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TPTBusiness
7e7e40b041
- 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
88 lines
4.5 KiB
Markdown
88 lines
4.5 KiB
Markdown
# Predix Prompts Index
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Centralized location for all LLM prompts used in the Predix trading system.
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## Structure
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```
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prompts/
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├── standard_prompts.yaml # Main EURUSD trading prompts (Factor Discovery, Evolution, Model Coder)
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├── local/ # Your improved prompts (NOT in Git!)
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├── patches/ # Override patches for Qlib scenarios
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│ ├── qlib_experiment_prompts.yaml
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│ ├── qlib_rd_loop_prompts.yaml
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│ └── qlib_scenarios_prompts.yaml
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├── app/ # Application-level prompts
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│ ├── ci/prompts.yaml # CI/CD prompts
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│ ├── qlib_rd_loop/prompts.yaml # Qlib RD Loop hypothesis generation
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│ ├── utils/prompts.yaml # APE prompts
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│ └── finetune/prompts.yaml # Finetune prompts
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├── components/ # Component prompts
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│ ├── agent/prompts.yaml # Context7 MCP documentation search
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│ ├── proposal/prompts.yaml # Hypothesis proposal generation
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│ ├── coder/
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│ │ ├── factor_coder/prompts.yaml # Factor code evaluator
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│ │ ├── model_coder/prompts.yaml # Model code evaluator
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│ │ ├── rl/prompts.yaml # RL trading coder (Chinese)
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│ │ ├── CoSTEER/prompts.yaml # Component analysis
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│ │ ├── finetune/prompts.yaml # LLM finetuning coder
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│ │ └── data_science/ # Data science pipeline
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│ │ ├── ensemble/prompts.yaml
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│ │ ├── feature/prompts.yaml
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│ │ ├── model/prompts.yaml
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│ │ ├── pipeline/prompts.yaml
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│ │ ├── raw_data_loader/prompts.yaml
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│ │ ├── share/prompts.yaml
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│ │ └── workflow/prompts.yaml
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├── scenarios/ # Scenario-specific prompts
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│ ├── qlib/ # Qlib EURUSD trading
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│ │ ├── prompts.yaml # Main Qlib scenario
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│ │ ├── experiment/prompts.yaml
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│ │ └── factor_experiment_loader/prompts.yaml
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│ ├── data_science/ # Data science scenarios
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│ │ ├── dev/prompts.yaml
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│ │ ├── runner/dev/prompts.yaml
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│ │ ├── proposal/exp_gen/prompts.yaml
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│ │ ├── proposal/exp_gen/prompts_v2.yaml # Largest file (82KB)
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│ │ ├── proposal/exp_gen/select/prompts.yaml
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│ │ └── scen/prompts.yaml
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│ ├── finetune/ # LLM finetuning
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│ │ ├── dev/prompts.yaml
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│ │ ├── proposal/prompts.yaml
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│ │ └── scen/prompts.yaml
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│ ├── kaggle/ # Kaggle competition
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│ │ ├── prompts.yaml
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│ │ ├── experiment/prompts.yaml
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│ │ └── knowledge_management/prompts.yaml
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│ ├── rl/ # Reinforcement learning (Chinese)
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│ │ ├── dev/prompts.yaml
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│ │ └── proposal/prompts.yaml
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│ └── general_model/prompts.yaml
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└── utils/ # Utility prompts
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└── prompts.yaml # Filter redundant text
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```
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## Active Prompts for EURUSD Trading
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The following prompts are actively used in the `rdagent fin_quant` trading loop:
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| Priority | File | Purpose |
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|----------|------|---------|
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| 1 | `standard_prompts.yaml` | Factor Discovery, Factor Evolution, Model Coder, Trading Strategy |
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| 2 | `rdagent/app/qlib_rd_loop/prompts.yaml` | Hypothesis generation for Qlib RD Loop |
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| 3 | `rdagent/scenarios/qlib/prompts.yaml` | Qlib scenario: hypothesis feedback, output format |
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| 4 | `rdagent/scenarios/qlib/factor_experiment_loader/prompts.yaml` | Factor viability, relevance, duplicate checks |
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| 5 | `rdagent/scenarios/qlib/experiment/prompts.yaml` | Qlib experiment background, factor interface |
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| 6 | `rdagent/components/coder/factor_coder/prompts.yaml` | Code evaluation, final decision |
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| 7 | `patches/qlib_scenarios_prompts.yaml` | EURUSD-specific overrides (1min data, market sessions) |
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| 8 | `patches/qlib_rd_loop_prompts.yaml` | EURUSD hypothesis generation overrides |
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## Key Changes (April 2026)
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- **Fixed:** All "daily frequency" references changed to "intraday 1-minute bars"
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- **Fixed:** `daily_pv.h5` renamed to `intraday_pv.h5` in data descriptions
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- **Fixed:** `FactorDatetimeDailyEvaluator` now accepts 1min-30min bars as correct for EURUSD
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## Total Files: 44 YAML files
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## Total Size: ~486 KB
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