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docs, core: error messaging [wip] (#27397)
This commit is contained in:
Erick Friis
GitHub
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202d7f6c4a
commit
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14
docs/docs/troubleshooting/errors/INVALID_PROMPT_INPUT.mdx
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docs/docs/troubleshooting/errors/INVALID_PROMPT_INPUT.mdx
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# INVALID_PROMPT_INPUT
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A [prompt template](/docs/concepts#prompt-templates) received missing or invalid input variables.
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## Troubleshooting
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The following may help resolve this error:
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- Double-check your prompt template to ensure that it is correct.
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- If you are using the default f-string format and you are using curly braces `{` anywhere in your template, they should be double escaped like this: `{{` (and if you want to render a double curly brace, you should use four curly braces: `{{{{`).
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- If you are using a [`MessagesPlaceholder`](/docs/concepts/#messagesplaceholder), make sure that you are passing in an array of messages or message-like objects.
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- If you are using shorthand tuples to declare your prompt template, make sure that the variable name is wrapped in curly braces (`["placeholder", "{messages}"]`).
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- Try viewing the inputs into your prompt template using [LangSmith](https://docs.smith.langchain.com/) or log statements to confirm they appear as expected.
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- If you are pulling a prompt from the [LangChain Prompt Hub](https://smith.langchain.com/prompts), try pulling and logging it or running it in isolation with a sample input to confirm that it is what you expect.
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272
docs/docs/troubleshooting/errors/INVALID_TOOL_RESULTS.ipynb
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docs/docs/troubleshooting/errors/INVALID_TOOL_RESULTS.ipynb
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docs/docs/troubleshooting/errors/MESSAGE_COERCION_FAILURE.ipynb
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docs/docs/troubleshooting/errors/MESSAGE_COERCION_FAILURE.ipynb
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{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# MESSAGE_COERCION_FAILURE\n",
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"\n",
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"Instead of always requiring instances of `BaseMessage`, several modules in LangChain take `MessageLikeRepresentation`, which is defined as:"
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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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"metadata": {},
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"outputs": [],
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"source": [
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"from typing import Union\n",
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"\n",
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"from langchain_core.prompts.chat import (\n",
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" BaseChatPromptTemplate,\n",
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" BaseMessage,\n",
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" BaseMessagePromptTemplate,\n",
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")\n",
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"\n",
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"MessageLikeRepresentation = Union[\n",
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" Union[BaseMessagePromptTemplate, BaseMessage, BaseChatPromptTemplate],\n",
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" tuple[\n",
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" Union[str, type],\n",
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" Union[str, list[dict], list[object]],\n",
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" ],\n",
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" str,\n",
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"]"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"These include OpenAI style message objects (`{ role: \"user\", content: \"Hello world!\" }`),\n",
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"tuples, and plain strings (which are converted to [`HumanMessages`](/docs/concepts#humanmessage)).\n",
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"\n",
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"If one of these modules receives a value outside of one of these formats, you will receive an error like the following:"
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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": 5,
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"metadata": {},
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"outputs": [
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{
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"ename": "ValueError",
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"evalue": "Message dict must contain 'role' and 'content' keys, got {'role': 'HumanMessage', 'random_field': 'random value'}",
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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;31mKeyError\u001b[0m Traceback (most recent call last)",
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"File \u001b[0;32m~/langchain/oss-py/libs/core/langchain_core/messages/utils.py:318\u001b[0m, in \u001b[0;36m_convert_to_message\u001b[0;34m(message)\u001b[0m\n\u001b[1;32m 317\u001b[0m \u001b[38;5;66;03m# None msg content is not allowed\u001b[39;00m\n\u001b[0;32m--> 318\u001b[0m msg_content \u001b[38;5;241m=\u001b[39m \u001b[43mmsg_kwargs\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;43mcontent\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m)\u001b[49m \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 319\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mKeyError\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m e:\n",
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"\u001b[0;31mKeyError\u001b[0m: 'content'",
