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-*.pcm filter=lfs diff=lfs merge=lfs -text
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2ch_b_dialogues.py

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-# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-#     http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-# TODO: Address all TODOs and remove all explanatory comments
-"""TODO: Add a description here."""
-
-
-import csv
-import json
-import os
-
-import datasets
-
-
-# TODO: Add BibTeX citation
-# Find for instance the citation on arxiv or on the dataset repo/website
-_CITATION = """\
-@InProceedings{huggingface:dataset,
-title = {2ch b dialogues},
-author={black_samorez},
-year={2022}
-}
-"""
-
-# TODO: Add description of the dataset here
-# You can copy an official description
-_DESCRIPTION = """\
-Dialogues build from 2ch.hk/b/ threads
-"""
-
-# TODO: Add a link to an official homepage for the dataset here
-_HOMEPAGE = "2ch.hk/b/"
-
-# TODO: Add the licence for the dataset here if you can find it
-_LICENSE = ""
-
-# TODO: Add link to the official dataset URLs here
-# The HuggingFace Datasets library doesn't host the datasets but only points to the original files.
-# This can be an arbitrary nested dict/list of URLs (see below in `_split_generators` method)
-_URLS = {
-    "dialogues": "dialogues.zip",
-}
-
-
-# TODO: Name of the dataset usually match the script name with CamelCase instead of snake_case
-class DvaChBDialogues(datasets.GeneratorBasedBuilder):
-    """TODO: Short description of my dataset."""
-
-    VERSION = datasets.Version("1.0.0")
-
-    # This is an example of a dataset with multiple configurations.
-    # If you don't want/need to define several sub-sets in your dataset,
-    # just remove the BUILDER_CONFIG_CLASS and the BUILDER_CONFIGS attributes.
-
-    # If you need to make complex sub-parts in the datasets with configurable options
-    # You can create your own builder configuration class to store attribute, inheriting from datasets.BuilderConfig
-    # BUILDER_CONFIG_CLASS = MyBuilderConfig
-
-    # You will be able to load one or the other configurations in the following list with
-    # data = datasets.load_dataset('my_dataset', 'first_domain')
-    # data = datasets.load_dataset('my_dataset', 'second_domain')
-    BUILDER_CONFIGS = [
-        datasets.BuilderConfig(name="dialogues", version=VERSION, description="Collected with collect.py in May 2022"),
-    ]
-
-    DEFAULT_CONFIG_NAME = "dialogues"  # It's not mandatory to have a default configuration. Just use one if it make sense.
-
-    def _info(self):
-        # TODO: This method specifies the datasets.DatasetInfo object which contains informations and typings for the dataset
-        features = datasets.Features(
-            {
-                "dialogue": datasets.Sequence(datasets.Value("string"))
-                # These are the features of your dataset like images, labels ...
-            }
-        )
-
-        return datasets.DatasetInfo(
-            # This is the description that will appear on the datasets page.
-            description=_DESCRIPTION,
-            # This defines the different columns of the dataset and their types
-            features=features,  # Here we define them above because they are different between the two configurations
-            # If there's a common (input, target) tuple from the features, uncomment supervised_keys line below and
-            # specify them. They'll be used if as_supervised=True in builder.as_dataset.
-            # supervised_keys=("sentence", "label"),
-            # Homepage of the dataset for documentation
-            homepage=_HOMEPAGE,
-            # License for the dataset if available
-            license=_LICENSE,
-            # Citation for the dataset
-            citation=_CITATION,
-        )
-
-    def _split_generators(self, dl_manager):
-        # TODO: This method is tasked with downloading/extracting the data and defining the splits depending on the configuration
-        # If several configurations are possible (listed in BUILDER_CONFIGS), the configuration selected by the user is in self.config.name
-
-        # dl_manager is a datasets.download.DownloadManager that can be used to download and extract URLS
-        # It can accept any type or nested list/dict and will give back the same structure with the url replaced with path to local files.
-        # By default the archives will be extracted and a path to a cached folder where they are extracted is returned instead of the archive
-        urls = _URLS[self.config.name]
-        data_dir = dl_manager.download_and_extract(urls)
-        return [
-            datasets.SplitGenerator(
-                name=datasets.Split.TRAIN,
-                # These kwargs will be passed to _generate_examples
-                gen_kwargs={
-                    "filepath": os.path.join(data_dir, "dialogues.jsonl"),
-                    "split": "train",
-                },
-            ),
-        ]
-
-    # method parameters are unpacked from `gen_kwargs` as given in `_split_generators`
-    def _generate_examples(self, filepath, split):
-        # TODO: This method handles input defined in _split_generators to yield (key, example) tuples from the dataset.
-        # The `key` is for legacy reasons (tfds) and is not important in itself, but must be unique for each example.
-        with open(filepath, encoding="utf-8") as f:
-            for key, row in enumerate(f):
-                data = json.loads(row)
-                # Yields examples as (key, example) tuples
-                yield key, {
-                    "dialogue": data["dialogue"],
-                }

