from fastapi import APIRouter, HTTPException from app.core.config import get_gemini_model from app.models.report_db_module import save_daily_log, save_structured_diary, get_yesterday_data, update_yesterday_ai_feedback, get_all_daily_notes, update_boss_comment, get_today_data from app.schemas.report_schemas import ReportAnalyzeRequest, SystemMessageRequest, YesterdayRequest from pydantic import BaseModel import json class BossCommentRequest(BaseModel): session_id: str date: str boss_comment: str router = APIRouter( prefix="/goal-skill-t/api", tags=["Report"] ) @router.post("/Report/boss-comment") async def save_boss_comment(request: BossCommentRequest): try: success = update_boss_comment( session_id=request.session_id, date=request.date, boss_comment=request.boss_comment ) if success: return {"status": "success", "message": "フィードバックを保存しました。"} else: return {"status": "error", "message": "該当する日付の記録が見つかりませんでした。"} except Exception as e: print(f"Save Boss Comment Error: {e}") raise HTTPException(status_code=500, detail="サーバーエラーが発生しました。") @router.get("/Report/all/{session_id}") async def fetch_all_logs(session_id: str): try: # daily_note에서 최신순으로 가져옴 rows = get_all_daily_notes(session_id) if not rows: return {"data": [], "message": "記録はありません。"} response_data = [] for row in rows: response_data.append({ "date": str(row.get('date', '')), "learning": row.get('learning', ''), "mindset": row.get('today_mindset', ''), "advice": row.get('advice', ''), "boss_comment": row.get('boss_comment', '') }) return {"data": response_data} except Exception as e: print(f"Fetch All Notes API Error: {e}") return {"data": [], "message": "データの読み取りに失敗しました。"} @router.post("/Report/system-message") async def get_system_message(request: SystemMessageRequest): try: client = get_gemini_model() # Setting Prompts by Message Type context_map = { "check_condition": "カリキュラムを作成する前に、現在のコンディション（日記）を入力するよう優しく促すメッセージ（日本語、1文、親しみやすい敬語）", "show_curriculum": "生成されたパーソナライズカリキュラムを提示し、確認してみるよう勧めるメッセージ（日本語、1文、自信のある口調）", "ask_feedback": "提示したカリキュラムが気に入ったか、感想を尋ねるメッセージ（日本語、1文）", "start_learning": "ユーザーがカリキュラムを承諾した際、力強く学習を始めようと励ますメッセージ（日本語、1文、情熱的な口調）" } target_context = context_map.get(request.message_type, "ユーザーへの自然な挨拶のメッセージ（日本語、1文）") prompt = f""" Task: Generate a natural, friendly system message in Japanese for an AI Tutor app. Context: {target_context} Constraint: Do not repeat the same phrase. Be creative but concise. Output only the Japanese text. """ response = client.models.generate_content( model="gemini-2.5-flash", contents=prompt, config={ "temperature": 0.9 } ) return {"message": response.text.strip()} except Exception as e: print(f"System Message Error: {e}") # Returns default hard-coding message in case of error (safety) fallback_map = { "check_condition": "カリキュラムを作成する前に、今日のあなたの状態を把握しますね。", "show_curriculum": "今日のパーソナライズされたカリキュラムです。確認してみてください。", "ask_feedback": "今回のカリキュラムはいかがですか？", "start_learning": "いいですね。では、すぐにカリキュラムを始めましょう！" } return {"message": fallback_map.get(request.message_type, "")} @router.post("/Report/analyze") async def analyze_diary(request: ReportAnalyzeRequest): try: client = get_gemini_model() # [CASE 1] Diary mode (is_note = True) if request.is_note: # 1. Remove AI analysis/encouragement generation logic (reflect request) # Ai_comment is set to None because it will be added later ai_reply = None # 2. Save DB (only save user input source, ai_comment is NULL) save_structured_diary( session_id=request.session_id, date=request.date, learning=request.learning, mindset=request.mindset, ai_comment=ai_reply ) # 3. Save bot logs (optional: only system message 'Save complete' is left) # save_daily_log(request.session_id, "bot", "日報を保存しました。") # 4. Front-end response # Instead of encouraging AI, we send a simple system message that the save is complete. return {"answer": "デイリーチェックを書いてくれてありがとう！