TradingAgents/tests
swj.premkumar 05ce55125f ### Added
- **Dynamic Parameter Tuning (The Learning Loop)**: Implemented full self-reflection cycle. The Reflector agent now parses its own advice into JSON (`rsi_period`, `stop_loss_pct`), persists it to `data_cache/runtime_config.json`, and the Market Analyst loads it to tune the Regime Detector in real-time.
- **Audit Archival**: Every tuning event is now archived to `results/{TICKER}/{DATE}/runtime_config.json` for historical auditing, ensuring we can reproduce why parameters changed on any given day.
- **Atomic Persistence**: Implemented `agent_utils.write_json_atomic` to prevent race conditions during config saves.
- **Centralized Config**: Moved hardcoded paths to `default_config.py` (DRY principle).

### Fixed
- **Reflector Logic Gap**: The Reflector was previously "shouting into the void"—making suggestions but having no mechanism to apply them. This circuit is now closed.
2026-01-13 06:40:07 -06:00
..
README.md Fixed 2026-01-11 20:13:01 -06:00
bench_yfinance.py feat: implement trend override, harden regime detection, and organize tests 2026-01-11 11:18:46 -06:00
demo_regime_detection.py The **TradingAgents** system is a risk-managed, LLM-driven trading engine designed to execute trades based on validated truth, not hallucinations. It connects hierarchical LLM agents with deterministic safety gates to ensure that every trade is architecturally sound, factually correct, and risk-compliant. 2026-01-09 19:28:49 -06:00
ignition_tests.py The **TradingAgents** system is a risk-managed, LLM-driven trading engine designed to execute trades based on validated truth, not hallucinations. It connects hierarchical LLM agents with deterministic safety gates to ensure that every trade is architecturally sound, factually correct, and risk-compliant. 2026-01-09 19:28:49 -06:00
test_analyst_node.py Fixed 2026-01-11 20:13:01 -06:00
test_anonymizer.py The **TradingAgents** system is a risk-managed, LLM-driven trading engine designed to execute trades based on validated truth, not hallucinations. It connects hierarchical LLM agents with deterministic safety gates to ensure that every trade is architecturally sound, factually correct, and risk-compliant. 2026-01-09 19:28:49 -06:00
test_fatal_flaw_fixes.py The **TradingAgents** system is a risk-managed, LLM-driven trading engine designed to execute trades based on validated truth, not hallucinations. It connects hierarchical LLM agents with deterministic safety gates to ensure that every trade is architecturally sound, factually correct, and risk-compliant. 2026-01-09 19:28:49 -06:00
test_finance_args.py Fixed 2026-01-11 20:13:01 -06:00
test_global_news.py feat: implement trend override, harden regime detection, and organize tests 2026-01-11 11:18:46 -06:00
test_google_api.py - **Insider Veto Protocol (Rule B)**: Hard-coded safety gate in `trading_graph.py` that blocks ALL buy signals if Net Insider Selling exceeds $50M while the stock is in a technical downtrend (Price < 50 SMA). This prevents "Falling Knife" catches. 2026-01-13 05:27:24 -06:00
test_integrated_workflow.py The **TradingAgents** system is a risk-managed, LLM-driven trading engine designed to execute trades based on validated truth, not hallucinations. It connects hierarchical LLM agents with deterministic safety gates to ensure that every trade is architecturally sound, factually correct, and risk-compliant. 2026-01-09 19:28:49 -06:00
test_macro_regime.py Fixed 2026-01-11 20:13:01 -06:00
test_market_node.py feat: implement trend override, harden regime detection, and organize tests 2026-01-11 11:18:46 -06:00
test_override.py feat: implement trend override, harden regime detection, and organize tests 2026-01-11 11:18:46 -06:00
test_pltr_regime.py Fixed 2026-01-11 20:13:01 -06:00
test_rag_isolator.py The **TradingAgents** system is a risk-managed, LLM-driven trading engine designed to execute trades based on validated truth, not hallucinations. It connects hierarchical LLM agents with deterministic safety gates to ensure that every trade is architecturally sound, factually correct, and risk-compliant. 2026-01-09 19:28:49 -06:00
test_regime_detection.py feat: implement trend override, harden regime detection, and organize tests 2026-01-11 11:18:46 -06:00
test_regime_detector.py The **TradingAgents** system is a risk-managed, LLM-driven trading engine designed to execute trades based on validated truth, not hallucinations. It connects hierarchical LLM agents with deterministic safety gates to ensure that every trade is architecturally sound, factually correct, and risk-compliant. 2026-01-09 19:28:49 -06:00
test_regime_propagation.py Fixed 2026-01-11 20:13:01 -06:00
test_semantic_fact_checker.py The **TradingAgents** system is a risk-managed, LLM-driven trading engine designed to execute trades based on validated truth, not hallucinations. It connects hierarchical LLM agents with deterministic safety gates to ensure that every trade is architecturally sound, factually correct, and risk-compliant. 2026-01-09 19:28:49 -06:00
torture_test_2022.py The **TradingAgents** system is a risk-managed, LLM-driven trading engine designed to execute trades based on validated truth, not hallucinations. It connects hierarchical LLM agents with deterministic safety gates to ensure that every trade is architecturally sound, factually correct, and risk-compliant. 2026-01-09 19:28:49 -06:00
verify_alpaca.py feat: implement trend override, harden regime detection, and organize tests 2026-01-11 11:18:46 -06:00
verify_google_key.py feat: implement trend override, harden regime detection, and organize tests 2026-01-11 11:18:46 -06:00
verify_local_embeddings.py feat: implement trend override, harden regime detection, and organize tests 2026-01-11 11:18:46 -06:00
verify_ollama_embeddings.py feat: implement trend override, harden regime detection, and organize tests 2026-01-11 11:18:46 -06:00
verify_override_fix.py Fixed 2026-01-11 20:13:01 -06:00
verify_pltr_pipeline.py Fixed 2026-01-11 20:13:01 -06:00
verify_reflection_loop.py ### Added 2026-01-13 06:40:07 -06:00
verify_regime_flow.py Fixed 2026-01-11 20:13:01 -06:00
verify_regime_integration.py feat: implement trend override, harden regime detection, and organize tests 2026-01-11 11:18:46 -06:00
verify_tei_native.py feat: implement trend override, harden regime detection, and organize tests 2026-01-11 11:18:46 -06:00