README.md

@@ -1,139 +0,0 @@
----
-annotations_creators:
-- no-annotation
-language_creators:
-- found
-language:
-- ru
-license: []
-multilinguality:
-- monolingual
-pretty_name: Dialogues mined from 2ch/b/.
-size_categories:
-- 10K<n<100K
-source_datasets:
-- original
-task_categories:
-- conversational
-task_ids:
-- dialogue-generation
----
-
-# Dataset Card for 2ch_b_dialogues
-
-## Table of Contents
-- [Dataset Description](#dataset-description)
-  - [Dataset Summary](#dataset-summary)
-  - [Supported Tasks](#supported-tasks-and-leaderboards)
-  - [Languages](#languages)
-- [Dataset Structure](#dataset-structure)
-  - [Data Instances](#data-instances)
-  - [Data Fields](#data-instances)
-  - [Data Splits](#data-instances)
-- [Dataset Creation](#dataset-creation)
-  - [Curation Rationale](#curation-rationale)
-  - [Source Data](#source-data)
-  - [Annotations](#annotations)
-  - [Personal and Sensitive Information](#personal-and-sensitive-information)
-- [Considerations for Using the Data](#considerations-for-using-the-data)
-  - [Social Impact of Dataset](#social-impact-of-dataset)
-  - [Discussion of Biases](#discussion-of-biases)
-  - [Other Known Limitations](#other-known-limitations)
-- [Additional Information](#additional-information)
-  - [Dataset Curators](#dataset-curators)
-  - [Licensing Information](#licensing-information)
-  - [Citation Information](#citation-information)
-
-## Dataset Description
-
-- **Homepage:** https://github.com/BlackSamorez/ebanko
-- **Repository:** [Needs More Information]
-- **Paper:** [Needs More Information]
-- **Leaderboard:** [Needs More Information]
-- **Point of Contact:** [Needs More Information]
-
-### Dataset Summary
-
-Russian language dialogues mined from 2ch.hk/b/
-
-### Supported Tasks and Leaderboards
-
-[Needs More Information]
-
-### Languages
-
-Russian
-
-## Dataset Structure
-
-### Data Instances
-
-{
-  "dialogue": ["Glad to hear!", "Fine, thank you!", "Hi, how are you?"]
-}
-
-### Data Fields
-
-- dialogue: list of posts ordered last-to-first
-
-### Data Splits
-
-[Needs More Information]
-
-## Dataset Creation
-
-### Curation Rationale
-
-Fun
-
-### Source Data
-
-#### Initial Data Collection and Normalization
-
-In a thread graph only vertices with single parent were selected. Then non-overlapping threads of dialogues were build.
-
-#### Who are the source language producers?
-
-2ch.hk/b/ users
-
-### Annotations
-
-#### Annotation process
-
-[Needs More Information]
-
-#### Who are the annotators?
-
-[Needs More Information]
-
-### Personal and Sensitive Information
-
-[Needs More Information]
-
-## Considerations for Using the Data
-
-### Social Impact of Dataset
-
-Morally questionable data
-
-### Discussion of Biases
-
-[Needs More Information]
-
-### Other Known Limitations
-
-[Needs More Information]
-
-## Additional Information
-
-### Dataset Curators
-
-blacks_samorez
-
-### Licensing Information
-
-[Needs More Information]
-
-### Citation Information
-
-[Needs More Information]

