Implement comprehensive Runpod deployment with S3 volume mount architecture for FP32 ML model training on Tesla V100 GPUs. ## Infrastructure Components ### Deployment Scripts (scripts/) - runpod_deploy.sh: Master deployment orchestrator (8-step workflow) - runpod_upload.sh: S3 upload for binaries and test data - upload_env_to_runpod.sh: Secure .env credentials upload - runpod_deploy_test.sh: Prerequisites validation ### Docker Configuration - Dockerfile.runpod: Multi-stage CUDA 12.1 runtime (~2GB, no binaries) - entrypoint.sh: Volume verification and training execution - Architecture: Volume mount (NO S3 downloads in pods) ### S3 Configuration - Bucket: se3zdnb5o4 (Iceland region: eur-is-1) - Endpoint: https://s3api-eur-is-1.runpod.io - Structure: binaries/, test_data/, models/, .env ### OpenTofu Infrastructure (terraform/runpod/) - main.tf: Pod and volume resources - variables.tf: Configuration variables - outputs.tf: Pod connection info - Security: NO credentials in state (uses volume .env) ## Deployment Assets Uploaded ### Training Binaries (77MB) - train_tft_parquet (23M) - TFT-225 features - train_mamba2_parquet (22M) - MAMBA-2 state space - train_dqn (22M) - Deep Q-Network - train_ppo (13M) - Proximal Policy Optimization ### Test Data (13.8 MB) - 9 Parquet files: ES.FUT, NQ.FUT, 6E.FUT, ZN.FUT (180-day datasets) ### Credentials - .env file (1.5 KB, private access, chmod 600) ## Documentation ### Deployment Guides - RUNPOD_DEPLOYMENT_READY_SUMMARY.md: Complete deployment status - RUNPOD_VOLUME_DEPLOYMENT_GUIDE.md: Step-by-step guide (42KB) - RUNPOD_DEPLOYMENT_QUICK_START.md: Quick reference - RUNPOD_UPLOAD_GUIDE.md: S3 upload instructions - RUNPOD_VOLUME_CONFIGURATION_COMPLETE.md: S3 setup report - RUNPOD_S3_PARQUET_UPLOAD_REPORT.md: Data upload verification ### Architecture Documentation - RUNPOD_VOLUME_MOUNT_ARCHITECTURE.md: Volume mount design - RUNPOD_S3_ARCHITECTURE_DIAGRAM.txt: S3 API vs filesystem access - DOCKERFILE_RUNPOD_FINAL_SUMMARY.md: Docker image specification ### Decision Documentation - RUNPOD_DEPLOYMENT_CHECKLIST.md: Go/no-go decision matrix (27KB) - RUNPOD_DEPLOYMENT_DECISION_TREE.md: Decision workflow - FP32_RUNPOD_DEPLOYMENT_READY.md: FP32 deployment readiness ## QAT Enhancements ### Core QAT Infrastructure - ml/src/memory_optimization/qat.rs: Enhanced QAT observer (+226 lines) - ml/src/memory_optimization/auto_batch_size.rs: OOM recovery (+84 lines) - ml/src/tft/qat_tft.rs: QAT TFT wrapper (+154 lines) - ml/src/trainers/tft.rs: QAT training integration (+433 lines) - ml/src/qat_metrics_exporter.rs: NEW - QAT metrics export ### QAT Testing - ml/tests/qat_integration_tests.rs: NEW - Integration test suite - ml/tests/qat_gradient_clipping_test.rs: NEW - Gradient clipping tests - ml/tests/qat_device_consistency_test.rs: Device mismatch tests (+205 lines) - ml/tests/qat_accuracy_validation_test.rs: Accuracy validation - ml/tests/qat_tft_integration_test.rs: TFT QAT integration ### QAT Documentation - ml/docs/QAT_GUIDE.md: Comprehensive QAT guide (+616 lines) - ml/docs/QAT_GRADIENT_CHECKPOINTING_WORKAROUND.md: