* feat(flow): report flow outcome and human-in-the-loop signals
A flow reported only that it started. FlowFinishedEvent, FlowFailedEvent,
MethodExecutionFailedEvent, MethodExecutionPausedEvent and FlowPausedEvent all
reached the console formatter and stopped there, and FlowInputRequestedEvent,
FlowInputReceivedEvent and ConversationTurnFailedEvent had no listener at all -
so success rate, failure rate and every HITL pause were unmeasurable.
Adds flow:completed, flow:failed, flow:method_failed, flow:paused,
flow:hitl_paused, flow:input_requested, flow:input_received and
flow:conversation_turn_failed as feature-usage spans, which the existing
feature-usage aggregation already reads.
Deliberately does not hold the Flow Execution span open to measure duration:
flow_executions_daily_target counts those spans at start, so a run that never
finishes would disappear from the count entirely. Duration needs its own span.
Counts only - flow names, method names, error text and flow state are never
recorded.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01ASfWmW3RGy4qAQm6s8U9jH
* feat(flow): record how long a flow ran
Adds a Flow Completed span carrying flow_name, duration_ms and outcome,
emitted when a flow finishes or fails. Elapsed time comes from a monotonic
stamp taken at flow start and cleared on use.
Kept separate from the Flow Execution span rather than holding that one open:
it is emitted and closed at start and the daily aggregate counts it, so
holding it would drop every run that is killed or crashes from the execution
count. A killed run now simply has no Flow Completed row, and the count is
unaffected.
Elapsed time is an explicit duration_ms attribute rather than the span's own
duration, which the ingestion pipeline stores as a suffixed string
("0.0000184s") that downstream aggregation parses to zero.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01ASfWmW3RGy4qAQm6s8U9jH
* feat(flow): tag flow origin and report resumed runs
Two gaps found while testing the pause/resume path end to end.
Resumed runs were invisible. There is no resume event: a restored run re-enters
through kickoff(), so it looked identical to a fresh start. flow:resumed is
derived from _is_execution_resuming at flow start, which makes
flow:paused - flow:resumed the abandonment rate.
Flow counts are dominated by CrewAI's own AgentExecutor, which is itself a Flow
and runs once per agent execution - it is the top flow in the warehouse by a
wide margin. Nothing distinguished it from a user's flows except guessing at the
name. Both Flow Execution and Flow Completed now carry origin: "internal" when
the flow class is defined under crewai.*, "user" otherwise. Tagging only the new
span would have left the existing daily count unsplittable.
Both span methods take origin with a default, so their signatures stay
backward compatible.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01ASfWmW3RGy4qAQm6s8U9jH
* fix(flow): scope outcome and resume signals to user flows
Two findings from review, both confirmed against the code.
Outcome features counted CrewAI's own flows. The agent executor, memory
encoding and memory recall are all Flows and all set suppress_flow_events;
they run far more often than anything a user wrote, so flow:completed,
flow:failed and flow:method_failed were mostly bookkeeping. Those three are now
emitted only for flows the caller wrote. Internal outcomes are still recorded
on the Flow Completed span, which carries origin.
flow:resumed counted checkpoint restores. _is_execution_resuming is set both by
from_pending (a human pause) and by a checkpoint restore that never paused for
anyone, so resumes could exceed pauses and the abandonment rate was unusable.
Keyed off _pending_feedback_context instead, which only from_pending sets.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01ASfWmW3RGy4qAQm6s8U9jH
* fix(flow): declare internal flows instead of inferring them
Three findings from review, all confirmed against the code.
Gating on suppress_flow_events was wrong. That flag asks for console quiet and
is a public field, so a caller who set it on their own flow silently lost
flow:completed, flow:failed and flow:method_failed.
Deciding origin from the defining module was also wrong. Flow.from_declaration()
returns a Flow typed in crewai.flow.flow, so a caller's declarative flow was
reported as one of CrewAI's own - the inversion this split exists to prevent.
Both had the same root cause: the discriminator was inferred. Flow now declares
is_crewai_internal, set on the agent executor and the memory encoding/recall
flows, and one helper serves both origin and the outcome gate.
