chore: import upstream snapshot with attribution

examples/financial_research_agent/agents/planner_agent.py

@@ -0,0 +1,35 @@
+from pydantic import BaseModel
+
+from agents import Agent
+
+# Generate a plan of searches to ground the financial analysis.
+# For a given financial question or company, we want to search for
+# recent news, official filings, analyst commentary, and other
+# relevant background.
+PROMPT = (
+    "You are a financial research planner. Given a request for financial analysis, "
+    "produce a set of web searches to gather the context needed. Aim for recent "
+    "headlines, earnings calls or 10‑K snippets, analyst commentary, and industry background. "
+    "Output between 5 and 15 search terms to query for."
+)
+
+
+class FinancialSearchItem(BaseModel):
+    reason: str
+    """Your reasoning for why this search is relevant."""
+
+    query: str
+    """The search term to feed into a web (or file) search."""
+
+
+class FinancialSearchPlan(BaseModel):
+    searches: list[FinancialSearchItem]
+    """A list of searches to perform."""
+
+
+planner_agent = Agent(
+    name="FinancialPlannerAgent",
+    instructions=PROMPT,
+    model="o3-mini",
+    output_type=FinancialSearchPlan,
+)