NEW - Workaround guide - QAT_BLOCKERS_ROOT_CAUSE_ANALYSIS.md: P0 blocker analysis (44KB) - QAT_ACCURACY_VALIDATION_REPORT.md: Accuracy comparison - QAT_GRADIENT_CLIPPING_VALIDATION_REPORT.md: Clipping validation ### QAT Monitoring - config/grafana/dashboards/qat-training-metrics.json: NEW - Grafana dashboard ## AWS CLI Configuration ### Credentials Setup - ~/.aws/credentials: Runpod profile configured - Access Key: user_2xxA3XcIFj16yfL3aBon9niiSpr - Secret Key: (from RUNPOD_S3_SECRET) - ~/.aws/config: Iceland region (eur-is-1) ## Production Readiness ### FP32 Models: ✅ READY FOR DEPLOYMENT - DQN: 15-20s training, ~6MB GPU memory - PPO: 7-10s training, ~145MB GPU memory - MAMBA-2: 2-3 min training, ~164MB GPU memory - TFT-225: 3-5 min training, ~500MB GPU memory - Total GPU Budget: 815MB (fits on 4GB+ Tesla V100) ### QAT Models: 🔴 BLOCKED - 24 tests implemented but DO NOT COMPILE (11 errors) - 3 P0 blockers: device mismatch, gradient checkpointing, OOM recovery - Timeline: 1-2 weeks to fix (13h P0 fixes + validation) ### Wave D Features: ✅ OPERATIONAL - 225 features fully integrated - Feature extraction: 5.10μs/bar (196x faster than target) - Wave D backtest: Sharpe 2.00, Win Rate 60%, Drawdown 15% - Database migration 045: Applied cleanly, zero conflicts ## Cost Analysis ### One-Time Setup - Network Volume: $4/month (50GB SSD) - Upload costs: FREE (S3 API included) ### Per Training Run (TFT-225) - GPU: Tesla V100-PCIE-16GB @ $0.29/hr - Training Time: ~4 hours - Cost per run: $1.16 ### Monthly (20 Training Runs) - Storage: $4.00/month - Training: $23.20/month (20 runs × $1.16) - Total: $27.20/month ## Security ### Credentials Management - ✅ NO credentials in Docker image - ✅ NO credentials in Terraform state - ✅ .env gitignored and not committed - ✅ .env file private on S3 (HTTP 401 on public access) - ✅ Docker Hub repository PRIVATE (jgrusewski/foxhunt) ### Access Control - S3 API: Local client uploads only - Volume mount: Pod filesystem access only - Authentication: AWS CLI with Runpod profile required ## Next Steps 1. ✅ COMPLETE: Build Docker image 2. ⏳ PENDING: Push to Docker Hub 3. ⏳ PENDING: Deploy pod via Runpod console 4. ⏳ PENDING: Validate training on Tesla V100 ## Performance Targets - Build time: 5-10 min - Upload time: ~20 sec (90MB total) - Pod startup: ~30 sec - Training time: 3-5 min (TFT-225) - Total deployment: ~40 min from start to first training run ## Test Status - FP32 tests: 597/608 passing (98.2%) - QAT tests: 0/24 passing (compilation errors) - Overall: 2,062/2,086 passing (98.8% excluding QAT) 🤖 Generated with Claude Code (https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
447 lines
15 KiB
Rust
447 lines
15 KiB
Rust
//! TDD Tests for TLI ML Trading Commands
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//!
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//! RED Phase: These tests are EXPECTED TO FAIL initially.
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//! The implementation will be created after these tests are written.
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//!
