Ibm db2 review fix - #1
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… and config validation
…ed at the end of every _run, so self.connection is always None when _connect is called next. The 'if not self.connection' guard was dead code.
…ng digits, multiple periods and dot-only strings (e.g. '.....' passed).
…e_embedding as keeping openai as a lazy optional import since it is not always required.
…ation as OpenAI(api_key=...) was recreated on every _generate_embedding call. Extract into _get_openai_client() which lazily initialises and caches self._openai_client on first use, reusing it for all subsequent queries.
…viour. 'OpenAI embedding fallback' implied it was optional. Replaced with 'Uses a custom embedding function if supplied, otherwise OpenAI embeddings.'
… and config validation
…6472) * fix: upgrade onnx to 1.22.0 and ignore unfixed nltk advisory in pip-audit * fix: sync pip-audit ignore list in pre-commit config with the workflow
…rd changes (#6471) * docs: rename ACP rules to policies across edge and v1.15.1 locales with redirects * docs: point ACP policies pages at the new policy screenshots * docs: address review — revert frozen v1.15.1 edits and fix redirect ordering * docs: prefix edge policies cross-links so they resolve until the next version cut * docs: move policies redirects above all wildcard redirects
…e state schema (#6466)
* fix(cli): unify `crewai run` flow input resolution; prompt from state schema
`crewai run` resolved the configured [tool.crewai] flow, but `--inputs` was
hard-gated behind `--definition` and routed through a separate branch — the two
ways of pointing at the same flow didn't share resolution, and required inputs
were never detected, prompted, or validated (a missing field only blew up at
runtime).
Now inputs and definition come from one place:
- Remove the "--inputs requires --definition" gate (cli.py, run_crew.py,
run_declarative_flow.py). `--inputs` alone resolves the configured flow,
exactly like a bare `crewai run`; `--definition` is purely an override. The
project-env re-exec forwards `--inputs` instead of rejecting it.
- Read the flow's state schema from the runtime Flow instance
(`type(flow.state).model_json_schema()`), which is reliable for both inline
`json_schema` and ref-imported `pydantic` state (the static definition's
json_schema is None for the common ref case).
- Plain `crewai run` detects required state fields (minus those satisfied by
state defaults) and prompts for them interactively, showing each field's
description; skipped in non-interactive / CREWAI_DMN mode.
- Validate against the schema before kickoff: pointed
"Missing required input 'x' — <description>" errors, and warn on unknown keys
with a did-you-mean suggestion (catches typos like `prospect_emai`).
`--inputs` on a non-flow project now errors clearly ("only supported for
declarative flows") instead of the old confusing gate.
Tests: schema-driven prompt/validate/override paths, unknown-key warning,
defaults-satisfy-required, type validation, and re-exec input forwarding.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01RBYGqJHC2TMC6fonFziuuh
* fix(cli): forward reserved `id` input to flow kickoff; ruff format
- Cursor: the schema filter treated an `id` key in --inputs as unknown and
dropped it, regressing kickoff's persistence-restore support (inputs["id"]).
Let `id` pass through untouched (test: reserved_id_input_is_forwarded).
- Apply ruff format to run_declarative_flow.py (fixes the lint-run
`ruff format --check` step).
