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feat(agents): hypothesis retry-with-error-feedback (max 1 retry)

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HypothesisAgent.propose ora riprova una volta in caso di parse o
validation error: il prompt user del retry include l'output precedente
(troncato a 800 char) e il messaggio di errore, così l'LLM può
auto-correggersi. Configurabile via max_retries (default 1).

Cambia il modello dati di HypothesisProposal: completion (singolare)
diventa completions: list[CompletionResult] con n_attempts. L'orchestrator
itera su completions per registrare il costo di ogni chiamata LLM,
incluse le retry.

Phase 1 v4 mostrava 64% di parse failure recuperabili: il retry punta
a tagliare quel tasso senza inflazionare i token oltre 2x worst-case.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
This commit is contained in:
AdrianoDev
2026-05-10 21:20:47 +02:00
parent 44eb6436c1
commit d4fcb42fc5
3 changed files with 193 additions and 47 deletions
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src/multi_swarm/orchestrator/run.py
+17 -15
View File
@@ -99,21 +99,23 @@ def run_phase1(
continue # elite gia' valutata in generazione precedente
repo.save_genome(run_id=run_id, generation_idx=gen, genome=genome)
proposal = hypothesis_agent.propose(genome, market)
cost_record = cost_tracker.record(
input_tokens=proposal.completion.input_tokens,
output_tokens=proposal.completion.output_tokens,
tier=proposal.completion.tier,
run_id=run_id,
agent_id=genome.id,
)
repo.save_cost_record(
run_id=run_id,
agent_id=genome.id,
tier=cost_record.tier.value,
input_tokens=cost_record.input_tokens,
output_tokens=cost_record.output_tokens,
cost_usd=cost_record.cost_usd,
)
# Registra costo per OGNI completion (incluse retry).
for completion in proposal.completions:
cost_record = cost_tracker.record(
input_tokens=completion.input_tokens,
output_tokens=completion.output_tokens,
tier=completion.tier,
run_id=run_id,
agent_id=genome.id,
)
repo.save_cost_record(
run_id=run_id,
agent_id=genome.id,
tier=cost_record.tier.value,
input_tokens=cost_record.input_tokens,
output_tokens=cost_record.output_tokens,
cost_usd=cost_record.cost_usd,
)
if proposal.strategy is None:
repo.save_evaluation(