Query traces, logs, and metrics in Pydantic Logfire
Logfire is a AACFlow integration in the Observability category. AACFlow is the AI workspace where teams build and deploy AI agents. AACFlow's Logfire integration provides 4 tools that AI agents can use inside AACFlow's visual workflow builder. Logfire connects with an API key. Get started at aacflow.io.
Последнее обновление
Integrate Pydantic Logfire into workflows. Run SQL over your observability data, search spans and logs with structured filters, pull an entire trace by ID, and confirm which project a read token targets.
Зарегистрируйтесь на aacflow.io за считаные секунды. Рабочее пространство готово сразу.
Откройте рабочее пространство, перетащите блок Logfire в конструктор воркфлоу и вставьте свой API-ключ Logfire.
Выберите нужный инструмент, подключите ИИ-агента для рассуждений или преобразования данных и запустите. Ваша автоматизация Logfire работает.
Готовые шаблоны с Logfire. Нажмите на любой, чтобы сразу создать его.
Инструментов Logfire, доступных агентам AACFlow: 4.
Search Logfire spans and logs using structured filters for message text, service, span name, severity, environment, and exceptions. Returns the most recent matches first without writing SQL.
Run a read-only SQL query against Logfire traces, logs, and metrics. Reads the records and metrics tables using PostgreSQL-compatible syntax.
Fetch every span and log belonging to a Logfire trace, ordered from earliest to latest, so a single request can be reconstructed end to end.
Resolve which Logfire organization and project a read token belongs to. Useful for confirming a credential targets the expected project before querying it.
AACFlow's Logfire integration adds 4 tools to the AI agents you build in AACFlow's visual workflow builder. Query traces, logs, and metrics in Pydantic Logfire.
