pyagent-patterns — Resolution (Tier 2)

pyagent_patterns.resolution.self_reflection.SelfReflection

Bases: Pattern

Generate → critique → refine iterative loop.

Parameters:

Name	Type	Description	Default
agent	Agent	The agent that generates and refines output.	required
critic	Agent | None	Optional separate critic agent. If None, the same agent self-critiques.	None
max_rounds	int	Maximum number of generate-critique rounds.	3
stop_phrase	str	If the critic's response contains this phrase, stop early.	'APPROVED'

pyagent_patterns.resolution.cross_reflection.CrossReflection

Bases: Pattern

Peer review: one agent generates, another reviews, generator revises.

Parameters:

Name	Type	Description	Default
generator	Agent	Agent that produces the initial output and revisions.	required
reviewer	Agent	Agent that reviews and provides feedback.	required
max_rounds	int	Maximum number of generate-review-revise cycles.	2
stop_phrase	str	If reviewer says this, stop early.	'APPROVED'

pyagent_patterns.resolution.debate.Debate

Bases: Pattern

Structured adversarial debate with judge resolution.

Parameters:

Name	Type	Description	Default
debaters	list[Agent]	List of agents, each arguing a different position.	required
judge	Agent	Agent that evaluates arguments and renders final decision.	required
rounds	int	Number of argumentation rounds.	3
positions	list[str] | None	Optional list of position labels (e.g., ["BUY", "SELL"]). If not provided, positions are assigned as "Position 1", "Position 2", etc.	None

pyagent_patterns.resolution.voting.Voting

Bases: Pattern

Independent voting with configurable aggregation strategy.

Parameters:

Name	Type	Description	Default
voters	list[Agent]	List of agents that each cast a vote.	required
strategy	VotingStrategy	Voting strategy (majority or weighted).	MAJORITY
weights	list[float] | None	Optional per-agent weights for weighted voting. Must match length of voters. Defaults to equal weights.	None
normalize	bool	If True, ask each voter to respond with a concise answer suitable for comparison.	True

pyagent_patterns.resolution.evaluator_optimizer.EvaluatorOptimizer

Bases: Pattern

Generate → evaluate → revise loop with explicit evaluation criteria.

Parameters:

Name	Type	Description	Default
generator	Agent	Agent that produces and revises output.	required
evaluator	Agent	Agent that scores output against criteria.	required
criteria	list[str] | None	List of evaluation criteria the evaluator checks.	None
max_rounds	int	Maximum optimization rounds.	3
pass_threshold	int	Score (1-10) at which the output is considered acceptable.	7