Extract duplicated Redis URL parsing into a shared cache_config utility.
Introduce ValkeyCache as a lightweight async key/value cache using
valkey-glide. Wire it into A2A task handling, agent card caching, and
file upload caching.
Part 1/4 of Valkey storage implementation.
fix: async-safe embeddings and resilient drain_writes
Add bytes→float validators on MemoryRecord and ItemState to handle
Valkey returning embeddings as raw bytes. Make embed_texts() safe when
called from an async context by using a thread pool. Improve
drain_writes() with per-save timeouts and error logging instead of
raising on failure.
Part 3/4 of Valkey storage implementation.
feat(valkey): ValkeyStorage vector memory backend
Add ValkeyStorage, a distributed StorageBackend implementation using
Valkey-GLIDE with Valkey Search for vector similarity. Wire it into
Memory as the 'valkey' storage option. Pin scrapegraph-py<2 to fix
unrelated upstream breakage.
Part 4/4 of Valkey storage implementation.
fix: use datetime.utcnow() for last_accessed consistency
MemoryRecord defaults use utcnow() for created_at and last_accessed.
Match that in ValkeyStorage.update_record() to avoid timezone
inconsistency in recency scoring.
feat(valkey): shared cache config + ValkeyCache for A2A and file uploads
Extract duplicated Redis URL parsing into a shared cache_config utility.
Introduce ValkeyCache as a lightweight async key/value cache using
valkey-glide. Wire it into A2A task handling, agent card caching, and
file upload caching.
Part 1/4 of Valkey storage implementation.
fix: handle non-numeric database path in cache URL parsing
Extract _parse_db_from_path() helper that catches ValueError for
paths like /mydb and defaults to 0 with a warning, instead of
crashing.
fix: async-safe embeddings and resilient drain_writes
Add bytes→float validators on MemoryRecord and ItemState to handle
Valkey returning embeddings as raw bytes. Make embed_texts() safe when
called from an async context by using a thread pool. Improve
drain_writes() with per-save timeouts and error logging instead of
raising on failure.
Part 3/4 of Valkey storage implementation.
fix: catch concurrent.futures.TimeoutError for Python 3.10 compat
In Python <3.11, concurrent.futures.TimeoutError is distinct from the
builtin TimeoutError. Catch both so the timeout warning path works
on all supported Python versions.
Enables keyless Azure auth (OIDC Workload Identity Federation, Managed
Identity, Azure CLI, env-configured Service Principal) without any
crewAI-specific configuration. Customers whose deployment environment
already sets the standard azure-identity env vars get keyless auth for
free; the existing API-key path is unchanged.
Linear: FAC-40
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.
