The LLM shouldn't be seeing parameters it cannot control in the
ToolMessage error it gets when it invokes a tool with incorrect args.
This fixes the behavior within langchain to address immediate issue.
We may want to change the behavior in langchain_core as well to prevent
validation of injected arguments. But this would be done in a separate
change
added some noqas, this is a quick patch to support a bug uncovered in
the quickstart, will resolve fully depending on where we centralize
ToolNode stuff.
**Description:** Added a beginner-friendly tip to the README to help
first-time contributors find a starting point. This is a documentation
improvement aimed at lowering the barrier for newcomers to participate
in open source.
**Issue:** No related issue
**Dependencies:** None
---
## Note to maintainers
I'm new to open source and this is my first PR! If there's anything that
needs improvement, please guide me and I'll be happy to learn and make
changes. Thank you for your patience! 😊
## What does this PR do?
- Added a noticeable beginner tip box after the badges section in README
- Provided specific guidance (Good First Issues link)
- Encourages newcomers to start with documentation fixes
## Why is this change needed?
- Makes it easier for new contributors to get started
- Provides clear direction and reduces confusion
- Creates a more welcoming open source community environment
---------
Co-authored-by: Mason Daugherty <mason@langchain.dev>
* The dependency is not used.
* It takes a long time to build in Python 3.14 as there are no prebuilt
binaries yet. This slows down CI a lot.
Co-authored-by: Mason Daugherty <mason@langchain.dev>
the fact that this was broken showcases that we need significantly
better test coverage, this is literally the most minimalistic usage of
this middleware there could be 😿
will document these two gotchas better for custom middleware
```py
from langchain.agents.middleware.shell_tool import ShellToolMiddleware
from langchain.agents import create_agent
agent = create_agent(model="openai:gpt-4",middleware = [ShellToolMiddleware()])
agent.invoke({"messages":[{"role": "user", "content": "hi"}]})
```
