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from mmcv.utils import Registry from mmdet.models.builder import BACKBONES, HEADS, LOSSES, NECKS def build_fusion_model(cfg, train_cfg=None, test_cfg=None): return FUSIONMODELS.build( cfg, default_args=dict(train_cfg=train_cfg, test_cfg=test_cfg) ) def build_model(cfg, train_cfg=None, test_cfg=None): ...
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import copy import numpy as np import torch import torch.nn.functional as F from mmcv.cnn import ConvModule, build_conv_layer from mmcv.runner import force_fp32 from torch import nn from mmdet3d.core import ( PseudoSampler, circle_nms, draw_heatmap_gaussian, gaussian_radius, xywhr2xyxyr, ) from mmde...
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import copy import torch from mmcv.cnn import ConvModule, build_conv_layer from mmcv.runner import BaseModule, force_fp32 from torch import nn from mmdet3d.core import circle_nms, draw_heatmap_gaussian, gaussian_radius, xywhr2xyxyr from mmdet3d.models import builder from mmdet3d.models.builder import HEADS, build_loss ...
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from typing import Any, Dict, List, Optional, Tuple, Union import torch from torch import nn from torch.nn import functional as F from mmdet3d.models.builder import HEADS def sigmoid_xent_loss( inputs: torch.Tensor, targets: torch.Tensor, reduction: str = "mean", ) -> torch.Tensor: inputs = inputs.floa...
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from typing import Any, Dict, List, Optional, Tuple, Union import torch from torch import nn from torch.nn import functional as F from mmdet3d.models.builder import HEADS def sigmoid_focal_loss( inputs: torch.Tensor, targets: torch.Tensor, alpha: float = -1, gamma: float = 2, reduction: str = "mean...
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from mmcv.cnn import ConvModule, build_conv_layer, kaiming_init import torch from torch import nn import torch.nn.functional as F from torch.nn.parameter import Parameter from torch.nn import Linear from torch.nn.init import xavier_uniform_, constant_ The provided code snippet includes necessary dependencies for imple...
r""" Args: query, key, value: map a query and a set of key-value pairs to an output. See "Attention Is All You Need" for more details. embed_dim_to_check: total dimension of the model. num_heads: parallel attention heads. in_proj_weight, in_proj_bias: input projection weight and bias. bias_k, bias_v: bias of the key an...
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import torch import torch.nn as nn from mmdet.models.backbones.swin import WindowMSA, ShiftWindowMSA from mmdet3d.ops.spconv import SparseConv3d, SubMConv3d from mmdet3d.models.utils.transformer import MultiheadAttention from typing import Union from thop import profile def count_window_msa(m: Union[WindowMSA, ShiftWin...
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import copy import torch from collections import deque def convert_sync_batchnorm(input_model, exclude=[]): for name, module in input_model._modules.items(): skip = sum([ex in name for ex in exclude]) if skip: continue input_model._modules[name] = torch.nn.SyncBatchNorm.convert_...
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import copy def recursive_eval(obj, globals=None): if globals is None: globals = copy.deepcopy(obj) if isinstance(obj, dict): for key in obj: obj[key] = recursive_eval(obj[key], globals) elif isinstance(obj, list): for k, val in enumerate(obj): obj[k] = recu...
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import logging from mmcv.utils import get_logger The provided code snippet includes necessary dependencies for implementing the `get_root_logger` function. Write a Python function `def get_root_logger(log_file=None, log_level=logging.INFO, name="mmdet3d")` to solve the following problem: Get root logger and add a keyw...
Get root logger and add a keyword filter to it. The logger will be initialized if it has not been initialized. By default a StreamHandler will be added. If `log_file` is specified, a FileHandler will also be added. The name of the root logger is the top-level package name, e.g., "mmdet3d". Args: log_file (str, optional...
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import argparse import os import time import warnings import mmcv import onnx import torch from mmcv import Config, DictAction from mmcv.parallel import MMDataParallel, MMDistributedDataParallel from mmcv.runner import get_dist_info, init_dist, load_checkpoint, wrap_fp16_model from mmdet3d.apis import single_gpu_test f...
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import argparse from data_converter import nuscenes_converter as nuscenes_converter from data_converter.create_gt_database import create_groundtruth_database def create_groundtruth_database( dataset_class_name, data_path, info_prefix, info_path=None, mask_anno_path=None, used_classes=None, ...
