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Init ColBERTv2 managed index #9656

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Dec 21, 2023
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Init ColBERTv2 managed index #9656

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Init ColBERTv2 managed index
hatianzhang Dec 21, 2023
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hatianzhang Dec 21, 2023
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hatianzhang Dec 21, 2023
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460 changes: 459 additions & 1 deletion docs/examples/managed/manage_retrieval_benchmark.ipynb
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101 changes: 0 additions & 101 deletions examples/paul_graham_essay/ColbertIndex.ipynb
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2 changes: 2 additions & 0 deletions llama_index/indices/__init__.py
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Original file line number Diff line number Diff line change
Expand Up @@ -31,6 +31,7 @@
load_index_from_storage,
load_indices_from_storage,
)
from llama_index.indices.managed.colbert_index import ColbertIndex
from llama_index.indices.managed.vectara import VectaraIndex
from llama_index.indices.managed.zilliz import ZillizCloudPipelineIndex
from llama_index.indices.multi_modal import MultiModalVectorStoreIndex
Expand All @@ -52,6 +53,7 @@
"SummaryIndex",
"TreeIndex",
"VectaraIndex",
"ColbertIndex",
"ZillizCloudPipelineIndex",
"DocumentSummaryIndex",
"KnowledgeGraphIndex",
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0 experimental/colbert_index/__init__.py → ...indices/managed/colbert_index/__init__.py
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12 changes: 6 additions & 6 deletions experimental/colbert_index/base.py → ...dex/indices/managed/colbert_index/base.py
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I wonder if this would make more sense as just a retriever? Similar to BM25Retriever ? Thoughts?

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colbertv2 indeed build index. it has its own indexer, retriever

Original file line number Diff line number Diff line change
Expand Up @@ -47,6 +47,7 @@ def __init__(
service_context: Optional[ServiceContext] = None,
storage_context: Optional[StorageContext] = None,
model_name: str = "colbert-ir/colbertv2.0",
index_name: str = "",
show_progress: bool = False,
nbits: int = 2,
gpus: int = 0,
Expand All @@ -58,6 +59,7 @@ def __init__(
) -> None:
self.model_name = model_name
self.index_path = "storage/colbert_index"
self.index_name = index_name
self.nbits = nbits
self.gpus = gpus
self.ranks = ranks
Expand All @@ -75,6 +77,7 @@ def __init__(
super().__init__(
nodes=nodes,
index_struct=index_struct,
index_name=index_name,
service_context=service_context,
storage_context=storage_context,
show_progress=show_progress,
Expand All @@ -100,7 +103,7 @@ def _build_index_from_nodes(self, nodes: Sequence[BaseNode]) -> IndexDict:
"""Generate a PLAID index from the ColBERT checkpoint via its hugging face
model_name.
"""
from colbert import Indexer, IndexUpdater, Searcher
from colbert import Indexer, Searcher
from colbert.infra import ColBERTConfig, Run, RunConfig

index_struct = IndexDict()
Expand All @@ -121,12 +124,9 @@ def _build_index_from_nodes(self, nodes: Sequence[BaseNode]) -> IndexDict:
kmeans_niters=self.kmeans_niters,
)
indexer = Indexer(checkpoint=self.model_name, config=config)
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@logan-markewich their indexer

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Yea I suppose. It just feels very similar to BM25 since you can't add or delete data from it? It doesn't fit our definition of index very well

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oh they do have CRUD for index data: https://github.com/stanford-futuredata/ColBERT/blob/117098348e5196ede1c8e396c1c14f24d9a8754e/colbert/index_updater.py

the previous pr does not support it. I will add them for another pr

this pr is mostly for testing retrieval performance

indexer.index("", collection=docs_list, overwrite=True)
indexer.index(name=self.index_name, collection=docs_list, overwrite=True)
self.store = Searcher(
index="", collection=docs_list, checkpoint=self.model_name
)
self.updater = IndexUpdater(
config=config, searcher=self.store, checkpoint=self.model_name
index=self.index_name, collection=docs_list, checkpoint=self.model_name
)
return index_struct

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0 experimental/colbert_index/retriever.py → ...ndices/managed/colbert_index/retriever.py
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