feat: add SEC 13F holdings analysis agent

python/configs/agent_cards/sec_agent.json

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+{
+    "name": "Sec13FundAgent",
+    "url": "http://localhost:10001/",
+    "enabled": true
+}

python/valuecell/agents/sec_13F_agent.py

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+import asyncio
+
+from agno.agent import Agent, RunResponse, RunResponseEvent  # noqa
+from agno.models.openrouter import OpenRouter
+from edgar import Company, set_identity
+from pydantic import BaseModel, Field, field_validator
+
+# from valuecell.core.agent.decorator import serve
+from valuecell.core.agent.types import BaseAgent
+from valuecell.core.agent.decorator import create_wrapped_agent
+
+
+class Sec13FundRequest(BaseModel):
+    ticker: str = Field(
+        ...,
+        description="Stock ticker symbol to analyze (e.g., 'AAPL', 'TSLA'). Only one ticker symbol is allowed per request.",
+    )
+
+    @field_validator("ticker")
+    @classmethod
+    def validate_tickers(cls, v):
+        return v
+
+
+# @serve(name="sec13fundAgent")
+class Sec13FundAgent(BaseAgent):
+    """
+    A simple agent that uses the SEC API to retrieve information about a company.
+    """
+
+    def __init__(self):
+        super().__init__()
+        # 用于解析查询的Agent
+        self.parser_agent = Agent(
+            model=OpenRouter(id="openai/gpt-5-mini"),
+            response_model=Sec13FundRequest,
+            markdown=True,
+        )
+        # 用于分析的Agent
+        self.analysis_agent = Agent(
+            model=OpenRouter(id="deepseek/deepseek-chat-v3-0324"),
+            markdown=True,
+        )
+
+    async def stream(self, query, session_id, task_id):
+        run_response = self.parser_agent.run(
+            f"Parse the following sec 13 funds request and extract the parameters: {query}"
+        )
+        sec_13_fund_request = run_response.content
+        company_name = sec_13_fund_request.ticker
+
+        set_identity("your.name@example.com")
+        # %%
+        brk = Company(company_name)
+        filings = brk.get_filings(form="13F-HR").head(3)
+
+        # %%
+        o = filings[1].obj()
+        current = o.infotable.to_json()
+
+        # %%
+        o = filings[2].obj()
+        pre = o.infotable.to_json()
+
+        analysis_prompt = f"""
+        As a professional investment analyst, please conduct an in-depth analysis of the following 13F holdings data:
+
+        ## Previous Holdings Data:
+        {pre}
+
+        ## Current Holdings Data:
+        {current}
+
+        ## Analysis Requirements:
+        Please provide professional analysis from the following perspectives:
+
+        ### 1. Holdings Changes Summary
+        - New Positions: List newly acquired stocks and potential investment rationale
+        - Exits/Reductions: Analyze divested stocks and speculated reasons
+        - Position Adjustments: Focus on stocks with position changes exceeding 20%
+
+        ### 2. Sector Allocation Analysis
+        - Sector Weight Changes: Adjustments in sector allocation percentages
+        - Investment Preferences: Changes in sector preferences reflected by capital flows
+        - Concentration Changes: Adjustments in portfolio concentration
+
+        ### 3. Key Holdings Analysis
+        - Specific changes in top 10 holdings
+        - Calculate increase/decrease percentages for major positions
+        - Analyze possible reasons for significant position adjustments
+
+        ### 4. Investment Strategy Insights
+        - Investment style adjustments reflected in holdings changes
+        - Market trend judgments and responses
+        - Changes in risk appetite
+
+        ## Output Requirements:
+        Please output analysis results in a clear structure, including:
+        - 📊 **Key Findings**: 3-5 critical insights
+        - 📈 **Important Data**: Specific change data and percentages
+        - 🎯 **Investment Insights**: Reference value for investors
+        - ⚠️ **Risk Alerts**: Risk points that need attention
+
+        Please ensure the analysis is objective and professional, based on factual data, avoiding excessive speculation.
+        """
+
+        result = self.analysis_agent.run(analysis_prompt)
+
+        yield {
+            "content": result.content,
+            "is_task_complete": True,
+        }
+
+
+if __name__ == "__main__":
+    agent = create_wrapped_agent(Sec13FundAgent)
+    asyncio.run(agent.serve())

python/valuecell/agents/sec_client.py

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+import asyncio
+from valuecell.core.agent.connect import RemoteConnections
+
+
+async def main():
+    # Create connection manager
+    connections = RemoteConnections()
+
+    # List all available Agents
+    available = connections.list_available_agents()
+    print(f"Available Agents: {available}")
+
+    # Start Agent
+    calc_url = await connections.start_agent("Sec13FundAgent")
+    print(f"Calculator Agent started at: {calc_url}")
+
+    # Get client and send message
+    client = await connections.get_client("Sec13FundAgent")
+    async for task, event in await client.send_message(
+        "伯克希尔最近持仓变化", streaming=True
+    ):
+        print(f"接收到Task: {task}")
+
+    print(f"Calculation result: {task.status}")
+
+    # Clean up resources
+    await connections.stop_all()
+
+
+if __name__ == "__main__":
+    asyncio.run(main())