543aba7547
reranking.multimodal (vllm provider only) attaches picture bytes to synthetic picture chunks before rerank; VLLMReranker sends them as content-parts documents (base64 data URI + description text) in the same /v1/rerank request as plain text documents.
54 lines
1.9 KiB
Python
54 lines
1.9 KiB
Python
from haiku.rag.config import AppConfig, Config
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from haiku.rag.reranking.base import RerankerBase
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def get_reranker(config: AppConfig = Config) -> RerankerBase | None:
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"""Build the configured reranker, or None if reranking is disabled or its
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optional dependency is not installed."""
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model = config.reranking.model
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if model is None:
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return None
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if config.reranking.multimodal and model.provider != "vllm":
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raise ValueError("reranking.multimodal is only supported on the vllm provider")
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try:
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if model.provider == "cohere":
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from haiku.rag.reranking.cohere import CohereReranker
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return CohereReranker()
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if model.provider == "vllm":
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if not model.base_url:
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raise ValueError("vLLM reranker requires base_url in reranking.model")
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from haiku.rag.reranking.vllm import VLLMReranker
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return VLLMReranker(model.name, model.base_url)
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if model.provider == "zeroentropy":
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from haiku.rag.reranking.zeroentropy import ZeroEntropyReranker
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return ZeroEntropyReranker(model.name or "zerank-1")
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if model.provider == "jina":
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from haiku.rag.reranking.jina import JinaReranker
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return JinaReranker(model.name or "jina-reranker-v3")
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if model.provider == "jina-local":
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from haiku.rag.reranking.jina_local import JinaLocalReranker
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return JinaLocalReranker(model.name or "jinaai/jina-reranker-v3")
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if model.provider == "cross-encoder":
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if not model.name:
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raise ValueError(
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"cross-encoder reranker requires name in reranking.model"
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)
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from haiku.rag.reranking.cross_encoder import CrossEncoderReranker
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return CrossEncoderReranker(model.name)
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except ImportError: # pragma: no cover
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return None
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raise ValueError(f"Unknown reranking provider: {model.provider}")
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