fa231a3642
Step 3 (prerequisite): - app/schemas.py: add ContentTypeConfig + AgentConfig Pydantic models - app/models.py: add agent_config (JSON, nullable) to LocalAgentConfig - alembic migration a3b9c0d1e2f3: ADD COLUMN agent_config Step 2 (runner refactor): - Remove _classify_file() and _BATCH_FILE_CLASSIFIER_PROMPT (LLM classification step) - Add Phase A: detect_content_type + preprocess (zero LLM, per file) - Add _UNIFIED_PROCESSING_PROMPT (hot-swappable via Langfuse "unified_processing") - Add helper functions: _format_projects, _format_metadata, _get_extraction_rules, _get_no_match_behavior - Single LLM call per file with tools (classify + extract + create) - Fix items_created: count create_* tool calls via _tool_calls_out param - test_agent_runner_v2.py: 10 cases (2.1-2.10) with Langfuse eval scoring Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
32 lines
711 B
Python
32 lines
711 B
Python
"""add agent_config to local_agent_configs
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Revision ID: a3b9c0d1e2f3
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Revises: 9a1f2d0b6c7e
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Create Date: 2026-04-07 00:00:00.000000
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"""
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from __future__ import annotations
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from typing import Sequence, Union
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from alembic import op
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import sqlalchemy as sa
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# revision identifiers, used by Alembic.
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revision: str = "a3b9c0d1e2f3"
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down_revision: Union[str, None] = "9a1f2d0b6c7e"
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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.add_column(
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"local_agent_configs",
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sa.Column("agent_config", sa.JSON(), nullable=True),
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)
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def downgrade() -> None:
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op.drop_column("local_agent_configs", "agent_config")
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