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community[minor]: Add CloudBlobLoader that supports loading data from cloud buckets (#21957)
Thank you for contributing to LangChain!
- [ ] **PR title**: "Add CloudBlobLoader"
- community: Add CloudBlobLoader
- [ ] **PR message**: Add cloud blob loader
- **Description:**
Langchain provides several approaches to read different file formats:
Specific loaders (`CVSLoader`) or blob-compatible loaders
(`FileSystemBlobLoader`). The only implementation proposed for
BlobLoader is `FileSystemBlobLoader`.
Many projects retrieve files from cloud storage. We propose a new
implementation of `BlobLoader` to read files from the three cloud
storage systems. The interface is strictly identical to
`FileSystemBlobLoader`. The only difference is the constructor, which
takes a cloud "url" object such as `s3://my-bucket`, `az://my-bucket`,
or `gs://my-bucket`.
By streamlining the process, this novel implementation eliminates the
requirement to pre-download files from cloud storage to local temporary
files (which are seldom removed).
The code relies on the
[CloudPathLib](https://cloudpathlib.drivendata.org/stable/) library to
interpret cloud URLs. This has been added as an optional dependency.
```Python
loader = CloudBlobLoader("s3://mybucket/id")
for blob in loader.yield_blobs():
print(blob)
```
- [X] **Dependencies:** CloudPathLib
- [X] **Twitter handle:** pprados
- [X] **Add tests and docs**: Add unit test, but it's easy to convert to
integration test, with some files in a cloud storage (see
`test_cloud_blob_loader.py`)
- [X] **Lint and test**: Run `make format`, `make lint` and `make test`
from the root of the package(s) you've modified.
Hello from Paris @hwchase17. Can you review this PR?
---------
Co-authored-by: Eugene Yurtsev <eugene@langchain.dev>
This commit is contained in:
Philippe PRADOS
GitHub
parent
74947ec894
commit
6dd621d636
@ -4,6 +4,9 @@ from typing import TYPE_CHECKING, Any
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from langchain_core.document_loaders import Blob, BlobLoader
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if TYPE_CHECKING:
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from langchain_community.document_loaders.blob_loaders.cloud_blob_loader import (
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CloudBlobLoader,
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)
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from langchain_community.document_loaders.blob_loaders.file_system import (
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FileSystemBlobLoader,
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)
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@ -13,6 +16,9 @@ if TYPE_CHECKING:
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_module_lookup = {
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"CloudBlobLoader": (
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"langchain_community.document_loaders.blob_loaders.cloud_blob_loader"
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),
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"FileSystemBlobLoader": (
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"langchain_community.document_loaders.blob_loaders.file_system"
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),
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@ -32,6 +38,7 @@ def __getattr__(name: str) -> Any:
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__all__ = [
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"BlobLoader",
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"Blob",
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"CloudBlobLoader",
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"FileSystemBlobLoader",
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"YoutubeAudioLoader",
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]
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@ -0,0 +1,289 @@
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"""Use to load blobs from the local file system."""
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import contextlib
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import mimetypes
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import tempfile
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from io import BufferedReader, BytesIO
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from pathlib import Path
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from typing import (
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TYPE_CHECKING,
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Callable,
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Generator,
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Iterable,
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Iterator,
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Optional,
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Sequence,
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TypeVar,
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Union,
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)
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from urllib.parse import urlparse
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if TYPE_CHECKING:
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from cloudpathlib import AnyPath
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from langchain_community.document_loaders.blob_loaders.schema import (
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Blob,
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BlobLoader,
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)
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T = TypeVar("T")
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class _CloudBlob(Blob):
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def as_string(self) -> str:
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"""Read data as a string."""
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from cloudpathlib import AnyPath
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if self.data is None and self.path:
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return AnyPath(self.path).read_text(encoding=self.encoding) # type: ignore
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elif isinstance(self.data, bytes):
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return self.data.decode(self.encoding)
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elif isinstance(self.data, str):
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return self.data
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else:
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raise ValueError(f"Unable to get string for blob {self}")
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def as_bytes(self) -> bytes:
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"""Read data as bytes."""
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from cloudpathlib import AnyPath
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if isinstance(self.data, bytes):
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return self.data
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elif isinstance(self.data, str):
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return self.data.encode(self.encoding)
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elif self.data is None and self.path:
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return AnyPath(self.path).read_bytes() # type: ignore
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else:
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raise ValueError(f"Unable to get bytes for blob {self}")
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@contextlib.contextmanager
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def as_bytes_io(self) -> Generator[Union[BytesIO, BufferedReader], None, None]:
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"""Read data as a byte stream."""
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from cloudpathlib import AnyPath
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if isinstance(self.data, bytes):
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yield BytesIO(self.data)
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elif self.data is None and self.path:
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return AnyPath(self.path).read_bytes() # type: ignore
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else:
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raise NotImplementedError(f"Unable to convert blob {self}")
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def _url_to_filename(url: str) -> str:
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"""
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Convert file:, s3:, az: or gs: url to localfile.
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If the file is not here, download it in a temporary file.
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"""
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from cloudpathlib import AnyPath
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url_parsed = urlparse(url)
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suffix = Path(url_parsed.path).suffix
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if url_parsed.scheme in ["s3", "az", "gs"]:
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with AnyPath(url).open("rb") as f: # type: ignore
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temp_file = tempfile.NamedTemporaryFile(suffix=suffix, delete=False)
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while True:
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buf = f.read()
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if not buf:
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break
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temp_file.write(buf)
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temp_file.close()
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file_path = temp_file.name
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elif url_parsed.scheme in ["file", ""]:
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file_path = url_parsed.path
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else:
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raise ValueError(f"Scheme {url_parsed.scheme} not supported")
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return file_path
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def _make_iterator(
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length_func: Callable[[], int], show_progress: bool = False
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) -> Callable[[Iterable[T]], Iterator[T]]:
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"""Create a function that optionally wraps an iterable in tqdm."""
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if show_progress:
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try:
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from tqdm.auto import tqdm
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except ImportError:
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raise ImportError(
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"You must install tqdm to use show_progress=True."
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"You can install tqdm with `pip install tqdm`."
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)
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# Make sure to provide `total` here so that tqdm can show
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# a progress bar that takes into account the total number of files.
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def _with_tqdm(iterable: Iterable[T]) -> Iterator[T]:
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"""Wrap an iterable in a tqdm progress bar."""
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return tqdm(iterable, total=length_func())
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iterator = _with_tqdm
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else:
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iterator = iter # type: ignore
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return iterator
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# PUBLIC API
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class CloudBlobLoader(BlobLoader):
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"""Load blobs from cloud URL or file:.
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Example:
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.. code-block:: python
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loader = CloudBlobLoader("s3://mybucket/id")
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for blob in loader.yield_blobs():
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print(blob)
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""" # noqa: E501
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def __init__(
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self,
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url: Union[str, "AnyPath"],
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*,
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glob: str = "**/[!.]*",
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exclude: Sequence[str] = (),
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suffixes: Optional[Sequence[str]] = None,
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show_progress: bool = False,
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) -> None:
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"""Initialize with a url and how to glob over it.
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Use [CloudPathLib](https://cloudpathlib.drivendata.org/).
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Args:
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url: Cloud URL to load from.
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If a path to a file is provided, glob/exclude/suffixes are ignored.
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glob: Glob pattern relative to the specified path
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by default set to pick up all non-hidden files
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exclude: patterns to exclude from results, use glob syntax
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suffixes: Provide to keep only files with these suffixes
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Useful when wanting to keep files with different suffixes
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Suffixes must include the dot, e.g. ".txt"
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show_progress: If true, will show a progress bar as the files are loaded.
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This forces an iteration through all matching files
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to count them prior to loading them.
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Examples:
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.. code-block:: python
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from langchain_community.document_loaders.blob_loaders import CloudBlobLoader
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# Load a single file.
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loader = CloudBlobLoader("s3://mybucket/id") # az://
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# Recursively load all text files in a directory.
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loader = CloudBlobLoader("az://mybucket/id", glob="**/*.txt")
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# Recursively load all non-hidden files in a directory.
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loader = CloudBlobLoader("gs://mybucket/id", glob="**/[!.]*")
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# Load all files in a directory without recursion.
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loader = CloudBlobLoader("s3://mybucket/id", glob="*")
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# Recursively load all files in a directory, except for py or pyc files.
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loader = CloudBlobLoader(
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"s3://mybucket/id",
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glob="**/*.txt",
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exclude=["**/*.py", "**/*.pyc"]
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)
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""" # noqa: E501
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from cloudpathlib import AnyPath
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url_parsed = urlparse(str(url))
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if url_parsed.scheme == "file":
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url = url_parsed.path
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if isinstance(url, str):
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self.path = AnyPath(url)
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else:
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self.path = url
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self.glob = glob
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self.suffixes = set(suffixes or [])
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self.show_progress = show_progress
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self.exclude = exclude
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def yield_blobs(
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self,
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) -> Iterable[Blob]:
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"""Yield blobs that match the requested pattern."""
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iterator = _make_iterator(
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length_func=self.count_matching_files, show_progress=self.show_progress
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)
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for path in iterator(self._yield_paths()):
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# yield Blob.from_path(path)
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yield self.from_path(path)
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def _yield_paths(self) -> Iterable["AnyPath"]:
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"""Yield paths that match the requested pattern."""
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if self.path.is_file(): # type: ignore
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yield self.path
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return
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paths = self.path.glob(self.glob)
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for path in paths:
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if self.exclude:
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if any(path.match(glob) for glob in self.exclude):
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continue
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if path.is_file():
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if self.suffixes and path.suffix not in self.suffixes:
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continue # FIXME
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yield path
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def count_matching_files(self) -> int:
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"""Count files that match the pattern without loading them."""
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# Carry out a full iteration to count the files without
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# materializing anything expensive in memory.
