index int64 0 50.7k | project_path stringclasses 279
values | completion_path stringlengths 57 199 | signature_postion stringlengths 3 11 | class_position stringlengths 3 11 | function_name stringlengths 1 62 | class_name stringlengths 0 55 | body_position stringlengths 3 11 | body_position_with_comments stringlengths 3 11 | masked_class stringlengths 14 8.32k | masked_class_with_comment stringlengths 14 8.32k | func_body stringlengths 9 6.72k | func_body_with_comment stringlengths 9 6.72k | len_func_body int64 1 643 | len_input int64 10 2.02k | len_output int64 4 1.9k | total int64 20 2.05k | file_code stringlengths 14 442k | file_code_with_comment stringlengths 14 442k |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
9,080 | /home/hieuvd/dung_repo/raw/stars_01/allenai_allennlp/allennlp | /home/hieuvd/dung_repo/raw/stars_01/allenai_allennlp/allennlp/allennlp/data/data_loaders/multitask_epoch_sampler.py | 61,62 | 49,66 | get_task_proportions | WeightedSampler | 62,66 | 62,66 | @MultiTaskEpochSampler.register("weighted")
class WeightedSampler(MultiTaskEpochSampler):
"""
Returns a weighted distribution over datasets at every epoch, where every
task has a weight.
Registered as a `MultiTaskEpochSampler` with name "weighted".
"""
def __init__(self, weights: Dict[str, flo... | @MultiTaskEpochSampler.register("weighted")
class WeightedSampler(MultiTaskEpochSampler):
"""
Returns a weighted distribution over datasets at every epoch, where every
task has a weight.
Registered as a `MultiTaskEpochSampler` with name "weighted".
"""
def __init__(self, weights: Dict[str, flo... | total = sum(self.weights[task] for task in data_loaders.keys())
return {task: self.weights[task] / total for task in data_loaders.keys()}
| total = sum(self.weights[task] for task in data_loaders.keys())
return {task: self.weights[task] / total for task in data_loaders.keys()}
| 16 | 149 | 55 | 204 | from typing import Any, Dict, Mapping
from allennlp.common.registrable import Registrable
from allennlp.data.data_loaders.data_loader import DataLoader
class MultiTaskEpochSampler(Registrable):
"""
A class that determines with what proportion each dataset should be sampled for a given epoch.
This is used... | from typing import Any, Dict, Mapping
from allennlp.common.registrable import Registrable
from allennlp.data.data_loaders.data_loader import DataLoader
class MultiTaskEpochSampler(Registrable):
"""
A class that determines with what proportion each dataset should be sampled for a given epoch.
This is used... |
9,084 | /home/hieuvd/dung_repo/raw/stars_01/allenai_allennlp/allennlp | /home/hieuvd/dung_repo/raw/stars_01/allenai_allennlp/allennlp/allennlp/data/dataset_readers/interleaving_dataset_reader.py | 91,92 | 18,122 | _read | InterleavingDatasetReader | 92,116 | 92,116 | @DatasetReader.register("interleaving")
class InterleavingDatasetReader(DatasetReader):
"""
A `DatasetReader` that wraps multiple other dataset readers,
and interleaves their instances, adding a `MetadataField` to
indicate the provenance of each instance.
Unlike most of our other dataset readers, h... | @DatasetReader.register("interleaving")
class InterleavingDatasetReader(DatasetReader):
"""
A `DatasetReader` that wraps multiple other dataset readers,
and interleaves their instances, adding a `MetadataField` to
indicate the provenance of each instance.
Unlike most of our other dataset readers, h... | if isinstance(file_path, str):
try:
file_paths = json.loads(file_path)
except json.JSONDecodeError:
raise ConfigurationError(
"the file_path for the InterleavingDatasetReader "
"needs to be a JSON-serialized dictiona... | if isinstance(file_path, str):
try:
file_paths = json.loads(file_path)
except json.JSONDecodeError:
raise ConfigurationError(
"the file_path for the InterleavingDatasetReader "
"needs to be a JSON-serialized dictiona... | 70 | 1,012 | 273 | 1,285 | from typing import Dict, Mapping, Iterable, Union, Optional
import json
from allennlp.common.checks import ConfigurationError
from allennlp.data.dataset_readers.dataset_reader import (
DatasetReader,
PathOrStr,
WorkerInfo,
DistributedInfo,
)
from allennlp.data.fields import MetadataField
from allennlp... | from typing import Dict, Mapping, Iterable, Union, Optional
import json
from allennlp.common.checks import ConfigurationError
from allennlp.data.dataset_readers.dataset_reader import (
DatasetReader,
PathOrStr,
WorkerInfo,
DistributedInfo,
)
from allennlp.data.fields import MetadataField
from allennlp... |
9,085 | /home/hieuvd/dung_repo/raw/stars_01/allenai_allennlp/allennlp | /home/hieuvd/dung_repo/raw/stars_01/allenai_allennlp/allennlp/allennlp/data/dataset_readers/multitask.py | 36,42 | 12,47 | read | MultiTaskDatasetReader | 42,47 | 42,47 | @DatasetReader.register("multitask")
class MultiTaskDatasetReader(DatasetReader):
"""
This `DatasetReader` simply collects a dictionary of other `DatasetReaders`. It is designed for
a different class (the `MultiTaskDataLoader`) to actually read from each of the underlying
dataset readers, and so this r... | @DatasetReader.register("multitask")
class MultiTaskDatasetReader(DatasetReader):
"""
This `DatasetReader` simply collects a dictionary of other `DatasetReaders`. It is designed for
a different class (the `MultiTaskDataLoader`) to actually read from each of the underlying
dataset readers, and so this r... | if force_task is None:
raise RuntimeError("This class is not designed to be called like this.")
return self.readers[force_task].read(file_paths)
| if force_task is None:
raise RuntimeError("This class is not designed to be called like this.")
return self.readers[force_task].read(file_paths)
| 17 | 394 | 51 | 445 | from os import PathLike
from typing import Dict, Iterator, Union, Optional
from allennlp.data.instance import Instance
from allennlp.data.dataset_readers.dataset_reader import (
DatasetReader,
WorkerInfo,
DatasetReaderInput,
)
@DatasetReader.register("multitask")
class MultiTaskDatasetReader(DatasetReade... | from os import PathLike
from typing import Dict, Iterator, Union, Optional
from allennlp.data.instance import Instance
from allennlp.data.dataset_readers.dataset_reader import (
DatasetReader,
WorkerInfo,
DatasetReaderInput,
)
@DatasetReader.register("multitask")
class MultiTaskDatasetReader(DatasetReade... |
9,086 | /home/hieuvd/dung_repo/raw/stars_01/allenai_allennlp/allennlp | /home/hieuvd/dung_repo/raw/stars_01/allenai_allennlp/allennlp/allennlp/data/dataset_readers/multitask.py | 71,72 | 47,80 | text_to_instance | _MultitaskDatasetReaderShim | 72,78 | 72,78 | @DatasetReader.register("multitask_shim")
class _MultitaskDatasetReaderShim(DatasetReader):
"""This dataset reader wraps another dataset reader and adds the name of the "task" into
each instance as a metadata field. You should not have to use this yourself."""
def __init__(self, inner: DatasetReader, head:... | @DatasetReader.register("multitask_shim")
class _MultitaskDatasetReaderShim(DatasetReader):
"""This dataset reader wraps another dataset reader and adds the name of the "task" into
each instance as a metadata field. You should not have to use this yourself."""
def __init__(self, inner: DatasetReader, head:... | from allennlp.data.fields import MetadataField
instance = self.inner.text_to_instance(*inputs)
instance.add_field("task", MetadataField(self.head))
return instance
| from allennlp.data.fields import MetadataField
instance = self.inner.text_to_instance(*inputs)
instance.add_field("task", MetadataField(self.head))
return instance
| 11 | 326 | 61 | 387 | from os import PathLike
from typing import Dict, Iterator, Union, Optional
from allennlp.data.instance import Instance
from allennlp.data.dataset_readers.dataset_reader import (
DatasetReader,
WorkerInfo,
DatasetReaderInput,
)
@DatasetReader.register("multitask")
class MultiTaskDatasetReader(DatasetReade... | from os import PathLike
from typing import Dict, Iterator, Union, Optional
from allennlp.data.instance import Instance
from allennlp.data.dataset_readers.dataset_reader import (
DatasetReader,
WorkerInfo,
DatasetReaderInput,
)
@DatasetReader.register("multitask")
class MultiTaskDatasetReader(DatasetReade... |
9,087 | /home/hieuvd/dung_repo/raw/stars_01/allenai_allennlp/allennlp | /home/hieuvd/dung_repo/raw/stars_01/allenai_allennlp/allennlp/allennlp/data/dataset_readers/sequence_tagging.py | 65,66 | 17,106 | _read | SequenceTaggingDatasetReader | 66,86 | 66,86 | @DatasetReader.register("sequence_tagging")
class SequenceTaggingDatasetReader(DatasetReader):
"""
Reads instances from a pretokenised file where each line is in the following format:
```
WORD###TAG [TAB] WORD###TAG [TAB] ..... \n
```
and converts it into a `Dataset` suitable for sequence tagg... | @DatasetReader.register("sequence_tagging")
class SequenceTaggingDatasetReader(DatasetReader):
"""
Reads instances from a pretokenised file where each line is in the following format:
```
WORD###TAG [TAB] WORD###TAG [TAB] ..... \n
```
and converts it into a `Dataset` suitable for sequence tagg... | # if `file_path` is a URL, redirect to the cache
file_path = cached_path(file_path)
with open(file_path, "r") as data_file:
logger.info("Reading instances from lines in file at: %s", file_path)
for line in self.shard_iterable(data_file):
line = line.strip... | # if `file_path` is a URL, redirect to the cache
file_path = cached_path(file_path)
with open(file_path, "r") as data_file:
logger.info("Reading instances from lines in file at: %s", file_path)
for line in self.shard_iterable(data_file):
line = line.strip... | 71 | 837 | 237 | 1,074 | from typing import Dict, List, Any
import logging
from allennlp.common.file_utils import cached_path
from allennlp.data.dataset_readers.dataset_reader import DatasetReader
from allennlp.data.fields import TextField, SequenceLabelField, MetadataField, Field
from allennlp.data.instance import Instance
from allennlp.dat... | from typing import Dict, List, Any
import logging
from allennlp.common.file_utils import cached_path
from allennlp.data.dataset_readers.dataset_reader import DatasetReader
from allennlp.data.fields import TextField, SequenceLabelField, MetadataField, Field
from allennlp.data.instance import Instance
from allennlp.dat... |
9,088 | /home/hieuvd/dung_repo/raw/stars_01/allenai_allennlp/allennlp | /home/hieuvd/dung_repo/raw/stars_01/allenai_allennlp/allennlp/allennlp/data/dataset_readers/sharded_dataset_reader.py | 59,60 | 16,87 | _read | ShardedDatasetReader | 60,87 | 60,87 | @DatasetReader.register("sharded")
class ShardedDatasetReader(DatasetReader):
"""
Wraps another dataset reader and uses it to read from multiple input files.
Note that in this case the `file_path` passed to `read()` should either be a glob path
or a path or URL to an archive file ('.zip' or '.tar.gz').... | @DatasetReader.register("sharded")
class ShardedDatasetReader(DatasetReader):
"""
Wraps another dataset reader and uses it to read from multiple input files.
Note that in this case the `file_path` passed to `read()` should either be a glob path
or a path or URL to an archive file ('.zip' or '.tar.gz').... | try:
maybe_extracted_archive = cached_path(file_path, extract_archive=True)
if not os.path.isdir(maybe_extracted_archive):
# This isn't a directory, so `file_path` is just a file.
raise ConfigurationError(f"{file_path} should be an archive or directory")
... | try:
maybe_extracted_archive = cached_path(file_path, extract_archive=True)
if not os.path.isdir(maybe_extracted_archive):
# This isn't a directory, so `file_path` is just a file.
raise ConfigurationError(f"{file_path} should be an archive or directory")
... | 110 | 513 | 376 | 889 | import glob
import logging
import os
from typing import Iterable
from allennlp.common.checks import ConfigurationError
from allennlp.common.file_utils import cached_path
from allennlp.data.dataset_readers.dataset_reader import DatasetReader, PathOrStr
from allennlp.data.instance import Instance
logger = logging.get... | import glob
import logging
import os
from typing import Iterable
from allennlp.common.checks import ConfigurationError
from allennlp.common.file_utils import cached_path
from allennlp.data.dataset_readers.dataset_reader import DatasetReader, PathOrStr
from allennlp.data.instance import Instance
logger = logging.get... |
9,089 | /home/hieuvd/dung_repo/raw/stars_01/allenai_allennlp/allennlp | /home/hieuvd/dung_repo/raw/stars_01/allenai_allennlp/allennlp/allennlp/data/dataset_readers/text_classification_json.py | 143,144 | 16,149 | apply_token_indexers | TextClassificationJsonReader | 144,149 | 144,149 | @DatasetReader.register("text_classification_json")
class TextClassificationJsonReader(DatasetReader):
"""
Reads tokens and their labels from a labeled text classification dataset.
The output of `read` is a list of `Instance` s with the fields:
tokens : `TextField` and
label : `LabelField`
... | @DatasetReader.register("text_classification_json")
class TextClassificationJsonReader(DatasetReader):
"""
Reads tokens and their labels from a labeled text classification dataset.
The output of `read` is a list of `Instance` s with the fields:
tokens : `TextField` and
label : `LabelField`
... | if self._segment_sentences:
for text_field in instance.fields["tokens"]: # type: ignore
text_field._token_indexers = self._token_indexers
else:
instance.fields["tokens"]._token_indexers = self._token_indexers # type: ignore
| if self._segment_sentences:
for text_field in instance.fields["tokens"]: # type: ignore
text_field._token_indexers = self._token_indexers
else:
instance.fields["tokens"]._token_indexers = self._token_indexers # type: ignore
| 19 | 1,495 | 83 | 1,578 | from typing import Dict, List, Union
import logging
import json
from allennlp.common.file_utils import cached_path
from allennlp.data.dataset_readers.dataset_reader import DatasetReader
from allennlp.data.fields import LabelField, TextField, Field, ListField
from allennlp.data.instance import Instance
from allennlp.da... | from typing import Dict, List, Union
import logging
import json
from allennlp.common.file_utils import cached_path
from allennlp.data.dataset_readers.dataset_reader import DatasetReader
from allennlp.data.fields import LabelField, TextField, Field, ListField
from allennlp.data.instance import Instance
from allennlp.da... |
9,090 | /home/hieuvd/dung_repo/raw/stars_01/allenai_allennlp/allennlp | /home/hieuvd/dung_repo/raw/stars_01/allenai_allennlp/allennlp/allennlp/data/fields/flag_field.py | 18,19 | 7,46 | get_padding_lengths | FlagField | 19,21 | 19,21 | class FlagField(Field[Any]):
"""
A class representing a flag, which must be constant across all instances in a batch.
This will be passed to a `forward` method as a single value of whatever type you pass in.
"""
__slots__ = ["flag_value"]
def __init__(self, flag_value: Any) -> None:
se... | class FlagField(Field[Any]):
"""
A class representing a flag, which must be constant across all instances in a batch.
This will be passed to a `forward` method as a single value of whatever type you pass in.
"""
__slots__ = ["flag_value"]
def __init__(self, flag_value: Any) -> None:
se... | return {}
| return {}
| 2 | 409 | 7 | 416 | from typing import Any, Dict, List
from allennlp.data.fields.field import Field
class FlagField(Field[Any]):
"""
A class representing a flag, which must be constant across all instances in a batch.
This will be passed to a `forward` method as a single value of whatever type you pass in.
"""
__s... | from typing import Any, Dict, List
from allennlp.data.fields.field import Field
class FlagField(Field[Any]):
"""
A class representing a flag, which must be constant across all instances in a batch.
This will be passed to a `forward` method as a single value of whatever type you pass in.
"""
__s... |
9,091 | /home/hieuvd/dung_repo/raw/stars_01/allenai_allennlp/allennlp | /home/hieuvd/dung_repo/raw/stars_01/allenai_allennlp/allennlp/allennlp/data/fields/list_field.py | 95,96 | 10,116 | empty_field | ListField | 96,105 | 96,105 | class ListField(SequenceField[DataArray]):
"""
A `ListField` is a list of other fields. You would use this to represent, e.g., a list of
answer options that are themselves `TextFields`.
This field will get converted into a tensor that has one more mode than the items in the list.
If this is a list... | class ListField(SequenceField[DataArray]):
"""
A `ListField` is a list of other fields. You would use this to represent, e.g., a list of
answer options that are themselves `TextFields`.
This field will get converted into a tensor that has one more mode than the items in the list.
If this is a list... | # Our "empty" list field will actually have a single field in the list, so that we can
# correctly construct nested lists. For example, if we have a type that is
# `ListField[ListField[LabelField]]`, we need the top-level `ListField` to know to
# construct a `ListField[LabelField]` when... | # Our "empty" list field will actually have a single field in the list, so that we can
# correctly construct nested lists. For example, if we have a type that is
# `ListField[ListField[LabelField]]`, we need the top-level `ListField` to know to
# construct a `ListField[LabelField]` when... | 91 | 1,303 | 182 | 1,485 | from typing import Dict, List, Iterator, Sequence, Any
from allennlp.data.fields.field import DataArray, Field
from allennlp.data.vocabulary import Vocabulary
from allennlp.data.fields.sequence_field import SequenceField
from allennlp.common.util import pad_sequence_to_length
class ListField(SequenceField[DataArray... | from typing import Dict, List, Iterator, Sequence, Any
from allennlp.data.fields.field import DataArray, Field
from allennlp.data.vocabulary import Vocabulary
from allennlp.data.fields.sequence_field import SequenceField
from allennlp.common.util import pad_sequence_to_length
class ListField(SequenceField[DataArray... |
9,092 | /home/hieuvd/dung_repo/raw/stars_01/allenai_allennlp/allennlp | /home/hieuvd/dung_repo/raw/stars_01/allenai_allennlp/allennlp/allennlp/data/fields/metadata_field.py | 65,66 | 7,69 | human_readable_repr | MetadataField | 66,69 | 66,69 | class MetadataField(Field[DataArray], Mapping[str, Any]):
"""
A `MetadataField` is a `Field` that does not get converted into tensors. It just carries
side information that might be needed later on, for computing some third-party metric, or
outputting debugging information, or whatever else you need. ... | class MetadataField(Field[DataArray], Mapping[str, Any]):
"""
A `MetadataField` is a `Field` that does not get converted into tensors. It just carries
side information that might be needed later on, for computing some third-party metric, or
outputting debugging information, or whatever else you need. ... | if hasattr(self.metadata, "human_readable_repr"):
return self.metadata.human_readable_repr()
return self.metadata
| if hasattr(self.metadata, "human_readable_repr"):
return self.metadata.human_readable_repr()
return self.metadata
| 7 | 592 | 44 | 636 | from typing import Any, Dict, List, Mapping
from allennlp.data.fields.field import DataArray, Field
class MetadataField(Field[DataArray], Mapping[str, Any]):
"""
A `MetadataField` is a `Field` that does not get converted into tensors. It just carries
side information that might be needed later on, for ... | from typing import Any, Dict, List, Mapping
from allennlp.data.fields.field import DataArray, Field
class MetadataField(Field[DataArray], Mapping[str, Any]):
"""
A `MetadataField` is a `Field` that does not get converted into tensors. It just carries
side information that might be needed later on, for ... |
9,093 | /home/hieuvd/dung_repo/raw/stars_01/allenai_allennlp/allennlp | /home/hieuvd/dung_repo/raw/stars_01/allenai_allennlp/allennlp/allennlp/data/fields/sequence_field.py | 14,15 | 4,22 | sequence_length | SequenceField | 18,20 | 15,20 | class SequenceField(Field[DataArray]):
"""
A `SequenceField` represents a sequence of things. This class just adds a method onto
`Field`: :func:`sequence_length`. It exists so that `SequenceLabelField`, `IndexField` and other
similar `Fields` can have a single type to require, with a consistent API, w... | class SequenceField(Field[DataArray]):
"""
A `SequenceField` represents a sequence of things. This class just adds a method onto
`Field`: :func:`sequence_length`. It exists so that `SequenceLabelField`, `IndexField` and other
similar `Fields` can have a single type to require, with a consistent API, w... | raise NotImplementedError
| """
How many elements are there in this sequence?
"""
raise NotImplementedError
| 2 | 195 | 11 | 206 | from allennlp.data.fields.field import DataArray, Field
class SequenceField(Field[DataArray]):
"""
A `SequenceField` represents a sequence of things. This class just adds a method onto
`Field`: :func:`sequence_length`. It exists so that `SequenceLabelField`, `IndexField` and other
similar `Fields` c... | from allennlp.data.fields.field import DataArray, Field
class SequenceField(Field[DataArray]):
"""
A `SequenceField` represents a sequence of things. This class just adds a method onto
`Field`: :func:`sequence_length`. It exists so that `SequenceLabelField`, `IndexField` and other
similar `Fields` c... |
9,094 | /home/hieuvd/dung_repo/raw/stars_01/allenai_allennlp/allennlp | /home/hieuvd/dung_repo/raw/stars_01/allenai_allennlp/allennlp/allennlp/data/instance.py | 88,91 | 8,123 | as_tensor_dict | Instance | 99,105 | 91,105 | class Instance(Mapping[str, Field]):
"""
An `Instance` is a collection of :class:`~allennlp.data.fields.field.Field` objects,
specifying the inputs and outputs to
some model. We don't make a distinction between inputs and outputs here, though - all
operations are done on all fields, and when we ret... | class Instance(Mapping[str, Field]):
"""
An `Instance` is a collection of :class:`~allennlp.data.fields.field.Field` objects,
specifying the inputs and outputs to
some model. We don't make a distinction between inputs and outputs here, though - all
operations are done on all fields, and when we ret... | padding_lengths = padding_lengths or self.get_padding_lengths()
tensors = {}
for field_name, field in self.fields.items():
tensors[field_name] = field.as_tensor(padding_lengths[field_name])
return tensors
| """
Pads each `Field` in this instance to the lengths given in `padding_lengths` (which is
keyed by field name, then by padding key, the same as the return value in
:func:`get_padding_lengths`), returning a list of torch tensors for each field.
