12. 세법해석례 RAG

AI 세무사 서비스가 2025년 3월에 출시된다고 합니다. 세무사회, “AI 세무사” 출시…”최신 법령, 예규·판례 등 실시간 검색” 기사에 따르면 LLM 기술과 RAG 기술을 결합하여 최신법령 및 예규․판례 등에 대한 세무서비스를 제공한다고 하는 데요.

국세법령정보시스템에는 13만 건이 넘는 세법해석례 질답 데이터가 있습니다. 세법 해석례 데이터와 Document 모델을 통해 세법해석례 질답 데이터를 저장 및 임베딩하고, 빠르게 문서 RAG를 구현해보겠습니다.

12.1. 데이터 다운로드

RAG를 위해서는 먼저 텍스트 데이터로서 세법해석례 질답 데이터가 필요합니다. 국세법령정보시스템에서는 이 데이터에 대한 API는 제공하지 않기에 직접 데이터를 수집했습니다. 총 13만건의 데이터 중에 샘플로 1000건의 데이터를 링크에서 다운받으실 수 있습니다. 이 중 sample-taxlaw-1000.jsonl 파일 (용량: 44MB)을 사용하겠습니다. 파일은 지금 받지 않으셔도 되구요. 아래에서 코드를 통해 자동 다운로드하겠습니다.

1{"page_content": "{\"문서ID\": \"010000000000001684\", \"제목\": \"건물의 신축・분양 등을 신탁회사에 위탁한 경우 취득가액의 계산 등\", \"문서번호\": \"법인46012-2799\", \"법령분류\": \"법인세\", \"요지\": \"건물의 신축・분양・임대・유지관리를 위탁하고 지급하는 비용의 취득가액, 손금구분 및 양도시 특별부가세 과세표준 계산\", \"회신\": \"부동산임대업 등을 영위하는 법인이 신탁업법에 의한 신탁회사에 건물의 신축․분양․임대․유지관리를 위탁하고 지급하는 신탁수수료 중 건물신축에 따른 신탁수수료는 당해 건물의 취득원가에 산입하고, 분양 등의 수익을 위해서 지출한 신탁수수료는 당해 법인의 각 사업연도 소득금액계산시 손금에 산입하는 것이며, 신탁회사에 위탁하여 신축한 건물을 양도하는 경우 특별부가세과세표준을 계산함에 있어 당해 건물의 취득원가에 산입하는 신탁수수료와 제세공과금(취득세, 등록세 등)은 양도가액에서 공제할 수있는 것이고, 위의 신탁과 관련하여 신탁회사가 위탁자를 대리하여 납부하는 제세공과금은 그 내용에 따라 취득원가(취득세,등록세 등)또는 손비(법인세법상 손금불산입하는 것은 제외)로 처리한다.\", \"파일내용\": \"[ 질 의 ] 1. 부동산신탁과 관련하여 신탁회사에 지급하는 각종 수수료가부동산임대업 등 사업을 영위하는 법인이나 개인사업자의손금이나 필요경비로 인정되는지. 인정되지 않는다면 그 근거는무엇인지 2. 부동산신탁과 관련하여 신탁회사에 지급하는 각종 수수료가양도소득세나 특별부가세 과세표준 계산시 양도가액에서공제받을 수 있는지 질의함\", \"공개여부\": \"공개\", \"문서분류\": \"질의\", \"생성일시\": \"1996-10-09 00:00:00\", \"수정일시\": \"2023-12-08 16:12:13\"}", "metadata": {"url": 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2{"page_content": "{\"문서ID\": \"010000000000025990\", \"제목\": \"성실신고 사업자에 대한 소득세 과세특례 적용 여부\", \"문서번호\": \"서면인터넷방문상담1팀-808\", \"법령분류\": \"종합소득세\", \"요지\": \"개인사업자가 당해 과세연도의 개시일부터 소급하여 1년 이내에 세금계산서 또는 계산서의 미교부 등 사유로 인하여 부가가치세, 소득세를 수정 신고하는 경우에는 성실신고사업장의 소득세 과세특례를 적용받을 수 없는 것임\", \"회신\": \"개인사업자가 당해 과세연도의 개시일부터 소급하여 1년 이내에 세금계산서 또는 계산서의 미교부 등 사유로 인하여 부가가치세․소득세를 수정 신고하는 경우에는 「조세특례제한법」 제122조의 2의 규정에 의한 소득세 과세특례를 적용받을 수 없는 것입니다.\", \"파일내용\": \"\", \"공개여부\": \"공개\", \"문서분류\": \"질의\", \"생성일시\": \"2006-06-19 00:00:00\", \"수정일시\": \"2023-12-08 16:12:13\"}", "metadata": {"url": "https://taxlaw.nts.go.kr/qt/USEQTA002P.do?ntstDcmId=010000000000025990"}, "embedding": [0.019581519, -0.007206708, -0.0100975735, -0.0022516702, 0.06572627, 0.040799376, -0.0112907365, 0.00029722558, 0.021108769, 0.013308887, 0.043362975, -0.021545125, -0.0029573413, -0.01734519, 0.0059828633, -0.023454187, -0.025881423, 0.009245314, 0.016267933, 0.006316949, 6.802098e-05, 0.03267223, -0.029399551, 0.016008846, 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3{"page_content": "{\"문서ID\": \"010000000000055280\", \"제목\": \"월드컵입장권을 종업원들에게 무상 지급시 근로소득 해당여부\", \"문서번호\": \"서일46011-11762\", \"법령분류\": \"종합소득세\", \"요지\": \"월드컵입장권을 구입하여 근로자에게 무상으로 지급한 경우 당해 근로자의 근로소득에 해당하는 것임.\", \"회신\": \"소득세법 제20조의 규정에 의하여 근로소득은 명칭여하에 불구하고 근로를 제공하고 지급받은 모든 대가에서 같은법 제12조 제4호 및 같은법시행령에 열거된 비과세 근로소득만을 제외하는 것으로, 월드컵입장권을 구입하여 근로자에게 무상으로 지급한 경우 당해 근로자의 근로소득에 해당하는 것입니다.\", \"파일내용\": \"1. 질의내용 요약 <월드컵입장권의 근로소득 과세여부> 1. 월드컵행사와 관련하여 재정경제부에서 월드컵 입장권의 발행, 판매에 대하여 부가가치세를 면제하는 특례조항을 조세특례제한법에 신설한 것은 국가적인 행사인 월드컵의 성공적 개최를 지원하기 위한 것임. 2. 월드컵행사의 성공적 개최를 지원한다는 취지에서 본다면, 기업들이 종업원들에게 구입, 배포한 월드컵입장권에 대해서도 근로소득세를 면제하는 것이 타당함. <질의내용> 기업이 월드컵입장권을 구입하여 종업원들에게 무상으로 배포하였을 때 근로소득으로 소득세 과세 여부 2. 질의내용에 대한 자료 가. 관련 조세 법령 (법률, 시행령, 시행규칙, 기본통칙) ○ 소득세법 제20조【근로소득】  ① 근로소득은 당해연도에 발생한 다음 각호의 소득으로 한다. (94.12.22. 개정) 1. 갑 종  가. 근로의 제공으로 인하여 받는 봉급ㆍ급료ㆍ보수ㆍ세비ㆍ임금ㆍ상여ㆍ수당과 이와 유사한 성질의 급여 ○ 소득세법시행령 제38조【근로소득의 범위】 ① 법 ...\", \"공개여부\": \"공개\", \"문서분류\": \"질의\", \"생성일시\": \"2002-12-27 00:00:00\", \"수정일시\": \"2023-12-08 16:12:13\"}", "metadata": {"url": "https://taxlaw.nts.go.kr/qt/USEQTA002P.do?ntstDcmId=010000000000055280"}, "embedding": [-0.000384256, -0.0010157578, -0.0054586525, 0.015422116, 0.0030623341, 0.010977548, -0.022530748, 0.019183934, -0.017443592, 0.010743271, -0.017483752, -0.038046572, 0.015823733, -0.0014567005, 0.015944218, -0.012691116, -0.0021084924, -0.007865012, 0.005505508, -0.005147399, -0.002950216, 0.034672987, 0.031272624, 0.0063187834, -0.03242393, -0.016118253, 0.021111699, 0.02530191, 0.005358248, 0.0196391, 0.0014567005, -0.0012801561, 0.0025385579, -0.068007246, -0.013608143, -0.017015198, 0.035610095, 0.016171802, 0.0141235525, -0.010515687, -0.050228976, -0.013949518, 0.015636312, -0.036520425, -0.0231064, 0.016921489, -0.00028489748, -0.0048495326, -0.03250425, 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jsonl 포맷이며, 각 줄은 page_content, metadata, embedding 필드로 구성됩니다. 별도 임베딩 과정없이 데이터베이스에 즉시 저장하실 수 있도록 page_content 문자열을 미리 text-embedding-3-large 임베딩 모델 (3072차원)로 처리해뒀습니다. 😉

