6a76ea894d034a3c8c3c013a65bf09a1d6d838c1
708 Commits
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6a76ea894d |
test(cli): add TDD regression tests for automation_profile._get_service() DI bypass
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Three BDD scenarios and two Robot Framework integration tests verifying that _get_service() in automation_profile.py resolves AutomationProfileService through the DI container rather than manually calling create_engine or sessionmaker (bug #990). Bug #990 was fixed by PR #1181 before this TDD test PR merged; the @tdd_expected_fail tag is therefore absent and these tests serve as permanent regression guards confirming the fix remains in place. ISSUES CLOSED: #1031 |
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ee1ec2b56d | chore: worker ruff auto-fix (pre-push lint gate) | ||
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5ede1c018a |
fix(server,sync): use A2aRequest.method not .operation in tests and helpers
The new entity-sync feature introduced A2aRequest with a `method` field (JSON-RPC 2.0 wire format), but several test/helper files used the wrong field name `operation` when constructing requests or logging, and checked non-existent `.status`/`.data` attributes on A2aResponse instead of `.result`/`.error`. Fixes: - asgi_app.py: log `a2a_request.method`, not `.operation` (typecheck error) - server_lifecycle_steps.py: send `method` key in JSON-RPC payload; look up status in `result` dict, not top-level response body - server_lifecycle.feature: expect "healthy" (what the handler returns), not "ok" - entity_sync_steps.py: construct A2aRequest(method=...) not (operation=...); assert on .result/.error instead of .status/.data - robot/helper_entity_sync.py: same method= and result/error fixes across sync_pull, sync_push, sync_status, sync_facade_no_service helpers - robot/helper_server_lifecycle.py: same method= and result path fixes ISSUES CLOSED: #1125 |
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ff9c6540a2 |
feat(server): entity sync (_cleveragents/sync/*)
Implement entity synchronization between client and server using the _cleveragents/sync/* A2A extension methods per the specification. Sync models (src/cleveragents/a2a/sync_models.py): - Pydantic v2 models for pull/push/status requests and responses - VectorClock with increment, merge, happens-before, and concurrency detection for distributed conflict detection - SyncEntitySnapshot, SyncConflict, SyncState, SyncQueueEntry models - SyncEntityType enum: actor, skill, action, plan, session - ConflictResolution enum: last_writer_wins, manual, server_wins, client_wins SyncService (src/cleveragents/application/services/sync_service.py): - pull(): download server namespace entities to local cache with incremental sync (since timestamps) and force-overwrite option - push(): push local entity definitions to server namespace with configurable conflict resolution strategy - status(): compare local and server entity versions, detect drift, report local-ahead, server-ahead, and concurrent conflicts - resolve_conflict(): manually resolve detected conflicts with winner selection (local or server) - Offline queue: enqueue_offline() and process_offline_queue() for retry on reconnect, with max-retries enforcement - The local/ namespace is never synced per specification A2A facade (src/cleveragents/a2a/facade.py): - Replaced sync stub handlers with real _handle_sync_pull, _handle_sync_push, _handle_sync_status routing to SyncService - Added sync_service property and TYPE_CHECKING import - Facade returns stubs when no SyncService is registered Tests: - Behave BDD: features/entity_sync.feature (65 scenarios, 247 steps) covering models, vector clocks, pull/push/status, conflict resolution, offline queue, facade integration, constructor validation, edge cases - Robot Framework: robot/entity_sync.robot (8 integration tests) ISSUES CLOSED: #866 |
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b5f56a6fb8 |
feat(server): team collaboration features
Implemented multi-user connection handling with user identity tracking (TeamMember with owner/admin/member/viewer roles), role-based access control (TeamPermission with read/write/admin/manage_members), concurrent session support (SessionRegistry with thread-safe locking and per-user/ per-project queries), and optimistic-locking conflict resolution (VersionStamp with last-writer-wins, reject, and merge strategies). Added TeamCollaborationService as the central orchestrator for all collaboration operations: team membership management, permission enforcement, session lifecycle, and version-stamp conflict detection/ resolution. The service cleans up user sessions when members are removed. Domain models follow existing patterns: Pydantic BaseModel with ConfigDict, StrEnum enums, ULID identifiers, and an error hierarchy rooted in TeamCollaborationError. Includes 48 Behave BDD scenarios (178 steps) covering all models, service operations, and edge cases, plus 15 Robot Framework integration tests for end-to-end workflow validation. ISSUES CLOSED: #863 |
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c6ccb85bb8 |
feat(server): ASGI endpoint via uvicorn
Implement FastAPI-based ASGI application served by uvicorn for the CleverAgents server mode. Add health check endpoint, A2A JSON-RPC routing, configurable host:port binding, and graceful shutdown handling. Server launches via `agents server start`. - Add FastAPI ASGI app factory at infrastructure/server/asgi_app.py with /.well-known/agent.json (Agent Card), /health (liveness), and /a2a (A2A JSON-RPC 2.0 dispatch via A2aLocalFacade) - Add ServerLifecycle class at infrastructure/server/server_lifecycle.py wrapping uvicorn.Server with SIGTERM/SIGINT graceful shutdown - Add `agents server start` CLI command with --host, --port, --log-level options, resolving defaults from Settings - Add fastapi>=0.115.0 dependency to pyproject.toml (uvicorn already present) - Add Behave BDD tests (features/server_lifecycle.feature, 20 scenarios) - Add Robot Framework integration tests (robot/server_lifecycle.robot) - Update CHANGELOG.md and vulture_whitelist.py ISSUES CLOSED: #862 |
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8dde6c81ef |
feat(server): implement PostgreSQL storage backend for server mode
Add PostgreSQL support as the server-mode storage backend alongside existing SQLite for local mode. Verify all ORM models are dialect- agnostic, configure connection pooling for multi-user access, add Docker Compose for local PG development, and wire database URL selection based on deployment mode. Changes: - Add psycopg2-binary dependency to pyproject.toml - Add server_mode, db_pool_size, db_max_overflow, db_pool_recycle settings to Settings with environment variable support - Add resolve_database_url() and is_postgresql() to Settings for mode-aware database URL resolution - Configure UnitOfWork engine creation with pool_size, max_overflow, pool_recycle, and pool_pre_ping for PostgreSQL connections - Update MigrationRunner to handle both SQLite and PostgreSQL backends - Add compare_type=True to Alembic env.py for dialect-aware migrations - Add docker-compose.yml with PostgreSQL 16-alpine for local development - Add Behave BDD feature (14 scenarios) covering settings, pool config, engine creation, ORM dialect compatibility, and migration runner - Add Robot Framework integration tests (12 test cases) for the abstraction layer with requires_postgresql tag for live PG tests Fixes: - Restore require_confirmation parameter to UnitOfWork.__init__ - Add argument validation to UnitOfWork.__init__ (fail-fast) - Add explicit PostgreSQL isolation_level (READ COMMITTED) - Add dispose() method and context manager support to UnitOfWork - Fix MigrationRunner.get_current_revision() to dispose engine - Fix Settings.is_postgresql() to handle ValueError gracefully ISSUES CLOSED: #878 |
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6aaf69e0a4 |