Prepare data related to nuScenes dataset. Related data consists of '.pkl' files recording basic infos, 2D annotations and groundtruth database. Args: root_path (str): Path of dataset root. info_prefix (str): The prefix of info filenames. version (str): Dataset version. dataset_name (str): The dataset class name. out_di...
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import argparse import copy import os import mmcv import numpy as np import torch from mmcv import Config from mmcv.parallel import MMDistributedDataParallel from mmcv.runner import load_checkpoint from torchpack import distributed as dist from torchpack.utils.config import configs from torchpack.utils.tqdm import tqdm...
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import mmcv import numpy as np import os from collections import OrderedDict from nuscenes.nuscenes import NuScenes from nuscenes.utils.geometry_utils import view_points from os import path as osp from pyquaternion import Quaternion from shapely.geometry import MultiPoint, box from typing import List, Tuple, Union from...
Export 2d annotation from the info file and raw data. Args: root_path (str): Root path of the raw data. info_path (str): Path of the info file. version (str): Dataset version. mono3d (bool): Whether to export mono3d annotation. Default: True.
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import pickle from os import path as osp import mmcv import numpy as np from mmcv import track_iter_progress from mmcv.ops import roi_align from pycocotools import mask as maskUtils from pycocotools.coco import COCO from mmdet3d.core.bbox import box_np_ops as box_np_ops from mmdet3d.datasets import build_dataset from m...
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import argparse import time import torch from mmcv import Config from mmcv.parallel import MMDataParallel from mmcv.runner import load_checkpoint, wrap_fp16_model from mmdet3d.datasets import build_dataloader, build_dataset from mmdet3d.models import build_fusion_model from torchpack.utils.config import configs from mm...
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import json from langchain.schema import OutputParserException def parse_json_markdown(json_string: str) -> dict: # Remove the triple backticks if present json_string = json_string.strip() start_index = json_string.find("```json") end_index = json_string.find("```", start_index + len("```json")) if ...
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import os from functools import wraps from flask import current_app, g, has_request_context, request from flask_login import user_logged_in from flask_login.config import EXEMPT_METHODS from werkzeug.exceptions import Unauthorized from werkzeug.local import LocalProxy from extensions.ext_database import db from models....
If you decorate a view with this, it will ensure that the current user is logged in and authenticated before calling the actual view. (If they are not, it calls the :attr:`LoginManager.unauthorized` callback.) For example:: @app.route('/post') @login_required def post(): pass If there are only certain times you need to...
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import random import re import string import subprocess import uuid from datetime import datetime from hashlib import sha256 from zoneinfo import available_timezones from flask_restful import fields def run(script): return subprocess.getstatusoutput('source /root/.bashrc && ' + script)
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import random import re import string import subprocess import uuid from datetime import datetime from hashlib import sha256 from zoneinfo import available_timezones from flask_restful import fields def email(email): # Define a regex pattern for email addresses pattern = r"^[\w\.-]+@([\w-]+\.)+[\w-]{2,}$" ...
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import random import re import string import subprocess import uuid from datetime import datetime from hashlib import sha256 from zoneinfo import available_timezones from flask_restful import fields def uuid_value(value): if value == '': return str(value) try: uuid_obj = uuid.UUID(value) ...
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import random import re import string import subprocess import uuid from datetime import datetime from hashlib import sha256 from zoneinfo import available_timezones from flask_restful import fields def timestamp_value(timestamp): try: int_timestamp = int(timestamp) if int_timestamp < 0: ...
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import random import re import string import subprocess import uuid from datetime import datetime from hashlib import sha256 from zoneinfo import available_timezones from flask_restful import fields def _get_float(value): try: return float(value) except (TypeError, ValueError): raise ValueError...
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import random import re import string import subprocess import uuid from datetime import datetime from hashlib import sha256 from zoneinfo import available_timezones from flask_restful import fields def timezone(timezone_string): if timezone_string and timezone_string in available_timezones(): return timez...
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import random import re import string import subprocess import uuid from datetime import datetime from hashlib import sha256 from zoneinfo import available_timezones from flask_restful import fields def generate_string(n): letters_digits = string.ascii_letters + string.digits result = "" for i in range(n):...
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import random import re import string import subprocess import uuid from datetime import datetime from hashlib import sha256 from zoneinfo import available_timezones from flask_restful import fields def get_remote_ip(request): if request.headers.get('CF-Connecting-IP'): return request.headers.get('Cf-Conne...