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"\nThe above exception was the direct cause of the following exception:\n",
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"\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)",
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"Cell \u001b[0;32mIn[5], line 10\u001b[0m\n\u001b[1;32m 3\u001b[0m uncoercible_message \u001b[38;5;241m=\u001b[39m {\n\u001b[1;32m 4\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mrole\u001b[39m\u001b[38;5;124m\"\u001b[39m: \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mHumanMessage\u001b[39m\u001b[38;5;124m\"\u001b[39m,\n\u001b[1;32m 5\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mrandom_field\u001b[39m\u001b[38;5;124m\"\u001b[39m: \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mrandom value\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 6\u001b[0m }\n\u001b[1;32m 8\u001b[0m model \u001b[38;5;241m=\u001b[39m ChatAnthropic(model\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mclaude-3-5-sonnet-20240620\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[0;32m---> 10\u001b[0m \u001b[43mmodel\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43minvoke\u001b[49m\u001b[43m(\u001b[49m\u001b[43m[\u001b[49m\u001b[43muncoercible_message\u001b[49m\u001b[43m]\u001b[49m\u001b[43m)\u001b[49m\n",
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"File \u001b[0;32m~/langchain/oss-py/libs/core/langchain_core/language_models/chat_models.py:287\u001b[0m, in \u001b[0;36mBaseChatModel.invoke\u001b[0;34m(self, input, config, stop, **kwargs)\u001b[0m\n\u001b[1;32m 275\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21minvoke\u001b[39m(\n\u001b[1;32m 276\u001b[0m \u001b[38;5;28mself\u001b[39m,\n\u001b[1;32m 277\u001b[0m \u001b[38;5;28minput\u001b[39m: LanguageModelInput,\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 281\u001b[0m \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs: Any,\n\u001b[1;32m 282\u001b[0m ) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m BaseMessage:\n\u001b[1;32m 283\u001b[0m config \u001b[38;5;241m=\u001b[39m ensure_config(config)\n\u001b[1;32m 284\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m cast(\n\u001b[1;32m 285\u001b[0m ChatGeneration,\n\u001b[1;32m 286\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mgenerate_prompt(\n\u001b[0;32m--> 287\u001b[0m [\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_convert_input\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43minput\u001b[39;49m\u001b[43m)\u001b[49m],\n\u001b[1;32m 288\u001b[0m stop\u001b[38;5;241m=\u001b[39mstop,\n\u001b[1;32m 289\u001b[0m callbacks\u001b[38;5;241m=\u001b[39mconfig\u001b[38;5;241m.\u001b[39mget(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mcallbacks\u001b[39m\u001b[38;5;124m\"\u001b[39m),\n\u001b[1;32m 290\u001b[0m tags\u001b[38;5;241m=\u001b[39mconfig\u001b[38;5;241m.\u001b[39mget(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mtags\u001b[39m\u001b[38;5;124m\"\u001b[39m),\n\u001b[1;32m 291\u001b[0m metadata\u001b[38;5;241m=\u001b[39mconfig\u001b[38;5;241m.\u001b[39mget(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mmetadata\u001b[39m\u001b[38;5;124m\"\u001b[39m),\n\u001b[1;32m 292\u001b[0m run_name\u001b[38;5;241m=\u001b[39mconfig\u001b[38;5;241m.\u001b[39mget(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mrun_name\u001b[39m\u001b[38;5;124m\"\u001b[39m),\n\u001b[1;32m 293\u001b[0m run_id\u001b[38;5;241m=\u001b[39mconfig\u001b[38;5;241m.\u001b[39mpop(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mrun_id\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;28;01mNone\u001b[39;00m),\n\u001b[1;32m 294\u001b[0m \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs,\n\u001b[1;32m 295\u001b[0m )\u001b[38;5;241m.\u001b[39mgenerations[\u001b[38;5;241m0\u001b[39m][\u001b[38;5;241m0\u001b[39m],\n\u001b[1;32m 296\u001b[0m )\u001b[38;5;241m.\u001b[39mmessage\n",
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"File \u001b[0;32m~/langchain/oss-py/libs/core/langchain_core/language_models/chat_models.py:267\u001b[0m, in \u001b[0;36mBaseChatModel._convert_input\u001b[0;34m(self, input)\u001b[0m\n\u001b[1;32m 265\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m StringPromptValue(text\u001b[38;5;241m=\u001b[39m\u001b[38;5;28minput\u001b[39m)\n\u001b[1;32m 266\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(\u001b[38;5;28minput\u001b[39m, Sequence):\n\u001b[0;32m--> 267\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m ChatPromptValue(messages\u001b[38;5;241m=\u001b[39m\u001b[43mconvert_to_messages\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43minput\u001b[39;49m\u001b[43m)\u001b[49m)\n\u001b[1;32m 268\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 269\u001b[0m msg \u001b[38;5;241m=\u001b[39m (\n\u001b[1;32m 270\u001b[0m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mInvalid input type \u001b[39m\u001b[38;5;132;01m{\u001b[39;00m\u001b[38;5;28mtype\u001b[39m(\u001b[38;5;28minput\u001b[39m)\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m. \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 271\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mMust be a PromptValue, str, or list of BaseMessages.\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 272\u001b[0m )\n",
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"File \u001b[0;32m~/langchain/oss-py/libs/core/langchain_core/messages/utils.py:348\u001b[0m, in \u001b[0;36mconvert_to_messages\u001b[0;34m(messages)\u001b[0m\n\u001b[1;32m 346\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(messages, PromptValue):\n\u001b[1;32m 347\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m messages\u001b[38;5;241m.\u001b[39mto_messages()\n\u001b[0;32m--> 348\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43m[\u001b[49m\u001b[43m_convert_to_message\u001b[49m\u001b[43m(\u001b[49m\u001b[43mm\u001b[49m\u001b[43m)\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mfor\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mm\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;129;43;01min\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mmessages\u001b[49m\u001b[43m]\u001b[49m\n",
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"File \u001b[0;32m~/langchain/oss-py/libs/core/langchain_core/messages/utils.py:348\u001b[0m, in \u001b[0;36m<listcomp>\u001b[0;34m(.0)\u001b[0m\n\u001b[1;32m 346\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(messages, PromptValue):\n\u001b[1;32m 347\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m messages\u001b[38;5;241m.\u001b[39mto_messages()\n\u001b[0;32m--> 348\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m [\u001b[43m_convert_to_message\u001b[49m\u001b[43m(\u001b[49m\u001b[43mm\u001b[49m\u001b[43m)\u001b[49m \u001b[38;5;28;01mfor\u001b[39;00m m \u001b[38;5;129;01min\u001b[39;00m messages]\n",
