From 230f501f98309971e276ce1c9e9cbaf141f74f06 Mon Sep 17 00:00:00 2001 From: aaron <> Date: Mon, 28 Apr 2025 10:42:02 +0800 Subject: [PATCH] add gold agent --- cryptoai/__pycache__/main.cpython-313.pyc | Bin 5964 -> 8109 bytes cryptoai/agents/gold_agent.py | 451 ++++++++++++++++++ .../__pycache__/binance_api.cpython-313.pyc | Bin 6825 -> 6825 bytes cryptoai/api/alltick_api.py | 134 ++++++ cryptoai/config/config.example.yaml | 22 + cryptoai/config/config.yaml | 26 +- cryptoai/main.py | 94 +++- .../__pycache__/config_loader.cpython-313.pyc | Bin 4301 -> 4938 bytes cryptoai/utils/config_loader.py | 55 ++- run.py | 3 + 10 files changed, 736 insertions(+), 49 deletions(-) create mode 100644 cryptoai/agents/gold_agent.py create mode 100644 cryptoai/api/alltick_api.py diff --git a/cryptoai/__pycache__/main.cpython-313.pyc b/cryptoai/__pycache__/main.cpython-313.pyc index 63647ecf9005df3b17563bb052e0363ca5a22b67..a802706143ca53662538693742f03681fc55b949 100644 GIT binary patch delta 4036 zcma)9du&tJ89&!=`(D2v$-U0QdDxB<@*o6CUgeo|Km#S@}vPStcTrm|;c6WU@R(xir#ZQ38xcFuL|Kor`Y zfYPn{zj|S0Mt5Dx+ClC0Q?P4a!tMX^34k$xEZ1su<{+o z?IzCT0IY%moS9YnOst9}nq;h+0Z+*|3#(@}J}XQ5Y^=&B^I3iJCW#!OG$~jLb38?G z1*{gy7W!yb*YX4a0TlqgLih&pkX-%9K>s258={7|{NYzb69IoKvC!6DMNS>ohW-lb zC2S#UX_mvdgf`Rntjbu1RW!?BiL`>Sf4EtyAqeWjE?FhfgTIg?QI}Q*j|_x^p(sb8 z*-2$>ZJ;j{8B8mJ-0<<(2vI0R?Fs8mNoqi%!=9yT>I~r5Py$f<6FT4XJ@_odD3gp@JmxD7+sp7{M zq~bCm-$N`Y;J+1{B>$AaHsy|3tI69zfnY2vh$>hTi}q1{lt&BysOpz<*biWfxROJf_prVq>0`#AvT}gViK(C(mB&5TtZWi0n_{}r;cKcg zBf6ccLaqc^gsa0{Bcw>0xC~w7cy(_sumUgW6~iy$0J%Gc&jhzXi|C*QlqI(kk$cYy zRw$?Rgb@m)8CFpR4ZEE8!R4JYCzOZ7_XTuYq29#6cB(|RS5*l-s-d$mNUhT6V_fF_ zb929X6<(sEL?bNJ?jcAxplvc}!qIRfIv9uqLmUq1@S?V{jKiThO$8!>{^64$KXw?8 znyW{|+&BMKySZosW>RpW=urP)6o2`m<2W41bvEkknw^Mt06o#az>uzIjwBA1KqKNV|)OP={s=DqDHonKKed0=yIy$OqDygzz=Z(%Fj+`E!C}I~4B_xLH*+O(>ME+}#PsbU z(quMi`i}<&j|}0hGoSn-Gdh)dWg_#+c~l+V{%AZi^L!@u^38Lj`8X_Q{2`n_^4!^) zF%xs%&*(xt^BquX8xFqk32@7dV{MvzYiQa~pAoV}3Tg{uWi z;R5LOEM{my&iNcbDTA^n$fD=AF39Sk-NKBZlt3Bs709fmbYkn&j>#Q@Wqqt;mNN3D z^-WWLuBW)-&3XM8(L6#mT!Kx@K9QqDzu=wLn)V={kX~Y= z_&xrF`vC6>@V0~34M8kXST$jrVkVjCN8{xQPe;65q5n z9!|J-^RCBuTlbd+c7X(Int5aGf&ogcPj=Oy(|xV8bQ=SHw`#Ky4W9!V_l$MBOZxe0 zHSSx=x0gx(P$oz3X_eoPJ;U$!5cBxfc$lXyRh$PZ-MCeIH_?o?nF<=K8Lr71dfIL{z;H6?nI|lwH+HcG}Iq@n2RDN z0zJ`>;c46c0}X!$Yrj^M5Ty&72`903!nXj>5Z`(i4|kp*>Il<>c>$nddW$&3E%D&* p*Tj$fy5t|2`t?EdJGf*aLI4>RJDHHuf0C(w)QNuD$ry3_{{iJcu+snl delta 2081 zcmZ`(eN00S?l=;eL*j&K) zL1PvNx!H)x{$TzC{9)LJ8gyC0A1;}3f4o{uv6*IxW6s3HZs4C9?`>gYs3&>%eB9qT z@7#0mIiJ7jcke&WSvt{MIgr zZBzwTa1=TEo3T06d3lQ~LC_qXM^20ykVYmG=b%_&aS-u(5EThhp~(eN{YMarlMrOD zv{&k4(72)>LDqquW2>natjF2bhw{)Vn3IdFGQO#CmS*9I+P77A2J9gX_kTv61C+*L3Jg zD8Y^gzh~@O3NU8ghJTw8hkK*3A$~iS`APr^K!n2L29a!uzFLQVR!!6R4rORwU4}TB z0X!|$u(v)pebbhj1#z+QyQ*B)NXliBd!-tn$)_{UF~j_OUCcUe^}1|?bIED9`u&Z3N7fo&L%&E_nPq+{}Nr(b&g~u zz+9L%RVGc9Gj%D`q0v@su@t8Zs*(j&Gu~7|tw0;GNn=c_wYQmz6FUN55S`qxDP z8LBdr$lx9r6XA;F-k<9`00PPlFMrOyp*`gotwKs;kqkel+=KYe#lu&=#j~!*#wn6fy%c)^%Q=0TjA^zxbk0c z6~|z>*`~)ioAX(1Uh%mKNKS+5J+Kt?>dQcY41ydX%(myJ@w#poW5Bd6Z^%!GCWVLEv29YaQYbCK= z+*ldA`QYMJ7tAOkgR!2z-q6YL&~e_5H(k^-4{+R432V^}OAU0R-z^n#4~ArzlY{X- zw8Pr;vX&<&j<`J3uov##jGN!aVNyMA6U(WeHZrKHC8U0Y|CcbAhF>&YW1VryK{;j)tV8VR5J6 z3#1%D!G288buFrkd>f@q7E;aqURe`jUMog%|cd>(F>_ttcjs@9~kUD)gOJ4Cu0I%0Epi}e-w8`J&z@3Sdw)YK+jAt3ou)3TqEq! zi!P{}vSk5gS0g#LsL!