If `padding_lengths` is omitted, w... | 18 | 1,303 | 79 | 1,382 | from typing import Dict, MutableMapping, Mapping
from allennlp.data.fields.field import DataArray, Field
from allennlp.data.vocabulary import Vocabulary
from allennlp.common.util import JsonDict
class Instance(Mapping[str, Field]):
"""
An `Instance` is a collection of :class:`~allennlp.data.fields.field.Fiel... | from typing import Dict, MutableMapping, Mapping
from allennlp.data.fields.field import DataArray, Field
from allennlp.data.vocabulary import Vocabulary
from allennlp.common.util import JsonDict
class Instance(Mapping[str, Field]):
"""
An `Instance` is a collection of :class:`~allennlp.data.fields.field.Fiel... |
9,095 | /home/hieuvd/dung_repo/raw/stars_01/allenai_allennlp/allennlp | /home/hieuvd/dung_repo/raw/stars_01/allenai_allennlp/allennlp/allennlp/data/samplers/batch_sampler.py | 11,12 | 7,20 | get_num_batches | BatchSampler | 12,14 | 12,14 | class BatchSampler(Registrable):
def get_batch_indices(self, instances: Sequence[Instance]) -> Iterable[List[int]]:
raise NotImplementedError
def get_num_batches(self, instances: Sequence[Instance]) -> int:
FILL_FUNC_BODY def get_batch_size(self) -> Optional[int]:
"""
Not all `BatchS... | class BatchSampler(Registrable):
def get_batch_indices(self, instances: Sequence[Instance]) -> Iterable[List[int]]:
raise NotImplementedError
def get_num_batches(self, instances: Sequence[Instance]) -> int:
FILL_FUNC_BODY def get_batch_size(self) -> Optional[int]:
"""
Not all `BatchS... | raise NotImplementedError
| raise NotImplementedError
| 2 | 139 | 11 | 150 | from typing import List, Iterable, Sequence, Optional
from allennlp.common.registrable import Registrable
from allennlp.data.instance import Instance
class BatchSampler(Registrable):
def get_batch_indices(self, instances: Sequence[Instance]) -> Iterable[List[int]]:
raise NotImplementedError
def get_... | from typing import List, Iterable, Sequence, Optional
from allennlp.common.registrable import Registrable
from allennlp.data.instance import Instance
class BatchSampler(Registrable):
def get_batch_indices(self, instances: Sequence[Instance]) -> Iterable[List[int]]:
raise NotImplementedError
def get_... |
9,096 | /home/hieuvd/dung_repo/raw/stars_01/allenai_allennlp/allennlp | /home/hieuvd/dung_repo/raw/stars_01/allenai_allennlp/allennlp/allennlp/data/samplers/bucket_batch_sampler.py | 15,16 | 1,173 | add_noise_to_value | 16,21 | 16,21 | import logging
import math
from typing import List, Iterable, Tuple, Sequence, Optional
import random
from allennlp.common.checks import ConfigurationError
from allennlp.common.util import lazy_groups_of
from allennlp.data.instance import Instance
from allennlp.data.samplers.batch_sampler import BatchSampler
logger ... | import logging
import math
from typing import List, Iterable, Tuple, Sequence, Optional
import random
from allennlp.common.checks import ConfigurationError
from allennlp.common.util import lazy_groups_of
from allennlp.data.instance import Instance
from allennlp.data.samplers.batch_sampler import BatchSampler
logger ... | noise_value = value * noise_param
noise = random.uniform(-noise_value, noise_value)
return value + noise
| noise_value = value * noise_param
noise = random.uniform(-noise_value, noise_value)
return value + noise
| 13 | 1,981 | 40 | 2,021 | import logging
import math
from typing import List, Iterable, Tuple, Sequence, Optional
import random
from allennlp.common.checks import ConfigurationError
from allennlp.common.util import lazy_groups_of
from allennlp.data.instance import Instance
from allennlp.data.samplers.batch_sampler import BatchSampler
logger ... | import logging
import math
from typing import List, Iterable, Tuple, Sequence, Optional
import random
from allennlp.common.checks import ConfigurationError
from allennlp.common.util import lazy_groups_of
from allennlp.data.instance import Instance
from allennlp.data.samplers.batch_sampler import BatchSampler
logger ... | |
9,097 | /home/hieuvd/dung_repo/raw/stars_01/allenai_allennlp/allennlp | /home/hieuvd/dung_repo/raw/stars_01/allenai_allennlp/allennlp/allennlp/data/samplers/bucket_batch_sampler.py | 82,85 | 21,173 | _argsort_by_padding | BucketBatchSampler | 90,116 | 85,116 | @BatchSampler.register("bucket")
class BucketBatchSampler(BatchSampler):
"""
An sampler which by default, argsorts batches with respect to the maximum input lengths `per
batch`. You can provide a list of field names and padding keys (or pass none, in which case they
will be inferred) which the dataset w... | @BatchSampler.register("bucket")
class BucketBatchSampler(BatchSampler):
"""
An sampler which by default, argsorts batches with respect to the maximum input lengths `per
batch`. You can provide a list of field names and padding keys (or pass none, in which case they
will be inferred) which the dataset w... | if not self.sorting_keys:
logger.info("No sorting keys given; trying to guess a good one")
self._guess_sorting_keys(instances)
logger.info(f"Using {self.sorting_keys} as the sorting keys")
instances_with_lengths = []
for instance in instances:
# Ma... | """
Argsorts the instances by their padding lengths, using the keys in
`sorting_keys` (in the order in which they are provided). `sorting_keys`
is a list of `(field_name, padding_key)` tuples.
"""
if not self.sorting_keys:
logger.info("No sorting keys given; t... | 102 | 1,495 | 391 | 1,886 | import logging
import math
from typing import List, Iterable, Tuple, Sequence, Optional
import random
from allennlp.common.checks import ConfigurationError
from allennlp.common.util import lazy_groups_of
from allennlp.data.instance import Instance
from allennlp.data.samplers.batch_sampler import BatchSampler
logger ... | import logging
import math
from typing import List, Iterable, Tuple, Sequence, Optional
import random
from allennlp.common.checks import ConfigurationError
from allennlp.common.util import lazy_groups_of
from allennlp.data.instance import Instance
from allennlp.data.samplers.batch_sampler import BatchSampler
logger ... |
9,098 | /home/hieuvd/dung_repo/raw/stars_01/allenai_allennlp/allennlp | /home/hieuvd/dung_repo/raw/stars_01/allenai_allennlp/allennlp/allennlp/data/samplers/max_tokens_batch_sampler.py | 62,67 | 16,112 | _lazy_groups_of_max_size | MaxTokensBatchSampler | 72,98 | 67,98 | @BatchSampler.register("max_tokens_sampler")
class MaxTokensBatchSampler(BucketBatchSampler):
"""
An sampler which by default, argsorts batches with respect to the maximum input lengths `per
batch`. Batches are then created such that the number of tokens in a batch does not exceed the given
maximum numb... | @BatchSampler.register("max_tokens_sampler")
class MaxTokensBatchSampler(BucketBatchSampler):
"""
An sampler which by default, argsorts batches with respect to the maximum input lengths `per
batch`. Batches are then created such that the number of tokens in a batch does not exceed the given
maximum numb... | cur_max_size = 0
group: List[A] = []
iterator = iter(iterable)
size_iter = iter(sizes)
for item, size in zip(iterator, size_iter):
if size > self.max_tokens:
logger.warning(
"Found instance of size %d, which is bigger than the exp... | """
Takes an `iterable` of data and an iterable `sizes` of the same length which represents the sizes of each
corresponding item in `iterable`. The instances from `iterable` are batched such that the total size
of the batch as computed from `sizes` does not exceed `max_size`.
"""... | 74 | 963 | 243 | 1,206 | import logging
import random
from typing import List, Iterable, Iterator, TypeVar, Sequence
from allennlp.data.instance import Instance
from allennlp.data.samplers.batch_sampler import BatchSampler
from allennlp.data.samplers.bucket_batch_sampler import BucketBatchSampler
logger = logging.getLogger(__name__)
A = T... | import logging
import random
from typing import List, Iterable, Iterator, TypeVar, Sequence
from allennlp.data.instance import Instance
from allennlp.data.samplers.batch_sampler import BatchSampler
from allennlp.data.samplers.bucket_batch_sampler import BucketBatchSampler
logger = logging.getLogger(__name__)
A = T... |
9,099 | /home/hieuvd/dung_repo/raw/stars_01/allenai_allennlp/allennlp | /home/hieuvd/dung_repo/raw/stars_01/allenai_allennlp/allennlp/allennlp/data/token_indexers/single_id_token_indexer.py | 76,79 | 13,119 | tokens_to_indices | SingleIdTokenIndexer | 79,93 | 79,93 | @TokenIndexer.register("single_id")
class SingleIdTokenIndexer(TokenIndexer):
"""
This :class:`TokenIndexer` represents tokens as single integers.
Registered as a `TokenIndexer` with name "single_id".
# Parameters
namespace : `Optional[str]`, optional (default=`"tokens"`)
We will use this... | @TokenIndexer.register("single_id")
class SingleIdTokenIndexer(TokenIndexer):
"""
This :class:`TokenIndexer` represents tokens as single integers.
Registered as a `TokenIndexer` with name "single_id".
# Parameters
namespace : `Optional[str]`, optional (default=`"tokens"`)
We will use this... | indices: List[int] = []
for token in itertools.chain(self._start_tokens, tokens, self._end_tokens):
text = self._get_feature_value(token)
if self.namespace is None:
# We could have a check here that `text` is an int; not sure it's worth it.
indice... | indices: List[int] = []
for token in itertools.chain(self._start_tokens, tokens, self._end_tokens):
text = self._get_feature_value(token)
if self.namespace is None:
# We could have a check here that `text` is an int; not sure it's worth it.
indice... | 49 | 1,295 | 169 | 1,464 | from typing import Dict, List, Optional, Any
import itertools
from allennlp.data.vocabulary import Vocabulary
from allennlp.data.tokenizers import Token
from allennlp.data.token_indexers.token_indexer import TokenIndexer, IndexedTokenList
_DEFAULT_VALUE = "THIS IS A REALLY UNLIKELY VALUE THAT HAS TO BE A STRING"
... | from typing import Dict, List, Optional, Any
import itertools
from allennlp.data.vocabulary import Vocabulary
from allennlp.data.tokenizers import Token
from allennlp.data.token_indexers.token_indexer import TokenIndexer, IndexedTokenList
_DEFAULT_VALUE = "THIS IS A REALLY UNLIKELY VALUE THAT HAS TO BE A STRING"
... |
9,100 | /home/hieuvd/dung_repo/raw/stars_01/allenai_allennlp/allennlp | /home/hieuvd/dung_repo/raw/stars_01/allenai_allennlp/allennlp/allennlp/data/tokenizers/character_tokenizer.py | 57,58 | 8,93 | tokenize | CharacterTokenizer | 58,80 | 58,80 | @Tokenizer.register("character")
class CharacterTokenizer(Tokenizer):
"""
A `CharacterTokenizer` splits strings into character tokens.
Registered as a `Tokenizer` with name "character".
# Parameters
byte_encoding : `str`, optional (default=`None`)
If not `None`, we will use this encoding ... | @Tokenizer.register("character")
class CharacterTokenizer(Tokenizer):
"""
A `CharacterTokenizer` splits strings into character tokens.
Registered as a `Tokenizer` with name "character".
# Parameters
byte_encoding : `str`, optional (default=`None`)
If not `None`, we will use this encoding ... | if self._lowercase_characters:
text = text.lower()
if self._byte_encoding is not None:
# We add 1 here so that we can still use 0 for masking, no matter what bytes we get out
# of this.
tokens = [Token(text_id=c + 1) for c in text.encode(self._byte_encodin... | if self._lowercase_characters:
text = text.lower()
if self._byte_encoding is not None:
# We add 1 here so that we can still use 0 for masking, no matter what bytes we get out
# of this.
tokens = [Token(text_id=c + 1) for c in text.encode(self._byte_encodin... | 88 | 809 | 290 | 1,099 | from typing import List, Union, Dict, Any
from allennlp.data.tokenizers.token_class import Token
from allennlp.data.tokenizers.tokenizer import Tokenizer
@Tokenizer.register("character")
class CharacterTokenizer(Tokenizer):
"""
A `CharacterTokenizer` splits strings into character tokens.
Registered as ... | from typing import List, Union, Dict, Any
from allennlp.data.tokenizers.token_class import Token
from allennlp.data.tokenizers.tokenizer import Tokenizer
@Tokenizer.register("character")
class CharacterTokenizer(Tokenizer):
"""
A `CharacterTokenizer` splits strings into character tokens.
Registered as ... |
9,101 | /home/hieuvd/dung_repo/raw/stars_01/allenai_allennlp/allennlp | /home/hieuvd/dung_repo/raw/stars_01/allenai_allennlp/allennlp/allennlp/data/tokenizers/letters_digits_tokenizer.py | 18,19 | 9,22 | tokenize | LettersDigitsTokenizer | 19,22 | 19,22 | @Tokenizer.register("letters_digits")
class LettersDigitsTokenizer(Tokenizer):
"""
A `Tokenizer` which keeps runs of (unicode) letters and runs of digits together, while
every other non-whitespace character becomes a separate word.
Registered as a `Tokenizer` with name "letters_digits".
"""
de... | @Tokenizer.register("letters_digits")
class LettersDigitsTokenizer(Tokenizer):
"""
A `Tokenizer` which keeps runs of (unicode) letters and runs of digits together, while
every other non-whitespace character becomes a separate word.
Registered as a `Tokenizer` with name "letters_digits".
"""
de... | # We use the [^\W\d_] pattern as a trick to match unicode letters
tokens = [Token(m.group(), idx=m.start()) for m in re.finditer(r"[^\W\d_]+|\d+|\S", text)]
return tokens
| # We use the [^\W\d_] pattern as a trick to match unicode letters
tokens = [Token(m.group(), idx=m.start()) for m in re.finditer(r"[^\W\d_]+|\d+|\S", text)]
return tokens
| 24 | 119 | 74 | 193 | import re
from typing import List
from allennlp.data.tokenizers.token_class import Token
from allennlp.data.tokenizers.tokenizer import Tokenizer
@Tokenizer.register("letters_digits")
class LettersDigitsTokenizer(Tokenizer):
"""
A `Tokenizer` which keeps runs of (unicode) letters and runs of digits together... | import re
from typing import List
from allennlp.data.tokenizers.token_class import Token
from allennlp.data.tokenizers.tokenizer import Tokenizer
@Tokenizer.register("letters_digits")
class LettersDigitsTokenizer(Tokenizer):
"""
A `Tokenizer` which keeps runs of (unicode) letters and runs of digits together... |
9,102 | /home/hieuvd/dung_repo/raw/stars_01/allenai_allennlp/allennlp | /home/hieuvd/dung_repo/raw/stars_01/allenai_allennlp/allennlp/allennlp/data/tokenizers/token_class.py | 114,115 | 1,127 | show_token | 115,127 | 115,127 | from dataclasses import dataclass
from typing import Optional
@dataclass(init=False, repr=False)
class Token:
"""
A simple token representation, keeping track of the token's text, offset in the passage it was
taken from, POS tag, dependency relation, and similar information. These fields match spacy's
... | from dataclasses import dataclass
from typing import Optional
@dataclass(init=False, repr=False)
class Token:
"""
A simple token representation, keeping track of the token's text, offset in the passage it was
taken from, POS tag, dependency relation, and similar information. These fields match spacy's
... | return (
f"{token.text} "
f"(idx: {token.idx}) "
f"(idx_end: {token.idx_end}) "
f"(lemma: {token.lemma_}) "
f"(pos: {token.pos_}) "
f"(tag: {token.tag_}) "
f"(dep: {token.dep_}) "
f"(ent_type: {token.ent_type_}) "
f"(text_id: {token.text_id}) "... | return (
f"{token.text} "
f"(idx: {token.idx}) "
f"(idx_end: {token.idx_end}) "
f"(lemma: {token.lemma_}) "
f"(pos: {token.pos_}) "
f"(tag: {token.tag_}) "
f"(dep: {token.dep_}) "
f"(ent_type: {token.ent_type_}) "
f"(text_id: {token.text_id}) "... | 32 | 1,114 | 158 | 1,272 | from dataclasses import dataclass
from typing import Optional
@dataclass(init=False, repr=False)
class Token:
"""
A simple token representation, keeping track of the token's text, offset in the passage it was
taken from, POS tag, dependency relation, and similar information. These fields match spacy's
... | from dataclasses import dataclass
from typing import Optional
@dataclass(init=False, repr=False)
class Token:
"""
A simple token representation, keeping track of the token's text, offset in the passage it was
taken from, POS tag, dependency relation, and similar information. These fields match spacy's
... | |
9,103 | /home/hieuvd/dung_repo/raw/stars_01/allenai_allennlp/allennlp | /home/hieuvd/dung_repo/raw/stars_01/allenai_allennlp/allennlp/allennlp/data/tokenizers/token_class.py | 104,105 | 5,114 | ensure_text | Token | 108,114 | 105,114 | @dataclass(init=False, repr=False)
class Token:
"""
A simple token representation, keeping track of the token's text, offset in the passage it was
taken from, POS tag, dependency relation, and similar information. These fields match spacy's
exactly, so we can just use a spacy token for this.
# Par... | @dataclass(init=False, repr=False)
class Token:
"""
A simple token representation, keeping track of the token's text, offset in the passage it was
taken from, POS tag, dependency relation, and similar information. These fields match spacy's
exactly, so we can just use a spacy token for this.
# Par... | if self.text is None:
raise ValueError("Unexpected null text for token")
else:
return self.text
| """
Return the `text` field, raising an exception if it's `None`.
"""
if self.text is None:
raise ValueError("Unexpected null text for token")
else:
return self.text
| 13 | 1,047 | 41 | 1,088 | from dataclasses import dataclass
from typing import Optional
@dataclass(init=False, repr=False)
class Token:
"""
A simple token representation, keeping track of the token's text, offset in the passage it was
taken from, POS tag, dependency relation, and similar information. These fields match spacy's
... | from dataclasses import dataclass
from typing import Optional
@dataclass(init=False, repr=False)
class Token:
"""
A simple token representation, keeping track of the token's text, offset in the passage it was
taken from, POS tag, dependency relation, and similar information. These fields match spacy's
... |
9,104 | /home/hieuvd/dung_repo/raw/stars_01/allenai_allennlp/allennlp | /home/hieuvd/dung_repo/raw/stars_01/allenai_allennlp/allennlp/allennlp/data/tokenizers/tokenizer.py | 77,78 | 11,82 | num_special_tokens_for_pair | Tokenizer | 81,82 | 78,82 | class Tokenizer(Registrable):
"""
A `Tokenizer` splits strings of text into tokens. Typically, this either splits text into
word tokens or character tokens, and those are the two tokenizer subclasses we have implemented
here, though you could imagine wanting to do other kinds of tokenization for struct... | class Tokenizer(Registrable):
"""
A `Tokenizer` splits strings of text into tokens. Typically, this either splits text into
word tokens or character tokens, and those are the two tokenizer subclasses we have implemented
here, though you could imagine wanting to do other kinds of tokenization for struct... | return 0
| """
Returns the number of special tokens added for a pair of sequences.
"""
return 0
| 2 | 692 | 6 | 698 | from typing import List, Optional
import logging
from allennlp.common import Registrable
from allennlp.data.tokenizers.token_class import Token
logger = logging.getLogger(__name__)
class Tokenizer(Registrable):
"""
A `Tokenizer` splits strings of text into tokens. Typically, this either splits text into
... | from typing import List, Optional
import logging
from allennlp.common import Registrable
from allennlp.data.tokenizers.token_class import Token
logger = logging.getLogger(__name__)
class Tokenizer(Registrable):
"""
A `Tokenizer` splits strings of text into tokens. Typically, this either splits text into
... |
9,105 | /home/hieuvd/dung_repo/raw/stars_01/allenai_allennlp/allennlp | /home/hieuvd/dung_repo/raw/stars_01/allenai_allennlp/allennlp/allennlp/data/tokenizers/whitespace_tokenizer.py | 22,23 | 8,27 | tokenize | WhitespaceTokenizer | 23,25 | 23,25 | @Tokenizer.register("whitespace")
@Tokenizer.register("just_spaces")
class WhitespaceTokenizer(Tokenizer):
"""
A `Tokenizer` that assumes you've already done your own tokenization somehow and have
separated the tokens by spaces. We just split the input string on whitespace and return the
resulting list... | @Tokenizer.register("whitespace")
@Tokenizer.register("just_spaces")
class WhitespaceTokenizer(Tokenizer):
"""
A `Tokenizer` that assumes you've already done your own tokenization somehow and have
separated the tokens by spaces. We just split the input string on whitespace and return the
resulting list... | return [Token(t) for t in text.split()]
| return [Token(t) for t in text.split()]
| 6 | 214 | 19 | 233 | from typing import List, Dict, Any
from allennlp.data.tokenizers.token_class import Token
from allennlp.data.tokenizers.tokenizer import Tokenizer
@Tokenizer.register("whitespace")
@Tokenizer.register("just_spaces")
class WhitespaceTokenizer(Tokenizer):
"""
A `Tokenizer` that assumes you've already done you... | from typing import List, Dict, Any
from allennlp.data.tokenizers.token_class import Token
from allennlp.data.tokenizers.tokenizer import Tokenizer
@Tokenizer.register("whitespace")
@Tokenizer.register("just_spaces")
class WhitespaceTokenizer(Tokenizer):
"""
A `Tokenizer` that assumes you've already done you... |
9,106 | /home/hieuvd/dung_repo/raw/stars_01/allenai_allennlp/allennlp | /home/hieuvd/dung_repo/raw/stars_01/allenai_allennlp/allennlp/allennlp/evaluation/serializers/serializers.py | 61,62 | 54,107 | _to_params | SimpleSerializer | 62,64 | 62,64 | @Serializer.register("simple")
class SimpleSerializer(Serializer):
"""
Very simple serializer. Only sanitizes the batches and outputs. Will use
a passed serializer function for the outputs if it exists.
"""
def _to_params(self) -> Dict[str, Any]:
FILL_FUNC_BODY def __call__(
self,
... | @Serializer.register("simple")
class SimpleSerializer(Serializer):
"""
Very simple serializer. Only sanitizes the batches and outputs. Will use
a passed serializer function for the outputs if it exists.
"""
def _to_params(self) -> Dict[str, Any]:
FILL_FUNC_BODY def __call__(
self,
... | return {"type": "simple"}
| return {"type": "simple"}
| 3 | 460 | 12 | 472 | from typing import Optional, Dict, Any, Callable
import logging
import json
from allennlp.common.util import sanitize
from allennlp.data.fields import TensorField
from allennlp.common import Registrable
from allennlp.data import DataLoader
logger = logging.getLogger(__name__)
class Serializer(Registrable):
"""
... | from typing import Optional, Dict, Any, Callable
import logging
import json
from allennlp.common.util import sanitize
from allennlp.data.fields import TensorField
from allennlp.common import Registrable
from allennlp.data import DataLoader
logger = logging.getLogger(__name__)
class Serializer(Registrable):
"""
... |
9,107 | /home/hieuvd/dung_repo/raw/stars_01/allenai_allennlp/allennlp | /home/hieuvd/dung_repo/raw/stars_01/allenai_allennlp/allennlp/allennlp/fairness/bias_mitigator_applicator.py | 98,99 | 21,103 | _maybe_warn_for_unseparable_batches | BiasMitigatorApplicator | 99,101 | 99,101 | @Model.register("bias_mitigator_applicator")
class BiasMitigatorApplicator(Model):
"""
Wrapper class to apply bias mitigation to any pretrained Model.
# Parameters
vocab : `Vocabulary`
Vocabulary of base model.
base_model : `Model`
Base model for which to mitigate biases.
bias_... | @Model.register("bias_mitigator_applicator")
class BiasMitigatorApplicator(Model):
"""
Wrapper class to apply bias mitigation to any pretrained Model.
# Parameters
vocab : `Vocabulary`
Vocabulary of base model.
base_model : `Model`
Base model for which to mitigate biases.
bias_... | return self.base_model._maybe_warn_for_unseparable_batches(*args, **kwargs)
| return self.base_model._maybe_warn_for_unseparable_batches(*args, **kwargs)
| 3 | 956 | 30 | 986 | """
A Model wrapper to mitigate biases in
contextual embeddings during finetuning
on a downstream task and test time.
Based on: Dev, S., Li, T., Phillips, J.M., & Srikumar, V. (2020).
[On Measuring and Mitigating Biased Inferences of Word Embeddings]
(https://api.semanticscholar.org/CorpusID:201670701).
ArXiv, abs/190... | """
A Model wrapper to mitigate biases in
contextual embeddings during finetuning
on a downstream task and test time.
Based on: Dev, S., Li, T., Phillips, J.M., & Srikumar, V. (2020).
[On Measuring and Mitigating Biased Inferences of Word Embeddings]
(https://api.semanticscholar.org/CorpusID:201670701).
ArXiv, abs/190... |
9,108 | /home/hieuvd/dung_repo/raw/stars_01/allenai_allennlp/allennlp | /home/hieuvd/dung_repo/raw/stars_01/allenai_allennlp/allennlp/allennlp/interpret/attackers/attacker.py | 24,32 | 8,60 | attack_from_json | Attacker | 59,60 | 32,60 | class Attacker(Registrable):
"""
An `Attacker` will modify an input (e.g., add or delete tokens) to try to change an AllenNLP
Predictor's output in a desired manner (e.g., make it incorrect).
"""
def __init__(self, predictor: Predictor) -> None:
self.predictor = predictor
def initializ... | class Attacker(Registrable):
"""
An `Attacker` will modify an input (e.g., add or delete tokens) to try to change an AllenNLP
Predictor's output in a desired manner (e.g., make it incorrect).