A failed conversational session was reported as completed. Its session closes
with FlowFinishedEvent whatever happened, so a failed turn produced
flow:conversation_turn_failed and flow:completed together. The turn failure is
now recorded on the flow and read back when the session finishes.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01ASfWmW3RGy4qAQm6s8U9jH
* refactor(flow): report flow lifecycle as spans, not feature usage
Flow start, completion, pause and method failure are lifecycle facts, and the
lifecycle is reported as spans everywhere else. Reporting them through
feature usage put them in a table that aggregates on the feature string alone -
it cannot carry origin, duration or outcome, so those signals could never be
split between a user's flows and the ones CrewAI runs for itself.
Adds Flow Paused and Flow Method Failed spans, and a resumed marker on Flow
Execution so a run restored from a pause is not counted as a second fresh
start. Removes the duplicate feature rows for completed, failed, method_failed,
paused and resumed - every one of those facts is now on a span, with more
attached to it than the feature row ever carried.
Feature usage keeps only genuine adoption signals: flow:hitl_paused,
flow:input_requested, flow:input_received and flow:conversation_turn_failed.
Also clears the conversational turn-failure flag on every terminal path. A turn
that failed without deferred finalization ends via FlowFailedEvent, and the flag
left set there marked the next run on that instance as failed.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01ASfWmW3RGy4qAQm6s8U9jH
* test(flow): update the flow_execution_span caller for the resumed argument
Adding the resumed marker changed a signature that tests/utilities/test_events.py
asserts on exactly, and that assertion was not re-run before pushing.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01ASfWmW3RGy4qAQm6s8U9jH
* test(flow): make the checkpoint-restore guard actually guard
The test asserted that flow:resumed was absent from feature usage, but that
signal moved onto the Flow Execution span. The assertion could no longer fail,
so a regression that mis-tagged checkpoint restores as resumes would have gone
unnoticed.
Now asserts the resumed attribute, and waits for the handlers: the manual emit
dispatches asynchronously, so the previous shape also read its result before the
listener had run.
Confirmed it discriminates - keying resumed off _is_execution_resuming again
fails it with [('RestoredFlow', True)] == [('RestoredFlow', False)].
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01ASfWmW3RGy4qAQm6s8U9jH
* fix(telemetry): record the resumed marker as a string
Verified end to end against the live collector and ClickHouse: the pipeline
encodes a boolean attribute as the presence of a vBool key, so false arrives as
the key simply being absent. That is invisible in the schema and easy to read
wrongly - crew_memory is extracted as "the attribute exists" and consequently
reports 1 for 99.8% of crews against a field that defaults to False.
A string leaves nothing to infer. Confirmed in the warehouse: the emitted span
reads resumed = "false".
Adds direct coverage for the attributes each flow span records, including both
resumed values, and resets the Telemetry singleton in the helper so more than
one span method can be exercised per session.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01ASfWmW3RGy4qAQm6s8U9jH
* feat: bump versions to 1.15.15
---------
Co-authored-by: Claude Opus 5 (1M context) <noreply@anthropic.com>
bedrock-agentcore 1.7.0 has GHSA-j6g5-3hh3-pgw8 (CVE-2026-16796, high):
argument-delimiter injection in CodeInterpreter.install_packages(). It fails
the pip-audit vulnerability scan on every PR in the repo.
The patch is 1.18.1, which requires boto3>=1.43.31. The old <1.8.0 cap plus
aiobotocore~=3.5.0 (botocore<1.42.92) made that unsatisfiable, so the AWS
stack moves together:
- bedrock-agentcore >=1.7.0,<1.8.0 -> >=1.18.1,<2.0.0
- boto3 ~=1.42.90 -> ~=1.43.46 (aws + bedrock extras)
- aiobotocore ~=3.5.0 -> ~=3.8.0 (aws + bedrock extras)
aiobotocore 3.8.0 allows botocore <1.43.47 and boto3 1.43.46 pins botocore
1.43.46, so the ranges overlap.
Verified: uv lock resolves, pip-audit reports no vulnerabilities (3 existing
ignores, none new), 48 bedrock tests pass, and both bedrock toolkits import
cleanly. BrowserClient.{start,stop,generate_ws_headers} and
CodeInterpreter.{start,stop,invoke} are unchanged in 1.18.1.