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01RBYGqJHC2TMC6fonFziuuh
* fix(cli): don't block persistence-restore resume on schema validation
Cursor (High): `crewai run --inputs '{"id":"…"}'` is a persistence resume —
kickoff hydrates full state from storage, so schema-required fields may come
from the restored state rather than --inputs. The new required-field
prompt/validation was erroring/prompting before kickoff, breaking resume. When
`id` is present in --inputs, forward the inputs unchanged and skip the
prompt/validation. Test: test_id_only_input_skips_required_validation.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01RBYGqJHC2TMC6fonFziuuh
* fix(cli): load project .env in the declarative-flow runner
The declarative-flow path never loaded .env — flow projects (type = "flow")
missed API keys/config that crew projects pick up. The JSON-crew path loads
Path.cwd()/.env with override=True (run_crew._run_json_crew); mirror that at
the top of run_declarative_flow() so flow projects behave the same regardless
of where crewai is installed. Test: run_declarative_flow_loads_project_env.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01RBYGqJHC2TMC6fonFziuuh
* feat(cli): unify runtime-input prompting across declarative flows and crews
Declarative (JSON) crews now resolve inputs the same way declarative flows
do, via a shared crewai_cli.input_prompt module (prompt_for_inputs,
parse_inputs_json, closest_name, is_interactive):
- accept --inputs (previously rejected for crews), forwarded to the crew
subprocess via CREWAI_JSON_CREW_INPUTS and validated before spinning up uv
- layer --inputs over the crew's declared `inputs` defaults
- prompt for missing {placeholder}s with the same UX as flows, and error
cleanly with a pointed per-name message when non-interactive
- warn on unknown keys with a "did you mean" suggestion
Unlike flows — whose state schema is authoritative, so unknown keys are
dropped — the crew placeholder scan is heuristic (agent/task text fields
only), so unrecognized keys are warned about but kept, to avoid discarding a
value a field the scan doesn't cover may rely on.
--inputs remains rejected for classic (Python/YAML) crews, which take their
inputs from main.py. run_declarative_flow's private input helpers move to the
shared module with no behavior change.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01RBYGqJHC2TMC6fonFziuuh
* test(crewai): update mirrored CLI test after run_crew input refactor
lib/crewai/tests/cli/test_run_crew.py imports crewai_cli internals and is
collected by the lib/crewai test job (Run Tests). It still imported
_prompt_for_missing_inputs, which was replaced by _resolve_crew_inputs, so
the module failed to import — erroring pytest at collection and cancelling
the rest of the matrix via fail-fast.
Point it at _resolve_crew_inputs and patch the prompt in the shared
crewai_cli.input_prompt module where prompting now lives.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01RBYGqJHC2TMC6fonFziuuh
* fix(cli): filter unknown --inputs keys even on flow persistence restore
Review follow-up: the `id` (persistence-restore) branch of
_resolve_flow_inputs returned the raw payload, so typo keys passed alongside
`id` skipped the unknown-key warning/drop and reached kickoff — which can
fail strict (extra="forbid") flow state models. The restore path now still
warns on and drops unknown keys (keeping `id` and known state fields); it
only skips the required-field prompt and pre-kickoff validation, which
persistence hydrates. Regression test: test_id_restore_still_drops_unknown_keys.
Also drop the duplicate module import in test_input_prompt.py (both `import`
and `from ... import` of crewai_cli.input_prompt) flagged by the code-quality
bot; monkeypatching now uses the string target form.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01RBYGqJHC2TMC6fonFziuuh
---------
Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
… Ollama (#6468) Follow-ups to #6462's caching: 1. Key the catalog cache by the exact API key (via a short, non-reversible sha256 digest — never the key itself), not just key-present vs absent. Switching to a different key for the same provider now misses the previous account's entry and refetches, instead of showing the old account's models. 2. Never cache local providers (Ollama). /api/tags is fast and installed models change out-of-band, so caching could keep offering a model the user just deleted until the entry expired. _is_cacheable() gates both cache read and write; the picker now re-probes every call and reflects what's installed. 3. Shorten the dynamic catalog TTL from 6h to 5m — a stale list (new/removed models, account changes) is worse than a ~1s refetch, and the cache only needs to spare repeated fetches within a wizard session. Tests: distinct-key cache entries, digest never stores the raw key, Ollama not cached (reflects deletions / never written), and dynamic TTL expiry. Claude-Session: https://claude.ai/code/session_01RBYGqJHC2TMC6fonFziuuh Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
* fix: drain memory writes before kickoff and flow completion events Background memory saves from the final task could still be in flight when `CrewKickoffCompletedEvent`/`FlowFinishedEvent` fired, so telemetry listeners tore down before `MemorySaveCompletedEvent` arrived and the save span surfaced as "Span orphaned" errors in traces despite the record persisting. `Crew` now drains all pending saves — including per-agent `agent.memory` pools, which the old `finally`-only drain missed entirely — before emitting the completion event, with the same ordering applied to both `FlowFinishedEvent` emit paths in the flow runtime. * fix: address review findings on the memory drain paths Bugbot and CodeRabbit flagged gaps in the drain coverage: the hierarchical `manager_agent` memory pool was never drained, `Crew.akickoff` lacked the exception-path safety net that sync `kickoff` has, and `finalize_session_traces` emitted the deferred session-end `FlowFinishedEvent` without draining first. Also offloads the pre-emit drains in the flow runtime to `asyncio.to_thread` so the blocking wait doesn't stall other coroutines sharing the event loop. * fix: flush event bus after memory drain in flow completion paths Bugbot flagged that flow paths went straight from the memory drain to `FlowFinishedEvent`, while crew kickoff flushes the bus in between. Save completion events emitted during the drain could still have pending async handlers when flow-finished triggered trace teardown. Adds a `crewai_event_bus.flush()` after the drain at both flow runtime emit sites and in `finalize_session_traces`, mirroring `Crew._create_crew_output`.
