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https://github.com/trustgraph-ai/trustgraph.git
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9f2bfbce0c
Workspace identity is now determined by queue infrastructure instead of message body fields, closing a privilege-escalation vector where a caller could spoof workspace in the request payload. - Add WorkspaceProcessor base class: discovers workspaces from config at startup, creates per-workspace consumers (queue:workspace), and manages consumer lifecycle on workspace create/delete events - Roll out to librarian, flow-svc, knowledge cores, and config-svc - Config service gets a dual-queue regime: a system queue for cross-workspace ops (getvalues-all-ws, bootstrapper writes to __workspaces__) and per-workspace queues for tenant-scoped ops, with workspace discovery from its own Cassandra store - Remove workspace field from request schemas (FlowRequest, LibrarianRequest, KnowledgeRequest, CollectionManagementRequest) and from DocumentMetadata / ProcessingMetadata — table stores now accept workspace as an explicit parameter - Strip workspace encode/decode from all message translators and gateway serializers - Gateway enforces workspace existence: reject requests targeting non-existent workspaces instead of routing to queues with no consumer - Config service provisions new workspaces from __template__ on creation - Add workspace lifecycle hooks to AsyncProcessor so any processor can react to workspace create/delete without subclassing WorkspaceProcessor
115 lines
3.5 KiB
Python
115 lines
3.5 KiB
Python
"""
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DefaultFlowStart initialiser — starts a named flow in a workspace
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using a specified blueprint.
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Separated from WorkspaceInit so deployments that want a workspace
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without an auto-started flow can simply omit this initialiser.
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Parameters
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----------
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workspace : str (default "default")
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Workspace in which to start the flow.
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flow_id : str (default "default")
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Identifier for the started flow.
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blueprint : str (required)
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Blueprint name (must already exist in the workspace's config,
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typically via TemplateSeed -> WorkspaceInit).
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description : str (default "Default")
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Human-readable description passed to flow-svc.
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parameters : dict (optional)
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Optional parameter overrides passed to start-flow.
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"""
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from trustgraph.schema import FlowRequest
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from .. base import Initialiser
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class DefaultFlowStart(Initialiser):
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def __init__(
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self,
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workspace="default",
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flow_id="default",
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blueprint=None,
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description="Default",
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parameters=None,
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**kwargs,
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):
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super().__init__(**kwargs)
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if not blueprint:
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raise ValueError(
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"DefaultFlowStart requires 'blueprint'"
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)
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self.workspace = workspace
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self.flow_id = flow_id
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self.blueprint = blueprint
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self.description = description
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self.parameters = dict(parameters) if parameters else {}
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async def run(self, ctx, old_flag, new_flag):
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workspaces = await ctx.config.keys(
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"__workspaces__", "workspace",
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)
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if self.workspace not in workspaces:
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raise RuntimeError(
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f"Workspace {self.workspace!r} does not exist yet"
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)
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flow = ctx.make_flow_client(self.workspace)
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await flow.start()
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try:
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# Check whether the flow already exists. Belt-and-braces
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# beyond the flag gate: if an operator stops and restarts the
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# bootstrapper after the flow is already running, we don't
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# want to blindly try to start it again.
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list_resp = await flow.request(
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FlowRequest(
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operation="list-flows",
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),
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timeout=10,
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)
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if list_resp.error:
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raise RuntimeError(
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f"list-flows failed: "
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f"{list_resp.error.type}: {list_resp.error.message}"
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)
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if self.flow_id in (list_resp.flow_ids or []):
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ctx.logger.info(
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f"Flow {self.flow_id!r} already running in workspace "
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f"{self.workspace!r}; nothing to do"
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)
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return
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ctx.logger.info(
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f"Starting flow {self.flow_id!r} "
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f"(blueprint={self.blueprint!r}) "
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f"in workspace {self.workspace!r}"
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)
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resp = await flow.request(
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FlowRequest(
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operation="start-flow",
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flow_id=self.flow_id,
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blueprint_name=self.blueprint,
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description=self.description,
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parameters=self.parameters,
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),
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timeout=30,
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)
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if resp.error:
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raise RuntimeError(
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f"start-flow failed: "
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f"{resp.error.type}: {resp.error.message}"
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)
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ctx.logger.info(
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f"Flow {self.flow_id!r} started"
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)
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finally:
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await flow.stop()
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