StructuredTool raises an error when instantiated

[Markus-sevend]

System Info

Environment:

Google COLAB project. When running !cat /etc/os-release it prints:

PRETTY_NAME="Ubuntu 22.04.2 LTS"
NAME="Ubuntu"
VERSION_ID="22.04"
VERSION="22.04.2 LTS (Jammy Jellyfish)"
VERSION_CODENAME=jammy
ID=ubuntu
ID_LIKE=debian
HOME_URL="https://www.ubuntu.com/"
SUPPORT_URL="https://help.ubuntu.com/"
BUG_REPORT_URL="https://bugs.launchpad.net/ubuntu/"
PRIVACY_POLICY_URL="https://www.ubuntu.com/legal/terms-and-policies/privacy-policy"
UBUNTU_CODENAME=jammy

Python Environment

!python -V:

Python 3.10.12

!pip show langchain:

Name: langchain
Version: 0.0.267
Summary: Building applications with LLMs through composability
Home-page: https://www.github.com/hwchase17/langchain
Author: 
Author-email: 
License: MIT
Location: /usr/local/lib/python3.10/dist-packages
Requires: aiohttp, async-timeout, dataclasses-json, langsmith, numexpr, numpy, openapi-schema-pydantic, pydantic, PyYAML, requests, SQLAlchemy, tenacity
Required-by: 

Who can help?

@hwchase17

Information

• The official example notebooks/scripts
• My own modified scripts

Related Components

• LLMs/Chat Models
• Embedding Models
• Prompts / Prompt Templates / Prompt Selectors
• Output Parsers
• Document Loaders
• Vector Stores / Retrievers
• Memory
• Agents / Agent Executors
• Tools / Toolkits
• Chains
• Callbacks/Tracing
• Async

Reproduction

Create a blank Google Colab Project (https://colab.research.google.com/#create=true) then add a code block and paste in this code:

!pip install langchain==0.0.267
# or try just '!pip install langchain' without the explicit version

from pydantic import BaseModel, Field

class InputArgsSchema(BaseModel):
  strarg: str = Field(description="The string argument for this tool")

# THIS WORKS:

from typing import Type

class Foo(BaseModel):
  my_base_model_subclass: Type[BaseModel] = Field(..., description="Equivalent to the args_schema field in langchain/StructuredTool")

my_foo = Foo(
    my_base_model_subclass=InputArgsSchema
)

print(f"My foo {my_foo} is successfully instantiated")

# BUT THIS DOES NOT:

from langchain.tools import StructuredTool

def my_tool_impl(strarg: str):
  print(f"Called myTool with strarg={strarg}")

my_tool = StructuredTool(
    name="my_tool",
    description="A demo tool for testing purposes",
    args_schema=InputArgsSchema,
    func=my_tool_impl
)

Now run the code block.

Expected behavior

The StructuredTool instance should be instantiated without an exception and the InputArgsSchema should be accepted as argument for args_schema.

[dosubot]

🤖

Hello,

Thank you for providing a detailed description of your issue. From the code you've shared, it seems like you're correctly defining InputArgsSchema as a subclass of BaseModel and using it as an argument for args_schema in the StructuredTool instantiation. This should work as expected.

However, without the exact error message, it's difficult to pinpoint the exact cause of the issue. The error could be due to a variety of reasons, such as a problem with the StructuredTool class, an issue with the Python environment in Google Colab, or a bug in the LangChain library.

To help us better understand the issue, could you please provide the exact error message that you're seeing when you try to instantiate the StructuredTool instance? This will give us more information to diagnose the problem.

In the meantime, you could try to debug the issue by adding some print statements in your code to check the type of InputArgsSchema and whether it's a subclass of BaseModel. For example:

print(isinstance(InputArgsSchema, BaseModel))

This will print True if InputArgsSchema is a subclass of BaseModel, and False otherwise.

Looking forward to your response.

Best,
Dosu

Sources

• libs/langchain/langchain/tools/base.py
• libs/langchain/tests/unit_tests/agents/test_tools.py

---

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[Markus-sevend]

Some updates on the topic:

The exact output and error message i get in the Colab environment (as suggested by @dosu-bot):

My foo my_base_model_subclass=<class '__main__.InputArgsSchema'> is successfully instantiated
---------------------------------------------------------------------------
ValidationError                           Traceback (most recent call last)
[<ipython-input-9-8e060e10267e>](https://localhost:8080/#) in <cell line: 28>()
     26   print(f"Called myTool with strarg={strarg}")
     27 
---> 28 my_tool = StructuredTool(
     29     name="my_tool",
     30     description="A demo tool for testing purposes",

[/usr/local/lib/python3.10/dist-packages/pydantic/v1/main.py](https://localhost:8080/#) in __init__(__pydantic_self__, **data)
    339         values, fields_set, validation_error = validate_model(__pydantic_self__.__class__, data)
    340         if validation_error:
--> 341             raise validation_error
    342         try:
    343             object_setattr(__pydantic_self__, '__dict__', values)

ValidationError: 1 validation error for StructuredTool
args_schema
  subclass of BaseModel expected (type=type_error.subclass; expected_class=BaseModel)

I can also reproduce this bug locally like so:

1. Setup a new blank venv and activate it
2. pip install langchain 0.0.267
3. remove the colab pip install statement from the code snippet (the "!pip install ...")
4. Run it

I debugged it locally and found that it seems like it is checking that args_schema is a subclass of the BaseModel in .../site-packages/pydantic/v1/main.py however my class inherits from the BaseModel in .../site-packages/pydantic/main.py (note the missing 'v1' sub-directory).