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num = 0
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for _ in self._yield_paths():
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num += 1
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return num
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@classmethod
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def from_path(
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cls,
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path: "AnyPath",
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*,
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encoding: str = "utf-8",
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mime_type: Optional[str] = None,
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guess_type: bool = True,
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metadata: Optional[dict] = None,
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) -> Blob:
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"""Load the blob from a path like object.
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Args:
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path: path like object to file to be read
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encoding: Encoding to use if decoding the bytes into a string
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mime_type: if provided, will be set as the mime-type of the data
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guess_type: If True, the mimetype will be guessed from the file extension,
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if a mime-type was not provided
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metadata: Metadata to associate with the blob
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Returns:
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Blob instance
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"""
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if mime_type is None and guess_type:
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_mimetype = mimetypes.guess_type(path)[0] if guess_type else None # type: ignore
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else:
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_mimetype = mime_type
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url_parsed = urlparse(str(path))
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if url_parsed.scheme in ["file", ""]:
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if url_parsed.scheme == "file":
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local_path = url_parsed.path
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else:
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local_path = str(path)
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return Blob(
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data=None,
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mimetype=_mimetype,
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encoding=encoding,
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path=local_path,
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metadata=metadata if metadata is not None else {},
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)
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return _CloudBlob(
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data=None,
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mimetype=_mimetype,
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encoding=encoding,
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path=str(path),
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metadata=metadata if metadata is not None else {},
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)
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71
libs/community/poetry.lock
generated
71
libs/community/poetry.lock
generated
@ -12,21 +12,6 @@ files = [
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{file = "aenum-3.1.15.tar.gz", hash = "sha256:8cbd76cd18c4f870ff39b24284d3ea028fbe8731a58df3aa581e434c575b9559"},
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]
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[[package]]
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name = "aerospike-vector-search"
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version = "0.6.1"
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description = "Aerospike Vector Search Client Library for Python"
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optional = true
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python-versions = ">3.8"
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files = [
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{file = "aerospike-vector-search-0.6.1.tar.gz", hash = "sha256:1d3dcf84221a08434a0b2fb4bbac040b3718a169cdd7e44a725eae2fdbad6a43"},
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{file = "aerospike_vector_search-0.6.1-py3-none-any.whl", hash = "sha256:cc7cc7c829f218c4ee9ccd93ca0ecad7104d81deac236309dcdf87e9c399fd35"},
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]
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[package.dependencies]
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grpcio = "*"
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protobuf = "*"
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[[package]]
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name = "aiodns"
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version = "3.1.1"
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@ -1065,6 +1050,26 @@ click = ">=4.0"
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[package.extras]
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test = ["pytest-cov"]
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[[package]]
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name = "cloudpathlib"
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version = "0.18.1"
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description = "pathlib-style classes for cloud storage services."
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optional = true
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python-versions = ">=3.7"
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files = [
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{file = "cloudpathlib-0.18.1-py3-none-any.whl", hash = "sha256:20efd5d772c75df91bb2ac52e053be53fd9000f5e9755fd92375a2a9fe6005e0"},
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{file = "cloudpathlib-0.18.1.tar.gz", hash = "sha256:ffd22f324bfbf9c3f2bc1bec6e8372cb372a0feef17c7f2b48030cd6810ea859"},
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]
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[package.dependencies]
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typing_extensions = {version = ">4", markers = "python_version < \"3.11\""}
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[package.extras]
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all = ["cloudpathlib[azure]", "cloudpathlib[gs]", "cloudpathlib[s3]"]
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azure = ["azure-storage-blob (>=12)"]
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gs = ["google-cloud-storage"]
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s3 = ["boto3"]
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[[package]]
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name = "cloudpickle"
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version = "3.0.0"
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@ -1185,7 +1190,6 @@ files = [
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{file = "contourpy-1.1.0-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:18a64814ae7bce73925131381603fff0116e2df25230dfc80d6d690aa6e20b37"},
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{file = "contourpy-1.1.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:90c81f22b4f572f8a2110b0b741bb64e5a6427e0a198b2cdc1fbaf85f352a3aa"},
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{file = "contourpy-1.1.0-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:53cc3a40635abedbec7f1bde60f8c189c49e84ac180c665f2cd7c162cc454baa"},
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{file = "contourpy-1.1.0-cp310-cp310-win32.whl", hash = "sha256:9b2dd2ca3ac561aceef4c7c13ba654aaa404cf885b187427760d7f7d4c57cff8"},
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{file = "contourpy-1.1.0-cp310-cp310-win_amd64.whl", hash = "sha256:1f795597073b09d631782e7245016a4323cf1cf0b4e06eef7ea6627e06a37ff2"},
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{file = "contourpy-1.1.0-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:0b7b04ed0961647691cfe5d82115dd072af7ce8846d31a5fac6c142dcce8b882"},
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{file = "contourpy-1.1.0-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:27bc79200c742f9746d7dd51a734ee326a292d77e7d94c8af6e08d1e6c15d545"},
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@ -1194,7 +1198,6 @@ files = [
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{file = "contourpy-1.1.0-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:e5cec36c5090e75a9ac9dbd0ff4a8cf7cecd60f1b6dc23a374c7d980a1cd710e"},
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{file = "contourpy-1.1.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:1f0cbd657e9bde94cd0e33aa7df94fb73c1ab7799378d3b3f902eb8eb2e04a3a"},
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{file = "contourpy-1.1.0-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:181cbace49874f4358e2929aaf7ba84006acb76694102e88dd15af861996c16e"},
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{file = "contourpy-1.1.0-cp311-cp311-win32.whl", hash = "sha256:edb989d31065b1acef3828a3688f88b2abb799a7db891c9e282df5ec7e46221b"},
|
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{file = "contourpy-1.1.0-cp311-cp311-win_amd64.whl", hash = "sha256:fb3b7d9e6243bfa1efb93ccfe64ec610d85cfe5aec2c25f97fbbd2e58b531256"},
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{file = "contourpy-1.1.0-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:bcb41692aa09aeb19c7c213411854402f29f6613845ad2453d30bf421fe68fed"},
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{file = "contourpy-1.1.0-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:5d123a5bc63cd34c27ff9c7ac1cd978909e9c71da12e05be0231c608048bb2ae"},
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@ -1203,7 +1206,6 @@ files = [
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{file = "contourpy-1.1.0-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:317267d915490d1e84577924bd61ba71bf8681a30e0d6c545f577363157e5e94"},
|
||||
