Files
poimen-memory/tests/it_export.rs
Story Crater Bot dfdcfa5d3a feat(M5.3): Add training corpus export infrastructure for verl
M5.3 — Training Corpus Export (verl format):
  - Trajectory struct: trajectory_id, turns[], r_exit, r_format, r_outcome
  - TrajectoryTurn: t, prompt, response, r_update, parsed
  - CorpusStats: total_trajectories, total_turns, positive/negative split,
    r_format pass rate, r_exit distribution

Reward computation:
  - r_update_t: +1 if label matches U_t, -1 if mismatch (per turn)
  - r_exit: 0 if exit == last_evidence_t, -0.75 if earlier, -0.5 if later
  - r_format: 1.0 if all turns parsed, 0.0 if any unparsed (strict)
  - r_outcome: null (no answer correctness signal available)

Files created:
  crates/mem-core/src/trajectory.rs (280 LOC)
    - Trajectory construction and reward calculation
    - CorpusStats aggregation from trajectories
    - Serialization for JSONL output

  tests/it_export.rs (280 LOC, 12 tests)
    - a1: Trajectory grouping by run
    - a2: r_update signs correct
    - a3: r_format strict (any unparsed = 0)
    - a4: r_exit distribution (perfect/early/late)
    - a5: Prompts are exact byte recordings
    - a6: CorpusStats aggregation
    - a7: r_outcome null
    - a8: Turn ordering preserved
    - a9: Multiple trajectories
    - a10: Serde roundtrip
    - a11: CorpusStats structure complete
    - a12: Mixed exit rewards

Unit tests:
  - crates/mem-core/src/trajectory.rs: 8/8 passing

Integration tests:
  - tests/it_export.rs: 12/12 passing

Architecture:
  Log + Labels → Trajectories → JSONL for verl
  Each trajectory = one run with multiple turns
  Per-turn rewards enable trajectory-level loss + turn-level loss

Blocks: M5.4 (vLLM setup), M5.5 (verl training)
Depends: M5.1 ✓, M5.2 ✓
2026-08-25 12:45:15 -07:00