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"File \u001b[0;32m~/langchain/oss-py/libs/core/langchain_core/messages/utils.py:321\u001b[0m, in \u001b[0;36m_convert_to_message\u001b[0;34m(message)\u001b[0m\n\u001b[1;32m 319\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mKeyError\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m e:\n\u001b[1;32m 320\u001b[0m msg \u001b[38;5;241m=\u001b[39m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mMessage dict must contain \u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mrole\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m and \u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mcontent\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m keys, got \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mmessage\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m--> 321\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(msg) \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01me\u001b[39;00m\n\u001b[1;32m 322\u001b[0m _message \u001b[38;5;241m=\u001b[39m _create_message_from_message_type(\n\u001b[1;32m 323\u001b[0m msg_type, msg_content, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mmsg_kwargs\n\u001b[1;32m 324\u001b[0m )\n\u001b[1;32m 325\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n",
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"\u001b[0;31mValueError\u001b[0m: Message dict must contain 'role' and 'content' keys, got {'role': 'HumanMessage', 'random_field': 'random value'}"
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]
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}
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],
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"source": [
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"from langchain_anthropic import ChatAnthropic\n",
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"\n",
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"uncoercible_message = {\"role\": \"HumanMessage\", \"random_field\": \"random value\"}\n",
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"\n",
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"model = ChatAnthropic(model=\"claude-3-5-sonnet-20240620\")\n",
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"\n",
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"model.invoke([uncoercible_message])"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Troubleshooting\n",
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"\n",
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"The following may help resolve this error:\n",
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"\n",
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"- Ensure that all inputs to chat models are an array of LangChain message classes or a supported message-like.\n",
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" - Check that there is no stringification or other unexpected transformation occuring.\n",
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"- Check the error's stack trace and add log or debugger statements."
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": []
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": ".venv",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.11.4"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}
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18
docs/docs/troubleshooting/errors/MODEL_AUTHENTICATION.mdx
Normal file
18
docs/docs/troubleshooting/errors/MODEL_AUTHENTICATION.mdx
Normal file
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# MODEL_AUTHENTICATION
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Your model provider is denying you access to their service.
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## Troubleshooting
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The following may help resolve this error:
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- Confirm that your API key or other credentials are correct.
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- If you are relying on an environment variable to authenticate, confirm that the variable name is correct and that it has a value set.
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- Note that environment variables can also be set by packages like `dotenv`.
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- For models, you can try explicitly passing an `api_key` parameter to rule out any environment variable issues like this:
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```python
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model = ChatOpenAI(api_key="YOUR_KEY_HERE")
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```
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- If you are using a proxy or other custom endpoint, make sure that your custom provider does not expect an alternative authentication scheme.
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10
docs/docs/troubleshooting/errors/MODEL_NOT_FOUND.mdx
Normal file
10
docs/docs/troubleshooting/errors/MODEL_NOT_FOUND.mdx
Normal file
@ -0,0 +1,10 @@
|
||||
# MODEL_NOT_FOUND
|
||||
|
||||
The model name you have specified is not acknowledged by your provider.
|
||||
|
||||
## Troubleshooting
|
||||
|
||||
The following may help resolve this error:
|
||||
|
||||
- Double check the model string you are passing in.
|
||||
- If you are using a proxy or other alternative host with a model wrapper, confirm that the permitted model names are not restricted or altered.
|
||||
13
docs/docs/troubleshooting/errors/MODEL_RATE_LIMIT.mdx
Normal file
13
docs/docs/troubleshooting/errors/MODEL_RATE_LIMIT.mdx
Normal file
@ -0,0 +1,13 @@
|
||||
# MODEL_RATE_LIMIT
|
||||
|
||||
You have hit the maximum number of requests that a model provider allows over a given time period and are being temporarily blocked.
|
||||
Generally, this error is temporary and your limit will reset after a certain amount of time.
|
||||
|
||||
## Troubleshooting
|
||||
|
||||
The following may help resolve this error:
|
||||
|
||||
- Contact your model provider and ask for a rate limit increase.
|
||||
- If many of your incoming requests are the same, utilize [model response caching](/docs/how_to/chat_model_caching/).
|
||||
- Spread requests across different providers if your application allows it.
|
||||
- Use a [`rate_limiter`](/docs/how_to/chat_model_rate_limiting/) to control the rate of requests to the model.
