Commit Graph

33 Commits

Author SHA1 Message Date
TPTBusiness 4eeb724ac5 fix: resolve dead code, shell injection risk, mutable defaults, and other bugs
- strategy_orchestrator.py: remove unreachable dead 'if not factor_values' after early return
- strategy_orchestrator.py: eliminate duplicate OHLVC load in evaluate_strategy
- env.py: escape single-quotes in Docker entry to prevent shell injection (CWE-78)
- env.py: replace mutable default args with None pattern in DockerEnv subclasses
- factor_runner.py: move pandarallel.initialize() from import-time to lazy init
2026-05-02 23:21:38 +02:00
TPTBusiness 5a5bf4d771 fix(qlib): correct indentation in except blocks in quant_proposal and factor_runner
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-04-30 13:30:49 +02:00
TPTBusiness 90a6999563 fix(security): real fix for B404/B603 (sys.executable in factor_runner.py #745) 2026-04-29 22:42:28 +02:00
TPTBusiness 018231d1f2 fix(security): real fix for B110 (logging in factor_runner.py #744) 2026-04-29 21:23:46 +02:00
TPTBusiness d2037a475a fix(loop): compress old experiment history in proposal prompt to reduce context size
- Summarize all but the 2 most recent experiments to compact bullet lines
  (factor name, PASS/FAIL, IC value, 120-char observation snippet) instead
  of including full verbatim traces; reduces prompt from ~121k to ~40-60k tokens
- Fix _evaluate_factor_directly and _save_factor_values to look for result.h5
  and factor.py in sub_workspace_list instead of experiment_workspace
- Fix Series.to_parquet() → Series.to_frame().to_parquet() in _save_factor_values
- Update factor_data_template README: correct bars-per-day (1440, not 96)
- Update prompts to accept 2024-only debug dataset output as valid factor result
- Fix factor_coder prompts: allow 2024 debug data in date-range instruction

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-04-25 09:10:39 +02:00
TPTBusiness 78fb607dbe fix(factors): detect and correct look-ahead bias in daily-constant factors
Daily factors (e.g. daily_log_return) carried same-day close data at 00:00,
giving the model end-of-day information at bar open — a classic look-ahead bias
that produced spurious IC=0.25 and Sharpe=24 with 98% win rate.

Changes:
- factor_runner.py: add _shift_daily_constant_factor_if_needed() that detects
  factors where >90% of days have a single unique intraday value, then shifts
  them by 1 trading day before IC computation
- prompts.yaml: add rule #7 instructing LLM to always shift(1) daily aggregates
  before forward-filling to minute bars

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-04-24 09:34:06 +02:00
TPTBusiness a8c23bd130 feat: Add AI Strategy Builder (StrategyCoSTEER) - Closed Source
Open Source Changes:
- Add prompt loader functions for strategy prompts
- Add factor values persistence (parquet) in factor_runner.py
- Add CLI command: predix build-strategies-ai
- Integrate strategy building into QuantRDLoop (every 50 factors)
- Add StrategyBuilder design documentation

Closed Source Files (NOT committed, in local/):
- strategy_coster.py - Main CoSTEER loop for strategies
- strategy_evaluator.py - Walk-forward backtesting
- strategy_runner.py - Strategy execution
- strategy_discovery_v1.yaml - LLM prompts

Usage:
  predix build-strategies-ai              # Build from top 50 factors
  predix build-strategies-ai -t 100       # Use top 100 factors
  predix build-strategies-ai -l 10        # 10 improvement loops

The system:
1. Loads top factors with time-series values
2. LLM generates strategy hypotheses
3. LLM writes strategy code (entry/exit rules)
4. Backtests strategy with walk-forward validation
5. LLM gets feedback and improves
6. Repeats until profitable strategy found
2026-04-05 19:30:12 +02:00
TPTBusiness 6a1c4760c9 fix: Handle Qlib Docker backtest failures gracefully (SECURITY FIX)
- Add _evaluate_factor_directly() to factor_runner.py
- When Qlib Docker returns None, try direct evaluation from result.h5
- Compute IC/Sharpe directly from factor values + forward returns
- Loop continues instead of hanging on Docker failures
- Fix MD5 security warning: usedforsecurity=False in cache_manager.py

