Middleware Classes
Text Editor Tools
- StateClaudeTextEditorToolMiddleware: In-memory text editor using agent
state
- FilesystemClaudeTextEditorToolMiddleware: Text editor operating on
real filesystem
Implementing Claude's text editor tools
https://docs.claude.com/en/docs/agents-and-tools/tool-use/text-editor-tool
Operations: view, create, str_replace, insert
Memory Tools
- StateClaudeMemoryToolMiddleware: Memory persistence in agent state
- FilesystemClaudeMemoryToolMiddleware: Memory persistence on filesystem
Implementing Claude's memory tools
https://docs.claude.com/en/docs/agents-and-tools/tool-use/memory-tool
Operations: Same as text editor plus delete and rename
File Search Tools
- StateFileSearchMiddleware: Search state-based files
Provides Glob and Grep tools with same schema as used by Claude Code
(but compatible with any model)
- Glob: Pattern matching (e.g., **/*.py, src/**/*.ts), sorted by
modification time
- Grep: Regex content search with output modes (files_with_matches,
content, count)
Usage
``` from langchain.agents import create_agent from langchain.agents.middleware import (
StateTextEditorToolMiddleware, StateFileSearchMiddleware, )
agent = create_agent( model=model, tools=[], middleware=[
StateTextEditorToolMiddleware(), StateFileSearchMiddleware(), ], ) ```
---------
Co-authored-by: Nuno Campos <nuno@boringbits.io>
Adds special private helper to allow direct injection of `ToolRuntime`
in tools, plus adding guards for generic annotations w/ `get_origin`.
Went w/ the private helper so that we didn't change behavior for other
injected types.
To make migration easier, things are more backwards compat
Very minimal footprint here
Will need to upgrade migration guide and other docs w/ this change
Adds `ToolRetryMiddleware` to automatically retry failed tool calls with
configurable exponential backoff, exception filtering, and error
handling.
## Example
```python
from langchain.agents import create_agent
from langchain.agents.middleware import ToolRetryMiddleware
from langchain_openai import ChatOpenAI
# Retry up to 3 times with exponential backoff
retry = ToolRetryMiddleware(
max_retries=3,
initial_delay=1.0,
backoff_factor=2.0,
)
agent = create_agent(
model=ChatOpenAI(model="gpt-4"),
tools=[search_tool, database_tool],
middleware=[retry],
)
# Tool failures are automatically retried
result = agent.invoke({"messages": [{"role": "user", "content": "Search for AI news"}]})
```
For advanced usage with specific exception handling:
```python
from requests.exceptions import Timeout, HTTPError
def should_retry(exc: Exception) -> bool:
# Only retry on 5xx errors or timeouts
if isinstance(exc, HTTPError):
return 500 <= exc.response.status_code < 600
return isinstance(exc, Timeout)
retry = ToolRetryMiddleware(
max_retries=4,
retry_on=should_retry,
tools=["search_database"], # Only apply to specific tools
)
```
Largely:
- Remove explicit `"Default is x"` since new refs show default inferred
from sig
- Inline code (useful for eventual parsing)
- Fix code block rendering (indentations)
The one risk point that I can see here is that model + tool call
counting now occurs in the `after_model` hook which introduces order
dependency (what if you have HITL execute before this hook and we jump
early to `model`, for example).
This is something users can work around at the moment and we can
document. We could also introduce a priority concept to middleware.