|
||||
126
docs/docs/troubleshooting/errors/OUTPUT_PARSING_FAILURE.ipynb
Normal file
126
docs/docs/troubleshooting/errors/OUTPUT_PARSING_FAILURE.ipynb
Normal file
@ -0,0 +1,126 @@
|
||||
{
|
||||
"cells": [
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"# OUTPUT_PARSING_FAILURE\n",
|
||||
"\n",
|
||||
"An [output parser](/docs/concepts#output-parsers) was unable to handle model output as expected.\n",
|
||||
"\n",
|
||||
"To illustrate this, let's say you have an output parser that expects a chat model to output JSON surrounded by a markdown code tag (triple backticks). Here would be an example of good input:"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 2,
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"{'foo': 'bar'}"
|
||||
]
|
||||
},
|
||||
"execution_count": 2,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"from langchain_core.messages import AIMessage\n",
|
||||
"from langchain_core.output_parsers import JsonOutputParser\n",
|
||||
"\n",
|
||||
"message = AIMessage(content='```\\n{\"foo\": \"bar\"}\\n```')\n",
|
||||
"output_parser = JsonOutputParser()\n",
|
||||
"output_parser.invoke(message)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"Internally, our JSON parser stripped out the markdown fence and newlines and then ran `json.loads`.\n",
|
||||
"\n",
|
||||
"If instead the chat model generated an output with malformed JSON, we will get an error:"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 9,
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"ename": "OutputParserException",
|
||||
"evalue": "Invalid json output: ```\n{{\"foo\":\n```",
|
||||
"output_type": "error",
|
||||
"traceback": [
|
||||
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
||||
"\u001b[0;31mJSONDecodeError\u001b[0m Traceback (most recent call last)",
|
||||
"File \u001b[0;32m~/langchain/oss-py/libs/core/langchain_core/output_parsers/json.py:83\u001b[0m, in \u001b[0;36mJsonOutputParser.parse_result\u001b[0;34m(self, result, partial)\u001b[0m\n\u001b[1;32m 82\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m---> 83\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mparse_json_markdown\u001b[49m\u001b[43m(\u001b[49m\u001b[43mtext\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 84\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m JSONDecodeError \u001b[38;5;28;01mas\u001b[39;00m e:\n",
|
||||
"File \u001b[0;32m~/langchain/oss-py/libs/core/langchain_core/utils/json.py:144\u001b[0m, in \u001b[0;36mparse_json_markdown\u001b[0;34m(json_string, parser)\u001b[0m\n\u001b[1;32m 143\u001b[0m json_str \u001b[38;5;241m=\u001b[39m json_string \u001b[38;5;28;01mif\u001b[39;00m match \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;28;01melse\u001b[39;00m match\u001b[38;5;241m.\u001b[39mgroup(\u001b[38;5;241m2\u001b[39m)\n\u001b[0;32m--> 144\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43m_parse_json\u001b[49m\u001b[43m(\u001b[49m\u001b[43mjson_str\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mparser\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mparser\u001b[49m\u001b[43m)\u001b[49m\n",
|
||||
"File \u001b[0;32m~/langchain/oss-py/libs/core/langchain_core/utils/json.py:160\u001b[0m, in \u001b[0;36m_parse_json\u001b[0;34m(json_str, parser)\u001b[0m\n\u001b[1;32m 159\u001b[0m \u001b[38;5;66;03m# Parse the JSON string into a Python dictionary\u001b[39;00m\n\u001b[0;32m--> 160\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mparser\u001b[49m\u001b[43m(\u001b[49m\u001b[43mjson_str\u001b[49m\u001b[43m)\u001b[49m\n",
|
||||
"File \u001b[0;32m~/langchain/oss-py/libs/core/langchain_core/utils/json.py:118\u001b[0m, in \u001b[0;36mparse_partial_json\u001b[0;34m(s, strict)\u001b[0m\n\u001b[1;32m 115\u001b[0m \u001b[38;5;66;03m# If we got here, we ran out of characters to remove\u001b[39;00m\n\u001b[1;32m 116\u001b[0m \u001b[38;5;66;03m# and still couldn't parse the string as JSON, so return the parse error\u001b[39;00m\n\u001b[1;32m 117\u001b[0m \u001b[38;5;66;03m# for the original string.\u001b[39;00m\n\u001b[0;32m--> 118\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mjson\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mloads\u001b[49m\u001b[43m(\u001b[49m\u001b[43ms\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mstrict\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mstrict\u001b[49m\u001b[43m)\u001b[49m\n",
|
||||
"File \u001b[0;32m~/.pyenv/versions/3.11.4/lib/python3.11/json/__init__.py:359\u001b[0m, in \u001b[0;36mloads\u001b[0;34m(s, cls, object_hook, parse_float, parse_int, parse_constant, object_pairs_hook, **kw)\u001b[0m\n\u001b[1;32m 358\u001b[0m kw[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mparse_constant\u001b[39m\u001b[38;5;124m'\u001b[39m] \u001b[38;5;241m=\u001b[39m parse_constant\n\u001b[0;32m--> 359\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[43mkw\u001b[49m\u001b[43m)\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mdecode\u001b[49m\u001b[43m(\u001b[49m\u001b[43ms\u001b[49m\u001b[43m)\u001b[49m\n",
|
||||
"File \u001b[0;32m~/.pyenv/versions/3.11.4/lib/python3.11/json/decoder.py:337\u001b[0m, in \u001b[0;36mJSONDecoder.decode\u001b[0;34m(self, s, _w)\u001b[0m\n\u001b[1;32m 333\u001b[0m \u001b[38;5;250m\u001b[39m\u001b[38;5;124;03m\"\"\"Return the Python representation of ``s`` (a ``str`` instance\u001b[39;00m\n\u001b[1;32m 334\u001b[0m \u001b[38;5;124;03mcontaining a JSON document).\u001b[39;00m\n\u001b[1;32m 335\u001b[0m \n\u001b[1;32m 336\u001b[0m \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[0;32m--> 337\u001b[0m obj, end \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mraw_decode\u001b[49m\u001b[43m(\u001b[49m\u001b[43ms\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43midx\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m_w\u001b[49m\u001b[43m(\u001b[49m\u001b[43ms\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m0\u001b[39;49m\u001b[43m)\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mend\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 338\u001b[0m end \u001b[38;5;241m=\u001b[39m _w(s, end)\u001b[38;5;241m.\u001b[39mend()\n",
