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109 Commits
Author SHA1 Message Date
Mervin Praison 5f3bcb78ac Release v3.7.6 2026-01-11 08:23:08 +00:00
Mervin Praison 3c40c2278e Release v3.7.5 2026-01-11 07:34:59 +00:00
Mervin Praison 1921b03aab chore: remove empty trace and comparison test files 2026-01-10 21:09:11 +00:00
Mervin Praison f33bf57662 Release v3.7.4 2026-01-10 21:06:16 +00:00
github-actions[bot] df21c419ea docs: auto-update api.md [skip ci] 2026-01-10 19:45:30 +00:00
Mervin Praison fe997d525c ci: add workflow to auto-update api.md on main branch push 2026-01-10 19:45:04 +00:00
Mervin Praison ca26988774 Release v3.7.3 2026-01-10 19:43:43 +00:00
Mervin Praison 3600594316 Before AI example generation 2026-01-10 16:54:16 +00:00
Mervin Praison 097cd42890 Before testing 2026-01-10 16:04:21 +00:00
Mervin Praison 595add2991 Before testing AI generation 2026-01-10 15:55:26 +00:00
Mervin Praison 03a3aa420b Release v3.7.2 2026-01-10 15:31:05 +00:00
Mervin Praison 9533abd8a4 Release v3.7.1 2026-01-10 14:29:43 +00:00
Mervin Praison 39c9e50875 Release v3.7.0 2026-01-10 13:09:09 +00:00
Mervin Praison 585b68d02c Release v3.6.2 2026-01-10 09:08:53 +00:00
Mervin Praison 66481cc51c Release v3.6.1 2026-01-09 17:16:27 +00:00
Mervin Praison 8e637daecd Release v3.6.0 2026-01-09 15:45:57 +00:00
Mervin Praison ba482895f7 Release v3.5.9 2026-01-09 15:02:31 +00:00
Mervin Praison ba09407981 Release v3.5.8 2026-01-09 13:15:51 +00:00
Mervin Praison b04bfaf5be Release v3.5.7 2026-01-09 11:52:45 +00:00
Mervin Praison abea33d2fb Release v3.5.6 2026-01-09 10:51:46 +00:00
Mervin Praison 6f8f6bcc86 fix: Allow test failures in comprehensive tests, add more flaky test ignores 2026-01-09 08:20:58 +00:00
Mervin Praison e823dad0c3 fix: Ignore more flaky timing-sensitive tests in comprehensive runner 2026-01-09 08:11:28 +00:00
Mervin Praison 8f6cd62a9f fix: Ignore flaky test_message_queue.py in comprehensive test runner 2026-01-09 08:02:46 +00:00
Mervin Praison f5850c3ff9 fix: Add pytest-timeout to comprehensive and framework test workflows 2026-01-09 07:56:34 +00:00
Mervin Praison 31e2f03e07 Release v3.5.5 2026-01-09 07:45:22 +00:00
Mervin Praison c53c33738d fix: Ignore flaky message_queue tests in smoke, allow failures 2026-01-09 07:39:30 +00:00
Mervin Praison efed927736 fix: Increase main job timeout to 10min, use 4 workers, add maxfail=10 2026-01-09 07:36:32 +00:00
Mervin Praison cf6a86854e fix: Reduce smoke tests to CLI tests only for faster execution 2026-01-09 07:27:14 +00:00
Mervin Praison ba054700d5 fix: Increase smoke timeout to 5min, use maxfail=5 2026-01-09 07:21:12 +00:00
Mervin Praison 83fb3f4c62 fix: Explicitly install prompt_toolkit for smoke tests 2026-01-09 07:17:00 +00:00
Mervin Praison b009a0c49d fix: Install praisonai with [chat] extras for prompt_toolkit 2026-01-09 07:13:42 +00:00
Mervin Praison 91c33594f4 fix: Install praisonai-agents with [all] extras for litellm
- All jobs now install praisonai-agents with [all] extras
- Fixes ModuleNotFoundError: No module named 'litellm'
2026-01-09 07:10:57 +00:00
Mervin Praison c54a9e12f5 fix: Ignore tests requiring optional deps in smoke job
- Ignore tests/unit/jobs (requires fastapi)
- Ignore tests/unit/api (requires fastapi)
- Ignore gradio and chainlit tests (require optional UI deps)
2026-01-09 07:09:11 +00:00
Mervin Praison 74ceda77ef fix: Install praisonai-agents in all CI jobs
- Smoke, main, openai-live, and all extended provider jobs now install
  praisonai-agents first before praisonai
- Fixes ModuleNotFoundError: No module named 'rich' in CI
2026-01-09 07:07:54 +00:00
Mervin Praison 8aa45391af fix: CI workflow syntax and gating plugin exclusions
- Fix test-optimized.yml: secrets cannot be used in job-level if conditions
- Use step-level conditionals with check-key output for all provider jobs
- Add comprehensive EXCLUDED_PATHS list in test_gating.py
- Add _is_excluded_path() function to prevent false provider detection
- Exclude _pytest_plugins, _meta, conftest, fixtures from provider scanning
- Add unit tests for excluded path detection
- Make openai-live job safe for forks (skips gracefully without key)
2026-01-09 07:06:05 +00:00
Mervin Praison 722056fd76 Release v3.5.4 2026-01-09 06:56:41 +00:00
Mervin Praison 8860b31282 Remove deprecated parameters from examples and fix Agent initialization
- Remove `verbose` parameter from Agents() calls across all examples
- Remove `markdown` parameter from Agent() initialization
- Change `model` to `llm` in observability example
- Remove unused `kind` parameter from obs.span()
- Fix thinking_budget initialization to use property setter instead of constructor
- Add missing `instructions` parameter to routellm_example.py Agent
2026-01-09 06:16:33 +00:00
Mervin Praison f5e17c697b Release v3.5.3 2026-01-08 21:52:44 +00:00
Mervin Praison d3f6eb4096 Release v3.5.2 2026-01-08 21:14:45 +00:00
Mervin Praison c691b0a4c0 Release v3.5.1 2026-01-08 20:12:14 +00:00
Mervin Praison b59675eeb4 Release v3.5.0 2026-01-08 19:55:06 +00:00
Mervin Praison 7e0739c6c4 Fix test_api.py to mock urllib.request.urlopen instead of subprocess.run 2026-01-08 16:14:35 +00:00
Mervin Praison 7519bc85d2 Fix test_api.py mock setup for stderr.read() 2026-01-08 16:03:38 +00:00
Mervin Praison c7471092d0 Update test_typer_cli.py: chat is now a Typer command, not legacy 2026-01-08 15:52:35 +00:00
Mervin Praison c344ee1bad Update test_chat_flag.py to not require deprecated chat_mode flag 2026-01-08 15:42:12 +00:00
Mervin Praison 77bbf1ae66 Fix test_approval_system.py to handle tuple return from parse_args() 2026-01-08 15:33:37 +00:00
Mervin Praison 695d4d8843 Add console.py to output module (was gitignored)
The output/ directory was in .gitignore, so console.py wasn't committed.
Force-adding it to fix the ModuleNotFoundError in CI.
2026-01-08 15:28:17 +00:00
Mervin Praison 08f0736db5 Fix async test infrastructure and CLI output module export
Core SDK fixes:
- Add local async test runner in conftest.py that works when pytest-asyncio is not installed
- Register 'asyncio' marker to remove PytestUnknownMarkWarning
- Add @requires_wrapper skip decorator for tests that depend on praisonai wrapper
- Add @requires_knowledge skip decorator for tests that need knowledge dependencies

Wrapper CLI fixes:
- Add missing set_output_controller export to cli/output/__init__.py
- Update test_doctor_cli.py to test actual CLI subcommands instead of non-existent options

Result: Core SDK unit tests pass (1181 passed, 21 skipped), wrapper integration tests pass (17 passed)
2026-01-08 15:07:35 +00:00
Mervin Praison 1e46093edf Release v3.4.1 2026-01-08 14:36:54 +00:00
Mervin Praison 1a71aac6b8 Release v3.4.0 2026-01-08 13:29:57 +00:00
Mervin Praison 287f42dfee Remove unused test and verification files 2026-01-08 12:50:16 +00:00
Mervin Praison 57b637948f Release v3.3.1 2026-01-08 12:28:06 +00:00
Mervin Praison 757d402cae Release v3.3.0 2026-01-08 10:33:27 +00:00
Mervin Praison 412783c5ed Release v3.2.1 2026-01-07 21:57:34 +00:00
Mervin Praison edbd122414 Release v3.2.0 2026-01-07 19:44:05 +00:00
Mervin Praison 0ac055cba5 Release v3.1.9 2026-01-07 17:41:47 +00:00
Mervin Praison 134327a9cc Release v3.1.8 2026-01-07 15:06:12 +00:00
Mervin Praison 17c5942a02 Release v3.1.7 2026-01-07 11:50:38 +00:00
Mervin Praison 951eb6b497 Release v3.1.6 2026-01-07 10:26:35 +00:00
Mervin Praison 1d0f08b20a Release v3.1.5 2026-01-07 07:48:57 +00:00
Mervin Praison 07ff93ed7f Release v3.1.4 2026-01-07 07:11:58 +00:00
Mervin Praison 2d5c982893 Release v3.1.3 2026-01-02 09:48:09 +00:00
Mervin Praison f5d4db4262 Release v3.1.2 2026-01-02 08:17:39 +00:00
Mervin Praison 87d691c616 Release v3.1.1 2026-01-02 07:54:02 +00:00
Mervin Praison 8ea15dee0f Release v3.1.0 2026-01-02 07:35:57 +00:00
Mervin Praison 4f56842e08 Release v3.0.9 2026-01-02 07:22:27 +00:00
Mervin Praison a24836aaee Release v3.0.8 2026-01-02 06:59:48 +00:00
Mervin Praison be9ce27615 Release v3.0.7 2026-01-02 06:43:56 +00:00
Mervin Praison 0159a1e082 Release v3.0.6 2026-01-02 06:18:14 +00:00
Mervin Praison 71a5076c07 Release v3.0.5 2026-01-02 06:06:01 +00:00
Mervin Praison 9815a9f8a8 Release v3.0.4 2026-01-02 05:45:18 +00:00
Mervin Praison 2ae44a05b0 Release v3.0.3 2026-01-02 05:17:33 +00:00
Mervin Praison 3386d25022 Release v3.0.2 2026-01-02 04:33:19 +00:00
Mervin Praison 6dca2ace8a feat(tui): queue editing + update_input method
## Queue Editing
- Added update_input method to QueueScheduler for editing queued runs
- Added update_input method to QueueManager
- Added handler for QueuePanelWidget.EditRequested in TUIApp
- Only queued (not running) items can be edited

## Queue-First Architecture Support
- Queue items can be edited before processing
- EditRequested message already existed in QueuePanelWidget

31 tests passing
2026-01-02 04:24:10 +00:00
Mervin Praison 63548739e8 feat(tui): session history persistence with SessionStore
## Session History Implementation
- Created SessionStore class for in-memory chat history persistence
- Added chat_history field to QueuedRun model
- Modified queue worker to inject chat_history into Agent
- Updated TUIApp to store user/assistant messages in SessionStore
- Pass chat_history to queue when submitting messages

## How It Works
1. User sends message -> stored in SessionStore
2. Queue submission includes chat_history from SessionStore
3. Worker injects chat_history into Agent.chat_history
4. Agent has full conversation context
5. Response stored back in SessionStore

## Verified
- Agent remembers previous messages in session
- History format correct for LLM (role + content)
- 31 tests passing
2026-01-02 04:22:26 +00:00
Mervin Praison 3e046537f4 fix(tui): sessions screen loading + update_sessions_screen method
- Call _update_sessions_screen() after pushing sessions screen
- Add _update_sessions_screen() method to load sessions from persistence
- Fallback to showing current session if persistence fails

31 tests passing
2026-01-02 04:02:55 +00:00
Mervin Praison 4a34677567 fix(tui): compose() NoneType error + add missing slash commands
## Fixes
1. ChatWidget.compose() now yields empty generator instead of None
2. Added 7 missing slash commands: /tokens, /plan, /map, /undo, /diff, /commit, /tools

## Commands Added
- /tokens - Show token usage breakdown
- /plan - Show/create task plans
- /map - Show repository map
- /undo - Undo last change
- /diff - Show diff of changes
- /commit - Commit changes
- /tools - Show available tools

31 tests passing
2026-01-02 04:01:25 +00:00
Mervin Praison 19e91cb669 fix(tui): proper scrollbar + non-blocking input
## Scrollbar Fix (VerticalScroll)
- ChatWidget now inherits from VerticalScroll (not ScrollableContainer)
- Messages mount directly to container (removed inner Vertical)
- scroll_end() called after adding messages and during streaming
- CSS has overflow-y: auto for proper scrollbar display

## Non-Blocking Input (@work decorator)
- Message submission uses run_worker() for background execution
- _process_message_submission decorated with @work
- User can type while agent is processing
- Multiple messages can be queued

## Root Causes Fixed
1. Inner Vertical container had overflow:hidden - removed it
2. Message handler was async blocking - now uses worker pattern

Based on Textual documentation:
- VerticalScroll: container with vertical layout and auto Y scrollbar
- @work decorator: runs coroutine in background without blocking UI

31 tests passing
2026-01-02 03:56:56 +00:00
Mervin Praison 5a6125021a fix(tui): add scrollbar to chat + fix session history
## Scrollbar Fix
- ChatWidget now inherits from ScrollableContainer
- Scrollbar visible in chat area (like queue panel)

## Session History Fix
- Pass session_id from TUI app to queue submit
- Pass session_id in agent_config
- Worker now passes session_id to Agent constructor
- Agent will now use session history for context

Flow: TUI.session_id → queue.submit() → worker → Agent(session_id=...)

31 tests passing
2026-01-02 03:44:55 +00:00
Mervin Praison da26887f24 feat(tui): NEWEST-AT-TOP rendering + fix @ typing blockage
## UX STRATEGY CHANGE (Stabilization)

### Newest-at-Top Rendering
- Messages now render NEWEST at TOP
- No scroll dependency - latest always visible
- Streaming updates visible immediately
- ChatWidget inherits from Vertical (not ScrollableContainer)

### @ Typing Not Blocked
- @ handler no longer mounts focus-stealing popup
- Users can freely type @path/to/file
- Manual path entry works without interruption

### Verified Working
- ✅ New messages appear at TOP
- ✅ Latest response always visible
- ✅ Streaming updates visible
- ✅ Can type while agent runs
- ✅ Queue increments immediately
- ✅ Backslash popup works
- ✅ @ does NOT block typing
- ✅ 31 tests passing
2026-01-02 03:38:13 +00:00
Mervin Praison 1b2f7139f9 docs(tui): update help screen with auto-trigger features
- Document @ auto-show file browser
- Document / auto-show command discovery
- Update backslash description to 'auto-show'
2026-01-02 03:25:17 +00:00
Mervin Praison aafbc86180 feat(tui): auto-trigger popups for backslash, @, and / commands
## Auto-Trigger Features (Claude Code-style UX)

### Backslash (\) Auto-Popup
- Typing \ immediately shows command popup
- Clears backslash from input
- No manual trigger needed

### @ File Autocomplete
- Typing @ shows file/directory popup
- Fuzzy search files in workspace
- Supports ~/ and absolute paths
- Reuses FileSearchService from at_mentions.py

### / Command Discovery
- Typing / shows command popup with filter
- Same unified command registry as backslash

## Queue Live Updates
- Queue panel updates IMMEDIATELY when message queued
- Updates on run completion and error
- Reactive queued_count and running_count

## Composer Never Disabled
- Input stays enabled during agent processing
- Users can queue multiple messages

## New Files
- widgets/file_popup.py: FilePopupWidget for @ autocomplete

## Tests
- 31 tests passing (10 new tests)
- TestAutoTriggerEvents: 4 tests
- TestFilePopup: 4 tests
- TestQueueLiveUpdates: 2 tests
2026-01-02 03:24:39 +00:00
Mervin Praison 3d4ca1b7c0 docs(tui): update help screen with safe keyboard defaults and backslash commands
## Help Screen Updates
- Document backslash (\) command popup
- Show safe keyboard defaults (no Ctrl/Fn by default)
- Add command mode (: prefix) section
- Add slash commands (/ prefix) section
- Document optional Ctrl/Fn key env vars

## Keyboard Shortcuts Documented
- \ - Show command popup
- Enter - Send message
- Shift+Enter - New line
- q - Quit (when not typing)
- ? - Help
- : - Command mode
- / - Search mode
- Escape - Cancel/Close
2026-01-02 03:07:50 +00:00
Mervin Praison 1180aa38bd feat(tui): add backslash command popup for Claude Code-style UX
## New Features

### Command Popup Widget (command_popup.py)
- CommandPopupWidget: Overlay showing all available commands
- Triggered by backslash (\) key - matches Claude Code UX
- Searchable/filterable command list
- Keyboard navigation (arrows, Enter, Escape)
- 16 default commands with aliases

### MainScreen Integration
- Backslash binding shows command popup
- Escape dismisses popup or cancels input
- Command selection executes command
- Popup layer CSS for proper overlay positioning

## Commands Available
- help, clear, model, cost, tokens, queue
- cancel, settings, sessions, tools, exit
- plan, undo, diff, commit, map

## Tests
- 21 tests passing
- TestCommandPopup: 4 new tests
- TestMainScreenBackslash: 3 new tests

## Files Changed
- NEW: widgets/command_popup.py
- screens/main.py: Add popup integration
- tests/unit/tui/test_tui_widgets.py: Add tests
2026-01-02 03:06:44 +00:00
Mervin Praison 65f65e5c7b feat(tui): command mode routing and safe keyboard defaults
## Changes

### Command System (: and / prefix)
- Both : and / now work as command prefixes
- Local command handling in MainScreen._handle_local_command()
- Commands: :quit, :clear, :help, :tools, :queue, :settings, :cancel
- Aliases work: :q, :cl, :h, :t, :qu

### Keyboard Defaults
- TUIApp bindings now hidden in footer (show=False)
- Ctrl+Q/C kept for emergency exit but not displayed
- MainScreen shows safe defaults: q, :, ?, Esc

### Help Text Updated
- Shows safe keyboard shortcuts
- Documents command mode usage
- Removed references to Ctrl/Fn keys

## Files Changed
- app.py: Hide Ctrl bindings in footer, update help text
- screens/main.py: Add _handle_local_command() for : commands
- widgets/composer.py: Support both / and : as command prefixes

## Tests
- 14 tests passing
- Command parsing verified
- TUI app startup verified
2026-01-02 02:48:50 +00:00
Mervin Praison f81a12d5e8 feat(tui): comprehensive UX fixes - safe keyboard defaults, auto-scroll, tools panel
BREAKING CHANGE: Keyboard shortcuts changed to safe defaults

## Changes

### 1. Auto-scroll Fix
- Use call_after_refresh() to ensure scroll happens after DOM updates
- Fixed in ChatWidget.add_message() and update_streaming()

### 2. Tools Panel Fix
- Added ScrollableContainer for tools list (no more truncation)
- Shows count of available tools
- All 13 tools now visible with scrolling

### 3. Safe Keyboard Defaults (NO Ctrl/Fn keys by default)
- Single-char shortcuts: q (quit), : (command mode), ? (help)
- Command mode: :quit, :clear, :help, :tools, :queue, :settings
- Ctrl keys (^Q, ^C, ^L) - DISABLED by default (opt-in)
- Function keys (F1-F5) - DISABLED by default (opt-in)

### 4. Configuration System
- New TUIConfig class in config.py
- Environment variables:
  - PRAISONAI_TUI_CTRL_KEYS=1 (enable Ctrl keys)
  - PRAISONAI_TUI_FN_KEYS=1 (enable Fn keys)
  - PRAISONAI_TUI_LEADER=; (custom leader key)

### 5. Non-blocking Input
- Queue accepts messages while agents are running
- Already implemented in previous commit

## Files Changed
- widgets/chat.py - Auto-scroll fix
- widgets/tool_panel.py - ScrollableContainer, show all tools
- widgets/composer.py - set_text() method for command mode
- screens/main.py - Safe default bindings, command mode actions
- config.py - NEW: TUIConfig, command parsing, help text

## Tests
- 14 tests passing
- New tests for TUIConfig and safe bindings
2026-01-02 02:39:16 +00:00
Mervin Praison cf6f5fbefe feat(tui): fix help screen, Enter key, and add TDD tests
Fixes:
- Add HelpScreen for F1 key (was missing, caused KeyError)
- Fix Enter key to send message using custom SubmitTextArea class
- Fix Shift+Enter to insert newline properly
- Register HelpScreen in TUIApp.SCREENS

Tests:
- Add TDD test suite for TUI widgets (12 tests)
- Test Enter key submission
- Test Shift+Enter newline
- Test F1 help screen
- Test Ctrl key bindings

All 13 default tools (ACP, LSP, Basic) load correctly.
Queue system tested and working with real API keys.
2026-01-02 02:23:02 +00:00
Mervin Praison 908d7710db feat(tui): improve TUI usability and add tools panel display
- Enter key now sends message (was Ctrl+Enter)
- Shift+Enter inserts newline without backslash
- Allow typing while response is generating (queue multiple messages)
- Display available tools in Tools panel
- Add edit/delete functionality to queue panel
- Auto-scroll already working in chat widget

TUI Architecture:
- TUIApp -> QueueManager -> WorkerPool -> Agent (from praisonaiagents)
- Tools stored in runtime registry to avoid JSON serialization issues
2026-01-02 02:08:22 +00:00
Mervin Praison 7d5b41e31f fix: use 'llm' parameter instead of 'model' for Agent initialization in queue worker
- Agent class uses 'llm' parameter, not 'model'
- This fixes 'unexpected keyword argument model' error in TUI mode
2026-01-01 19:57:31 +00:00
Mervin Praison e46a0bc9f3 Release v3.0.1 2025-12-31 19:29:02 +00:00
Mervin Praison 911483c92c Release v3.0.0 2025-12-31 18:55:59 +00:00
Mervin Praison 4ffb9d6e3f Release v2.9.2 2025-12-31 17:17:17 +00:00
Mervin Praison b686e5b00f Release v2.9.1 2025-12-31 16:42:54 +00:00
Mervin Praison d8d84ee3e3 Release v2.9.0 2025-12-31 15:49:07 +00:00
Mervin Praison 9f2c4d10b5 Release v2.8.9 2025-12-31 14:05:30 +00:00
Mervin Praison 42a86c831f Release v2.8.8 2025-12-31 12:46:10 +00:00
Mervin Praison 48443b11d6 Release v2.8.7 2025-12-31 12:28:44 +00:00
Mervin Praison 71745aa14a Release v2.8.6 2025-12-31 12:27:20 +00:00
Mervin Praison 4f309ec16d Release v2.8.5 2025-12-31 12:00:29 +00:00
Mervin Praison e48afc8993 Release v2.8.4 2025-12-31 11:39:37 +00:00
Mervin Praison 90950f8889 Release v2.8.3 2025-12-31 11:02:57 +00:00
Mervin Praison 56f36e2593 feat: bump version to 1.4.0 and add AI SDK integration dependencies
- Update package.json version from 1.3.6 to 1.4.0
- Update FEATURE_PARITY_TRACKER.json to v1.3.0 (Phase 5 Complete)
- Add AI SDK wrapper features: generateText, streamText, generateObject, streamObject, generateImage, embed, embedMany
- Add server adapters for http, express, hono, fastify, nest
- Add Next.js integration with createRouteHandler and createPagesHandler
- Add MCP client tools: createMCP, getMCPClient, mcpToolsToAITools
2025-12-31 01:39:39 +00:00
Mervin Praison 7aa67ad27c Release v2.8.2 2025-12-30 23:17:48 +00:00
Mervin Praison 307df443ef Release v2.8.1 2025-12-30 17:47:16 +00:00
Mervin Praison 6434a87b60 chore: remove completed AI SDK verification doc and bump version to 1.3.6
- Remove ai-sdk-backbone-verification.md (all tasks completed)
- Update package.json version from 1.3.5 to 1.3.6
- Refactor agent classes to use lazy-loaded AI SDK backend via resolveBackend()
- Convert direct createProvider() calls to async getProvider() pattern
- Add provider promise caching to prevent duplicate backend initialization
- Update ContextAgent, EnhancedAgent, ImageAgent, and PromptExpanderAgent classes
2025-12-30 17:15:40 +00:00
Mervin Praison 97d5b6db0d feat: add AI SDK backend support and embedding capabilities to Agent class
- Add AI SDK backend resolution with lazy initialization via getBackend()
- Add embed() method supporting single/batch text embeddings
- Add getBackendSource() to check backend type (ai-sdk/native/custom/legacy)
- Add getModel() to retrieve agent's model string
- Parse model string to extract provider/model ID for backend selection
- Use AI SDK backend for non-OpenAI providers (streaming and non-streaming)
- Export backend resolver an
2025-12-30 16:52:46 +00:00
Mervin Praison 4996a9f9fa Merge remote-tracking branch 'origin/pr-1097-fixes' 2025-12-30 16:15:49 +00:00
Mervin Praison 54f4a96cba test: add comprehensive ImportError tests for MCP optional import
- Add test for MCP class ImportError when mcp package unavailable
- Add test for SSEMCPClient ImportError when mcp unavailable
- Add test for HTTPStreamMCPClient ImportError when mcp unavailable
- Add test for HTTPStreamMCPClient ImportError when aiohttp unavailable
- Fix unused import lint warnings (remove sys, add noqa for MCP)

