Gigachat

In [ ]:

%pip install llama-index-embeddings-gigachat

%pip install llama-index-embeddings-gigachat

In [ ]:

!pip install llama-index

!pip install llama-index

In [ ]:

from llama_index.embeddings.gigachat import GigaChatEmbedding

gigachat_embedding = GigaChatEmbedding(
    auth_data="your-auth-data",
    scope="your-scope",  # Set scope 'GIGACHAT_API_PERS' for personal use or 'GIGACHAT_API_CORP' for corporate use.
)

queries_embedding = gigachat_embedding._get_query_embeddings(
    ["This is a passage!", "This is another passage"]
)
print(queries_embedding)

text_embedding = gigachat_embedding._get_text_embedding("Where is blue?")
print(text_embedding)

from llama_index.embeddings.gigachat import GigaChatEmbedding gigachat_embedding = GigaChatEmbedding( auth_data="your-auth-data", scope="your-scope", # Set scope 'GIGACHAT_API_PERS' for personal use or 'GIGACHAT_API_CORP' for corporate use. ) queries_embedding = gigachat_embedding._get_query_embeddings( ["This is a passage!", "This is another passage"] ) print(queries_embedding) text_embedding = gigachat_embedding._get_text_embedding("Where is blue?") print(text_embedding)