"""
def __init__(self, predictor: Predictor) -> None:
self.predictor = predictor
def initializ... | raise NotImplementedError()
| """
This function finds a modification to the input text that would change the model's
prediction in some desired manner (e.g., an adversarial attack).
# Parameters
inputs : `JsonDict`
The input you want to attack (the same as the argument to a Predictor, e.g.,
... | 2 | 552 | 10 | 562 | from typing import List
from allennlp.common import Registrable
from allennlp.common.util import JsonDict
from allennlp.predictors import Predictor
class Attacker(Registrable):
"""
An `Attacker` will modify an input (e.g., add or delete tokens) to try to change an AllenNLP
Predictor's output in a desired... | from typing import List
from allennlp.common import Registrable
from allennlp.common.util import JsonDict
from allennlp.predictors import Predictor
class Attacker(Registrable):
"""
An `Attacker` will modify an input (e.g., add or delete tokens) to try to change an AllenNLP
Predictor's output in a desired... |
9,109 | /home/hieuvd/dung_repo/raw/stars_01/allenai_allennlp/allennlp | /home/hieuvd/dung_repo/raw/stars_01/allenai_allennlp/allennlp/allennlp/interpret/attackers/utils.py | 5,8 | 1,50 | get_fields_to_compare | 25,40 | 8,40 | from allennlp.common.util import JsonDict
from allennlp.data import Instance
def get_fields_to_compare(
inputs: JsonDict, instance: Instance, input_field_to_attack: str
) -> JsonDict:
FILL_FUNC_BODYdef instance_has_changed(instance: Instance, fields_to_compare: JsonDict):
if "clusters" in fields_to_compare:
... | from allennlp.common.util import JsonDict
from allennlp.data import Instance
def get_fields_to_compare(
inputs: JsonDict, instance: Instance, input_field_to_attack: str
) -> JsonDict:
"""
Gets a list of the fields that should be checked for equality after an attack is performed.
# Parameters
inp... | # TODO(mattg): this really should live on the Predictor. We have some messy stuff for, e.g.,
# reading comprehension models, and the interpret code can't really know about the internals of
# that (or at least it shouldn't now, and once we split out the reading comprehension repo, it
# really *can't*).
... | """
Gets a list of the fields that should be checked for equality after an attack is performed.
# Parameters
inputs : `JsonDict`
The input you want to attack, similar to the argument to a Predictor, e.g., predict_json().
instance : `Instance`
A labeled instance that is output from ... | 81 | 423 | 182 | 605 | from allennlp.common.util import JsonDict
from allennlp.data import Instance
def get_fields_to_compare(
inputs: JsonDict, instance: Instance, input_field_to_attack: str
) -> JsonDict:
FILL_FUNC_BODYdef instance_has_changed(instance: Instance, fields_to_compare: JsonDict):
if "clusters" in fields_to_compare:
... | from allennlp.common.util import JsonDict
from allennlp.data import Instance
def get_fields_to_compare(
inputs: JsonDict, instance: Instance, input_field_to_attack: str
) -> JsonDict:
"""
Gets a list of the fields that should be checked for equality after an attack is performed.
# Parameters
inp... | |
9,110 | /home/hieuvd/dung_repo/raw/stars_01/allenai_allennlp/allennlp | /home/hieuvd/dung_repo/raw/stars_01/allenai_allennlp/allennlp/allennlp/modules/seq2seq_encoders/seq2seq_encoder.py | 24,25 | 5,38 | get_output_dim | Seq2SeqEncoder | 29,31 | 25,31 | class Seq2SeqEncoder(_EncoderBase, Registrable):
"""
A `Seq2SeqEncoder` is a `Module` that takes as input a sequence of vectors and returns a
modified sequence of vectors. Input shape : `(batch_size, sequence_length, input_dim)`; output
shape : `(batch_size, sequence_length, output_dim)`.
We add t... | class Seq2SeqEncoder(_EncoderBase, Registrable):
"""
A `Seq2SeqEncoder` is a `Module` that takes as input a sequence of vectors and returns a
modified sequence of vectors. Input shape : `(batch_size, sequence_length, input_dim)`; output
shape : `(batch_size, sequence_length, output_dim)`.
We add t... | raise NotImplementedError
| """
Returns the dimension of each vector in the sequence output by this `Seq2SeqEncoder`.
This is `not` the shape of the returned tensor, but the last element of that shape.
"""
raise NotImplementedError
| 2 | 408 | 11 | 419 | from allennlp.modules.encoder_base import _EncoderBase
from allennlp.common import Registrable
class Seq2SeqEncoder(_EncoderBase, Registrable):
"""
A `Seq2SeqEncoder` is a `Module` that takes as input a sequence of vectors and returns a
modified sequence of vectors. Input shape : `(batch_size, sequence_l... | from allennlp.modules.encoder_base import _EncoderBase
from allennlp.common import Registrable
class Seq2SeqEncoder(_EncoderBase, Registrable):
"""
A `Seq2SeqEncoder` is a `Module` that takes as input a sequence of vectors and returns a
modified sequence of vectors. Input shape : `(batch_size, sequence_l... |
9,111 | /home/hieuvd/dung_repo/raw/stars_01/allenai_allennlp/allennlp | /home/hieuvd/dung_repo/raw/stars_01/allenai_allennlp/allennlp/allennlp/modules/seq2vec_encoders/seq2vec_encoder.py | 24,25 | 5,30 | get_output_dim | Seq2VecEncoder | 29,30 | 25,30 | class Seq2VecEncoder(_EncoderBase, Registrable):
"""
A `Seq2VecEncoder` is a `Module` that takes as input a sequence of vectors and returns a
single vector. Input shape : `(batch_size, sequence_length, input_dim)`; output shape:
`(batch_size, output_dim)`.
We add two methods to the basic `Module` ... | class Seq2VecEncoder(_EncoderBase, Registrable):
"""
A `Seq2VecEncoder` is a `Module` that takes as input a sequence of vectors and returns a
single vector. Input shape : `(batch_size, sequence_length, input_dim)`; output shape:
`(batch_size, output_dim)`.
We add two methods to the basic `Module` ... | raise NotImplementedError
| """
Returns the dimension of the final vector output by this `Seq2VecEncoder`. This is `not`
the shape of the returned tensor, but the last element of that shape.
"""
raise NotImplementedError
| 2 | 324 | 9 | 333 | from allennlp.modules.encoder_base import _EncoderBase
from allennlp.common import Registrable
class Seq2VecEncoder(_EncoderBase, Registrable):
"""
A `Seq2VecEncoder` is a `Module` that takes as input a sequence of vectors and returns a
single vector. Input shape : `(batch_size, sequence_length, input_di... | from allennlp.modules.encoder_base import _EncoderBase
from allennlp.common import Registrable
class Seq2VecEncoder(_EncoderBase, Registrable):
"""
A `Seq2VecEncoder` is a `Module` that takes as input a sequence of vectors and returns a
single vector. Input shape : `(batch_size, sequence_length, input_di... |
9,112 | /home/hieuvd/dung_repo/raw/stars_01/allenai_allennlp/allennlp | /home/hieuvd/dung_repo/raw/stars_01/allenai_allennlp/allennlp/allennlp/modules/transformer/bimodal_connection_layer.py | 88,96 | 32,116 | forward | BiModalConnectionLayer | 96,116 | 96,116 | class BiModalConnectionLayer(TransformerModule, FromParams):
_pretrained_mapping = {"biAttention": "bimodal_attention", "biOutput": "bimodal_output"}
def __init__(
self,
hidden_size1: int,
hidden_size2: int,
combined_hidden_size: int,
intermediate_size1: int,
in... | class BiModalConnectionLayer(TransformerModule, FromParams):
_pretrained_mapping = {"biAttention": "bimodal_attention", "biOutput": "bimodal_output"}
def __init__(
self,
hidden_size1: int,
hidden_size2: int,
combined_hidden_size: int,
intermediate_size1: int,
in... |
bi_output1, bi_output2 = self.bimodal_attention(
input_tensor1,
input_tensor2,
attention_mask1,
attention_mask2,
co_attention_mask,
)
attention_output1, attention_output2 = self.bimodal_output(
bi_output2, input_tensor1, b... |
bi_output1, bi_output2 = self.bimodal_attention(
input_tensor1,
input_tensor2,
attention_mask1,
attention_mask2,
co_attention_mask,
)
attention_output1, attention_output2 = self.bimodal_output(
bi_output2, input_tensor1, b... | 36 | 566 | 224 | 790 | from allennlp.common import FromParams
from allennlp.modules.transformer.activation_layer import ActivationLayer
from allennlp.modules.transformer.output_layer import OutputLayer
from allennlp.modules.transformer.bimodal_attention import BiModalAttention
from allennlp.modules.transformer.transformer_module import Tra... | from allennlp.common import FromParams
from allennlp.modules.transformer.activation_layer import ActivationLayer
from allennlp.modules.transformer.output_layer import OutputLayer
from allennlp.modules.transformer.bimodal_attention import BiModalAttention
from allennlp.modules.transformer.transformer_module import Tra... |
9,113 | /home/hieuvd/dung_repo/raw/stars_01/allenai_allennlp/allennlp | /home/hieuvd/dung_repo/raw/stars_01/allenai_allennlp/allennlp/allennlp/modules/transformer/bimodal_connection_layer.py | 24,25 | 10,32 | forward | BiModalOutput | 25,32 | 25,32 | class BiModalOutput(TransformerModule, FromParams):
def __init__(
self,
hidden_size1: int,
hidden_size2: int,
combined_hidden_size: int,
dropout1: float,
dropout2: float,
):
super().__init__()
self.bert_output1 = OutputLayer(combined_hidden_size, ... | class BiModalOutput(TransformerModule, FromParams):
def __init__(
self,
hidden_size1: int,
hidden_size2: int,
combined_hidden_size: int,
dropout1: float,
dropout2: float,
):
super().__init__()
self.bert_output1 = OutputLayer(combined_hidden_size, ... |
hidden_states1 = self.bert_output1(hidden_states1, input_tensor1)
hidden_states2 = self.bert_output2(hidden_states2, input_tensor2)
return hidden_states1, hidden_states2
|
hidden_states1 = self.bert_output1(hidden_states1, input_tensor1)
hidden_states2 = self.bert_output2(hidden_states2, input_tensor2)
return hidden_states1, hidden_states2
| 11 | 174 | 71 | 245 | from allennlp.common import FromParams
from allennlp.modules.transformer.activation_layer import ActivationLayer
from allennlp.modules.transformer.output_layer import OutputLayer
from allennlp.modules.transformer.bimodal_attention import BiModalAttention
from allennlp.modules.transformer.transformer_module import Tra... | from allennlp.common import FromParams
from allennlp.modules.transformer.activation_layer import ActivationLayer
from allennlp.modules.transformer.output_layer import OutputLayer
from allennlp.modules.transformer.bimodal_attention import BiModalAttention
from allennlp.modules.transformer.transformer_module import Tra... |
9,114 | /home/hieuvd/dung_repo/raw/stars_01/allenai_allennlp/allennlp | /home/hieuvd/dung_repo/raw/stars_01/allenai_allennlp/allennlp/allennlp/predictors/multitask.py | 56,57 | 15,92 | predict_instance | MultiTaskPredictor | 57,67 | 57,67 | @Predictor.register("multitask")
class MultiTaskPredictor(Predictor):
"""
Predictor for multitask models.
Registered as a `Predictor` with name "multitask".
This predictor is tightly coupled to `MultiTaskDatasetReader` and `MultiTaskModel`, and will not work if
used with other readers or models.
... | @Predictor.register("multitask")
class MultiTaskPredictor(Predictor):
"""
Predictor for multitask models.
Registered as a `Predictor` with name "multitask".
This predictor is tightly coupled to `MultiTaskDatasetReader` and `MultiTaskModel`, and will not work if
used with other readers or models.
... | task_field = instance["task"]
if not isinstance(task_field, MetadataField):
raise ValueError(self._WRONG_FIELD_ERROR)
task: str = task_field.metadata
if not isinstance(self._dataset_reader, MultiTaskDatasetReader):
raise ConfigurationError(self._WRONG_READER_ERROR... | task_field = instance["task"]
if not isinstance(task_field, MetadataField):
raise ValueError(self._WRONG_FIELD_ERROR)
task: str = task_field.metadata
if not isinstance(self._dataset_reader, MultiTaskDatasetReader):
raise ConfigurationError(self._WRONG_READER_ERROR... | 25 | 814 | 145 | 959 | import collections
from typing import Type, List, Dict
from allennlp.common import JsonDict
from allennlp.data import Instance
from allennlp.models.multitask import MultiTaskModel
from allennlp.predictors.predictor import Predictor
from allennlp.common.util import sanitize
from allennlp.data.fields import MetadataFie... | import collections
from typing import Type, List, Dict
from allennlp.common import JsonDict
from allennlp.data import Instance
from allennlp.models.multitask import MultiTaskModel
from allennlp.predictors.predictor import Predictor
from allennlp.common.util import sanitize
from allennlp.data.fields import MetadataFie... |
9,115 | /home/hieuvd/dung_repo/raw/stars_01/allenai_allennlp/allennlp | /home/hieuvd/dung_repo/raw/stars_01/allenai_allennlp/allennlp/allennlp/tools/archive_surgery.py | 28,29 | 1,83 | main | 29,80 | 29,80 | #! /usr/bin/env python
"""
Helper script for modifying config.json files that are locked inside
model.tar.gz archives. This is useful if you need to rename things or
add or remove values, usually because of changes to the library.
This script will untar the archive to a temp directory, launch an editor
to modify the c... | #! /usr/bin/env python
"""
Helper script for modifying config.json files that are locked inside
model.tar.gz archives. This is useful if you need to rename things or
add or remove values, usually because of changes to the library.
This script will untar the archive to a temp directory, launch an editor
to modify the c... | parser = argparse.ArgumentParser(
description="Perform surgery on a model.tar.gz archive",
formatter_class=argparse.ArgumentDefaultsHelpFormatter,
)
parser.add_argument("--input-file", required=True, help="path to input file")
parser.add_argument(
"--editor",
default=os.... | parser = argparse.ArgumentParser(
description="Perform surgery on a model.tar.gz archive",
formatter_class=argparse.ArgumentDefaultsHelpFormatter,
)
parser.add_argument("--input-file", required=True, help="path to input file")
parser.add_argument(
"--editor",
default=os.... | 150 | 241 | 608 | 849 | #! /usr/bin/env python
"""
Helper script for modifying config.json files that are locked inside
model.tar.gz archives. This is useful if you need to rename things or
add or remove values, usually because of changes to the library.
This script will untar the archive to a temp directory, launch an editor
to modify the c... | #! /usr/bin/env python
"""
Helper script for modifying config.json files that are locked inside
model.tar.gz archives. This is useful if you need to rename things or
add or remove values, usually because of changes to the library.
This script will untar the archive to a temp directory, launch an editor
to modify the c... | |
9,116 | /home/hieuvd/dung_repo/raw/stars_01/allenai_allennlp/allennlp | /home/hieuvd/dung_repo/raw/stars_01/allenai_allennlp/allennlp/allennlp/tools/inspect_cache.py | 7,8 | 1,30 | main | 8,28 | 8,28 | import os
from allennlp.common.file_utils import CACHE_DIRECTORY
from allennlp.common.file_utils import filename_to_url
def main():
FILL_FUNC_BODYif __name__ == "__main__":
main()
| import os
from allennlp.common.file_utils import CACHE_DIRECTORY
from allennlp.common.file_utils import filename_to_url
def main():
FILL_FUNC_BODYif __name__ == "__main__":
main()
| print(f"Looking for datasets in {CACHE_DIRECTORY}...")
if not os.path.exists(CACHE_DIRECTORY):
print("Directory does not exist.")
print("No cached datasets found.")
cached_files = os.listdir(CACHE_DIRECTORY)
if not cached_files:
print("Directory is empty.")
print("No ca... | print(f"Looking for datasets in {CACHE_DIRECTORY}...")
if not os.path.exists(CACHE_DIRECTORY):
print("Directory does not exist.")
print("No cached datasets found.")
cached_files = os.listdir(CACHE_DIRECTORY)
if not cached_files:
print("Directory is empty.")
print("No ca... | 53 | 71 | 206 | 277 | import os
from allennlp.common.file_utils import CACHE_DIRECTORY
from allennlp.common.file_utils import filename_to_url
def main():
FILL_FUNC_BODYif __name__ == "__main__":
main()
| import os
from allennlp.common.file_utils import CACHE_DIRECTORY
from allennlp.common.file_utils import filename_to_url
def main():
FILL_FUNC_BODYif __name__ == "__main__":
main()
| |
9,117 | /home/hieuvd/dung_repo/raw/stars_01/allenai_allennlp/allennlp | /home/hieuvd/dung_repo/raw/stars_01/allenai_allennlp/allennlp/allennlp/training/callbacks/confidence_checks.py | 37,50 | 13,64 | on_batch | ConfidenceChecksCallback | 50,64 | 50,64 | @TrainerCallback.register("sanity_checks")
@TrainerCallback.register("confidence_checks")
class ConfidenceChecksCallback(TrainerCallback):
"""
Performs model confidence checks.
Checks performed:
* `NormalizationBiasVerification` for detecting invalid combinations of
bias and normalization layer... | @TrainerCallback.register("sanity_checks")
@TrainerCallback.register("confidence_checks")
class ConfidenceChecksCallback(TrainerCallback):
"""
Performs model confidence checks.
Checks performed:
* `NormalizationBiasVerification` for detecting invalid combinations of
bias and normalization layer... | if not is_primary:
return None
# We destroy the hooks after the first batch, since we only want to
# perform this check once.
if epoch == 0 and batch_number == 1 and is_training:
self._verification.destroy_hooks()
detected_pairs = self._verification.c... | if not is_primary:
return None
# We destroy the hooks after the first batch, since we only want to
# perform this check once.
if epoch == 0 and batch_number == 1 and is_training:
self._verification.destroy_hooks()
detected_pairs = self._verification.c... | 54 | 383 | 145 | 528 | from typing import List, Dict, Any, Optional, TYPE_CHECKING
from allennlp.training.callbacks.callback import TrainerCallback
from allennlp.data import TensorDict
from allennlp.confidence_checks.normalization_bias_verification import NormalizationBiasVerification
if TYPE_CHECKING:
from allennlp.training.gradient_... | from typing import List, Dict, Any, Optional, TYPE_CHECKING
from allennlp.training.callbacks.callback import TrainerCallback
from allennlp.data import TensorDict
from allennlp.confidence_checks.normalization_bias_verification import NormalizationBiasVerification
if TYPE_CHECKING:
from allennlp.training.gradient_... |
9,118 | /home/hieuvd/dung_repo/raw/stars_01/allenai_allennlp/allennlp | /home/hieuvd/dung_repo/raw/stars_01/allenai_allennlp/allennlp/allennlp/training/callbacks/should_validate.py | 54,55 | 9,61 | _should_validate | ShouldValidateCallback | 55,61 | 55,61 | @TrainerCallback.register("should_validate_callback")
class ShouldValidateCallback(TrainerCallback):
"""
A callback that you can pass to the `GradientDescentTrainer` to change the frequency of
validation during training. If `validation_start` is not `None`, validation will not occur until
`validation_st... | @TrainerCallback.register("should_validate_callback")
class ShouldValidateCallback(TrainerCallback):
"""
A callback that you can pass to the `GradientDescentTrainer` to change the frequency of
validation during training. If `validation_start` is not `None`, validation will not occur until
`validation_st... | should_validate = True
if self._validation_start is not None and epoch < self._validation_start:
should_validate = False
elif self._validation_interval is not None and epoch % self._validation_interval != 0:
should_validate = False
return should_validate
| should_validate = True
if self._validation_start is not None and epoch < self._validation_start:
should_validate = False
elif self._validation_interval is not None and epoch % self._validation_interval != 0:
should_validate = False
return should_validate
| 31 | 517 | 76 | 593 | from typing import Dict, Any, TYPE_CHECKING, Optional
from allennlp.training.callbacks.callback import TrainerCallback
if TYPE_CHECKING:
from allennlp.training.gradient_descent_trainer import GradientDescentTrainer
@TrainerCallback.register("should_validate_callback")
class ShouldValidateCallback(TrainerCallbac... | from typing import Dict, Any, TYPE_CHECKING, Optional
from allennlp.training.callbacks.callback import TrainerCallback
if TYPE_CHECKING:
from allennlp.training.gradient_descent_trainer import GradientDescentTrainer
@TrainerCallback.register("should_validate_callback")
class ShouldValidateCallback(TrainerCallbac... |
9,119 | /home/hieuvd/dung_repo/raw/stars_01/allenai_allennlp/allennlp | /home/hieuvd/dung_repo/raw/stars_01/allenai_allennlp/allennlp/allennlp/training/callbacks/track_epoch.py | 24,32 | 9,33 | on_epoch | TrackEpochCallback | 32,33 | 32,33 | @TrainerCallback.register("track_epoch_callback")
class TrackEpochCallback(TrainerCallback):
"""
A callback that you can pass to the `GradientDescentTrainer` to access the current epoch number
in your model during training. This callback sets `model.epoch`, which can be read inside of
`model.forward()`.... | @TrainerCallback.register("track_epoch_callback")
class TrackEpochCallback(TrainerCallback):
"""
A callback that you can pass to the `GradientDescentTrainer` to access the current epoch number
in your model during training. This callback sets `model.epoch`, which can be read inside of
`model.forward()`.... | trainer.model.epoch = epoch + 1 # type: ignore[assignment]
| trainer.model.epoch = epoch + 1 # type: ignore[assignment]
| 8 | 273 | 23 | 296 | from typing import Dict, Any, TYPE_CHECKING
from allennlp.training.callbacks.callback import TrainerCallback
if TYPE_CHECKING:
from allennlp.training.gradient_descent_trainer import GradientDescentTrainer
@TrainerCallback.register("track_epoch_callback")
class TrackEpochCallback(TrainerCallback):
"""
A ... | from typing import Dict, Any, TYPE_CHECKING
from allennlp.training.callbacks.callback import TrainerCallback
if TYPE_CHECKING:
from allennlp.training.gradient_descent_trainer import GradientDescentTrainer
@TrainerCallback.register("track_epoch_callback")
class TrackEpochCallback(TrainerCallback):
"""
A ... |
9,120 | /home/hieuvd/dung_repo/raw/stars_01/allenai_allennlp/allennlp | /home/hieuvd/dung_repo/raw/stars_01/allenai_allennlp/allennlp/allennlp/training/metric_tracker.py | 77,78 | 6,134 | load_state_dict | MetricTracker | 81,91 | 78,91 | class MetricTracker:
"""
This class tracks a metric during training for the dual purposes of early stopping
and for knowing whether the current value is the best so far. It mimics the PyTorch
`state_dict` / `load_state_dict` interface, so that it can be checkpointed along with
your model and optimiz... | class MetricTracker:
"""
This class tracks a metric during training for the dual purposes of early stopping
and for knowing whether the current value is the best so far. It mimics the PyTorch
`state_dict` / `load_state_dict` interface, so that it can be checkpointed along with
your model and optimiz... | self._best_so_far = state_dict["best_so_far"]
self._epochs_with_no_improvement = state_dict["epochs_with_no_improvement"]
self._is_best_so_far = state_dict["is_best_so_far"]
self._epoch_number = state_dict["epoch_number"]
self.best_epoch = state_dict["best_epoch"]
# Even... | """
A `Trainer` can use this to hydrate a metric tracker from a serialized state.
