# 文件差异报告 # 当前文件: tradingagents\dataflows\interface.py # 中文版文件: TradingAgentsCN\tradingagents\dataflows\interface.py # 生成时间: 周日 2025/07/06 --- current/interface.py+++ chinese_version/interface.py@@ -1,5 +1,6 @@ from typing import Annotated, Dict from .reddit_utils import fetch_top_from_category +from .chinese_finance_utils import get_chinese_social_sentiment from .yfin_utils import * from .stockstats_utils import * from .googlenews_utils import * @@ -43,7 +44,14 @@ result = get_data_in_range(ticker, before, curr_date, "news_data", DATA_DIR) if len(result) == 0: - return "" + error_msg = f"⚠️ 无法获取{ticker}的新闻数据 ({before} 到 {curr_date})\n" + error_msg += f"可能的原因：\n" + error_msg += f"1. 数据文件不存在或路径配置错误\n" + error_msg += f"2. 指定日期范围内没有新闻数据\n" + error_msg += f"3. 需要先下载或更新Finnhub新闻数据\n" + error_msg += f"建议：检查数据目录配置或重新获取新闻数据" + print(f"📰 [DEBUG] {error_msg}") + return error_msg combined_result = "" for day, data in result.items(): @@ -772,36 +780,217 @@ return response.output[1].content[0].text +def get_fundamentals_finnhub(ticker, curr_date): + """ + 使用Finnhub API获取股票基本面数据作为OpenAI的备选方案 + Args: + ticker (str): 股票代码 + curr_date (str): 当前日期，格式为yyyy-mm-dd + Returns: + str: 格式化的基本面数据报告 + """ + try: + import finnhub + import os + from .cache_manager import get_cache + + # 检查缓存 + cache = get_cache() + cached_key = cache.find_cached_fundamentals_data(ticker, data_source="finnhub") + if cached_key: + cached_data = cache.load_fundamentals_data(cached_key) + if cached_data: + print(f"💾 [DEBUG] 从缓存加载Finnhub基本面数据: {ticker}") + return cached_data + + # 获取Finnhub API密钥 + api_key = os.getenv('FINNHUB_API_KEY') + if not api_key: + return "错误：未配置FINNHUB_API_KEY环境变量" + + # 初始化Finnhub客户端 + finnhub_client = finnhub.Client(api_key=api_key) + + print(f"📊 [DEBUG] 使用Finnhub API获取 {ticker} 的基本面数据...") + + # 获取基本财务数据 + try: + basic_financials = finnhub_client.company_basic_financials(ticker, 'all') + except Exception as e: + print(f"❌ [DEBUG] Finnhub基本财务数据获取失败: {str(e)}") + basic_financials = None + + # 获取公司概况 + try: + company_profile = finnhub_client.company_profile2(symbol=ticker) + except Exception as e: + print(f"❌ [DEBUG] Finnhub公司概况获取失败: {str(e)}") + company_profile = None + + # 获取收益数据 + try: + earnings = finnhub_client.company_earnings(ticker, limit=4) + except Exception as e: + print(f"❌ [DEBUG] Finnhub收益数据获取失败: {str(e)}") + earnings = None + + # 格式化报告 + report = f"# {ticker} 基本面分析报告（Finnhub数据源）\n\n" + report += f"**数据获取时间**: {curr_date}\n" + report += f"**数据来源**: Finnhub API\n\n" + + # 公司概况部分 + if company_profile: + report += "## 公司概况\n" + report += f"- **公司名称**: {company_profile.get('name', 'N/A')}\n" + report += f"- **行业**: {company_profile.get('finnhubIndustry', 'N/A')}\n" + report += f"- **国家**: {company_profile.get('country', 'N/A')}\n" + report += f"- **货币**: {company_profile.get('currency', 'N/A')}\n" + report += f"- **市值**: {company_profile.get('marketCapitalization', 'N/A')} 百万美元\n" + report += f"- **流通股数**: {company_profile.get('shareOutstanding', 'N/A')} 百万股\n\n" + + # 基本财务指标 + if basic_financials and 'metric' in basic_financials: + metrics = basic_financials['metric'] + report += "## 关键财务指标\n" + report += "| 指标 | 数值 |\n" + report += "|------|------|\n" + + # 估值指标 + if 'peBasicExclExtraTTM' in metrics: + report += f"| 市盈率 (PE) | {metrics['peBasicExclExtraTTM']:.2f} |\n" + if 'psAnnual' in metrics: + report += f"| 市销率 (PS) | {metrics['psAnnual']:.2f} |\n" + if 'pbAnnual' in metrics: + report += f"| 市净率 (PB) | {metrics['pbAnnual']:.2f} |\n" + + # 盈利能力指标 + if 'roeTTM' in metrics: + report += f"| 净资产收益率 (ROE) | {metrics['roeTTM']:.2f}% |\n" + if 'roaTTM' in metrics: + report += f"| 总资产收益率 (ROA) | {metrics['roaTTM']:.2f}% |\n" + if 'netProfitMarginTTM' in metrics: + report += f"| 净利润率 | {metrics['netProfitMarginTTM']:.2f}% |\n" + + # 财务健康指标 + if 'currentRatioAnnual' in metrics: + report += f"| 流动比率 | {metrics['currentRatioAnnual']:.2f} |\n" + if 'totalDebt/totalEquityAnnual' in metrics: + report += f"| 负债权益比 | {metrics['totalDebt/totalEquityAnnual']:.2f} |\n" + + report += "\n" + + # 收益历史 + if earnings: + report += "## 收益历史\n" + report += "| 季度 | 实际EPS | 预期EPS | 差异 |\n" + report += "|------|---------|---------|------|\n" + for earning in earnings[:4]: # 显示最近4个季度 + actual = earning.get('actual', 'N/A') + estimate = earning.get('estimate', 'N/A') + period = earning.get('period', 'N/A') + surprise = earning.get('surprise', 'N/A') + report += f"| {period} | {actual} | {estimate} | {surprise} |\n" + report += "\n" + + # 数据可用性说明 + report += "## 数据说明\n" + report += "- 本报告使用Finnhub API提供的官方财务数据\n" + report += "- 数据来源于公司财报和SEC文件\n" + report += "- TTM表示过去12个月数据\n" + report += "- Annual表示年度数据\n\n" + + if not basic_financials and not company_profile and not earnings: + report += "⚠️ **警告**: 无法获取该股票的基本面数据，可能原因：\n" + report += "- 股票代码不正确\n" + report += "- Finnhub API限制\n" + report += "- 该股票暂无基本面数据\n" + + # 保存到缓存 + if report and len(report) > 100: # 只有当报告有实际内容时才缓存 + cache.save_fundamentals_data(ticker, report, data_source="finnhub") + + print(f"📊 [DEBUG] Finnhub基本面数据获取完成，报告长度: {len(report)}") + return report + + except ImportError: + return "错误：未安装finnhub-python库，请运行: pip install finnhub-python" + except Exception as e: + print(f"❌ [DEBUG] Finnhub基本面数据获取失败: {str(e)}") + return f"Finnhub基本面数据获取失败: {str(e)}" + + def get_fundamentals_openai(ticker, curr_date): - config = get_config() - client = OpenAI(base_url=config["backend_url"]) - - response = client.responses.create( - model=config["quick_think_llm"], - input=[ - { - "role": "system", - "content": [ - { - "type": "input_text", - "text": f"Can you search Fundamental for discussions on {ticker} during of the month before {curr_date} to the month of {curr_date}. Make sure you only get the data posted during that period. List as a table, with PE/PS/Cash flow/ etc", - } - ], - } - ], - text={"format": {"type": "text"}}, - reasoning={}, - tools=[ - { - "type": "web_search_preview", - "user_location": {"type": "approximate"}, - "search_context_size": "low", - } - ], - temperature=1, - max_output_tokens=4096, - top_p=1, - store=True, - ) - - return response.output[1].content[0].text + """ + 获取股票基本面数据，优先使用OpenAI，失败时回退到Finnhub API + 支持缓存机制以提高性能 + Args: + ticker (str): 股票代码 + curr_date (str): 当前日期，格式为yyyy-mm-dd + Returns: + str: 基本面数据报告 + """ + try: + from .cache_manager import get_cache + + # 检查缓存 - 优先检查OpenAI缓存 + cache = get_cache() + cached_key = cache.find_cached_fundamentals_data(ticker, data_source="openai") + if cached_key: + cached_data = cache.load_fundamentals_data(cached_key) + if cached_data: + print(f"💾 [DEBUG] 从缓存加载OpenAI基本面数据: {ticker}") + return cached_data + + config = get_config() + + # 检查是否配置了OpenAI相关设置 + if not config.get("backend_url") or not config.get("quick_think_llm"): + print(f"📊 [DEBUG] OpenAI配置不完整，直接使用Finnhub API") + return get_fundamentals_finnhub(ticker, curr_date) + + print(f"📊 [DEBUG] 尝试使用OpenAI获取 {ticker} 的基本面数据...") + + client = OpenAI(base_url=config["backend_url"]) + + response = client.responses.create( + model=config["quick_think_llm"], + input=[ + { + "role": "system", + "content": [ + { + "type": "input_text", + "text": f"Can you search Fundamental for discussions on {ticker} during of the month before {curr_date} to the month of {curr_date}. Make sure you only get the data posted during that period. List as a table, with PE/PS/Cash flow/ etc", + } + ], + } + ], + text={"format": {"type": "text"}}, + reasoning={}, + tools=[ + { + "type": "web_search_preview", + "user_location": {"type": "approximate"}, + "search_context_size": "low", + } + ], + temperature=1, + max_output_tokens=4096, + top_p=1, + store=True, + ) + + result = response.output[1].content[0].text + + # 保存到缓存 + if result and len(result) > 100: # 只有当结果有实际内容时才缓存 + cache.save_fundamentals_data(ticker, result, data_source="openai") + + print(f"📊 [DEBUG] OpenAI基本面数据获取成功，长度: {len(result)}") + return result + + except Exception as e: + print(f"❌ [DEBUG] OpenAI基本面数据获取失败: {str(e)}") + print(f"📊 [DEBUG] 回退到Finnhub API...") + return get_fundamentals_finnhub(ticker, curr_date)