15c542d92c
Add the analysis role's execution path: a two-phase orchestration
(per-scenario diagnosis gathered in parallel, then a synthesis pass)
that reads the existing campaign report aggregation plus capped failure
samples, validates the LLM's JSON against the report schema, and strips
fabricated run/scenario references before persisting. Results upsert one
row per campaign (generating/completed/failed) with the model config
snapshot; GET/POST /api/campaigns/{id}/analysis expose the state machine,
guarding non-terminal campaigns and missing analysis models with 400s.
39 lines
1.4 KiB
Python
39 lines
1.4 KiB
Python
"""add campaign_analyses table
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Revision ID: c8f5e4b13d26
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Revises: b7e4d3a92c15
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Create Date: 2026-08-03
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"""
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from typing import Sequence, Union
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import sqlalchemy as sa
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import sqlmodel # noqa: F401
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from alembic import op
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revision: str = "c8f5e4b13d26"
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down_revision: Union[str, Sequence[str], None] = "b7e4d3a92c15"
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branch_labels: Union[str, Sequence[str], None] = None
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depends_on: Union[str, Sequence[str], None] = None
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def upgrade() -> None:
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op.create_table(
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"campaign_analyses",
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sa.Column("id", sqlmodel.sql.sqltypes.AutoString(), nullable=False),
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sa.Column("campaign_id", sqlmodel.sql.sqltypes.AutoString(), nullable=False),
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sa.Column("status", sqlmodel.sql.sqltypes.AutoString(), nullable=False),
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sa.Column("result", sqlmodel.sql.sqltypes.AutoString(), nullable=True),
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sa.Column("model_config_id", sqlmodel.sql.sqltypes.AutoString(), nullable=True),
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sa.Column("error", sqlmodel.sql.sqltypes.AutoString(), nullable=True),
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sa.Column("triggered_by", sqlmodel.sql.sqltypes.AutoString(), nullable=False),
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sa.Column("created_at", sa.DateTime(), nullable=True),
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sa.Column("updated_at", sa.DateTime(), nullable=True),
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sa.PrimaryKeyConstraint("id"),
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sa.UniqueConstraint("campaign_id", name="uq_campaign_analyses_campaign_id"),
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)
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def downgrade() -> None:
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op.drop_table("campaign_analyses")
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