49 lines
1.8 KiB
Python
49 lines
1.8 KiB
Python
# SPDX-License-Identifier: AGPL-3.0-only
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# Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
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"""Scope identifiers (kb_<id> / thread_<id>) + per-scope embedder resolver."""
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from __future__ import annotations
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from storage.studio_db import get_connection, list_chat_settings
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from utils.rag.config import resolve_embedder
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RAG_DEFAULTS_KEY = "rag.defaults"
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def thread_settings_key(thread_id: str) -> str:
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return f"thread:{thread_id}:rag"
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def resolve_scope_embedder(scope: str) -> str | None:
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"""KB → kb.embedding_model; thread → per-thread/defaults/matrix. None = use default."""
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if scope.startswith("kb_"):
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kb_id = scope[len("kb_") :]
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with get_connection() as conn:
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row = conn.execute(
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"SELECT embedding_model FROM rag_knowledge_bases WHERE id = ?",
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(kb_id,),
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).fetchone()
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return row["embedding_model"] if row else None
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if scope.startswith("thread_"):
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thread_id = scope[len("thread_") :]
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all_settings = list_chat_settings()
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defaults = all_settings.get(RAG_DEFAULTS_KEY) or {}
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if not isinstance(defaults, dict):
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defaults = {}
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per_thread = all_settings.get(thread_settings_key(thread_id)) or {}
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if not isinstance(per_thread, dict):
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per_thread = {}
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explicit = per_thread.get("embedding_model") or defaults.get("embedding_model")
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if explicit:
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return explicit
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mode = per_thread.get("mode") or defaults.get("mode") or "multimodal"
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chunking_strategy = (
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per_thread.get("chunking_strategy")
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or defaults.get("chunking_strategy")
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or "standard"
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)
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return resolve_embedder(mode, chunking_strategy)
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return None
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