* Support legacy OpenAI base URL env var * Add custom OpenAI-compatible endpoint support * Refactor OpenAI completion module test to restore original module state - Added logic to save and restore the original OpenAI completion module during the test to prevent issues with class re-imports affecting subsequent tests. - Ensured that the test checks for the presence of the module and its attributes only after the module is properly reloaded. - Improved test reliability by avoiding potential failures due to module state changes across tests. * addressing comments
…ck) (#6484) * feat(cli): run declarative flows on the TUI with a headless terminal fallback Declarative flows now run on the CrewRunApp TUI when interactive, matching declarative crews and conversational flows. Headless contexts — CREWAI_DMN (deploy), piped output, CI, any non-TTY — fall back to the direct-terminal kickoff, gated by is_interactive() (folds in the CREWAI_DMN check and requires a real TTY). The TUI shows per-method progress: a new STEPS panel driven by flow method events (FlowStarted / MethodExecutionStarted/Finished/Failed), each labeled with its declarative call type (crew/agent/expression/…) read from the flow definition. Crews/agents inside a method keep streaming in the main panel via the existing crew/task/LLM handlers. - crew_run_tui.py: _run_flow_worker (flow.kickoff in a thread worker; reuses _on_crew_done/_on_crew_failed + _stringify_output), _is_flow_run gate so crew rendering is byte-identical, flow-event subscriptions building _flow_steps, and the STEPS sidebar + flow-aware header. - run_declarative_flow.py: is_interactive() branch → _run_declarative_flow_tui (EventListener, method-type map from flow._definition, crew-parity exit codes and deploy chaining) or the existing terminal path. Deviation from the approved plan: gate on is_interactive() rather than is_dmn_mode_enabled() alone, so non-TTY runs (CI/pipes/CliRunner) never launch a TUI — this also keeps existing headless flow tests green. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01RBYGqJHC2TMC6fonFziuuh * fix(cli): force flow events on for the TUI so STEPS renders under suppress_flow_events Review follow-up: the STEPS panel and header are driven by flow method events (FlowStarted / MethodExecution*), but the declarative runtime skips emitting those when the flow declared config.suppress_flow_events. Interactive TUI runs would then keep STEPS on "waiting…" and the header on "Starting flow…" while nested crews still execute. _run_declarative_flow_tui now forces flow.suppress_flow_events = False for the interactive run (mirroring how the conversational path mutates the flow for the TUI). The headless/terminal path never reaches this and keeps the flow's declared setting. Regression test: test_run_declarative_flow_tui_enables_flow_events. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01RBYGqJHC2TMC6fonFziuuh * fix(cli): clear flow header's current method when a method ends Review follow-up: the flow header keys off _current_method, which was set on MethodExecutionStarted but never cleared on Finished/Failed. Between steps (or after a failed method before kickoff exits) the header kept spinning the old method name while the STEPS sidebar already showed it done/failed. _clear_current_method now drops the header's active method when it ends, falling back to another still-active step (methods can overlap) or none. The header's idle fallback shows "Working…" once a step has run and "Starting flow…" only before the first method. Tests: test_current_method_clears_and_falls_back_across_overlap, plus a _current_method assertion in test_flow_method_events_build_steps. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01RBYGqJHC2TMC6fonFziuuh * fix: suppress flow console panels in TUI mode; clear header agent on method change Two review follow-ups: 1) Method panels break Textual TUI (Cursor): forcing suppress_flow_events off so the STEPS panel receives events also un-gated the EventListener's Rich flow/method panels (ConsoleFormatter.print_panel prints is_flow=True panels regardless of verbose), which interleave with Textual and corrupt the TUI. print_panel now skips is_flow panels when is_tui_mode() is set (the same context the TUI worker already establishes and the tracing listeners already honor). Non-TUI/headless flow runs are unaffected. Test: test_console_formatter_tui_mode. 2) Flow header showed a stale agent (CodeRabbit): _current_agent persisted across methods. It's now cleared when a method starts and when the active method changes, so the header never shows the previous method's agent until a new agent event arrives. Test: test_flow_method_transitions_clear_current_agent. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01RBYGqJHC2TMC6fonFziuuh * fix(cli): keep flow name over nested crews; show paused flow methods Two review follow-ups on the flow TUI: 1) Crew kickoff renamed the flow (Cursor): CrewKickoffStartedEvent overwrote _crew_name / the app title with a nested `call: crew` step's crew name, so the post-run summary could be labeled with a child crew. The rename is now gated on `not _is_flow_run`, preserving the flow's name; crew runs still adopt the crew name. Tests: test_crew_kickoff_does_not_rename_flow_run, test_crew_kickoff_renames_in_crew_mode. 2) Paused methods showed active (Cursor): the TUI didn't handle MethodExecutionPausedEvent, so a @human_feedback pause left the STEPS spinner running (flow status panels are suppressed in TUI mode). It now marks the step "paused" (⏸, teal) and the header shows "waiting for feedback" instead of a spinner. Test: test_method_paused_marks_step_paused. Note: interactively *providing* human feedback from the flow TUI is a separate follow-up; this only makes the pause visible instead of a silent stuck spinner. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01RBYGqJHC2TMC6fonFziuuh * fix(cli): run human-feedback declarative flows on the terminal, not the TUI Two review follow-ups, both rooted in @human_feedback methods: - Paused flow marked complete (Cursor): async human feedback makes kickoff RETURN a HumanFeedbackPending marker (not raise), which _run_flow_worker would stringify and report as a successful completion with exit 0. - Sync feedback breaks TUI (Cursor): default (sync) @human_feedback collects input via the flow runtime's Rich console.print + blocking input(), which interleaves with Textual and leaves the user unable to review output or submit feedback. run_declarative_flow now routes any flow whose declarative definition declares human feedback (_flow_uses_human_feedback) to the terminal path, where blocking input and Rich prompts work natively — regardless of interactivity. Non-feedback flows still get the TUI. Tests: test_flow_uses_human_feedback_detection, test_human_feedback_flow_uses_terminal_even_when_interactive. Fully interactive human feedback inside the TUI remains a separate follow-up. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01RBYGqJHC2TMC6fonFziuuh * refactor(cli): address review — Flow typing, debug logging, flow-vs-crew naming Review follow-ups from @lucasgomide: - Type flow helpers as Flow[Any] (via TYPE_CHECKING import) instead of Any and drop the defensive getattr chains — _definition is a typed PrivateAttr and name/suppress_flow_events are typed fields, so attribute access is safe. - Replace the silent `except Exception: pass` blocks with logger.debug(..., exc_info=True) so unexpected failures are diagnosable in the field (_flow_method_types, _flow_uses_human_feedback, suppress_flow_events toggle). - Flow-vs-crew naming: the flow worker now uses group="flow" (was the misleading "crew"), and the shared completion/failure handlers report the run with an entity-aware noun ("flow" vs "crew") via _run_noun. Deferred (separate PR): the os._exit(130) hard-kill on user quit is kept as-is to match the existing crew convention (run_crew._run_json_crew). Tests: test_flow_done_uses_flow_wording_for_unfinished_tool; existing crew wording tests unchanged. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01RBYGqJHC2TMC6fonFziuuh --------- Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
…turns falsy (#6505) In conversational flows, a falsy return from an overridden route_turn() fell back to the sticky state.last_intent from a previous turn, silently re-running the prior turn's handler for an unhandled input. The fallback exists for the legacy default_intents path, where receive_user_message() classifies the intent fresh each turn. Track that per-turn classification in _turn_classified_intent (cleared on every turn reset) and route on it instead, so a falsy route_turn() now falls through to the built-in answer_from_history/converse defaults and never reuses stale routing state. Fixes EPD-176. Co-authored-by: Claude Fable 5 <noreply@anthropic.com> Co-authored-by: Lorenze Jay <63378463+lorenzejay@users.noreply.github.com>
