id int64 0 190k | prompt stringlengths 21 13.4M | docstring stringlengths 1 12k ⌀ |
|---|---|---|
6,228 | import logging
import os
import random
import re
import time
import json
import abc
from logging import LogRecord
from typing import Any
import uuid
from threading import Lock
from colorama import Fore, Style
from XAgent.utils import Singleton, TaskSaveItem
logger = Logger()
class TaskSaveItem:
"""
This class ... | null |
6,229 | import logging
import os
import random
import re
import time
import json
import abc
from logging import LogRecord
from typing import Any
import uuid
from threading import Lock
from colorama import Fore, Style
from XAgent.utils import Singleton, TaskSaveItem
logger = Logger()
def print_assistant_thoughts(
# ai_name... | null |
6,230 | import json
from colorama import Fore
from XAgent.config import CONFIG
from XAgent.agent.base_agent import BaseAgent
from XAgent.agent.summarize import summarize_action, summarize_plan, clip_text
from XAgent.core import XAgentCoreComponents
from XAgent.data_structure.node import ToolNode
from XAgent.data_structure.tree... | Function to generate messages for each node. Args: now_node: The current ToolNode instance. task_handler: Handler of the tasks. max_length: Maximum length of the subtask chain. config: The configuration settings. Returns: The sequence of messages for the current node. |
6,231 | import json
from typing import Dict
The provided code snippet includes necessary dependencies for implementing the `get_command` function. Write a Python function `def get_command(response_json: Dict)` to solve the following problem:
Parses the response and returns the command name and arguments. This function will ra... | Parses the response and returns the command name and arguments. This function will raise the exception `json.decoder.JSONDecodeError` if the response is not valid JSON. Any other error that occurs is also caught and the function returns an "Error:" message with the exception message. Args: response_json (Dict): The res... |
6,232 | SYSTEM_PROMPT = '''You are plan-rectify agent, your task is to iteratively rectify a plan of a query.
--- Background Information ---
PLAN AND SUBTASK:
A plan has a tree manner of subtasks: task 1 contains subtasks task 1.1, task 1.2, task 1.3, and task 1.2 contains subtasks 1.2.1, 1.2.2...
Please remember:
1.The plan t... | The example that will be given to the dispatcher to generate the prompt Returns: example_input: the user query or the task example_system_prompt: the system prompt example_user_prompt: the user prompt |
6,233 | SYSTEM_PROMPT = '''You are an efficient plan-generation agent, your task is to decompose a query into several subtasks that describe must achieved goals for the query.
--- Background Information ---
PLAN AND SUBTASK:
A plan has a tree manner of subtasks: task 1 contatins subtasks task 1.1, task 1.2, task 1.3, ... and t... | The example that will be given to the dispatcher to generate the prompt Returns: example_input: the user query or the task example_system_prompt: the system prompt example_user_prompt: the user prompt |
6,234 | SYSTEM_PROMPT = '''You are an experimental cutting-edge super capable autonomous agent specialized in learning from environmental feeback and following rules to do correct and efficient actions.
Your decisions must always be made independently without seeking user assistance.
You can interactive with real world throug... | The example that will be given to the dispatcher to generate the prompt Returns: example_input: the user query or the task example_system_prompt: the system prompt example_user_prompt: the user prompt |
6,235 | SYSTEM_PROMPT = '''You are a posterior_knowledge_obtainer. You have performed some subtask together with:
1.Some intermediate thoughts, this is the reasoning path.
2.Some tool calls, which can interact with physical world, and provide in-time and accurate data.
3.A workspace, a minimal file system and code executer.
Yo... | The example that will be given to the dispatcher to generate the prompt Returns: example_input: the user query or the task example_system_prompt: the system prompt example_user_prompt: the user prompt |
6,236 | import json
import json5
from typing import List
from colorama import Fore, Style
from copy import deepcopy
from XAgent.logs import logger
from XAgent.workflow.base_query import BaseQuery
from XAgent.utils import TaskSaveItem, RequiredAbilities, PlanOperationStatusCode, TaskStatusCode
from XAgent.message_history import... | Parses the function output item into a Plan object. Args: function_output_item (dict): The dictionary representing the function output item. Returns: Plan: The parsed Plan object. |
6,237 | import json
import json5
from typing import List
from copy import deepcopy
from XAgent.utils import RequiredAbilities
from XAgent.data_structure.node import ToolNode
from XAgent.workflow.plan_exec import Plan
from XAgent.agent.summarize import summarize_action,summarize_plan
from XAgent.ai_functions import function_man... | Reflects on the previous actions and generates the posterior knowledge. Args: all_plan (Plan): The complete plan of actions. terminal_plan (Plan): The plan of actions at the terminal. finish_node (ToolNode): The node that represents the finishing tool. tool_functions_description_list (List[dict]): A list of dictionarie... |
6,238 | from XAgent.logs import logger
from XAgent.config import CONFIG,get_apiconfig_by_model,get_model_name
import requests
import traceback
logger = Logger()
CONFIG = XAgentConfig.get_default_config()
def get_model_name(model_name: str = None):
"""
Get the normalized model name for a given input model name.