feat(server): implement PostgreSQL storage backend for server mode
Add PostgreSQL support as the server-mode storage backend alongside existing SQLite for local mode. Verify all ORM models are dialect- agnostic, configure connection pooling for multi-user access, add Docker Compose for local PG development, and wire database URL selection based on deployment mode. Changes: - Add psycopg2-binary dependency to pyproject.toml - Add server_mode, db_pool_size, db_max_overflow, db_pool_recycle settings to Settings with environment variable support - Add resolve_database_url() and is_postgresql() to Settings for mode-aware database URL resolution - Configure UnitOfWork engine creation with pool_size, max_overflow, pool_recycle, and pool_pre_ping for PostgreSQL connections - Update MigrationRunner to handle both SQLite and PostgreSQL backends - Add compare_type=True to Alembic env.py for dialect-aware migrations - Add docker-compose.yml with PostgreSQL 16-alpine for local development - Add Behave BDD feature (14 scenarios) covering settings, pool config, engine creation, ORM dialect compatibility, and migration runner - Add Robot Framework integration tests (12 test cases) for the abstraction layer with requires_postgresql tag for live PG tests ISSUES CLOSED: #878 |
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2dd920078a |
fix(tests): add resolve_actor_options to mock lifecycle helpers
The PR added resolve_actor_options() to StrategyActor, LLMStrategizeActor, and LLMExecuteActor, but the three mock lifecycle SimpleNamespace objects used by tests did not include this method, causing AttributeError at runtime: - features/mocks/mock_strategy_llm.py: make_mock_lifecycle() used by robot/helper_strategy_actor.py (strategy_actor.robot llm-json test) and features/steps/strategy_actor_llm_steps.py - features/steps/llm_actors_coverage_steps.py: _make_mock_lifecycle() used by llm_actors_coverage.feature scenarios - robot/helper_m5_e2e_context.py: inline lifecycle SimpleNamespace used by m5_e2e_verification.robot Execute Phase LLM Uses ACMS Context All three now include resolve_actor_options=MagicMock(return_value=None) matching the None-return contract the actors use when no custom backend is configured. ISSUES CLOSED: #11256 |
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3e13411fcf
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fix(actors): distinguish namespace/name from provider/model in actor name parsing
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When action YAML references actors using namespace/name format (e.g. `strategy_actor: local/my-strategist`), `_parse_actor_name()` incorrectly treated the namespace prefix as a provider name, causing `ValueError: Unknown provider type: local`. Changes: - `_is_known_provider()`: New utility function (strategy_resolution.py) that checks whether a slash-separated first segment matches a known `ProviderType` value (openai, anthropic, etc.). Consolidated into a single implementation; llm_actors.py now imports from strategy_resolution.py. - `_parse_actor_name()`: When the first segment IS a known provider, preserves existing behaviour (provider/model). When it is NOT a known provider, treats the input as namespace/name and returns the full name as the model identifier with the default provider. Callers SHOULD pre-resolve namespace/name references via the actor registry before calling this function. Both implementations (strategy_resolution.py and llm_actors.py) updated; ProviderType import moved to top level. - `PlanLifecycleService.resolve_actor_provider_model()`: New method that resolves a namespaced actor name (e.g. local/my-strategist) to provider/model format by looking up the actor record and extracting its provider and model fields. - `LifecycleService` Protocol (strategy_resolution.py): Added `resolve_actor_provider_model` to the protocol, eliminating the need for `# type: ignore[union-attr]` at call sites. - `PlanLifecycleProtocol` (llm_actors.py): Added `resolve_actor_provider_model` to the protocol. - Caller pre-resolution: StrategyActor, LLMStrategizeActor, LLMExecuteActor, SessionWorkflow._resolve_llm(), and CLI session commands now pre-resolve actor names through the lifecycle service or via injected actor_resolver callables before calling `_parse_actor_name()`, ensuring namespace/name references are correctly mapped to their underlying LLM providers. - `_build_actor_resolver()` (cli/commands/session.py) and `_build_actor_resolver_for_session_workflow()` (a2a/facade.py): Moved `_is_known_provider` imports to top level; removed redundant `except (NotFoundError, Exception)`; added warning logging for outer exception handlers. - `make_mock_lifecycle()` (mock_strategy_llm.py) and `_make_mock_lifecycle()` (llm_actors_coverage_steps.py): Added `resolve_actor_provider_model` to mock lifecycle services for test compatibility. - Added `@tdd_issue @tdd_issue_11254` tags to all new BDD scenarios related to namespace/name disambiguation in llm_actors_coverage, strategy_actor_llm, and plan_lifecycle_service_coverage_boost_r4 feature files. - Updated docs/CHANGELOG.md with the fix entry. ISSUES CLOSED: #11254 |
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652769c46c |
feat(tui): wire normal text input to LLM via A2A facade
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Wires the TUI normal text input path to the LLM via A2aLocalFacade, closing the gap where typing a message produced no LLM call. All infrastructure (facade, SessionWorkflow, ProviderRegistry) already existed in the CLI; this PR adds the TUI wiring on top. Key changes: - _run_llm_dispatch(): module-level, Textual-free dispatch function covering all domain exception paths with user-friendly messages - _format_worker_outcome(): testable worker result/error translator - _create_tui_session(): DB-backed session with persona actor binding - _build_tui_facade(): wired A2aLocalFacade + SessionWorkflow singleton - run_worker(thread=True, exclusive=True): non-blocking, serialised - _dispatch_gen counter: prevents cancelled worker callbacks from corrupting the multi-turn transcript - SessionView.transcript: accumulated conversation history, pre-escaped - Markup escaping: _escape() applied before transcript storage - on_mount focus: prompt.focus() so keyboard input is received Tests: 18 BDD scenarios + 6 Robot Framework integration tests with FakeListLLM (no real API keys required). ISSUES CLOSED: #11230 |
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eb46f0ff54 |
fix(plan): add tier hydration and improve architecture review output (#10938)
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## Summary This PR fixes issue #10878 where architecture reviews were truncated because the regex pattern for parsing file output would stop at the first ``` encountered in the Markdown report. ## Changes - Change file delimiters from ``` to >>>>>>>/<<<<<<< to avoid Markdown conflicts - Add tier hydration before strategize phase in plan_executor.py - Increase max_tokens to 16384 in llm_actors.py for longer outputs - Increase context_max_tokens_hot from 16000 to 32000 in settings.py - Fix get_hot_view → get_hot_fragments in strategy_actor.py and plan_executor.py - Add opencode to skip directories in context_tier_hydrator.py - Change sandbox output location to plan-output/ directory in plan.py - Add get_context_summary stub method to acms_service.py ## Testing Run architecture review action and verify the output report is complete with all sections. Reviewed-on: #10938 |
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0c5724c2f6 |
feat(actor-run): wire ToolCallingRuntime into actor run for skill-based tool calling
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Implements the full tool-calling path for `agents actor run --skill` so that LLM
actors can actually invoke tools through the ToolCallingRuntime loop when a skill
is attached.
