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from __future__ import annotations
from typing import Dict, Any
from ..state import AgentState
from .workflow import build_workflow_app
def run_pipeline(topic: str, mode: str = "blog") -> AgentState:
"""
High-level helper to run the full workflow from scratch.
"""
initial_state: AgentState = {
"topic": topic,
"mode": mode,
"research_snippets": [],
"outline": [],
"draft": "",
"revised_draft": "",
"final_output": "",
"meta": {},
}
app = build_workflow_app()
final_state: Dict[str, Any] = app.invoke(initial_state) # type: ignore[assignment]
# LangGraph returns a dict compatible with AgentState
return final_state # type: ignore[return-value]
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