README.md

Trading Agents Verification Suite

This folder contains unit tests and verification scripts to validate the functionality of the Trading Agents system.

Available Tests

Core Logic Tests

  1. test_regime_detection.py

    • Purpose: Validates mathematical components (ADX, Volatility, Hurst) of the RegimeDetector.
    • Usage: python tests/test_regime_detection.py
  2. test_market_node.py

    • Purpose: End-to-end verification of market_analyst_node. Checks data fetching logic and regime integration.
    • Usage: python tests/test_market_node.py
  3. test_override.py

    • Purpose: Unit tests for "Don't Fight the Tape" safety logic. Verifies protection of growth leaders.
    • Usage: python tests/test_override.py

Integration & API Tests

  1. test_global_news.py

    • Purpose: Verifies news fetching capabilities.
    • Usage: python tests/test_global_news.py
  2. test_google_api.py & verify_google_key.py

    • Purpose: Validates Google Gemini API connectivity and key validity.
    • Usage: python tests/test_google_api.py
  3. verify_alpaca.py

    • Purpose: Checks Alpaca trading API connection.
    • Usage: python tests/verify_alpaca.py

Infrastructure & Performance

  1. verify_local_embeddings.py & verify_ollama_embeddings.py

    • Purpose: Validates local embedding models (Ollama/TEI) for RAG.
    • Usage: python tests/verify_local_embeddings.py
  2. verify_tei_native.py

    • Purpose: Tests Text Embeddings Inference (TEI) native endpoint.
    • Usage: python tests/verify_tei_native.py
  3. bench_yfinance.py

    • Purpose: Benchmarks yfinance data fetch performance (latency/throughput).
    • Usage: python tests/bench_yfinance.py
  4. verify_regime_integration.py

    • Purpose: Integration test for regime detection within the broader graph context.
    • Usage: python tests/verify_regime_integration.py
  5. test_finance_args.py

    • Purpose: Verifies robustness of financial tools against extraneous LLM arguments and type mismatches.
    • Usage: python tests/test_finance_args.py

How to Run

Ensure your virtual environment is activated:

source .venv/bin/activate
export PYTHONPATH=$PYTHONPATH:.
python tests/test_market_node.py