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@ -3553,7 +3555,6 @@ optional = false
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@ -4133,7 +4134,6 @@ files = [
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|
||||
{file = "PyYAML-6.0.1-cp38-cp38-win32.whl", hash = "sha256:184c5108a2aca3c5b3d3bf9395d50893a7ab82a38004c8f61c258d4428e80206"},
|
||||
{file = "PyYAML-6.0.1-cp38-cp38-win_amd64.whl", hash = "sha256:1e2722cc9fbb45d9b87631ac70924c11d3a401b2d7f410cc0e3bbf249f2dca62"},
|
||||
{file = "PyYAML-6.0.1-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:9eb6caa9a297fc2c2fb8862bc5370d0303ddba53ba97e71f08023b6cd73d16a8"},
|
||||
@ -7200,7 +7184,6 @@ files = [
|
||||
{file = "PyYAML-6.0.1-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:5773183b6446b2c99bb77e77595dd486303b4faab2b086e7b17bc6bef28865f6"},
|
||||
{file = "PyYAML-6.0.1-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:b786eecbdf8499b9ca1d697215862083bd6d2a99965554781d0d8d1ad31e13a0"},
|
||||
{file = "PyYAML-6.0.1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:bc1bf2925a1ecd43da378f4db9e4f799775d6367bdb94671027b73b393a7c42c"},
|
||||
{file = "PyYAML-6.0.1-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:04ac92ad1925b2cff1db0cfebffb6ffc43457495c9b3c39d3fcae417d7125dc5"},
|
||||
{file = "PyYAML-6.0.1-cp39-cp39-win32.whl", hash = "sha256:faca3bdcf85b2fc05d06ff3fbc1f83e1391b3e724afa3feba7d13eeab355484c"},
|
||||
{file = "PyYAML-6.0.1-cp39-cp39-win_amd64.whl", hash = "sha256:510c9deebc5c0225e8c96813043e62b680ba2f9c50a08d3724c7f28a747d1486"},
|
||||
{file = "PyYAML-6.0.1.tar.gz", hash = "sha256:bfdf460b1736c775f2ba9f6a92bca30bc2095067b8a9d77876d1fad6cc3b4a43"},
|
||||
@ -8364,9 +8347,7 @@ python-versions = ">=3.7"
|
||||
files = [
|
||||
{file = "SQLAlchemy-2.0.28-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:e0b148ab0438f72ad21cb004ce3bdaafd28465c4276af66df3b9ecd2037bf252"},
|
||||
{file = "SQLAlchemy-2.0.28-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:bbda76961eb8f27e6ad3c84d1dc56d5bc61ba8f02bd20fcf3450bd421c2fcc9c"},
|
||||
{file = "SQLAlchemy-2.0.28-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:feea693c452d85ea0015ebe3bb9cd15b6f49acc1a31c28b3c50f4db0f8fb1e71"},
|
||||
{file = "SQLAlchemy-2.0.28-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:5da98815f82dce0cb31fd1e873a0cb30934971d15b74e0d78cf21f9e1b05953f"},
|
||||
{file = "SQLAlchemy-2.0.28-cp310-cp310-musllinux_1_1_aarch64.whl", hash = "sha256:4a5adf383c73f2d49ad15ff363a8748319ff84c371eed59ffd0127355d6ea1da"},
|
||||
{file = "SQLAlchemy-2.0.28-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:56856b871146bfead25fbcaed098269d90b744eea5cb32a952df00d542cdd368"},
|
||||
{file = "SQLAlchemy-2.0.28-cp310-cp310-win32.whl", hash = "sha256:943aa74a11f5806ab68278284a4ddd282d3fb348a0e96db9b42cb81bf731acdc"},
|
||||
{file = "SQLAlchemy-2.0.28-cp310-cp310-win_amd64.whl", hash = "sha256:c6c4da4843e0dabde41b8f2e8147438330924114f541949e6318358a56d1875a"},
|
||||
@ -8387,25 +8368,19 @@ files = [
|
||||
{file = "SQLAlchemy-2.0.28-cp312-cp312-win32.whl", hash = "sha256:a921002be69ac3ab2cf0c3017c4e6a3377f800f1fca7f254c13b5f1a2f10022c"},
|
||||
{file = "SQLAlchemy-2.0.28-cp312-cp312-win_amd64.whl", hash = "sha256:b4a2cf92995635b64876dc141af0ef089c6eea7e05898d8d8865e71a326c0385"},
|
||||
{file = "SQLAlchemy-2.0.28-cp37-cp37m-macosx_10_9_x86_64.whl", hash = "sha256:8e91b5e341f8c7f1e5020db8e5602f3ed045a29f8e27f7f565e0bdee3338f2c7"},
|
||||
{file = "SQLAlchemy-2.0.28-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:45c7b78dfc7278329f27be02c44abc0d69fe235495bb8e16ec7ef1b1a17952db"},
|
||||
{file = "SQLAlchemy-2.0.28-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:3eba73ef2c30695cb7eabcdb33bb3d0b878595737479e152468f3ba97a9c22a4"},
|
||||
{file = "SQLAlchemy-2.0.28-cp37-cp37m-musllinux_1_1_aarch64.whl", hash = "sha256:5df5d1dafb8eee89384fb7a1f79128118bc0ba50ce0db27a40750f6f91aa99d5"},
|
||||
{file = "SQLAlchemy-2.0.28-cp37-cp37m-musllinux_1_1_x86_64.whl", hash = "sha256:2858bbab1681ee5406650202950dc8f00e83b06a198741b7c656e63818633526"},
|
||||
{file = "SQLAlchemy-2.0.28-cp37-cp37m-win32.whl", hash = "sha256:9461802f2e965de5cff80c5a13bc945abea7edaa1d29360b485c3d2b56cdb075"},
|
||||
{file = "SQLAlchemy-2.0.28-cp37-cp37m-win_amd64.whl", hash = "sha256:a6bec1c010a6d65b3ed88c863d56b9ea5eeefdf62b5e39cafd08c65f5ce5198b"},
|
||||
{file = "SQLAlchemy-2.0.28-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:843a882cadebecc655a68bd9a5b8aa39b3c52f4a9a5572a3036fb1bb2ccdc197"},
|
||||
{file = "SQLAlchemy-2.0.28-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:dbb990612c36163c6072723523d2be7c3eb1517bbdd63fe50449f56afafd1133"},
|
||||
{file = "SQLAlchemy-2.0.28-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:bd7e4baf9161d076b9a7e432fce06217b9bd90cfb8f1d543d6e8c4595627edb9"},
|
||||
{file = "SQLAlchemy-2.0.28-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:e0a5354cb4de9b64bccb6ea33162cb83e03dbefa0d892db88a672f5aad638a75"},
|
||||
{file = "SQLAlchemy-2.0.28-cp38-cp38-musllinux_1_1_aarch64.whl", hash = "sha256:fffcc8edc508801ed2e6a4e7b0d150a62196fd28b4e16ab9f65192e8186102b6"},
|
||||
{file = "SQLAlchemy-2.0.28-cp38-cp38-musllinux_1_1_x86_64.whl", hash = "sha256:aca7b6d99a4541b2ebab4494f6c8c2f947e0df4ac859ced575238e1d6ca5716b"},
|
||||
{file = "SQLAlchemy-2.0.28-cp38-cp38-win32.whl", hash = "sha256:8c7f10720fc34d14abad5b647bc8202202f4948498927d9f1b4df0fb1cf391b7"},
|
||||
{file = "SQLAlchemy-2.0.28-cp38-cp38-win_amd64.whl", hash = "sha256:243feb6882b06a2af68ecf4bec8813d99452a1b62ba2be917ce6283852cf701b"},
|
||||
{file = "SQLAlchemy-2.0.28-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:fc4974d3684f28b61b9a90fcb4c41fb340fd4b6a50c04365704a4da5a9603b05"},
|
||||
{file = "SQLAlchemy-2.0.28-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:87724e7ed2a936fdda2c05dbd99d395c91ea3c96f029a033a4a20e008dd876bf"},
|
||||
{file = "SQLAlchemy-2.0.28-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:68722e6a550f5de2e3cfe9da6afb9a7dd15ef7032afa5651b0f0c6b3adb8815d"},
|
||||
{file = "SQLAlchemy-2.0.28-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:328529f7c7f90adcd65aed06a161851f83f475c2f664a898af574893f55d9e53"},
|
||||
{file = "SQLAlchemy-2.0.28-cp39-cp39-musllinux_1_1_aarch64.whl", hash = "sha256:df40c16a7e8be7413b885c9bf900d402918cc848be08a59b022478804ea076b8"},
|
||||
{file = "SQLAlchemy-2.0.28-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:426f2fa71331a64f5132369ede5171c52fd1df1bd9727ce621f38b5b24f48750"},
|
||||
{file = "SQLAlchemy-2.0.28-cp39-cp39-win32.whl", hash = "sha256:33157920b233bc542ce497a81a2e1452e685a11834c5763933b440fedd1d8e2d"},
|
||||
{file = "SQLAlchemy-2.0.28-cp39-cp39-win_amd64.whl", hash = "sha256:2f60843068e432311c886c5f03c4664acaef507cf716f6c60d5fde7265be9d7b"},
|
||||
@ -10099,9 +10074,9 @@ testing = ["big-O", "jaraco.functools", "jaraco.itertools", "more-itertools", "p
|
||||
|
||||
[extras]
|
||||
cli = ["typer"]
|
||||
extended-testing = ["aerospike-vector-search", "aiosqlite", "aleph-alpha-client", "anthropic", "arxiv", "assemblyai", "atlassian-python-api", "azure-ai-documentintelligence", "azure-identity", "azure-search-documents", "beautifulsoup4", "bibtexparser", "cassio", "chardet", "cloudpickle", "cloudpickle", "cohere", "databricks-vectorsearch", "datasets", "dgml-utils", "elasticsearch", "esprima", "faiss-cpu", "feedparser", "fireworks-ai", "friendli-client", "geopandas", "gitpython", "google-cloud-documentai", "gql", "gradientai", "hdbcli", "hologres-vector", "html2text", "httpx", "httpx-sse", "javelin-sdk", "jinja2", "jq", "jsonschema", "lxml", "markdownify", "motor", "msal", "mwparserfromhell", "mwxml", "newspaper3k", "numexpr", "nvidia-riva-client", "oci", "openai", "openapi-pydantic", "oracle-ads", "oracledb", "pandas", "pdfminer-six", "pgvector", "praw", "premai", "psychicapi", "py-trello", "pyjwt", "pymupdf", "pypdf", "pypdfium2", "pyspark", "rank-bm25", "rapidfuzz", "rapidocr-onnxruntime", "rdflib", "requests-toolbelt", "rspace_client", "scikit-learn", "sqlite-vss", "streamlit", "sympy", "telethon", "tidb-vector", "timescale-vector", "tqdm", "tree-sitter", "tree-sitter-languages", "upstash-redis", "vdms", "xata", "xmltodict"]
|
||||
extended-testing = ["aiosqlite", "aleph-alpha-client", "anthropic", "arxiv", "assemblyai", "atlassian-python-api", "azure-ai-documentintelligence", "azure-identity", "azure-search-documents", "beautifulsoup4", "bibtexparser", "cassio", "chardet", "cloudpathlib", "cloudpickle", "cloudpickle", "cohere", "databricks-vectorsearch", "datasets", "dgml-utils", "elasticsearch", "esprima", "faiss-cpu", "feedparser", "fireworks-ai", "friendli-client", "geopandas", "gitpython", "google-cloud-documentai", "gql", "gradientai", "hdbcli", "hologres-vector", "html2text", "httpx", "httpx-sse", "javelin-sdk", "jinja2", "jq", "jsonschema", "lxml", "markdownify", "motor", "msal", "mwparserfromhell", "mwxml", "newspaper3k", "numexpr", "nvidia-riva-client", "oci", "openai", "openapi-pydantic", "oracle-ads", "oracledb", "pandas", "pdfminer-six", "pgvector", "praw", "premai", "psychicapi", "py-trello", "pyjwt", "pymupdf", "pypdf", "pypdfium2", "pyspark", "rank-bm25", "rapidfuzz", "rapidocr-onnxruntime", "rdflib", "requests-toolbelt", "rspace_client", "scikit-learn", "sqlite-vss", "streamlit", "sympy", "telethon", "tidb-vector", "timescale-vector", "tqdm", "tree-sitter", "tree-sitter-languages", "upstash-redis", "vdms", "xata", "xmltodict"]
|
||||
|
||||
[metadata]
|
||||
lock-version = "2.0"
|
||||
python-versions = ">=3.8.1,<4.0"
|
||||
content-hash = "6fbb50e2a8146f8fc2590c8de1a194c7bbc7dd2cfd3d2fd090247aadc01e63f1"
|
||||
content-hash = "1a30f88ba6352cfd5af8d3b7b6418ec01bad42c73e6096b1a3ccef06cb36709b"
|
||||
|
||||
@ -104,7 +104,8 @@ vdms = {version = "^0.0.20", optional = true}
|
||||
httpx-sse = {version = "^0.4.0", optional = true}
|
||||
pyjwt = {version = "^2.8.0", optional = true}
|
||||
oracledb = {version = "^2.2.0", optional = true}
|
||||
aerospike-vector-search = {version = "^0.6.1", optional = true}
|
||||
cloudpathlib = { version = "^0.18", optional = true }
|
||||
|
||||
|
||||
[tool.poetry.group.test]
|
||||
optional = true
|
||||
@ -202,7 +203,6 @@ cli = ["typer"]
|
||||
# Please use new-line on formatting to make it easier to add new packages without
|
||||
# merge-conflicts
|
||||
extended_testing = [
|
||||
"aerospike-vector-search",
|
||||
"aleph-alpha-client",
|
||||
"aiosqlite",
|
||||
"assemblyai",
|
||||
@ -267,6 +267,7 @@ extended_testing = [
|
||||
"praw",
|
||||
"databricks-vectorsearch",
|
||||
"cloudpickle",
|
||||
"cloudpathlib",
|
||||
"dgml-utils",
|
||||
"cohere",
|
||||
"tree-sitter",
|
||||
@ -287,7 +288,7 @@ extended_testing = [
|
||||
"vdms",
|
||||
"httpx-sse",
|
||||
"pyjwt",
|
||||
"oracledb"
|
||||
"oracledb",
|
||||
]
|
||||
|
||||
[tool.ruff]
|
||||
|
||||
@ -0,0 +1,166 @@
|
||||
"""Verify that file system blob loader works as expected."""
