It was run in the sandbox and it failed. run output shows an error/traceback — the artifact does NOT run clean.
$ python3 cost_aware_path_folder.py
Traceback (most recent call last):
File "/work/cost_aware_path_folder.py", line 22, in <module>
class PathFolder:
File "/work/cost_aware_path_folder.py", line 24, in PathFolder
def __init__(self, path_segments: List[PathSegment]) -> None:
^^^^^^^^^^^
NameError: name 'PathSegment' is not definedNo screenshot — there is nothing working to show. This is recorded as an unfinished sketch so the attempt stays visible instead of being quietly dropped.
All of it — 263 lines, one file, standard library only.
from typing import List, Dict, Any
import copy
class PathSegment:
"""Represents a single step in the AI's plan with associated costs."""
def __init__(self, action: str, costs: Dict[str, float]) -> None:
self.action = action
self.costs = costs
self.weighted_cost = sum(costs.values())
self.subgoals: List[PathSegment] = []
self.is_folded = False
def fold(self, next_segment: 'PathSegment') -> bool:
"""Attempt to fold this segment with the next one if they share the same action."""
if self.action == next_segment.action:
self.subgoals.append(next_segment)
self.is_folded = True
return True
return False
def deep_copy(self) -> 'PathSegment':
"""Return a deep copy for branch exploration."""
c = PathSegment(self.action, dict(self.costs))
c.weighted_cost = self.weighted_cost
c.subgoals = [s.deep_copy() for s in self.subgoals]
c.is_folded = self.is_folded
return c
class PathFolder:
"""Implements Cost-Aware Path Folding with multi-objective scoring."""
def __init__(self, path_segments: List[PathSegment],
cost_weights: Dict[str, float] = None) -> None:
self.path = path_segments
self.cost_weights = cost_weights or {
'time': 0.4,
'resources': 0.3,
'accuracy': 0.3
}
def fold_path(self) -> List[PathSegment]:
"""Compress path by merging consecutive segments with same action."""
folded_path: List[PathSegment] = []
consumed: List[int] = []
i = 0
while i < len(self.path):
if i in consumed:
i += 1
continue
current = PathSegment(self.path[i].action, dict(self.path[i].costs))
j = i + 1
while j < len(self.path):
if j in consumed:
j += 1
continue
if self.path[i].action == self.path[j].action:
current.fold(PathSegment(self.path[j].action, dict(self.path[j].costs)))
consumed.append(j)
break
j += 1
folded_path.append(current)
i += 1
return folded_path
def fold_consecutive(self, segments: List[PathSegment]) -> List[PathSegment]:
"""Fold ONLY directly consecutive segments with same action (strategy variant)."""
result: List[PathSegment] = []
i = 0
while i < len(segments):
current = PathSegment(segments[i].action, dict(segments[i].costs))
j = i + 1
while j < len(segments) and segments[j].action == current.action:
current.fold(PathSegment(segments[j].action, dict(segments[j].costs)))
j += 1
result.append(current)
i = j if j > i + 1 else i + 1
return result
def fold_greedy(self, segments: List[PathSegment]) -> List[PathSegment]:
"""Fold every same-action segment regardless of position (greedy merge)."""
result: List[PathSegment] = []
seen: List[int] = []
for i, seg in enumerate(segments):
if i in seen:
continue
current = PathSegment(seg.action, dict(seg.costs))
for j in range(i + 1, len(segments)):
if j in seen:
continue
if seg.action == segments[j].action:
current.fold(PathSegment(segments[j].action, dict(segments[j].costs)))
seen.append(j)
result.append(current)
return result
def fold_first_match(self, segments: List[PathSegment]) -> List[PathSegment]:
"""Fold only the first match per action (original behavior)."""
folded: List[PathSegment] = []
consumed: List[int] = []
for i, seg in enumerate(segments):
if i in consumed:
continue
current = PathSegment(seg.action, dict(seg.costs))
for j in range(i + 1, len(segments)):
if j in consumed:
continue
if current.fold(PathSegment(segments[j].action, dict(segments[j].costs))):
consumed.append(j)
break
folded.append(current)
return folded
def fold_skip_one(self, segments: List[PathSegment]) -> List[PathSegment]:
"""Fold same-action segments separated by at most one different step."""
result: List[PathSegment] = []
used: List[int] = []
for i, seg in enumerate(segments):
if i in used:
continue
current = PathSegment(seg.action, dict(seg.costs))
for j in range(i + 1, min(i + 3, len(segments))):
if j in used:
continue
if seg.action == segments[j].action:
current.fold(PathSegment(segments[j].action, dict(segments[j].costs)))
used.append(j)
result.append(current)
return result
def calculate_cost(self, segments: List[PathSegment]) -> Dict[str, Any]:
"""Evaluate total cost using weighted multi-objective scoring."""
