He Tao
40 lines
1.3 KiB
Python
40 lines
1.3 KiB
Python
# Copyright (c) 2025 Bytedance Ltd. and/or its affiliates
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# SPDX-License-Identifier: MIT
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from langgraph.graph import END, START, StateGraph
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from src.podcast.graph.audio_mixer_node import audio_mixer_node
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from src.podcast.graph.script_writer_node import script_writer_node
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from src.podcast.graph.state import PodcastState
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from src.podcast.graph.tts_node import tts_node
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def build_graph():
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"""Build and return the podcast workflow graph."""
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# build state graph
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builder = StateGraph(PodcastState)
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builder.add_node("script_writer", script_writer_node)
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builder.add_node("tts", tts_node)
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builder.add_node("audio_mixer", audio_mixer_node)
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builder.add_edge(START, "script_writer")
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builder.add_edge("script_writer", "tts")
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builder.add_edge("tts", "audio_mixer")
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builder.add_edge("audio_mixer", END)
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return builder.compile()
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workflow = build_graph()
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if __name__ == "__main__":
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from dotenv import load_dotenv
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load_dotenv()
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report_content = open("examples/nanjing_tangbao.md").read()
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final_state = workflow.invoke({"input": report_content})
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for line in final_state["script"].lines:
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print("<M>" if line.speaker == "male" else "<F>", line.text)
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with open("final.mp3", "wb") as f:
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f.write(final_state["output"])
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