さあ、『カリキュラム』ボタンを押して、実習を始めよう！"} # [CASE 2] General feedback/conversation mode (is_note = False) else: # Maintain existing conversation logic (if the user has entered it in the chat window) save_daily_log(request.session_id, "user", request.message) prompt = f""" User Feedback: "{request.message}" Task: Reply naturally in Japanese to the user's feedback. """ response = client.models.generate_content( model="gemini-2.5-flash", contents=prompt ) ai_reply = response.text.strip() save_daily_log(request.session_id, "bot", ai_reply) return {"answer": ai_reply} except Exception as e: print(f"Report Analyze Error: {e}") return {"answer": "サーバー通信中にエラーが発生しました。"} @router.post("/Report/yesterday") async def fetch_yesterday_log(request: YesterdayRequest): try: row = get_yesterday_data(request.session_id) # [Debugging] print(f"DEBUG ROW DATA: {row}") if not row: return {"data": None, "message": "昨日の記録はありません。"} ai_comment = row.get('ai_comment') advice = row.get('advice') # If either is empty, try creating if not ai_comment or not advice: try: client = get_gemini_model() # User Recordings user_learning = row.get('learning', 'なし') user_mindset = row.get('today_mindset', 'なし') # Creating Prompts prompt = f""" Task: Analyze the user's daily study log and provide feedback in JSON format. [User Log] Learning: {user_learning} Mindset: {user_mindset} [Requirements] 1. "ai_comment": A warm, encouraging compliment about their learning or mindset (Japanese, polite tone). 2. "advice": A brief, practical tip for better journaling or efficient studying based on the log (Japanese, polite tone). 3. Output must be valid JSON only. No markdown formatting. Example format: {{"ai_comment": "...", "advice": "..."}} """ # Call Gemini response = client.models.generate_content( model="gemini-2.5-flash", contents=prompt, config={"response_mime_type": "application/json"} # JSON Forced (with model support) ) # Result parsing import json generated_data = json.loads(response.text) new_ai_comment = generated_data.get("ai_comment", "素晴らしい取り組みですね！") new_advice = generated_data.get("advice", "継続は力なりです。") # Update DB update_yesterday_ai_feedback(row['id'], new_ai_comment, new_advice) # Reflects to current memory (that way, it can be seen immediately in return value) ai_comment = new_ai_comment advice = new_advice except Exception as e: print(f"AI Feedback Generation Error: {e}") # Show default values in case of creation failure (save DB or save default values) ai_comment = "素晴らしい進捗ですね！" advice = "今日もこの調子で頑張りましょう。" # Structured data return (for HTML rendering) # DB 컬럼명: date, learning, today_mindset, boss_comment response_data = { "date": str(row.get('date', '')), # String conversion safety for date objects "learning": row.get('learning', ''), "mindset": row.get('today_mindset', ''), "boss_comment": row.get('boss_comment', ''), "ai_comment": ai_comment, "advice": advice } return {"data": response_data} except Exception as e: print(f"Yesterday API Error: {e}") return {"data": None, "message": "データの読み込みに失敗しました。"} @router.get("/Report/today-status/{session_id}") async def fetch_today_status(session_id: str): try: # report_db_module.py에 이미 정의된 get_today_data 함수 사용 row = get_today_data(session_id) if row and row.get('boss_comment'): return { "has_comment": True, "boss_comment": row.get('boss_comment'), "message": "今日のコメントがあります。" } else: return { "has_comment": False, "boss_comment": None, "message": "今日のコメントはまだありません。" } except Exception as e: print(f"Today Status API Error: {e}") return {"has_comment": False, "boss_comment": None}