"""
self._best_so_far = state_dict["best_so_far"]
self._epochs_with_no_improvement = state_dict["epochs_with_no_improvement"]
self._is_best_so_far = state_dict["is_best_so_far"]
self... | 45 | 1,333 | 193 | 1,526 | from typing import Optional, Dict, Any, List, Union
from allennlp.common.checks import ConfigurationError
class MetricTracker:
"""
This class tracks a metric during training for the dual purposes of early stopping
and for knowing whether the current value is the best so far. It mimics the PyTorch
`st... | from typing import Optional, Dict, Any, List, Union
from allennlp.common.checks import ConfigurationError
class MetricTracker:
"""
This class tracks a metric during training for the dual purposes of early stopping
and for knowing whether the current value is the best so far. It mimics the PyTorch
`st... |
9,121 | /home/hieuvd/dung_repo/raw/stars_01/allenai_allennlp/allennlp | /home/hieuvd/dung_repo/raw/stars_01/allenai_allennlp/allennlp/allennlp/training/metrics/average.py | 28,29 | 5,43 | get_metric | Average | 34,40 | 29,40 | @Metric.register("average")
class Average(Metric):
"""
This [`Metric`](./metric.md) breaks with the typical `Metric` API and just stores values that were
computed in some fashion outside of a `Metric`. If you have some external code that computes
the metric for you, for instance, you can use this to re... | @Metric.register("average")
class Average(Metric):
"""
This [`Metric`](./metric.md) breaks with the typical `Metric` API and just stores values that were
computed in some fashion outside of a `Metric`. If you have some external code that computes
the metric for you, for instance, you can use this to re... |
average_value = self._total_value / self._count if self._count > 0 else 0.0
if reset:
self.reset()
return float(average_value)
| """
# Returns
The average of all values that were passed to `__call__`.
"""
average_value = self._total_value / self._count if self._count > 0 else 0.0
if reset:
self.reset()
return float(average_value)
| 16 | 301 | 55 | 356 | from allennlp.training.metrics.metric import Metric
from allennlp.nn.util import dist_reduce_sum
@Metric.register("average")
class Average(Metric):
"""
This [`Metric`](./metric.md) breaks with the typical `Metric` API and just stores values that were
computed in some fashion outside of a `Metric`. If you... | from allennlp.training.metrics.metric import Metric
from allennlp.nn.util import dist_reduce_sum
@Metric.register("average")
class Average(Metric):
"""
This [`Metric`](./metric.md) breaks with the typical `Metric` API and just stores values that were
computed in some fashion outside of a `Metric`. If you... |
9,122 | /home/hieuvd/dung_repo/raw/stars_01/allenai_allennlp/allennlp | /home/hieuvd/dung_repo/raw/stars_01/allenai_allennlp/allennlp/allennlp/training/metrics/f1_measure.py | 65,67 | 7,75 | _false_negatives | F1Measure | 67,75 | 67,75 | @Metric.register("f1")
class F1Measure(FBetaMeasure):
"""
Computes Precision, Recall and F1 with respect to a given `positive_label`.
For example, for a BIO tagging scheme, you would pass the classification index of
the tag you are interested in, resulting in the Precision, Recall and F1 score being
... | @Metric.register("f1")
class F1Measure(FBetaMeasure):
"""
Computes Precision, Recall and F1 with respect to a given `positive_label`.
For example, for a BIO tagging scheme, you would pass the classification index of
the tag you are interested in, resulting in the Precision, Recall and F1 score being
... | # When this metric is never called, `self._true_sum` is None,
# under which case we return 0.0 for backward compatibility.
if self._true_sum is None:
return 0.0
else:
# `self._true_sum` is the total number of instances under each _true_ class,
# includ... | # When this metric is never called, `self._true_sum` is None,
# under which case we return 0.0 for backward compatibility.
if self._true_sum is None:
return 0.0
else:
# `self._true_sum` is the total number of instances under each _true_ class,
# includ... | 50 | 667 | 123 | 790 | from typing import Dict
from allennlp.training.metrics.metric import Metric
from allennlp.training.metrics.fbeta_measure import FBetaMeasure
@Metric.register("f1")
class F1Measure(FBetaMeasure):
"""
Computes Precision, Recall and F1 with respect to a given `positive_label`.
For example, for a BIO tagging... | from typing import Dict
from allennlp.training.metrics.metric import Metric
from allennlp.training.metrics.fbeta_measure import FBetaMeasure
@Metric.register("f1")
class F1Measure(FBetaMeasure):
"""
Computes Precision, Recall and F1 with respect to a given `positive_label`.
For example, for a BIO tagging... |
9,123 | /home/hieuvd/dung_repo/raw/stars_01/allenai_allennlp/allennlp | /home/hieuvd/dung_repo/raw/stars_01/allenai_allennlp/allennlp/allennlp/training/metrics/fbeta_verbose_measure.py | 78,79 | 8,155 | get_metric | FBetaVerboseMeasure | 93,155 | 79,155 | @Metric.register("fbeta_verbose")
class FBetaVerboseMeasure(FBetaMeasure):
"""Compute precision, recall, F-measure and support for each class.
This is basically the same as `FBetaMeasure` (the super class)
with two differences:
- it always returns a dictionary of floats, while `FBetaMeasure`
... | @Metric.register("fbeta_verbose")
class FBetaVerboseMeasure(FBetaMeasure):
"""Compute precision, recall, F-measure and support for each class.
This is basically the same as `FBetaMeasure` (the super class)
with two differences:
- it always returns a dictionary of floats, while `FBetaMeasure`
... | if self._true_positive_sum is None or self._pred_sum is None or self._true_sum is None:
raise RuntimeError("You have never called this metric before.")
tp_sum = self._true_positive_sum
pred_sum = self._pred_sum
true_sum = self._true_sum
if self._labels is not None:
... | """
# Returns
<class>-precision : `float`
<class>-recall : `float`
<class>-fscore : `float`
<avg>-precision : `float`
<avg>-recall : `float`
<avg>-fscore : `float`
where <class> is the index (or the label if `index_to_label` is given)
of ... | 207 | 1,010 | 853 | 1,863 | from typing import List, Dict
from allennlp.common.util import nan_safe_tensor_divide
from allennlp.training.metrics.metric import Metric
from allennlp.training.metrics.fbeta_measure import FBetaMeasure
@Metric.register("fbeta_verbose")
class FBetaVerboseMeasure(FBetaMeasure):
"""Compute precision, recall, F-mea... | from typing import List, Dict
from allennlp.common.util import nan_safe_tensor_divide
from allennlp.training.metrics.metric import Metric
from allennlp.training.metrics.fbeta_measure import FBetaMeasure
@Metric.register("fbeta_verbose")
class FBetaVerboseMeasure(FBetaMeasure):
"""Compute precision, recall, F-mea... |
9,124 | /home/hieuvd/dung_repo/raw/stars_01/allenai_allennlp/allennlp | /home/hieuvd/dung_repo/raw/stars_01/allenai_allennlp/allennlp/allennlp/training/metrics/perplexity.py | 19,20 | 7,31 | get_metric | Perplexity | 25,31 | 20,31 | @Metric.register("perplexity")
class Perplexity(Average):
"""
Perplexity is a common metric used for evaluating how well a language model
predicts a sample.
Notes
-----
Assumes negative log likelihood loss of each batch (base e). Provides the
average perplexity of the batches.
"""
... | @Metric.register("perplexity")
class Perplexity(Average):
"""
Perplexity is a common metric used for evaluating how well a language model
predicts a sample.
Notes
-----
Assumes negative log likelihood loss of each batch (base e). Provides the
average perplexity of the batches.
"""
... | average_loss = super().get_metric(reset)
if average_loss == 0:
return 0.0
# Exponentiate the loss to compute perplexity
return math.exp(average_loss)
| """
# Returns
The accumulated perplexity.
"""
average_loss = super().get_metric(reset)
if average_loss == 0:
return 0.0
# Exponentiate the loss to compute perplexity
return math.exp(average_loss)
| 18 | 133 | 62 | 195 | import math
from allennlp.training.metrics.average import Average
from allennlp.training.metrics.metric import Metric
@Metric.register("perplexity")
class Perplexity(Average):
"""
Perplexity is a common metric used for evaluating how well a language model
predicts a sample.
Notes
-----
Assum... | import math
from allennlp.training.metrics.average import Average
from allennlp.training.metrics.metric import Metric
@Metric.register("perplexity")
class Perplexity(Average):
"""
Perplexity is a common metric used for evaluating how well a language model
predicts a sample.
Notes
-----
Assum... |
9,125 | /home/hieuvd/dung_repo/raw/stars_01/allenai_allennlp/allennlp | /home/hieuvd/dung_repo/raw/stars_01/allenai_allennlp/allennlp/benchmarks/data/tokenizers/character_tokenizer_bench.py | 15,16 | 1,17 | bench_character_tokenizer | 16,17 | 16,17 | from allennlp.data.tokenizers import CharacterTokenizer
tokenizer = CharacterTokenizer()
passage = (
"Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor "
"incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis "
"nostrud exercitation ullamco laboris nisi ut... | from allennlp.data.tokenizers import CharacterTokenizer
tokenizer = CharacterTokenizer()
passage = (
"Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor "
"incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis "
"nostrud exercitation ullamco laboris nisi ut... | benchmark(tokenizer.tokenize, passage)
| benchmark(tokenizer.tokenize, passage)
| 2 | 234 | 13 | 247 | from allennlp.data.tokenizers import CharacterTokenizer
tokenizer = CharacterTokenizer()
passage = (
"Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor "
"incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis "
"nostrud exercitation ullamco laboris nisi ut... | from allennlp.data.tokenizers import CharacterTokenizer
tokenizer = CharacterTokenizer()
passage = (
"Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor "
"incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis "
"nostrud exercitation ullamco laboris nisi ut... | |
9,127 | /home/hieuvd/dung_repo/raw/stars_01/allenai_allennlp/allennlp | /home/hieuvd/dung_repo/raw/stars_01/allenai_allennlp/allennlp/scripts/ai2_internal/resume_daemon.py | 74,75 | 59,89 | is_end_state | BeakerStatus | 75,89 | 75,89 | class BeakerStatus(Enum):
submitted = "submitted"
provisioning = "provisioning"
initializing = "initializing"
running = "running"
terminating = "terminating"
preempted = "preempted"
succeeded = "succeeded"
skipped = "skipped"
stopped = "stopped"
failed = "failed"
def __str__... | class BeakerStatus(Enum):
submitted = "submitted"
provisioning = "provisioning"
initializing = "initializing"
running = "running"
terminating = "terminating"
preempted = "preempted"
succeeded = "succeeded"
skipped = "skipped"
stopped = "stopped"
failed = "failed"
def __str__... | if self is BeakerStatus.preempted:
return True
elif self is BeakerStatus.succeeded:
return True
elif self is BeakerStatus.skipped:
return True
elif self is BeakerStatus.stopped:
return True
elif self is BeakerStatus.failed:
... | if self is BeakerStatus.preempted:
return True
elif self is BeakerStatus.succeeded:
return True
elif self is BeakerStatus.skipped:
return True
elif self is BeakerStatus.stopped:
return True
elif self is BeakerStatus.failed:
... | 33 | 133 | 106 | 239 | #! /usr/bin/env python3
# Tool to automatically resume preemptible beaker experiments created with run_with_beaker.py.
#
# Examples
# --------
#
# Ensure an experiment will be resumed:
# resume_daemon.py --action=start --experiment-id=$YOUR_EXPERIMENT_ID
#
# Stop resuming an experiment:
# resume_daemon.py --action=sto... | #! /usr/bin/env python3
# Tool to automatically resume preemptible beaker experiments created with run_with_beaker.py.
#
# Examples
# --------
#
# Ensure an experiment will be resumed:
# resume_daemon.py --action=start --experiment-id=$YOUR_EXPERIMENT_ID
#
# Stop resuming an experiment:
# resume_daemon.py --action=sto... |
9,128 | /home/hieuvd/dung_repo/raw/stars_01/allenai_allennlp/allennlp | /home/hieuvd/dung_repo/raw/stars_01/allenai_allennlp/allennlp/scripts/ai2_internal/resume_daemon.py | 90,91 | 89,154 | get_status | BeakerWrapper | 91,147 | 91,147 | class BeakerWrapper:
def get_status(self, experiment_id: str) -> BeakerStatus:
FILL_FUNC_BODY def resume(self, experiment_id: str) -> str:
command = ["beaker", "experiment", "resume", f"--experiment-name={experiment_id}"]
# Small delay to avoid thrashing Beaker.
time.sleep(BEAKER_QUERY_IN... | class BeakerWrapper:
def get_status(self, experiment_id: str) -> BeakerStatus:
FILL_FUNC_BODY def resume(self, experiment_id: str) -> str:
command = ["beaker", "experiment", "resume", f"--experiment-name={experiment_id}"]
# Small delay to avoid thrashing Beaker.
time.sleep(BEAKER_QUERY_IN... | command = ["beaker", "experiment", "inspect", experiment_id]
experiment_json = subprocess.check_output(command)
# Example output from beaker.
# brendanr.local$ beaker experiment inspect ex_g7knlblsjxxk
# [
# {
# "id": "ex_g7knlblsjxxk",
# ... | command = ["beaker", "experiment", "inspect", experiment_id]
experiment_json = subprocess.check_output(command)
# Example output from beaker.
# brendanr.local$ beaker experiment inspect ex_g7knlblsjxxk
# [
# {
# "id": "ex_g7knlblsjxxk",
# ... | 189 | 139 | 723 | 862 | #! /usr/bin/env python3
# Tool to automatically resume preemptible beaker experiments created with run_with_beaker.py.
#
# Examples
# --------
#
# Ensure an experiment will be resumed:
# resume_daemon.py --action=start --experiment-id=$YOUR_EXPERIMENT_ID
#
# Stop resuming an experiment:
# resume_daemon.py --action=sto... | #! /usr/bin/env python3
# Tool to automatically resume preemptible beaker experiments created with run_with_beaker.py.
#
# Examples
# --------
#
# Ensure an experiment will be resumed:
# resume_daemon.py --action=start --experiment-id=$YOUR_EXPERIMENT_ID
#
# Stop resuming an experiment:
# resume_daemon.py --action=sto... |
9,130 | /home/hieuvd/dung_repo/raw/stars_01/allenai_allennlp/allennlp | /home/hieuvd/dung_repo/raw/stars_01/allenai_allennlp/allennlp/scripts/check_links.py | 42,43 | 1,110 | url_ok | 44,54 | 43,54 | #!/usr/bin/env python
# encoding: UTF-8
"""
Goes through all the inline-links in markdown files and reports the breakages.
"""
import re
import sys
import pathlib
import os
from multiprocessing.dummy import Pool
from typing import Tuple, NamedTuple, Optional
import requests
OK_STATUS_CODES = (
200,
401, #... | #!/usr/bin/env python
# encoding: UTF-8
"""
Goes through all the inline-links in markdown files and reports the breakages.
"""
import re
import sys
import pathlib
import os
from multiprocessing.dummy import Pool
from typing import Tuple, NamedTuple, Optional
import requests
OK_STATUS_CODES = (
200,
401, #... | try:
result = http_session.head(match_tuple.link, timeout=5, allow_redirects=True)
return (
result.ok or result.status_code in OK_STATUS_CODES,
f"status code = {result.status_code}",
)
except (requests.ConnectionError, requests.Timeout):
return False, "con... | """Check if a URL is reachable."""
try:
result = http_session.head(match_tuple.link, timeout=5, allow_redirects=True)
return (
result.ok or result.status_code in OK_STATUS_CODES,
f"status code = {result.status_code}",
)
except (requests.ConnectionError, reques... | 25 | 1,037 | 109 | 1,146 | #!/usr/bin/env python
# encoding: UTF-8
"""
Goes through all the inline-links in markdown files and reports the breakages.
"""
import re
import sys
import pathlib
import os
from multiprocessing.dummy import Pool
from typing import Tuple, NamedTuple, Optional
import requests
OK_STATUS_CODES = (
200,
401, #... | #!/usr/bin/env python
# encoding: UTF-8
"""
Goes through all the inline-links in markdown files and reports the breakages.
"""
import re
import sys
import pathlib
import os
from multiprocessing.dummy import Pool
from typing import Tuple, NamedTuple, Optional
import requests
OK_STATUS_CODES = (
200,
401, #... | |
9,131 | /home/hieuvd/dung_repo/raw/stars_01/allenai_allennlp/allennlp | /home/hieuvd/dung_repo/raw/stars_01/allenai_allennlp/allennlp/scripts/get_version.py | 32,33 | 1,46 | main | 33,44 | 33,44 | #!/usr/bin/env python
import argparse
from typing import Dict
import requests
def parse_args():
parser = argparse.ArgumentParser()
parser.add_argument("version_type", choices=["stable", "latest", "current"])
return parser.parse_args()
def get_current_version() -> str:
VERSION: Dict[str, str] = {}
... | #!/usr/bin/env python
import argparse
from typing import Dict
import requests
def parse_args():
parser = argparse.ArgumentParser()
parser.add_argument("version_type", choices=["stable", "latest", "current"])
return parser.parse_args()
def get_current_version() -> str:
VERSION: Dict[str, str] = {}
... | opts = parse_args()
if opts.version_type == "stable":
print(get_stable_version())
elif opts.version_type == "latest":
print(get_latest_version())
elif opts.version_type == "current":
print(get_current_version())
else:
raise NotImplementedError
| opts = parse_args()
if opts.version_type == "stable":
print(get_stable_version())
elif opts.version_type == "latest":
print(get_latest_version())
elif opts.version_type == "current":
print(get_current_version())
else:
raise NotImplementedError
| 21 | 300 | 99 | 399 | #!/usr/bin/env python
import argparse
from typing import Dict
import requests
def parse_args():
parser = argparse.ArgumentParser()
parser.add_argument("version_type", choices=["stable", "latest", "current"])
return parser.parse_args()
def get_current_version() -> str:
VERSION: Dict[str, str] = {}
... | #!/usr/bin/env python
import argparse
from typing import Dict
import requests
def parse_args():
parser = argparse.ArgumentParser()
parser.add_argument("version_type", choices=["stable", "latest", "current"])
return parser.parse_args()
def get_current_version() -> str:
VERSION: Dict[str, str] = {}
... | |
9,132 | /home/hieuvd/dung_repo/raw/stars_01/allenai_allennlp/allennlp | /home/hieuvd/dung_repo/raw/stars_01/allenai_allennlp/allennlp/scripts/release_notes.py | 21,22 | 1,62 | get_change_log_notes | 22,47 | 22,47 | # encoding: utf-8
"""
Prepares markdown release notes for GitHub releases.
"""
import os
from typing import List
from allennlp.version import VERSION
TAG = os.environ["TAG"]
ADDED_HEADER = "### Added 🎉"
CHANGED_HEADER = "### Changed ⚠️"
FIXED_HEADER = "### Fixed ✅"
REMOVED_HEADER = "### Removed 👋"
def get_cha... | # encoding: utf-8
"""
Prepares markdown release notes for GitHub releases.
"""
import os
from typing import List
from allennlp.version import VERSION
TAG = os.environ["TAG"]
ADDED_HEADER = "### Added 🎉"
CHANGED_HEADER = "### Changed ⚠️"
FIXED_HEADER = "### Fixed ✅"
REMOVED_HEADER = "### Removed 👋"
def get_cha... | in_current_section = False
current_section_notes: List[str] = []
with open("CHANGELOG.md") as changelog:
for line in changelog:
if line.startswith("## "):
if line.startswith("## Unreleased"):
continue
if line.startswith(f"## [{TAG}]"):
... | in_current_section = False
current_section_notes: List[str] = []
with open("CHANGELOG.md") as changelog:
for line in changelog:
if line.startswith("## "):
if line.startswith("## Unreleased"):
continue
if line.startswith(f"## [{TAG}]"):
... | 75 | 283 | 308 | 591 | # encoding: utf-8
"""
Prepares markdown release notes for GitHub releases.
"""
import os
from typing import List
from allennlp.version import VERSION
TAG = os.environ["TAG"]
ADDED_HEADER = "### Added 🎉"
CHANGED_HEADER = "### Changed ⚠️"
FIXED_HEADER = "### Fixed ✅"
REMOVED_HEADER = "### Removed 👋"
def get_cha... | # encoding: utf-8
"""
Prepares markdown release notes for GitHub releases.
"""
import os
from typing import List
from allennlp.version import VERSION
TAG = os.environ["TAG"]
ADDED_HEADER = "### Added 🎉"
CHANGED_HEADER = "### Changed ⚠️"
FIXED_HEADER = "### Fixed ✅"
REMOVED_HEADER = "### Removed 👋"
def get_cha... | |
9,133 | /home/hieuvd/dung_repo/raw/stars_01/allenai_allennlp/allennlp | /home/hieuvd/dung_repo/raw/stars_01/allenai_allennlp/allennlp/scripts/train_fixtures.py | 21,22 | 1,76 | train_fixture | 22,44 | 22,44 | #!/usr/bin/env python
import glob
import logging
import os
import re
import shutil
import sys
import tempfile
sys.path.insert(0, os.path.dirname(os.path.abspath(os.path.join(__file__, os.pardir))))
from allennlp.commands.test_install import _get_module_root
from allennlp.commands.train import train_model_from_file, t... | #!/usr/bin/env python
import glob
import logging
import os
import re
import shutil
import sys
import tempfile
sys.path.insert(0, os.path.dirname(os.path.abspath(os.path.join(__file__, os.pardir))))
from allennlp.commands.test_install import _get_module_root
from allennlp.commands.train import train_model_from_file, t... | config_file = config_prefix + config_filename
serialization_dir = config_prefix + "serialization"
# Train model doesn't like it if we have incomplete serialization
# directories, so remove them if they exist.
if os.path.exists(serialization_dir):
shutil.rmtree(serialization_dir)
# train... | config_file = config_prefix + config_filename
serialization_dir = config_prefix + "serialization"
# Train model doesn't like it if we have incomplete serialization
# directories, so remove them if they exist.
if os.path.exists(serialization_dir):
shutil.rmtree(serialization_dir)
# train... | 59 | 585 | 249 | 834 | #!/usr/bin/env python
import glob
import logging
import os
import re
import shutil
import sys
import tempfile
sys.path.insert(0, os.path.dirname(os.path.abspath(os.path.join(__file__, os.pardir))))
from allennlp.commands.test_install import _get_module_root
from allennlp.commands.train import train_model_from_file, t... | #!/usr/bin/env python
import glob
import logging
import os
import re
import shutil
import sys
import tempfile
sys.path.insert(0, os.path.dirname(os.path.abspath(os.path.join(__file__, os.pardir))))
from allennlp.commands.test_install import _get_module_root
from allennlp.commands.train import train_model_from_file, t... | |
9,134 | /home/hieuvd/dung_repo/raw/stars_01/allenai_allennlp/allennlp | /home/hieuvd/dung_repo/raw/stars_01/allenai_allennlp/allennlp/setup.py | 18,19 | 1,108 | parse_requirements_file | 19,53 | 19,53 | from collections import defaultdict
from setuptools import find_packages, setup
# PEP0440 compatible formatted version, see:
# https://www.python.org/dev/peps/pep-0440/
#
# release markers:
# X.Y
# X.Y.Z # For bugfix releases
#
# pre-release markers:
# X.YaN # Alpha release
# X.YbN # Beta release
# X.Y... | from collections import defaultdict
from setuptools import find_packages, setup
# PEP0440 compatible formatted version, see:
# https://www.python.org/dev/peps/pep-0440/
#
# release markers:
# X.Y
# X.Y.Z # For bugfix releases
#
# pre-release markers:
# X.YaN # Alpha release
# X.YbN # Beta release
# X.Y... | requirements = []
extras = defaultdict(list)
with open(path) as requirements_file:
import re
def fix_url_dependencies(req: str) -> str:
"""Pip and setuptools disagree about how URL dependencies should be handled."""
m = re.match(
r"^(git\+)?(https|ssh... | requirements = []
extras = defaultdict(list)
with open(path) as requirements_file:
import re
def fix_url_dependencies(req: str) -> str:
"""Pip and setuptools disagree about how URL dependencies should be handled."""