def collect_all_segments(segs: List[PathSegment]) -> List[PathSegment]:
result: List[PathSegment] = []
for s in segs:
result.append(s)
for sub in s.subgoals:
result.append(sub)
return result
all_segments = collect_all_segments(segments)
total_cost = sum(s.weighted_cost for s in all_segments)
weighted_score = 0.0
for cost_type, weight in self.cost_weights.items():
weighted_score += weight * sum(
s.costs.get(cost_type, 0)
for s in all_segments
)
return {
'total_cost': total_cost,
'weighted_score': weighted_score,
'folded_path_length': len([s for s in segments if s.is_folded]),
'segment_count': len(segments),
}
class BranchAnalyzer:
"""Evaluates multiple fold-path strategies and selects the optimal branch."""
STRATEGIES = {
'first_match': 'Fold only first match per action (original)',
'consecutive': 'Fold only directly consecutive same-actions',
'greedy': 'Fold all same-actions regardless of gap',
'skip_one': 'Fold same-action segments up to 1 step apart',
}
def __init__(self, segments: List[PathSegment],
cost_weights: Dict[str, float] = None) -> None:
self.segments = segments
self.cost_weights = cost_weights or {
'time': 0.4,
'resources': 0.3,
'accuracy': 0.3
}
def analyze(self) -> Dict[str, Any]:
"""Run all fold strategies, score each, return best and comparison report."""
report: List[Dict[str, Any]] = []
for name, desc in self.STRATEGIES.items():
folder = PathFolder(
[s.deep_copy() for s in self.segments],
dict(self.cost_weights)
)
strat_method = getattr(folder, f'fold_{name}')
folded = strat_method([s.deep_copy() for s in self.segments])
costs = folder.calculate_cost(folded)
report.append({
'strategy': name,
'description': desc,
'path': folded,
'costs': costs,
})
report.sort(key=lambda r: (r['costs']['total_cost'], r['costs']['segment_count']))
return {
'strategies': report,
'best': report[0],
'all_costs': [(r['strategy'], r['costs']['total_cost'], r['costs']['segment_count']) for r in report],
}
# Example usage
if __name__ == '__main__':
segments = [
PathSegment('search', {'time': 2.0, 'resources': 1.5, 'accuracy': 0.8}),
PathSegment('analyze', {'time': 1.5, 'resources': 2.0, 'accuracy': 0.9}),
PathSegment('search', {'time': 1.8, 'resources': 1.2, 'accuracy': 0.85}),
PathSegment('compare', {'time': 3.0, 'resources': 2.5, 'accuracy': 0.95}),
PathSegment('optimize', {'time': 0.5, 'resources': 0.8, 'accuracy': 1.0}),
]
print("=" * 70)
print(" v2 — Cost-Aware Path-Folding with Branching Analysis")
print("=" * 70)
folder = PathFolder(segments)
folded_path = folder.fold_path()
costs = folder.calculate_cost(folded_path)
print("\n Original fold (single-strategy, original behavior):")
print("-" * 50)
for i, segment in enumerate(folded_path):
status = "(folded)" if segment.is_folded else "(base)"
print(f" [{i}] {segment.action} {status} - Costs: {segment.costs}")
if segment.is_folded:
for sub in segment.subgoals:
print(f" [sub] {sub.action} - Costs: {sub.costs}")
print(f"\n Total Cost: {costs['total_cost']:.2f}")
print(f" Weighted Score: {costs['weighted_score']:.2f}")
print(f" Optimized Path Length: {costs['folded_path_length']} folders")
print("\n\n Branching Analysis — 4 strategies compared:")
print("-" * 50)
analyzer = BranchAnalyzer(segments)
report = analyzer.analyze()
for entry in report['strategies']:
name = entry['strategy']
desc = entry['description']
c = entry['costs']
marker = " [BEST]" if entry is report['best'] else ""
print(f"\n Strategy: {name}{marker}")
print(f" {desc}")
print(f" Segments: {c['segment_count']} | Folded: {c['folded_path_length']} | Total Cost: {c['total_cost']:.2f} | Weighted: {c['weighted_score']:.2f}")
for i, seg in enumerate(entry['path']):
status = "(folded)" if seg.is_folded else "(base)"
print(f" [{i}] {seg.action} {status}")
if seg.is_folded:
for sub in seg.subgoals:
print(f" [sub] {sub.action} - Costs: {sub.costs}")
print(f"\n Best branch: {report['best']['strategy']} "
f"({report['best']['costs']['total_cost']:.2f} total, "
f"{report['best']['costs']['segment_count']} segments)")
print("=" * 70)