`OSSS.ai.dependencies.graph_engine`¶

`OSSS.ai.dependencies.graph_engine` ¶

Advanced dependency graph engine with topological ordering and circular dependency detection.

This module provides sophisticated dependency management that extends beyond simple sequential execution to support complex dependency graphs with validation, optimization, and advanced routing capabilities.

`DependencyType` ¶

Bases: Enum

Types of dependencies between agents.

`ExecutionPriority` ¶

Bases: Enum

Execution priority levels for agents.

`ResourceConstraint` ¶

Bases: BaseModel

Resource constraint for agent execution.

Migrated from dataclass to Pydantic BaseModel for enhanced validation, serialization, and integration with the OSSS Pydantic ecosystem.

`DependencyEdge` ¶

Bases: BaseModel

An edge in the dependency graph representing a dependency relationship.

Migrated from dataclass to Pydantic BaseModel for enhanced validation, serialization, and integration with the OSSS Pydantic ecosystem.

`is_satisfied(context)` ¶

Check if dependency condition is satisfied.

`DependencyNode` ¶

Bases: BaseModel

A node in the dependency graph representing an agent and its constraints.

Migrated from dataclass to Pydantic BaseModel for enhanced validation, serialization, and integration with the OSSS Pydantic ecosystem.

`can_execute(context)` ¶

Check if node can execute given current context.

`CircularDependencyError` ¶

Bases: Exception

Raised when circular dependencies are detected in the graph.

`DependencyValidationError` ¶

Bases: Exception

Raised when dependency graph validation fails.

`TopologicalSort` ¶

Utility class for topological sorting with cycle detection.

`sort(nodes, edges)` `staticmethod` ¶

Perform topological sort on the dependency graph.

Parameters¶

nodes : List[str] List of node identifiers edges : List[DependencyEdge] List of dependency edges

Returns¶

List[str] Topologically sorted list of nodes

Raises¶

CircularDependencyError If circular dependencies are detected

`DependencyGraphEngine` ¶

Advanced dependency graph engine for agent execution planning.

Provides topological ordering, circular dependency detection, conditional dependencies, and optimization capabilities for complex agent execution graphs.

`add_node(node)` ¶

Add a node to the dependency graph.

`add_edge(edge)` ¶

Add a dependency edge to the graph.

`remove_node(agent_id)` ¶

Remove a node and all its edges from the graph.

`add_dependency(from_agent, to_agent, dependency_type=DependencyType.HARD, condition=None, weight=1.0, **kwargs)` ¶

Convenience method to add a dependency between two agents.

`get_execution_order(context=None)` ¶

Get optimal execution order for all agents.

Parameters¶

context : Optional[AgentContext] Current execution context for evaluating conditional dependencies

Returns¶

List[str] List of agent IDs in optimal execution order

`get_parallel_groups(context=None)` ¶

Get groups of agents that can execute in parallel.

Returns¶

List[List[str]] List of groups, where each group contains agents that can run in parallel

`validate_graph()` ¶

Validate the dependency graph for consistency and correctness.

Returns¶

List[str] List of validation warnings/errors

`get_dependency_impact(agent_id)` ¶

Analyze the impact of a specific agent on the dependency graph.

Parameters¶

agent_id : str ID of the agent to analyze

Returns¶

Dict[str, Any] Impact analysis including dependents, dependencies, and criticality

`optimize_for_latency()` ¶

Optimize execution order to minimize total latency.

`optimize_for_reliability()` ¶

Optimize execution order to maximize reliability.

`get_execution_statistics()` ¶

Get statistics about the dependency graph and execution patterns.

OSSS.ai.dependencies.graph_engine¶