Files changed:
- rdagent/scenarios/qlib/developer/factor_runner.py
- rdagent/app/qlib_rd_loop/quant.py
- rdagent/scenarios/qlib/local/cache_manager.py
2026-04-05 09:21:33 +02:00
TPTBusiness c049742df7 feat: Integrate factor code/description saving into fin_quant process
- Modify factor_runner.py to save factor_code and factor_description
- Add _extract_factor_info() method to extract code from experiment
- Update _save_factor_json() to include code and description
- Now every backtest automatically saves to results/factors/ with:
  * Full factor implementation code
  * Extracted description (docstring or comments)
  * IC, Sharpe, Win Rate, Max Drawdown metrics

This means the normal trading loop (rdagent fin_quant) now automatically
saves complete factor information to results/factors/ - same format as
predix_full_eval.py.
2026-04-04 22:27:14 +02:00
TPTBusiness 25865f9c77 fix: Add missing os import in factor_runner.py
- Fix NameError: name 'os' is not defined
- This caused all 23 parallel runs to fail
- _ensure_results_dirs() uses os functions but import was missing

Tests should still pass
2026-04-04 11:26:39 +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
TPTBusiness 7e7e40b041 feat: Fix 1min data integration and centralize all prompts
- Fix daily/1min contradiction in factor_experiment_loader prompts
- Rename daily_pv.h5 to intraday_pv.h5 (generate.py, utils.py, README)
- Fix FactorDatetimeDailyEvaluator to accept 1min bars as correct
- Add _write_run_log() to log every factor attempt to results/logs/
- Add _ensure_results_dirs() to create all result directories
- Extract all 44 prompt YAML files to prompts/ centralized directory
- Add prompts/INDEX.md for navigation

Tests: 93 passed
2026-04-04 08:20:58 +02:00
TPTBusiness 574a9cb75e fix: Resolve 88% empty backtest results + path fixes
Root Cause: Qlib configs used cn_data (Chinese stocks) instead of eurusd
- provider_uri: cn_data → eurusd_1min_data
- market: csi300 → eurusd
- topk: 50 → 1 (single-asset EURUSD, was opening 0 positions)
- n_drop: 5 → 0, limit_threshold: 0.095 → 0.0

Add failed run tracking and validation:
- factor_runner.py: Validate results before DB save, track failed runs
- model_runner.py: Same validation and tracking
- results_db.py: generate_results_summary() → RESULTS_SUMMARY.md
- extract_results.py: Failed run tracking, progress indicators

Fix project root paths in all modules:
- ResultsDatabase: correct path from rdagent/results/ → results/
- factor_runner: db, factors, failed_runs paths
- model_runner: failed_runs path

All 246 tests passing.
2026-04-03 16:21:59 +02:00
TPTBusiness 612ed8a802 fix: Ensure backtest results save to DB and JSON files
- Remove duplicate DB save from quant.py (keep only in factor_runner)
- Add explicit DB path creation with mkdir -p
- Add JSON factor summaries to results/factors/
- Add debug logging for result structure
- Fix logger.debug -> logger.info (RDAgentLog compatibility)
- Update tests to match new architecture (240/240 passing)
- Enhance extract_results.py with progress indicators
2026-04-03 15:46:52 +02:00
TPTBusiness 633b5639de fix: Add nosec comments for schema migration SQL in results_db.py
Bandit false positive B608: Schema migration uses controlled column names,
not user input. Add nosec comments to suppress warning.
2026-04-03 14:37:22 +02:00
TPTBusiness 74d5a8234e feat: Integrate critical features into fin_quant workflow (P0+P1)
Connect Protection Manager, Results Database, model_loader, and Technical
Indicators to the main fin_quant trading loop.

P0 - CRITICAL INTEGRATIONS:

1. PROTECTION MANAGER in factor_runner.py
   - Automatic protection check after every backtest
   - Factors with >15% drawdown are rejected
   - Cooldown, stoploss guard, low performance filters active
   - Error handling: workflow continues if protection fails

2. RESULTS DATABASE in quant.py
   - Auto-save experiment results to SQLite after each loop
   - Stores: IC, Sharpe, Max DD, Annualized Return, Win Rate
   - Queryable via ResultsDatabase API
   - Error handling: warning logged, workflow continues

P1 - IMPORTANT INTEGRATIONS:

3. MODEL LOADER in model_coder.py
   - Loads models/local/ as baseline reference for LLM
   - Transformer, TCN, PatchTST, CNN+LSTM now used as starting point
   - LLM can improve upon existing models instead of from scratch