* chore: bump json-repair to 0.60.1 and un-ignore fixed vulns in scan
- json-repair 0.25.3 -> 0.60.1 (fixes GHSA-xf7x-x43h-rpqh)
- pyOpenSSL already at 26.2.0 in lock (covers CVE-2026-27448, CVE-2026-27459)
- remove the corresponding --ignore-vuln flags from vulnerability-scan.yml
* fix: adapt _safe_repair_json to json-repair 0.60 semantics
json-repair >= 0.60 returns an empty string for plain-text input and
wraps brace-enclosed junk in a single-element list instead of the old
""/{} sentinel values. Treat both as unrepairable so the original
tool input is preserved.
* chore: fix CI - bump gitpython/pyasn1, drop stale type ignores
- gitpython 3.1.50 -> 3.1.52 (GHSA-2f96-g7mh-g2hx, GHSA-v396-v7q4-x2qj,
GHSA-956x-8gvw-wg5v; fixed in 3.1.51)
- pyasn1 0.6.3 -> 0.6.4 (GHSA-8ppf-4f7h-5ppj, GHSA-hm4w-wwcw-mr6r)
- json-repair 0.60 ships type stubs; remove now-unused
type: ignore[import-untyped] comments flagged by mypy
### Overview
`BedrockCompletion.acall()` (the async completion path used when a crew is kicked off asynchronously) requires `aiobotocore` to build its async client. The `bedrock` extra, however, only declared `boto3`. Crews configured with an AWS Bedrock model work fine under a synchronous `kickoff()`, since that path only needs `boto3`, but raise `NotImplementedError: Async support for AWS Bedrock requires aiobotocore` as soon as they're kicked off asynchronously, since `aiobotocore` was never installed.
The fix adds `aiobotocore` to the `bedrock` extra, so `crewai[bedrock]` installs both the sync (`boto3`) and async (`aiobotocore`) dependencies the native Bedrock provider needs. The lockfile is regenerated to match. The exception message is also corrected — it previously pointed to a `bedrock-async` extra that never existed in `pyproject.toml`.
### Changes
- `lib/crewai/pyproject.toml`: add `aiobotocore~=3.5.0` to the `bedrock` extra
- `uv.lock`: regenerated to reflect the updated `bedrock` extra
- `lib/crewai/src/crewai/llms/providers/bedrock/completion.py`: fix the install hint in the `NotImplementedError` message to reference the real `bedrock` extra instead of the nonexistent `bedrock-async`
The previous `~=1.34.0` pin kept us on the unmaintained 1.34 line —
last patched as `1.34.1` in June 2025, eight minor releases behind
upstream — and caused `_create_exp_backoff_generator` `ImportError`
crashes in factory deployments where the OpenTelemetry Operator's
injected init container shadows
`opentelemetry.exporter.otlp.proto.common._internal` with >=1.35 while
our `opentelemetry-exporter-otlp-proto-grpc==1.34.1` still imports the
removed private symbol. Pinning to `~=1.42.0` tracks the current
upstream stable line; the resolver now lands on 1.42.1 and our public
OTel trace API usage is unaffected.
* docs: add "One Card per Step" Studio page (AGE-107)
Document the merge of the task and agent nodes into a single step card on
the Studio canvas. Written as evergreen present-tense feature docs with a
dated rollout banner (June 24th) for the pre-launch customer announcement;
the banner is the only time-bound content and is flagged for removal after
ship. Added in edge + v1.14.7 across en, pt-BR, ko, and ar, with nav entries
in docs.json and three canvas/editor/swap screenshots.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
* fix: bump bedrock agentcore dependencies
---------
Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Co-authored-by: alex-clawd <alex@crewai.com>
* feat: update pyproject.toml to specify wheel targets
Added a new section to the pyproject.toml file to include only specific files in the wheel build, enhancing the packaging process. Updated tests to verify the inclusion of these targets.
* feat: add memory save event handling to activity log
Implemented event handlers for MemorySaveStartedEvent, MemorySaveCompletedEvent, and MemorySaveFailedEvent in the crew_run_tui module. This allows the application to log memory save operations, capturing their status and details in the activity log. Added corresponding tests to verify the correct logging behavior for successful and failed memory saves.
* feat: enhance memory save event handling in activity log
Added functionality to suppress nested memory save events and updated the handling of MemorySaveStartedEvent, MemorySaveCompletedEvent, and MemorySaveFailedEvent to improve logging accuracy. Introduced new tests to verify the correct behavior of memory save events, including scenarios for nested events and completion updates for timed-out entries.
