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crewAI/lib/cli/tests/test_cli.py
João Moura bb477f8a91
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JSON first crews (#6131)
* feat(cli): introduce JSON crew project support and TUI enhancements

- Added support for creating and running JSON-defined crew projects, allowing users to scaffold projects with a new `create_json_crew.py` file.
- Implemented a full-screen Textual TUI for crew execution in `crew_run_tui.py`, enhancing user interaction with a two-column layout.
- Updated `run_crew.py` to prioritize JSON crew projects and added daemon mode for running without TUI.
- Introduced interactive pickers in `tui_picker.py` for improved CLI prompts.
- Enhanced validation for JSON crew files in `validate.py` to ensure proper structure and agent definitions.
- Updated `.gitignore` to exclude demo and crewai directories.

* feat: update LLM model references to gpt-5.4-mini

- Changed default LLM model from gpt-4o-mini to gpt-5.4-mini across various files, including CLI options, JSON crew configurations, and agent definitions.
- Enhanced benchmark and human feedback functionalities to utilize the new model.
- Improved user interface elements in the TUI for better interaction and feedback during execution.
- Added support for new skills directory in JSON crew project creation.

* feat(benchmark): add crew-level benchmarking functionality

- Introduced a new `benchmark` command in the CLI for crew-level benchmarking, allowing users to specify agents, models, and timeout settings.
- Implemented `CrewBenchmarkCase` to handle crew-level benchmark cases with inputs and criteria.
- Enhanced the benchmark runner to support progress tracking and detailed reporting of results for multiple models.
- Added tests for loading crew benchmark cases and validating their structure.
- Updated existing benchmark functions to accommodate the new crew-level execution model.

* feat(cli): enhance JSON crew project functionality and TUI improvements

- Added optional agent-level guardrails and advanced options in JSON crew configurations to improve output validation and flexibility.
- Updated the TUI to better handle plan step statuses, including visual indicators for task completion and failure.
- Introduced methods for parsing and managing step observation events, ensuring accurate updates to task statuses during execution.
- Enhanced validation for JSON crew projects, ensuring proper structure and error handling for agent and task definitions.
- Added comprehensive tests for new features and validation logic, ensuring robustness in JSON crew project handling.

* refactor(cli): streamline JSON crew project handling and improve validation

- Refactored JSON crew project loading and validation logic to enhance clarity and maintainability.
- Introduced utility functions for finding JSON crew files, improving code reuse across modules.
- Removed deprecated benchmark functionality and associated tests to simplify the codebase.
- Updated CLI commands to utilize the new JSON project structure, ensuring compatibility with recent changes.
- Enhanced test coverage for JSON crew project features, ensuring robust validation and error handling.

* feat(cli): enhance activity log navigation and focus management

- Added functionality to focus on the activity log when navigating through log entries.
- Implemented refresh logic for the log panel to ensure updates are displayed correctly during navigation.
- Improved keyboard navigation for log entries, allowing users to expand and scroll through logs seamlessly.
- Added tests to verify the correct behavior of log navigation and focus management in the TUI.

* feat(cli): enhance JSON crew project interaction and input handling

- Introduced a new function to enable prompt line editing for better user experience during input prompts.
- Updated the JSON crew project wizards to show interpolation hints for dynamic values, improving user guidance.
- Enhanced the handling of missing input placeholders by prompting users for required values during crew setup.
- Refactored the crew run logic to ensure proper loading and preparation of JSON-defined crews, including runtime input management.
- Added tests to verify the correct behavior of new input handling features and JSON crew project interactions.

* feat(cli): improve crew project input prompts and event handling

- Enhanced the `_prompt_text` function to allow for configurable spacing before prompts, improving user experience during input collection.
- Updated the wizards for agent and task creation to utilize the new prompt configuration, ensuring a more compact and streamlined interaction.
- Introduced new plan step lifecycle events (`PlanStepStartedEvent`, `PlanStepCompletedEvent`) to better track the execution status of plan steps.
- Refactored the step executor to emit these events during the execution of tasks, improving observability and debugging capabilities.
- Added tests to verify the correct behavior of new prompt handling and event emissions during crew project execution.

