Ng6 h d dl mZmZmZmZ d dlmZ d dlmZm Z m
Z
dZ dZ dZ
G d dee Zd S )
)AnyDictListOptional)
Embeddings) BaseModel
ConfigDictFieldzBAAI/bge-small-en-v1.5z9Represent this question for searching relevant passages: u9 为这个句子生成表示以用于检索相关文章：c V e Zd ZU dZdZeed< eZe ed< dZ
e e ed< e e
Zee ef ed< e e
Zee ef ed< eZe ed < d
Ze ed < d ef fd
Z edd Zdee deee fdZde dee fdZ xZS )IpexLLMBgeEmbeddingsa Wrapper around the BGE embedding model
with IPEX-LLM optimizations on Intel CPUs and GPUs.
To use, you should have the ``ipex-llm``
and ``sentence_transformers`` package installed. Refer to
`here `_
for installation on Intel CPU.
Example on Intel CPU:
.. code-block:: python
from langchain_community.embeddings import IpexLLMBgeEmbeddings
embedding_model = IpexLLMBgeEmbeddings(
model_name="BAAI/bge-large-en-v1.5",
model_kwargs={},
encode_kwargs={"normalize_embeddings": True},
)
Refer to
`here `_
for installation on Intel GPU.
Example on Intel GPU:
.. code-block:: python
from langchain_community.embeddings import IpexLLMBgeEmbeddings
embedding_model = IpexLLMBgeEmbeddings(
model_name="BAAI/bge-large-en-v1.5",
model_kwargs={"device": "xpu"},
encode_kwargs={"normalize_embeddings": True},
)
Nclient
model_name cache_folder)default_factory model_kwargs
encode_kwargsquery_instruction embed_instructionkwargsc z t j di | ddl}ddlm}m} n+# t $ r }d}t
d| d| d |d}~ww xY wd| j vr
d | j d< | j d d
vr t d | j d d |j | j
fd
| j i| j | _ || j | _ || j | _ | j d dk r1| j
d | _ d| j
v rt | _ dS dS )z$Initialize the sentence_transformer.r N)_optimize_post
_optimize_prezChttps://python.langchain.com/v0.1/docs/integrations/text_embedding/zDCould not import ipex_llm or sentence_transformers. Please refer to zD/ipex_llm/ for install required packages on Intel CPU. And refer to z;/ipex_llm_gpu/ for install required packages on Intel GPU. devicecpu)r xpuzXIpexLLMBgeEmbeddings currently only supports device to be 'cpu' or 'xpu', but you have: .r r z-zh )super__init__sentence_transformers ipex_llm.transformers.convertr r ImportErrorr
ValueErrorSentenceTransformerr r r
halfto DEFAULT_QUERY_BGE_INSTRUCTION_ZHr )selfr r! r r excbase_url __class__s c/var/www/html/ai-engine/env/lib/python3.11/site-packages/langchain_community/embeddings/ipex_llm.pyr z IpexLLMBgeEmbeddings.__init__C s ""6""" ( ( ( ( S S S S S S S S S
U
?#+? ? !)? ? ?
4, , ,*/D h ' X &n < < P151B81LP P P
@+? O
*.*;
?C?P
$mDK00 $nT[11 X &% / / +**,,//66DK DO # #%ED " " " $ #s )
AA Aforbidr )extraprotected_namespacestextsreturnc x fd|D } j j |fi j }| S )zCompute doc embeddings using a HuggingFace transformer model.
Args:
texts: The list of texts to embed.
Returns:
List of embeddings, one for each text.
c L g | ] }j | d d z !S )
)r replace).0tr) s r-
z8IpexLLMBgeEmbeddings.embed_documents..x s/ NNN1'!))D#*>*>>NNN )r
encoder tolist)r) r1
embeddingss ` r- embed_documentsz$IpexLLMBgeEmbeddings.embed_documentso sP ONNNNNN'T['DD1CDD
"""r; textc | dd } | j j | j |z fi | j }| S )zCompute query embeddings using a HuggingFace transformer model.
Args:
text: The text to embed.
Returns:
Embeddings for the text.
r5 r6 )r7 r
r< r r r= )r) r@ embeddings r- embed_queryz IpexLLMBgeEmbeddings.embed_query| s\ ||D#&&&DK& "T )
-1-?
!!!r; ) __name__
__module__ __qualname____doc__r
r __annotations__DEFAULT_BGE_MODELr strr r r
dictr r r DEFAULT_QUERY_BGE_INSTRUCTION_ENr r r r model_configr floatr? rC
__classcell__)r, s @r- r r s{ ! !F FC'J''' "&L(3-&&&K#(5#>#>#>L$sCx.>>>1$)E$$?$?$?M4S>???R =s===1 s 4(F (F (F (F (F (F (FT :H2FFFL #T#Y #4U 3D # # # #
"
"U
"
"
"
"
"
"
"
"r; r N)typingr r r r langchain_core.embeddingsr pydanticr r r
rI rL r( r r r; r- rS s - , , , , , , , , , , , 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 1, ? ! $_ y" y" y" y" y"9j y" y" y" y" y"r;