55 lines
1.1 KiB
Python
55 lines
1.1 KiB
Python
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"""
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llm-semantic-cache: Semantic caching for LLM API calls.
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Cut LLM costs 30% with one decorator.
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"""
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__version__ = "0.1.0"
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__author__ = "Karthick Raja M"
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__license__ = "MIT"
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# Core exports
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from semantic_llm_cache.config import CacheConfig
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from semantic_llm_cache.core import (
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CacheContext,
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CachedLLM,
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cache,
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get_default_backend,
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set_default_backend,
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)
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from semantic_llm_cache.exceptions import (
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CacheBackendError,
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CacheNotFoundError,
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CacheSerializationError,
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PromptCacheError,
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)
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from semantic_llm_cache.stats import CacheStats, clear_cache, get_stats, invalidate
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from semantic_llm_cache.storage import StorageBackend
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__all__ = [
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# Version info
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"__version__",
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"__author__",
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"__license__",
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# Core API
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"cache",
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"CacheContext",
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"CachedLLM",
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"get_default_backend",
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"set_default_backend",
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# Storage
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"StorageBackend",
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# Statistics
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"CacheStats",
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"get_stats",
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"clear_cache",
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"invalidate",
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# Configuration
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"CacheConfig",
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# Exceptions
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"PromptCacheError",
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"CacheBackendError",
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"CacheSerializationError",
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"CacheNotFoundError",
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]
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