repo stringlengths 7 90 | file_url stringlengths 81 315 | file_path stringlengths 4 228 | content stringlengths 0 32.8k | language stringclasses 1
value | license stringclasses 7
values | commit_sha stringlengths 40 40 | retrieved_at stringdate 2026-01-04 14:38:15 2026-01-05 02:33:18 | truncated bool 2
classes |
|---|---|---|---|---|---|---|---|---|
cwjokaka/bilibili_member_crawler | https://github.com/cwjokaka/bilibili_member_crawler/blob/a4b9cb64b073ec452f1b12b5225539e53996689b/exception/sql_insert_exception.py | exception/sql_insert_exception.py | from exception.bilibili_exception import BilibiliException
class SqlInsertException(BilibiliException):
def __init__(self, msg) -> None:
super().__init__(msg)
| python | MIT | a4b9cb64b073ec452f1b12b5225539e53996689b | 2026-01-05T07:13:29.310919Z | false |
cwjokaka/bilibili_member_crawler | https://github.com/cwjokaka/bilibili_member_crawler/blob/a4b9cb64b073ec452f1b12b5225539e53996689b/exception/sql_already_exists_exception.py | exception/sql_already_exists_exception.py | from exception.bilibili_exception import BilibiliException
class SqlAlreadyExistsException(BilibiliException):
def __init__(self, msg) -> None:
super().__init__(msg)
| python | MIT | a4b9cb64b073ec452f1b12b5225539e53996689b | 2026-01-05T07:13:29.310919Z | false |
cwjokaka/bilibili_member_crawler | https://github.com/cwjokaka/bilibili_member_crawler/blob/a4b9cb64b073ec452f1b12b5225539e53996689b/exception/__init__.py | exception/__init__.py | python | MIT | a4b9cb64b073ec452f1b12b5225539e53996689b | 2026-01-05T07:13:29.310919Z | false | |
cwjokaka/bilibili_member_crawler | https://github.com/cwjokaka/bilibili_member_crawler/blob/a4b9cb64b073ec452f1b12b5225539e53996689b/exception/user_not_found_exception.py | exception/user_not_found_exception.py | from exception.bilibili_exception import BilibiliException
class UserNotFoundException(BilibiliException):
def __init__(self, msg) -> None:
super().__init__(msg)
| python | MIT | a4b9cb64b073ec452f1b12b5225539e53996689b | 2026-01-05T07:13:29.310919Z | false |
aaugustin/datedelta | https://github.com/aaugustin/datedelta/blob/82df8cc33b270fe5b06870b2ca2591faf1d3241c/test_datedelta.py | test_datedelta.py | # For convenience and readability in tests, use short aliases.
import pickle
from datetime import date as d
from datetime import timedelta as td
import pytest
from datedelta import datedelta as dd
from datedelta import DAY, MONTH, WEEK, YEAR
@pytest.mark.parametrize(
("constant", "value"),
[
(DAY, d... | python | BSD-3-Clause | 82df8cc33b270fe5b06870b2ca2591faf1d3241c | 2026-01-05T07:13:33.593315Z | false |
aaugustin/datedelta | https://github.com/aaugustin/datedelta/blob/82df8cc33b270fe5b06870b2ca2591faf1d3241c/datedelta.py | datedelta.py | import datetime
class datedelta:
__slots__ = ["_years", "_months", "_days"]
def __init__(self, *, years=0, months=0, days=0):
int_years = int(years)
int_months = int(months)
int_days = int(days)
if int_years != years:
raise ValueError("years must be an integer val... | python | BSD-3-Clause | 82df8cc33b270fe5b06870b2ca2591faf1d3241c | 2026-01-05T07:13:33.593315Z | false |
aantonop/wifiportal21 | https://github.com/aantonop/wifiportal21/blob/73c6e1120eeeb2b4a1c1684bc61062ab77fde85f/setup.py | setup.py | #!/usr/bin/env python
from setuptools import setup, find_packages
setup(
name='wifiportal21',
version = "0.1",
packages=['wifiportal21'],
package_data={'wifiportal21': ['templates/*','static/*']},
include_package_data=True,
license='http://opensource.org/licenses/MIT',
author='Andreas M. An... | python | MIT | 73c6e1120eeeb2b4a1c1684bc61062ab77fde85f | 2026-01-05T07:13:34.315735Z | false |
aantonop/wifiportal21 | https://github.com/aantonop/wifiportal21/blob/73c6e1120eeeb2b4a1c1684bc61062ab77fde85f/config.py | config.py | receiving_key = "xpub6F8dWKbomfy7qmQ9Ma16SAwL3H9xMyaEjAfsEhtRjt5Bx3MFHTgDjvp4eZfUZES4i4AgaVGzVPyCKbSufdVsFvfR4wNjKRGraJrv5nLVs4h" # m/44'/0'/0'/0
SATOSHIS_PER_MINUTE = 2000
| python | MIT | 73c6e1120eeeb2b4a1c1684bc61062ab77fde85f | 2026-01-05T07:13:34.315735Z | false |
aantonop/wifiportal21 | https://github.com/aantonop/wifiportal21/blob/73c6e1120eeeb2b4a1c1684bc61062ab77fde85f/wifiportal21/__init__.py | wifiportal21/__init__.py | python | MIT | 73c6e1120eeeb2b4a1c1684bc61062ab77fde85f | 2026-01-05T07:13:34.315735Z | false | |
aantonop/wifiportal21 | https://github.com/aantonop/wifiportal21/blob/73c6e1120eeeb2b4a1c1684bc61062ab77fde85f/wifiportal21/auth_server.py | wifiportal21/auth_server.py | #!/usr/bin/env python
import logging
import requests
import flask
from flask import Flask
from flask_sqlalchemy import SQLAlchemy
from flask import request, flash, redirect, render_template, url_for
from flask import jsonify
from two1.lib.bitcoin.crypto import HDKey, HDPublicKey
from two1.lib.wallet.hd_account impor... | python | MIT | 73c6e1120eeeb2b4a1c1684bc61062ab77fde85f | 2026-01-05T07:13:34.315735Z | false |
CuriousLearner/GeeksForGeeksScrapper | https://github.com/CuriousLearner/GeeksForGeeksScrapper/blob/1b683913d9eb3a1f60140920c33c46afc9c3de79/g4g.py | g4g.py | #!/usr/bin/python
import requests
from os import system
from sys import exit
from time import sleep
from requests.exceptions import ConnectionError
from bs4 import BeautifulSoup
from article import Article
BASE_URL = "http://www.geeksforgeeks.org/"
articles = []
CHOICE_TO_CATEGORY_MAPPING = {
1: "c",
2: ... | python | MIT | 1b683913d9eb3a1f60140920c33c46afc9c3de79 | 2026-01-05T07:13:34.983476Z | false |
CuriousLearner/GeeksForGeeksScrapper | https://github.com/CuriousLearner/GeeksForGeeksScrapper/blob/1b683913d9eb3a1f60140920c33c46afc9c3de79/article.py | article.py | class Article(object):
""" This Class Contains the title and the content of the article.
