File size: 2,251 Bytes
3818a51
 
 
 
 
 
ea9eade
af4e958
3818a51
 
ea9eade
3818a51
ea9eade
3818a51
af4e958
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
3818a51
ea9eade
 
 
3818a51
 
ea9eade
3818a51
ea9eade
3818a51
 
 
ea9eade
 
 
3818a51
ea9eade
3818a51
ea9eade
 
3818a51
 
 
ea9eade
 
af4e958
 
3818a51
c2dd900
 
 
3818a51
ea9eade
 
 
 
 
 
 
 
 
 
 
 
 
3818a51
 
 
ea9eade
3818a51
 
 
ea9eade
 
3818a51
 
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
[build-system]
requires = ["setuptools>=65.0", "wheel"]
build-backend = "setuptools.build_meta"

[project]
name = "fraudshield"
version = "0.2.0"
description = "Production-grade OpenEnv environment for e-commerce fraud detection. Simulates marketplace fraud review with deterministic graders, dense rewards, and reproducible baselines."
readme = "README.md"
requires-python = ">=3.10"
license = { text = "MIT" }
authors = [
    { name = "Devika J", email = "devikaj2005@gmail.com" },
]
keywords = [
    "openenv",
    "reinforcement-learning",
    "fraud-detection",
    "agent-evaluation",
    "e-commerce",
    "environment",
]
classifiers = [
    "Development Status :: 5 - Production/Stable",
    "Environment :: Web Environment",
    "Intended Audience :: Developers",
    "Intended Audience :: Science/Research",
    "License :: OSI Approved :: MIT License",
    "Operating System :: OS Independent",
    "Programming Language :: Python :: 3",
    "Programming Language :: Python :: 3.10",
    "Programming Language :: Python :: 3.11",
    "Programming Language :: Python :: 3.12",
    "Topic :: Scientific/Engineering :: Artificial Intelligence",
]
dependencies = [
    "fastapi>=0.115.0",
    "numpy>=1.24.0",
    "openai>=1.40.0",
    "openenv-core>=0.2.0",
    "pandas>=2.0.0",
    "pydantic>=2.0.0",
    "scikit-learn>=1.3.0",
    "uvicorn>=0.30.0",
]

[project.optional-dependencies]
data = [
    "kaggle>=1.6.0",
]
dev = [
    "black>=24.0.0",
    "ipython>=8.0.0",
    "pytest>=7.4.0",
    "ruff>=0.4.0",
]

[project.urls]
Homepage = "https://github.com/DevikaJ2005/fraudshield"
Repository = "https://github.com/DevikaJ2005/fraudshield.git"
Documentation = "https://github.com/DevikaJ2005/fraudshield/blob/main/README.md"
BugTracker = "https://github.com/DevikaJ2005/fraudshield/issues"

[project.scripts]
server = "server.app:main"

[tool.setuptools]
py-modules = [
    "data_loader",
    "download_kaggle_data",
    "fraudshield_env",
    "graders",
    "inference",
    "inference_llm",
    "llm_agent",
    "models",
]

[tool.setuptools.packages.find]
include = ["server"]

[tool.black]
line-length = 100
target-version = ["py310", "py311"]

[tool.ruff]
line-length = 100

[tool.ruff.lint]
select = ["E", "F", "W"]
ignore = ["E501"]