{"categories":[{"label":"Artificial Intelligence","url":"https://skillfed.io/packages/category/scientific-engineering-artificial-intelligence/10"}],"enrichment":{"capability":"Adds durable execution to Pydantic AI agents by checkpointing model and tool calls to Postgres, allowing crashed workers to resume from the last completed step without token loss.","skillfed_tags":["agent-durability","postgres-backed","fault-tolerance"],"use_cases":["Long-running analysis agents that call LLMs multiple times and must survive worker restarts without token waste.","Multi-step agentic workflows with tool calls that need to resume from the last completed step after crashes.","Production deployments where Postgres is already present and external orchestration services are not available.","Cost-sensitive agent applications where re-running expensive model calls after a failure is unacceptable.","Batch processing of agent tasks with guaranteed completion despite transient worker failures."],"what_it_does":"Pydantic AI Absurd wraps Pydantic AI agents with durable execution backed by Postgres. When an agent runs inside an Absurd task, every model call and tool invocation is checkpointed to the database. If the worker process crashes mid-execution, a new worker can resume from the last completed step without restarting the entire run or re-spending tokens on already-completed API calls.\n\nThe package integrates Absurd's task queue and durability layer directly into Pydantic AI's agent runtime, eliminating the need for external infrastructure like Temporal or Redis. You define tasks using decorators, spawn them with parameters, and call agent.run() inside the task\u2014Absurd handles checkpointing and recovery transparently. It's designed for scenarios where agent runs are long, expensive, or prone to interruption.","worth_installing":"Yes, if you run Pydantic AI agents in production and want durability without external infrastructure. The low install friction, permissive license, and active maintenance make it a practical choice for teams already using Postgres. Verify that Postgres schema setup and performance overhead align with your deployment model before committing."},"id":"pydantic-ai-absurd","links":{"html":"https://skillfed.io/packages/pydantic-ai-absurd","md":"https://skillfed.io/packages/pydantic-ai-absurd.md","pypi":"https://pypi.org/project/pydantic-ai-absurd/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-07-28","license_spdx":"MIT","license_treatment":"permissive","name":"pydantic-ai-absurd","python_support":"supports_current","summary":"Durable execution of Pydantic AI agents on Postgres via Absurd."},"popularity":{"monthly_downloads":104826,"position":12735,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"0.7.0"}