mirror of
https://github.com/Alexander-D-Karpov/akarpov
synced 2024-11-21 20:56:34 +03:00
removed unused dependencies from project, moved files process to external service
This commit is contained in:
parent
03c7c5309c
commit
f5835d2821
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@ -15,3 +15,5 @@ LAST_FM_SECRET=
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SPOTIFY_ID=
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SPOTIFY_SECRET=
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YANDEX_TOKEN=
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PREVIEW_SERVICE_API_KEY=
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PREVIEW_SERVICE_URL=
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@ -1,51 +0,0 @@
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import pycld2 as cld2
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import spacy
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import torch
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from transformers import AutoModel, AutoTokenizer
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# load ml classes and models on first request
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# TODO: move to outer server/service
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nlp = None
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ru_nlp = None
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ru_model = None
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ru_tokenizer = None
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device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
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def get_text_embedding(text: str):
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global nlp, ru_nlp, ru_model, ru_tokenizer
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is_reliable, text_bytes_found, details = cld2.detect(text)
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if is_reliable:
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lang = details[0]
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if lang[1] in ["ru", "en"]:
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lang = lang[1]
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else:
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return None
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else:
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return None
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if lang == "ru":
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if not ru_nlp:
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ru_nlp = spacy.load("ru_core_news_md", disable=["parser", "ner"])
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lema = " ".join([token.lemma_ for token in ru_nlp(text)])
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if not ru_model:
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ru_model = AutoModel.from_pretrained("DeepPavlov/rubert-base-cased")
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if not ru_tokenizer:
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ru_tokenizer = AutoTokenizer.from_pretrained("DeepPavlov/rubert-base-cased")
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encodings = ru_tokenizer(
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lema, # the texts to be tokenized
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padding=True, # pad the texts to the maximum length (so that all outputs have the same length)
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return_tensors="pt", # return the tensors (not lists)
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)
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with torch.no_grad():
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# get the model embeddings
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embeds = ru_model(**encodings)
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embeds = embeds[0]
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elif lang == "en":
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embeds = None
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else:
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embeds = None
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return embeds
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@ -1,16 +1,10 @@
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import textract
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from akarpov.files.models import File
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def view(file: File):
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static = ""
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content = ""
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text = (
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textract.process(file.file.path, extension="doc", output_encoding="utf8")
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.decode("utf8")
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.replace("\t", " ")
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)
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text = file.content.replace("\t", " ")
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for line in text.split("\n"):
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content += f"<p class='mt-1'>{line}</p>"
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return static, content
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@ -1,16 +1,10 @@
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import textract
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from akarpov.files.models import File
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def view(file: File):
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static = ""
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content = ""
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text = (
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textract.process(file.file.path, extension="docx", output_encoding="utf8")
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.decode("utf8")
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.replace("\t", " ")
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)
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text = file.content.replace("\t", " ")
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for line in text.split("\n"):
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content += f"<p class='mt-1'>{line}</p>"
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return static, content
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@ -1,16 +1,10 @@
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import textract
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from akarpov.files.models import File
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def view(file: File):
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static = ""
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content = ""
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text = (
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textract.process(file.file.path, extension="odt", output_encoding="utf8")
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.decode("utf8")
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.replace("\t", " ")
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)
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text = file.content.replace("\t", " ")
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for line in text.split("\n"):
