* fix: wrapper architecture gaps - async-unsafe bridges, unguarded tools.py, loop-bound primitives (fixes#1582)
- Gap 1: Replace asyncio.run() cold-starts with _async_bridge.run_sync()
in _webhook_approval.py, _http_approval.py, and integrations/base.py
- Gap 2: Add PRAISONAI_ALLOW_LOCAL_TOOLS opt-in for tools.py execution
across agents_generator.py, cli/main.py, and api/call.py
- Gap 3: Move AsyncAgentScheduler._stop_event to _ensure_async_primitives()
lifecycle for proper loop binding consistency
Co-authored-by: MervinPraison <[email protected]>
* fix: address P1/P2 regressions from issue #1582 architectural review
- Fix tools/ directory loading regression in agents_generator.py (iterate py files vs pass directory)
- Fix AsyncScheduler stop() race condition (remove _ensure_async_primitives call that replaces live events)
- Fix unreachable success message in cli/main.py (move outside else branch)
- Fix brittle path validation in _safe_loader.py (use Path.relative_to vs string prefix)
- Fix exception message leakage in api/call.py (sanitize raised errors)
- Fix undefined logger in cli/main.py recipe tools handling
- Fix function filtering to exclude imported callables
- Fix tool class extraction to handle per-class errors
Co-authored-by: Mervin Praison <[email protected]>
* test: update test_async_agent_scheduler tests to call _ensure_async_primitives()
Five tests bypass start() and manipulate _stop_event directly. After this
PR's Gap 3 fix moved asyncio primitive creation from __init__ to
_ensure_async_primitives() (the architecturally-correct lifecycle per
AGENTS.md), those tests fail with 'NoneType has no attribute set'.
Add an explicit scheduler._ensure_async_primitives() call in each of the
5 affected tests so they get a fully-initialized scheduler without going
through start().
Verified: all 36 scheduler + webhook_approval tests pass.
---------
Co-authored-by: praisonai-triage-agent[bot] <272766704+praisonai-triage-agent[bot]@users.noreply.github.com>
Co-authored-by: MervinPraison <[email protected]>
Co-authored-by: Cascade <[email protected]>
* fix(tests): mark profiler timing tests with @allow_sleep (follow-up #1580)
The merged version of PR #1580 tightened the profiler-test bounds from
'> 0' to '>= 5' ms, but failed to opt out of conftest's autouse
'fast_sleep' fixture (tests/conftest.py:183) which clamps time.sleep
to 1ms. Result: test_api_call_context_manager and test_streaming_tracker
fail with ~1.1ms duration on every run.
Add the documented opt-out marker (@pytest.mark.allow_sleep) so the
tests get a real 50ms sleep and the >= 5ms assertion is meaningful.
Verified locally: all 12 sandbox + profiler tests pass.
* refactor(tests): move allow_sleep explanations to docstrings
Per Gemini code review feedback, moved inline comments explaining the
@pytest.mark.allow_sleep marker into test docstrings for better PEP 257
compliance. The marker opts out of conftest fast_sleep fixture clamping.
Co-authored-by: Mervin Praison <[email protected]>
---------
Co-authored-by: Cascade <[email protected]>
Co-authored-by: praisonai-triage-agent[bot] <272766704+praisonai-triage-agent[bot]@users.noreply.github.com>
Co-authored-by: Mervin Praison <[email protected]>
* fix(tests): clear 25 pre-existing test-infrastructure failures
Targeted, test-only cleanup. **No production code changes.**
Confirmed via triage that none of the 67 wrapper+core SDK test failures
post-v4.6.32 are functional regressions from PRs #1577/#1578/#1579 — all
are stale tests, missing skip guards, fixture bugs, or timing flakes
that pre-date the release.
This commit fixes the four highest-confidence categories:
* sandbox/test_sandlock_sandbox.py: macOS resolves /var/folders via the
/private/var/folders symlink, so _safe_sandbox_path() returns the
realpath form while sandbox._temp_dir holds the unresolved mkdtemp
output. Compare via os.path.realpath() so the assertion holds on both
macOS and Linux. Implementation is correct and unchanged.
* test_profiler_advanced.py: relax flaky timing bounds for
test_api_call_context_manager and test_streaming_tracker. time.sleep
precision is too coarse on busy CI runners to reliably exceed 10ms
with a 10ms sleep; bumped to 50ms and asserted only that the recorded
duration is positive. Matches AGENTS.md guidance that tests must not
depend on timing.
* test_push_client.py: PushClient._send checks
self._transport.is_connected (not the internal _connected flag), so
the mock transport must report itself as connected. The fixture set
c._connected=True but forgot mock_transport.connected=True, causing
every send-path test to raise ConnectionError. Single-line fixture
fix unblocks 8 tests.
* test_ag2_adapter.py: PR #1561 refactored framework validation to
delegate to FrameworkAdapter.is_available(), which performs a real
ag2 import. Existing tests still patch the legacy AG2_AVAILABLE flag
and so fail with ImportError when ag2 is not installed. Added
pytest.importorskip('ag2') at module scope to skip the suite when
the SDK is missing — re-enable by updating mocks to patch the
adapter directly.
Verified locally:
- 12 sandbox + profiler tests: PASS (was 3 failing)
- 10 push_client tests: PASS (was 8 failing)
- 14 ag2 tests: SKIP when ag2 missing (was 14 failing)
Net wrapper-suite improvement: 25 fewer failures (38 -> 13).
* fix(tests): strengthen timing assertions and sandbox path validation
Addresses reviewer feedback from CodeRabbit:
- Profiler tests: Change timing assertions from >0 to >=5ms to catch unit errors
- Sandbox tests: Tighten path prefix assertion with os.sep for directory boundaries
These changes improve test reliability and catch potential regressions while
maintaining tolerance for CI timing variations.
Co-authored-by: Mervin Praison <[email protected]>
---------
Co-authored-by: Cascade <[email protected]>
Co-authored-by: praisonai-triage-agent[bot] <272766704+praisonai-triage-agent[bot]@users.noreply.github.com>
Co-authored-by: Mervin Praison <[email protected]>
* fix(wrapper): restore #1561 auto-discovery dispatcher in __main__.py (closes#1576)
When #1548 merged at d0d87a74, the conflict in __main__.py was resolved
by taking the PR's heuristic-based dispatcher (_is_legacy_invocation),
discarding the strictly-better auto-discovery dispatcher introduced in
#1561 (4b1103c6). Two pre-existing tests have been red on main since:
FAILED test_auto_lazy_loading.py::TestThreadSafety::test_typer_commands_concurrent_calls_all_return_set
FAILED test_auto_lazy_loading.py::TestThreadSafety::test_typer_commands_failure_does_not_poison_cache
Both fail with: AttributeError: module 'praisonai.__main__' has no
attribute '_get_typer_commands'.
Restore __main__.py to the version from 4b1103c6 (#1561). The restored
dispatcher reintroduces:
- _typer_commands_cache + _typer_commands_lock: thread-safe cached
Typer command discovery via Click introspection.
- _get_typer_commands(): defensive logger.warning + non-poisoning
cache on failure (next caller can retry).
- _find_first_command(argv): flag/value-flag aware first-positional
finder.
- _run_typer / _run_legacy: clear separation of dispatch paths with
explicit argv save/restore.
- main() routing rules: 1) --version, 2) --help, 3) no argv,
4) first arg in Typer command set, 5) everything else -> legacy.
Routing-by-discovered-command-set is strictly better than the heuristic:
new Typer commands are picked up automatically with no opt-in, and
discovery is fail-loud at dispatch time (register_commands() inside
_run_typer) while the cache layer is best-effort.
Behavior preserved from #1548:
- --version still short-circuits before importing praisonai.cli.*
(verified via new sys.modules eviction test).
- register_commands() exceptions still propagate from _run_typer
(no silent degradation).
test_main_dispatcher.py rewritten to cover the restored API:
- TestFindFirstCommand (7 tests)
- TestGetTyperCommandsCache (4 tests)
- TestVersionShortCircuit (3 tests, incl. sys.modules-eviction proof)
- TestMainRouting (8 tests)
- TestRunLegacyArgvRestoration (3 tests with discriminating argv[0])
- TestRunTyperArgvRestoration (1 test with discriminating argv[0])
Total: 26 tests, all green.
Verification:
- test_auto_lazy_loading.py::TestThreadSafety: 5/5 pass (was 3/5).
- test_main_dispatcher.py: 26/26 pass.
- test_async_bridge.py: 7/7 pass.
- Smoke probe: clean exit; daemon thread invariants intact.
- Broad sweep (1417 tests): 1412 pass / 5 fail / 2 skip. All 5
failures are pre-existing on main, verified by running
test_gateway_install_failure on both branches.
Fixes#1576.
* fix(review): address all reviewer findings on #1577
CodeRabbit Major #1 (cli/app.py partial-registration cache poisoning):
register_commands() flipped _commands_registered=True BEFORE running its
50+ command imports and app.add_typer() calls. If any import failed
mid-flight the sentinel stayed set, and a later caller would
short-circuit and dispatch against a half-built command tree. Move the
sentinel assignment to the END of register_commands(), and document why
in the docstring + inline comment. (In practice the bug is largely
mitigated today by the unconditional register_commands() call at module
import time on line 683 — but defense in depth costs nothing and the
invariant is now correct.)
CodeRabbit Major #2 (_run_typer race against partial registration):
_run_typer() called register_commands() WITHOUT holding the new
_typer_commands_lock, so a concurrent _get_typer_commands() caller
could observe partial state. Hold the lock around register_commands()
in _run_typer too. CRITICAL: do NOT route through _get_typer_commands()
itself, because that method intentionally swallows exceptions to keep
the cache best-effort — wrapping _run_typer in that swallow would
silently downgrade real registration errors (e.g. ImportError from a
missing optional dep) to Typer's 'no commands' behaviour. Inline
comment spells this out.
Greptile P2 #1 (test_typer_registration_failure_propagates removed):
The deleted test pinned the fail-loud guarantee from #1577's
description. Re-introduced as TestTyperRegistrationFailureFailsLoud
with two cases (ImportError and RuntimeError both propagate) so a
future refactor that wraps register_commands() in defensive try/except
will fail CI.
Greptile P2 #2 (missing trailing newline at EOF in __main__.py):
Trivial; added.
Verification:
- test_main_dispatcher.py: 28/28 pass (was 26)
- test_auto_lazy_loading.py::TestThreadSafety: 5/5 pass
- test_async_bridge.py: 7/7 pass
- Smoke probe: clean exit, daemon thread invariants intact.
---------
Co-authored-by: MervinPraison <[email protected]>
* fix(security): gate template tools.py autoload behind PRAISONAI_ALLOW_TEMPLATE_TOOLS
create_tool_registry_with_overrides() previously walked into the current
working directory and the recipe template directory, exec_module()-ing
any tools.py file it found. When a recipe is fetched from a remote
registry (e.g. GitHub via the recipe-share workflow), this gives an
unauthenticated attacker arbitrary code execution in the server process
the moment the recipe is loaded \u2014 the tools.py runs at import time
before any allow-list / sandbox / approval check fires.
Disable the implicit autoload by default. The legacy behaviour is
preserved for trusted local workflows by setting the env var
PRAISONAI_ALLOW_TEMPLATE_TOOLS=1 (also accepts true/yes/on, case
insensitive).
Explicit, opt-in entry points are unchanged and remain the supported
way to load custom tool modules:
- override_files=[...] # explicit file paths
- override_dirs=[...] # explicit directory scan
- tools_sources=... # TEMPLATE.yaml directive
- registry={...} # caller-built registry
Both autoload sites are gated:
- create_tool_registry_with_overrides(): cwd/tools.py + template_dir/tools.py
- resolve_tools(): template_dir/tools.py
Tests
-----
Added src/praisonai/tests/unit/templates/test_tool_override_autoload_gate.py
(5 tests). The fixture writes a malicious tools.py that drops a marker
file in tempdir and asserts the marker DOES NOT appear by default:
- test_template_tools_py_not_executed_by_default
- test_resolve_tools_does_not_execute_template_tools_py_by_default
- test_cwd_tools_py_not_executed_by_default
- test_opt_in_env_var_re_enables_autoload (legacy compat)
- test_explicit_override_files_still_work_without_opt_in (regression)
Updated test_templates.py::test_tools_py_loaded to set
PRAISONAI_ALLOW_TEMPLATE_TOOLS=1 via monkeypatch (the test pins the
legacy contract; that contract now requires explicit opt-in).
Verified: 83/83 in src/praisonai/tests/unit/test_templates.py +
src/praisonai/tests/unit/templates/ pass.
* fix(review): address coderabbit + greptile findings on #1579
CodeRabbit Minor (blind 'except Exception: pass' in implicit-load
paths):
The three implicit-load sites (cwd autoload, template autoload in
create_tool_registry_with_overrides, template autoload in
resolve_tools) silently swallowed every failure, making it impossible
for opt-in operators to debug a broken tools.py. Add a module-level
'logger = logging.getLogger(__name__)' and replace each 'pass' with
'logger.debug("failed to autoload ...", exc_info=True)'. The
skip-on-error contract is preserved (these blocks are best-effort by
design); only the silent failure mode is removed.
Greptile P2 (opt-in test misses CWD autoload path):
test_opt_in_env_var_re_enables_autoload only verified the template_dir
opt-in path. Added test_opt_in_env_var_re_enables_cwd_autoload as a
parallel test for the cwd path, so legacy-behaviour-preservation
coverage is symmetric with the default-deny tests
(test_cwd_tools_py_not_executed_by_default vs the new opt-in mirror).
Verification:
- test_tool_override_autoload_gate.py: 6/6 pass (was 5)
- test_templates.py: 78/78 pass (no regressions)
---------
Co-authored-by: MervinPraison <[email protected]>
A URL such as 'http://127.0.0.1:6666\\@1.1.1.1' parses with hostname
'1.1.1.1' via urllib.parse.urlparse but is dispatched to '127.0.0.1' by
requests/httpx. Hostname-based SSRF allow/deny checks that trust
urlparse alone can therefore be smuggled past with a backslash in the
authority section, exposing localhost services. ASCII control characters
in the URL (newline, NUL, DEL, etc.) can produce similar parser
disagreement and HTTP request smuggling.
Reject any URL containing a backslash anywhere or any ASCII control
character (codepoint < 0x20 or == 0x7f) before urlparse runs. Also
reject non-string input early.
Tests in tests/unit/tools/test_spider_url_validation.py cover:
- the real-world advisory payload 'http://127.0.0.1:6666\\@1.1.1.1'
- backslash anywhere in the URL
- NUL and CR/LF control characters
- non-string (None / int) input
- regression: normal public URLs still allowed
- regression: existing loopback/localhost block still fires
All 6 tests pass; the existing _validate_url contract for IP/private/
metadata/internal-domain blocking is preserved.
Co-authored-by: MervinPraison <[email protected]>
* fix(wrapper): _async_bridge daemon thread + tests for unified CLI dispatcher
Two small wrapper-layer fixes that surfaced during the post-#1548 review:
1) src/praisonai/praisonai/_async_bridge.py
- Mark the background event-loop thread as daemon=True so short-lived
scripts (CLI commands, smoke tests, single-shot agent invocations)
exit cleanly. The previous daemon=False thread, combined with
atexit-registered shutdown, allowed the interpreter to hang for the
full PRAISONAI_RUN_SYNC_TIMEOUT (default 300s) on exit when the
loop's shutdown coroutine couldn't drain.
- Drop the atexit registration that races interpreter shutdown.
Long-running servers (gateway, a2u, mcp_server) can still call the
public shutdown() hook explicitly to cancel in-flight tasks.
- DRY the loop+thread bring-up into _spawn_locked() shared by get()
and get_unlocked().
- Tighten run_sync(): raise RuntimeError loudly when called from
inside a running loop (was previously a dead 'running' var followed
by a blocking fut.result that would deadlock the caller's loop).
2) src/praisonai/tests/unit/cli/test_main_dispatcher.py (new, 20 tests)
- Cover _is_legacy_invocation: empty/flag/prompt/yaml-existing/yaml-
missing/typer-subcommand cases.
- Cover --version / -V short-circuit path and verify it does not
import the Typer app or legacy runner.
- Cover legacy routing for free-text prompts and existing YAML files,
including PraisonAI.main() returning False -> exit code 1, and
sys.argv restoration after dispatch.
- Cover Typer routing for no-args, --help, subcommand, and ImportError
during register_commands() (must propagate; fail-loud design).
- Cover SystemExit propagation from Typer with non-zero code.
All tests run in <0.4s. Smoke test exits cleanly (was hanging until
PRAISONAI_RUN_SYNC_TIMEOUT before the daemon=True fix).
* fix: address reviewer feedback
- Generalize docstring references to avoid maintenance overhead
- Improve test coverage for argv restoration by using discriminating values
Co-authored-by: Mervin Praison <[email protected]>
* fix(review): layer remaining greptile P2 + coderabbit major fixes; relocate smoke
Builds on triage-agent commit 79eec467 (which addressed gemini medium and
attempted greptile P2 #1) by addressing the still-open findings and
fixing two issues introduced by that commit.
1) _async_bridge._spawn_locked: enforce 'caller must hold the lock'
invariant via 'assert self._lock.locked()'
(greptile P2 #2: 'get_unlocked() is now a transparent alias \u2014
contract is unenforced').
2) test_main_dispatcher.test_version_does_not_import_typer_app:
replace mock.patch('praisonai.cli.app.register_commands') with
sys.modules eviction of all praisonai.cli.* modules. mock.patch
with a dotted target imports the target module on entry, which
defeats the 'no Typer app import on --version' invariant the test
claims to verify (coderabbit major; verified via
docs.python.org/3/library/unittest.mock.html).
3) test_main_dispatcher.test_{legacy,typer}_path_restores_argv:
set sys.argv[0] to a non-'praisonai' value. The dispatcher rewrites
sys.argv to ['praisonai'] + sys.argv[1:] inside the try block, so
the previous argv values (and the variant in 79eec467 with
'--extra-arg') were identical to the rewrite \u2014 the assertion
passed regardless of whether 'finally' restored argv. Differing
argv[0] makes the assertion catch a missing finally clause
(greptile P2 #1: 'finally-restore tests had no discriminating power').
4) test_async_bridge.py:
- Removed the file at repo root (clutter; not under
src/praisonai/tests/; uses 'from src.praisonai.praisonai...'
source-tree import that won't work for installed users).
- Added src/praisonai/tests/unit/test_async_bridge.py as proper
unittest.TestCase tests with the helper renamed from 'test_coro'
to '_coro' so pytest does not auto-collect it as a test
(coderabbit major on the original file).
- Added a regression test for the new _spawn_locked() lock assert.
- Coroutine .close() on the RuntimeError path so '-W error::RuntimeWarning'
stays clean.
Verified: 27/27 pass (20 dispatcher + 7 async bridge), no warnings.
---------
Co-authored-by: MervinPraison <[email protected]>
Co-authored-by: praisonai-triage-agent[bot] <272766704+praisonai-triage-agent[bot]@users.noreply.github.com>
Co-authored-by: Mervin Praison <[email protected]>
The file was at the package-root tests/ tree which is not a valid pytest root for this repo. The proper sibling location is src/praisonai/tests/unit/integrations/ alongside test_managed_agents.py and test_base_integration.py. The file imports from praisonai.integrations (HostedAgent / LocalAgent), so it belongs with the wrapper-layer tests.
- Fix Gap 1: Route async tool execution through safety pipeline
* _achat_completion now calls execute_tool_async() instead of direct tool(**args)
* Ensures all safety checks (approval, timeout, circuit breaker) apply to async path
- Fix Gap 2a: Add guardrail validation to sync execution path
* Port guardrail validation logic from arun_task to run_task
* Ensures consistency between sync and async task execution
- Fix Gap 2b: Fix verbose mode to use proper process orchestration
* Replace direct task iteration with callback-based display
* Maintains process orchestration (workflow/hierarchical/sequential) in verbose mode
- Fix Gap 3: Implement proper error classification and retry handling
* Replace Exception swallowing with structured LLMError classification
* Add recursion depth limit to context overflow recovery
* Set failed task status and check dependencies in sequential process
* Use task retry_delay policy instead of hardcoded sleep(1)
Fixes#1570🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: MervinPraison <[email protected]>
This commit addresses three critical production gaps in the wrapper layer:
1. **Gap 1: Import-time global warnings patch** (cli/main.py:43)
- Move warnings.showwarning patch from import-time to explicit opt-in
- Add install_warning_filters() called only when CLI starts
- Add atexit cleanup with _uninstall_warning_filters()
- Library users now get unpatched warnings module
2. **Gap 2: Single-slot OpenAI client thrashing** (auto.py:236-258)
- Replace single-slot cache with bounded LRU using OrderedDict
- Support up to 8 concurrent clients (_OPENAI_CLIENT_CACHE_MAX)
- Multi-tenant safe: each (api_key, base_url) gets own client
- Proper LRU eviction with connection cleanup
3. **Gap 3: Unbounded profiler buffers** (profiler.py:233-304)
- Replace unbounded List with bounded deque(maxlen=10000)
- Configurable via PRAISONAI_PROFILE_MAX environment variable
- All record buffers bounded: _timings, _imports, _flow, _api_calls, etc.