... | null |
6,239 | import json
import openai
from XAgent.logs import logger
from XAgent.config import CONFIG, get_apiconfig_by_model, get_model_name
from tenacity import (
retry,
stop_after_attempt,
wait_exponential,
retry_if_not_exception_type,
wait_chain,
wait_none,
)
import importlib.metadata as metadata
impor... | Handle operation of OpenAI chat completion. This function operates OpenAI chat completion with provided arguments. It gets the model name, applies a JSON web token, if the response indicates the context length has been exceeded, it attempts to get a higher-capacity language model if it exists in the configuration and r... |
6,240 | import json
import openai
from XAgent.logs import logger
from XAgent.config import CONFIG, get_apiconfig_by_model, get_model_name
from tenacity import (
retry,
stop_after_attempt,
wait_exponential,
retry_if_not_exception_type,
wait_chain,
wait_none,
)
import importlib.metadata as metadata
impor... | Handle operation of OpenAI v1.x.x chat completion. This function operates OpenAI v1.x.x chat completion with provided arguments. It gets the model name, applies a JSON web token, if the response indicates the context length has been exceeded, it attempts to get a higher-capacity language model if it exists in the confi... |
6,241 | import os
import base64
import uuid
import json5 as json
import requests
from colorama import Fore
from XAgent.utils import ToolCallStatusCode
from XAgent.ai_functions import function_manager
from XAgent.recorder import RunningRecoder
def is_wrapped_response(obj: dict) -> bool:
"""
Check if the response object ... | Unwrap the tool response object. Args: obj: The tool response object. logger: The logger. Returns: The unwrapped tool response object. |
6,242 | import asyncio
from contextlib import contextmanager
import json
import os
import threading
import traceback
import uuid
from datetime import datetime
from typing import List
from colorama import Fore
from apscheduler.schedulers.asyncio import AsyncIOScheduler
from apscheduler.schedulers.blocking import BlockingSchedul... | Provide a transactional scope around a series of operations. |
6,243 | from xgen.parser import FunctionParser
from xgen.server.datamodel import *
from xgen.server.message_formater import format
import xgen.text.generate as generate
from xgen.models.transformers import XTransformers
from outlines.models.transformers import TransformersTokenizer
from vllm.sampling_params import LogitsProces... | null |
6,244 | from xgen.parser import FunctionParser
from xgen.server.datamodel import *
from xgen.server.message_formater import format
import xgen.text.generate as generate
from xgen.models.transformers import XTransformers
from outlines.models.transformers import TransformersTokenizer
from vllm.sampling_params import LogitsProces... | null |
6,245 | from typing import TYPE_CHECKING, Dict, List, Optional, Set, Union
import interegular
from cachetools import TTLCache
from outlines.text.generate.regex import Regex
from outlines.text.fsm import create_fsm_index_tokenizer, make_deterministic_fsm
def to_hash(vocabulary, regex_str, eos_token):
string = f"vocabulary:... | null |
6,246 | from typing import TYPE_CHECKING, Dict, List, Optional, Set, Union
import interegular
from cachetools import TTLCache
from outlines.text.generate.regex import Regex
from outlines.text.fsm import create_fsm_index_tokenizer, make_deterministic_fsm
class XRegex(Regex):
def __init__(
self,
model,
... | null |
6,247 | from transformers.generation.logits_process import (
LogitsProcessorList,
RepetitionPenaltyLogitsProcessor,
TemperatureLogitsWarper,
TopKLogitsWarper,
TopPLogitsWarper,
)
from outlines.models.transformers import Transformers,TransformersTokenizer
from typing import TYPE_CHECKING, List, Optional, Tup... | generate the logits processor with params |
6,248 | import json
import os
import orjson
from io import StringIO
from ruamel import yaml
def yaml_load(string):
def my_load(string, dump_method):
if dump_method == 'yaml':
return yaml_load(string)
elif dump_method == 'json':
return json.loads(string)
else:
raise NotImplementedError | null |
6,249 | import os
from contextlib import redirect_stdout
import argparse
from copy import deepcopy
from XAgent.config import CONFIG, ARGS
from command import CommandLine, CommandLineParam
The provided code snippet includes necessary dependencies for implementing the `parse_args` function. Write a Python function `def parse_ar... | Parse the command line arguments and return them as an argparse.Namespace object. Returns: argparse.Namespace: An object containing command line arguments and their values. |
6,250 | import os
from contextlib import redirect_stdout
import argparse
from copy import deepcopy
from XAgent.config import CONFIG, ARGS
from command import CommandLine, CommandLineParam
def start_command_line(args_dict: dict) -> None:
"""
Start the command line interface with the provided arguments.
