llama-index packs zephyr_query_engine integration
Project description
Zephyr Query Engine Pack
Create a query engine using completely local and private models -- HuggingFaceH4/zephyr-7b-beta
for the LLM and BAAI/bge-base-en-v1.5
for embeddings.
CLI Usage
You can download llamapacks directly using llamaindex-cli
, which comes installed with the llama-index
python package:
llamaindex-cli download-llamapack ZephyrQueryEnginePack --download-dir ./zephyr_pack
You can then inspect the files at ./zephyr_pack
and use them as a template for your own project.
Code Usage
You can download the pack to a the ./zephyr_pack
directory:
from llama_index.core.llama_pack import download_llama_pack
# download and install dependencies
ZephyrQueryEnginePack = download_llama_pack(
"ZephyrQueryEnginePack", "./zephyr_pack"
)
# You can use any llama-hub loader to get documents!
zephyr_pack = ZephyrQueryEnginePack(documents)
From here, you can use the pack, or inspect and modify the pack in ./zephyr_pack
.
The run()
function is a light wrapper around index.as_query_engine().query()
.
response = zephyr_pack.run(
"What did the author do growing up?", similarity_top_k=2
)
You can also use modules individually.
# Use the llm
llm = zephyr_pack.llm
response = llm.complete("What is HuggingFace?")
# Use the index directly
index = zephyr_pack.index
query_engine = index.as_query_engine()
retriever = index.as_retriever()
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