|
||||
import os
|
||||
import tempfile
|
||||
from typing import Generator
|
||||
from urllib.parse import urlparse
|
||||
|
||||
import pytest
|
||||
|
||||
from langchain_community.document_loaders.blob_loaders import CloudBlobLoader
|
||||
|
||||
|
||||
@pytest.fixture
|
||||
def toy_dir() -> Generator[str, None, None]:
|
||||
"""Yield a pre-populated directory to test the blob loader."""
|
||||
with tempfile.TemporaryDirectory() as temp_dir:
|
||||
# Create test.txt
|
||||
with open(os.path.join(temp_dir, "test.txt"), "w") as test_txt:
|
||||
test_txt.write("This is a test.txt file.")
|
||||
|
||||
# Create test.html
|
||||
with open(os.path.join(temp_dir, "test.html"), "w") as test_html:
|
||||
test_html.write(
|
||||
"<html><body><h1>This is a test.html file.</h1></body></html>"
|
||||
)
|
||||
|
||||
# Create .hidden_file
|
||||
with open(os.path.join(temp_dir, ".hidden_file"), "w") as hidden_file:
|
||||
hidden_file.write("This is a hidden file.")
|
||||
|
||||
# Create some_dir/nested_file.txt
|
||||
some_dir = os.path.join(temp_dir, "some_dir")
|
||||
os.makedirs(some_dir)
|
||||
with open(os.path.join(some_dir, "nested_file.txt"), "w") as nested_file:
|
||||
nested_file.write("This is a nested_file.txt file.")
|
||||
|
||||
# Create some_dir/other_dir/more_nested.txt
|
||||
other_dir = os.path.join(some_dir, "other_dir")
|
||||
os.makedirs(other_dir)
|
||||
with open(os.path.join(other_dir, "more_nested.txt"), "w") as nested_file:
|
||||
nested_file.write("This is a more_nested.txt file.")
|
||||
|
||||
yield f"file://{temp_dir}"
|
||||
|
||||
|
||||
# @pytest.fixture
|
||||
# @pytest.mark.requires("boto3")
|
||||
# def toy_dir() -> str:
|
||||
# return "s3://ppr-langchain-test"
|
||||
|
||||
|
||||
_TEST_CASES = [
|
||||
{
|
||||
"glob": "**/[!.]*",
|
||||
"suffixes": None,
|
||||
"exclude": (),
|
||||
"relative_filenames": [
|
||||
"test.html",
|
||||
"test.txt",
|
||||
"some_dir/nested_file.txt",
|
||||
"some_dir/other_dir/more_nested.txt",
|
||||
],
|
||||
},
|
||||
{
|
||||
"glob": "*",
|
||||
"suffixes": None,
|
||||
"exclude": (),
|
||||
"relative_filenames": ["test.html", "test.txt", ".hidden_file"],
|
||||
},
|
||||
{
|
||||
"glob": "**/*.html",
|
||||
"suffixes": None,
|
||||
"exclude": (),
|
||||
"relative_filenames": ["test.html"],
|
||||
},
|
||||
{
|
||||
"glob": "*/*.txt",
|
||||
"suffixes": None,
|
||||
"exclude": (),
|
||||
"relative_filenames": ["some_dir/nested_file.txt"],
|
||||
},
|
||||
{
|
||||
"glob": "**/*.txt",
|
||||
"suffixes": None,
|
||||
"exclude": (),
|
||||
"relative_filenames": [
|
||||
"test.txt",
|
||||
"some_dir/nested_file.txt",
|
||||
"some_dir/other_dir/more_nested.txt",
|
||||
],
|
||||
},
|
||||
{
|
||||
"glob": "**/*",
|
||||
"suffixes": [".txt"],
|
||||
"exclude": (),
|
||||
"relative_filenames": [
|
||||
"test.txt",
|
||||
"some_dir/nested_file.txt",
|
||||
"some_dir/other_dir/more_nested.txt",
|
||||
],
|
||||
},
|
||||
{
|
||||
"glob": "meeeeeeow",
|
||||
"suffixes": None,
|
||||
"exclude": (),
|
||||
"relative_filenames": [],
|
||||
},
|
||||
{
|
||||
"glob": "*",
|
||||
"suffixes": [".html", ".txt"],
|
||||
"exclude": (),
|
||||
"relative_filenames": ["test.html", "test.txt"],
|
||||
},
|
||||
# Using exclude patterns
|
||||
{
|
||||
"glob": "**/*",
|
||||
"suffixes": [".txt"],
|
||||
"exclude": ("some_dir/*",),
|
||||
"relative_filenames": ["test.txt", "some_dir/other_dir/more_nested.txt"],
|
||||
},
|
||||
# Using 2 exclude patterns, one of which is recursive
|
||||
{
|
||||
"glob": "**/*",
|
||||
"suffixes": None,
|
||||
"exclude": ("**/*.txt", ".hidden*"),
|
||||
"relative_filenames": ["test.html"],
|
||||
},
|
||||
]
|
||||
|
||||
|
||||
@pytest.mark.requires("cloudpathlib")
|
||||
@pytest.mark.parametrize("params", _TEST_CASES)
|
||||
def test_file_names_exist(toy_dir: str, params: dict) -> None:
|
||||
"""Verify that the file names exist."""
|
||||
|
||||
glob_pattern = params["glob"]
|
||||
suffixes = params["suffixes"]
|
||||
exclude = params["exclude"]
|
||||
relative_filenames = params["relative_filenames"]
|
||||
|
||||
loader = CloudBlobLoader(
|
||||
toy_dir, glob=glob_pattern, suffixes=suffixes, exclude=exclude
|
||||
)
|
||||
blobs = list(loader.yield_blobs())
|
||||
|
||||
url_parsed = urlparse(toy_dir)
|
||||
scheme = ""
|
||||
if url_parsed.scheme == "file":
|
||||
scheme = "file://"
|
||||
|
||||
file_names = sorted(f"{scheme}{blob.path}" for blob in blobs)
|
||||
|
||||
expected_filenames = sorted(
|
||||
str(toy_dir + "/" + relative_filename)
|
||||
for relative_filename in relative_filenames
|
||||
)
|
||||
|
||||
assert file_names == expected_filenames
|
||||
assert loader.count_matching_files() == len(relative_filenames)
|
||||
|
||||
|
||||
@pytest.mark.requires("cloudpathlib")
|
||||
def test_show_progress(toy_dir: str) -> None:
|
||||
"""Verify that file system loader works with a progress bar."""
|
||||
loader = CloudBlobLoader(toy_dir)
|
||||
blobs = list(loader.yield_blobs())
|
||||
assert len(blobs) == loader.count_matching_files()
|
||||
@ -6,6 +6,7 @@ def test_public_api() -> None:
|
||||
assert sorted(__all__) == [
|
||||
"Blob",
|
||||
"BlobLoader",
|
||||
"CloudBlobLoader",
|
||||
"FileSystemBlobLoader",
|
||||
"YoutubeAudioLoader",
|
||||
]