The title can be use as key to the article link for the navigation purpose. """
def __init__(self, title, content):
self.title = title
self.content = content
| python | MIT | 1b683913d9eb3a1f60140920c33c46afc9c3de79 | 2026-01-05T07:13:34.983476Z | false |
Berkeley-NLP/Agent-Eval-Refine | https://github.com/Berkeley-NLP/Agent-Eval-Refine/blob/0eef6eba80d91d99d99133c319f464d7adf47abe/exps/android_exp/client.py | exps/android_exp/client.py | from gradio_client import Client
from PIL import Image
from env import AndroidAction, ActionType
from typing import Dict, Union
from time import sleep
from abc import ABC, abstractmethod
class AbstractAgent(ABC):
@abstractmethod
def act(self, task:str, image_path:str)->Union[AndroidAction, Dict]:
pas... | python | BSD-3-Clause | 0eef6eba80d91d99d99133c319f464d7adf47abe | 2026-01-05T07:13:34.281805Z | false |
Berkeley-NLP/Agent-Eval-Refine | https://github.com/Berkeley-NLP/Agent-Eval-Refine/blob/0eef6eba80d91d99d99133c319f464d7adf47abe/exps/android_exp/runner.py | exps/android_exp/runner.py | from env import AndroidEnv
from client import AbstractAgent
import time
import time
import uuid
import os
import json
from termcolor import colored, cprint
def create_human_friendly_uid():
current_time_str = time.strftime("%m%d_%H%M%S")
# Generate a random UUID
random_uuid = str(uuid.uuid4()).split("-")[0... | python | BSD-3-Clause | 0eef6eba80d91d99d99133c319f464d7adf47abe | 2026-01-05T07:13:34.281805Z | false |
Berkeley-NLP/Agent-Eval-Refine | https://github.com/Berkeley-NLP/Agent-Eval-Refine/blob/0eef6eba80d91d99d99133c319f464d7adf47abe/exps/android_exp/main.py | exps/android_exp/main.py | from env import AndroidEnv, AndroidAction, ActionType
from runner import Runner
from client import CogAgent, AutoUI
import argparse
import json
import os
def main(args):
if args.agent == "cogagent":
agent = CogAgent("https://6cbe60874cce4c4f3e<removed>/")
elif args.agent == "autoui-large":
age... | python | BSD-3-Clause | 0eef6eba80d91d99d99133c319f464d7adf47abe | 2026-01-05T07:13:34.281805Z | false |
Berkeley-NLP/Agent-Eval-Refine | https://github.com/Berkeley-NLP/Agent-Eval-Refine/blob/0eef6eba80d91d99d99133c319f464d7adf47abe/exps/android_exp/env.py | exps/android_exp/env.py | import os
import shutil
from dataclasses import dataclass
from typing import List, Tuple, Union
from enum import Enum
import subprocess, signal
import re
from time import sleep
from appium import webdriver
from appium.options.android import UiAutomator2Options
import base64
from PIL import Image
from io import BytesI... | python | BSD-3-Clause | 0eef6eba80d91d99d99133c319f464d7adf47abe | 2026-01-05T07:13:34.281805Z | false |
Berkeley-NLP/Agent-Eval-Refine | https://github.com/Berkeley-NLP/Agent-Eval-Refine/blob/0eef6eba80d91d99d99133c319f464d7adf47abe/exps/android_exp/models/Auto-UI/action_matching.py | exps/android_exp/models/Auto-UI/action_matching.py | '''
Adapted from https://github.com/google-research/google-research/tree/master/android_in_the_wild
'''
# import jax
# import jax.numpy as jnp
import numpy as np
import action_type as action_type_lib
_TAP_DISTANCE_THRESHOLD = 0.14 # Fraction of the screen
ANNOTATION_WIDTH_AUGMENT_FRACTION = 1.4
ANNOTATION_HEIGHT_A... | python | BSD-3-Clause | 0eef6eba80d91d99d99133c319f464d7adf47abe | 2026-01-05T07:13:34.281805Z | false |
Berkeley-NLP/Agent-Eval-Refine | https://github.com/Berkeley-NLP/Agent-Eval-Refine/blob/0eef6eba80d91d99d99133c319f464d7adf47abe/exps/android_exp/models/Auto-UI/action_type.py | exps/android_exp/models/Auto-UI/action_type.py | '''
Adapted from https://github.com/google-research/google-research/tree/master/android_in_the_wild
'''
import enum
class ActionType(enum.IntEnum):
# Placeholders for unused enum values
UNUSED_0 = 0
UNUSED_1 = 1
UNUSED_2 = 2
UNUSED_8 = 8
UNUSED_9 = 9
########### Agent actions ###########
# A type a... | python | BSD-3-Clause | 0eef6eba80d91d99d99133c319f464d7adf47abe | 2026-01-05T07:13:34.281805Z | false |
Berkeley-NLP/Agent-Eval-Refine | https://github.com/Berkeley-NLP/Agent-Eval-Refine/blob/0eef6eba80d91d99d99133c319f464d7adf47abe/exps/android_exp/models/Auto-UI/serve_base.py | exps/android_exp/models/Auto-UI/serve_base.py | import os
import numpy as np
import torch
import os
import re
import json
import argparse
import random
from transformers import AutoTokenizer, DataCollatorForSeq2Seq, Seq2SeqTrainingArguments, Seq2SeqTrainer
from model import T5ForMultimodalGeneration
from infer_utils import ImageFeatureExtractor
from PIL import Image... | python | BSD-3-Clause | 0eef6eba80d91d99d99133c319f464d7adf47abe | 2026-01-05T07:13:34.281805Z | false |
Berkeley-NLP/Agent-Eval-Refine | https://github.com/Berkeley-NLP/Agent-Eval-Refine/blob/0eef6eba80d91d99d99133c319f464d7adf47abe/exps/android_exp/models/Auto-UI/utils_data.py | exps/android_exp/models/Auto-UI/utils_data.py | from torch.utils.data import Dataset
import torch
import pickle
from tqdm import tqdm
import action_matching, action_type
import numpy as np
import numpy as jnp
# import jax.numpy as jnp
import random
import re
img_shape = {
"resnet": (512, 2048),
"clip": (49, 2048),
"detr": (100, 256),
"vit": (577, 768... | python | BSD-3-Clause | 0eef6eba80d91d99d99133c319f464d7adf47abe | 2026-01-05T07:13:34.281805Z | false |
Berkeley-NLP/Agent-Eval-Refine | https://github.com/Berkeley-NLP/Agent-Eval-Refine/blob/0eef6eba80d91d99d99133c319f464d7adf47abe/exps/android_exp/models/Auto-UI/fetch_features.py | exps/android_exp/models/Auto-UI/fetch_features.py | import action_type, action_matching
import tensorflow as tf
import numpy as np
from tqdm import tqdm
import json
import jax.numpy as jnp
import argparse
import pickle
import torch
import tensorflow as tf
from PIL import Image
from transformers import AutoProcessor, Blip2Model
device = "cuda" if torch.cuda.is_available... | python | BSD-3-Clause | 0eef6eba80d91d99d99133c319f464d7adf47abe | 2026-01-05T07:13:34.281805Z | false |
Berkeley-NLP/Agent-Eval-Refine | https://github.com/Berkeley-NLP/Agent-Eval-Refine/blob/0eef6eba80d91d99d99133c319f464d7adf47abe/exps/android_exp/models/Auto-UI/model.py | exps/android_exp/models/Auto-UI/model.py | '''
Adapted from https://github.com/huggingface/transformers
'''
from transformers import T5Config, T5ForConditionalGeneration
from transformers.models.t5.modeling_t5 import T5Stack, __HEAD_MASK_WARNING_MSG
import copy
from transformers.modeling_outputs import BaseModelOutput, Seq2SeqLMOutput
from typing import Option... | python | BSD-3-Clause | 0eef6eba80d91d99d99133c319f464d7adf47abe | 2026-01-05T07:13:34.281805Z | false |
Berkeley-NLP/Agent-Eval-Refine | https://github.com/Berkeley-NLP/Agent-Eval-Refine/blob/0eef6eba80d91d99d99133c319f464d7adf47abe/exps/android_exp/models/Auto-UI/main.py | exps/android_exp/models/Auto-UI/main.py | import os
import numpy as np
import torch
import os
import re
import json
import argparse
import random
from transformers import AutoTokenizer, DataCollatorForSeq2Seq, Seq2SeqTrainingArguments, Seq2SeqTrainer
from model import T5ForMultimodalGeneration
from utils_data import AITWDatasetImg, load_data
from rich.table im... | python | BSD-3-Clause | 0eef6eba80d91d99d99133c319f464d7adf47abe | 2026-01-05T07:13:34.281805Z | false |
Berkeley-NLP/Agent-Eval-Refine | https://github.com/Berkeley-NLP/Agent-Eval-Refine/blob/0eef6eba80d91d99d99133c319f464d7adf47abe/exps/android_exp/models/Auto-UI/serve_large.py | exps/android_exp/models/Auto-UI/serve_large.py | import os
import numpy as np
import torch
import os
import re
import json
import argparse
import random
from transformers import AutoTokenizer, DataCollatorForSeq2Seq, Seq2SeqTrainingArguments, Seq2SeqTrainer
from model import T5ForMultimodalGeneration
from infer_utils import ImageFeatureExtractor
from PIL import Image... | python | BSD-3-Clause | 0eef6eba80d91d99d99133c319f464d7adf47abe | 2026-01-05T07:13:34.281805Z | false |
Berkeley-NLP/Agent-Eval-Refine | https://github.com/Berkeley-NLP/Agent-Eval-Refine/blob/0eef6eba80d91d99d99133c319f464d7adf47abe/exps/android_exp/models/Auto-UI/infer_utils.py | exps/android_exp/models/Auto-UI/infer_utils.py | import torch
from PIL import Image
from transformers import AutoProcessor, Blip2Model, AutoTokenizer
from model import T5ForMultimodalGeneration
class ImageFeatureExtractor:
def __init__(self):
# Set device based on CUDA availability
self.device = "cuda" if torch.cuda.is_available() else "cpu"
... | python | BSD-3-Clause | 0eef6eba80d91d99d99133c319f464d7adf47abe | 2026-01-05T07:13:34.281805Z | false |
Berkeley-NLP/Agent-Eval-Refine | https://github.com/Berkeley-NLP/Agent-Eval-Refine/blob/0eef6eba80d91d99d99133c319f464d7adf47abe/exps/android_exp/models/CogAgent/web_demo_simple.py | exps/android_exp/models/CogAgent/web_demo_simple.py | """
This script is a simple web demo of the CogVLM and CogAgent models, designed for easy and quick demonstrations.
For a more sophisticated user interface, users are encouraged to refer to the 'composite_demo',
which is built with a more aesthetically pleasing Streamlit framework.