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content += f"<p class='mt-1'>{line}</p>"
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return static, content
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@ -1,5 +1,3 @@
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import textract
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from akarpov.files.models import File
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@ -7,11 +5,7 @@ def view(file: File) -> (str, str):
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static = f"""
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<meta property="og:title" content="{file.name}" />
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"""
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text = (
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textract.process(file.file.path, extension="ogg", output_encoding="utf8")
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.decode("utf8")
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.replace("\t", " ")
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)
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text = file.content.replace("\t", " ")
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content = (
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"""
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<div id="waveform">
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@ -1,42 +0,0 @@
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from nltk.corpus import stopwords
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from nltk.stem import WordNetLemmatizer
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from nltk.tokenize import word_tokenize
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from pymorphy3 import MorphAnalyzer
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# Set up stop words
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english_stopwords = set(stopwords.words("english"))
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russian_stopwords = set(stopwords.words("russian"))
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# Set up lemmatizers
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english_lemmatizer = None
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russian_lemmatizer = None
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def lemmatize_and_remove_stopwords(text, language="english"):
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# Tokenize the text
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global english_lemmatizer, russian_lemmatizer
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tokens = word_tokenize(text)
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# Lemmatize each token based on the specified language
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lemmatized_tokens = []
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for token in tokens:
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if language == "russian":
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if not russian_lemmatizer:
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russian_lemmatizer = MorphAnalyzer()
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lemmatized_token = russian_lemmatizer.parse(token)[0].normal_form
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else: # Default to English
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if not english_lemmatizer:
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english_lemmatizer = WordNetLemmatizer()
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lemmatized_token = english_lemmatizer.lemmatize(token)
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lemmatized_tokens.append(lemmatized_token)
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# Remove stop words
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filtered_tokens = [
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token
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for token in lemmatized_tokens
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if token not in english_stopwords and token not in russian_stopwords
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]
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# Reconstruct the text
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filtered_text = " ".join(filtered_tokens)
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return filtered_text
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@ -1,8 +1,4 @@
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from math import ceil
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import magic
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from PIL import Image, ImageDraw, ImageFont
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from preview_generator.manager import PreviewManager
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from akarpov.files.models import File
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@ -19,90 +15,11 @@
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manager = None
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def textfile_to_image(textfile_path) -> Image:
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"""Convert text file to a grayscale image.
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arguments:
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textfile_path - the content of this file will be converted to an image
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font_path - path to a font file (for example impact.ttf)
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"""
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# parse the file into lines stripped of whitespace on the right side
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with open(textfile_path) as f:
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lines = tuple(line.rstrip() for line in f.readlines())
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font: ImageFont = None
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large_font = 20 # get better resolution with larger size
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for font_filename in COMMON_MONO_FONT_FILENAMES:
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try:
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font = ImageFont.truetype(font_filename, size=large_font)
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print(f'Using font "{font_filename}".')
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break
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except OSError:
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print(f'Could not load font "{font_filename}".')
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if font is None:
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font = ImageFont.load_default()
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print("Using default font.")
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def _font_points_to_pixels(pt):
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return round(pt * 96.0 / 72)
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margin_pixels = 20
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# height of the background image
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tallest_line = max(lines, key=lambda line: font.getsize(line)[PIL_HEIGHT_INDEX])
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max_line_height = _font_points_to_pixels(
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font.getsize(tallest_line)[PIL_HEIGHT_INDEX]