$6-2#Wp5)in+x3NFT{^NG&gvHqw2xvBOCPi6(q?r%AcwE!g HTn_&LPCw)g diff --git a/cryptoai/agents/gold_agent.py b/cryptoai/agents/gold_agent.py new file mode 100644 index 0000000..7607e4b --- /dev/null +++ b/cryptoai/agents/gold_agent.py @@ -0,0 +1,451 @@ +import os +import sys +import pandas as pd +import numpy as np +from typing import Dict, Any, List, Optional, Tuple +import datetime +import time +import json +from datetime import datetime, timedelta + +# 添加项目根目录到Python路径 +sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__)))) + +from api.binance_api import BinanceAPI +from api.alltick_api import AllTickAPI +from api.deepseek_api import DeepSeekAPI +from models.data_processor import DataProcessor +from utils.config_loader import ConfigLoader +from utils.dingtalk_bot import DingTalkBot + + +class GoldAgent: + """黄金分析智能体，用于分析黄金市场数据并生成交易策略""" + + def __init__(self, config_path: str = None): + """ + 初始化黄金分析智能体 + + Args: + config_path: 配置文件路径，如果为None，则使用默认路径 + """ + # 加载配置 + self.config_loader = ConfigLoader(config_path) + + # 获取各部分配置 + self.binance_config = self.config_loader.get_binance_config() + self.deepseek_config = self.config_loader.get_deepseek_config() + self.alltick_config = self.config_loader.get_config('alltick') + self.gold_config = self.config_loader.get_config('gold') # 黄金特定配置 + self.data_config = self.config_loader.get_data_config() + self.agent_config = self.config_loader.get_agent_config() + self.dingtalk_config = self.config_loader.get_dingtalk_config() + + # 初始化API客户端 + self.binance_api = BinanceAPI( + api_key=self.binance_config['api_key'], + api_secret=self.binance_config['api_secret'], + test_mode=self.binance_config['test_mode'] + ) + + # 初始化AllTick API客户端（用于获取黄金数据） + self.alltick_api = AllTickAPI( + api_key=self.alltick_config['api_key'] + ) + + self.deepseek_api = DeepSeekAPI( + api_key=self.deepseek_config['api_key'], + model=self.deepseek_config['model'] + ) + + # 初始化数据处理器 + self.data_processor = DataProcessor(storage_path=os.path.join(self.data_config['storage_path'], 'gold')) + + # 初始化钉钉机器人（如果启用） + self.dingtalk_bot = None + if self.dingtalk_config.get('enabled', False): + self.dingtalk_bot = DingTalkBot( + webhook_url=self.dingtalk_config['webhook_url'], + secret=self.dingtalk_config.get('secret') + ) + print("钉钉机器人已启用") + + # 设置黄金交易对 + self.gold_symbols = self.gold_config.get('symbols', ["XAUUSD"]) # 默认黄金/美元 + + # 设置时间间隔 + self.time_interval = self.gold_config.get('time_interval', '1d') # 默认日线 + + # 风险等级 + self.risk_level = self.agent_config['risk_level'] + + def fetch_historical_data(self, symbol: str, days: int = 180) -> pd.DataFrame: + """ + 获取历史数据 + + Args: + symbol: 黄金交易对符号，例如 'XAUUSD' + days: 要获取的天数 + + Returns: + 历史数据DataFrame + """ + print(f"获取{symbol}的历史数据（{days}天）...") + + # 计算开始时间 + start_time = datetime.now() - timedelta(days=days) + start_str = start_time.strftime("%Y-%m-%d") + + try: + # 使用AllTick API获取黄金K线数据 + data = self.alltick_api.get_historical_klines( + symbol=symbol, + interval=self.time_interval, + start_str=start_str, + limit=days # 请求天数对应的K线数量 + ) + except Exception as e: + print(f"从AllTick获取数据出错: {e}") + + if data.empty: + print(f"无法获取{symbol}的历史数据") + return pd.DataFrame() + + # 保存原始数据 + raw_data_path = self.data_processor.save_data(symbol, data, data_type='raw') + print(f"原始数据已保存到: {raw_data_path}") + + return data + + def process_data(self, symbol: str, data: pd.DataFrame) -> pd.DataFrame: + """ + 处理数据 + + Args: + symbol: 黄金交易对符号，例如 'XAUUSD' + data: 原始数据 + + Returns: + 处理后的数据 + """ + print(f"处理{symbol}的数据...") + + # 预处理数据 + processed_data = self.data_processor.preprocess_market_data(symbol, data) + + # 