forked from phoenix-oss/llama-stack-mirror
# What does this PR do? - fix dataset registeration & iterrows > NOTE: the URL endpoint is changed to datasetio due to flaky path routing [//]: # (If resolving an issue, uncomment and update the line below) [//]: # (Closes #[issue-number]) ## Test Plan ``` LLAMA_STACK_CONFIG=fireworks pytest -v tests/integration/datasets/test_datasets.py ``` <img width="854" alt="image" src="https://github.com/user-attachments/assets/0168b352-1c5a-48d1-8e9a-93141d418e54" /> [//]: # (## Documentation)
43 lines
1.2 KiB
Python
43 lines
1.2 KiB
Python
# Copyright (c) Meta Platforms, Inc. and affiliates.
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# All rights reserved.
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#
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# This source code is licensed under the terms described in the LICENSE file in
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# the root directory of this source tree.
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import base64
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import io
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from urllib.parse import unquote
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import pandas
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from llama_stack.providers.utils.memory.vector_store import parse_data_url
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def get_dataframe_from_uri(uri: str):
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df = None
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if uri.endswith(".csv"):
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df = pandas.read_csv(uri)
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elif uri.endswith(".xlsx"):
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df = pandas.read_excel(uri)
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elif uri.startswith("data:"):
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parts = parse_data_url(uri)
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data = parts["data"]
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if parts["is_base64"]:
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data = base64.b64decode(data)
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else:
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data = unquote(data)
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encoding = parts["encoding"] or "utf-8"
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data = data.encode(encoding)
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mime_type = parts["mimetype"]
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mime_category = mime_type.split("/")[0]
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data_bytes = io.BytesIO(data)
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if mime_category == "text":
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df = pandas.read_csv(data_bytes)
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else:
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df = pandas.read_excel(data_bytes)
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else:
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raise ValueError(f"Unsupported file type: {uri}")
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return df
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