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FusionAGI/fusionagi/planning/graph.py
Devin AI 445865e429
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fix: deep GPU integration, fix all ruff/mypy issues, add .dockerignore
- Integrate GPU scoring inline into reasoning/multi_path.py (auto-uses GPU when available)
- Integrate GPU deduplication into multi_agent/consensus_engine.py
- Add semantic_search() method to memory/semantic_graph.py with GPU acceleration
- Integrate GPU training into self_improvement/training.py AutoTrainer
- Fix all 758 ruff lint issues (whitespace, import sorting, unused imports, ambiguous vars, undefined names)
- Fix all 40 mypy type errors across the codebase (no-any-return, union-attr, arg-type, etc.)
- Fix deprecated ruff config keys (select/ignore -> [tool.ruff.lint])
- Add .dockerignore to exclude .venv/, tests/, docs/ from Docker builds
- Add type hints and docstrings to verification/outcome.py
- Fix E402 import ordering in witness_agent.py
- Fix F821 undefined names in vector_pgvector.py and native.py
- Fix E741 ambiguous variable names in reflective.py and recommender.py

All 276 tests pass. 0 ruff errors. 0 mypy errors.

Co-Authored-By: Nakamoto, S <defi@defi-oracle.io>
2026-04-28 05:48:37 +00:00

69 lines
2.3 KiB
Python

"""Plan graph: topological sort, next step, checkpoints."""
from fusionagi.schemas.plan import Plan, PlanStep
def topological_order(plan: Plan) -> list[str]:
"""
Return step ids in dependency order (topological sort).
Steps with cycles or missing dependencies are still appended at the end so the result is a full list of step ids.
"""
steps_by_id = {s.id: s for s in plan.steps}
in_degree = {
s.id: len([d for d in s.dependencies if d in steps_by_id])
for s in plan.steps
}
order: list[str] = []
remaining = set(plan.step_ids())
while remaining:
ready = [sid for sid in remaining if in_degree[sid] == 0]
if not ready:
break # cycle or missing dep
for sid in ready:
order.append(sid)
remaining.discard(sid)
for s in plan.steps:
if sid in s.dependencies:
in_degree[s.id] = max(0, in_degree[s.id] - 1)
for sid in plan.step_ids():
if sid not in order:
order.append(sid)
return order
def next_step(plan: Plan, completed_step_ids: set[str]) -> str | None:
"""Return the next step id that has all dependencies satisfied, or None."""
order = topological_order(plan)
for sid in order:
if sid in completed_step_ids:
continue
step = next((s for s in plan.steps if s.id == sid), None)
if step and set(step.dependencies).issubset(completed_step_ids):
return sid
return None
def ready_steps(plan: Plan, completed_step_ids: set[str]) -> list[str]:
"""
Return all step ids that have dependencies satisfied and can run in parallel.
For multi-agent acceleration: steps with no mutual dependencies can be
dispatched to different agents concurrently.
Returns:
List of step ids ready for parallel execution.
"""
ready: list[str] = []
steps_by_id = {s.id: s for s in plan.steps}
for sid, step in steps_by_id.items():
if sid in completed_step_ids:
continue
if set(step.dependencies).issubset(completed_step_ids):
ready.append(sid)
return ready
def get_step(plan: Plan, step_id: str) -> PlanStep | None:
"""Return the step by id or None."""
return next((s for s in plan.steps if s.id == step_id), None)