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//! Test Coverage:
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//! - `tli trade ml submit` - Submit ML-generated order
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//! - `tli trade ml predictions` - View prediction history
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//! - `tli trade ml performance` - View model performance
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//! - Error handling for missing required arguments
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//! - Model filtering and limit options
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// Suppress false-positive unused_crate_dependencies warnings
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// dev-dependencies are shared across ALL test targets in the crate
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// This test may not use all deps, but they are required by other integration tests
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#![allow(unused_crate_dependencies)]
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use assert_cmd::Command;
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use predicates::prelude::*;
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use serial_test::serial;
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use std::path::PathBuf;
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// ============================================================================
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// Test Authentication Helper Module
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// ============================================================================
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//
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// Provides test setup/teardown for JWT authentication in integration tests.
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// Uses real JWT token generation and FileTokenStorage for authenticity.
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//
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// ANTI-WORKAROUND COMPLIANCE:
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// ✅ Real JWT token generation using jsonwebtoken crate
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// ✅ Real FileTokenStorage (just with test tokens in temp directory)
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// ✅ Proper cleanup after tests complete
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// ❌ NO STUBS or mocks
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// ❌ NO PLACEHOLDERS or simplified tokens
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mod test_auth {
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use anyhow::{Context, Result};
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use std::path::PathBuf;
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/// Setup test authentication environment
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///
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/// Creates valid JWT tokens in a temporary directory and returns the path
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/// for cleanup. Tokens are valid for 1 hour.
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///
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/// # Returns
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/// * `Ok(PathBuf)` - Path to temporary token directory (for cleanup)
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/// * `Err(anyhow::Error)` - Failed to setup authentication
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pub fn setup_test_auth() -> Result<PathBuf> {
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use tli::auth::jwt_generator;
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use tli::auth::token_manager::{FileTokenStorage, TokenStorage};
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// Create isolated temp directory for this test run
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let temp_dir =
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std::env::temp_dir().join(format!("foxhunt_tli_test_{}", std::process::id()));
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// Create FileTokenStorage in temp directory
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let storage = FileTokenStorage::with_directory(temp_dir.clone())
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.context("Failed to create FileTokenStorage for tests")?;
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// Generate valid access token (1 hour expiry)
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let (access_token, _jti) = jwt_generator::generate_access_token(
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"test_user",
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vec!["trader".to_string()],
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vec![
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"api.access".to_string(),
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"trading.submit".to_string(),
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"trading.view".to_string(),
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],
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3600, // 1 hour
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)
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.context("Failed to generate test access token")?;
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// Generate valid refresh token (2 hours expiry)
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let (refresh_token, _jti) = jwt_generator::generate_refresh_token(
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"test_user",
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7200, // 2 hours
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)
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.context("Failed to generate test refresh token")?;
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// Use tokio runtime to store tokens (FileTokenStorage is async)
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tokio::runtime::Runtime::new()
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.context("Failed to create tokio runtime")?
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.block_on(async {
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storage
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.store_access_token(&access_token)
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.await
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.context("Failed to store test access token")?;
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storage
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.store_refresh_token(&refresh_token)
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.await
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.context("Failed to store test refresh token")?;
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Ok::<(), anyhow::Error>(())
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})?;
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println!(
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"✓ Test authentication setup complete in: {}",
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temp_dir.display()
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);
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Ok(temp_dir)
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}
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/// Cleanup test authentication environment
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///
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/// Removes temporary token directory and all tokens.
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///
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/// # Arguments
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/// * `token_dir` - Path to temporary token directory from setup_test_auth()
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pub fn cleanup_test_auth(token_dir: &PathBuf) {
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if token_dir.exists() {
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if let Err(e) = std::fs::remove_dir_all(token_dir) {
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eprintln!("⚠ Warning: Failed to cleanup test token directory: {}", e);
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} else {
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println!("✓ Test authentication cleanup complete");
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}
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}
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}
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/// Setup authentication with environment override
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///
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/// Creates tokens in temporary directory and sets XDG_CONFIG_HOME to
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/// redirect FileTokenStorage to that temp directory.
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///
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/// Also sets FOXHUNT_ENCRYPTION_KEY to ensure consistent encryption/decryption
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/// between test process and TLI binary process.
