tegwick
267368eb60
Add OpenAI-compatible embedding support (works with both OpenAI and OpenRouter), file-based embedding cache with content-digest invalidation, and pure-Python cosine similarity utilities for downstream redundancy detection. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
51 lines
1.6 KiB
Python
51 lines
1.6 KiB
Python
"""
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Factory for creating embedding adapters by provider name.
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"""
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from typing import Optional, Any
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from markitect.llm.embedding_adapter import EmbeddingAdapter
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from markitect.llm.exceptions import LLMConfigurationError
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_EMBEDDING_PROVIDERS = {
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"openai": "markitect.llm.embedding_openai.OpenAICompatibleEmbeddingAdapter",
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"openrouter": "markitect.llm.embedding_openai.OpenAICompatibleEmbeddingAdapter",
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}
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def create_embedding_adapter(
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provider: str = "openai",
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model: Optional[str] = None,
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api_key: Optional[str] = None,
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**kwargs: Any,
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) -> EmbeddingAdapter:
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"""Instantiate an :class:`EmbeddingAdapter` for the given *provider*.
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Args:
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provider: ``"openai"`` or ``"openrouter"``.
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model: Embedding model name (e.g. ``"text-embedding-3-small"``).
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api_key: Explicit API key.
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**kwargs: Extra keyword arguments forwarded to the adapter.
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Returns:
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A ready-to-use :class:`EmbeddingAdapter` instance.
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Raises:
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LLMConfigurationError: If *provider* is not recognised.
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"""
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if provider not in _EMBEDDING_PROVIDERS:
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known = ", ".join(sorted(_EMBEDDING_PROVIDERS))
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raise LLMConfigurationError(
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f"Unknown embedding provider {provider!r}. Choose from: {known}",
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context={"provider": provider},
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)
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# Lazy import
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fqn = _EMBEDDING_PROVIDERS[provider]
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module_path, class_name = fqn.rsplit(".", 1)
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import importlib
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mod = importlib.import_module(module_path)
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cls = getattr(mod, class_name)
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return cls(model=model, api_key=api_key, provider=provider, **kwargs)
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