Replace sequential predict() calls with predict_batch() in both
build_kronos_factor and evaluate_kronos_model. Up to batch_size windows
are processed simultaneously on GPU, reducing per-window time from ~10s
to ~0.13s (measured: 10 windows in 1.3s on RTX 5060 Ti).
Adds --batch-size / -b option (default 32) to both kronos-factor and
kronos-eval CLI commands. Falls back to single inference per window if
a batch fails. Refactors timestamp preparation into _build_window_inputs.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- Add vbt_backtest.py as single source of truth for all metric formulas
(Sharpe, drawdown, IC, transaction costs) — backtest_engine.py and
strategy_orchestrator.py now delegate to it
- Add LLMUnavailableError to exception.py; rd_loop.py catches it at the
proposal stage and raises LoopResumeError to avoid corrupting trace
history with None hypotheses
- Guard record() against None exp/hypothesis so loop resets leave
trace.hist in a consistent state
- Refactor strategy_orchestrator and optuna_optimizer to use unified
backtest path; remove duplicate metric calculation code
- Add predix_rebacktest_unified.py script for offline re-evaluation
- Update tests and README
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Added beautiful CLI dashboard screenshot showing:
- System status (factors, strategies, security)
- Available commands
- Quick start guide
Renamed from German filename to cli-welcome-screen.png
Implement automatic trading protection system to prevent excessive losses:
PROTECTIONS (100% original code, NOT copied from Freqtrade):
- Max Drawdown Protection: Blocks trading when DD > 15% (configurable)
- Cooldown Period: 4h mandatory rest after 5% loss
- Stoploss Guard: Detects stoploss clusters (>5 per day)
- Low Performance Filter: Filters factors with Sharpe < 0.5, Win Rate < 40%
ARCHITECTURE:
- Base protection interface with common utilities
- 4 specialized protection implementations
- ProtectionManager orchestrates all active protections
- Time-based blocking with automatic expiry
TESTS (32 total, ALL PASS):
- 25 unit tests in test/backtesting/test_protections.py
- 7 integration tests in test/integration/test_all_features.py
- Tests cover: normal operation, edge cases, error handling
DOCUMENTATION:
- Update QWEN.md with development guidelines for AI assistant
* Mandatory rules: Update QWEN.md, README, requirements.txt, tests
* Pre-commit checklist
* Example workflow
- Update README.md with protection system features
- Update project structure with new modules
All code is 100% original - NO license issues with Freqtrade GPLv3.
- Created ATTRIBUTION.md explaining MIT License requirements
- Added attribution requirements to README.md
- Clarifies what users must do when using this code:
* Keep MIT License text
* Keep copyright notice
* Provide attribution to original project
- Includes examples of good and bad attribution
- Explains legal basis and consequences of violations
- Adds License badge to README header
Co-authored-by: Qwen-Coder <qwen-coder@alibabacloud.com>
- Removed 'Inspiriert von' comments from all source files
- Added comprehensive Acknowledgments section to README.md
- Credits to:
* Microsoft RD-Agent (MIT) - R&D framework foundation
* TradingAgents (Apache 2.0) - Multi-agent patterns
* ai-hedge-fund - Macro analysis and risk management concepts
- Clarified that all code is originally written and implemented independently
- Ensures license compliance (MIT, Apache 2.0 compatible)
Co-authored-by: Qwen-Coder <qwen-coder@alibabacloud.com>
- Added acknowledgment section crediting Microsoft RD-Agent
- Link to original project: https://github.com/microsoft/RD-Agent
- Clarifies that Predix extends RD-Agent with forex-specific features
* update rdagent cmd
* fix log error message
* use multiProcessing.Process instead of subprocess.Popen
* add traces to gitignore
* add user interactor in RDLoop (finance scenarios)
* add interactor (feedback, hypothesis) for quant scens
* fix the test_end in qlib conf
* add features init config, general instruction to qlib scenarios
* set base features for based exp
* fix bug when combine factors
* move traces folder to git_ignore_folder
* fix bug in features init
* fix quant interact bug
* fix logger warning error
* bug fixes
* modify rdagent logger, now it can set file output
* adjust cli functions and fix logger bug
* fix server port transport problem
* update server_ui in cli
* add web code
* fix CI problem
* black fix
* update web ui README
* update README
* update readme
* update data science docs part1
* update data science docs part2
* update data science docs part3
* update data science docs part4
* update data science docs part5
* format with isort
* update data science docs part6
* add check environment scripts
* format with isort
* format with isort
* merge env_check to health_check
* format with isort
* format with black
* optimize code
* use boolean cli options
* replace fire with typer
* replace fire with typer
* optimizing parameter and variable naming
* docs: update explanation for separate config use in litellm
* docs: update default backend to `rdagent.oai.backend.LiteLLMAPIBackend`
* docs: update .rst format
* Update installation_and_configuration.rst
* docs: add MLE-bench details to README
* docs: update README with revised MLE-bench description and leaderboard
* docs: update RD-Agent text and add trial info in README
* Update README.md
* Update README.md
* update by M
* update format
* Add documents
* docs: update RD-Agent references to R&D-Agent
* docs: update README with MLE-Bench complexity level details
TPTBusiness