- Maintain backward compatible singleton pattern
All fixes follow AGENTS.md principles:
- No global singletons ✓
- Multi-agent safe by default ✓
- Production-ready, safe by default ✓
- No perf impact: lazy imports, optional deps ✓
Co-authored-by: MervinPraison <[email protected]>
* fix: add proper exception handling and cleanup in AsyncAgentScheduler
- Added try/finally block in _run_schedule() to ensure is_running flag is always cleared
- Fixed exception handling in stop() method to properly catch and log non-cancelled exceptions
- Ensured is_running=False is always set in finally block to prevent scheduler state corruption
Fixes#1565
* fix: improve exception handling idiom and add unit tests for AsyncAgentScheduler
- Replace awkward `except (CancelledError, Exception) as e: if not isinstance(...)`
with idiomatic two separate `except` clauses in stop()
- Add 18 unit tests in test_async_agent_scheduler.py covering:
- stop() finally block always clears is_running (normal exit, task exception)
- stop() timeout/cancel path handles CancelledError silently
- stop() timeout/cancel path logs non-CancelledError exceptions
- _run_schedule() finally block clears is_running on stop event, exception, and cancellation
- Full start/stop lifecycle, stats, execute_once"
Agent-Logs-Url: https://github.com/MervinPraison/PraisonAI/sessions/fbb94408-0f2b-46a5-9ae5-1daae9a5c683
Co-authored-by: MervinPraison <[email protected]>
* fix: handle all exceptions from wait_for in AsyncAgentScheduler.stop()
- Add exception handling for non-timeout exceptions from asyncio.wait_for()
- Catches CancelledError (treats as expected during shutdown)
- Catches other exceptions and logs them instead of propagating
- Update test to verify new logging behavior instead of expecting exception propagation
- Resolves issue identified by Greptile and CodeRabbit reviewers
Co-authored-by: Mervin Praison <[email protected]>
---------
Co-authored-by: praisonai-triage-agent[bot] <272766704+praisonai-triage-agent[bot]@users.noreply.github.com>
Co-authored-by: copilot-swe-agent[bot] <[email protected]>
Co-authored-by: MervinPraison <[email protected]>
Co-authored-by: Mervin Praison <[email protected]>
* fix: core SDK architectural gaps - retry jitter, timeout enforcement, configurable exception handling (fixes#1553)
- Gap 2: Added jitter to LLM retry delays in error_classifier.py to prevent thundering herd in multi-agent setups
- Gap 1: Added missing timeout enforcement to sync workflow() method for feature parity with async version
- Gap 3: Added configurable failure policies (fail_on_callback_error, fail_on_memory_error) to task execution
- Improved error visibility in _verify_memory_ready() and store_in_memory() methods
- All changes maintain backward compatibility and follow protocol-driven core SDK principles
Co-authored-by: MervinPraison <[email protected]>
* fix: correct failure policy enforcement and improve retry jitter
- Fix P1 critical bug: failure policies now properly enforced
- agents.py: respect fail_on_callback_error and fail_on_memory_error flags
- task.py: memory operation failures now re-raise when configured
- task.py: attach non_fatal_errors before re-raising exceptions
- Improve retry jitter to prevent instant retries
- error_classifier.py: use equal jitter with minimum floor for RATE_LIMIT and TRANSIENT
- prevents zero-delay retries that could worsen thundering herd issues
- Replace problematic root-level test with proper pytest structure
- Remove test_architectural_fixes.py with hardcoded paths
- Add comprehensive unit tests under tests/unit/ for all three gaps
- Tests verify jitter behavior, failure policy enforcement, timeout configuration
Co-authored-by: Mervin Praison <[email protected]>
* fix: correct failure policy attach + update legacy retry tests for jitter
Two follow-up fixes for PR #1554:
1. task.py:778 — `hasattr(task_output, 'non_fatal_errors')` was always True
(Pydantic field defaults to None). Replaced with
`getattr(task_output, 'non_fatal_errors', None) is None` so non_fatal_errors
are correctly attached when no callback re-raise occurred. Verified by the
PR's own test_non_fatal_errors_attached_to_output test.
2. tests/unit/llm/test_error_classifier.py — the legacy TestRetryLogic class
asserted exact deterministic delay values, which broke after issue #1553's
intentional jitter for thundering-herd prevention. Updated the assertions
to assert the documented [base_delay, exp_max] range. The new dedicated
test_error_classifier_jitter.py covers the variance/floor invariants.
Verified: 33/33 affected tests now pass. Other failures (managed_backend,
permissions, learn_gaps, thread_safety) are pre-existing on main.
---------
Co-authored-by: praisonai-triage-agent[bot] <272766704+praisonai-triage-agent[bot]@users.noreply.github.com>
Co-authored-by: MervinPraison <[email protected]>
Co-authored-by: Cascade <[email protected]>
- Fix test_managed_agent_compute_provider_errors to expect DeprecationWarning instead of ValueError
- Add 3-layer skip guards to all 4 runtime example scripts for clean exit without credentials
- Preserve backward compatibility while implementing the HostedAgent/LocalAgent architectural split
Co-authored-by: praisonai-triage-agent[bot] <272766704+praisonai-triage-agent[bot]@users.noreply.github.com>
Co-authored-by: Mervin Praison <[email protected]>
* fix: ManagedAgent(provider=) overload conflates hosted-runtime vs LLM-routing — propose HostedAgent / LocalAgent split (fixes#1549)
- Create new HostedAgent class for hosted runtimes (Anthropic managed infrastructure)
- Create new LocalAgent class for local loops with optional cloud compute
- Update ManagedAgent factory with deprecation warnings for LLM routing overload
- Add proper error handling for compute provider misuse
- Maintain full backward compatibility with all existing imports
- Update examples to demonstrate new clear semantics
- Add comprehensive tests for new backend semantics
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-authored-by: MervinPraison <[email protected]>
* examples: update managed-agents provider examples to use new HostedAgent/LocalAgent classes
- Create new canonical examples demonstrating HostedAgent vs LocalAgent usage
- Update existing examples to use clear semantic distinctions
- Add runtime_hosted_anthropic.py for true managed runtime usage
- Add runtime_local_*.py examples for local execution with different LLMs
- Update all_providers.py to use LocalAgent with compute backends
- Update local_basic.py to use LocalAgent semantics
- Add comprehensive test suite for backend semantics
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-authored-by: MervinPraison <[email protected]>
* fix: resolve P1 backward compatibility and routing issues
- Fix ManagedAgent compute provider routing: maintain backward compatibility
for e2b/modal/etc by routing to LocalManagedAgent with deprecation warning
instead of ValueError (fixes hard breaking change)
- Fix LocalAgent provider preservation: preserve provider value for LLM routing
to maintain _resolve_model() prefix behavior (ollama/, gemini/)
- Fix spurious deprecation warnings: auto-detected provider=local no longer
triggers warnings for users who never passed provider=
- Remove unused os import from hosted_agent.py
- Improve error messages with provider-specific guidance
- Fix test fragility with exact warning counts and identity checks
Addresses all P1 issues identified by Greptile and CodeRabbit reviewers.
Co-authored-by: Mervin Praison <[email protected]>
---------
Co-authored-by: praisonai-triage-agent[bot] <272766704+praisonai-triage-agent[bot]@users.noreply.github.com>
Co-authored-by: MervinPraison <[email protected]>
* fix: add missing praisonai_platform.db module (fixes#1542)
- Create missing db/ directory with __init__.py, base.py, and models.py
- Add all required database models: User, Workspace, Agent, Issue, etc.
- Implement SQLAlchemy base configuration with init_db, get_session
- Fix package imports with lazy loading in __init__.py
- Resolves ModuleNotFoundError that prevented tests from running
Tests now begin executing instead of failing at import.
Co-authored-by: praisonai-triage-agent[bot] <praisonai-triage-agent[bot]@users.noreply.github.com>
* fix: address critical P1 runtime issues found by reviewers
- Fix User model field mismatch: change username/hashed_password to name/password_hash to match auth_service.py expectations
- Fix get_session() signature incompatibility: update deps.py to properly use async generator pattern
- Add missing foreign key constraints for user references (assignee_id, created_by_id, author_id, actor_id)
- Fix timezone handling: add timezone=True to all DateTime columns to match _utcnow()
- Make reset_engine async and properly dispose connections to prevent leaks
- Add database_url parameter to get_engine for test flexibility
- Remove unused imports (Engine, Boolean)
- Fix wildcard import in db/__init__.py using explicit module import for side effects
- Add __dir__ method to main __init__.py for better tab completion
Fixes all P1 runtime issues identified by Greptile and CodeRabbit reviewers.
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-authored-by: Mervin Praison <[email protected]>
---------
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Co-authored-by: praisonai-triage-agent[bot] <praisonai-triage-agent[bot]@users.noreply.github.com>
Co-authored-by: Mervin Praison <[email protected]>
* fix: use _completion_with_retry for follow-up responses in streaming
Replace bare litellm.completion() calls with self._completion_with_retry()
in both streaming follow-up (line 3404) and non-streaming fallback (line 3440)
to ensure consistent retry logic for rate limits and transient errors.
Also surface errors to users instead of silently swallowing them.
Fixes#1536
Co-authored-by: MervinPraison <[email protected]>
* fix: sanitize error messages in streaming follow-up responses
- Replace raw exception exposure in user-visible yield with sanitized message
- Add correlation ID for debugging while hiding internal details
- Maintain detailed logging for troubleshooting
- Follows security best practices for error handling
Co-authored-by: Mervin Praison <[email protected]>
---------
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Co-authored-by: MervinPraison <[email protected]>
* fix: prevent test collection failures from optional modules
Fixes test collection issues when optional dependencies (praisonaiui,
google.generativeai) are not installed in base setup.
Changes:
- praisonai/inc/models.py: Add try/catch guards around importlib.util.find_spec()
calls to handle missing parent packages gracefully
- praisonai/ui/_aiui_datastore.py: Move dependency imports to lazy loading
in __init__ to allow module import during test collection
Resolves#1541
Co-authored-by: praisonai-triage-agent[bot] <praisonai-triage-agent[bot]@users.noreply.github.com>
* fix: implement thread-safe class factory for _aiui_datastore and DRY refactor for models
- Replace dangerous runtime __bases__ mutation with thread-safe lazy class factory
- Ensure BaseDataStore.__init__ is properly called via super().__init__()
- Add _is_module_available() helper to eliminate code duplication in models.py
- Maintain lazy loading behavior for test collection compatibility
- Fix critical thread safety and initialization issues identified by reviewers
Co-authored-by: Mervin Praison <[email protected]>
---------
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Co-authored-by: praisonai-triage-agent[bot] <praisonai-triage-agent[bot]@users.noreply.github.com>
Co-authored-by: Mervin Praison <[email protected]>
* fix: make session store fcntl import cross-platform compatible (fixes#1540)
- Add conditional fcntl import like file_memory.py already has
- Use _HAS_FCNTL flag to check fcntl availability before usage
- Windows uses msvcrt for locking, Unix uses fcntl when available
- Fixes Windows test collection failure due to missing fcntl module
Co-authored-by: praisonai-triage-agent[bot] <praisonai-triage-agent[bot]@users.noreply.github.com>
* fix: add one-time warning for degraded file locking
Addresses CodeRabbit feedback about silent no-op locking when fcntl
is unavailable on non-Windows platforms. Adds module-level sentinel
to emit warning only once, following AGENTS.md error handling principles.
Co-authored-by: Mervin Praison <[email protected]>
---------
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Co-authored-by: Mervin Praison <[email protected]>
* fix(phase1b): make CLI backend tests actually run (refs #1530, #1531)
Problem: After PR #1531 merged, 19/34 shipped unit tests for the Phase 1b
CLI Backend Protocol were failing because they were written against
fabricated APIs that do not exist on this codebase:
- test_yaml_cli_backend.py: used AgentsGenerator(config=...) and
.create_agents_and_tasks(); neither the kwarg nor the method exist.
- test_cli_backend_flag.py, test_external_agents_backcompat.py:
called PraisonAI().parse_args() which deliberately short-circuits to
parse_known_args([]) when PYTEST_CURRENT_TEST is in env, so patched
sys.argv was ignored and --help never raised SystemExit.
The Phase 1b *feature* works end-to-end (verified via manual CLI smoke:
'praisonai backends list' prints claude-code, --cli-backend flag accepts
registered ids, mutual exclusion fires). The tests, however, were dead
weight; CI just skipped them.
Fix:
1. Extract the YAML cli_backend resolution block (23 lines) from
agents_generator.py into a new module-level helper
_resolve_yaml_cli_backend(cli_backend_config, logger). Zero behaviour
change for existing callers; PraisonAgent(..., cli_backend=...)
wiring is unchanged.
2. Rewrite test_yaml_cli_backend.py to call that helper directly (8
tests). Covers: string id, dict+overrides, missing id, None, import
error, unknown id, invalid type, plus a real end-to-end resolve
against the registered claude-code backend.
3. Rewrite test_cli_backend_flag.py to drive the CLI via subprocess
(7 tests), stripping PYTEST_* env vars so parse_args does not
short-circuit. Covers: --cli-backend in --help, registered backend
accepted, unknown backend rejected, mutual exclusion with
--external-agent, backends list subcommand (bare and with 'list'),
and unknown subcommand reporting.
4. Rewrite test_external_agents_backcompat.py as a mix of direct
imports (ExternalAgentsHandler, ClaudeCodeIntegration) and
subprocess argparse checks (6 tests). Guards against regression
of --external-agent {claude,gemini,codex,cursor} and
--external-agent-direct.
Result: 34/34 tests pass locally (6 backcompat + 7 CLI + 8 YAML + 13
existing claude-backend). No production code behaviour change - only
test suite + a small helper extraction in agents_generator.py.
* fix: address reviewer feedback from CodeRabbit and Greptile
- Fix ImportError path to preserve requested backend ID in log messages
- Remove dead try/except code in --help test
- Fix trailing PYTHONPATH separator issue in test environments
- Add missing returncode assertion for error cases
Co-authored-by: Mervin Praison <[email protected]>
* docs(tests): add inline comments documenting coupling to backends handler
Addresses remaining CodeRabbit nit on test_cli_backend_flag.py. No test
logic change; only docstring additions that document the coupling
between the subprocess tests and the 'backends' subcommand handler in
praisonai.cli.main (default-to-list behaviour and '[red]Unknown
backends subcommand: ...[/red]' error wording).
---------
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Fixes#1524
Complete the Chainlit→aiui migration started in #1443. Deletes ~6,900 LOC of dead Chainlit code across 28 files, fixes the runtime-crash import in serve.py, wires real WebRTC voice via aiui's OpenAIRealtimeManager, hardens realtime/agents-dashboard bindings to 127.0.0.1, and restores ImportError install-hint guards at all UI entry points.
Squash of 4 commits:
- 648291e3: initial deletion (12 files, ~5,337 LOC, cli/main.py scaffolding, serve.py fix, realtime rewiring)
- 682a9486: security + orphan cleanup (5 more files + 4 stale test files)
- d019e0e8: cli/commands/realtime.py hardening (copilot)
- 25452527: create_aiui_agents_interface → 127.0.0.1 (coderabbit)
All 6 acceptance criteria from #1524 validated:
✓ Zero executable chainlit refs in source
✓ pyproject.toml free of chainlit
✓ praisonai serve ui does not crash
✓ praisonai ui realtime uses real WebRTC
✓ praisonai doctor probes praisonaiui
✓ Fresh-install test suite green without chainlit (44/44 local pass)
Two list_pending() methods on PairingStore dropped channel_type/channel_id/created_at keys that CLI and test_pending_persists_across_instances depended on. Consolidated into single method with both new UI-friendly keys and original canonical keys.
Validated locally:
- 170 passed, 2 skipped on gateway unit + integration + bots integration suite
- Pre-existing test_pending_persists_across_instances now green
- CodeRabbit + GitGuardian green, mergeStateStatus CLEAN
Closes#1510
Wires existing PairingStore into Chainlit UI dashboard with admin-only banner and one-click approve/deny.
Validated locally:
- 20/20 pairing_routes unit tests pass
- Integration test properly skipped when chainlit not installed (importorskip)
- Module-level chainlit import moved inside functions (matches #1517 pattern)
- CodeRabbit + GitGuardian green
- Mergeable against current main
* fix(onboard): honour PRAISONAI_NO_PROMPT + add --yes/-y flag (non-interactive)
Wizard now short-circuits every Prompt.ask / Confirm.ask / input() /
getpass.getpass() to its default when:
- PRAISONAI_NO_PROMPT=1 (the env var install.sh already forwards), or
- stdin is not a TTY (piped / CI / daemon restart path).
Also adds a discoverable CLI flag: praisonai onboard --yes (-y, or
--non-interactive). --yes sets the env var for the process so every
nested call sees it consistently.
Closes the UX gap flagged in the manual onboard test where the wizard
would hang forever when stdin was closed (daemon post-install reconfig,
install.sh piped flow when user answered Y then walked away, CI runs).
Tests:
tests/unit/cli/test_onboard_non_interactive.py — 8 tests incl. an
end-to-end regression canary that boobytraps rich.prompt.Prompt.ask /
Confirm.ask / input / getpass and asserts OnboardWizard.run() does not
invoke any of them when non-interactive.
Backward compatible: interactive default is unchanged.
* fix(onboard): normalize PRAISONAI_NO_PROMPT values case-insensitively
Agent-Logs-Url: https://github.com/MervinPraison/PraisonAI/sessions/37538306-5c79-454f-9487-b2e92845d694
Co-authored-by: MervinPraison <[email protected]>
* test(onboard): harden tty mocking in non-interactive env tests
Agent-Logs-Url: https://github.com/MervinPraison/PraisonAI/sessions/37538306-5c79-454f-9487-b2e92845d694
Co-authored-by: MervinPraison <[email protected]>
* fix(onboard): improve code quality based on reviewer feedback
- Fix locals() check by initializing daemon_success early
- Add clarifying comment about intentional env var persistence
Co-authored-by: Mervin Praison <[email protected]>
---------
Co-authored-by: copilot-swe-agent[bot] <[email protected]>
Co-authored-by: MervinPraison <[email protected]>
Co-authored-by: praisonai-triage-agent[bot] <272766704+praisonai-triage-agent[bot]@users.noreply.github.com>
* fix: restore allowlist enforcement in gateway daemon mode (fixes#1494)
- Extract allowed_users, allowed_channels, group_policy from channel config
- Pass these fields to BotConfig instead of dropping them at server.py:1367
- Add warning when no allowed_users configured
- Add comprehensive unit tests for allowlist round-trip verification
- Fixes critical security bug where daemon mode ignored user allowlists
Co-authored-by: MervinPraison <[email protected]>
* test: rewrite test_channel_allowlist to test real WebSocketGateway instead of mock
- Remove MockGateway class that reimplemented production logic
- Test actual WebSocketGateway.start_channels() method via async pytest
- Mock only _create_bot to prevent network connections, all allowlist logic is real
- Add regression test that demonstrates failure if production fix is reverted
- Maintain all original test coverage with proper parametrization
- Tests now verify server.py:1367-1394 allowlist extraction actually works
Co-authored-by: Mervin Praison <[email protected]>
---------
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Co-authored-by: MervinPraison <[email protected]>
* fix(onboard): install daemon by default + OS-aware management hints
Two small UX wins layered on top of PR #1491's prompt-reduction work:
1) Remove the last inline yes/no question
---------------------------------------
Before:
Install as background service (daemon)? [y/n] (y): _
95% of users pressed Enter. Non-developers didn't know what
'daemon' meant. If we install by default and they change their
mind, 'praisonai gateway uninstall' removes it in one command.
So: install silently, no prompt.
This finishes the goal of the previous PR: the only questions
that remain in 'praisonai onboard' are the three that genuinely
need a user answer — platform, token, and allowlist.
2) Tell users how to manage / restart / re-onboard the daemon
-----------------------------------------------------------
The old Done panel showed 'praisonai bot start' (foreground) and
'praisonai gateway status'. That answered 'is it running?' but
not 'how do I restart / stop / re-run the wizard?'.
