colcaroli
234ebba103
Introduces websearch.py (Tavily) + knowledge.py to ground chat responses in search results, tagging.py to tag user and assistant messages via LLM and pick related topics for the Discord useless-tips job, and word_memory.py to track recent conversation nouns (surfaced in the new WordPool.vue sidebar) used to pick tip topics close to a related tag.
38 lines
1.4 KiB
Python
38 lines
1.4 KiB
Python
from sqlalchemy.orm import Session as DBSession
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from app.core.config import KNOWLEDGE_CONTEXT_LIMIT
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from app.db.models import KnowledgeEntry, KnowledgeSource
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def save_knowledge(db: DBSession, query: str, summary: str, sources: list[dict]) -> KnowledgeEntry:
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"""Web検索で得た知見をDBに保存する。"""
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entry = KnowledgeEntry(query=query, summary=summary)
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db.add(entry)
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db.flush()
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for src in sources:
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if not src.get("url"):
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continue
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db.add(KnowledgeSource(entry_id=entry.id, title=src.get("title", ""), url=src["url"]))
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db.commit()
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db.refresh(entry)
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return entry
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def get_knowledge_context(db: DBSession) -> str | None:
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"""蓄積された知識を、システムプロンプトに注入できる形のテキストにして返す。"""
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entries = (
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db.query(KnowledgeEntry)
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.order_by(KnowledgeEntry.created_at.desc())
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.limit(KNOWLEDGE_CONTEXT_LIMIT)
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.all()
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)
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if not entries:
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return None
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blocks = []
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for entry in reversed(entries):
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urls = ", ".join(s.url for s in entry.sources) or "出典不明"
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blocks.append(f"- 「{entry.query}」について: {entry.summary}\n (出典: {urls})")
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return "以下はこれまでのWeb検索で得た知識です。関連する話題が出たら活用してください:\n\n" + "\n".join(blocks)
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