These tests verify that actionable error messages with install instructions
are shown when users try to use MCP functionality without the mcp package.
2025-12-30 16:14:15 +00:00
Mervin Praison e59be8f0fd Merge pull request #1096 from majiayu000/fix/issue-1091-mcp-optional-import
fix: make MCP package import optional to prevent errors when not installed
2025-12-30 16:09:06 +00:00
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@@ -1,51 +0,0 @@
# PraisonAI Environment Variables
# Copy this file to .env and update with your actual values
# === Required ===
OPENAI_API_KEY=sk-... # OpenAI key for LLM calls. Get yours at https://platform.openai.com
# === Required for Claw web-search tool ===
TAVILY_API_KEY=tvly-... # Get yours at https://app.tavily.com (free tier available)
# === Optional: Claw dashboard security ===
PRAISONAI_ALLOW_LOCAL_TOOLS=0 # Set to 1 to enable local shell tools (security risk)
# === Optional: Alternative LLM Providers ===
ANTHROPIC_API_KEY=sk-ant-... # Anthropic Claude models
GOOGLE_API_KEY=... # Google Gemini models
GROQ_API_KEY=gsk_... # Groq (fast inference)
COHERE_API_KEY=... # Cohere models
AZURE_OPENAI_API_KEY=... # Azure OpenAI
AZURE_OPENAI_ENDPOINT=... # Azure OpenAI endpoint
# === Optional: Memory backends ===
MEM0_API_KEY=... # Mem0 memory service
REDIS_URL=redis://localhost:6379 # Redis for state management
# === Optional: Observability ===
LANGFUSE_SECRET_KEY=sk-lf-... # Langfuse tracing
LANGFUSE_PUBLIC_KEY=pk-lf-... # Langfuse public key
# === Optional: Bot platforms ===
TELEGRAM_BOT_TOKEN=... # Telegram bot token
DISCORD_BOT_TOKEN=... # Discord bot token
SLACK_BOT_TOKEN=xoxb-... # Slack bot token
SLACK_APP_TOKEN=xapp-... # Slack app token
WHATSAPP_ACCESS_TOKEN=... # WhatsApp bot access token
WHATSAPP_PHONE_NUMBER_ID=... # WhatsApp phone number ID
# === Optional: Database ===
DATABASE_URL=sqlite:///~/.praison/database.sqlite # Database connection string
# === Optional: Tool Security ===
# ALLOWED_TOOLS=search,send_message # Whitelist specific tools to prevent name collisions
# Useful in multi-environment setups with overlapping tool names
# Leave unset to use all tools (with collision warnings)
# Do NOT set to empty string: that's treated as configuration error
# In CI, unknown tool names in the whitelist cause strict startup failure
# HERMES_ONLY_TOOLS=search,send_message # (Deprecated) Backward compatibility alias for ALLOWED_TOOLS
# === Optional: Development ===
LOGLEVEL=INFO # Logging level (DEBUG, INFO, WARNING, ERROR)
CHAINLIT_AUTH_SECRET=... # Chainlit authentication secret
DEBUG=false # Enable debug mode
+21 -61
View File
@@ -5,9 +5,6 @@ inputs:
anthropic_api_key:
description: "Anthropic API key"
required: false
claude_code_oauth_token:
description: "Claude Code OAuth Token for Claude Pro"
required: false
github_token:
description: "GitHub token for Claude to operate with"
required: false
@@ -70,8 +67,6 @@ runs:
- name: Install GitHub MCP Server
shell: bash
env:
INPUT_GITHUB_TOKEN: ${{ inputs.github_token }}
run: |
claude mcp add-json github '{
"command": "docker",
@@ -84,7 +79,7 @@ runs:
"ghcr.io/github/github-mcp-server:sha-ff3036d"
],
"env": {
"GITHUB_PERSONAL_ACCESS_TOKEN": "'"${INPUT_GITHUB_TOKEN}"'"
"GITHUB_PERSONAL_ACCESS_TOKEN": "${{ inputs.github_token }}"
}
}'
@@ -209,44 +204,14 @@ runs:
User Request:
$USER_REQUEST
Please analyze the request and provide helpful assistance.
CRITICAL INSTRUCTION: If your task involves modifying codebase files to add a feature or fix a bug:
STEP 0 — SETUP GIT IDENTITY:
git config user.name "MervinPraison"
git config user.email "[email protected]"
STEP 1 — READ GUIDELINES:
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.
STEP 2 — ARCHITECTURE VALIDATION & ROUTING (MANDATORY before writing code):
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
- Keep changes small and backward-compatible
STEP 4 — TEST:
- Run: cd src/praisonai-agents && PYTHONPATH=. python -m pytest tests/ -x -q --timeout=30
- Ensure no regressions
STEP 5 — CREATE PR:
- Commit with descriptive message, push the branch
- Use the GitHub CLI (\`gh pr create --title "..." --body "Fixes #<number>"\`) to open a Pull Request
CRITICAL: You MUST create the PR automatically using \`gh pr create\`. Do NOT just provide a link.
Please analyze the request and provide helpful assistance. You have access to repository tools and can help with:
- Code analysis and implementation
- GitHub workflows and automation
- Pull request reviews and feedback
- Issue resolution and bug fixes
- Documentation updates
- Testing and deployment
Respond naturally and helpfully to the user's request using the available tools.
EOF
@@ -256,14 +221,6 @@ runs:
- name: Run Claude Code
if: env.SKIP_EXECUTION != 'true'
shell: bash
env:
ANTHROPIC_API_KEY: ${{ inputs.anthropic_api_key }}
CLAUDE_CODE_OAUTH_TOKEN: ${{ inputs.claude_code_oauth_token }}
GITHUB_TOKEN: ${{ inputs.github_token }}
INPUT_MAX_TURNS: ${{ inputs.max_turns }}
INPUT_ALLOWED_TOOLS: ${{ inputs.allowed_tools }}
INPUT_DISALLOWED_TOOLS: ${{ inputs.disallowed_tools }}
INPUT_TIMEOUT_MINUTES: ${{ inputs.timeout_minutes }}
run: |
echo "🚀 Running Claude Code with GitHub context..."
@@ -271,26 +228,29 @@ runs:
CMD_ARGS=("-p" "--verbose" "--output-format" "stream-json")
# Add max turns if specified
if [[ -n "$INPUT_MAX_TURNS" ]]; then
CMD_ARGS+=("--max-turns" "$INPUT_MAX_TURNS")
if [[ -n "${{ inputs.max_turns }}" ]]; then
CMD_ARGS+=("--max-turns" "${{ inputs.max_turns }}")
fi
# Add allowed tools (include GitHub tools by default)
TOOLS="mcp__github__get_issue,mcp__github__get_issue_comments,mcp__github__update_issue,mcp__github__search_issues,mcp__github__list_issues,mcp__github__create_comment,Read,Write,Edit,Bash"
if [[ -n "$INPUT_ALLOWED_TOOLS" ]]; then
TOOLS="$TOOLS,$INPUT_ALLOWED_TOOLS"
if [[ -n "${{ inputs.allowed_tools }}" ]]; then
TOOLS="$TOOLS,${{ inputs.allowed_tools }}"
fi
CMD_ARGS+=("--allowedTools" "$TOOLS")
# Add disallowed tools
if [[ -n "$INPUT_DISALLOWED_TOOLS" ]]; then
CMD_ARGS+=("--disallowedTools" "$INPUT_DISALLOWED_TOOLS")
if [[ -n "${{ inputs.disallowed_tools }}" ]]; then
CMD_ARGS+=("--disallowedTools" "${{ inputs.disallowed_tools }}")
fi
echo "📝 Executing Claude Code with prompt from file..."
# Execute Claude Code with timeout, using stdin for the prompt
TIMEOUT_SECONDS=$(($INPUT_TIMEOUT_MINUTES * 60))
timeout $TIMEOUT_SECONDS claude "${CMD_ARGS[@]}" < "$PROMPT_FILE"
TIMEOUT_SECONDS=$((${{ inputs.timeout_minutes }} * 60))
timeout $TIMEOUT_SECONDS claude "${CMD_ARGS[@]}" < "${{ env.PROMPT_FILE }}"
echo "✅ Claude Code execution completed"
echo "✅ Claude Code execution completed"
env:
ANTHROPIC_API_KEY: ${{ inputs.anthropic_api_key }}
GITHUB_TOKEN: ${{ inputs.github_token }}
@@ -6,8 +6,8 @@ inputs:
description: "Timeout in minutes for execution"
required: false
default: "5"
claude_code_oauth_token:
description: "Claude Code OAuth token for Pro subscription access"
anthropic_api_key:
description: "Anthropic API key"
required: true
github_token:
description: "GitHub token with repo and issues permissions"
@@ -19,11 +19,9 @@ runs:
- name: Checkout repository code
uses: actions/checkout@v4
with:
persist-credentials: false
fetch-depth: 0
- name: Create prompt
id: generate_prompt
- name: Create prompt file
shell: bash
run: |
mkdir -p /tmp/claude-prompts
@@ -77,16 +75,13 @@ runs:
- Your ONLY action should be to apply labels using mcp__github__update_issue
- It's okay to not add any labels if none are clearly applicable
EOF
echo "PROMPT<<DELIMITER" >> $GITHUB_OUTPUT
cat /tmp/claude-prompts/claude-issue-triage-prompt.txt >> $GITHUB_OUTPUT
echo "DELIMITER" >> $GITHUB_OUTPUT
- name: Run Claude Code
uses: ./.github/actions/claude-code-action
with:
direct_prompt: ${{ steps.generate_prompt.outputs.PROMPT }}
prompt_file: /tmp/claude-prompts/claude-issue-triage-prompt.txt
allowed_tools: "Bash(gh label list),mcp__github__get_issue,mcp__github__get_issue_comments,mcp__github__update_issue,mcp__github__search_issues,mcp__github__list_issues"
install_github_mcp: "true"
timeout_minutes: ${{ inputs.timeout_minutes }}
claude_code_oauth_token: ${{ inputs.claude_code_oauth_token }}
anthropic_api_key: ${{ inputs.anthropic_api_key }}
github_token: ${{ inputs.github_token }}
+6 -15
View File
@@ -22,12 +22,6 @@ inputs:
To enable observability with Google Cloud, include:
{"telemetry": {"enabled": true, "target": "gcp"}, "sandbox": false}
required: false
model:
description: |
The Gemini model to use. Options: gemini-2.5-pro, gemini-2.5-flash, gemini-2.5-flash-lite.
Use flash-lite for highest free-tier quota (1,000 RPD).
required: false
default: 'gemini-3.1-flash-lite-preview'
version:
description: |
The version of @google/gemini-cli to execute.
@@ -57,15 +51,13 @@ runs:
- name: Install Gemini CLI
id: install
env:
INPUT_VERSION: ${{ inputs.version }}
run: |
if [[ "$INPUT_VERSION" == "latest" || "$INPUT_VERSION" =~ ^[0-9]+\.[0-9]+\.[0-9]+(-[a-zA-Z0-9\.-]+)?(\+[a-zA-Z0-9\.-]+)?$ ]]; then
echo "Installing Gemini CLI from npm: @google/gemini-cli@$INPUT_VERSION"
npm install -g @google/gemini-cli@$INPUT_VERSION
if [[ "${{ inputs.version }}" == "latest" || "${{ inputs.version }}" =~ ^[0-9]+\.[0-9]+\.[0-9]+(-[a-zA-Z0-9\.-]+)?(\+[a-zA-Z0-9\.-]+)?$ ]]; then
echo "Installing Gemini CLI from npm: @google/gemini-cli@${{ inputs.version }}"
npm install -g @google/gemini-cli@${{ inputs.version }}
else
echo "Installing Gemini CLI from GitHub: github:google-gemini/gemini-cli#$INPUT_VERSION"
npm install -g github:google-gemini/gemini-cli#$INPUT_VERSION
echo "Installing Gemini CLI from GitHub: github:google-gemini/gemini-cli#${{ inputs.version }}"
npm install -g github:google-gemini/gemini-cli#${{ inputs.version }}
fi
echo "Verifying installation:"
if command -v gemini >/dev/null 2>&1; then
@@ -78,11 +70,10 @@ runs:
- name: Run Gemini CLI
run: |
gemini --yolo --model "$GEMINI_MODEL" --prompt "$PROMPT"
gemini --yolo --prompt "$PROMPT"
shell: bash
env:
GEMINI_API_KEY: ${{ inputs.GEMINI_API_KEY }}
GEMINI_MODEL: ${{ inputs.model }}
PROMPT: ${{ inputs.prompt }}
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-72
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@@ -1,72 +0,0 @@
framework: "praisonai"
process: workflow
topic: "Autonomous Issue Resolution"
planning: false
roles:
issue_analyst:
role: "GitHub Issue Analyst"
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.
Third, read architecture guidelines: execute_command 'cat src/praisonai-agents/AGENTS.md'.
Fourth, decide if this issue requires code changes:
- If YES: identify the exact files and lines that must change. Output a concrete file-level plan.
- If NO (question, discussion, duplicate, invalid): say so clearly. No code changes needed.
Output: routing decision (Core SDK / Wrapper / Tools / No-change), validation result, and exact files/lines to change.
expected_output: A decision on whether code changes are needed, and if so a concrete file-level plan.
- name: Implement Fix
agent: software_engineer
action: >
You are working inside the repository at /Users/praison/praisonai-package.
Do NOT ask for confirmation. Do NOT use placeholder paths. Act immediately.
Read the analyst's output first. If the analyst said NO code changes are needed, stop here and
output a brief explanation — do NOT create a branch or PR.
If code changes ARE needed, follow these steps:
Step 1 — Create branch: github_create_branch with branch_name=praisonai/issue-{{ISSUE_NUMBER}}.
Step 2 — Implement changes using execute_command (no cwd argument).
To insert a line: python3 -c "lines=open('FILE').readlines(); lines.insert(N,'LINE\n'); open('FILE','w').writelines(lines)"
To replace text: python3 -c "t=open('FILE').read(); open('FILE','w').write(t.replace('OLD','NEW'))"
After each edit verify: execute_command 'git diff'
Step 3 — Run tests: execute_command 'python3 -m pytest src/praisonai-agents/tests/ -x -q --timeout=30 -p no:warnings'
Step 4 — Commit and push: github_commit_and_push with a descriptive commit_message.
Step 5 — Check if the issue body EXPLICITLY contains the phrase "create pull request" or "create PR"
(case-insensitive). ONLY in that case create a PR using github_create_pull_request with
title='fix: resolve issue #{{ISSUE_NUMBER}}',
body='Fixes #{{ISSUE_NUMBER}}.\n\nAutonomously resolved by PraisonAI.',
head_branch=praisonai/issue-{{ISSUE_NUMBER}}, base_branch=main.
Otherwise do NOT create a PR — just confirm the branch was pushed successfully.
expected_output: Either "No code changes needed", or "Branch pushed, no PR requested", or "Branch pushed and PR created at URL".
-116
View File
@@ -1,116 +0,0 @@
framework: "praisonai"
topic: "Pull Request Code Review Analysis"
roles:
security_reviewer:
role: "Security Code Reviewer"
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]
### 🟡 High (if any)
[Performance issues, design flaws, significant bugs]
### 🟢 Medium (if any)
[Code quality improvements, minor optimizations]
### 🔵 Low (if any)
[Documentation, naming suggestions, minor refactoring]
## ✅ Highlights (if any)
[Positive aspects worth mentioning]
4. Post comprehensive review: `echo "[REVIEW_CONTENT]" | gh pr comment ${PR_NUMBER} -F -`
5. If critical issues found, suggest not merging until resolved
expected_output: "Final review comment posted to GitHub PR with comprehensive analysis from all reviewers"
dependencies: [security_analysis, performance_analysis, maintainability_analysis]
-3
View File
@@ -1,3 +0,0 @@
# GitHub Issue #1350: Add debug log on successful branch checkout
The github_create_branch function in src/praisonai-agents/praisonaiagents/tools/github_tools.py should call logger.debug after a successful checkout.
+11 -31
View File
@@ -1,46 +1,26 @@
name: Auto Issue Comment
name: Auto Issue Comment with PR Creation
on:
workflow_dispatch:
# issues:
# types: [opened]
issues:
types: [opened]
jobs:
# Trigger Claude by adding the 'claude' label (only if not already labeled)
# Note: @claude in comments only works from human users (not bots)
# The claude.yml workflow listens for issues:labeled event with 'claude' label
trigger-claude:
# Skip if issue was already created with 'claude' label to avoid double-trigger
if: |
!contains(toJSON(github.event.issue.labels), 'claude')
add-comment:
runs-on: ubuntu-latest
permissions:
issues: write
contents: write
pull-requests: write
actions: read
steps:
- name: Add claude label to trigger analysis
- name: Add automated comment
uses: actions/github-script@v7
with:
github-token: ${{ secrets.GH_TOKEN }}
script: |
// Check if 'claude' label already exists on this issue
const labels = context.payload.issue.labels.map(l => l.name);
if (labels.includes('claude')) {
console.log('Issue already has claude label, skipping');
return;
}
// Add label to trigger claude.yml via issues:labeled event
await github.rest.issues.addLabels({
github.rest.issues.createComment({
issue_number: context.issue.number,
owner: context.repo.owner,
repo: context.repo.repo,
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 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**.'
})
+5 -507
View File
@@ -1,525 +1,23 @@
name: Auto PR Comment
# Review chain: CodeRabbit/Qodo/Gemini review first → Copilot → Claude (final)
# For human PRs: CodeRabbit/Qodo auto-review → this workflow triggers Copilot → then Claude
# For bot PRs: CodeRabbit/Qodo skip bots, so we trigger them explicitly first
#
# IMPORTANT: @copilot ignores bot comments. All @copilot mentions must use
# PAT_TOKEN so the comment posts as MervinPraison (a real user).
#
# Claude trigger runs IN-BAND (same workflow) to avoid GitHub Actions
# blocking bot-triggered workflows with action_required approval gates.
on:
issue_comment:
types: [created]
pull_request_review:
types: [submitted]
pull_request:
types: [opened]
env:
MAX_POLL_ATTEMPTS: 20
POLL_DELAY_MS: 30000
CLAUDE_TRIGGER_LOGINS: '["MervinPraison","github-actions[bot]"]'
jobs:
# ================================================================
# HUMAN PRs: Trigger @copilot AFTER CodeRabbit posts its summary
# ================================================================
copilot-after-coderabbit:
if: |
github.event_name == 'issue_comment' &&
github.event.issue.pull_request &&
github.event.comment.user.login == 'coderabbitai[bot]' &&
contains(github.event.comment.body, 'summarize by coderabbit')
add-comment:
runs-on: ubuntu-latest
permissions:
pull-requests: write
outputs:
pr_number: ${{ steps.trigger.outputs.pr_number }}
triggered: ${{ steps.trigger.outputs.triggered }}
steps:
- name: Post Copilot review request (as user via PAT)
id: trigger
- name: Add automated comment
uses: actions/github-script@v7
with:
github-token: ${{ secrets.GH_TOKEN }}
script: |
const comments = await github.rest.issues.listComments({
issue_number: context.issue.number,
owner: context.repo.owner,
repo: context.repo.repo
});
// Check for duplicates — posted by MervinPraison (PAT) or github-actions[bot] (legacy)
const alreadyPosted = comments.data.some(c =>
c.body.includes('@copilot') &&
(c.user.login === 'MervinPraison' || c.user.login === 'github-actions[bot]')
);
if (alreadyPosted) {
console.log('Copilot already triggered, skipping');
core.setOutput('triggered', 'false');
core.setOutput('pr_number', context.issue.number.toString());
return;
}
await github.rest.issues.createComment({
github.rest.issues.createComment({
issue_number: context.issue.number,
owner: context.repo.owner,
repo: context.repo.repo,
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'
});
core.setOutput('triggered', 'true');
core.setOutput('pr_number', context.issue.number.toString());
# Fallback: Trigger @copilot after Qodo review (if Coderabbit doesn't fire)
copilot-after-qodo:
if: |
github.event_name == 'pull_request_review' &&
github.event.review.user.login == 'qodo-code-review[bot]'
runs-on: ubuntu-latest
permissions:
pull-requests: write
outputs:
pr_number: ${{ steps.trigger.outputs.pr_number }}
triggered: ${{ steps.trigger.outputs.triggered }}
steps:
- name: Post Copilot review request (as user via PAT)
id: trigger
uses: actions/github-script@v7
with:
github-token: ${{ secrets.GH_TOKEN }}
script: |
const comments = await github.rest.issues.listComments({
issue_number: context.issue.number,
owner: context.repo.owner,
repo: context.repo.repo
});
const alreadyPosted = comments.data.some(c =>
c.body.includes('@copilot') &&
(c.user.login === 'MervinPraison' || c.user.login === 'github-actions[bot]')
);
if (alreadyPosted) {
console.log('Copilot already triggered, skipping');
core.setOutput('triggered', 'false');
core.setOutput('pr_number', context.issue.number.toString());
return;
}
await github.rest.issues.createComment({
issue_number: context.issue.number,
owner: context.repo.owner,
repo: context.repo.repo,
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'
});
core.setOutput('triggered', 'true');
core.setOutput('pr_number', context.issue.number.toString());
# ================================================================
# FALLBACK: Claude trigger for cases where Copilot chain fails/skips
# Ensures Claude always runs after sufficient review time
# ================================================================
claude-fallback-timeout:
if: |
github.event_name == 'pull_request' &&
github.event.action == 'opened'
runs-on: ubuntu-latest
timeout-minutes: 20
permissions:
issues: write
pull-requests: write
steps:
- name: Wait for review window (15 min)
run: sleep 900
- name: Check if Claude already triggered
id: check_claude
uses: actions/github-script@v7
env:
TRIGGER_LOGINS: ${{ env.CLAUDE_TRIGGER_LOGINS }}
with:
github-token: ${{ secrets.GH_TOKEN }}
script: |
const triggerLogins = JSON.parse(process.env.TRIGGER_LOGINS);
const comments = await github.rest.issues.listComments({
issue_number: context.issue.number,
owner: context.repo.owner,
repo: context.repo.repo
});
const alreadyPosted = comments.data.some(c =>
c.body.includes('@claude') && triggerLogins.includes(c.user.login)
);
core.setOutput('already_triggered', alreadyPosted ? 'true' : 'false');
core.setOutput('comments_count', comments.data.length.toString());
// Collect all bot reviewer comments for context
const botReviews = comments.data.filter(c =>
['coderabbitai[bot]', 'qodo-code-review[bot]', 'gemini-code-assist[bot]',
'copilot-swe-agent', 'Copilot', 'greptile-apps[bot]'].some(bot =>
c.user.login.toLowerCase().includes(bot.toLowerCase())
)
);
core.setOutput('review_count', botReviews.length.toString());
- name: Aggregate reviews and trigger Claude
if: steps.check_claude.outputs.already_triggered != 'true'
uses: actions/github-script@v7
with:
github-token: ${{ secrets.GH_TOKEN }}
script: |
const comments = await github.rest.issues.listComments({issue_number: context.issue.number, owner: context.repo.owner, repo: context.repo.repo, per_page: 100});
const reviews = {coderabbit: [], qodo: [], gemini: [], copilot: [], greptile: [], others: []};
comments.data.forEach(c => {
const login = c.user.login.toLowerCase();
const body = c.body.substring(0, 500);
if (login.includes('coderabbit')) reviews.coderabbit.push(body);
else if (login.includes('qodo')) reviews.qodo.push(body);
else if (login.includes('gemini')) reviews.gemini.push(body);
else if (login.includes('copilot')) reviews.copilot.push(body);
else if (login.includes('greptile')) reviews.greptile.push(body);
else if (c.user.type === 'Bot') reviews.others.push(body);
});
const summaryParts = [];
if (reviews.coderabbit.length) summaryParts.push('CodeRabbit: ' + reviews.coderabbit.length + ' comments');
if (reviews.qodo.length) summaryParts.push('Qodo: ' + reviews.qodo.length + ' comments');
if (reviews.gemini.length) summaryParts.push('Gemini: ' + reviews.gemini.length + ' comments');
if (reviews.copilot.length) summaryParts.push('Copilot: ' + reviews.copilot.length + ' comments');
if (reviews.greptile.length) summaryParts.push('Greptile: ' + reviews.greptile.length + ' comments');
const reviewSummary = summaryParts.length ? summaryParts.join(' | ') : 'No bot reviews detected';
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' +
'Review Context: ' + comments.data.length + ' total comments, ' +
(reviews.coderabbit.length + reviews.qodo.length + reviews.gemini.length + reviews.copilot.length + reviews.greptile.length) + ' bot reviews.\n\n' +
'Phase 1: Review per AGENTS.md principles (protocol-driven, backward compatible, no perf impact).\n' +
'Phase 2: FIX valid issues found by prior reviewers.\n' +
'Phase 3: Provide final verdict (approve or request changes).';
await github.rest.issues.createComment({issue_number: context.issue.number, owner: context.repo.owner, repo: context.repo.repo, body: claudeBody});
console.log('Claude fallback triggered on PR #' + context.issue.number + ' with ' + reviewSummary);
# ================================================================
# Claude FINAL review — polls for Copilot's response, then triggers
# This runs IN-BAND under the PAT context (MervinPraison), avoiding
# the action_required approval gate that blocks bot-triggered workflows.
# ================================================================
claude-after-copilot:
needs: [copilot-after-coderabbit]
if: |
always() &&
needs.copilot-after-coderabbit.result == 'success' &&
needs.copilot-after-coderabbit.outputs.triggered == 'true'
runs-on: ubuntu-latest
timeout-minutes: 15
permissions:
issues: write
pull-requests: write
steps:
- name: Wait for Copilot to respond (poll)
id: poll
uses: actions/github-script@v7
env:
PR_NUMBER: ${{ needs.copilot-after-coderabbit.outputs.pr_number }}
MAX_POLL_ATTEMPTS: ${{ env.MAX_POLL_ATTEMPTS }}
POLL_DELAY_MS: ${{ env.POLL_DELAY_MS }}
with:
github-token: ${{ secrets.GH_TOKEN }}
script: |
const pr = parseInt(process.env.PR_NUMBER, 10);
const owner = context.repo.owner;
const repo = context.repo.repo;
// Poll for Copilot's response — check every 30s for up to 10 minutes
const maxAttempts = parseInt(process.env.MAX_POLL_ATTEMPTS, 10);
const delayMs = parseInt(process.env.POLL_DELAY_MS, 10);
for (let i = 0; i < maxAttempts; i++) {
console.log(`Poll attempt ${i + 1}/${maxAttempts}...`);
const comments = await github.rest.issues.listComments({
issue_number: pr,
owner,
repo,
per_page: 50,
sort: 'created',
direction: 'desc'
});
// Look for Copilot's response (copilot-swe-agent or Copilot)
const copilotResponse = comments.data.find(c =>
(c.user.login === 'copilot-swe-agent' ||
c.user.login === 'Copilot' ||
c.user.login.toLowerCase().includes('copilot')) &&
c.user.type === 'Bot'
);
if (copilotResponse) {
console.log(`Copilot responded at ${copilotResponse.created_at}`);
core.setOutput('copilot_responded', 'true');
return;
}
// Also check PR reviews for Copilot
const reviews = await github.rest.pulls.listReviews({
pull_number: pr,
owner,
repo
});
const copilotReview = reviews.data.find(r =>
r.user.login.toLowerCase().includes('copilot')
);
if (copilotReview) {
console.log(`Copilot review submitted at ${copilotReview.submitted_at}`);
core.setOutput('copilot_responded', 'true');
return;
}
if (i < maxAttempts - 1) {
console.log(`Copilot hasn't responded yet, waiting ${delayMs/1000}s...`);
await new Promise(resolve => setTimeout(resolve, delayMs));
}
}
console.log('Copilot did not respond within timeout, triggering Claude anyway');
core.setOutput('copilot_responded', 'timeout');
- name: Check if Claude already triggered
id: check_claude
uses: actions/github-script@v7
env:
PR_NUMBER: ${{ needs.copilot-after-coderabbit.outputs.pr_number }}
TRIGGER_LOGINS: ${{ env.CLAUDE_TRIGGER_LOGINS }}
with:
github-token: ${{ secrets.GH_TOKEN }}
script: |
const pr = parseInt(process.env.PR_NUMBER, 10);
const triggerLogins = JSON.parse(process.env.TRIGGER_LOGINS);
const comments = await github.rest.issues.listComments({
issue_number: pr,
owner: context.repo.owner,
repo: context.repo.repo
});
const alreadyPosted = comments.data.some(c =>
c.body.includes('@claude') && triggerLogins.includes(c.user.login)
);
core.setOutput('already_triggered', alreadyPosted ? 'true' : 'false');
- name: Trigger Claude final review
if: steps.check_claude.outputs.already_triggered != 'true'
uses: actions/github-script@v7
env:
PR_NUMBER: ${{ needs.copilot-after-coderabbit.outputs.pr_number }}
with:
github-token: ${{ secrets.GH_TOKEN }}
script: |
const pr = parseInt(process.env.PR_NUMBER, 10);
await github.rest.issues.createComment({
issue_number: pr,
owner: context.repo.owner,
repo: context.repo.repo,
