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https://github.com/bytedance/deer-flow.git
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edf345cd72
- Freeze all config models (AppConfig + 15 sub-configs) with frozen=True - Purify from_file() — remove 9 load_*_from_dict() side-effect calls - Replace mtime/reload/push/pop machinery with single ContextVar + init_app_config() - Delete 10 sub-module globals and their getters/setters/loaders - Migrate 50+ consumers from get_*_config() to get_app_config().xxx - Expand DeerFlowContext: app_config + thread_id + agent_name (frozen dataclass) - Wire into Gateway runtime (worker.py) and DeerFlowClient via context= parameter - Remove sandbox_id from runtime.context — flows through ThreadState.sandbox only - Middleware/tools access runtime.context directly via Runtime[DeerFlowContext] generic - resolve_context() retained at server entry points for LangGraph Server fallback
28 lines
1.0 KiB
Python
28 lines
1.0 KiB
Python
"""Configuration for LangGraph checkpointer."""
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from typing import Literal
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from pydantic import BaseModel, ConfigDict, Field
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CheckpointerType = Literal["memory", "sqlite", "postgres"]
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class CheckpointerConfig(BaseModel):
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"""Configuration for LangGraph state persistence checkpointer."""
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model_config = ConfigDict(frozen=True)
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type: CheckpointerType = Field(
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description="Checkpointer backend type. "
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"'memory' is in-process only (lost on restart). "
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"'sqlite' persists to a local file (requires langgraph-checkpoint-sqlite). "
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"'postgres' persists to PostgreSQL (requires langgraph-checkpoint-postgres)."
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)
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connection_string: str | None = Field(
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default=None,
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description="Connection string for sqlite (file path) or postgres (DSN). "
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"Required for sqlite and postgres types. "
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"For sqlite, use a file path like '.deer-flow/checkpoints.db' or ':memory:' for in-memory. "
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"For postgres, use a DSN like 'postgresql://user:pass@localhost:5432/db'.",
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)
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