|
||||
|
||||
133
poetry.lock
generated
133
poetry.lock
generated
@ -1,4 +1,4 @@
|
||||
# This file is automatically @generated by Poetry 1.6.1 and should not be changed by hand.
|
||||
# This file is automatically @generated by Poetry 1.8.2 and should not be changed by hand.
|
||||
|
||||
[[package]]
|
||||
name = "aiohttp"
|
||||
@ -1351,7 +1351,6 @@ optional = false
|
||||
python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*, !=3.5.*, !=3.6.*"
|
||||
files = [
|
||||
{file = "jsonpointer-2.4-py2.py3-none-any.whl", hash = "sha256:15d51bba20eea3165644553647711d150376234112651b4f1811022aecad7d7a"},
|
||||
{file = "jsonpointer-2.4.tar.gz", hash = "sha256:585cee82b70211fa9e6043b7bb89db6e1aa49524340dde8ad6b63206ea689d88"},
|
||||
]
|
||||
|
||||
[[package]]
|
||||
@ -1694,7 +1693,7 @@ files = [
|
||||
|
||||
[[package]]
|
||||
name = "langchain"
|
||||
version = "0.1.16"
|
||||
version = "0.2.0"
|
||||
description = "Building applications with LLMs through composability"
|
||||
optional = false
|
||||
python-versions = ">=3.8.1,<4.0"
|
||||
@ -1705,10 +1704,8 @@ develop = true
|
||||
aiohttp = "^3.8.3"
|
||||
async-timeout = {version = "^4.0.0", markers = "python_version < \"3.11\""}
|
||||
dataclasses-json = ">= 0.5.7, < 0.7"
|
||||
jsonpatch = "^1.33"
|
||||
langchain-community = ">=0.0.32,<0.1"
|
||||
langchain-core = "^0.1.42"
|
||||
langchain-text-splitters = ">=0.0.1,<0.1"
|
||||
langchain-core = "^0.2.0"
|
||||
langchain-text-splitters = "^0.2.0"
|
||||
langsmith = "^0.1.17"
|
||||
numpy = "^1"
|
||||
pydantic = ">=1,<3"
|
||||
@ -1725,10 +1722,10 @@ cli = ["typer (>=0.9.0,<0.10.0)"]
|
||||
cohere = ["cohere (>=4,<6)"]
|
||||
docarray = ["docarray[hnswlib] (>=0.32.0,<0.33.0)"]
|
||||
embeddings = ["sentence-transformers (>=2,<3)"]
|
||||
extended-testing = ["aiosqlite (>=0.19.0,<0.20.0)", "aleph-alpha-client (>=2.15.0,<3.0.0)", "anthropic (>=0.3.11,<0.4.0)", "arxiv (>=1.4,<2.0)", "assemblyai (>=0.17.0,<0.18.0)", "atlassian-python-api (>=3.36.0,<4.0.0)", "beautifulsoup4 (>=4,<5)", "bibtexparser (>=1.4.0,<2.0.0)", "cassio (>=0.1.0,<0.2.0)", "chardet (>=5.1.0,<6.0.0)", "cohere (>=4,<6)", "couchbase (>=4.1.9,<5.0.0)", "dashvector (>=1.0.1,<2.0.0)", "databricks-vectorsearch (>=0.21,<0.22)", "datasets (>=2.15.0,<3.0.0)", "dgml-utils (>=0.3.0,<0.4.0)", "esprima (>=4.0.1,<5.0.0)", "faiss-cpu (>=1,<2)", "feedparser (>=6.0.10,<7.0.0)", "fireworks-ai (>=0.9.0,<0.10.0)", "geopandas (>=0.13.1,<0.14.0)", "gitpython (>=3.1.32,<4.0.0)", "google-cloud-documentai (>=2.20.1,<3.0.0)", "gql (>=3.4.1,<4.0.0)", "hologres-vector (>=0.0.6,<0.0.7)", "html2text (>=2020.1.16,<2021.0.0)", "javelin-sdk (>=0.1.8,<0.2.0)", "jinja2 (>=3,<4)", "jq (>=1.4.1,<2.0.0)", "jsonschema (>1)", "langchain-openai (>=0.0.2,<0.1)", "lxml (>=4.9.3,<6.0)", "markdownify (>=0.11.6,<0.12.0)", "motor (>=3.3.1,<4.0.0)", "msal (>=1.25.0,<2.0.0)", "mwparserfromhell (>=0.6.4,<0.7.0)", "mwxml (>=0.3.3,<0.4.0)", "newspaper3k (>=0.2.8,<0.3.0)", "numexpr (>=2.8.6,<3.0.0)", "openai (<2)", "openai (<2)", "openapi-pydantic (>=0.3.2,<0.4.0)", "pandas (>=2.0.1,<3.0.0)", "pdfminer-six (>=20221105,<20221106)", "pgvector (>=0.1.6,<0.2.0)", "praw (>=7.7.1,<8.0.0)", "psychicapi (>=0.8.0,<0.9.0)", "py-trello (>=0.19.0,<0.20.0)", "pymupdf (>=1.22.3,<2.0.0)", "pypdf (>=3.4.0,<4.0.0)", "pypdfium2 (>=4.10.0,<5.0.0)", "pyspark (>=3.4.0,<4.0.0)", "rank-bm25 (>=0.2.2,<0.3.0)", "rapidfuzz (>=3.1.1,<4.0.0)", "rapidocr-onnxruntime (>=1.3.2,<2.0.0)", "rdflib (==7.0.0)", "requests-toolbelt (>=1.0.0,<2.0.0)", "rspace_client (>=2.5.0,<3.0.0)", "scikit-learn (>=1.2.2,<2.0.0)", "sqlite-vss (>=0.1.2,<0.2.0)", "streamlit (>=1.18.0,<2.0.0)", "sympy (>=1.12,<2.0)", "telethon (>=1.28.5,<2.0.0)", "timescale-vector (>=0.0.1,<0.0.2)", "tqdm (>=4.48.0)", "upstash-redis (>=0.15.0,<0.16.0)", "xata (>=1.0.0a7,<2.0.0)", "xmltodict (>=0.13.0,<0.14.0)"]
|
||||
extended-testing = ["aiosqlite (>=0.19.0,<0.20.0)", "aleph-alpha-client (>=2.15.0,<3.0.0)", "anthropic (>=0.3.11,<0.4.0)", "arxiv (>=1.4,<2.0)", "assemblyai (>=0.17.0,<0.18.0)", "atlassian-python-api (>=3.36.0,<4.0.0)", "beautifulsoup4 (>=4,<5)", "bibtexparser (>=1.4.0,<2.0.0)", "cassio (>=0.1.0,<0.2.0)", "chardet (>=5.1.0,<6.0.0)", "cohere (>=4,<6)", "couchbase (>=4.1.9,<5.0.0)", "dashvector (>=1.0.1,<2.0.0)", "databricks-vectorsearch (>=0.21,<0.22)", "datasets (>=2.15.0,<3.0.0)", "dgml-utils (>=0.3.0,<0.4.0)", "esprima (>=4.0.1,<5.0.0)", "faiss-cpu (>=1,<2)", "feedparser (>=6.0.10,<7.0.0)", "fireworks-ai (>=0.9.0,<0.10.0)", "geopandas (>=0.13.1,<0.14.0)", "gitpython (>=3.1.32,<4.0.0)", "google-cloud-documentai (>=2.20.1,<3.0.0)", "gql (>=3.4.1,<4.0.0)", "hologres-vector (>=0.0.6,<0.0.7)", "html2text (>=2020.1.16,<2021.0.0)", "javelin-sdk (>=0.1.8,<0.2.0)", "jinja2 (>=3,<4)", "jq (>=1.4.1,<2.0.0)", "jsonschema (>1)", "langchain-openai (>=0.1,<0.2)", "lxml (>=4.9.3,<6.0)", "markdownify (>=0.11.6,<0.12.0)", "motor (>=3.3.1,<4.0.0)", "msal (>=1.25.0,<2.0.0)", "mwparserfromhell (>=0.6.4,<0.7.0)", "mwxml (>=0.3.3,<0.4.0)", "newspaper3k (>=0.2.8,<0.3.0)", "numexpr (>=2.8.6,<3.0.0)", "openai (<2)", "openai (<2)", "openapi-pydantic (>=0.3.2,<0.4.0)", "pandas (>=2.0.1,<3.0.0)", "pdfminer-six (>=20221105,<20221106)", "pgvector (>=0.1.6,<0.2.0)", "praw (>=7.7.1,<8.0.0)", "psychicapi (>=0.8.0,<0.9.0)", "py-trello (>=0.19.0,<0.20.0)", "pymupdf (>=1.22.3,<2.0.0)", "pypdf (>=3.4.0,<4.0.0)", "pypdfium2 (>=4.10.0,<5.0.0)", "pyspark (>=3.4.0,<4.0.0)", "rank-bm25 (>=0.2.2,<0.3.0)", "rapidfuzz (>=3.1.1,<4.0.0)", "rapidocr-onnxruntime (>=1.3.2,<2.0.0)", "rdflib (==7.0.0)", "requests-toolbelt (>=1.0.0,<2.0.0)", "rspace_client (>=2.5.0,<3.0.0)", "scikit-learn (>=1.2.2,<2.0.0)", "sqlite-vss (>=0.1.2,<0.2.0)", "streamlit (>=1.18.0,<2.0.0)", "sympy (>=1.12,<2.0)", "telethon (>=1.28.5,<2.0.0)", "timescale-vector (>=0.0.1,<0.0.2)", "tqdm (>=4.48.0)", "upstash-redis (>=0.15.0,<0.16.0)", "xata (>=1.0.0a7,<2.0.0)", "xmltodict (>=0.13.0,<0.14.0)"]
|
||||
javascript = ["esprima (>=4.0.1,<5.0.0)"]
|
||||
llms = ["clarifai (>=9.1.0)", "cohere (>=4,<6)", "huggingface_hub (>=0,<1)", "manifest-ml (>=0.0.1,<0.0.2)", "nlpcloud (>=1,<2)", "openai (<2)", "openlm (>=0.0.5,<0.0.6)", "torch (>=1,<3)", "transformers (>=4,<5)"]
|
||||
openai = ["openai (<2)", "tiktoken (>=0.3.2,<0.6.0)"]
|
||||
openai = ["openai (<2)", "tiktoken (>=0.7,<1.0)"]
|
||||
qdrant = ["qdrant-client (>=1.3.1,<2.0.0)"]
|
||||
text-helpers = ["chardet (>=5.1.0,<6.0.0)"]
|
||||
|
||||
@ -1738,7 +1735,7 @@ url = "libs/langchain"
|
||||
|
||||
[[package]]
|
||||
name = "langchain-community"
|
||||
version = "0.0.35"
|
||||
version = "0.2.0"
|
||||
description = "Community contributed LangChain integrations."