Usage:
- Use the interface to upload... | python | BSD-3-Clause | 0eef6eba80d91d99d99133c319f464d7adf47abe | 2026-01-05T07:13:34.281805Z | false |
Berkeley-NLP/Agent-Eval-Refine | https://github.com/Berkeley-NLP/Agent-Eval-Refine/blob/0eef6eba80d91d99d99133c319f464d7adf47abe/exps/ios_exp/collect_trajectories.py | exps/ios_exp/collect_trajectories.py | from gradio_client import Client
import argparse
from env import IOSEnv, ALL_TASKS
from utils import translate_action
from tqdm import tqdm
import json
import random
def main(args):
client = Client(args.gardio_http)
env = IOSEnv(save_path=args.save_path, udid=args.udid, device_path=args.device_path)
epis... | python | BSD-3-Clause | 0eef6eba80d91d99d99133c319f464d7adf47abe | 2026-01-05T07:13:34.281805Z | false |
Berkeley-NLP/Agent-Eval-Refine | https://github.com/Berkeley-NLP/Agent-Eval-Refine/blob/0eef6eba80d91d99d99133c319f464d7adf47abe/exps/ios_exp/utils.py | exps/ios_exp/utils.py | import random
COMMAND_MAP = {
"swipe right": "idb ui swipe --udid {udid} 200 200 300 200 --duration 0.1",
"swipe left": "idb ui swipe --udid {udid} 400 200 300 200 --duration 0.1",
"swipe up": "idb ui swipe --udid {udid} 200 400 200 200 --duration 0.1",
"swipe down": "idb ui swipe --udid {udid} 200 200 ... | python | BSD-3-Clause | 0eef6eba80d91d99d99133c319f464d7adf47abe | 2026-01-05T07:13:34.281805Z | false |
Berkeley-NLP/Agent-Eval-Refine | https://github.com/Berkeley-NLP/Agent-Eval-Refine/blob/0eef6eba80d91d99d99133c319f464d7adf47abe/exps/ios_exp/env.py | exps/ios_exp/env.py | import time
import os
import subprocess
import signal
import cv2
import random
from PIL import Image
import json
with open("train_tasks.json", "r") as fb:
ALL_TASKS = json.load(fb)
TASK_PROMPT = 'What steps do I need to take to "{task}"?(with grounding)'
ALL_TASKS = [TASK_PROMPT.format(task=task) for task in ALL_T... | python | BSD-3-Clause | 0eef6eba80d91d99d99133c319f464d7adf47abe | 2026-01-05T07:13:34.281805Z | false |
Berkeley-NLP/Agent-Eval-Refine | https://github.com/Berkeley-NLP/Agent-Eval-Refine/blob/0eef6eba80d91d99d99133c319f464d7adf47abe/exps/webarena_exp/run.py | exps/webarena_exp/run.py | """Script to run end-to-end evaluation on the benchmark"""
import argparse
import glob
import json
import logging
import os
import random
import subprocess
import tempfile
import time
from pathlib import Path
import openai
from agent import (
Agent,
PromptAgent,
TeacherForcingAgent,
construct_agent,
)... | python | BSD-3-Clause | 0eef6eba80d91d99d99133c319f464d7adf47abe | 2026-01-05T07:13:34.281805Z | false |
Berkeley-NLP/Agent-Eval-Refine | https://github.com/Berkeley-NLP/Agent-Eval-Refine/blob/0eef6eba80d91d99d99133c319f464d7adf47abe/exps/webarena_exp/setup.py | exps/webarena_exp/setup.py | from setuptools import setup
if __name__ == "__main__":
setup()
| python | BSD-3-Clause | 0eef6eba80d91d99d99133c319f464d7adf47abe | 2026-01-05T07:13:34.281805Z | false |
Berkeley-NLP/Agent-Eval-Refine | https://github.com/Berkeley-NLP/Agent-Eval-Refine/blob/0eef6eba80d91d99d99133c319f464d7adf47abe/exps/webarena_exp/minimal_example.py | exps/webarena_exp/minimal_example.py | #!/usr/bin/env python3
# type: ignore
import json
import os
import re
import subprocess
import time
SLEEP = 1.5
# set the URLs of each website, we use the demo sites as an example
os.environ[
"SHOPPING"
] = "http://ec2-3-131-244-37.us-east-2.compute.amazonaws.com:7770"
os.environ[
"SHOPPING_ADMIN"
] = "http:/... | python | BSD-3-Clause | 0eef6eba80d91d99d99133c319f464d7adf47abe | 2026-01-05T07:13:34.281805Z | false |
Berkeley-NLP/Agent-Eval-Refine | https://github.com/Berkeley-NLP/Agent-Eval-Refine/blob/0eef6eba80d91d99d99133c319f464d7adf47abe/exps/webarena_exp/run_reflexion.py | exps/webarena_exp/run_reflexion.py | """Script to run end-to-end evaluation on the benchmark"""
import argparse
import glob
import json
import logging
import os
import copy
import random
import subprocess
import tempfile
import time
from pathlib import Path
import openai
import openai.error
from agent import (
Agent,
PromptAgent,
TeacherForc... | python | BSD-3-Clause | 0eef6eba80d91d99d99133c319f464d7adf47abe | 2026-01-05T07:13:34.281805Z | false |
Berkeley-NLP/Agent-Eval-Refine | https://github.com/Berkeley-NLP/Agent-Eval-Refine/blob/0eef6eba80d91d99d99133c319f464d7adf47abe/exps/webarena_exp/scripts/generate_test_data.py | exps/webarena_exp/scripts/generate_test_data.py | """Replace the website placeholders with website domains from env_config
Generate the test data"""
import json
from browser_env.env_config import *
def main() -> None:
with open("config_files/test.raw.json", "r") as f:
raw = f.read()
raw = raw.replace("__GITLAB__", GITLAB)
raw = raw.replace("__RE... | python | BSD-3-Clause | 0eef6eba80d91d99d99133c319f464d7adf47abe | 2026-01-05T07:13:34.281805Z | false |
Berkeley-NLP/Agent-Eval-Refine | https://github.com/Berkeley-NLP/Agent-Eval-Refine/blob/0eef6eba80d91d99d99133c319f464d7adf47abe/exps/webarena_exp/scripts/check_error_runs.py | exps/webarena_exp/scripts/check_error_runs.py | """Some executions may failed.
This script checks the recordings, print the task ids.
It deletes the recordings if needed."""
import argparse
import glob
import os
import shutil
import sys
def merge_logs(result_folder: str, args: argparse.Namespace) -> str:
if not os.path.exists(f"{result_folder}/log_files.txt"):... | python | BSD-3-Clause | 0eef6eba80d91d99d99133c319f464d7adf47abe | 2026-01-05T07:13:34.281805Z | false |
Berkeley-NLP/Agent-Eval-Refine | https://github.com/Berkeley-NLP/Agent-Eval-Refine/blob/0eef6eba80d91d99d99133c319f464d7adf47abe/exps/webarena_exp/scripts/html2json.py | exps/webarena_exp/scripts/html2json.py | import argparse
import base64
import glob
import json
import os
from collections import defaultdict
from typing import Any
from bs4 import BeautifulSoup
def main(result_folder: str, config_json: str) -> None:
all_data = {}
template_to_id: dict[str, Any] = defaultdict(lambda: len(template_to_id))
with op... | python | BSD-3-Clause | 0eef6eba80d91d99d99133c319f464d7adf47abe | 2026-01-05T07:13:34.281805Z | false |
Berkeley-NLP/Agent-Eval-Refine | https://github.com/Berkeley-NLP/Agent-Eval-Refine/blob/0eef6eba80d91d99d99133c319f464d7adf47abe/exps/webarena_exp/scripts/collect_obs.py | exps/webarena_exp/scripts/collect_obs.py | """Simple script to quickly get the observation of a page"""
import json
import re
import time
from typing import Dict, Optional, Tuple, Type, Union, cast
import pytest
from playwright.sync_api import Page, expect
from browser_env import (
ScriptBrowserEnv,
create_id_based_action,
create_key_press_action... | python | BSD-3-Clause | 0eef6eba80d91d99d99133c319f464d7adf47abe | 2026-01-05T07:13:34.281805Z | false |