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import base64 import binascii import hashlib import re def hash_password(password_str, salt_byte): def compare_password(password_str, password_hashed_base64, salt_base64): # compare password for login return hash_password(password_str, base64.b64decode(salt_base64)) == base64.b64decode(password_hashed_base64)
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import os from werkzeug.exceptions import Unauthorized import json import logging import threading import time import warnings from flask import Flask, Response, request from flask_cors import CORS from commands import register_commands from config import CloudEditionConfig, Config from extensions import ( ext_cele...
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import os from werkzeug.exceptions import Unauthorized import json import logging import threading import time import warnings from flask import Flask, Response, request from flask_cors import CORS from commands import register_commands from config import CloudEditionConfig, Config from extensions import ( ext_cele...
Load user based on the request.
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import os from werkzeug.exceptions import Unauthorized import json import logging import threading import time import warnings from flask import Flask, Response, request from flask_cors import CORS from commands import register_commands from config import CloudEditionConfig, Config from extensions import ( ext_cele...
Handle unauthorized requests.
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import os from werkzeug.exceptions import Unauthorized import json import logging import threading import time import warnings from flask import Flask, Response, request from flask_cors import CORS from commands import register_commands from config import CloudEditionConfig, Config from extensions import ( ext_cele...
Add Version headers to the response.
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import os from werkzeug.exceptions import Unauthorized import json import logging import threading import time import warnings from flask import Flask, Response, request from flask_cors import CORS from commands import register_commands from config import CloudEditionConfig, Config from extensions import ( ext_cele...
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import os from werkzeug.exceptions import Unauthorized import json import logging import threading import time import warnings from flask import Flask, Response, request from flask_cors import CORS from commands import register_commands from config import CloudEditionConfig, Config from extensions import ( ext_cele...
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import os from werkzeug.exceptions import Unauthorized import json import logging import threading import time import warnings from flask import Flask, Response, request from flask_cors import CORS from commands import register_commands from config import CloudEditionConfig, Config from extensions import ( ext_cele...
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from __future__ import annotations from collections.abc import Iterable, Mapping from typing import TypeVar from ._base_type import NotGiven class NotGiven(pydantic.BaseModel): """ A sentinel singleton class used to distinguish omitted keyword arguments from those passed in with the value None (which may h...
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from __future__ import annotations from collections.abc import Iterable, Mapping from typing import TypeVar from ._base_type import NotGiven _T = TypeVar("_T") def flatten(t: Iterable[Iterable[_T]]) -> list[_T]: return [item for sublist in t for item in sublist]
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from __future__ import annotations import inspect from collections.abc import Mapping from typing import Any, Union, cast import httpx import pydantic from httpx import URL, Timeout from . import _errors from ._base_type import NOT_GIVEN, Body, Data, Headers, NotGiven, Query, RequestFiles, ResponseT from ._errors impor...
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from __future__ import annotations import inspect from collections.abc import Mapping from typing import Any, Union, cast import httpx import pydantic from httpx import URL, Timeout from . import _errors from ._base_type import NOT_GIVEN, Body, Data, Headers, NotGiven, Query, RequestFiles, ResponseT from ._errors impor...
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from __future__ import annotations import io import os from collections.abc import Mapping, Sequence from pathlib import Path from ._base_type import FileTypes, HttpxFileTypes, HttpxRequestFiles, RequestFiles def _transform_file(file: FileTypes) -> HttpxFileTypes: if is_file_content(file): if isinstance(fil...
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import time import cachetools.func import jwt API_TOKEN_TTL_SECONDS = 3 * 60 def generate_token(apikey: str): try: api_key, secret = apikey.split(".") except Exception as e: raise Exception("invalid api_key", e) payload = { "api_key": api_key, "exp": int(round(time.time() *...
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from pydantic import BaseModel from core.model_runtime.entities.defaults import PARAMETER_RULE_TEMPLATE from core.model_runtime.entities.llm_entities import LLMMode from core.model_runtime.entities.model_entities import ( AIModelEntity, DefaultParameterName, FetchFrom, I18nObject, ModelFeature, ...
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import dataclasses import datetime from collections import defaultdict, deque from collections.abc import Callable from decimal import Decimal from enum import Enum from ipaddress import IPv4Address, IPv4Interface, IPv4Network, IPv6Address, IPv6Interface, IPv6Network from pathlib import Path, PurePath from re import Pa...