|
||||
optional = false
|
||||
python-versions = ">=3.8.1,<4.0"
|
||||
@ -1748,7 +1745,8 @@ develop = true
|
||||
[package.dependencies]
|
||||
aiohttp = "^3.8.3"
|
||||
dataclasses-json = ">= 0.5.7, < 0.7"
|
||||
langchain-core = "^0.1.47"
|
||||
langchain = "^0.2.0"
|
||||
langchain-core = "^0.2.0"
|
||||
langsmith = "^0.1.0"
|
||||
numpy = "^1"
|
||||
PyYAML = ">=5.3"
|
||||
@ -1758,7 +1756,7 @@ tenacity = "^8.1.0"
|
||||
|
||||
[package.extras]
|
||||
cli = ["typer (>=0.9.0,<0.10.0)"]
|
||||
extended-testing = ["aiosqlite (>=0.19.0,<0.20.0)", "aleph-alpha-client (>=2.15.0,<3.0.0)", "anthropic (>=0.3.11,<0.4.0)", "arxiv (>=1.4,<2.0)", "assemblyai (>=0.17.0,<0.18.0)", "atlassian-python-api (>=3.36.0,<4.0.0)", "azure-ai-documentintelligence (>=1.0.0b1,<2.0.0)", "azure-identity (>=1.15.0,<2.0.0)", "azure-search-documents (==11.4.0)", "beautifulsoup4 (>=4,<5)", "bibtexparser (>=1.4.0,<2.0.0)", "cassio (>=0.1.6,<0.2.0)", "chardet (>=5.1.0,<6.0.0)", "cloudpickle (>=2.0.0)", "cloudpickle (>=2.0.0)", "cohere (>=4,<5)", "databricks-vectorsearch (>=0.21,<0.22)", "datasets (>=2.15.0,<3.0.0)", "dgml-utils (>=0.3.0,<0.4.0)", "elasticsearch (>=8.12.0,<9.0.0)", "esprima (>=4.0.1,<5.0.0)", "faiss-cpu (>=1,<2)", "feedparser (>=6.0.10,<7.0.0)", "fireworks-ai (>=0.9.0,<0.10.0)", "friendli-client (>=1.2.4,<2.0.0)", "geopandas (>=0.13.1,<0.14.0)", "gitpython (>=3.1.32,<4.0.0)", "google-cloud-documentai (>=2.20.1,<3.0.0)", "gql (>=3.4.1,<4.0.0)", "gradientai (>=1.4.0,<2.0.0)", "hdbcli (>=2.19.21,<3.0.0)", "hologres-vector (>=0.0.6,<0.0.7)", "html2text (>=2020.1.16,<2021.0.0)", "httpx (>=0.24.1,<0.25.0)", "httpx-sse (>=0.4.0,<0.5.0)", "javelin-sdk (>=0.1.8,<0.2.0)", "jinja2 (>=3,<4)", "jq (>=1.4.1,<2.0.0)", "jsonschema (>1)", "lxml (>=4.9.3,<6.0)", "markdownify (>=0.11.6,<0.12.0)", "motor (>=3.3.1,<4.0.0)", "msal (>=1.25.0,<2.0.0)", "mwparserfromhell (>=0.6.4,<0.7.0)", "mwxml (>=0.3.3,<0.4.0)", "newspaper3k (>=0.2.8,<0.3.0)", "numexpr (>=2.8.6,<3.0.0)", "nvidia-riva-client (>=2.14.0,<3.0.0)", "oci (>=2.119.1,<3.0.0)", "openai (<2)", "openapi-pydantic (>=0.3.2,<0.4.0)", "oracle-ads (>=2.9.1,<3.0.0)", "pandas (>=2.0.1,<3.0.0)", "pdfminer-six (>=20221105,<20221106)", "pgvector (>=0.1.6,<0.2.0)", "praw (>=7.7.1,<8.0.0)", "premai (>=0.3.25,<0.4.0)", "psychicapi (>=0.8.0,<0.9.0)", "py-trello (>=0.19.0,<0.20.0)", "pyjwt (>=2.8.0,<3.0.0)", "pymupdf (>=1.22.3,<2.0.0)", "pypdf (>=3.4.0,<4.0.0)", "pypdfium2 (>=4.10.0,<5.0.0)", "pyspark (>=3.4.0,<4.0.0)", "rank-bm25 (>=0.2.2,<0.3.0)", "rapidfuzz (>=3.1.1,<4.0.0)", "rapidocr-onnxruntime (>=1.3.2,<2.0.0)", "rdflib (==7.0.0)", "requests-toolbelt (>=1.0.0,<2.0.0)", "rspace_client (>=2.5.0,<3.0.0)", "scikit-learn (>=1.2.2,<2.0.0)", "sqlite-vss (>=0.1.2,<0.2.0)", "streamlit (>=1.18.0,<2.0.0)", "sympy (>=1.12,<2.0)", "telethon (>=1.28.5,<2.0.0)", "tidb-vector (>=0.0.3,<1.0.0)", "timescale-vector (>=0.0.1,<0.0.2)", "tqdm (>=4.48.0)", "tree-sitter (>=0.20.2,<0.21.0)", "tree-sitter-languages (>=1.8.0,<2.0.0)", "upstash-redis (>=0.15.0,<0.16.0)", "vdms (>=0.0.20,<0.0.21)", "xata (>=1.0.0a7,<2.0.0)", "xmltodict (>=0.13.0,<0.14.0)"]
|
||||
extended-testing = ["aiosqlite (>=0.19.0,<0.20.0)", "aleph-alpha-client (>=2.15.0,<3.0.0)", "anthropic (>=0.3.11,<0.4.0)", "arxiv (>=1.4,<2.0)", "assemblyai (>=0.17.0,<0.18.0)", "atlassian-python-api (>=3.36.0,<4.0.0)", "azure-ai-documentintelligence (>=1.0.0b1,<2.0.0)", "azure-identity (>=1.15.0,<2.0.0)", "azure-search-documents (==11.4.0)", "beautifulsoup4 (>=4,<5)", "bibtexparser (>=1.4.0,<2.0.0)", "cassio (>=0.1.6,<0.2.0)", "chardet (>=5.1.0,<6.0.0)", "cloudpathlib (>=0.18,<0.19)", "cloudpickle (>=2.0.0)", "cloudpickle (>=2.0.0)", "cohere (>=4,<5)", "databricks-vectorsearch (>=0.21,<0.22)", "datasets (>=2.15.0,<3.0.0)", "dgml-utils (>=0.3.0,<0.4.0)", "elasticsearch (>=8.12.0,<9.0.0)", "esprima (>=4.0.1,<5.0.0)", "faiss-cpu (>=1,<2)", "feedparser (>=6.0.10,<7.0.0)", "fireworks-ai (>=0.9.0,<0.10.0)", "friendli-client (>=1.2.4,<2.0.0)", "geopandas (>=0.13.1,<0.14.0)", "gitpython (>=3.1.32,<4.0.0)", "google-cloud-documentai (>=2.20.1,<3.0.0)", "gql (>=3.4.1,<4.0.0)", "gradientai (>=1.4.0,<2.0.0)", "hdbcli (>=2.19.21,<3.0.0)", "hologres-vector (>=0.0.6,<0.0.7)", "html2text (>=2020.1.16,<2021.0.0)", "httpx (>=0.24.1,<0.25.0)", "httpx-sse (>=0.4.0,<0.5.0)", "javelin-sdk (>=0.1.8,<0.2.0)", "jinja2 (>=3,<4)", "jq (>=1.4.1,<2.0.0)", "jsonschema (>1)", "lxml (>=4.9.3,<6.0)", "markdownify (>=0.11.6,<0.12.0)", "motor (>=3.3.1,<4.0.0)", "msal (>=1.25.0,<2.0.0)", "mwparserfromhell (>=0.6.4,<0.7.0)", "mwxml (>=0.3.3,<0.4.0)", "newspaper3k (>=0.2.8,<0.3.0)", "numexpr (>=2.8.6,<3.0.0)", "nvidia-riva-client (>=2.14.0,<3.0.0)", "oci (>=2.119.1,<3.0.0)", "openai (<2)", "openapi-pydantic (>=0.3.2,<0.4.0)", "oracle-ads (>=2.9.1,<3.0.0)", "oracledb (>=2.2.0,<3.0.0)", "pandas (>=2.0.1,<3.0.0)", "pdfminer-six (>=20221105,<20221106)", "pgvector (>=0.1.6,<0.2.0)", "praw (>=7.7.1,<8.0.0)", "premai (>=0.3.25,<0.4.0)", "psychicapi (>=0.8.0,<0.9.0)", "py-trello (>=0.19.0,<0.20.0)", "pyjwt (>=2.8.0,<3.0.0)", "pymupdf (>=1.22.3,<2.0.0)", "pypdf (>=3.4.0,<4.0.0)", "pypdfium2 (>=4.10.0,<5.0.0)", "pyspark (>=3.4.0,<4.0.0)", "rank-bm25 (>=0.2.2,<0.3.0)", "rapidfuzz (>=3.1.1,<4.0.0)", "rapidocr-onnxruntime (>=1.3.2,<2.0.0)", "rdflib (==7.0.0)", "requests-toolbelt (>=1.0.0,<2.0.0)", "rspace_client (>=2.5.0,<3.0.0)", "scikit-learn (>=1.2.2,<2.0.0)", "sqlite-vss (>=0.1.2,<0.2.0)", "streamlit (>=1.18.0,<2.0.0)", "sympy (>=1.12,<2.0)", "telethon (>=1.28.5,<2.0.0)", "tidb-vector (>=0.0.3,<1.0.0)", "timescale-vector (>=0.0.1,<0.0.2)", "tqdm (>=4.48.0)", "tree-sitter (>=0.20.2,<0.21.0)", "tree-sitter-languages (>=1.8.0,<2.0.0)", "upstash-redis (>=0.15.0,<0.16.0)", "vdms (>=0.0.20,<0.0.21)", "xata (>=1.0.0a7,<2.0.0)", "xmltodict (>=0.13.0,<0.14.0)"]
|
||||
|
||||
[package.source]
|
||||
type = "directory"
|
||||
@ -1766,7 +1764,7 @@ url = "libs/community"
|
||||
|
||||
[[package]]
|
||||
name = "langchain-core"
|
||||
version = "0.1.47"
|
||||
version = "0.2.0"
|
||||
description = "Building applications with LLMs through composability"
|
||||
optional = false
|
||||
python-versions = ">=3.8.1,<4.0"
|
||||
@ -1790,7 +1788,7 @@ url = "libs/core"
|
||||
|
||||
[[package]]
|
||||
name = "langchain-experimental"
|
||||
version = "0.0.57"
|
||||
version = "0.0.59"
|
||||
description = "Building applications with LLMs through composability"
|
||||
optional = false
|
||||
python-versions = ">=3.8.1,<4.0"
|
||||
@ -1798,8 +1796,8 @@ files = []
|
||||
develop = true
|
||||
|
||||
[package.dependencies]
|
||||
langchain = "^0.1.15"
|
||||
langchain-core = "^0.1.41"
|
||||
langchain-community = "^0.2"
|
||||
langchain-core = "^0.2"
|
||||
|
||||
[package.extras]
|
||||
extended-testing = ["faker (>=19.3.1,<20.0.0)", "jinja2 (>=3,<4)", "pandas (>=2.0.1,<3.0.0)", "presidio-analyzer (>=2.2.352,<3.0.0)", "presidio-anonymizer (>=2.2.352,<3.0.0)", "sentence-transformers (>=2,<3)", "tabulate (>=0.9.0,<0.10.0)", "vowpal-wabbit-next (==0.6.0)"]
|
||||
@ -1810,7 +1808,7 @@ url = "libs/experimental"
|
||||
|
||||
[[package]]
|
||||
name = "langchain-openai"
|
||||
version = "0.1.4"
|
||||
version = "0.1.7"
|
||||
description = "An integration package connecting OpenAI and LangChain"