Berkeley-NLP/Agent-Eval-Refine | https://github.com/Berkeley-NLP/Agent-Eval-Refine/blob/0eef6eba80d91d99d99133c319f464d7adf47abe/exps/webarena_exp/tests/conftest.py | exps/webarena_exp/tests/conftest.py | from typing import AsyncGenerator, Generator
import pytest
import pytest_asyncio
from browser_env import AsyncScriptBrowserEnv, ScriptBrowserEnv
HEADLESS = True
SLOW_MO = 0
@pytest.fixture(scope="function")
def script_browser_env() -> Generator[ScriptBrowserEnv, None, None]:
"""Create a ScriptBrowserEnv instan... | python | BSD-3-Clause | 0eef6eba80d91d99d99133c319f464d7adf47abe | 2026-01-05T07:13:34.281805Z | false |
Berkeley-NLP/Agent-Eval-Refine | https://github.com/Berkeley-NLP/Agent-Eval-Refine/blob/0eef6eba80d91d99d99133c319f464d7adf47abe/exps/webarena_exp/tests/test_browser_env/test_actions.py | exps/webarena_exp/tests/test_browser_env/test_actions.py | import numpy as np
from browser_env import *
def test_is_equivalent() -> None:
for action_type in ActionTypes.__members__.values():
action_a = create_random_action()
action_b = create_random_action()
if action_a["action_type"] != action_b["action_type"]:
assert not is_equivale... | python | BSD-3-Clause | 0eef6eba80d91d99d99133c319f464d7adf47abe | 2026-01-05T07:13:34.281805Z | false |
Berkeley-NLP/Agent-Eval-Refine | https://github.com/Berkeley-NLP/Agent-Eval-Refine/blob/0eef6eba80d91d99d99133c319f464d7adf47abe/exps/webarena_exp/tests/test_browser_env/test_auth_cookie.py | exps/webarena_exp/tests/test_browser_env/test_auth_cookie.py | import asyncio
import json
from browser_env import *
auth_json = {
"cookies": [
{
"name": "session-username",
"value": "standard_user",
"domain": "www.saucedemo.com",
"path": "/",
"httpOnly": False,
"secure": False,
"sameS... | python | BSD-3-Clause | 0eef6eba80d91d99d99133c319f464d7adf47abe | 2026-01-05T07:13:34.281805Z | false |
Berkeley-NLP/Agent-Eval-Refine | https://github.com/Berkeley-NLP/Agent-Eval-Refine/blob/0eef6eba80d91d99d99133c319f464d7adf47abe/exps/webarena_exp/tests/test_browser_env/test_action_functionalities.py | exps/webarena_exp/tests/test_browser_env/test_action_functionalities.py | import re
from typing import Dict, Optional, Tuple, Type, Union, cast
import pytest
from playwright.sync_api import Page, expect
from browser_env import (
ScriptBrowserEnv,
create_id_based_action,
create_key_press_action,
create_playwright_action,
create_scroll_action,
)
HEADLESS = True
SLOW_MO =... | python | BSD-3-Clause | 0eef6eba80d91d99d99133c319f464d7adf47abe | 2026-01-05T07:13:34.281805Z | false |
Berkeley-NLP/Agent-Eval-Refine | https://github.com/Berkeley-NLP/Agent-Eval-Refine/blob/0eef6eba80d91d99d99133c319f464d7adf47abe/exps/webarena_exp/tests/test_browser_env/test_script_browser_env.py | exps/webarena_exp/tests/test_browser_env/test_script_browser_env.py | import asyncio
import collections
import json
import tempfile
from typing import Callable, Dict, Optional, Tuple, Type, Union, cast
import pytest
from gymnasium.vector import AsyncVectorEnv
from playwright.sync_api import Page
from browser_env import (
Action,
AsyncScriptBrowserEnv,
DetachedPage,
Scri... | python | BSD-3-Clause | 0eef6eba80d91d99d99133c319f464d7adf47abe | 2026-01-05T07:13:34.281805Z | false |
Berkeley-NLP/Agent-Eval-Refine | https://github.com/Berkeley-NLP/Agent-Eval-Refine/blob/0eef6eba80d91d99d99133c319f464d7adf47abe/exps/webarena_exp/tests/test_browser_env/test_playwright_actions.py | exps/webarena_exp/tests/test_browser_env/test_playwright_actions.py | from typing import Dict, Generator, Optional, Tuple, Type, Union, cast
import pytest
from playwright.sync_api import Page
from browser_env import ScriptBrowserEnv, create_playwright_action
HEADLESS = True
SLOW_MO = 0
def test_frame_locator(script_browser_env: ScriptBrowserEnv) -> None:
env = script_browser_env... | python | BSD-3-Clause | 0eef6eba80d91d99d99133c319f464d7adf47abe | 2026-01-05T07:13:34.281805Z | false |
Berkeley-NLP/Agent-Eval-Refine | https://github.com/Berkeley-NLP/Agent-Eval-Refine/blob/0eef6eba80d91d99d99133c319f464d7adf47abe/exps/webarena_exp/tests/test_evaluation_harness/test_evaluators.py | exps/webarena_exp/tests/test_evaluation_harness/test_evaluators.py | import json
import os
import random
from glob import glob
from pathlib import Path
from typing import Any
import pytest
from py import test
from agent import Agent, TeacherForcingAgent
from browser_env import ActionTypes, ScriptBrowserEnv
from browser_env.env_config import *
from evaluation_harness import (
HTMLC... | python | BSD-3-Clause | 0eef6eba80d91d99d99133c319f464d7adf47abe | 2026-01-05T07:13:34.281805Z | false |
Berkeley-NLP/Agent-Eval-Refine | https://github.com/Berkeley-NLP/Agent-Eval-Refine/blob/0eef6eba80d91d99d99133c319f464d7adf47abe/exps/webarena_exp/tests/test_evaluation_harness/test_helper_functions.py | exps/webarena_exp/tests/test_evaluation_harness/test_helper_functions.py | import json
import os
from pathlib import Path
from browser_env import ScriptBrowserEnv
from browser_env.env_config import *
from evaluation_harness.helper_functions import (
gitlab_get_project_memeber_role,
)
HEADLESS = True
config_file_folder = "tests/test_evaluation_harness/configs"
def test_gitlab_get_proje... | python | BSD-3-Clause | 0eef6eba80d91d99d99133c319f464d7adf47abe | 2026-01-05T07:13:34.281805Z | false |
Berkeley-NLP/Agent-Eval-Refine | https://github.com/Berkeley-NLP/Agent-Eval-Refine/blob/0eef6eba80d91d99d99133c319f464d7adf47abe/exps/webarena_exp/evaluation_harness/evaluators.py | exps/webarena_exp/evaluation_harness/evaluators.py | """base class for evaluation"""
# answer string match
import collections
import html
import importlib
import json
import time
import urllib
from pathlib import Path
from typing import Any, Tuple, Union
from beartype import beartype
from nltk.tokenize import word_tokenize # type: ignore
from playwright.sync_api import... | python | BSD-3-Clause | 0eef6eba80d91d99d99133c319f464d7adf47abe | 2026-01-05T07:13:34.281805Z | false |
Berkeley-NLP/Agent-Eval-Refine | https://github.com/Berkeley-NLP/Agent-Eval-Refine/blob/0eef6eba80d91d99d99133c319f464d7adf47abe/exps/webarena_exp/evaluation_harness/__init__.py | exps/webarena_exp/evaluation_harness/__init__.py | from .evaluators import *
from .helper_functions import (
shopping_get_latest_order_url,
shopping_get_sku_latest_review_author,
shopping_get_sku_latest_review_rating,
)
| python | BSD-3-Clause | 0eef6eba80d91d99d99133c319f464d7adf47abe | 2026-01-05T07:13:34.281805Z | false |
Berkeley-NLP/Agent-Eval-Refine | https://github.com/Berkeley-NLP/Agent-Eval-Refine/blob/0eef6eba80d91d99d99133c319f464d7adf47abe/exps/webarena_exp/evaluation_harness/helper_functions.py | exps/webarena_exp/evaluation_harness/helper_functions.py | """Implements helper functions to assist evaluation cases where other evaluators are not suitable."""
