mirror of
https://github.com/Alexander-D-Karpov/akarpov
synced 2024-11-25 14:03:44 +03:00
added ml better support, better site notifications
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parent
513de19a16
commit
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0
akarpov/common/ml/__init__.py
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0
akarpov/common/ml/__init__.py
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51
akarpov/common/ml/text.py
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akarpov/common/ml/text.py
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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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akarpov/files/migrations/0025_create_vector_ps.py
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akarpov/files/migrations/0025_create_vector_ps.py
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from django.db import migrations
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from pgvector.django import VectorExtension
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class Migration(migrations.Migration):
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dependencies = [
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("files", "0024_alter_file_options_alter_filereport_options_and_more"),
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]
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operations = [VectorExtension()]
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akarpov/files/migrations/0026_file_embeddings.py
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akarpov/files/migrations/0026_file_embeddings.py
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# Generated by Django 4.2.5 on 2023-09-16 18:33
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from django.db import migrations
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import pgvector.django
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class Migration(migrations.Migration):
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dependencies = [
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("files", "0025_create_vector_ps"),
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]
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operations = [
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migrations.AddField(
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model_name="file",
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name="embeddings",
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field=pgvector.django.VectorField(dimensions=768, null=True),
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),
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]
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akarpov/files/migrations/0027_merge_20230925_2023.py
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akarpov/files/migrations/0027_merge_20230925_2023.py
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# Generated by Django 4.2.5 on 2023-09-25 17:23
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from django.db import migrations
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class Migration(migrations.Migration):
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dependencies = [
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("files", "0025_file_notify_user_on_view_alter_basefileitem_parent"),
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("files", "0026_file_embeddings"),
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]
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operations = []
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akarpov/files/migrations/0028_file_content_file_lang.py
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akarpov/files/migrations/0028_file_content_file_lang.py
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# Generated by Django 4.2.5 on 2023-09-26 09:04
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from django.db import migrations, models
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class Migration(migrations.Migration):
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dependencies = [
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("files", "0027_merge_20230925_2023"),
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]
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operations = [
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migrations.AddField(
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model_name="file",
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name="content",
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field=models.TextField(default="", max_length=10000),
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preserve_default=False,
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),
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migrations.AddField(
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model_name="file",
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name="lang",
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field=models.CharField(
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choices=[("ru", "ru"), ("en", "en")], default="en", max_length=2
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),
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preserve_default=False,
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),
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]
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@ -17,6 +17,7 @@
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from django.urls import reverse
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from model_utils.fields import AutoCreatedField, AutoLastModifiedField
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from model_utils.models import TimeStampedModel
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from pgvector.django import VectorField
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from polymorphic.models import PolymorphicModel
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from akarpov.files.services.files import trash_file_upload, user_unique_file_upload
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@ -69,6 +70,9 @@ class File(BaseFileItem, TimeStampedModel, ShortLinkModel, UserHistoryModel):
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preview = FileField(blank=True, upload_to="file/previews/")
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file_obj = FileField(blank=False, upload_to=user_unique_file_upload)
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embeddings = VectorField(dimensions=768, null=True)
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content = TextField(max_length=10000)
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lang = CharField(max_length=2, choices=[("ru", "ru"), ("en", "en")])
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# meta
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name = CharField(max_length=255, null=True, blank=True)
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akarpov/files/services/text.py
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akarpov/files/services/text.py
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import textract
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def extract_file_text(file: str) -> str:
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text = textract.process(file)
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return text
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@ -132,6 +132,10 @@
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<footer class="row bg-light py-1 mt-auto text-center">
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<div class="col"> Writen by <a href="/about">sanspie</a>, find source code <a href="https://github.com/Alexander-D-Karpov/akarpov">here</a> </div>
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</footer>
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<div id="toastContainer" class="toast-container position-fixed bottom-0 end-0 p-3">
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</div>
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</div>