|
||||
optional = false
|
||||
python-versions = ">=3.8.1,<4.0"
|
||||
@ -1818,9 +1816,9 @@ files = []
|
||||
develop = true
|
||||
|
||||
[package.dependencies]
|
||||
langchain-core = "^0.1.46"
|
||||
openai = "^1.10.0"
|
||||
tiktoken = ">=0.5.2,<1"
|
||||
langchain-core = ">=0.2.0,<0.3"
|
||||
openai = "^1.24.0"
|
||||
tiktoken = ">=0.7,<1"
|
||||
|
||||
[package.source]
|
||||
type = "directory"
|
||||
@ -1828,7 +1826,7 @@ url = "libs/partners/openai"
|
||||
|
||||
[[package]]
|
||||
name = "langchain-text-splitters"
|
||||
version = "0.0.1"
|
||||
version = "0.2.0"
|
||||
description = "LangChain text splitting utilities"
|
||||
optional = false
|
||||
python-versions = ">=3.8.1,<4.0"
|
||||
@ -1836,7 +1834,7 @@ files = []
|
||||
develop = true
|
||||
|
||||
[package.dependencies]
|
||||
langchain-core = "^0.1.28"
|
||||
langchain-core = "^0.2.0"
|
||||
|
||||
[package.extras]
|
||||
extended-testing = ["beautifulsoup4 (>=4.12.3,<5.0.0)", "lxml (>=4.9.3,<6.0)"]
|
||||
@ -2475,13 +2473,13 @@ testing = ["matplotlib", "pytest", "pytest-cov"]
|
||||
|
||||
[[package]]
|
||||
name = "openai"
|
||||
version = "1.16.1"
|
||||
version = "1.30.1"
|
||||
description = "The official Python library for the openai API"
|
||||
optional = false
|
||||
python-versions = ">=3.7.1"
|
||||
files = [
|
||||
{file = "openai-1.16.1-py3-none-any.whl", hash = "sha256:77ef3db6110071f7154859e234250fb945a36554207a30a4491092eadb73fcb5"},
|
||||
{file = "openai-1.16.1.tar.gz", hash = "sha256:58922c785d167458b46e3c76e7b1bc2306f313ee9b71791e84cbf590abe160f2"},
|
||||
{file = "openai-1.30.1-py3-none-any.whl", hash = "sha256:c9fb3c3545c118bbce8deb824397b9433a66d0d0ede6a96f7009c95b76de4a46"},
|
||||
{file = "openai-1.30.1.tar.gz", hash = "sha256:4f85190e577cba0b066e1950b8eb9b11d25bc7ebcc43a86b326ce1bfa564ec74"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
@ -3003,7 +3001,6 @@ files = [
|
||||
{file = "PyYAML-6.0.1-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:69b023b2b4daa7548bcfbd4aa3da05b3a74b772db9e23b982788168117739938"},
|
||||
{file = "PyYAML-6.0.1-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:81e0b275a9ecc9c0c0c07b4b90ba548307583c125f54d5b6946cfee6360c733d"},
|
||||
{file = "PyYAML-6.0.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:ba336e390cd8e4d1739f42dfe9bb83a3cc2e80f567d8805e11b46f4a943f5515"},
|
||||
{file = "PyYAML-6.0.1-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:326c013efe8048858a6d312ddd31d56e468118ad4cdeda36c719bf5bb6192290"},
|
||||
{file = "PyYAML-6.0.1-cp310-cp310-win32.whl", hash = "sha256:bd4af7373a854424dabd882decdc5579653d7868b8fb26dc7d0e99f823aa5924"},
|
||||
{file = "PyYAML-6.0.1-cp310-cp310-win_amd64.whl", hash = "sha256:fd1592b3fdf65fff2ad0004b5e363300ef59ced41c2e6b3a99d4089fa8c5435d"},
|
||||
{file = "PyYAML-6.0.1-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:6965a7bc3cf88e5a1c3bd2e0b5c22f8d677dc88a455344035f03399034eb3007"},
|
||||
@ -3011,16 +3008,8 @@ files = [
|
||||
{file = "PyYAML-6.0.1-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:42f8152b8dbc4fe7d96729ec2b99c7097d656dc1213a3229ca5383f973a5ed6d"},
|
||||
{file = "PyYAML-6.0.1-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:062582fca9fabdd2c8b54a3ef1c978d786e0f6b3a1510e0ac93ef59e0ddae2bc"},
|
||||
{file = "PyYAML-6.0.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:d2b04aac4d386b172d5b9692e2d2da8de7bfb6c387fa4f801fbf6fb2e6ba4673"},
|
||||
{file = "PyYAML-6.0.1-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:e7d73685e87afe9f3b36c799222440d6cf362062f78be1013661b00c5c6f678b"},
|
||||
{file = "PyYAML-6.0.1-cp311-cp311-win32.whl", hash = "sha256:1635fd110e8d85d55237ab316b5b011de701ea0f29d07611174a1b42f1444741"},
|
||||
{file = "PyYAML-6.0.1-cp311-cp311-win_amd64.whl", hash = "sha256:bf07ee2fef7014951eeb99f56f39c9bb4af143d8aa3c21b1677805985307da34"},
|
||||
{file = "PyYAML-6.0.1-cp312-cp312-macosx_10_9_x86_64.whl", hash = "sha256:855fb52b0dc35af121542a76b9a84f8d1cd886ea97c84703eaa6d88e37a2ad28"},
|
||||
{file = "PyYAML-6.0.1-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:40df9b996c2b73138957fe23a16a4f0ba614f4c0efce1e9406a184b6d07fa3a9"},
|
||||
{file = "PyYAML-6.0.1-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:a08c6f0fe150303c1c6b71ebcd7213c2858041a7e01975da3a99aed1e7a378ef"},
|
||||
{file = "PyYAML-6.0.1-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:6c22bec3fbe2524cde73d7ada88f6566758a8f7227bfbf93a408a9d86bcc12a0"},
|
||||
{file = "PyYAML-6.0.1-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:8d4e9c88387b0f5c7d5f281e55304de64cf7f9c0021a3525bd3b1c542da3b0e4"},
|
||||
{file = "PyYAML-6.0.1-cp312-cp312-win32.whl", hash = "sha256:d483d2cdf104e7c9fa60c544d92981f12ad66a457afae824d146093b8c294c54"},
|
||||
{file = "PyYAML-6.0.1-cp312-cp312-win_amd64.whl", hash = "sha256:0d3304d8c0adc42be59c5f8a4d9e3d7379e6955ad754aa9d6ab7a398b59dd1df"},
|
||||
{file = "PyYAML-6.0.1-cp36-cp36m-macosx_10_9_x86_64.whl", hash = "sha256:50550eb667afee136e9a77d6dc71ae76a44df8b3e51e41b77f6de2932bfe0f47"},
|
||||
{file = "PyYAML-6.0.1-cp36-cp36m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:1fe35611261b29bd1de0070f0b2f47cb6ff71fa6595c077e42bd0c419fa27b98"},
|
||||
{file = "PyYAML-6.0.1-cp36-cp36m-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:704219a11b772aea0d8ecd7058d0082713c3562b4e271b849ad7dc4a5c90c13c"},
|
||||
@ -3037,7 +3026,6 @@ files = [
|
||||
{file = "PyYAML-6.0.1-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:a0cd17c15d3bb3fa06978b4e8958dcdc6e0174ccea823003a106c7d4d7899ac5"},
|
||||
{file = "PyYAML-6.0.1-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:28c119d996beec18c05208a8bd78cbe4007878c6dd15091efb73a30e90539696"},
|
||||
{file = "PyYAML-6.0.1-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:7e07cbde391ba96ab58e532ff4803f79c4129397514e1413a7dc761ccd755735"},
|
||||
{file = "PyYAML-6.0.1-cp38-cp38-musllinux_1_1_x86_64.whl", hash = "sha256:49a183be227561de579b4a36efbb21b3eab9651dd81b1858589f796549873dd6"},
|
||||
{file = "PyYAML-6.0.1-cp38-cp38-win32.whl", hash = "sha256:184c5108a2aca3c5b3d3bf9395d50893a7ab82a38004c8f61c258d4428e80206"},
|
||||
{file = "PyYAML-6.0.1-cp38-cp38-win_amd64.whl", hash = "sha256:1e2722cc9fbb45d9b87631ac70924c11d3a401b2d7f410cc0e3bbf249f2dca62"},
|
||||
{file = "PyYAML-6.0.1-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:9eb6caa9a297fc2c2fb8862bc5370d0303ddba53ba97e71f08023b6cd73d16a8"},
|
||||
@ -3045,7 +3033,6 @@ files = [
|
||||
{file = "PyYAML-6.0.1-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:5773183b6446b2c99bb77e77595dd486303b4faab2b086e7b17bc6bef28865f6"},
|
||||
{file = "PyYAML-6.0.1-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:b786eecbdf8499b9ca1d697215862083bd6d2a99965554781d0d8d1ad31e13a0"},
|
||||
{file = "PyYAML-6.0.1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:bc1bf2925a1ecd43da378f4db9e4f799775d6367bdb94671027b73b393a7c42c"},
|
||||
{file = "PyYAML-6.0.1-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:04ac92ad1925b2cff1db0cfebffb6ffc43457495c9b3c39d3fcae417d7125dc5"},
|
||||
{file = "PyYAML-6.0.1-cp39-cp39-win32.whl", hash = "sha256:faca3bdcf85b2fc05d06ff3fbc1f83e1391b3e724afa3feba7d13eeab355484c"},