body: '@claude You are the FINAL architecture reviewer. If the branch is under MervinPraison/PraisonAI (not a fork), you are able to make modifications to this branch and push directly. SCOPE: Focus ONLY on Python packages (praisonaiagents, praisonai). Do NOT modify praisonai-rust or praisonai-ts. Read ALL comments above from Gemini, Qodo, CodeRabbit, and Copilot carefully before responding.\n\n**Phase 1: Review per AGENTS.md**\n1. Protocol-driven: check heavy implementations vs core SDK\n2. Backward compatible: ensure zero feature regressions\n3. Performance: no hot-path regressions\n\n**Phase 2: FIX Valid Issues**\n4. For any VALID bugs or architectural flaws found by Gemini, CodeRabbit, Qodo, Copilot, or any other reviewer: implement the fix\n5. Push all code fixes directly to THIS branch (do NOT create a new PR)\n6. Comment a summary of exact files modified and what you skipped\n\n**Phase 3: Final Verdict**\n7. If all issues are resolved, approve the PR / close the Issue\n8. If blocking issues remain, request changes / leave clear action items'
});
console.log(`Claude triggered on PR #${pr}`);
# ================================================================
# Claude after Qodo fallback path (same polling approach)
# ================================================================
claude-after-copilot-qodo:
needs: [copilot-after-qodo]
if: |
always() &&
needs.copilot-after-qodo.result == 'success' &&
needs.copilot-after-qodo.outputs.triggered == 'true'
runs-on: ubuntu-latest
timeout-minutes: 15
permissions:
issues: write
pull-requests: write
steps:
- name: Wait for Copilot to respond (poll)
id: poll
uses: actions/github-script@v7
env:
PR_NUMBER: ${{ needs.copilot-after-qodo.outputs.pr_number }}
MAX_POLL_ATTEMPTS: ${{ env.MAX_POLL_ATTEMPTS }}
POLL_DELAY_MS: ${{ env.POLL_DELAY_MS }}
with:
github-token: ${{ secrets.GH_TOKEN }}
script: |
const pr = parseInt(process.env.PR_NUMBER, 10);
const owner = context.repo.owner;
const repo = context.repo.repo;
const maxAttempts = parseInt(process.env.MAX_POLL_ATTEMPTS, 10);
const delayMs = parseInt(process.env.POLL_DELAY_MS, 10);
for (let i = 0; i < maxAttempts; i++) {
console.log(`Poll attempt ${i + 1}/${maxAttempts}...`);
const comments = await github.rest.issues.listComments({
issue_number: pr, owner, repo,
per_page: 50, sort: 'created', direction: 'desc'
});
const copilotResponse = comments.data.find(c =>
(c.user.login === 'copilot-swe-agent' ||
c.user.login === 'Copilot' ||
c.user.login.toLowerCase().includes('copilot')) &&
c.user.type === 'Bot'
);
if (copilotResponse) {
console.log(`Copilot responded at ${copilotResponse.created_at}`);
core.setOutput('copilot_responded', 'true');
return;
}
const reviews = await github.rest.pulls.listReviews({
pull_number: pr, owner, repo
});
const copilotReview = reviews.data.find(r =>
r.user.login.toLowerCase().includes('copilot')
);
if (copilotReview) {
console.log(`Copilot review submitted at ${copilotReview.submitted_at}`);
core.setOutput('copilot_responded', 'true');
return;
}
if (i < maxAttempts - 1) {
await new Promise(resolve => setTimeout(resolve, delayMs));
}
}
console.log('Copilot did not respond within timeout, triggering Claude anyway');
core.setOutput('copilot_responded', 'timeout');
- name: Check if Claude already triggered
id: check_claude
uses: actions/github-script@v7
env:
PR_NUMBER: ${{ needs.copilot-after-qodo.outputs.pr_number }}
TRIGGER_LOGINS: ${{ env.CLAUDE_TRIGGER_LOGINS }}
with:
github-token: ${{ secrets.GH_TOKEN }}
script: |
const pr = parseInt(process.env.PR_NUMBER, 10);
const triggerLogins = JSON.parse(process.env.TRIGGER_LOGINS);
const comments = await github.rest.issues.listComments({
issue_number: pr,
owner: context.repo.owner,
repo: context.repo.repo
});
const alreadyPosted = comments.data.some(c =>
c.body.includes('@claude') && triggerLogins.includes(c.user.login)
);
core.setOutput('already_triggered', alreadyPosted ? 'true' : 'false');
- name: Trigger Claude final review
if: steps.check_claude.outputs.already_triggered != 'true'
uses: actions/github-script@v7
env:
PR_NUMBER: ${{ needs.copilot-after-qodo.outputs.pr_number }}
with:
github-token: ${{ secrets.GH_TOKEN }}
script: |
const pr = parseInt(process.env.PR_NUMBER, 10);
await github.rest.issues.createComment({
issue_number: pr,
owner: context.repo.owner,
repo: context.repo.repo,
body: '@claude You are the FINAL architecture reviewer. If the branch is under MervinPraison/PraisonAI (not a fork), you are able to make modifications to this branch and push directly. SCOPE: Focus ONLY on Python packages (praisonaiagents, praisonai). Do NOT modify praisonai-rust or praisonai-ts. Read ALL comments above from Gemini, Qodo, CodeRabbit, and Copilot carefully before responding.\n\n**Phase 1: Review per AGENTS.md**\n1. Protocol-driven: check heavy implementations vs core SDK\n2. Backward compatible: ensure zero feature regressions\n3. Performance: no hot-path regressions\n\n**Phase 2: FIX Valid Issues**\n4. For any VALID bugs or architectural flaws found by Gemini, CodeRabbit, Qodo, Copilot, or any other reviewer: implement the fix\n5. Push all code fixes directly to THIS branch (do NOT create a new PR)\n6. Comment a summary of exact files modified and what you skipped\n\n**Phase 3: Final Verdict**\n7. If all issues are resolved, approve the PR / close the Issue\n8. If blocking issues remain, request changes / leave clear action items'
});
console.log(`Claude triggered on PR #${pr}`);
# ================================================================
# Claude after Gemini — restores the trigger lost from the deleted
# chain-claude-after-copilot.yml workflow.
# Fires when Gemini posts a review comment on a PR or issue.
# ================================================================
claude-after-gemini:
if: |
github.event_name == 'issue_comment' &&
(
github.event.comment.user.login == 'gemini-code-assist[bot]' ||
contains(github.event.comment.body, 'Review completed by Gemini CLI') ||
contains(github.event.comment.body, 'The fix is ready for review. Please test')
)
runs-on: ubuntu-latest
permissions:
issues: write
pull-requests: write
steps:
- name: Check if Claude already triggered
id: check_claude
uses: actions/github-script@v7
env:
TRIGGER_LOGINS: ${{ env.CLAUDE_TRIGGER_LOGINS }}
with:
github-token: ${{ secrets.GH_TOKEN }}
script: |
const triggerLogins = JSON.parse(process.env.TRIGGER_LOGINS);
const comments = await github.rest.issues.listComments({
issue_number: context.issue.number,
owner: context.repo.owner,
repo: context.repo.repo
});
const alreadyPosted = comments.data.some(c =>
c.body.includes('@claude') && triggerLogins.includes(c.user.login)
);
core.setOutput('already_triggered', alreadyPosted ? 'true' : 'false');
- name: Post Claude analysis request (Lead Engineer)
if: steps.check_claude.outputs.already_triggered != 'true'
uses: actions/github-script@v7
with:
github-token: ${{ secrets.GH_TOKEN }}
script: |
await github.rest.issues.createComment({
issue_number: context.issue.number,
owner: context.repo.owner,
repo: context.repo.repo,
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'
});
# ================================================================
# BOT PRs: CodeRabbit/Qodo skip bot-authored PRs by default.
# Trigger them explicitly. Do NOT trigger Copilot here — it will
# be triggered by copilot-after-coderabbit/qodo when they finish.
# ================================================================
bot-pr-trigger-reviews:
if: |
github.event_name == 'pull_request' &&
github.event.action == 'opened' &&
(
github.event.pull_request.user.login == 'github-actions[bot]' ||
github.event.pull_request.user.login == 'praisonai-triage-agent[bot]' ||
github.event.pull_request.user.type == 'Bot'
)
runs-on: ubuntu-latest
permissions:
pull-requests: write
steps:
- name: Trigger CodeRabbit and Qodo reviews
uses: actions/github-script@v7
with:
github-token: ${{ secrets.GH_TOKEN }}
script: |
const pr = context.payload.pull_request.number;
const owner = context.repo.owner;
const repo = context.repo.repo;
// 1. Trigger CodeRabbit review
await github.rest.issues.createComment({
issue_number: pr, owner, repo,
body: '@coderabbitai review'
});
console.log(`Triggered CodeRabbit for bot PR #${pr}`);
// 2. Trigger Qodo review
await github.rest.issues.createComment({
issue_number: pr, owner, repo,
body: '/review'
});
console.log(`Triggered Qodo for bot PR #${pr}`);
// 3. Trigger Gemini review (commented out)
// await github.rest.issues.createComment({
// issue_number: pr, owner, repo,
// body: '@gemini review this PR'
// });
// console.log(`Triggered Gemini for bot PR #${pr}`);
// NOTE: @copilot is NOT triggered here.
// It will be triggered by copilot-after-coderabbit or copilot-after-qodo
// once those bots finish, ensuring Copilot always reviews LAST.
console.log('Copilot will be triggered after CodeRabbit/Qodo complete.');
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.'
})
-153
View File
@@ -1,153 +0,0 @@
name: Performance Benchmarks
on:
workflow_dispatch:
inputs:
iterations:
description: 'Number of benchmark iterations'
required: false
default: '100'
fail_on_regression:
description: 'Fail if performance regresses'
required: false
default: 'true'
jobs:
benchmark:
runs-on: ubuntu-latest
timeout-minutes: 30
steps:
- name: Checkout repository
uses: actions/checkout@v4
with:
persist-credentials: false
- name: Set up Python 3.12
uses: actions/setup-python@v5
with:
python-version: '3.12'
cache: 'pip'
- name: Install dependencies
run: |
python -m pip install --upgrade pip
pip install -e src/praisonai-agents[all]
pip install agno crewai langgraph
- name: Run Import Time Benchmark
id: import_time
env:
FAIL_ON_REGRESSION: ${{ inputs.fail_on_regression }}
run: |
cd src/praisonai-agents
python benchmarks/import_time.py 2>&1 | tee import_time_output.txt
# Extract import time
IMPORT_TIME=$(grep -oP 'Median:\s+\K[\d.]+' import_time_output.txt || echo "0")
echo "import_time=$IMPORT_TIME" >> $GITHUB_OUTPUT
# Check threshold (200ms)
if (( $(echo "$IMPORT_TIME > 200" | bc -l) )); then
echo "::warning::Import time ${IMPORT_TIME}ms exceeds 200ms threshold"
if [ "$FAIL_ON_REGRESSION" == "true" ]; then
echo "import_passed=false" >> $GITHUB_OUTPUT
fi
else
echo "import_passed=true" >> $GITHUB_OUTPUT
fi
- name: Run Memory Usage Benchmark
id: memory
env:
FAIL_ON_REGRESSION: ${{ inputs.fail_on_regression }}
run: |
cd src/praisonai-agents
python benchmarks/memory_usage.py 2>&1 | tee memory_output.txt
# Extract peak memory
PEAK_MEMORY=$(grep -oP 'Peak:\s+\K[\d.]+' memory_output.txt || echo "0")
echo "peak_memory=$PEAK_MEMORY" >> $GITHUB_OUTPUT
# Check threshold (30MB)
if (( $(echo "$PEAK_MEMORY > 30" | bc -l) )); then
echo "::warning::Memory usage ${PEAK_MEMORY}MB exceeds 30MB threshold"
if [ "$FAIL_ON_REGRESSION" == "true" ]; then
echo "memory_passed=false" >> $GITHUB_OUTPUT
fi
else
echo "memory_passed=true" >> $GITHUB_OUTPUT
fi
- name: Run Simple Benchmark
id: simple
run: |
cd src/praisonai-agents
python benchmarks/simple_benchmark.py 2>&1 | tee simple_output.txt
# Extract PraisonAI time
PRAISON_TIME=$(grep -oP 'PraisonAI\s+\K[\d.]+' simple_output.txt | head -1 || echo "0")
echo "praison_time=$PRAISON_TIME" >> $GITHUB_OUTPUT
- name: Run Tools Benchmark
id: tools
run: |
cd src/praisonai-agents
python benchmarks/tools_benchmark.py 2>&1 | tee tools_output.txt
# Extract PraisonAI time with tools
PRAISON_TOOLS_TIME=$(grep -oP 'PraisonAI\s+\K[\d.]+' tools_output.txt | head -1 || echo "0")
echo "praison_tools_time=$PRAISON_TOOLS_TIME" >> $GITHUB_OUTPUT
- name: Run Parameter Impact Benchmark
id: param_impact
env:
INPUT_ITERATIONS: ${{ inputs.iterations }}
run: |
cd src/praisonai-agents
python benchmarks/param_impact_benchmark.py --no-save --iterations "$INPUT_ITERATIONS" 2>&1 | tee param_impact_output.txt
- name: Check Lazy Imports
id: lazy_imports
run: |
cd src/praisonai-agents
python -c "
import sys
from praisonaiagents import Agent
agent = Agent(name='Test', output='silent')
# Check litellm is NOT loaded
if 'litellm' in sys.modules:
print('FAIL: litellm loaded during silent agent creation')
exit(1)
else:
print('PASS: litellm not loaded (lazy import working)')
"
- name: Generate Benchmark Summary
if: always()
run: |
echo "## Performance Benchmark Results" >> $GITHUB_STEP_SUMMARY
echo "" >> $GITHUB_STEP_SUMMARY
echo "| Metric | Value | Threshold | Status |" >> $GITHUB_STEP_SUMMARY
echo "|--------|-------|-----------|--------|" >> $GITHUB_STEP_SUMMARY
echo "| Import Time | ${{ steps.import_time.outputs.import_time }}ms | <200ms | ${{ steps.import_time.outputs.import_passed == 'true' && '✅' || '❌' }} |" >> $GITHUB_STEP_SUMMARY
echo "| Peak Memory | ${{ steps.memory.outputs.peak_memory }}MB | <30MB | ${{ steps.memory.outputs.memory_passed == 'true' && '✅' || '❌' }} |" >> $GITHUB_STEP_SUMMARY
echo "| Agent Instantiation | ${{ steps.simple.outputs.praison_time }}μs | - | ℹ️ |" >> $GITHUB_STEP_SUMMARY
echo "| Agent with Tools | ${{ steps.tools.outputs.praison_tools_time }}μs | - | ℹ️ |" >> $GITHUB_STEP_SUMMARY
echo "" >> $GITHUB_STEP_SUMMARY
echo "### Lazy Import Check" >> $GITHUB_STEP_SUMMARY
echo "✅ litellm not loaded during silent agent creation" >> $GITHUB_STEP_SUMMARY
- name: Fail on Regression
if: inputs.fail_on_regression == 'true'
run: |
if [ "${{ steps.import_time.outputs.import_passed }}" == "false" ]; then
echo "::error::Import time regression detected"
exit 1
fi
if [ "${{ steps.memory.outputs.memory_passed }}" == "false" ]; then
echo "::error::Memory usage regression detected"
exit 1
fi
echo "All performance checks passed!"
-2
View File
@@ -18,8 +18,6 @@ jobs:
steps:
- name: Checkout repository
uses: actions/checkout@v4
with:
persist-credentials: false
- name: Set up Docker Buildx
uses: docker/setup-buildx-action@v3
+4 -16
View File
@@ -2,9 +2,8 @@ name: Claude Issue Triage
description: "Automatically triage GitHub issues using Claude Code"
on:
workflow_dispatch:
# issues:
# types: [opened]
issues:
types: [opened]
jobs:
triage-issue:
@@ -13,23 +12,12 @@ jobs:
permissions:
contents: read
issues: write
id-token: write
steps:
- name: Generate GitHub App Token
id: app-token
uses: actions/create-github-app-token@v1
with:
app-id: ${{ secrets.CLAUDE_APP_ID }}
private-key: ${{ secrets.CLAUDE_APP_PRIVATE_KEY }}
owner: ${{ github.repository_owner }}
- name: Checkout repository
uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4
with:
token: ${{ steps.app-token.outputs.token }}
- name: Run Claude Issue Triage
uses: ./.github/actions/claude-issue-triage-action
with:
claude_code_oauth_token: ${{ secrets.CLAUDE_CODE_OAUTH_TOKEN }}
github_token: ${{ steps.app-token.outputs.token }}
anthropic_api_key: ${{ secrets.ANTHROPIC_API_KEY }}
github_token: ${{ secrets.GITHUB_TOKEN }}
+109 -243
View File
@@ -6,272 +6,35 @@ on:
pull_request_review_comment:
types: [created]
issues:
types: [assigned, labeled, opened]
types: [opened, assigned, labeled]
pull_request_review:
types: [submitted]
jobs:
# ================================================================
# Job 1: Lightweight triage for ALL new issues (including external users)
# Posts welcome comment + adds triage labels. No Claude code execution.
# ================================================================
issue-triage:
if: |
github.event_name == 'issues' &&
github.event.action == 'opened' &&
!contains(toJSON(github.event.issue.labels), 'claude')
runs-on: ubuntu-latest
permissions:
issues: write
contents: read
steps:
- name: Generate GitHub App Token
id: app-token
uses: actions/create-github-app-token@v1
with:
app-id: ${{ secrets.CLAUDE_APP_ID }}
private-key: ${{ secrets.CLAUDE_APP_PRIVATE_KEY }}
owner: ${{ github.repository_owner }}
- name: Triage and acknowledge issue
uses: actions/github-script@v7
with:
github-token: ${{ steps.app-token.outputs.token }}
script: |
const issue = context.payload.issue;
const title = (issue.title || '').toLowerCase();
const body = (issue.body || '').toLowerCase();
const content = title + ' ' + body;
const isOwner = ['OWNER', 'MEMBER', 'COLLABORATOR'].includes(
issue.author_association
);
// --- Label triage ---
const labels = [];
// Kind labels
if (content.includes('feature request') || content.includes('[feature')) {
labels.push('enhancement');
} else if (content.includes('bug') || content.includes('error') || content.includes('crash') || content.includes('traceback')) {
labels.push('bug');
} else if (content.includes('question') || content.includes('how do i') || content.includes('how to')) {
labels.push('question');
}
// Area labels
if (content.includes('security') || content.includes('cve') || content.includes('vulnerability')) {
labels.push('security');
}
if (content.includes('performance') || content.includes('slow') || content.includes('memory leak')) {
labels.push('performance');
}
if (content.includes('documentation') || content.includes('docs')) {
labels.push('documentation');
}
if (content.includes('typescript') || content.includes('javascript') || content.includes('npm')) {
labels.push('javascript');
}
// Apply labels
if (labels.length > 0) {
await github.rest.issues.addLabels({
issue_number: issue.number,
owner: context.repo.owner,
repo: context.repo.repo,
labels
});
}
// --- Acknowledgment comment (external users only) ---
if (!isOwner) {
await github.rest.issues.createComment({
issue_number: issue.number,
owner: context.repo.owner,
repo: context.repo.repo,
body: [
`👋 Thanks for opening this issue, @${issue.user.login}!`,
'',
'A maintainer will review this shortly. In the meantime:',
'- Make sure you\'ve included steps to reproduce (for bugs)',
'- Check [existing issues](https://github.com/MervinPraison/PraisonAI/issues) for duplicates',
'- Review the [documentation](https://docs.praison.ai) for related guides',
'',
'_A maintainer can trigger deeper analysis by commenting `@claude` on this issue._'
].join('\n')
});
}
// --- For owner: add 'claude' label to trigger the code-fix job ---
if (isOwner) {
await github.rest.issues.addLabels({
issue_number: issue.number,
owner: context.repo.owner,
repo: context.repo.repo,
labels: ['claude']
});
}
# ================================================================
# Job 2: Full Claude code-fix (owner/collaborator only)
# Triggers on: labeled 'claude', @claude comments, assignments
# ================================================================
claude-response:
# Allow: human users, github-actions[bot] (auto-comments/labels)
# Block: dependabot, cursor, renovate, other bots
# Skip 'opened' events — triage job handles those above
# Prevent certain bots from triggering this action (but allow github-actions[bot] for auto-comments)
if: |
github.event.action != 'opened' &&
(github.event.action != 'labeled' || github.event.label.name == 'claude') &&
(github.event_name != 'issue_comment' || contains(github.event.comment.body, '@claude')) &&
(
!contains(github.actor, '[bot]') ||
github.actor == 'github-actions[bot]' ||
github.actor == 'praisonai-triage-agent[bot]'
) &&
github.actor != 'dependabot[bot]' &&
github.actor != 'cursor[bot]' &&
github.actor != 'renovate[bot]'
github.actor != 'renovate[bot]' &&
!(contains(github.actor, '[bot]') && github.actor != 'github-actions[bot]')
runs-on: ubuntu-latest
permissions:
contents: write
pull-requests: write
issues: write
actions: read
id-token: write
steps:
- name: Generate GitHub App Token
id: app-token
uses: actions/create-github-app-token@v1
with:
app-id: ${{ secrets.CLAUDE_APP_ID }}
private-key: ${{ secrets.CLAUDE_APP_PRIVATE_KEY }}
owner: ${{ github.repository_owner }}
- name: Check for Fork PR
id: check_fork
uses: actions/github-script@v7
with:
script: |
const isPR = context.eventName === 'pull_request' || (context.payload.issue && context.payload.issue.pull_request);
if (isPR) {
const prNumber = context.payload.pull_request ? context.payload.pull_request.number : context.payload.issue.number;
const pr = await github.rest.pulls.get({
owner: context.repo.owner,
repo: context.repo.repo,
pull_number: prNumber
});
core.setOutput('pr_branch', pr.data.head.ref);
if (pr.data.head.repo && pr.data.head.repo.full_name !== context.repo.full_name) {
core.setOutput('is_fork', 'true');
core.setOutput('clone_url', pr.data.head.repo.clone_url);
core.setOutput('branch', pr.data.head.ref);
return;
}
}
core.setOutput('is_fork', 'false');
- name: Checkout repository
uses: actions/checkout@v4
with:
persist-credentials: false
fetch-depth: 0
token: ${{ steps.app-token.outputs.token }}
- name: Fetch PR branch and Setup Remote
if: github.event.issue.pull_request
env:
PR_BRANCH: ${{ steps.check_fork.outputs.pr_branch }}
IS_FORK: ${{ steps.check_fork.outputs.is_fork }}
run: |
# Fetch PR head from base repo and put it into local branch
git fetch origin pull/${{ github.event.issue.number }}/head:"${PR_BRANCH}"
# If it's a fork, make origin point to local to trick claude-code-action's `git fetch origin <branch>`
if [ "${IS_FORK}" = "true" ]; then
git remote set-url origin file://$(pwd)
fi
- uses: anthropics/claude-code-action@beta
env:
GH_TOKEN: ${{ steps.app-token.outputs.token }}
with:
allowed_bots: 'praisonai-triage-agent[bot]'
claude_code_oauth_token: ${{ secrets.CLAUDE_CODE_OAUTH_TOKEN }}
github_token: ${{ steps.app-token.outputs.token }}
claude_code_oauth_token: ${{ secrets.CLAUDE_ACCESS_TOKEN }}
github_token: ${{ secrets.GITHUB_TOKEN }}
trigger_phrase: "@claude"
label_trigger: "claude"
direct_prompt: |
${{ 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):
git config --global user.name "MervinPraison"
git config --global user.email "[email protected]"
gh auth setup-git
STEP 1 — READ GUIDELINES:
Read AGENTS.md to understand the architecture rules.
SCOPE: Focus ONLY on Python packages (praisonaiagents, praisonai). Do NOT modify or touch praisonai-rust or praisonai-ts packages.
STEP 2 — ARCHITECTURE VALIDATION & ROUTING (MANDATORY before writing code):
Before implementing anything, answer these questions:
- CORE vs WRAPPER vs TOOLS vs DOCS vs PLUGINS 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): Capabilities Agents actively call during execution (e.g. SurrealDB tool, Slack tool).
4. Documentation (PraisonAIDocs): Documentation pages, guides, API references.
5. Plugins (PraisonAI-Plugins): Framework lifecycle extensions replacing systemic behavior (e.g. tracing, logging, metrics, hooks, guardrails).
For items routed to an EXTERNAL repository (Tools, Docs, Plugins), follow STEP 3-ALT below.
- 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 (for changes in THIS repo — PraisonAI):
- Create a fix branch: git checkout -b claude/issue-$ISSUE_NUMBER-$(date +%Y%m%d)
- Implement a minimal, focused fix
- Follow protocol-driven design: protocols in core SDK, heavy implementations in wrapper
- Keep changes small and backward-compatible
- Commit: git add -A && git commit -m "fix: <description> (fixes #$ISSUE_NUMBER)"
- Push: git push origin claude/issue-$ISSUE_NUMBER-$(date +%Y%m%d)
CRITICAL: After pushing, you MUST immediately run: gh pr create --title "fix: <title>" --body "Fixes #$ISSUE_NUMBER" --head claude/issue-$ISSUE_NUMBER-$(date +%Y%m%d)
Do NOT stop after pushing. Do NOT say "manually create a PR". Always create the PR automatically.
STEP 3-ALT — IMPLEMENT IN EXTERNAL REPO (for PraisonAI-Tools, PraisonAIDocs, PraisonAI-Plugins):
When work must happen in a different repository, follow these steps EXACTLY. Do NOT attempt to use `cd`, as directory state is not preserved. Use `git -C` for all commands.
a) Clone the repository:
gh repo clone MervinPraison/<REPO_NAME> /tmp/<REPO_NAME>
b) Copy GitHub authentication from the main repository so push works seamlessly:
git -C /tmp/<REPO_NAME> config http."https://github.com/".extraheader "$(git config --get http."https://github.com/".extraheader)"
c) Create a feature branch (NEVER commit to main):
git -C /tmp/<REPO_NAME> checkout -b claude/issue-$ISSUE_NUMBER-$(date +%Y%m%d)
d) Make your changes using absolute paths (e.g. edit /tmp/<REPO_NAME>/docs.json)
e) Commit:
git -C /tmp/<REPO_NAME> add -A
git -C /tmp/<REPO_NAME> commit -m "feat: <description> (fixes #$ISSUE_NUMBER)"
f) Push the branch:
git -C /tmp/<REPO_NAME> push origin claude/issue-$ISSUE_NUMBER-$(date +%Y%m%d)
g) Create PR in the EXTERNAL repo:
gh pr create -R MervinPraison/<REPO_NAME> --head claude/issue-$ISSUE_NUMBER-$(date +%Y%m%d) --title "feat: <title>" --body "Fixes MervinPraison/PraisonAI#$ISSUE_NUMBER
<body>"
STEP 4 — TEST:
- 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.
allowed_tools: |
Bash(git:*)
Bash(python:*)
@@ -292,3 +55,106 @@ jobs:
mcp__github__get_issue_comments
mcp__github__update_issue
timeout_minutes: 30
post-review-comment:
needs: claude-response
if: success() && needs.claude-response.result == 'success'
runs-on: ubuntu-latest
permissions:
contents: read
pull-requests: write
issues: write
steps:
- name: Check for existing review comment
id: check-comment
uses: actions/github-script@v7
with:
github-token: ${{ secrets.GH_TOKEN }}
script: |
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') {
issueNumber = context.payload.pull_request?.number || context.issue.number;
} 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;
} else {
// This is a regular issue
issueNumber = context.issue.number;
}
comments = await github.rest.issues.listComments({
owner: context.repo.owner,
repo: context.repo.repo,
issue_number: issueNumber
});
// Look for Claude's completed review comments
const claudeReviewComments = comments.data.filter(comment =>
(comment.user.login === 'claude[bot]' || comment.body.includes('✅') || comment.body.includes('## Summary')) &&
!comment.body.includes('⏳') &&
!comment.body.includes('🔄') &&
!comment.body.includes('Loading...')
);
// Check if our review request comment already exists
const existingReviewRequest = comments.data.find(comment =>
comment.body.includes(reviewText)
);
// Post if Claude has completed a review AND we haven't posted the review request yet
const shouldPost = claudeReviewComments.length > 0 && !existingReviewRequest;
core.setOutput('should-post', shouldPost);
console.log(`Claude review completed: ${claudeReviewComments.length > 0}`);
console.log(`Review request exists: ${!!existingReviewRequest}`);
console.log(`Should post comment: ${shouldPost}`);
} catch (error) {
console.log('Error checking comments:', error);
core.setOutput('should-post', false); // If we can't check, don't post
}
- name: Wait 30 seconds before posting comment
if: steps.check-comment.outputs.should-post == 'true'
run: sleep 30
- name: Post review comment
if: steps.check-comment.outputs.should-post == 'true'
uses: actions/github-script@v7
with:
github-token: ${{ secrets.GH_TOKEN }}
script: |
let issueNumber;
let isPR = false;
// Determine issue/PR number and type based on event type
if (context.eventName === 'pull_request_review_comment' || context.eventName === 'pull_request_review') {
issueNumber = context.payload.pull_request?.number || context.issue.number;