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)
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realistic_line_height = max_line_height * 0.8
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image_height = int(ceil(realistic_line_height * len(lines) + 2 * margin_pixels))
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widest_line = max(lines, key=lambda s: font.getsize(s)[PIL_WIDTH_INDEX])
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max_line_width = _font_points_to_pixels(font.getsize(widest_line)[PIL_WIDTH_INDEX])
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image_width = int(ceil(max_line_width + (2 * margin_pixels)))
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# draw the background
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background_color = 255 # white
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image = Image.new(
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PIL_GRAYSCALE, (image_width, image_height), color=background_color
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)
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draw = ImageDraw.Draw(image)
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font_color = 0
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horizontal_position = margin_pixels
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for i, line in enumerate(lines):
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vertical_position = int(round(margin_pixels + (i * realistic_line_height)))
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draw.text(
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(horizontal_position, vertical_position), line, fill=font_color, font=font
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)
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return image
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def create_preview(file_path: str) -> str:
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global manager
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# TODO: add text image generation/code image
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if not manager:
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manager = PreviewManager(cache_path, create_folder=True)
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if manager.has_jpeg_preview(file_path):
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return manager.get_jpeg_preview(file_path, height=500)
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return ""
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def get_file_mimetype(file_path: str) -> str:
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mime = magic.Magic(mime=True)
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return mime.from_file(file_path)
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def get_description(file_path: str) -> str:
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global manager
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if not manager:
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manager = PreviewManager(cache_path, create_folder=True)
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if manager.has_text_preview(file_path):
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return manager.get_text_preview(file_path)
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return ""
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def get_base_meta(file: File):
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preview = file.preview.url if file.preview else ""
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description = file.description if file.description else ""
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@ -11,12 +11,6 @@
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from akarpov.files.models import File
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from ..documents import FileDocument
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from .lema import lemmatize_and_remove_stopwords
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"""
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Calculus on types of searches:
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https://new.akarpov.ru/files/FZUTFBIyfbdlDHVzxUNU
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"""
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class BaseSearch:
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@ -140,23 +134,20 @@ class SimilaritySearch(BaseSearch):
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def search(self, query: str) -> QuerySet[File]:
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if self.queryset is None:
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raise ValueError("Queryset cannot be None for similarity search")
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language = "russian" if re.search("[а-яА-Я]", query) else "english"
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filtered_query = lemmatize_and_remove_stopwords(query, language=language)
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queryset = (
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self.queryset.annotate(
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name_similarity=Coalesce(
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TrigramSimilarity(UnaccentLower("name"), filtered_query),
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TrigramSimilarity(UnaccentLower("name"), query),
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Value(0),
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output_field=FloatField(),
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),
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description_similarity=Coalesce(
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TrigramSimilarity(UnaccentLower("description"), filtered_query),
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TrigramSimilarity(UnaccentLower("description"), query),
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Value(0),
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output_field=FloatField(),
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),
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content_similarity=Coalesce(
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TrigramSimilarity(UnaccentLower("content"), filtered_query),
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TrigramSimilarity(UnaccentLower("content"), query),
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Value(0),
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output_field=FloatField(),
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),
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@ -1,18 +0,0 @@
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import chardet
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import textract
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from textract.exceptions import ExtensionNotSupported
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def extract_file_text(file: str) -> str:
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try:
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text = textract.process(file)
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except ExtensionNotSupported:
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try:
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rawdata = open(file, "rb").read()
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enc = chardet.detect(rawdata)
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with open(file, encoding=enc["encoding"]) as f:
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text = f.read()
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except Exception:
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return ""
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return text
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@ -1,40 +1,69 @@
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import os
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import base64
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import time
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from urllib.parse import urljoin
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import requests
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import structlog
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from celery import shared_task
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from django.conf import settings
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from django.core import management
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from django.core.files import File
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from django.core.files.base import ContentFile
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from akarpov.files.models import File as FileModel
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from akarpov.files.services.preview import create_preview, get_file_mimetype
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from akarpov.files.services.text import extract_file_text
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logger = structlog.get_logger(__name__)
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def sanitize_content(content):
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"""Remove NUL (0x00) characters from the content."""
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if isinstance(content, str):
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return content.replace("\x00", "")
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elif isinstance(content, bytes):
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return content.replace(b"\x00", b"")
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return content
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@shared_task()
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def process_file(pk: int):
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pth = None
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file = FileModel.objects.get(pk=pk)
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if not file.name:
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file.name = file.file.name.split("/")[-1]
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try:
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pth = create_preview(file.file.path)
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if pth:
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with open(pth, "rb") as f:
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api_url = urljoin(settings.PREVIEW_SERVICE_URL, "/process_file/")
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files = {"file": (file.name, file.file.open("rb"))}
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headers = {
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"X-API-Key": settings.PREVIEW_SERVICE_API_KEY,
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"Accept": "application/json",
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}
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response = requests.post(api_url, files=files, headers=headers)
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if response.status_code != 200:
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logger.error(f"Failed to process file {pk}: {response.text}")
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return
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result = response.json()
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file.file_type = result["file_type"]
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file.content = sanitize_content(result["content"])
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if result["preview"]:
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image_data = base64.b64decode(result["preview"])
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file.preview.save(
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pth.split("/")[-1],
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File(f),
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save=False,
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f"{file.name}_preview.jpg", ContentFile(image_data), save=False
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)
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file.save()
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logger.info(f"File {pk} processed successfully")
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except Exception as e:
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logger.error(e)
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file.file_type = get_file_mimetype(file.file.path)
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file.content = extract_file_text(file.file.path)
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file.save(update_fields=["preview", "name", "file_type", "content"])
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if pth and os.path.isfile(pth):
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os.remove(pth)
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logger.error(f"Error processing file {pk}: {str(e)}")
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finally:
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file.file.close()
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return pk
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|
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@ -6,6 +6,7 @@
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from akarpov.common.api.permissions import IsAdminOrReadOnly, IsCreatorOrReadOnly
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from akarpov.music.api.serializers import (
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AddSongToPlaylistSerializer,
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AllSearchSerializer,
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AnonMusicUserSerializer,
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FullAlbumSerializer,
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FullAuthorSerializer,
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|
@ -19,7 +20,6 @@
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ListSongSlugsSerializer,
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PlaylistSerializer,
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SongSerializer,
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AllSearchSerializer,
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)
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from akarpov.music.models import (
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Album,
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|
@ -29,7 +29,7 @@
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SongUserRating,
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UserListenHistory,
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)
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from akarpov.music.services.search import search_song, search_album, search_author
