transformation 섹션 정보 출력

db-migration
jaehwang 2026-06-02 16:21:19 +09:00
parent 484ee41810
commit 2232273200
4 changed files with 45 additions and 2 deletions

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@ -6,6 +6,7 @@ from integrations.llm.schemas.report import (
CriticalIssuesInput, CriticalIssuesOutput, CriticalIssuesInput, CriticalIssuesOutput,
YouTubeDiagnosisInput, YouTubeDiagnosisOutput, YouTubeDiagnosisInput, YouTubeDiagnosisOutput,
BrandConsistencyInput, BrandConsistencyOutput, BrandConsistencyInput, BrandConsistencyOutput,
TransformationInput, TransformationProposal,
) )
from integrations.llm.schemas.plan import PlanInput, PlanOutput from integrations.llm.schemas.plan import PlanInput, PlanOutput
from integrations.llm.schemas.market import ( from integrations.llm.schemas.market import (
@ -106,3 +107,10 @@ critical_issues_prompt = Prompt(
input_class=CriticalIssuesInput, input_class=CriticalIssuesInput,
output_class=CriticalIssuesOutput, output_class=CriticalIssuesOutput,
) )
transformation_prompt = Prompt(
file_name="transformation_prompt.txt",
prompt_model="REPORT_MODEL",
input_class=TransformationInput,
output_class=TransformationProposal,
)

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@ -368,6 +368,13 @@ class CriticalIssuesOutput(BaseModel):
diagnosis: list[DiagnosisItem] diagnosis: list[DiagnosisItem]
# --- Transformation ---
class TransformationInput(BaseModel):
clinic_name: str | None = None
data: str | None = None
# --- BrandConsistency --- # --- BrandConsistency ---
class BrandConsistencyInput(BaseModel): class BrandConsistencyInput(BaseModel):

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@ -0,0 +1,14 @@
다음은 성형외과/피부과 {clinic_name} 의 전 채널 수집 데이터입니다.
{data}
위 데이터를 바탕으로 이 병원의 마케팅 전환 전략을 수립해줘.
아래 5개 항목을 포함한 JSON을 출력해줘.
1. brand_identity: 브랜드 아이덴티티 개선 항목 (area, as_is, to_be)
2. content_strategy: 콘텐츠 전략 개선 항목 (area, as_is, to_be)
3. platform_strategies: 플랫폼별 전략 (platform, icon, current_metric, target_metric, strategies[{strategy, detail}])
4. website_improvements: 웹사이트 개선 항목 (area, as_is, to_be)
5. new_channel_proposals: 신규 채널 제안 (channel, priority, rationale)
출처 번호([1], [2] 등)는 포함하지 마.

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@ -8,8 +8,8 @@ from common.db.run import select_run, update_run_report, update_run_plan
from common.db.source import select_run_raw_data, select_run_mainpage_url from common.db.source import select_run_raw_data, select_run_mainpage_url
from common.db.market import select_market from common.db.market import select_market
from integrations.llm.llm_service import LLMService from integrations.llm.llm_service import LLMService
from integrations.llm.prompt import report_prompt, plan_prompt, youtube_diagnosis_prompt, brand_consistency_prompt, critical_issues_prompt from integrations.llm.prompt import report_prompt, plan_prompt, youtube_diagnosis_prompt, brand_consistency_prompt, critical_issues_prompt, transformation_prompt
from integrations.llm.schemas.report import ReportOutput, ClinicSnapshot, YouTubeAudit, BrandConsistencyOutput, CriticalIssuesOutput, DiagnosisItem from integrations.llm.schemas.report import ReportOutput, ClinicSnapshot, YouTubeAudit, BrandConsistencyOutput, CriticalIssuesOutput, DiagnosisItem, TransformationProposal
from integrations.llm.schemas.plan import PlanOutput from integrations.llm.schemas.plan import PlanOutput
logger = logging.getLogger(__name__) logger = logging.getLogger(__name__)
@ -208,6 +208,17 @@ async def _build_youtube_audit(youtube: dict) -> dict:
return YouTubeAudit.model_validate(yt_patch).model_dump() return YouTubeAudit.model_validate(yt_patch).model_dump()
async def _build_transformation(analysis_run_id: str, raw: dict) -> dict:
result: TransformationProposal = await LLMService(provider="perplexity").generate(
transformation_prompt,
{
"clinic_name": (raw.get("mainpage") or {}).get("clinicName"),
"data": json.dumps(raw, ensure_ascii=False),
},
)
return result.model_dump()
async def _build_critical_issues(analysis_run_id: str, raw: dict) -> list[dict]: async def _build_critical_issues(analysis_run_id: str, raw: dict) -> list[dict]:
result: CriticalIssuesOutput = await LLMService(provider="perplexity").generate( result: CriticalIssuesOutput = await LLMService(provider="perplexity").generate(
critical_issues_prompt, critical_issues_prompt,
@ -255,6 +266,7 @@ async def _build_overrides(analysis_run_id: str) -> dict:
brand = await generate_brand_consistency(analysis_run_id) brand = await generate_brand_consistency(analysis_run_id)
brand_patch = brand.model_dump()["brand_inconsistencies"] brand_patch = brand.model_dump()["brand_inconsistencies"]
critical_issues = await _build_critical_issues(analysis_run_id, raw) critical_issues = await _build_critical_issues(analysis_run_id, raw)
transformation = await _build_transformation(analysis_run_id, raw)
fb_patch: dict = {} fb_patch: dict = {}
if fb_pages: if fb_pages:
@ -273,6 +285,8 @@ async def _build_overrides(analysis_run_id: str) -> dict:
overrides["youtube_audit"] = yt_patch overrides["youtube_audit"] = yt_patch
if critical_issues: if critical_issues:
overrides["problem_diagnosis"] = critical_issues overrides["problem_diagnosis"] = critical_issues
if transformation:
overrides["transformation"] = transformation
return overrides return overrides