first commit

.gitignore

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+.env
+.venv/

.idea/.gitignore

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+# Default ignored files
+/shelf/
+/workspace.xml
+# Editor-based HTTP Client requests
+/httpRequests/

.idea/inspectionProfiles/Project_Default.xml

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+<component name="InspectionProjectProfileManager">
+  <profile version="1.0">
+    <option name="myName" value="Project Default" />
+    <inspection_tool class="PyStubPackagesAdvertiser" enabled="true" level="WARNING" enabled_by_default="true">
+      <option name="ignoredPackages">
+        <list>
+          <option value="pandas" />
+        </list>
+      </option>
+    </inspection_tool>
+  </profile>
+</component>

.idea/inspectionProfiles/profiles_settings.xml

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+<component name="InspectionProjectProfileManager">
+  <settings>
+    <option name="USE_PROJECT_PROFILE" value="false" />
+    <version value="1.0" />
+  </settings>
+</component>

.idea/misc.xml

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+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="ProjectRootManager" version="2" project-jdk-name="~/files/code/python/stock_agent/.venv" project-jdk-type="Python SDK" />
+</project>

.idea/modules.xml

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+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="ProjectModuleManager">
+    <modules>
+      <module fileurl="file://$PROJECT_DIR$/.idea/stock_agent.iml" filepath="$PROJECT_DIR$/.idea/stock_agent.iml" />
+    </modules>
+  </component>
+</project>

.idea/stock_agent.iml

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+<?xml version="1.0" encoding="UTF-8"?>
+<module type="PYTHON_MODULE" version="4">
+  <component name="NewModuleRootManager">
+    <content url="file://$MODULE_DIR$">
+      <excludeFolder url="file://$MODULE_DIR$/.venv" />
+    </content>
+    <orderEntry type="jdk" jdkName="~/files/code/python/stock_agent/.venv" jdkType="Python SDK" />
+    <orderEntry type="sourceFolder" forTests="false" />
+  </component>
+  <component name="PackageRequirementsSettings" />
+  <component name="PyDocumentationSettings" />
+  <component name="ReSTService" />
+  <component name="TestRunnerService" />
+</module>

.idea/vcs.xml

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+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="VcsDirectoryMappings">
+    <mapping directory="$PROJECT_DIR$" vcs="Git" />
+  </component>
+</project>

adata_test.py

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+from adata import stock
+import pandas as pd
+
+# 显示所有列
+pd.set_option('display.max_columns', None)
+# 显示所有行
+pd.set_option('display.max_rows', None)
+# 显示单元格完整内容（不截断长文本）
+pd.set_option('display.max_colwidth', None)
+# 不自动折行
+pd.set_option('display.expand_frame_repr', False)
+
+
+def get_fina_info(stock_code="600699"):
+
+    df = stock.finance.get_core_index(stock_code=stock_code)
+
+    data = df[['report_date', 'report_type', 'total_rev', 'total_rev_yoy_gr','net_profit_attr_sh', 'net_profit_yoy_gr',
+               'non_gaap_net_profit', 'non_gaap_net_profit_yoy_gr', 'roe_wtd', 'gross_margin', 'net_margin', 'quick_ratio',
+               'inv_turn_rate', 'acct_recv_turn_rate']]
+
+    last_type = data['report_type'].to_list()[0]
+
+    recent_df = data[data.report_type == last_type].iloc[:2,:].reset_index(drop=True)
+
+    recent_df.rename(columns={"report_date": "报告日期",
+                        "report_type": "报告类型",
+                        "total_rev":"营业总收入",
+                        "total_rev_yoy_gr":"营业总收入同比增长率",
+                        "net_profit_attr_sh":"归母净利润",
+                        "net_profit_yoy_gr":"归母净利润同比增长率",
+                        "non_gaap_net_profit":"扣非净利润",
+                        "non_gaap_net_profit_yoy_gr":"扣非净利润同比增长率",
+                        "roe_wtd":"加权净资产收益率",
+                        "gross_margin":"销售毛利率",
+                        "net_margin":"销售净利率",
+                        "quick_ratio":"速动比率",
+                        "inv_turn_rate":"存货周转率",
+                        "acct_recv_turn_rate":"应收账款周转率"
+                        }, inplace=True)
+
+    formatted_lines = []
+    for _, row in recent_df.iterrows():
+        line_items = []
+        for col, val in zip(recent_df.columns, row):
+            # 判断是否为数字类型
+            if isinstance(val, (int, float)):
+                # 如果列名包含"率"，则格式化为保留两位小数并加上 %
+                if "率" in col:
+                    formatted_val = f"{val:.2f}%"
+                else:
+                    # 其他数字：格式化为带千分位、保留两位小数
+                    formatted_val = f"{val:,.2f}"
+            else:
+                # 非数字类型（如日期、文本）直接转为字符串
+                formatted_val = str(val)
+
+            line_items.append(f"{col}：{formatted_val}")
+
+        # 将这一期的所有字段用换行符拼接
+        formatted_lines.append("\n".join(line_items))
+
+    # 3. 组装最终报告文本
+    final_report = f"近两期{last_type}主要财务数据如下：\n" + "\n\n".join(formatted_lines)
+
+    return final_report
+
+
+if __name__ == "__main__":
+    print(get_fina_info(stock_code="600105"))

