Fix: Add case-insensitive validation for request fields

app/pipeline/analysis_pipeline.py

@@ -52,29 +52,20 @@ def run_analysis_pipeline(payload: AnalyzeRequest) -> Dict[str, object]:
         for message in conversation
         if message.sender.strip().upper() == "OTHER" and message.content.strip()
     ]
-    logger.info(
-        "Pipeline start: %d turns (other=%d)",
-        len(conversation),
-        len(other_contents),
-    )
 
     # 1. 입력에서 대화 유형 수신 (유형별 신호 범위 결정을 위함)
     conversation_type = payload.type
-    logger.info("Step 1 conversation_type(from input): %s", conversation_type)
 
     # 2. 규칙 기반 신호 추출 (유형 기반 + 공통 신호) (위험 신호 후보 추출)
     allowed_signals = resolve_risk_signals(conversation_type)
     rule_signals = analyze_conversation(other_contents, allowed_signals=allowed_signals)
-    logger.info("Step 2 signals: %s", rule_signals)
 
     # 3. RAG 쿼리 보강 (근거 자료 확보를 위한 검색 품질 향상)
     signal_terms = signal_query_terms(rule_signals)
     matched_phrases = extract_signal_phrases(other_contents, allowed_signals=allowed_signals)
-    logger.info("Step 3 query_terms=%s matched_phrases=%s", signal_terms, matched_phrases)
 
     # 4. 결정 오케스트레이터 (위험 단계 산출)
     risk_stage = decide_risk_stage(rule_signals)
-    logger.info("Step 4 risk_stage: %s", risk_stage)
 
     # 5. RAG 검색 (근거 자료 확보)
     retrieval_request = RetrievalRequest(
@@ -85,7 +76,6 @@ def run_analysis_pipeline(payload: AnalyzeRequest) -> Dict[str, object]:
         matched_phrases=matched_phrases,
     )
     references = retrieve_evidence(retrieval_request)
-    logger.info("Step 5 references: %d", len(references))
 
     # 6. 안전 행동 생성 (LLM: references + 대화 발췌 사용) (최종 응답 생성)
     conversation_lines = _build_conversation_excerpt(
@@ -94,7 +84,6 @@ def run_analysis_pipeline(payload: AnalyzeRequest) -> Dict[str, object]:
     safe_actions = generate_safe_actions(
         risk_stage, conversation_type, references, conversation_lines, payload.platform
     )
-    logger.info("Step 6 safe_actions generated")
 
     rag_references = [
         {"source": reference.source, "summary": reference.note} for reference in references

app/schemas/request.py

@@ -1,7 +1,7 @@
 from datetime import datetime
-from typing import List, Literal
+from typing import List, Literal, Optional
 
-from pydantic import BaseModel, Field
+from pydantic import BaseModel, Field, field_validator
 
 
 class Message(BaseModel):
@@ -11,6 +11,20 @@ class Message(BaseModel):
     content: str = Field(..., description="Message content")
     sender: str = Field(..., description="Message sender (e.g. ME, OTHER)")
     timestamp: datetime = Field(..., description="Message timestamp in ISO 8601")
+
+    @field_validator("type", mode="before")
+    @classmethod
+    def uppercase_type(cls, v):
+        if isinstance(v, str):
+            return v.upper()
+        return v
+
+    @field_validator("sender", mode="before")
+    @classmethod
+    def uppercase_sender(cls, v):
+        if isinstance(v, str):
+            return v.upper()
+        return v
 
 
 class AnalyzeRequest(BaseModel):
@@ -19,9 +33,16 @@ class AnalyzeRequest(BaseModel):
     platform: Literal["INSTAGRAM", "TELEGRAM"] = Field(
         ..., description="Platform name (INSTAGRAM or TELEGRAM)"
     )
-    type: Literal["구직", "중고거래", "재테크", "부업"] = Field(
-        ..., description="Conversation type (구직, 중고거래, 재테크, 부업)"
+    type: Optional[Literal["구직", "중고거래", "재테크", "부업"]] = Field(
+        None, description="Conversation type (구직, 중고거래, 재테크, 부업)"
     )
+
+    @field_validator("platform", mode="before")
+    @classmethod
+    def uppercase_platform(cls, v):
+        if isinstance(v, str):
+            return v.upper()
+        return v
 
 
 class ReportRequest(BaseModel):