OSS (v1-alpha)
LangChain and LangGraph
pip install -U langchain-community
import requests from langchain_community.embeddings import JinaEmbeddings from numpy import dot from numpy.linalg import norm from PIL import Image
text_embeddings = JinaEmbeddings( jina_api_key="jina_*", model_name="jina-embeddings-v2-base-en" )
text = "This is a test document."
query_result = text_embeddings.embed_query(text)
print(query_result)
doc_result = text_embeddings.embed_documents([text])
print(doc_result)
multimodal_embeddings = JinaEmbeddings(jina_api_key="jina_*", model_name="jina-clip-v1")
image = "https://avatars.githubusercontent.com/u/126733545?v=4" description = "Logo of a parrot and a chain on green background" im = Image.open(requests.get(image, stream=True).raw) print("Image:") display(im)
image_result = multimodal_embeddings.embed_images([image])
print(image_result)
description_result = multimodal_embeddings.embed_documents([description])
print(description_result)
cosine_similarity = dot(image_result[0], description_result[0]) / ( norm(image_result[0]) * norm(description_result[0]) )
print(cosine_similarity)
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