NexQuant

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Commit Graph

Author	SHA1	Message	Date
TPTBusiness	95b14fcfc8	chore(logging): size-based rotation and cap LLM call content - Switch log rotation from midnight-only ("00:00") to size-based: per-command logs: 50 MB, all.log: 100 MB (with gz compression) - Shorten retention from 30/60 days to 7 days - Cap llm_calls.jsonl entries to 500 chars per field to prevent GB-scale files from long-running loops Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>	2026-04-30 07:19:27 +02:00
TPTBusiness	f24f678713	feat(logging): write complete LLM prompts and responses to daily JSONL log Add log_llm_call() to daily_log.py that appends every LLM interaction (system prompt, user prompt, response, duration_ms) as a JSON object to logs/YYYY-MM-DD/llm_calls.jsonl. Call it from both chat completion paths in base.py so all LLM activity — factor generation, strategy generation, feedback, proposals — is captured in a human-readable, grep/jq-friendly format alongside the existing binary pickle logs. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>	2026-04-17 21:46:28 +02:00
TPTBusiness	2cec08bc91	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>	2026-04-16 07:20:08 +02:00

Author

SHA1

Message

Date

TPTBusiness

95b14fcfc8

chore(logging): size-based rotation and cap LLM call content

- Switch log rotation from midnight-only ("00:00") to size-based:
  per-command logs: 50 MB, all.log: 100 MB (with gz compression)
- Shorten retention from 30/60 days to 7 days
- Cap llm_calls.jsonl entries to 500 chars per field to prevent
  GB-scale files from long-running loops

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

2026-04-30 07:19:27 +02:00

TPTBusiness

f24f678713

feat(logging): write complete LLM prompts and responses to daily JSONL log

Add log_llm_call() to daily_log.py that appends every LLM interaction
(system prompt, user prompt, response, duration_ms) as a JSON object to
logs/YYYY-MM-DD/llm_calls.jsonl. Call it from both chat completion paths
in base.py so all LLM activity — factor generation, strategy generation,
feedback, proposals — is captured in a human-readable, grep/jq-friendly
format alongside the existing binary pickle logs.

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

2026-04-17 21:46:28 +02:00

TPTBusiness

2cec08bc91

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>

2026-04-16 07:20:08 +02:00

3 Commits