Args:
... | Execute the command line process based on the parsed arguments. If quiet mode is enabled, redirect stdout to a file specified by the recorder's record_root_dir. Args: args (argparse.Namespace): Parsed command line arguments. quiet_mode (bool): Whether to run in quiet mode, outputting to a file instead of the terminal. |
6,251 | import os
import psutil
import uvicorn
import httpx
import asyncio
import traceback
import datetime
import docker.types
from fastapi import FastAPI, Cookie,Request,HTTPException,Response
from fastapi.responses import JSONResponse,RedirectResponse
from config import CONFIG,logger,MANAGER_ID
from connections import db,do... | Event handler triggered on startup of the app. Sets up necessary configurations like checking and creating table nodes if not exists in databse, creating subprocess to update node status, and registering path to node. |
6,252 | import os
import psutil
import uvicorn
import httpx
import asyncio
import traceback
import datetime
import docker.types
from fastapi import FastAPI, Cookie,Request,HTTPException,Response
from fastapi.responses import JSONResponse,RedirectResponse
from config import CONFIG,logger,MANAGER_ID
from connections import db,do... | Event handler on shutdown of the app. Specifically closes the database cursor if the database type os sqlite3. |
6,253 | import os
import psutil
import uvicorn
import httpx
import asyncio
import traceback
import datetime
import docker.types
from fastapi import FastAPI, Cookie,Request,HTTPException,Response
from fastapi.responses import JSONResponse,RedirectResponse
from config import CONFIG,logger,MANAGER_ID
from connections import db,do... | Endpoint to check if the service is running. Returns: str: "alive" |
6,254 | import os
import psutil
import uvicorn
import httpx
import asyncio
import traceback
import datetime
import docker.types
from fastapi import FastAPI, Cookie,Request,HTTPException,Response
from fastapi.responses import JSONResponse,RedirectResponse
from config import CONFIG,logger,MANAGER_ID
from connections import db,do... | Fetch server version and node info, create docker container and set the response cookies with the key "node_id" and value as the id of the created container. Also, adds the created node's details to the databse and waits for the node to startup. Returns: JSONResponse: A response object with status, headers and cookies ... |
6,255 | import os
import psutil
import uvicorn
import httpx
import asyncio
import traceback
import datetime
import docker.types
from fastapi import FastAPI, Cookie,Request,HTTPException,Response
from fastapi.responses import JSONResponse,RedirectResponse
from config import CONFIG,logger,MANAGER_ID
from connections import db,do... | Reconnect session of a node. Fetches node info and restarts the node if it exists. Args: node_id (str, optional): The unique identifier of the node. Defaults to Cookie(None). Returns: str: Success message if node restarts successfully. Raises: HTTPException: If node restart timeout occurs. |
6,256 | import os
import psutil
import uvicorn
import httpx
import asyncio
import traceback
import datetime
import docker.types
from fastapi import FastAPI, Cookie,Request,HTTPException,Response
from fastapi.responses import JSONResponse,RedirectResponse
from config import CONFIG,logger,MANAGER_ID
from connections import db,do... | Close session of a node. Fetches node info and stops the node if it exists and is not already exited. Args: node_id (str, optional): The unique identifier of the node. Defaults to Cookie(None). Returns: str: Success message if node stops successfully. |
6,257 | import os
import psutil
import uvicorn
import httpx
import asyncio
import traceback
import datetime
import docker.types
from fastapi import FastAPI, Cookie,Request,HTTPException,Response
from fastapi.responses import JSONResponse,RedirectResponse
from config import CONFIG,logger,MANAGER_ID
from connections import db,do... | Release session of a node. Fetches node info and kills the node if it exists and is not already exited. Also, removes the node. Args: node_id (str, optional): The unique identifier of the node. Defaults to Cookie(None). Returns: str: Success message if node is successfully killed and removed. |
6,258 | import os
import sys
import zipfile
import traceback
from typing import Coroutine,List
from fastapi import FastAPI,Body,UploadFile
from fastapi.requests import Request
from fastapi.exceptions import HTTPException
from starlette.responses import FileResponse
from config import CONFIG,logger
from core.register import Too... | Startup function to initialize the required services and variables for the application. |
6,259 | import os
import sys
import zipfile
import traceback
from typing import Coroutine,List
from fastapi import FastAPI,Body,UploadFile
from fastapi.requests import Request
from fastapi.exceptions import HTTPException
from starlette.responses import FileResponse
from config import CONFIG,logger
from core.register import Too... | Root function that returns a message Hello World. Returns: dict: A dictionary containing a welcoming message. |
6,260 | import os
import sys
import zipfile
import traceback
from typing import Coroutine,List
from fastapi import FastAPI,Body,UploadFile
from fastapi.requests import Request
from fastapi.exceptions import HTTPException
from starlette.responses import FileResponse
from config import CONFIG,logger
from core.register import Too... | This function allows the user to upload a file to the work directory defined in configuration file. Args: file (fastapi.UploadFile): The file to be uploaded. Returns: dict: A message denoting successful upload of the file. |
6,261 | import os
import sys
import zipfile
import traceback