New panel groups the commands by intent and emits the correct
restart line for the platform detected at runtime:
Manage the daemon:
praisonai gateway status # is it running?
praisonai gateway logs # tail the logs
launchctl kickstart -k gui/$(id -u)/ai.praison.bot # macOS
systemctl --user restart ai.praison.bot # Linux
praisonai gateway uninstall # remove the daemon
Re-run or reconfigure:
praisonai onboard # change tokens / add platforms
praisonai gateway start # run in foreground (skip daemon)
praisonai doctor # diagnose the whole stack
The launchd label ('ai.praison.bot') is the one defined in
praisonai/daemon/launchd.py LABEL. Commands and subcommands
referenced above were validated against 'praisonai --help' +
'praisonai gateway --help' before shipping.
3) Plain-flow parity
------------------
The non-rich fallback (_run_plain) also now installs the daemon
by default and prints the same 4-line next-steps block so
terminals without rich aren't stuck with a bare 'Start with: …'.
Validation:
- The only 'Confirm.ask' call still in wizard.run() is the
'Overwrite with fresh config?' guard from PR #1491.
- 9/9 existing onboard tests pass.
- Smoke-tested install against the live daemon on macOS —
plist regenerated, 'praisonai gateway status' reports healthy.
Note on the 'start daemon' question: 'praisonai gateway start' runs
the gateway in the FOREGROUND. The daemon auto-starts it in the
background via launchd/systemd (the plist's ProgramArguments is
literally 'praisonai gateway start --config $abs_config'). The new
panel makes this distinction explicit so users don't double-start
the server.
* fix(onboard): address reviewer feedback - service names, idempotency, token detection
- Fix Linux service name mismatch (ai.praison.bot -> praisonai-bot)
- Add Windows-specific restart command (schtasks instead of shell operators)
- Fix token detection in plain flow for existing environment variables
- Make daemon install idempotent by checking status first
- Extract duplicate daemon install logic into helper method
- Adjust Done panel text based on daemon install success
Co-authored-by: Mervin Praison <[email protected]>
---------
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* feat(approval): default tool-safety policy (block destructive ops)
Block destructive tools by default without adding ANY new Agent()
kwarg. Opt out per-agent with approval='full' or globally with
PRAISONAI_TOOL_SAFETY=off.
User ask (#1491 discussion):
> 'by default are you not auto approving tools, you auto approve
> tools, if users need they can disable, the tools shouldnt
> delete, but could get all required information and create and
> edit'
> 'don't bloat Agent() class'
Design (zero new kwargs):
- praisonaiagents/approval/registry.py
Add PERMISSION_PRESETS['default'] = {delete_file, acp_delete_file,
move_file, copy_file, execute_command, acp_execute_command,
execute_code, kill_process}.
Add PERMISSION_PRESETS['off'] as alias of 'full' for the env knob.
'default' intentionally leaves write_file, acp_create_file,
acp_edit_file, read_file, search_*, get_* UNBLOCKED — per the
user's 'create and edit should work, delete should not' rule.
- praisonaiagents/agent/agent.py (10-line block inside the existing
'elif approval is False or approval is None:' branch)
When no approval= kwarg is passed, read PRAISONAI_TOOL_SAFETY
(default 'default'). If set to off/full/none/0/false → no extra
policy. Otherwise apply the matching preset's frozenset to
self._perm_deny. Everything else in the approval path stays
untouched.
- tests/unit/approval/test_default_tool_safety.py (new)
10 focused tests covering:
- preset contains destructive ops, excludes read/create/edit
- off/full presets are empty
- Agent auto-picks 'default' preset with no env and no kwarg
- PRAISONAI_TOOL_SAFETY=off / full disables the policy
- PRAISONAI_TOOL_SAFETY=safe upgrades to the stricter preset
- explicit Agent(approval='full') overrides env
- unknown env value (typo) falls back to no blocks, doesn't crash
- GUARD-RAIL: assert no new Agent() kwargs leaked into signature
(forbidden names: tool_safety, safety, permission,
permissions, deny_tools). If this fires, the feature drifted
from its no-bloat invariant and needs a conscious review.
End-to-end verified against the installed Agent:
deny set: [acp_delete_file, acp_execute_command, copy_file,
delete_file, execute_code, execute_command,
kill_process, move_file]
read_file → 'content of /tmp/x' (allowed)
delete_file → {'error': 'blocked by permission policy'}
execute_command → {'error': 'blocked by permission policy'}
BACKWARD-COMPAT NOTE
Pre-4.6.27 Agent() silently allowed LLM-driven delete_file /
execute_command. This commit flips that default to 'block'. Agents
that relied on the old behaviour need one of:
export PRAISONAI_TOOL_SAFETY=off # global opt-out
Agent(..., approval='full') # per-agent opt-out
The blocked path returns a clean error dict (permission_denied=True)
rather than raising, so LLMs reason about the denial and typically
switch strategies instead of failing the session.
* refactor(approval): simplify safety env preset handling
Agent-Logs-Url: https://github.com/MervinPraison/PraisonAI/sessions/72ccbfde-a1a4-4f29-bcbf-025decef88ca
Co-authored-by: MervinPraison <[email protected]>
* fix(approval): honor empty presets when resolving tool safety env
Agent-Logs-Url: https://github.com/MervinPraison/PraisonAI/sessions/72ccbfde-a1a4-4f29-bcbf-025decef88ca
Co-authored-by: MervinPraison <[email protected]>
* fix(approval): improve env validation and security for tool-safety policy
- Unknown PRAISONAI_TOOL_SAFETY values now fall back to 'default' preset instead of disabling safety
- Added warning logging for unknown values to aid debugging
- Simplified env validation logic per reviewer feedback
- Fixed read_only preset redundancy (removed duplicate tools already in DEFAULT_DANGEROUS_TOOLS)
- Updated tests to match improved security behavior
Addresses security concerns from Copilot and logic improvements from Gemini reviewer feedback.
Co-authored-by: Mervin Praison <[email protected]>
---------
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Co-authored-by: MervinPraison <[email protected]>
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Co-authored-by: Mervin Praison <[email protected]>
* fix(onboard): drop unused home_channel + trim confusing prompts
Before: the bot onboarding wizard asked 9 questions across 5 steps and
emitted config the codebase never reads:
1. Platform(s)
2. <platform> token
3. Allowed user IDs
4. Home channel / user ID for proactive messages ← dead config
5. Agent name ← everyone pressed Enter
6. Agent instructions ← everyone pressed Enter
7. Config file path ← user typed 'n' → wrote
a literal file named 'n'
8. Install as background service?
9. Overwrite existing file? (conditional)
Real user feedback (#1487):
> 'I didn't understand TELEGRAM_HOME_CHANNEL'
> 'don't you think we are asking too many questions?'
This change removes four of those prompts and the dead YAML emit:
- home_channel (all 4 platforms): verified no consumer in the
gateway scheduler path (uses explicit
DeliveryTarget.channel_id, not home_channel).
Dropped from PLATFORMS dict, rich flow, plain flow,
and _generate_bot_yaml output.
- Agent name + instructions: defaults already applied in __init__
(assistant, 'You are a helpful AI assistant.').
Users who want custom agents edit bot.yaml, which
has the full schema and stays the single source of
truth.
- Config file path: replaced free-text prompt with canonical path
(~/.praisonai/bot.yaml). Fixes the 'n' → literal
filename 'n' bug. Overwrite-confirm remains with
default=True so the wizard stays idempotent.
After: 4 real questions — platform, token, allowlist, install daemon?
Everything else either has a sensible default or is derived from
earlier answers.
Tests: updated tests/unit/cli/test_onboard_security.py to assert the
ABSENCE of home_channel_env in PLATFORMS and in generated YAML, so a
future copy-paste can't silently re-introduce dead config. 9/9 pass.
Verified live:
- /health → healthy after gateway restart with patched code
- mean reply latency 1.59s across 5 prompts (still < 2s, unchanged
from the 4.6.26 baseline — no perf regression)
- generated bot.yaml no longer contains home_channel lines
- PLATFORMS carries no home_channel_env keys
* fix(onboard): address reviewer feedback
- Fix overwrite default from True to False (safer for destructive actions)
- Remove stale docstring references to removed home-channel feature
- Remove dead home_env assignment that's never used
- Update comments to reflect current behavior
Co-authored-by: Mervin Praison <[email protected]>
---------
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* fix(gateway): default reflection to False for YAML-defined agents
Chat channels (Telegram/Discord/Slack/WhatsApp) exposed by the
gateway were slow because _create_agents_from_config() hard-coded:
reflection = agent_def.get('reflection', True)
With reflection=True, every message runs the self-critique loop
(1..max_reflect=3 extra LLM round-trips) before replying. Measured
on gpt-4o-mini with the bot.yaml the onboard wizard generates:
reflection=True → 12.33s (258 chars, self-reflected answer)
reflection=False → 1.57s (6 chars, direct answer)
That is ~8x latency for the simplest prompt. Real Telegram users
feel this as 'the bot takes ages to reply'.
The SDK already defaults self_reflect=False for instruction-based
agents (agent.py:1447). The gateway was overriding that sensible
default. This change restores it; users who want deeper answers
can still opt in per-agent with 'reflection: true' in bot.yaml.
Verified with live daemon:
- /health: healthy
- agent.self_reflect = False
- e2e Agent.start('hello') = 2.9s (was 12.3s)
* test(gateway): align reflection default tests with gateway behavior
Agent-Logs-Url: https://github.com/MervinPraison/PraisonAI/sessions/dac34406-5d0c-4e51-a1d6-4658f3165512
Co-authored-by: MervinPraison <[email protected]>
* fix: address reviewer feedback - improve comments, docstring, and tests
- Move reflection comment closer to assignment (Gemini feedback)
- Update docstring to reflect new default: False (Copilot feedback)
- Fix failing test to expect reflection=False (Copilot feedback)
Co-authored-by: Mervin Praison <[email protected]>
---------
Co-authored-by: copilot-swe-agent[bot] <[email protected]>
Co-authored-by: MervinPraison <[email protected]>
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Co-authored-by: Mervin Praison <[email protected]>
* fix(install.sh): suppress duplicate next-steps after bot onboard
When the user completes 'praisonai onboard' through the installer, the
wizard prints a full '✅ Done' Rich panel showing:
- Dashboard URL (praisonai claw → http://127.0.0.1:8082)
- Start bot command
- Gateway /health and /info endpoints + auth token
- Doctor / gateway status commands
Previously install.sh then also called print_next_steps() which re-listed
some of the same things plus a redundant 'praisonai onboard' hint the
user had literally just run. This looked confusing:
╭─ ✅ Done ─╮ ← the real final summary
│ ... │
╰───────────╯
Installation complete! ← second summary, duplicates info
Next steps:
Set up a messaging bot: ← user just did this
praisonai onboard
Fix: track BOT_ONBOARDED=1 when the wizard succeeds and skip
print_next_steps() entirely in that path. The wizard panel is the
single source of truth. If the user declined or the wizard failed,
print_next_steps() still runs so they have guidance.
Also clarified dashboard UI line as 'localhost only' to answer the
natural 'why no token?' question — praisonai claw binds to 127.0.0.1
by default and has no URL-level auth; see praisonai/cli/commands/claw.py
for the LAN-exposure warning path.
* refactor(install.sh): remove redundant BOT_ONBOARDED guard in print_next_steps
Agent-Logs-Url: https://github.com/MervinPraison/PraisonAI/sessions/616f106e-fe4b-4c90-9b3b-f8a49b572201
Co-authored-by: MervinPraison <[email protected]>
---------
Co-authored-by: copilot-swe-agent[bot] <[email protected]>
Co-authored-by: MervinPraison <[email protected]>
* fix(gateway): unbreak daemon — remove duplicated start_with_config block + guard push attrs
Two root causes for 'praisonai gateway status' showing the launchd
daemon running while port 8765 refuses connections after
curl | bash onboarding in v4.6.22:
1. server.py had 84 lines of duplicated/malformed code appended to
start_with_config(), causing IndentationError at module import time.
The launchd service crash-looped (KeepAlive=true) and filled
bot-stderr.log with ~68MB of tracebacks. Removed the duplicated
tail so the method ends correctly at stop_channels().
2. /health references self._push_enabled / _channel_mgr / _presence_mgr /
_redis_pubsub, but PR #1483 moved push infra out of the core gateway.
Once the daemon stayed up, the first health probe raised
AttributeError: 'WebSocketGateway' object has no attribute '_push_enabled',
producing HTTP 500. Guard every push attribute access with getattr
so health reports cleanly when push is disabled.
Verified: fresh launchd kickstart, curl http://127.0.0.1:8765/health
returns {"status": "healthy", ...}; praisonai gateway status reports
'Gateway Status: healthy'.
* fix(gateway): guard private redis_pubsub._client access for robustness
Apply defensive getattr() to redis_pubsub._client to maintain consistency
with other push attribute guards and prevent future AttributeError if
the Redis adapter implementation changes.
Addresses feedback from CodeRabbit and Gemini reviewers.
Co-authored-by: Mervin Praison <[email protected]>
---------
Co-authored-by: praisonai-triage-agent[bot] <272766704+praisonai-triage-agent[bot]@users.noreply.github.com>
Co-authored-by: Mervin Praison <[email protected]>
* fix: Agent Skills gaps - approval scoping, progressive disclosure, observability, budget, safer defaults (fixes#1478)
Implements all 6 gaps identified in the Agent Skills architecture review:
G-A (CRITICAL): Fixed approval scoping bug where skills with allowed-tools
accidentally granted AutoApprove for ALL tools to an agent. Now uses
per-tool auto-approval registry for precise scoping.
G-B: Added SkillActivationProtocol for progressive disclosure, enabling
Claude Code-style skill activation where only descriptions are shown
initially with full bodies loaded on demand.
G-C: Added SkillDiscoveredEvent and SkillActivatedEvent for observability
and telemetry integration to track skill usage patterns.
G-D: Added SkillPromptBudget to prevent unbounded system-prompt growth
with large skill libraries. Supports multiple budgeting strategies.
G-E: Made run_skill_script safer by default - now only enabled when
explicitly requested via PRAISONAI_ENABLE_SKILL_TOOLS=1 or when a skill
declares it in allowed-tools.
G-F: Added tool_from_skill() adapter in wrapper for users who want
'skill = tool' ergonomics with existing tool registries.
All changes are backward compatible and follow protocol-driven architecture.
Import time remains <20ms. Comprehensive tests included.
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-authored-by: MervinPraison <[email protected]>
* fix: address critical architecture and security issues identified in code review
- Fix CRITICAL approval scoping security leak where unnamed agents could create global auto-approvals
- Fix budget strategy application to sort skills before count truncation for correct alpha ordering
- Fix character count estimation to include XML tags, escaping, and location fields for accuracy
- Fix skill-to-tool adapter to properly handle arguments and set metadata during decoration
- Fix type annotations for optional parameters
- Improve error handling with per-tool logging to prevent silent failures
Co-authored-by: Mervin Praison <[email protected]>
* fix: align PR #1481 tests with design + repair corrupted gateway/server.py
- tests/unit/skills/test_approval_scoping: drop mock-patch of local import;
match explicit per-agent-only scope for auto_approve_tool.
- tests/unit/skills/test_budget: expected default strategy='fifo' (impl).
- capabilities/skills.tool_from_skill: set __name__/__qualname__/__doc__
on inner function before @tool decoration so schema + introspection see
the final identity.
- tests/unit/test_tool_from_skill: rewrite mock-based tests to patch the
real load_skill in praisonaiagents.skills (monkeypatch) and simulate
ImportError via builtins.__import__ blocker.
- gateway/server.py: strip 84 lines of duplicated/corrupted try/finally
blocks after run() (pre-existing SyntaxError masked by stale .pyc).
---------
Co-authored-by: praisonai-triage-agent[bot] <272766704+praisonai-triage-agent[bot]@users.noreply.github.com>
Co-authored-by: MervinPraison <[email protected]>
* refactor: Move PushClient and transports from core SDK to wrapper (fixes#1482)
- Move PushClient (388 LOC) from core to praisonai/push/client.py
- Move WebSocketTransport and PollingTransport from core to praisonai/push/transports.py
- Extract PushTransportProtocol to core praisonaiagents/push/protocols.py
- Convert core push/__init__.py to lazy re-export shim following gateway pattern
- Maintain backward compatibility for all import paths
- Core SDK now has only protocols and lightweight utilities (<80 LOC per file)
- Heavy implementations correctly moved to wrapper package
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: MervinPraison <[email protected]>
* fix: add backward compatibility shims and optimize lazy loading
- Add client.py and transports.py shims to maintain backward compatibility
for existing imports like 'from praisonaiagents.push.client import PushClient'
- Sort __all__ alphabetically in wrapper package (Ruff RUF022 compliance)
- Optimize lazy loading by hoisting importlib and simplifying mapping
- Fixes critical issue where tests/unit/test_push_client.py:8 would break
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-authored-by: Mervin Praison <[email protected]>
---------
Co-authored-by: praisonai-triage-agent[bot] <272766704+praisonai-triage-agent[bot]@users.noreply.github.com>
Co-authored-by: MervinPraison <[email protected]>
* feat: implement self-improving agent loop foundation
Adds core capabilities for agents to learn and persist knowledge as skills:
Core SDK (praisonaiagents):
- Add SkillMutatorProtocol for agent-managed skill CRUD operations
- Extend LearnConfig with nudge_interval, propose_skills fields
- Add _maybe_emit_nudge() method for periodic knowledge persistence prompts
- Wire improvements auto-extraction in LearnManager.process_conversation()
Wrapper (praisonai):
- Create skill_manage tool for agent skill management
- Implement BasicSkillMutator with safe propose/approve workflow
- Add integration test demonstrating end-to-end self-improving loop
This enables the core self-improving claim: agents can learn procedures
and persist them as skills for reuse across sessions.
Fixes#1471🤖 Generated with [Claude Code](https://claude.ai/code)
Co-authored-by: MervinPraison <[email protected]>
* security: fix path traversal vulnerabilities and broken approve flow
- Add comprehensive path validation to prevent directory traversal attacks
- Fix broken propose/approve workflow for non-create actions
- Add proper validation for all skill name parameters
- Fix integration test to use isolated storage instead of global state
- Fix performance issue: lazy initialization of skill mutator
- Ensure edit action properly stages proposals instead of creating {name}_edit
Security improvements:
- Validate file_path parameters in write_file, remove_file, patch
- Reject dangerous patterns: .., /, \, ~
- Use resolved path checks to prevent escape attempts
- Add name validation to all CRUD operations
Fixes issues identified in Copilot security review.
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-authored-by: Mervin Praison <[email protected]>
* fix: wire nudge mechanism + remove scope-creep doc
- Wire _maybe_emit_nudge() into post-turn flow in tool_execution.py
(both sync and async paths). Previously defined but never invoked,
so LearnConfig(nudge_interval>0) had no effect.
- Nudge is appended to chat_history as a system message so it is
visible on the next LLM call. Zero overhead when nudge_interval=0.
- Remove root-level SELF_IMPROVING_AGENT_FEATURES.md (scope creep;
not requested by issue #1471).
* update
* fix: address security and performance issues in push notification system
- SECURITY: Move auth tokens from URL query params to Authorization headers
- PERFORMANCE: Make receive loop non-blocking for ACKs and callbacks
- ERROR HANDLING: Add HTTP status checks in polling transport
- ERROR HANDLING: Use robust URL parsing for WebSocket to HTTP conversion
- ERROR HANDLING: Fail fast when sending on disconnected transport
- CODE QUALITY: Remove duplicate test file content
Addresses issues identified by Gemini, CodeRabbit, and Copilot reviewers.
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-authored-by: Claude <[email protected]>
---------
Co-authored-by: praisonai-triage-agent[bot] <272766704+praisonai-triage-agent[bot]@users.noreply.github.com>
Co-authored-by: MervinPraison <[email protected]>
Co-authored-by: Claude <[email protected]>
Resolves#1473: (1) Lazy telemetry defaults — no more disk I/O or env mutation at import time, (2) Deferred async primitives — asyncio.Event/Lock created lazily inside event loop context (eliminates 'different loop' RuntimeError), (3) Unified scheduler — new scheduler/shared.py with ScheduleParser/backoff_delay/safe_call, used by both sync and async schedulers. Backoff is now 30s initial, exponential to 300s cap with 10%% jitter — consistent across both schedulers. 113 scheduler/async unit tests pass locally.
Architecture gaps resolved per #1465: (1) async bridge consolidation via run_sync across 6 persistence files, (2) removed mutable shared state in ClaudeCodeIntegration, (3) double-checked locking in db/adapter.py, integrations/registry.py, tool_resolver.py. Restored class-level _availability_cache (fixes regression in TestAvailabilityCache) with thread-safe lock. All 17 base integration tests pass locally.
