feat: add giteeAI risk control identification. (#12946)
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from typing import Any, Union
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import requests
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from core.tools.entities.tool_entities import ToolInvokeMessage
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from core.tools.tool.builtin_tool import BuiltinTool
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class GiteeAIToolRiskControl(BuiltinTool):
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def _invoke(
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self, user_id: str, tool_parameters: dict[str, Any]
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) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]:
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headers = {
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"content-type": "application/json",
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"authorization": f"Bearer {self.runtime.credentials['api_key']}",
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}
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inputs = [{"type": "text", "text": tool_parameters.get("input-text")}]
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model = tool_parameters.get("model", "Security-semantic-filtering")
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payload = {"model": model, "input": inputs}
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url = "https://ai.gitee.com/v1/moderations"
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response = requests.post(url, json=payload, headers=headers)
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if response.status_code != 200:
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return self.create_text_message(f"Got Error Response:{response.text}")
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return [self.create_text_message(response.content.decode("utf-8"))]
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identity:
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name: risk control
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author: gitee_ai
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label:
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en_US: risk control identification
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zh_Hans: 风控识别
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icon: icon.svg
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description:
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human:
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en_US: Ensuring the protection and compliance of sensitive information through the filtering and analysis of data semantics
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zh_Hans: 通过对数据语义的过滤和分析,确保敏感信息的保护和合规性
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llm: This tool is used to risk control identification.
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parameters:
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- name: model
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type: string
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required: true
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default: Security-semantic-filtering
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label:
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en_US: Service Model
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zh_Hans: 服务模型
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form: form
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- name: input-text
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type: string
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required: true
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label:
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en_US: Input Text
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zh_Hans: 输入文本
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human_description:
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en_US: The text input for filtering and analysis.
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zh_Hans: 用于分析过滤的文本
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llm_description: The text input for filtering and analysis.
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form: llm
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