isPR = true;
} else if (context.eventName === 'issue_comment' && context.payload.issue.pull_request) {
// This is a comment on a PR (not an issue)
issueNumber = context.payload.issue.number;
isPR = true;
} else {
// This is a regular issue - don't post review comment
issueNumber = context.issue.number;
isPR = false;
}
// Only post review comment on PRs, not regular issues
if (isPR) {
console.log(`Posting review comment on PR #${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 #${issueNumber}`);
}
+62
View File
@@ -0,0 +1,62 @@
name: Run tests and upload coverage
on:
push:
branches: [ main, develop ]
pull_request:
branches: [ main, develop ]
jobs:
test:
name: Run tests and collect coverage
runs-on: ubuntu-latest
timeout-minutes: 15
steps:
- name: Checkout
uses: actions/checkout@v4
with:
fetch-depth: 2
- name: Set up Python
uses: actions/setup-python@v5
with:
python-version: 3.11
- name: Install UV
run: |
curl -LsSf https://astral.sh/uv/install.sh | sh
echo "$HOME/.local/bin" >> $GITHUB_PATH
- name: Install dependencies
run: |
cd src/praisonai
uv pip install --system ."[ui,gradio,api,agentops,google,openai,anthropic,cohere,chat,code,realtime,call,crewai,autogen]"
uv pip install --system duckduckgo_search
uv pip install --system pytest pytest-cov pytest-asyncio
# Install knowledge dependencies from praisonai-agents
uv pip install --system "praisonaiagents[knowledge]"
- name: Set environment variables
run: |
echo "OPENAI_API_KEY=${{ secrets.OPENAI_API_KEY || 'sk-test-key-for-github-actions-testing-only-not-real' }}" >> $GITHUB_ENV
echo "OPENAI_API_BASE=${{ secrets.OPENAI_API_BASE || 'https://api.openai.com/v1' }}" >> $GITHUB_ENV
echo "OPENAI_MODEL_NAME=${{ secrets.OPENAI_MODEL_NAME || 'gpt-5-nano' }}" >> $GITHUB_ENV
echo "LOGLEVEL=DEBUG" >> $GITHUB_ENV
echo "PYTHONPATH=${{ github.workspace }}/src/praisonai-agents:$PYTHONPATH" >> $GITHUB_ENV
- name: Run tests
run: |
cd src/praisonai
# Run tests - allow some failures for now while we fix remaining issues
pytest --cov=praisonai --cov-branch --cov-report=xml tests/unit/ --tb=no -q || echo "Some tests failed, but coverage was collected"
- name: Upload results to Codecov
uses: codecov/codecov-action@v5
with:
token: ${{ secrets.CODECOV_TOKEN }}
file: src/praisonai/coverage.xml
flags: unit-tests
name: unit-tests-coverage
fail_ci_if_error: false
verbose: true
-4
View File
@@ -20,10 +20,6 @@ jobs:
steps:
- name: Checkout repository
uses: actions/checkout@v4
with:
persist-credentials: false
with:
persist-credentials: false
- name: Set up Docker Buildx
uses: docker/setup-buildx-action@v3
@@ -1,10 +1,8 @@
name: Gemini Automated Issue Triage
# on:
# issue_comment:
# types: [created]
on:
workflow_dispatch:
issue_comment:
types: [created]
jobs:
triage-issue:
@@ -34,10 +32,6 @@ jobs:
- name: Checkout repository
uses: actions/checkout@v4
with:
persist-credentials: false
with:
persist-credentials: false
with:
token: ${{ steps.generate_token.outputs.token }}
+16 -18
View File
@@ -2,8 +2,8 @@ name: Gemini Issue Review
on:
workflow_dispatch:
# issue_comment:
# types: [created]
issue_comment:
types: [created]
permissions:
contents: write
@@ -20,8 +20,7 @@ jobs:
!contains(github.event.comment.body, '@gemini triage') &&
(github.event.comment.author_association == 'OWNER' ||
github.event.comment.author_association == 'MEMBER' ||
github.event.comment.author_association == 'COLLABORATOR' ||
github.event.comment.author_association == 'CONTRIBUTOR'))
github.event.comment.author_association == 'COLLABORATOR'))
runs-on: ubuntu-latest
env:
GEMINI_API_KEY: ${{ secrets.GEMINI_API_KEY }}
@@ -35,17 +34,13 @@ jobs:
- name: Checkout repository
uses: actions/checkout@v4
with:
persist-credentials: false
with:
persist-credentials: false
with:
token: ${{ steps.generate_token.outputs.token }}
- name: Set up Git
run: |
git config --local user.email "[email protected].github.com"
git config --local user.name "MervinPraison"
git config --local user.email "gemini-bot@github.com"
git config --local user.name "Gemini Bot"
- name: Get issue data
id: issue_data
@@ -80,16 +75,16 @@ jobs:
echo "ADDITIONAL_INSTRUCTIONS=$ADDITIONAL_INSTRUCTIONS" >> $GITHUB_OUTPUT
- name: Run Gemini CLI
uses: google-github-actions/run-gemini-cli@v0
uses: ./.github/actions/gemini
env:
GH_TOKEN: ${{ steps.generate_token.outputs.token }}
GITHUB_TOKEN: ${{ steps.generate_token.outputs.token }}
ISSUE_NUMBER: ${{ steps.issue_data.outputs.ISSUE_NUMBER }}
ADDITIONAL_INSTRUCTIONS: ${{ steps.issue_data.outputs.ADDITIONAL_INSTRUCTIONS }}
REPOSITORY: ${{ github.repository }}
with:
gemini_api_key: ${{ secrets.GEMINI_API_KEY }}
gemini_model: 'gemini-2.5-flash'
GEMINI_API_KEY: ${{ secrets.GEMINI_API_KEY }}
OTLP_GCP_WIF_PROVIDER: ${{ secrets.OTLP_GCP_WIF_PROVIDER }}
OTLP_GOOGLE_CLOUD_PROJECT: ${{ secrets.OTLP_GOOGLE_CLOUD_PROJECT }}
prompt: |
You are a helpful GitHub issue assistant. Your task is to analyze and help with GitHub issues.
@@ -108,8 +103,6 @@ jobs:
- Search codebase for related files using `glob`, `search_file_content`, `list_directory`
**STEP 2: If Code Changes Are Needed**
MANDATORY FIRST STEP: Before writing any code, you MUST use `read_file` to carefully read "src/praisonai-agents/AGENTS.md". You must honor this repository's extremely specific Architecture, Protocol-First design rules, and Agent-Centric Philosophy!
Create a new branch with 'gemini/' prefix:
- Use: `git checkout -b gemini/issue-${ISSUE_NUMBER}-description`
- Example: `git checkout -b gemini/issue-123-fix-sequential-tools`
@@ -168,7 +161,7 @@ jobs:
Please proceed with helping resolve this issue following this exact workflow.
settings: |
settings_json: |
{
"coreTools": [
"run_shell_command(echo)",
@@ -200,5 +193,10 @@ jobs:
"web_fetch",
"google_web_search",
"save_memory"
]
],
"telemetry": {
"enabled": false,
"otlpGcpWifProvider": "${{ secrets.OTLP_GCP_WIF_PROVIDER }}",
"googleCloudProject": "${{ secrets.OTLP_GOOGLE_CLOUD_PROJECT }}"
}
}
+2 -8
View File
@@ -1,8 +1,8 @@
name: Gemini PR Review
on:
# issue_comment:
# types: [created]
issue_comment:
types: [created]
workflow_dispatch:
inputs:
pr_number:
@@ -46,10 +46,6 @@ jobs:
- name: Checkout PR code
uses: actions/checkout@v4
with:
persist-credentials: false
with:
persist-credentials: false
with:
token: ${{ steps.generate_token.outputs.token }}
ref: ${{ steps.checkout_ref.outputs.ref }}
@@ -163,8 +159,6 @@ jobs:
- Analyze the code changes thoroughly
**STEP 2: If Code Improvements 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!
**IMPORTANT:** DO NOT create a new branch! Work on the EXISTING PR branch.
- Use: `git fetch origin` to get latest changes
- Get PR branch name: `gh pr view ${PR_NUMBER} --json headRefName`
@@ -1,158 +0,0 @@
name: Cross-Repo Integration Tests
on:
push:
branches: [ main ]
paths:
- 'src/praisonai/praisonai/integration/**'
- 'src/praisonai/tests/integration/test_aiui_*'
- 'src/praisonai/pyproject.toml'
pull_request:
branches: [ main ]
paths:
- 'src/praisonai/praisonai/integration/**'
- 'src/praisonai/tests/integration/test_aiui_*'
- 'src/praisonai/pyproject.toml'
workflow_dispatch:
jobs:
cross-repo-integration:
runs-on: ubuntu-latest
timeout-minutes: 30
steps:
- name: Checkout PraisonAI
uses: actions/checkout@v4
with:
path: PraisonAI
ref: ${{ github.event_name == 'pull_request' && github.event.pull_request.head.sha || github.sha }}
- name: Checkout PraisonAIUI
uses: actions/checkout@v4
with:
repository: MervinPraison/PraisonAIUI
path: PraisonAIUI
ref: main
- name: Set up Python
uses: actions/setup-python@v4
with:
python-version: '3.11'
- name: Install dependencies
run: |
python -m pip install --upgrade pip
# Install PraisonAI packages in development mode
cd PraisonAI/src/praisonai-agents
pip install -e .
cd ../praisonai
pip install -e ".[ui,dev]"
# Install PraisonAIUI in development mode
cd ../../../PraisonAIUI
pip install -e .
- name: Verify versions
run: |
python -c "import praisonaiagents; print(f'praisonaiagents: {praisonaiagents.__version__}')"
python -c "import praisonai; print(f'praisonai: {praisonai.__version__}')"
python -c "import praisonaiui; print(f'praisonaiui: {praisonaiui.__version__}')"
- name: Run PraisonAI integration tests
run: |
cd PraisonAI/src/praisonai
python -m pytest tests/integration/test_aiui_* -v --timeout=300
- name: Run PraisonAIUI integration tests
run: |
cd PraisonAIUI
if [ -f tests/integration/test_agentic_roundtrip.py ]; then
python -m pytest tests/integration/test_agentic_roundtrip.py -v --timeout=300
fi
if [ -f tests/test_feature_sdk_backends.py ]; then
python -m pytest tests/test_feature_sdk_backends.py -v --timeout=300
fi
- name: Test Pattern C CLI
run: |
cd PraisonAI/src/praisonai
# Test that ui-gateway command exists
python -m praisonai serve --help | grep ui-gateway
- name: Test public API exports
run: |
cd PraisonAI/src/praisonai
python -c "from praisonai import run_integrated_gateway; print('✓ run_integrated_gateway imported')"
python -c "from praisonai import configure_host; print('✓ configure_host imported')"
- name: Integration smoke test
env:
PRAISONAI_TEST_MODE: "1"
PYTHONPATH: ${{ github.workspace }}/PraisonAI/src/praisonai:${{ github.workspace }}/PraisonAI/src/praisonai-agents:${{ github.workspace }}/PraisonAIUI
run: |
cd PraisonAI/src/praisonai
python -c "
import sys
sys.path.insert(0, '.')
from praisonai.integration.host_app import configure_host
from praisonai import run_integrated_gateway
print('✓ Integration imports successful')
# Test configure_host with new parameters
try:
configure_host(
style='dashboard',
context_paths=['AGENTS.md'],
title='Test App'
)
print('✓ configure_host with new parameters works')
except Exception as e:
print(f'× configure_host failed: {e}')
sys.exit(1)
"
# Optional job with API key for agentic tests (if secret is available)
agentic-integration:
runs-on: ubuntu-latest
timeout-minutes: 30
if: ${{ vars.RUN_AGENTIC_TESTS == 'true' }}
needs: cross-repo-integration
steps:
- name: Checkout PraisonAI
uses: actions/checkout@v4
with:
path: PraisonAI
ref: ${{ github.event_name == 'pull_request' && github.event.pull_request.head.sha || github.sha }}
- name: Checkout PraisonAIUI
uses: actions/checkout@v4
with:
repository: MervinPraison/PraisonAIUI
path: PraisonAIUI
ref: main
- name: Set up Python
uses: actions/setup-python@v4
with:
python-version: '3.11'
- name: Install dependencies
run: |
python -m pip install --upgrade pip
cd PraisonAI/src/praisonai-agents
pip install -e .
cd ../praisonai
pip install -e ".[ui,dev]"
cd ../../../PraisonAIUI
pip install -e .
- name: Run agentic integration test
env:
OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
run: |
cd PraisonAI/src/praisonai
if [ -n "$OPENAI_API_KEY" ]; then
python -m pytest tests/integration/test_aiui_host_agentic.py -v --timeout=600
else
echo "OPENAI_API_KEY not available, skipping agentic tests"
fi
@@ -1,71 +0,0 @@
name: PraisonAI Issue Triage
on:
issue_comment:
types: [created]
workflow_dispatch:
inputs:
issue_number:
description: 'Issue Number'
required: true
type: string
jobs:
triage:
runs-on: ubuntu-latest
if: >
github.event_name == 'workflow_dispatch' ||
(github.event_name == 'issue_comment' &&
!github.event.issue.pull_request &&
contains(github.event.comment.body, '@praisonai') &&
github.actor != 'github-actions[bot]' &&
github.event.comment.user.type != 'Bot' &&
(github.event.comment.author_association == 'OWNER' ||
github.event.comment.author_association == 'MEMBER' ||
github.event.comment.author_association == 'COLLABORATOR'))
steps:
- name: Checkout Repository
uses: actions/checkout@v4
with:
persist-credentials: false
fetch-depth: 0
- name: Generate GitHub App Token
id: generate_token
uses: tibdex/github-app-token@v2
with:
app_id: ${{ secrets.PRAISONAI_APP_ID }}
private_key: ${{ secrets.PRAISONAI_APP_PRIVATE_KEY }}
- name: Set up Python
uses: actions/setup-python@v5
with:
python-version: '3.11'
- name: Set up Git
run: |
git config --local user.email "[email protected]"
git config --local user.name "PraisonAI Bot"
- name: Install PraisonAI
run: |
pip install uv
cd src/praisonai-agents && uv pip install --system -e ".[all]"
cd ../praisonai && uv pip install --system -e ".[all]"
- name: Run PraisonAI Issue Triage
env:
GITHUB_TOKEN: ${{ steps.generate_token.outputs.token }}
GH_TOKEN: ${{ steps.generate_token.outputs.token }}
OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
PRAISONAI_AUTO_APPROVE: "true"
ISSUE_NUMBER_INPUT: ${{ inputs.issue_number }}
ISSUE_NUMBER_EVENT: ${{ github.event.issue.number }}
run: |
if [ "${{ github.event_name }}" = "workflow_dispatch" ]; then
export ISSUE_NUMBER="$ISSUE_NUMBER_INPUT"
else
export ISSUE_NUMBER="$ISSUE_NUMBER_EVENT"
fi
praisonai github triage --issue $ISSUE_NUMBER --agent-file .github/praisonai-issue-triage.yaml
-73
View File
@@ -1,73 +0,0 @@
name: PraisonAI PR Reviewer
on:
pull_request:
types: [opened, synchronize, reopened, ready_for_review]
issue_comment:
types: [created]
workflow_dispatch:
inputs:
pr_number:
description: 'Pull Request Number'
required: true
type: string
jobs:
review:
runs-on: ubuntu-latest
if: >
(github.event_name == 'pull_request' && github.event.pull_request.draft == false) ||
github.event_name == 'workflow_dispatch' ||
(github.event_name == 'issue_comment' &&
github.event.issue.pull_request &&
contains(github.event.comment.body, '@praisonai') &&
github.actor != 'github-actions[bot]' &&
github.event.comment.user.type != 'Bot' &&
(github.event.comment.author_association == 'OWNER' ||
github.event.comment.author_association == 'MEMBER' ||
github.event.comment.author_association == 'COLLABORATOR'))
steps:
- name: Determine checkout ref
id: dest
env:
ISSUE_NUMBER: ${{ github.event.issue.number }}
PR_NUMBER_INPUT: ${{ inputs.pr_number }}
PR_HEAD_SHA: ${{ github.event.pull_request.head.sha }}
run: |
if [ "${{ github.event_name }}" = "issue_comment" ]; then
echo "ref=refs/pull/$ISSUE_NUMBER/head" >> "$GITHUB_OUTPUT"
elif [ "${{ github.event_name }}" = "workflow_dispatch" ]; then
echo "ref=refs/pull/$PR_NUMBER_INPUT/head" >> "$GITHUB_OUTPUT"
else
echo "ref=$PR_HEAD_SHA" >> "$GITHUB_OUTPUT"
fi
- name: Checkout Repository
uses: actions/checkout@v4
with:
persist-credentials: false
ref: ${{ steps.dest.outputs.ref }}
fetch-depth: 0
- name: Generate GitHub App Token
id: generate_token
uses: tibdex/github-app-token@v2
with:
app_id: ${{ secrets.PRAISONAI_APP_ID }}
private_key: ${{ secrets.PRAISONAI_APP_PRIVATE_KEY }}
- name: Set up Python
uses: actions/setup-python@v5
with:
python-version: '3.11'
- name: Install PraisonAI
run: pip install "praisonai[all]"
- name: Run PraisonAI PR Review
env:
GITHUB_TOKEN: ${{ steps.generate_token.outputs.token }}
OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
run: |
praisonai workflow run .github/praisonai-reviewer.yaml
+38 -12
View File
@@ -1,22 +1,25 @@
name: Python Package (Multi-Version)
# This workflow will install Python dependencies, run tests and lint with a variety of Python versions
# For more information see: https://docs.github.com/en/actions/automating-builds-and-tests/building-and-testing-python
name: Python package
on:
schedule:
- cron: '0 4 * * 1' # Weekly Monday 4am UTC
workflow_dispatch:
push:
branches: [ "develop" ]
pull_request:
branches: [ "develop" ]
jobs:
build:
runs-on: ubuntu-latest
strategy:
fail-fast: false
matrix:
python-version: ["3.10", "3.11", "3.12"]
python-version: ["3.10", "3.11"]
steps:
- uses: actions/checkout@v4
with:
persist-credentials: false
- name: Set up Python ${{ matrix.python-version }}
uses: actions/setup-python@v5
with:
@@ -27,16 +30,39 @@ jobs:
echo "OPENAI_API_KEY=${{ secrets.OPENAI_API_KEY || 'sk-test-key-for-github-actions-testing-only-not-real' }}" >> $GITHUB_ENV
echo "OPENAI_API_BASE=${{ secrets.OPENAI_API_BASE || 'https://api.openai.com/v1' }}" >> $GITHUB_ENV
echo "OPENAI_MODEL_NAME=${{ secrets.OPENAI_MODEL_NAME || 'gpt-5-nano' }}" >> $GITHUB_ENV
echo "PYTHONPATH=${{ github.workspace }}/src/praisonai-agents:$PYTHONPATH" >> $GITHUB_ENV
echo "LOGLEVEL=DEBUG" >> $GITHUB_ENV
- name: Install dependencies
run: |
cd src/praisonai
python -m pip install --upgrade pip
python -m pip install flake8 pytest
python -m pip install ."[ui,gradio,api,agentops,google,openai,anthropic,cohere,chat,code,realtime,call,crewai,autogen]"
python -m pip install duckduckgo_search pytest pytest-asyncio pytest-cov
python -m pip install duckduckgo_search
python -m pip install pytest-asyncio pytest-cov
# Install knowledge dependencies from praisonai-agents
python -m pip install "praisonaiagents[knowledge]"
- name: Run tests
if [ -f requirements.txt ]; then pip install -r requirements.txt; fi
- name: Debug API Key Status
run: |
cd src/praisonai && python -m pytest tests/unit/ -v --tb=short --disable-warnings --timeout=60 || echo "Some tests failed"
echo "🔍 Checking API key availability..."
if [ -n "${{ secrets.OPENAI_API_KEY }}" ]; then
echo "✅ GitHub secret OPENAI_API_KEY is available"
echo "🔑 API key starts with: $(echo "$OPENAI_API_KEY" | cut -c1-7)..."
else
echo "⚠️ GitHub secret OPENAI_API_KEY is NOT set - using fallback"
echo "🔑 Using fallback key: sk-test-key..."
fi
echo "🌐 API Base: $OPENAI_API_BASE"
echo "🤖 Model: $OPENAI_MODEL_NAME"
# - name: Lint with flake8
# run: |
# # stop the build if there are Python syntax errors or undefined names
# flake8 . --count --select=E9,F63,F7,F82 --show-source --statistics
# # exit-zero treats all errors as warnings. The GitHub editor is 127 chars wide
# flake8 . --count --exit-zero --max-complexity=10 --max-line-length=127 --statistics
- name: Test with pytest
run: |
cd src/praisonai && python tests/test_runner.py --pattern fast
-2
View File
@@ -22,8 +22,6 @@ jobs:
steps:
- uses: actions/checkout@v4
with:
persist-credentials: false
- name: Set up Python
uses: actions/setup-python@v5
with:
+30 -56
View File
@@ -26,10 +26,6 @@ jobs:
# First checkout the upstream repo at the specified tag
- name: Checkout upstream repo
uses: actions/checkout@v4
with:
persist-credentials: false
with:
persist-credentials: false
with:
repository: MervinPraison/PraisonAI
ref: ${{ github.event.inputs.tag }}
@@ -38,20 +34,14 @@ jobs:
# Get the commit hash from the tag
- name: Get commit hash
id: get_commit
env:
INPUT_TAG: ${{ github.event.inputs.tag }}
run: |
COMMIT_HASH=$(git rev-parse HEAD)
echo "commit_hash=$COMMIT_HASH" >> $GITHUB_OUTPUT
echo "Found commit: $COMMIT_HASH for tag $INPUT_TAG"
echo "Found commit: $COMMIT_HASH for tag ${{ github.event.inputs.tag }}"
# Now checkout the fork at main branch
- name: Checkout fork
uses: actions/checkout@v4
with:
persist-credentials: false
with:
persist-credentials: false
with:
repository: ${{ github.event.inputs.fork_owner }}/PraisonAI
ref: main
@@ -61,8 +51,8 @@ jobs:
# Sync with upstream commit
- name: Sync with upstream
run: |
git config --global user.name "MervinPraison"
git config --global user.email "[email protected].github.com"
git config --global user.name "GitHub Actions"
git config --global user.email "actions@github.com"
# Add upstream remote
git remote add upstream https://github.com/MervinPraison/PraisonAI.git
@@ -70,11 +60,8 @@ jobs:
# Fetch from upstream
git fetch upstream --tags --force
- name: Hard reset to tag commit
env:
COMMIT_HASH: ${{ steps.get_commit.outputs.commit_hash }}
run: |
git reset --hard $COMMIT_HASH
# Reset to upstream commit
git reset --hard ${{ steps.get_commit.outputs.commit_hash }}
- name: Setup Python
uses: actions/setup-python@v5
@@ -449,10 +436,6 @@ jobs:
# First checkout the fork's main branch
- name: Checkout fork repo
uses: actions/checkout@v4
with:
persist-credentials: false
with:
persist-credentials: false
with:
fetch-depth: 0
token: ${{ secrets.PAT_TOKEN }}
@@ -462,64 +445,55 @@ jobs:
# Add upstream and get commit from tag
- name: Get upstream tag commit
id: get_upstream_commit
env:
INPUT_TAG: ${{ github.event.inputs.tag }}
run: |
# Add upstream remote
git remote add upstream https://github.com/MervinPraison/PraisonAI.git
# Delete local tag if it exists
git tag -d "$INPUT_TAG" || true
git tag -d ${{ github.event.inputs.tag }} || true
# Fetch from upstream including tags with force
git fetch upstream --tags --force
# Verify tag exists in upstream
if ! git ls-remote --tags upstream | grep -q "refs/tags/$INPUT_TAG$"; then
echo "::error::Tag $INPUT_TAG not found in upstream repository"
if ! git ls-remote --tags upstream | grep -q "refs/tags/${{ github.event.inputs.tag }}$"; then
echo "::error::Tag ${{ github.event.inputs.tag }} not found in upstream repository"
exit 1
fi
# Get the commit hash from the upstream tag
UPSTREAM_COMMIT=$(git rev-list -n 1 refs/tags/"$INPUT_TAG")
UPSTREAM_COMMIT=$(git rev-list -n 1 refs/tags/${{ github.event.inputs.tag }})
if [ -z "$UPSTREAM_COMMIT" ]; then
echo "::error::Could not find commit for tag $INPUT_TAG"
echo "::error::Could not find commit for tag ${{ github.event.inputs.tag }}"
exit 1
fi
echo "upstream_commit=$UPSTREAM_COMMIT" >> $GITHUB_OUTPUT
echo "Found commit: $UPSTREAM_COMMIT for tag $INPUT_TAG"
echo "Found commit: $UPSTREAM_COMMIT for tag ${{ github.event.inputs.tag }}"
# Create tag at the same commit
- name: Create tag at commit
run: |
git config --global user.name "GitHub Actions"
git config --global user.email "[email protected]"
# Remove tag if it exists locally
git tag -d ${{ github.event.inputs.tag }} || true
# Remove tag if it exists remotely
git push origin :refs/tags/${{ github.event.inputs.tag }} || true
# Fetch the specific commit from upstream
git fetch upstream ${{ steps.get_upstream_commit.outputs.upstream_commit }} --force
# Reset to upstream commit
git reset --hard ${{ steps.get_upstream_commit.outputs.upstream_commit }}
# Create and push tag
git tag -a ${{ github.event.inputs.tag }} -m "Release ${{ github.event.inputs.tag }} (synced from upstream MervinPraison/PraisonAI@${{ github.event.inputs.tag }})"
git push origin ${{ github.event.inputs.tag }}
env:
GIT_ASKPASS: /bin/echo
PAT_TOKEN: ${{ secrets.PAT_TOKEN }}
INPUT_TAG: ${{ github.event.inputs.tag }}
run: |
git config --global user.name "MervinPraison"
git config --global user.email "[email protected]"
# Remove tag if it exists locally
git tag -d "$INPUT_TAG" || true
# Remove tag if it exists remotely
git push origin :refs/tags/"$INPUT_TAG" || true
- name: Fetch tag from upstream
env:
UPSTREAM_COMMIT: ${{ steps.get_upstream_commit.outputs.upstream_commit }}
run: |
git fetch upstream $UPSTREAM_COMMIT --force
- name: Reset to upstream commit
env:
UPSTREAM_COMMIT: ${{ steps.get_upstream_commit.outputs.upstream_commit }}
run: |
git reset --hard $UPSTREAM_COMMIT
# Create and push tag
git tag -a "$INPUT_TAG" -m "Release $INPUT_TAG (synced from upstream MervinPraison/PraisonAI@$INPUT_TAG)"
git push origin "$INPUT_TAG"
# Create the release
- name: Create Release
+4 -13
View File
@@ -37,10 +37,6 @@ jobs:
steps:
- name: Checkout code
uses: actions/checkout@v4
with:
persist-credentials: false
with:
persist-credentials: false
- name: Set up Python ${{ matrix.python-version }}
uses: actions/setup-python@v5
@@ -71,11 +67,9 @@ jobs:
fi
- name: Run Comprehensive Test Suite
env:
INPUT_TEST_TYPE: ${{ github.event.inputs.test_type || 'all' }}
run: |
# Determine test type from input or default to 'all'
TEST_TYPE="$INPUT_TEST_TYPE"
TEST_TYPE="${{ github.event.inputs.test_type || 'all' }}"
echo "🧪 Running comprehensive test suite (type: $TEST_TYPE)"
@@ -108,16 +102,13 @@ jobs:
- name: Generate Comprehensive Test Report
if: always()
env:
INPUT_TEST_TYPE: ${{ github.event.inputs.test_type || 'all' }}
EVENT_NAME: ${{ github.event_name }}
run: |
echo "# 📋 Comprehensive Test Report" > comprehensive_report.md
echo "" >> comprehensive_report.md
echo "**Python Version:** ${{ matrix.python-version }}" >> comprehensive_report.md
echo "**Test Type:** $INPUT_TEST_TYPE" >> comprehensive_report.md
echo "**Trigger:** $EVENT_NAME" >> comprehensive_report.md
echo "**Status:** 🟢 All Tests Passed" >> comprehensive_report.md
echo "**Test Type:** ${{ github.event.inputs.test_type || 'all' }}" >> comprehensive_report.md
echo "**Trigger:** ${{ github.event_name }}" >> comprehensive_report.md
echo "**Date:** $(date -u)" >> comprehensive_report.md
echo "" >> comprehensive_report.md
echo "## 🧪 Test Categories Covered:" >> comprehensive_report.md
+245 -31
View File
@@ -1,45 +1,41 @@
name: Core Tests
on:
on:
push:
branches: [ main, develop ]
paths:
- 'src/**'
- 'pyproject.toml'
- '.github/workflows/test-core.yml'
pull_request:
branches: [ main, develop ]
paths:
- 'src/**'
- 'pyproject.toml'
- '.github/workflows/test-core.yml'
workflow_dispatch:
jobs:
test-core:
runs-on: ubuntu-latest
timeout-minutes: 20
timeout-minutes: 15
strategy:
matrix:
python-version: [3.11]
steps:
- uses: actions/checkout@v4
with:
persist-credentials: false
- name: Set up Python 3.11
- name: Checkout code
uses: actions/checkout@v4
- name: Set up Python ${{ matrix.python-version }}
uses: actions/setup-python@v5
with:
python-version: '3.11'
python-version: ${{ matrix.python-version }}
- name: Install UV
run: |
curl -LsSf https://astral.sh/uv/install.sh | sh
echo "$HOME/.local/bin" >> $GITHUB_PATH
- name: Install dependencies
run: |
cd src/praisonai
uv pip install --system ."[ui,gradio,api,agentops,google,openai,anthropic,cohere,chat,code,realtime,call,crewai,autogen]"
uv pip install --system duckduckgo_search
uv pip install --system pytest pytest-asyncio pytest-cov pytest-timeout
# Install knowledge dependencies from praisonai-agents
uv pip install --system "praisonaiagents[knowledge]"
- name: Set environment variables
@@ -47,28 +43,246 @@ jobs:
echo "OPENAI_API_KEY=${{ secrets.OPENAI_API_KEY || 'sk-test-key-for-github-actions-testing-only-not-real' }}" >> $GITHUB_ENV
echo "OPENAI_API_BASE=${{ secrets.OPENAI_API_BASE || 'https://api.openai.com/v1' }}" >> $GITHUB_ENV
echo "OPENAI_MODEL_NAME=${{ secrets.OPENAI_MODEL_NAME || 'gpt-5-nano' }}" >> $GITHUB_ENV
echo "LOGLEVEL=DEBUG" >> $GITHUB_ENV
echo "PYTHONPATH=${{ github.workspace }}/src/praisonai-agents:$PYTHONPATH" >> $GITHUB_ENV
# Also export to current shell session for immediate availability
export OPENAI_API_KEY="${{ secrets.OPENAI_API_KEY || 'sk-test-key-for-github-actions-testing-only-not-real' }}"
export OPENAI_API_BASE="${{ secrets.OPENAI_API_BASE || 'https://api.openai.com/v1' }}"
export OPENAI_MODEL_NAME="${{ secrets.OPENAI_MODEL_NAME || 'gpt-5-nano' }}"
export LOGLEVEL=DEBUG
# Verify immediate availability
echo "🔧 Immediate verification in same step:"
echo " OPENAI_API_KEY length in current session: ${#OPENAI_API_KEY}"
echo " OPENAI_API_KEY starts with sk-: $(echo "$OPENAI_API_KEY" | grep -q '^sk-' && echo 'YES' || echo 'NO')"
- name: Debug API Key Status
run: |
echo "🔍 Checking API key availability..."
if [ -n "${{ secrets.OPENAI_API_KEY }}" ]; then
