feat(chains): add QuestionProfile model and profile‑extraction chain

* Pydantic 모델 `QuestionProfile` 정의
  - 시계열·집계·필터·그룹화·랭킹·기간비교 플래그와 `intent_type` 포함
* `profile_prompt` 템플릿 추가
* `create_profile_extraction_chain()` 함수로 LLM 기반 프로파일 추출 지원

Author: seyoung4503

llm_utils/chains.py

@@ -4,12 +4,14 @@
     MessagesPlaceholder,
     SystemMessagePromptTemplate,
 )
+from pydantic import BaseModel, Field
 
 from .llm_factory import get_llm
 
 from dotenv import load_dotenv
 from prompt.template_loader import get_prompt_template
 
+
 env_path = os.path.join(os.getcwd(), ".env")
 
 if os.path.exists(env_path):
@@ -20,6 +22,16 @@
 llm = get_llm()
 
 
+class QuestionProfile(BaseModel):
+    is_timeseries: bool = Field(description="시계열 분석 필요 여부")
+    is_aggregation: bool = Field(description="집계 함수 필요 여부")
+    has_filter: bool = Field(description="조건 필터 필요 여부")
+    is_grouped: bool = Field(description="그룹화 필요 여부")
+    has_ranking: bool = Field(description="정렬/순위 필요 여부")
+    has_temporal_comparison: bool = Field(description="기간 비교 포함 여부")
+    intent_type: str = Field(description="질문의 주요 의도 유형")
+
+
 def create_query_refiner_chain(llm):
     prompt = get_prompt_template("query_refiner_prompt")
     tool_choice_prompt = ChatPromptTemplate.from_messages(
@@ -101,6 +113,33 @@ def create_query_refiner_with_profile_chain(llm):
     return tool_choice_prompt | llm
 
 
+from langchain.prompts import PromptTemplate
+
+profile_prompt = PromptTemplate(
+    input_variables=["question"],
+    template="""
+You are an assistant that analyzes a user question and extracts the following profiles as JSON:
+- is_timeseries (boolean)
+- is_aggregation (boolean)
+- has_filter (boolean)
+- is_grouped (boolean)
+- has_ranking (boolean)
+- has_temporal_comparison (boolean)
+- intent_type (one of: trend, lookup, comparison, distribution)
+
+Return only valid JSON matching the QuestionProfile schema.
+
+Question:
+{question}
+""".strip(),
+)
+
+
+def create_profile_extraction_chain(llm):
+    chain = profile_prompt | llm.with_structured_output(QuestionProfile)
+    return chain
+
+
 query_refiner_chain = create_query_refiner_chain(llm)
 query_maker_chain = create_query_maker_chain(llm)
 query_refiner_with_profile_chain = create_query_refiner_with_profile_chain(llm)