Changed the default host for the claw command from "0.0.0.0" to "127.0.0.1" to improve security by binding to loopback only. Added a warning for users opting to expose the dashboard on a LAN without built-in authentication. Updated version to 1.6.20 in pyproject.toml and uv.lock.
- Bump version to 1.6.19 in pyproject.toml and uv.lock
- Enhance `install.sh` to always prompt for bot onboarding with clearer messaging
- Update integration test to reflect changes in bot onboarding prompt visibility and logic
- Updated bot command to resolve configuration paths from environment variables.
- Added new path utility functions for clarity and maintainability.
- Updated version to 1.6.16 for package consistency.
- Enhanced help messages for commands to reflect new default path behavior.
Updated the motion graphics agent factory example with detailed steps
for creating a title-card animation, including necessary function
calls and content requirements. Added a new installation command
to the README for easier setup.
Added functionality to read and persist the GATEWAY_AUTH_TOKEN across daemon restarts. This ensures the dashboard link remains consistent, improving user experience. Updated version to 1.6.15 and made necessary adjustments to related files.
Introduced several Python scripts demonstrating motion graphics rendering
and GitTools safety features. Includes examples for basic rendering,
Git repository validation, and agent factories. These enhancements aim
to provide a comprehensive toolkit for creating and managing motion
graphics projects efficiently.
- Incremented version to 1.6.13 in pyproject.toml and uv.lock.
- Modified _generate_bot_yaml function to support both single and multi-agent configurations.
- Updated launchd, systemd, and Windows daemon scripts to use gateway start instead of bot start for better compatibility with multi-bot setups.
- onboard: refuse to install daemon when no token was captured for
the selected platforms (previously it installed a broken service
that would crash-loop). Lists missing platforms and tells the user
to rerun onboard with credentials.
- onboard: daemon-install default flipped to YES when tokens are
present (matches hermes UX; previously default NO left bots
offline by default).
- onboard: final panel now references 'praisonai gateway status'
(real command) instead of 'praisonai bot status' (doesn't exist).
- doctor: resolve praisonaiagents version via importlib.metadata
(the package does not expose __version__), so the check no longer
reports 'praisonaiagents unknown installed'.
- pyproject: add aiui to [bot] and [all] so the chat dashboard is
available immediately after onboarding a messaging bot.
- onboard: every setting (token, extra env vars, allowlist, home
channel) now shows the existing (masked) value and lets the user
update or keep it, mirroring hermes-agent setup.
- onboard: support 'clear' keyword on allowlist prompt to restore
open access.
- _save_env_vars: None as a value now deletes the key from
~/.praisonai/.env (previously empty strings were silently skipped).
- Bumps praisonaiagents to 1.6.11.
Updated the version in `pyproject.toml` and `uv.lock` to 1.6.10.
Modified dependencies in `pyproject.toml` for clarity and to include
new libraries necessary for core agent functionality. Fixed file
handling in the SetupHandler and improved path resolution in tests.
Added checks for missing required arguments in the setup command tests.
* feat: wire up bot onboarding + gateway daemon install + Windows support
Wire existing OnboardWizard (254 lines) to CLI and extend gateway commands
for cross-platform daemon management. Adds Windows Scheduled Task support.
New Commands:
- praisonai onboard - messaging bot setup wizard
- praisonai gateway install/uninstall/logs - daemon management
- praisonai bot install-daemon - convenience alias
Platform Support:
- Linux systemd user units
- macOS LaunchAgent
- Windows Scheduled Tasks (with Startup folder fallback)
Enhanced install.sh:
- Offers bot onboarding after LLM setup
- Detects existing messaging tokens
- Respects NO_ONBOARD flag
Fixes#1454🤖 Generated with [Claude Code](https://claude.ai/code)
Co-authored-by: MervinPraison <[email protected]>
* fix: stabilize onboarding and daemon CLI paths
Agent-Logs-Url: https://github.com/MervinPraison/PraisonAI/sessions/56b7de0e-b6b5-4139-a3fd-d3a47e5d7ce7
Co-authored-by: MervinPraison <[email protected]>
* fix: harden daemon command wiring and test hooks
Agent-Logs-Url: https://github.com/MervinPraison/PraisonAI/sessions/56b7de0e-b6b5-4139-a3fd-d3a47e5d7ce7
Co-authored-by: MervinPraison <[email protected]>
* feat(onboard): telegram security + .env persistence + password-hidden input
Brings bot onboarding to parity with hermes/openclaw reference CLIs:
- Persist tokens + allowlist + home channel atomically to ~/.praisonai/.env
(chmod 600, tmp-then-rename). No more ephemeral os.environ-only state.
- Password-hidden token input via Rich password prompt (rich path) and
getpass (plain fallback). Tokens no longer echo to terminal.
- Per-platform ALLOWED_USERS allowlist prompt with security warning when
skipped (anyone who finds the bot can use it).
- Per-platform HOME_CHANNEL prompt for proactive/cron delivery, defaulting
to first allowed user ID.
- Platform-specific user-ID discovery hints (@userinfobot for Telegram,
Developer Mode for Discord, member ID for Slack, E.164 for WhatsApp).
- bot.yaml now references ${..._ALLOWED_USERS} and ${..._HOME_CHANNEL}
for every channel, keeping secrets out of the yaml file.
Also fixes:
- gateway.py: print_warn() -> print_warning() (correct method name on
OutputController). Prevents AttributeError on daemon status/install/logs.
- test_onboard_command.py: patch the actual source of run_onboard
(features.onboard) since the commands module imports it lazily.
Refs #1454
Co-authored-by: MervinPraison <[email protected]>
---------
Co-authored-by: praisonai-triage-agent[bot] <272766704+praisonai-triage-agent[bot]@users.noreply.github.com>
Co-authored-by: MervinPraison <[email protected]>
Co-authored-by: copilot-swe-agent[bot] <[email protected]>
Co-authored-by: MervinPraison <[email protected]>
Co-authored-by: onboard-enhance <[email protected]>
- Fix TypeError when sessions have updated_at=None by using 'or' operator
- Add regression test for None updated_at values in session store
- Ensures sessions with None updated_at sort last (as intended)
Fixes#1445
Co-authored-by: praisonai-triage-agent[bot] <272766704+praisonai-triage-agent[bot]@users.noreply.github.com>
* fix(langextract): bridge ContextTraceEmitter so real agent events flow into sink
Problem
-------
The merged langextract integration (#1412, PR #1413) wired LangextractSink
to get_default_emitter()/ActionEvent only. That pipeline has just two
producers in the entire core SDK (RouterAgent token usage, PlanningAgent
plan_created), so a typical single-agent run with '--observe langextract'
or 'praisonai langextract render <yaml>' produced an empty HTML file.
The base agent runtime (chat_mixin, tool_execution, unified_execution_mixin)
actually emits rich lifecycle events via ContextTraceEmitter /
ContextTraceSinkProtocol in praisonaiagents.trace.context_events.
Fix (wrapper-only, zero core changes)
-------------------------------------
- observability/langextract.py: add _ContextToActionBridge adapter that
forwards ContextEvent -> ActionEvent (agent_start, tool_call_start/end,
llm_response->OUTPUT, agent_end). Expose LangextractSink.context_sink().
- cli/app.py: _setup_langextract_observability now also installs a
ContextTraceEmitter wired to the bridge.
- cli/commands/langextract.py: 'render' command does the same wiring for
the duration of the workflow run.
- tests: add 3 regression tests covering the bridge and setup path.
Incidental fix
--------------
agents_generator.py:1112 had a local 'import os' inside an 'if
acp/lsp enabled' block that shadowed the module-level import and caused
UnboundLocalError at line 1179 for any YAML run with acp/lsp disabled.
Removed the redundant local import.
Verification
------------
- 19/19 langextract unit tests pass (16 existing + 3 new).
- Real agentic e2e: Agent.start() with --observe langextract now produces
non-empty trace.html (3036 B) + trace.jsonl (1356 B) with agent_run and
final_output extractions.
- 'praisonai langextract render simple.yaml' end-to-end now produces
render.html and render.jsonl; previously printed 'Trace was not rendered'.
* test(langextract): make context-emitter setup test deterministic
Agent-Logs-Url: https://github.com/MervinPraison/PraisonAI/sessions/cec32ee8-0573-405f-86d1-6a28fb51b609
Co-authored-by: MervinPraison <[email protected]>
* test(langextract): cover setup behavior with and without optional dependency
Agent-Logs-Url: https://github.com/MervinPraison/PraisonAI/sessions/cec32ee8-0573-405f-86d1-6a28fb51b609
Co-authored-by: MervinPraison <[email protected]>
* fix(langextract): improve error handling, test reliability, and reduce code duplication
- Add LangextractSink.bridge_context_events() helper method to centralize context emitter setup
- Fix silent exception swallowing in langextract render command - now properly reports bridge failures
- Add proper skipif guard for optional dependency tests
- Use callback pattern for clean separation of CLI concerns
Co-authored-by: Mervin Praison <[email protected]>
* test(langextract): remove skipif referencing undefined _langextract_available helper
---------
Co-authored-by: copilot-swe-agent[bot] <[email protected]>
Co-authored-by: MervinPraison <[email protected]>
Co-authored-by: praisonai-triage-agent[bot] <272766704+praisonai-triage-agent[bot]@users.noreply.github.com>
Co-authored-by: Mervin Praison <[email protected]>
* feat: consolidate tool alias mappings into single source of truth (fixes#1431)
- Create shared _tool_aliases.py with canonical TOOL_ALIAS_MAP
- Remove duplicate TOOL_MAPPING from managed_agents.py
- Remove duplicate TOOL_ALIAS_MAP from managed_local.py
- Resolve mapping conflicts: grep->search_file, web_fetch->web_fetch, edit->apply_diff
- Add comprehensive unit tests for alias consistency
- Ensure backward compatibility for existing callers
Co-authored-by: MervinPraison <[email protected]>
* test: enhance backward compatibility test for web_search alias
Add web_search to test inputs to ensure the alias mapping
from web_search -> search_web is properly tested, addressing
reviewer feedback from Copilot.
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-authored-by: Mervin Praison <[email protected]>
* test: fix double-praisonai import paths in tool alias tests
---------
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Co-authored-by: MervinPraison <[email protected]>
Validated locally: all 3 fixes work with real CLIs (gemini returns response with flash-lite default, codex works outside git repos, cursor surfaces auth errors clearly instead of silent empty). Closes#1415.
* fix: --n8n flag Docker networking and endpoint issues (fixes#1406)
- Add Docker-aware URL generation using host.docker.internal on macOS/Windows
- Fix HTTP Request nodes to use /agents endpoint instead of non-existent /agents/{id}
- Add helpful Docker networking tips in CLI and initialization
- Update CLI help text to mention Docker networking gotchas
Co-authored-by: MervinPraison <[email protected]>
* test: add n8n CLI coverage and sanitize generated agent id
Agent-Logs-Url: https://github.com/MervinPraison/PraisonAI/sessions/dfc8acb0-ac39-4d91-b930-586894119671
Co-authored-by: MervinPraison <[email protected]>
* fix: harden n8n agent id generation and add focused CLI tests
Agent-Logs-Url: https://github.com/MervinPraison/PraisonAI/sessions/dfc8acb0-ac39-4d91-b930-586894119671
Co-authored-by: MervinPraison <[email protected]>
* fix: address critical n8n reviewer feedback
- Fix API endpoint from POST /agents to POST /agents/{agent_id}/invoke to match actual API
- Add port parameter to _default_api_url to respect CLI --port flag
- Require N8N_DOCKER=1 env var for Docker detection to prevent false positives
- Update API URL when n8n_url changes in execute() method
- Use json.dumps for proper JavaScript string escaping in n8n expressions
- Update CLI help text to clarify Docker platform requirements (macOS/Windows only)
- Add URL path normalization with rstrip('/') for consistency
Addresses reviewer feedback from CodeRabbit, Gemini, and Copilot regarding
Docker detection logic, API contract compliance, and configuration handling.
Co-authored-by: Mervin Praison <[email protected]>
---------
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Co-authored-by: MervinPraison <[email protected]>
Co-authored-by: copilot-swe-agent[bot] <[email protected]>
Co-authored-by: MervinPraison <[email protected]>
* fix: n8n converter - fix missing connections, remove read-only fields, use httpRequest node type (fixes#1404)
- Fix Bug 1: Add missing agent-to-agent connections via _build_sequential_connections()
- Fix Bug 2: Remove read-only fields (updatedAt, tags, staticData, etc.) from n8n API payload
- Fix Bug 3: Change from chainLlm to httpRequest node type pointing to PraisonAI API
- All fixes tested with 2-agent workflow successfully
Co-authored-by: MervinPraison <[email protected]>
* fix: align n8n tests and reverse converter with httpRequest nodes
Agent-Logs-Url: https://github.com/MervinPraison/PraisonAI/sessions/37dde90a-1f27-4635-ac13-b564202f6f93
Co-authored-by: MervinPraison <[email protected]>
* fix: normalize n8n agent id sanitization and reverse parsing
Agent-Logs-Url: https://github.com/MervinPraison/PraisonAI/sessions/37dde90a-1f27-4635-ac13-b564202f6f93
Co-authored-by: MervinPraison <[email protected]>
* fix: normalize n8n agent id sanitization and reverse parsing
- Fix API field names: use 'message' instead of 'query' for request body
- Fix API response field: use 'result' instead of 'response' for chaining
- Fix API URL path: use '/api/v1/agents/{id}/invoke' format
- Filter workflow output to only n8n Public API allowed fields
- Update reverse converter to recognize httpRequest nodes with PraisonAI API pattern
- Update tests to match new API structure and field filtering
- Remove redundant sequential connection logic
Addresses reviewer feedback from Gemini, CodeRabbit, and Copilot
Co-Authored-By: Mervin Praison <[email protected]>
---------
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Co-authored-by: MervinPraison <[email protected]>
Co-authored-by: copilot-swe-agent[bot] <[email protected]>
Co-authored-by: MervinPraison <[email protected]>
Updated the flow export command to utilize `click` for output format selection, improving consistency with other commands. Bumped version to 1.6.6 in `pyproject.toml` and `uv.lock`.
- Fix P0: Wire UnifiedExecutionMixin into Agent class inheritance (Gap 1 now functional)
- Fix P0: Fix deadlock bug in _run_async_in_sync_context using dedicated thread with new event loop
- Fix P0: Fix ImportError by correcting tool_execution import path and using self.execute_tool_async
- Fix P0: Add llm_instance fallback to llm attribute for default Agent constructor paths
- Fix P1: Replace asyncio.coroutine with AsyncMock in tests for Python 3.11+ compatibility
- Fix P1: Yield REQUEST_START event in streaming protocol instead of only emitting to stream_emitter
- Fix P2: Use Optional[str] type annotations instead of implicit str = None
- Fix P2: Remove rate limit errors from recoverable patterns (non-streaming fallback won't help)
- Fix P2: Remove placeholder bug reference URL in AnthropicStreamingAdapter
All three architectural gaps are now fully functional:
- Gap 1: Sync/async duplication eliminated via unified async-first execution core
- Gap 2: Parallel tool execution working with proper ExecutionConfig integration
- Gap 3: Streaming protocol with provider-specific adapters and observable fallback
Co-authored-by: Mervin Praison <[email protected]>
- Add parallel_tool_calls field to ExecutionConfig dataclass
- Update Agent class to consolidate parameter per architecture guidelines
- Add deprecation warning for standalone parallel_tool_calls parameter
- Maintain backward compatibility with fallback logic
- Update chat_mixin.py to use getattr() for safe attribute access
- Fix missing parallel_tool_calls in async get_response_async path
- Update tests to use new ExecutionConfig(parallel_tool_calls=True) pattern
Follows AGENTS.md Section 5.3 parameter consolidation pattern:
'False=disabled, True=defaults, Config=custom'
This addresses architectural concerns about Agent class bloat while
maintaining full backward compatibility.
Co-authored-by: Mervin Praison <[email protected]>
- Add graceful fallback for missing FastAPI/Pydantic dependencies
- Fix Field import to use lambda fallback when Pydantic not available
- Add FASTAPI_AVAILABLE flag to conditionally define models and router
- Improve error handling and module loading robustness
- Add AgentInvokeAPI with FastAPI router for n8n → PraisonAI direction
- POST /api/v1/agents/{agent_id}/invoke endpoint for workflow invocation
- Support for both sync and async agents with session management
- Agent registry for programmatic agent registration
- Comprehensive error handling and validation with Pydantic models
- Integration with existing FastAPI app in api/call.py
- Complete unit tests with FastAPI TestClient
- Full bidirectional integration example with interactive demo
- Follows AGENTS.md architecture guidelines (API in wrapper package)
Co-authored-by: MervinPraison <[email protected]>
- Added SSHSandbox for remote server execution via SSH with asyncssh
- Added ModalSandbox for serverless GPU execution on Modal platform
- Added DaytonaSandbox for cloud development environment execution
- Updated sandbox __init__.py with lazy loading for new backends
- Added optional dependencies: [ssh], [modal], [daytona] in pyproject.toml
- Created comprehensive unit tests for all new sandbox backends
- Added examples/python/sandbox_remote.py with usage demonstrations
- All backends implement complete SandboxProtocol interface
- Follows protocol-driven architecture with implementations in wrapper package
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-authored-by: MervinPraison <[email protected]>
- Import GatewayEventType from protocols to fix EventType ambiguity
- Update PlatformWorkspaceContext constructor to require workspace_id
- Fix workspace context assertions to parse JSON response format
- Handle empty description case returning JSON payload instead of None
- Remove model/tools assertions from agent config test (not in schema)
- Use proper UUID generation for test workspace IDs
Addresses architectural gaps identified in Issue #1392, specifically Gap 2:
LLM Tool Calls Execute Sequentially - No Parallelism for Batched Tool Calls.
Changes:
- Add ToolCallExecutor protocol with sequential/parallel implementations
- Add Agent(parallel_tool_calls=True) flag with backward compatibility (default False)
- Update llm.py get_response() and get_response_stream() to use ToolCallExecutor
- Update Agent.chat() to pass parallel_tool_calls setting to LLM
- Add comprehensive tests demonstrating ~3x latency improvement for parallel execution
Benefits:
- When LLM returns multiple tool calls, they execute concurrently instead of sequentially
- Respects existing per-tool timeout infrastructure
- Thread-safe with bounded workers (default 5)
- Zero regression risk (opt-in feature, default preserves current behavior)
- Result ordering matches input order
Test results show 2.98x speedup for 3 concurrent tool calls vs sequential execution.
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-authored-by: Claude <[email protected]>
- Add directory validation for --path parameter (prevents NotADirectoryError)
- Fix --limit 0 behavior to show zero results instead of forcing one
- Resolve examples_path to absolute to fix relative_to() errors
Addresses CodeRabbit and Copilot review feedback.
Co-authored-by: Mervin Praison <[email protected]>
- Fix hardcoded localhost → use dynamic hostname for remote access
- Implement proper process management to prevent orphaned processes
- Add signal handlers with cleanup and restoration
- Fix CLI routing for flow/dashboard commands in main.py
- Move FastAPI imports inside function to reduce startup overhead
- Change default host to 127.0.0.1 (secure by default)
- Add service startup verification with 15s timeout
- Rename command from 'unified' to 'dashboard' (no conflicts found)
- Forward host parameter to child services for consistency
- Improve error handling with clear install instructions
Addresses all reviewer feedback from CodeRabbit, Gemini, and Copilot.
Co-authored-by: Mervin Praison <[email protected]>
- Fix hardcoded localhost for remote access compatibility
- Implement proper process cleanup to prevent orphaned processes
- Add flow and unified commands to special_commands CLI router
- Add lazy imports with error handling for optional dependencies
- Improve error handling with proper HTTP status codes
- Add centralized port configuration and process tracking
- Remove static file writing, serve HTML from memory
- Add debug logging and troubleshooting support
Addresses reviewer feedback from Gemini, CodeRabbit, and Copilot.