|
||||
"File \u001b[0;32m~/.pyenv/versions/3.11.4/lib/python3.11/json/decoder.py:353\u001b[0m, in \u001b[0;36mJSONDecoder.raw_decode\u001b[0;34m(self, s, idx)\u001b[0m\n\u001b[1;32m 352\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m--> 353\u001b[0m obj, end \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mscan_once\u001b[49m\u001b[43m(\u001b[49m\u001b[43ms\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43midx\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 354\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mStopIteration\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m err:\n",
|
||||
"\u001b[0;31mJSONDecodeError\u001b[0m: Expecting property name enclosed in double quotes: line 1 column 2 (char 1)",
|
||||
"\nThe above exception was the direct cause of the following exception:\n",
|
||||
"\u001b[0;31mOutputParserException\u001b[0m Traceback (most recent call last)",
|
||||
"Cell \u001b[0;32mIn[9], line 3\u001b[0m\n\u001b[1;32m 1\u001b[0m message \u001b[38;5;241m=\u001b[39m AIMessage(content\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m```\u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;124m{{\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mfoo\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m:\u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;124m```\u001b[39m\u001b[38;5;124m'\u001b[39m)\n\u001b[1;32m 2\u001b[0m output_parser \u001b[38;5;241m=\u001b[39m JsonOutputParser()\n\u001b[0;32m----> 3\u001b[0m \u001b[43moutput_parser\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43minvoke\u001b[49m\u001b[43m(\u001b[49m\u001b[43mmessage\u001b[49m\u001b[43m)\u001b[49m\n",
|
||||
"File \u001b[0;32m~/langchain/oss-py/libs/core/langchain_core/output_parsers/base.py:193\u001b[0m, in \u001b[0;36mBaseOutputParser.invoke\u001b[0;34m(self, input, config, **kwargs)\u001b[0m\n\u001b[1;32m 186\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21minvoke\u001b[39m(\n\u001b[1;32m 187\u001b[0m \u001b[38;5;28mself\u001b[39m,\n\u001b[1;32m 188\u001b[0m \u001b[38;5;28minput\u001b[39m: Union[\u001b[38;5;28mstr\u001b[39m, BaseMessage],\n\u001b[1;32m 189\u001b[0m config: Optional[RunnableConfig] \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m,\n\u001b[1;32m 190\u001b[0m \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs: Any,\n\u001b[1;32m 191\u001b[0m ) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m T:\n\u001b[1;32m 192\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(\u001b[38;5;28minput\u001b[39m, BaseMessage):\n\u001b[0;32m--> 193\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[43m_call_with_config\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 194\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;28;43;01mlambda\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43minner_input\u001b[49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mparse_result\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 195\u001b[0m \u001b[43m \u001b[49m\u001b[43m[\u001b[49m\u001b[43mChatGeneration\u001b[49m\u001b[43m(\u001b[49m\u001b[43mmessage\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43minner_input\u001b[49m\u001b[43m)\u001b[49m\u001b[43m]\u001b[49m\n\u001b[1;32m 196\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 197\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;28;43minput\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m 198\u001b[0m \u001b[43m \u001b[49m\u001b[43mconfig\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 199\u001b[0m \u001b[43m \u001b[49m\u001b[43mrun_type\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mparser\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m 200\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 201\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 202\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_call_with_config(\n\u001b[1;32m 203\u001b[0m \u001b[38;5;28;01mlambda\u001b[39;00m inner_input: \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mparse_result([Generation(text\u001b[38;5;241m=\u001b[39minner_input)]),\n\u001b[1;32m 204\u001b[0m \u001b[38;5;28minput\u001b[39m,\n\u001b[1;32m 205\u001b[0m config,\n\u001b[1;32m 206\u001b[0m run_type\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mparser\u001b[39m\u001b[38;5;124m\"\u001b[39m,\n\u001b[1;32m 207\u001b[0m )\n",
|
||||
"File \u001b[0;32m~/langchain/oss-py/libs/core/langchain_core/runnables/base.py:1927\u001b[0m, in \u001b[0;36mRunnable._call_with_config\u001b[0;34m(self, func, input, config, run_type, serialized, **kwargs)\u001b[0m\n\u001b[1;32m 1923\u001b[0m context \u001b[38;5;241m=\u001b[39m copy_context()\n\u001b[1;32m 1924\u001b[0m context\u001b[38;5;241m.\u001b[39mrun(_set_config_context, child_config)\n\u001b[1;32m 1925\u001b[0m output \u001b[38;5;241m=\u001b[39m cast(\n\u001b[1;32m 1926\u001b[0m Output,\n\u001b[0;32m-> 1927\u001b[0m \u001b[43mcontext\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mrun\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 1928\u001b[0m \u001b[43m \u001b[49m\u001b[43mcall_func_with_variable_args\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;66;43;03m# type: ignore[arg-type]\u001b[39;49;00m\n\u001b[1;32m 1929\u001b[0m \u001b[43m \u001b[49m\u001b[43mfunc\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;66;43;03m# type: ignore[arg-type]\u001b[39;49;00m\n\u001b[1;32m 1930\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;28;43minput\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;66;43;03m# type: ignore[arg-type]\u001b[39;49;00m\n\u001b[1;32m 1931\u001b[0m \u001b[43m \u001b[49m\u001b[43mconfig\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1932\u001b[0m \u001b[43m \u001b[49m\u001b[43mrun_manager\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1933\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 1934\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m,\n\u001b[1;32m 1935\u001b[0m )\n\u001b[1;32m 1936\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\u001b[1;32m 1937\u001b[0m run_manager\u001b[38;5;241m.\u001b[39mon_chain_error(e)\n",