4. TECHNICAL INDICATORS in factor_coder.py
   - RSI, MACD, Bollinger Bands, CCI, ATR available to LLM
   - Import paths and usage examples in prompts
   - Better factor generation with professional indicators

TESTS (32 new, ALL PASS):
- 23 integration tests in test/qlib/test_fin_quant_integration.py
- 9 enhanced integration tests in test/integration/test_all_features.py
- All 183 tests pass (122 backtesting + 29 qlib + 32 new)

Modified files:
- rdagent/app/qlib_rd_loop/quant.py: Results Database integration
- rdagent/scenarios/qlib/developer/factor_runner.py: Protection Manager
- rdagent/scenarios/qlib/developer/model_coder.py: model_loader baseline
- rdagent/scenarios/qlib/developer/factor_coder.py: Technical indicators
- test/qlib/test_fin_quant_integration.py: NEW - 23 integration tests
- test/integration/test_all_features.py: 9 enhanced tests
2026-04-03 14:10:44 +02:00
XianBW 14395488b9 feat: add a web UI server (#1345)
* update rdagent cmd

* fix log error message

* use multiProcessing.Process instead of subprocess.Popen

* add traces to gitignore

* add user interactor in RDLoop (finance scenarios)

* add interactor (feedback, hypothesis) for quant scens

* fix the test_end in qlib conf

* add features init config, general instruction to qlib scenarios

* set base features for based exp

* fix bug when combine factors

* move traces folder to git_ignore_folder

* fix bug in features init

* fix quant interact bug

* fix logger warning error

* bug fixes

* modify rdagent logger, now it can set file output

* adjust cli functions and fix logger bug

* fix server port transport problem

* update server_ui in cli

* add web code

* fix CI problem

* black fix

* update web ui README

* update README

* update readme
2026-03-18 14:04:52 +08:00
Linlang 3dbd703828 fix: prevent calendar index overflow when signal data ends early (#1324)
* fix: prevent calendar index overflow when signal data ends early

* fix: make test_end optional to resolve Qlib backtest calendar misalignment

* fix: enhance GPU information output in get_gpu_info function

* fix: improve GPU information output in get_gpu_info function for better clarity

---------

Co-authored-by: Xu Yang <peteryang@vip.qq.com>
2026-01-13 14:41:35 +08:00
Linlang 19dbeb93e9 refactor: unify qlib experiment configs, runners, and templates (#1320)
* refactor: unify qlib experiment configs, runners, and templates

* fix: use PropSetting instances instead of class attributes in qlib runners

* docs: add configurable train/valid/test time segments for fintech scenarios
2026-01-07 12:49:15 +08:00
Yuante Li 7134a51afa fix: fix some bugs in RD-Agent(Q) (#1143)
* fix some bugs in RD-Agent(Q)

* fix factor from report

* fix ci
2025-08-01 13:20:09 +08:00
Yuante Li 4b838d3f45 refactor: refactor RD-Agent(Q) configuration files (#972)
* refactor rdagent(q) conf files

* fix

* fix ci
2025-06-18 12:28:29 +08:00
Yuante Li d1019cb568 feat: add RD-Agent-Quant scenario (#838)
* fix model input shape bug and costeer_model bug

* fix a bug

* fix a bug in docker result extraction

* a system-level optimization

* add a filter of stdout

* update

* add stdout to model

* model training_hyperparameters update

* quant scenario

* update some quant settings

* llm choose action

* Thompson Sampling Bandit for action choosing

* refine both scens

* add trace messages for quant scen

* fix some bugs

* fix some bugs

* update

* update

* update

* fix

* fix

* fix

* update for merge

* fix ci

* fix some bugs

* fix ci

* fix ci

* fix ci

* fix ci

* refactor

* default qlib4rdagent local env downloading

* fix ci

* fix ci

* fix a bug

* fix ci

* fix: align all prompts on template (#908)