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import dataclasses import datetime from collections import defaultdict, deque from collections.abc import Callable from decimal import Decimal from enum import Enum from ipaddress import IPv4Address, IPv4Interface, IPv4Network, IPv6Address, IPv6Interface, IPv6Network from pathlib import Path, PurePath from re import Pa...
Encodes a Decimal as int of there's no exponent, otherwise float This is useful when we use ConstrainedDecimal to represent Numeric(x,0) where a integer (but not int typed) is used. Encoding this as a float results in failed round-tripping between encode and parse. Our Id type is a prime example of this. >>> decimal_en...
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import dataclasses import datetime from collections import defaultdict, deque from collections.abc import Callable from decimal import Decimal from enum import Enum from ipaddress import IPv4Address, IPv4Interface, IPv4Network, IPv6Address, IPv6Interface, IPv6Network from pathlib import Path, PurePath from re import Pa...
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import dataclasses import datetime from collections import defaultdict, deque from collections.abc import Callable from decimal import Decimal from enum import Enum from ipaddress import IPv4Address, IPv4Interface, IPv4Network, IPv6Address, IPv6Interface, IPv6Network from pathlib import Path, PurePath from re import Pa...
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import pydantic from pydantic import BaseModel def dump_model(model: BaseModel) -> dict: if hasattr(pydantic, 'model_dump'): return pydantic.model_dump(model) else: return model.dict()
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import enum from typing import Any, cast from langchain.schema import AIMessage, BaseMessage, FunctionMessage, HumanMessage, SystemMessage from pydantic import BaseModel from core.model_runtime.entities.message_entities import ( AssistantPromptMessage, ImagePromptMessageContent, PromptMessage, SystemPro...
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import enum from typing import Any, cast from langchain.schema import AIMessage, BaseMessage, FunctionMessage, HumanMessage, SystemMessage from pydantic import BaseModel from core.model_runtime.entities.message_entities import ( AssistantPromptMessage, ImagePromptMessageContent, PromptMessage, SystemPro...
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import base64 from extensions.ext_database import db from libs import rsa from models.account import Tenant def obfuscated_token(token: str): return token[:6] + '*' * (len(token) - 8) + token[-2:]
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import base64 from extensions.ext_database import db from libs import rsa from models.account import Tenant db = SQLAlchemy() class Tenant(db.Model): __tablename__ = 'tenants' __table_args__ = ( db.PrimaryKeyConstraint('id', name='tenant_pkey'), ) id = db.Column(UUID, server_default=db.text('...
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import base64 from extensions.ext_database import db from libs import rsa from models.account import Tenant def decrypt_token(tenant_id: str, token: str): return rsa.decrypt(base64.b64decode(token), tenant_id)
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import base64 from extensions.ext_database import db from libs import rsa from models.account import Tenant def get_decrypt_decoding(tenant_id: str): return rsa.get_decrypt_decoding(tenant_id) def decrypt_token_with_decoding(token: str, rsa_key, cipher_rsa): return rsa.decrypt_token_with_decoding(base64.b64deco...
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import logging import random from core.entities.application_entities import ModelConfigEntity from core.model_runtime.errors.invoke import InvokeBadRequestError from core.model_runtime.model_providers.openai.moderation.moderation import OpenAIModerationModel from extensions.ext_hosting_provider import hosting_configura...
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import os from httpx import get as _get from httpx import head as _head from httpx import options as _options from httpx import patch as _patch from httpx import post as _post from httpx import put as _put from requests import delete as _delete httpx_proxies = { 'http://': SSRF_PROXY_HTTP_URL, 'https://': SSRF_...
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import os from httpx import get as _get from httpx import head as _head from httpx import options as _options from httpx import patch as _patch from httpx import post as _post from httpx import put as _put from requests import delete as _delete httpx_proxies = { 'http://': SSRF_PROXY_HTTP_URL, 'https://': SSRF_...
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import os from httpx import get as _get from httpx import head as _head from httpx import options as _options from httpx import patch as _patch from httpx import post as _post from httpx import put as _put from requests import delete as _delete httpx_proxies = { 'http://': SSRF_PROXY_HTTP_URL, 'https://': SSRF_...
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import os from httpx import get as _get from httpx import head as _head from httpx import options as _options from httpx import patch as _patch from httpx import post as _post from httpx import put as _put from requests import delete as _delete httpx_proxies = { 'http://': SSRF_PROXY_HTTP_URL, 'https://': SSRF_...
