U h@sNddlmZmZmZmZddlmZddlmZm Z m Z GdddeeZ dS))AnyDictListOptional) Embeddings) BaseModelFieldroot_validatorc@s|eZdZUdZeed<eed<edddZe ed<edddZ e ed<edd dZ e ed <ed d dZ e ed <ed d dZe ed <ed d dZe ed <ed ddZe ed<edddZee ed<edddZee ed<edddZee ed<edddZe ed<edddZeeed<GdddZed ddeedddZeeeeedddZeeedd d!ZdS)"LlamaCppEmbeddingsallama.cpp embedding models. To use, you should have the llama-cpp-python library installed, and provide the path to the Llama model as a named parameter to the constructor. Check out: https://github.com/abetlen/llama-cpp-python Example: .. code-block:: python from langchain_community.embeddings import LlamaCppEmbeddings llama = LlamaCppEmbeddings(model_path="/path/to/model.bin") client model_pathin_ctx)aliasn_partsseedFf16_kv logits_all vocab_only use_mlockN n_threadsn_batch n_gpu_layersTverbosedevicec@seZdZdZdS)zLlamaCppEmbeddings.ConfigZforbidN)__name__ __module__ __qualname__extrarrK/tmp/pip-unpacked-wheel-9gdii04g/langchain_community/embeddings/llamacpp.pyConfig?sr!)preZskip_on_failure)valuesreturnc sd}dddddddd d d d g }fd d|D}ddk rLd|d<z(ddlm}||fddi|d<WnPtk rtdYn6tk r}ztd|d|W5d}~XYnXS)z4Validate that llama-cpp-python library is installed.r r rrrrrrrrrrcsi|]}||qSrr).0kr#rr Ssz;LlamaCppEmbeddings.validate_environment..rNr)Llama embeddingTr zCould not import llama-cpp-python library. Please install the llama-cpp-python library to use this embedding model: pip install llama-cpp-pythonz&Could not load Llama model from path: z. Received error )Z llama_cppr) ImportError Exception ValueError)clsr#r Zmodel_param_namesZ model_paramsr)err'r validate_environmentBs8    z'LlamaCppEmbeddings.validate_environment)textsr$cCs|j|}dd|dDS)zEmbed a list of documents using the Llama model. Args: texts: The list of texts to embed. Returns: List of embeddings, one for each text. cSsg|]}ttt|dqS)r*)listmapfloat)r%r/rrr tsz6LlamaCppEmbeddings.embed_documents..data)r Zcreate_embedding)selfr1Z embeddingsrrr embed_documentsjs z"LlamaCppEmbeddings.embed_documents)textr$cCs|j|}ttt|S)zEmbed a query using the Llama model. Args: text: The text to embed. Returns: Embeddings for the text. )r embedr2r3r4)r7r9r*rrr embed_queryvs zLlamaCppEmbeddings.embed_query)rrr__doc__r__annotations__strrr intrrrboolrrrrrrrrrr!r rr0rr4r8r;rrrr r s(   ' r N) typingrrrrZlangchain_core.embeddingsrZlangchain_core.pydantic_v1rrr r rrrr s