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geekyrakshit
commited on
Commit
·
abd20d0
1
Parent(s):
9a6c015
update: colpali index syncs with wandb artifact
Browse files
.gitignore
CHANGED
@@ -7,4 +7,6 @@ cursor_prompt.txt
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test.py
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**.pdf
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images/
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wandb/
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test.py
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**.pdf
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images/
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wandb/
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.byaldi/
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artifacts/
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medrag_multi_modal/document_loader/load_image.py
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@@ -3,11 +3,11 @@ import os
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from typing import Optional
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import rich
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import weave
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from pdf2image.pdf2image import convert_from_path
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from PIL import Image
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import wandb
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from medrag_multi_modal.document_loader.load_text import TextLoader
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from typing import Optional
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import rich
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import wandb
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import weave
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from pdf2image.pdf2image import convert_from_path
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from PIL import Image
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from medrag_multi_modal.document_loader.load_text import TextLoader
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medrag_multi_modal/retrieval/__init__.py
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@@ -1,3 +1,3 @@
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from .multi_modal_retrieval import MultiModalRetriever
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__all__ = ["MultiModalRetriever"]
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from .multi_modal_retrieval import MultiModalRetriever
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__all__ = ["MultiModalRetriever"]
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medrag_multi_modal/retrieval/multi_modal_retrieval.py
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@@ -1,22 +1,39 @@
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import weave
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from byaldi import RAGMultiModalModel
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import wandb
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class MultiModalRetriever(weave.Model):
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model_name: str
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_docs_retrieval_model: RAGMultiModalModel
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def __init__(self, model_name: str = "vidore/colpali-v1.2"):
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super().__init__(model_name=model_name)
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self._docs_retrieval_model = RAGMultiModalModel.from_pretrained(self.model_name)
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def index(self, data_artifact_name: str, weave_dataset_name: str, index_name: str):
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if wandb.run:
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artifact = wandb.use_artifact(data_artifact_name, type=
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artifact_dir = artifact.download()
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else:
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api = wandb.Api()
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artifact = api.artifact(data_artifact_name)
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artifact_dir = artifact.download()
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self._docs_retrieval_model.index(
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import os
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import wandb
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import weave
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from byaldi import RAGMultiModalModel
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class MultiModalRetriever(weave.Model):
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model_name: str
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_docs_retrieval_model: RAGMultiModalModel
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def __init__(self, model_name: str = "vidore/colpali-v1.2"):
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super().__init__(model_name=model_name)
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self._docs_retrieval_model = RAGMultiModalModel.from_pretrained(self.model_name)
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def index(self, data_artifact_name: str, weave_dataset_name: str, index_name: str):
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if wandb.run:
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artifact = wandb.use_artifact(data_artifact_name, type="dataset")
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artifact_dir = artifact.download()
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else:
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api = wandb.Api()
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artifact = api.artifact(data_artifact_name)
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artifact_dir = artifact.download()
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self._docs_retrieval_model.index(
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input_path=artifact_dir,
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index_name=index_name,
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store_collection_with_index=False,
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overwrite=True,
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)
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if wandb.run:
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artifact = wandb.Artifact(
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name=index_name,
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type="colpali-index",
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metadata={"weave_dataset_name": weave_dataset_name},
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)
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artifact.add_dir(
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local_path=os.path.join(".byaldi", index_name), name="index"
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)
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artifact.save()
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