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import os from httpx import get as _get from httpx import head as _head from httpx import options as _options from httpx import patch as _patch from httpx import post as _post from httpx import put as _put from requests import delete as _delete requests_proxies = { 'http': SSRF_PROXY_HTTP_URL, 'https': SSRF_PRO...
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import os from httpx import get as _get from httpx import head as _head from httpx import options as _options from httpx import patch as _patch from httpx import post as _post from httpx import put as _put from requests import delete as _delete httpx_proxies = { 'http://': SSRF_PROXY_HTTP_URL, 'https://': SSRF_...
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import os from httpx import get as _get from httpx import head as _head from httpx import options as _options from httpx import patch as _patch from httpx import post as _post from httpx import put as _put from requests import delete as _delete httpx_proxies = { 'http://': SSRF_PROXY_HTTP_URL, 'https://': SSRF_...
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import concurrent.futures from typing import NamedTuple, Optional, cast class FileEncoding(NamedTuple): """A file encoding as the NamedTuple.""" encoding: Optional[str] """The encoding of the file.""" confidence: float """The confidence of the encoding.""" language: Optional[str] """The lang...
Try to detect the file encoding. Returns a list of `FileEncoding` tuples with the detected encodings ordered by confidence. Args: file_path: The path to the file to detect the encoding for. timeout: The timeout in seconds for the encoding detection.
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from __future__ import annotations import copy import logging import re from abc import ABC, abstractmethod from collections.abc import Callable, Collection, Iterable, Sequence, Set from dataclasses import dataclass from enum import Enum from typing import ( Any, Literal, Optional, TypedDict, TypeVa...
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from __future__ import annotations import copy import logging import re from abc import ABC, abstractmethod from collections.abc import Callable, Collection, Iterable, Sequence, Set from dataclasses import dataclass from enum import Enum from typing import ( Any, Literal, Optional, TypedDict, TypeVa...
Split incoming text and return chunks using tokenizer.
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import uuid def is_valid_uuid(uuid_str: str) -> bool: try: uuid.UUID(uuid_str) return True except Exception: return False
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import hashlib import json import os import re import site import subprocess import tempfile import unicodedata from contextlib import contextmanager import requests from bs4 import BeautifulSoup, CData, Comment, NavigableString from newspaper import Article from regex import regex from core.rag.extractor import extrac...
Page through `text` and return a substring of `max_length` characters starting from `cursor`.
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import hashlib import json import os import re import site import subprocess import tempfile import unicodedata from contextlib import contextmanager import requests from bs4 import BeautifulSoup, CData, Comment, NavigableString from newspaper import Article from regex import regex from core.rag.extractor import extrac...
Fetch URL and return the contents as a string.
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from pydantic import BaseModel The provided code snippet includes necessary dependencies for implementing the `serialize_base_model_array` function. Write a Python function `def serialize_base_model_array(l: list[BaseModel]) -> str` to solve the following problem: {"__root__": [BaseModel, BaseModel, ...]} Here is the...
{"__root__": [BaseModel, BaseModel, ...]}
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from pydantic import BaseModel The provided code snippet includes necessary dependencies for implementing the `serialize_base_model_dict` function. Write a Python function `def serialize_base_model_dict(b: dict) -> str` to solve the following problem: {"__root__": {BaseModel}} Here is the function: def serialize_bas...
{"__root__": {BaseModel}}
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import sqlalchemy as sa from alembic import op def upgrade(): # ### commands auto generated by Alembic - please adjust! ### with op.batch_alter_table('app_model_configs', schema=None) as batch_op: batch_op.add_column(sa.Column('external_data_tools', sa.Text(), nullable=True)) # ### end Alembic com...
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import sqlalchemy as sa from alembic import op def downgrade(): # ### commands auto generated by Alembic - please adjust! ### with op.batch_alter_table('app_model_configs', schema=None) as batch_op: batch_op.drop_column('external_data_tools') # ### end Alembic commands ###
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import sqlalchemy as sa from alembic import op from sqlalchemy.dialects import postgresql def upgrade(): # ### commands auto generated by Alembic - please adjust! ### op.create_table('tool_providers', sa.Column('id', postgresql.UUID(), server_default=sa.text('uuid_generate_v4()'), nullable=False), sa.C...