m = re.match(
r"^(git\+)?(https|ssh... | 107 | 765 | 394 | 1,159 | from collections import defaultdict
from setuptools import find_packages, setup
# PEP0440 compatible formatted version, see:
# https://www.python.org/dev/peps/pep-0440/
#
# release markers:
# X.Y
# X.Y.Z # For bugfix releases
#
# pre-release markers:
# X.YaN # Alpha release
# X.YbN # Beta release
# X.Y... | from collections import defaultdict
from setuptools import find_packages, setup
# PEP0440 compatible formatted version, see:
# https://www.python.org/dev/peps/pep-0440/
#
# release markers:
# X.Y
# X.Y.Z # For bugfix releases
#
# pre-release markers:
# X.YaN # Alpha release
# X.YbN # Beta release
# X.Y... | |
9,476 | /home/hieuvd/dung_repo/raw/stars_01/apenwarr_sshuttle/sshuttle | /home/hieuvd/dung_repo/raw/stars_01/apenwarr_sshuttle/sshuttle/setup.py | 23,24 | 1,62 | version_scheme | 24,28 | 24,28 | #!/usr/bin/env python
# Copyright 2012-2014 Brian May
#
# This file is part of python-tldap.
#
# python-tldap is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your opt... | #!/usr/bin/env python
# Copyright 2012-2014 Brian May
#
# This file is part of python-tldap.
#
# python-tldap is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your opt... | from setuptools_scm.version import guess_next_dev_version
version = guess_next_dev_version(version)
return version.lstrip("v")
| from setuptools_scm.version import guess_next_dev_version
version = guess_next_dev_version(version)
return version.lstrip("v")
| 9 | 609 | 47 | 656 | #!/usr/bin/env python
# Copyright 2012-2014 Brian May
#
# This file is part of python-tldap.
#
# python-tldap is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your opt... | #!/usr/bin/env python
# Copyright 2012-2014 Brian May
#
# This file is part of python-tldap.
#
# python-tldap is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your opt... | |
9,478 | /home/hieuvd/dung_repo/raw/stars_01/apenwarr_sshuttle/sshuttle | /home/hieuvd/dung_repo/raw/stars_01/apenwarr_sshuttle/sshuttle/sshuttle/client.py | 242,243 | 169,286 | start | FirewallClient | 243,273 | 243,273 | class FirewallClient:
def __init__(self, method_name):
self.auto_nets = []
python_path = os.path.dirname(os.path.dirname(__file__))
argvbase = ([sys.executable, sys.argv[0]] +
['-v'] * (helpers.verbose or 0) +
['--method', method_name] +
... | class FirewallClient:
def __init__(self, method_name):
self.auto_nets = []
python_path = os.path.dirname(os.path.dirname(__file__))
argvbase = ([sys.executable, sys.argv[0]] +
['-v'] * (helpers.verbose or 0) +
['--method', method_name] +
... | self.pfile.write(b'ROUTES\n')
for (family, ip, width) in self.subnets_include + self.auto_nets:
self.pfile.write(b'%d,%d,0,%s\n'
% (family, width, ip.encode("ASCII")))
for (family, ip, width) in self.subnets_exclude:
self.pfile.write(b'%d,%d,1... | self.pfile.write(b'ROUTES\n')
for (family, ip, width) in self.subnets_include + self.auto_nets:
self.pfile.write(b'%d,%d,0,%s\n'
% (family, width, ip.encode("ASCII")))
for (family, ip, width) in self.subnets_exclude:
self.pfile.write(b'%d,%d,1... | 73 | 1,044 | 426 | 1,470 | import socket
import errno
import re
import signal
import time
import subprocess as ssubprocess
import sshuttle.helpers as helpers
import os
import sshuttle.ssnet as ssnet
import sshuttle.ssh as ssh
import sshuttle.ssyslog as ssyslog
import sys
import platform
from sshuttle.ssnet import SockWrapper, Handler, Proxy, Mux... | import socket
import errno
import re
import signal
import time
import subprocess as ssubprocess
import sshuttle.helpers as helpers
import os
import sshuttle.ssnet as ssnet
import sshuttle.ssh as ssh
import sshuttle.ssyslog as ssyslog
import sys
import platform
from sshuttle.ssnet import SockWrapper, Handler, Proxy, Mux... |
9,479 | /home/hieuvd/dung_repo/raw/stars_01/apenwarr_sshuttle/sshuttle | /home/hieuvd/dung_repo/raw/stars_01/apenwarr_sshuttle/sshuttle/sshuttle/client.py | 104,105 | 95,169 | setsockopt | MultiListener | 105,111 | 105,111 | class MultiListener:
def __init__(self, type=socket.SOCK_STREAM, proto=0):
self.type = type
self.proto = proto
self.v6 = None
self.v4 = None
self.bind_called = False
def setsockopt(self, level, optname, value):
FILL_FUNC_BODY def add_handler(self, handlers, callback,... | class MultiListener:
def __init__(self, type=socket.SOCK_STREAM, proto=0):
self.type = type
self.proto = proto
self.v6 = None
self.v4 = None
self.bind_called = False
def setsockopt(self, level, optname, value):
FILL_FUNC_BODY def add_handler(self, handlers, callback,... | assert(self.bind_called)
if self.v6:
self.v6.setsockopt(level, optname, value)
if self.v4:
self.v4.setsockopt(level, optname, value)
| assert(self.bind_called)
if self.v6:
self.v6.setsockopt(level, optname, value)
if self.v4:
self.v4.setsockopt(level, optname, value)
| 11 | 747 | 69 | 816 | import socket
import errno
import re
import signal
import time
import subprocess as ssubprocess
import sshuttle.helpers as helpers
import os
import sshuttle.ssnet as ssnet
import sshuttle.ssh as ssh
import sshuttle.ssyslog as ssyslog
import sys
import platform
from sshuttle.ssnet import SockWrapper, Handler, Proxy, Mux... | import socket
import errno
import re
import signal
import time
import subprocess as ssubprocess
import sshuttle.helpers as helpers
import os
import sshuttle.ssnet as ssnet
import sshuttle.ssh as ssh
import sshuttle.ssyslog as ssyslog
import sys
import platform
from sshuttle.ssnet import SockWrapper, Handler, Proxy, Mux... |
9,480 | /home/hieuvd/dung_repo/raw/stars_01/apenwarr_sshuttle/sshuttle | /home/hieuvd/dung_repo/raw/stars_01/apenwarr_sshuttle/sshuttle/sshuttle/helpers.py | 9,10 | 1,97 | log | 10,28 | 10,28 | import sys
import socket
import errno
logprefix = ''
verbose = 0
def log(s):
FILL_FUNC_BODYdef debug1(s):
if verbose >= 1:
log(s)
def debug2(s):
if verbose >= 2:
log(s)
def debug3(s):
if verbose >= 3:
log(s)
class Fatal(Exception):
pass
def resolvconf_nameservers():
... | import sys
import socket
import errno
logprefix = ''
verbose = 0
def log(s):
FILL_FUNC_BODYdef debug1(s):
if verbose >= 1:
log(s)
def debug2(s):
if verbose >= 2:
log(s)
def debug3(s):
if verbose >= 3:
log(s)
class Fatal(Exception):
pass
def resolvconf_nameservers():
... | global logprefix
try:
sys.stdout.flush()
if s.find("\n") != -1:
prefix = logprefix
s = s.rstrip("\n")
for line in s.split("\n"):
sys.stderr.write(prefix + line + "\n")
prefix = "---> "
else:
sys.stderr.write(... | global logprefix
try:
sys.stdout.flush()
if s.find("\n") != -1:
prefix = logprefix
s = s.rstrip("\n")
for line in s.split("\n"):
sys.stderr.write(prefix + line + "\n")
prefix = "---> "
else:
sys.stderr.write(... | 60 | 538 | 185 | 723 | import sys
import socket
import errno
logprefix = ''
verbose = 0
def log(s):
FILL_FUNC_BODYdef debug1(s):
if verbose >= 1:
log(s)
def debug2(s):
if verbose >= 2:
log(s)
def debug3(s):
if verbose >= 3:
log(s)
class Fatal(Exception):
pass
def resolvconf_nameservers():
... | import sys
import socket
import errno
logprefix = ''
verbose = 0
def log(s):
FILL_FUNC_BODYdef debug1(s):
if verbose >= 1:
log(s)
def debug2(s):
if verbose >= 2:
log(s)
def debug3(s):
if verbose >= 3:
log(s)
class Fatal(Exception):
pass
def resolvconf_nameservers():
... | |
9,482 | /home/hieuvd/dung_repo/raw/stars_01/apenwarr_sshuttle/sshuttle | /home/hieuvd/dung_repo/raw/stars_01/apenwarr_sshuttle/sshuttle/sshuttle/linux.py | 30,31 | 1,63 | ipt | 31,43 | 31,43 | import socket
import subprocess as ssubprocess
from sshuttle.helpers import log, debug1, Fatal, family_to_string
def nonfatal(func, *args):
try:
func(*args)
except Fatal as e:
log('error: %s\n' % e)
def ipt_chain_exists(family, table, name):
if family == socket.AF_INET6:
cmd = 'i... | import socket
import subprocess as ssubprocess
from sshuttle.helpers import log, debug1, Fatal, family_to_string
def nonfatal(func, *args):
try:
func(*args)
except Fatal as e:
log('error: %s\n' % e)
def ipt_chain_exists(family, table, name):
if family == socket.AF_INET6:
cmd = 'i... | if family == socket.AF_INET6:
argv = ['ip6tables', '-t', table] + list(args)
elif family == socket.AF_INET:
argv = ['iptables', '-t', table] + list(args)
else:
raise Exception('Unsupported family "%s"' % family_to_string(family))
debug1('>> %s\n' % ' '.join(argv))
rv = ssubpr... | if family == socket.AF_INET6:
argv = ['ip6tables', '-t', table] + list(args)
elif family == socket.AF_INET:
argv = ['iptables', '-t', table] + list(args)
else:
raise Exception('Unsupported family "%s"' % family_to_string(family))
debug1('>> %s\n' % ' '.join(argv))
rv = ssubpr... | 46 | 520 | 161 | 681 | import socket
import subprocess as ssubprocess
from sshuttle.helpers import log, debug1, Fatal, family_to_string
def nonfatal(func, *args):
try:
func(*args)
except Fatal as e:
log('error: %s\n' % e)
def ipt_chain_exists(family, table, name):
if family == socket.AF_INET6:
cmd = 'i... | import socket
import subprocess as ssubprocess
from sshuttle.helpers import log, debug1, Fatal, family_to_string
def nonfatal(func, *args):
try:
func(*args)
except Fatal as e:
log('error: %s\n' % e)
def ipt_chain_exists(family, table, name):
if family == socket.AF_INET6:
cmd = 'i... | |
9,483 | /home/hieuvd/dung_repo/raw/stars_01/apenwarr_sshuttle/sshuttle | /home/hieuvd/dung_repo/raw/stars_01/apenwarr_sshuttle/sshuttle/sshuttle/methods/nat.py | 14,15 | 7,90 | setup_firewall | Method | 15,65 | 15,65 | class Method(BaseMethod):
# We name the chain based on the transproxy port number so that it's
# possible to run multiple copies of sshuttle at the same time. Of course,
# the multiple copies shouldn't have overlapping subnets, or only the most-
# recently-started one will win (because we use "-I OUTP... | class Method(BaseMethod):
# We name the chain based on the transproxy port number so that it's
# possible to run multiple copies of sshuttle at the same time. Of course,
# the multiple copies shouldn't have overlapping subnets, or only the most-
# recently-started one will win (because we use "-I OUTP... | # only ipv4 supported with NAT
if family != socket.AF_INET:
raise Exception(
'Address family "%s" unsupported by nat method_name'
% family_to_string(family))
if udp:
raise Exception("UDP not supported by nat method_name")
table = "... | # only ipv4 supported with NAT
if family != socket.AF_INET:
raise Exception(
'Address family "%s" unsupported by nat method_name'
% family_to_string(family))
if udp:
raise Exception("UDP not supported by nat method_name")
table = "... | 190 | 400 | 627 | 1,027 | import socket
from sshuttle.helpers import family_to_string
from sshuttle.linux import ipt, ipt_ttl, ipt_chain_exists, nonfatal
from sshuttle.methods import BaseMethod
class Method(BaseMethod):
# We name the chain based on the transproxy port number so that it's
# possible to run multiple copies of sshuttle ... | import socket
from sshuttle.helpers import family_to_string
from sshuttle.linux import ipt, ipt_ttl, ipt_chain_exists, nonfatal
from sshuttle.methods import BaseMethod
class Method(BaseMethod):
# We name the chain based on the transproxy port number so that it's
# possible to run multiple copies of sshuttle ... |
9,486 | /home/hieuvd/dung_repo/raw/stars_01/apenwarr_sshuttle/sshuttle | /home/hieuvd/dung_repo/raw/stars_01/apenwarr_sshuttle/sshuttle/sshuttle/options.py | 104,105 | 77,216 | _gen_usage | Options | 105,166 | 105,166 | class Options:
"""Option parser.
When constructed, two strings are mandatory. The first one is the command
name showed before error messages. The second one is a string called an
optspec that specifies the synopsis and option flags and their description.
For more information about optspecs, consult... | class Options:
"""Option parser.
When constructed, two strings are mandatory. The first one is the command
name showed before error messages. The second one is a string called an
optspec that specifies the synopsis and option flags and their description.
For more information about optspecs, consult... | out = []
lines = self.optspec.strip().split('\n')
lines.reverse()
first_syn = True
while lines:
l = lines.pop()
if l == '--':
break
out.append('%s: %s\n' % (first_syn and 'usage' or ' or', l))
first_syn = False
... | out = []
lines = self.optspec.strip().split('\n')
lines.reverse()
first_syn = True
while lines:
l = lines.pop()
if l == '--':
break
out.append('%s: %s\n' % (first_syn and 'usage' or ' or', l))
first_syn = False
... | 195 | 794 | 768 | 1,562 | """Command-line options parser.
With the help of an options spec string, easily parse command-line options.
"""
import sys
import os
import textwrap
import getopt
import re
import struct
class OptDict:
def __init__(self):
self._opts = {}
def __setitem__(self, k, v):
if k.startswith('no-') or... | """Command-line options parser.
With the help of an options spec string, easily parse command-line options.
"""
import sys
import os
import textwrap
import getopt
import re
import struct
class OptDict:
def __init__(self):
self._opts = {}
def __setitem__(self, k, v):
if k.startswith('no-') or... |
9,487 | /home/hieuvd/dung_repo/raw/stars_01/apenwarr_sshuttle/sshuttle | /home/hieuvd/dung_repo/raw/stars_01/apenwarr_sshuttle/sshuttle/sshuttle/ssh.py | 55,56 | 1,131 | connect | 56,131 | 56,131 | import sys
import os
import re
import socket
import zlib
import imp
import subprocess as ssubprocess
import sshuttle.helpers as helpers
from sshuttle.helpers import debug2
def readfile(name):
tokens = name.split(".")
f = None
token = tokens[0]
token_name = [token]
token_str = ".".join(token_name)... | import sys
import os
import re
import socket
import zlib
import imp
import subprocess as ssubprocess
import sshuttle.helpers as helpers
from sshuttle.helpers import debug2
def readfile(name):
tokens = name.split(".")
f = None
token = tokens[0]
token_name = [token]
token_str = ".".join(token_name)... | portl = []
if (rhostport or '').count(':') > 1:
if rhostport.count(']') or rhostport.count('['):
result = rhostport.split(']')
rhost = result[0].strip('[')
if len(result) > 1:
result[1] = result[1].strip(':')
if result[1] is not '':
... | portl = []
if (rhostport or '').count(':') > 1:
if rhostport.count(']') or rhostport.count('['):
result = rhostport.split(']')
rhost = result[0].strip('[')
if len(result) > 1:
result[1] = result[1].strip(':')
if result[1] is not '':
... | 252 | 406 | 986 | 1,392 | import sys
import os
import re
import socket
import zlib
import imp
import subprocess as ssubprocess
import sshuttle.helpers as helpers
from sshuttle.helpers import debug2
def readfile(name):
tokens = name.split(".")
f = None
token = tokens[0]
token_name = [token]
token_str = ".".join(token_name)... | import sys
import os
import re
import socket
import zlib
import imp
import subprocess as ssubprocess
import sshuttle.helpers as helpers
from sshuttle.helpers import debug2
def readfile(name):
tokens = name.split(".")
f = None
token = tokens[0]
token_name = [token]
token_str = ".".join(token_name)... | |
9,488 | /home/hieuvd/dung_repo/raw/stars_01/apenwarr_sshuttle/sshuttle | /home/hieuvd/dung_repo/raw/stars_01/apenwarr_sshuttle/sshuttle/sshuttle/ssyslog.py | 9,10 | 1,20 | start_syslog | 10,16 | 10,16 | import sys
import os
import subprocess as ssubprocess
_p = None
def start_syslog():
FILL_FUNC_BODYdef stderr_to_syslog():
sys.stdout.flush()
sys.stderr.flush()
os.dup2(_p.stdin.fileno(), 2)
| import sys
import os
import subprocess as ssubprocess
_p = None
def start_syslog():
FILL_FUNC_BODYdef stderr_to_syslog():
sys.stdout.flush()
sys.stderr.flush()
os.dup2(_p.stdin.fileno(), 2)
| global _p
_p = ssubprocess.Popen(['logger',
'-p', 'daemon.notice',
'-t', 'sshuttle'], stdin=ssubprocess.PIPE)
| global _p
_p = ssubprocess.Popen(['logger',
'-p', 'daemon.notice',
'-t', 'sshuttle'], stdin=ssubprocess.PIPE)
| 10 | 87 | 58 | 145 | import sys
import os
import subprocess as ssubprocess
_p = None
def start_syslog():
FILL_FUNC_BODYdef stderr_to_syslog():
sys.stdout.flush()
sys.stderr.flush()
os.dup2(_p.stdin.fileno(), 2)
| import sys
import os
import subprocess as ssubprocess
_p = None
def start_syslog():
FILL_FUNC_BODYdef stderr_to_syslog():
sys.stdout.flush()
sys.stderr.flush()
os.dup2(_p.stdin.fileno(), 2)
| |
9,559 | /home/hieuvd/dung_repo/raw/stars_01/assafelovic_gpt-researcher/gpt-researcher | /home/hieuvd/dung_repo/raw/stars_01/assafelovic_gpt-researcher/gpt-researcher/backend/report_type/basic_report/basic_report.py | 12,13 | 4,23 | run | BasicReport | 13,23 | 13,23 | class BasicReport():
def __init__(self, query: str, report_type: str, source_urls, config_path: str, websocket: WebSocket):
self.query = query
self.report_type = report_type
self.source_urls = source_urls
self.config_path = config_path
self.websocket = websocket
... | class BasicReport():
def __init__(self, query: str, report_type: str, source_urls, config_path: str, websocket: WebSocket):
self.query = query
self.report_type = report_type
self.source_urls = source_urls
self.config_path = config_path
self.websocket = websocket
... | # Initialize researcher
researcher = GPTResearcher(self.query, self.report_type, self.source_urls, self.config_path, self.websocket)
# Run research
await researcher.conduct_research()
# and generate report
report = await researcher.write_report()... | # Initialize researcher
researcher = GPTResearcher(self.query, self.report_type, self.source_urls, self.config_path, self.websocket)
# Run research
await researcher.conduct_research()
# and generate report
report = await researcher.write_report()... | 25 | 112 | 101 | 213 | from gpt_researcher.master.agent import GPTResearcher
from fastapi import WebSocket
class BasicReport():
def __init__(self, query: str, report_type: str, source_urls, config_path: str, websocket: WebSocket):
self.query = query
self.report_type = report_type
self.source_urls = source_urls
... | from gpt_researcher.master.agent import GPTResearcher
from fastapi import WebSocket
class BasicReport():
def __init__(self, query: str, report_type: str, source_urls, config_path: str, websocket: WebSocket):
self.query = query
self.report_type = report_type
self.source_urls = source_urls
... |
9,560 | /home/hieuvd/dung_repo/raw/stars_01/assafelovic_gpt-researcher/gpt-researcher | /home/hieuvd/dung_repo/raw/stars_01/assafelovic_gpt-researcher/gpt-researcher/backend/report_type/detailed_report/detailed_report.py | 29,30 | 10,144 | run | DetailedReport | 30,51 | 30,51 | class DetailedReport():
def __init__(self, query: str, source_urls, config_path: str, websocket: WebSocket, subtopics=[]):
self.query = query
self.source_urls = source_urls
self.config_path = config_path
self.websocket = websocket
self.subtopics = subtopics
#... | class DetailedReport():
def __init__(self, query: str, source_urls, config_path: str, websocket: WebSocket, subtopics=[]):
self.query = query
self.source_urls = source_urls
self.config_path = config_path
self.websocket = websocket
self.subtopics = subtopics
#... |
# Conduct initial research using the main assistant
await self._initial_research()
# Get list of all subtopics
subtopics = await self._get_all_subtopics()
# Generate report introduction
report_introduction = await self.main_task_assistant.write_introduction()
... |
# Conduct initial research using the main assistant
await self._initial_research()
# Get list of all subtopics
subtopics = await self._get_all_subtopics()
# Generate report introduction
report_introduction = await self.main_task_assistant.write_introduction()
... | 72 | 1,355 | 227 | 1,582 | import asyncio
from fastapi import WebSocket
from gpt_researcher.master.agent import GPTResearcher
from gpt_researcher.master.functions import (add_source_urls, extract_headers,
table_of_contents)
class DetailedReport():
def __init__(self, query: str, source_urls, co... | import asyncio
from fastapi import WebSocket
from gpt_researcher.master.agent import GPTResearcher
from gpt_researcher.master.functions import (add_source_urls, extract_headers,
table_of_contents)
class DetailedReport():
def __init__(self, query: str, source_urls, co... |
9,561 | /home/hieuvd/dung_repo/raw/stars_01/assafelovic_gpt-researcher/gpt-researcher | /home/hieuvd/dung_repo/raw/stars_01/assafelovic_gpt-researcher/gpt-researcher/backend/server.py | 40,42 | 1,66 | websocket_endpoint | 42,66 | 42,66 | from fastapi import FastAPI, Request, WebSocket, WebSocketDisconnect
from fastapi.staticfiles import StaticFiles
from fastapi.templating import Jinja2Templates
from pydantic import BaseModel
from backend.websocket_manager import WebSocketManager
from backend.utils import write_md_to_pdf, write_md_to_word, write_text_to... | from fastapi import FastAPI, Request, WebSocket, WebSocketDisconnect
from fastapi.staticfiles import StaticFiles
from fastapi.templating import Jinja2Templates
from pydantic import BaseModel
from backend.websocket_manager import WebSocketManager
from backend.utils import write_md_to_pdf, write_md_to_word, write_text_to... | await manager.connect(websocket)
try:
while True:
data = await websocket.receive_text()
if data.startswith("start"):
json_data = json.loads(data[6:])
task = json_data.get("task")
report_type = json_data.get("report_type")
... | await manager.connect(websocket)
try:
while True:
data = await websocket.receive_text()
if data.startswith("start"):
json_data = json.loads(data[6:])
task = json_data.get("task")
report_type = json_data.get("report_type")
... | 86 | 374 | 325 | 699 | from fastapi import FastAPI, Request, WebSocket, WebSocketDisconnect
from fastapi.staticfiles import StaticFiles
from fastapi.templating import Jinja2Templates
from pydantic import BaseModel
from backend.websocket_manager import WebSocketManager
from backend.utils import write_md_to_pdf, write_md_to_word, write_text_to... | from fastapi import FastAPI, Request, WebSocket, WebSocketDisconnect
from fastapi.staticfiles import StaticFiles
from fastapi.templating import Jinja2Templates
from pydantic import BaseModel
from backend.websocket_manager import WebSocketManager
from backend.utils import write_md_to_pdf, write_md_to_word, write_text_to... | |
9,562 | /home/hieuvd/dung_repo/raw/stars_01/assafelovic_gpt-researcher/gpt-researcher | /home/hieuvd/dung_repo/raw/stars_01/assafelovic_gpt-researcher/gpt-researcher/backend/utils.py | 60,61 | 1,90 | write_md_to_word | 69,90 | 61,90 | import aiofiles
import urllib
import uuid
from md2pdf.core import md2pdf
import mistune
from docx import Document
from htmldocx import HtmlToDocx
async def write_to_file(filename: str, text: str) -> None:
"""Asynchronously write text to a file in UTF-8 encoding.
Args:
filename (str): The filename to w... | import aiofiles
import urllib
import uuid
from md2pdf.core import md2pdf
import mistune
from docx import Document
from htmldocx import HtmlToDocx
async def write_to_file(filename: str, text: str) -> None:
"""Asynchronously write text to a file in UTF-8 encoding.