참고

jsonl 포맷은 JSON Lines 텍스트 포맷으로, 각 줄이 하나의 유효한 JSON 객체를 포함하고 있는 텍스트 파일입니다. 각 줄은 줄바꿈 문자(newline)로 구분되며, 각 줄의 JSON 객체는 서로 독립적입니다. 이는 대용량 데이터를 다룰 때 유용한 포맷으로, 스트리밍 처리가 가능하고 메모리 효율적입니다.

12.2. 모델 정의

세법해석례는 빽다방 모델 메뉴와 데이터 성격이 다르니, 별도의 Document 모델로 관리하겠습니다. Document 추상화 모델 페이지에서 다룬 Document 추상화 모델 상속을 상속받고, 인덱스 정의를 추가합니다. Document 모델 디폴트 설정으로 임베딩 모델은 text-embedding-3-small을 사용하고 임베딩 차원은 1536이며 embedding 모델 필드 타입이 VectorField입니다.

chat/models.py
 1class TaxLawDocument(Document):
 2    # category = models.ForeignKey(...)
 3
 4    class Meta:
 5        indexes = [
 6            HnswIndex(
 7                name="taxlaw_doc_idx",
 8                fields=["embedding"],
 9                m=16,
10                ef_construction=64,
11                opclasses=["vector_cosine_ops"],
12            ),
13        ]

그런데, 앞서 살펴본 sample-taxlaw-1000.jsonl 데이터는 text-embedding-3-large 모델을 통해 임베딩 되었기에 3072차원 벡터입니다. 그런데 VectorField 필드는 2000차원까지만 담을 수 있기에 모델 필드 변경이 필요합니다.

