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Copy file name to clipboardExpand all lines: docs/explorer/api/client-setup.md
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The SDK exposes a `Client` class. To create an object of this type, you need two variables: the Invariant API endpoint URL and the API key.
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## Getting the API Key
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Navigate to the <imgclass='inline-invariant'src="../../assets/logo.svg"/> [Invariant Explorer](https://explorer.invariantlabs.ai) and create an account via GitHub Sign-In.
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Navigate to the <imgclass='inline-invariant'src="{{ base_url }}/assets/logo.svg"/> [Invariant Explorer](https://explorer.invariantlabs.ai) and create an account via GitHub Sign-In.
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Once you have created an account, go to your [User Settings](https://explorer.invariantlabs.ai/settings) and generate an API key.
Copy file name to clipboardExpand all lines: docs/explorer/api/uploading-traces/file-uploads.md
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To upload a dataset to Explorer, navigate to the [home page](https://explorer.invariantlabs.ai) and click on the `New Dataset` button. This will open the file upload dialog.
Click on the `Choose a File` button and select the dataset file from your local machine. Once the file is selected, click on the `Create` button to start the upload process.
Copy file name to clipboardExpand all lines: docs/guardrails/dataflow-rules.md
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Due to their dynamic nature, agentic systems often mix and combine data from different sources, and can easily leak sensitive information. Guardrails provides a simple way to define dataflow rules, to ensure that sensitive data never leaves the system through unintended channels.
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This is important to understand, as it forms the basis for threat modeling and risk assessment. In contrast to traditional software, agentic systems are highly dynamic, meaning tools and APIs can be called in arbitrary ways, and the agent's behavior can change based on the context and the task at hand.
## Constraining Your Agent's Capability space with Rules
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Invariant’s guardrailing runtime allows you to express these constraints declaratively, ensuring the agent only operates within predefined security boundaries—even in dynamic and open-ended environments. This makes it easier to detect policy violations, reduce risk exposure, and maintain trust in agentic systems.
Unconstrained, this agent can easily fail, allowing a bad actor or sheer malfunction to induce failure states such as data leaks, spamming, or even phishing attacks.
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This behavior has the risk that the agent may be prompt injected by an untrusted email, leading to malicious behavior. A possible such scenario is illustratd in the figure below, where an attacker sends a malicious email to the agent, which then leaks sensitive information to the attacker.
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Guardrails provide you a powerful way to enforce such security policies, and to limit the agent's tool interface to only the tools and functions that are necessary for the task at hand.
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