Co-authored-by: Guillaume <guillaume@stackone.com>

* feat(langgraph): add integration helpers, aligned example, and docs

- Add stackone_ai/integrations/langgraph with:

  - to_tool_node, to_tool_executor

  - bind_model_with_tools, create_react_agent

- Add examples/langgraph_tool_node.py matching README snippet (English comments)

- Update README with a minimal LangGraph agent loop (tools_condition) and prereqs

- examples now document installing langgraph and langchain-openai explicitly

* fix: update langgraph integration to use ToolNode instead of deprecated ToolExecutor

- Replace ToolExecutor import with ToolNode in TYPE_CHECKING block
- Update to_tool_executor function to return ToolNode instead of deprecated ToolExecutor
- Add mypy override to ignore missing imports for langgraph modules
- Fix linting issue with blank line whitespace in docstring

* fix: mcp mypy error

* fix: resolve mypy type errors for langgraph ToolNode fallback

- Use class-based fallback instead of assignment for ToolNode in TYPE_CHECKING block
- Add type: ignore for no-redef to handle the intentional redefinition
- This fixes compatibility with Python 3.9 mypy type checking

* fix: update CI to conditionally exclude server.py for Python 3.9

- Run mypy on server.py only for Python 3.10+ where MCP dependencies are available
- Exclude server.py for Python 3.9 to avoid MCP import errors
- This ensures type checking works correctly across all supported Python versions

* fix: configure mypy to handle MCP library syntax errors

- Add comprehensive mypy overrides for mcp module
- Configure mypy to install types automatically in CI
- Exclude .venv directory from type checking
- This resolves pattern matching syntax errors from mcp library dependencies

* fix: pin python 3.10 version

- Remove unused type: ignore comment for try block
- Add type: ignore for MCP decorator functions to handle untyped
decorators
- Set mypy python_version to 3.10 to properly handle pattern matching
syntax
- All mypy checks now pass successfully

* feat: add feedback collection tool and implicit feedback system

Add meta_collect_tool_feedback tool for collecting user feedback about
StackOne tool performance. The tool is automatically included in the
toolset and can be invoked by AI agents after user consent.

Features:
- Feedback collection tool with Pydantic validation
- Automatic whitespace trimming and input cleaning
- Support for custom base URLs
- Integration with StackOneToolSet
- OpenAI and LangChain format support

Also includes implicit feedback system for automatic behavioral feedback
to LangSmith:
- Behavior analyzer for detecting quick refinements
- Session tracking for tool call history
- LangSmith client integration
- Configurable via environment variables

Breaking changes:
- Updated StackOneTool.execute() signature to include options parameter
- Updated meta tools execute methods to support options parameter

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>

* changing tests

* Fix linting errors: line length, imports, and trailing whitespace

* feat: add minimal feedback collection tool

- Add feedback tool that sends data to API endpoint
- No LangSmith integration - just API calls
- Simple validation with Pydantic
- Auto-included in StackOneToolSet
- 6 focused tests covering validation, execution, and integration

* cleanup: remove implicit feedback files - focus on feedback tool only

* fix: remove implicit feedback imports and fix call method

- Remove implicit feedback imports from __init__.py
- Fix base class call method to not pass options parameter
- All 6 feedback tests now passing

* fix: remove unused typing.Any import

* fix: resolve mypy errors

- Remove implicit feedback imports and unreachable code
- Fix execute method signature to match base class
- All mypy checks now pass

* fix: remove unused variables after implicit feedback cleanup

- Remove unused start_time, call_params, end_time variables
- All linting checks now pass (Ruff + Mypy)

* feat: support multiple account IDs in feedback tool

- Allow account_id to be string or list of strings
- Send same feedback to each account individually
- Return combined results with success/failure counts
- Add comprehensive tests for validation and execution
- All 9 tests passing, linting clean

* refactor: format tool.execute calls for improved readability

- Adjust formatting of tool.execute calls in test_feedback.py for consistency
- Enhance code clarity by aligning dictionary entries
- All tests remain passing

* refactor: improve feedback tests - remove redundancy

- Split large validation test into focused, single-purpose tests
- Consolidate execution tests to avoid duplication
- Combine multiple account success/error scenarios into one test
- Remove redundant integration test class
- All 10 tests still passing, better organization

* improving test suite

---------

Co-authored-by: Claude <noreply@anthropic.com>

Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>