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///
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/// This approach allows the actual TLI binary to find the test tokens
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/// without code modifications.
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///
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/// # Returns
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/// * `Ok((PathBuf, Option<String>, Option<String>))` - (temp_dir, original_config_home, original_encryption_key) for cleanup
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pub fn setup_test_auth_with_env_override() -> Result<(PathBuf, Option<String>, Option<String>)>
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{
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// Save original environment variables
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let original_config_home = std::env::var("XDG_CONFIG_HOME").ok();
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let original_encryption_key = std::env::var("FOXHUNT_ENCRYPTION_KEY").ok();
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// Generate a consistent encryption key for this test run
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// This ensures both the test process and TLI binary use the same key
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let encryption_key = hex::encode([42u8; 32]); // Simple deterministic key for tests
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std::env::set_var("FOXHUNT_ENCRYPTION_KEY", &encryption_key);
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// Create temp directory structure: temp/foxhunt-tli/tokens/
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let temp_base =
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std::env::temp_dir().join(format!("foxhunt_tli_config_{}", std::process::id()));
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let config_home = temp_base.clone();
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let token_dir = config_home.join("foxhunt-tli").join("tokens");
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std::fs::create_dir_all(&token_dir)
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.context("Failed to create token directory structure")?;
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// Set XDG_CONFIG_HOME to temp directory
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std::env::set_var("XDG_CONFIG_HOME", &config_home);
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// Generate and store tokens
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use tli::auth::jwt_generator;
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use tli::auth::token_manager::{FileTokenStorage, TokenStorage};
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let storage = FileTokenStorage::new()
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.context("Failed to create FileTokenStorage (should use temp XDG_CONFIG_HOME)")?;
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let (access_token, _) = jwt_generator::generate_access_token(
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"test_user",
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vec!["trader".to_string()],
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vec![
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"api.access".to_string(),
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"trading.submit".to_string(),
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"trading.view".to_string(),
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],
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3600,
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)?;
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let (refresh_token, _) = jwt_generator::generate_refresh_token("test_user", 7200)?;
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tokio::runtime::Runtime::new()?.block_on(async {
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storage.store_access_token(&access_token).await?;
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storage.store_refresh_token(&refresh_token).await?;
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Ok::<(), anyhow::Error>(())
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})?;
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println!(
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"✓ Test auth with env override: XDG_CONFIG_HOME={}, FOXHUNT_ENCRYPTION_KEY=<set>",
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config_home.display()
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);
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Ok((temp_base, original_config_home, original_encryption_key))
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}
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/// Cleanup authentication environment override
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pub fn cleanup_test_auth_with_env_override(
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temp_base: &PathBuf,
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original_config_home: Option<String>,
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original_encryption_key: Option<String>,
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) {
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// Restore original XDG_CONFIG_HOME
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match original_config_home {
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Some(original) => std::env::set_var("XDG_CONFIG_HOME", original),
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None => std::env::remove_var("XDG_CONFIG_HOME"),
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}
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// Restore original FOXHUNT_ENCRYPTION_KEY
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match original_encryption_key {
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Some(original) => std::env::set_var("FOXHUNT_ENCRYPTION_KEY", original),
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None => std::env::remove_var("FOXHUNT_ENCRYPTION_KEY"),
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}
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// Cleanup temp directory
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if temp_base.exists() {
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let _ = std::fs::remove_dir_all(temp_base);
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}
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}
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}
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/// RED TEST 1: ML order submission command
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/// Expected to FAIL - command doesn't exist yet
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#[test]
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#[serial]
