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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
28 lines
533 B
Python
28 lines
533 B
Python
"""Chunk enumeration module.
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Defines the types of data chunks used in streaming responses.
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"""
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from enum import Enum
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class ChunkEnum(str, Enum):
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"""Enumeration of possible chunk categories for stream processing.
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This enum defines the various types of chunks that can be transmitted
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during a streaming response from an LLM or agent system.
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"""
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THINK = "think"
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CONTENT = "content"
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TOOL_CALL = "tool_call"
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TOOL_RESULT = "tool_result"
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USAGE = "usage"
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ERROR = "error"
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DONE = "done"
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