Args:
filename (str): The filename to w... | file_path = f"outputs/{filename}.docx"
try:
# Convert report markdown to HTML
html = mistune.html(text)
# Create a document object
doc = Document()
# Convert the html generated from the report to document format
HtmlToDocx().add_html_to_document(html, doc)
... | """Converts Markdown text to a DOCX file and returns the file path.
Args:
text (str): Markdown text to convert.
Returns:
str: The encoded file path of the generated DOCX.
"""
file_path = f"outputs/{filename}.docx"
try:
# Convert report markdown to HTML
html = m... | 64 | 663 | 211 | 874 | import aiofiles
import urllib
import uuid
from md2pdf.core import md2pdf
import mistune
from docx import Document
from htmldocx import HtmlToDocx
async def write_to_file(filename: str, text: str) -> None:
"""Asynchronously write text to a file in UTF-8 encoding.
Args:
filename (str): The filename to w... | import aiofiles
import urllib
import uuid
from md2pdf.core import md2pdf
import mistune
from docx import Document
from htmldocx import HtmlToDocx
async def write_to_file(filename: str, text: str) -> None:
"""Asynchronously write text to a file in UTF-8 encoding.
Args:
filename (str): The filename to w... | |
9,563 | /home/hieuvd/dung_repo/raw/stars_01/assafelovic_gpt-researcher/gpt-researcher | /home/hieuvd/dung_repo/raw/stars_01/assafelovic_gpt-researcher/gpt-researcher/backend/websocket_manager.py | 61,62 | 1,80 | run_agent | 63,80 | 62,80 | # connect any client to gpt-researcher using websocket
import asyncio
import datetime
from typing import Dict, List
from fastapi import WebSocket
from backend.report_type import BasicReport, DetailedReport
from gpt_researcher.utils.enum import ReportType
class WebSocketManager:
"""Manage websockets"""
def... | # connect any client to gpt-researcher using websocket
import asyncio
import datetime
from typing import Dict, List
from fastapi import WebSocket
from backend.report_type import BasicReport, DetailedReport
from gpt_researcher.utils.enum import ReportType
class WebSocketManager:
"""Manage websockets"""
def... | # measure time
start_time = datetime.datetime.now()
# add customized JSON config file path here
config_path = ""
# Instead of running the agent directly run it through the different report type classes
if report_type == ReportType.DetailedReport.value:
researcher = DetailedReport(query=t... | """Run the agent."""
# measure time
start_time = datetime.datetime.now()
# add customized JSON config file path here
config_path = ""
# Instead of running the agent directly run it through the different report type classes
if report_type == ReportType.DetailedReport.value:
researcher... | 72 | 577 | 240 | 817 | # connect any client to gpt-researcher using websocket
import asyncio
import datetime
from typing import Dict, List
from fastapi import WebSocket
from backend.report_type import BasicReport, DetailedReport
from gpt_researcher.utils.enum import ReportType
class WebSocketManager:
"""Manage websockets"""
def... | # connect any client to gpt-researcher using websocket
import asyncio
import datetime
from typing import Dict, List
from fastapi import WebSocket
from backend.report_type import BasicReport, DetailedReport
from gpt_researcher.utils.enum import ReportType
class WebSocketManager:
"""Manage websockets"""
def... | |
9,564 | /home/hieuvd/dung_repo/raw/stars_01/assafelovic_gpt-researcher/gpt-researcher | /home/hieuvd/dung_repo/raw/stars_01/assafelovic_gpt-researcher/gpt-researcher/backend/websocket_manager.py | 38,39 | 13,61 | connect | WebSocketManager | 40,46 | 39,46 | class WebSocketManager:
"""Manage websockets"""
def __init__(self):
"""Initialize the WebSocketManager class."""
self.active_connections: List[WebSocket] = []
self.sender_tasks: Dict[WebSocket, asyncio.Task] = {}
self.message_queues: Dict[WebSocket, asyncio.Queue] = {}
asyn... | class WebSocketManager:
"""Manage websockets"""
def __init__(self):
"""Initialize the WebSocketManager class."""
self.active_connections: List[WebSocket] = []
self.sender_tasks: Dict[WebSocket, asyncio.Task] = {}
self.message_queues: Dict[WebSocket, asyncio.Queue] = {}
asyn... | await websocket.accept()
self.active_connections.append(websocket)
self.message_queues[websocket] = asyncio.Queue()
self.sender_tasks[websocket] = asyncio.create_task(
self.start_sender(websocket))
| """Connect a websocket."""
await websocket.accept()
self.active_connections.append(websocket)
self.message_queues[websocket] = asyncio.Queue()
self.sender_tasks[websocket] = asyncio.create_task(
self.start_sender(websocket))
| 10 | 405 | 84 | 489 | # connect any client to gpt-researcher using websocket
import asyncio
import datetime
from typing import Dict, List
from fastapi import WebSocket
from backend.report_type import BasicReport, DetailedReport
from gpt_researcher.utils.enum import ReportType
class WebSocketManager:
"""Manage websockets"""
def... | # connect any client to gpt-researcher using websocket
import asyncio
import datetime
from typing import Dict, List
from fastapi import WebSocket
from backend.report_type import BasicReport, DetailedReport
from gpt_researcher.utils.enum import ReportType
class WebSocketManager:
"""Manage websockets"""
def... |
9,565 | /home/hieuvd/dung_repo/raw/stars_01/assafelovic_gpt-researcher/gpt-researcher | /home/hieuvd/dung_repo/raw/stars_01/assafelovic_gpt-researcher/gpt-researcher/cli.py | 70,71 | 1,94 | main | 75,90 | 71,90 | """
Provides a command line interface for the GPTResearcher class.
Usage:
```shell
python cli.py "<query>" --report_type <report_type>
```
"""
import asyncio
import argparse
from argparse import RawTextHelpFormatter
from uuid import uuid4
from dotenv import load_dotenv
from gpt_researcher import GPTResearcher
from... | """
Provides a command line interface for the GPTResearcher class.
Usage:
```shell
python cli.py "<query>" --report_type <report_type>
```
"""
import asyncio
import argparse
from argparse import RawTextHelpFormatter
from uuid import uuid4
from dotenv import load_dotenv
from gpt_researcher import GPTResearcher
from... | researcher = GPTResearcher(
query=args.query,
report_type=args.report_type)
await researcher.conduct_research()
report = await researcher.write_report()
# Write the report to a file
artifact_filepath = f"outputs/{uuid4()}.md"
with open(artifact_filepath, "w") as f:
f.w... | """
Conduct research on the given query, generate the report, and write
it as a markdown file to the output directory.
"""
researcher = GPTResearcher(
query=args.query,
report_type=args.report_type)
await researcher.conduct_research()
report = await researcher.write_report... | 31 | 586 | 142 | 728 | """
Provides a command line interface for the GPTResearcher class.
Usage:
```shell
python cli.py "<query>" --report_type <report_type>
```
"""
import asyncio
import argparse
from argparse import RawTextHelpFormatter
from uuid import uuid4
from dotenv import load_dotenv
from gpt_researcher import GPTResearcher
from... | """
Provides a command line interface for the GPTResearcher class.
Usage:
```shell
python cli.py "<query>" --report_type <report_type>
```
"""
import asyncio
import argparse
from argparse import RawTextHelpFormatter
from uuid import uuid4
from dotenv import load_dotenv
from gpt_researcher import GPTResearcher
from... | |
9,566 | /home/hieuvd/dung_repo/raw/stars_01/assafelovic_gpt-researcher/gpt-researcher | /home/hieuvd/dung_repo/raw/stars_01/assafelovic_gpt-researcher/gpt-researcher/examples/sample_report.py | 5,6 | 1,27 | main | 9,25 | 6,25 | from gpt_researcher import GPTResearcher
import asyncio
async def main():
FILL_FUNC_BODYif __name__ == "__main__":
asyncio.run(main())
| from gpt_researcher import GPTResearcher
import asyncio
async def main():
"""
This is a sample script that shows how to run a research report.
"""
FILL_FUNC_BODYif __name__ == "__main__":
asyncio.run(main())
| # Query
query = "What happened in the latest burning man floods?"
# Report Type
report_type = "research_report"
# Initialize the researcher
researcher = GPTResearcher(query=query, report_type=report_type, config_path=None)
# Conduct research on the given query
await researcher.conduct_... | """
This is a sample script that shows how to run a research report.
"""
# Query
query = "What happened in the latest burning man floods?"
# Report Type
report_type = "research_report"
# Initialize the researcher
researcher = GPTResearcher(query=query, report_type=report_type, conf... | 46 | 77 | 138 | 215 | from gpt_researcher import GPTResearcher
import asyncio
async def main():
FILL_FUNC_BODYif __name__ == "__main__":
asyncio.run(main())
| from gpt_researcher import GPTResearcher
import asyncio
async def main():
"""
This is a sample script that shows how to run a research report.
"""
FILL_FUNC_BODYif __name__ == "__main__":
asyncio.run(main())
| |
9,567 | /home/hieuvd/dung_repo/raw/stars_01/assafelovic_gpt-researcher/gpt-researcher | /home/hieuvd/dung_repo/raw/stars_01/assafelovic_gpt-researcher/gpt-researcher/gpt_researcher/config/config.py | 35,36 | 6,44 | load_config_file | Config | 37,44 | 36,44 | class Config:
"""Config class for GPT Researcher."""
def __init__(self, config_file: str = None):
"""Initialize the config class."""
self.config_file = config_file if config_file else os.getenv('CONFIG_FILE')
self.retriever = os.getenv('SEARCH_RETRIEVER', "tavily")
self.embeddin... | class Config:
"""Config class for GPT Researcher."""
def __init__(self, config_file: str = None):
"""Initialize the config class."""
self.config_file = config_file if config_file else os.getenv('CONFIG_FILE')
self.retriever = os.getenv('SEARCH_RETRIEVER', "tavily")
self.embeddin... | if self.config_file is None:
return None
with open(self.config_file, "r") as f:
config = json.load(f)
for key, value in config.items():
self.__dict__[key] = value
| """Load the config file."""
if self.config_file is None:
return None
with open(self.config_file, "r") as f:
config = json.load(f)
for key, value in config.items():
self.__dict__[key] = value
| 22 | 732 | 72 | 804 | # config file
import json
import os
class Config:
"""Config class for GPT Researcher."""
def __init__(self, config_file: str = None):
"""Initialize the config class."""
self.config_file = config_file if config_file else os.getenv('CONFIG_FILE')
self.retriever = os.getenv('SEARCH_RETRI... | # config file
import json
import os
class Config:
"""Config class for GPT Researcher."""
def __init__(self, config_file: str = None):
"""Initialize the config class."""
self.config_file = config_file if config_file else os.getenv('CONFIG_FILE')
self.retriever = os.getenv('SEARCH_RETRI... |
9,568 | /home/hieuvd/dung_repo/raw/stars_01/assafelovic_gpt-researcher/gpt-researcher | /home/hieuvd/dung_repo/raw/stars_01/assafelovic_gpt-researcher/gpt-researcher/gpt_researcher/context/compression.py | 20,21 | 12,45 | _get_contextual_retriever | ContextCompressor | 21,35 | 21,35 | class ContextCompressor:
def __init__(self, documents, embeddings, max_results=5, **kwargs):
self.max_results = max_results
self.documents = documents
self.kwargs = kwargs
self.embeddings = embeddings
self.similarity_threshold = 0.38
def _get_contextual_retriever(self):
... | class ContextCompressor:
def __init__(self, documents, embeddings, max_results=5, **kwargs):
self.max_results = max_results
self.documents = documents
self.kwargs = kwargs
self.embeddings = embeddings
self.similarity_threshold = 0.38
def _get_contextual_retriever(self):
... | splitter = RecursiveCharacterTextSplitter(chunk_size=1000, chunk_overlap=100)
relevance_filter = EmbeddingsFilter(embeddings=self.embeddings,
similarity_threshold=self.similarity_threshold)
pipeline_compressor = DocumentCompressorPipeline(
... | splitter = RecursiveCharacterTextSplitter(chunk_size=1000, chunk_overlap=100)
relevance_filter = EmbeddingsFilter(embeddings=self.embeddings,
similarity_threshold=self.similarity_threshold)
pipeline_compressor = DocumentCompressorPipeline(
... | 27 | 277 | 195 | 472 | from .retriever import SearchAPIRetriever
from langchain.retrievers import (
ContextualCompressionRetriever,
)
from langchain.retrievers.document_compressors import (
DocumentCompressorPipeline,
EmbeddingsFilter,
)
from langchain.text_splitter import RecursiveCharacterTextSplitter
class ContextCompressor:... | from .retriever import SearchAPIRetriever
from langchain.retrievers import (
ContextualCompressionRetriever,
)
from langchain.retrievers.document_compressors import (
DocumentCompressorPipeline,
EmbeddingsFilter,
)
from langchain.text_splitter import RecursiveCharacterTextSplitter
class ContextCompressor:... |
9,569 | /home/hieuvd/dung_repo/raw/stars_01/assafelovic_gpt-researcher/gpt-researcher | /home/hieuvd/dung_repo/raw/stars_01/assafelovic_gpt-researcher/gpt-researcher/gpt_researcher/context/retriever.py | 14,17 | 10,30 | _get_relevant_documents | SearchAPIRetriever | 17,30 | 17,30 | class SearchAPIRetriever(BaseRetriever):
"""Search API retriever."""
pages: List[Dict] = []
def _get_relevant_documents(
self, query: str, *, run_manager: CallbackManagerForRetrieverRun
) -> List[Document]:
FILL_FUNC_BODY | class SearchAPIRetriever(BaseRetriever):
"""Search API retriever."""
pages: List[Dict] = []
def _get_relevant_documents(
self, query: str, *, run_manager: CallbackManagerForRetrieverRun
) -> List[Document]:
FILL_FUNC_BODY |
docs = [
Document(
page_content=page.get("raw_content", ""),
metadata={
"title": page.get("title", ""),
"source": page.get("url", ""),
},
)
for page in self.pages
]
retur... |
docs = [
Document(
page_content=page.get("raw_content", ""),
metadata={
"title": page.get("title", ""),
"source": page.get("url", ""),
},
)
for page in self.pages
]
retur... | 22 | 88 | 94 | 182 | import os
from enum import Enum
from typing import Any, Dict, List, Optional
from langchain.callbacks.manager import CallbackManagerForRetrieverRun
from langchain.schema import Document
from langchain.schema.retriever import BaseRetriever
class SearchAPIRetriever(BaseRetriever):
"""Search API retriever."""
p... | import os
from enum import Enum
from typing import Any, Dict, List, Optional
from langchain.callbacks.manager import CallbackManagerForRetrieverRun
from langchain.schema import Document
from langchain.schema.retriever import BaseRetriever
class SearchAPIRetriever(BaseRetriever):
"""Search API retriever."""
p... |
9,570 | /home/hieuvd/dung_repo/raw/stars_01/assafelovic_gpt-researcher/gpt-researcher | /home/hieuvd/dung_repo/raw/stars_01/assafelovic_gpt-researcher/gpt-researcher/gpt_researcher/llm_provider/azureopenai/azureopenai.py | 68,69 | 20,86 | stream_response | AzureOpenAIProvider | 69,86 | 69,86 | class AzureOpenAIProvider:
def __init__(
self,
deployment_name,
temperature,
max_tokens
):
self.deployment_name = deployment_name
self.temperature = temperature
self.max_tokens = max_tokens
self.api_key = self.get_api_key()
self.llm = self... | class AzureOpenAIProvider:
def __init__(
self,
deployment_name,
temperature,
max_tokens
):
self.deployment_name = deployment_name
self.temperature = temperature
self.max_tokens = max_tokens
self.api_key = self.get_api_key()
self.llm = self... | paragraph = ""
response = ""
# Streaming the response using the chain astream method from langchain
async for chunk in self.llm.astream(messages):
content = chunk.content
if content is not None:
response += content
paragraph += con... | paragraph = ""
response = ""
# Streaming the response using the chain astream method from langchain
async for chunk in self.llm.astream(messages):
content = chunk.content
if content is not None:
response += content
paragraph += con... | 57 | 406 | 162 | 568 | import os
from colorama import Fore, Style
from langchain_openai import AzureChatOpenAI
'''
Please note:
Needs additional env vars such as:
AZURE_OPENAI_ENDPOINT e.g. https://xxxx.openai.azure.com/",
AZURE_OPENAI_API_KEY e.g "xxxxxxxxxxxxxxxxxxxxx",
OPENAI_API_VERSION, e.g. "2024-03-01-preview" but need... | import os
from colorama import Fore, Style
from langchain_openai import AzureChatOpenAI
'''
Please note:
Needs additional env vars such as:
AZURE_OPENAI_ENDPOINT e.g. https://xxxx.openai.azure.com/",
AZURE_OPENAI_API_KEY e.g "xxxxxxxxxxxxxxxxxxxxx",
OPENAI_API_VERSION, e.g. "2024-03-01-preview" but need... |
9,571 | /home/hieuvd/dung_repo/raw/stars_01/assafelovic_gpt-researcher/gpt-researcher | /home/hieuvd/dung_repo/raw/stars_01/assafelovic_gpt-researcher/gpt-researcher/gpt_researcher/llm_provider/google/google.py | 86,87 | 8,104 | stream_response | GoogleProvider | 87,104 | 87,104 | class GoogleProvider:
def __init__(
self,
model,
temperature,
max_tokens
):
# May be extended to support more google models in the future
self.model = "gemini-pro"
self.temperature = temperature
self.max_tokens = max_tokens
self.api_key = ... | class GoogleProvider:
def __init__(
self,
model,
temperature,
max_tokens
):
# May be extended to support more google models in the future
self.model = "gemini-pro"
self.temperature = temperature
self.max_tokens = max_tokens
self.api_key = ... | paragraph = ""
response = ""
# Streaming the response using the chain astream method from langchain
async for chunk in self.llm.astream(messages):
content = chunk.content
if content is not None:
response += content
paragraph += con... | paragraph = ""
response = ""
# Streaming the response using the chain astream method from langchain
async for chunk in self.llm.astream(messages):
content = chunk.content
if content is not None:
response += content
paragraph += con... | 57 | 731 | 161 | 892 | import os
from colorama import Fore, Style
from langchain_core.messages import HumanMessage, SystemMessage
from langchain_google_genai import ChatGoogleGenerativeAI
class GoogleProvider:
def __init__(
self,
model,
temperature,
max_tokens
):
# May be extended to suppor... | import os
from colorama import Fore, Style
from langchain_core.messages import HumanMessage, SystemMessage
from langchain_google_genai import ChatGoogleGenerativeAI
class GoogleProvider:
def __init__(
self,
model,
temperature,
max_tokens
):
# May be extended to suppor... |
9,573 | /home/hieuvd/dung_repo/raw/stars_01/assafelovic_gpt-researcher/gpt-researcher | /home/hieuvd/dung_repo/raw/stars_01/assafelovic_gpt-researcher/gpt-researcher/gpt_researcher/llm_provider/openai/openai.py | 22,23 | 7,86 | get_api_key | OpenAIProvider | 28,35 | 23,35 | class OpenAIProvider:
def __init__(
self,
model,
temperature,
max_tokens
):
self.model = model
self.temperature = temperature
self.max_tokens = max_tokens
self.api_key = self.get_api_key()
self.base_url = self.get_base_url()
self.l... | class OpenAIProvider:
def __init__(
self,
model,
temperature,
max_tokens
):
self.model = model
self.temperature = temperature
self.max_tokens = max_tokens
self.api_key = self.get_api_key()
self.base_url = self.get_base_url()
self.l... | try:
api_key = os.environ["OPENAI_API_KEY"]
except KeyError:
raise Exception(
"OpenAI API key not found. Please set the OPENAI_API_KEY environment variable.")
return api_key
| """
Gets the OpenAI API key
Returns:
"""
try:
api_key = os.environ["OPENAI_API_KEY"]
except KeyError:
raise Exception(
"OpenAI API key not found. Please set the OPENAI_API_KEY environment variable.")
return api_key
| 21 | 575 | 71 | 646 | import os
from colorama import Fore, Style
from langchain_openai import ChatOpenAI
class OpenAIProvider:
def __init__(
self,
model,
temperature,
max_tokens
):
self.model = model
self.temperature = temperature
self.max_tokens = max_tokens
self.a... | import os
from colorama import Fore, Style
from langchain_openai import ChatOpenAI
class OpenAIProvider:
def __init__(
self,
model,
temperature,
max_tokens
):
self.model = model
self.temperature = temperature
self.max_tokens = max_tokens
self.a... |
9,575 | /home/hieuvd/dung_repo/raw/stars_01/assafelovic_gpt-researcher/gpt-researcher | /home/hieuvd/dung_repo/raw/stars_01/assafelovic_gpt-researcher/gpt-researcher/gpt_researcher/retrievers/bing/bing.py | 34,35 | 9,89 | search | BingSearch | 40,89 | 35,89 | class BingSearch():
"""
Bing Search Retriever
"""
def __init__(self, query):
"""
Initializes the BingSearch object
Args:
query:
"""
self.query = query
self.api_key = self.get_api_key()
def get_api_key(self):
"""
Gets the Bi... | class BingSearch():
"""
Bing Search Retriever
"""
def __init__(self, query):
"""
Initializes the BingSearch object
Args:
query:
"""
self.query = query
self.api_key = self.get_api_key()
def get_api_key(self):
"""
Gets the Bi... | print("Searching with query {0}...".format(self.query))
"""Useful for general internet search queries using the Bing API."""
# Search the query
url = "https://api.bing.microsoft.com/v7.0/search"
headers = {
'Ocp-Apim-Subscription-Key': self.api_key,
'Content-Ty... | """
Searches the query
Returns:
"""
print("Searching with query {0}...".format(self.query))
"""Useful for general internet search queries using the Bing API."""