Core changes:
- reactive/tool_caller.py (new): ToolCallingLLMCaller implements the LLMCaller protocol;
binds tool schemas via bind_tools(), threads SystemMessage+HumanMessage on first call
and AIMessage+ToolMessages on subsequent calls, extracts tool calls from LangChain
responses following the LangChainSessionCaller pattern.
- reactive/tool_caller.py: bidirectional tool name encoding via uppercase sentinels
(_encode_tool_name / _decode_tool_name) to make CleverAgents namespaced tool names
("builtin/file-read", "server:local/tool") compatible with Anthropic's tool name
pattern ^[a-zA-Z0-9_-]{1,128}$. Uses _C_ for ":" and _S_ for "/" — uppercase
sentinels are safe because valid CleverAgents tool names forbid uppercase letters.
Encoding applied in _resolve_llm() before bind_tools(); decoding applied in invoke()
when extracting tool calls from the LLM response.
- reactive/tool_agent.py (new): ToolCallingAgent builds a per-run local ToolRegistry from
resolved skill tool entries by looking up names in the shared builtin_registry; drives
ToolCallingRuntime.run_tool_loop(); exposes last_result for tool_calls surfacing.
- reactive/application.py: (ST-1) _make_agent_instance() now always merges skill tools
instead of silently dropping them when actor has no base tools list; routes
tools+llm→ToolCallingAgent, tools+non-llm→SimpleToolAgent, no-tools+llm→SimpleLLMAgent;
(ST-4) _builtin_registry created at startup with register_file_tools/git/subplan;
(ST-6) _tally_tool_calls() + last_run_tool_calls property.
- reactive/graph_executor.py: (ST-5) ToolCallingAgent added to isinstance check in
_invoke_agent() so context dict is forwarded for Jinja2 rendering.
- cli/commands/actor_run.py: prints "Tool Calls: {n}" when > 0.
Test fixes:
- features/steps/actor_cli_run_steps.py: _make_app() sets last_run_tool_calls=0 to avoid
MagicMock>int TypeError in Python 3.13.
- features/steps/actor_run_signature_resolve_steps.py: same fix.
- robot/helper_actor_run_signature.py: same fix.
- features/reactive_application_coverage_boost.feature: updated scenario to verify new
correct behavior (LLM+skills → ToolCallingAgent, not silently kept as SimpleLLMAgent).
BDD coverage: 34 scenarios in features/actor_run_tool_calling.feature covering
tool call success, multi-turn loop, no-skill regression, silent-drop fix, LLMCaller
internals, _build_tool_registry edge cases, last_run_tool_calls tallying,
tool name encoding/decoding, and LLM response decoding.
ISSUES CLOSED: #11211
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f4cea72248 |
fix(ci): update all merge_invariants callers to use 4-param signature
The PR #11143 adds action_invariants as a 4th parameter to merge_invariants() and InvariantSet.merge(), but two call sites were not updated: - benchmarks/invariant_merge_bench.py: 5 calls with 3 positional args - robot/helper_m3_e2e_verification.py: 2 calls using keyword args All call sites now pass action_invariants=[] for backward-compatible empty-action behavior. |
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97c1007bb5
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feat(events): wire domain services to emit missing EventBus events
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Add TokenAuthMiddleware to emit AUTH_SUCCESS/AUTH_FAILURE with spec-aligned audit details and wire it through the DI container using server.token resolution. Add Behave and Robot coverage for auth event emission and end-to-end audit persistence, and update audit subscriber producer notes and changelog. ISSUES CLOSED: #714 |
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b41f536da6 |
fix(automation): respect automation profile gates in lifecycle service and async jobs
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Add BDD regression tests for issue #4328 automation profile gates Tests verify that complete_strategize() and complete_execute() respect automation profile thresholds and do NOT unconditionally call auto_progress(). Covers 8 built-in profiles: manual, full-auto, supervised, auto, review_before_apply, ci, trusted ISSUES CLOSED: #4328 |
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cc8e013f9b |
fix(actor): handle nested actor type and combined config.actor field in v3 YAML
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Two defects in ActorConfiguration._extract_v3_actor() prevented YAML files
using the spec-canonical nested actors map format from being registered:
Defect A: The method looked for the 'type' field inside the 'config:' block
(config_block.get('type')) instead of at the actor-entry level
(first_entry.get('type')). Because the spec places 'type' at
actors.<name>.type — a sibling of 'config:', not a child of it — the v3
detection branch never fired for nested-actors-map YAMLs, causing
_extract_v3_actor() to return (None, None, None, False) immediately.
Defect B: Even if the type was found, the method only consulted separate
config.provider and config.model keys; it never parsed the combined
config.actor: 'provider/model' shorthand. Without the combined-field
fallback, provider and model remained None for all spec-canonical YAMLs
that use the shorthand, causing from_blob() to raise
'BadParameter: provider is required'.