import json
from typing import Any
from urllib.parse import urlparse
import requests
from playwright.sync_api import CDPSession, Page
from browser_env.env_config import (
ACCOUNTS,
GITLAB,
MAP,
REDDIT... | python | BSD-3-Clause | 0eef6eba80d91d99d99133c319f464d7adf47abe | 2026-01-05T07:13:34.281805Z | false |
Berkeley-NLP/Agent-Eval-Refine | https://github.com/Berkeley-NLP/Agent-Eval-Refine/blob/0eef6eba80d91d99d99133c319f464d7adf47abe/exps/webarena_exp/browser_env/constants.py | exps/webarena_exp/browser_env/constants.py | from typing import Literal
ROLES = (
"alert",
"alertdialog",
"application",
"article",
"banner",
"blockquote",
"button",
"caption",
"cell",
"checkbox",
"code",
"columnheader",
"combobox",
"complementary",
"contentinfo",
"definition",
"deletion",
"... | python | BSD-3-Clause | 0eef6eba80d91d99d99133c319f464d7adf47abe | 2026-01-05T07:13:34.281805Z | false |
Berkeley-NLP/Agent-Eval-Refine | https://github.com/Berkeley-NLP/Agent-Eval-Refine/blob/0eef6eba80d91d99d99133c319f464d7adf47abe/exps/webarena_exp/browser_env/auto_login.py | exps/webarena_exp/browser_env/auto_login.py | """Script to automatically login each website"""
import argparse
import glob
import os
import time
from concurrent.futures import ThreadPoolExecutor
from itertools import combinations
from pathlib import Path
from playwright.sync_api import sync_playwright
from browser_env.env_config import (
ACCOUNTS,
GITLAB... | python | BSD-3-Clause | 0eef6eba80d91d99d99133c319f464d7adf47abe | 2026-01-05T07:13:34.281805Z | false |
Berkeley-NLP/Agent-Eval-Refine | https://github.com/Berkeley-NLP/Agent-Eval-Refine/blob/0eef6eba80d91d99d99133c319f464d7adf47abe/exps/webarena_exp/browser_env/env_config.py | exps/webarena_exp/browser_env/env_config.py | # websites domain
import os
REDDIT = os.environ.get("REDDIT", "")
SHOPPING = os.environ.get("SHOPPING", "")
SHOPPING_ADMIN = os.environ.get("SHOPPING_ADMIN", "")
GITLAB = os.environ.get("GITLAB", "")
WIKIPEDIA = os.environ.get("WIKIPEDIA", "")
MAP = os.environ.get("MAP", "")
HOMEPAGE = os.environ.get("HOMEPAGE", "")
... | python | BSD-3-Clause | 0eef6eba80d91d99d99133c319f464d7adf47abe | 2026-01-05T07:13:34.281805Z | false |
Berkeley-NLP/Agent-Eval-Refine | https://github.com/Berkeley-NLP/Agent-Eval-Refine/blob/0eef6eba80d91d99d99133c319f464d7adf47abe/exps/webarena_exp/browser_env/processors.py | exps/webarena_exp/browser_env/processors.py | import json
import re
from collections import defaultdict
from typing import Any, TypedDict, Union
import numpy as np
import numpy.typing as npt
from gymnasium import spaces
from playwright.sync_api import CDPSession, Page, ViewportSize
from browser_env.constants import (
ASCII_CHARSET,
FREQ_UNICODE_CHARSET,
... | python | BSD-3-Clause | 0eef6eba80d91d99d99133c319f464d7adf47abe | 2026-01-05T07:13:34.281805Z | false |
Berkeley-NLP/Agent-Eval-Refine | https://github.com/Berkeley-NLP/Agent-Eval-Refine/blob/0eef6eba80d91d99d99133c319f464d7adf47abe/exps/webarena_exp/browser_env/utils.py | exps/webarena_exp/browser_env/utils.py | from dataclasses import dataclass
from io import BytesIO
from typing import Any, Dict, TypedDict, Union
import numpy as np
import numpy.typing as npt
from PIL import Image
@dataclass
class DetachedPage:
url: str
content: str # html
def png_bytes_to_numpy(png: bytes) -> npt.NDArray[np.uint8]:
"""Conver... | python | BSD-3-Clause | 0eef6eba80d91d99d99133c319f464d7adf47abe | 2026-01-05T07:13:34.281805Z | false |
Berkeley-NLP/Agent-Eval-Refine | https://github.com/Berkeley-NLP/Agent-Eval-Refine/blob/0eef6eba80d91d99d99133c319f464d7adf47abe/exps/webarena_exp/browser_env/async_envs.py | exps/webarena_exp/browser_env/async_envs.py | import asyncio
import json
from dataclasses import dataclass
from pathlib import Path
import numpy as np
import numpy.typing as npt
from gymnasium import Env
from gymnasium.spaces import Box, Text
from playwright.async_api import Page, ViewportSize, async_playwright
from .actions import Action, aexecute_action, get_a... | python | BSD-3-Clause | 0eef6eba80d91d99d99133c319f464d7adf47abe | 2026-01-05T07:13:34.281805Z | false |
Berkeley-NLP/Agent-Eval-Refine | https://github.com/Berkeley-NLP/Agent-Eval-Refine/blob/0eef6eba80d91d99d99133c319f464d7adf47abe/exps/webarena_exp/browser_env/__init__.py | exps/webarena_exp/browser_env/__init__.py | import asyncio
from .actions import (
Action,
ActionParsingError,
ActionTypes,
action2create_function,
action2str,
create_check_action,
create_click_action,
create_focus_and_click_action,
create_focus_and_type_action,
create_go_back_action,
create_go_forward_action,
crea... | python | BSD-3-Clause | 0eef6eba80d91d99d99133c319f464d7adf47abe | 2026-01-05T07:13:34.281805Z | false |
Berkeley-NLP/Agent-Eval-Refine | https://github.com/Berkeley-NLP/Agent-Eval-Refine/blob/0eef6eba80d91d99d99133c319f464d7adf47abe/exps/webarena_exp/browser_env/envs.py | exps/webarena_exp/browser_env/envs.py | import json
import re
import time
from collections import defaultdict
from dataclasses import dataclass
from pathlib import Path
from typing import Any, Union
import numpy as np
import numpy.typing as npt
from beartype import beartype
from beartype.door import is_bearable
from gymnasium import Env
from gymnasium.space... | python | BSD-3-Clause | 0eef6eba80d91d99d99133c319f464d7adf47abe | 2026-01-05T07:13:34.281805Z | false |
Berkeley-NLP/Agent-Eval-Refine | https://github.com/Berkeley-NLP/Agent-Eval-Refine/blob/0eef6eba80d91d99d99133c319f464d7adf47abe/exps/webarena_exp/browser_env/actions.py | exps/webarena_exp/browser_env/actions.py | """
Browser Env action space.
Inspited by Farama-Foundation/miniwob-plusplus
"""
import ast
import random
import re
import string
from enum import IntEnum
from itertools import chain
from typing import Any, TypedDict, Union, cast
import numpy as np
import numpy.typing as npt
from beartype import beartype
from gymnasiu... | python | BSD-3-Clause | 0eef6eba80d91d99d99133c319f464d7adf47abe | 2026-01-05T07:13:34.281805Z | true |
Berkeley-NLP/Agent-Eval-Refine | https://github.com/Berkeley-NLP/Agent-Eval-Refine/blob/0eef6eba80d91d99d99133c319f464d7adf47abe/exps/webarena_exp/browser_env/helper_functions.py | exps/webarena_exp/browser_env/helper_functions.py | import base64
import io
import json
import re
from pathlib import Path
from typing import Any, Optional
import numpy as np
from PIL import Image
from agent.prompts import *
from browser_env import (
Action,
ActionTypes,
ObservationMetadata,
StateInfo,
action2str,
)
HTML_TEMPLATE = """
<!DOCTYPE h... | python | BSD-3-Clause | 0eef6eba80d91d99d99133c319f464d7adf47abe | 2026-01-05T07:13:34.281805Z | false |
Berkeley-NLP/Agent-Eval-Refine | https://github.com/Berkeley-NLP/Agent-Eval-Refine/blob/0eef6eba80d91d99d99133c319f464d7adf47abe/exps/webarena_exp/browser_env/trajectory.py | exps/webarena_exp/browser_env/trajectory.py | from typing import Union
from .actions import Action
from .utils import StateInfo
Trajectory = list[Union[StateInfo, Action]]
| python | BSD-3-Clause | 0eef6eba80d91d99d99133c319f464d7adf47abe | 2026-01-05T07:13:34.281805Z | false |
Berkeley-NLP/Agent-Eval-Refine | https://github.com/Berkeley-NLP/Agent-Eval-Refine/blob/0eef6eba80d91d99d99133c319f464d7adf47abe/exps/webarena_exp/llms/utils.py | exps/webarena_exp/llms/utils.py | import argparse
from typing import Any
import time
from llms import (
generate_from_huggingface_completion,
generate_from_openai_chat_completion,
generate_from_openai_completion,
lm_config,
)
APIInput = str | list[Any] | dict[str, Any]
def call_llm(
lm_config: lm_config.LMConfig,
prompt: API... | python | BSD-3-Clause | 0eef6eba80d91d99d99133c319f464d7adf47abe | 2026-01-05T07:13:34.281805Z | false |
Berkeley-NLP/Agent-Eval-Refine | https://github.com/Berkeley-NLP/Agent-Eval-Refine/blob/0eef6eba80d91d99d99133c319f464d7adf47abe/exps/webarena_exp/llms/__init__.py | exps/webarena_exp/llms/__init__.py | """This module is adapt from https://github.com/zeno-ml/zeno-build"""
from .providers.hf_utils import generate_from_huggingface_completion
from .providers.openai_utils import (
generate_from_openai_chat_completion,
generate_from_openai_completion,
)
from .utils import call_llm
__all__ = [
"generate_from_op... | python | BSD-3-Clause | 0eef6eba80d91d99d99133c319f464d7adf47abe | 2026-01-05T07:13:34.281805Z | false |
Berkeley-NLP/Agent-Eval-Refine | https://github.com/Berkeley-NLP/Agent-Eval-Refine/blob/0eef6eba80d91d99d99133c319f464d7adf47abe/exps/webarena_exp/llms/tokenizers.py | exps/webarena_exp/llms/tokenizers.py | from typing import Any
import tiktoken
from transformers import LlamaTokenizer # type: ignore
class Tokenizer(object):
def __init__(self, provider: str, model_name: str) -> None:
if provider == "openai":
self.tokenizer = tiktoken.encoding_for_model(model_name)
elif provider == "huggi... | python | BSD-3-Clause | 0eef6eba80d91d99d99133c319f464d7adf47abe | 2026-01-05T07:13:34.281805Z | false |
Berkeley-NLP/Agent-Eval-Refine | https://github.com/Berkeley-NLP/Agent-Eval-Refine/blob/0eef6eba80d91d99d99133c319f464d7adf47abe/exps/webarena_exp/llms/lm_config.py | exps/webarena_exp/llms/lm_config.py | """Config for language models."""
from __future__ import annotations
import argparse
import dataclasses
from dataclasses import dataclass
from typing import Any
@dataclass(frozen=True)
class LMConfig:
"""A config for a language model.