# Search the query
url = "https://api.bing.microsoft.com/v7.0/search"
headers = {
... | 119 | 206 | 440 | 646 | # Bing Search Retriever
# libraries
import os
import requests
import json
class BingSearch():
"""
Bing Search Retriever
"""
def __init__(self, query):
"""
Initializes the BingSearch object
Args:
query:
"""
self.query = query
self.api_key = s... | # Bing Search Retriever
# libraries
import os
import requests
import json
class BingSearch():
"""
Bing Search Retriever
"""
def __init__(self, query):
"""
Initializes the BingSearch object
Args:
query:
"""
self.query = query
self.api_key = s... |
9,576 | /home/hieuvd/dung_repo/raw/stars_01/assafelovic_gpt-researcher/gpt-researcher | /home/hieuvd/dung_repo/raw/stars_01/assafelovic_gpt-researcher/gpt-researcher/gpt_researcher/retrievers/duckduckgo/duckduckgo.py | 13,14 | 5,22 | search | Duckduckgo | 20,22 | 14,22 | class Duckduckgo:
"""
Duckduckgo API Retriever
"""
def __init__(self, query):
self.ddg = DDGS()
self.query = query
def search(self, max_results=5):
FILL_FUNC_BODY | class Duckduckgo:
"""
Duckduckgo API Retriever
"""
def __init__(self, query):
self.ddg = DDGS()
self.query = query
def search(self, max_results=5):
"""
Performs the search
:param query:
:param max_results:
:return:
"""
FILL_FUNC_BODY | ddgs_gen = self.ddg.text(self.query, region='wt-wt', max_results=max_results)
return ddgs_gen | """
Performs the search
:param query:
:param max_results:
:return:
"""
ddgs_gen = self.ddg.text(self.query, region='wt-wt', max_results=max_results)
return ddgs_gen | 7 | 108 | 43 | 151 | from itertools import islice
from duckduckgo_search import DDGS
class Duckduckgo:
"""
Duckduckgo API Retriever
"""
def __init__(self, query):
self.ddg = DDGS()
self.query = query
def search(self, max_results=5):
FILL_FUNC_BODY | from itertools import islice
from duckduckgo_search import DDGS
class Duckduckgo:
"""
Duckduckgo API Retriever
"""
def __init__(self, query):
self.ddg = DDGS()
self.query = query
def search(self, max_results=5):
"""
Performs the search
:param query:
... |
9,577 | /home/hieuvd/dung_repo/raw/stars_01/assafelovic_gpt-researcher/gpt-researcher | /home/hieuvd/dung_repo/raw/stars_01/assafelovic_gpt-researcher/gpt-researcher/gpt_researcher/retrievers/google/google.py | 53,54 | 10,89 | search | GoogleSearch | 59,89 | 54,89 | class GoogleSearch:
"""
Tavily API Retriever
"""
def __init__(self, query):
"""
Initializes the TavilySearch object
Args:
query:
"""
self.query = query
self.api_key = self.get_api_key() #GOOGLE_API_KEY
self.cx_key = self.get_cx_key() #G... | class GoogleSearch:
"""
Tavily API Retriever
"""
def __init__(self, query):
"""
Initializes the TavilySearch object
Args:
query:
"""
self.query = query
self.api_key = self.get_api_key() #GOOGLE_API_KEY
self.cx_key = self.get_cx_key() #G... | """Useful for general internet search queries using the Google API."""
print("Searching with query {0}...".format(self.query))
url = f"https://www.googleapis.com/customsearch/v1?key={self.api_key}&cx={self.cx_key}&q={self.query}&start=1"
resp = requests.get(url)
if resp is None:... | """
Searches the query
Returns:
"""
"""Useful for general internet search queries using the Google API."""
print("Searching with query {0}...".format(self.query))
url = f"https://www.googleapis.com/customsearch/v1?key={self.api_key}&cx={self.cx_key}&q={self.query... | 82 | 430 | 304 | 734 | # Tavily API Retriever
# libraries
import os
import requests
import json
from tavily import TavilyClient
class GoogleSearch:
"""
Tavily API Retriever
"""
def __init__(self, query):
"""
Initializes the TavilySearch object
Args:
query:
"""
self.query ... | # Tavily API Retriever
# libraries
import os
import requests
import json
from tavily import TavilyClient
class GoogleSearch:
"""
Tavily API Retriever
"""
def __init__(self, query):
"""
Initializes the TavilySearch object
Args:
query:
"""
self.query ... |
9,578 | /home/hieuvd/dung_repo/raw/stars_01/assafelovic_gpt-researcher/gpt-researcher | /home/hieuvd/dung_repo/raw/stars_01/assafelovic_gpt-researcher/gpt-researcher/gpt_researcher/retrievers/searx/searx.py | 37,38 | 9,48 | search | SearxSearch | 43,48 | 38,48 | class SearxSearch():
"""
Tavily API Retriever
"""
def __init__(self, query):
"""
Initializes the TavilySearch object
Args:
query:
"""
self.query = query
self.api_key = self.get_api_key()
self.client = TavilyClient(self.api_key)
def... | class SearxSearch():
"""
Tavily API Retriever
"""
def __init__(self, query):
"""
Initializes the TavilySearch object
Args:
query:
"""
self.query = query
self.api_key = self.get_api_key()
self.client = TavilyClient(self.api_key)
def... | searx = SearxSearchWrapper(searx_host=os.environ["SEARX_URL"])
results = searx.results(self.query, max_results)
# Normalizing results to match the format of the other search APIs
search_response = [{"href": obj["link"], "body": obj["snippet"]} for obj in results]
return search_re... | """
Searches the query
Returns:
"""
searx = SearxSearchWrapper(searx_host=os.environ["SEARX_URL"])
results = searx.results(self.query, max_results)
# Normalizing results to match the format of the other search APIs
search_response = [{"href": obj["link"],... | 31 | 252 | 104 | 356 | # Tavily API Retriever
# libraries
import os
from tavily import TavilyClient
from langchain_community.utilities import SearxSearchWrapper
class SearxSearch():
"""
Tavily API Retriever
"""
def __init__(self, query):
"""
Initializes the TavilySearch object
Args:
quer... | # Tavily API Retriever
# libraries
import os
from tavily import TavilyClient
from langchain_community.utilities import SearxSearchWrapper
class SearxSearch():
"""
Tavily API Retriever
"""
def __init__(self, query):
"""
Initializes the TavilySearch object
Args:
quer... |
9,579 | /home/hieuvd/dung_repo/raw/stars_01/assafelovic_gpt-researcher/gpt-researcher | /home/hieuvd/dung_repo/raw/stars_01/assafelovic_gpt-researcher/gpt-researcher/gpt_researcher/retrievers/serpapi/serpapi.py | 36,37 | 9,79 | search | SerpApiSearch | 42,79 | 37,79 | class SerpApiSearch():
"""
SerpApi Retriever
"""
def __init__(self, query):
"""
Initializes the SerpApiSearch object
Args:
query:
"""
raise NotImplementedError("SerpApiSearch is not fully implemented yet.")
self.query = query
self.api_k... | class SerpApiSearch():
"""
SerpApi Retriever
"""
def __init__(self, query):
"""
Initializes the SerpApiSearch object
Args:
query:
"""
raise NotImplementedError("SerpApiSearch is not fully implemented yet.")
self.query = query
self.api_k... | print("Searching with query {0}...".format(self.query))
"""Useful for general internet search queries using SerpApi."""
# Perform the search
# TODO: query needs to be url encoded, so the code won't work as is.
# Encoding should look something like this (but this is untested):
... | """
Searches the query
Returns:
"""
print("Searching with query {0}...".format(self.query))
"""Useful for general internet search queries using SerpApi."""
# Perform the search
# TODO: query needs to be url encoded, so the code won't work as is.
... | 127 | 250 | 380 | 630 | # SerpApi Retriever
# libraries
import os
import requests
import json
class SerpApiSearch():
"""
SerpApi Retriever
"""
def __init__(self, query):
"""
Initializes the SerpApiSearch object
Args:
query:
"""
raise NotImplementedError("SerpApiSearch is n... | # SerpApi Retriever
# libraries
import os
import requests
import json
class SerpApiSearch():
"""
SerpApi Retriever
"""
def __init__(self, query):
"""
Initializes the SerpApiSearch object
Args:
query:
"""
raise NotImplementedError("SerpApiSearch is n... |
9,580 | /home/hieuvd/dung_repo/raw/stars_01/assafelovic_gpt-researcher/gpt-researcher | /home/hieuvd/dung_repo/raw/stars_01/assafelovic_gpt-researcher/gpt-researcher/gpt_researcher/retrievers/serper/serper.py | 35,36 | 9,82 | search | SerperSearch | 41,82 | 36,82 | class SerperSearch():
"""
Google Serper Retriever
"""
def __init__(self, query):
"""
Initializes the SerperSearch object
Args:
query:
"""
self.query = query
self.api_key = self.get_api_key()
def get_api_key(self):
"""
Gets ... | class SerperSearch():
"""
Google Serper Retriever
"""
def __init__(self, query):
"""
Initializes the SerperSearch object
Args:
query:
"""
self.query = query
self.api_key = self.get_api_key()
def get_api_key(self):
"""
Gets ... | print("Searching with query {0}...".format(self.query))
"""Useful for general internet search queries using the Serp API."""
# Search the query (see https://serper.dev/playground for the format)
url = "https://google.serper.dev/search"
headers = {
'X-API-KEY': self.api... | """
Searches the query
Returns:
"""
print("Searching with query {0}...".format(self.query))
"""Useful for general internet search queries using the Serp API."""
# Search the query (see https://serper.dev/playground for the format)
url = "https://google.... | 110 | 224 | 372 | 596 | # Google Serper Retriever
# libraries
import os
import requests
import json
class SerperSearch():
"""
Google Serper Retriever
"""
def __init__(self, query):
"""
Initializes the SerperSearch object
Args:
query:
"""
self.query = query
self.api... | # Google Serper Retriever
# libraries
import os
import requests
import json
class SerperSearch():
"""
Google Serper Retriever
"""
def __init__(self, query):
"""
Initializes the SerperSearch object
Args:
query:
"""
self.query = query
self.api... |
9,581 | /home/hieuvd/dung_repo/raw/stars_01/assafelovic_gpt-researcher/gpt-researcher | /home/hieuvd/dung_repo/raw/stars_01/assafelovic_gpt-researcher/gpt-researcher/gpt_researcher/retrievers/tavily_news/tavily_news.py | 23,24 | 8,48 | get_api_key | TavilyNews | 29,37 | 24,37 | class TavilyNews():
"""
Tavily News API Retriever
Retrieve news articles from the Tavily News API
"""
def __init__(self, query):
"""
Initializes the TavilySearch object
Args:
query:
"""
self.query = query
self.api_key = self.get_api_key()
... | class TavilyNews():
"""
Tavily News API Retriever
Retrieve news articles from the Tavily News API
"""
def __init__(self, query):
"""
Initializes the TavilySearch object
Args:
query:
"""
self.query = query
self.api_key = self.get_api_key()
... | # Get the API key
try:
api_key = os.environ["TAVILY_API_KEY"]
except:
raise Exception("Tavily API key not found. Please set the TAVILY_API_KEY environment variable. "
"You can get a key at https://app.tavily.com")
return api_key
| """
Gets the Tavily API key
Returns:
"""
# Get the API key
try:
api_key = os.environ["TAVILY_API_KEY"]
except:
raise Exception("Tavily API key not found. Please set the TAVILY_API_KEY environment variable. "
"Yo... | 32 | 271 | 97 | 368 | # Tavily API Retriever
# libraries
import os
from tavily import TavilyClient
class TavilyNews():
"""
Tavily News API Retriever
Retrieve news articles from the Tavily News API
"""
def __init__(self, query):
"""
Initializes the TavilySearch object
Args:
query:
... | # Tavily API Retriever
# libraries
import os
from tavily import TavilyClient
class TavilyNews():
"""
Tavily News API Retriever
Retrieve news articles from the Tavily News API
"""
def __init__(self, query):
"""
Initializes the TavilySearch object
Args:
query:
... |
9,582 | /home/hieuvd/dung_repo/raw/stars_01/assafelovic_gpt-researcher/gpt-researcher | /home/hieuvd/dung_repo/raw/stars_01/assafelovic_gpt-researcher/gpt-researcher/gpt_researcher/retrievers/tavily_search/tavily_search.py | 37,38 | 9,53 | search | TavilySearch | 43,53 | 38,53 | class TavilySearch():
"""
Tavily API Retriever
"""
def __init__(self, query):
"""
Initializes the TavilySearch object
Args:
query:
"""
self.query = query
self.api_key = self.get_api_key()
self.client = TavilyClient(self.api_key)
de... | class TavilySearch():
"""
Tavily API Retriever
"""
def __init__(self, query):
"""
Initializes the TavilySearch object
Args:
query:
"""
self.query = query
self.api_key = self.get_api_key()
self.client = TavilyClient(self.api_key)
de... | try:
# Search the query
results = self.client.search(self.query, search_depth="advanced", max_results=max_results)
# Return the results
search_response = [{"href": obj["url"], "body": obj["content"]} for obj in results.get("results", [])]
except Exception ... | """
Searches the query
Returns:
"""
try:
# Search the query
results = self.client.search(self.query, search_depth="advanced", max_results=max_results)
# Return the results
search_response = [{"href": obj["url"], "body": obj["conten... | 50 | 259 | 169 | 428 | # Tavily API Retriever
# libraries
import os
from tavily import TavilyClient
from duckduckgo_search import DDGS
class TavilySearch():
"""
Tavily API Retriever
"""
def __init__(self, query):
"""
Initializes the TavilySearch object
Args:
query:
"""
se... | # Tavily API Retriever
# libraries
import os
from tavily import TavilyClient
from duckduckgo_search import DDGS
class TavilySearch():
"""
Tavily API Retriever
"""
def __init__(self, query):
"""
Initializes the TavilySearch object
Args:
query:
"""
se... |
9,583 | /home/hieuvd/dung_repo/raw/stars_01/assafelovic_gpt-researcher/gpt-researcher | /home/hieuvd/dung_repo/raw/stars_01/assafelovic_gpt-researcher/gpt-researcher/gpt_researcher/scraper/arxiv/arxiv.py | 10,11 | 4,23 | scrape | ArxivScraper | 19,23 | 11,23 | class ArxivScraper:
def __init__(self, link, session=None):
self.link = link
self.session = session
def scrape(self):
FILL_FUNC_BODY | class ArxivScraper:
def __init__(self, link, session=None):
self.link = link
self.session = session
def scrape(self):
"""
The function scrapes relevant documents from Arxiv based on a given link and returns the content
of the first document.
Returns:
... | query = self.link.split("/")[-1]
retriever = ArxivRetriever(load_max_docs=2, doc_content_chars_max=None)
docs = retriever.get_relevant_documents(query=query)
return docs[0].page_content
| """
The function scrapes relevant documents from Arxiv based on a given link and returns the content
of the first document.
Returns:
The code is returning the page content of the first document retrieved by the ArxivRetriever
for a given query extracted from th... | 12 | 131 | 82 | 213 | from langchain_community.retrievers import ArxivRetriever
class ArxivScraper:
def __init__(self, link, session=None):
self.link = link
self.session = session
def scrape(self):
FILL_FUNC_BODY | from langchain_community.retrievers import ArxivRetriever
class ArxivScraper:
def __init__(self, link, session=None):
self.link = link
self.session = session
def scrape(self):
"""
The function scrapes relevant documents from Arxiv based on a given link and returns the content... |
9,584 | /home/hieuvd/dung_repo/raw/stars_01/assafelovic_gpt-researcher/gpt-researcher | /home/hieuvd/dung_repo/raw/stars_01/assafelovic_gpt-researcher/gpt-researcher/gpt_researcher/scraper/beautiful_soup/beautiful_soup.py | 40,41 | 4,54 | get_content_from_url | BeautifulSoupScraper | 49,54 | 41,54 | class BeautifulSoupScraper:
def __init__(self, link, session=None):
self.link = link
self.session = session
def scrape(self):
"""
This function scrapes content from a webpage by making a GET request, parsing the HTML using
BeautifulSoup, and extracting script and style ... | class BeautifulSoupScraper:
def __init__(self, link, session=None):
self.link = link
self.session = session
def scrape(self):
"""
This function scrapes content from a webpage by making a GET request, parsing the HTML using
BeautifulSoup, and extracting script and style ... | text = ""
tags = ["p", "h1", "h2", "h3", "h4", "h5"]
for element in soup.find_all(tags): # Find all the <p> elements
text += element.text + "\n"
return text
| """Get the text from the soup
Args:
soup (BeautifulSoup): The soup to get the text from
Returns:
str: The text from the soup
"""
text = ""
tags = ["p", "h1", "h2", "h3", "h4", "h5"]
for element in soup.find_all(tags): # Find all the <p> ... | 28 | 457 | 74 | 531 | from bs4 import BeautifulSoup
class BeautifulSoupScraper:
def __init__(self, link, session=None):
self.link = link
self.session = session
def scrape(self):
"""
This function scrapes content from a webpage by making a GET request, parsing the HTML using
BeautifulSoup, ... | from bs4 import BeautifulSoup
class BeautifulSoupScraper:
def __init__(self, link, session=None):
self.link = link
self.session = session
def scrape(self):
"""
This function scrapes content from a webpage by making a GET request, parsing the HTML using
BeautifulSoup, ... |
9,585 | /home/hieuvd/dung_repo/raw/stars_01/assafelovic_gpt-researcher/gpt-researcher | /home/hieuvd/dung_repo/raw/stars_01/assafelovic_gpt-researcher/gpt-researcher/gpt_researcher/scraper/newspaper/newspaper.py | 10,11 | 4,43 | scrape | NewspaperScraper | 21,43 | 11,43 | class NewspaperScraper:
def __init__(self, link, session=None):
self.link = link
self.session = session
def scrape(self) -> str:
FILL_FUNC_BODY | class NewspaperScraper:
def __init__(self, link, session=None):
self.link = link
self.session = session
def scrape(self) -> str:
"""
This Python function scrapes an article from a given link, extracts the title and text content,
and returns them concatenated with a colo... | try:
article = Article(
self.link,
language="en",
memoize_articles=False,
fetch_images=False,
)
article.download()
article.parse()
title = article.title
text = article.text
... | """
This Python function scrapes an article from a given link, extracts the title and text content,
and returns them concatenated with a colon.
Returns:
The `scrape` method returns a string that contains the title of the article followed by a
colon and the text... | 49 | 179 | 159 | 338 | from newspaper import Article
class NewspaperScraper:
def __init__(self, link, session=None):
self.link = link
self.session = session
def scrape(self) -> str:
FILL_FUNC_BODY | from newspaper import Article
class NewspaperScraper:
def __init__(self, link, session=None):
self.link = link
self.session = session
def scrape(self) -> str:
"""
This Python function scrapes an article from a given link, extracts the title and text content,
and retur... |
9,586 | /home/hieuvd/dung_repo/raw/stars_01/assafelovic_gpt-researcher/gpt-researcher | /home/hieuvd/dung_repo/raw/stars_01/assafelovic_gpt-researcher/gpt-researcher/gpt_researcher/scraper/pymupdf/pymupdf.py | 10,11 | 4,22 | scrape | PyMuPDFScraper | 19,22 | 11,22 | class PyMuPDFScraper:
def __init__(self, link, session=None):
self.link = link
self.session = session
def scrape(self) -> str:
FILL_FUNC_BODY | class PyMuPDFScraper:
def __init__(self, link, session=None):
self.link = link
self.session = session
def scrape(self) -> str:
"""
The `scrape` function uses PyMuPDFLoader to load a document from a given link and returns it as
a string.
Returns:
... | loader = PyMuPDFLoader(self.link)
doc = loader.load()
return str(doc)
| """
The `scrape` function uses PyMuPDFLoader to load a document from a given link and returns it as
a string.
Returns:
The `scrape` method is returning a string representation of the `doc` object, which is loaded
using PyMuPDFLoader from the provided link.
... | 8 | 143 | 32 | 175 | from langchain_community.document_loaders import PyMuPDFLoader
class PyMuPDFScraper:
def __init__(self, link, session=None):
self.link = link
self.session = session
def scrape(self) -> str:
FILL_FUNC_BODY | from langchain_community.document_loaders import PyMuPDFLoader
class PyMuPDFScraper:
def __init__(self, link, session=None):
self.link = link
self.session = session
def scrape(self) -> str:
"""
The `scrape` function uses PyMuPDFLoader to load a document from a given link and ... |
9,587 | /home/hieuvd/dung_repo/raw/stars_01/assafelovic_gpt-researcher/gpt-researcher | /home/hieuvd/dung_repo/raw/stars_01/assafelovic_gpt-researcher/gpt-researcher/gpt_researcher/scraper/scraper.py | 41,42 | 15,96 | extract_data_from_link | Scraper | 45,57 | 42,57 | class Scraper:
"""
Scraper class to extract the content from the links
"""
def __init__(self, urls, user_agent, scraper):
"""
Initialize the Scraper class.
Args:
urls:
"""
self.urls = urls
self.session = requests.Session()
self.session... | class Scraper:
"""
Scraper class to extract the content from the links
"""
def __init__(self, urls, user_agent, scraper):
"""
Initialize the Scraper class.
Args:
urls:
"""
self.urls = urls
self.session = requests.Session()
self.session... | content = ""
try:
Scraper = self.get_scraper(link)
scraper = Scraper(link, session)
content = scraper.scrape()
if len(content) < 100:
return {"url": link, "raw_content": None}
return {"url": link, "raw_content": content}
... | """
Extracts the data from the link
"""
content = ""
try:
Scraper = self.get_scraper(link)
scraper = Scraper(link, session)
content = scraper.scrape()
if len(content) < 100:
return {"url": link, "raw_content": None}... | 37 | 727 | 127 | 854 | from concurrent.futures.thread import ThreadPoolExecutor
from functools import partial
import requests
from gpt_researcher.scraper import (
ArxivScraper,
BeautifulSoupScraper,
NewspaperScraper,
PyMuPDFScraper,
WebBaseLoaderScraper,
)
class Scraper:
"""
Scraper class to extract the conten... | from concurrent.futures.thread import ThreadPoolExecutor
from functools import partial
import requests
from gpt_researcher.scraper import (
ArxivScraper,
BeautifulSoupScraper,
NewspaperScraper,
PyMuPDFScraper,
WebBaseLoaderScraper,
)
class Scraper:
"""
Scraper class to extract the conten... |
9,588 | /home/hieuvd/dung_repo/raw/stars_01/assafelovic_gpt-researcher/gpt-researcher | /home/hieuvd/dung_repo/raw/stars_01/assafelovic_gpt-researcher/gpt-researcher/gpt_researcher/scraper/web_base_loader/web_base_loader.py | 10,11 | 4,34 | scrape | WebBaseLoaderScraper | 20,34 | 11,34 | class WebBaseLoaderScraper:
def __init__(self, link, session=None):
self.link = link
self.session = session
def scrape(self) -> str:
FILL_FUNC_BODY | class WebBaseLoaderScraper:
def __init__(self, link, session=None):
self.link = link
self.session = session
def scrape(self) -> str:
"""
This Python function scrapes content from a webpage using a WebBaseLoader object and returns the
concatenated page content.
... | try:
loader = WebBaseLoader(self.link)
loader.requests_kwargs = {"verify": False}
docs = loader.load()
content = ""
for doc in docs:
content += doc.page_content
return content
except Exception as e:
pr... | """
This Python function scrapes content from a webpage using a WebBaseLoader object and returns the
concatenated page content.
Returns:
The `scrape` method is returning a string variable named `content` which contains the
concatenated page content from the doc... | 34 | 162 | 107 | 269 | from langchain_community.document_loaders import WebBaseLoader
class WebBaseLoaderScraper:
def __init__(self, link, session=None):
self.link = link
self.session = session
def scrape(self) -> str:
FILL_FUNC_BODY | from langchain_community.document_loaders import WebBaseLoader
class WebBaseLoaderScraper:
def __init__(self, link, session=None):
self.link = link
self.session = session
def scrape(self) -> str:
"""
This Python function scrapes content from a webpage using a WebBaseLoader ob... |
9,589 | /home/hieuvd/dung_repo/raw/stars_01/assafelovic_gpt-researcher/gpt-researcher | /home/hieuvd/dung_repo/raw/stars_01/assafelovic_gpt-researcher/gpt-researcher/multi_agents/agents/publisher.py | 19,20 | 9,58 | generate_layout | PublisherAgent | 20,44 | 20,44 | class PublisherAgent:
def __init__(self, output_dir: str):
self.output_dir = output_dir
async def publish_research_report(self, research_state: dict, publish_formats: dict):
layout = self.generate_layout(research_state)
await self.write_report_by_formats(layout, publish_formats)
... | class PublisherAgent:
def __init__(self, output_dir: str):
self.output_dir = output_dir
async def publish_research_report(self, research_state: dict, publish_formats: dict):
layout = self.generate_layout(research_state)
await self.write_report_by_formats(layout, publish_formats)
... | sections = '\n\n'.join(f"{value}"
for subheader in research_state.get("research_data")
for key, value in subheader.items())
references = '\n'.join(f"{reference}" for reference in research_state.get("sources"))
headers = research_s... | sections = '\n\n'.join(f"{value}"
for subheader in research_state.get("research_data")
for key, value in subheader.items())
references = '\n'.join(f"{reference}" for reference in research_state.get("sources"))
headers = research_s... | 45 | 367 | 253 | 620 | from .utils.file_formats import \
write_md_to_pdf, \
write_md_to_word, \
write_text_to_md
from .utils.views import print_agent_output
class PublisherAgent:
def __init__(self, output_dir: str):
self.output_dir = output_dir
async def publish_research_report(self, research_state: dict, publ... | from .utils.file_formats import \
write_md_to_pdf, \
write_md_to_word, \
write_text_to_md
from .utils.views import print_agent_output
class PublisherAgent:
def __init__(self, output_dir: str):
self.output_dir = output_dir
async def publish_research_report(self, research_state: dict, publ... |
9,590 | /home/hieuvd/dung_repo/raw/stars_01/assafelovic_gpt-researcher/gpt-researcher | /home/hieuvd/dung_repo/raw/stars_01/assafelovic_gpt-researcher/gpt-researcher/multi_agents/agents/reviewer.py | 12,13 | 8,63 | review_draft | ReviewerAgent | 18,50 | 13,50 | class ReviewerAgent:
def __init__(self):
pass
def review_draft(self, draft_state: dict):
FILL_FUNC_BODY def run(self, draft_state: dict):
task = draft_state.get("task")
guidelines = task.get("guidelines")
to_follow_guidelines = task.get("follow_guidelines")
review = N... | class ReviewerAgent:
def __init__(self):
pass
def review_draft(self, draft_state: dict):
"""
Review a draft article
:param draft_state:
:return:
"""
FILL_FUNC_BODY def run(self, draft_state: dict):
task = draft_state.get("task")
guidelines = ta... | task = draft_state.get("task")
guidelines = '- '.join(guideline for guideline in task.get("guidelines"))
revision_notes = draft_state.get("revision_notes")
revise_prompt = f"""The reviser has already revised the draft based on your previous review notes with the following feedback:
{rev... | """
Review a draft article
:param draft_state:
:return:
"""
task = draft_state.get("task")
guidelines = '- '.join(guideline for guideline in task.get("guidelines"))
revision_notes = draft_state.get("revision_notes")
revise_prompt = f"""The reviser... | 177 | 265 | 394 | 659 | from .utils.views import print_agent_output
from .utils.llms import call_model
TEMPLATE = """You are an expert research article reviewer. \
Your goal is to review research drafts and provide feedback to the reviser only based on specific guidelines. \
"""
class ReviewerAgent:
def __init__(self):
pass
... | from .utils.views import print_agent_output
from .utils.llms import call_model
TEMPLATE = """You are an expert research article reviewer. \
Your goal is to review research drafts and provide feedback to the reviser only based on specific guidelines. \
"""
class ReviewerAgent:
def __init__(self):
pass
... |
9,591 | /home/hieuvd/dung_repo/raw/stars_01/assafelovic_gpt-researcher/gpt-researcher | /home/hieuvd/dung_repo/raw/stars_01/assafelovic_gpt-researcher/gpt-researcher/multi_agents/agents/reviser.py | 18,19 | 14,51 | revise_draft | ReviserAgent | 24,44 | 19,44 | class ReviserAgent:
def __init__(self):
pass
def revise_draft(self, draft_state: dict):
FILL_FUNC_BODY def run(self, draft_state: dict):
draft_title = draft_state.get("title")
print_agent_output(f"Rewriting draft based on feedback...", agent="REVISOR")
revision = self.revise_... | class ReviserAgent:
def __init__(self):
pass
def revise_draft(self, draft_state: dict):
"""
Review a draft article
:param draft_state:
:return:
"""
FILL_FUNC_BODY def run(self, draft_state: dict):
draft_title = draft_state.get("title")
print_ag... | review = draft_state.get("review")
task = draft_state.get("task")
draft_report = draft_state.get("draft")
prompt = [{
"role": "system",
"content": "You are an expert writer. Your goal is to revise drafts based on reviewer notes."
