mirror of
https://github.com/eigent-ai/eigent.git
synced 2026-05-03 06:00:17 +00:00
36 lines
1.4 KiB
Python
36 lines
1.4 KiB
Python
import os
|
|
from camel.models import BaseAudioModel, BaseModelBackend
|
|
from camel.toolkits import AudioAnalysisToolkit as BaseAudioAnalysisToolkit
|
|
|
|
from app.component.environment import env
|
|
from app.service.task import Agents
|
|
from app.utils.listen.toolkit_listen import listen_toolkit
|
|
from app.utils.toolkit.abstract_toolkit import AbstractToolkit
|
|
|
|
|
|
class AudioAnalysisToolkit(BaseAudioAnalysisToolkit, AbstractToolkit):
|
|
agent_name: str = Agents.multi_modal_agent
|
|
|
|
def __init__(
|
|
self,
|
|
api_task_id: str,
|
|
cache_dir: str | None = None,
|
|
transcribe_model: BaseAudioModel | None = None,
|
|
audio_reasoning_model: BaseModelBackend | None = None,
|
|
timeout: float | None = None,
|
|
):
|
|
if cache_dir is None:
|
|
cache_dir = env("file_save_path", os.path.expanduser("~/.eigent/tmp/"))
|
|
super().__init__(cache_dir, transcribe_model, audio_reasoning_model, timeout)
|
|
self.api_task_id = api_task_id
|
|
|
|
@listen_toolkit(
|
|
BaseAudioAnalysisToolkit.audio2text,
|
|
lambda _, audio_path, question: f"transcribe audio from {audio_path} and ask question: {question}",
|
|
)
|
|
def ask_question_about_audio(self, audio_path: str, question: str) -> str:
|
|
return super().ask_question_about_audio(audio_path, question)
|
|
|
|
@listen_toolkit(BaseAudioAnalysisToolkit.audio2text)
|
|
def audio2text(self, audio_path: str) -> str:
|
|
return super().audio2text(audio_path)
|