from typing import Coroutine,List
from fastapi import FastAPI,Body,UploadFile
from fastapi.requests import Request
from fastapi.exceptions import HTTPException
from starlette.responses import FileResponse
from config import CONFIG,logger
from core.register import Too... | This function downloads a file from the work directory. Args: file_path (str): The path of the file to be downloaded. file_type (str, optional): Type of the file. Defaults to 'text/plain'. Returns: starlette.responses.FileResponse: File response containing the requested file for user to download. |
6,262 | import os
import sys
import zipfile
import traceback
from typing import Coroutine,List
from fastapi import FastAPI,Body,UploadFile
from fastapi.requests import Request
from fastapi.exceptions import HTTPException
from starlette.responses import FileResponse
from config import CONFIG,logger
from core.register import Too... | This function downloads the workspace which is a directory consisting of all the uploaded files. Returns: starlette.responses.FileResponse: File response containing the workspace for the user to download. |
6,263 | import os
import sys
import zipfile
import traceback
from typing import Coroutine,List
from fastapi import FastAPI,Body,UploadFile
from fastapi.requests import Request
from fastapi.exceptions import HTTPException
from starlette.responses import FileResponse
from config import CONFIG,logger
from core.register import Too... | This function generates the structure of the workspace directory. Returns: dict: A dictionary depicting the structure of the workspace directory. |
6,264 | import os
import sys
import zipfile
import traceback
from typing import Coroutine,List
from fastapi import FastAPI,Body,UploadFile
from fastapi.requests import Request
from fastapi.exceptions import HTTPException
from starlette.responses import FileResponse
from config import CONFIG,logger
from core.register import Too... | This function returns the available tools and environments registered in the ToolRegister. Returns: dict: A dictionary of available tools, environments and the JSON representation of the tools. |
6,265 | import os
import sys
import zipfile
import traceback
from typing import Coroutine,List
from fastapi import FastAPI,Body,UploadFile
from fastapi.requests import Request
from fastapi.exceptions import HTTPException
from starlette.responses import FileResponse
from config import CONFIG,logger
from core.register import Too... | This function retrieves the tool names based on a query question using the ADA retriever. Args: question (str): The query question for which tools are to be retrieved. top_k (int, optional): The number of top similar tools to be retrieved. Defaults to 5. Returns: dict: A dictionary with the list of retrieved tools and ... |
6,266 | import os
import sys
import zipfile
import traceback
from typing import Coroutine,List
from fastapi import FastAPI,Body,UploadFile
from fastapi.requests import Request
from fastapi.exceptions import HTTPException
from starlette.responses import FileResponse
from config import CONFIG,logger
from core.register import Too... | This function returns the JSON schema for the given list of tools. Args: tool_names (List[str]): List of tool names for which JSON schema is required. Returns: dict: JSON schema dictionary for all the available tools and list of error names for missing tools. |
6,267 | import os
import sys
import zipfile
import traceback
from typing import Coroutine,List
from fastapi import FastAPI,Body,UploadFile
from fastapi.requests import Request
from fastapi.exceptions import HTTPException
from starlette.responses import FileResponse
from config import CONFIG,logger
from core.register import Too... | This function returns the JSON schema for the given list of tool environments. Args: env_names (List[str]): List of environment names for which JSON schema is required. Returns: dict: JSON schema dictionary for all the available environments and list of error names for missing environments. |
6,268 | import os
import sys
import zipfile
import traceback
from typing import Coroutine,List
from fastapi import FastAPI,Body,UploadFile
from fastapi.requests import Request
from fastapi.exceptions import HTTPException
from starlette.responses import FileResponse
from config import CONFIG,logger
from core.register import Too... | This function allows the user to register a new tool by providing the tool name and code. Args: tool_name (str): The name of the new tool. code (str): The code for the new tool. Returns: dict: A dictionary representing the registered tool. Raises: HTTPException: If an error occurs during registering the new tool. |
6,269 | import os
import sys
import zipfile
import traceback
from typing import Coroutine,List
from fastapi import FastAPI,Body,UploadFile
from fastapi.requests import Request
from fastapi.exceptions import HTTPException
from starlette.responses import FileResponse
from config import CONFIG,logger
from core.register import Too... | This function executes a tool with the provided arguments and environment. Args: tool_name (str): The name of the tool to be executed. arguments (dict): The arguments for executing the tool. env_name (str, optional): The name of the tool environment in which tool is to be executed. Defaults to None. Returns: dict: The ... |
6,270 | import logging
import importlib
import traceback
from copy import deepcopy
from typing import Optional,Callable,Any,Type,Union
from core.base import BaseEnv
from core.labels import ToolLabels,EnvLabels
from core.exceptions import ToolNotFound,EnvNotFound,ToolRegisterError
from config import CONFIG
class BaseEnv:
"... | null |
6,271 | import logging
import inspect
import docstring_parser