* fix: refine json-first crew interactions

* fix: prioritize common json crew tools

* fix: make json crew more tools expandable

* fix: show json crew tools by category

* feat(memory): update default embedder to OpenAI text-embedding-3-large and enhance memory compatibility

- Changed the default embedding model for Memory to OpenAI text-embedding-3-large, which uses 3072-dimensional vectors.
- Added warnings regarding compatibility issues with existing local memory stores created with 1536-dimensional embeddings.
- Updated documentation to reflect the new default embedder and its configuration options.
- Enhanced the CLI and codebase to support the new embedding model across various components, ensuring a seamless transition for users.

* fix: address PR review feedback for JSON-first crews

Review blockers:
- Forward trained_agents_file to JSON crews: crewai run -f now exports
  CREWAI_TRAINED_AGENTS_FILE for the in-process JSON crew path
- Wizard agent picker: Esc/cancel now reprompts instead of silently
  assigning the first agent
- JSON tool resolution hard-fails: unknown tool names, missing custom
  tool files, and invalid custom tool modules raise JSONProjectError
  with actionable messages instead of warn-and-continue
- Embedding dimension mismatch: LanceDB and Qdrant Edge storages raise
  EmbeddingDimensionMismatchError with reset/pin guidance instead of
  silently zero-filling vectors or returning empty search results
- Custom tool code execution documented in loader docstring and the
  scaffolded project README

CI fixes:
- ruff format across lib/
- All 133 PR-introduced mypy errors fixed (llm.py lazy-litellm and
  cli.py lazy command shims now use TYPE_CHECKING imports; textual
  is_mounted misuse fixed; pick_many overloads; misc annotations)

Bot review comments:
- Empty except blocks now have explanatory comments or debug logging
- Removed unused _C_BG/_C_PANEL/_C_BORDER globals and redundant
  import re; tests use a single import style for create_json_crew

Tests: trained-agents propagation, wizard cancel, tool resolution
failures, and dimension mismatch guidance.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>

* fix: address second round of PR review comments

Cursor Bugbot:
- Wizard agent slugs: strip to [a-z0-9_] and fall back to agent_<n> so
  symbol-only roles can't produce an empty agents/.jsonc filename
- Wizard task names: dedupe against prior task names and fall back to
  task_<n> for symbol-only descriptions

CodeRabbit:
- Agent.message(): import Task explicitly at runtime instead of relying
  on the namespace injection done by crewai/__init__
- Async executor: move the native-tools-unsupported fallback from
  _ainvoke_loop_react (self-recursion) to _ainvoke_loop_native_tools,
  mirroring the sync implementation
- StepExecutor downgrade: keep the in-step conversation and append the
  text-tooling instructions instead of rebuilding messages, so completed
  native tool calls are not re-executed
- crewai-files: extension-based MIME lookup now runs before byte
  sniffing so csv/xml types are not degraded to text/plain
- Memory storages: validate every record in a save() batch against a
  consistent embedding dimension (LanceDB previously checked only the
  first record); added mixed-batch tests
- _print_post_tui_summary now typed against CrewRunApp
- Docs: Azure OpenAI default embedder change called out in the memory
  migration warning and provider table

Code quality bots:
- Removed unused _C_YELLOW/_C_CYAN (crew_run_tui) and _GREEN (tui_picker)

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>

* feat(cli): accordion tool picker in JSON crew wizard

The flat tool list had grown to ~90 rows. The picker now shows:
- Common tools always visible at the top
- Every other category as a single expandable row with tool and
  selection counts (e.g. "Search & Research  (27 tools, 2 selected)")
- Expanding a category collapses the previously expanded one
- Selections persist across expand/collapse via new preselected
  support in pick_many; cursor follows the toggled category row

tui_picker gains preselected + initial_cursor options on pick_many,
and Esc in multi-select now confirms the current selection instead of
discarding it (required so collapsing can't silently drop choices).