|
||||
"File \u001b[0;32m~/langchain/oss-py/libs/core/langchain_core/runnables/config.py:396\u001b[0m, in \u001b[0;36mcall_func_with_variable_args\u001b[0;34m(func, input, config, run_manager, **kwargs)\u001b[0m\n\u001b[1;32m 394\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m run_manager \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;129;01mand\u001b[39;00m accepts_run_manager(func):\n\u001b[1;32m 395\u001b[0m kwargs[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mrun_manager\u001b[39m\u001b[38;5;124m\"\u001b[39m] \u001b[38;5;241m=\u001b[39m run_manager\n\u001b[0;32m--> 396\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfunc\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43minput\u001b[39;49m\u001b[43m,\u001b[49m\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",
|
||||
"File \u001b[0;32m~/langchain/oss-py/libs/core/langchain_core/output_parsers/base.py:194\u001b[0m, in \u001b[0;36mBaseOutputParser.invoke.<locals>.<lambda>\u001b[0;34m(inner_input)\u001b[0m\n\u001b[1;32m 186\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21minvoke\u001b[39m(\n\u001b[1;32m 187\u001b[0m \u001b[38;5;28mself\u001b[39m,\n\u001b[1;32m 188\u001b[0m \u001b[38;5;28minput\u001b[39m: Union[\u001b[38;5;28mstr\u001b[39m, BaseMessage],\n\u001b[1;32m 189\u001b[0m config: Optional[RunnableConfig] \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m,\n\u001b[1;32m 190\u001b[0m \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs: Any,\n\u001b[1;32m 191\u001b[0m ) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m T:\n\u001b[1;32m 192\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(\u001b[38;5;28minput\u001b[39m, BaseMessage):\n\u001b[1;32m 193\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_call_with_config(\n\u001b[0;32m--> 194\u001b[0m \u001b[38;5;28;01mlambda\u001b[39;00m inner_input: \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mparse_result\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 195\u001b[0m \u001b[43m \u001b[49m\u001b[43m[\u001b[49m\u001b[43mChatGeneration\u001b[49m\u001b[43m(\u001b[49m\u001b[43mmessage\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43minner_input\u001b[49m\u001b[43m)\u001b[49m\u001b[43m]\u001b[49m\n\u001b[1;32m 196\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m,\n\u001b[1;32m 197\u001b[0m \u001b[38;5;28minput\u001b[39m,\n\u001b[1;32m 198\u001b[0m config,\n\u001b[1;32m 199\u001b[0m run_type\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mparser\u001b[39m\u001b[38;5;124m\"\u001b[39m,\n\u001b[1;32m 200\u001b[0m )\n\u001b[1;32m 201\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 202\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_call_with_config(\n\u001b[1;32m 203\u001b[0m \u001b[38;5;28;01mlambda\u001b[39;00m inner_input: \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mparse_result([Generation(text\u001b[38;5;241m=\u001b[39minner_input)]),\n\u001b[1;32m 204\u001b[0m \u001b[38;5;28minput\u001b[39m,\n\u001b[1;32m 205\u001b[0m config,\n\u001b[1;32m 206\u001b[0m run_type\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mparser\u001b[39m\u001b[38;5;124m\"\u001b[39m,\n\u001b[1;32m 207\u001b[0m )\n",
|
||||
"File \u001b[0;32m~/langchain/oss-py/libs/core/langchain_core/output_parsers/json.py:86\u001b[0m, in \u001b[0;36mJsonOutputParser.parse_result\u001b[0;34m(self, result, partial)\u001b[0m\n\u001b[1;32m 84\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m JSONDecodeError \u001b[38;5;28;01mas\u001b[39;00m e:\n\u001b[1;32m 85\u001b[0m msg \u001b[38;5;241m=\u001b[39m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mInvalid json output: \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mtext\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m---> 86\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m OutputParserException(msg, llm_output\u001b[38;5;241m=\u001b[39mtext) \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01me\u001b[39;00m\n",
|
||||
"\u001b[0;31mOutputParserException\u001b[0m: Invalid json output: ```\n{{\"foo\":\n```"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"message = AIMessage(content='```\\n{{\"foo\":\\n```')\n",
|
||||
"output_parser = JsonOutputParser()\n",
|
||||
"output_parser.invoke(message)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"Note that some prebuilt constructs like [legacy LangChain agents](/docs/how_to/agent_executor) and chains may use output parsers internally,\n",
|
||||
"so you may see this error even if you're not visibly instantiating and using an output parser.\n",
|
||||
"\n",
|
||||
"## Troubleshooting\n",
|
||||
"\n",
|
||||
"The following may help resolve this error:\n",
|
||||
"\n",
|
||||
"- Consider using [tool calling or other structured output techniques](/docs/how_to/structured_output/) if possible without an output parser to reliably output parseable values.\n",
|
||||
" - If you are using a prebuilt chain or agent, use [LangGraph](https://langchain-ai.github.io/langgraph/) to compose your logic explicitly instead.\n",
|
||||
"- Add more precise formatting instructions to your prompt. In the above example, adding `\"You must always return valid JSON fenced by a markdown code block. Do not return any additional text.\"` to your input may help steer the model to returning the expected format.\n",
|
||||
"- If you are using a smaller or less capable model, try using a more capable one.\n",
|
||||
"- Add [LLM-powered retries](/docs/how_to/output_parser_fixing/)."
