trajectory
Skill1 starsChanged 31 days agoMITView on GitHub
Instructions for the upstream workflow: Trajectory learning — stores solver trajectories and searches similar past optimizations to inform future decisions
2 other projects use a version of this.
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Most recently taken up by
- dynos-fit/dynos-worktheir own version, first seen Oct 13, 2026
- zedarvates/botte-secretetheir own version, first seen Aug 8, 2026
Other versions2 projects use a version of this.
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- dynos-fit/dynos-work★ 2same name
- zedarvates/botte-secrete★ 2same name
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The file
Files
Trajectory learning
Package scope and prerequisites
This catalog ships instructions, not the executable runtime. Python modules, scripts, local services and optional tools named below must be installed separately from the upstream project. Check their availability before running commands; if they are missing, explain the prerequisite instead of claiming execution or results. The host agent may use model tokens while following these instructions.
Overview
Stocke les trajectoires d'optimisation des solveurs déterministes. Décrit la recherche de solutions antérieures similaires. Mesurer la latence, vérifier les prérequis et valider la pertinence avant réutilisation.
Compatible avec ~/.hermes/scripts/trajectory_search.py (Hermes Trajectory Memory).
Files
| Fichier | Rôle |
skills/trajectory/__init__.py | capture(), search(), load(), stats() |
skills/trajectory/store/trajectories.jsonl | Stockage JSON Lines |
Usage
from skills.trajectory import capture, search, get_stats
# Capturer une trajectoire
tid = capture(
solver="bin_pack",
task="pack 3 database backups into 10GB capacity",
parameters={"items": [("db1", 4), ("db2", 7), ("db3", 3)], "capacity": 10},
result={"bins": [...], "bin_count": 2},
latency=0.002,
tokens_saved=500,
)
# Rechercher des trajectoires similaires
hits = search("pack items into capacity")
for h in hits:
print(f"[{h['score']:.2f}] {h['trajectory']['task']}")
# Statistiques
stats = get_stats()
print(f"Total: {stats['total']}, Tokens saved: {stats['total_tokens_saved']}")Integration with solvers
Dans skills/solvers/solvers.py, chaque fonction peut capturer sa trajectoire:
from skills.trajectory import capture
def assign_balanced(tasks, workers):
result = ... # existing logic
capture("assign_balanced", f"assign {len(tasks)} tasks to {len(workers)} workers",
{"tasks": tasks, "workers": workers}, result, latency=latency())
return resultIntegration with Hermes
Les fichiers sont compatibles: Botte peut lire les trajectoires Hermes et vice-versa:
# Lire les trajectoires Hermes
from skills.trajectory import load
hermes_trajs = load("~/.hermes/trajectory_store/trajectories.jsonl")Pitfalls
- Rotation automatique à 5000 entrées
- TF-IDF uniquement — pas de sémantique profonde
- Latence de capture < 1ms (append-only)
- Thread-safe pour usage concurrent
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