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from akarpov.music.services.search import search_album, search_author, search_song
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from akarpov.music.tasks import listen_to_song
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from akarpov.users.models import User
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|
|
|
@ -1,7 +1,7 @@
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from django_elasticsearch_dsl import Document, fields
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from django_elasticsearch_dsl.registries import registry
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from akarpov.music.models import Song, Album, Author
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from akarpov.music.models import Album, Author, Song
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|
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@registry.register_document
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|
|
|
@ -3,8 +3,8 @@
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from django_elasticsearch_dsl.registries import registry
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from elasticsearch_dsl import Q as ES_Q
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|
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from akarpov.music.documents import SongDocument, AlbumDocument, AuthorDocument
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from akarpov.music.models import Song, Author, Album
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from akarpov.music.documents import AlbumDocument, AuthorDocument, SongDocument
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from akarpov.music.models import Album, Author, Song
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|
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def search_song(query):
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|
|
|
@ -35,7 +35,8 @@ def album_create(sender, instance, created, **kwargs):
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|
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|
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@receiver(post_save)
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def send_que_status(sender, instance, created, **kwargs): ...
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def send_que_status(sender, instance, created, **kwargs):
|
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...
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|
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|
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@receiver(pre_save, sender=SongUserRating)
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|
|
|
@ -4,7 +4,6 @@
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import pylast
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import spotipy
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import structlog
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import ytmusicapi
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from asgiref.sync import async_to_sync
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from celery import shared_task
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from channels.layers import get_channel_layer
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|
@ -12,6 +11,7 @@
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from django.utils import timezone
|
||||
from django.utils.timezone import now
|
||||
from spotipy import SpotifyClientCredentials
|
||||
from ytmusicapi import YTMusic
|
||||
|
||||
from akarpov.music.api.serializers import SongSerializer
|
||||
from akarpov.music.models import (
|
||||
|
|
|
@ -3,6 +3,4 @@
|
|||
set -o errexit
|
||||
set -o nounset
|
||||
|
||||
/install_preview_dependencies
|
||||
|
||||
celery -A config.celery_app worker --autoscale 20 -l INFO
|
||||
|
|
|
@ -1,14 +0,0 @@
|
|||
#!/bin/bash
|
||||
|
||||
apt-get update
|
||||
apt-get install wget libnotify4 scribus libappindicator3-1 libayatana-indicator3-7 libdbusmenu-glib4 libdbusmenu-gtk3-4
|
||||
apt-get install -y poppler-utils libfile-mimeinfo-perl ghostscript libsecret-1-0 zlib1g-dev libjpeg-dev imagemagick libmagic1 libreoffice inkscape xvfb
|
||||
apt-get install -y libxml2-dev libxslt1-dev antiword unrtf tesseract-ocr flac lame libmad0 libsox-fmt-mp3 sox swig
|
||||
apt-get install -y python-dev-is-python3 libxml2-dev libxslt1-dev antiword unrtf poppler-utils tesseract-ocr \
|
||||
flac ffmpeg lame libmad0 libsox-fmt-mp3 sox libjpeg-dev swig
|
||||
wget https://github.com/jgraph/drawio-desktop/releases/download/v13.0.3/draw.io-amd64-13.0.3.deb
|
||||
dpkg -i draw.io-amd64-13.0.3.deb
|
||||
rm draw.io-amd64-13.0.3.deb
|
||||
apt-get purge -y --auto-remove -o APT:AutoRemove:RecommendsImportant=false && \
|
||||
rm -rf /var/lib/apt/lists/*
|
||||
preview --check-dependencies
|
|
@ -758,3 +758,9 @@
|
|||
SECURE_PROXY_SSL_HEADER = ("HTTP_X_FORWARDED_PROTO", "https")
|
||||
USE_X_FORWARDED_HOST = True
|
||||
USE_X_FORWARDED_PORT = True
|
||||
|
||||
|
||||
# PREVIEW
|
||||
# ------------------------------------------------------------------------------
|
||||
PREVIEW_SERVICE_URL = env("PREVIEW_SERVICE_URL", default=None)
|
||||
PREVIEW_SERVICE_API_KEY = env("PREVIEW_SERVICE_API_KEY", default=None)
|
||||
|
|
5764
poetry.lock
generated
5764
poetry.lock
generated
File diff suppressed because it is too large
Load Diff
|
@ -69,7 +69,6 @@ channels = {extras = ["daphne"], version = "^4.0.0"}
|
|||
django-upload-validator = "^1.1.6"
|
||||
markdown = "^3.4.4"
|
||||
pydotplus = "^2.0.2"
|
||||
preview-generator = "^0.29"
|
||||
uuid = "^1.30"
|
||||
mutagen = "^1.46.0"
|
||||
pydub = "^0.25.1"
|
||||
|
@ -100,11 +99,8 @@ pytest-mock = "^3.11.1"
|
|||
pytest-asyncio = "^0.21.1"
|
||||
pytest-lambda = "^2.2.0"
|
||||
pgvector = "^0.2.2"
|
||||
pycld2 = "^0.41"
|
||||
uuid6 = "^2023.5.2"
|
||||
uvicorn = "0.23.2"
|
||||
nltk = "^3.8.1"
|
||||
pymorphy3 = "^1.2.1"
|
||||
pymorphy3-dicts-ru = "^2.4.417150.4580142"
|
||||
fastapi = "0.103.0"
|
||||
pydantic-settings = "^2.0.3"
|
||||
|
@ -118,9 +114,9 @@ spotdl = "^4.2.4"
|
|||
fuzzywuzzy = "^0.18.0"
|
||||
python-levenshtein = "^0.23.0"
|
||||
pylast = "^5.2.0"
|
||||
textract = {git = "https://github.com/Alexander-D-Karpov/textract.git", branch = "master"}
|
||||
librosa = "^0.10.1"
|
||||
django-ckeditor-5 = "^0.2.12"
|
||||
chardet = "^5.2.0"
|
||||
|
||||
|
||||
[build-system]
|
||||
|
|
|
@ -1,6 +0,0 @@
|
|||
from haystack import Document
|
||||
from milvus_haystack import MilvusDocumentStore
|
||||
|
||||
ds = MilvusDocumentStore()
|
||||
ds.write_documents([Document("Some Content")])
|
||||
ds.get_all_documents()
|
2185
search/poetry.lock
generated
2185
search/poetry.lock
generated
File diff suppressed because it is too large
Load Diff
|
@ -1,18 +0,0 @@
|
|||
[tool.poetry]
|
||||
name = "search"
|
||||
version = "0.1.0"
|
||||
description = ""
|
||||
authors = ["Alexander-D-Karpov <alexandr.d.karpov@gmail.com>"]
|
||||
readme = "README.md"
|
||||
|
||||
[tool.poetry.dependencies]
|
||||
python = "^3.11"
|
||||
fastapi = "0.99.1"
|
||||
pydantic = "1.10.13"
|
||||
transformers = {version = "4.34.1", extras = ["torch"]}
|
||||
torch = ">=2.0.0, !=2.0.1, !=2.1.0"
|
||||
farm-haystack = {extras = ["faiss"], version = "^1.21.2"}
|
||||
|
||||
[build-system]
|
||||
requires = ["poetry-core>=1.0.0"]
|
||||
build-backend = "poetry.core.masonry.api"
|
|
@ -1,4 +0,0 @@
|
|||
#!/bin/bash
|
||||
python -m spacy download en_core_web_lg
|
||||
python -m spacy download xx_sent_ud_sm
|
||||
python -m spacy download ru_core_news_lg
|
Loading…
Reference in New Issue
Block a user