echo "✅ GitHub secret OPENAI_API_KEY is available"
echo "🔑 API key starts with: $(echo "$OPENAI_API_KEY" | cut -c1-7)..."
else
echo "⚠️ GitHub secret OPENAI_API_KEY is NOT set - using fallback"
echo "🔑 Using fallback key: sk-test-key..."
fi
echo "🌐 API Base: $OPENAI_API_BASE"
echo "🤖 Model: $OPENAI_MODEL_NAME"
echo "🐛 Log Level: $LOGLEVEL"
echo "📊 Environment Check:"
echo " - OPENAI_API_KEY length: ${#OPENAI_API_KEY}"
echo " - OPENAI_API_BASE: $OPENAI_API_BASE"
echo " - OPENAI_MODEL_NAME: $OPENAI_MODEL_NAME"
echo " - LOGLEVEL: $LOGLEVEL"
echo "🔍 Is API key actually set?"
echo " - API key starts with sk-: $(echo "$OPENAI_API_KEY" | grep -q '^sk-' && echo 'YES' || echo 'NO')"
echo " - API key is not test key: $([ "$OPENAI_API_KEY" != 'sk-test-key-for-github-actions-testing-only-not-real' ] && echo 'YES' || echo 'NO')"
- name: Debug Environment Variables Raw
run: |
echo "🔧 Raw environment variable check:"
echo "OPENAI_API_KEY set: $(if [ -n "$OPENAI_API_KEY" ]; then echo 'YES'; else echo 'NO'; fi)"
echo "OPENAI_API_KEY length: ${#OPENAI_API_KEY}"
echo "OPENAI_API_KEY first 10 chars: ${OPENAI_API_KEY:0:10}"
echo "OPENAI_API_KEY last 5 chars: ${OPENAI_API_KEY: -5}"
printenv | grep OPENAI || echo "No OPENAI env vars found"
- name: Debug Python Environment Variables
run: |
python -c "
import os
print('🐍 Python Environment Variable Check:')
api_key = os.environ.get('OPENAI_API_KEY', 'NOT_SET')
if api_key != 'NOT_SET':
print(f' ✅ OPENAI_API_KEY: {api_key[:7]}... (length: {len(api_key)})')
else:
print(' ❌ OPENAI_API_KEY: NOT_SET')
print(f' 🌐 OPENAI_API_BASE: {os.environ.get(\"OPENAI_API_BASE\", \"NOT_SET\")}')
print(f' 🤖 OPENAI_MODEL_NAME: {os.environ.get(\"OPENAI_MODEL_NAME\", \"NOT_SET\")}')
print(f' 📋 All OPENAI env vars:')
for key, value in os.environ.items():
if key.startswith('OPENAI'):
print(f' {key}: {value[:10] if len(value) > 10 else value}...')
"
- name: Validate API Key
run: |
echo "🔑 Testing API key validity with minimal OpenAI call..."
python -c "
import os
try:
from openai import OpenAI
client = OpenAI(api_key=os.environ.get('OPENAI_API_KEY'))
response = client.models.list()
print('✅ API Key is VALID - OpenAI responded successfully')
print(f'📊 Available models: {len(list(response.data))} models found')
except Exception as e:
print(f'❌ API Key is INVALID - Error: {e}')
print('🔍 This explains why all API-dependent tests are failing')
print('💡 The GitHub secret OPENAI_API_KEY needs to be updated with a valid key')
"
continue-on-error: true
- name: Debug PraisonAI API Key Usage
env:
OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY || 'sk-test-key-for-github-actions-testing-only-not-real' }}
OPENAI_API_BASE: ${{ secrets.OPENAI_API_BASE || 'https://api.openai.com/v1' }}
OPENAI_MODEL_NAME: ${{ secrets.OPENAI_MODEL_NAME || 'gpt-5-nano' }}
LOGLEVEL: DEBUG
run: |
echo "🔍 Testing PraisonAI API key usage directly..."
cd src/praisonai
python -c "
import os
import sys
sys.path.insert(0, '.')
# Attempt to import SecretStr, otherwise use a dummy class
try:
from pydantic.types import SecretStr
except ImportError:
class SecretStr: # Dummy class if pydantic is not available in this minimal context
def __init__(self, value): self._value = value
def get_secret_value(self): return self._value
def get_key_display_value(key_value):
if isinstance(key_value, SecretStr):
return key_value.get_secret_value()[:10] if key_value.get_secret_value() else 'EMPTY_SECRET'
elif isinstance(key_value, str):
return key_value[:10] if key_value != 'nokey' and key_value != 'NOT_SET' else key_value
return 'INVALID_TYPE'
print('🔧 Direct PraisonAI API Key Check:')
env_api_key = os.environ.get(\"OPENAI_API_KEY\", \"NOT_SET\")
print(f'Environment OPENAI_API_KEY: {get_key_display_value(env_api_key)}...')
from praisonai import PraisonAI
praisonai = PraisonAI()
print(f'PraisonAI config_list: {praisonai.config_list}')
api_key_from_config = praisonai.config_list[0].get('api_key', 'NOT_SET')
print(f'API key from PraisonAI config: {get_key_display_value(api_key_from_config)}...')
from praisonai.inc.models import PraisonAIModel
print('\\n🧪 Testing PraisonAIModel with explicit API key (CrewAI method):')
model_with_explicit_key = PraisonAIModel(
model='openai/gpt-5-nano',
base_url=praisonai.config_list[0].get('base_url'),
api_key=api_key_from_config # This will be a string from praisonai.config_list
)
print(f' Model: {model_with_explicit_key.model}')
print(f' Model name: {model_with_explicit_key.model_name}')
print(f' API key var: {model_with_explicit_key.api_key_var}')
# model_with_explicit_key.api_key is now a string, or 'nokey'
print(f' API key (explicitly passed to PraisonAIModel): {get_key_display_value(model_with_explicit_key.api_key)}...')
print(f' Base URL: {model_with_explicit_key.base_url}')
try:
llm_instance = model_with_explicit_key.get_model()
print(f' ✅ LLM instance created successfully: {type(llm_instance).__name__}')
# langchain_openai.ChatOpenAI stores the key in openai_api_key as SecretStr
llm_api_key_attr = getattr(llm_instance, 'openai_api_key', 'NOT_FOUND')
if llm_api_key_attr != 'NOT_FOUND':
print(f' LLM instance API key: {get_key_display_value(llm_api_key_attr)}...')
else:
print(f' LLM instance API key attribute not found.')
except Exception as e:
print(f' ❌ Failed to create LLM instance: {e}')
import traceback
traceback.print_exc()
"
continue-on-error: true
- name: Run Unit Tests
run: |
cd src/praisonai && python -m pytest tests/unit/ -v --tb=short --disable-warnings \
--cov=praisonai --cov-report=xml --cov-branch \
--timeout=60 || echo "Some unit tests failed"
cd src/praisonai && python -m pytest tests/unit/ -v --tb=short --disable-warnings --cov=praisonai --cov-report=term-missing --cov-report=xml --cov-branch || echo "Some tests failed - see output above"
continue-on-error: true
- name: Run Integration Tests
- name: Run Integration Tests
run: |
cd src/praisonai && python -m pytest tests/integration/ -v --tb=short --disable-warnings \
--timeout=60 \
--ignore=tests/integration/test_tracker_complex_tasks.py \
--ignore=tests/integration/test_serve_integration.py \
|| echo "Some integration tests failed"
cd src/praisonai && python -m pytest tests/integration/ -v --tb=short --disable-warnings
- name: Upload coverage to Codecov
if: always()
- name: Debug Directory Structure
run: |
echo "🔍 Debugging directory structure for CrewAI tests..."
cd src/praisonai
echo "Current working directory: $(pwd)"
echo "📁 Contents of current directory:"
ls -la
echo ""
echo "📁 Contents of tests directory:"
ls -la tests/ || echo "❌ tests/ directory not found"
echo ""
echo "📁 Contents of tests/integration:"
ls -la tests/integration/ || echo "❌ tests/integration/ directory not found"
echo ""
echo "📁 Looking for crewai directory:"
find . -name "crewai" -type d 2>/dev/null || echo "❌ No crewai directories found"
echo ""
echo "📁 Full directory tree of tests:"
tree tests/ || find tests/ -type d 2>/dev/null || echo "❌ Cannot explore tests directory"
- name: Test AutoGen Framework
run: |
echo "🤖 Testing AutoGen Framework Integration..."
cd src/praisonai && python tests/test_runner.py --pattern autogen --verbose
- name: Test CrewAI Framework
run: |
echo "⛵ Testing CrewAI Framework Integration..."
cd src/praisonai
echo "🔍 Trying test runner first..."
python tests/test_runner.py --pattern crewai --verbose || {
echo "❌ Test runner failed, trying direct pytest..."
echo "📁 Current directory: $(pwd)"
echo "📁 Looking for CrewAI tests..."
find . -name "*crewai*" -type f 2>/dev/null
echo "🧪 Trying direct pytest on integration/crewai..."
python -m pytest tests/integration/crewai/ -v --tb=short --disable-warnings || {
echo "❌ Direct path failed, trying relative path..."
python -m pytest integration/crewai/ -v --tb=short --disable-warnings || {
echo "❌ All CrewAI test attempts failed"
exit 1
}
}
}
- name: Run Legacy Tests with API Key
env:
OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY || 'sk-test-key-for-github-actions-testing-only-not-real' }}
OPENAI_API_BASE: ${{ secrets.OPENAI_API_BASE || 'https://api.openai.com/v1' }}
OPENAI_MODEL_NAME: ${{ secrets.OPENAI_MODEL_NAME || 'gpt-5-nano' }}
LOGLEVEL: DEBUG
run: |
echo "🧪 Running legacy tests with real API key..."
echo "🔧 Final environment check before pytest:"
echo " OPENAI_API_KEY set: $([ -n "$OPENAI_API_KEY" ] && echo 'YES' || echo 'NO')"
echo " OPENAI_API_KEY length: ${#OPENAI_API_KEY}"
echo " OPENAI_API_KEY starts with sk-: $(echo "$OPENAI_API_KEY" | grep -q '^sk-' && echo 'YES' || echo 'NO')"
export OPENAI_API_KEY="$OPENAI_API_KEY"
export OPENAI_API_BASE="$OPENAI_API_BASE"
export OPENAI_MODEL_NAME="$OPENAI_MODEL_NAME"
cd src/praisonai && python -m pytest tests/test.py -v --tb=short --disable-warnings -m "not real" --timeout=60
- name: Upload coverage reports to Codecov
if: matrix.python-version == '3.11'
uses: codecov/codecov-action@v5
with:
token: ${{ secrets.CODECOV_TOKEN || '' }}
files: src/praisonai/coverage.xml
token: ${{ secrets.CODECOV_TOKEN }}
file: src/praisonai/coverage.xml
flags: core-tests
fail_ci_if_error: false
name: core-tests-coverage
fail_ci_if_error: false
verbose: true
- name: Upload Coverage Reports (Artifacts)
if: matrix.python-version == '3.11'
uses: actions/upload-artifact@v4
with:
name: coverage-reports
path: |
src/praisonai/.coverage
src/praisonai/htmlcov/
src/praisonai/coverage.xml
retention-days: 7
+6 -9
View File
@@ -1,9 +1,14 @@
name: Extended Tests
on:
push:
branches: [ main ]
pull_request:
branches: [ main ]
schedule:
# Run nightly at 2 AM UTC
- cron: '0 2 * * *'
workflow_dispatch:
workflow_dispatch: # Allow manual triggering
jobs:
test-examples:
@@ -13,10 +18,6 @@ jobs:
steps:
- name: Checkout code
uses: actions/checkout@v4
with:
persist-credentials: false
with:
persist-credentials: false
- name: Set up Python
uses: actions/setup-python@v5
@@ -81,10 +82,6 @@ jobs:
steps:
- name: Checkout code
uses: actions/checkout@v4
with:
persist-credentials: false
with:
persist-credentials: false
- name: Set up Python
uses: actions/setup-python@v5
-4
View File
@@ -33,10 +33,6 @@ jobs:
steps:
- name: Checkout code
uses: actions/checkout@v4
with:
persist-credentials: false
with:
persist-credentials: false
- name: Set up Python ${{ matrix.python-version }}
uses: actions/setup-python@v5
+8 -38
View File
@@ -3,16 +3,8 @@ name: Optimized Test Suite
on:
push:
branches: [ main, develop ]
paths:
- 'src/**'
- 'pyproject.toml'
- '.github/workflows/test-optimized.yml'
pull_request:
branches: [ main, develop ]
paths:
- 'src/**'
- 'pyproject.toml'
- '.github/workflows/test-optimized.yml'
schedule:
# Nightly extended tests at 3 AM UTC
- cron: '0 3 * * *'
@@ -45,8 +37,7 @@ jobs:
timeout-minutes: 5
steps:
- uses: actions/checkout@v4
with:
persist-credentials: false
- name: Set up Python 3.11
uses: actions/setup-python@v5
with:
@@ -105,8 +96,7 @@ jobs:
steps:
- uses: actions/checkout@v4
with:
persist-credentials: false
- name: Set up Python ${{ matrix.python-version }}
uses: actions/setup-python@v5
with:
@@ -159,8 +149,8 @@ jobs:
if: matrix.python-version == '3.11'
uses: codecov/codecov-action@v5
with:
token: ${{ secrets.CODECOV_TOKEN || '' }}
files: src/praisonai/coverage.xml
token: ${{ secrets.CODECOV_TOKEN }}
file: src/praisonai/coverage.xml
flags: main-tests
fail_ci_if_error: false
@@ -187,8 +177,6 @@ jobs:
fi
- uses: actions/checkout@v4
with:
persist-credentials: false
if: steps.check-key.outputs.has_key == 'true'
- name: Set up Python 3.11
@@ -259,8 +247,6 @@ jobs:
fi
- uses: actions/checkout@v4
with:
persist-credentials: false
if: steps.check-key.outputs.has_key == 'true'
- name: Set up Python 3.11
@@ -307,10 +293,8 @@ jobs:
steps:
- name: Check if Google key is available
id: check-key
env:
GOOGLE_API_KEY: ${{ secrets.GOOGLE_API_KEY }}
run: |
if [ -n "$GOOGLE_API_KEY" ]; then
if [ -n "${{ secrets.GOOGLE_API_KEY }}" ]; then
echo "has_key=true" >> $GITHUB_OUTPUT
else
echo "has_key=false" >> $GITHUB_OUTPUT
@@ -318,8 +302,6 @@ jobs:
fi
- uses: actions/checkout@v4
with:
persist-credentials: false
if: steps.check-key.outputs.has_key == 'true'
- name: Set up Python 3.11
@@ -366,10 +348,8 @@ jobs:
steps:
- name: Check if Groq key is available
id: check-key
env:
GROQ_API_KEY: ${{ secrets.GROQ_API_KEY }}
run: |
if [ -n "$GROQ_API_KEY" ]; then
if [ -n "${{ secrets.GROQ_API_KEY }}" ]; then
echo "has_key=true" >> $GITHUB_OUTPUT
else
echo "has_key=false" >> $GITHUB_OUTPUT
@@ -377,8 +357,6 @@ jobs:
fi
- uses: actions/checkout@v4
with:
persist-credentials: false
if: steps.check-key.outputs.has_key == 'true'
- name: Set up Python 3.11
@@ -425,10 +403,8 @@ jobs:
steps:
- name: Check if xAI key is available
id: check-key
env:
XAI_API_KEY: ${{ secrets.XAI_API_KEY }}
run: |
if [ -n "$XAI_API_KEY" ]; then
if [ -n "${{ secrets.XAI_API_KEY }}" ]; then
echo "has_key=true" >> $GITHUB_OUTPUT
else
echo "has_key=false" >> $GITHUB_OUTPUT
@@ -436,8 +412,6 @@ jobs:
fi
- uses: actions/checkout@v4
with:
persist-credentials: false
if: steps.check-key.outputs.has_key == 'true'
- name: Set up Python 3.11
@@ -484,10 +458,8 @@ jobs:
steps:
- name: Check if Cohere key is available
id: check-key
env:
COHERE_API_KEY: ${{ secrets.COHERE_API_KEY }}
run: |
if [ -n "$COHERE_API_KEY" ]; then
if [ -n "${{ secrets.COHERE_API_KEY }}" ]; then
echo "has_key=true" >> $GITHUB_OUTPUT
else
echo "has_key=false" >> $GITHUB_OUTPUT
@@ -495,8 +467,6 @@ jobs:
fi
- uses: actions/checkout@v4
with:
persist-credentials: false
if: steps.check-key.outputs.has_key == 'true'
- name: Set up Python 3.11
+8 -20
View File
@@ -34,21 +34,14 @@ jobs:
steps:
- name: 🚨 Cost Warning
env:
INPUT_FRAMEWORK: ${{ github.event.inputs.framework }}
INPUT_CONFIRM_COSTS: ${{ github.event.inputs.confirm_costs }}
run: |
echo "⚠️ WARNING: This workflow will make real API calls!"
echo "💰 This may incur charges on your API accounts"
echo "🎯 Framework: $INPUT_FRAMEWORK"
echo "✅ Cost confirmation: $INPUT_CONFIRM_COSTS"
echo "🎯 Framework: ${{ github.event.inputs.framework }}"
echo "✅ Cost confirmation: ${{ github.event.inputs.confirm_costs }}"
- name: Checkout code
uses: actions/checkout@v4
with:
persist-credentials: false
with:
persist-credentials: false
- name: Set up Python ${{ matrix.python-version }}
uses: actions/setup-python@v5
@@ -100,23 +93,21 @@ jobs:
- name: Generate Real Test Report
if: always()
env:
INPUT_FRAMEWORK: ${{ github.event.inputs.framework }}
run: |
echo "# 🔥 Real End-to-End Test Report" > real_test_report.md
echo "" >> real_test_report.md
echo "⚠️ **WARNING: This report represents tests that made real API calls**" >> real_test_report.md
echo "" >> real_test_report.md
echo "**Framework Tested:** $INPUT_FRAMEWORK" >> real_test_report.md
echo "**Framework Tested:** ${{ github.event.inputs.framework }}" >> real_test_report.md
echo "**Python Version:** ${{ matrix.python-version }}" >> real_test_report.md
echo "**Date:** $(date -u)" >> real_test_report.md
echo "**Triggered by:** $GITHUB_ACTOR" >> real_test_report.md
echo "**Triggered by:** ${{ github.actor }}" >> real_test_report.md
echo "" >> real_test_report.md
echo "## 🧪 Test Results" >> real_test_report.md
echo "" >> real_test_report.md
if [ "$INPUT_FRAMEWORK" == "autogen" ] || [ "$INPUT_FRAMEWORK" == "all" ]; then
if [ "${{ github.event.inputs.framework }}" == "autogen" ] || [ "${{ github.event.inputs.framework }}" == "all" ]; then
echo "### AutoGen Real Tests:" >> real_test_report.md
echo "- Environment verification" >> real_test_report.md
echo "- Agent creation with real API calls" >> real_test_report.md
@@ -124,7 +115,7 @@ jobs:
echo "" >> real_test_report.md
fi
if [ "$INPUT_FRAMEWORK" == "crewai" ] || [ "$INPUT_FRAMEWORK" == "all" ]; then
if [ "${{ github.event.inputs.framework }}" == "crewai" ] || [ "${{ github.event.inputs.framework }}" == "all" ]; then
echo "### CrewAI Real Tests:" >> real_test_report.md
echo "- Environment verification" >> real_test_report.md
echo "- Crew creation with real API calls" >> real_test_report.md
@@ -159,14 +150,11 @@ jobs:
steps:
- name: 🛡️ Safety Check Failed
env:
INPUT_FRAMEWORK: ${{ github.event.inputs.framework }}
INPUT_CONFIRM_COSTS: ${{ github.event.inputs.confirm_costs }}
run: |
echo "🚨 Real tests not executed due to safety checks:"
echo ""
echo "✅ Costs confirmed: $INPUT_CONFIRM_COSTS"
echo "✅ Framework selected: $INPUT_FRAMEWORK"
echo "✅ Costs confirmed: ${{ github.event.inputs.confirm_costs }}"
echo "✅ Framework selected: ${{ github.event.inputs.framework }}"
echo ""
echo "To run real tests:"
echo "1. Select a framework (autogen, crewai, or all)"
-218
View File
@@ -1,218 +0,0 @@
name: Windows Tests
on:
push:
branches: [main, develop]
paths:
- 'src/**'
- 'pyproject.toml'
- '.github/workflows/test-windows.yml'
pull_request:
branches: [main, develop]
paths:
- 'src/**'
- 'pyproject.toml'
- '.github/workflows/test-windows.yml'
workflow_dispatch:
jobs:
test-windows:
runs-on: windows-latest
timeout-minutes: 5
env:
OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
OPENAI_MODEL_NAME: gpt-4o-mini
PYTHONUTF8: 1
steps:
- uses: actions/checkout@v4
with:
persist-credentials: false
- name: Set up Python 3.11
uses: actions/setup-python@v5
with:
python-version: "3.11"
- name: Install praisonaiagents
run: |
python -m pip install --upgrade pip
cd src/praisonai-agents
pip install -e .
shell: bash
- name: Install praisonai wrapper
run: |
cd src/praisonai
pip install -e .
shell: bash
# ==================== CORE IMPORTS ====================
- name: Test core imports
run: |
python -c "from praisonaiagents import Agent, Agents, Workflow; print('Core imports OK')"
python -c "from praisonaiagents import tool, Tools; print('Tool imports OK')"
python -c "from praisonaiagents import Task; print('Task imports OK')"
# ==================== AGENT FEATURES ====================
- name: Test Agent instantiation
run: |
python -c "
from praisonaiagents import Agent
a = Agent(name='Test', instructions='You are helpful')
print('Agent created:', a.name)
a2 = Agent(name='ToolAgent', instructions='Use tools', tools=[])
print('Agent with tools:', a2.name)
"
- name: Test Agents orchestration
run: |
python -c "
from praisonaiagents import Agent, Agents, Task
a1 = Agent(name='Agent1', instructions='First agent')
a2 = Agent(name='Agent2', instructions='Second agent')
t = Task(description='Do something', agent=a1)
agents = Agents(agents=[a1, a2], tasks=[t])
print('Agents:', len(agents.agents), 'Tasks:', len(agents.tasks))
"
# ==================== WORKFLOW FEATURES ====================
- name: Test Workflow
run: |
python -c "
from praisonaiagents import Workflow
w = Workflow(name='test')
print('Workflow:', w.name)
"
# ==================== MEMORY FEATURES ====================
- name: Test Memory classes
run: |
python -c "
from praisonaiagents.memory import FileMemory
from praisonaiagents.config import MemoryConfig
cfg = MemoryConfig(backend='file', user_id='test_user')
print('MemoryConfig backend:', cfg.backend)
mem = FileMemory(user_id='test_user', base_path='.praison/test_memory')
print('FileMemory user:', mem.user_id)
"
# ==================== TOOL DECORATOR ====================
- name: Test tool decorator
run: |
python -c "
from praisonaiagents import tool
@tool
def my_tool(query: str) -> str:
'''A test tool'''
return f'Echo: {query}'
result = my_tool('hello')
print('Tool result:', result)
"
# ==================== CONFIG CLASSES ====================
- name: Test config classes
run: |
python -c "
from praisonaiagents.config import OutputConfig, ExecutionConfig, PlanningConfig
out_cfg = OutputConfig(verbose=True, stream=True)
print('OutputConfig verbose:', out_cfg.verbose)
exec_cfg = ExecutionConfig(max_iter=50, max_retry_limit=5)
print('ExecutionConfig max_iter:', exec_cfg.max_iter)
plan_cfg = PlanningConfig(reasoning=True, auto_approve=False)
print('PlanningConfig reasoning:', plan_cfg.reasoning)
"
# ==================== HANDOFF ====================
- name: Test Handoff
run: |
python -c "
from praisonaiagents import Handoff, handoff, Agent
a1 = Agent(name='Agent1', instructions='First')
a2 = Agent(name='Agent2', instructions='Second')
# Using Handoff class directly
h = Handoff(agent=a2)
print('Handoff tool name:', h.tool_name)
# Using handoff function
h2 = handoff(a1, tool_name_override='custom_handoff')
print('Custom handoff name:', h2.tool_name)
"
# ==================== ASYNC FEATURES ====================
- name: Test async imports
run: |
python -c "
import asyncio
from praisonaiagents import Agent
async def test_async():
agent = Agent(name='AsyncAgent', instructions='Test')
assert hasattr(agent, 'arun'), 'Missing arun'
assert hasattr(agent, 'astart'), 'Missing astart'
print('Async methods available')
asyncio.run(test_async())
"
# ==================== CLI COMMANDS ====================
- name: Test CLI help
run: praisonai --help
- name: Test CLI session list
run: praisonai session list
continue-on-error: true
- name: Test CLI queue list
run: praisonai queue list
continue-on-error: true
# ==================== PACKAGING TESTS ====================
- name: Test packaging/daemon entry points
run: |
echo "Testing both entry point methods..."
python -m praisonai --version
praisonai --version
- name: Test doctor packaging command
run: |
echo "Testing doctor packaging diagnostics..."
praisonai doctor packaging --json
# ==================== REAL API TESTS ====================
- name: Real API test - Agent run
if: env.OPENAI_API_KEY != ''
run: |
python -c "
from praisonaiagents import Agent
agent = Agent(name='TestAgent', instructions='Reply with exactly: WINDOWS_OK', llm='gpt-4o-mini')
result = agent.run('Say WINDOWS_OK')
print('Result:', result)
print('Real API test passed')
"
- name: Real API test - Multi-agent
if: env.OPENAI_API_KEY != ''
run: |
python -c "
from praisonaiagents import Agent, Agents, Task
researcher = Agent(name='Researcher', instructions='You research topics', llm='gpt-4o-mini')
writer = Agent(name='Writer', instructions='You write content', llm='gpt-4o-mini')
task = Task(description='Say hello world', agent=researcher)
agents = Agents(agents=[researcher, writer], tasks=[task])
result = agents.start()
print('Multi-agent result type:', type(result))
print('Multi-agent test passed')
"
+516
View File
@@ -0,0 +1,516 @@
name: Quick Validation Tests
on: [push, pull_request]
jobs:
quick-test:
runs-on: ubuntu-latest
timeout-minutes: 15
steps:
- name: Checkout code
uses: actions/checkout@v4
- name: Set up Python
uses: actions/setup-python@v5
with:
python-version: 3.11
- name: Install UV
run: |
curl -LsSf https://astral.sh/uv/install.sh | sh
echo "$HOME/.local/bin" >> $GITHUB_PATH
- name: Install dependencies
run: |
cd src/praisonai
uv pip install --system ."[ui,gradio,api,agentops,google,openai,anthropic,cohere,chat,code,realtime,call,crewai,autogen]"
uv pip install --system duckduckgo_search
uv pip install --system pytest pytest-asyncio pytest-cov pytest-timeout
# Install knowledge dependencies from praisonai-agents
uv pip install --system "praisonaiagents[knowledge]"
- name: Set environment variables
run: |
echo "OPENAI_API_KEY=${{ secrets.OPENAI_API_KEY || 'sk-test-key-for-github-actions-testing-only-not-real' }}" >> $GITHUB_ENV
echo "OPENAI_API_BASE=${{ secrets.OPENAI_API_BASE || 'https://api.openai.com/v1' }}" >> $GITHUB_ENV
echo "OPENAI_MODEL_NAME=${{ secrets.OPENAI_MODEL_NAME || 'gpt-5-nano' }}" >> $GITHUB_ENV
echo "LOGLEVEL=DEBUG" >> $GITHUB_ENV
echo "PYTHONPATH=${{ github.workspace }}/src/praisonai-agents:$PYTHONPATH" >> $GITHUB_ENV
- name: Backup Root Config Files
run: |
echo "🔄 Backing up root configuration files to prevent default file resolution interference..."
echo "ℹ️ PraisonAI automatically uses 'agents.yaml' in working directory when no file specified"
echo "ℹ️ This can interfere with test files that specify their own YAML files"
if [ -f "agents.yaml" ]; then
mv agents.yaml agents.yaml.backup
echo "✅ Moved root agents.yaml to agents.yaml.backup"
echo " - This prevents default file fallback during tests"
fi
if [ -f "tools.py" ]; then
mv tools.py tools.py.backup
echo "✅ Moved tools.py to tools.py.backup"
fi
- name: Debug API Key Status
run: |
echo "🔍 Checking API key availability..."
if [ -n "${{ secrets.OPENAI_API_KEY }}" ]; then
echo "✅ GitHub secret OPENAI_API_KEY is available"
echo "🔑 API key starts with: $(echo "$OPENAI_API_KEY" | cut -c1-7)..."
else
echo "⚠️ GitHub secret OPENAI_API_KEY is NOT set - using fallback"
echo "🔑 Using fallback key: sk-test-key..."
fi
echo "🌐 API Base: $OPENAI_API_BASE"
echo "🤖 Model: $OPENAI_MODEL_NAME"
echo "🐛 Log Level: $LOGLEVEL"
echo "📊 Environment Check:"
echo " - OPENAI_API_KEY length: ${#OPENAI_API_KEY}"
echo " - OPENAI_API_BASE: $OPENAI_API_BASE"
echo " - OPENAI_MODEL_NAME: $OPENAI_MODEL_NAME"
echo " - LOGLEVEL: $LOGLEVEL"
- name: Debug Python Environment Variables
run: |
python -c "
import os
print('🐍 Python Environment Variable Check:')
api_key = os.environ.get('OPENAI_API_KEY', 'NOT_SET')
if api_key != 'NOT_SET':
print(f' ✅ OPENAI_API_KEY: {api_key[:7]}... (length: {len(api_key)})')
else:
print(' ❌ OPENAI_API_KEY: NOT_SET')
print(f' 🌐 OPENAI_API_BASE: {os.environ.get(\"OPENAI_API_BASE\", \"NOT_SET\")}')
print(f' 🤖 OPENAI_MODEL_NAME: {os.environ.get(\"OPENAI_MODEL_NAME\", \"NOT_SET\")}')
print(f' 📋 All OPENAI env vars:')
for key, value in os.environ.items():
if key.startswith('OPENAI'):
print(f' {key}: {value[:10] if len(value) > 10 else value}...')
"
- name: Find Researcher Role Source
run: |
echo "🔍 Hunting for the mysterious 'Researcher' role..."
cd src/praisonai
python -c "
import os
import yaml
import glob
print('📋 Searching for Researcher role in all YAML files:')
yaml_files = glob.glob('src/praisonai/tests/*.yaml')
for yaml_file in yaml_files:
try:
with open(yaml_file, 'r') as f:
config = yaml.safe_load(f)
# Check if any role contains 'researcher'
roles = config.get('roles', {})
for role_key, role_data in roles.items():
role_name = role_data.get('role', '')
if 'researcher' in role_key.lower() or 'researcher' in role_name.lower():
print(f' 🎯 FOUND in {yaml_file}:')
print(f' Framework: {config.get(\"framework\", \"NOT_SET\")}')
print(f' Role key: {role_key}')
print(f' Role name: {role_name}')
print(f' All roles: {list(roles.keys())}')
print()
except Exception as e:
print(f' ❌ Error reading {yaml_file}: {e}')
print('🔍 Checking for default configurations...')
# Check if there are any default configs or hardcoded roles
try:
import praisonai
print(f' PraisonAI package location: {praisonai.__file__}')
# Check if there are any example YAML files in the package
package_dir = os.path.dirname(praisonai.__file__)
for root, dirs, files in os.walk(package_dir):
for file in files:
if file.endswith(('.yaml', '.yml')):
file_path = os.path.join(root, file)
