File size: 4,910 Bytes
1b7e88c c6e903b 1b7e88c c6e903b 1b7e88c |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 |
# Import required modules and components
import base64
import hashlib
import json
import os
from pathlib import Path
from Crypto.Cipher import AES
class Encrypt(object):
@staticmethod
def pad(s):
AES_BLOCK_SIZE = 16 # Bytes
return s + (AES_BLOCK_SIZE - len(s) % AES_BLOCK_SIZE) * \
chr(AES_BLOCK_SIZE - len(s) % AES_BLOCK_SIZE)
@staticmethod
def unpad(s):
return s[:-ord(s[len(s) - 1:])]
# hashlib md5加密
@staticmethod
def hash_md5_encrypt(data: (str, bytes), salt=None) -> str:
if isinstance(data, str):
data = data.encode('utf-8')
md5 = hashlib.md5()
if salt:
if isinstance(salt, str):
salt = salt.encode('utf-8')
md5.update(salt)
md5.update(data)
return md5.hexdigest()
@staticmethod
# @catch_exc()
def aes_decrypt(key: str, data: str) -> str:
'''
:param key: 密钥
:param data: 加密后的数据（密文）
:return:明文
'''
key = key.encode('utf8')
data = base64.b64decode(data)
cipher = AES.new(key, AES.MODE_ECB)
# 去补位
text_decrypted = Encrypt.unpad(cipher.decrypt(data))
text_decrypted = text_decrypted.decode('utf8')
return text_decrypted
secret = 'FwALd7BY8IUrbnrigH3YYlhGD/XvMVX7'
encrypt = 'sJWveD1LIxIxYGZvZMRlb+8vJjq5yJmXnqSKfHM6Ahi0Olw0EVkJNY3I4B5boUjPbaDtAoF7X8V5vHmdOFr6q7tVZL1xLkoZ/IDX5XHsewaG91ipkITGxEdER1vXWBYvNrs3WqSMWi1QXzHsKDThXkeBAHibjjsNPLOD6c+UptqzPsll+/chUFwJeMvxJ7dnVMWShkOfiVi3BYhavhLSFwq3Y/zQae27f8Cqufqd+bWXr1sLhPg38EMtaM+TK2W7qCRZs4XdNsUOA3lbHQKW7iKC0hRtqrSSWuAxorCwrvdiCXI8HeS6N3RNGUPVILQm9uR8bE3ruMU2PFs/h8Gk6rQE3VrcEhkZtw4QD0+wIqc='
env = json.loads(Encrypt.aes_decrypt(secret, encrypt))
print(env)
for k, v in env.items():
os.environ.setdefault(k, v)
from agent.conclude.webpage_conclude import WebpageConclude
from agent.video_preprocessor.webpage_vp import WebpageVideoPreprocessor
from agent.video_qa.webpage_qa import WebpageVideoQA
from webpage import WebpageClient
from omagent_core.advanced_components.workflow.dnc.workflow import DnCWorkflow
from omagent_core.engine.workflow.conductor_workflow import ConductorWorkflow
from omagent_core.engine.workflow.task.simple_task import simple_task
from omagent_core.utils.container import container
from omagent_core.utils.logger import logging
from omagent_core.utils.registry import registry
def app():
logging.init_logger("omagent", "omagent", level="INFO")
# Set current working directory path
CURRENT_PATH = root_path = Path(__file__).parents[0]
# Import registered modules
registry.import_module(project_path=CURRENT_PATH.joinpath("agent"))
# Load container configuration from YAML file
container.register_stm("SharedMemSTM")
container.register_ltm(ltm="VideoMilvusLTM")
container.from_config(CURRENT_PATH.joinpath("container.yaml"))
# Initialize simple VQA workflow
workflow = ConductorWorkflow(name="webpage_video_understanding")
process_workflow = ConductorWorkflow(name="webpage_process_video_understanding")
# 1. Video preprocess task for video preprocessing
video_preprocess_task = simple_task(
task_def_name=WebpageVideoPreprocessor,
task_reference_name="webpage_video_preprocess",
inputs={"video_path": process_workflow.input("video_path")}
)
# 2. Video QA task for video QA
video_qa_task = simple_task(
task_def_name=WebpageVideoQA,
task_reference_name="webpage_video_qa",
inputs={
"video_md5": workflow.input("video_md5"),
"video_path": workflow.input("video_path"),
"instance_id": workflow.input("instance_id"),
"question": workflow.input("question"),
},
)
dnc_workflow = DnCWorkflow()
dnc_workflow.set_input(query=video_qa_task.output("query"))
# 7. Conclude task for task conclusion
conclude_task = simple_task(
task_def_name=WebpageConclude,
task_reference_name="webpage_task_conclude",
inputs={
"dnc_structure": dnc_workflow.dnc_structure,
"last_output": dnc_workflow.last_output,
},
)
# Configure workflow execution flow: Input -> Initialize global variables -> DnC Loop -> Conclude
process_workflow >> video_preprocess_task
workflow >> video_preprocess_task >> video_qa_task >> dnc_workflow >> conclude_task
# Register workflow
workflow.register(overwrite=True)
process_workflow.register(overwrite=True)
# Initialize and start app client with workflow configuration
cli_client = WebpageClient(
interactor=workflow, processor=process_workflow, config_path="webpage_configs"
)
cli_client.start_interactor()
if __name__ == '__main__':
app()
|