llama-index-packs-fusion-retriever 0.4.0

llama-index packs fusion_retriever integration

Fusion Retriever Packs

Hybrid Fusion Pack

This LlamaPack provides an example of our hybrid fusion retriever method.

This specific template fuses results from our vector retriever and bm25 retriever; of course, you can provide any template you want.

Check out the notebook here.

CLI Usage

You can download llamapacks directly using llamaindex-cli, which comes installed with the llama-index python package:

llamaindex-cli download-llamapack HybridFusionRetrieverPack --download-dir ./hybrid_fusion_pack

You can then inspect the files at ./hybrid_fusion_pack and use them as a template for your own project.

Code Usage

You can download the pack to a the ./hybrid_fusion_pack directory:

from llama_index.core.llama_pack import download_llama_pack

# download and install dependencies
HybridFusionRetrieverPack = download_llama_pack(
    "HybridFusionRetrieverPack", "./hybrid_fusion_pack"
)

From here, you can use the pack, or inspect and modify the pack in ./hybrid_fusion_pack.

Then, you can set up the pack like so:

# create the pack
hybrid_fusion_pack = HybridFusionRetrieverPack(
    nodes, chunk_size=256, vector_similarity_top_k=2, bm25_similarity_top_k=2
)

The run() function is a light wrapper around query_engine.query().

response = hybrid_fusion_pack.run("Tell me about a Music celebritiy.")

You can also use modules individually.

# use the fusion retriever
nodes = hybrid_fusion_pack.fusion_retriever.retrieve("query_str")

# use the vector retriever
nodes = hybrid_fusion_pack.vector_retriever.retrieve("query_str")
# use the bm25 retriever
nodes = hybrid_fusion_pack.bm25_retriever.retrieve("query_str")

# get the query engine
query_engine = hybrid_fusion_pack.query_engine

Query Rewriting Retriever Pack

This LlamaPack provides an example of query rewriting through our fusion retriever.

This specific template takes in a single retriever, and generates multiple queries against the retriever, and then fuses the results together.

Check out the notebook here.

CLI Usage

You can download llamapacks directly using llamaindex-cli, which comes installed with the llama-index python package:

llamaindex-cli download-llamapack QueryRewritingRetrieverPack --download-dir ./query_rewriting_pack

You can then inspect the files at ./query_rewriting_pack and use them as a template for your own project.

Code Usage

You can download the pack to a the ./query_rewriting_pack directory:

from llama_index.core.llama_pack import download_llama_pack

# download and install dependencies
QueryRewritingRetrieverPack = download_llama_pack(
    "QueryRewritingRetrieverPack", "./query_rewriting_pack"
)

From here, you can use the pack, or inspect and modify the pack in ./query_rewriting_pack.

Then, you can set up the pack like so:

# create the pack
query_rewriting_pack = QueryRewritingRetrieverPack(
    nodes,
    chunk_size=256,
    vector_similarity_top_k=2,
)

The run() function is a light wrapper around query_engine.query().

response = query_rewriting_pack.run("Tell me a bout a Music celebritiy.")

You can also use modules individually.

# use the fusion retriever
nodes = query_rewriting_pack.fusion_retriever.retrieve("query_str")

# use the vector retriever
nodes = query_rewriting_pack.vector_retriever.retrieve("query_str")

# get the query engine
query_engine = query_rewriting_pack.query_engine