LLAMA 2¶

Llama 2 is a open-access large language models released by Meta. The Llama 2 ranging in scale from 7B to 70B parameters (7B, 13B, 70B). We can check the model details in Llama 2

Download the model:

Llama 2 model download here

Import Semantic AI:

from semantic_ai.llm import Llama

llama_llm = await Llama(model_name_or_path="model_name_or_path").llm_model()

Vector Database:

Now we are going to use Elastic Search vector database.

from semantic_ai.indexer import ElasticsearchIndexer
from semantic_ai.embeddings.huggingface import HFEmbeddings

embeddings = await HFEmbeddings().embed()
elastic_search = await ElasticsearchIndexer(
        url="http://localhost:9200",
        index_name="test_index",
        embedding=embeddings
).create()

Search:

from semantic_ai.search.semantic_search import Search
search_obj = Search(
            model=llama_llm,
            load_vector_db=elastic_search
)
query = "What is an AI"
search = await search_obj.generate(query)

We can change the top_k value and prompt using top_k and ‘prompt’ params respectively

search_obj = Search(
            model=llama_llm,
            load_vector_db=elastic_search,
            top_k=5,
            prompt=prompt
)
query = "What is an AI"
search = await search_obj.generate(query)