* Fix memory save activity log handling
* Normalize alpha package versions
* Update scaffolded crew dependency
* feat: add button to copy setup instructions for CrewAI coding agents
Introduced a button in the documentation that allows users to easily copy setup instructions for CrewAI coding agents. The instructions include installation steps, environment setup, and best practices for using the CrewAI CLI. This enhancement aims to streamline the onboarding process for new users.
* Improve missing CrewAI install guidance
* fix: address pr review feedback
* fix: avoid mismatched memory save rows
* fix: wait for queued memory save events
* fix: avoid matching memory saves on missing ids
* chore: normalize prerelease version to 1.14.8a1
The litellm extra was capped at <1.85, which excludes future
patch lines and reintroduces resolution failures under uv/pip.
Widen to >=1.84.0,<2 so the extra resolves cleanly against
crewai's openai/python-dotenv pins.
Closes OSS-71
* Enhance memory reset functionality and JSON crew handling
- Added `reset_all` method to the `Memory` class to reset the entire memory store, ignoring `root_scope`.
- Updated the `Crew` class to utilize `reset_all` when resetting memory.
- Enhanced the `_reset_flow_memory` function to check for `Memory` instances and call `reset_all` accordingly.
- Introduced helper functions to load JSON crew configurations and handle project declarations, improving the reset command's flexibility.
- Added tests to validate the new JSON crew memory reset behavior and ensure proper handling of declared flow projects.
* Fix memory reset review issues
* Bump litellm for security advisory
* fix: resolve pip-audit CVEs for aiohttp, docling, docling-core, pip
- aiohttp 3.13.4 → 3.14.0: fixes GHSA-jg22-mg44-37j8, GHSA-hg6j-4rv6-33pg
- docling 2.84.0 → 2.97.0: fixes GHSA-cjqg-rq2h-2fvj, GHSA-pj2v-ggqh-cmq2,
GHSA-r3xg-rg9j-67fv, GHSA-q29v-xc37-wh5m
- docling-core 2.74.0 → 2.79.0: fixes GHSA-j5xp-7m2f-49jv, GHSA-jmmv-h3mp-59v8
- pip 26.1.1 → 26.1.2: fixes PYSEC-2026-196
docling-core 2.74.1+ requires pydantic-settings>=2.14.0, so the crewai pin
is loosened from ~=2.10.1 to >=2.10.1,<3. pydantic-settings resolves to
2.14.1 in the lock.
* fix: correct aiohttp CVE floor to 3.14.0 (not 3.13.5)
* test: shim AsyncStreamReaderMixin for vcrpy under aiohttp 3.14.0
aiohttp 3.14.0 removed aiohttp.streams.AsyncStreamReaderMixin (folded into
StreamReader). vcrpy's aiohttp stub still subclasses it, so vcr's patch
machinery raised AttributeError at test collection. Restore an equivalent
mixin in conftest before vcr is imported.
* test: rebuild vcrpy MockClientResponse init for aiohttp 3.14.0
aiohttp 3.14.0 added a required stream_writer kwarg to ClientResponse.__init__
and reads stream_writer.output_size when writer is None. vcrpy's
MockClientResponse doesn't pass it, raising TypeError at cassette playback.
Rebuild the super().__init__ call from the live signature (defaulting required
keyword-only args to None, with a stream_writer stub exposing output_size) so
it survives future aiohttp signature additions too.
* test: avoid deprecated get_event_loop in vcrpy aiohttp shim
asyncio.get_event_loop() emits a DeprecationWarning (and can RuntimeError)
when no current loop is set on Python 3.12+. Prefer get_running_loop() (the
real cassette-playback path always has one) and fall back to a single cached
loop in sync contexts, since the mock only stores the loop and calls
get_debug().
* fix: pull docling-core[chunking] so HierarchicalChunker imports
docling 2.97 split into docling-slim, moving the chunker's code-chunking
deps (tree-sitter, semchunk, language grammars) behind docling-core's
[chunking] extra. crewai's knowledge source imports HierarchicalChunker,
whose package __init__ eagerly imports those submodules -> ModuleNotFoundError
('tree_sitter') without the extra. Request docling-core[chunking]; carry the
extra in override-dependencies too, since overrides replace the whole
requirement and would otherwise strip it.
