feat: add daily log rotation, llama health wait, factor auto-fixer, and README updates

- Add rdagent/log/daily_log.py: daily-rotating structured logs per command
  (fin_quant, strategies, evaluate, parallel) with loguru; all.log combined sink
- predix.py: route TeeWriter output to logs/YYYY-MM-DD/ instead of root dir;
  wrap quant() and evaluate() in daily_log.session() for start/stop/duration tracking
- rdagent/app/cli.py: fin_quant_cli waits for llama.cpp /health endpoint before
  starting pipeline (up to 300 s); daily_log integration for fin_quant,
  generate_strategies, eval_all, parallel commands
- scripts/predix_gen_strategies_real_bt.py: daily_log integration with
  per-strategy ACCEPTED/REJECTED entries and summary on completion
- rdagent/components/coder/factor_coder/auto_fixer.py: new module that patches
  common LLM-generated factor issues (min_periods, inf/NaN, groupby.transform,
  MultiIndex corrections)
- rdagent/components/coder/factor_coder/prompts.yaml: add critical rules for
  EURUSD 1-min intraday factors (min_periods, inf handling, groupby, date range)
- README.md: document --reasoning off and --n-gpu-layers 28 for llama-server;
  explain VRAM constraints when Ollama is running alongside llama.cpp
- .bandit.yml: suppress B615 (HuggingFace unsafe download) for RL benchmark files

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

rdagent/components/coder/factor_coder/prompts.yaml

@@ -46,9 +46,16 @@ evolving_strategy_factor_implementation_v1_system: |-
   1. The user might provide you the correct code to similar factors. Your should learn from these code to write the correct code.
   2. The user might provide you the failed former code and the corresponding feedback to the code. The feedback contains to the execution, the code and the factor value. You should analyze the feedback and try to correct the latest code.
   3. The user might provide you the suggestion to the latest fail code and some similar fail to correct pairs. Each pair contains the fail code with similar error and the corresponding corrected version code. You should learn from these suggestion to write the correct code.
-  
+
   Your must write your code based on your former latest attempt below which consists of your former code and code feedback, you should read the former attempt carefully and must not modify the right part of your former code.
 
+  CRITICAL RULES FOR EURUSD 1-MINUTE INTRADAY FACTORS:
+  - ALWAYS use `min_periods=N` where N equals the window size in rolling calculations (e.g., `.rolling(20, min_periods=20)`)
+  - ALWAYS handle infinite values after division: `.replace([np.inf, -np.inf], np.nan)` before saving results
+  - ALWAYS use `groupby(level=1)` or `groupby('instrument')` before rolling operations on MultiIndex dataframes
+  - Process the COMPLETE date range (2020-2026), do NOT filter by date
+  - Use `groupby().transform()` instead of `groupby().apply()` for single-column assignments
+
   Notice that you should not add any other text before or after the json format.
 
   {% if queried_former_failed_knowledge|length != 0 %}