12.3. 2000 차원을 넘는 벡터를 저장할려면?

text-embedding-3-small 모델은 1536 차원 벡터를 생성하고, text-embedding-3-large 모델은 3072 차원 벡터를 생성합니다. VectorField 모델 필드는 데이터베이스 타입이 vector 이고 최대 2000 차원까지만 지원하기에 3072 차원 벡터를 저장할 수 없습니다.

HalfVectorField 모델 필드는 데이터베이스 타입이 halfvector 이고 최대 4000 차원까지 지원합니다. 3072차원 벡터를 저장하기에 적합합니다. 아래와 같이 임베딩 모델, 차원수, 필드타입을 변경합니다. 벡터 연산 클래스도 모델 필드 타입에 맞춰 halfvec_cosine_ops로 변경해야만 합니다.

chat/models.py
 1from pgvector.django import HalfVectorField
 2
 3class TaxlawDocument(Document):
 4    embedding_model = "text-embedding-3-large"
 5    embedding_dimensions = 1536 * 2
 6
 7    embedding = HalfVectorField(
 8        dimensions=embedding_dimensions, editable=False
 9    )
10
11    class Meta:
12        indexes = [
13            HnswIndex(
14                name="taxlaw_doc_idx",
15                fields=["embedding"],
16                m=16,
17                ef_construction=64,
18                opclasses=["halfvec_cosine_ops"],  # halfvec 타입용 코사인 거리 연산 클래스
19            ),
20        ]

코사인 거리를 사용할 때

  • VectorField 타입에서는 vector_cosine_ops를 사용하셔야 하며,

  • HalfVectorField 타입에서는 halfvec_cosine_ops를 사용하셔야 합니다.

이를 맞춰주지 않으시면, makemigrations 단계에서는 오류가 발생하지 않지만 migrate 단계에서 데이터베이스 단에서 오류가 발생하여 마이그레이션에 실패합니다.

그런데, migrate 단계에서 오류를 만나는 것은 너무 늦죠. 모델 코드를 수정하는 즉시 그 오류 상황을 인지할 수 있으면 베스트일 텐데요. 이를 위해 장고에서는 System check framework를 지원해줍니다.

12.4. check 프레임워크를 통한 모델 설정 검증

장고에서는 System check framework를 통해 장고 프로젝트 내 다양한 문제들을 파악하고 이를 수정할 수 있는 힌트를 제공해줍니다. manage.py check 명령을 통해 명시적으로 실행할 수도 있고, manage.py runserver, manage.py migrate 명령에서 자동으로 수행됩니다.

이를 활용하면, embedding_dimensions 설정은 3072로 지정했는 데, embedding 필드는 HalfVectorField가 아닌 VectorField일 경우에는 아래와 같은 에러 메시지를 남길 수 있게 됩니다.

../_images/system-check-1.png

Document 모델의 임베딩 관련 설정과 필드를 검증하도록 하겠습니다.

  • embedding_dimensions 속성과 embedding 필드가 정의되어 있는지 확인

  • 차원 수에 따른 적절한 벡터 필드 타입 사용 여부 확인

    • 2000차원 이하: VectorField 사용 가능

    • 2000차원 초과: HalfVectorField 필수

  • 벡터 필드 타입에 맞는 연산자 클래스 사용 확인

    • HNSW, IVFFlat 인덱스 타입 확인

각 에러 메시지는 debug, info, warning, error, critical 레벨을 지원합니다.

chat/models.py
from django.core import checks
from django.core.exceptions import FieldDoesNotExist
from pgvector.django import IvfflatIndex

class Document(models.Model):
    # ...

    @classmethod
    def check(cls, **kwargs):
        embedding_field_name = "embedding"

        errors = super().check(**kwargs)

        def add_error(msg: str, hint: str = None):
            errors.append(checks.Error(msg, hint=hint, obj=cls))

        embedding_dimensions: int = getattr(cls, "embedding_dimensions", None)
        if embedding_dimensions is None:
            add_error(
                "embedding_dimensions 클래스 변수가 누락되었습니다.",
                hint="embedding_dimensions 설정을 추가해주세요.",
            )

        try:
            embedding_field = cls._meta.get_field(embedding_field_name)
        except FieldDoesNotExist:
            add_error(
                f"{embedding_field_name} 필드가 누락되었습니다.",
                hint="embedding 필드를 추가해주세요.",
            )
        else:
            if embedding_dimensions > 2000:
                if not isinstance(embedding_field, HalfVectorField):
                    add_error(
                        f"{embedding_dimensions} 차원은 {embedding_field.__class__.__name__}에서 지원하지 않습니다.",
                        hint=f"{embedding_dimensions} 차원 이상은 HalfVectorField를 사용해주세요.",
                    )

            for index in cls._meta.indexes:
                if embedding_field_name in index.fields:
                    if isinstance(index, (HnswIndex, IvfflatIndex)):
                        if embedding_dimensions <= 2000:
                            for opclass_name in index.opclasses:
                                if "halfvec_" in opclass_name:
                                    add_error(
                                        f"{embedding_field.name} 필드는 {embedding_field.__class__.__name__} 타입으로서 "
                                        f"{opclass_name}를 지원하지 않습니다.",
                                        hint=f"{opclass_name.replace('halfvec_', 'vector_')}로 변경해주세요.",
                                    )
                        else:
                            for opclass_name in index.opclasses:
                                if "vector_" in opclass_name:
                                    add_error(
                                        f"{embedding_field.name} 필드는 {embedding_field.__class__.__name__} 타입으로서 "
                                        f"{opclass_name}를 지원하지 않습니다.",
                                        hint=f"{opclass_name.replace('vector_', 'halfvec_')}로 변경해주세요.",
                                    )
                    else:
                        add_error(
                            f"Document 모델 check 메서드에서 {index.__class__.__name__}에 대한 확인이 누락되었습니다.",
                            hint=f"{index.__class__.__name__} 인덱스에 대한 check 루틴을 보완해주세요.",
                        )