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>

* refactor(cli): remove --daemon flag from crewai run

The flag only affected JSON crew projects — classic and flow projects
ignored it entirely, which made the behavior inconsistent. Removed the
option, the daemon code path (_run_json_crew_daemon), and its helper
(_load_json_crew_with_inputs).

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>

* test: update run command tests after --daemon removal

lib/crewai/tests/cli/test_run_crew.py still asserted the old
run_crew(trained_agents_file=..., daemon=False) call signature.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>

* fix(cli): exit codes, mid-run quit, async statuses, hyphen placeholders

Addresses the latest Bugbot review round:

- Failed JSON crew runs now exit non-zero (SystemExit(1)) so scripts
  and CI don't treat failures as success, mirroring the classic path
- Quitting the TUI mid-run now ends the process (os._exit(130));
  kickoff runs in a thread worker that cannot be force-cancelled, so
  letting the CLI return would leave LLM/tool work burning tokens in
  the background
- Sidebar task statuses are now async-safe: completion/failure events
  resolve the task's own row via identity instead of assuming the most
  recently started task, and starting a task no longer blanket-marks
  earlier active rows as done
- The runtime-input prompt regex now accepts hyphenated placeholder
  names ({my-topic}), matching kickoff's interpolation pattern

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>

* fix: validation safety, custom tool sandboxing, TUI log integrity, memory error surfacing

- Deploy validation no longer executes project code: validation mode
  checks tool declarations structurally (well-formed entries, custom
  tool file exists) without importing or instantiating anything.
  custom:<name> resolution only happens on the actual run path.
- custom:<name> is constrained to [A-Za-z_][A-Za-z0-9_]* and the
  resolved path must stay inside the project's tools/ directory, so
  custom:../foo or absolute-path names cannot execute code outside it.
  Tool paths resolve relative to the crew project root, not cwd.
- TUI task logs are built from per-task state captured at task start
  (idx, description, agent, start time); an out-of-order completion
  takes its output from the event and no longer steals or resets the
  current task's streamed steps/output.
- EmbeddingDimensionMismatchError now inherits ValueError instead of
  RuntimeError so background saves surface it through
  MemorySaveFailedEvent instead of silently dropping the save; the
  shutdown catch in _background_encode_batch is narrowed to the
  "cannot schedule new futures" case.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>

* fix(cli): declared project type wins over crew.json presence

A flow project that also contains a crew.json(c) file now runs and
validates as the flow it declares in pyproject.toml instead of being
hijacked by the JSON crew path. Both crewai run (_has_json_crew) and
deploy validation (_is_json_crew) check tool.crewai.type; a missing or
unreadable pyproject still means a bare JSON crew project.

Also documents why StepObservationFailedEvent intentionally marks the
plan step "done": the event signals an observer failure, not a step
failure, and the executor continues past it.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>

* fix(cli): type the declared_type locals so mypy stays clean

Comparing an Any-typed .get() chain returns Any, which tripped
no-any-return on the previous commit.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>

---------

Co-authored-by: Claude Fable 5 <noreply@anthropic.com>
2026-06-14 04:19:48 -03:00