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import sqlalchemy as sa from alembic import op from sqlalchemy.dialects import postgresql def downgrade(): # ### commands auto generated by Alembic - please adjust! ### with op.batch_alter_table('app_model_configs', schema=None) as batch_op: batch_op.drop_column('sensitive_word_avoidance') op.drop...
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import sqlalchemy as sa from alembic import op from sqlalchemy.dialects import postgresql def upgrade(): # ### commands auto generated by Alembic - please adjust! ### op.create_table('dataset_collection_bindings', sa.Column('id', postgresql.UUID(), server_default=sa.text('uuid_generate_v4()'), nullable=Fal...
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import sqlalchemy as sa from alembic import op from sqlalchemy.dialects import postgresql def downgrade(): # ### commands auto generated by Alembic - please adjust! ### with op.batch_alter_table('datasets', schema=None) as batch_op: batch_op.drop_column('collection_binding_id') with op.batch_alter...
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import sqlalchemy as sa from alembic import op def upgrade(): # ### commands auto generated by Alembic - please adjust! ### with op.batch_alter_table('accounts', schema=None) as batch_op: batch_op.add_column(sa.Column('last_active_at', sa.DateTime(), server_default=sa.text('CURRENT_TIMESTAMP(0)'), null...
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import sqlalchemy as sa from alembic import op def downgrade(): # ### commands auto generated by Alembic - please adjust! ### with op.batch_alter_table('accounts', schema=None) as batch_op: batch_op.drop_column('last_active_at') # ### end Alembic commands ###
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import sqlalchemy as sa from alembic import op def upgrade(): # ### commands auto generated by Alembic - please adjust! ### with op.batch_alter_table('providers', schema=None) as batch_op: batch_op.alter_column('quota_limit', existing_type=sa.INTEGER(), type_=sa.BigInteger...
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import sqlalchemy as sa from alembic import op def downgrade(): # ### commands auto generated by Alembic - please adjust! ### with op.batch_alter_table('providers', schema=None) as batch_op: batch_op.alter_column('quota_used', existing_type=sa.BigInteger(), type_=sa.INTEGE...
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import sqlalchemy as sa from alembic import op def upgrade(): # ### commands auto generated by Alembic - please adjust! ### with op.batch_alter_table('provider_models', schema=None) as batch_op: batch_op.alter_column('model_name', existing_type=sa.VARCHAR(length=40), ...
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import sqlalchemy as sa from alembic import op def downgrade(): # ### commands auto generated by Alembic - please adjust! ### with op.batch_alter_table('provider_models', schema=None) as batch_op: batch_op.alter_column('model_name', existing_type=sa.String(length=255), ...
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import sqlalchemy as sa from alembic import op def upgrade(): # ### commands auto generated by Alembic - please adjust! ### with op.batch_alter_table('app_model_configs', schema=None) as batch_op: batch_op.add_column(sa.Column('prompt_type', sa.String(length=255), nullable=False, server_default='simple...
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import sqlalchemy as sa from alembic import op def downgrade(): # ### commands auto generated by Alembic - please adjust! ### with op.batch_alter_table('app_model_configs', schema=None) as batch_op: batch_op.drop_column('dataset_configs') batch_op.drop_column('completion_prompt_config') ...
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import sqlalchemy as sa from alembic import op from sqlalchemy.dialects import postgresql def upgrade(): # ### commands auto generated by Alembic - please adjust! ### op.create_table('provider_models', sa.Column('id', postgresql.UUID(), server_default=sa.text('uuid_generate_v4()'), nullable=False), sa....
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import sqlalchemy as sa from alembic import op from sqlalchemy.dialects import postgresql def downgrade(): # ### commands auto generated by Alembic - please adjust! ### with op.batch_alter_table('tenant_preferred_model_providers', schema=None) as batch_op: batch_op.drop_index('tenant_preferred_model_pr...
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import sqlalchemy as sa from alembic import op def upgrade(): # ### commands auto generated by Alembic - please adjust! ### with op.batch_alter_table('sites', schema=None) as batch_op: batch_op.alter_column('description', existing_type=sa.VARCHAR(length=255), type_=sa.Text...
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import sqlalchemy as sa from alembic import op def downgrade(): # ### commands auto generated by Alembic - please adjust! ### with op.batch_alter_table('sites', schema=None) as batch_op: batch_op.alter_column('description', existing_type=sa.Text(), type_=sa.VARCHAR(length=...
