feat: support Podcast generation

src/podcast/graph/audio_mixer_node.py

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+import logging
+
+from src.podcast.graph.state import PodcastState
+
+logger = logging.getLogger(__name__)
+
+
+def audio_mixer_node(state: PodcastState):
+    logger.info("Mixing audio chunks for podcast...")
+    audio_chunks = state["audio_chunks"]
+    combined_audio = b"".join(audio_chunks)
+    logger.info("The podcast audio is now ready.")
+    return {"output": combined_audio}

src/podcast/graph/builder.py

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+from langgraph.graph import END, START, StateGraph
+
+from .audio_mixer_node import audio_mixer_node
+from .script_writer_node import script_writer_node
+from .state import PodcastState
+from .tts_node import tts_node
+
+
+def build_graph():
+    """Build and return the podcast workflow graph."""
+    # build state graph
+    builder = StateGraph(PodcastState)
+    builder.add_node("script_writer", script_writer_node)
+    builder.add_node("tts", tts_node)
+    builder.add_node("audio_mixer", audio_mixer_node)
+    builder.add_edge(START, "script_writer")
+    builder.add_edge("script_writer", "tts")
+    builder.add_edge("tts", "audio_mixer")
+    builder.add_edge("audio_mixer", END)
+    return builder.compile()
+
+
+if __name__ == "__main__":
+    from dotenv import load_dotenv
+
+    load_dotenv()
+
+    report_content = open("examples/nanjing_tangbao.md").read()
+    workflow = build_graph()
+    final_state = workflow.invoke({"input": report_content})
+    for line in final_state["script"].lines:
+        print("<M>" if line.speaker == "male" else "<F>", line.text)
+
+    with open("final.mp3", "wb") as f:
+        f.write(final_state["output"])

src/podcast/graph/script_writer_node.py

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+import logging
+
+from langchain.schema import HumanMessage, SystemMessage
+
+from src.config.agents import AGENT_LLM_MAP
+from src.llms.llm import get_llm_by_type
+from src.prompts.template import get_prompt_template
+
+from ..types import Script
+from .state import PodcastState
+
+logger = logging.getLogger(__name__)
+
+
+def script_writer_node(state: PodcastState):
+    logger.info("Generating script for podcast...")
+    model = get_llm_by_type(
+        AGENT_LLM_MAP["podcast_script_writer"]
+    ).with_structured_output(Script)
+    script = model.invoke(
+        [
+            SystemMessage(content=get_prompt_template("podcast_script_writer")),
+            HumanMessage(content=state["input"]),
+        ],
+    )
+    logging.info(script)
+    return {"script": script, "audio_chunks": []}

src/podcast/graph/state.py

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+from typing import Optional
+
+from langgraph.graph import MessagesState
+
+from ..types import Script
+
+
+class PodcastState(MessagesState):
+    """State for the podcast generation."""
+
+    # Input
+    input: str = ""
+
+    # Output
+    output: Optional[bytes] = None
+
+    # Assets
+    script: Optional[Script] = None
+    audio_chunks: list[bytes] = []

src/podcast/graph/tts_node.py

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+import base64
+import logging
+import os
+
+from src.podcast.graph.state import PodcastState
+from src.tools.tts import VolcengineTTS
+
+logger = logging.getLogger(__name__)
+
+
+def tts_node(state: PodcastState):
+    logger.info("Generating audio chunks for podcast...")
+    tts_client = _create_tts_client()
+    for line in state["script"].lines:
+        tts_client.voice_type = (
+            "BV002_streaming" if line.speaker == "male" else "BV001_streaming"
+        )
+        result = tts_client.text_to_speech(line.text, speed_ratio=1.1)
+        if result["success"]:
+            audio_data = result["audio_data"]
+            audio_chunk = base64.b64decode(audio_data)
+            state["audio_chunks"].append(audio_chunk)
+        else:
+            logger.error(result["error"])
+    return {
+        "audio_chunks": state["audio_chunks"],
+    }
+
+
+def _create_tts_client():
+    app_id = os.getenv("VOLCENGINE_TTS_APPID", "")
+    if not app_id:
+        raise Exception("VOLCENGINE_TTS_APPID is not set")
+    access_token = os.getenv("VOLCENGINE_TTS_ACCESS_TOKEN", "")
+    if not access_token:
+        raise Exception("VOLCENGINE_TTS_ACCESS_TOKEN is not set")
+    cluster = os.getenv("VOLCENGINE_TTS_CLUSTER", "volcano_tts")
+    voice_type = "BV001_streaming"
+    return VolcengineTTS(
+        appid=app_id,
+        access_token=access_token,
+        cluster=cluster,
+        voice_type=voice_type,
+    )