""" Analysis API routes (local-only). Implements multi-dimensional analysis plus lightweight task/history APIs for the frontend. """ from flask import Blueprint, request, jsonify, Response import json import traceback import time from app.services.analysis import AnalysisService, reflect_analysis from app.utils.logger import get_logger from app.utils.db import get_db_connection from app.utils.language import detect_request_language logger = get_logger(__name__) analysis_bp = Blueprint('analysis', __name__) DEFAULT_USER_ID = 1 def _now_ts() -> int: return int(time.time()) def _normalize_symbol(symbol: str) -> str: return (symbol or '').strip().upper() def _store_task(market: str, symbol: str, model: str, language: str, status: str, result: dict = None, error_message: str = "") -> int: now = _now_ts() result_json = json.dumps(result or {}, ensure_ascii=False) with get_db_connection() as db: cur = db.cursor() cur.execute( """ INSERT INTO qd_analysis_tasks (user_id, market, symbol, model, language, status, result_json, error_message, created_at, completed_at) VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?) """, (DEFAULT_USER_ID, market, symbol, model or '', language or 'en-US', status, result_json, error_message or '', now, now if status in ['completed', 'failed'] else None) ) task_id = cur.lastrowid db.commit() cur.close() return int(task_id) def _get_task(task_id: int) -> dict: with get_db_connection() as db: cur = db.cursor() cur.execute("SELECT * FROM qd_analysis_tasks WHERE id = ? AND user_id = ?", (task_id, DEFAULT_USER_ID)) row = cur.fetchone() cur.close() return row or None def _parse_result_json(row: dict) -> dict: if not row: return {} raw = row.get('result_json') or '' try: return json.loads(raw) if raw else {} except Exception: return {} @analysis_bp.route('/multi', methods=['POST']) @analysis_bp.route('/multiAnalysis', methods=['POST']) # compatibility with legacy naming def multi_analysis(): """ Multi-dimensional analysis. Request body: market: Market (AShare, USStock, HShare, Crypto, Forex, Futures) symbol: Symbol language: Optional; if omitted we will detect from request headers (X-App-Lang / Accept-Language) """ try: data = request.get_json() if not data: return jsonify({ 'code': 0, 'msg': 'Request body is required', 'data': None }), 400 market = data.get('market', '') symbol = data.get('symbol', '') language = detect_request_language(request, body=data, default='en-US') model = data.get('model', None) use_multi_agent = data.get('use_multi_agent', None) # None -> use backend default timeframe = data.get('timeframe', '1D') if not symbol or not market: return jsonify({ 'code': 0, 'msg': 'Missing required parameters', 'data': None }), 400 # Normalize/defend input for local-only mode. market = str(market).strip() symbol = _normalize_symbol(symbol) language = str(language or 'en-US') model = str(model) if model else None logger.info(f"Analyze request: {market}:{symbol}, use_multi_agent={use_multi_agent}, model={model}") # Create analysis service instance (local-only; no paid credits) service = AnalysisService(use_multi_agent=use_multi_agent) result = service.analyze(market, symbol, language, model=model, timeframe=timeframe) # Persist as "completed" history (no paid credits in local mode). task_id = _store_task(market, symbol, model or '', language, 'completed', result=result, error_message='') # Keep frontend compatible: if it expects task polling, it can still use the id. result_payload = dict(result or {}) result_payload['task_id'] = task_id return jsonify({'code': 1, 'msg': 'success', 'data': result_payload}) except Exception as e: logger.error(f"Analysis failed: {str(e)}") logger.error(traceback.format_exc()) try: market = (data or {}).get('market', '') if 'data' in locals() else '' symbol = (data or {}).get('symbol', '') if 'data' in locals() else '' language = detect_request_language(request, body=(data or {}), default='en-US') model = (data or {}).get('model', '') if 'data' in locals() else '' market = str(market).strip() symbol = _normalize_symbol(symbol) _store_task(market, symbol, model, language, 'failed', result={}, error_message=str(e)) except Exception: pass return jsonify({ 'code': 0, 'msg': f'Analysis failed: {str(e)}', 'data': None }), 500 @analysis_bp.route('/getTaskStatus', methods=['POST']) def get_task_status(): """Frontend compatibility: return task status + result by task_id.""" try: data = request.get_json() or {} task_id = int(data.get('task_id') or 0) if not task_id: return jsonify({'code': 0, 'msg': 'Missing task_id', 'data': None}), 400 row = _get_task(task_id) if not row: return jsonify({'code': 0, 'msg': 'Task not found', 'data': None}), 404 payload = { 'id': row.get('id'), 'market': row.get('market'), 'symbol': row.get('symbol'), 'status': row.get('status'), 'error_message': row.get('error_message') or '', 'result': _parse_result_json(row) } return jsonify({'code': 1, 'msg': 'success', 'data': payload}) except Exception as e: