- 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
`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
Add a single declaration loader shared by API and CLI callers.
- Add FlowDefinition.from_declaration for FlowDefinition instances, dictionaries, YAML/JSON strings, and file paths
- Add Flow.from_declaration to build runnable flows directly from the same inputs
- Route declarative flow CLI loading through Flow.from_declaration so path handling and validation stay centralized
```
# Load just the serializable definition when you do not need to run it yet.
definition = FlowDefinition.from_declaration(path="flows/research.crewai")
definition = FlowDefinition.from_declaration(contents=flow_yaml)
definition = FlowDefinition.from_declaration(contents=flow_dict)
# Build a runnable flow directly from the same declaration inputs.
flow = Flow.from_declaration(path="flows/research.crewai")
flow = Flow.from_declaration(contents=flow_yaml)
flow = Flow.from_declaration(contents=flow_dict)
flow = Flow.from_declaration(contents=definition)
# Run it like any other flow.
result = flow.kickoff(inputs={"topic": "AI agents"})
# The CLI now goes through the same path-based loader.
# crewai run --definition flows/research.crewai
```
* Add declarative Flow CLI support
Currently, declarative flows can be loaded by the runtime, but the CLI
still treats them as an experimental definition file instead of a
first-class Flow project shape.
With this PR, `crewai create flow --declarative` scaffolds a YAML-backed
Flow project, and `crewai run`, `crewai flow kickoff`, and `crewai flow
plot` can run against the configured definition.
This also lets crew actions reference reusable crew definition files or
folders and override their inputs from the Flow definition, so
declarative flows can compose existing declarative crews without
inlining everything.
* Address code review comments