* use template to render all prompts

* fix CI

---------

Co-authored-by: Xu Yang <xuyang1@microsoft.com>

* add fin_quant in cli

* fix a bug

* fix ci

* fix some bugs

* refactor

* remove the columns in hypothesis if no value generated in this column

* fix a bug

* fix ci

* fix conda env

* add qlib gitignore

* remove existed qlib folder & install torch in qlib conda

* fix workspace ui in feedback

* align model config in coder and runner in docker or conda

* fix CI

* fix CI

---------

Co-authored-by: Xu Yang <peteryang@vip.qq.com>
Co-authored-by: Xu Yang <xuyang1@microsoft.com>
2025-05-29 16:16:51 +08:00
Linlang c263ece07c fix: fix combined_factors_df.pkl not loading in docker (#697)
* Fix combined_factors_df.pkl not loading in docker

* change combined factors file type

* change qlib commit id
2025-03-18 18:36:21 +08:00
you-n-g 5baed909e7 refactor: refactor core framework to better propogate feedbacks (#599)
* refactor: Update type annotations and remove unused class in evolving modules

* refactor: Simplify evolving agent and feedback handling in CoSTEER module

* lint & CI

* mypy

* ruff for core

* mypy

* refactor: remove unnecessary comments and update feedback handling logic

* refactor: Add prev_task_feedback parameter to evolving strategies

* feat: Clear folder before extracting zip file in DockerEnv

* fix: Correct retrieval of last experiment from history
2025-02-16 01:40:44 +08:00
Xu Yang a1865dd6d5 Update factor_runner.py to ignore failed implementation (#514) 2025-01-02 23:29:52 +08:00
Xu Yang 768229427d feat: use unified pickle cacher & move llm config into a isolated config (#424)
* simplify RDAgent conf

* add unified cacher(untested)

* fix small bugs

* fix a bug

* fix a small bug in runner

* use hash_key = None to skip cache

* fix CI

* in factor execution, ignore cache when raise exception

* add file locker to avoid mp calling

* fix CI

* use function __module__ name as folder in cache
2024-10-14 17:34:09 +08:00
Xu Yang 4eca5fd8c0 use mp to execute all feature and fix a small bug in config (#157) 2024-08-03 10:17:01 +08:00
WinstonLiyt 317ad89599 fix: fix some small bugs in report-factor loop (#152)
* Init todo

* update all code

* update

* Extract factors from financial reports loop finished

* Fix two small bugs.

* Delete rdagent/app/qlib_rd_loop/run_script.sh

* Minor mod

* Delete rdagent/app/qlib_rd_loop/nohup.out

* Fix a small bug in file reading.

* some updates

* Update the detailed process and prompt of factor loop.

* Evaluation & dataset

* Optimize the prompt for generating hypotheses and feedback in the factor loop.

* Generate new data

* dataset generation

* Performed further optimizations on the factor loop and report extraction loop, added log handling for both processes, and implemented a screenshot feature for report extraction.

* Update rdagent/components/coder/factor_coder/CoSTEER/evaluators.py

* Update package.txt for fitz.

* add the result

* Performed further optimizations on the factor loop and report extraction loop, added log handling for both processes, and implemented a screenshot feature for report extraction. (#100) (#102)

- Performed further optimizations on the factor loop and report extraction loop.
- Added log handling for both processes.
- Implemented a screenshot feature for report extraction.

* Analysis

* Optimized log output.

* Factor update

* A draft of the "Quick Start" section for README

* Add scenario descriptions.

* Updates

* Adjust content

* Enable logging of backtesting in Qlib and store rich-text descriptions in Trace. Support one-step debugging for factor extraction.

* Reformat analysis.py

* CI fix

* Refactor

* remove useless code

* fix bugs (#111)

* Fix two small bugs.

* Fix a merge bug.

* Fix two small bugs.

* fix some bugs.

* Fix some format bugs.

* Restore a file.

* Fix a format bug.

* draft renew of evaluators

* fix a small bug.

* fix a small bug

* Support Factor Report Loop

* Update framework for extracting factors from research reports.

* Refactor report-based factor extraction and fix minor bugs.

* fix a small bug of log.

* change some prompts

* improve factor_runner

* fix a small bug

* change some prompts

* cancel some comments

* cancel some comments and fix some bugs

* fix some bugs in factor from reports loop

---------

Co-authored-by: Young <afe.young@gmail.com>
Co-authored-by: you-n-g <you-n-g@users.noreply.github.com>
Co-authored-by: Taozhi Wang <taozhi.mark.wang@gmail.com>
Co-authored-by: Suhan Cui <51844791+SH-Src@users.noreply.github.com>
2024-08-02 17:14:12 +08:00
WinstonLiyt c6bf4e5015 fix: Comprehensive update to factor extraction. (#143)
* Init todo

* update all code

* update

* Extract factors from financial reports loop finished

* Fix two small bugs.