Attributes:
provider: The name of the API provider.
mode... | python | BSD-3-Clause | 0eef6eba80d91d99d99133c319f464d7adf47abe | 2026-01-05T07:13:34.281805Z | false |
Berkeley-NLP/Agent-Eval-Refine | https://github.com/Berkeley-NLP/Agent-Eval-Refine/blob/0eef6eba80d91d99d99133c319f464d7adf47abe/exps/webarena_exp/llms/providers/hf_utils.py | exps/webarena_exp/llms/providers/hf_utils.py | from text_generation import Client # type: ignore
def generate_from_huggingface_completion(
prompt: str,
model_endpoint: str,
temperature: float,
top_p: float,
max_new_tokens: int,
stop_sequences: list[str] | None = None,
) -> str:
client = Client(model_endpoint, timeout=60)
generatio... | python | BSD-3-Clause | 0eef6eba80d91d99d99133c319f464d7adf47abe | 2026-01-05T07:13:34.281805Z | false |
Berkeley-NLP/Agent-Eval-Refine | https://github.com/Berkeley-NLP/Agent-Eval-Refine/blob/0eef6eba80d91d99d99133c319f464d7adf47abe/exps/webarena_exp/llms/providers/openai_utils.py | exps/webarena_exp/llms/providers/openai_utils.py | """Tools to generate from OpenAI prompts.
Adopted from https://github.com/zeno-ml/zeno-build/"""
import asyncio
import logging
import os
import random
import time
from typing import Any
import aiolimiter
import openai
import openai.error
from tqdm.asyncio import tqdm_asyncio
def retry_with_exponential_backoff( # t... | python | BSD-3-Clause | 0eef6eba80d91d99d99133c319f464d7adf47abe | 2026-01-05T07:13:34.281805Z | false |
Berkeley-NLP/Agent-Eval-Refine | https://github.com/Berkeley-NLP/Agent-Eval-Refine/blob/0eef6eba80d91d99d99133c319f464d7adf47abe/exps/webarena_exp/environment_docker/webarena-homepage/app.py | exps/webarena_exp/environment_docker/webarena-homepage/app.py | from flask import Flask, render_template
app = Flask(__name__)
@app.route("/")
def index() -> str:
return render_template("index.html")
@app.route("/scratchpad.html")
def scratchpad() -> str:
return render_template("scratchpad.html")
@app.route("/calculator.html")
def calculator() -> str:
return rend... | python | BSD-3-Clause | 0eef6eba80d91d99d99133c319f464d7adf47abe | 2026-01-05T07:13:34.281805Z | false |
Berkeley-NLP/Agent-Eval-Refine | https://github.com/Berkeley-NLP/Agent-Eval-Refine/blob/0eef6eba80d91d99d99133c319f464d7adf47abe/exps/webarena_exp/agent/evaluator.py | exps/webarena_exp/agent/evaluator.py | import os
from typing import Any
from gradio_client import Client
from browser_env import Trajectory
import numpy as np
import tempfile
from PIL import Image
from typing import Union, Literal
import time
from agent_eval.clients import LM_Client, GPT4V_Client
from agent_eval.eval.evaluator import Evaluator
import multip... | python | BSD-3-Clause | 0eef6eba80d91d99d99133c319f464d7adf47abe | 2026-01-05T07:13:34.281805Z | false |
Berkeley-NLP/Agent-Eval-Refine | https://github.com/Berkeley-NLP/Agent-Eval-Refine/blob/0eef6eba80d91d99d99133c319f464d7adf47abe/exps/webarena_exp/agent/__init__.py | exps/webarena_exp/agent/__init__.py | from .agent import (
Agent,
PromptAgent,
TeacherForcingAgent,
construct_agent,
)
__all__ = ["Agent", "TeacherForcingAgent", "PromptAgent", "construct_agent"]
| python | BSD-3-Clause | 0eef6eba80d91d99d99133c319f464d7adf47abe | 2026-01-05T07:13:34.281805Z | false |
Berkeley-NLP/Agent-Eval-Refine | https://github.com/Berkeley-NLP/Agent-Eval-Refine/blob/0eef6eba80d91d99d99133c319f464d7adf47abe/exps/webarena_exp/agent/agent.py | exps/webarena_exp/agent/agent.py | import argparse
import json
from typing import Any
import tiktoken
from beartype import beartype
from agent.prompts import *
from browser_env import Trajectory
from browser_env.actions import (
Action,
ActionParsingError,
create_id_based_action,
create_none_action,
create_playwright_action,
)
from... | python | BSD-3-Clause | 0eef6eba80d91d99d99133c319f464d7adf47abe | 2026-01-05T07:13:34.281805Z | false |
Berkeley-NLP/Agent-Eval-Refine | https://github.com/Berkeley-NLP/Agent-Eval-Refine/blob/0eef6eba80d91d99d99133c319f464d7adf47abe/exps/webarena_exp/agent/prompts/prompt_constructor.py | exps/webarena_exp/agent/prompts/prompt_constructor.py | import json
import re
from pathlib import Path
from typing import Any, TypedDict
from browser_env import Action, ActionParsingError, Trajectory
from browser_env.env_config import URL_MAPPINGS
from browser_env.utils import StateInfo
from llms import lm_config
from llms.tokenizers import Tokenizer
from llms.utils import... | python | BSD-3-Clause | 0eef6eba80d91d99d99133c319f464d7adf47abe | 2026-01-05T07:13:34.281805Z | false |
Berkeley-NLP/Agent-Eval-Refine | https://github.com/Berkeley-NLP/Agent-Eval-Refine/blob/0eef6eba80d91d99d99133c319f464d7adf47abe/exps/webarena_exp/agent/prompts/to_json.py | exps/webarena_exp/agent/prompts/to_json.py | import glob
import importlib
import json
import os
# use the current directory as the root
def run() -> None:
"""Convert all python files in agent/prompts to json files in agent/prompts/jsons
Python files are easiser to edit
"""
for p_file in glob.glob(f"agent/prompts/raw/*.py"):
# import the... | python | BSD-3-Clause | 0eef6eba80d91d99d99133c319f464d7adf47abe | 2026-01-05T07:13:34.281805Z | false |
Berkeley-NLP/Agent-Eval-Refine | https://github.com/Berkeley-NLP/Agent-Eval-Refine/blob/0eef6eba80d91d99d99133c319f464d7adf47abe/exps/webarena_exp/agent/prompts/__init__.py | exps/webarena_exp/agent/prompts/__init__.py | from .prompt_constructor import *
| python | BSD-3-Clause | 0eef6eba80d91d99d99133c319f464d7adf47abe | 2026-01-05T07:13:34.281805Z | false |
Berkeley-NLP/Agent-Eval-Refine | https://github.com/Berkeley-NLP/Agent-Eval-Refine/blob/0eef6eba80d91d99d99133c319f464d7adf47abe/exps/webarena_exp/agent/prompts/raw/p_cot_id_actree_2s_no_na.py | exps/webarena_exp/agent/prompts/raw/p_cot_id_actree_2s_no_na.py | prompt = {
"intro": """You are an autonomous intelligent agent tasked with navigating a web browser. You will be given web-based tasks. These tasks will be accomplished through the use of specific actions you can issue.
Here's the information you'll have:
The user's objective: This is the task you're trying to comple... | python | BSD-3-Clause | 0eef6eba80d91d99d99133c319f464d7adf47abe | 2026-01-05T07:13:34.281805Z | false |
Berkeley-NLP/Agent-Eval-Refine | https://github.com/Berkeley-NLP/Agent-Eval-Refine/blob/0eef6eba80d91d99d99133c319f464d7adf47abe/exps/webarena_exp/agent/prompts/raw/reflexion_generation.py | exps/webarena_exp/agent/prompts/raw/reflexion_generation.py | prompt = {
"intro": """You are an autonomous intelligent agent tasked with navigating a web browser. You will be given web-based tasks. These tasks will be accomplished through the use of specific actions you can issue.
Here's the information you'll have:
The user's objective: This is the task you're trying to comple... | python | BSD-3-Clause | 0eef6eba80d91d99d99133c319f464d7adf47abe | 2026-01-05T07:13:34.281805Z | false |
Berkeley-NLP/Agent-Eval-Refine | https://github.com/Berkeley-NLP/Agent-Eval-Refine/blob/0eef6eba80d91d99d99133c319f464d7adf47abe/exps/webarena_exp/agent/prompts/raw/p_direct_id_actree_3s_llama.py | exps/webarena_exp/agent/prompts/raw/p_direct_id_actree_3s_llama.py | prompt = {
"intro": """You are an autonomous intelligent agent tasked with navigating a web browser. The actions you can perform fall into several categories:
Page Operation Actions:
`click [id]`: This action clicks on an element with a specific id on the webpage.
