The OpenAI-format tool schema sets strict: true but this was dropped
during conversion to Anthropic/Bedrock formats, so neither provider
used constrained decoding. Without it, the model can return string
"None" instead of JSON null for nullable fields, causing Pydantic
validation failures.
- Pass RuntimeState through the event bus and enable entity auto-registration
- Introduce checkpointing API:
- .checkpoint(), .from_checkpoint(), and async checkpoint support
- Provider-based storage with BaseProvider and JsonProvider
- Mid-task resume and kickoff() integration
- Add EventRecord tracking and full event serialization with subtype preservation
- Enable checkpoint fidelity via llm_type and executor_type discriminators
- Refactor executor architecture:
- Convert executors, tools, prompts, and TokenProcess to BaseModel
- Introduce proper base classes with typed fields (CrewAgentExecutorMixin, BaseAgentExecutor)
- Add generic from_checkpoint with full LLM serialization
- Support executor back-references and resume-safe initialization
- Refactor runtime state system:
- Move RuntimeState into state/ module with async checkpoint support
- Add entity serialization improvements and JSON-safe round-tripping
- Implement event scope tracking and replay for accurate resume behavior
- Improve tool and schema handling:
- Make BaseTool fully serializable with JSON round-trip support
- Serialize args_schema via JSON schema and dynamically reconstruct models
- Add automatic subclass restoration via tool_type discriminator
- Enhance Flow checkpointing:
- Support restoring execution state and subclass-aware deserialization
- Performance improvements:
- Cache handler signature inspection
- Optimize event emission and metadata preparation
- General cleanup:
- Remove dead checkpoint payload structures
- Simplify entity registration and serialization logic
* fix: bump litellm to >=1.83.0 to address CVE-2026-35030
Bump litellm from <=1.82.6 to >=1.83.0 to fix JWT auth bypass via
OIDC cache key collision (CVE-2026-35030). Also widen devtools openai
pin from ~=1.83.0 to >=1.83.0,<3 to resolve the version conflict
(litellm 1.83.0 requires openai>=2.8.0).
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
* fix: resolve mypy errors from litellm bump
- Remove unused type: ignore[import-untyped] on instructor import
- Remove all unused type: ignore[union-attr] comments (litellm types fixed)
- Add hasattr guard for tool_call.function — new litellm adds
ChatCompletionMessageCustomToolCall to the union which lacks .function
* fix: tighten litellm pin to ~=1.83.0 (patch-only bumps)
>=1.83.0,<2 is too wide — litellm has had breaking changes between
minors. ~=1.83.0 means >=1.83.0,<1.84.0 — gets CVE patches but won't
pull in breaking minor releases.
* ci: bump uv from 0.8.4 to 0.11.3
* fix: resolve mypy errors in openai completion from 2.x type changes
Use isinstance checks with concrete openai response types instead of
string comparisons for proper type narrowing. Update code interpreter
handling for outputs/OutputImage API changes in openai 2.x.
* fix: pre-cache tiktoken encoding before VCR intercepts requests
---------
Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Co-authored-by: Alex <alex@crewai.com>
Co-authored-by: Greyson LaLonde <greyson@crewai.com>
* chore: update uv.lock with new dependency groups and versioning adjustments
- Added a new revision number and updated resolution markers for Python version compatibility.
- Introduced a 'dev' dependency group with specific versions for various development tools.
- Updated sdist and wheels entries to include upload timestamps for better tracking.
- Adjusted numpy dependencies to specify versions based on Python version markers.
* feat: bump versions to 1.14.0a1
lancedb 0.30.1 dropped the win_amd64 wheel, breaking installation on
Windows. Pin to <0.30.1 so uv resolves to a version that still ships
Windows binaries.
The litellm optional dependency had a wide upper bound (<3) that allowed
any future litellm release to be installed automatically. This means
breaking changes in new litellm versions could affect customers immediately.
Pins the upper bound to <=1.82.6 (current latest known-good version).
When newer litellm versions are tested and validated, bump this bound
explicitly.
introduce the agent skills standard for packaging reusable instructions that agents can discover and activate at runtime.
- skills defined via SKILL.md with yaml frontmatter and markdown body
- three-level progressive disclosure: metadata, instructions, resources
- filesystem discovery with directory name validation
- skill lifecycle events (discovery, loaded, activated, failed)
- crew-level skills resolved once and shared across agents
- skill context injected into both task execution and standalone kickoff
* refactor: update step callback methods to support asynchronous invocation
- Replaced synchronous step callback invocations with asynchronous counterparts in the CrewAgentExecutor class.
- Introduced a new async method _ainvoke_step_callback to handle step callbacks in an async context, improving responsiveness and performance in asynchronous workflows.
* chore: bump version to 1.10.1b1 across multiple files
- Updated version strings from 1.10.1b to 1.10.1b1 in various project files including pyproject.toml and __init__.py files.
- Adjusted dependency specifications to reflect the new version in relevant templates and modules.