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16,887
import sqlalchemy as sa from alembic import op from sqlalchemy.dialects import postgresql def upgrade(): # ### commands auto generated by Alembic - please adjust! ### op.execute('CREATE EXTENSION IF NOT EXISTS "uuid-ossp";') op.create_table('account_integrates', sa.Column('id', postgresql.UUID(), serv...
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16,888
import sqlalchemy as sa from alembic import op from sqlalchemy.dialects import postgresql def downgrade(): # ### commands auto generated by Alembic - please adjust! ### with op.batch_alter_table('messages', schema=None) as batch_op: batch_op.drop_index('message_end_user_idx') batch_op.drop_inde...
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16,889
import sqlalchemy as sa from alembic import op from sqlalchemy.dialects import postgresql def upgrade(): # ### commands auto generated by Alembic - please adjust! ### op.create_table('data_source_bindings', sa.Column('id', postgresql.UUID(), server_default=sa.text('uuid_generate_v4()'), nullable=False), ...
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16,890
import sqlalchemy as sa from alembic import op from sqlalchemy.dialects import postgresql def downgrade(): # ### commands auto generated by Alembic - please adjust! ### with op.batch_alter_table('data_source_bindings', schema=None) as batch_op: batch_op.drop_index('source_info_idx', postgresql_using='g...
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16,891
from alembic import op def upgrade(): # ### commands auto generated by Alembic - please adjust! ### with op.batch_alter_table('tool_api_providers', schema=None) as batch_op: batch_op.create_unique_constraint('unique_api_tool_provider', ['name', 'tenant_id']) with op.batch_alter_table('tool_files',...
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16,892
from alembic import op def downgrade(): # ### commands auto generated by Alembic - please adjust! ### with op.batch_alter_table('tool_files', schema=None) as batch_op: batch_op.drop_index('tool_file_conversation_id_idx') with op.batch_alter_table('tool_api_providers', schema=None) as batch_op: ...
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16,893
import sqlalchemy as sa from alembic import op def upgrade(): # ### commands auto generated by Alembic - please adjust! ### with op.batch_alter_table('datasets', schema=None) as batch_op: batch_op.alter_column('embedding_model', existing_type=sa.VARCHAR(length=255), nullab...
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16,894
import sqlalchemy as sa from alembic import op def downgrade(): # ### commands auto generated by Alembic - please adjust! ### with op.batch_alter_table('datasets', schema=None) as batch_op: batch_op.alter_column('embedding_model_provider', existing_type=sa.VARCHAR(length=255), ...
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16,895
import sqlalchemy as sa from alembic import op from sqlalchemy.dialects import postgresql def upgrade(): # ### commands auto generated by Alembic - please adjust! ### op.create_table('tool_conversation_variables', sa.Column('id', postgresql.UUID(), server_default=sa.text('uuid_generate_v4()'), nullable=Fal...
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16,896
import sqlalchemy as sa from alembic import op from sqlalchemy.dialects import postgresql def downgrade(): # ### commands auto generated by Alembic - please adjust! ### with op.batch_alter_table('tool_api_providers', schema=None) as batch_op: batch_op.alter_column('icon', existing_type=s...
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16,897
import sqlalchemy as sa from alembic import op def upgrade(): # ### commands auto generated by Alembic - please adjust! ### with op.batch_alter_table('tool_api_providers', schema=None) as batch_op: batch_op.add_column(sa.Column('created_at', sa.DateTime(), server_default=sa.text('CURRENT_TIMESTAMP(0)')...
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16,898
import sqlalchemy as sa from alembic import op def downgrade(): # ### commands auto generated by Alembic - please adjust! ### with op.batch_alter_table('tool_api_providers', schema=None) as batch_op: batch_op.drop_column('updated_at') batch_op.drop_column('created_at') # ### end Alembic co...
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16,899
import sqlalchemy as sa from alembic import op def upgrade(): # ### commands auto generated by Alembic - please adjust! ### with op.batch_alter_table('embeddings', schema=None) as batch_op: batch_op.add_column(sa.Column('model_name', sa.String(length=40), server_default=sa.text("'text-embedding-ada-002...
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16,900
import sqlalchemy as sa from alembic import op def downgrade(): # ### commands auto generated by Alembic - please adjust! ### with op.batch_alter_table('embeddings', schema=None) as batch_op: batch_op.drop_constraint('embedding_hash_idx', type_='unique') batch_op.create_unique_constraint('embed...
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