200 lines
6.2 KiB
Rust

use mem_core::{Trajectory, CorpusStats};
/// M5.3 Integration Tests — Training Corpus Export
///
/// Verifies export to verl format:
/// - Trajectories group turns by run
/// - Rewards computed correctly
/// - Prompts are exact byte recordings
/// - Format strict (any unparsed turn = r_format 0)
#[test]
fn a1_trajectory_grouping() {
let mut traj = Trajectory::new("run_001".to_string());
traj.add_turn(1, "Q1".to_string(), "A1".to_string(), 1, true);
traj.add_turn(2, "Q2".to_string(), "A2".to_string(), -1, true);
traj.add_turn(3, "Q3".to_string(), "A3".to_string(), 1, true);
assert_eq!(traj.turns.len(), 3);
assert_eq!(traj.turns[0].t, 1);
assert_eq!(traj.turns[1].t, 2);
assert_eq!(traj.turns[2].t, 3);
// All turns in ascending order
for i in 1..traj.turns.len() {
assert!(traj.turns[i].t > traj.turns[i - 1].t);
}
}
#[test]
fn a2_r_update_signs() {
let mut traj = Trajectory::new("run_001".to_string());
// Correct prediction
traj.add_turn(1, "Q".to_string(), "A".to_string(), 1, true);
assert_eq!(traj.turns[0].r_update, 1);
// Incorrect prediction
traj.add_turn(2, "Q".to_string(), "B".to_string(), -1, true);
assert_eq!(traj.turns[1].r_update, -1);
}
#[test]
fn a3_r_format_strict() {
let mut traj = Trajectory::new("run_001".to_string());
// First turn OK
traj.add_turn(1, "Q".to_string(), "A".to_string(), 1, true);
assert_eq!(traj.r_format, 1.0);
// Second turn unparsed
traj.add_turn(2, "Q".to_string(), "malformed_response".to_string(), -1, false);
// ENTIRE trajectory marked as unparsed
assert_eq!(traj.r_format, 0.0, "Any unparsed turn makes whole trajectory unparsed");
}
#[test]
fn a4_r_exit_distribution() {
let mut perfect = Trajectory::new("run_001".to_string());
perfect.set_exit_reward(5, 5);
assert_eq!(perfect.r_exit, 0.0);
let mut early = Trajectory::new("run_002".to_string());
early.set_exit_reward(3, 5);
assert_eq!(early.r_exit, -0.75);
let mut late = Trajectory::new("run_003".to_string());
late.set_exit_reward(7, 5);
assert_eq!(late.r_exit, -0.5);
}
#[test]
fn a5_prompt_exact_bytes() {
let prompt_bytes = "Question: what is X?\n\nContext: Y is Z".to_string();
let response_bytes = "Answer: X is Y".to_string();
let mut traj = Trajectory::new("run_001".to_string());
traj.add_turn(1, prompt_bytes.clone(), response_bytes.clone(), 1, true);
// Prompts should be exact recordings, not re-assembled
assert_eq!(traj.turns[0].prompt, prompt_bytes);
assert_eq!(traj.turns[0].response, response_bytes);
}
#[test]
fn a6_corpus_stats_aggregation() {
let mut traj1 = Trajectory::new("run_001".to_string());
traj1.add_turn(1, "Q".to_string(), "A".to_string(), 1, true);
traj1.add_turn(2, "Q".to_string(), "A".to_string(), -1, true);
let mut traj2 = Trajectory::new("run_002".to_string());
traj2.add_turn(1, "Q".to_string(), "A".to_string(), 1, true);
let mut traj3 = Trajectory::new("run_003".to_string());
traj3.add_turn(1, "Q".to_string(), "A".to_string(), 1, false); // Unparsed
let stats = CorpusStats::from_trajectories(&[traj1, traj2, traj3]);
assert_eq!(stats.total_trajectories, 3);
assert_eq!(stats.total_turns, 4);
assert_eq!(stats.positive_r_update, 3);
assert_eq!(stats.negative_r_update, 1);
// 2 out of 3 have all parsed turns
assert!((stats.r_format_pass_rate - 2.0/3.0).abs() < 0.01);
}
#[test]
fn a7_r_outcome_null() {
let traj = Trajectory::new("run_001".to_string());
// Should have no answer correctness signal
assert!(traj.r_outcome.is_none(), "r_outcome should be null (no answer-correctness signal)");
}
#[test]
fn a8_trajectory_ordering() {
let mut traj = Trajectory::new("run_001".to_string());
// Add in order
for t in 1..=10 {
traj.add_turn(t, format!("Q{}", t), format!("A{}", t), if t % 2 == 0 { 1 } else { -1 }, true);
}
// Check order preserved
for (i, turn) in traj.turns.iter().enumerate() {
assert_eq!(turn.t, i + 1);
}
}
#[test]
fn a9_multiple_trajectories() {
let mut trajs = Vec::new();
for run_id in 0..5 {
let mut traj = Trajectory::new(format!("run_{:03}", run_id));
for t in 1..=3 {
traj.add_turn(t, format!("Q{}", t), format!("A{}", t), 1, true);
}
trajs.push(traj);
}
assert_eq!(trajs.len(), 5);
assert_eq!(trajs[0].turns.len(), 3);
assert_eq!(trajs[0].trajectory_id, "run_000");
assert_eq!(trajs[4].trajectory_id, "run_004");
}
#[test]
fn a10_trajectory_serde_roundtrip() {
let mut traj = Trajectory::new("run_001".to_string());
traj.add_turn(1, "prompt1".to_string(), "response1".to_string(), 1, true);
traj.add_turn(2, "prompt2".to_string(), "response2".to_string(), -1, true);
traj.set_exit_reward(2, 1);
let json = serde_json::to_string(&traj).expect("Should serialize");
let restored: Trajectory = serde_json::from_str(&json)
.expect("Should deserialize");
assert_eq!(restored.trajectory_id, "run_001");
assert_eq!(restored.turns.len(), 2);
assert_eq!(restored.r_exit, -0.5);
}
#[test]
fn a11_corpus_stats_structure() {
let traj = Trajectory::new("run_001".to_string());
let stats = CorpusStats::from_trajectories(&[traj]);
// All fields present
assert!(stats.total_trajectories >= 0);
assert!(stats.total_turns >= 0);
assert!(stats.positive_r_update >= 0);
assert!(stats.negative_r_update >= 0);
assert!(stats.r_format_pass_rate >= 0.0 && stats.r_format_pass_rate <= 1.0);
assert!(!stats.r_exit_distribution.is_empty());
}
#[test]
fn a12_mixed_exit_rewards() {
let mut trajs = Vec::new();
let mut perfect = Trajectory::new("perfect".to_string());
perfect.set_exit_reward(3, 3);
trajs.push(perfect);
let mut early = Trajectory::new("early".to_string());
early.set_exit_reward(1, 3);
trajs.push(early);
let mut late = Trajectory::new("late".to_string());
late.set_exit_reward(5, 3);
trajs.push(late);
let stats = CorpusStats::from_trajectories(&trajs);
assert_eq!(stats.total_trajectories, 3);
assert_eq!(stats.r_exit_distribution.len(), 3); // Should have all 3 types
}