So to address the issue/bug again it should work with the BaseModel without the 'v1' part as this is the one thats imported when running from pydantic import BaseModel.

[dosubot]

🤖

Hello,

From the code you've shared, it seems like you're correctly defining InputArgsSchema as a subclass of BaseModel and passing it as the args_schema argument when instantiating StructuredTool. However, without the exact error message, it's difficult to pinpoint the exact issue.

The StructuredTool class in LangChain expects args_schema to be a subclass of BaseModel. The error might be related to how the args_schema is being used within the StructuredTool class.

Could you please provide the exact error message you're receiving when trying to instantiate the StructuredTool instance? This will help me understand the issue better and provide a more accurate solution.

Also, please ensure that the my_tool_impl function is correctly defined and matches the InputArgsSchema. The function should accept a single argument of type str, as defined in your InputArgsSchema.

Looking forward to your response.

Sources

• libs/langchain/langchain/tools/base.py

---

This response is meant to be useful and save you time. It is not meant to be a precise solution, but rather a starting point for your own research.

Help me be more useful! Please leave a 👍 if this is helpful and 👎 if it is irrelevant.

If you want to continue the conversation, start your reply with @dosu-bot.

[Markus-sevend]

@dosu-bot I did provide the error message in my comment

[Markus-sevend]

Ah i found what caused the problem: Pydantic has released a new version on June 30, 2023: https://docs.pydantic.dev/2.0/blog/pydantic-v2-final/

LangChain should consider updating to the new pydantic version then or otherwise document this issue and the requirement to use the Pydantic v1 BaseModel. In the meantime this should fix the error:

# causes bug if pydantic 2.x is installed:
# from pydantic import BaseModel

# this works for now
from pydantic.v1 import BaseModel

[dosubot]

🤖

Thank you for bringing this to our attention. You're correct that LangChain version 0.0.267 has some compatibility issues with Pydantic v2.0. This is due to the differences between Pydantic v1 and v2, and the way LangChain handles these differences.

As you've found, a temporary workaround is to import BaseModel from pydantic.v1 instead of pydantic. This is because LangChain is currently designed to be compatible with both Pydantic v1 and v2 to accommodate dependencies and dependents that may be using either version. The code creates namespaces for Pydantic v1 and v2, allowing for unambiguous use of either API.

However, it's important to avoid mixing Pydantic v1 and v2 code. If you're using Pydantic v2's BaseModel and Field to define your args_schema and passing it to a LangChain Tool that's still using Pydantic v1, you'll encounter a ValidationError. Here's the correct way to do it:

from langchain.tools.base import Tool
from pydantic.v1 import BaseModel, Field # <-- Uses v1 namespace

class CalculatorInput(BaseModel):
    question: str = Field()

Tool.from_function( # <-- tool uses v1 namespace
    func=lambda question: 'hello',
    name="Calculator",
    description="useful for when you need to answer questions about math",
    args_schema=CalculatorInput
)

We're aware of this issue and are working on making LangChain compatible with Pydantic v2.0. As of langchain==0.0.267 the pydantic version is uncapped and should largely be cross-compatible with pydantic v1 and v2. There are still some known pydantic v2 failure modes explained in issue #9337, and some potentially unknown failure modes. We encourage users to provide feedback if they are still running into issues.

We appreciate your patience and understanding as we work to resolve this issue. Please let us know if you have any other questions or concerns.

Sources

• Support for Pydantic v2
• libs/experimental/langchain_experimental/pydantic_v1/init.py
• libs/langchain/langchain/pydantic_v1/init.py
• docs/extras/guides/pydantic_compatibility.md

---

This response is meant to be useful and save you time. It is not meant to be a precise solution, but rather a starting point for your own research.

Help me be more useful! Please leave a 👍 if this is helpful and 👎 if it is irrelevant.

If you want to continue the conversation, start your reply with @dosu-bot.

[eyurtsev]

@Markus-sevend thanks for reporting the issue see:

• Pydantic compatibility: No Breaking Changes #9337
• https://github.com/langchain-ai/langchain/blob/master/docs/extras/guides/pydantic_compatibility.md

[dosubot]

Hi, @Markus-sevend! I'm Dosu, and I'm helping the LangChain team manage their backlog. I wanted to let you know that we are marking this issue as stale.

From what I understand, the issue you reported is related to instantiating a StructuredTool instance with an args_schema argument, which raises an exception. It seems that the error is caused by a compatibility issue between LangChain and Pydantic v2.0. However, the LangChain team has debugged the issue and found a temporary workaround. The workaround involves importing BaseModel from pydantic.v1 instead of pydantic. Additionally, the team is actively working on making LangChain fully compatible with Pydantic v2.0.

Now, we would like to know if this issue is still relevant to the latest version of the LangChain repository. If it is, please let us know by commenting on this issue. Otherwise, feel free to close the issue yourself, or it will be automatically closed in 7 days.

Thank you for your understanding and patience. If you have any further questions or concerns, please don't hesitate to reach out.

[hminooei]

For me, installing pydantic 1.10.10 worked: pip install pydantic==1.10.10