from typing import Optional,Callable,Any,Type,Union
from core.base import BaseEnv
from core.labels import ToolLabels,EnvLabels
from config import CONFIG
def generate_tool_labels(
name: str = None,
enabled: bool = True,
disabled_reason: Optional[str] = No... | The tool decorator for class, used to create tool objects from ordinary class. |
6,272 | import re
from fastapi import HTTPException
ansi_escape = re.compile(r'\x1B(?:[@-Z\\-_]|\[[0-?]*[ -/]*[@-~])')
The provided code snippet includes necessary dependencies for implementing the `remove_color` function. Write a Python function `def remove_color(text)` to solve the following problem:
Removes ANSI escape seq... | Removes ANSI escape sequences i.e. colors, from the text. Args: text (str): The text from which color needs to be removed. Returns: str: The filtered text with no color. |
6,273 | import asyncio
from config import CONFIG
from core.register import toolwrapper
from core.exceptions import ToolExecutionError
ALL_SHELLS: dict[int, asyncio.subprocess.Process] = {}
async def read_exec_proc_display(exec_proc: asyncio.subprocess.Process):
display = ""
for pipe, name in zip([exec_proc.stderr,exec_... | The shell tool that execute shell command in root privilege, return the output and error. You can use this tool to install packages, download files, run programs, etc. Set run_async=True to run the command in a new thread and return instantly if your command is time costly like install packages, host services. Example:... |
6,274 | import os
import json
import httpx
from typing import Type
from copy import deepcopy
from config import CONFIG
from core.base import BaseEnv
from core.register import toolwrapper
from utils.retriever import standardizing
API_INFOS = {}
def convert_rapidapi_desc_to_code(rapidapi_desc:dict)->list[dict]:
tool_desc = {... | Dynamic adding api functions to RapidAPIENnv. |
6,275 | import subprocess
import sys
import select
import os
import io
from typing import Union,Dict,Any
from core.base import BaseEnv
from core.register import toolwrapper,get_func_name
from core.exceptions import OutputNotReady
import os
if os.path.exists("XAgentServer/application/core/prod_server_envs.py") and XAgent... | Reading the `subprocess.PIPE` when readable. If `text` is `True`, return str, else return bytes. |
6,276 | import requests
from config import CONFIG
from core.register import toolwrapper
bing_cfg = CONFIG['bing']
The provided code snippet includes necessary dependencies for implementing the `bing_search` function. Write a Python function `def bing_search(query:str,region:str = None)->str|list[str]` to solve the following p... | Return 3 most relevant results of a Bing search using the official Bing API. This tool does not provide website details, use other tools to browse website if you need. :param string query: The search query. :param string? region: The region code of the search, default to `en-US`. Available regions: `en-US`, `zh-CN`, `j... |
6,277 | import asyncio
from config import CONFIG
from core.register import toolwrapper
from core.envs.filesystem import FileSystemEnv
CODE_FS = FileSystemEnv()
CONFIG = XAgentConfig.get_default_config()
The provided code snippet includes necessary dependencies for implementing the `run_interpreter` function. Write a Python f... | The code interpreter tool that runs code and return the output. The `code` will be written to file `filename` and the `command` will be executed in a shell. Example: ``` run_interpreter(code='print("hello world")',command='python code.py') ``` :param string? code: The code to be written, default to `None`, which means ... |
6,278 | import requests
import xmltodict
from config import CONFIG
from core.register import toolwrapper
The provided code snippet includes necessary dependencies for implementing the `calculator` function. Write a Python function `def calculator(expression:str)->str` to solve the following problem:
It is a simple calculator,... | It is a simple calculator, which can execute Python expressions: e.g., "(123 + 234) / 23 * 1.5 - 8". :param string expression: The python expression you requested. :return string: The execution results of the expression. |
6,279 | import base64
from typing import Callable,Dict,Any
from config import logger
The provided code snippet includes necessary dependencies for implementing the `is_base64` function. Write a Python function `def is_base64(s:str) -> bool` to solve the following problem:
Check if the given string is a base64 sting or not. Ar... | Check if the given string is a base64 sting or not. Args: s (str): the string to be checked. Returns: bool: Returns True if the given string is a base64 string, False otherwise. |
6,280 | import os
import importlib
def import_all_modules_in_folder(file,name):
current_dir = os.path.dirname(file)
all_modules = []
for item in os.listdir(current_dir):
item_path = os.path.join(current_dir, item)
if os.path.isfile(item_path) and item != '__init__.py' and item.endswith('.py'):
... | null |
6,281 | import asyncio
import functools
import time
from colorama import Fore
from XAgentServer.exts.exception_ext import XAgentTimeoutError, XAgentCloseError
from inputimeout import inputimeout, TimeoutOccurred
from XAgentServer.application.global_val import redis
import math
The provided code snippet includes necessary depe... | Decorator function to time the execution of a function. Args: func (Function): The function to be timed. Returns: wrapper (Function): The wrapped function with added timing functionality. |
6,282 | import traceback
import uvicorn
from colorama import Fore
from fastapi import FastAPI, Request, Response
from fastapi.exceptions import RequestValidationError
from fastapi.middleware.cors import CORSMiddleware