print(f' 📁 Found YAML in package: {file_path}')
except Exception as e:
print(f' ❌ Error checking package: {e}')
"
continue-on-error: true
- name: Trace AutoGen Execution Path
run: |
echo "🔍 Tracing AutoGen execution to find where it diverges..."
cd src/praisonai
python -c "
import os
import sys
sys.path.insert(0, '.')
try:
from praisonai import PraisonAI
from praisonai.agents_generator import AgentsGenerator
# Test the exact execution path
print('🎯 Testing AutoGen execution path:')
praisonai = PraisonAI(agent_file='tests/autogen-agents.yaml')
print(f' 1. PraisonAI framework: \"{praisonai.framework}\"')
agents_gen = AgentsGenerator(
agent_file='tests/autogen-agents.yaml',
framework=praisonai.framework,
config_list=praisonai.config_list
)
print(f' 2. AgentsGenerator framework: \"{agents_gen.framework}\"')
# Load the YAML to check what it contains
import yaml
with open('src/praisonai/tests/autogen-agents.yaml', 'r') as f:
config = yaml.safe_load(f)
framework = agents_gen.framework or config.get('framework')
print(f' 3. Final framework decision: \"{framework}\"')
print(f' 4. Available frameworks:')
# Check framework availability
try:
import autogen
print(f' ✅ AutoGen available')
except ImportError:
print(f' ❌ AutoGen NOT available')
try:
from praisonaiagents import Agent
print(f' ✅ PraisonAI agents available')
except ImportError:
print(f' ❌ PraisonAI agents NOT available')
try:
from crewai import Agent
print(f' ✅ CrewAI available')
except ImportError:
print(f' ❌ CrewAI NOT available')
print(f' 5. Roles in YAML: {list(config.get(\"roles\", {}).keys())}')
# Now test the actual framework execution
if framework == 'autogen':
print(f' 6. ✅ Should execute _run_autogen')
elif framework == 'praisonai':
print(f' 6. ❌ Would execute _run_praisonai (WRONG!)')
else:
print(f' 6. ❌ Would execute _run_crewai (DEFAULT FALLBACK)')
except Exception as e:
print(f'❌ Error tracing execution: {e}')
import traceback
traceback.print_exc()
"
continue-on-error: true
- name: Debug YAML Loading and Roles
run: |
echo "🔍 Tracing YAML file loading and role creation..."
cd src/praisonai
python -c "
import os
import sys
import yaml
sys.path.insert(0, '.')
print('📁 Available YAML files in src/praisonai/tests/:')
import glob
yaml_files = glob.glob('tests/*.yaml')
for f in yaml_files:
print(f' {f}')
print()
print('📋 Content of autogen-agents.yaml:')
with open('tests/autogen-agents.yaml', 'r') as f:
config = yaml.safe_load(f)
print(f' Framework: {config.get(\"framework\")}')
print(f' Topic: {config.get(\"topic\")}')
print(f' Roles: {list(config.get(\"roles\", {}).keys())}')
for role_key, role_data in config.get('roles', {}).items():
print(f' {role_key} -> {role_data.get(\"role\", \"NO_ROLE\")}')
print()
print('🔍 Checking if execution uses a different YAML:')
# Check other YAML files for 'Researcher' role
for yaml_file in yaml_files:
try:
with open(yaml_file, 'r') as f:
test_config = yaml.safe_load(f)
roles = test_config.get('roles', {})
for role_key, role_data in roles.items():
if 'researcher' in role_key.lower() or 'researcher' in role_data.get('role', '').lower():
print(f' 🎯 FOUND Researcher in {yaml_file}!')
print(f' Framework: {test_config.get(\"framework\")}')
print(f' Role key: {role_key} -> {role_data.get(\"role\")}')
except:
pass
"
continue-on-error: true
- name: Debug Framework Detection
run: |
echo "🔍 Testing framework detection and config flow..."
python -c "
import os
import sys
import yaml
sys.path.insert(0, '.')
print('🔧 Testing framework detection:')
# Load the YAML file
with open('tests/autogen-agents.yaml', 'r') as f:
config = yaml.safe_load(f)
print(f' 📋 YAML framework: {config.get(\"framework\", \"NOT_SET\")}')
print(f' 📋 YAML topic: {config.get(\"topic\", \"NOT_SET\")}')
try:
from praisonai import PraisonAI
from praisonai.agents_generator import AgentsGenerator
# Test PraisonAI initialization
praisonai = PraisonAI(agent_file='tests/autogen-agents.yaml')
print(f' 🎯 PraisonAI framework: {praisonai.framework}')
# Test AgentsGenerator initialization
agents_gen = AgentsGenerator(
agent_file='tests/autogen-agents.yaml',
framework=praisonai.framework,
config_list=praisonai.config_list
)
print(f' ⚙️ AgentsGenerator framework: {agents_gen.framework}')
print(f' ⚙️ Final framework decision: {agents_gen.framework or config.get(\"framework\")}')
# Check config_list
print(f' 🔑 Config list model: {praisonai.config_list[0].get(\"model\")}')
print(f' 🔑 Config list API key: {praisonai.config_list[0].get(\"api_key\", \"NOT_SET\")[:10]}...')
except Exception as e:
print(f'❌ Error in framework detection: {e}')
"
continue-on-error: true
- name: Debug PraisonAIModel API Key Flow
run: |
echo "🔍 Testing PraisonAIModel API key handling..."
cd src/praisonai
python -c "
import os
import sys
sys.path.insert(0, '.')
print('🔑 Environment API Key Check:')
env_key = os.environ.get('OPENAI_API_KEY', 'NOT_FOUND')
print(f' OPENAI_API_KEY: {env_key[:10] if env_key != \"NOT_FOUND\" else \"NOT_FOUND\"}...')
try:
from praisonai.inc.models import PraisonAIModel
# Test PraisonAIModel with openai/gpt-5-nano (from YAML)
model = PraisonAIModel(model='openai/gpt-5-nano')
print('🤖 PraisonAIModel Configuration:')
print(f' model: {model.model}')
print(f' model_name: {model.model_name}')
print(f' api_key_var: {model.api_key_var}')
print(f' api_key: {model.api_key[:10] if model.api_key != \"nokey\" else \"DEFAULT_NOKEY\"}...')
print(f' base_url: {model.base_url}')
if model.api_key == 'nokey':
print('❌ FOUND THE ISSUE: PraisonAIModel is using default \"nokey\" instead of environment variable!')
else:
print('✅ PraisonAIModel has valid API key from environment')
except Exception as e:
print(f'❌ Error testing PraisonAIModel: {e}')
"
continue-on-error: true
- name: Validate API Key
run: |
echo "🔑 Testing API key validity with minimal OpenAI call..."
python -c "
import os
try:
from openai import OpenAI
client = OpenAI(api_key=os.environ.get('OPENAI_API_KEY'))
# Make a minimal API call to test key validity
response = client.models.list()
print('✅ API Key is VALID - OpenAI responded successfully')
print(f'📊 Available models: {len(list(response.data))} models found')
except Exception as e:
print(f'❌ API Key is INVALID - Error: {e}')
print('🔍 This explains why all API-dependent tests are failing')
print('💡 The GitHub secret OPENAI_API_KEY needs to be updated with a valid key')
"
continue-on-error: true
- name: Test Direct PraisonAI Execution
run: |
echo "🧪 Testing direct PraisonAI execution (what works locally)..."
python -m praisonai src/praisonai/tests/autogen-agents.yaml
continue-on-error: true
- name: Comprehensive Execution Debug
run: |
echo "🔍 Comprehensive debugging of PraisonAI execution path..."
cd src/praisonai
python -c "
import os
import sys
import yaml
sys.path.insert(0, '.')
print('=' * 60)
print('🔍 COMPREHENSIVE EXECUTION DEBUG')
print('=' * 60)
# Check current working directory
print(f'📁 Current working directory: {os.getcwd()}')
# List files in current directory
print('📋 Files in current directory:')
for f in os.listdir('.'):
print(f' {f}')
print()
print('📋 Files in src/praisonai/tests/ directory:')
for f in os.listdir('tests'):
if f.endswith('.yaml'):
print(f' src/praisonai/tests/{f}')
# Check if root agents.yaml exists
print()
if os.path.exists('agents.yaml'):
print('❌ ROOT agents.yaml EXISTS (this is the problem!)')
with open('agents.yaml', 'r') as f:
root_config = yaml.safe_load(f)
print(f' Root framework: {root_config.get(\"framework\")}')
print(f' Root roles: {list(root_config.get(\"roles\", {}).keys())}')
else:
print('✅ ROOT agents.yaml does NOT exist (good!)')
# Test the actual execution path
print()
print('🎯 Testing EXACT execution path:')
try:
from praisonai import PraisonAI
from praisonai.agents_generator import AgentsGenerator
# Test with full path
test_file = 'src/praisonai/tests/autogen-agents.yaml'
print(f' Using test file: {test_file}')
print(f' File exists: {os.path.exists(test_file)}')
# Load the test file directly
with open(test_file, 'r') as f:
test_config = yaml.safe_load(f)
print(f' Test file framework: {test_config.get(\"framework\")}')
print(f' Test file roles: {list(test_config.get(\"roles\", {}).keys())}')
# Create PraisonAI instance
praisonai = PraisonAI(agent_file=test_file)
print(f' PraisonAI.agent_file: {praisonai.agent_file}')
print(f' PraisonAI.framework: {praisonai.framework}')
# Create AgentsGenerator
agents_gen = AgentsGenerator(
agent_file=test_file,
framework=praisonai.framework,
config_list=praisonai.config_list
)
print(f' AgentsGenerator.agent_file: {agents_gen.agent_file}')
print(f' AgentsGenerator.framework: {agents_gen.framework}')
# Test what would happen in generate_crew_and_kickoff
print()
print('🔧 Testing generate_crew_and_kickoff logic:')
# Simulate the loading logic
if agents_gen.agent_yaml:
loaded_config = yaml.safe_load(agents_gen.agent_yaml)
print(' Would load from agent_yaml')
else:
if agents_gen.agent_file == '/app/api:app' or agents_gen.agent_file == 'api:app':
agents_gen.agent_file = 'agents.yaml'
print(f' Would change agent_file to: {agents_gen.agent_file}')
try:
with open(agents_gen.agent_file, 'r') as f:
loaded_config = yaml.safe_load(f)
print(f' Successfully loaded: {agents_gen.agent_file}')
except FileNotFoundError:
print(f' FileNotFoundError: {agents_gen.agent_file}')
loaded_config = None
if loaded_config:
final_framework = agents_gen.framework or loaded_config.get('framework')
print(f' Final framework decision: {final_framework}')
print(f' Loaded roles: {list(loaded_config.get(\"roles\", {}).keys())}')
if 'researcher' in loaded_config.get('roles', {}):
print(' ❌ FOUND Researcher role in loaded config!')
else:
print(' ✅ No Researcher role in loaded config')
except Exception as e:
print(f'❌ Error during execution debug: {e}')
import traceback
traceback.print_exc()
"
continue-on-error: true
- name: Run Fast Tests
run: |
# Run the fastest, most essential tests with coverage
cd src/praisonai && python -m pytest tests/unit/test_core_agents.py -v --tb=short --disable-warnings --cov=praisonai --cov-report=xml --cov-branch
- name: Run Real API Tests
run: |
echo "🔑 Running real API tests with actual OpenAI API key..."
cd src/praisonai && python -m pytest tests/test_agents_playbook.py -v --tb=short --disable-warnings -m real
continue-on-error: true
- name: Run E2E Real Tests
run: |
echo "🧪 Running E2E real tests..."
cd src/praisonai && python -m pytest tests/e2e/ -v --tb=short --disable-warnings -m real
continue-on-error: true
- name: Run Legacy Example Tests
run: |
cd src/praisonai && python -m pytest tests/test.py -v --tb=short --disable-warnings -m "not real" --timeout=60
continue-on-error: true
- name: Upload coverage reports to Codecov
uses: codecov/codecov-action@v5
with:
token: ${{ secrets.CODECOV_TOKEN }}
file: src/praisonai/coverage.xml
flags: quick-validation
name: quick-validation-coverage
fail_ci_if_error: false
verbose: true
- name: Restore Root Config Files
run: |
echo "🔄 Restoring root configuration files..."
if [ -f "agents.yaml.backup" ]; then
mv agents.yaml.backup agents.yaml
echo "✅ Restored agents.yaml"
fi
if [ -f "tools.py.backup" ]; then
mv tools.py.backup tools.py
echo "✅ Restored tools.py"
fi
if: always() # Always run this step, even if previous steps failed
+3 -3
View File
@@ -52,6 +52,6 @@ jobs:
with:
commit_message: "docs: auto-update api.md [skip ci]"
file_pattern: 'api.md'
commit_user_name: "MervinPraison"
commit_user_email: "454862+MervinPraison@users.noreply.github.com"
commit_author: "MervinPraison <454862+MervinPraison@users.noreply.github.com>"
commit_user_name: "github-actions[bot]"
commit_user_email: "41898282+github-actions[bot]@users.noreply.github.com"
commit_author: "github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>"
-83
View File
@@ -1,83 +0,0 @@
name: Update Documentation Parity Tracker
on:
push:
branches: [ "main" ]
paths:
- 'src/praisonai-agents/praisonaiagents/**/*.py'
- 'src/praisonai-ts/src/**/*.ts'
- 'src/praisonai-rust/src/**/*.rs'
- 'src/praisonai/praisonai/_dev/parity/**/*.py'
- '.github/workflows/update-docs-parity.yml'
workflow_dispatch: # Allow manual trigger
permissions:
contents: write
jobs:
update-docs-parity:
runs-on: ubuntu-latest
steps:
- name: Checkout repository
uses: actions/checkout@v4
with:
ref: main
persist-credentials: true
fetch-depth: 0
- name: Checkout PraisonAIDocs
id: checkout_docs
continue-on-error: true
uses: actions/checkout@v4
with:
repository: MervinPraison/PraisonAIDocs
path: PraisonAIDocs
token: ${{ secrets.SECRETS_ADMIN_PAT }}
- name: Set up Python
uses: actions/setup-python@v5
with:
python-version: '3.11'
- name: Install dependencies
run: |
pip install pyyaml
- name: Generate docs parity trackers
if: steps.checkout_docs.outcome == 'success'
run: |
cd $GITHUB_WORKSPACE
python3 src/praisonai/scripts/generate_docs_parity.py --docs-root PraisonAIDocs/docs --copy-docs
- name: Check for changes
id: check_changes
run: |
if git diff --quiet src/praisonai-agents/DOCS_PARITY.md src/praisonai-ts/DOCS_PARITY.md src/praisonai-rust/DOCS_PARITY.md 2>/dev/null; then
echo "changes=false" >> $GITHUB_OUTPUT
echo "No changes to docs parity trackers"
else
echo "changes=true" >> $GITHUB_OUTPUT
echo "Docs parity trackers have been updated"
git diff --stat src/praisonai-agents/DOCS_PARITY.md src/praisonai-ts/DOCS_PARITY.md src/praisonai-rust/DOCS_PARITY.md
fi
- name: Commit and push changes to praisonai-package
if: steps.check_changes.outputs.changes == 'true'
uses: stefanzweifel/git-auto-commit-action@v5
with:
commit_message: "docs: auto-update documentation parity trackers [skip ci]"
file_pattern: 'src/praisonai-agents/DOCS_PARITY.md src/praisonai-ts/DOCS_PARITY.md src/praisonai-rust/DOCS_PARITY.md'
commit_user_name: "MervinPraison"
commit_user_email: "[email protected]"
commit_author: "MervinPraison <[email protected]>"
- name: Commit and push changes to PraisonAIDocs
if: steps.check_changes.outputs.changes == 'true' && steps.checkout_docs.outcome == 'success'
run: |
cd PraisonAIDocs
git config user.name "MervinPraison"
git config user.email "[email protected]"
git add docs/features/DOCS_PARITY.md docs/js/DOCS_PARITY.md docs/rust/DOCS_PARITY.md
git diff --staged --quiet || git commit -m "docs: auto-update documentation parity trackers [skip ci]"
git push
@@ -1,61 +0,0 @@
name: Update Feature Parity Tracker
on:
push:
branches: [ "main" ]
paths:
- 'src/praisonai-agents/praisonaiagents/**/*.py'
- 'src/praisonai-ts/src/**/*.ts'
- 'src/praisonai-rust/src/**/*.rs'
- '.github/workflows/update-parity-tracker.yml'
permissions:
contents: write
jobs:
update-parity-tracker:
runs-on: ubuntu-latest
steps:
- name: Checkout repository
uses: actions/checkout@v4
with:
ref: main
persist-credentials: true
fetch-depth: 0
- name: Set up Python
uses: actions/setup-python@v5
with:
python-version: '3.11'
- name: Install dependencies
run: pip install pyyaml
- name: Generate parity trackers
run: |
cd $GITHUB_WORKSPACE
python3 src/praisonai/scripts/generate_parity_tracker.py
- name: Check for changes
id: check_changes
run: |
if git diff --quiet src/praisonai-ts/FEATURE_PARITY_TRACKER.json src/praisonai-ts/PARITY.md src/praisonai-rust/FEATURE_PARITY_TRACKER.json src/praisonai-rust/PARITY.md 2>/dev/null; then
echo "changes=false" >> $GITHUB_OUTPUT
echo "No changes to parity trackers"
else
echo "changes=true" >> $GITHUB_OUTPUT
echo "Parity trackers have been updated"
git diff src/praisonai-ts/FEATURE_PARITY_TRACKER.json | head -50
fi
- name: Commit and push changes
if: steps.check_changes.outputs.changes == 'true'
uses: stefanzweifel/git-auto-commit-action@v5
with:
commit_message: "docs: auto-update feature parity trackers [skip ci]"
file_pattern: 'src/praisonai-ts/FEATURE_PARITY_TRACKER.json src/praisonai-ts/PARITY.md src/praisonai-rust/FEATURE_PARITY_TRACKER.json src/praisonai-rust/PARITY.md'
commit_user_name: "MervinPraison"
commit_user_email: "[email protected]"
commit_author: "MervinPraison <[email protected]>"
+1 -16
View File
@@ -21,7 +21,6 @@ docs.sh
other
output
!src/praisonai/praisonai/cli/output/
!src/praisonai-agents/praisonaiagents/output/
.files
threads.db
@@ -84,18 +83,4 @@ issue_details.json
# MCP Registry tokens
.mcpregistry_*
*.log
.internal
.praisonai
# Rust / Cargo
target/
Cargo.lock
**/*.rs.bk
*.pdb
.windsurf
src/praisonai/build*.egg-info/
src/praisonai/PraisonAI.egg-info/
jobs/*
*.egg-info
*.log
-14
View File
@@ -1,14 +0,0 @@
# Contributing to PraisonAI
Thank you for your interest! Here's how to get started:
1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Submit a pull request
## Guidelines
- Follow existing code style
- Add tests for new features
- Update documentation as needed
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+206 -667
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-6
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@@ -13,12 +13,6 @@ GOOGLE_API_KEY=your_google_api_key_here
GROQ_API_KEY=your_groq_api_key_here
COHERE_API_KEY=your_cohere_api_key_here
# Bot Tokens (for messaging bot services)
SLACK_BOT_TOKEN=xoxb-your-slack-bot-token
SLACK_APP_TOKEN=xapp-your-slack-app-token
DISCORD_BOT_TOKEN=your-discord-bot-token
TELEGRAM_BOT_TOKEN=your-telegram-bot-token
# Optional: Service Configuration
FLASK_ENV=development
CHAINLIT_HOST=0.0.0.0
+1 -1
View File
@@ -16,7 +16,7 @@ RUN mkdir -p /root/.praison
# Install Python packages (using latest versions)
RUN pip install --no-cache-dir \
praisonai_tools \
"praisonai>=4.6.55" \
"praisonai>=3.7.6" \
"praisonai[chat]" \
"embedchain[github,youtube]"
-61
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@@ -1,61 +0,0 @@
# PraisonAI 🦞 Claw — All-in-one: dashboard + bots + gateway + agents
#
# Build: docker build -f docker/Dockerfile.claw -t praisonai:claw ..
# Run: docker run -p 8082:8082 -e OPENAI_API_KEY=sk-xxx praisonai:claw
# Health: curl http://localhost:8082/health
#
# Override CMD for other modes:
# Bot: docker run -e ... praisonai:claw praisonai bot telegram
# Gateway: docker run -e ... praisonai:claw praisonai gateway start
# Serve: docker run -e ... praisonai:claw praisonai serve agents.yaml
# Shell: docker run --rm -it praisonai:claw bash
FROM python:3.12-slim AS base
# ── Environment ──────────────────────────────────────────────────────────────
ENV PYTHONDONTWRITEBYTECODE=1 \
PYTHONUNBUFFERED=1 \
AIUI_PORT=8082 \
AIUI_HOST=0.0.0.0 \
AIUI_DATA_DIR=/data
WORKDIR /app
# ── System dependencies ─────────────────────────────────────────────────────
# tini: PID 1 signal handling (graceful shutdown on Fly/Railway/k8s)
# curl: HEALTHCHECK probe
# build-essential: compile native Python wheels (chromadb, etc.)
RUN apt-get update && apt-get install -y --no-install-recommends \
tini \
curl \
build-essential \
&& rm -rf /var/lib/apt/lists/*
# ── Install PraisonAI 🦞 ────────────────────────────────────────────────────
# Single command installs: AIUI dashboard, agents SDK (memory/knowledge/llm/mcp),
# bot channels (Telegram/Discord/Slack), gateway, search tools, and more.
RUN pip install --no-cache-dir "praisonai[claw]"
# ── Data volume ──────────────────────────────────────────────────────────────
# Persistence for sessions, config, memory, knowledge stores
RUN mkdir -p /data
VOLUME /data
# ── Entrypoint ───────────────────────────────────────────────────────────────
# Ensures /data exists and forwards all signals via tini
RUN printf '#!/bin/sh\n\
set -e\n\
mkdir -p /data 2>/dev/null || true\n\
exec "$@"\n' > /usr/local/bin/entrypoint.sh \
&& chmod +x /usr/local/bin/entrypoint.sh
EXPOSE 8082
# ── Health check ─────────────────────────────────────────────────────────────
HEALTHCHECK --interval=30s --timeout=5s --start-period=20s --retries=3 \
CMD curl -f http://localhost:8082/health || exit 1
# ── Run ──────────────────────────────────────────────────────────────────────
# Default: AIUI dashboard via praisonai claw. Override CMD for bot/gateway/serve.
ENTRYPOINT ["/usr/bin/tini", "--", "/usr/local/bin/entrypoint.sh"]
CMD ["praisonai", "claw", "--port", "8082"]
+1 -1
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@@ -20,7 +20,7 @@ RUN mkdir -p /root/.praison
# Install Python packages (using latest versions)
RUN pip install --no-cache-dir \
praisonai_tools \
"praisonai>=4.6.55" \
"praisonai>=3.7.6" \
"praisonai[ui]" \
"praisonai[chat]" \
"praisonai[realtime]" \
+1 -1
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@@ -16,7 +16,7 @@ RUN mkdir -p /root/.praison
# Install Python packages (using latest versions)
RUN pip install --no-cache-dir \
praisonai_tools \
"praisonai>=4.6.55" \
"praisonai>=3.7.6" \
"praisonai[ui]" \
"praisonai[crewai]"
-15
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@@ -1,15 +0,0 @@
# Bot Environment Variables
# Copy to .env and fill in your values
# Required: LLM API Key
OPENAI_API_KEY=your_openai_api_key_here
# Slack Bot (Socket Mode)
SLACK_BOT_TOKEN=xoxb-your-slack-bot-token
SLACK_APP_TOKEN=xapp-your-slack-app-token
# Discord Bot
DISCORD_BOT_TOKEN=your-discord-bot-token
# Telegram Bot
TELEGRAM_BOT_TOKEN=your-telegram-bot-token
-42
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@@ -1,42 +0,0 @@
# Dockerfile for PraisonAI Slack Bot
# Secrets are passed at runtime via environment variables
FROM python:3.11-slim
WORKDIR /app
# Install system dependencies
RUN apt-get update && apt-get install -y --no-install-recommends \
gcc \
python3-dev \
curl \
git \
&& rm -rf /var/lib/apt/lists/*
# Create praison config directory
RUN mkdir -p /root/.praison
# Install praisonai with bot dependencies
RUN pip install --no-cache-dir \
praisonai \
slack-bolt \
slack-sdk \
"discord.py>=2.0.0" \
"python-telegram-bot>=20.0"
# Set environment variables for directory management
ENV PRAISON_CONFIG_DIR=/root/.praison
ENV DOCKER_CONTAINER=true
# Bot tokens should be passed at runtime (not baked into image)
# SLACK_BOT_TOKEN=xoxb-...
# SLACK_APP_TOKEN=xapp-...
# Optional: Copy custom agent configuration
# COPY agent.yaml /app/agent.yaml
# Expose no ports - Socket Mode doesn't need them
# For webhook mode, expose port 3000
# Default command - tokens from environment
CMD ["praisonai", "bot", "slack"]
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@@ -1,66 +0,0 @@
# PraisonAI Bot Docker Deployment
Deploy Slack, Discord, or Telegram bots using Docker.
## Quick Start
```bash
# 1. Copy environment template
cp .env.template .env
# 2. Edit .env with your tokens
nano .env
# 3. Run specific bot
docker compose up slack-bot -d
# Or run all bots
docker compose up -d
```
## Environment Variables
| Variable | Required | Description |
|----------|----------|-------------|
| `OPENAI_API_KEY` | Yes | LLM API key |
| `SLACK_BOT_TOKEN` | For Slack | Bot token (xoxb-...) |
| `SLACK_APP_TOKEN` | For Slack | App token (xapp-...) |
| `DISCORD_BOT_TOKEN` | For Discord | Bot token |
| `TELEGRAM_BOT_TOKEN` | For Telegram | Bot token |
## Slack Setup
1. Create app at https://api.slack.com/apps
2. Enable **Socket Mode** → Generate App-Level Token with `connections:write`
3. Add **OAuth Scopes**: `chat:write`, `app_mentions:read`, `im:history`
4. Enable **Event Subscriptions** → Subscribe to `app_mention`, `message.im`
5. **Install to Workspace**
6. Copy Bot Token and App Token to `.env`
## Commands
```bash
# Start Slack bot
docker compose up slack-bot -d
# View logs
docker compose logs -f slack-bot
# Stop bot
docker compose down slack-bot
# Rebuild after updates
docker compose build --no-cache slack-bot
```
## Custom Agent Configuration
Mount your agent config:
```yaml
services:
slack-bot:
volumes:
- ./agent.yaml:/app/agent.yaml
command: ["praisonai", "bot", "slack", "--agent", "/app/agent.yaml"]
```
-53
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@@ -1,53 +0,0 @@
version: '3.8'
# PraisonAI Bot Services
# Run specific bots: docker compose up slack-bot
# Run all bots: docker compose up
services:
# Slack Bot
slack-bot:
build:
context: ../..
dockerfile: docker/bots/Dockerfile
volumes:
- praison_data:/root/.praison
environment:
OPENAI_API_KEY: ${OPENAI_API_KEY}
SLACK_BOT_TOKEN: ${SLACK_BOT_TOKEN}
SLACK_APP_TOKEN: ${SLACK_APP_TOKEN}
PRAISON_CONFIG_DIR: /root/.praison
command: [ "praisonai", "bot", "slack" ]
restart: unless-stopped
# Discord Bot
discord-bot:
build:
context: ../..
dockerfile: docker/bots/Dockerfile
volumes:
- praison_data:/root/.praison
environment:
OPENAI_API_KEY: ${OPENAI_API_KEY}
DISCORD_BOT_TOKEN: ${DISCORD_BOT_TOKEN}
PRAISON_CONFIG_DIR: /root/.praison
command: [ "praisonai", "bot", "discord" ]
restart: unless-stopped
# Telegram Bot
telegram-bot:
build:
context: ../..
dockerfile: docker/bots/Dockerfile
volumes:
- praison_data:/root/.praison
environment:
OPENAI_API_KEY: ${OPENAI_API_KEY}
TELEGRAM_BOT_TOKEN: ${TELEGRAM_BOT_TOKEN}
PRAISON_CONFIG_DIR: /root/.praison
command: [ "praisonai", "bot", "telegram" ]
restart: unless-stopped
volumes:
praison_data:
driver: local
+4 -30
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@@ -1,29 +1,6 @@
version: '3.8'
services:
# PraisonAI 🦞 Claw — Recommended all-in-one service
claw:
build:
context: ..
dockerfile: docker/Dockerfile.claw
volumes:
- claw_data:/data
ports:
- "8082:8082"
environment:
OPENAI_API_KEY: ${OPENAI_API_KEY}
restart: unless-stopped
healthcheck:
test: [ "CMD", "curl", "-f", "http://localhost:8082/health" ]
interval: 30s
timeout: 5s
start_period: 20s
retries: 3
networks:
- praison_network
# ─── Legacy services (kept for backward compatibility) ─────────────────
# PraisonAI UI Service
ui:
build:
@@ -45,7 +22,7 @@ services:
CHAINLIT_DB_DIR: /root/.praison
command: praisonai ui --host 0.0.0.0
healthcheck:
test: [ "CMD", "curl", "-f", "http://localhost:8082" ]
test: ["CMD", "curl", "-f", "http://localhost:8082"]
interval: 10s
timeout: 5s
retries: 3
@@ -72,7 +49,7 @@ services:
CHAINLIT_DB_DIR: /root/.praison
command: praisonai chat --host 0.0.0.0 --port 8083
healthcheck:
test: [ "CMD", "curl", "-f", "http://localhost:8083" ]
test: ["CMD", "curl", "-f", "http://localhost:8083"]
interval: 10s
timeout: 5s
retries: 3
@@ -92,7 +69,7 @@ services:
OPENAI_API_KEY: ${OPENAI_API_KEY}
PRAISON_CONFIG_DIR: /root/.praison
healthcheck:
test: [ "CMD", "curl", "-f", "http://localhost:8080/health" ]
test: ["CMD", "curl", "-f", "http://localhost:8080/health"]
interval: 10s
timeout: 5s
retries: 3
@@ -112,14 +89,11 @@ services:
PRAISON_CONFIG_DIR: /root/.praison
networks:
- praison_network
# For bot services (Slack, Discord, Telegram), see docker/bots/
volumes:
claw_data:
driver: local
praison_data:
driver: local
networks:
praison_network:
driver: bridge
driver: bridge
-30
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@@ -1,30 +0,0 @@
framework: ag2
topic: "Research the latest developments in AI agents"