        return errors

TaxLawDocument 모델에서 embedding 필드 재정의 코드를 제거하시면, 부모의 VectorField 타입으로 동작할 것이구요. 아래의 시스템 체크 오류 메시지를 확인하실 수 있습니다. :-)

../_images/system-check-1.png

이제 설정에 오류가 있어도, 장고에서 알려주기에 부담없이 모델을 작성하실 수 있겠죠? 😉

12.5. 데이터 붓기

모델과 마이그레이션이 오류없이 잘 구성되었습니다. 마이그레이션을 수행해서 데이터베이스에 테이블을 생성해줍니다.

uv run python manage.py makemigrations chat
uv run python manage.py migrate chat

장고 쉘을 구동하시고 아래 코드를 실행하시면, 1000건의 세법 해석례 jsonl 데이터를 자동으로 다운받고, TaxLawDocument 모델을 통해 Postgres 데이터베이스에 데이터를 저장합니다.

# uv run python manage.py shell_plus --print-sql

import json
from urllib.request import urlopen

from chat.models import TaxLawDocument

jsonl_url = "https://github.com/pyhub-kr/dump-data/raw/refs/heads/main/rag/sample-taxlaw-1000.jsonl"

print(f"Downloading {jsonl_url} ...")
res_data: bytes = urlopen(jsonl_url).read()
print(f"Downloaded {len(res_data)} bytes.")
jsonl_data: str = res_data.decode("utf-8")

doc_list = []
for line in jsonl_data.splitlines():
    obj = json.loads(line)
    doc_list.append(
        TaxLawDocument(
            page_content=obj["page_content"],
            metadata=obj["metadata"],
            embedding=obj["embedding"],
        )
    )

print(f"Creating {len(doc_list)} documents...")
TaxLawDocument.objects.bulk_create(doc_list)
print("Saved.")

total = TaxLawDocument.objects.all().count()
print(f"Total: {total}")

실행결과

Downloading https://github.com/pyhub-kr/dump-data/raw/refs/heads/main/rag/sample-taxlaw-1000.jsonl ...
Downloaded 44343331 bytes.
Creating 1000 documents...
INSERT INTO "chat_taxlawdocument" ("page_content", "metadata", "created_at", "updated_at", "embedding")
VALUES ('{"문서ID": "010000000000001684", "제목": "건물의 신축・분양 등을 신탁회사에 위탁한 경우 취득가액의 계산 등", "문서번호": "법인46012-2799", "법령분류": "법인세", "요지": "건물의 신축・분양・임대・유지관리를 위탁하법인이 신탁업법에 의한 신탁회사에 건물의 신축․분양․임대․유지관리를 위탁하고 지급하는 신탁수수료 중 건물신축에 따른 신탁수수료는 당해 건물의 취득원가에 산입하고, 분양 등의 수익을 위해서 지출한 신탁수수료는 당해 법인의 각 건물을 양도하는 경우 특별부가세과세표준을 계산함에 있어 당해 건물의 취득원가에 산입하는 신탁수수료와 제세공과금(취득세, 등록세 등)은 양도가액에서 공제할 수있는 것이고, 위의 신탁과 관련하여 신탁회사가 위탁자를 대리하여[.., '{"url": "https://taxlaw.nt

Execution time: 36.341453s [Database: default]
Saved.
SELECT COUNT(*) AS "__count"
FROM "chat_taxlawdocument"

Execution time: 0.009042s [Database: default]
Total: 1000

데이터베이스에 접속하여 chat_taxlawdocument 테이블을 조회해보면, 1000건의 데이터가 저장된 것을 확인할 수 있습니다.

../_images/tax-raw-table.png

파이참을 통해 조회해본 chat_taxlawdocument 테이블 데이터

12.6. 질문과 유사한 세법해석례 문서 찾기

세법해석례 RAG를 위한 데이터가 모두 준비되었습니다. 장고 쉘에서 TaxLawDocument 모델의 search 메서드를 호출하여 질문과 유사한 세법해석례 문서를 찾아보겠습니다.

question = "재화 수출하는 경우 영세율 첨부 서류로 수출실적명세서가 없는 경우 해결 방법"
doc_list = await TaxLawDocument.objects.search(question)
for idx, doc in enumerate(doc_list, 1):
    print(f"문서 #{idx} : 코사인 거리 {doc.distance:.3f}")
    print(doc)
    print()

아래와 같이 실행되고, 총 4개의 문서가 검색되었습니다. search 메서드에서는 디폴트로 4개의 문서를 반환토록 구현되어 있습니다. 검색된 문서 내용을 살펴보시면 문서 #1에서 “수출실적명세서” 문서가 검색됨을 확인하실 수 있습니다.

