63 lines
2.1 KiB
Python
63 lines
2.1 KiB
Python
from typing import Optional
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from chromadb.utils import embedding_functions
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from embedchain.helper_classes.json_serializable import register_deserializable
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from .BaseAppConfig import BaseAppConfig
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@register_deserializable
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class OpenSourceAppConfig(BaseAppConfig):
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"""
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Config to initialize an embedchain custom `OpenSourceApp` 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=None,
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host=None,
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port=None,
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id=None,
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collection_name=None,
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collect_metrics: Optional[bool] = None,
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model=None,
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):
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"""
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:param log_level: Optional. (String) Debug level
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['DEBUG', 'INFO', 'WARNING', 'ERROR', 'CRITICAL'].
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:param id: Optional. ID of the app. Document metadata will have this id.
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:param collection_name: Optional. Collection name for the database.
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:param host: Optional. Hostname for the database server.
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:param port: Optional. Port for the database server.
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:param collect_metrics: Defaults to True. Send anonymous telemetry to improve embedchain.
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:param model: Optional. GPT4ALL uses the model to instantiate the class.
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So unlike `App`, it has to be provided before querying.
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"""
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self.model = model or "orca-mini-3b.ggmlv3.q4_0.bin"
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super().__init__(
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log_level=log_level,
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embedding_fn=OpenSourceAppConfig.default_embedding_function(),
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host=host,
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port=port,
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id=id,
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collection_name=collection_name,
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collect_metrics=collect_metrics,
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)
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@staticmethod
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def default_embedding_function():
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"""
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Sets embedding function to default (`all-MiniLM-L6-v2`).
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:returns: The default embedding function
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"""
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try:
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return embedding_functions.SentenceTransformerEmbeddingFunction(model_name="all-MiniLM-L6-v2")
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except ValueError as e:
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print(e)
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raise ModuleNotFoundError(
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"The open source app requires extra dependencies. Install with `pip install embedchain[opensource]`"
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) from None
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