Both defects had to be fixed together because Defect A blocked the code
from ever reaching the path where Defect B would otherwise have been
encountered.
The combined-format parser (config.actor split on first '/') is inserted
after the explicit config.provider / config.model lookups so that explicit
separate fields always take precedence over the shorthand when both are
present.
Parsing logic extracted into _parse_combined_actor_field() helper to
eliminate DRY violation. Both provider and model halves validated
consistently (empty provider half was previously silently inferred).
Adds Behave scenarios covering: nested actors map + combined config.actor
(success), explicit config.provider precedence over config.actor,
explicit config.model precedence over config.actor, genuinely missing
provider/model raising validation error, and malformed combined values
(empty model half, empty provider half, missing delimiter). Adds a Robot
integration test for the combined-actor YAML path with provider/model
assertions via show. Restores accidentally deleted TOOL and GRAPH Robot
integration tests. Mirrors provider/model extraction in
step_run_actor_update for assertion step compatibility.
ISSUES CLOSED: #11189
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d31d9226f9 |
test(wf10_batch.robot): request that LLM not create files (#11133)
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Closes: #11007 ## Description Asks LLM to not create files. ## Type of Change - [ X ] Bug fix (non-breaking change which fixes an issue) - [ X ] Test improvements ## Quality Checklist - [ ] Code follows the project's coding standards (see CONTRIBUTING.md) - [ ] All public/protected methods have argument validation - [ ] Static typing is complete (no `Any` unless justified) - [ ] `nox -s typecheck` passes with no errors - [ ] `nox -s lint` passes with no errors - [ ] Unit tests written/updated (Behave scenarios in `features/`) - [ ] Integration tests written/updated (Robot suites in `robot/`) if applicable - [ ] Coverage remains above 85% (`nox -s coverage_report`) - [ ] No security issues introduced (`nox -s security_scan`) - [ ] No dead code introduced (`nox -s dead_code`) - [ ] Documentation updated if behavior changed ## Testing Running in git.cleverthis.com is the only real test possible. ### Test Commands Run ```bash nox -s unit_tests # Behave tests nox -s typecheck # Type checking nox -s lint # Linting nox -s coverage_report # Coverage ``` ## Related Issues Closes #11007 Reviewed-on: #11133 Reviewed-by: Hamza Khyari <hamza.khyari@cleverthis.com> |
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9fe69c468c
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test(plan): add tdd issue-capture test for cleanup_stale destroying execute output before apply
Add two Behave scenarios tagged @tdd_issue, @tdd_issue_11121, and @tdd_expected_fail that capture bug #11121: _create_sandbox_for_plan() calls GitWorktreeSandbox.cleanup_stale() unconditionally on every execute invocation, including when the plan is already in execute/complete state awaiting apply. Scenario 1 asserts that the cleveragents/plan-<id> branch survives a second call to _create_sandbox_for_plan() on an execute/complete plan. This assertion fails because cleanup_stale deletes the branch regardless of plan state. Scenario 2 asserts that plan apply would find at least one artifact after a re-invoked execute on an execute/complete plan. This assertion fails because the branch (holding execute output) was destroyed by cleanup_stale. Both scenarios use @tdd_expected_fail so CI passes while the bug is unfixed. The @mock_only tag ensures no database is created for these git-only tests. The companion fix is tracked in issue #11121. Additional CI fixes bundled in this commit: - Fixed PlanGenerationGraph recursion bug: _should_retry() was mutating state in-place but LangGraph conditional edge functions cannot persist state mutations. Replaced with a proper _handle_retry() node that increments retry_count via state returns, resolving the GraphRecursionError that was crashing the integration tests. Updated the graph to include handle_retry as the 5th node, routing validate→should_retry→handle_retry→analyze. - Fixed TDD quality gate (scripts/tdd_quality_gate.py): Renamed @tdd_bug_N tags to @tdd_issue_N to match the CONTRIBUTING.md specification. Added _diff_is_tdd_issue_capture() detection so that TDD issue-capture PRs (which add @tdd_expected_fail rather than remove it) pass the quality gate correctly. Updated all related tests (Behave unit tests, Robot integration tests, and test helpers) to use the new tag naming. ISSUES CLOSED: #11120 |
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d25a060c58 |
Revert "feat(ci): implement TDD bug tag quality gate for bug fix PRs"
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This reverts commit
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b4a514e0f4 |
fix(cli): add spec-required --data-dir, --config-path, and -v global options to main_callback
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Implements ADR-021 §Global CLI Flags and ADR-024 §Resolution Chain.
All three global options were missing from main_callback(), causing any
invocation with these flags to crash with 'No such option'.