|
||||
]
|
||||
}
|
||||
],
|
||||
"metadata": {
|
||||
"kernelspec": {
|
||||
"display_name": ".venv",
|
||||
"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": "3.11.4"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 2
|
||||
}
|
||||
12
docs/docs/troubleshooting/errors/index.mdx
Normal file
12
docs/docs/troubleshooting/errors/index.mdx
Normal file
@ -0,0 +1,12 @@
|
||||
# Error codes
|
||||
|
||||
This page contains guides around resolving common errors you may find while building with LangChain.
|
||||
Errors referenced below will have an `lc_error_code` property corresponding to one of the below codes when they are thrown in code.
|
||||
|
||||
- [INVALID_PROMPT_INPUT](/docs/troubleshooting/errors/INVALID_PROMPT_INPUT)
|
||||
- [INVALID_TOOL_RESULTS](/docs/troubleshooting/errors/INVALID_TOOL_RESULTS)
|
||||
- [MESSAGE_COERCION_FAILURE](/docs/troubleshooting/errors/MESSAGE_COERCION_FAILURE)
|
||||
- [MODEL_AUTHENTICATION](/docs/troubleshooting/errors/MODEL_AUTHENTICATION)
|
||||
- [MODEL_NOT_FOUND](/docs/troubleshooting/errors/MODEL_NOT_FOUND)
|
||||
- [MODEL_RATE_LIMIT](/docs/troubleshooting/errors/MODEL_RATE_LIMIT)
|
||||
- [OUTPUT_PARSING_FAILURE](/docs/troubleshooting/errors/OUTPUT_PARSING_FAILURE)
|
||||
@ -181,6 +181,11 @@ const config = {
|
||||
docId: "people",
|
||||
label: "People",
|
||||
},
|
||||
{
|
||||
type: "doc",
|
||||
docId: "troubleshooting/errors/index",
|
||||
label: "Error reference",
|
||||
},
|
||||
{
|
||||
type: 'html',
|
||||
value: '<hr class="dropdown-separator" style="margin-top: 0.5rem; margin-bottom: 0.5rem">',
|
||||
|
||||
@ -1,5 +1,6 @@
|
||||
"""Custom **exceptions** for LangChain."""
|
||||
|
||||
from enum import Enum
|
||||
from typing import Any, Optional
|
||||
|
||||
|
||||
@ -39,6 +40,10 @@ class OutputParserException(ValueError, LangChainException): # noqa: N818
|
||||
llm_output: Optional[str] = None,
|
||||
send_to_llm: bool = False,
|
||||
):
|
||||
if isinstance(error, str):
|
||||
error = create_message(
|
||||
message=error, error_code=ErrorCode.OUTPUT_PARSING_FAILURE
|
||||
)
|
||||
super().__init__(error)
|
||||
if send_to_llm and (observation is None or llm_output is None):
|
||||
msg = (
|
||||
@ -49,3 +54,21 @@ class OutputParserException(ValueError, LangChainException): # noqa: N818
|
||||
self.observation = observation
|
||||
self.llm_output = llm_output
|
||||
self.send_to_llm = send_to_llm
|
||||
|
||||
|
||||
class ErrorCode(Enum):
|
||||
INVALID_PROMPT_INPUT = "INVALID_PROMPT_INPUT"
|
||||
INVALID_TOOL_RESULTS = "INVALID_TOOL_RESULTS"
|
||||
MESSAGE_COERCION_FAILURE = "MESSAGE_COERCION_FAILURE"
|
||||
MODEL_AUTHENTICATION = "MODEL_AUTHENTICATION"
|
||||
MODEL_NOT_FOUND = "MODEL_NOT_FOUND"
|
||||
MODEL_RATE_LIMIT = "MODEL_RATE_LIMIT"
|
||||
OUTPUT_PARSING_FAILURE = "OUTPUT_PARSING_FAILURE"
|
||||
|
||||
|
||||
def create_message(*, message: str, error_code: ErrorCode) -> str:
|
||||
return (
|
||||
f"{message}\n"
|
||||
"For troubleshooting, visit: https://python.langchain.com/docs/"
|
||||
f"troubleshooting/errors/{error_code.value}"
|
||||
)
|
||||
|
||||
@ -28,6 +28,7 @@ from typing import (
|
||||
|
||||
from pydantic import Discriminator, Field, Tag
|
||||
|
||||
from langchain_core.exceptions import ErrorCode, create_message
|
||||
from langchain_core.messages.ai import AIMessage, AIMessageChunk
|
||||
from langchain_core.messages.base import BaseMessage, BaseMessageChunk
|
||||
from langchain_core.messages.chat import ChatMessage, ChatMessageChunk
|
||||
@ -274,6 +275,7 @@ def _create_message_from_message_type(
|
||||
f"Unexpected message type: '{message_type}'. Use one of 'human',"
|
||||
f" 'user', 'ai', 'assistant', 'function', 'tool', or 'system'."