* fix(agent): report per-call usage metrics on kickoff results Agent.kickoff() populated result.usage_metrics from the LLM instance's lifetime token accumulator, so counts grew across calls and pooled across agents sharing one LLM object — a second agent's first turn appeared to cost the whole preceding session. Snapshot the accumulator when a kickoff starts and report the delta on the result (guardrail retries included), via the new UsageMetrics.delta_since(). The LLM instance's cumulative counters are untouched: get_token_usage_summary() keeps lifetime totals for crew-level aggregation, and its docstring now states that scope explicitly. Applies to both Agent and the deprecated LiteAgent, sync and async paths. Fixes EPD-177. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> * refactor(agent): drop lite_agent.py diff, add guardrail-retry usage test Per review: LiteAgent's kickoff path is no longer used, so the per-call usage snapshot only needs to live in agent/core.py — revert the lite_agent.py changes entirely. This also removes the duplicated _current_usage_summary helper and the instance-attr baseline CodeRabbit flagged. Add the requested guardrail-retry regression test: a guardrail that rejects the first attempt and accepts the second must yield usage_metrics covering both attempts (2x a single-attempt kickoff). Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> --------- Co-authored-by: Claude Fable 5 <noreply@anthropic.com>
…sults (#6507) Agent.kickoff() returned LiteAgentOutput with a plain dict at .usage_metrics and no token_usage attribute, while Crew.kickoff() returned CrewOutput with a UsageMetrics object at .token_usage and no usage_metrics attribute — so a usage accessor written for one path raised AttributeError on the other, and every consumer had to duck-type both shapes. Give both result types both surfaces, each name with one consistent shape everywhere: .token_usage is a UsageMetrics object and .usage_metrics is a plain dict, on both LiteAgentOutput and CrewOutput. Added as read-only properties, so existing fields, serialization, and constructors are unchanged. Fixes EPD-178. Co-authored-by: Claude Fable 5 <noreply@anthropic.com>
…ion (#6508)
* fix(tools): stop rewriting the authored tool description at construction
BaseTool.model_post_init silently replaced the public description field
with the LLM-facing composite ("Tool Name: ...\nTool Arguments: ...\n
Tool Description: <authored>"), breaking equality assertions on authored
text and hiding the extra prompt tokens from token-careful authors.
The authored description now survives construction as written. The
composite is composed on demand via a new formatted_description property
on BaseTool and CrewStructuredTool (shared format_description_for_llm
helper), and every prompt path that relied on the baked-in composite —
render_text_description_and_args, ToolUsage._render, and tool-usage
error messages — now renders through it, so the text the LLM sees is
unchanged.
The helper strips any pre-existing composite block before composing, so
tools deserialized from old checkpoints and adapters that still bake the
composite into the field (e.g. the crewai-tools MCP adapter) don't get
double-wrapped. BaseTool._generate_description remains as a no-op hook
because subclasses override it and model_post_init still calls it.
Fixes EPD-179.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
* fix(tools): harden composite-description handling after review
- Anchor the pre-baked-composite check to the actual three-line block
shape instead of a naive substring match, so authored prose that
merely mentions "Tool Description:" is never truncated (CodeRabbit /
Bugbot review finding). Shared as
strip_composite_description_prefix() and reused by the function-
calling schema builder, which had the same naive split.
- Make render_text_description_and_args tolerate duck-typed tools
without a real formatted_description string (fixes CI: step-executor
tests pass Mock tools whose auto-created attribute is not a str).