Changes:
- src/cleveragents/cli/main.py
* Add _VERBOSITY_LOG_LEVELS tuple mapping verbose count to log levels
(0=CRITICAL/silent, 1=ERROR, 2=WARNING, 3=INFO, 4=DEBUG, 5+=DEBUG)
* Add --data-dir PATH option: validates path is a directory if it exists,
sets CLEVERAGENTS_DATA_DIR env var, resets Settings singleton
* Add --config-path PATH option: validates file exists and is a file,
sets CLEVERAGENTS_CONFIG_PATH env var for ConfigService to pick up
* Add -v (count=True) option: wires verbose count to configure_structlog
* Store all three values in ctx.obj for subcommand access
* Update _print_basic_help() to include the three new global options so
'cleveragents --help' (fast path) also lists them
* In the catch-all Exception handler, print the original exception
type+message directly to err_console so actionable details remain
visible even when log level is CRITICAL (e.g. 'No such option')
- src/cleveragents/application/services/config_service.py
* ConfigService.__init__ now checks CLEVERAGENTS_CONFIG_PATH env var
when no explicit config_path is passed, completing the resolution
chain for --config-path CLI override
Tests (all passing):
- features/cli_global_options.feature (21 Behave scenarios)
- features/steps/cli_global_options_steps.py
- robot/cli_global_options.robot (8 Robot Framework integration tests)
- robot/helper_cli_global_options.py
Quality gates: lint ✓ typecheck ✓ unit_tests ✓ integration_tests ✓
Coverage: 96.52% (threshold 96.5% ✓)
ISSUES CLOSED: #6785
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e8d2f76466
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feat(ci): implement TDD bug tag quality gate for bug fix PRs
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Add an automated quality gate that enforces TDD bug fix workflow rules on pull requests. The gate parses PR descriptions for bug-closing keywords (Closes/Fixes/Resolves #N, ISSUES CLOSED: #N), searches the codebase for corresponding TDD tests tagged @tdd_bug_N, and verifies that @tdd_expected_fail tags have been removed. Key components: - scripts/tdd_quality_gate.py: Main quality gate script with PR description parsing, TDD test discovery, and tag removal verification. All public functions validate arguments fail-fast and are statically typed. - noxfile.py: New tdd_quality_gate session that reads PR_DESCRIPTION from the environment and runs the quality gate script. - .forgejo/workflows/ci.yml: New tdd_quality_gate CI job that runs only on pull_request events, passing the PR body as PR_DESCRIPTION. - features/tdd_quality_gate.feature: 46 Behave scenarios covering PR parsing, TDD test search, tag removal verification, full gate logic, robot diff handling, edge cases, argument validation, bool guards, co-located bug false-positive guard, and main() CLI entry point. - features/steps/tdd_quality_gate_steps.py: Step definitions for all Behave scenarios using temporary directories for isolation. - robot/tdd_quality_gate.robot: 15 Robot Framework integration tests exercising the gate end-to-end via a helper subprocess. - robot/helper_tdd_quality_gate.py: Helper script for Robot tests with sentinel-based sub-commands. Review-round fixes applied: - check_expected_fail_removed now uses _contains_tag_token for word-boundary matching (avoids false positives on partial tag names) - Diff expected-fail removal detection tracks flags at file level instead of per-hunk (fixes false negatives when tags span hunks) - parse_bug_refs filters out issue number zero - Redundant double error reporting eliminated (file-level check short-circuits the diff-level check) - run_quality_gate returns (errors, bug_refs) tuple to avoid redundant re-parsing in main() - Regex compilation cached via functools.lru_cache - Nox session no longer installs the full project (stdlib only) - CI checkout uses fetch-depth: 0 for reliable merge-base resolution Review-round 2 fixes applied: - _diff_has_expected_fail_removal_for_bug now requires the removed line to contain both the expected-fail tag and the specific bug tag (fixes false positives when two bugs share the same test file) - check_expected_fail_removed error messages use the correct tag prefix per file type (@tdd_bug_N for .feature, tdd_bug_N for .robot) - bool values rejected by bug-number validation guards in find_tdd_tests, check_expected_fail_removed, and _diff_has_expected_fail_removal_for_bug - File-read error handling catches UnicodeDecodeError alongside OSError (root-safe unreadable-file handling via invalid-UTF-8 test fixture) - Temp directory cleanup added to after_scenario hook in environment.py - 8 new Behave scenarios: bool type guards (2), co-located bug false-positive regression (1), run_quality_gate argument validation (3), and main() CLI entry point exit codes (2) Review-round 3 fixes applied: - Synthetic PR diff helper (_default_pr_diff_for_bug_refs) now auto-detects .robot vs .feature file type from the temp search tree and generates the matching diff format (fixes under-tested robot-format diff code path in multi-bug integration scenarios) - check_expected_fail_removed test step now filters files by bug tag via find_tdd_tests before checking (matches production path in run_quality_gate) - after_scenario temp directory cleanup no longer sets context.temp_dir = None (fixes cleanup conflict with cli_init_yes_flag_steps.py cleanup functions that run after hooks) - 2 new Behave scenarios: multi-line PR description parsing, and non-string pr_diff type guard for run_quality_gate ISSUES CLOSED: #629 |
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87a7ce35d7 |
feat(session): implement real LLM actor invocation in session tell
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Replace the M3 stub in `agents session tell` with real orchestrator actor
invocation via `SessionWorkflow.tell()`. The stub echoed a canned
`Acknowledged: ...` response without calling any LLM or actor; this
commit wires up the full pipeline:
Architecture:
- New `SessionWorkflow` (Application layer) orchestrates LLM invocation
for session tell. Accepts a `ProviderRegistry` and `ToolRegistry`;
falls back to `FakeListLLM` when no provider is configured.
- `LangChainSessionCaller` implements the `LLMCaller` protocol, building
history-aware LangChain message lists from the session conversation and
invoking the LLM via `ToolCallingRuntime.run_tool_loop()`.
- `TellResult` (Pydantic BaseModel) carries the assistant response plus
token usage (input_tokens, output_tokens, cost_usd, duration_ms).
Domain / service layer:
- `SessionActorNotConfiguredError` added to the session domain model;
raised when tell is invoked with no actor on the session and no
`--actor` override. Clear message; CLI exits with code 1.
- `SessionService.get_messages()` abstract method added (+ implementation
in `PersistentSessionService`) to load ordered message history.
A2A facade:
- `A2aLocalFacade` gains `message/send` and `message/stream` standard
A2A operation handlers that route to `SessionWorkflow.tell()`.
Total supported operations count: 42 → 44.
CLI:
- `session tell` command delegates to `_build_session_workflow()`
(patchable factory) instead of directly calling `SessionService`.
- Non-streaming: `SessionWorkflow.tell()` returns `TellResult`; output
includes a Usage panel (Rich/Plain) or a `usage` object (JSON/YAML).
- Streaming: `SessionWorkflow.tell_stream()` yields tokens; CLI prints
them via `console.print` (not raw `sys.stdout.write`).
- Token usage recorded via `SessionService.update_token_usage()` in
both paths.
Tests:
- New Behave feature `session_tell_llm.feature` (4 scenarios): real LLM
response persisted; streaming yields tokens; no-actor exits code 1;
`--actor` override resolves correctly.
- New Robot suite `session_tell_llm.robot` (4 tests): end-to-end with
stub LLM injected via monkey-patching `_resolve_llm`.
- Updated all existing `session tell` test steps to patch
`_build_session_workflow` returning a mock `TellResult` so tests
remain isolated from the LLM layer.
- Updated operation-count assertions (42 → 44) in
`a2a_cli_facade_integration`, `consolidated_misc`,
`m6_autonomy_acceptance` feature files and steps.
Cycle 7 (Review ID 8088) fixes:
- Blocker 4: Split `session_workflow.py` (was 801 lines) into two files:
`session_workflow.py` (467 lines) and `session_caller.py` (318 lines).
Extracted: `LangChainSessionCaller`, `extract_content`,
`extract_token_usage`, `estimate_cost`, `estimate_tokens`,
`history_to_langchain_messages`, and stub classes.
