ahmet c471db80e1 feat(cli): add three-tier LLM provider setup with dynamic Ollama model listing ... - Add quick/mid/deep thinking tiers, each with independent provider selection - Fetch available Ollama models dynamically via /api/tags instead of hardcoded list - Add mid-thinking agent selection (select_mid_thinking_agent) - Support provider-specific thinking config (Gemini thinking level, OpenAI reasoning effort) - Update default_config and trading_graph to wire three-tier LLM setup Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>		2026-03-13 13:20:50 +01:00
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__init__.py	chore(release): v0.1.0 – initial public release of TradingAgents	2025-06-05 04:27:57 -07:00
conditional_logic.py	refactor: rename risky/safe agents to aggressive/conservative	2026-02-03 22:27:20 +00:00
propagation.py	feat: add footer statistics tracking with LangChain callbacks	2026-02-03 22:27:20 +00:00
reflection.py	chore(release): v0.1.0 – initial public release of TradingAgents	2025-06-05 04:27:57 -07:00
setup.py	feat(cli): add three-tier LLM provider setup with dynamic Ollama model listing	2026-03-13 13:20:50 +01:00
signal_processing.py	chore(release): v0.1.0 – initial public release of TradingAgents	2025-06-05 04:27:57 -07:00
trading_graph.py	feat(cli): add three-tier LLM provider setup with dynamic Ollama model listing	2026-03-13 13:20:50 +01:00