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()