collect.py

@@ -1,129 +0,0 @@
-import pandas as pd
-import numpy as np
-from tqdm import tqdm, trange
-import json
-from time import sleep
-
-import api2ch
-import html2text
-import re
-import os
-
-API = api2ch.DvachApi('b')
-
-if os.path.exists("parsed_threads.json"):
-    with open("parsed_threads.json", "r") as file:
-        PARSED_TREADS = set(json.load(file)["ids"])
-else:
-    PARSED_TREADS = set()
-
-REPLY_RE = re.compile(">>[0-9]+")
-
-HTML_STRIPPER = html2text.HTML2Text()
-HTML_STRIPPER.ignore_links = True
-HTML_STRIPPER.ignore_images = True
-HTML_STRIPPER.ignore_emphasis = True
-
-def SaveParsed():
-    with open("parsed_threads.json", "w") as file:
-        json.dump({"ids": list(PARSED_TREADS)}, file)
-        
-def ThreadGood(thread):
-    return thread.reply_count > 20
-
-def AppendDialogues(id, dialogues):
-    with open("dialogues.jsonl", "a") as file:
-        for dialogue in dialogues:
-            json.dump({"id": id, "dialogue": dialogue}, file, ensure_ascii=False)
-            file.write("\n")
-
-def FilterAndPrepareText(text):
-    text = HTML_STRIPPER.handle(text)
-    text = text.lower()
-    text = text.replace("\n", " ")
-    text = text.replace("(op)", "")
-    if text.find("бамп") != -1:
-        return
-    text = re.sub(' +', ' ', text)
-    text = re.sub('^ ', '', text)
-    text = re.sub(' $', '', text)
-    return text
-
-class Post:
-    def __init__(self, idx: int, text: str):
-        self.idx = idx
-        
-        self.parents = []
-        while True:
-            reply_match = REPLY_RE.match(text)
-            if reply_match is not None:
-                parent_id = int(reply_match.group(0)[2:])
-                span = reply_match.span()
-                self.parents.append(parent_id)
-                text = text[:span[0]] + text[span[1]:]
-                text = re.sub('^ ', '', text)
-                text = re.sub(' $', '', text)
-            else:
-                break
-        self.text = text
-        
-        self.children = []
-        self.dialogue = [self.text]
-        self.appeared = False
-                
-    def __repr__(self):
-        return {"idx": self.idx, "parents": self.parents, "text": self.text}.__repr__()
-    
-    def build_random_dialogue(self, context):
-        self.appeared = True
-        if len(self.dialogue) != 1:
-            return self.dialogue
-        if len(self.parents) == 0:
-            return self.dialogue
-        chosen_parent = self.parents[0]
-        if chosen_parent in context.keys():
-            self.dialogue.extend(context[chosen_parent].build_random_dialogue(context))
-        return self.dialogue
-            
-def BuildDialogues(thread):
-    posts = {}
-    for post in thread:
-        idx = post.num
-        text = FilterAndPrepareText(post.comment)
-        if text is not None:
-            posts[idx] = Post(idx, text)
-    
-    for _, post in reversed(posts.items()):
-        if not post.appeared:
-            post.build_random_dialogue(posts)
-            
-    return [post.dialogue for post in list(posts.values()) if len(post.dialogue) > 1]
-
-def main():
-    print("Started collecting...")
-    while True:
-        while True:
-            try:
-                board = API.get_board()
-                break
-            except:
-                print(f"Failed to fetch board. Sleeping for 60s")
-                sleep(60)
-        print("Got board")
-            
-        for thread in board:
-            if thread.num not in PARSED_TREADS and ThreadGood(thread):
-                PARSED_TREADS.add(thread.num)
-                try:
-                    thread = API.get_thread(thread.num)
-                except:
-                    continue
-                dialogues = BuildDialogues(thread)
-                AppendDialogues(thread[0].num, dialogues)
-        print("Parsed")
-        SaveParsed()
-        print("Saved. Sleeping for 10m")
-        sleep(600)
-        
-if __name__ == "__main__":
-    main()

dialogues.jsonl

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-oid sha256:e45c097dc98f53fe8d2cfc05308631aba88e0c58b337f8232f38733a1c917985
-size 112897459

dialogues.zip → dialogues/2ch_b_dialogues-train.parquet

@@ -1,3 +1,3 @@
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-size 11359216
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+size 10979948