SELECT "chat_taxlawdocument"."id",
    "chat_taxlawdocument"."page_content",
    "chat_taxlawdocument"."metadata",
    "chat_taxlawdocument"."created_at",
    "chat_taxlawdocument"."updated_at",
    "chat_taxlawdocument"."embedding", ("chat_taxlawdocument"."embedding" <=> '[0.012661192566156387,
    0.00366991083137691,
    -0.006133993621915579,

Execution time: 0.037542s [Database: default]

문서 #1 : 코사인 거리 0.425
Document(metadata={'url': 'https://taxlaw.nts.go.kr/qt/USEQTA002P.do?ntstDcmId=010000000000035248'}, page_content='{"문서ID": "010000000000035248", "제목": "직수출 재화의 영세율 첨부서류", "문서번호": "서삼46015-12043", "법령분류": "부가가치세", "요지": "수출하는 재화의 영세율 첨부서류는 수출실적명세서로 하는 것이나 외화획득내역을 입증할 수 있는 증빙서류로 갈음할 수 있음", "회신": "부가가치세법 제11조 제1항 제1호 및 동법 시행령 제24조 제1항 제1호의 규정에 의한 부가가치세 영세율이 적용되는 수출하는 재화에 있어서 부가가치세 예정신고 또는 확정신고시에 제출하여야 하는 영세율 첨부서류는 동법 시행령 제64조 제3항 제1호의 규정에 의한 재정경제부령이 정하는 수출실적명세서(전자계산조직에 의하여 처리된 테이프 또는 디스켓을 포함하며, 소포우편에 의하여 수출한 경우에는 당해 우체국장이 발행하는 소포수령증)로 하는 것이나,        부득이한 사유로 인하여 당해 서류를 첨부할 수 없는 때에는 국세청장이 정하는 서류로써 갈음할 수 있는 것이며, 법령 또는 훈령에 정한 서류를 제출할 수 없는 경우에는 영세율 규정에 의한 외화획득명세서에 당해 외화획득내역을 입증할 수 있는 증빙서류를 첨부하여 제출하는 것입니다.", "파일내용": "1. 질의내용 요약 당사는 직수출시 수출실적명세서에 수출대금입금증명서를 첨부하고 내국신용장이니 구매확인서에 의하는 경우 관련 사본을 첨부하여 부가세 신고를 하여왔던 바, 타업체에 의하면 2002년 7월부터는 직수출의 경우에는 수출실적명세서만을 첨부하여 신고가능하다고 하는 바, 이의 타당여부? 2. 질의내용에 대한 자료 가. 관련 조세법령(법률,시행령,시행규칙) ○ 부가가치세법 제11조 【영세율 적용】 ① 다음 각호의 재화 또는 용역의 공급에 대하여는 영의 세율을 적용한다. 1. 수출하는 재화 ○ 부가가치세법 시행령 제24조 【수출의 범위】 ① 법 제11조 제1항 제1호의 규정에 의한 수출은 다음 각호의 것으로 한다.(2001. 12. 31 개정) 1. 내국물품(우리나라 선박에 의하여 채포된 수산물을 포함한다)을 외국으로 반출하는 것  2. 국내의 사업장에서 계약과 대가수령 등 거래가 이루어지는 것으로서 다음 각목의 1에 해당하는 것 (2001. 12. 31 개정) 가. 대외무역법에 ...", "공개여부": "공개", "문서분류": "질의", "생성일시": "2003-12-31 00:00:00", "수정일시": "2023-12-08 16:12:13"}')

문서 #2 : 코사인 거리 0.433
Document(metadata={'url': 'https://taxlaw.nts.go.kr/qt/USEQTA002P.do?ntstDcmId=010000000000009322'}, page_content='{"문서ID": "010000000000009322", "제목": "국제기구에 납품하는 재화의 영세율 첨부서류", "문서번호": "부가1265.1-1676", "법령분류": "부가가치세", "요지": "국제기구 납품재화의 영세율 첨부서류는 수출대금입금증명서 또는 당해 외국정부기관 등이 발급한 납품사실을 증명할 수 있는 서류임", "회신": "영세율 첨부서류는 부가가치세법시행령 제64조 제3항 제6호에 규정한 수출대금입금증명서 또는 당해 외국정부기관 등이 발급한 납품사실을 증명할 수 있는 서류이나, 당해 서류를 부득이한 사유로 인하여 제출할 수 없는 경우에는 외화입금증명서 또는 외환매입증명서나 외국환매각증명서를 첨부한다. (영 제64조 제3항 제6호, ’82. 12. 31 개정)", "파일내용": "", "공개여부": "공개", "문서분류": "질의", "생성일시": "1982-06-24 00:00:00", "수정일시": "2023-12-08 16:12:13"}')

문서 #3 : 코사인 거리 0.509
Document(metadata={'url': 'https://taxlaw.nts.go.kr/qt/USEQTA002P.do?ntstDcmId=010000000000008161'}, page_content='{"문서ID": "010000000000008161", "제목": "영세율 첨부서류의 미제출시 영세율 적용 여부", "문서번호": "간세1235-2578", "법령분류": "부가가치세", "요지": "영세율 적용대상 과세표준에 대한 신고 시 신고불이행, 신고누락, 첨부서류의 미제출에 관계없이 사실상 적용대상임이 확인되는 경우 영세율이 적용됨", "회신": "사업자가 영세율 적용대상 과세표준에 대하여 예정신고 또는 확정신고 시 신고불이행, 신고누락, 첨부서류의 미제출에 관계없이 사실상 영세율 적용대상임이 확인되는 경우에 한하여 영세율이 적용된다.", "파일내용": "", "공개여부": "공개", "문서분류": "질의", "생성일시": "1978-09-08 00:00:00", "수정일시": "2023-12-08 16:12:13"}')

