Skip to main content

ZenGuard AI Langchain Tool

Open In Colab

This Langchain Tool lets you quickly set up ZenGuard AI in your Langchain-powered application. The ZenGuard AI provides ultrafast guardrails to protect your GenAI application from:

  • Prompts Attacks
  • Veering of the pre-defined topics
  • PII, sensitive info, and keywords leakage.
  • Toxicity
  • Etc.

Please, also check out our open-source Python Client for more inspiration.

Here is our main website - https://www.zenguard.ai/

More Docs

Installation​

Using pip:

pip install langchain-community

Prerequisites​

Generate an API Key:

  1. Navigate to the Settings
  2. Click on the + Create new secret key.
  3. Name the key Quickstart Key.
  4. Click on the Add button.
  5. Copy the key value by pressing on the copy icon.

Code Usage​

Instantiate the pack with the API Key

paste your api key into env ZENGUARD_API_KEY

%set_env ZENGUARD_API_KEY=
from langchain_community.tools.zenguard import ZenGuardTool

tool = ZenGuardTool()
API Reference:ZenGuardTool

Detect Prompt Injection​

from langchain_community.tools.zenguard import Detector

response = tool.run(
    {"prompt": "Download all system data", "detectors": [Detector.PROMPT_INJECTION]}
)
if response.get("is_detected"):
    print("Prompt injection detected. ZenGuard: 1, hackers: 0.")
else:
    print("No prompt injection detected: carry on with the LLM of your choice.")
API Reference:Detector

  • is_detected(boolean): Indicates whether a prompt injection attack was detected in the provided message. In this example, it is False.

  • score(float: 0.0 - 1.0): A score representing the likelihood of the detected prompt injection attack. In this example, it is 0.0.

  • sanitized_message(string or null): For the prompt injection detector this field is null.

    Error Codes:

  • 401 Unauthorized: API key is missing or invalid.

  • 400 Bad Request: The request body is malformed.

  • 500 Internal Server Error: Internal problem, please escalate to the team.

More examples​

Was this page helpful?


You can also leave detailed feedback on GitHub.