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</div>
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</div>
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{% endblock inline_javascript %}
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{% if request.user.is_authenticated %}
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<script>
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{# TODO: add automatic socket host retrieve #}
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let socket = new WebSocket(`ws://127.0.0.1:8000/ws/notifications/`);
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{% if request.is_secure %}
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let socket = new WebSocket(`wss://{{ request.get_host }}/ws/notifications/`);
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{% else %}
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let socket = new WebSocket(`ws://{{ request.get_host }}/ws/notifications/`);
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{% endif %}
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function sleep(ms) {
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return new Promise(resolve => setTimeout(resolve, ms));
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}
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function timeSince(date) {
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let seconds = Math.floor((new Date() - date) / 1000);
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let interval = seconds / 31536000;
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if (interval > 1) {
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return Math.floor(interval) + " years";
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}
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interval = seconds / 2592000;
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if (interval > 1) {
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return Math.floor(interval) + " months";
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}
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interval = seconds / 86400;
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if (interval > 1) {
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return Math.floor(interval) + " days";
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}
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interval = seconds / 3600;
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if (interval > 1) {
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return Math.floor(interval) + " hours";
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}
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interval = seconds / 60;
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if (interval > 1) {
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return Math.floor(interval) + " minutes";
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}
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return Math.floor(seconds) + " seconds";
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}
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const toastContainer = document.getElementById('toastContainer')
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let fn = async function(event) {
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let data = JSON.parse(event.data)
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console.log(data)
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alert(data.body)
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{# TODO add pretty pop up #}
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const toast = document.createElement("div")
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toast.id = "liveToast"
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toast.className = "toast mb-4 ml-2"
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toast.setAttribute("role", "alert")
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toast.setAttribute("aria-live", "assertive")
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toast.setAttribute("aria-atomic", "true")
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toast.innerHTML = `<div class="toast-header">
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<strong class="me-auto">${data.title}</strong>
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<small>${timeSince(Date.parse(data.created))} ago</small>
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<button type="button" class="btn-close" data-bs-dismiss="toast" aria-label="Close"></button>
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</div>
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<div class="toast-body">
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${data.body}
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</div>`
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toastContainer.appendChild(toast)
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const toastBootstrap = bootstrap.Toast.getOrCreateInstance(toast)
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toastBootstrap.show()
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}
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socket.onmessage = fn
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@ -28,6 +28,8 @@ RUN apt-get update && \
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apt-get install -y build-essential libpq-dev gettext libmagic-dev libjpeg-dev zlib1g-dev && \
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# Dependencies for file preview generation
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apt-get install -y webp libimage-exiftool-perl libmagickwand-dev ffmpeg libgdal-dev && \
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# ML dependencies \
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# none for now
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apt-get purge -y --auto-remove -o APT:AutoRemove:RecommendsImportant=false && \
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rm -rf /var/lib/apt/lists/*
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FROM postgres:14
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RUN apt-get update && \
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apt-get install -y postgresql-14-pgvector && \
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apt-get purge -y --auto-remove -o APT:AutoRemove:RecommendsImportant=false && \
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rm -rf /var/lib/apt/lists/*
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COPY ./compose/production/postgres/maintenance /usr/local/bin/maintenance
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RUN chmod +x /usr/local/bin/maintenance/*
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RUN mv /usr/local/bin/maintenance/* /usr/local/bin \
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# SHORTENER
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# ------------------------------------------------------------------------------
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SHORTENER_REDIRECT_TO = "http://127.0.0.1:8000"
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SHORTENER_HOST = "http://127.0.0.1:3000"
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SHORTENER_REDIRECT_TO = "https://dev2.akarpov.ru"
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SHORTENER_HOST = "https://dev.akarpov.ru"
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383
poetry.lock
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383
poetry.lock
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Load Diff
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@ -107,6 +107,8 @@ pytest-xdist = "^3.3.1"
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pytest-mock = "^3.11.1"
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pytest-asyncio = "^0.21.1"
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pytest-lambda = "^2.2.0"
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pgvector = "^0.2.2"
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pycld2 = "^0.41"
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[build-system]
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