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fn test_tli_trade_ml_submit_command() {
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// Setup test authentication
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let (temp_base, original_config, original_key) = test_auth::setup_test_auth_with_env_override()
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.expect("Failed to setup test authentication");
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let mut cmd = Command::cargo_bin("tli").unwrap();
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cmd.arg("trade")
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.arg("ml")
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.arg("submit")
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.arg("--symbol")
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.arg("ES.FUT")
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.arg("--account")
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.arg("test_account");
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// This will FAIL because the command doesn't exist yet (RED phase)
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cmd.assert()
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.success()
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.stdout(predicate::str::contains("ML order submitted"))
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.stdout(predicate::str::contains("Order ID:"))
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.stdout(predicate::str::contains("Confidence:"));
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// Cleanup
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test_auth::cleanup_test_auth_with_env_override(&temp_base, original_config, original_key);
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}
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/// RED TEST 2: ML predictions viewing command
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/// Expected to FAIL - command doesn't exist yet
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#[serial]
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#[test]
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fn test_tli_trade_ml_predictions_command() {
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// Setup test authentication
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let (temp_base, original_config, original_key) = test_auth::setup_test_auth_with_env_override()
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.expect("Failed to setup test authentication");
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let mut cmd = Command::cargo_bin("tli").unwrap();
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cmd.arg("trade")
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.arg("ml")
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.arg("predictions")
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.arg("--symbol")
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.arg("ES.FUT")
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.arg("--limit")
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.arg("10");
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// This will FAIL because the command doesn't exist yet (RED phase)
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cmd.assert()
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.success()
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.stdout(predicate::str::contains("ML Predictions for ES.FUT"))
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.stdout(predicate::str::contains("Predicted Action"))
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.stdout(predicate::str::contains("Confidence"));
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// Cleanup
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test_auth::cleanup_test_auth_with_env_override(&temp_base, original_config, original_key);
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}
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/// RED TEST 3: ML performance metrics command
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/// Expected to FAIL - command doesn't exist yet
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#[serial]
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#[test]
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fn test_tli_trade_ml_performance_command() {
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// Setup test authentication
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let (temp_base, original_config, original_key) = test_auth::setup_test_auth_with_env_override()
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.expect("Failed to setup test authentication");
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let mut cmd = Command::cargo_bin("tli").unwrap();
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cmd.arg("trade").arg("ml").arg("performance");
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// This will FAIL because the command doesn't exist yet (RED phase)
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cmd.assert()
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.success()
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.stdout(predicate::str::contains("ML Model Performance"))
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.stdout(predicate::str::contains("Accuracy"))
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.stdout(predicate::str::contains("Sharpe Ratio"));
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// Cleanup
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test_auth::cleanup_test_auth_with_env_override(&temp_base, original_config, original_key);
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}
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/// RED TEST 4: ML order submission with specific model selection
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/// Expected to FAIL - command doesn't exist yet
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#[serial]
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#[test]
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fn test_tli_trade_ml_submit_with_model_filter() {
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// Setup test authentication
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let (temp_base, original_config, original_key) = test_auth::setup_test_auth_with_env_override()
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.expect("Failed to setup test authentication");
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let mut cmd = Command::cargo_bin("tli").unwrap();
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cmd.arg("trade")
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.arg("ml")
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.arg("submit")
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.arg("--symbol").arg("ES.FUT")
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.arg("--model").arg("DQN") // Use DQN only, not ensemble
