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- Implement BaseComponent with async lifecycle and context management - Add ApplicationContext for managing component initialization and registry - Create Application class for orchestrating job execution and lifecycle - Add AS LLM components with OpenAI chat model wrapper - Implement AS LLM formatter components with OpenAI formatter - Add client implementations including base, HTTP and ReMe clients - Create embedding model base class with caching and batching support - Implement file store base class with vector and full-text search - Add file watcher components for monitoring file system changes - Create job components for executing workflows - Implement service components for exposing jobs via different protocols - Add configuration schema with ApplicationConfig and ComponentConfig - Include utility modules for case conversion, chunking, logging and similarity - Register component types and create component registry system
21 lines
479 B
Python
21 lines
479 B
Python
"""Schema"""
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from .application_config import ApplicationConfig, ComponentConfig, JobConfig
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from .base_node import BaseNode
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from .file_chunk import FileChunk
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from .file_metadata import FileMetadata
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from .request import Request
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from .response import Response
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from .stream_chunk import StreamChunk
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__all__ = [
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"ApplicationConfig",
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"ComponentConfig",
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"JobConfig",
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"BaseNode",
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"FileChunk",
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"FileMetadata",
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"Request",
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"Response",
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"StreamChunk",
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]
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