forked from phoenix-oss/llama-stack-mirror
# What does this PR do? - Configured ruff linter to automatically fix import sorting issues. - Set --exit-non-zero-on-fix to ensure non-zero exit code when fixes are applied. - Enabled the 'I' selection to focus on import-related linting rules. - Ran the linter, and formatted all codebase imports accordingly. - Removed the black dep from the "dev" group since we use ruff Signed-off-by: Sébastien Han <seb@redhat.com> [//]: # (If resolving an issue, uncomment and update the line below) [//]: # (Closes #[issue-number]) ## Test Plan [Describe the tests you ran to verify your changes with result summaries. *Provide clear instructions so the plan can be easily re-executed.*] [//]: # (## Documentation) [//]: # (- [ ] Added a Changelog entry if the change is significant) Signed-off-by: Sébastien Han <seb@redhat.com>
44 lines
1.2 KiB
Python
44 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.apis.common.content_types import URL
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from llama_stack.providers.utils.memory.vector_store import parse_data_url
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def get_dataframe_from_url(url: URL):
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df = None
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if url.uri.endswith(".csv"):
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df = pandas.read_csv(url.uri)
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elif url.uri.endswith(".xlsx"):
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df = pandas.read_excel(url.uri)
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elif url.uri.startswith("data:"):
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parts = parse_data_url(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: {url}")
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return df
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