from fastapi.responses import JSONResponse
from XAgentServer.application.core.envs import XAgentServerEnv
from... | Exception middleware |
6,283 | import traceback
import uvicorn
from colorama import Fore
from fastapi import FastAPI, Request, Response
from fastapi.exceptions import RequestValidationError
from fastapi.middleware.cors import CORSMiddleware
from fastapi.responses import JSONResponse
from XAgentServer.application.core.envs import XAgentServerEnv
from... | start up event |
6,284 | import traceback
import uvicorn
from colorama import Fore
from fastapi import FastAPI, Request, Response
from fastapi.exceptions import RequestValidationError
from fastapi.middleware.cors import CORSMiddleware
from fastapi.responses import JSONResponse
from XAgentServer.application.core.envs import XAgentServerEnv
from... | shut down event |
6,285 | import traceback
import uvicorn
from colorama import Fore
from fastapi import FastAPI, Request, Response
from fastapi.exceptions import RequestValidationError
from fastapi.middleware.cors import CORSMiddleware
from fastapi.responses import JSONResponse
from XAgentServer.application.core.envs import XAgentServerEnv
from... | handle validation exception Args: request (Request): _description_ exc (RequestValidationError): _description_ Returns: _type_: _description_ |
6,286 | import base64
import os
from XAgentServer.application.cruds.user import UserCRUD
from XAgentServer.database.models import Raw
from XAgentServer.exts.exception_ext import XAgentWebSocketConnectError
class UserCRUD(metaclass=abc.ABCMeta):
"""
User CRUD
"""
def get_user_list(cls, db: Session) -> list[XAg... | check user for websocket connection |
6,287 | import base64
import os
from XAgentServer.application.cruds.user import UserCRUD
from XAgentServer.database.models import Raw
from XAgentServer.exts.exception_ext import XAgentWebSocketConnectError
class Raw(Base):
"""Raw Data"""
__tablename__ = "raw"
# id/id
id = Column(Integer, primary_key=True, inde... | handle data for websocket response |
6,288 | import base64
import os
from XAgentServer.application.cruds.user import UserCRUD
from XAgentServer.database.models import Raw
from XAgentServer.exts.exception_ext import XAgentWebSocketConnectError
The provided code snippet includes necessary dependencies for implementing the `handle_workspace_filelist` function. Writ... | handle workspace file list Args: file_list (_type_): file_list is a list of file name Returns: List[Dict]: element list, each element is a dict with name and suffix |
6,289 | from datetime import datetime
import time
import json
import os
from typing import List
import uuid
import zipfile
from fastapi import APIRouter, Depends, File, Form, UploadFile
import requests
from sqlalchemy.orm import Session
from XAgentServer.application.core.envs import XAgentServerEnv
from XAgentServer.applicatio... | get all interactions by user_id |
6,290 | from datetime import datetime
import time
import json
import os
from typing import List
import uuid
import zipfile
from fastapi import APIRouter, Depends, File, Form, UploadFile
import requests
from sqlalchemy.orm import Session
from XAgentServer.application.core.envs import XAgentServerEnv
from XAgentServer.applicatio... | initialize conv env |
6,291 | from datetime import datetime
import time
import json
import os
from typing import List
import uuid
import zipfile
from fastapi import APIRouter, Depends, File, Form, UploadFile
import requests
from sqlalchemy.orm import Session
from XAgentServer.application.core.envs import XAgentServerEnv
from XAgentServer.applicatio... | get all interactions by user id |
6,292 | from datetime import datetime
import time
import json
import os
from typing import List
import uuid
import zipfile
from fastapi import APIRouter, Depends, File, Form, UploadFile
import requests
from sqlalchemy.orm import Session
from XAgentServer.application.core.envs import XAgentServerEnv
from XAgentServer.applicatio... | update_interaction_description |
6,293 | from datetime import datetime
import time
import json
import os
from typing import List
import uuid
import zipfile
from fastapi import APIRouter, Depends, File, Form, UploadFile
import requests
from sqlalchemy.orm import Session
from XAgentServer.application.core.envs import XAgentServerEnv
from XAgentServer.applicatio... | community, this api is runing on x-agent.net |
6,294 | from datetime import datetime
import time
import json
import os
from typing import List
import uuid
import zipfile
from fastapi import APIRouter, Depends, File, Form, UploadFile
import requests
from sqlalchemy.orm import Session
from XAgentServer.application.core.envs import XAgentServerEnv
from XAgentServer.applicatio... | delete |
6,295 | from datetime import datetime
import time
import json
import os
from typing import List
import uuid
import zipfile
from fastapi import APIRouter, Depends, File, Form, UploadFile
import requests
from sqlalchemy.orm import Session
from XAgentServer.application.core.envs import XAgentServerEnv
from XAgentServer.applicatio... | update parameter |
6,296 | from datetime import datetime
import time
import json
import os
from typing import List
import uuid
import zipfile
from fastapi import APIRouter, Depends, File, Form, UploadFile
import requests
from sqlalchemy.orm import Session
from XAgentServer.application.core.envs import XAgentServerEnv
from XAgentServer.applicatio... | update description |
6,297 | import smtplib
import uuid
from datetime import datetime
from fastapi import APIRouter, Depends, Form, Query
from sqlalchemy.orm import Session
from XAgentServer.application.core.envs import XAgentServerEnv
from XAgentServer.application.cruds.user import UserCRUD
from XAgentServer.application.dependence import get_db