}, {
"role": "... | """
Review a draft article
:param draft_state:
:return:
"""
review = draft_state.get("review")
task = draft_state.get("task")
draft_report = draft_state.get("draft")
prompt = [{
"role": "system",
"content": "You are an exper... | 112 | 208 | 279 | 487 | from .utils.views import print_agent_output
from .utils.llms import call_model
import json
sample_revision_notes = """
{
"draft": {
draft title: The revised draft that you are submitting for review
},
"revision_notes": Your message to the reviewer about the changes you made to the draft based on their feed... | from .utils.views import print_agent_output
from .utils.llms import call_model
import json
sample_revision_notes = """
{
"draft": {
draft title: The revised draft that you are submitting for review
},
"revision_notes": Your message to the reviewer about the changes you made to the draft based on their feed... |
9,592 | /home/hieuvd/dung_repo/raw/stars_01/assafelovic_gpt-researcher/gpt-researcher | /home/hieuvd/dung_repo/raw/stars_01/assafelovic_gpt-researcher/gpt-researcher/multi_agents/agents/utils/file_formats.py | 10,11 | 1,99 | write_to_file | 17,24 | 11,24 | import aiofiles
import urllib
import uuid
import mistune
from md2pdf.core import md2pdf
from docx import Document
from htmldocx import HtmlToDocx
async def write_to_file(filename: str, text: str) -> None:
FILL_FUNC_BODYasync def write_text_to_md(text: str, path: str) -> str:
"""Writes text to a Markdown file and ... | import aiofiles
import urllib
import uuid
import mistune
from md2pdf.core import md2pdf
from docx import Document
from htmldocx import HtmlToDocx
async def write_to_file(filename: str, text: str) -> None:
"""Asynchronously write text to a file in UTF-8 encoding.
Args:
filename (str): The filename to ... | # Convert text to UTF-8, replacing any problematic characters
text_utf8 = text.encode('utf-8', errors='replace').decode('utf-8')
async with aiofiles.open(filename, "w", encoding='utf-8') as file:
await file.write(text_utf8)
| """Asynchronously write text to a file in UTF-8 encoding.
Args:
filename (str): The filename to write to.
text (str): The text to write.
"""
# Convert text to UTF-8, replacing any problematic characters
text_utf8 = text.encode('utf-8', errors='replace').decode('utf-8')
async wi... | 22 | 825 | 90 | 915 | import aiofiles
import urllib
import uuid
import mistune
from md2pdf.core import md2pdf
from docx import Document
from htmldocx import HtmlToDocx
async def write_to_file(filename: str, text: str) -> None:
FILL_FUNC_BODYasync def write_text_to_md(text: str, path: str) -> str:
"""Writes text to a Markdown file and ... | import aiofiles
import urllib
import uuid
import mistune
from md2pdf.core import md2pdf
from docx import Document
from htmldocx import HtmlToDocx
async def write_to_file(filename: str, text: str) -> None:
"""Asynchronously write text to a file in UTF-8 encoding.
Args:
filename (str): The filename to ... | |
9,593 | /home/hieuvd/dung_repo/raw/stars_01/assafelovic_gpt-researcher/gpt-researcher | /home/hieuvd/dung_repo/raw/stars_01/assafelovic_gpt-researcher/gpt-researcher/multi_agents/agents/utils/llms.py | 5,6 | 1,16 | call_model | 6,16 | 6,16 | from langchain.adapters.openai import convert_openai_messages
from langchain_openai import ChatOpenAI
def call_model(prompt: list, model: str, max_retries: int = 2, response_format: str = None) -> str:
FILL_FUNC_BODY | from langchain.adapters.openai import convert_openai_messages
from langchain_openai import ChatOpenAI
def call_model(prompt: list, model: str, max_retries: int = 2, response_format: str = None) -> str:
FILL_FUNC_BODY |
optional_params = {}
if response_format == 'json':
optional_params = {
"response_format": {"type": "json_object"}
}
lc_messages = convert_openai_messages(prompt)
response = ChatOpenAI(model=model, max_retries=max_retries, model_kwargs=optional_params).invoke(lc_messages).co... |
optional_params = {}
if response_format == 'json':
optional_params = {
"response_format": {"type": "json_object"}
}
lc_messages = convert_openai_messages(prompt)
response = ChatOpenAI(model=model, max_retries=max_retries, model_kwargs=optional_params).invoke(lc_messages).co... | 24 | 77 | 111 | 188 | from langchain.adapters.openai import convert_openai_messages
from langchain_openai import ChatOpenAI
def call_model(prompt: list, model: str, max_retries: int = 2, response_format: str = None) -> str:
FILL_FUNC_BODY | from langchain.adapters.openai import convert_openai_messages
from langchain_openai import ChatOpenAI
def call_model(prompt: list, model: str, max_retries: int = 2, response_format: str = None) -> str:
FILL_FUNC_BODY | |
9,594 | /home/hieuvd/dung_repo/raw/stars_01/assafelovic_gpt-researcher/gpt-researcher | /home/hieuvd/dung_repo/raw/stars_01/assafelovic_gpt-researcher/gpt-researcher/multi_agents/agents/utils/views.py | 15,16 | 1,17 | print_agent_output | 16,17 | 16,17 | from colorama import Fore, Style
from enum import Enum
class AgentColor(Enum):
RESEARCHER = Fore.LIGHTBLUE_EX
EDITOR = Fore.YELLOW
WRITER = Fore.LIGHTGREEN_EX
PUBLISHER = Fore.MAGENTA
REVIEWER = Fore.CYAN
REVISOR = Fore.LIGHTWHITE_EX
MASTER = Fore.LIGHTYELLOW_EX
def print_agent_output(ou... | from colorama import Fore, Style
from enum import Enum
class AgentColor(Enum):
RESEARCHER = Fore.LIGHTBLUE_EX
EDITOR = Fore.YELLOW
WRITER = Fore.LIGHTGREEN_EX
PUBLISHER = Fore.MAGENTA
REVIEWER = Fore.CYAN
REVISOR = Fore.LIGHTWHITE_EX
MASTER = Fore.LIGHTYELLOW_EX
def print_agent_output(ou... | print(f"{AgentColor[agent].value}{agent}: {output}{Style.RESET_ALL}") | print(f"{AgentColor[agent].value}{agent}: {output}{Style.RESET_ALL}") | 2 | 155 | 27 | 182 | from colorama import Fore, Style
from enum import Enum
class AgentColor(Enum):
RESEARCHER = Fore.LIGHTBLUE_EX
EDITOR = Fore.YELLOW
WRITER = Fore.LIGHTGREEN_EX
PUBLISHER = Fore.MAGENTA
REVIEWER = Fore.CYAN
REVISOR = Fore.LIGHTWHITE_EX
MASTER = Fore.LIGHTYELLOW_EX
def print_agent_output(ou... | from colorama import Fore, Style
from enum import Enum
class AgentColor(Enum):
RESEARCHER = Fore.LIGHTBLUE_EX
EDITOR = Fore.YELLOW
WRITER = Fore.LIGHTGREEN_EX
PUBLISHER = Fore.MAGENTA
REVIEWER = Fore.CYAN
REVISOR = Fore.LIGHTWHITE_EX
MASTER = Fore.LIGHTYELLOW_EX
def print_agent_output(ou... | |
9,595 | /home/hieuvd/dung_repo/raw/stars_01/assafelovic_gpt-researcher/gpt-researcher | /home/hieuvd/dung_repo/raw/stars_01/assafelovic_gpt-researcher/gpt-researcher/multi_agents/main.py | 13,14 | 1,23 | main | 14,21 | 14,21 | from dotenv import load_dotenv
from agents import MasterAgent
import asyncio
import json
import os
# Run with LangSmith if API key is set
if os.environ.get("LANGCHAIN_API_KEY"):
os.environ["LANGCHAIN_TRACING_V2"] = "true"
load_dotenv()
async def main():
FILL_FUNC_BODYif __name__ == "__main__":
asyncio.run(ma... | from dotenv import load_dotenv
from agents import MasterAgent
import asyncio
import json
import os
# Run with LangSmith if API key is set
if os.environ.get("LANGCHAIN_API_KEY"):
os.environ["LANGCHAIN_TRACING_V2"] = "true"
load_dotenv()
async def main():
FILL_FUNC_BODYif __name__ == "__main__":
asyncio.run(ma... | with open('task.json', 'r') as f:
task = json.load(f)
master_agent = MasterAgent(task)
research_report = await master_agent.run()
print(research_report)
| with open('task.json', 'r') as f:
task = json.load(f)
master_agent = MasterAgent(task)
research_report = await master_agent.run()
print(research_report)
| 16 | 123 | 67 | 190 | from dotenv import load_dotenv
from agents import MasterAgent
import asyncio
import json
import os
# Run with LangSmith if API key is set
if os.environ.get("LANGCHAIN_API_KEY"):
os.environ["LANGCHAIN_TRACING_V2"] = "true"
load_dotenv()
async def main():
FILL_FUNC_BODYif __name__ == "__main__":
asyncio.run(ma... | from dotenv import load_dotenv
from agents import MasterAgent
import asyncio
import json
import os
# Run with LangSmith if API key is set
if os.environ.get("LANGCHAIN_API_KEY"):
os.environ["LANGCHAIN_TRACING_V2"] = "true"
load_dotenv()
async def main():
FILL_FUNC_BODYif __name__ == "__main__":
asyncio.run(ma... | |
9,596 | /home/hieuvd/dung_repo/raw/stars_01/assafelovic_gpt-researcher/gpt-researcher | /home/hieuvd/dung_repo/raw/stars_01/assafelovic_gpt-researcher/gpt-researcher/scraping/processing/html.py | 8,9 | 1,34 | extract_hyperlinks | 18,24 | 9,24 | """HTML processing functions"""
from __future__ import annotations
from bs4 import BeautifulSoup
from requests.compat import urljoin
def extract_hyperlinks(soup: BeautifulSoup, base_url: str) -> list[tuple[str, str]]:
FILL_FUNC_BODYdef format_hyperlinks(hyperlinks: list[tuple[str, str]]) -> list[str]:
"""Format ... | """HTML processing functions"""
from __future__ import annotations
from bs4 import BeautifulSoup
from requests.compat import urljoin
def extract_hyperlinks(soup: BeautifulSoup, base_url: str) -> list[tuple[str, str]]:
"""Extract hyperlinks from a BeautifulSoup object
Args:
soup (BeautifulSoup): The ... | return [
(link.text, urljoin(base_url, link["href"]))
for link in soup.find_all("a", href=True)
]
| """Extract hyperlinks from a BeautifulSoup object
Args:
soup (BeautifulSoup): The BeautifulSoup object
base_url (str): The base URL
Returns:
List[Tuple[str, str]]: The extracted hyperlinks
"""
return [
(link.text, urljoin(base_url, link["href"]))
for link in... | 11 | 262 | 51 | 313 | """HTML processing functions"""
from __future__ import annotations
from bs4 import BeautifulSoup
from requests.compat import urljoin
def extract_hyperlinks(soup: BeautifulSoup, base_url: str) -> list[tuple[str, str]]:
FILL_FUNC_BODYdef format_hyperlinks(hyperlinks: list[tuple[str, str]]) -> list[str]:
"""Format ... | """HTML processing functions"""
from __future__ import annotations
from bs4 import BeautifulSoup
from requests.compat import urljoin
def extract_hyperlinks(soup: BeautifulSoup, base_url: str) -> list[tuple[str, str]]:
"""Extract hyperlinks from a BeautifulSoup object
Args:
soup (BeautifulSoup): The ... | |
9,597 | /home/hieuvd/dung_repo/raw/stars_01/assafelovic_gpt-researcher/gpt-researcher | /home/hieuvd/dung_repo/raw/stars_01/assafelovic_gpt-researcher/gpt-researcher/scraping/scrape_skills.py | 19,20 | 1,32 | scrape_pdf_with_arxiv | 29,32 | 20,32 | from langchain.document_loaders import PyMuPDFLoader
from langchain.retrievers import ArxivRetriever
def scrape_pdf_with_pymupdf(url) -> str:
"""Scrape a pdf with pymupdf
Args:
url (str): The url of the pdf to scrape
Returns:
str: The text scraped from the pdf
"""
loader = PyMuPD... | from langchain.document_loaders import PyMuPDFLoader
from langchain.retrievers import ArxivRetriever
def scrape_pdf_with_pymupdf(url) -> str:
"""Scrape a pdf with pymupdf
Args:
url (str): The url of the pdf to scrape
Returns:
str: The text scraped from the pdf
"""
loader = PyMuPD... | retriever = ArxivRetriever(load_max_docs=2, doc_content_chars_max=None)
docs = retriever.get_relevant_documents(query=query)
return docs[0].page_content | """Scrape a pdf with arxiv
default document length of 70000 about ~15 pages or None for no limit
Args:
query (str): The query to search for
Returns:
str: The text scraped from the pdf
"""
retriever = ArxivRetriever(load_max_docs=2, doc_content_chars_max=None)
docs = retriev... | 9 | 232 | 66 | 298 | from langchain.document_loaders import PyMuPDFLoader
from langchain.retrievers import ArxivRetriever
def scrape_pdf_with_pymupdf(url) -> str:
"""Scrape a pdf with pymupdf
Args:
url (str): The url of the pdf to scrape
Returns:
str: The text scraped from the pdf
"""
loader = PyMuPD... | from langchain.document_loaders import PyMuPDFLoader
from langchain.retrievers import ArxivRetriever
def scrape_pdf_with_pymupdf(url) -> str:
"""Scrape a pdf with pymupdf
Args:
url (str): The url of the pdf to scrape
Returns:
str: The text scraped from the pdf
"""
loader = PyMuPD... | |
9,598 | /home/hieuvd/dung_repo/raw/stars_01/automl_auto-sklearn/auto-sklearn | /home/hieuvd/dung_repo/raw/stars_01/automl_auto-sklearn/auto-sklearn/autosklearn/evaluation/util.py | 9,12 | 1,57 | read_queue | 12,37 | 12,37 | from typing import Any, Dict, List, Optional, Tuple, Union
import multiprocessing
import queue
__all__ = ["read_queue"]
def read_queue(
queue_: multiprocessing.Queue,
) -> List[Dict[str, Union[str, bool, int, float, List, Dict, Tuple]]]:
FILL_FUNC_BODYdef empty_queue(queue_: multiprocessing.Queue) -> None:
... | from typing import Any, Dict, List, Optional, Tuple, Union
import multiprocessing
import queue
__all__ = ["read_queue"]
def read_queue(
queue_: multiprocessing.Queue,
) -> List[Dict[str, Union[str, bool, int, float, List, Dict, Tuple]]]:
FILL_FUNC_BODYdef empty_queue(queue_: multiprocessing.Queue) -> None:
... | stack = []
while True:
try:
return_value = queue_.get(timeout=1)
except queue.Empty:
break
# Check if there is a special placeholder value which tells us that
# we don't have to wait until the queue times out in order to
# retrieve the final value... | stack = []
while True:
try:
return_value = queue_.get(timeout=1)
except queue.Empty:
break
# Check if there is a special placeholder value which tells us that
# we don't have to wait until the queue times out in order to
# retrieve the final value... | 70 | 262 | 198 | 460 | from typing import Any, Dict, List, Optional, Tuple, Union
import multiprocessing
import queue
__all__ = ["read_queue"]
def read_queue(
queue_: multiprocessing.Queue,
) -> List[Dict[str, Union[str, bool, int, float, List, Dict, Tuple]]]:
FILL_FUNC_BODYdef empty_queue(queue_: multiprocessing.Queue) -> None:
... | from typing import Any, Dict, List, Optional, Tuple, Union
import multiprocessing
import queue
__all__ = ["read_queue"]
def read_queue(
queue_: multiprocessing.Queue,
) -> List[Dict[str, Union[str, bool, int, float, List, Dict, Tuple]]]:
FILL_FUNC_BODYdef empty_queue(queue_: multiprocessing.Queue) -> None:
... | |
9,599 | /home/hieuvd/dung_repo/raw/stars_01/automl_auto-sklearn/auto-sklearn | /home/hieuvd/dung_repo/raw/stars_01/automl_auto-sklearn/auto-sklearn/autosklearn/metalearning/mismbo.py | 15,18 | 1,38 | suggest_via_metalearning | 18,38 | 18,38 | # -*- encoding: utf-8 -*-
import time
from autosklearn.constants import (
MULTICLASS_CLASSIFICATION,
MULTILABEL_CLASSIFICATION,
TASK_TYPES_TO_STRING,
)
from autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner import (
MetaLearningOptimizer,
)
def suggest_via_metalearning(
meta_ba... | # -*- encoding: utf-8 -*-
import time
from autosklearn.constants import (
MULTICLASS_CLASSIFICATION,
MULTILABEL_CLASSIFICATION,
TASK_TYPES_TO_STRING,
)
from autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner import (
MetaLearningOptimizer,
)
def suggest_via_metalearning(
meta_ba... |
if task == MULTILABEL_CLASSIFICATION:
task = MULTICLASS_CLASSIFICATION
task = TASK_TYPES_TO_STRING[task]
logger.info(task)
start = time.time()
ml = MetaLearningOptimizer(
dataset_name=dataset_name,
configuration_space=meta_base.configuration_space,
meta_base=meta_... |
if task == MULTILABEL_CLASSIFICATION:
task = MULTICLASS_CLASSIFICATION
task = TASK_TYPES_TO_STRING[task]
logger.info(task)
start = time.time()
ml = MetaLearningOptimizer(
dataset_name=dataset_name,
configuration_space=meta_base.configuration_space,
meta_base=meta_... | 37 | 158 | 219 | 377 | # -*- encoding: utf-8 -*-
import time
from autosklearn.constants import (
MULTICLASS_CLASSIFICATION,
MULTILABEL_CLASSIFICATION,
TASK_TYPES_TO_STRING,
)
from autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner import (
MetaLearningOptimizer,
)
def suggest_via_metalearning(
meta_ba... | # -*- encoding: utf-8 -*-
import time
from autosklearn.constants import (
MULTICLASS_CLASSIFICATION,
MULTILABEL_CLASSIFICATION,
TASK_TYPES_TO_STRING,
)
from autosklearn.metalearning.optimizers.metalearn_optimizer.metalearner import (
MetaLearningOptimizer,
)
def suggest_via_metalearning(
meta_ba... | |
9,600 | /home/hieuvd/dung_repo/raw/stars_01/automl_auto-sklearn/auto-sklearn | /home/hieuvd/dung_repo/raw/stars_01/automl_auto-sklearn/auto-sklearn/autosklearn/metalearning/optimizers/metalearn_optimizer/metalearn_optimizer_parser.py | 1,2 | 1,3 | manipulate_config | 2,3 | 2,3 | def manipulate_config(config):
FILL_FUNC_BODY | def manipulate_config(config):
FILL_FUNC_BODY | return config
| return config
| 2 | 19 | 5 | 24 | def manipulate_config(config):
FILL_FUNC_BODY | def manipulate_config(config):
FILL_FUNC_BODY | |
9,601 | /home/hieuvd/dung_repo/raw/stars_01/automl_auto-sklearn/auto-sklearn | /home/hieuvd/dung_repo/raw/stars_01/automl_auto-sklearn/auto-sklearn/autosklearn/pipeline/components/data_preprocessing/rescaling/none.py | 21,25 | 11,46 | get_properties | NoRescalingComponent | 25,46 | 25,46 | class NoRescalingComponent(Rescaling, AutoSklearnPreprocessingAlgorithm):
def fit(
self, X: PIPELINE_DATA_DTYPE, y: Optional[PIPELINE_DATA_DTYPE] = None
) -> "AutoSklearnPreprocessingAlgorithm":
self.preprocessor = "passthrough"
return self
def transform(self, X: PIPELINE_DATA_DTYPE... | class NoRescalingComponent(Rescaling, AutoSklearnPreprocessingAlgorithm):
def fit(
self, X: PIPELINE_DATA_DTYPE, y: Optional[PIPELINE_DATA_DTYPE] = None
) -> "AutoSklearnPreprocessingAlgorithm":
self.preprocessor = "passthrough"
return self
def transform(self, X: PIPELINE_DATA_DTYPE... | return {
"shortname": "NoRescaling",
"name": "NoRescaling",
"handles_missing_values": False,
"handles_nominal_values": False,
"handles_numerical_features": True,
"prefers_data_scaled": False,
"prefers_data_normalized": False,
... | return {
"shortname": "NoRescaling",
"name": "NoRescaling",
"handles_missing_values": False,
"handles_nominal_values": False,
"handles_numerical_features": True,
"prefers_data_scaled": False,
"prefers_data_normalized": False,
... | 49 | 192 | 258 | 450 | from typing import Dict, Optional, Tuple, Union
from autosklearn.pipeline.base import DATASET_PROPERTIES_TYPE, PIPELINE_DATA_DTYPE
from autosklearn.pipeline.components.base import AutoSklearnPreprocessingAlgorithm
from autosklearn.pipeline.components.data_preprocessing.rescaling.abstract_rescaling import ( # noqa: E5... | from typing import Dict, Optional, Tuple, Union
from autosklearn.pipeline.base import DATASET_PROPERTIES_TYPE, PIPELINE_DATA_DTYPE
from autosklearn.pipeline.components.base import AutoSklearnPreprocessingAlgorithm
from autosklearn.pipeline.components.data_preprocessing.rescaling.abstract_rescaling import ( # noqa: E5... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.