feat: Integrate tensortrade RL model into consensus engine

[laurentvv]

This PR integrates tensortrade and stable-baselines3 to introduce a new Reinforcement Learning (RL) model to the trading AI's hybrid consensus engine.

• Added src/tensortrade_model.py which wraps the TensorTrade framework to create a realistic trading environment compatible with Gym APIs and trains a quick PPO agent using stable-baselines3 to generate Buy/Sell/Hold actions with confidence probabilities.
• Updated src/enhanced_trading_example.py to trigger the TensorTrade prediction module and incorporate its insights into the consensus engine (model_predictions["tensortrade"]).
• Refactored src/enhanced_decision_engine.py to accept the TensorTrade inputs. The base weights logic was updated to gracefully re-distribute decisioning weight, allocating 10% to TensorTrade as requested by the user.
• Updated pyproject.toml to lock dependencies appropriately within the compatibility matrix (numpy==1.26.4 to prevent bugs with tensortrade, and setting correct bounds for stable-baselines3).
• Linted using ruff and ran standard unittest test coverage.

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PR created automatically by Jules for task 6788355586345579924 started by @laurentvv

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Code Review Summary

Status: No Issues Found | Recommendation: Merge

Files Reviewed (4 files)

• .agents/skills/alphaear-news/scripts/content_extractor.py
• .agents/skills/alphaear-news/scripts/database_manager.py
• .agents/skills/alphaear-news/scripts/news_tools.py
• .agents/skills/alphaear-news/tests/test_news.py

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_{Reviewed by step-3.5-flash · 295,968 tokens}