a bgU@sZddlmZmZmZddlmZddlmZmZm Z m Z ddl m Z GdddeeZ dS))AnyListOptional) Embeddings) BaseModel ConfigDictFieldmodel_validator)Selfc@seZdZUdZdZeed<eddZe ed<eddd Z e ed<ed d d Z e ed <ed d d Z e ed <ed dd Zeed<ed dd Zeed<ed dd Zeed<ed dd Zeed<eddd Zee ed<eddd Zee ed<eddd Zee ed<eddd Zeed<eddd Zee ed<edddZeddedddZee eeed d!d"Z e eed#d$d%Z!dS)&LlamaCppEmbeddingsallama.cpp embedding models. To use, you should have the llama-cpp-python library installed, and provide the path to the Llama model as a named parameter to the constructor. Check out: https://github.com/abetlen/llama-cpp-python Example: .. code-block:: python from langchain_community.embeddings import LlamaCppEmbeddings llama = LlamaCppEmbeddings(model_path="/path/to/model.bin") Nclient)default model_pathin_ctx)aliasn_partsseedFf16_kv logits_all vocab_only use_mlock n_threadsn_batch n_gpu_layersTverbosedeviceZforbid)extraZprotected_namespacesafter)mode)returnc sj}gd}fdd|D}jdur4j|d<jsz&ddlm}||fdd i|_WnPtyztd Yn8ty}z td |d |WYd}~n d}~00S) z4Validate that llama-cpp-python library is installed.) rrrrrrrrrrrcsi|]}|t|qSr)getattr).0kselfru/var/www/html/cobodadashboardai.evdpl.com/venv/lib/python3.9/site-packages/langchain_community/embeddings/llamacpp.py Vz;LlamaCppEmbeddings.validate_environment..Nrr)Llama embeddingTzCould not import llama-cpp-python library. Please install the llama-cpp-python library to use this embedding model: pip install llama-cpp-pythonz&Could not load Llama model from path: z. Received error )rrr Z llama_cppr+ ImportError Exception ValueError)r'rZmodel_param_namesZ model_paramsr+err&r(validate_environmentEs(     z'LlamaCppEmbeddings.validate_environment)textsr"c Cs|j|}g}|dD]}zRt|ddtrT|dD]}|ttt|q8n|ttt|dWqttfy|ttt|dYq0q|S)zEmbed a list of documents using the Llama model. Args: texts: The list of texts to embed. Returns: List of embeddings, one for each text. datar,r) r Zcreate_embedding isinstancelistappendmapfloat IndexError TypeError)r'r2Z embeddingsZfinal_embeddingsr0r3rrr(embed_documentsns    z"LlamaCppEmbeddings.embed_documents)textr"cCs:|j|}t|ts$ttt|Sttt|dSdS)zEmbed a query using the Llama model. Args: text: The text to embed. Returns: Embeddings for the text. rN)r Zembedr4r5r7r8)r'r<r,rrr( embed_querys  zLlamaCppEmbeddings.embed_query)"__name__ __module__ __qualname____doc__r r__annotations__rrstrrintrrrboolrrrrrrrrrrZ model_configr r r1rr8r;r=rrrr(r s.  (r N)typingrrrZlangchain_core.embeddingsrZpydanticrrrr Ztyping_extensionsr r rrrr(s