f... | register user |
6,298 | import smtplib
import uuid
from datetime import datetime
from fastapi import APIRouter, Depends, Form, Query
from sqlalchemy.orm import Session
from XAgentServer.application.core.envs import XAgentServerEnv
from XAgentServer.application.cruds.user import UserCRUD
from XAgentServer.application.dependence import get_db
f... | user auth |
6,299 | import smtplib
import uuid
from datetime import datetime
from fastapi import APIRouter, Depends, Form, Query
from sqlalchemy.orm import Session
from XAgentServer.application.core.envs import XAgentServerEnv
from XAgentServer.application.cruds.user import UserCRUD
from XAgentServer.application.dependence import get_db
f... | login |
6,300 | import smtplib
import uuid
from datetime import datetime
from fastapi import APIRouter, Depends, Form, Query
from sqlalchemy.orm import Session
from XAgentServer.application.core.envs import XAgentServerEnv
from XAgentServer.application.cruds.user import UserCRUD
from XAgentServer.application.dependence import get_db
f... | check token is effective |
6,301 | import base64
import json
import os
from typing import List
import uuid
from fastapi import APIRouter, Depends, File, Form, HTTPException, UploadFile
from fastapi.responses import FileResponse
from sqlalchemy.orm import Session
from XAgentServer.application.core.envs import XAgentServerEnv
from XAgentServer.application... | Upload Files |
6,302 | import os
from colorama import Fore
from XAgentServer.application.core.envs import XAgentServerEnv
from XAgentServer.application.global_val import (init_executor, init_yag)
from XAgentServer.loggers.logs import Logger
from XAgentServer.database.connect import SessionLocal
class XAgentServerEnv:
"""
XAgentServe... | logger |
6,303 | import abc
import json
import logging
import os
import random
import re
import time
from logging import LogRecord
from typing import Any
from colorama import Fore, Style
def remove_color_codes(s: str) -> str:
ansi_escape = re.compile(r"\x1B(?:[@-Z\\-_]|\[[0-?]*[ -/]*[@-~])")
return ansi_escape.sub("", s) | null |
6,304 | global_map = {}
def add_to_map(key, value):
global_map[key] = value | null |
6,305 | global_map = {}
def lookup_in_map(key):
return global_map.get(key) | null |
6,306 | import math
import copy
import os
import warnings
import torch
import torch.utils.checkpoint
import torch.nn.functional as F
from torch import nn
from torch.nn import CrossEntropyLoss, LayerNorm
from torch.nn.utils import skip_init
from typing import Optional, Tuple, Union, List, Callable
from transformers.utils import... | Load tf checkpoints in a pytorch model. |
6,307 | import math
import copy
import os
import warnings
import torch
import torch.utils.checkpoint
import torch.nn.functional as F
from torch import nn
from torch.nn import CrossEntropyLoss, LayerNorm
from torch.nn.utils import skip_init
from typing import Optional, Tuple, Union, List, Callable
from transformers.utils import... | null |
6,308 | import math
import copy
import os
import warnings
import torch
import torch.utils.checkpoint
import torch.nn.functional as F
from torch import nn
from torch.nn import CrossEntropyLoss, LayerNorm
from torch.nn.utils import skip_init
from typing import Optional, Tuple, Union, List, Callable
from transformers.utils import... | null |
6,309 | import math
import copy
import os
import warnings
import torch
import torch.utils.checkpoint
import torch.nn.functional as F
from torch import nn
from torch.nn import CrossEntropyLoss, LayerNorm
from torch.nn.utils import skip_init
from typing import Optional, Tuple, Union, List, Callable
from transformers.utils import... | null |
6,310 | import logging
import math
import os
import sys
from dataclasses import dataclass, field
from itertools import chain
from typing import Optional
import datasets
import evaluate
import torch
from datasets import load_dataset
from typing import Dict
import transformers
from transformers import (
CONFIG_MAPPING,
M... | null |
6,311 | import json
import torch
from torch.utils.data import Dataset
from transformers import AutoTokenizer
tokenizer = AutoTokenizer.from_pretrained(
"THUDM/chatglm-6b", trust_remote_code=True)
def get_masks_and_position_ids(
seq, seq_len, context_length, device, gmask=False, position_encoding_2d=True
):
def chat_da... | null |
6,312 | import random
import numpy as np
import torch.utils.data as data
from PIL import Image
import torchvision.transforms as transforms
from abc import ABC, abstractmethod
def get_params(opt, size):
w, h = size
new_h = h
new_w = w
if opt.preprocess == 'resize_and_crop':
new_h = new_w = opt.load_size... | null |
6,313 | import random
import numpy as np
import torch.utils.data as data
from PIL import Image
import torchvision.transforms as transforms
from abc import ABC, abstractmethod
def __make_power_2(img, base, method=Image.BICUBIC):
def __scale_width(img, target_size, crop_size, method=Image.BICUBIC):
def __crop(img, pos, size):
de... | null |
6,314 | import torch.utils.data as data
from PIL import Image
import os
def is_image_file(filename):
return any(filename.endswith(extension) for extension in IMG_EXTENSIONS)
def make_dataset(dir, max_dataset_size=float("inf")):
images = []
assert os.path.isdir(dir), '%s is not a valid directory' % dir
for roo... | null |
6,315 | import torch.utils.data as data
from PIL import Image
import os
def default_loader(path):
return Image.open(path).convert('RGB') | null |
6,316 | from pix2pix.data.base_dataset import BaseDataset
from pix2pix.data.image_folder import make_dataset
from pix2pix.util.guidedfilter import GuidedFilter
import numpy as np
import os
import torch
from PIL import Image
def normalize(img):
img = img * 2
img = img - 1