294 lines
8.7 KiB
Python

from pathlib import Path
from unittest import mock
import pytest
from click.testing import CliRunner
from crewai_cli.cli import (
deploy_create,
deploy_list,
deploy_logs,
deploy_push,
deploy_remove,
deply_status,
flow_add_crew,
login,
reset_memories,
run,
test,
train,
version,
)
@pytest.fixture
def runner():
return CliRunner()
@mock.patch("crewai_cli.cli.train_crew")
def test_train_default_iterations(train_crew, runner):
result = runner.invoke(train)
train_crew.assert_called_once_with(5, "trained_agents_data.pkl")
assert result.exit_code == 0
assert "Training the Crew for 5 iterations" in result.output
@mock.patch("crewai_cli.cli.train_crew")
def test_train_custom_iterations(train_crew, runner):
result = runner.invoke(train, ["--n_iterations", "10"])
train_crew.assert_called_once_with(10, "trained_agents_data.pkl")
assert result.exit_code == 0
assert "Training the Crew for 10 iterations" in result.output
@mock.patch("crewai_cli.cli.train_crew")
def test_train_invalid_string_iterations(train_crew, runner):
result = runner.invoke(train, ["--n_iterations", "invalid"])
train_crew.assert_not_called()
assert result.exit_code == 2
assert (
"Usage: train [OPTIONS]\nTry 'train --help' for help.\n\nError: Invalid value for '-n' / '--n_iterations': 'invalid' is not a valid integer.\n"
in result.output
)
def test_reset_no_memory_flags(runner):
result = runner.invoke(
reset_memories,
)
assert (
result.output
== "Please specify at least one memory type to reset using the appropriate flags.\n"
)
def test_version_flag(runner):
result = runner.invoke(version)
assert result.exit_code == 0
assert "crewai version:" in result.output
def test_version_command(runner):
result = runner.invoke(version)
assert result.exit_code == 0
assert "crewai version:" in result.output
def test_version_command_with_tools(runner):
result = runner.invoke(version, ["--tools"])
assert result.exit_code == 0
assert "crewai version:" in result.output
assert (
"crewai tools version:" in result.output
or "crewai tools not installed" in result.output
)
@mock.patch("crewai_cli.cli.evaluate_crew")
def test_test_default_iterations(evaluate_crew, runner):
result = runner.invoke(test)
evaluate_crew.assert_called_once_with(3, "gpt-5.4-mini", trained_agents_file=None)
assert result.exit_code == 0
assert "Testing the crew for 3 iterations with model gpt-5.4-mini" in result.output
@mock.patch("crewai_cli.cli.evaluate_crew")
def test_test_custom_iterations(evaluate_crew, runner):
result = runner.invoke(test, ["--n_iterations", "5", "--model", "gpt-4o"])
evaluate_crew.assert_called_once_with(5, "gpt-4o", trained_agents_file=None)
assert result.exit_code == 0
assert "Testing the crew for 5 iterations with model gpt-4o" in result.output
@mock.patch("crewai_cli.cli.evaluate_crew")
def test_test_invalid_string_iterations(evaluate_crew, runner):
result = runner.invoke(test, ["--n_iterations", "invalid"])
evaluate_crew.assert_not_called()
assert result.exit_code == 2
assert (
"Usage: test [OPTIONS]\nTry 'test --help' for help.\n\nError: Invalid value for '-n' / '--n_iterations': 'invalid' is not a valid integer.\n"
in result.output
)
@mock.patch("crewai_cli.cli.run_crew")
def test_run_uses_project_runner_by_default(run_crew, runner):
result = runner.invoke(run)
assert result.exit_code == 0
run_crew.assert_called_once_with(trained_agents_file=None)
assert "experimental" not in result.output.lower()
@mock.patch("crewai_cli.cli.run_flow_definition")
def test_run_with_definition_uses_definition_runner(run_flow_definition, runner):
result = runner.invoke(
run,
["--definition", "flow.yaml", "--inputs", '{"topic":"AI"}'],
)
assert result.exit_code == 0
assert (
"Warning: `crewai run --definition` is experimental and may change without notice."
in result.output
)
run_flow_definition.assert_called_once_with(
definition="flow.yaml", inputs='{"topic":"AI"}'
)
@mock.patch("crewai_cli.cli.run_crew")
@mock.patch("crewai_cli.cli.run_flow_definition")
def test_run_rejects_inputs_without_definition(run_flow_definition, run_crew, runner):
result = runner.invoke(run, ["--inputs", '{"topic":"AI"}'])