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-authored-by: Mervin Praison <[email protected]>
This commit addresses the top 3 architectural violations against the stated philosophy:
1. FIXED: Dual LLM execution paths (DRY violation)
- Removed three-branch fork in chat_mixin.py
- Unified all LLM providers through single protocol-driven dispatcher
- Eliminated duplicate logic between LiteLLM and OpenAI paths
- Enhanced unified dispatcher to handle all parameters from legacy paths
2. FIXED: Eager loading of subsystems (performance violation)
- Converted memory/__init__.py to lazy loading using __getattr__
- Moved heavy imports (FileMemory, RulesManager, DocsManager, MCPConfig) to lazy loading
- Agent(instructions='hi') no longer loads unused subsystems at import time
3. IMPROVED: Agent mixin architecture
- Unified dispatcher now protocol-driven rather than inheritance-based
- Lazy loading reduces mixin impact when features aren't used
- Foundation for future protocol composition improvements
Addresses violations of:
- DRY principle: Single LLM execution path eliminates duplication
- Protocol-driven core: Unified dispatcher follows protocol pattern
- Lazy imports: Memory subsystems load only when used
- Performance-first: No import-time overhead for unused features
Aligns with AGENTS.md philosophy:
'Protocols/hooks in core, heavy impl in wrapper/tools'
'Lazy imports, optional deps, no heavy module-level work'
'DRY · Protocol-driven core · No perf impact'
Fixes#1382
Co-authored-by: MervinPraison <[email protected]>
- Add missing copy and time imports to top of workflows.py (Gemini/Copilot)
- Fix handoff chain reset at workflow start to prevent false positives (Copilot)
- Fix session key duplication in session.py agent keys (Copilot)
- Move ToolExecutionError import to top of tool_execution.py (Gemini)
- Remove commented dead code in session.py cleanup (Gemini)
Co-authored-by: Mervin Praison <[email protected]>
Added support for an extended agent card through callbacks.
Implemented new methods for task listing and push notification configuration.
Enhanced task handling to support immediate return configurations,
allowing for background processing of tasks.
Refactored multiple agent-related functions to incorporate these features,
resulting in significant improvements to the A2A functionality.
- Fix undefined response_format variable in async unified dispatch path
- Fix message slicing bug that drops first user message when no system prompt
- Fix thread safety issues in IndexRegistry singleton with proper class-level lock
- Fix thread safety in memory registry using @lru_cache for atomic singleton
- All critical P0/P1 issues from reviewers now resolved
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-authored-by: Mervin Praison <[email protected]>
- Fix checkpoint pruning logic reversal (use newest-last semantics)
- Add CHECKPOINTS_PRUNED event type to replace ERROR for normal operations
- Fix ThreadPoolExecutor timeout bypass with explicit executor lifecycle
- Unify AsyncSafeState to use single thread lock across sync/async contexts
- Fix agent cleanup to target actual live clients (llm_instance, openai_client)
- Sync memory fallback logic across async/structured STM entry points
- Move contextvars import to module level for better performance
Addresses critical concurrency, security, and data integrity issues.
Co-authored-by: Mervin Praison <[email protected]>
Implements unified dashboard combining Flow Builder, Claw Dashboard, and Chat UI
at localhost:3000. Users can now access all PraisonAI visual interfaces from
one place:
- Flow Visual Builder (port 7860) - Create agents and workflows visually
- Claw Dashboard (port 8082) - Full featured dashboard with Telegram/Discord bots
- Clean Chat UI (port 8081) - Simple chat interface
New command: praisonai unified
- Single entry point at localhost:3000
- On-demand service launching
- Real-time service status monitoring
- Responsive iframe-based interface
Fixes#1369
Co-authored-by: praisonai-triage-agent[bot] <praisonai-triage-agent[bot]@users.noreply.github.com>
- Add PlatformWorkspaceContext class implementing WorkspaceContextProtocol
- Provides workspace context and agent config via database queries
- Scopes agent queries to workspace for security
- Returns None for missing workspace/agent as per spec
- Export PlatformWorkspaceContext from services module
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-authored-by: MervinPraison <[email protected]>
Added new authentication and authorization features for PraisonAI Agents.
This includes the implementation of `AuthIdentity`, `AuthBackendProtocol`, and related schemas.
The new API routes and services facilitate session management, role checks,
and workspace context provision for enhanced security and user identity management.
The issue was caused by a local variable 'backend' in the memory configuration
processing that was shadowing the 'backend' parameter from the Agent constructor.
When memory=True was passed to the Agent, the memory backend string (e.g., 'file')
was incorrectly assigned to self.backend instead of the external managed backend.
This caused a RuntimeError: Backend str does not support execute() method when
the Agent tried to delegate to what it thought was a managed backend but was
actually a string.
Changes:
- Rename local variable from 'backend' to 'memory_backend' to avoid shadowing
- Preserves the original backend parameter functionality
- Fixes the issue where memory=True would break external backend delegation
Fixes#1371
Co-authored-by: praisonai-triage-agent[bot] <praisonai-triage-agent[bot]@users.noreply.github.com>
Implemented a concurrency registry to control concurrent task execution
for agents, allowing users to set limits per agent name. Also added message
sink protocols for managing sequenced task execution messages, enabling
replay of agent outputs and tool calls.
New files include:
- agent/concurrency.py
- task/message_sink.py
Updated the task module to include the new protocols in exports.
Total changes across 13 files with 1099 insertions.
- Add global --observe flag to CLI with PRAISONAI_OBSERVE env var support
- Wire observability automatically into Langflow Agent and Agents components
- Update langfuse_example.py to use current TraceSinkProtocol API
- Graceful degradation when Langfuse not installed
Enables users to run:
- praisonai run workflow.yaml --observe langfuse
- PRAISONAI_OBSERVE=langfuse praisonai flow
Fixes#1364 (Phase 1)
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <[email protected]>
- Fix IndexRegistry singleton broken in knowledge/index.py (P0)
- Fix sync/async unified dispatch default inconsistency
- Fix message slicing logic that drops first user message
- Add thread safety to all singleton patterns with double-checked locking
- Enhance Ollama adapter to handle both dict and list-shaped tool payloads
Addresses feedback from Greptile, Gemini, CodeRabbit, and Copilot reviewers.
Fixes remaining critical issues in architectural gap PR.
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-authored-by: Mervin Praison <[email protected]>
Added multiple examples demonstrating the creation and management of agents,
environments, sessions, and custom tools in the managed agents architecture.
This comprehensive set of examples now includes functionalities such as
tool selection, disabling tools, and updating agent configurations, providing
users with clear guidance on utilizing the framework effectively.
Gap 1: Enable unified LLM dispatch by default
- Changed _use_unified_llm_dispatch default from False to True
- Removed dead if False: code block in chat_mixin.py:583-607
- Eliminates triple execution paths for better sync/async feature parity
Gap 2: Extend provider adapter protocol for complete dispatch replacement
- Added 6 new methods to LLMProviderAdapterProtocol: parse_tool_calls,
should_skip_streaming_with_tools, recover_tool_calls_from_text,
inject_cache_control, extract_reasoning_tokens
- Implemented Ollama-specific tool recovery and Gemini streaming skip logic
- Foundation to replace 24+ hardcoded provider checks with adapter calls
Gap 3: Replace singletons with instance-based registries
- Converted IndexRegistry from __new__ singleton to normal class with default()
- Replaced module-level _memory_registry with get_default_memory_registry()
- Added ServerRegistry class to replace global _server_* dicts in agent.py
- Enables multi-agent safe execution and independent registries per agent
Fixes#1362
Co-authored-by: MervinPraison <[email protected]>
- Add backend delegation logic to run(), start(), and chat() methods
- Delegate to external managed agent backend when available
- Fallback to local execution when no backend is configured
- Handle both streaming and non-streaming execution modes
- Add comprehensive test coverage for delegation functionality
- Fix remaining P1 architectural issue from PR reviews
This completes the hybrid execution feature for external managed agent backends.
Co-authored-by: Mervin Praison <[email protected]>
Fixes ArtiPACKED vulnerability (GHSA-3959-6v5q-45q2) where GitHub tokens
were being persisted in .git/config and could leak through artifacts.
- Added persist-credentials: false to 25+ workflow files
- Fixed duplicate with blocks in claude.yml and build-image.yml
- Fixed .github/actions/claude-issue-triage-action/action.yml
Addresses three critical issues identified in code review:
1. CRITICAL: Fix exception path to always emit JSON to stdout
- Previously only printed warning to stderr on exception
- Now emits fallback JSON to maintain tooling reliability
2. HIGH: Capture final_agent metrics when --final-agent used
- Previously only captured original agent metrics
- Now intelligently selects final_agent when available
3. MEDIUM: Move json import to module top per PEP 8
- Moved import json from inline to module level
- Removed redundant inline import sys
Fixes ensure --metrics-json flag maintains reliability contract
for downstream tooling like Terminal-Bench.
Co-authored-by: Mervin Praison <[email protected]>
- Add missing asyncio import to prevent NameError
- Fix asyncio.wait_for with async generator using deadline-based timeout
- Add exception chaining to preserve original traceback context
- Ensures stream() method now works without TypeError
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <[email protected]>
- Fix authentication header: use x-api-key instead of Authorization Bearer
- Fix session cache bug: store session_id instead of session_key
- Fix SSE parsing: use readline() for proper line-by-line processing
- Add timeout enforcement to async operations
- Persist API key when loaded from environment variables
- Make AnthropicManagedProvider inherit from ManagedBackendProtocol
- Add regression tests for session caching and API key persistence
Addresses P0 issues identified by reviewers (Greptile, CodeRabbit, Copilot, Gemini)
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Mervin Praison <[email protected]>
- Implement ManagedAgentIntegration class in praisonai/integrations/
- Add support for Anthropic Managed Agents API
- Add backend parameter to Agent class for hybrid execution
- Zero new dependencies (uses existing aiohttp)
- Follow existing BaseCLIIntegration pattern
- Include comprehensive tests
Fixes#1358
Co-authored-by: MervinPraison <[email protected]>
- Add --metrics-json command-line flag to enable JSON cost output
- Output structured metrics including cost_usd, tokens_in, tokens_out, model, request_count
- Enables programmatic cost tracking for Terminal-Bench and other tools
- Uses existing MetricsHandler for data extraction
- Fixes CLI cost tracking gap identified in issue #1356🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: MervinPraison <[email protected]>
Added `praisonai_wrapper_agent.py` for a CLI-based agent approach.
Updated `README.md` to include integration details for both external
and wrapper agents, and added examples for usage. Enhanced `job.yaml`
with configuration options for the wrapper agent. Minor updates
to existing files to improve clarity and maintainability.
Added support for custom git author information from environment variables
in the CLI. Updated version to 1.5.143 in project files. Adjusted
git commit commands to include the author if provided.
Added tracing instructions for Langfuse and updated the default user
name and email settings in CheckpointConfig and FileSnapshot to fetch
from environment variables. Bumped version to 1.5.142.
- Added Langfuse tracing documentation to README.
- Introduced user_name and user_email parameters in CheckpointService and FileSnapshot classes for custom Git configuration.
- Updated relevant methods to utilize new parameters for better user identification in commits.
- Added a new image for Langfuse tracing under .github/images.
- Add __enter__/__exit__ context manager support to AsyncSafeState for backward compatibility
- Add chat_history property setter to prevent AttributeError on assignments
- Fix validate_output to call _llm_validate instead of non-existent validate method
- Update all _memory references to _memory_instance in AsyncMemoryMixin
- Replace deprecated asyncio.get_event_loop() with get_running_loop()
Fixes critical runtime errors that would break core Agent functionality.
All changes maintain backward compatibility and follow AGENTS.md principles.
Co-authored-by: Mervin Praison <[email protected]>
- Add __enter__/__exit__ context manager support to AsyncSafeState for backward compatibility
- Add chat_history property setter to prevent AttributeError on assignments
- Fix memory attribute references throughout AsyncMemoryMixin (_memory → _memory_instance)
- Fix LLMGuardrail.validate_output to use _llm_validate instead of non-existent validate method
- Move GuardrailChain implementation out of protocols.py for cleaner separation
- Update deprecated asyncio.get_event_loop() to asyncio.get_running_loop()
All changes maintain backward compatibility and align with AGENTS.md principles.
Co-authored-by: Mervin Praison <[email protected]>
- Changed repository reference for install.sh from praisonai-package to MervinPraison/PraisonAI.
- Improved sync mechanism to only copy files if there are changes, ensuring the latest version is served.
- Added references to official resources and documentation in the security audit workflow.
- Included guidelines for creating security advisories and reporting vulnerabilities.
- Gap 1: Add AsyncSafeState dual-lock abstraction for async/sync agent state protection
- Gap 2: Add GuardrailProtocol with fail-closed error handling for production safety
- Gap 3: Add AsyncMemoryMixin for async-safe memory operations without event loop blocking
Fixes core async/concurrency issues, improves guardrails safety model, and enables
proper async memory operations as outlined in issue analysis.
Co-authored-by: MervinPraison <[email protected]>
Enhance `bump_and_release.py` and `release.py` scripts to add specific
release files instead of all changes. Introduced a check for
uncommitted changes with informative error messages. This reduces the
risk of accidental changes during the release process.
Refactor instructions for issue analysts and software engineers to
enhance clarity. Details include requiring issue number discovery via
local environment and simplifying commit and PR messaging to remove
explicit issue number references.
- Add asyncio queue inbox to GatewaySession for concurrency
- Intercept and enqueue messages while session is executing
- Resolve GatewaySession stepper background worker thread processing
- Implement RecipeBotAdapter to bridge declarative recipes to conversational agents
- Register support for --recipe flag in bot start commands
- Refactor 'praisonai serve recipe' to boot WebSocketGateway instead
* security: Fix CORS Configuration Vulnerabilities (CWE-942) - Replace wildcard origins
- Replace allow_origins=['*'] with secure environment-based configurations
- Update browser server to use BROWSER_CORS_ORIGINS env var with localhost defaults
- Update jobs server to use JOBS_CORS_ORIGINS env var with localhost defaults
- Update example API to use API_CORS_ORIGINS env var with localhost defaults
- Remove wildcard defaults from ServerConfig, GatewayConfig, and AppConfig
- Add secure localhost defaults to MCP server transport
- Update tests and documentation to reflect secure defaults
- Restrict CORS methods and headers to essential ones only
Fixes#1321 - Addresses 3 instances of CWE-942 vulnerabilities
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-authored-by: praisonai-triage-agent[bot] <praisonai-triage-agent[bot]@users.noreply.github.com>
* fix: Address 3 CORS bugs found in review - chrome-extension regex, http_stream headers, server.py methods/headers
Agent-Logs-Url: https://github.com/MervinPraison/PraisonAI/sessions/b76a2075-da18-4ad5-82e8-79fc09457529
Co-authored-by: MervinPraison <[email protected]>
* security: Fix remaining CORS vulnerabilities (CWE-942)
- Add environment-based CORS defaults (empty for production)
- Validate env vars to reject wildcard origins (*)
- Add missing Idempotency-Key header to jobs CORS
- Unify WebSocket and HTTP CORS origin validation
- Make http_stream transport environment-aware
Fixes all critical security issues identified by code reviewers:
- Production no longer allows localhost by default
- Environment variables cannot bypass security with *
- WebSocket uses same origin validation as CORS middleware
- Jobs API properly supports Idempotency-Key header
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-authored-by: Mervin Praison <[email protected]>
---------
Co-authored-by: praisonai-triage-agent[bot] <272766704+praisonai-triage-agent[bot]@users.noreply.github.com>
Co-authored-by: praisonai-triage-agent[bot] <praisonai-triage-agent[bot]@users.noreply.github.com>
Co-authored-by: copilot-swe-agent[bot] <[email protected]>
Co-authored-by: MervinPraison <[email protected]>
Co-authored-by: Mervin Praison <[email protected]>
Updated action and workflow files to use consistent input variable references.
This includes changes to environment variable handling for better clarity
and maintainability, enhancing code quality and reducing potential errors.
* fix(security): replace insecure MD5 with SHA-256 and disable debug mode
Replace all 29 instances of hashlib.md5() with hashlib.sha256() across
22 files. MD5 is cryptographically broken (CWE-328) and should not be
used for hashing, even for non-security purposes like cache keys and
content fingerprints.
Also disable debug=True in api.py (CWE-489) to prevent information
leakage in production deployments.
Vulnerabilities fixed:
- 28x CWE-328: Use of Weak Hash (MD5 → SHA-256)
- 1x CWE-489: Active Debug Code (debug=True → debug=False)
Detected by semgrep (p/owasp-top-ten, p/python).
Verified by re-scan: 66 findings → 37 remaining (29 fixed).
Remaining findings (require manual review):
- 14x shell injection (subprocess with user input)
- 10x subprocess shell=True
- 3x wildcard CORS
- 5x tainted env args in subprocess
Co-Authored-By: Claude Opus 4.6 (1M context) <[email protected]>
* fix: address review feedback on MD5→SHA-256 migration
Fixes raised by Gemini Code Assist, Qodo, and CodeRabbit:
1. templates/security.py: algorithm="md5" now raises ValueError
instead of silently returning SHA-256 digest
2. recipe/security.py: CycloneDX serialNumber now uses uuid5()
for RFC 4122 compliant UUID format (was 64-char hexdigest)
3. agent/agent.py: backward-compatible session ID — checks for
legacy MD5-based session file on disk before using new SHA-256 ID
4. snapshot/snapshot.py: backward-compatible shadow repo path —
adopts legacy MD5-based directory if it exists on disk
Co-Authored-By: Claude Opus 4.6 (1M context) <[email protected]>
---------
Co-authored-by: Michael Winczuk <[email protected]>
Co-authored-by: Claude Opus 4.6 (1M context) <[email protected]>
Updated unit and integration tests for better readability and maintainability.
Replaced repetitive subprocess calls with a dedicated `run_doctor` function in
the doctor CLI tests, and improved error handling in the handoff error tests.
Removed unnecessary test cases and cleaned up assertions for clarity.
Total changes: 57 insertions, 151 deletions across 10 files.
Replaced the old use cases section with a more detailed table outlining specific applications of AI agents across various industries, enhancing clarity and usability for readers.
- Remove unreachable dead code (issues list never populated)
- Fix misleading warning message to distinguish channel vs global warnings
- Improve exception handling: ValueError for config errors (FAIL) vs runtime errors (ERROR)
- Make bot checks accessible via CLI by:
- Converting to registry-based @register_check decorators
- Adding bot_checks to register_all_checks()
- Adding 'bots' subcommand to CLI actions and category mapping
Co-authored-by: Mervin Praison <[email protected]>
- Add check_bot_security() function to bot_checks.py doctor module
- Validates allowlist/blocklist configuration across channels
- Warns about overly permissive group policies (respond_all vs mention_only)
- Checks for PRAISONAI_GATEWAY_SECRET to ensure pairing persistence
- Provides actionable remediation guidance for secure configurations
- Integrates with existing doctor framework for 'praisonai doctor --category bots'
This implements the 'doctor-style check' component requested in issue #1313
for auditing risky bot security configurations before production deployment.
Fixes#1313🤖 Generated with [Claude Code](https://claude.ai/code)
Co-authored-by: praisonai-triage-agent[bot] <praisonai-triage-agent[bot]@users.noreply.github.com>
Moved the highlighted section from the middle to the bottom of the README for better visibility. Adjusted image and quote formatting to maintain clarity and consistency.
Improved installation instructions for SDK, CLI, Dashboard, and Builders
with example commands. Added new visual elements for better engagement.
Removed redundant elements to streamline content.
Revise main description to emphasize hiring autonomous AI agents.
Condense sections for quick paths and performance, improving the overall flow.
Remove outdated use cases and provide a more engaging introduction to PraisonAI.
- Add Awaitable import and update TaskExecutorProtocol return type for async compatibility
- Add error handling for missing executor agents with clear remediation message
- Fix variable substitution to include team-level variables for async/sync consistency
- Remove unused Union import (already done in previous commit)
Addresses valid reviewer feedback from CodeRabbit, Qodo, Copilot, and Gemini.
Co-authored-by: Mervin Praison <[email protected]>
- Remove duplicate adapters.py file to eliminate multiple sources of truth
- Replace runtime class mutation with composition-based unified dispatch for safety
- Fix missing tool execution parameters in unified sync mode
- Preserve hooks and post-processing flow in unified paths to maintain observability
- Fix duplicate verbose kwarg crash in LiteLLMAdapter
- Fix protocol violations in sync wrappers (no asyncio.run in library internals)
- Fix message extraction logic to prevent prompt duplication
- Make OpenAIAdapter sync delegate to async as required by protocol
- Improve test suite with proper sync/async parity and performance regression tests
- Add comprehensive real agentic test as required by AGENTS.md
All critical issues from reviewers addressed while maintaining backward compatibility.
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-authored-by: Mervin Praison <[email protected]>
Implemented automatic discovery and loading of protocol-driven plugins
via pip in the `PluginManager`. The new method `discover_entry_points`
fetches entry points from the `praisonai.plugins` group, loads callable
plugins, and registers them. Updated version number to 1.5.117.
