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TPTBusiness
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Connect all Predix components into unified trading system: INTEGRATION (ALL 295 TESTS PASS): - RL Trading connected with Protection Manager - RL Trading connected with Backtesting Engine - CLI command 'rdagent rl_trading' added (train/backtest/live modes) - Graceful fallback for users without stable-baselines3 OPEN SOURCE COMPATIBILITY: - System works WITHOUT stable-baselines3 (momentum fallback) - System works WITHOUT local models/prompts (uses standard) - Clear warning messages when optional deps missing - GitHub users get FULLY WORKING system CLOSED SOURCE PROTECTION: - models/local/, prompts/local/, .env stay local only - .gitignore properly configured - Our alpha (best models/prompts) remains private DOCUMENTATION: - QWEN.md: Open/closed source strategy - QWEN.md: Development guidelines for AI assistant - QWEN.md: Open source compatibility principle - README.md: RL Trading CLI commands and examples - requirements/rl.txt: Optional RL dependencies Modified files: - rdagent/app/cli.py: Added rl_trading command - rdagent/components/backtesting/backtest_engine.py: RL backtest support - rdagent/components/coder/rl/costeer.py: Protection Manager integration - rdagent/components/coder/rl/__init__.py: Conditional imports + fallback - rdagent/components/coder/rl/fallback.py: NEW - Simple momentum fallback - requirements.txt: Optional RL deps commented - requirements/rl.txt: NEW - Full RL dependencies - test/integration/test_all_features.py: 7 new integration tests - QWEN.md: Open source strategy + development guidelines - README.md: RL Trading documentation 295 tests pass: 67 integration + 89 RL + 139 backtesting
96 lines
1.5 KiB
Plaintext
96 lines
1.5 KiB
Plaintext
# Requirements for runtime.
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pydantic-settings
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python-Levenshtein
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scikit-learn
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filelock
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loguru
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fire
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fuzzywuzzy
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openai
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litellm>=1.73 # to support `from litellm import get_valid_models`
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azure.identity
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pyarrow
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rich
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tqdm
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typer
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numpy # we use numpy as default data format. So we have to install numpy
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pandas # we use pandas as default data format. So we have to install pandas
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pandarallel # parallelize pandas
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matplotlib
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langchain
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langchain-community
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tiktoken
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pymupdf # Extract shotsreens from pdf
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# PDF related
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pypdf
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azure-ai-formrecognizer
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# factor implementations
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tables
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# CI Fix Tool
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tree-sitter-python
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tree-sitter
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python-dotenv
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# infrastructure related.
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docker
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# crawler related
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webdriver-manager
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# demo related
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streamlit>=1.47 # to support input_c.text_area(..., height="content", ...)
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plotly
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st-theme
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randomname
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flask
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flask-cors
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networkx
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# kaggle crawler
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selenium
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kaggle
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nbformat # also used for notebook conversion
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# tool
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setuptools-scm
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seaborn
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azure.ai.inference
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# data folder desc
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humanize
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genson
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# mlflow
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mlflow
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azureml-mlflow
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types-pytz
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# Agent
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pydantic-ai-slim[mcp,openai,prefect]
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nest-asyncio
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# visualize SFT train
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tensorboard # tensorboard --logdir git_ignore_folder/RD-Agent_workspace
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prefect
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# HuggingFace datasets
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datasets
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# DuckDuckGo search
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duckduckgo-search
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# Testing
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pytest
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pytest-cov
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# RL Trading (optional - system works without these)
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# Install for full RL training: pip install stable-baselines3[extra] gymnasium
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# Without these, RL trading uses simple momentum fallback
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# stable-baselines3[extra]>=2.0.0
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# gymnasium>=0.29.0 |