计算额外的黄金特定指标 + processed_data = self._calculate_gold_indicators(processed_data) + + # 保存处理后的数据 + processed_data_path = self.data_processor.save_data(symbol, processed_data, data_type='processed') + print(f"处理后的数据已保存到: {processed_data_path}") + + return processed_data + + def _calculate_gold_indicators(self, data: pd.DataFrame) -> pd.DataFrame: + """ + 计算黄金特定技术指标 + + Args: + data: 预处理后的数据 + + Returns: + 添加了黄金特定指标的数据 + """ + # 复制数据，避免修改原始数据 + df = data.copy() + + # 黄金波动率指标 (GVZ - Gold Volatility Index) + df['close_pct_change'] = df['close'].pct_change() + df['GVZ'] = df['close_pct_change'].rolling(window=20).std() * 100 + + # 黄金与美元指数相关性 (模拟数据，实际应用中需要获取美元指数数据) + df['USD_correlation'] = np.random.normal(-0.6, 0.2, len(df)) # 模拟负相关 + + # 季节性因素 (根据日期生成季节性指标) + df['month'] = pd.to_datetime(df.index).month + df['seasonal_factor'] = df['month'].apply(lambda m: 1 if m in [1, 8, 9, 12] else -1 if m in [3, 4, 6, 7] else 0) + + # 黄金看涨/看跌指标 (计算基于多个指标的综合信号) + df['gold_bull_signal'] = np.where( + (df['RSI'] < 30) & (df['close'] > df['MA50']) & (df['seasonal_factor'] >= 0), + 1, # 看涨信号 + np.where( + (df['RSI'] > 70) & (df['close'] < df['MA50']) & (df['seasonal_factor'] <= 0), + -1, # 看跌信号 + 0 # 中性 + ) + ) + + return df + + def _format_market_data(self, market_data: Dict[str, Any]) -> str: + """ + 格式化市场数据为适合大模型的格式 + + Args: + market_data: 市场数据 + + Returns: + 格式化的数据字符串 + """ + # 这里可以根据实际情况调整格式化方式 + return json.dumps(market_data, indent=2) + + def _build_gold_analysis_prompt(self, formatted_data: str) -> str: + """ + 构建黄金分析提示词 + + Args: + formatted_data: 格式化的市场数据 + + Returns: + 提示词 + """ + return f"""请对以下黄金市场K线数据进行深入分析，并给出交易建议。请使用中文回复。 + +数据: +{formatted_data} + +请严格按照以下步骤分析: +1. 分析主要技术指标(包括RSI、MACD、布林带、均线等)，判断当前黄金市场趋势 +2. 基于K线数据和斐波那契回调水平，确定关键支撑位和压力位 +3. 分析黄金特定指标(GVZ波动率指标、与美元相关性、季节性因素)对价格的影响 +4. 考虑全球宏观经济、地缘政治、通胀预期等因素对黄金价格的影响 +5. 根据技术分析和基本面因素给出清晰的交易建议 +6. 评估当前操作建议的紧迫性 + +请以JSON格式回复，仅包含以下字段: +- market_trend: 市场趋势 (牛市, 熊市, 震荡) +- technical_analysis: 技术指标详细分析 (重点分析RSI、MACD、布林带、均线交叉等情况) +- gold_specific_indicators: 黄金特有指标分析 (波动率、美元相关性、季节性) +- macro_factors: 宏观经济因素分析 (通胀、利率、地缘政治等) +- support_levels: 基于斐波那契回调的支撑位列表（标明各个支撑位对应的斐波那契水平） +- resistance_levels: 基于斐波那契回调的阻力位列表（同样标明对应水平） +- volume_analysis: 交易量分析，重点关注量价关系 +- recommendation: 操作建议 (买入、卖出或等待) +- entry_points: 推荐入场点位 +- exit_points: 推荐出场点位 +- stop_loss: 建议止损位 +- take_profit: 建议止盈位 +- urgency_level: 操作紧迫性评级 (1-5，1为最低紧迫性，5为最高紧迫性) +- urgency_reason: 紧迫性评级的原因说明 +- summary: 分析总结（不超过70字） + +请确保回复为有效的JSON格式，分析要精准专业。重点关注黄金的避险属性、通胀对冲功能以及与主要货币的相关性。""" + + def analyze_gold(self) -> Dict[str, Dict[str, Any]]: + """ + 分析所有支持的黄金交易对 + + Returns: + 所有交易对的分析结果 + """ + results = {} + + for symbol in self.gold_symbols: + print(f"\n开始分析{symbol}...") + + # 获取并处理数据 + raw_data = self.fetch_historical_data(symbol, days=self.gold_config.get('historical_days', 180)) + + if not raw_data.empty: + processed_data = self.process_data(symbol, raw_data) + + # 准备市场数据 + market_data = { + "symbol": symbol, + "current_price": float(processed_data['close'].iloc[-1]), + "price_change_24h": float(processed_data['close'].iloc[-1] - processed_data['close'].iloc[-2]), + "price_change_percentage_24h": float((processed_data['close'].iloc[-1] - processed_data['close'].iloc[-2]) / processed_data['close'].iloc[-2] * 