- Remove unused Union import from protocols.py
- Update _build_execution_context() to return ExecutionContext dataclass
- Update _process_task_result() to accept ExecutionContext and return TaskResult
- Fix execute_task/aexecute_task to use attribute access on ExecutionContext
- Remove trailing whitespace in protocols.py
Addresses reviewer feedback from Qodo, Gemini, CodeRabbit, and Copilot
regarding protocol usage consistency and type safety.
Co-authored-by: Mervin Praison <[email protected]>
This commit addresses Issue #1304 by consolidating the dual execution paths
in the LLM layer (LiteLLM vs OpenAI) into a single async-first protocol-driven
architecture, eliminating DRY violations and maintenance burden.
Key changes:
- Added UnifiedLLMDispatcher with provider adapter pattern
- Created LiteLLMAdapter and OpenAIAdapter for protocol conformance
- Enhanced agent chat logic with opt-in unified dispatch
- Maintained full backward compatibility (existing code unchanged)
- Established protocol-driven foundation for future provider additions
Benefits:
✅ Single async chat completion implementation
✅ Sync methods as thin wrappers around async
✅ Protocol-driven provider selection
✅ Elimination of dual execution paths
✅ All existing functionality preserved
Files added:
- praisonaiagents/llm/unified_adapters.py (protocol adapters)
- praisonaiagents/agent/unified_chat_mixin.py (unified implementation)
- test_unified_llm.py (verification tests)
Files modified:
- praisonaiagents/llm/__init__.py (updated exports)
- praisonaiagents/agent/chat_mixin.py (added unified dispatch option)
The unified dispatch is opt-in via _use_unified_llm_dispatch flag, ensuring
zero impact on existing deployments while enabling clean migration path.
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <[email protected]>
- Fix GeminiAdapter tool names to match GEMINI_INTERNAL_TOOLS constants
- Fix OllamaAdapter threshold to match LLM.OLLAMA_SUMMARY_ITERATION_THRESHOLD = 1
- Extract generic AdapterRegistry[T] base class to eliminate DRY violation
- Add debug logging to registry exception handling (no longer silent)
- Move InMemoryAdapter from __init__.py to its own in_memory_adapter.py module
- Add 38 unit tests covering all new adapter and registry code paths"
Agent-Logs-Url: https://github.com/MervinPraison/PraisonAI/sessions/0fc360e2-23ac-43a1-8a56-50dd4686feb1
Co-authored-by: MervinPraison <[email protected]>
Shows how to replace scattered provider dispatch in llm.py with clean adapters:
- DefaultAdapter: Base implementation with sensible fallbacks
- OllamaAdapter: Replaces OLLAMA_SUMMARY_ITERATION_THRESHOLD logic
- AnthropicAdapter: Handles Claude prompt caching capabilities
- GeminiAdapter: Handles gemini_internal_tools formatting
- get_provider_adapter(): Replaces model.startswith() branching
This demonstrates the systematic approach for Gap 2 - extracting the 40+
provider branches from core into clean, testable adapters.
Co-authored-by: MervinPraison <[email protected]>
- Fix entry points never discovered in main flow (plugins.enable now calls discover_entry_points)
- Fix fragile entry_points fallback using robust try/except pattern from ToolRegistry
- Fix non-deterministic tests by mocking importlib.metadata properly
- Fix overbroad import monkeypatch to only affect importlib.metadata
- Add thread safety with proper _lock usage in register() and discover_entry_points()
- Add positive test case for successful entry point loading and registration
All reviewer feedback from Qodo, Gemini, CodeRabbit addressed.
Co-authored-by: Mervin Praison <[email protected]>
- Fix HandoffConfig.max_concurrent default from 3 to 5 per issue requirements
- Fix deadlock bug: parallel_handoffs() now treats max_concurrent<=0 as unlimited
- Fix BaseException handling to prevent non-HandoffResult objects in return list
- Export parallel_handoffs in package __init__.py for public API access
- Remove broken documentation URL from deprecation warning
- Wire allow_parallel flag to control parallel_handoffs() behavior
- Fix unused variable warning by prefixing with underscore
These changes address all critical bugs and API inconsistencies identified
by code reviewers while maintaining backward compatibility.
Co-authored-by: Mervin Praison <[email protected]>
- Fix threading.Lock used with async with in Process class (issue #1289)
* Replace sync lock creation with lazy async lock initialization
* Prevents runtime AttributeError in aworkflow method
- Improve thread safety in AsyncPostgres lazy lock initialization
* Add double-checked locking pattern to prevent race conditions
* Ensures only one asyncio.Lock instance created across coroutines
- Remove redundant asyncio import in async_postgres.py
- Improve exception chaining for better error diagnostics
Addresses critical issues raised by Gemini, Qodo, CodeRabbit reviewers.
Co-authored-by: Mervin Praison <[email protected]>
- Add discover_entry_points() method to PluginManager for automatic plugin discovery
- Support pip-installed plugins via 'praisonaiagents.plugins' entry_points group
- Compatible with Python 3.8+ using importlib.metadata
- Graceful error handling for missing dependencies
- Added comprehensive unit tests for entry_points discovery
- Enables external plugin packages like PraisonAI-Plugins to be auto-discovered
Fixes#1293
Co-authored-by: Mervin Praison <[email protected]>
Addresses Gap 2 from issue #1289:
1. Replace asyncio.Lock() with threading.Lock() in Process.__init__() - asyncio.Lock in sync constructor fails outside event loop
2. Add async lock protection to async postgres store init() to prevent race conditions creating duplicate connection pools
3. Fix memory state store _maybe_save() race condition where multiple threads could trigger overlapping saves
4. Verified existing thread safety in global error_logs, callbacks already properly protected with locks
5. Verified MemoryMixin already has proper thread safety with _history_lock
These changes ensure multi-agent safety by eliminating race conditions and thread safety issues that could corrupt state or cause crashes when running multiple agents concurrently.
Co-authored-by: Mervin Praison <[email protected]>
Refactor tests for `LangfuseSinkEmit` to use agent spans with a consistent
identifier format. Update assertions to reflect changes in method
validations for agent classes in `TestApiMdGenerator`. Adjusted several
mock object usages for improved clarity and consistency across tests.
Root cause of issue #1283 failure:
1. git config was local, not --global, so identity failed in cloned repos
2. External repos (PraisonAIDocs) were cloned with bare https (no auth)
3. Claude tried to push to main instead of a feature branch
Fix:
- Use --global git config for identity across all repos
- Add STEP 3-ALT with explicit cross-repo workflow using gh repo clone
- gh repo clone auto-configures auth token for push
- Add PraisonAI-Plugins and PraisonAIDocs to routing table
- Explicit instructions to never use bare git clone https://
- Resolve merge conflicts with main branch
- Fix getattr sandbox inconsistency by removing getattr from blocked AST calls
- Combine dangerous patterns from both branches for comprehensive protection
- Allow _safe_getattr implementation to work properly in sandbox mode
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-authored-by: Claude <[email protected]>
- Fix ModelNotAvailableError to properly pass provider/model to base exception
- Fix RateLimitError type annotation (Optional[str] instead of str = None)
- Fix ContextLengthExceededError to accept and pass provider/model parameters
- Add async aretrieve method to RetrievalStrategyProtocol for async I/O support
- Add missing newline at end of protocols.py file
Addresses review feedback from code reviewers.
Co-authored-by: Mervin Praison <[email protected]>
Moved test agents and tools to a dedicated fixtures directory. Updated test scripts to reference the new file paths. Removed obsolete test agent and tool files. Improved instructions for running tests.
Explicitly tells Claude to clone and open PRs in MervinPraison/PraisonAI-Tools
when a request is for an external tool, integration, or community extension.
- Improved `get_agent_ledger` method in `ledger.py` by adding validation
for `agent_id` to raise a `ValueError` if it is empty.
- Updated `_get_output_path` in `monitor.py` to include detailed path
sanitization steps and added checks to prevent path traversal attacks.
- Refined agent name sanitation and fallback techniques to ensure unique
naming.
- Incremented version number to `1.5.114` in `pyproject.toml` and
`uv.lock`.
After rebase, commit 72e477f added runtime support for:
- context str/dict -> restore to type hint
- autonomy str -> restore to type hint
- approval dict -> restore to type hint
- learn str -> restore to type hint
templates str remains removed (resolve() with no presets returns None).
Updated all docstrings to document actual supported types including new forms.
Agent-Logs-Url: https://github.com/MervinPraison/PraisonAI/sessions/e371c8e1-a816-4fb2-8eb8-a18242daa2de
Co-authored-by: MervinPraison <[email protected]>
- Add missing 'from starlette.routing import Mount' import
- Mount was used on line 1046 but not imported
- Fixes NameError when launching agents in MCP mode
🤖 Generated with Claude Code
Co-authored-by: MervinPraison <[email protected]>
- Add string preset handling in _init_autonomy() for autonomy='full_auto' etc.
- Add str/dict support in context_manager property for context='summarize' etc.
- Add dict-to-ApprovalConfig conversion for approval={'backend': ..., 'all_tools': True}
- Add string mode handling in learn parameter for learn='agentic' etc.
- Fix AUTONOMY_PRESETS to use 'level' field (not 'mode') per AutonomyConfig
Resolves type hint/implementation mismatches identified by code reviewers.
All new type hints now have proper runtime support.
Co-authored-by: Mervin Praison <[email protected]>
- Remove _global_hooks, enable_observability(), disable_observability(), and get_hooks()
- Observability is now strictly per-agent/per-pipeline to comply with AGENTS.md Rule 4.5
- Agent class already correctly uses per-instance ObservabilityHooks() when observe=True
- Eliminates shared mutable state between agents for multi-agent safety
Addresses critical architecture gap identified in PR #1277 final review.
Co-authored-by: Mervin Praison <[email protected]>
* fix(ci): integrate Claude final review directly into auto-pr-comment workflow to bypass action_required approval gate
* fix(ci): address review issues in auto-pr-comment workflow
- Fix template injection: use env vars + process.env instead of inline ${{ }} in JS
- Add timeout-minutes: 15 to polling jobs (prevent runaway Actions minutes)
- Add issues: write permission to all Claude-trigger jobs
- Restore claude-after-gemini job lost when chain-claude-after-copilot.yml was deleted
- DRY: extract polling constants and trigger login list to workflow-level env vars
Agent-Logs-Url: https://github.com/MervinPraison/PraisonAI/sessions/0ff67a7f-85be-4e2e-a16f-f3f48ebfefb5
Co-authored-by: MervinPraison <[email protected]>
---------
Co-authored-by: copilot-swe-agent[bot] <[email protected]>
Co-authored-by: MervinPraison <[email protected]>
* fix: remove global logging monkey-patch from memory.py
Remove logging.Logger.trace monkey-patch that violated protocol-driven
architecture by modifying global state at import time. The trace
functionality remains available locally within the memory module.
This addresses one architectural violation from issue #1262 while
maintaining backward compatibility and keeping changes minimal.
Co-authored-by: Mervin Praison <[email protected]>
* fix: replace logger.trace() with logger.log(TRACE_LEVEL) after removing monkey-patch
Agent-Logs-Url: https://github.com/MervinPraison/PraisonAI/sessions/56f044b6-1424-4985-b09b-afe047dadd8b
Co-authored-by: MervinPraison <[email protected]>
---------
Co-authored-by: MervinPraison <[email protected]>
Co-authored-by: Mervin Praison <[email protected]>
Co-authored-by: copilot-swe-agent[bot] <[email protected]>
- Add _safe_extractall() to reject absolute paths, '..' traversal, and path escape in tar archives
- Validate name/version from manifest BEFORE any filesystem operation in LocalRegistry.publish
- Add path confinement check ensuring resolved recipe_dir stays under recipes_path
- Validate URL path params in RegistryServer publish endpoint (early 400 rejection)
- Replace vulnerable tar.extractall() calls in both LocalRegistry and HttpRegistry
- Bump version to 4.5.113
* fix(sandbox): update sandlock integration to use real API surface
- Replace sandlock.is_available() with landlock_abi_version() >= 6 check
- Remove non-existent TimeoutError and SecurityViolationError exception handling
- Remove invalid max_cpu_time_seconds parameter from Policy constructor
- Update sandbox.run() to only pass cmd and timeout (remove env/cwd)
- Update tests to use correct API mocks
Fixes#1258
Co-authored-by: Mervin Praison <[email protected]>
* fix(sandbox): fix ABI version threshold, remove dead except block, unused var, and fix test mocks
Agent-Logs-Url: https://github.com/MervinPraison/PraisonAI/sessions/ee8122be-e5f3-47dd-bcb6-c0994df15169
Co-authored-by: MervinPraison <[email protected]>
* fix(sandbox): implement proper sandlock Result status mapping and improve test reliability
- Fix exit_code status mapping: Check result.success and exit_code before returning SandboxStatus.COMPLETED
- Update test mocks to return proper Result objects with success/exit_code instead of raising exceptions
- Add integration test that exercises real sandlock API if available
- Address reviewer feedback from CodeRabbit, Qodo, Gemini, and Copilot
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-authored-by: MervinPraison <[email protected]>
---------
Co-authored-by: MervinPraison <[email protected]>
Co-authored-by: Mervin Praison <[email protected]>
Co-authored-by: copilot-swe-agent[bot] <[email protected]>
Updated the tools in multiple example scripts to use `list_files` instead of `list_directory`. Removed unnecessary global variables and functions in `shell_tools.py` for better clarity and performance. Updated the `approval` flag in agent configurations to `False` for consistency across examples.
Updated the user email in multiple GitHub workflows to a no-reply address for better privacy. This change ensures consistency across the repository's automation scripts.
fix(examples): update web configuration in agent examples
Modified web configuration in `agent_centric_api.py` examples to utilize `WebConfig`. This enhances clarity and control over the web search functionality.
test(unit): skip integration test without API key
Added a condition to skip the `test_circuit_breaker_real_agentic` if the OpenAI API key is not set. This prevents unnecessary test failures in the absence of required credentials.
* feat: enhance evaluation framework with EvalSuite, ComparisonEval, and SafetyEval
- Add EvalSuite orchestrator for running multiple evaluations with aggregated results
- Add ComparisonEval for side-by-side A/B testing of agent outputs across criteria
- Add SafetyEval for detecting harmful/biased/inappropriate content across 6 categories
- Update eval/__init__.py with new exports and lazy loading
- Add comprehensive unit tests for all new components (150+ test cases)
- Follow protocol-driven architecture with zero performance impact
- Maintain backward compatibility with existing eval framework
Addresses #1245🤖 Generated with [Claude Code](https://claude.ai/code)
Co-authored-by: Mervin Praison <[email protected]>
* fix(eval): resolve critical issues and add real agentic tests
- Add missing _make_llm_call method to BaseLLMGrader for ComparisonGrader and SafetyGrader
- Fix after_run() calls to pass required result parameter
- Fix winner parsing logic to prevent 'Agent B' misclassification as 'agent_a'
- Fix safety score parsing to prevent LLM override of worse category scores
- Fix EvalSuite fail_fast behavior to properly re-raise RuntimeError
- Add support for AccuracyResult avg_score in EvalSuite scoring
- Fix Python type hints compatibility (tuple[str,str] → tuple)
- Add comprehensive real agentic integration tests that call agent.start()
Addresses all critical issues identified in code reviews and fulfills
AGENTS.md Section 9.4 requirement for real agentic tests.
Co-authored-by: Mervin Praison <[email protected]>
---------
Co-authored-by: MervinPraison <[email protected]>
Co-authored-by: Mervin Praison <[email protected]>
Co-authored-by: praisonai-triage-agent[bot] <272766704+praisonai-triage-agent[bot]@users.noreply.github.com>
- PostgreSQL: validate table name against safe identifier regex to
prevent SQL injection via user-controlled table parameter
- MongoDB: escape regex metacharacters in list_keys prefix to prevent
ReDoS / unexpected pattern matching
- MongoDB: use $setOnInsert for created_at so it is preserved on
update (was being overwritten on every save)
- DynamoDB: replace raw string FilterExpression with proper Boto3
Attr().begins_with() condition in list_keys
- DynamoDB: remove redundant boto3 import in _create_table (already
imported in _get_table)
Agent-Logs-Url: https://github.com/MervinPraison/PraisonAI/sessions/c012c607-294a-4cef-864d-91a2bccca2dd
Co-authored-by: MervinPraison <[email protected]>
- Remove eager module-level imports of heavy backends (Redis/MongoDB/PostgreSQL/DynamoDB)
- Implement lazy loading in get_backend() function using getattr() only when needed
- Update __all__ exports to only include lightweight backends
- Add module-level __getattr__ for backward compatibility
- Follow praisonaiagents/db pattern for proper separation of core vs wrapper
Fixes critical architectural violation where heavy wrapper dependencies
were being imported at module level, breaking the lazy loading design.
Core SDK imports now work without wrapper package (< 50ms import time).
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-authored-by: Mervin Praison <[email protected]>
Compromised versions 1.14.1 and 0.30.4 were removed from npm registry
but semver ranges (^1.7.9) could resolve to malicious versions if
they're re-released or exist in alternate registries.
Pinning to exact version 1.8.4 prevents this attack vector entirely.
The base claude-code-action does not accept 'prompt_file' or 'install_github_mcp'.
This routes the prompt properly through 'direct_prompt' using GitHub step outputs.
Updated README.md to include a new section for the PraisonAI UI,
providing installation instructions and a brief description.
Bumped version numbers in pyproject.toml and lock files to
reflect changes and dependency updates.
Updated package version to 1.5.99 and introduced new memory handling
features in PraisonAI components. Added configuration for session
tracking in memory save. Included additional tests for agent and task
components to ensure correct functionality and integration.
Relocated image assets from the public directory to the .github/images directory. Updated references in README files to reflect the new asset locations. Added a new GIF asset for showcasing command execution. Total of 14 files changed with 16 insertions and 8 deletions.
- STEP 0: Set git identity to MervinPraison for all commits
- STEP 2: Mandatory bloat validation checklist before writing code
- Checks: protocol-driven design, no heavy impls in core SDK, no duplication,
proper Agent inheritance, lazy imports, no agent.py growth, no name collisions
- If checks fail: close issue with explanation instead of creating bad PRs
- Strengthen attribute access guards in code execution sandbox
- Parameterize SQL IN clauses in data layer
- Add URL scheme validation for API base URLs
- Use plain string matching instead of regex for tool search
Merges centralized logging (_logging.py, 152 files migrated) and resilience utility (utils/resilience.py). Also fixes CI/CD workflows and test fixtures.
Closes#1131#1132
Updated logger level settings to use consistent DEBUG and WARNING levels
based on the verbosity of the application. This enhances logging clarity
and ensures that third-party loggers are set to WARNING by default.
Adjusted imports to maintain consistent logging behavior across various
modules for better maintainability. Additionally, bumped version in
pyproject.toml to 1.5.89.
- Introduced a new agent for cross-posting on multiple social media platforms with required environment variables.
- Added a video generation example using HeyGen and ElevenLabs, demonstrating autonomous video production.
- Created YAML workflow for sequential multi-agent processing in video generation.
- Updated several test files to accommodate new features and examples.
## Critical Fixes:
- **agent.py (IndentationError)**: Removed 137 lines of orphaned MCP code (lines 8849-8983)
that caused an IndentationError on import, completely breaking the SDK. This was
dead code from a bad merge — partially commented out code with live import statements.
- **python_tools.py (Sandbox)**: Fixed subprocess sandbox that was too restrictive:
- Added missing builtins: getattr, ValueError, TypeError, KeyError, etc.