- Blocker 5: Route CLI streaming path through
`_facade_dispatch("message/stream", ...)` instead of directly
calling `workflow.tell_stream()`. The facade's
`_handle_message_stream` falls back to non-streaming with
`streamed: false` (acceptable for this milestone per the spec).
- Updated streaming test assertion to validate full response presence
(no longer checks token-by-token word positions, since the facade
fallback returns a complete message).
ISSUES CLOSED: #5784
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78be08870c
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fix(cli): validate actor provider field at correct config nesting level
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- Actor configuration in V3 is now obtained from the nested configuration parameter, according to the specification. - Removed the legacy V2 fallback support and the tests affected by that removal. Mocked existing steps to allow remaining V2 features to be covered/tested. - Fix add() to pass unsafe flag to add_v3() for proper unsafe actor handling - Add _extract_nested_v3_config() to extract provider/model from nested actors.<name>.config block before v3 schema validation - Remove v2 extraction test scenarios from consolidated_actor.feature that call removed _extract_v2_actor() and _extract_v2_options() methods - Update test YAML in actor_registry_spec_yaml_steps.py to exercise nested type detection (no top-level type field) - Add @tdd_issue_4300 regression test tag to existing spec-compliant actors map scenario ISSUES CLOSED: #4300 |
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6e1646d565 |
fix(plan): wrap plan tree JSON/YAML output in spec-required command envelope.\n\nISSUES CLOSED: #9163
# Conflicts: # CONTRIBUTORS.md |
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b588de18d6 |
fix(tui): rebase onto master and add CHANGELOG entry for prompt symbol fix (#6431)
Rebases the TUI prompt symbol fix onto the latest master, resolving conflicts with the TextArea→Input refactor and the dollar-prefix shell mode addition. Adds the missing CHANGELOG.md entry for #6431 and removes the now-obsolete tui_prompt_textarea feature/steps that tested the old TextArea-based implementation. ISSUES CLOSED: #6431 |
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15e72b8407
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fix(events): log full exception details in ReactiveEventBus.emit() error handler
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Add exc_info=True to the _logger.warning() call in the per-handler exception block of ReactiveEventBus.emit(). The handler already logged error=str(exc) (the exception message text), but omitted the traceback. With exc_info=True structlog now forwards the full traceback to the configured log output, giving developers the diagnostic detail needed to debug subscriber failures in production. Remove the @tdd_expected_fail tag from the traceback scenario in features/tdd_event_bus_exception_swallow.feature so that both TDD scenarios (#988) run as normal regression guards. Fix TDD tags in robot/tdd_e2e_implicit_init.robot: replace incorrect tdd_bug/tdd_bug_1023 tags with the canonical tdd_issue/tdd_issue_1023/ tdd_expected_fail tags so the tdd_expected_fail_listener properly inverts results while bug #1023 remains open. ISSUES CLOSED: #988 |
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bef7f3175b
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fix(tests): resolve integration test failures in behave parallel log filtering
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Fix the integration test helper so that it can load scripts/run_behave_parallel.py outside of nox sessions. The helper imports the runner module via importlib, which triggers the top-level from behave_pass_suppress_formatter import PassSuppressFormatter. When invoked from integration tests (or any non-nox context), neither behave_pass_suppress_formatter nor the behave_parallel package (created by noxfile.py for unit_tests) is on sys.path, causing a ModuleNotFoundError and all 6 Robot tests to fail with exit code 1. The fix adds scripts/ to sys.path before loading the runner module so that from behave_pass_suppress_formatter import PassSuppressFormatter resolves correctly. This mirrors the approach already used in noxfile.py's unit_tests session for the behave-parallel package. Also addresses review feedback: - Removes one blank line from scripts/run_behave_parallel.py to bring it to 499 lines, satisfying the project's <500-line code style rule. - Moves in-function behave imports (Configuration, StreamOpener) in features/steps/behave_parallel_log_filtering_steps.py to the top-level import block alongside the existing behave imports, complying with the project's rule that all imports must be at the top of the file. Refs: #10987 |
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5db663cb63 |
fix(actor): read actor_ref from NodeDefinition field in _detect_subgraph_cycles
Fix cross-actor subgraph cycle detection in the actor compiler by reading
actor_ref from the top-level NodeDefinition field instead of the config dict.
The _detect_subgraph_cycles(), _map_node(), and compile_actor() functions
were all reading node.config.get("actor_ref", "") instead of node.actor_ref.
Because actor_ref is a typed, validated Pydantic field on NodeDefinition (not
a key inside the untyped config dict), the old code always returned an empty
string, causing cross-actor cycle detection to silently fail and leaving the
system vulnerable to infinite recursion at runtime.
Changes:
- Fix all three call sites in src/cleveragents/actor/compiler.py
- Add Behave regression tests (features/actor_subgraph_cycle_detection.feature)
with @tdd_issue and @tdd_issue_1431 tags on all scenarios
- Add Robot Framework integration test (robot/actor_compiler.robot)
- Fix existing test helpers to use actor_ref as top-level field
- Add CHANGELOG entry
ISSUES CLOSED: #1431
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ad31e75af6 |
fix(cli): address reviewer feedback on actor remove --format option
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- Validate --format argument before any side effects; raise typer.BadParameter with a clear message for unsupported format values (fail-fast principle) - Pass normalised fmt_value (lowercased) to format_output instead of raw fmt to ensure consistent behaviour regardless of input casing - Rewrite robot/helper_actor_remove_cli.py to exercise the real CLI end-to-end via subprocess (no mocking); seeds a test actor via agents actor add, then removes it with --format json and validates the JSON envelope ISSUES CLOSED: #6491 |
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8384f53e28 |
test(cli): cover actor remove format regression (#6491)
Add Robot regression coverage for `actor remove --format json`, document the flag in the CLI synopsis, and record the fix in the changelog.\n\nISSUES CLOSED: #6491 |
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988a169831 |
docs: add InvariantReconciliationActor API docs, devcontainer discovery module guide, and mkdocs nav
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- docs/api/actor.md: Add InvariantReconciliationActor section documenting the built-in reconciliation actor introduced in v3.8.0, including the reconciliation algorithm, ReconciliationResult/ConflictRecord/ScopeInvariants data classes, standalone reconcile_invariants() function, DI registration, and failure behaviour. - docs/modules/devcontainer-discovery.md: New module guide for the devcontainer auto-discovery system (v3.8.0 fix #2615), covering DevcontainerDiscoveryResult, discover_devcontainers(), is_trigger_type(), monorepo named-config support, and gotchas. - mkdocs.yml: Add 'Devcontainer Auto-Discovery' to the Modules nav section, alongside shell-safety, uko-provenance, invariant-reconciliation, context-hydration, and git-worktree-sandbox module docs. - robot/coverage_threshold.robot: Add tdd_issue and tdd_issue_4305 tags to the Noxfile Contains Coverage Threshold Constant test case. ISSUES CLOSED: #4485 |
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cecca72b8e |
test(behave): Reduce the coverage level to 96.5%
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cc24d8c8ac |
fix(cli): remove legacy plan commands from help output
Completely removed all legacy plan commands from the CLI:
- Removed tell, build, new, current, cd, continue CLI commands
- Removed programmatic wrapper functions (tell_command, build_command, etc.)