문서 #4 : 코사인 거리 0.524
Document(metadata={'url': 'https://taxlaw.nts.go.kr/qt/USEQTA002P.do?ntstDcmId=010000000000099002'}, page_content='{"문서ID": "010000000000099002", "제목": "수정세금계산서를 교부하여야 하는지 여부", "문서번호": "부가22601-1789", "법령분류": "부가가치세", "요지": "수출품생산업자가 수출신용장을 수출업자에게 양도하고 수출대행계약을 체결하여 재화를 수출하는 경우 세금계산서 교부의무가 면제되는 것이나, 수출품생산업자가 이를 착오로 세금계산서를 교부한 경우 수정세금계산서를 교부하여야 하는 것임", "회신": "1. 귀 질의1의 경우 수출품생산업자가 수출신용장을 수출업자에게 양도하고 수출대행계약을 체결하여 재화를 수출하는 경우에는 당해 수출품생산업자가 수출업자로부터 완제품내국신용장을 개설받았다하더라도 세금계산서 교부의무가 면제되는 것이나, 수출품생산업자가 이를 착오하여 세금계산서를 교부한 경우에는 부가가치세법 시행령 제59조의 규정에 의하여 수정세금계산서를 교부하여야 하는 것이며  2. 귀 질의2의 경우는 별첨 소득세 기본통칙 3-1-4...28을 참고.", "파일내용": "1. 질의내용 요약 ○ 수출업자(A)로써 대행 수출시 수출품생산업자(B)에게 수출대행계약서와 함께 완제품 내국신용장을 개설하여 주었습니다. 부가세법 16조 (통칙5-2-12)에는 이러한 경우에도 세금계산서 교부가 면제된다고 되어 있는데 실질적인 거래에서는 B가 A앞으로 세금계산서를 발행하여야 은행에서 NEGO가 되며 결재됩니다. 이럴때 세금계산서 처리 문제를 A입장에서 질의함. 가. 부가세 신고시 발행된 매입세금계산서 나. 소득세에서의 수입금액에의 포함여부. 2. 관련 조세 법령 (법률, 시행령, 시행규칙, 기본통칙) ○ 부가가치세법 시행령 제59조 ○ 소득세법 기본통칙 3-1-4...28 【수출대행의 경우 총수입금액】", "공개여부": "공개", "문서분류": "질의", "생성일시": "1987-08-31 00:00:00", "수정일시": "2023-12-08 16:12:13"}')

12.7. 세법해석례 RAG 챗봇 구현

이제 아래의 시스템 프롬프트를 적용하여 세법해석례 RAG를 구현해보겠습니다. 먼저 시스템 프롬프트를 정의하고, 질문과 유사한 문서를 검색하구요.

시스템 프롬프트 예시
 1system_prompt = """
 2대한민국 세무/회계 정보 챗봇으로서, 주어진 질답 지식에서 사실과 의견을 구별하여 사실 정보만을 정리하고,
 3각 답변에 해당 정보의 출처까지 함께 기입하여 답변하세요.
 4
 5# Steps
 6
 71. 이해하기: 질문과 제공된 지식을 주의 깊게 읽고 정확히 이해합니다.
 82. 정보 구분하기: 질답 지식에서 사실과 의견을 식별합니다.
 9  - 사실: 검증 가능한 데이터, 법률, 규정 및 수치 등
10  - 의견: 개인의 견해, 해석, 추천 등
113. 사실 정리하기: 식별된 사실 정보를 논리적이고 명확하게 정리하며, 불필요한 부분은 제거합니다.
124. 답변 작성하기: 정리된 사실 정보를 바탕으로 명료하고 간결한 문장으로 구성된 단락 형태의 답변을 작성합니다. 반드시 해당 사실 정보의 출처를 함께 명시합니다.
13  - 가능한 경우 신뢰할 수 있는 출처(예: 정부 기관, 공식 문서, 학술자료 등)를 포함합니다.
14  - 출처가 확인되지 않거나 없는 경우, “출처를 찾을 수 없습니다”라고 명시합니다.
15  - 출처에 문서ID가 포함된 경우, 반드시 문서ID를 기입하고 아래 URL 형식을 참고하여 해당 URL도 함께 포함합니다.
16
17# Output Format
18
19- 명료하고 간결한 문장으로 구성된 단락 형태의 답변
20- 답변 내에 사용한 정보의 출처를 반드시 포함하여 작성
21
22# Notes
23
24- 각 세무/회계 정보를 객관적으로 평가하여 답변을 작성합니다.
25- 모호하거나 불확실한 정보는 제외합니다.
26- 답변에 반드시 관련 사실 정보의 출처를 함께 기입하여 객관성과 신뢰성을 높입니다.
27"""
28
29question = "재화 수출하는 경우 영세율 첨부 서류로 수출실적명세서가 없는 경우 해결 방법"
30
31# 지식 검색
32doc_list = await TaxLawDocument.objects.search(question)
33print(f"{len(doc_list)}개의 문서가 검색되었습니다.")
34for idx, doc in enumerate(doc_list, 1):
35    print(f"문서 #{idx} : 코사인 거리 {doc.distance:.3f}")
36    print(doc)
37    print()
38
39context = str(doc_list)  # 지식 컨텍스트 문자열 생성

앞서 검색된 지식과 질문을 LLM 모델엔 제공하여, RAG 챗봇을 완성합니다. LLM 모델에 따라 답변 결과가 다르므로, 여러 모델을 활용하여 최적의 답변을 찾아봅니다. 이중 Anthropic 모델이 가장 마음에 드네요.

