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Amós e Souza Fernandes commited on
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Commit ajust ppo 4 e 5

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  1. agents/__pycache__/DeepPortfolioAgent.cpython-312.pyc +0 -0
  2. agents/__pycache__/custom_policies.cpython-312.pyc +0 -0
  3. agents/__pycache__/data_handler_multi_asset.cpython-312.pyc +0 -0
  4. agents/__pycache__/deep_portfolio.cpython-312.pyc +0 -0
  5. agents/__pycache__/deep_portfolio_torch.cpython-312.pyc +0 -0
  6. agents/__pycache__/portfolio_environment.cpython-312.pyc +0 -0
  7. agents/__pycache__/portfolio_features_extractor_torch.cpython-312.pyc +0 -0
  8. agents/ppo_deep_portfolio_tensorboard/PPO_3/events.out.tfevents.1750336135.verticalagent-X555LPB.200649.0 +2 -2
  9. agents/ppo_deep_portfolio_tensorboard/PPO_4/events.out.tfevents.1750378516.codespaces-72cb68.19798.0 +3 -0
  10. agents/ppo_deep_portfolio_tensorboard/PPO_5/events.out.tfevents.1750410414.codespaces-72cb68.3578.0 +3 -0
  11. agents/requirements.txt +21 -0
  12. agents/train_rl_portfolio_agent.py +9 -1
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agents/requirements.txt ADDED
@@ -0,0 +1,21 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ pandas
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+ numpy
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+ scikit-learn
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+ tensorflow
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+ streamlit
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+ matplotlib
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+ fastapi
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+ uvicorn
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+ httpx
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+ pydantic
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+ python-dotenv
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+ loguru
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+ # agno @ git+https://github.com/agno-agi/agno.git
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+ jinja2
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+ yfinance
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+ PyJWT
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+ transformers
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+ gymnasium
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+ tf-keras
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+ ccxt
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+ pandas_ta
agents/train_rl_portfolio_agent.py CHANGED
@@ -661,9 +661,17 @@ model_ppo = PPO(
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  print("Iniciando treinamento do agente PPO com rede customizada...")
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  model_ppo.learn(total_timesteps=1000000, progress_bar=True) # Comece com menos timesteps para teste (ex: 50k)
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- model_ppo.save("rl_models/ppo_custom_deep_portfolio_agent")
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  print("Modelo RL com política customizada treinado e salvo.")
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  #----------
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  print("Iniciando treinamento do agente PPO com rede customizada...")
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  model_ppo.learn(total_timesteps=1000000, progress_bar=True) # Comece com menos timesteps para teste (ex: 50k)
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+ model_ppo.save("app/model/ppo_custom_deep_portfolio_agent")
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  print("Modelo RL com política customizada treinado e salvo.")
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+ model_ppo.save("app/model/model3")
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+ print("Modelo RL com política customizada treinado e salvo.")
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+
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+ model_ppo.save("app/model/model2.h5")
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+ print("Modelo RL com política customizada treinado e salvo.")
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+
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+
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+
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  #----------
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