- Removed legacy deprecation message
- Updated help text to indicate V3 Plan Lifecycle exclusively
- Removed stale references to tell/build in help output and command validation
Removes the legacy 'tell' and 'build' CLI shortcuts from main.py:
- Removed echo lines advertising tell/build commands
- Removed tell/build from valid_cmds list
- Removed tell/build from _LIGHTWEIGHT_COMMANDS frozenset
- These dead entries were preventing helpful error messages
Test infrastructure improvements:
- Event bus exception test: Patch the module-level logger during emit() so that
structlog.testing.capture_logs() can capture the logs. Without patching, the
module-level logger created at import time is not captured by the context manager.
- Session create/list commands: Suppress cleveragents.mcp logger to CRITICAL level
during JSON/YAML output formatting to prevent health check warnings with ANSI codes
from being written to stdout before JSON output, which breaks JSON parsing.
- Extended plan_cli_coverage_boost with scenarios for estimation_result,
invariants, execution_environment, validation_summary, and checkpoint
coverage in _plan_spec_dict
Documentation:
- Created docs/Legacy_to_V3_Guide.md with comprehensive migration instructions
- Updated CONTRIBUTING.md to document removal of legacy workflow
- Updated CHANGELOG.md to reference issue #4181 instead of PR #10800
ISSUES CLOSED: #4181
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57930c9fb3 |
fix(wf10): fixing more of the add/add problems
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Closes #10861 |
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e249afa30e
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fix(wf10_batch): fix add/add conflict
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Closes: #10861 |
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e6878c2c30 |
fix(audit): protect AuditService._ensure_session() with threading.Lock
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3e85ff797d |
chore(deps): remove duplicate langchain-anthropic dependency and clean up stale backup file
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- Remove duplicate langchain-anthropic>=0.2.0 from pyproject.toml dependencies - Remove stale robot/core_cli_commands.robot.backup file (not covered by gitignore) This cleanup eliminates a duplicate dependency declaration and removes an untracked backup file from the testing directory. ISSUES CLOSED: #0 |
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9b9bb80e05 |
fix(container): remove devcontainer-file from CONTAINER_RESOURCE_TYPES
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devcontainer-file is a read-only config file resource, not a running container. Including it in CONTAINER_RESOURCE_TYPES causes validate_container_available() to return True when only a config file is linked, even though no actual container is available. Closes #10598 |
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80bc9c552d |
test: restore and enhance e2e test coverage
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Fix malformed imports in helper_m1_e2e_verification.py and helper_m4_e2e_cli.py where 'from helpers_common import reset_global_state' was incorrectly inserted inside a parenthesized import block, causing Python syntax errors and breaking the lint and unit_tests CI gates. Also fix import ordering in helper_m2_e2e_verification.py, helper_m5_e2e_context.py, helper_m5_e2e_support.py, and helper_m5_e2e_verification.py to satisfy ruff I001 import-sort rules by placing helpers_common imports in the correct group alongside other local robot/ helper imports. ISSUES CLOSED: #8459 |
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7aa50ac489 |
fix(e2e): restore M5/WF14 tests broken by JSON envelope and stale config
- Add NO_COLOR=1 to E2E Suite Setup and Test Environment to prevent Rich from injecting ANSI escape codes into JSON output, which breaks Extract JSON From Stdout and JSON assertions in M5/WF14 acceptance tests. - Add reset_global_state() calls to all M1/M2/M4/M5 E2E verification helpers to clear Settings singleton, DI container, provider registry, and SQLAlchemy engine cache between parallel pabot worker runs. - Propagate NO_COLOR=1 at suite-setup level in E2E and integration test resource files so all Run Process subprocesses inherit clean terminal output mode. Root causes: 1. Missing NO_COLOR=1 caused Rich ANSI codes in CLI JSON output, making json.loads() failures in robot Extract JSON From Stdout 2. Stale Settings singleton carried provider keys and DB paths between pabot workers, causing UNIQUE constraint violations and stale config lookups in context policy and server mode E2E tests. Related: PR #9912 |
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90b6b2a43f |
fix(tui): fix Throbber Rejects Invalid Styles test indentation and add CHANGELOG entry
Use Fix Python Indentation + temp file in robot/tui_throbber.robot to correctly reconstruct indentation stripped by Robot Framework's Catenate keyword in the Throbber Rejects Invalid Styles test case. Add indentation_library.py to the suite's Library imports. Add CHANGELOG.md fix entry for #6357. ISSUES CLOSED: #6357 |
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7be0078963 | fix(tui): narrow exception handling and add test tags to throbber widget | ||
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f3ba86a520 |
fix(tui): restore LoadingThrobber widget and tui_throbber robot tests
The LoadingThrobber widget and its associated Robot Framework integration tests were developed on the feat/issue-6357-tui-loading-states branch but were never merged to master. This commit restores: - robot/tui_throbber.robot: Integration tests for the LoadingThrobber widget covering show/hide cycle, style switching, and invalid style rejection - src/cleveragents/tui/widgets/throbber.py: The LoadingThrobber implementation with rainbow and quotes animation styles - src/cleveragents/tui/quotes.py: Quote loader module for the throbber - src/cleveragents/tui/data/throbber_quotes.txt: Curated quote collection The failing test 'Throbber Rejects Invalid Styles' in robot/tui_throbber.robot was identified by UAT testing [AUTO-UAT-3] as failing because the production code (LoadingThrobber) was missing from master while the test file was expected to be present. ISSUES CLOSED: #6357 |
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8dc55655e9 |
feat(actor): make built-in actors virtual, resolved on-demand from provider registry