위에서 선언한 system_prompt, context, question 변수를 활용합니다.

import os
import openai

client = openai.AsyncClient(api_key=os.getenv("OPENAI_API_KEY"))
response = await client.chat.completions.create(
    model="gpt-4o-mini",
    # model="gpt-4o",
    messages=[
        {"role": "system", "content": system_prompt + f"\n\n참고 문서: {context}"},
        {"role": "user", "content": question},
    ],
)
print(response.usage, end="\n\n")
print("[AI]", response.choices[0].message.content)

gpt-4o-mini 실행 결과

CompletionUsage(completion_tokens=180, prompt_tokens=2623, total_tokens=2803, completion_tokens_details=CompletionTokensDetails(accepted_prediction_tokens=0, audio_tokens=0, reasoning_tokens=0, rejected_prediction_tokens=0), prompt_tokens_details=PromptTokensDetails(audio_tokens=0, cached_tokens=0))

[AI] 재화 수출 시 영세율 적용을 위한 첨부 서류로 수출실적명세서를 제출할 수 없는 경우, 외화획득내역을 입증할 수 있는 증빙서류를 대신 첨부하여 제출할 수 있습니다. 이는 부가가치세법 시행령 제64조 및 관련 지침에 따른 것입니다. 따라서, 만약 수출실적명세서를 제출할 수 없는 상황이라면, 해당 외화획득내역을 입증할 수 있는証빙서류를 준비하여 제출하면 됩니다.

출처: 부가가치세법 시행령 제64조, [문서ID: 010000000000035248](https://taxlaw.nts.go.kr/qt/USEQTA002P.do?ntstDcmId=010000000000035248)

gpt-4o 실행 결과

CompletionUsage(completion_tokens=171, prompt_tokens=2623, total_tokens=2794, completion_tokens_details=CompletionTokensDetails(accepted_prediction_tokens=0, audio_tokens=0, reasoning_tokens=0, rejected_prediction_tokens=0), prompt_tokens_details=PromptTokensDetails(audio_tokens=0, cached_tokens=0))

[AI] 재화 수출 시 영세율 첨부서류로 수출실적명세서를 제공할 수 없는 경우, 국세청장이 정하는 다른 서류로 대체할 수 있습니다. 예를 들어, 외화 획득 내역을 입증할 수 있는 증빙서류를 첨부하여 영세율을 적용받을 수 있습니다. 이는 “부가가치세법 제11조 제1항 제1호” 및 동법 시행령 제24조 제1항 제1호의 규정에 명시되어 있습니다.

출처: [국세청 문서ID 010000000000035248](https://taxlaw.nts.go.kr/qt/USEQTA002P.do?ntstDcmId=010000000000035248)

Anthropic API Keys 페이지를 통해 API Key 발급받으시고, ANTHROPIC_API_KEY 환경변수로서 로딩해주세요. anthropic 라이브러리가 필요합니다. 지원 모델은 Anthropic API 문서 참고하세요.

import os
from anthropic import Anthropic

client = Anthropic(api_key=os.getenv("ANTHROPIC_API_KEY"))
response = client.messages.create(
    max_tokens=1024,
    model="claude-3-5-sonnet-latest",
    # model="claude-3-5-haiku-latest",
    messages=[
        {
            "role": "user",
            "content": system_prompt
            + "\n"
            + context
            + "\n\nQuestion: "
            + question,
        },
    ],
)
print(response.usage, end="\n\n")
print("[AI]", "\n".join(block.text for block in response.content))

claude-3-5-sonnet-latest 실행 결과

Usage(cache_creation_input_tokens=0, cache_read_input_tokens=0, input_tokens=3730, output_tokens=555)

[AI] 부가가치세 영세율 관련 첨부서류에 대해 다음과 같이 답변 드립니다:

1. 기본적인 첨부서류 - 재화 수출 시 부가가치세 예정신고 또는 확정신고 시 제출해야 하는 기본 첨부서류는 수출실적명세서입니다. - 전자계산조직에 의한 테이프나 디스켓도 포함되며, 소포우편 수출의 경우 우체국장이 발행하는 소포수령증으로 대체 가능합니다.

2. 수출실적명세서를 제출할 수 없는 경우의 대체 방안 - 부득이한 사유로 수출실적명세서를 첨부할 수 없는 경우, 국세청장이 정하는 서류로 대체할 수 있습니다. - 법령이나 훈령에 정한 서류를 제출할 수 없는 경우, 외화획득명세서에 해당 외화획득내역을 입증할 수 있는 증빙서류를 첨부하여 제출할 수 있습니다.

