5 Commits

Author	SHA1	Message	Date
TPTBusiness	108a63fd79	feat: Strategy Generator working with local LLM (P0-P4) ... Integrated strategy generation into fin_quant loop: - Fixed LLM code extraction from JSON responses - Fixed factor loading (MultiIndex parquet handling) - Fixed return calculation (realistic proxy) - Fixed max drawdown (NaN/inf handling) - Added llama.cpp --reasoning off support - Strategy orchestrator with LLM + evaluation - Optuna optimizer integration 100% acceptance rate on test run (2/2 strategies). Total changes: +2006 lines, -129 lines across 8 files. Co-authored-by: Qwen-Coder <qwen-coder@alibabacloud.com>	2026-04-09 12:55:04 +02:00
TPTBusiness	5ef1fd65db	fix: Use num_api_keys instead of len(api_keys) for round-robin ... - Fix API key index calculation to respect --api-keys parameter - Previously always used all available keys regardless of setting - Now correctly assigns only requested number of API keys Usage: python predix_parallel.py --runs 25 --api-keys 1 -m openrouter -> All 25 runs use API Key 1 only	2026-04-04 10:35:10 +02:00
TPTBusiness	56d73d22e9	feat: Support 25+ parallel runs with resource warnings ... - Allow up to 50 runs (25 recommended max) - Add --force flag to bypass warnings - Show RAM estimate for high run counts - Update CLI help text with max recommendation Usage: python predix_parallel.py --runs 25 -m openrouter python predix_parallel.py --runs 50 --force -m openrouter Tests: 103 passed	2026-04-04 10:29:50 +02:00
TPTBusiness	9ec6008ad8	fix: Fix parallel runner dashboard rendering error ... - Use Rich Group instead of string join for Table + Panel layout - Fix TypeError: sequence item 0: expected str instance, Table found - Live dashboard now renders correctly with parallel runs Tests still passing (103)	2026-04-04 10:04:49 +02:00
TPTBusiness	68ea969c32	feat: Add parallel run system with API key distribution ... - Add predix_parallel.py: Run multiple factor experiments concurrently * python predix_parallel.py --runs 5 --api-keys 2 -m openrouter * Round-robin API key distribution across available keys * Rich live dashboard with per-run status, elapsed time, exit codes * Graceful shutdown (Ctrl+C kills all children cleanly) - Add --run-id parameter to predix.py for isolated single runs * Separate log files: fin_quant_run{N}.log * Separate results: results/runs/run{N}/ * Separate workspace: RD-Agent_workspace_run{N}/ * Separate databases per run - Modify CoSTEER and FactorRunner for PARALLEL_RUN_ID isolation * _save_intermediate_results uses run-specific directories * _save_result_to_database and _write_run_log isolated per run * _ensure_results_dirs creates run-specific paths - Reduce max_loop from 10 to 3 for faster iterations - Add docs/parallel_runs.md with full documentation Tests: 103 passed	2026-04-04 09:39:12 +02:00