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Replace the DB-persistence approach for built-in actors with in-memory virtual resolution. Built-in actors (e.g. openai/gpt-4o, anthropic/claude-sonnet) are now resolved on-demand from ProviderRegistry at query time and merged with persisted custom actors — no database writes occur for built-in actors. Key changes: - Add ActorRegistry._resolve_virtual_builtin_actors(): generates virtual Actor objects in-memory from configured providers (is_built_in=True, id=None) - ActorRegistry.list()/list_actors(): merges virtual built-ins with custom DB actors; custom actors win on name collision; result sorted alphabetically - ActorRegistry.get()/get_actor(): DB-first, virtual built-in fallback, NotFoundError if neither - ActorRegistry.remove()/remove_actor(): rejects virtual built-in names with ValidationError - ActorRegistry.set_default_actor(): stores only the actor name string via new actor_preferences singleton table; no actor row created for virtual built-ins - ActorRegistry.get_default_actor(): reads preference name, resolves via DB→virtual chain, returns actor with is_default=True - Remove ensure_built_in_actors() entirely — 20+ call sites cleaned up including plan.py - Remove ActorRepository.upsert_built_in() — no longer needed - Remove is_built_in from ActorModel DB column (kept on Actor domain model for virtual actors) - New Alembic migration m10_001_virtual_builtin_actors: drops is_built_in column, adds actor_preferences singleton table - Add ActorService.set_default_actor_name() and get_default_actor_name() for preference storage without requiring a DB actor row - Update 15+ Behave step files and 5 feature files; add new features/virtual_builtin_actors.feature with 8 scenarios covering list, show, remove, set-default, get-default, no-DB-writes guarantees - Rewrite tests/actor/test_registry_builtin_yaml.py: TestEnsureBuiltInActorsWithYaml → TestResolveVirtualBuiltinActors plus new TestListActors, TestGetActor, TestRemoveActor, TestDefaultActor test classes Quality gates: lint ✓, typecheck ✓, unit_tests ✓ (15674 scenarios), coverage ✓ (97.10%), integration_tests ✓ (1997 tests) ISSUES CLOSED: #10923 |
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0127b6f745 |
fix(reactive): synthesise execution route for type:llm actors in ReactiveConfigParser
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When _build_from_v3() creates agents for type:llm or type:tool actors, and when _build() processes the nested actors: map format (cleveragents version 3.0 YAML), no RouteConfig is produced. run_single_shot() then falls through to the RxPY stream path which has no subscribers, causing the LLM to never be invoked and the command to silently return empty output. Fix A: after creating the agent in _build_from_v3() for type:llm/tool, call _synthesise_single_node_route() to add a graph route with a message_router node (catch-all rule), an actor node, and an edge to "end". Fix B: after the agent loop in _build(), if rc.agents is non-empty and rc.routes is empty, synthesise a default route using the cleveragents default_actor (or the first agent). Fix C: in _build(), the nested actors: map path now translates the v3 actor: "provider/model" key into separate provider and model keys in the agent config dict. SimpleLLMAgent._resolve_llm() expects these keys; without this translation, the LLM provider defaults to None (OpenAI) regardless of the configured actor reference. 13 BDD scenarios in actor_v3_route_synthesis.feature: - Flat v3 LLM/tool builds produce non-empty routes - Route structure has router + actor nodes with edge to end - Nested actors: map format produces routes, respects default_actor - Explicit routes are not duplicated - run_single_shot returns non-empty output with synthesised routes - Graph actor regression guard - Nested actors: map with actor key infers provider and model - Nested actors: map with actor key without slash sets model only - Nested actors: map with explicit provider/model keeps them unchanged ISSUES CLOSED: #10807 |
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790eb6f001 |
test(data): introduce dynamic data generation and externalize test data in Behave and Robot Framework suites
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- Added Faker dependency to pyproject.toml for dynamic test data generation - Created features/test_data_factory.py with TestDataGenerator and ContextFragmentFactory classes for Behave tests - Created robot/helper_test_data_factory.py with RobotTestDataGenerator and factory classes for Robot Framework tests - Created features/test_data_loader.py to load externalized test data from JSON files - Created features/fixtures/test_data_samples.json with realistic test data samples - Updated robot/helper_acms_fusion.py to use dynamic test data generation instead of hardcoded values like "alpha" and "beta" - All quality gates passing: lint, typecheck, unit tests, integration tests, coverage ≥ 97% ISSUES CLOSED: #9048 |
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d512123d1c |
fix(actor): support v3 Actor YAML schema in CLI registration and execution
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The actor CLI was ignoring the v3 ActorConfigSchema format, preventing spec-compliant actors with type/route/skills/lsp fields from being registered or executed. Three components were fixed: ActorConfiguration.from_blob() now detects v3 format (top-level "type" key with value llm/graph/tool) and extracts provider from the model string, falling through to v2 extraction when v3 does not match. ActorRegistry.add() now routes v3 YAML through full ActorConfigSchema validation, persists description/skills/lsp in the config blob, and compiles graph actors with compile_actor() storing metadata. Legacy v2 YAML continues through the original path unchanged. ReactiveConfigParser._build() now synthesises reactive agents and graph routes from v3 actor data so that agents actor run can execute v3 actors through the existing ReactiveCleverAgentsApp pipeline. ISSUES CLOSED: #6283 |
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05b58630bf |
style(a2a): apply ruff format to integration test helper
Apply ruff format to robot/helper_a2a_session_plan_lifecycle_integration.py to fix CI lint failure. Changes are purely formatting (whitespace, line wrapping) with no logic modifications. ISSUES CLOSED: #10032 |
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d306e6e33c |
test(a2a): add integration tests for full A2A session and plan lifecycle
- Added robot/a2a_session_plan_lifecycle_integration.robot: Robot Framework integration test suite with 7 test cases covering the full A2A session and plan lifecycle, event queue publish/subscribe, guard enforcement (budget cap, tool call limit, denylist), and plan rollback with session state consistency. - Added robot/helper_a2a_session_plan_lifecycle_integration.py: Helper script with real service instances (no mocks) using in-memory SQLite, wiring up A2A facade, session service, plan lifecycle service, event queue, and autonomy guardrail service. ISSUES CLOSED: #10032 |