b[49m\u001b[43m(\u001b[49m\u001b[43mtool_input\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 379\u001b[0m tool_args, tool_kwargs \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_to_args_and_kwargs(parsed_input)\n\u001b[1;32m 380\u001b[0m observation \u001b[38;5;241m=\u001b[39m (\n\u001b[1;32m 381\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_run(\u001b[38;5;241m*\u001b[39mtool_args, run_manager\u001b[38;5;241m=\u001b[39mrun_manager, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mtool_kwargs)\n\u001b[1;32m 382\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m new_arg_supported\n\u001b[1;32m 383\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_run(\u001b[38;5;241m*\u001b[39mtool_args, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mtool_kwargs)\n\u001b[1;32m 384\u001b[0m )\n",
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"File \u001b[0;32m~/langchain/libs/core/langchain_core/tools.py:283\u001b[0m, in \u001b[0;36mBaseTool._parse_input\u001b[0;34m(self, tool_input)\u001b[0m\n\u001b[1;32m 281\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 282\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m input_args \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[0;32m--> 283\u001b[0m result \u001b[38;5;241m=\u001b[39m \u001b[43minput_args\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mparse_obj\u001b[49m\u001b[43m(\u001b[49m\u001b[43mtool_input\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 284\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m {\n\u001b[1;32m 285\u001b[0m k: \u001b[38;5;28mgetattr\u001b[39m(result, k)\n\u001b[1;32m 286\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m k, v \u001b[38;5;129;01min\u001b[39;00m result\u001b[38;5;241m.\u001b[39mdict()\u001b[38;5;241m.\u001b[39mitems()\n\u001b[1;32m 287\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m k \u001b[38;5;129;01min\u001b[39;00m tool_input\n\u001b[1;32m 288\u001b[0m }\n\u001b[1;32m 289\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m tool_input\n",
|
|
"File \u001b[0;32m~/langchain/.venv/lib/python3.9/site-packages/pydantic/v1/main.py:526\u001b[0m, in \u001b[0;36mBaseModel.parse_obj\u001b[0;34m(cls, obj)\u001b[0m\n\u001b[1;32m 524\u001b[0m exc \u001b[38;5;241m=\u001b[39m \u001b[38;5;167;01mTypeError\u001b[39;00m(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;132;01m{\u001b[39;00m\u001b[38;5;28mcls\u001b[39m\u001b[38;5;241m.\u001b[39m\u001b[38;5;18m__name__\u001b[39m\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m expected dict not \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mobj\u001b[38;5;241m.\u001b[39m\u001b[38;5;18m__class__\u001b[39m\u001b[38;5;241m.\u001b[39m\u001b[38;5;18m__name__\u001b[39m\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m'\u001b[39m)\n\u001b[1;32m 525\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m ValidationError([ErrorWrapper(exc, loc\u001b[38;5;241m=\u001b[39mROOT_KEY)], \u001b[38;5;28mcls\u001b[39m) \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01me\u001b[39;00m\n\u001b[0;32m--> 526\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mcls\u001b[39;49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mobj\u001b[49m\u001b[43m)\u001b[49m\n",
|
|
"File \u001b[0;32m~/langchain/.venv/lib/python3.9/site-packages/pydantic/v1/main.py:341\u001b[0m, in \u001b[0;36mBaseModel.__init__\u001b[0;34m(__pydantic_self__, **data)\u001b[0m\n\u001b[1;32m 339\u001b[0m values, fields_set, validation_error \u001b[38;5;241m=\u001b[39m validate_model(__pydantic_self__\u001b[38;5;241m.\u001b[39m\u001b[38;5;18m__class__\u001b[39m, data)\n\u001b[1;32m 340\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m validation_error:\n\u001b[0;32m--> 341\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m validation_error\n\u001b[1;32m 342\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[1;32m 343\u001b[0m object_setattr(__pydantic_self__, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124m__dict__\u001b[39m\u001b[38;5;124m'\u001b[39m, values)\n",