* Delete rdagent/app/qlib_rd_loop/run_script.sh

* Minor mod

* Delete rdagent/app/qlib_rd_loop/nohup.out

* Fix a small bug in file reading.

* some updates

* Update the detailed process and prompt of factor loop.

* Evaluation & dataset

* Optimize the prompt for generating hypotheses and feedback in the factor loop.

* Generate new data

* dataset generation

* Performed further optimizations on the factor loop and report extraction loop, added log handling for both processes, and implemented a screenshot feature for report extraction.

* Update rdagent/components/coder/factor_coder/CoSTEER/evaluators.py

* Update package.txt for fitz.

* add the result

* Performed further optimizations on the factor loop and report extraction loop, added log handling for both processes, and implemented a screenshot feature for report extraction. (#100) (#102)

- Performed further optimizations on the factor loop and report extraction loop.
- Added log handling for both processes.
- Implemented a screenshot feature for report extraction.

* Analysis

* Optimized log output.

* Factor update

* A draft of the "Quick Start" section for README

* Add scenario descriptions.

* Updates

* Adjust content

* Enable logging of backtesting in Qlib and store rich-text descriptions in Trace. Support one-step debugging for factor extraction.

* Reformat analysis.py

* CI fix

* Refactor

* remove useless code

* fix bugs (#111)

* Fix two small bugs.

* Fix a merge bug.

* Fix two small bugs.

* fix some bugs.

* Fix some format bugs.

* Restore a file.

* Fix a format bug.

* draft renew of evaluators

* fix a small bug.

* fix a small bug

* Support Factor Report Loop

* Update framework for extracting factors from research reports.

* Refactor report-based factor extraction and fix minor bugs.

* fix a small bug of log.

* change some prompts

* improve factor_runner

* fix a small bug

* change some prompts

* cancel some comments

* cancel some comments and fix some bugs

---------

Co-authored-by: Young <afe.young@gmail.com>
Co-authored-by: you-n-g <you-n-g@users.noreply.github.com>
Co-authored-by: Taozhi Wang <taozhi.mark.wang@gmail.com>
Co-authored-by: Suhan Cui <51844791+SH-Src@users.noreply.github.com>
2024-08-02 15:04:49 +08:00
Xu Yang 060f569720 feat: filter feature which is high correlation to former implemented features (#145)
* filter feature which is high correlation to former implemented features

* use multiprocessing to calculate IC and some minor fix
2024-08-02 14:41:17 +08:00
WinstonLiyt c17244a317 Extract factors from financial reports loop finished. (#90)
- Extract factors from financial reports loop finished.

- Fix some small bugs.
2024-07-20 12:31:40 +08:00
Linlang 276b462f40 Fix ruff error1 (#81)
* fix_ruff_error1

* fix_ruff_error

* fix ruff error

* fix ruff error

* pass model.py

* rename exception class

* rename exception class

* rename func name generate_feedback

* remove prepare args

* optimize code

* optimize code

* fix code error
2024-07-18 22:36:04 +08:00
Xu Yang e0a24fb46f Several update on the repo (see desc) (#76)
* ignore result csv file

* fix app scripts

* rename taskgenerator to developer and generate to develop

* fix a config bug in coder

* fix a small bug in factor coder evaluators

* remove a single logger in factor coder evaluators

* fix a small bug in model coder main.py

* rename Implementation to Workspace

* move the prepare the inject_code into FBWorkspace to align all the behavior

* fix a small bug in model feedback

* remove debug lines for multi processing and simplify evaluators multi proc

* add a copy function to workspace to freeze the workspace && add config prefix to speed up debugging

* make hypothesisgen a abc class

* use Qlib***Experiment

* fix a small bug

* rename Imp to Ws

* rename sub_implementations to sub_workspace_list

* fix a bug in feedback not presented as content in prompts

* move proposal pys to proposal folder

* reformat the folder

* align factor and model qlib workspace and use template to handle the workspace

* add a filter to evoagent to filter out false evo

* align multi_proc_n into RDAGENT seeting

* handle when runner gets empty experiment

* fix logger merge remaining problems

* fix black and isort automatically
2024-07-17 15:00:13 +08:00