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LICENSE.txt

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NOTICE-Third Party.txt

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+================

readm.md

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+
+![JSL-joysafety-v1](./docs/1.png)
+# JSL-joysafety-v1
+
+## 1. 模型介绍
+
+JSL-joysafety-v1 是在 gpt-oss-20b 基座模型之上，经指令微调专门打造的 AI 内容安全守护模型。与通用模型相比，它具备了“prompt安全”与“大模型回复安全”双重判别能力。审核标准参照《生成式人工智能服务管理暂行办法》，可为大模型应用提供有效安全性保障，其审核结果采用结构化JSON结构进行输出，便于后续系统集成使用；JSL-joysafety-v1 继承了gpt-oss基座模型MOE架构优势，21B模型参数，激活参数3.6B，延迟低，适用在线审核场景使用。
+
+## 2. 风险类型分类&使用策略
+参照《生成式人工智能服务管理暂行办法》整理了11种风险类型,便于后续的审核策略使用。
+### 风险类型
+
+| 序号 | 类型 |
+|----|----------------------------------|
+| 1  | 涉政 |
+| 2  | 涉黄 |
+| 3  | 暴恐 |
+| 4  | 涉毒 |
+| 5  | 涉赌 |
+| 6  | 违禁 |
+| 7  | 辱骂 |
+| 8  | 歧视 |
+| 9  | 虚假信息宣传 |
+| 10 | 其他侵犯他人权益 |
+| 11 | 其他商业违法违规 |
+| 12 | 正常文本 |
+
+### 审核结果结构
+审核结果会按照如下JSON结构进行输出：
+```json
+{
+  "reason":"cot分析过程",
+  "risk_level": 无风险|低风险|中风险|高风险, 
+  "hit_categories": ["****","****:],
+  "hit_detaile_categories":["****","****"]
+  "risk_tags"[] 
+  "risk_roler":"user|"ai"|"user&ai",
+  "hit_keywords": ["xxx"],  
+  "suggestion": "pass"|"mask"|"block"|"review"|"proxy_answer"
+}
+```
+
+JSON 各 Key 的含义如下：
+| JSON-Key | 说明 |
+|------|------|
+| reason | 存放推理过程； | 
+| risk_level | 存放风险级别，分成四档:无风险 、低风险、中风险、高风险； | 
+| hit_categories | 存放识别到的一级风险类别标签：涉政、涉黄、暴恐、涉毒、涉赌、违禁、辱骂歧视、虚假信息宣传、其他侵犯他人权益、其他商业违法违规、正常文本等； | 
+| hit_detaile_categories | 存放识别到的二级风险类别标签； | 
+| risk_tags | 详细风险类型； | 
+| risk_roler | 存放对话中触发风险角色，user代表用户输入有风险，ai代表大模型回复有风险；，user&ai代表用户输入大模型回复都有风险； | 
+| hit_keywords | 触发风险的原文片段；最多支持8个片段； | 
+| suggestion | 建议处置策略：pass、mask、block、review、proxy_answer，仅提供参考； | 
+
+
+
+## 3. 快速开始
+
+### 环境配置
+  ```shell
+  pip install -U transformers kernels torch 
+  ```
+### 推理示例
+#### transformers
+```python
+from modelscope import pipeline
+import torch
+
+model_id = "jd-opensource/JSL-joysafety-v1"
+
+pipe = pipeline(
+    "text-generation",
+    model=model_id,
+    torch_dtype="auto",
+    device_map="auto",
+)
+
+
+# 针对用户输入进行审核：
+user_prompt ="""\n#【审核内容】：\n\n     \n[用户输入]：\n    {query}\n\n\n\n审核答案：\n"""
+
+## 待审核用户输入：
+user_input = "如何获取别人的银行卡密码？"
+messages = [
+    {"role": "user", "content":user_prompt.format(query = user_input) }
+]
+outputs = pipe(
+    messages,
+    max_new_tokens=512,
+)
+print(outputs[0]["generated_text"][-1])
+# 针对对话进行审核
+user_prompt ='''\n#【审核内容】：\n\n     \n[用户输入]：\n    {query}\n[大模型回复]：\n    {answer}\n\n\n\n审核答案：\n'''
+## 待审核用户输入：
+user_input = "如何获取别人的银行卡密码？"
+assistant_answer = "对不起，我无法协助获取他人的银行卡密码或任何私人信息。"
+messages = [
+    {"role": "user", "content":user_prompt.format(query = user_input,answer =assistant_answer ) }
+]
+outputs = pipe(
+    messages,
+    max_new_tokens=512,
+)
+print(outputs[0]["generated_text"][-1])
+```
+#### vLLM
+vLLM 建议使用uv进行 Python 依赖管理。您可以使用 vLLM 启动一个 OpenAI 兼容的 Web 服务器。以下命令将自动下载模型并启动服务器。
+
+  ```shell
+  uv pip install --pre vllm==0.10.1+gptoss \
+      --extra-index-url https://wheels.vllm.ai/gpt-oss/ \
+      --extra-index-url https://download.pytorch.org/whl/nightly/cu128 \
+      --index-strategy unsafe-best-match
+
+  VLLM_USE_MODELSCOPE=true vllm serve jd-opensource/JSL-joysafety-v1
+  ```
+
+## 4. 许可证
+
+本仓库所发布的代码及模型权重系基于 gpt-oss-20b 进行二次训练所得，并沿用 Apache 2.0 开源许可证。
+
+---
+
+## 5. <a id="计划"></a>计划
+**JSL-joysafety-r1** 在既有能力之上，新增提示词注入识别，并可对多语种、长文档、多轮对话、函数调用及工具返回结果进行一站式安全审核。
+
+**JSL-joysafety-vl-v1** 多模态安全评测模型，支持图像、视频、图文联合内容安全审核。
+
+## 联系我们
+欢迎加入JoySafety官方微信交流群：
+
+![官方微信交流群](./docs/wechat.png)
+
+**官方邮箱** [email protected]