47 lines
1.8 KiB
Python
47 lines
1.8 KiB
Python
from typing import Optional
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from dotenv import load_dotenv
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from embedchain.helper.json_serializable import register_deserializable
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from embedchain.vectordb.base import BaseVectorDB
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from .base_app_config import BaseAppConfig
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load_dotenv()
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@register_deserializable
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class CustomAppConfig(BaseAppConfig):
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"""
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Config to initialize an embedchain custom `App` instance, with extra config options.
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"""
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def __init__(
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self,
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log_level: str = "WARNING",
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db: Optional[BaseVectorDB] = None,
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id: Optional[str] = None,
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collect_metrics: Optional[bool] = None,
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collection_name: Optional[str] = None,
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):
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"""
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Initializes a configuration class instance for an Custom App.
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Most of the configuration is done in the `CustomApp` class itself.
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:param log_level: Debug level ['DEBUG', 'INFO', 'WARNING', 'ERROR', 'CRITICAL'], defaults to "WARNING"
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:type log_level: str, optional
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:param db: A database class. It is recommended to set this directly in the `CustomApp` class, not this config,
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defaults to None
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:type db: Optional[BaseVectorDB], optional
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:param id: ID of the app. Document metadata will have this id., defaults to None
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:type id: Optional[str], optional
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:param collect_metrics: Send anonymous telemetry to improve embedchain, defaults to True
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:type collect_metrics: Optional[bool], optional
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:param collection_name: Default collection name. It's recommended to use app.db.set_collection_name() instead,
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defaults to None
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:type collection_name: Optional[str], optional
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"""
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super().__init__(
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log_level=log_level, db=db, id=id, collect_metrics=collect_metrics, collection_name=collection_name
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)
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