72 lines
2.5 KiB
Python
72 lines
2.5 KiB
Python
"""
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Copyright 2024-2026 ChatterMate
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License.
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"""
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from typing import List
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from uuid import UUID
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from agno.tools import Toolkit
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from agno.utils.log import logger
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from app.database import SessionLocal
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from app.models.faq import FAQ
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from app.repositories.faq import FAQRepository
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# Word-overlap ranking beats a whole-string ILIKE here: a visitor's
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# natural-language question rarely appears verbatim in an FAQ, but shares
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# meaningful words with the right one.
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_MIN_WORD_LEN = 3
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_MAX_RESULTS = 5
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class FAQSearchTool(Toolkit):
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"""Lets the help-center answer agent search the org's PUBLISHED FAQs.
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Read-only and org-scoped — never exposes drafts or other orgs' content."""
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def __init__(self, organization_id: UUID):
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super().__init__(name="faq_search")
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self.organization_id = organization_id
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self.register(self.search_faqs)
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def search_faqs(self, query: str) -> str:
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"""Search this help center's published FAQs for a question.
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Args:
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query: What the visitor wants to know.
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"""
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try:
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with SessionLocal() as db:
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faqs = FAQRepository(db).get_published_for_org(self.organization_id)
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ranked = _rank(faqs, query)
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if not ranked:
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return "No published FAQs matched that question."
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return "\n\n".join(f"Q: {faq.question}\nA: {faq.answer}" for faq in ranked)
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except Exception as e:
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logger.error(f"FAQ search failed: {e}")
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return "Error searching the FAQs."
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def _rank(faqs: List[FAQ], query: str) -> List[FAQ]:
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words = {w for w in query.casefold().split() if len(w) > _MIN_WORD_LEN}
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if not words:
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return faqs[:_MAX_RESULTS]
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scored = [
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(len(words & set(f"{faq.question} {faq.answer}".casefold().split())), faq)
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for faq in faqs
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]
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scored = [(score, faq) for score, faq in scored if score > 0]
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scored.sort(key=lambda pair: pair[0], reverse=True)
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return [faq for _score, faq in scored[:_MAX_RESULTS]]
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