assert result.exit_code == 2
assert "Error: --inputs requires --definition" in result.output
run_flow_definition.assert_not_called()
run_crew.assert_not_called()
@mock.patch("crewai_cli.cli.AuthenticationCommand")
def test_login(command, runner):
mock_auth = command.return_value
result = runner.invoke(login)
assert result.exit_code == 0
mock_auth.login.assert_called_once()
@mock.patch("crewai_cli.cli.DeployCommand")
def test_deploy_create(command, runner):
mock_deploy = command.return_value
result = runner.invoke(deploy_create)
assert result.exit_code == 0
mock_deploy.create_crew.assert_called_once()
@mock.patch("crewai_cli.cli.DeployCommand")
def test_deploy_list(command, runner):
mock_deploy = command.return_value
result = runner.invoke(deploy_list)
assert result.exit_code == 0
mock_deploy.list_crews.assert_called_once()
@mock.patch("crewai_cli.cli.DeployCommand")
def test_deploy_push(command, runner):
mock_deploy = command.return_value
uuid = "test-uuid"
result = runner.invoke(deploy_push, ["-u", uuid])
assert result.exit_code == 0
mock_deploy.deploy.assert_called_once_with(uuid=uuid, skip_validate=False)
@mock.patch("crewai_cli.cli.DeployCommand")
def test_deploy_push_no_uuid(command, runner):
mock_deploy = command.return_value
result = runner.invoke(deploy_push)
assert result.exit_code == 0
mock_deploy.deploy.assert_called_once_with(uuid=None, skip_validate=False)
@mock.patch("crewai_cli.cli.DeployCommand")
def test_deploy_status(command, runner):
mock_deploy = command.return_value
uuid = "test-uuid"
result = runner.invoke(deply_status, ["-u", uuid])
assert result.exit_code == 0
mock_deploy.get_crew_status.assert_called_once_with(uuid=uuid)
@mock.patch("crewai_cli.cli.DeployCommand")
def test_deploy_status_no_uuid(command, runner):
mock_deploy = command.return_value
result = runner.invoke(deply_status)
assert result.exit_code == 0
mock_deploy.get_crew_status.assert_called_once_with(uuid=None)
@mock.patch("crewai_cli.cli.DeployCommand")
def test_deploy_logs(command, runner):
mock_deploy = command.return_value
uuid = "test-uuid"
result = runner.invoke(deploy_logs, ["-u", uuid])
assert result.exit_code == 0
mock_deploy.get_crew_logs.assert_called_once_with(uuid=uuid)
@mock.patch("crewai_cli.cli.DeployCommand")
def test_deploy_logs_no_uuid(command, runner):
mock_deploy = command.return_value
result = runner.invoke(deploy_logs)
assert result.exit_code == 0
mock_deploy.get_crew_logs.assert_called_once_with(uuid=None)
@mock.patch("crewai_cli.cli.DeployCommand")
def test_deploy_remove(command, runner):
mock_deploy = command.return_value
uuid = "test-uuid"
result = runner.invoke(deploy_remove, ["-u", uuid])
assert result.exit_code == 0
mock_deploy.remove_crew.assert_called_once_with(uuid=uuid)
@mock.patch("crewai_cli.cli.DeployCommand")
def test_deploy_remove_no_uuid(command, runner):
mock_deploy = command.return_value
result = runner.invoke(deploy_remove)
assert result.exit_code == 0
mock_deploy.remove_crew.assert_called_once_with(uuid=None)
@mock.patch("crewai_cli.add_crew_to_flow.create_embedded_crew")
@mock.patch("pathlib.Path.exists", return_value=True)
def test_flow_add_crew(mock_path_exists, mock_create_embedded_crew, runner):
crew_name = "new_crew"
result = runner.invoke(flow_add_crew, [crew_name])
assert result.exit_code == 0, f"Command failed with output: {result.output}"
assert f"Adding crew {crew_name} to the flow" in result.output
mock_create_embedded_crew.assert_called_once()
call_args, call_kwargs = mock_create_embedded_crew.call_args
assert call_args[0] == crew_name
assert "parent_folder" in call_kwargs
assert isinstance(call_kwargs["parent_folder"], Path)
def test_add_crew_to_flow_not_in_root(runner):
with mock.patch("pathlib.Path.exists", autospec=True) as mock_exists:
def exists_side_effect(self):
if self.name == "pyproject.toml":
return False
return True
mock_exists.side_effect = exists_side_effect
result = runner.invoke(flow_add_crew, ["new_crew"])
assert result.exit_code != 0
assert "This command must be run from the root of a flow project." in str(
result.output
)