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Community: Update and fix ZenGuardTool docs and add ZenguardTool to init files (#23415)
Thank you for contributing to LangChain! - [x] **PR title**: "community: update docs and add tool to init.py" - [x] **PR message**: - **Description:** Fixed some errors and comments in the docs and added our ZenGuardTool and additional classes to init.py for easy access when importing - **Question:** when will you update the langchain-community package in pypi to make our tool available? - [x] **Lint and test**: Run `make format`, `make lint` and `make test` from the root of the package(s) you've modified. See contribution guidelines for more: https://python.langchain.com/docs/contributing/ Thank you for review! --------- Co-authored-by: Baur <baur.krykpayev@gmail.com>
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@@ -4,11 +4,11 @@
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# ZenGuard AI Langchain Tool\n",
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"# ZenGuard AI\n",
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"\n",
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"<a href=\"https://colab.research.google.com/github/langchain-ai/langchail/blob/main/docs/docs/integrations/tools/zenguard.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\" /></a>\n",
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"<a href=\"https://colab.research.google.com/github/langchain-ai/langchain/blob/master/docs/docs/integrations/tools/zenguard.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\" /></a>\n",
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"\n",
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"This Langchain Tool lets you quickly set up [ZenGuard AI](https://www.zenguard.ai/) in your Langchain-powered application. The ZenGuard AI provides ultrafast guardrails to protect your GenAI application from:\n",
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"This tool lets you quickly set up [ZenGuard AI](https://www.zenguard.ai/) in your Langchain-powered application. The ZenGuard AI provides ultrafast guardrails to protect your GenAI application from:\n",
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"\n",
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"- Prompts Attacks\n",
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"- Veering of the pre-defined topics\n",
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@@ -86,7 +86,7 @@
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},
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"outputs": [],
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"source": [
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"%set_env ZENGUARD_API_KEY="
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"%set_env ZENGUARD_API_KEY=your_api_key"
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]
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},
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{
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@@ -131,6 +131,7 @@
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"* `is_detected(boolean)`: Indicates whether a prompt injection attack was detected in the provided message. In this example, it is False.\n",
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" * `score(float: 0.0 - 1.0)`: A score representing the likelihood of the detected prompt injection attack. In this example, it is 0.0.\n",
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" * `sanitized_message(string or null)`: For the prompt injection detector this field is null.\n",
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" * `latency(float or null)`: Time in milliseconds during which the detection was performed\n",
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"\n",
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" **Error Codes:**\n",
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"\n",
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