`type [id] [content] [press_enter_after=0|1]`: Use th... | python | BSD-3-Clause | 0eef6eba80d91d99d99133c319f464d7adf47abe | 2026-01-05T07:13:34.281805Z | false |
Berkeley-NLP/Agent-Eval-Refine | https://github.com/Berkeley-NLP/Agent-Eval-Refine/blob/0eef6eba80d91d99d99133c319f464d7adf47abe/exps/webarena_exp/agent/prompts/raw/p_cot_id_actree_2s.py | exps/webarena_exp/agent/prompts/raw/p_cot_id_actree_2s.py | prompt = {
"intro": """You are an autonomous intelligent agent tasked with navigating a web browser. You will be given web-based tasks. These tasks will be accomplished through the use of specific actions you can issue.
Here's the information you'll have:
The user's objective: This is the task you're trying to comple... | python | BSD-3-Clause | 0eef6eba80d91d99d99133c319f464d7adf47abe | 2026-01-05T07:13:34.281805Z | false |
Berkeley-NLP/Agent-Eval-Refine | https://github.com/Berkeley-NLP/Agent-Eval-Refine/blob/0eef6eba80d91d99d99133c319f464d7adf47abe/exps/webarena_exp/agent/prompts/raw/p_direct_id_actree_2s_no_na.py | exps/webarena_exp/agent/prompts/raw/p_direct_id_actree_2s_no_na.py | prompt = {
"intro": """You are an autonomous intelligent agent tasked with navigating a web browser. You will be given web-based tasks. These tasks will be accomplished through the use of specific actions you can issue.
Here's the information you'll have:
The user's objective: This is the task you're trying to comple... | python | BSD-3-Clause | 0eef6eba80d91d99d99133c319f464d7adf47abe | 2026-01-05T07:13:34.281805Z | false |
Berkeley-NLP/Agent-Eval-Refine | https://github.com/Berkeley-NLP/Agent-Eval-Refine/blob/0eef6eba80d91d99d99133c319f464d7adf47abe/exps/webarena_exp/agent/prompts/raw/p_cot_id_actree_2s_reflexion.py | exps/webarena_exp/agent/prompts/raw/p_cot_id_actree_2s_reflexion.py | prompt = {
"intro": """You are an autonomous intelligent agent tasked with navigating a web browser. You will be given web-based tasks. These tasks will be accomplished through the use of specific actions you can issue.
Here's the information you'll have:
The user's objective: This is the task you're trying to comple... | python | BSD-3-Clause | 0eef6eba80d91d99d99133c319f464d7adf47abe | 2026-01-05T07:13:34.281805Z | false |
Berkeley-NLP/Agent-Eval-Refine | https://github.com/Berkeley-NLP/Agent-Eval-Refine/blob/0eef6eba80d91d99d99133c319f464d7adf47abe/exps/webarena_exp/agent/prompts/raw/p_direct_id_actree_2s.py | exps/webarena_exp/agent/prompts/raw/p_direct_id_actree_2s.py | prompt = {
"intro": """You are an autonomous intelligent agent tasked with navigating a web browser. You will be given web-based tasks. These tasks will be accomplished through the use of specific actions you can issue.
Here's the information you'll have:
The user's objective: This is the task you're trying to comple... | python | BSD-3-Clause | 0eef6eba80d91d99d99133c319f464d7adf47abe | 2026-01-05T07:13:34.281805Z | false |
Berkeley-NLP/Agent-Eval-Refine | https://github.com/Berkeley-NLP/Agent-Eval-Refine/blob/0eef6eba80d91d99d99133c319f464d7adf47abe/agent_eval/setup.py | agent_eval/setup.py | from setuptools import setup
setup(
name="agent_eval",
version="0.0.1",
packages=["agent_eval"],
install_requires=[
"openai",
"requests",
"pillow",
"bs4",
"matplotlib",
"termcolor",
"human_id",
"pandas",
"easy_ocr",
"einops... | python | BSD-3-Clause | 0eef6eba80d91d99d99133c319f464d7adf47abe | 2026-01-05T07:13:34.281805Z | false |
Berkeley-NLP/Agent-Eval-Refine | https://github.com/Berkeley-NLP/Agent-Eval-Refine/blob/0eef6eba80d91d99d99133c319f464d7adf47abe/agent_eval/scripts/run_eval_android.py | agent_eval/scripts/run_eval_android.py | from tqdm import tqdm
import json
from human_id import generate_id
import os
import argparse
import multiprocessing as mp
from agent_eval.clients import LM_Client, GPT4V_Client
from agent_eval.domains.unified import UniTrajectoryDataset
from agent_eval.eval.evaluator import Evaluator
from agent_eval.eval.metrics impor... | python | BSD-3-Clause | 0eef6eba80d91d99d99133c319f464d7adf47abe | 2026-01-05T07:13:34.281805Z | false |
Berkeley-NLP/Agent-Eval-Refine | https://github.com/Berkeley-NLP/Agent-Eval-Refine/blob/0eef6eba80d91d99d99133c319f464d7adf47abe/agent_eval/scripts/run_eval_web.py | agent_eval/scripts/run_eval_web.py | from tqdm import tqdm
import json
from human_id import generate_id
import os
import argparse
import multiprocessing as mp
import traceback
from agent_eval.clients import LM_Client, GPT4V_Client
from agent_eval.domains.unified import UniTrajectoryDataset
from agent_eval.eval.evaluator import Evaluator
from agent_eval.e... | python | BSD-3-Clause | 0eef6eba80d91d99d99133c319f464d7adf47abe | 2026-01-05T07:13:34.281805Z | false |
Berkeley-NLP/Agent-Eval-Refine | https://github.com/Berkeley-NLP/Agent-Eval-Refine/blob/0eef6eba80d91d99d99133c319f464d7adf47abe/agent_eval/scripts/annotate_ios_dense.py | agent_eval/scripts/annotate_ios_dense.py | from agent_eval.eval.annotator import Annotator
from agent_eval.domains.unified import UniTrajectoryDataset
from agent_eval.clients import LM_Client, GPT4V_Client
import multiprocessing as mp
from tqdm import tqdm
import json
def process_sample(
traj_info: dict,
model: str,
):
try:
print("processi... | python | BSD-3-Clause | 0eef6eba80d91d99d99133c319f464d7adf47abe | 2026-01-05T07:13:34.281805Z | false |
Berkeley-NLP/Agent-Eval-Refine | https://github.com/Berkeley-NLP/Agent-Eval-Refine/blob/0eef6eba80d91d99d99133c319f464d7adf47abe/agent_eval/agent_eval/utils.py | agent_eval/agent_eval/utils.py | from PIL import Image
import matplotlib.pyplot as plt
import numpy as np
def display_images(images):
"""Display list of PIL images in a 2xN grid."""
n = len(images)
# Calculate grid shape
cols = int(np.ceil(n / 2.0))
rows = 2 if n > 1 else 1
cols, rows = rows, cols # Swap
# Create a ... | python | BSD-3-Clause | 0eef6eba80d91d99d99133c319f464d7adf47abe | 2026-01-05T07:13:34.281805Z | false |
Berkeley-NLP/Agent-Eval-Refine | https://github.com/Berkeley-NLP/Agent-Eval-Refine/blob/0eef6eba80d91d99d99133c319f464d7adf47abe/agent_eval/agent_eval/__init__.py | agent_eval/agent_eval/__init__.py | python | BSD-3-Clause | 0eef6eba80d91d99d99133c319f464d7adf47abe | 2026-01-05T07:13:34.281805Z | false | |
Berkeley-NLP/Agent-Eval-Refine | https://github.com/Berkeley-NLP/Agent-Eval-Refine/blob/0eef6eba80d91d99d99133c319f464d7adf47abe/agent_eval/agent_eval/clients.py | agent_eval/agent_eval/clients.py | import openai
from openai.api_resources import ChatCompletion
# from openai import OpenAI, AsyncOpenAI
import requests
from typing import List, Union, Dict, Optional, Tuple
from PIL import Image
from io import BytesIO
import base64
# from openai.types.chat.chat_completion import ChatCompletion
import os
import reques... | python | BSD-3-Clause | 0eef6eba80d91d99d99133c319f464d7adf47abe | 2026-01-05T07:13:34.281805Z | false |
Berkeley-NLP/Agent-Eval-Refine | https://github.com/Berkeley-NLP/Agent-Eval-Refine/blob/0eef6eba80d91d99d99133c319f464d7adf47abe/agent_eval/agent_eval/domains/unified.py | agent_eval/agent_eval/domains/unified.py | from PIL import Image
import os
import json
from typing import List, Dict, Any, Tuple
from collections import defaultdict
from termcolor import cprint
import re
import numpy as np
class UniTrajectoryDataset:
def __init__(
self,
dataset_path: str,
eval_log_names: List[str],
captioner... | python | BSD-3-Clause | 0eef6eba80d91d99d99133c319f464d7adf47abe | 2026-01-05T07:13:34.281805Z | false |
Berkeley-NLP/Agent-Eval-Refine | https://github.com/Berkeley-NLP/Agent-Eval-Refine/blob/0eef6eba80d91d99d99133c319f464d7adf47abe/agent_eval/agent_eval/domains/unify_webarena.py | agent_eval/agent_eval/domains/unify_webarena.py | # %%
import agent_eval
from agent_eval.domains.webarena import extract_trajectory_info, extract_eval_results
import json
import os
# %%
# raw_dataset_path = "/home/<user>/code/WebArena/webarena_traj/102023_release_v2/919_gpt4_8k_cot"
# output_dataset_path = "/home/<user>/data/GUI_Proj/unified_datasets/webarena-gpt4cot... | python | BSD-3-Clause | 0eef6eba80d91d99d99133c319f464d7adf47abe | 2026-01-05T07:13:34.281805Z | false |
Berkeley-NLP/Agent-Eval-Refine | https://github.com/Berkeley-NLP/Agent-Eval-Refine/blob/0eef6eba80d91d99d99133c319f464d7adf47abe/agent_eval/agent_eval/domains/__init__.py | agent_eval/agent_eval/domains/__init__.py | python | BSD-3-Clause | 0eef6eba80d91d99d99133c319f464d7adf47abe | 2026-01-05T07:13:34.281805Z | false | |
Berkeley-NLP/Agent-Eval-Refine | https://github.com/Berkeley-NLP/Agent-Eval-Refine/blob/0eef6eba80d91d99d99133c319f464d7adf47abe/agent_eval/agent_eval/domains/webarena.py | agent_eval/agent_eval/domains/webarena.py | import base64
from bs4 import BeautifulSoup
from io import BytesIO
from PIL import Image
import os
import json
import re
import random
def extract_eval_results(merged_log: str):
"""Extract the evaluation results from the merged log file."""