|
|
"\u001b[0;31mValidationError\u001b[0m: 1 validation error for complex_toolSchema\ndict_arg\n field required (type=value_error.missing)"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"chain.invoke(\n",
|
|
" \"use complex tool. the args are 5, 2.1, empty dictionary. don't forget dict_arg\"\n",
|
|
")"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "890d989d-2d39-4571-9a55-d3496b9b5d27",
|
|
"metadata": {},
|
|
"source": [
|
|
"## Try/except tool call\n",
|
|
"\n",
|
|
"The simplest way to more gracefully handle errors is to try/except the tool-calling step and return a helpful message on errors:"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 6,
|
|
"id": "8fedb550-683d-45ae-8876-ae7acb332019",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"from typing import Any\n",
|
|
"\n",
|
|
"from langchain_core.runnables import Runnable, RunnableConfig\n",
|
|
"\n",
|
|
"\n",
|
|
"def try_except_tool(tool_args: dict, config: RunnableConfig) -> Runnable:\n",
|
|
" try:\n",
|
|
" complex_tool.invoke(tool_args, config=config)\n",
|
|
" except Exception as e:\n",
|
|
" return f\"Calling tool with arguments:\\n\\n{tool_args}\\n\\nraised the following error:\\n\\n{type(e)}: {e}\"\n",
|
|
"\n",
|
|
"\n",
|
|
"chain = llm_with_tools | (lambda msg: msg.tool_calls[0][\"args\"]) | try_except_tool"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 15,
|
|
"id": "71a2c98d-c0be-4c0a-bb3d-41ad4596526c",
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"Calling tool with arguments:\n",
|
|
"\n",
|
|
"{'int_arg': 5, 'float_arg': 2.1}\n",
|
|
"\n",
|
|
"raised the following error:\n",
|
|
"\n",
|
|
"<class 'pydantic.v1.error_wrappers.ValidationError'>: 1 validation error for complex_toolSchema\n",
|
|
"dict_arg\n",
|
|
" field required (type=value_error.missing)\n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"print(\n",
|
|
" chain.invoke(\n",
|
|
" \"use complex tool. the args are 5, 2.1, empty dictionary. don't forget dict_arg\"\n",
|
|
" )\n",
|
|
")"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "3b2f6393-cb47-49d0-921c-09550a049fe4",
|
|
"metadata": {},
|
|
"source": [
|
|
"## Fallbacks\n",
|
|
"\n",
|
|
"We can also try to fallback to a better model in the event of a tool invocation error. In this case we'll fall back to an identical chain that uses `gpt-4-1106-preview` instead of `gpt-3.5-turbo`."
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 17,
|
|
"id": "02cc4223-35fa-4240-976a-012299ca703c",
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"10.5"
|
|
]
|
|
},
|
|
"execution_count": 17,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"chain = llm_with_tools | (lambda msg: msg.tool_calls[0][\"args\"]) | complex_tool\n",
|
|
"better_model = ChatOpenAI(model=\"gpt-4-1106-preview\", temperature=0).bind_tools(\n",
|
|
" [complex_tool], tool_choice=\"complex_tool\"\n",
|
|
")\n",
|
|
"better_chain = better_model | (lambda msg: msg.tool_calls[0][\"args\"]) | complex_tool\n",
|
|
"\n",
|
|
"chain_with_fallback = chain.with_fallbacks([better_chain])\n",
|
|
"chain_with_fallback.invoke(\n",
|
|
" \"use complex tool. the args are 5, 2.1, empty dictionary. don't forget dict_arg\"\n",
|
|
")"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "412f8c4e-cc83-4d87-84a1-5ba2f8edb1e9",
|
|
"metadata": {},
|
|
"source": [
|
|
"Looking at the [Langsmith trace](https://smith.langchain.com/public/00e91fc2-e1a4-4b0f-a82e-e6b3119d196c/r) for this chain run, we can see that the first chain call fails as expected and it's the fallback that succeeds."