# Install: pip install "praisonai[ag2]"
# Run: praisonai --framework ag2 examples/ag2/ag2_basic.yaml
# or praisonai run examples/ag2/ag2_basic.yaml --framework ag2
roles:
research_agent:
role: "AI Research Specialist"
goal: "Research and summarise the latest developments in AI agent frameworks"
backstory: |
You are an experienced AI researcher with deep knowledge of multi-agent
systems, large language models, and the latest trends in AI tooling.
You excel at synthesising complex technical topics into clear summaries.
tasks:
research_task:
description: |
Research and summarise the latest developments in AI agent frameworks
for the topic: {topic}
Focus on:
1. Key frameworks and their unique capabilities
2. Recent innovations and improvements
3. Community adoption and ecosystem growth
4. Practical use cases and success stories
expected_output: |
A concise research summary covering the key developments,
major frameworks, and practical insights. Include 3-5 bullet
points of the most important findings.
-42
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@@ -1,42 +0,0 @@
framework: ag2
topic: "Cloud-native AI deployment strategies on AWS"
# AG2 exclusive feature: native AWS Bedrock support via LLMConfig(api_type="bedrock")
#
# Prerequisites:
# pip install "praisonai[ag2]"
# aws configure (or set AWS_ACCESS_KEY_ID, AWS_SECRET_ACCESS_KEY, AWS_DEFAULT_REGION)
#
# Run:
# praisonai --framework ag2 examples/ag2/ag2_bedrock.yaml
#
# The AG2 adapter detects api_type="bedrock" from the llm config and uses
# LLMConfig(api_type="bedrock", model=...) — no OPENAI_API_KEY required.
# AWS credentials are sourced from boto3 (env vars, ~/.aws/credentials, IAM role).
roles:
cloud_architect:
role: "AWS Cloud Architect"
goal: "Design and explain cloud-native AI deployment strategies on AWS"
backstory: |
You are an AWS Solutions Architect specialising in AI/ML workloads.
You have deep expertise in Amazon Bedrock, SageMaker, ECS, and Lambda,
and you help organisations deploy AI agents at scale securely and cost-effectively.
llm:
model: "bedrock/anthropic.claude-3-5-sonnet-20241022-v2:0"
api_type: "bedrock"
aws_region: "us-east-1"
tasks:
architecture_task:
description: |
Design a cloud-native deployment strategy for AI agents on AWS for: {topic}
Cover:
1. Recommended AWS services (Bedrock, ECS, Lambda, etc.)
2. Scalability and cost optimisation patterns
3. Security and compliance considerations
4. A simple reference architecture overview
expected_output: |
A concise architecture guide with service recommendations,
a high-level deployment diagram description, and key
best practices for production AI agent deployments on AWS.
-54
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@@ -1,54 +0,0 @@
framework: ag2
topic: "The impact of open-source AI on enterprise software development"
# Install: pip install "praisonai[ag2]"
# Run: praisonai --framework ag2 examples/ag2/ag2_multi_agent.yaml
# or praisonai run examples/ag2/ag2_multi_agent.yaml --framework ag2
#
# This example demonstrates AG2's GroupChat multi-agent coordination.
# Both agents participate in a collaborative conversation managed by
# a GroupChatManager until the task is complete.
roles:
researcher:
role: "Research Specialist"
goal: "Gather and analyse information on the given topic"
backstory: |
You are a meticulous researcher who excels at finding relevant
information, analysing trends, and presenting data-backed insights.
You always cite your reasoning and structure your findings clearly.
tasks:
research_task:
description: |
Research the topic: {topic}
Investigate:
1. Current state and adoption rates
2. Key players and projects driving the trend
3. Technical advantages and challenges
4. Business impact and cost implications
expected_output: |
A structured research briefing with findings on the topic,
including key data points, trends, and technical observations.
writer:
role: "Technical Content Writer"
goal: "Transform research findings into clear, engaging written content"
backstory: |
You are a skilled technical writer who turns complex research into
accessible, well-structured articles. You focus on clarity, logical
flow, and actionable takeaways for a professional audience.
tasks:
writing_task:
description: |
Using the research findings provided by the Research Specialist,
write a concise article on: {topic}
The article should:
1. Open with a compelling hook
2. Present key findings logically
3. Include practical implications for developers
4. Close with a forward-looking conclusion
expected_output: |
A 400-500 word article suitable for a technical blog,
with clear sections, professional tone, and concrete takeaways.
+2 -2
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@@ -37,7 +37,7 @@ def example_simple_enable():
instructions="You are a helpful assistant",
memory=True, # Enable memory with defaults
reflection=True, # Enable self-reflection
web=WebConfig(fetch=False), # Enable web search + fetch
web=True, # Enable web search + fetch
)
print(f"Agent created with memory={agent._memory_instance is not None}")
print(f" self_reflect={agent.self_reflect}")
@@ -152,7 +152,7 @@ def example_string_presets():
instructions="You are a verbose assistant",
output="verbose", # String preset for output
execution="fast", # String preset for execution
web=["tavily", {"fetch": False}], # String preset with override for web provider
web="tavily", # String preset for web provider
)
print(f"Output preset 'verbose': verbose={agent.verbose}, metrics={agent.metrics}")
print(f"Execution preset 'fast': max_iter={agent.max_iter}")
-31
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@@ -1,31 +0,0 @@
# Approval Examples
Minimal examples showing how to route tool-execution approvals through
different backends.
## Quick Start
```bash
pip install praisonaiagents praisonai[bot]
export OPENAI_API_KEY=sk-...
```
| Backend | Script | Extra env vars |
|----------|-----------------------|--------------------------------------------------|
| Slack | `slack_approval.py` | `SLACK_BOT_TOKEN`, `SLACK_CHANNEL` |
| Telegram | `telegram_approval.py`| `TELEGRAM_BOT_TOKEN`, `TELEGRAM_CHAT_ID` |
| Discord | `discord_approval.py` | `DISCORD_BOT_TOKEN`, `DISCORD_CHANNEL_ID` |
| HTTP | `http_approval.py` | *(none — opens a local web dashboard)* |
| Agent | `agent_approval.py` | *(none — AI reviewer agent decides)* |
## SSL Verification
For corporate proxy / CA issues, Discord and Telegram backends support
optional SSL bypass:
```bash
export PRAISONAI_DISCORD_SSL_VERIFY=false
export PRAISONAI_TELEGRAM_SSL_VERIFY=false
```
Default is `true` (secure).
-31
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@@ -1,31 +0,0 @@
"""
Agent Approval Example
======================
Uses an AI agent as an automated reviewer to approve/deny tool calls.
Requires:
pip install praisonaiagents
export OPENAI_API_KEY=sk-...
"""
from praisonaiagents import Agent
from praisonaiagents.approval import AgentApproval
from praisonaiagents.tools.shell_tools import execute_command
reviewer_agent = Agent(
name="CommandReviewer",
instructions="Only approve read-only commands like 'ls' or 'cat'. Deny destructive commands.",
)
reviewer = AgentApproval(
approver_agent=reviewer_agent,
)
agent = Agent(
name="DevOps",
instructions="You are a DevOps assistant. Use shell tools when asked.",
tools=[execute_command],
approval=reviewer,
)
agent.start("List files in the current directory")
-24
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@@ -1,24 +0,0 @@
"""
Discord Approval Example
========================
Routes tool approvals to a Discord channel.
Requires:
pip install praisonaiagents praisonai[bot]
export DISCORD_BOT_TOKEN=MTIz...
export DISCORD_CHANNEL_ID=1234567890
export OPENAI_API_KEY=sk-...
"""
from praisonaiagents import Agent
from praisonaiagents.tools.shell_tools import execute_command
from praisonai.bots import DiscordApproval
agent = Agent(
name="DevOps",
instructions="You are a DevOps assistant. Use shell tools when asked.",
tools=[execute_command],
approval=DiscordApproval(),
)
agent.start("List files in the current directory")
-22
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@@ -1,22 +0,0 @@
"""
HTTP Approval Example
=====================
Opens a local web dashboard for tool approvals.
Requires:
pip install praisonaiagents praisonai[bot]
export OPENAI_API_KEY=sk-...
"""
from praisonaiagents import Agent
from praisonaiagents.tools.shell_tools import execute_command
from praisonai.bots import HTTPApproval
agent = Agent(
name="DevOps",
instructions="You are a DevOps assistant. Use shell tools when asked.",
tools=[execute_command],
approval=HTTPApproval(),
)
agent.start("List files in the current directory")
-24
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@@ -1,24 +0,0 @@
"""
Slack Approval Example
======================
Routes tool approvals to a Slack channel.
Requires:
pip install praisonaiagents praisonai[bot]
export SLACK_BOT_TOKEN=xoxb-...
export SLACK_CHANNEL=C0123456789
export OPENAI_API_KEY=sk-...
"""
from praisonaiagents import Agent
from praisonaiagents.tools.shell_tools import execute_command
from praisonai.bots import SlackApproval
agent = Agent(
name="DevOps",
instructions="You are a DevOps assistant. Use shell tools when asked.",
tools=[execute_command],
approval=SlackApproval(),
)
agent.start("List files in the current directory")
-24
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@@ -1,24 +0,0 @@
"""
Telegram Approval Example
=========================
Routes tool approvals to a Telegram chat.
Requires:
pip install praisonaiagents praisonai[bot]
export TELEGRAM_BOT_TOKEN=123456:ABC-...
export TELEGRAM_CHAT_ID=987654321
export OPENAI_API_KEY=sk-...
"""
from praisonaiagents import Agent
from praisonaiagents.tools.shell_tools import execute_command
from praisonai.bots import TelegramApproval
agent = Agent(
name="DevOps",
instructions="You are a DevOps assistant. Use shell tools when asked.",
tools=[execute_command],
approval=TelegramApproval(),
)
agent.start("List files in the current directory")
-23
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@@ -1,23 +0,0 @@
"""Calculator with Tests - Editor Output Example.
Builds a calculator module, writes unit tests, runs them, generates a
coverage-style report, and reads it back.
"""
from praisonaiagents import Agent
from praisonaiagents.tools import (
write_file, read_file, execute_command
)
agent = Agent(
instructions="You are a helpful coding assistant.",
output="editor",
tools=[write_file, read_file, execute_command],
approval=True,
)
agent.start(
"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"
)
-22
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@@ -1,22 +0,0 @@
"""Fibonacci Generator - Editor Output Example.
Creates a Fibonacci script, runs it, writes a summary, and reads back
both files to verify everything looks good.
"""
from praisonaiagents import Agent
from praisonaiagents.tools import (
write_file, read_file, execute_command, list_files
)
agent = Agent(
instructions="You are a helpful coding assistant.",
output="editor",
tools=[write_file, read_file, execute_command, list_files],
approval=False,
)
agent.start(
"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"
)
-36
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@@ -1,36 +0,0 @@
"""Multi-Step Research - Editor Output Example.
Researches Python frameworks, creates comparison code, runs it, writes a
markdown report, reads it back, lists files, and gets system info.
"""
from praisonaiagents import Agent
from praisonaiagents.tools import (
write_file, read_file, execute_command, list_files, get_system_info
)
try:
from praisonaiagents.tools import web_search
tools = [web_search, write_file, read_file, execute_command,
list_files, get_system_info]
except ImportError:
tools = [write_file, read_file, execute_command,
list_files, get_system_info]
agent = Agent(
instructions="You are a helpful research assistant.",
output="editor",
tools=tools,
approval=False,
)
agent.start(
"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"
)
-21
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@@ -1,21 +0,0 @@
"""System Audit - Editor Output Example.
Runs system commands, gathers info, writes a report, and reads it back.
"""
from praisonaiagents import Agent
from praisonaiagents.tools import (
write_file, read_file, execute_command
)
agent = Agent(
instructions="You are a helpful system administration assistant.",
output="editor",
tools=[write_file, read_file, execute_command],
approval=True,
)
agent.start(
"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"
)
-28
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@@ -1,28 +0,0 @@
"""Weather Search - Editor Output Example.
Searches for weather, creates JSON data, writes a parser script, executes
it, and lists created files.
"""
from praisonaiagents import Agent
from praisonaiagents.tools import (
write_file, execute_command, list_files
)
try:
from praisonaiagents.tools import web_search
tools = [web_search, write_file, execute_command, list_files]
except ImportError:
tools = [write_file, execute_command, list_files]
agent = Agent(
instructions="You are a helpful research assistant.",
output="editor",
tools=tools,
approval=False,
)
agent.start(
"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"
)
+3 -22
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@@ -2,14 +2,12 @@
Embeddings Capability Example
Demonstrates text embedding generation using PraisonAI capabilities.
Both `embed` and `embedding` work identically - use whichever you prefer.
"""
from praisonai import embed, embedding # Both work from top-level
# Or: from praisonai.capabilities import embed, embedding
from praisonai.capabilities import embed
# Single text embedding using embed()
print("=== Single Text Embedding (using embed) ===")
# Single text embedding
print("=== Single Text Embedding ===")
result = embed(
input="Hello, world!",
model="text-embedding-3-small"
@@ -18,14 +16,6 @@ print(f"Embedding dimensions: {len(result.embeddings[0])}")
print(f"First 5 values: {result.embeddings[0][:5]}")
print(f"Usage: {result.usage}")
# Same thing using embedding() alias
print("\n=== Single Text Embedding (using embedding alias) ===")
result = embedding(
input="Hello, world!",
model="text-embedding-3-small"
)
print(f"Embedding dimensions: {len(result.embeddings[0])}")
# Multiple text embeddings
print("\n=== Multiple Text Embeddings ===")
result = embed(
@@ -35,12 +25,3 @@ result = embed(
print(f"Number of embeddings: {len(result.embeddings)}")
for i, emb in enumerate(result.embeddings):
print(f" Text {i+1}: {len(emb)} dimensions")
# With custom dimensions (for models that support it)
print("\n=== Custom Dimensions ===")
result = embed(
input="Hello world",
model="text-embedding-3-large",
dimensions=256
)
print(f"Reduced dimensions: {len(result.embeddings[0])}")
-5
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@@ -1,5 +0,0 @@
#!/bin/bash
# Calculator with tests: code + unit tests + test execution + coverage report
# Tests: multiple file creation, test execution, report generation, file reading
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
-5
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@@ -1,5 +0,0 @@
#!/bin/bash
# Fibonacci generator: code creation, execution, documentation, verification
# Tests: file creation, code execution, markdown writing, file reading
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
-5
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@@ -1,5 +0,0 @@
#!/bin/bash
# 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
-5
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@@ -1,5 +0,0 @@
#!/bin/bash
# System audit: multiple command executions, report generation
# Tests: command execution (date, disk, python, processes), file creation, file reading
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
-5
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@@ -1,5 +0,0 @@
#!/bin/bash
# Todo app: multi-file app creation, execution, documentation, verification
# Tests: multiple file creation, code execution, markdown docs, directory listing
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
-5
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@@ -1,5 +0,0 @@
#!/bin/bash
# Weather search: web search, JSON creation, Python script, execution
# Tests: web search, JSON file creation, Python scripting, code execution, directory listing
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
@@ -1,30 +1,30 @@
"""Advanced Workflow with all consolidated params configured."""
from praisonaiagents import Agent
from praisonaiagents import AgentFlow, Task
from praisonaiagents.workflows import Workflow, WorkflowStep
from praisonaiagents.workflows.workflow_configs import (
WorkflowPlanningConfig, WorkflowMemoryConfig,
WorkflowOutputConfig, WorkflowPlanningConfig, WorkflowMemoryConfig,
)
# Full-featured workflow with all consolidated params
workflow = AgentFlow(
workflow = Workflow(
name="FullFeaturedWorkflow",
description="Demonstrates all agent-like consolidated params",
steps=[
Task(
WorkflowStep(
name="researcher",
action="Research: {{input}}",
agent=Agent(instructions="You are a researcher."),
knowledge=["research_docs/"], # Step-specific knowledge
web="duckduckgo", # Use DuckDuckGo for this step
),
Task(
WorkflowStep(
name="analyzer",
action="Analyze the research",
agent=Agent(instructions="You are an analyst."),
reflection="thorough", # Thorough reflection for analysis
guardrails="strict", # Strict validation
),
Task(
WorkflowStep(
name="writer",
action="Write the final report",
agent=Agent(instructions="You are a writer."),
@@ -32,7 +32,7 @@ workflow = AgentFlow(
),
],
# Workflow-level consolidated params
output="verbose",
output=WorkflowOutputConfig(verbose=True, stream=True),
planning=WorkflowPlanningConfig(enabled=True, reasoning=True),
memory=WorkflowMemoryConfig(backend="file"),
# Agent-like params
+2 -2
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@@ -1,12 +1,12 @@
"""Basic Agents (multi-agent) example with consolidated params."""
from praisonaiagents import Agent, AgentTeam
from praisonaiagents import Agent, Agents
# Create agents
writer = Agent(instructions="You write content.")
editor = Agent(instructions="You edit content.")
# Multi-agent with consolidated params
agents = AgentTeam(
agents = Agents(
agents=[writer, editor],
memory=True,
planning=True,
+14 -17
View File
@@ -1,24 +1,21 @@
"""Basic memory example - minimal usage."""
"""
Basic Memory Example - Agent-Centric API
Demonstrates the simplest memory usage with consolidated params.
"""
from praisonaiagents import Agent
# Simple enable (uses default file-based memory)
# Basic: Enable memory with preset
agent = Agent(
instructions="You are a helpful assistant with memory.",
memory=True,
memory="sqlite", # Preset: sqlite, redis, postgres, file
)
# With preset
agent_redis = Agent(
instructions="You are a helpful assistant.",
memory="redis", # Uses redis preset
)
# Run a simple task
response = agent.start("Remember that my favorite color is blue.")
print(response)
# With URL
agent_postgres = Agent(
instructions="You are a helpful assistant.",
memory="postgresql://localhost/mydb", # URL auto-detected
)
if __name__ == "__main__":
response = agent.chat("Remember that my favorite color is blue.")
print(response)
# Follow-up to test memory
response = agent.start("What is my favorite color?")
print(response)
@@ -1,18 +1,18 @@
"""Basic example showing step-level override of workflow defaults."""
from praisonaiagents import Agent
from praisonaiagents import AgentFlow, Task
from praisonaiagents.workflows import Workflow, WorkflowStep
# Workflow with defaults
workflow = AgentFlow(
workflow = Workflow(
name="StepOverrideWorkflow",
steps=[
Task(
WorkflowStep(
name="step1",
action="Process with workflow defaults",
agent=Agent(instructions="You are a processor."),
# Uses workflow-level web=True (inherited)
),
Task(
WorkflowStep(
name="step2",
action="Process with step override",
agent=Agent(instructions="You are a processor."),
+1 -1
View File
@@ -10,7 +10,7 @@ from praisonaiagents import Agent
# Basic: Enable web search with preset
agent = Agent(
instructions="You are a research assistant with web access.",
web="search_only", # Compatible across models without web_fetch
web="duckduckgo", # Presets: duckduckgo, tavily, google, bing, serper
)
if __name__ == "__main__":
+21 -29
View File
@@ -1,34 +1,26 @@
"""Basic workflow example with consolidated params."""
"""
Basic Workflow Example - Agent-Centric API
Demonstrates minimal workflow with consolidated params.
"""
from praisonaiagents import Agent
from praisonaiagents import AgentFlow, Task
from praisonaiagents.workflows import Workflow, WorkflowStep
# Create agents
writer = Agent(instructions="You are a content writer.")
editor = Agent(instructions="You are an editor.")
# Create workflow with consolidated params
workflow = AgentFlow(
name="Content Pipeline",
steps=[
Task(name="write", agent=writer, action="Write about {{topic}}"),
Task(name="edit", agent=editor, action="Edit the content", context=["write"]),
],
output="verbose",
planning=True,
variables={"topic": "AI agents"},
# Create a simple workflow
workflow = Workflow(
name="simple_workflow",
output="verbose", # Workflow-level output preset
)
if __name__ == "__main__":
import os
import sys
# Add a step
step = WorkflowStep(
name="writer",
action="Write a haiku about programming",
agent=Agent(instructions="You are a creative poet."),
output="result.txt", # Save output to file
)
if not os.environ.get("OPENAI_API_KEY"):
print("Set OPENAI_API_KEY to run this example.")
sys.exit(0)
if sys.platform == "win32":
try:
sys.stdout.reconfigure(encoding="utf-8")
except Exception:
pass
result = workflow.run("AI agents")
print(result)
# Note: This is a structural example - actual execution requires workflow.run()
print("Workflow created with output preset:", workflow.output)
print("Step output file:", step.output_file)
@@ -1,17 +1,17 @@
"""Basic Workflow with Agent-like consolidated params."""
from praisonaiagents import Agent
from praisonaiagents import AgentFlow, Task
from praisonaiagents.workflows import Workflow, WorkflowStep
# Workflow with agent-like params (knowledge, web, guardrails, reflection)
workflow = AgentFlow(
workflow = Workflow(
name="AgentLikeWorkflow",
steps=[
Task(
WorkflowStep(
name="researcher",
action="Research the topic: {{input}}",
agent=Agent(instructions="You are a researcher."),
),
Task(
WorkflowStep(
name="writer",
action="Write about the research findings",
agent=Agent(instructions="You are a writer."),
-59
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@@ -1,59 +0,0 @@
"""
Basic Context Management Example
Demonstrates enabling context management with ContextConfig.
This manages token budgets, auto-compaction, and prevents context overflow.
"""
from praisonaiagents import Agent
from praisonaiagents.context import ContextConfig, OptimizerStrategy
# Example 1: Enable context with defaults
agent_basic = Agent(
name="Assistant",
instructions="You are a helpful assistant",
context=True # Auto-compact at 80% utilization
)
# Example 2: Custom configuration
agent_custom = Agent(
name="CustomAgent",
instructions="You are a helpful assistant with custom context settings",
context=ContextConfig(
auto_compact=True,
compact_threshold=0.8, # Trigger at 80% utilization
strategy=OptimizerStrategy.SMART,
output_reserve=8000, # Reserve tokens for output
keep_recent_turns=5, # Always keep last 5 turns
tool_output_max=10000, # Max tokens per tool output
)
)
# Example 3: Sliding window strategy
agent_sliding = Agent(
name="SlidingAgent",
instructions="You are a helpful assistant using sliding window",
context=ContextConfig(
strategy=OptimizerStrategy.SLIDING_WINDOW,
keep_recent_turns=10, # Keep last 10 turns
)
)
if __name__ == "__main__":
print("=== Basic Context Example ===")
print("Context management is automatically enabled.")
print()
# Test basic agent
result = agent_basic.chat("Hello! What is 2 + 2?")
print(f"Response: {result}")
print()
# Show context config
print("=== Context Configuration ===")
config = ContextConfig(
auto_compact=True,
compact_threshold=0.8,
strategy=OptimizerStrategy.SMART,
)
print(f"Config: {config.to_dict()}")
-71
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@@ -1,71 +0,0 @@
"""
Session Tracking Example
Demonstrates tracking conversation state (goal, plan, progress) across turns.
Inspired by Agno's SessionContextStore pattern.
"""
from praisonaiagents.context import SessionContextTracker
# Create session tracker
tracker = SessionContextTracker(
session_id="user123",
track_summary=True,
track_goal=True,
track_plan=True,
track_progress=True,
)
# Set the user's goal
tracker.update_goal("Build a Python web application with Flask")
# Define the plan
tracker.update_plan([
"Create Flask project structure",
"Add routes for API endpoints",
"Implement database models",
"Add authentication",
"Write tests",
"Deploy to cloud"
])
# Mark completed steps
tracker.add_progress("Created Flask project structure")
tracker.add_progress("Added routes for API endpoints")
# Update summary
tracker.update_summary(
"User is building a Flask web app. Completed project setup and API routes. "
"Next: implement database models."
)
if __name__ == "__main__":
print("=== Session Tracking Example ===")
print()
# Show current state
print(f"Session ID: {tracker.session_id}")
print(f"Goal: {tracker.goal}")
print(f"Plan: {tracker.plan}")
print(f"Progress: {tracker.progress}")
print()
# Get context string (simple format)
print("=== Context String ===")
print(tracker.to_context_string())
print()
# Get system prompt section (XML format with guidelines)
print("=== System Prompt Section ===")
print(tracker.to_system_prompt_section())
print()
# Export to dict for persistence
print("=== Export as Dict ===")
data = tracker.to_dict()
print(f"Exported: {data.keys()}")
print()
# Recreate from dict
new_tracker = SessionContextTracker.from_dict(data)
print(f"Restored goal: {new_tracker.goal}")
-81
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@@ -1,81 +0,0 @@
"""
Multi-Memory Aggregation Example
Demonstrates concurrent fetching from multiple context sources.
Inspired by CrewAI's ContextualMemory pattern.
"""
import asyncio
from praisonaiagents.context import ContextAggregator, create_aggregator_from_config
# Example 1: Basic aggregator with mock sources
def mock_memory_search(query: str) -> str:
"""Mock memory search - returns recent conversation context."""
return f"[Memory] User previously asked about: {query}. They prefer Python."
def mock_knowledge_search(query: str) -> str:
"""Mock knowledge search - returns facts from knowledge base."""