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.arg("--account").arg("test_account");
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// This will FAIL because the command doesn't exist yet (RED phase)
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cmd.assert()
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.success()
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.stdout(predicate::str::contains("Model:"))
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.stdout(predicate::str::contains("DQN"));
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// Cleanup
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test_auth::cleanup_test_auth_with_env_override(&temp_base, original_config, original_key);
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}
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/// RED TEST 5: ML predictions with model and limit filters
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/// Expected to FAIL - command doesn't exist yet
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#[serial]
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#[test]
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fn test_tli_trade_ml_predictions_with_filters() {
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// Setup test authentication
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let (temp_base, original_config, original_key) = test_auth::setup_test_auth_with_env_override()
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.expect("Failed to setup test authentication");
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let mut cmd = Command::cargo_bin("tli").unwrap();
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cmd.arg("trade")
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.arg("ml")
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.arg("predictions")
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.arg("--symbol")
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.arg("ES.FUT")
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.arg("--model")
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.arg("MAMBA2")
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.arg("--limit")
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.arg("5");
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// This will FAIL because the command doesn't exist yet (RED phase)
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cmd.assert()
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.success()
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.stdout(predicate::str::contains("MAMBA2"));
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// Cleanup
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test_auth::cleanup_test_auth_with_env_override(&temp_base, original_config, original_key);
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}
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/// RED TEST 6: Error handling - missing required symbol argument
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/// Expected to FAIL - command doesn't exist yet
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#[test]
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fn test_tli_trade_ml_submit_requires_symbol() {
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let mut cmd = Command::cargo_bin("tli").unwrap();
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cmd.arg("trade")
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.arg("ml")
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.arg("submit")
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.arg("--account")
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.arg("test_account");
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// This will FAIL because the command doesn't exist yet (RED phase)
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cmd.assert()
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.failure()
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.stderr(predicate::str::contains("required").or(predicate::str::contains("symbol")));
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}
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/// RED TEST 7: Error handling - missing required account argument
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/// Expected to FAIL - command doesn't exist yet
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#[test]
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fn test_tli_trade_ml_submit_requires_account() {
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let mut cmd = Command::cargo_bin("tli").unwrap();
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cmd.arg("trade")
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.arg("ml")
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.arg("submit")
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.arg("--symbol")
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.arg("ES.FUT");
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// This will FAIL because the command doesn't exist yet (RED phase)
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cmd.assert()
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|
.failure()
|
|
.stderr(predicate::str::contains("required").or(predicate::str::contains("account")));
|
|
}
|
|
|
|
/// RED TEST 8: ML performance with model filter
|
|
/// Expected to FAIL - command doesn't exist yet
|
|
#[serial]
|
|
#[test]
|
|
fn test_tli_trade_ml_performance_with_model_filter() {
|
|
// Setup test authentication
|
|
let (temp_base, original_config, original_key) = test_auth::setup_test_auth_with_env_override()
|
|
.expect("Failed to setup test authentication");
|
|
|
|
let mut cmd = Command::cargo_bin("tli").unwrap();
|
|
|
|
cmd.arg("trade")
|
|
.arg("ml")
|
|
.arg("performance")
|
|
.arg("--model")
|
|
.arg("PPO");
|
|
|
|
// This will FAIL because the command doesn't exist yet (RED phase)
|
|
cmd.assert()
|
|
.success()
|
|
.stdout(predicate::str::contains("PPO"));
|
|
|
|
// Cleanup
|
|
test_auth::cleanup_test_auth_with_env_override(&temp_base, original_config, original_key);
|
|
}
|
|
|
|
/// RED TEST 9: Ensemble mode output verification
|
|
/// Expected to FAIL - command doesn't exist yet
|
|
#[test]
|
|
#[serial]
|
|
fn test_tli_trade_ml_submit_ensemble_mode() {
|
|
// Setup test authentication
|
|
let (temp_base, original_config, original_key) = test_auth::setup_test_auth_with_env_override()
|
|
.expect("Failed to setup test authentication");
|
|
|
|
let mut cmd = Command::cargo_bin("tli").unwrap();
|
|
|
|
cmd.arg("trade")
|
|
.arg("ml")
|
|
.arg("submit")
|
|
.arg("--symbol")
|
|
.arg("ES.FUT")
|
|
.arg("--account")
|
|
.arg("test_account");
|
|
// No --model flag = ensemble mode
|
|
|
|
// This will FAIL because the command doesn't exist yet (RED phase)
|
|
cmd.assert()
|
|
.success()
|
|
.stdout(predicate::str::contains("Ensemble"));
|
|
|
|
// Cleanup
|
|
test_auth::cleanup_test_auth_with_env_override(&temp_base, original_config, original_key);
|
|
}
|