logger.error(f"get_task_status failed: {str(e)}") logger.error(traceback.format_exc()) return jsonify({'code': 0, 'msg': str(e), 'data': None}), 500 @analysis_bp.route('/getHistoryList', methods=['POST']) def get_history_list(): """Frontend compatibility: paginated analysis history for the single user.""" try: data = request.get_json() or {} page = int(data.get('page') or 1) pagesize = int(data.get('pagesize') or 20) page = max(page, 1) pagesize = min(max(pagesize, 1), 100) offset = (page - 1) * pagesize with get_db_connection() as db: cur = db.cursor() cur.execute("SELECT COUNT(1) as cnt FROM qd_analysis_tasks WHERE user_id = ?", (DEFAULT_USER_ID,)) total = int((cur.fetchone() or {}).get('cnt') or 0) cur.execute( """ SELECT id, market, symbol, model, status, error_message, created_at, completed_at, result_json FROM qd_analysis_tasks WHERE user_id = ? ORDER BY id DESC LIMIT ? OFFSET ? """, (DEFAULT_USER_ID, pagesize, offset) ) rows = cur.fetchall() or [] cur.close() out = [] for r in rows: has_result = bool((r.get('result_json') or '').strip()) out.append({ 'id': r.get('id'), 'market': r.get('market'), 'symbol': r.get('symbol'), 'model': r.get('model') or '', 'status': r.get('status'), 'has_result': has_result, 'error_message': r.get('error_message') or '', 'createtime': int(r.get('created_at') or 0), 'completetime': int(r.get('completed_at') or 0) if r.get('completed_at') else None }) return jsonify({'code': 1, 'msg': 'success', 'data': {'list': out, 'total': total}}) except Exception as e: logger.error(f"get_history_list failed: {str(e)}") logger.error(traceback.format_exc()) return jsonify({'code': 0, 'msg': str(e), 'data': {'list': [], 'total': 0}}), 500 @analysis_bp.route('/createTask', methods=['POST']) def create_task(): """ Compatibility endpoint for legacy frontend. In local-only mode we do not run a separate async worker; we create a completed task record immediately. """ try: data = request.get_json() or {} market = str((data.get('market') or '')).strip() symbol = _normalize_symbol(data.get('symbol')) language = detect_request_language(request, body=data, default='en-US') model = data.get('model') or '' if not market or not symbol: return jsonify({'code': 0, 'msg': 'Missing market or symbol', 'data': None}), 400 # Create a placeholder "pending" task so frontend can show task_id if it needs it. task_id = _store_task(market, symbol, str(model), language, 'pending', result={}, error_message='') return jsonify({'code': 1, 'msg': 'success', 'data': {'task_id': task_id, 'status': 'pending'}}) except Exception as e: logger.error(f"create_task failed: {str(e)}") logger.error(traceback.format_exc()) return jsonify({'code': 0, 'msg': str(e), 'data': None}), 500 @analysis_bp.route('/stream', methods=['POST']) def stream_analysis(): """Streaming analysis (SSE).""" try: data = request.get_json() if not data: return jsonify({'code': 0, 'msg': 'Request body is required'}), 400 market = data.get('market', '') symbol = data.get('symbol', '') language = detect_request_language(request, body=data, default='en-US') use_multi_agent = data.get('use_multi_agent', None) timeframe = data.get('timeframe', '1D') def generate(): try: yield f"data: {json.dumps({'status': 'started', 'message': 'Analysis started'})}\n\n" service = AnalysisService(use_multi_agent=use_multi_agent) result = service.analyze(market, symbol, language, timeframe=timeframe) yield f"data: {json.dumps({'status': 'completed', 'data': result})}\n\n" except Exception as e: yield f"data: {json.dumps({'status': 'error', 'message': str(e)})}\n\n" return Response( generate(), mimetype='text/event-stream', headers={ 'Cache-Control': 'no-cache', 'Connection': 'keep-alive', 'X-Accel-Buffering': 'no' } ) except Exception as e: logger.error(f"Streaming analysis failed: {str(e)}") return jsonify({'code': 0, 'msg': str(e)}), 500 @analysis_bp.route('/reflect', methods=['POST']) def reflect(): """ Reflection API. Learn from post-trade outcomes and update agent memory (local-only). Body: market: Market symbol: Symbol decision: BUY/SELL/HOLD returns: Optional return percentage result: Optional free-text outcome """ try: data = request.get_json() if not data: return jsonify({ 'code': 0, 'msg': 'Request body is required', 'data': None }), 400 market = data.get('market', '') symbol = data.get('symbol', '') decision = data.get('decision', '') returns = data.get('returns', None) result = data.get('result', None) if not symbol or not market or not decision: return jsonify({ 'code': 0, 'msg': 'Missing required parameters (market, symbol, decision)', 'data': None }), 400 logger.info(f"Reflection: {market}:{symbol}, decision={decision}, returns={returns}") reflect_analysis(market, symbol, decision, returns, result) return jsonify({ 'code': 1, 'msg': 'success', 'data': None }) except Exception as e: logger.error(f"Reflection failed: {str(e)}") logger.error(traceback.format_exc()) return jsonify({ 'code': 0, 'msg': f'Reflection failed: {str(e)}', 'data': None }), 500