results = {}
for line in merged_log.splitlines():
if '[Res... | python | BSD-3-Clause | 0eef6eba80d91d99d99133c319f464d7adf47abe | 2026-01-05T07:13:34.281805Z | false |
Berkeley-NLP/Agent-Eval-Refine | https://github.com/Berkeley-NLP/Agent-Eval-Refine/blob/0eef6eba80d91d99d99133c319f464d7adf47abe/agent_eval/agent_eval/captioner/annotate_screenshots.py | agent_eval/agent_eval/captioner/annotate_screenshots.py | # %%
from agent_eval.clients import GPT4V_Client
from PIL import Image
import os, time
import random
from tqdm import tqdm
import json
from langdetect import detect as lang_detect
import pytesseract
random.seed(42)
# %%
def get_cap(img):
# if random.random() < 0.5:
# print("=")
# else:
# prin... | python | BSD-3-Clause | 0eef6eba80d91d99d99133c319f464d7adf47abe | 2026-01-05T07:13:34.281805Z | false |
Berkeley-NLP/Agent-Eval-Refine | https://github.com/Berkeley-NLP/Agent-Eval-Refine/blob/0eef6eba80d91d99d99133c319f464d7adf47abe/agent_eval/agent_eval/captioner/prepare_caps_sub.py | agent_eval/agent_eval/captioner/prepare_caps_sub.py | import os
import json
from tqdm import tqdm
from gradio_client import Client
from collections import defaultdict
def save(this_obj, file_path):
with open(file_path, 'w') as f:
json.dump(this_obj, f)
def predict(img_path, client):
result = client.predict(
img_path, # str in 'text' Textbox ... | python | BSD-3-Clause | 0eef6eba80d91d99d99133c319f464d7adf47abe | 2026-01-05T07:13:34.281805Z | false |
Berkeley-NLP/Agent-Eval-Refine | https://github.com/Berkeley-NLP/Agent-Eval-Refine/blob/0eef6eba80d91d99d99133c319f464d7adf47abe/agent_eval/agent_eval/captioner/utils.py | agent_eval/agent_eval/captioner/utils.py | def detect_repetition() | python | BSD-3-Clause | 0eef6eba80d91d99d99133c319f464d7adf47abe | 2026-01-05T07:13:34.281805Z | false |
Berkeley-NLP/Agent-Eval-Refine | https://github.com/Berkeley-NLP/Agent-Eval-Refine/blob/0eef6eba80d91d99d99133c319f464d7adf47abe/agent_eval/agent_eval/captioner/__init__.py | agent_eval/agent_eval/captioner/__init__.py | python | BSD-3-Clause | 0eef6eba80d91d99d99133c319f464d7adf47abe | 2026-01-05T07:13:34.281805Z | false | |
Berkeley-NLP/Agent-Eval-Refine | https://github.com/Berkeley-NLP/Agent-Eval-Refine/blob/0eef6eba80d91d99d99133c319f464d7adf47abe/agent_eval/agent_eval/captioner/captioner_server.py | agent_eval/agent_eval/captioner/captioner_server.py | from transformers import (
AutoModelForCausalLM,
AutoTokenizer,
__version__,
GenerationConfig,
)
from PIL import Image
import gradio as gr
import argparse
import tempfile
from PIL import Image
import easyocr
import torch
assert (
__version__ == "4.32.0"
), "Please use transformers version 4.32.0, ... | python | BSD-3-Clause | 0eef6eba80d91d99d99133c319f464d7adf47abe | 2026-01-05T07:13:34.281805Z | false |
Berkeley-NLP/Agent-Eval-Refine | https://github.com/Berkeley-NLP/Agent-Eval-Refine/blob/0eef6eba80d91d99d99133c319f464d7adf47abe/agent_eval/agent_eval/eval/prompts.py | agent_eval/agent_eval/eval/prompts.py | def build_obs_simplifier_prompt(cap, intent, response) -> str:
prompt = f"""Given the following user question and context, extract part of the context that is unbiased, so that using that text alone would be good context for providing an unbiased answer to the user query.
**User Query**: The bot responded with "{r... | python | BSD-3-Clause | 0eef6eba80d91d99d99133c319f464d7adf47abe | 2026-01-05T07:13:34.281805Z | false |
Berkeley-NLP/Agent-Eval-Refine | https://github.com/Berkeley-NLP/Agent-Eval-Refine/blob/0eef6eba80d91d99d99133c319f464d7adf47abe/agent_eval/agent_eval/eval/metrics.py | agent_eval/agent_eval/eval/metrics.py | import os
import json
import pandas as pd
LABEL_CORRECTION = {
"24": False,
"201": False,
"225": False,
"247": False,
"390": False,
"435": False,
"466": False,
"677": False,
"678": False,
"679": False,
"680": False,
"752": False,
"792": False,
"793": False,
}
d... | python | BSD-3-Clause | 0eef6eba80d91d99d99133c319f464d7adf47abe | 2026-01-05T07:13:34.281805Z | false |
Berkeley-NLP/Agent-Eval-Refine | https://github.com/Berkeley-NLP/Agent-Eval-Refine/blob/0eef6eba80d91d99d99133c319f464d7adf47abe/agent_eval/agent_eval/eval/annotate_app.py | agent_eval/agent_eval/eval/annotate_app.py | import gradio as gr
from matplotlib import pyplot as plt
import math
import io
from PIL import Image
from numpy import asarray
from agent_eval.domains.unified import UniTrajectoryDataset
import time
import json
from collections import defaultdict
import os
def main(dataset_abs_path, log_name):
annotation_log_path... | python | BSD-3-Clause | 0eef6eba80d91d99d99133c319f464d7adf47abe | 2026-01-05T07:13:34.281805Z | false |
Berkeley-NLP/Agent-Eval-Refine | https://github.com/Berkeley-NLP/Agent-Eval-Refine/blob/0eef6eba80d91d99d99133c319f464d7adf47abe/agent_eval/agent_eval/eval/annotator.py | agent_eval/agent_eval/eval/annotator.py | import json
import os
from typing import Any, List, Tuple
from termcolor import cprint
sys_prompt_v1_icl = """You are a GUI Trajectory Evaluator. Your task is to observe a bot's action within a graphical user interface (GUI) and classify its behavior into one of four categories based on its progress towards a specifi... | python | BSD-3-Clause | 0eef6eba80d91d99d99133c319f464d7adf47abe | 2026-01-05T07:13:34.281805Z | false |
Berkeley-NLP/Agent-Eval-Refine | https://github.com/Berkeley-NLP/Agent-Eval-Refine/blob/0eef6eba80d91d99d99133c319f464d7adf47abe/agent_eval/agent_eval/eval/evaluator.py | agent_eval/agent_eval/eval/evaluator.py | import json
import os
from typing import Any, List, Tuple
from termcolor import cprint
from agent_eval.eval.prompts import *
class Evaluator:
def __init__(self, lm_clients, log_save_path=None):
self.lm_clients = lm_clients
self.log_save_path = log_save_path
def __call__(self, info, client="... | python | BSD-3-Clause | 0eef6eba80d91d99d99133c319f464d7adf47abe | 2026-01-05T07:13:34.281805Z | false |
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