fix(chatbot): row_factory=dict_row در sync_chunks و fetch_all_chunks
بدون آن، psycopg3 تاپل برمیگرداند و row["model"] خطای «tuple indices must be integers or slices, not str» میداد؛ نتیجه: «Initial index sync failed» و unavailable ماندن چت با وجود امبد موفق.
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@@ -77,6 +77,7 @@ def sync_chunks(chunks: list[dict], force: bool = False) -> dict:
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خروجی: آمار عملیات برای لاگ.
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"""
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import psycopg
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from psycopg.rows import dict_row
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from psycopg.types.json import Jsonb
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from .embeddings import get_embeddings
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@@ -84,7 +85,10 @@ def sync_chunks(chunks: list[dict], force: bool = False) -> dict:
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model = settings.embedding_model
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wanted = {c["doc_id"]: c for c in chunks}
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with psycopg.connect(chatbot_dsn(), autocommit=True, connect_timeout=10) as conn:
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# row_factory لازم است: پایینتر row["model"]/row["doc_id"] خوانده میشود و
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# پیشفرض psycopg3 تاپل برمیگرداند (خطای tuple indices must be integers).
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with psycopg.connect(chatbot_dsn(), autocommit=True, connect_timeout=10,
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row_factory=dict_row) as conn:
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existing: dict[str, str] = {}
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if not force:
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for row in conn.execute("SELECT doc_id, content_hash, model FROM chatbot_chunks").fetchall():
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@@ -136,8 +140,10 @@ def sync_chunks(chunks: list[dict], force: bool = False) -> dict:
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def fetch_all_chunks() -> list[dict]:
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"""همه قطعات ذخیرهشده (برای ساخت BM25 در حافظه)."""
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import psycopg
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from psycopg.rows import dict_row
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with psycopg.connect(chatbot_dsn(), autocommit=True, connect_timeout=10) as conn:
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with psycopg.connect(chatbot_dsn(), autocommit=True, connect_timeout=10,
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row_factory=dict_row) as conn:
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rows = conn.execute(
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"SELECT doc_id, content_hash, content FROM chatbot_chunks ORDER BY doc_id"
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).fetchall()
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