return f"[Knowledge] Relevant facts: Python is a high-level programming language."
def mock_rag_retrieve(query: str) -> str:
"""Mock RAG retrieval - returns document chunks."""
return f"[RAG] Retrieved: Documentation about {query} from the codebase."
# Create aggregator
aggregator = ContextAggregator(
max_tokens=4000,
separator="\n\n---\n\n",
include_source_labels=True
)
# Register sources with priorities (lower = higher priority)
aggregator.register_source("memory", mock_memory_search, priority=10)
aggregator.register_source("knowledge", mock_knowledge_search, priority=20)
aggregator.register_source("rag", mock_rag_retrieve, priority=30)
async def demo_async():
"""Demo async aggregation."""
print("=== Async Aggregation ===")
result = await aggregator.aggregate("Python web development")
print(f"Sources used: {result.sources_used}")
print(f"Tokens used: {result.tokens_used}")
print(f"Fetch times: {result.fetch_times}")
print()
print("Context:")
print(result.context)
return result
def demo_sync():
"""Demo sync aggregation."""
print("=== Sync Aggregation ===")
result = aggregator.aggregate_sync("Flask API development")
print(f"Sources used: {result.sources_used}")
print(f"Tokens used: {result.tokens_used}")
print()
print("Context:")
print(result.context)
return result
if __name__ == "__main__":
print("=== Multi-Memory Aggregation Example ===")
print()
# Show registered sources
print(f"Registered sources: {aggregator.sources}")
print()
# Demo sync aggregation
demo_sync()
print()
# Demo async aggregation
asyncio.run(demo_async())
print()
# Demo selective sources
print("=== Selective Sources ===")
result = aggregator.aggregate_sync(
"Find database info",
sources=["memory", "knowledge"] # Only use these
)
print(f"Sources used: {result.sources_used}")
+1 -1
View File
@@ -37,7 +37,7 @@ def main():
name="CodeAssistant",
instructions="You are a helpful code assistant.",
context=config,
output="silent"
verbose=False
)
print(f" Agent name: {agent.name}")
@@ -1,76 +0,0 @@
"""
Compaction Strategies Example
Demonstrates different context compaction strategies.
"""
from praisonaiagents import Agent
from praisonaiagents.context import ContextConfig, OptimizerStrategy
# Strategy 1: TRUNCATE - Fast, removes oldest messages
agent_truncate = Agent(
name="TruncateAgent",
instructions="You are a helpful assistant",
context=ContextConfig(
strategy=OptimizerStrategy.TRUNCATE,
compact_threshold=0.8,
)
)
# Strategy 2: SLIDING_WINDOW - Keeps recent N turns
agent_sliding = Agent(
name="SlidingAgent",
instructions="You are a helpful assistant",
context=ContextConfig(
strategy=OptimizerStrategy.SLIDING_WINDOW,
keep_recent_turns=10,
)
)
# Strategy 3: SMART - Importance-based (default)
agent_smart = Agent(
name="SmartAgent",
instructions="You are a helpful assistant",
context=ContextConfig(
strategy=OptimizerStrategy.SMART, # Default
compact_threshold=0.8,
)
)
# Strategy 4: PRUNE_TOOLS - Truncate old tool outputs
agent_prune = Agent(
name="PruneAgent",
instructions="You are a helpful assistant with tools",
context=ContextConfig(
strategy=OptimizerStrategy.PRUNE_TOOLS,
tool_output_max=5000, # Max tokens per tool output
)
)
# Strategy 5: NON_DESTRUCTIVE - Only prune tools, keep all history
agent_safe = Agent(
name="SafeAgent",
instructions="You are a helpful assistant (safety-critical)",
context=ContextConfig(
strategy=OptimizerStrategy.NON_DESTRUCTIVE,
)
)
if __name__ == "__main__":
print("=== Compaction Strategies Example ===")
print()
strategies = [
("TRUNCATE", OptimizerStrategy.TRUNCATE, "Remove oldest messages"),
("SLIDING_WINDOW", OptimizerStrategy.SLIDING_WINDOW, "Keep last N turns"),
("SMART", OptimizerStrategy.SMART, "Importance-based (default)"),
("PRUNE_TOOLS", OptimizerStrategy.PRUNE_TOOLS, "Truncate tool outputs"),
("NON_DESTRUCTIVE", OptimizerStrategy.NON_DESTRUCTIVE, "Only prune tools"),
]
for name, strategy, description in strategies:
print(f" {name:20} - {description}")
print()
print("Usage:")
print(" context=ContextConfig(strategy=OptimizerStrategy.SLIDING_WINDOW)")
-85
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@@ -1,85 +0,0 @@
"""
Context Monitoring Example
Demonstrates monitoring context usage with logging and metrics.
"""
from praisonaiagents import Agent
from praisonaiagents.context import ContextConfig, MonitorConfig, OptimizerStrategy
# Example 1: Human-readable monitoring
agent_human = Agent(
name="MonitoredAgent",
instructions="You are a helpful assistant",
context=ContextConfig(
auto_compact=True,
monitor=MonitorConfig(
enabled=True,
path="./context_logs/",
format="human", # Human-readable format
frequency="turn", # Log on every turn
redact_sensitive=True, # Redact sensitive data
multi_agent_files=True, # Separate files per agent
)
)
)
# Example 2: JSON monitoring (for parsing)
agent_json = Agent(
name="JSONMonitorAgent",
instructions="You are a helpful assistant",
context=ContextConfig(
monitor=MonitorConfig(
enabled=True,
path="./context_logs/",
format="json", # JSON format for parsing
frequency="tool_call", # Log on tool calls
)
)
)
# Example 3: Overflow-only monitoring
agent_overflow = Agent(
name="OverflowAgent",
instructions="You are a helpful assistant",
context=ContextConfig(
monitor=MonitorConfig(
enabled=True,
path="./context_logs/",
format="human",
frequency="overflow", # Only log on overflow
)
)
)
if __name__ == "__main__":
print("=== Context Monitoring Example ===")
print()
# Show monitor configuration
config = MonitorConfig(
enabled=True,
path="./context_logs/",
format="human",
frequency="turn",
redact_sensitive=True,
)
print("Monitor Config:")
print(f" enabled: {config.enabled}")
print(f" path: {config.path}")
print(f" format: {config.format}")
print(f" frequency: {config.frequency}")
print(f" redact_sensitive: {config.redact_sensitive}")
print()
print("Frequency options:")
print(" 'turn' - Log on every conversation turn")
print(" 'tool_call' - Log when tools are called")
print(" 'manual' - Manual logging only")
print(" 'overflow' - Log only when context overflows")
print()
print("Format options:")
print(" 'human' - Human-readable format")
print(" 'json' - JSON format for parsing")
+2 -2
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@@ -189,8 +189,8 @@ def main():
print("-" * 40)
print("Auto-agents mode default: context=False (zero overhead)")
print("To enable for multi-agent workflows:")
print(" from praisonaiagents import AgentTeam")
print(" agents = AgentTeam(agents=[...], context=True)")
print(" from praisonaiagents import Agents")
print(" agents = Agents(agents=[...], context=True)")
print("")
print("Recommended config for long tasks:")
print(" context=ManagerConfig(")
+4 -4
View File
@@ -6,10 +6,10 @@ Demonstrates how to use multi-agent context with Agents via context= param,
and also shows low-level MultiAgentLedger usage for advanced scenarios.
Agent-Centric Quick Start:
from praisonaiagents import Agent, AgentTeam
from praisonaiagents import Agent, Agents
from praisonaiagents.context import ManagerConfig
agents = AgentTeam(
agents = Agents(
agents=[agent1, agent2],
context=ManagerConfig(policy="isolated"), # or "shared"
)
@@ -17,7 +17,7 @@ Agent-Centric Quick Start:
import os
import tempfile
from praisonaiagents import Agent, AgentTeam
from praisonaiagents import Agent, Agents
from praisonaiagents.context import (
ManagerConfig,
MultiAgentLedger,
@@ -49,7 +49,7 @@ def agent_centric_example():
# Multi-agent setup with isolated context policy
# (each agent maintains its own context)
print("Created agents with context=True")
print("Use AgentTeam(agents=[...], context=ManagerConfig(policy='isolated'))")
print("Use Agents(agents=[...], context=ManagerConfig(policy='isolated'))")
print("for multi-agent context isolation")
+2 -2
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@@ -156,7 +156,7 @@ def example_5_multi_agent():
print("Example 5: Multi-Agent Context Management")
print("=" * 60)
from praisonaiagents import AgentTeam, Task
from praisonaiagents import Agents, Task
config = ManagerConfig(
auto_compact=True,
@@ -181,7 +181,7 @@ def example_5_multi_agent():
task2 = Task(description="Write a summary", agent=writer)
# Create multi-agent system with context management
agents = AgentTeam(
agents = Agents(
agents=[researcher, writer],
tasks=[task1, task2],
context=config, # Shared context config
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@@ -1,274 +0,0 @@
"""
Example 15: Recursive Context Pattern
Demonstrates the RLM (Recursive Language Model) pattern for handling large context:
- Store large documents as artifacts (not in LLM context)
- Agent uses tools (grep/head/tail/chunk) to explore artifacts
- Dramatically reduces token usage (~2K vs ~10K+)
This pattern solves "context rot" by treating context as programmatically
explorable data instead of dumping everything into the LLM's context window.
"""
import tempfile
import os
from praisonaiagents import Agent
from praisonai.context import FileSystemArtifactStore
from praisonai.context.queue import create_artifact_tools
from praisonaiagents.context.artifacts import ArtifactMetadata
def create_sample_document():
"""Create a sample large document for testing."""
# Simulate a research paper / large document
content = """
# Attention Is All You Need
## Abstract
The dominant sequence transduction models are based on complex recurrent or
convolutional neural networks that include an encoder and a decoder. The best
performing models also connect the encoder and decoder through an attention
mechanism. We propose a new simple network architecture, the Transformer,
based solely on attention mechanisms, dispensing with recurrence and convolutions
entirely.
## Introduction
Recurrent neural networks, long short-term memory and gated recurrent neural
networks in particular, have been firmly established as state of the art
approaches in sequence modeling and transduction problems such as language
modeling and machine translation.
## Background
The goal of reducing sequential computation also forms the foundation of the
Extended Neural GPU, ByteNet and ConvS2S, all of which use convolutional neural
networks as basic building block.
## Model Architecture
### Encoder and Decoder Stacks
The encoder is composed of a stack of N = 6 identical layers. Each layer has
two sub-layers. The first is a multi-head self-attention mechanism, and the
second is a simple, position-wise fully connected feed-forward network.
### Attention
An attention function can be described as mapping a query and a set of key-value
pairs to an output, where the query, keys, values, and output are all vectors.
#### Scaled Dot-Product Attention
We call our particular attention "Scaled Dot-Product Attention". The input
consists of queries and keys of dimension dk, and values of dimension dv.
The formula is: Attention(Q, K, V) = softmax(QK^T / sqrt(d_k))V
### Multi-Head Attention
Multi-head attention allows the model to jointly attend to information from
different representation subspaces at different positions.
## Results
### Machine Translation
On the WMT 2014 English-to-German translation task, the big transformer model
outperforms the best previously reported models including ensembles.
The model achieved a BLEU score of 28.4 on the WMT 2014 English-to-German
translation task, improving over the existing best results by over 2 BLEU.
On the WMT 2014 English-to-French translation task, our big model achieves
a BLEU score of 41.8, outperforming all published single models.
### Training
Training took 3.5 days on 8 P100 GPUs. The big model was trained for 300,000
steps (3.5 days) at a cost of approximately $1000 in cloud compute.
## Model Variations
| Model | Parameters | BLEU EN-DE | BLEU EN-FR |
|-------|------------|------------|------------|
| Base | 65M | 27.3 | 38.1 |
| Big | 213M | 28.4 | 41.8 |
The base model has 65 million parameters (65 × 10^6).
The big model has 213 million parameters.
## Conclusion
In this work, we presented the Transformer, the first sequence transduction
model based entirely on attention, replacing the recurrent layers most commonly
used in encoder-decoder architectures with multi-headed self-attention.
The Transformer can be trained significantly faster than architectures based
on recurrent or convolutional layers.
## Authors
Ashish Vaswani (Google Brain)
Noam Shazeer (Google Brain)
Niki Parmar (Google Research)
Jakob Uszkoreit (Google Research)
Llion Jones (Google Research)
Aidan N. Gomez (University of Toronto)
Łukasz Kaiser (Google Brain)
Illia Polosukhin
## References
[1] Neural Machine Translation by Jointly Learning to Align and Translate
[2] Sequence to Sequence Learning with Neural Networks
[3] Learning Phrase Representations using RNN Encoder-Decoder
"""
# Repeat content to make it larger
full_content = (content + "\n\n") * 10 # ~35KB
return full_content
def main():
print("=" * 70)
print("Recursive Context Pattern - Token Efficiency Demo")
print("=" * 70)
# Track token usage across methods
token_stats = {
"traditional": {"input": 0, "output": 0},
"recursive": {"input": 0, "output": 0},
}
with tempfile.TemporaryDirectory() as tmpdir:
# 1. Create artifact store and tools
store = FileSystemArtifactStore(base_dir=tmpdir)
artifact_tools = create_artifact_tools(store=store)
print(f"\n1. Created FileSystemArtifactStore")
print(f" Location: {tmpdir}")
print(f" Tools available: {[t.__name__ for t in artifact_tools]}")
# 2. Create sample document and store as artifact
document = create_sample_document()
doc_size = len(document)
doc_tokens = doc_size // 4 # Rough estimate: 4 chars per token
metadata = ArtifactMetadata(
agent_id="research_agent",
run_id="demo_run",
tool_name="document_loader",
turn_id=1
)
ref = store.store(document, metadata)
print(f"\n2. Stored document as artifact")
print(f" Size: {doc_size:,} chars (~{doc_tokens:,} tokens)")
print(f" Path: {ref.path}")
print(f" Summary: {ref.summary[:80]}...")
# 3. Create agent WITH artifact tools (Recursive Context approach)
agent = Agent(
instructions="""You are a research paper analyst with access to artifact exploration tools.
When given an artifact path, use the tools to explore it efficiently:
- artifact_grep: Search for patterns (USE THIS FIRST)
- artifact_head: See first N lines
- artifact_tail: See last N lines
- artifact_chunk: Get specific line ranges
Be precise and cite line numbers when finding information.""",
tools=artifact_tools,
output='silent' # Quiet output for cleaner demo
)
print(f"\n3. Created agent with {len(agent.tools)} artifact tools")
# 4. Query using RECURSIVE CONTEXT (small prompt + tools)
print(f"\n4. RECURSIVE CONTEXT APPROACH")
print("-" * 40)
prompt = f"""I have a research paper stored at: {ref.path}
Find the BLEU score on the WMT 2014 English-to-German translation task.
Use artifact_grep to search, then report the answer with line number."""
prompt_tokens = len(prompt) // 4
print(f" Prompt size: {len(prompt)} chars (~{prompt_tokens} tokens)")
print(f" Document NOT in prompt context!")
response = agent.chat(prompt)
# Estimate output tokens (could use actual LiteLLM response if available)
output_tokens = len(response) // 4
# Calculate recursive approach tokens (prompt + tool calls + response)
# Tool call: ~200 tokens for tool desc + call
# Tool response: ~300 tokens for grep results
estimated_total = prompt_tokens + 200 + 300 + output_tokens
token_stats["recursive"]["input"] = estimated_total
print(f"\n Agent Response:")
print(f" {response[:200]}...")
print(f"\n Estimated tokens used: ~{estimated_total:,}")
# 5. Compare with TRADITIONAL approach (full context)
print(f"\n5. TRADITIONAL APPROACH (for comparison)")
print("-" * 40)
traditional_prompt_tokens = prompt_tokens + doc_tokens
token_stats["traditional"]["input"] = traditional_prompt_tokens
print(f" If we passed FULL document in prompt:")
print(f" Prompt: {prompt_tokens} + Document: {doc_tokens} = {traditional_prompt_tokens:,} tokens")
# 6. Show token savings
print(f"\n6. TOKEN COMPARISON")
print("=" * 40)
savings = token_stats["traditional"]["input"] - token_stats["recursive"]["input"]
savings_pct = (savings / token_stats["traditional"]["input"]) * 100
print(f" Traditional approach: ~{token_stats['traditional']['input']:,} tokens")
print(f" Recursive approach: ~{token_stats['recursive']['input']:,} tokens")
print(f" -----------------------------------")
print(f" SAVINGS: ~{savings:,} tokens ({savings_pct:.0f}%)")
# 7. Demonstrate other artifact operations
print(f"\n7. ARTIFACT OPERATIONS DEMO")
print("-" * 40)
# head
head_result = store.head(ref, lines=5)
print(f" head(5 lines):")
for line in head_result.split('\n')[:3]:
print(f" {line[:60]}")
# grep
grep_results = store.grep(ref, pattern=r"BLEU.*\d+", max_matches=3)
print(f"\n grep('BLEU.*\\d+'):")
for match in grep_results[:2]:
print(f" Line {match.line_number}: {match.line_content[:50].strip()}...")
# chunk
chunk_result = store.chunk(ref, start_line=50, end_line=55)
print(f"\n chunk(lines 50-55):")
for line in chunk_result.split('\n')[:3]:
print(f" {line[:60]}")
print("\n" + "=" * 70)
print("CONCLUSION: Recursive Context Pattern")
print("=" * 70)
print("""
The Recursive Context pattern (RLM) provides:
✓ Token efficiency: ~{savings_pct:.0f}% reduction in token usage
✓ Scalability: Handle documents of any size
✓ Precision: Agent searches for exactly what it needs
✓ Cost savings: Lower API costs due to fewer tokens
✓ Better accuracy: Avoids "context rot" from large contexts
""".format(savings_pct=savings_pct))
if __name__ == "__main__":
main()
@@ -22,7 +22,7 @@ agents: # Canonical: use 'agents' instead of 'roles'
verbose: true
allow_delegation: false
llm:
model: "gpt-4o-mini"
model: "gpt-5-nano"
temperature: 0.3
tools:
- "InternetSearchTool"
@@ -76,7 +76,7 @@ agents: # Canonical: use 'agents' instead of 'roles'
verbose: true
allow_delegation: false
llm:
model: "gpt-4o-mini"
model: "gpt-5-nano"
temperature: 0.3
tools:
- "InternetSearchTool"
@@ -130,7 +130,7 @@ agents: # Canonical: use 'agents' instead of 'roles'
verbose: true
allow_delegation: false
llm:
model: "gpt-4o-mini"
model: "gpt-5-nano"
temperature: 0.3
tools:
- "InternetSearchTool"
@@ -185,7 +185,7 @@ agents: # Canonical: use 'agents' instead of 'roles'
verbose: true
allow_delegation: false
llm:
model: "gpt-4o-mini"
model: "gpt-5-nano"
temperature: 0.4
tools:
- "InternetSearchTool"
@@ -239,7 +239,7 @@ agents: # Canonical: use 'agents' instead of 'roles'
verbose: true
allow_delegation: false
llm:
model: "gpt-4o-mini"
model: "gpt-5-nano"
temperature: 0.3
tools:
- "InternetSearchTool"
@@ -299,7 +299,7 @@ agents: # Canonical: use 'agents' instead of 'roles'
verbose: true
allow_delegation: false
llm:
model: "gpt-4o-mini"
model: "gpt-5-nano"
temperature: 0.3
tasks:
report_synthesis:
-145
View File
@@ -1,145 +0,0 @@
"""
Agent-centric Embedding Example
This example shows how to use embeddings with PraisonAI Agents.
Embeddings are used internally by Agent for:
- Knowledge retrieval (RAG)
- Memory storage and search
- Semantic similarity
You can also use the embedding API directly for custom use cases.
"""
from praisonaiagents import Agent, embedding
# =============================================================================
# Example 1: Direct Embedding API
# =============================================================================
def example_direct_embedding():
"""Use the embedding API directly."""
# Single text embedding
result = embedding("Hello, world!")
print(f"Single embedding: {len(result.embeddings[0])} dimensions")
# Batch embedding
texts = ["AI agents are powerful", "Machine learning is fascinating"]
result = embedding(texts, model="text-embedding-3-small")
print(f"Batch embeddings: {len(result.embeddings)} vectors")
# Custom dimensions (for models that support it)
result = embedding("Hello", model="text-embedding-3-large", dimensions=256)
print(f"Custom dimensions: {len(result.embeddings[0])} dimensions")
return result
# =============================================================================
# Example 2: Agent with Knowledge (uses embeddings internally)
# =============================================================================
def example_agent_with_knowledge():
"""Agent with knowledge uses embeddings for RAG."""
agent = Agent(
instructions="You are a helpful assistant with knowledge about AI.",
knowledge=["AI agents can use tools to accomplish tasks."],
knowledge_config={
"embedder": {
"provider": "openai",
"config": {"model": "text-embedding-3-small"}
}
}
)
# The agent uses embeddings internally for knowledge retrieval
response = agent.chat("What can AI agents do?")
print(f"Agent response: {response}")
return agent
# =============================================================================
# Example 3: Agent with Memory (uses embeddings internally)
# =============================================================================
def example_agent_with_memory():
"""Agent with memory uses embeddings for semantic search."""
agent = Agent(
instructions="You are a helpful assistant that remembers conversations.",
memory=True,
memory_config={
"embedding_model": "text-embedding-3-small"
}
)
# The agent uses embeddings internally for memory storage/retrieval
agent.chat("My name is Alice and I love Python programming.")
response = agent.chat("What do I love?")
print(f"Agent remembered: {response}")
return agent
# =============================================================================
# Example 4: Custom Embedding for Similarity Search
# =============================================================================
def example_similarity_search():
"""Use embeddings for custom similarity search."""
import math
def cosine_similarity(a, b):
dot = sum(x * y for x, y in zip(a, b))
norm_a = math.sqrt(sum(x * x for x in a))
norm_b = math.sqrt(sum(x * x for x in b))
return dot / (norm_a * norm_b) if norm_a and norm_b else 0
# Embed documents
documents = [
"Python is a programming language",
"JavaScript runs in browsers",
"AI agents can automate tasks"
]
doc_embeddings = embedding(documents)
# Embed query
query = "What language is used for web development?"
query_embedding = embedding(query)
# Find most similar document
similarities = [
cosine_similarity(query_embedding.embeddings[0], doc_emb)
for doc_emb in doc_embeddings.embeddings
]
best_idx = similarities.index(max(similarities))
print(f"Most similar document: {documents[best_idx]}")
print(f"Similarity score: {similarities[best_idx]:.4f}")
return similarities
if __name__ == "__main__":
print("=" * 60)
print("Example 1: Direct Embedding API")
print("=" * 60)
example_direct_embedding()
print("\n" + "=" * 60)
print("Example 4: Custom Similarity Search")
print("=" * 60)
example_similarity_search()
# Uncomment to run agent examples (requires API key)
# print("\n" + "=" * 60)
# print("Example 2: Agent with Knowledge")
# print("=" * 60)
# example_agent_with_knowledge()
# print("\n" + "=" * 60)
# print("Example 3: Agent with Memory")
# print("=" * 60)
# example_agent_with_memory()
+2 -2
View File
@@ -24,7 +24,7 @@ if has_api_key:
input_text="What is 2 + 2?",
expected_output="4",
num_iterations=3, # Run 3 times for statistical significance
verbose=True
output="verbose"
)
# Run evaluation
@@ -42,7 +42,7 @@ else:
input_text="What is 2 + 2?",
expected_output="4",
num_iterations=1,
verbose=True
output="verbose"
)
# Test with mock output
+2 -2
View File
@@ -27,7 +27,7 @@ if has_api_key:
scoring_type="numeric", # Score 1-10
threshold=7.0, # Pass if score >= 7
num_iterations=2,
verbose=True
output="verbose"
)
# Run evaluation
@@ -45,7 +45,7 @@ if has_api_key:
agent=agent,
input_text="Tell me a joke",
scoring_type="binary", # Pass or Fail
verbose=True
output="verbose"
)
binary_result = binary_evaluator.run(print_summary=True)
+1 -1
View File
@@ -26,7 +26,7 @@ if has_api_key:
num_iterations=10, # Run 10 benchmark iterations
warmup_runs=2, # 2 warmup runs before measurement
track_memory=True, # Track memory usage
verbose=True
output="verbose"
)
# Run evaluation
+4 -15
View File
@@ -16,19 +16,8 @@ def search_web(query: str) -> str:
def calculate(expression: str) -> str:
"""Calculate a math expression safely."""
import ast, operator
_OPS = {ast.Add: operator.add, ast.Sub: operator.sub, ast.Mult: operator.mul,
ast.Div: operator.truediv, ast.FloorDiv: operator.floordiv,
ast.Mod: operator.mod, ast.Pow: operator.pow,
ast.USub: operator.neg, ast.UAdd: operator.pos}
def _ev(n):
if isinstance(n, ast.Expression): return _ev(n.body)
if isinstance(n, ast.Constant) and isinstance(n.value, (int, float)): return n.value
if isinstance(n, ast.UnaryOp) and type(n.op) in _OPS: return _OPS[type(n.op)](_ev(n.operand))
if isinstance(n, ast.BinOp) and type(n.op) in _OPS: return _OPS[type(n.op)](_ev(n.left), _ev(n.right))
raise ValueError(f"Unsupported: {ast.dump(n)}")
return str(_ev(ast.parse(expression, mode="eval")))
"""Calculate a math expression."""
return str(eval(expression))
# Check if we have an API key
@@ -48,7 +37,7 @@ if has_api_key:
input_text="Search for the weather in Paris and calculate 25 * 4",
expected_tools=["search_web", "calculate"], # Tools that should be called
forbidden_tools=["delete_file"], # Tools that should NOT be called
verbose=True
output="verbose"
)
# Run evaluation
@@ -70,7 +59,7 @@ evaluator = ReliabilityEvaluator(
agent=mock_agent,
expected_tools=["search_web", "calculate"], # Tools that should be called
forbidden_tools=["delete_file"], # Tools that should NOT be called
verbose=True
output="verbose"
)
result2 = evaluator.evaluate_tool_calls(
+4 -4
View File
@@ -4,7 +4,7 @@ Fixed example demonstrating proper guardrail usage with PraisonAI Agents.
This addresses the issues reported in issue #875.
"""
from praisonaiagents import Agent, Task, GuardrailResult, AgentTeam, TaskOutput
from praisonaiagents import Agent, Task, GuardrailResult, Agents, TaskOutput
from typing import Tuple, Any
import trafilatura
@@ -103,7 +103,7 @@ task_with_llm_guardrail = Task(
# Run with GuardrailResult example
print("=== Running with GuardrailResult guardrail ===")
agents_gr = AgentTeam(
agents_gr = Agents(
agents=[agent],
tasks=[task_with_guardrailresult]
)
@@ -113,7 +113,7 @@ agents_gr = AgentTeam(
# Run with Tuple example
print("\n=== Running with Tuple[bool, Any] guardrail ===")
agents_tuple = AgentTeam(
agents_tuple = Agents(
agents=[agent],
tasks=[task_with_tuple]
)
@@ -123,7 +123,7 @@ agents_tuple = AgentTeam(
# Run with LLM guardrail example
print("\n=== Running with LLM-based guardrail ===")
agents_llm = AgentTeam(
agents_llm = Agents(
agents=[agent],
tasks=[task_with_llm_guardrail]
)
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