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https://github.com/bytedance/deer-flow.git
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rayhpeng
1ff6b5f7ab
Introduce a unified database configuration (DatabaseConfig) that controls both the LangGraph checkpointer and the DeerFlow application persistence layer from a single `database:` config section. New modules: - deerflow.config.database_config — Pydantic config with memory/sqlite/postgres backends - deerflow.persistence — async engine lifecycle, DeclarativeBase with to_dict mixin, Alembic skeleton - deerflow.runtime.runs.store — RunStore ABC + MemoryRunStore implementation Gateway integration initializes/tears down the persistence engine in the existing langgraph_runtime() context manager. Legacy checkpointer config is preserved for backward compatibility. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
39 lines
646 B
INI
39 lines
646 B
INI
[alembic]
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script_location = %(here)s
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# Default URL for offline mode / autogenerate.
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# Runtime uses engine from DeerFlow config.
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sqlalchemy.url = sqlite+aiosqlite:///./data/app.db
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[loggers]
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keys = root,sqlalchemy,alembic
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[handlers]
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keys = console
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[formatters]
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keys = generic
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[logger_root]
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level = WARN
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handlers = console
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[logger_sqlalchemy]
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level = WARN
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handlers =
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qualname = sqlalchemy.engine
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[logger_alembic]
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level = INFO
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handlers =
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qualname = alembic
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[handler_console]
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class = StreamHandler
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args = (sys.stderr,)
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level = NOTSET
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formatter = generic
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[formatter_generic]
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format = %(levelname)-5.5s [%(name)s] %(message)s
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datefmt = %H:%M:%S
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