main.py

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+import os
+from langchain_classic.agents import AgentExecutor, create_tool_calling_agent
+from langchain_core.prompts import ChatPromptTemplate
+from langchain_core.output_parsers import StrOutputParser
+from langchain_openai import ChatOpenAI
+from dotenv import load_dotenv
+from adata import stock
+from langchain_core.tools import tool
+from telegram import Update
+from telegram.ext import ApplicationBuilder, ContextTypes, CommandHandler, MessageHandler, filters
+
+load_dotenv()
+
+
+# ================= 你的原有逻辑（完全保留） =================
+@tool
+def get_fina_info(stock_code: str) -> str:
+    """获取指定股票代码的财务数据。当需要获取财务数据的时使用此工具"""
+    df = stock.finance.get_core_index(stock_code=stock_code)
+
+    data = df[['report_date', 'report_type', 'total_rev', 'total_rev_yoy_gr', 'net_profit_attr_sh', 'net_profit_yoy_gr',
+               'non_gaap_net_profit', 'non_gaap_net_profit_yoy_gr', 'roe_wtd', 'gross_margin', 'net_margin',
+               'quick_ratio',
+               'inv_turn_rate', 'acct_recv_turn_rate']]
+
+    last_type = data['report_type'].to_list()[0]
+    recent_df = data[data.report_type == last_type].iloc[:2, :].reset_index(drop=True)
+
+    recent_df.rename(columns={"report_date": "报告日期", "report_type": "报告类型", "total_rev": "营业总收入",
+                              "total_rev_yoy_gr": "营业总收入同比增长率", "net_profit_attr_sh": "归母净利润",
+                              "net_profit_yoy_gr": "归母净利润同比增长率", "non_gaap_net_profit": "扣非净利润",
+                              "non_gaap_net_profit_yoy_gr": "扣非净利润同比增长率", "roe_wtd": "加权净资产收益率",
+                              "gross_margin": "销售毛利率", "net_margin": "销售净利率", "quick_ratio": "速动比率",
+                              "inv_turn_rate": "存货周转率", "acct_recv_turn_rate": "应收账款周转率"
+                              }, inplace=True)
+
+    formatted_lines = []
+    for _, row in recent_df.iterrows():
+        line_items = []
+        for col, val in zip(recent_df.columns, row):
+            if isinstance(val, (int, float)):
+                if "率" in col:
+                    formatted_val = f"{val:.2f}%"
+                else:
+                    formatted_val = f"{val:,.2f}"
+            else:
+                formatted_val = str(val)
+            line_items.append(f"{col}：{formatted_val}")
+        formatted_lines.append("\n".join(line_items))
+
+    final_report = f"近两期{last_type}主要财务数据如下：\n" + "\n\n".join(formatted_lines)
+    return final_report
+
+
+class MyOutputParser(StrOutputParser):
+    def parse(self, text) -> str:
+        return text.strip()
+
+
+llm = ChatOpenAI(model="deepseek-v4-flash")
+tools = [get_fina_info]
+template = """
+你是一个专业的股票分析助手。用户会输入一个股票代码，你可以使用工具来获取其财务数据，之后根据获取到的财务数据来分析这家公司的基本面情况。
+"""
+chat_prompt = ChatPromptTemplate.from_messages([
+    ("system", template),
+    ("human", "{input}"),
+    ("placeholder", "{agent_scratchpad}"),
+])
+
+agent = create_tool_calling_agent(llm, tools, chat_prompt)
+agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
+
+
+# ================= 新增：Telegram 机器人交互逻辑 =================
+async def start(update: Update, context: ContextTypes.DEFAULT_TYPE):
+    """处理 /start 命令"""
+    await update.message.reply_text("你好！我是你的股票分析助手，请直接发送类似“分析一下600699的基本面”的消息。")
+
+
+async def handle_message(update: Update, context: ContextTypes.DEFAULT_TYPE):
+    """处理普通文本消息，调用你的 Agent"""
+    user_input = update.message.text
+    # 提示用户正在处理，因为 Agent 调用工具可能需要几秒钟
+    await update.message.reply_text("🤔 正在分析，请稍候...")
+
+    try:
+        # 调用你原有的 Agent 逻辑
+        res = agent_executor.invoke({"input": user_input})
+        output = res["output"]
+    except Exception as e:
+        output = f"分析出错：{str(e)}"
+
+    await update.message.reply_text(output)
+
+
+if __name__ == "__main__":
+    # 从环境变量读取 Token
+    token = os.getenv("TELEGRAM_BOT_TOKEN")
+    if not token:
+        raise ValueError("未在 .env 文件中找到 TELEGRAM_BOT_TOKEN")
+
+    proxy_url = "http://127.0.0.1:8889"
+
+    # 启动机器人
+    application = ApplicationBuilder().token(token).proxy(proxy_url).get_updates_proxy(proxy_url).build()
+    application.add_handler(CommandHandler("start", start))
+    application.add_handler(MessageHandler(filters.TEXT & ~filters.COMMAND, handle_message))
+
+    print("Telegram Bot 正在运行...")
+    application.run_polling()