|
||||
)
|
||||
msg = create_message(message=msg, error_code=ErrorCode.MESSAGE_COERCION_FAILURE)
|
||||
raise ValueError(msg)
|
||||
return message
|
||||
|
||||
@ -318,12 +320,16 @@ def _convert_to_message(message: MessageLikeRepresentation) -> BaseMessage:
|
||||
msg_content = msg_kwargs.pop("content") or ""
|
||||
except KeyError as e:
|
||||
msg = f"Message dict must contain 'role' and 'content' keys, got {message}"
|
||||
msg = create_message(
|
||||
message=msg, error_code=ErrorCode.MESSAGE_COERCION_FAILURE
|
||||
)
|
||||
raise ValueError(msg) from e
|
||||
_message = _create_message_from_message_type(
|
||||
msg_type, msg_content, **msg_kwargs
|
||||
)
|
||||
else:
|
||||
msg = f"Unsupported message type: {type(message)}"
|
||||
msg = create_message(message=msg, error_code=ErrorCode.MESSAGE_COERCION_FAILURE)
|
||||
raise NotImplementedError(msg)
|
||||
|
||||
return _message
|
||||
@ -1327,6 +1333,7 @@ def _msg_to_chunk(message: BaseMessage) -> BaseMessageChunk:
|
||||
f"Unrecognized message class {message.__class__}. Supported classes are "
|
||||
f"{list(_MSG_CHUNK_MAP.keys())}"
|
||||
)
|
||||
msg = create_message(message=msg, error_code=ErrorCode.MESSAGE_COERCION_FAILURE)
|
||||
raise ValueError(msg)
|
||||
|
||||
|
||||
@ -1343,6 +1350,7 @@ def _chunk_to_msg(chunk: BaseMessageChunk) -> BaseMessage:
|
||||
f"Unrecognized message chunk class {chunk.__class__}. Supported classes are "
|
||||
f"{list(_CHUNK_MSG_MAP.keys())}"
|
||||
)
|
||||
msg = create_message(message=msg, error_code=ErrorCode.MESSAGE_COERCION_FAILURE)
|
||||
raise ValueError(msg)
|
||||
|
||||
|
||||
|
||||
@ -21,6 +21,7 @@ import yaml
|
||||
from pydantic import BaseModel, ConfigDict, Field, model_validator
|
||||
from typing_extensions import Self, override
|
||||
|
||||
from langchain_core.exceptions import ErrorCode, create_message
|
||||
from langchain_core.load import dumpd
|
||||
from langchain_core.output_parsers.base import BaseOutputParser
|
||||
from langchain_core.prompt_values import (
|
||||
@ -74,18 +75,24 @@ class BasePromptTemplate(
|
||||
"Cannot have an input variable named 'stop', as it is used internally,"
|
||||
" please rename."
|
||||
)
|
||||
raise ValueError(msg)
|
||||
raise ValueError(
|
||||
create_message(message=msg, error_code=ErrorCode.INVALID_PROMPT_INPUT)
|
||||
)
|
||||
if "stop" in self.partial_variables:
|
||||
msg = (
|
||||
"Cannot have an partial variable named 'stop', as it is used "
|
||||
"internally, please rename."
|
||||
)
|
||||
raise ValueError(msg)
|
||||
raise ValueError(
|
||||
create_message(message=msg, error_code=ErrorCode.INVALID_PROMPT_INPUT)
|
||||
)
|
||||
|
||||
overall = set(self.input_variables).intersection(self.partial_variables)
|
||||
if overall:
|
||||
msg = f"Found overlapping input and partial variables: {overall}"
|
||||
raise ValueError(msg)
|
||||
raise ValueError(
|
||||
create_message(message=msg, error_code=ErrorCode.INVALID_PROMPT_INPUT)
|
||||
)
|
||||
return self
|
||||
|
||||
@classmethod
|
||||
@ -148,7 +155,11 @@ class BasePromptTemplate(
|
||||
f"Expected mapping type as input to {self.__class__.__name__}. "
|
||||
f"Received {type(inner_input)}."
|
||||
)
|
||||
raise TypeError(msg)
|
||||
raise TypeError(
|
||||
create_message(
|
||||
message=msg, error_code=ErrorCode.INVALID_PROMPT_INPUT
|
||||
)
|
||||
)
|
||||
missing = set(self.input_variables).difference(inner_input)
|
||||
if missing:
|
||||
msg = (
|
||||
@ -162,7 +173,9 @@ class BasePromptTemplate(
|
||||
" and not a variable, please escape it with double curly braces like: "
|
||||
f"'{{{{{example_key}}}}}'."
|
||||
)
|
||||
raise KeyError(msg)
|
||||
raise KeyError(
|
||||
create_message(message=msg, error_code=ErrorCode.INVALID_PROMPT_INPUT)
|
||||
)
|
||||
return inner_input
|
||||
|
||||
def _format_prompt_with_error_handling(self, inner_input: dict) -> PromptValue:
|
||||
@ -381,7 +394,9 @@ def _get_document_info(doc: Document, prompt: BasePromptTemplate[str]) -> dict:
|
||||
f"{required_metadata}. Received document with missing metadata: "
|
||||
f"{list(missing_metadata)}."
|
||||
)
|
||||
raise ValueError(msg)
|
||||
raise ValueError(
|
||||
create_message(message=msg, error_code=ErrorCode.INVALID_PROMPT_INPUT)
|
||||
)
|
||||
return {k: base_info[k] for k in prompt.input_variables}
|
||||
|
||||
|
||||
|
||||
Loading…
Reference in New Issue
Block a user