100), + "historical_prices": processed_data['close'].tail(100).tolist(), + "volumes": processed_data['volume'].tail(100).tolist(), + "technical_indicators": { + "rsi": float(processed_data['RSI'].iloc[-1]), + "macd": float(processed_data['MACD'].iloc[-1]), + "macd_signal": float(processed_data['MACD_Signal'].iloc[-1]), + "bollinger_upper": float(processed_data['Bollinger_Upper'].iloc[-1]), + "bollinger_lower": float(processed_data['Bollinger_Lower'].iloc[-1]), + "ma5": float(processed_data['MA5'].iloc[-1]), + "ma10": float(processed_data['MA10'].iloc[-1]), + "ma20": float(processed_data['MA20'].iloc[-1]), + "ma50": float(processed_data['MA50'].iloc[-1]), + "ma200": float(processed_data['MA50'].iloc[-1]) if 'MA200' not in processed_data else float(processed_data['MA200'].iloc[-1]), + "atr": float(processed_data['ATR'].iloc[-1]) + }, + "gold_specific_indicators": { + "gvz": float(processed_data['GVZ'].iloc[-1]), + "usd_correlation": float(processed_data['USD_correlation'].iloc[-1]), + "seasonal_factor": float(processed_data['seasonal_factor'].iloc[-1]), + "gold_bull_signal": float(processed_data['gold_bull_signal'].iloc[-1]) + }, + "klines": processed_data[['open', 'high', 'low', 'close', 'volume']].tail(30).to_dict('records') + } + + # 将市场数据格式化为适合大模型的格式 + formatted_data = self._format_market_data(market_data) + + # 构建提示词 + prompt = self._build_gold_analysis_prompt(formatted_data) + + # 调用API获取分析和交易建议 + response, usage = self.deepseek_api.call_model(prompt, task_type="黄金分析", symbol=symbol) + + # 解析响应 + analysis_result = self.deepseek_api.extract_json_from_response(response) + + # 添加token使用信息 + if usage: + analysis_result["_token_usage"] = usage + + # 整合结果 + results[symbol] = { + "analysis": analysis_result, + "timestamp": datetime.now().isoformat() + } + + # 如果钉钉机器人已启用，发送分析报告 + if self.dingtalk_bot: + try: + print(f"发送{symbol}分析报告到钉钉...") + response = self.dingtalk_bot.send_analysis_report(symbol, results[symbol]) + if response.get('errcode') == 0: + print(f"{symbol}分析报告发送成功") + else: + print(f"{symbol}分析报告发送失败: {response}") + except Exception as e: + print(f"发送{symbol}分析报告时出错: {e}") + + print(f"{symbol}分析完成") + else: + print(f"跳过{symbol}分析，无法获取数据") + + return results + + def send_notifications(self, symbol: str, analysis_data: Dict[str, Any]) -> bool: + """ + 发送分析结果通知 + + Args: + symbol: 交易对符号 + analysis_data: 分析数据 + + Returns: + 发送是否成功 + """ + if not self.dingtalk_bot: + print(f"钉钉通知未启用，跳过发送 {symbol} 的分析结果") + return False + + try: + # 使用已初始化的钉钉机器人实例发送完整分析报告 + response = self.dingtalk_bot.send_analysis_report(symbol, analysis_data) + + if response.get('errcode') == 0: + print(f"成功发送 {symbol} 分析结果到钉钉") + return True + else: + print(f"发送 {symbol} 分析结果到钉钉失败: {response}") + return False + + except Exception as e: + print(f"发送钉钉通知时出错: {e}") + return False + + def run_analysis_cycle(self) -> Dict[str, Any]: + """ + 运行一个完整的分析周期 + + Returns: + 分析结果 + """ + print(f"开始新的黄金分析周期，时间：{datetime.now().isoformat()}") + + results = self.analyze_gold() + + # 保存分析结果 + timestamp = datetime.now().strftime("%Y%m%d%H%M%S") + results_dir = os.path.join(self.data_config['storage_path'], 'gold', 'analysis_results') + os.makedirs(results_dir, exist_ok=True) + + results_file = os.path.join(results_dir, f"gold_analysis_results_{timestamp}.json") + + with open(results_file, 'w', encoding='utf-8') as f: + json.dump(results, f, indent=2, ensure_ascii=False) + + print(f"分析结果已保存到：{results_file}") + + # 导出 DeepSeek API token 使用情况 + self._export_token_usage() + + return results + + def _export_token_usage(self) -> None: + """ + 导出 DeepSeek API token 使用情况 + """ + try: + # 每天导出一次详细的JSON数据 + today = datetime.now().strftime("%Y%m%d") + token_usage_dir = os.path.join(self.data_config['storage_path'], 'gold', 'token_usage') + os.makedirs(token_usage_dir, exist_ok=True) + + json_file = os.path.join(token_usage_dir, f"deepseek_token_usage_{today}.json") + + # 如果文件不存在，导出一次 + if not os.path.exists(json_file): + exported_file = self.deepseek_api.export_token_usage(json_file) + if exported_file: + print(f"DeepSeek API token 使用情况已导出到：{exported_file}") + + # 每次都导出CSV格式的统计数据 + csv_file = os.path.join(token_usage_dir, f"deepseek_token_usage_{today}.csv") + self.deepseek_api.export_token_usage(csv_file, "csv") + + # 输出当前使用情况统计 + stats = self.deepseek_api.get_token_usage_stats() + print(f"DeepSeek API token 使用统计：") + print(f"- 总调用次数: {stats['total_calls']}") + print(f"- 总token数: {stats['total_tokens']}") + print(f"- 输入token: {stats['total_prompt_tokens']}") + print(f"- 输出token: {stats['total_completion_tokens']}") + print(f"- 平均每次调用: {stats['average_tokens_per_call']:.2f} tokens") + + except Exception as e: + print(f"导出 token 使用情况时出错: {e}") + + def start_agent(self, run_once: bool = False) -> None: + """ + 启动智能体 + + Args: + run_once: 是否只运行一次分析周期 + """ + print("启动黄金分析智能体...") + + try: + if run_once: + self.run_analysis_cycle() + # 导出最终的token使用情况 + self._export_token_usage() + else: + while True: + self.run_analysis_cycle() + + # 等待下一个分析周期 + analysis_interval = self.gold_config.get('analysis_interval', + self.agent_config['analysis_interval']) + print(f"等待{analysis_interval}分钟后进行下一次分析...") + time.sleep(analysis_interval * 60) + + except KeyboardInterrupt: + print("\n智能体已停止") + # 导出最终的token使用情况 + self._export_token_usage() + + except Exception as e: + print(f"智能体运行时出错: {e}") + import traceback + traceback.print_exc() + # 发生错误时也尝试导出token使用情况 + self._export_token_usage() \ No newline at end of file diff --git a/cryptoai/api/__pycache__/binance_api.cpython-313.pyc b/cryptoai/api/__pycache__/binance_api.cpython-313.pyc index 31ea87baff06ab42a683ae3cfea14a704c3da79e..ba2dfef0a86641db2ec5e792d0e22ea34ac69de0 100644 GIT binary patch delta 20 acmZ2!y3&;UGcPX}0}yO|!ncuoo)iE;E(Q7k delta 20 acmZ2!y3&;UGcPX}0}%XO&byI&o)iE;vjzkJ diff --git a/cryptoai/api/alltick_api.py b/cryptoai/api/alltick_api.py new file mode 100644 index 0000000..2c0da57 --- /dev/null +++ b/cryptoai/api/alltick_api.py @@ -0,0 +1,134 @@ +#!/usr/bin/env python +# -*- coding: utf-8 -*- + +import os +import json +import requests +import urllib.parse +from typing import Dict, Any, Optional +from datetime import datetime +import pandas as pd + + +class AllTickAPI: + """AllTick API客户端，用于获取黄金等商品的K线数据""" + + def __init__(self, api_key: str): + """ + 初始化AllTick API客户端 + + Args: + api_key: AllTick API密钥 + """ + self.api_key = api_key + self.base_url = "https://quote.alltick.io/quote-b-api" + self.session = requests.Session() + + def get_historical_klines(self, symbol: str, interval: str, start_str: Optional[str] = None, + limit: int = 500) -> pd.DataFrame: + """ + 获取历史K线数据 + + Args: + symbol: 交易对符号，例如 "XAUUSD" + interval: K线时间间隔，可选: 1m, 5m, 15m, 30m, 1h, 2h, 4h, 1d, 1w, 1M + start_str: 开始时间，格式为 "YYYY-MM-DD" + limit: 获取的K线数量，最大为1000 + + Returns: + K线数据的DataFrame + """ + # 转换时间间隔格式 + kline_type = self._convert_interval(interval) + + # 计算结束时间戳 + end_timestamp = 0 # 0表示从当前时间开始查询 + + # 限制查询数量 + query_kline_num = min(limit, 1000) # AllTick API每次最多查询1000根K线 + + # 构建查询参数 + query_data = { + "trace": datetime.now().strftime("%Y%m%d%H%M%S"), + "data": { + "code": symbol, + "kline_type": kline_type, + "kline_timestamp_end": end_timestamp, + "query_kline_num": query_kline_num, + "adjust_type": 0 # 0: 除权 + } + } + + # 对查询参数进行编码 + encoded_query = urllib.parse.quote(json.dumps(query_data)) + + # 构建完整的URL + url = f"{self.base_url}/kline?token={self.api_key}&query={encoded_query}" + + try: + # 发送请求 + response = self.session.get(url) + response.raise_for_status() # 如果响应状态码不是200，则抛出异常 + + # 解析响应 + result = response.json() + + # 检查返回状态 + if result.get("ret") != 200: + print(f"请求出错: {result.get('msg')}") + return pd.DataFrame() + + # 获取K线数据 + kline_data = result.get("data", {}).get("kline_list", []) + + if not kline_data: + print(f"未获取到{symbol}的K线数据") + return pd.DataFrame() + + # 转换为DataFrame + df = pd.DataFrame(kline_data) + + # 转换列类型 + df["timestamp"] = pd.to_datetime(df["timestamp"].astype(int), unit="s") + df["open"] = df["open_price"].astype(float) + df["high"] = df["high_price"].astype(float) + df["low"] = df["low_price"].astype(float) + df["close"] = df["close_price"].astype(float) + df["volume"] = df["volume"].astype(float) + + # 设置索引 + df.set_index("timestamp", inplace=True) + + # 选择需要的列 + df = df[["open", "high", "low", "close", "volume"]] + + return df + + except Exception as e: + print(f"获取K线数据时出错: {e}") + return pd.DataFrame() + + def _convert_interval(self, interval: str) -> int: + """ + 将Binance格式的时间间隔转换为AllTick格式 + + Args: + interval: Binance格式的时间间隔，例如 "1m", "1h", "1d" + + Returns: + AllTick格式的K线类型 + """ + interval_map = { + "1m": 1, # 1分钟K + "5m": 2, # 5分钟K + "15m": 3, # 15分钟K + "30m": 4, # 30分钟K + "1h": 5, # 小时K + "2h": 6, # 2小时K + "4h": 7, # 4小时K + "1d": 8, # 日K + "1w": 9, # 周K + "1M": 10 # 月K + } + + return interval_map.get(interval, 8) # 默认返回日K \ No newline at end of file diff --git a/cryptoai/config/config.example.yaml b/cryptoai/config/config.example.yaml index 04c5fb0..59d30fa 100644 --- a/cryptoai/config/config.example.yaml +++ b/cryptoai/config/config.example.yaml @@ -9,6 +9,13 @@ deepseek: api_key: "your_deepseek_api_key_here" model: "deepseek-chat" # 使用的模型 +# AllTick API设置（用于获取黄金数据） +alltick: + api_key: "6c7ba077eee07f6f270e219d4848700e-c-app" + symbols: + - "XAUUSD" # 黄金/美元 + # - "XAGUSD" # 白银/美元 + # 加密货币设置 crypto: base_currencies: @@ -20,6 +27,21 @@ crypto: quote_currency: "USDT" time_interval: "4h" # 可选: 1m, 5m, 15m, 30m, 1h, 4h, 1d +# 黄金市场分析配置 +gold: + # 黄金交易对 + symbols: ["XAUUSD"] + # 历史数据天数 + historical_days: 180 + # 时间间隔 + time_interval: "1d" + # 分析间隔（分钟） + analysis_interval: 360 + # 是否启用宏观经济因素分析 + enable_macro_analysis: true + # 是否保存图表 + save_charts: true + # 数据设置 data: storage_path: "./cryptoai/data" diff --git a/cryptoai/config/config.yaml b/cryptoai/config/config.yaml index 722c953..9153311 100644 --- a/cryptoai/config/config.yaml +++ b/cryptoai/config/config.yaml @@ -9,17 +9,39 @@ deepseek: api_key: "sk-9f6b56f08796435d988cf202e37f6ee3" model: "deepseek-chat" # 使用的模型 +# AllTick API设置（用于获取黄金数据） +alltick: + api_key: "ee66d8e2868fd988fffacec40d078df8-c-app" + symbols: + - "XAUUSD" # 黄金/美元 + # - "XAGUSD" # 白银/美元 + # 加密货币设置 crypto: base_currencies: - - "BTC" + # - "ONDO" # - "ETH" # - "BNB" # - "SOL" - # - "SUI" + - "SUI" quote_currency: "USDT" time_interval: "4h" # 可选: 1m, 5m, 15m, 30m, 1h, 4h, 1d +# 黄金市场分析配置 +gold: + # 黄金交易对 + symbols: ["GOLD"] + # 历史数据天数 + historical_days: 180 + # 时间间隔 + time_interval: "1d" + # 分析间隔（分钟） + analysis_interval: 360 + # 是否启用宏观经济因素分析 + enable_macro_analysis: true + # 是否保存图表 + save_charts: true + # 数据设置 data: storage_path: "./cryptoai/data" diff --git a/cryptoai/main.py b/cryptoai/main.py index 0dd641f..7be881d 100644 --- a/cryptoai/main.py +++ b/cryptoai/main.py @@ -12,6 +12,7 @@ parent_dir = os.path.dirname(current_dir) sys.path.append(parent_dir) from cryptoai.agents.crypto_agent import CryptoAgent +from cryptoai.agents.gold_agent import GoldAgent from cryptoai.utils.config_loader import ConfigLoader @@ -38,6 +39,13 @@ def parse_arguments(): choices=['low', 'medium', 'high'], help='风险等级，默认使用配置中的值') + parser.add_argument('--agent', type=str, default='crypto', + choices=['crypto', 'gold'], + help='要使用的智能体类型，默认为加密货币智能体') + + parser.add_argument('--alltick-key', type=str, default=None, + help='AllTick API密钥，用于获取黄金等商品数据') + return parser.parse_args() @@ -56,28 +64,41 @@ def override_config_with_args(config_loader: ConfigLoader, args) -> None: # 覆盖配置 if args.symbol: - crypto_config['base_currencies'] = [args.symbol.replace(crypto_config['quote_currency'], '')] + if args.agent == 'crypto': + crypto_config['base_currencies'] = [args.symbol.replace(crypto_config['quote_currency'], '')] + elif args.agent == 'gold': + gold_config = config_loader.get_config('gold') + gold_config['symbols'] = [args.symbol] if args.days: data_config['historical_days'] = args.days if args.interval: - crypto_config['time_interval'] = args.interval + if args.agent == 'crypto': + crypto_config['time_interval'] = args.interval + elif args.agent == 'gold': + gold_config = config_loader.get_config('gold') + gold_config['time_interval'] = args.interval if args.risk_level: agent_config['risk_level'] = args.risk_level + # 设置AllTick API密钥 + if args.alltick_key: + alltick_config = config_loader.get_config('alltick') + alltick_config['api_key'] = args.alltick_key + # 保存修改后的配置 # 注意：这只是修改了内存中的配置，没有写入文件 # 如果需要保存到文件，可以实现一个 save_config 方法 -def analyze_single_symbol(agent: CryptoAgent, symbol: str, days: int = 30) -> Dict[str, Any]: +def analyze_single_symbol(agent, symbol: str, days: int = 30) -> Dict[str, Any]: """ 分析单个交易对 Args: - agent: 加密货币智能体 + agent: 智能体实例 symbol: 交易对符号 days: 历史数据天数 @@ -95,21 +116,26 @@ def analyze_single_symbol(agent: CryptoAgent, symbol: str, days: int = 30) -> Di processed_data = agent.process_data(symbol, raw_data) - # 分析市场 - analysis_result = agent.analyze_market(symbol, processed_data) - - # 预测价格 - prediction_result = agent.predict_price(symbol) - - # 生成策略 - strategy = agent.generate_strategy(symbol, analysis_result) - - # 整合结果 - result = { - "analysis": analysis_result, - "prediction": prediction_result, - "strategy": strategy - } + # 根据agent类型执行不同的分析 + if isinstance(agent, CryptoAgent): + # 分析市场 + analysis_result = agent.analyze_market(symbol, processed_data) + + # 预测价格 + prediction_result = agent.predict_price(symbol) + + # 生成策略 + strategy = agent.generate_strategy(symbol, analysis_result) + + # 整合结果 + result = { + "analysis": analysis_result, + "prediction": prediction_result, + "strategy": strategy + } + elif isinstance(agent, GoldAgent): + # 黄金agent没有单独的analyze_market方法，使用完整分析 + result = agent.analyze_gold() print(f"{symbol}分析完成") @@ -128,20 +154,36 @@ def main(): # 使用命令行参数覆盖配置 override_config_with_args(config_loader, args) - # 创建智能体 - agent = CryptoAgent(config_path=args.config) + # 根据agent类型创建不同的智能体 + if args.agent == 'crypto': + agent = CryptoAgent(config_path=args.config) + print("已启动加密货币分析智能体") + elif args.agent == 'gold': + agent = GoldAgent(config_path=args.config) + print("已启动黄金分析智能体") # 如果指定了单个交易对 if args.symbol: result = analyze_single_symbol( agent=agent, symbol=args.symbol, - days=args.days or agent.data_config['historical_days'] + days=args.days or ( + agent.data_config['historical_days'] if isinstance(agent, CryptoAgent) + else agent.gold_config.get('historical_days', 180) + ) ) - print("\n分析结果:") - print(f"市场趋势: {result.get('analysis', {}).get('market_trend', 'unknown')}") - print(f"24小时预测: {result.get('prediction', {}).get('prediction_24h', {})}") - print(f"建议操作: {result.get('strategy', {}).get('position', 'unknown')}") + + if isinstance(agent, CryptoAgent): + print("\n分析结果:") + print(f"市场趋势: {result.get('analysis', {}).get('market_trend', 'unknown')}") + print(f"24小时预测: {result.get('prediction', {}).get('prediction_24h', {})}") + print(f"建议操作: {result.get('strategy', {}).get('position', 'unknown')}") + elif isinstance(agent, GoldAgent) and result: + print("\n分析结果:") + symbol_result = result.get(args.symbol, {}) + analysis = symbol_result.get('analysis', {}) + print(f"市场趋势: {analysis.get('market_trend', 'unknown')}") + print(f"建议操作: {analysis.get('recommendation', 'unknown')}") else: # 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获取当前文件的目录 - current_dir = os.path.dirname(os.path.dirname(os.path.abspath(__file__))) - config_path = os.path.join(current_dir, "config", "config.yaml") + # 默认配置文件路径 + current_dir = os.path.dirname(os.path.abspath(__file__)) + config_dir = os.path.join(os.path.dirname(current_dir), 'config') + config_path = os.path.join(config_dir, 'config.yaml') + + # 如果默认配置文件不存在，则使用示例配置文件 + if not os.path.exists(config_path): + config_path = os.path.join(config_dir, 'config.example.yaml') + print(f"配置文件 config.yaml 不存在，使用示例配置文件: {config_path}") self.config_path = config_path - self.config_data = self._load_config() + + # 加载配置 + self.config = self._load_config() def _load_config(self) -> Dict[str, Any]: """ 加载配置文件 Returns: - 配置数据字典 + 配置字典 """ try: - with open(self.config_path, 'r', encoding='utf-8') as file: - config_data = yaml.safe_load(file) - return config_data + with open(self.config_path, 'r', encoding='utf-8') as f: + config = yaml.safe_load(f) + print(f"已加载配置文件: {self.config_path}") + return config except Exception as e: - print(f"加载配置文件时出错: {e}") + print(f"加载配置文件失败: {e}") return {} - def get_config(self, section: str = None) -> Dict[str, Any]: + def get_config(self, section: str) -> Dict[str, Any]: """ - 获取配置数据 + 获取指定部分的配置 Args: - section: 配置部分名称，如果为None，则返回整个配置 + section: 配置部分名称 Returns: - 配置数据或指定部分的配置数据 + 配置字典 """ - if section is None: - return self.config_data - - return self.config_data.get(section, {}) + return self.config.get(section, {}) def get_binance_config(self) -> Dict[str, Any]: - """获取Binance API配置""" + """获取Binance配置""" return self.get_config('binance') def get_deepseek_config(self) -> Dict[str, Any]: - """获取DeepSeek API配置""" + """获取DeepSeek配置""" return self.get_config('deepseek') + def get_alltick_config(self) -> Dict[str, Any]: + """获取AllTick配置""" + return self.get_config('alltick') + def get_crypto_config(self) -> Dict[str, Any]: """获取加密货币配置""" return self.get_config('crypto') diff --git a/run.py b/run.py index 2c1efb1..d4668db 100755 --- a/run.py +++ b/run.py @@ -10,6 +10,9 @@ CryptoAI 启动脚本 python run.py --symbol BTCUSDT # 只分析指定的交易对 python run.py --days 7 # 获取7天的历史数据 python run.py --risk-level low # 设置低风险等级 + python run.py --agent gold # 使用黄金分析智能体 + python run.py --agent crypto # 使用加密货币分析智能体 + python run.py --alltick-key KEY # 设置AllTick API密钥 """ import sys