- Added __build_class__ for function/class definition support
- Fixed exec() to use shared globals so defined functions can see each other
- Added _safe_getattr wrapper in subprocess for defense-in-depth dunder blocking
- **circuit_breaker.py**: Fixed reset_all() to clear registry entries (not just reset state)
## Test Fixes:
- test_circuit_breaker.py: Fixed success_threshold mismatch, added setup/teardown cleanup
- test_tools_reliability.py: Fixed psutil mock injection for lazy-imported modules
- test_python_tools_sandbox.py: Updated security test expectations for sandbox mode
- Added __init__.py files to 13 test subdirectories for pytest module resolution
## Metrics:
- agent.py: 9053 → 8916 lines (-137 lines of dead code)
- Import time: 67.5ms (well under 200ms target)
- Unit tests: 4473 passed, 50 skipped (7 pre-existing failures)
- Add lightweight CircuitBreaker class with open/half-open/closed states
- Integrate with existing retry utilities in tools/retry.py
- Add health monitoring and graceful degradation support
- Provide integration helpers for LLM, Memory, and MCP systems
- Include comprehensive tests with real agentic test
- Maintain backward compatibility and zero performance regression
- Follow protocol-driven architecture from AGENTS.md
Fixes#1141🤖 Generated with [Claude Code](https://claude.ai/code)
Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
Co-authored-by: Mervin Praison <[email protected]>
- Create centralized config/resolver.py with protocol-driven design
- Add ConfigRegistry for tracking all environment variables
- Implement caching and type conversion for performance
- Add validation to warn about unknown/deprecated vars
- Extend 'praison config' CLI with env discovery and validation
- Maintain 100% backward compatibility with existing os.getenv() usage
- Follow AGENTS.md principles: protocol-driven, no performance impact
Fixes#1140 - 317+ scattered env var reads now have unified entry point
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
Co-authored-by: Mervin Praison <[email protected]>
- Add global server state lock (_agents_server_lock) to protect FastAPI endpoint registration
- Add task ID assignment lock (_task_id_lock) to prevent race conditions in parallel execution
- Add state mutation lock (_state_lock) to protect AgentTeam shared variables and _state
- Thread-safe protection for all critical sections in server startup and state management
Fixes#1152🤖 Generated with [Claude Code](https://claude.ai/code)
Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
Co-authored-by: Mervin Praison <[email protected]>
Fixes issue #1128 by systematically replacing problematic exception
handling patterns that were masking real errors and making debugging
extremely difficult.
Changes:
- Replace bare 'except:' clauses with 'except Exception:' to avoid
catching SystemExit/KeyboardInterrupt
- Add structured debug logging for all previously silent exceptions
- Maintain backward compatibility and zero performance impact
- Focus on core SDK modules: memory, tools, LLM, telemetry
Key areas fixed:
- Memory operations: Now log failed tracing and cleanup operations
- Telemetry: Debug logging for PostHog failures and queue errors
- LLM client: Debug logging for cost calculation and display failures
- Tools: Debug logging for browser checks and capability detection
- Code execution: Debug logging for temp file cleanup failures
All exception handling now provides context for debugging while
maintaining the fail-safe behavior required for production use.
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
Co-authored-by: Mervin Praison <[email protected]>
- Add code_sandbox_mode parameter to ExecutionConfig (default: 'sandbox')
- Implement _execute_code_sandboxed() using subprocess isolation
- Maintain backward compatibility with 'direct' mode (legacy)
- Subprocess sandbox runs in clean environment (no env vars, files, network)
- Same security validations: AST parsing + text pattern blocking
- Zero performance regression: lazy imports, same API
- All existing security tests pass
- Safe by default: new installs use sandboxed mode
Resolves security vulnerability where exec() ran in same process
with access to filesystem, network, and environment variables.
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
Co-authored-by: Mervin Praison <[email protected]>
* fix: implement token tracking in RouterAgent for cost observability
- Add TokenUsage dataclass with structured token consumption data
- Enhance LLM.get_response() with optional return_token_usage parameter
- Update RouterAgent to track tokens and costs per model selection
- Emit token usage via existing trace infrastructure for observability
- Maintain full backward compatibility with zero performance regression
Resolves issue #1138 - RouterAgent now provides complete cost visibility
for multi-agent routing scenarios, addressing the TODO at line 234.
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <[email protected]>
* fix: correct critical bugs in _prepare_return_value token tracking
- Move _prepare_return_value closure to before the try block in
get_response() so it's defined before use
- Fix infinite recursion: both branches called themselves instead
of returning the text value
- Revert _prepare_return_value usage from 7 out-of-scope methods
(_process_stream_delta, get_response_async, _extract_from_responses_output,
_stream_responses_api, _stream_responses_api_async, response, aresponse)
where it was a NameError and would corrupt return tuple structure
Agent-Logs-Url: https://github.com/MervinPraison/PraisonAI/sessions/1b069906-c514-4c5f-8c93-34c345db5fd0
Co-authored-by: MervinPraison <[email protected]>
---------
Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
Co-authored-by: Claude <[email protected]>
Co-authored-by: copilot-swe-agent[bot] <[email protected]>
Co-authored-by: MervinPraison <[email protected]>
Fixes identified issues from PR #1179:
- Add type hints to chat(), run(), start(), execute_tool(), execute() methods
- Fix ephemeral() return type to Generator[None, None, None] for context manager
- Add Optional[str] return types for methods that can return None (chat, run, execute)
- Add type hints to all property getters and setters
- Add type annotations to **kwargs parameters
This resolves type checker warnings and improves IDE autocompletion support.
Co-authored-by: Mervin Praison <[email protected]>
- Use thread-safe registry.unregister() in remove_tool()
- Use thread-safe registry.list_tools() in list_tools()
- Add double-checked locking to get_registry() singleton
- Prevents race conditions in multi-agent deployments
Related to #1167 and closed PR #1182
Co-authored-by: Mervin Praison <[email protected]>
* fix: implement lazy loading for tools imports to improve package startup time
- Remove eager imports of tools modules from __init__.py (lines 63-66, 72)
- Add tools imports to _LAZY_IMPORTS mapping for proper lazy loading
- Create embedding proxy to resolve function vs subpackage conflict
- Maintain 100% backward compatibility with existing imports
- Improve startup performance by loading tools only when accessed
Fixes#1168
This addresses the core SDK eagerly importing heavy modules issue by:
1. Moving from .tools.* imports to lazy loading system
2. Using existing _LAZY_IMPORTS infrastructure
3. Resolving embedding function import conflict via proxy
4. Zero breaking changes to public API
Performance improvement: Base import reduced from heavy module loading
to lightweight protocol-driven imports following AGENTS.md principles.
Co-authored-by: Mervin Praison <[email protected]>
* fix: address lazy loading implementation issues
- Remove eager config import, move to lazy loading in _custom_handler
- Remove heavy modules from fallback_modules to prevent imports on typos
- Add proper tools/config/memory/workflows module access via _custom_handler
- Fix _EmbeddingProxy introspection with __wrapped__ and __signature__ properties
- Remove dead code in _custom_handler for embedding/embeddings
- Clean up duplicate comments and self-referential error messages
- Maintain full backward compatibility while improving startup performance
Fixes all issues identified in code review by Copilot, CodeRabbit, and Qodo.
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-authored-by: Mervin Praison <[email protected]>
* fix: address lazy loading implementation issues
- Fix _get_embedding_func to avoid overwriting embedding proxy
- Clean up dead code comments
- Update comments for clarity
- All validation tests pass: pa.tools, pa.config, embedding introspection
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Mervin Praison <[email protected]>
---------
Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
Co-authored-by: Mervin Praison <[email protected]>
Bot PR chain: trigger CodeRabbit + Qodo + Gemini → they post reviews →
copilot-after-coderabbit/qodo fires → Copilot reviews → Claude chains.
Copilot is NEVER triggered directly for bot PRs anymore. It waits
for upstream reviewers to finish first.
CodeRabbit and Qodo skip bot-authored PRs by default, breaking the
entire review chain (no reviews → no Copilot → no Claude).
Added bot-pr-review-chain job that fires on PR opened by
github-actions[bot] and directly triggers @coderabbitai, /review,
and @copilot.
Root .gitignore line 22 has 'output' which was excluding the
praisonaiagents/output/ module from git. This caused Windows CI
ModuleNotFoundError: No module named 'praisonaiagents.output.models'
Added gitignore exemption and force-added the missing files.
Was checking for 'copilot-swe-agent' but actual PR reviewer
posts as 'copilot-pull-request-reviewer[bot]'. This is why
Claude's final review was never triggered after Copilot.
Root cause: issues created with '--label claude' triggered both
'issues:opened' and 'issues:labeled' events in claude.yml.
Fix: remove 'opened' from claude.yml triggers (only fire on label).
Also: auto-issue-comment.yml skips if 'claude' label already exists.
Claude was only providing PR links instead of creating them.
CLAUDE.md is auto-read by claude-code-action and instructs Claude
to always use 'gh pr create' to create PRs automatically.
Root cause: PR #1170 had no Coderabbit review, so Copilot/Claude
were never triggered. Now fires after either reviewer, with dedup
check to prevent double @copilot comments.
Added detailed sections in README for using YAML with agents, including
two comprehensive examples illustrating agent collaboration and custom
tools. Updated AGENTS.md to reflect CLI and YAML parity, and emphasized
the requirement for real agentic tests in the implementation checklist.
- auto-pr-comment.yml: posts @copilot immediately on PR open
- auto-issue-comment.yml: posts @copilot immediately on issue open
- chain-claude-after-copilot.yml: watches for copilot-swe-agent comment,
then posts @claude as final reviewer (event-driven, no sleep delays)
- Saves ~16 min of wasted runner time per PR
- auto-pr-comment.yml: Copilot at T+6min (bloat guard), Claude at T+17min (final reviewer)
- auto-issue-comment.yml: Copilot triages first, Claude implements fix after
- claude.yml: remove post-review-comment job (caused infinite review cycles)
- Each bot has specialized role prompt instead of generic review
Security (#1157): Replace eval() with json.loads() in singlestore_vector.py,
AST-whitelisted evaluator in ai_generator.py, and AST node validation in
job_workflow.py/hybrid_workflow.py to prevent arbitrary code execution.
Performance (#1154): Convert eager module-level Rich imports to lazy
function-level imports in main.py, agents.py, knowledge.py, video_agent.py,
and image_agent.py — Rich is no longer loaded on `import praisonaiagents`.
https://claude.ai/code/session_01MZtrpciafckLxpmrn1z6P2
- Introduced `BudgetExceededError` for handling budget overages.
- Implemented budget tracking in the `Agent` class.
- Added properties for total cost and cost summary.
- Updated various agents to support budget constraints.
- Enhanced lazy loading to include new budget-related components.
- Extensive test coverage added for the new budget features.
LiteLLM v1.82.7 and v1.82.8 contained a credential stealer from a
supply chain attack (compromised PyPI maintainer via Trivy CI/CD).
Both versions removed from PyPI.
PraisonAI was NOT affected (installed 1.81.1), but as a defensive
measure, cap the upper bound at 1.82.6 (latest safe) until LiteLLM
completes their supply-chain review and resumes releases.
Ref: https://docs.litellm.ai/blog/security-update-march-2026
#1134: Decouple execute_code from optional deps (black/pylint/autopep8)
- execute_code is now a standalone module-level function
- PythonTools class retained for analyze/format/lint (lazy-init)
- Agents can now use execute_code without heavy optional deps
#1129: Thread-safety for remaining global mutable state
- Add _lazy_import_lock with double-checked locking for all 6 lazy-import
caches (_rich_console, _rich_live, _llm_module, _main_module, etc.)
- Add _env_cache_lock for class-level env var caches
(_env_output_mode, _default_model)
#1137: Clarify misleading TODO comment
- Updated TODO in llm.py to clarify this is code-level DRY, not
duplicate API calls per request
- Reject empty strings, keys containing "=" or NUL in _validate_env_key()
(CodeRabbit: malformed keys should fail during validation, not at os.environ)
- Validate root config is a dict after yaml.safe_load() (handles list/scalar/None)
- Validate deployment section is a dict before .get() calls
- Both raise ValueError caught by the existing handler → clean CLI error
- Add test_malformed_env_keys_rejected, test_non_dict_root_config_rejected,
test_non_dict_deployment_rejected (7 tests total, all passing)
Extract ~120 lines of duplicated approval code from _execute_tool_impl()
and execute_tool_async() into shared helpers _check_tool_approval_sync()
and _check_tool_approval_async(). Add threading.Lock to protect
_agent_counter, _server_started, _registered_agents, and _shared_apps
against concurrent access in multi-agent scenarios.
https://claude.ai/code/session_01WiGKiwTBj7xo5YoF3PYjWF
The --schedule-config YAML file allows setting arbitrary environment
variables via the "environment" section. An attacker who can supply or
modify this file could set keys like LD_PRELOAD, PATH, PYTHONPATH, etc.
to achieve arbitrary code execution.
Add _validate_env_key() with a blocklist of security-sensitive env var
names (dynamic linker, search paths, proxies) and call it before each
os.environ assignment in the schedule-config loading path.
Also add unit tests for the validation function.
- Replace hardcoded CHAINLIT_AUTH_SECRET with secrets.token_hex(32) fallback in all 5 UI files
(agents.py, bot.py, chat.py, code.py, realtime.py) — secret was public in git history
- Use hmac.compare_digest() for constant-time API key comparison in recipe/serve.py
- Disable debug=True by default in deploy.py generated api.py; use DEBUG env var
- Restrict exec() __builtins__ to safe subset in job_workflow.py inline Python execution;
prevents __import__('os').system() and similar arbitrary code execution patterns
Skipped shell=True changes (would break YAML run: steps with pipes/env vars) and
CORS wildcard changes (would break browser extension without env var migration path).
These require separate architectural discussion.
- Replace eval(e) in unified_server.py with AST-based safe math evaluator
- Replace exec(script_content) in run_with_langtrace.py with subprocess.run()
- Add nh3.clean() output sanitization in api.py to prevent XSS from markdown links
- Replace eval() in basic-tools.ts and custom-tool.ts with regex allowlist + Function constructor
- Replace eval() in simplified-api-test.ts and comprehensive-live.test.ts with safe evaluator
All changes are in example files and dev helper scripts only.
No SDK core code modified. Unit tests: 4341 passed, 0 new failures.
Updated the availability check for Crawl4AI to include Playwright browser installation advice. Improved error handling when starting the web crawler, ensuring users are informed if necessary binaries are missing. Incremented version in pyproject.toml to 1.5.78 and added new dependencies for crawling functionality.
Implemented logging for job execution history via a new RunRecord class.
This includes methods for logging job runs, retrieving execution history,
and persisting the history to a file. Enhancements to the config store
allow for configurable maximum history depth, improving traceability
of job executions.
Introduced a new schedule store utilizing YAML files for
persistence. This allows scheduled jobs to be stored under
the "schedules" key in the existing config.yaml, enhancing
thread safety and maintaining existing config information.
Updated related modules to integrate the new store.
Added a new ScheduleStoreProtocol to standardize schedule persistence backends.
Updated ScheduleLoop and ScheduleRunner to use the protocol, allowing various
implementations for schedule storage. Introduced _run_schedule_loop in BotOS
to ensure scheduled jobs execute alongside bot tasks. Updated project version to
1.5.75 for this update.
Improved the URL normalization logic to handle comma-separated URLs
passed as a single string. Updated version numbers in pyproject.toml
and uv.lock files to reflect the latest changes.
Updated email_tools to auto-detect available email backends (AgentMail or SMTP) based on environment variables. This refactor simplifies usage by providing generic tools while maintaining backend-specific functionalities. Enhanced documentation to reflect these changes and improve usability.
Enhanced BotConfig and related classes to support multiple operation modes (poll, ws, webhook, hybrid) and configurable webhook port. Updated documentation and validation for new parameters in the AgentMailBot for improved flexibility in message handling. Bumped version to 1.5.71.
feat(email_tools): add reply_email and create_inbox functions
Implemented reply_email for responding to emails and create_inbox for
creating new email inboxes in the AgentMail system. Updated integration
in the tool mappings and profiles to include new functionalities.
Enhanced tests to cover the new features.
```
Added an allowlist for MCP server commands to improve security by
rejecting disallowed and dangerous commands in the MCPHandler class.
Updated tests to verify the new validation logic and ensure expected
executables are accepted. Bumped version to 1.5.69.
feat(email): add AgentMail tools for sending and managing emails
- Introduced send_email, list_emails, and read_email functions.
- Added email_tools module for agent interaction.
- Updated tool mappings to include email functionalities.
- Included example YAML configuration for an AgentMail bot.
- Enhanced tests for email tools and added new test cases.
```
feat(bots): add email bot examples and functionalities
This commit introduces a new email bot feature, enabling agents to
interact through email via IMAP/SMTP. It includes example usage,
custom configurations, and a multi-platform approach, enhancing the
bot's usability in diverse environments.
```
docs(readme): refine performance section and enhance descriptions
Updated the performance metrics and descriptions to clarify advantages of PraisonAI. Improved consistency in terminology for better readability.
```
feat(bots): add EmailBot for IMAP polling and SMTP sending
This commit introduces the EmailBot, enabling integration with email
services using IMAP for receiving messages and SMTP for sending.
Updates include new environment variables for configuration,
enhancements to the bot registry, and modifications to schema and
initialization logic for seamless integration.
```
fix(agent): handle potential None value for agent name
Updated agent hash generation to default to "agent" when name is None.
Bumped version to 1.5.63 to reflect this change.
```
feat(tests): add deep performance profiling integration test
Introduced a new integration test to run cProfile-wrapped Agent prompts.
This test stores detailed function-level breakdown as JSONL for regression
tracking and comparison of performance over time. Updated version number
and modified documentation accordingly.
```
feat(llm): add support for OpenAI Responses API
- Implemented methods to check model compatibility with the Responses API.
- Added functionality to transform Chat Completions messages to Responses API parameters.
- Updated agent and budgeter context for new model types and limits.
- Cleaned up test cases for database integration to remove unnecessary parameters.
```
Added a guideline in the system prompt to explain actions before tool calls, enhancing clarity and transparency in interactions. Updated version to 1.5.58 to reflect changes.
Added a `_doom_recovery_active` flag to manage agent behavior during
doom loops. This prevents normal termination signals when a doom loop
is detected, allowing the system to handle recovery more effectively.
Updated relevant sections in `agent.py` and adjusted unit tests to
reflect changes. Bumped version to 1.5.56.
Improved handling of agent's chat responses, including better
doom loop detection. Added intermediate narrative emission for LLM
tool calls, enhancing transparency in execution logic.
Updated tests to cover new functionality.
This test evaluates the functionality of the tool_completion fix
with a detailed multi-tool prompt. It includes tasks such as
web searching, file creation, execution, and reporting.
- Added completion callback for tool-call completion if the model used tools and produced a substantive response.
- Updated `execute_tool` and `_execute_tool_with_context` methods to include `tool_call_id` for better event correlation.
- Improved logging for tool execution within the agent's framework.
Introduced `store_learning` and `search_learning` functions to
facilitate categorized storage and retrieval of user insights and
preferences. Enhanced agent interaction by allowing agents to
remember and recollect user behaviors across sessions. Updated
agent state to include a learn manager for integration with the
learning system.
- Introduced optional bearer token for POST /a2a requests
- Added serve method for standalone A2A server using FastAPI
- Updated router to enforce authentication when token is set
- Enhanced message parsing to support additional part types
Added detailed usage examples for single, multi agents, MCP, custom tools, and persistence. Included a quick reference for CLI commands to improve user onboarding. Removed outdated sections for clarity.
Updated the "Why PraisonAI?" section for clarity and conciseness,
retaining key features while enabling easier navigation with an
expandable details section to view all features.
Modified logo dimensions and enhanced the documentation layout by
refactoring sections related to quick start instructions and added
details on supported LLM providers. Overall goal was to improve
readability and user experience.
Updated README.md to reflect changes in logo paths, added new features,
and improved contribution guidelines. Added 24 new provider icons to
public directory for better integration visibility.
Revised feature names for clarity and consistency, changing "Dashboard UI" to "AgentClaw." Added a new section outlining various use cases for AI agents across multiple industries. Updated links and formatting for better readability.
Updated Dockerfiles and project files to use praisonai version 4.5.43
and praisonaiagents version 1.5.43 for improved functionality and
features. Added new 'claw' command in the CLI for enhanced user
experience.
Updated the project description to highlight key features and capabilities, including automation, supported platforms, and other enhancements for better understanding.
Revised multiple links in the README to point to the correct documentation
pages, specifically changing references from features to concepts to enhance
user navigation and comprehension.
Added a new entry for the Dashboard UI in the README and updated
the version of `praisonaiagents` to 1.5.41 in the relevant files.
This reflects recent changes and improvements in UI capabilities.
Updated README.md to highlight new bot functionalities including Telegram,
Discord, Slack, and WhatsApp integration. Increased version to 1.5.40
in `pyproject.toml` for `praisonaiagents`. Expanded dependencies for
claw in the main `pyproject.toml`. Enhanced .gitignore to include
build files.
Replaced outdated links in the README file with new feature documentation
links to ensure users have access to the latest information about the
project's capabilities.
Added several new features to the README.md including Sessions + Auto-Save, Telemetry, Policy Engine, Thinking Budgets, Background Tasks, Doom Loop Detection, Graph Memory, RAG + Quality-Based RAG, and Sandbox Execution.
Enhanced the features section with specific feature descriptions and
usage examples to provide clearer insights into the framework's
capabilities and benefits for new users.
The README.md has been significantly updated with a focus on clear
guidance and reduced verbosity. Many sections were condensed or
removed, resulting in a net decrease in lines while enhancing
navigation and support links for users.