|
||||
{file = "PyYAML-6.0.1-cp39-cp39-win_amd64.whl", hash = "sha256:510c9deebc5c0225e8c96813043e62b680ba2f9c50a08d3724c7f28a747d1486"},
|
||||
{file = "PyYAML-6.0.1.tar.gz", hash = "sha256:bfdf460b1736c775f2ba9f6a92bca30bc2095067b8a9d77876d1fad6cc3b4a43"},
|
||||
@ -3962,47 +3949,47 @@ typing = ["mypy (>=1.6,<2.0)", "traitlets (>=5.11.1)"]
|
||||
|
||||
[[package]]
|
||||
name = "tiktoken"
|
||||
version = "0.6.0"
|
||||
version = "0.7.0"
|
||||
description = "tiktoken is a fast BPE tokeniser for use with OpenAI's models"
|
||||
optional = false
|
||||
python-versions = ">=3.8"
|
||||
files = [
|
||||
{file = "tiktoken-0.6.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:277de84ccd8fa12730a6b4067456e5cf72fef6300bea61d506c09e45658d41ac"},
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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||||
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||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
{file = "tiktoken-0.6.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:b2048e1086b48e3c8c6e2ceeac866561374cd57a84622fa49a6b245ffecb7744"},
|
||||
{file = "tiktoken-0.6.0-cp39-cp39-musllinux_1_1_aarch64.whl", hash = "sha256:07f229a5eb250b6403a61200199cecf0aac4aa23c3ecc1c11c1ca002cbb8f159"},
|
||||
{file = "tiktoken-0.6.0-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:432aa3be8436177b0db5a2b3e7cc28fd6c693f783b2f8722539ba16a867d0c6a"},
|
||||
{file = "tiktoken-0.6.0-cp39-cp39-win_amd64.whl", hash = "sha256:8bfe8a19c8b5c40d121ee7938cd9c6a278e5b97dc035fd61714b4f0399d2f7a1"},
|
||||
{file = "tiktoken-0.6.0.tar.gz", hash = "sha256:ace62a4ede83c75b0374a2ddfa4b76903cf483e9cb06247f566be3bf14e6beed"},
|
||||
{file = "tiktoken-0.7.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:485f3cc6aba7c6b6ce388ba634fbba656d9ee27f766216f45146beb4ac18b25f"},
|
||||
{file = "tiktoken-0.7.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:e54be9a2cd2f6d6ffa3517b064983fb695c9a9d8aa7d574d1ef3c3f931a99225"},
|
||||
{file = "tiktoken-0.7.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:79383a6e2c654c6040e5f8506f3750db9ddd71b550c724e673203b4f6b4b4590"},
|
||||
{file = "tiktoken-0.7.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:5d4511c52caacf3c4981d1ae2df85908bd31853f33d30b345c8b6830763f769c"},
|
||||
{file = "tiktoken-0.7.0-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:13c94efacdd3de9aff824a788353aa5749c0faee1fbe3816df365ea450b82311"},
|
||||
{file = "tiktoken-0.7.0-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:8e58c7eb29d2ab35a7a8929cbeea60216a4ccdf42efa8974d8e176d50c9a3df5"},
|
||||
{file = "tiktoken-0.7.0-cp310-cp310-win_amd64.whl", hash = "sha256:21a20c3bd1dd3e55b91c1331bf25f4af522c525e771691adbc9a69336fa7f702"},
|
||||
{file = "tiktoken-0.7.0-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:10c7674f81e6e350fcbed7c09a65bca9356eaab27fb2dac65a1e440f2bcfe30f"},
|
||||
{file = "tiktoken-0.7.0-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:084cec29713bc9d4189a937f8a35dbdfa785bd1235a34c1124fe2323821ee93f"},
|
||||
{file = "tiktoken-0.7.0-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:811229fde1652fedcca7c6dfe76724d0908775b353556d8a71ed74d866f73f7b"},
|
||||
{file = "tiktoken-0.7.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:86b6e7dc2e7ad1b3757e8a24597415bafcfb454cebf9a33a01f2e6ba2e663992"},
|
||||
{file = "tiktoken-0.7.0-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:1063c5748be36344c7e18c7913c53e2cca116764c2080177e57d62c7ad4576d1"},
|
||||
{file = "tiktoken-0.7.0-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:20295d21419bfcca092644f7e2f2138ff947a6eb8cfc732c09cc7d76988d4a89"},
|
||||
{file = "tiktoken-0.7.0-cp311-cp311-win_amd64.whl", hash = "sha256:959d993749b083acc57a317cbc643fb85c014d055b2119b739487288f4e5d1cb"},
|
||||
{file = "tiktoken-0.7.0-cp312-cp312-macosx_10_9_x86_64.whl", hash = "sha256:71c55d066388c55a9c00f61d2c456a6086673ab7dec22dd739c23f77195b1908"},
|
||||
{file = "tiktoken-0.7.0-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:09ed925bccaa8043e34c519fbb2f99110bd07c6fd67714793c21ac298e449410"},
|
||||
{file = "tiktoken-0.7.0-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:03c6c40ff1db0f48a7b4d2dafeae73a5607aacb472fa11f125e7baf9dce73704"},
|
||||
{file = "tiktoken-0.7.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:d20b5c6af30e621b4aca094ee61777a44118f52d886dbe4f02b70dfe05c15350"},
|
||||
{file = "tiktoken-0.7.0-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:d427614c3e074004efa2f2411e16c826f9df427d3c70a54725cae860f09e4bf4"},
|
||||
{file = "tiktoken-0.7.0-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:8c46d7af7b8c6987fac9b9f61041b452afe92eb087d29c9ce54951280f899a97"},
|
||||
{file = "tiktoken-0.7.0-cp312-cp312-win_amd64.whl", hash = "sha256:0bc603c30b9e371e7c4c7935aba02af5994a909fc3c0fe66e7004070858d3f8f"},
|
||||
{file = "tiktoken-0.7.0-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:2398fecd38c921bcd68418675a6d155fad5f5e14c2e92fcf5fe566fa5485a858"},
|
||||
{file = "tiktoken-0.7.0-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:8f5f6afb52fb8a7ea1c811e435e4188f2bef81b5e0f7a8635cc79b0eef0193d6"},
|
||||
{file = "tiktoken-0.7.0-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:861f9ee616766d736be4147abac500732b505bf7013cfaf019b85892637f235e"},
|
||||
{file = "tiktoken-0.7.0-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:54031f95c6939f6b78122c0aa03a93273a96365103793a22e1793ee86da31685"},
|
||||
{file = "tiktoken-0.7.0-cp38-cp38-musllinux_1_2_aarch64.whl", hash = "sha256:fffdcb319b614cf14f04d02a52e26b1d1ae14a570f90e9b55461a72672f7b13d"},
|
||||
{file = "tiktoken-0.7.0-cp38-cp38-musllinux_1_2_x86_64.whl", hash = "sha256:c72baaeaefa03ff9ba9688624143c858d1f6b755bb85d456d59e529e17234769"},
|
||||
{file = "tiktoken-0.7.0-cp38-cp38-win_amd64.whl", hash = "sha256:131b8aeb043a8f112aad9f46011dced25d62629091e51d9dc1adbf4a1cc6aa98"},
|
||||
{file = "tiktoken-0.7.0-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:cabc6dc77460df44ec5b879e68692c63551ae4fae7460dd4ff17181df75f1db7"},
|
||||
{file = "tiktoken-0.7.0-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:8d57f29171255f74c0aeacd0651e29aa47dff6f070cb9f35ebc14c82278f3b25"},
|
||||
{file = "tiktoken-0.7.0-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:2ee92776fdbb3efa02a83f968c19d4997a55c8e9ce7be821ceee04a1d1ee149c"},
|
||||
{file = "tiktoken-0.7.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:e215292e99cb41fbc96988ef62ea63bb0ce1e15f2c147a61acc319f8b4cbe5bf"},
|
||||
{file = "tiktoken-0.7.0-cp39-cp39-musllinux_1_2_aarch64.whl", hash = "sha256:8a81bac94769cab437dd3ab0b8a4bc4e0f9cf6835bcaa88de71f39af1791727a"},
|
||||
{file = "tiktoken-0.7.0-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:d6d73ea93e91d5ca771256dfc9d1d29f5a554b83821a1dc0891987636e0ae226"},
|
||||
{file = "tiktoken-0.7.0-cp39-cp39-win_amd64.whl", hash = "sha256:2bcb28ddf79ffa424f171dfeef9a4daff61a94c631ca6813f43967cb263b83b9"},
|
||||
{file = "tiktoken-0.7.0.tar.gz", hash = "sha256:1077266e949c24e0291f6c350433c6f0971365ece2b173a23bc3b9f9defef6b6"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
|
||||
Loading…
Reference in New Issue
Block a user