출처: 국세청 세무사례, 문서ID: 010000000000035248 URL: https://taxlaw.nts.go.kr/qt/USEQTA002P.do?ntstDcmId=010000000000035248

참고사항: 영세율 적용대상임이 사실상 확인되는 경우에는 첨부서류 미제출에 관계없이 영세율이 적용됩니다. 출처: 국세청 세무사례, 문서ID: 010000000000008161 URL: https://taxlaw.nts.go.kr/qt/USEQTA002P.do?ntstDcmId=010000000000008161

claude-3-5-haiku-latest 실행 결과

Usage(cache_creation_input_tokens=0, cache_read_input_tokens=0, input_tokens=3730, output_tokens=455)

[AI] 재화 수출 시 영세율 첨부 서류와 관련하여 다음과 같은 사실을 정리할 수 있습니다:

수출하는 재화의 영세율 첨부서류는 원칙적으로 수출실적명세서이나, 부득이한 사유로 해당 서류를 첨부할 수 없는 경우 대체 방법이 있습니다. 이 경우 국세청장이 정하는 서류로 대체할 수 있으며, 구체적으로는 외화획득명세서에 외화획득내역을 입증할 수 있는 증빙서류를 첨부하여 제출할 수 있습니다.

출처: - 국세청 세무해석 문서 (문서ID: 010000000000035248) - URL: https://taxlaw.nts.go.kr/qt/USEQTA002P.do?ntstDcmId=010000000000035248

추가로, 국세청은 사실상 영세율 적용대상임이 확인되는 경우 신고불이행, 신고누락, 첨부서류 미제출에도 불구하고 영세율을 적용할 수 있음을 명확히 하고 있습니다.

출처: - 국세청 세무해석 문서 (문서ID: 010000000000008161) - URL: https://taxlaw.nts.go.kr/qt/USEQTA002P.do?ntstDcmId=010000000000008161

Google AI Studio 페이지를 통해 API Key 발급받으시고, GEMINI_API_KEY 환경변수로서 로딩해주세요. google-genai 라이브러리를 통해서 API를 호출합니다.

import os
from google import genai
from google.genai import types

client = genai.Client(api_key=os.getenv("GEMINI_API_KEY"))

response = client.models.generate_content(
    model="gemini-2.0-flash",
    config=types.GenerateContentConfig(
        system_instruction=system_prompt + f"\n\n참고 문서: {context}",
    ),
    contents=question,
)
print(response.usage_metadata, end="\n\n")
print("[AI]", response.text)

실행 결과

cached_content_token_count=None candidates_token_count=250 prompt_token_count=3025 total_token_count=3275

[AI] 수출하는 재화에 대한 부가가치세 영세율 적용 시, 원칙적으로는 수출실적명세서를 제출해야 합니다. 하지만 부득이한 사유로 수출실적명세서를 첨부할 수 없는 경우에는 국세청장이 정하는 서류로 대체할 수 있습니다. 이때, 영세율 적용을 위해 외화획득명세서에 해당 외화획득 내역을 입증할 수 있는 증빙서류를 첨부하여 제출해야 합니다. (출처: 국세법령정보시스템, 문서번호 서삼46015-12043, URL: [https://taxlaw.nts.go.kr/qt/USEQTA002P.do?ntstDcmId=010000000000035248](https://taxlaw.nts.go.kr/qt/USEQTA002P.do?ntstDcmId=010000000000035248))

DeepSeek 공식문서 참고하셔서 API Key 발급받으시고 DEEPSEEK_API_KEY 환경변수로서 로딩해주세요. openai 라이브러리를 통해서 딥시크 API를 호출합니다. api_key 항목에는 딥시크 API Key를 입력하시고 base_url 항목에는 https://api.deepseek.com을 입력해주세요. 나머진 OpenAI 라이브러리 사용법과 동일합니다.

import os
import openai

client = openai.AsyncClient(
    api_key=os.getenv("DEEPSEEK_API_KEY"),
    base_url="https://api.deepseek.com",
)
response = await client.chat.completions.create(
    model="deepseek-chat",
    messages=[
        {"role": "system", "content": system_prompt + f"\n\n참고 문서: {context}"},
        {"role": "user", "content": question},
    ],
)
print(response.usage, end="\n\n")
print("[AI]", response.choices[0].message.content)

계정 잔고를 확인해주세요.

계정 잔고가 없으면 아래 Insufficient Balance 오류가 발생합니다.

APIStatusError: Error code: 402 - {'error': {'message': 'Insufficient Balance', 'type': 'unknown_error', 'param': None, 'code': 'invalid_request_error'}}

deepseek-chat 모델은 DeepSeek-V3 모델을 통해 처리되며, deekseek-reasoner 모델은 DeepSeek-R1 모델을 통해 처리됩니다.

Claude Sonnet API가 가장 비싸지만 저는 가장 좋은 답변으로 와닿았습니다. OpenAI는 이과 감성, Claude API가 문과 감성이 있는 느낌입니다.

API 가격

각 모델의 답변과 API 가격을 참고해서, 비용 대비 최적의 모델을 상황에 맞춰 사용하세요.

OpenAI API 가격, Anthropic API 가격, Google API 가격, DeepSeek API 가격

모델

Input 토큰 가격 (1백만 토큰)

Output 토큰 가격 (1백만 토큰)

OpenAI gpt-4o-mini

$0.15

$0.60

OpenAI gpt-4o

$2.50

$10.00

Anthropic Claude 3.5 Haiku

$0.80

$4.00

Anthropic Claude 3.5 Sonnet

$3.00

$15.00

DeepSeek deepseek-chat

$0.14

$0.28

DeekSeek deepseek-reasoner

$0.55

$2.19