Added an optional session_id parameter to DeliveryTarget and scheduling
functions to preserve conversation context during job execution. This
enhancement allows agents to access prior chat history and improves
overall task management flexibility. Updated relevant documentation and
CLI commands accordingly.
Added a MongoDB backend for storage, which allows document-oriented
data storage. Implemented protocol-compliant aliases for memory operations
to improve consistency. Updated related memory management logic to support
new functionality, enhancing overall performance and user experience.
Updated various parts of the codebase to centralize directory paths
using the new `paths.py` utility. This improves maintainability and
consistency across the project when accessing directory paths for
plugins, snapshots, memory, and configuration.
Added integration and unit tests to ensure correct behavior of path
configurations.
MODEL_WINDOWS had two entries for gpt-4o-mini and none for gpt-4o.
The first entry was clearly intended to be gpt-4o based on context.
This meant gpt-4o users got no context window match, potentially
causing suboptimal chunking or fallback behavior.
Signed-off-by: JiangNan <[email protected]>
When an agent is created with instructions but no explicit name, and
memory history is enabled, name can be None. Calling .encode() on None
raises AttributeError. Fall back to "agent" when name is None.
Signed-off-by: JiangNan <[email protected]>
- Implement lazy loading for WebSocketGateway and GatewaySession in the
gateway module, allowing easier access without needing wrapper imports.
- Enhance SessionData to include gateway session ID and agent ID.
- Introduce methods in DefaultSessionStore for querying sessions by agent
and linking sessions to gateway sessions.
Introduced new YAML workflow examples demonstrating agent-centric steps
and hybrid workflows. The agent-centric job workflow supports roles
like Technical Writer and includes quality checks, while the hybrid
workflow combines deterministic steps with multi-agent coordination.
Updated version to 1.5.26 for the praisonai-agents package.
Added examples for file-based actions (line count and system info)
and YAML-defined actions in new workflow files. Updated relevant
files to support these actions, enhancing the capabilities for
custom workflows. Updated package version to 1.5.25.
run_skill_script executes arbitrary .py/.sh/.js scripts via subprocess.run
without any approval gate. Add @require_approval(risk_level='critical') to
both the class method and module-level wrapper, matching the pattern used
by shell_tools and python_tools.
- Discord: test DISCORD_CHANNEL_ID env fallback, SSL verify default/override
- Telegram: test TELEGRAM_CHAT_ID env fallback, SSL verify default/override
- Webhook: test integer status does not crash str().lower()
MANDATORY: Before writing any code, you MUST carefully read "src/praisonai-agents/AGENTS.md" to understand this repository's extremely specific Architecture, Protocol-First design rules, and Agent-Centric Philosophy.
Before implementing anything, answer these questions:
- CORE vs WRAPPER vs TOOLS ROUTING:
1. Core SDK (praisonaiagents/): Only core protocols, base classes, decorators. No heavy implementations.
2. Wrapper (praisonai/): CLI, heavy implementations, optional dependencies.
3. Tools (PraisonAI-Tools): Specific integrations, external tools (e.g. SurrealDB, Slack), and community extensions MUST go to the `MervinPraison/PraisonAI-Tools` repository. If the feature is a tool, clone `https://github.com/MervinPraison/PraisonAI-Tools`, implement it there, and create the PR using `gh pr create -R MervinPraison/PraisonAI-Tools`.
- Does it duplicate existing functionality? Check if Agent already supports this via existing params (reflection, planning, tools, hooks, memory).
- Does it inherit from Agent properly? New agent types MUST inherit Agent, not wrap it with composition.
- Does it add new dependencies? Only optional deps allowed, must be lazy-imported.
- Will agent.py grow larger? If the change adds >50 lines to agent.py, find a way to extract instead.
- Is there a name collision with existing exports in __init__.py?
If ANY of these conceptual checks fail (excluding routing), add a comment to the issue explaining why and close it. Do NOT create a PR.
STEP 3 — IMPLEMENT:
- Create a new git branch appropriately named (e.g. \`feature/issue-<number>\`)
- Follow protocol-driven design: protocols in core SDK, heavy implementations in wrapper
goal:"Read the GitHub issue, understand the required changes, and map the problem to the local codebase"
backstory:"You are an expert software analyst who reads bug reports and feature requests. You excel at taking a problem description and finding exactly which files in the codebase need to be modified. Your primary job is discovery and planning."
tools:
- "execute_command"
software_engineer:
role:"Autonomous Software Engineer"
goal:"Implement required code changes on a branch, run tests, commit, and push"
backstory:"You are a senior software engineer. You always branch first, implement changes using shell commands, verify with git diff, run tests, then commit and push. You never create a Pull Request unless the issue body explicitly requests one."
tools:
- "execute_command"
- "github_create_branch"
- "github_commit_and_push"
- "github_create_pull_request"
steps:
- name:Analyze Issue
agent:issue_analyst
action:>
Thoroughly analyze the issue and the repository. Follow these steps in order.
First, set up git identity: execute_command 'git config user.name PraisonAI' then
execute_command 'git config user.email [email protected]'. Do NOT pass cwd.
Second, read the issue: execute_command 'cat .github/triage-context.md'. Do NOT pass cwd.
goal:"Identify security vulnerabilities, authentication issues, input validation problems, and unsafe code practices in the PR changes"
backstory:"You are a cybersecurity expert specializing in code analysis. You have extensive experience in identifying common security flaws like injection attacks, authentication bypasses, exposed secrets, and unsafe data handling patterns."
tools:
- "execute_command"
performance_reviewer:
role:"Performance Code Reviewer"
goal:"Analyze code changes for performance implications, identify bottlenecks, inefficient algorithms, and resource usage issues"
backstory:"You are a performance optimization specialist with deep knowledge of algorithm efficiency, memory management, and system performance. You excel at spotting code that could cause performance degradation."
tools:
- "execute_command"
maintainability_reviewer:
role:"Code Quality & Maintainability Reviewer"
goal:"Evaluate code structure, readability, documentation, naming conventions, and adherence to best practices"
backstory:"You are a software engineering expert focused on code quality and maintainability. You ensure code follows established patterns, is well-documented, and will be easy for future developers to understand and modify."
tools:
- "execute_command"
lead_reviewer:
role:"Lead Technical Reviewer"
goal:"Synthesize all review feedback, make final recommendations, and post comprehensive review comments to the GitHub PR"
backstory:"You are a senior technical lead responsible for final review decisions. You coordinate input from security, performance, and maintainability reviewers to provide balanced, actionable feedback to the development team."
tools:
- "execute_command"
steps:
- name:security_analysis
agent:security_reviewer
action:|
Analyze the PR diff for security issues:
1. Extract PR details: `echo "$PR_DATA"`
2. Get changed files: `echo "$CHANGED_FILES"`
3. Review full diff: `gh pr diff ${PR_NUMBER}`
4. Look for:
- Hardcoded secrets, API keys, passwords
- SQL injection vulnerabilities
- XSS vulnerabilities
- Authentication/authorization bypasses
- Unsafe file operations
- Command injection risks
- Missing input validation
- Exposed sensitive data
5. Document findings with file paths and line numbers
expected_output:"Detailed security analysis report with specific vulnerabilities found, severity levels, and remediation suggestions"
- name:performance_analysis
agent:performance_reviewer
action:|
Analyze the PR diff for performance issues:
1. Review algorithm complexity changes
2. Check for inefficient database queries
3. Identify memory leaks or excessive allocations
4. Look for hot-path regressions
5. Check for blocking I/O operations
6. Analyze module-level imports that could slow startup
7. Review caching implementations
8. Check for recursive operations without termination
9. Document performance concerns with impact estimates
expected_output:"Performance analysis report highlighting bottlenecks, efficiency concerns, and optimization recommendations"
- name:maintainability_analysis
agent:maintainability_reviewer
action:|
Analyze the PR diff for code quality and maintainability:
1. Check naming conventions consistency
2. Evaluate code structure and organization
3. Review documentation completeness
4. Check for DRY violations
5. Analyze error handling patterns
6. Review test coverage for changes
7. Check adherence to repository coding standards
8. Evaluate API design consistency
9. Look for technical debt introduction
expected_output:"Code quality analysis with specific recommendations for improving maintainability and readability"
- name:final_review
agent:lead_reviewer
action:|
Synthesize all reviews and post final comprehensive feedback:
1. Collect input from security, performance, and maintainability reviews
2. Prioritize findings by severity (Critical, High, Medium, Low)
3. Create structured review comment using this format:
## 📋 Review Summary
[2-3 sentence overview and assessment]
## 🔍 General Feedback
[Overall patterns and observations]
## 🎯 Specific Feedback
### 🔴 Critical (if any)
[Security vulnerabilities, breaking changes, major bugs]
console.log('Issue already has claude label, skipping');
return;
}
// Add label to trigger claude.yml via issues:labeled event
await github.rest.issues.addLabels({
issue_number: context.issue.number,
owner: context.repo.owner,
repo: context.repo.repo,
body: '@claude review this issue and do a detailed analysis and fix this if the existing code doesn\'t have the solution implemented. Making sure it has backward compatibility, no existing features removed. After making those changes, again review the applied changes. Use @web to search if you dont know any information or to find the latest documentation or to find the latest version. Run the code if you think you need to run it to test it. Minimal code change to start with if required any changes. MAINLY IT SHOULD NOT IMPACT ON THE CURRENT SPEED OF EXECUTION of existing features, not increasing the overhead. **Please create a PR using gh tool with your changes**.'
})
labels: ['claude']
});
// Also post instructions as a comment for context
await github.rest.issues.createComment({
issue_number: context.issue.number,
owner: context.repo.owner,
repo: context.repo.repo,
body: '🤖 Auto-triaging with Claude. Analyzing issue and implementing a fix...\n\nClaude will:\n1. Classify this issue\n2. Search codebase for root cause\n3. Implement a minimal fix following AGENTS.md\n4. Create a PR with the changes'
body: '@claude review this pull request and do a detailed analysis and fix this if the existing code doesn\'t have the solution implemented. Making sure it has backward compatibility, no existing features removed. After making those changes, again review the applied changes. Use @web to search if you dont know any information or to find the latest documentation or to find the latest version. Run the code if you think you need to run it to test it. Minimal code change to start with if required any changes. MAINLY IT SHOULD NOT IMPACT ON THE CURRENT SPEED OF EXECUTION of existing features, not increasing the overhead.'
})
body: '@copilot Do a thorough review of this PR. Read ALL existing reviewer comments above from Qodo, Coderabbit, and Gemini first — incorporate their findings.\n\nReview areas:\n1. **Bloat check**: Are changes minimal and focused? Any unnecessary code or scope creep?\n2. **Security**: Any hardcoded secrets, unsafe eval/exec, missing input validation?\n3. **Performance**: Any module-level heavy imports? Hot-path regressions?\n4. **Tests**: Are tests included? Do they cover the changes adequately?\n5. **Backward compat**: Any public API changes without deprecation?\n6. **Code quality**: DRY violations, naming conventions, error handling?\n7. **Address reviewer feedback**: If Qodo, Coderabbit, or Gemini flagged valid issues, include them in your review\n8. Suggest specific improvements with code examples where possible'
body: '@copilot Do a thorough review of this PR. Read ALL existing reviewer comments above first.\n\nReview areas:\n1. **Bloat check**: Are changes minimal and focused?\n2. **Security**: Any hardcoded secrets, unsafe eval/exec, missing input validation?\n3. **Performance**: Any module-level heavy imports? Hot-path regressions?\n4. **Tests**: Are tests included? Do they cover the changes adequately?\n5. **Backward compat**: Any public API changes without deprecation?\n6. **Code quality**: DRY violations, naming conventions, error handling?\n7. Suggest specific improvements with code examples where possible'
const claudeBody = '@claude You are the FINAL architecture reviewer. If the branch is under MervinPraison/PraisonAI (not a fork), you are able to make modifications to this branch and push directly. SCOPE: Focus ONLY on Python packages (praisonaiagents, praisonai). Do NOT modify praisonai-rust or praisonai-ts. ' + reviewSummary + '.\n\n' +
body: '@claude You are the FINAL architecture reviewer. If the branch is under MervinPraison/PraisonAI (not a fork), you are able to make modifications to this branch and push directly. SCOPE: Focus ONLY on Python packages (praisonaiagents, praisonai). Do NOT modify praisonai-rust or praisonai-ts. Read ALL comments above from Gemini, Qodo, CodeRabbit, and Copilot carefully before responding.\n\n**Phase 1: Review per AGENTS.md**\n1. Protocol-driven: check heavy implementations vs core SDK\n2. Backward compatible: ensure zero feature regressions\n3. Performance: no hot-path regressions\n\n**Phase 2: FIX Valid Issues**\n4. For any VALID bugs or architectural flaws found by Gemini, CodeRabbit, Qodo, Copilot, or any other reviewer: implement the fix\n5. Push all code fixes directly to THIS branch (do NOT create a new PR)\n6. Comment a summary of exact files modified and what you skipped\n\n**Phase 3: Final Verdict**\n7. If all issues are resolved, approve the PR / close the Issue\n8. If blocking issues remain, request changes / leave clear action items'
body: '@claude You are the FINAL architecture reviewer. If the branch is under MervinPraison/PraisonAI (not a fork), you are able to make modifications to this branch and push directly. SCOPE: Focus ONLY on Python packages (praisonaiagents, praisonai). Do NOT modify praisonai-rust or praisonai-ts. Read ALL comments above from Gemini, Qodo, CodeRabbit, and Copilot carefully before responding.\n\n**Phase 1: Review per AGENTS.md**\n1. Protocol-driven: check heavy implementations vs core SDK\n2. Backward compatible: ensure zero feature regressions\n3. Performance: no hot-path regressions\n\n**Phase 2: FIX Valid Issues**\n4. For any VALID bugs or architectural flaws found by Gemini, CodeRabbit, Qodo, Copilot, or any other reviewer: implement the fix\n5. Push all code fixes directly to THIS branch (do NOT create a new PR)\n6. Comment a summary of exact files modified and what you skipped\n\n**Phase 3: Final Verdict**\n7. If all issues are resolved, approve the PR / close the Issue\n8. If blocking issues remain, request changes / leave clear action items'
body: '@claude You are the Lead Engineer. If the branch is under MervinPraison/PraisonAI (not a fork), you are able to make modifications to this branch and push directly. SCOPE: Focus ONLY on Python packages (praisonaiagents, praisonai). Do NOT modify praisonai-rust or praisonai-ts. Read ALL analysis and reviews above carefully (Gemini, CodeRabbit, Qodo, Copilot, etc).\n\n**Phase 1: Review per AGENTS.md**\n1. Protocol-driven: check heavy implementations vs core SDK\n2. Backward compatible: ensure zero feature regressions\n3. Performance: no hot-path regressions\n\n**Phase 2: FIX Valid Issues**\n4. For any VALID bugs or architectural flaws found by Gemini, CodeRabbit, Qodo, Copilot, or any other reviewer: implement the fix\n5. Push all code fixes directly to THIS branch (do NOT create a new PR)\n6. Comment a summary of exact files modified and what you skipped\n\n**Phase 3: Final Verdict**\n7. If all issues are resolved, approve the PR / close the Issue\n8. If blocking issues remain, request changes / leave clear action items'
${{ steps.check_fork.outputs.is_fork == 'true' && 'CRITICAL: THIS IS A PULL REQUEST FROM A FORK. YOU DO NOT HAVE PUSH PERMISSIONS TO THIS REPOSITORY. ONLY READ FILES, VALIDATE CODE, AND PROVIDE YOUR COMMENTS/FEEDBACK DIRECTLY IN THIS PR VIA COMMENTS. DO NOT ATTEMPT TO PUSH OR CREATE PULL REQUESTS.\n\n' || 'NOTE: The branch is under MervinPraison/PraisonAI (not a fork). You are able to make modifications and push directly to this branch.\n\n' }}
You are working on the PraisonAI SDK. Follow AGENTS.md strictly.
STEP 0 — SETUP GIT IDENTITY & AUTH (GLOBAL — required for all repos):
When work must happen in a different repository, follow these steps EXACTLY. Do NOT attempt to use `cd`, as directory state is not preserved. Use `git -C` for all commands.
- For SDK changes: cd src/praisonai-agents && PYTHONPATH=. python -m pytest tests/ -x -q --timeout=30
- For docs changes: verify files exist and are valid markdown/MDX
- Ensure no regressions
STEP 5 — CREATE PR:
- Commit with descriptive message, push, and create PR using `gh pr create`
- For external repos, use `gh pr create -R MervinPraison/<REPO_NAME>`
CRITICAL: You MUST create the PR automatically using `gh pr create`. Do NOT just provide a link or say "manual push required".
NOTE: If you worked on an external repo, the wrapper action will report "No commits" for the main repo at the end. This is expected, do not worry about it.
const reviewText = '@claude review if the changes made in the above branch are as per the requirements and make changes to the above branch if issues still exist.';
let comments = [];
let issueNumber;
try {
// Determine issue/PR number based on event type
if (context.eventName === 'pull_request_review_comment' || context.eventName === 'pull_request_review') {
} else if (context.eventName === 'issue_comment' && context.payload.issue.pull_request) {
// This is a comment on a PR (not an issue)
issueNumber = context.payload.issue.number;
isPR = true;
} else {
// This is a regular issue - don't post review comment
issueNumber = context.issue.number;
isPR = false;
}
// Only post review comment on PRs, not regular issues
if (isPR) {
console.log(`Posting review comment on PR #${issueNumber}`);
await github.rest.issues.createComment({
issue_number: issueNumber,
owner: context.repo.owner,
repo: context.repo.repo,
body: '@claude review if the changes made in the above branch are as per the requirements and make changes to the above branch if issues still exist. MAINLY IT SHOULD NOT IMPACT ON THE CURRENT SPEED OF EXECUTION of existing features, not increasing the overhead.'
});
} else {
console.log(`Skipping review comment for regular issue #${issueNumber}`);
You are a helpful GitHub issue assistant. Your task is to analyze and help with GitHub issues.
@@ -103,6 +108,8 @@ jobs:
- Search codebase for related files using `glob`, `search_file_content`, `list_directory`
**STEP 2: If Code Changes Are Needed**
MANDATORY FIRST STEP: Before writing any code, you MUST use `read_file` to carefully read "src/praisonai-agents/AGENTS.md". You must honor this repository's extremely specific Architecture, Protocol-First design rules, and Agent-Centric Philosophy!
MANDATORY FIRST STEP: Before writing any code, you MUST use `read_file` to carefully read "src/praisonai-agents/AGENTS.md". You must honor this repository's extremely specific Architecture, Protocol-First design rules, and Agent-Centric Philosophy!
**IMPORTANT:** DO NOT create a new branch! Work on the EXISTING PR branch.
praisonai "Build a mini calculator - create /tmp/calculator.py with add, subtract, multiply, divide functions, write unit tests in /tmp/test_calculator.py using unittest, run the tests to make sure they pass, then generate a coverage-style report in /tmp/calc_report.md listing which functions were tested and read it back" --trust
praisonai "Create a Python file at /tmp/fibonacci.py that generates the first 20 Fibonacci numbers, run it to verify the output is correct, then write a summary to /tmp/fib_summary.md explaining the algorithm you used and the output, finally read back both files to confirm everything looks good" --trust
# Multi-step research: web search, file creation, code execution, reporting
# Tests: web search, file write, code execution, markdown report, file read, directory listing, system info
praisonai "Research the top 3 Python web frameworks (Django, FastAPI, Flask), then: 1) Search the web for each framework's latest version and key features, 2) Create a file called /tmp/framework_comparison.py that contains a Python dictionary with the comparison data, 3) Execute the code to verify the dictionary is valid, 4) Write a markdown report to /tmp/framework_report.md summarizing your findings in a table format, 5) Read back the report file to verify it was written correctly, 6) List the files in /tmp to confirm both files exist, 7) Get system info to note what OS this report was generated on, 8) Analyze the Python code you wrote for any issues, 9) Format the Python code properly, 10) Finally search for any recent news about Python 3.13 features" --trust
praisonai "Investigate my system - get the current date, check disk usage, find out what Python version is installed, list running processes sorted by memory, then write all findings to /tmp/system_audit.md as a neat report and read it back to verify" --trust
praisonai "Write a todo list app at /tmp/todo.py with functions to add, remove, and list tasks stored in /tmp/todos.json, run the script with some sample tasks added, then create documentation at /tmp/todo_docs.md explaining usage with examples, and verify all three files exist" --trust
praisonai "Search the web for the current weather in Tokyo, create a JSON file at /tmp/weather_data.json with the findings, then write a Python script at /tmp/parse_weather.py that reads the JSON and prints a formatted weather report, execute the script, and list all files you created in /tmp" --trust
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