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
---------
Co-authored-by: Claude Fable 5 <noreply@anthropic.com>
Co-authored-by: Lorenze Jay <63378463+lorenzejay@users.noreply.github.com>
… (#6509) * fix(tools)!: make tool-result caching opt-in instead of on by default Tool-result caching defaulted to on (Crew.cache=True, and standalone agents self-wired a CacheHandler at construction), so an LLM calling the same tool with identical arguments twice in one run silently got the first result back without the tool executing. For live-data tools that is a confidently stale answer; for state-mutating tools the second action is silently dropped. Caching is now opt-in with the machinery unchanged: - Crew.cache defaults to False; Crew(cache=True) restores today's behavior exactly (agents still default to participating when a crew offers its handler, and Agent(cache=False) still opts an agent out). - Standalone agents no longer self-wire a cache; Agent(cache=True) or an explicit cache_handler opts in. Previously even Crew(cache=False) agents cached via this self-wired handler. - Per-tool cache_function write gating is unchanged once opted in. Existing tests that exercised the caching machinery now opt in explicitly; new regression tests cover the default (both identical calls execute), crew-level opt-in dedup, and agent-level wiring. Fixes EPD-180. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> * fix(agent): don't let copy() turn the cache default into an explicit opt-in Agent.copy() rebuilds from model_dump(), which includes the field default cache=True, so the copy's model_fields_set contained "cache" and _setup_agent_executor wired a CacheHandler the source agent never opted into (Bugbot review finding). Drop "cache" from the dump when it was not explicitly set on the source; explicit opt-ins still survive copying. Also sync the Crew and BaseAgent class docstrings with the new opt-in cache semantics (CodeRabbit review findings). Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> * fix(agent): preserve cache_handler-only opt-in across Agent.copy() copy() excludes cache_handler from the rebuilt agent, so an agent that opted into tool-result caching solely via an explicit cache_handler lost caching after copy() (Bugbot review finding). Carry the consent as cache=True on the copy when the source has a handler wired and hasn't explicitly disabled caching — the copy wires its own fresh handler, matching pre-change copy semantics (copies never shared the source's handler instance). Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> * fix(crew): offer the crew cache handler to the hierarchical manager The hierarchical manager agent is created in _create_manager_agent, outside the validation-time agents loop that offers the crew's cache handler — and managers no longer self-wire a handler — so Crew(cache=True) hierarchical runs never cached the manager's delegation tool calls (Bugbot review finding). Offer the shared crew handler when the crew opted in; a user-provided manager with cache=False stays excluded via the existing set_cache_handler gate. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> * fix(agent): only construction-time cache opt-ins survive Agent.copy() The previous copy() fix treated any wired cache_handler as consent, but agents that merely received the crew's shared handler at kickoff (set_cache_handler from Crew(cache=True)) never opted in themselves — their copies must not become standalone cachers (Bugbot review finding). Record the opt-in signal in _setup_agent_executor, which runs at construction before any crew wiring can happen, and have copy() consult that flag instead of inspecting cache_handler after the fact. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> --------- Co-authored-by: Claude Fable 5 <noreply@anthropic.com>
…story (#6510) handle_turn() (and stream_turn) decided "did the handler append its reply?" by snapshotting the assistant-message count before kickoff and appending the stringified result when the count came back unchanged. A handler that appends its reply and then trims state.messages to a cap — a normal bounded-context pattern — left the count unchanged, so the fallback appended the reply a second time on every turn once trimming engaged, and the duplicates then crowded real turns out of the capped window. Replace the count heuristic with an explicit per-turn flag: append_assistant_message() sets _assistant_reply_appended, handle_turn and stream_turn clear it before kickoff and only fall back when no assistant message was appended during the turn. The now-unused _assistant_message_count() helper is removed. Fixes EPD-181. Co-authored-by: Claude Fable 5 <noreply@anthropic.com>
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…ibm-db2-review-fix # Conflicts: # docs/v1.13.0/en/tools/database-data/db2searchtool.mdx # lib/crewai-tools/src/crewai_tools/tools/db2_search_tool/README.md # lib/crewai-tools/src/crewai_tools/tools/db2_search_tool/__init__.py # lib/crewai-tools/src/crewai_tools/tools/db2_search_tool/db2_search_tool.py
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