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ulleo
3fd6fa867d
- Add extract_keywords() to LLMService with conversation context support, using process_stream + start_log/end_log for logging consistency - Add expand_with_terminology() to expand keywords with synonym matching - Add fusion scoring in calc_table_embedding(): α * vec_score + (1-α) * keyword_score - Add calc_keyword_score() with multi-level matching: table name exact (1.0), comment exact (0.9), comment substring (0.7), table name partial (0.25-0.5), field comment exact (0.5), field comment substring (0.4), field name partial (0.3) - Scoring considers keyword coverage rate to differentiate tables with different numbers of matched keywords - Extracted keywords persisted to ChatRecord for reuse across endpoints - get_terminology_template() supports comma-separated keyword input with per-keyword matching for higher precision - Add TABLE_EMBEDDING_ALPHA and TABLE_EMBEDDING_KEYWORD_ENABLED config
32 lines
956 B
Python
32 lines
956 B
Python
"""072_chat_record
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Revision ID: f898322341a5
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Revises: a2e2ecfa5a9c
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Create Date: 2026-09-14 15:54:47.921806
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"""
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from alembic import op
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import sqlalchemy as sa
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import sqlmodel.sql.sqltypes
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from sqlalchemy.dialects import postgresql
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# revision identifiers, used by Alembic.
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revision = 'f898322341a5'
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down_revision = 'a2e2ecfa5a9c'
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branch_labels = None
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depends_on = None
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def upgrade():
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# ### commands auto generated by Alembic - please adjust! ###
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op.add_column('chat_record', sa.Column('extracted_keywords', sa.Text(), nullable=True, comment='关键词'))
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op.add_column('chat_record', sa.Column('expanded_keywords', sa.Text(), nullable=True, comment='扩展后的关键词'))
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# ### end Alembic commands ###
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def downgrade():
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# ### commands auto generated by Alembic - please adjust! ###
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op.drop_column('chat_record', 'extracted_keywords')
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op.drop_column('chat_record', 'expanded_keywords')
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# ### end Alembic commands ###
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