return img | null |
6,317 | from pix2pix.data.base_dataset import BaseDataset
from pix2pix.data.image_folder import make_dataset
from pix2pix.util.guidedfilter import GuidedFilter
import numpy as np
import os
import torch
from PIL import Image
def normalize01(img):
return (img - torch.min(img)) / (torch.max(img)-torch.min(img)) | null |
6,318 | import torch
import torch.nn as nn
from torch.nn import init
import functools
from torch.optim import lr_scheduler
The provided code snippet includes necessary dependencies for implementing the `get_scheduler` function. Write a Python function `def get_scheduler(optimizer, opt)` to solve the following problem:
Return ... | Return a learning rate scheduler Parameters: optimizer -- the optimizer of the network opt (option class) -- stores all the experiment flags; needs to be a subclass of BaseOptions． opt.lr_policy is the name of learning rate policy: linear | step | plateau | cosine For 'linear', we keep the same learning rate for the fi... |
6,319 | import torch
import torch.nn as nn
from torch.nn import init
import functools
from torch.optim import lr_scheduler
def get_norm_layer(norm_type='instance'):
"""Return a normalization layer
Parameters:
norm_type (str) -- the name of the normalization layer: batch | instance | none
For BatchNorm, we u... | Create a generator Parameters: input_nc (int) -- the number of channels in input images output_nc (int) -- the number of channels in output images ngf (int) -- the number of filters in the last conv layer netG (str) -- the architecture's name: resnet_9blocks | resnet_6blocks | unet_256 | unet_128 norm (str) -- the name... |
6,320 | import torch
import torch.nn as nn
from torch.nn import init
import functools
from torch.optim import lr_scheduler
def get_norm_layer(norm_type='instance'):
"""Return a normalization layer
Parameters:
norm_type (str) -- the name of the normalization layer: batch | instance | none
For BatchNorm, we u... | Create a discriminator Parameters: input_nc (int) -- the number of channels in input images ndf (int) -- the number of filters in the first conv layer netD (str) -- the architecture's name: basic | n_layers | pixel n_layers_D (int) -- the number of conv layers in the discriminator; effective when netD=='n_layers' norm ... |
6,321 | import torch
import torch.nn as nn
from torch.nn import init
import functools
from torch.optim import lr_scheduler
The provided code snippet includes necessary dependencies for implementing the `cal_gradient_penalty` function. Write a Python function `def cal_gradient_penalty(netD, real_data, fake_data, device, type='... | Calculate the gradient penalty loss, used in WGAN-GP paper https://arxiv.org/abs/1704.00028 Arguments: netD (network) -- discriminator network real_data (tensor array) -- real images fake_data (tensor array) -- generated images from the generator device (str) -- GPU / CPU: from torch.device('cuda:{}'.format(self.gpu_id... |
6,322 | from __future__ import print_function
import torch
import numpy as np
from PIL import Image
import os
The provided code snippet includes necessary dependencies for implementing the `diagnose_network` function. Write a Python function `def diagnose_network(net, name='network')` to solve the following problem:
Calculate... | Calculate and print the mean of average absolute(gradients) Parameters: net (torch network) -- Torch network name (str) -- the name of the network |
6,323 | from __future__ import print_function
import torch
import numpy as np
from PIL import Image
import os
The provided code snippet includes necessary dependencies for implementing the `print_numpy` function. Write a Python function `def print_numpy(x, val=True, shp=False)` to solve the following problem:
Print the mean, ... | Print the mean, min, max, median, std, and size of a numpy array Parameters: val (bool) -- if print the values of the numpy array shp (bool) -- if print the shape of the numpy array |
6,324 | from __future__ import print_function
import torch
import numpy as np
from PIL import Image
import os
def mkdir(path):
"""create a single empty directory if it didn't exist
Parameters:
path (str) -- a single directory path
"""
if not os.path.exists(path):
os.makedirs(path)
The provided ... | create empty directories if they don't exist Parameters: paths (str list) -- a list of directory paths |
6,325 | import numpy as np
import os
import sys
import ntpath
import time
from . import util, html
from subprocess import Popen, PIPE
import torch
The provided code snippet includes necessary dependencies for implementing the `save_images` function. Write a Python function `def save_images(webpage, visuals, image_path, aspect... | Save images to the disk. Parameters: webpage (the HTML class) -- the HTML webpage class that stores these imaegs (see html.py for more details) visuals (OrderedDict) -- an ordered dictionary that stores (name, images (either tensor or numpy) ) pairs image_path (str) -- the string is used to create image paths aspect_ra... |
6,326 | import os
import cv2
import glob
import numpy as np
import imageio
from MiDaS.MiDaS_utils import write_depth
BOOST_BASE = 'BoostingMonocularDepth'
BOOST_INPUTS = 'inputs'
BOOST_OUTPUTS = 'outputs'
def clean_folder(folder, img_exts=['.png', '.jpg', '.npy']):
def resize_depth(depth, width, height):
def run_boostmonodept... | null |
6,327 | import os
import glob
import cv2
import scipy.misc as misc
from skimage.transform import resize
import numpy as np
from functools import reduce
from operator import mul
import torch
from torch import nn
import matplotlib.pyplot as plt
import re
from scipy.ndimage import gaussian_filter
from skimage.feature import canny... | null |
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