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "304b59cd-cd25-4205-9769-36595c8f3b59",
|
|
"metadata": {},
|
|
"source": [
|
|
"## Retry with exception\n",
|
|
"\n",
|
|
"To take things one step further, we can try to automatically re-run the chain with the exception passed in, so that the model may be able to correct its behavior:"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 13,
|
|
"id": "b5659956-9454-468a-9753-a3ff9052b8f5",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"import json\n",
|
|
"from typing import Any\n",
|
|
"\n",
|
|
"from langchain_core.messages import AIMessage, HumanMessage, ToolCall, ToolMessage\n",
|
|
"from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder\n",
|
|
"from langchain_core.runnables import RunnablePassthrough\n",
|
|
"\n",
|
|
"\n",
|
|
"class CustomToolException(Exception):\n",
|
|
" \"\"\"Custom LangChain tool exception.\"\"\"\n",
|
|
"\n",
|
|
" def __init__(self, tool_call: ToolCall, exception: Exception) -> None:\n",
|
|
" super().__init__()\n",
|
|
" self.tool_call = tool_call\n",
|
|
" self.exception = exception\n",
|
|
"\n",
|
|
"\n",
|
|
"def tool_custom_exception(msg: AIMessage, config: RunnableConfig) -> Runnable:\n",
|
|
" try:\n",
|
|
" return complex_tool.invoke(msg.tool_calls[0][\"args\"], config=config)\n",
|
|
" except Exception as e:\n",
|
|
" raise CustomToolException(msg.tool_calls[0], e)\n",
|
|
"\n",
|
|
"\n",
|
|
"def exception_to_messages(inputs: dict) -> dict:\n",
|
|
" exception = inputs.pop(\"exception\")\n",
|
|
"\n",
|
|
" # Add historical messages to the original input, so the model knows that it made a mistake with the last tool call.\n",
|
|
" messages = [\n",
|
|
" AIMessage(content=\"\", tool_calls=[exception.tool_call]),\n",
|
|
" ToolMessage(\n",
|
|
" tool_call_id=exception.tool_call[\"id\"], content=str(exception.exception)\n",
|
|
" ),\n",
|
|
" HumanMessage(\n",
|
|
" content=\"The last tool call raised an exception. Try calling the tool again with corrected arguments. Do not repeat mistakes.\"\n",
|
|
" ),\n",
|
|
" ]\n",
|
|
" inputs[\"last_output\"] = messages\n",
|
|
" return inputs\n",
|
|
"\n",
|
|
"\n",
|
|
"# We add a last_output MessagesPlaceholder to our prompt which if not passed in doesn't\n",
|
|
"# affect the prompt at all, but gives us the option to insert an arbitrary list of Messages\n",
|
|
"# into the prompt if needed. We'll use this on retries to insert the error message.\n",
|
|
"prompt = ChatPromptTemplate.from_messages(\n",
|
|
" [(\"human\", \"{input}\"), MessagesPlaceholder(\"last_output\", optional=True)]\n",
|
|
")\n",
|
|
"chain = prompt | llm_with_tools | tool_custom_exception\n",
|
|
"\n",
|
|
"# If the initial chain call fails, we rerun it withe the exception passed in as a message.\n",
|
|
"self_correcting_chain = chain.with_fallbacks(\n",
|
|
" [exception_to_messages | chain], exception_key=\"exception\"\n",
|
|
")"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 14,
|
|
"id": "4c45f5bd-cbb4-47d5-b4b6-aec50673c750",
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"10.5"
|
|
]
|
|
},
|
|
"execution_count": 14,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"self_correcting_chain.invoke(\n",
|
|
" {\n",
|
|
" \"input\": \"use complex tool. the args are 5, 2.1, empty dictionary. don't forget dict_arg\"\n",
|
|
" }\n",
|
|
")"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "50d269a9-3cab-4a37-ba2f-805296453627",
|
|
"metadata": {},
|
|
"source": [
|
|
"And our chain succeeds! Looking at the [LangSmith trace](https://smith.langchain.com/public/c11e804c-e14f-4059-bd09-64766f999c14/r), we can see that indeed our initial chain still fails, and it's only on retrying that the chain succeeds."
|
|
]
|
|
}
|
|
],
|
|
"metadata": {
|
|
"kernelspec": {
|
|
"display_name": "Python 3 (ipykernel)",
|
|
"language": "python",
|
|
"name": "python3"
|
|
},
|
|
"language_info": {
|
|
"codemirror_mode": {
|
|
"name": "ipython",
|
|
"version": 3
|
|
},
|
|
"file_extension": ".py",
|
|
"mimetype": "text/x-python",
|
|
"name": "python",
|
|
"nbconvert_exporter": "python",
|
|
"pygments_lexer": "ipython3",
|
|
"version": "3.10.1"
|
|
}
|
|
},
|
|
"nbformat": 4,
|
|
"nbformat_minor": 5
|
|
}
|