diff --git a/README.md b/README.md index 5b2b166..403f439 100644 --- a/README.md +++ b/README.md @@ -184,6 +184,6 @@ MIT License - see LICENSE file for details. ## Disclaimers -Please note that Guardrails may use Third-Party Services such as the [Presidio open-source framework](https://github.com/microsoft/presidio), which are subject to their own terms and conditions and are not developed or verified by OpenAI. For more information on configuring guardrails, please visit: [platform.openai.com/guardrails](https://platform.openai.com/guardrails) +Please note that Guardrails may use Third-Party Services such as the [Presidio open-source framework](https://github.com/microsoft/presidio), which are subject to their own terms and conditions and are not developed or verified by OpenAI. For more information on configuring guardrails, please visit: [guardrails.openai.com](https://guardrails.openai.com/) Developers are responsible for implementing appropriate safeguards to prevent storage or misuse of sensitive or prohibited content (including but not limited to personal data, child sexual abuse material, or other illegal content). OpenAI disclaims liability for any logging or retention of such content by developers. Developers must ensure their systems comply with all applicable data protection and content safety laws, and should avoid persisting any blocked content generated or intercepted by Guardrails. diff --git a/docs/agents_sdk_integration.md b/docs/agents_sdk_integration.md index 203d7ad..57fdb9c 100644 --- a/docs/agents_sdk_integration.md +++ b/docs/agents_sdk_integration.md @@ -99,7 +99,7 @@ const agent = new GuardrailAgent({ config: configDict, ... }); ## Next Steps -- Use the [Guardrails Wizard](https://platform.openai.com/guardrails) to generate your configuration +- Use the [Guardrails Wizard](https://guardrails.openai.com/) to generate your configuration - Explore available guardrails for your use case - Learn about pipeline configuration in our [quickstart](./quickstart.md) - For more details on the OpenAI Agents SDK, refer to the [Agent SDK documentation](https://openai.github.io/openai-agents-js/). diff --git a/docs/evals.md b/docs/evals.md index 57c22f8..7586a31 100644 --- a/docs/evals.md +++ b/docs/evals.md @@ -39,7 +39,7 @@ The evals tool is included with the TypeScript package. No additional dependenci Export a configuration from the Guardrails Wizard UI and pass its path via `--config-path`. -- Open the [Wizard UI](https://platform.openai.com/guardrails) +- Open the [Wizard UI](https://guardrails.openai.com/) - Configure the guardrails you want to evaluate - Use Export to download the config file (JSON) - Run the evaluator with `--config-path /path/to/exported_config.json` @@ -160,4 +160,4 @@ npm run eval -- --config-path config.json --dataset-path data.jsonl --base-url h ## Next Steps - See the [API Reference](./ref/eval/guardrail_evals.md) for detailed documentation -- Use [Wizard UI](https://platform.openai.com/guardrails) for configuring guardrails without code \ No newline at end of file +- Use [Wizard UI](https://guardrails.openai.com/) for configuring guardrails without code \ No newline at end of file diff --git a/docs/index.md b/docs/index.md index 7f47832..7a50952 100644 --- a/docs/index.md +++ b/docs/index.md @@ -1,6 +1,6 @@ # Guardrails -**Guardrails** is a safety framework for LLM applications that automatically validates inputs and outputs using configurable checks. Use the [Guardrails Wizard](https://platform.openai.com/guardrails) to create configurations, then drop in our client classes for automatic validation. +**Guardrails** is a safety framework for LLM applications that automatically validates inputs and outputs using configurable checks. Use the [Guardrails Wizard](https://guardrails.openai.com/) to create configurations, then drop in our client classes for automatic validation. ![Guardrails Wizard](assets/images/guardrails_wizard_screenshot.png) @@ -55,7 +55,7 @@ main(); - [Quickstart](./quickstart.md) - [Examples](./examples.md) - See real implementations -- [Guardrails Wizard](https://platform.openai.com/guardrails) - Create configurations visually +- [Guardrails Wizard](https://guardrails.openai.com/) - Create configurations visually ## Disclaimers diff --git a/docs/quickstart.md b/docs/quickstart.md index fd9f7e8..91bca84 100644 --- a/docs/quickstart.md +++ b/docs/quickstart.md @@ -16,7 +16,7 @@ export OPENAI_API_KEY=sk-... ## Create Pipeline Configuration -The fastest way is using the [Guardrails Wizard](https://platform.openai.com/guardrails) - a no-code tool for creating configurations. +The fastest way is using the [Guardrails Wizard](https://guardrails.openai.com/) - a no-code tool for creating configurations. Or define manually: diff --git a/src/checks/hallucination-detection.ts b/src/checks/hallucination-detection.ts index 7b21539..a9ed130 100644 --- a/src/checks/hallucination-detection.ts +++ b/src/checks/hallucination-detection.ts @@ -8,8 +8,8 @@ * **IMPORTANT: A valid OpenAI vector store must be created before using this guardrail.** * * To create an OpenAI vector store, you can: - * - * 1. **Use the Guardrails Wizard**: Configure the guardrail through the [Guardrails Wizard](https://platform.openai.com/guardrails), which provides an option to create a vector store if you don't already have one. + * + * 1. **Use the Guardrails Wizard**: Configure the guardrail through the [Guardrails Wizard](https://guardrails.openai.com/), which provides an option to create a vector store if you don't already have one. * 2. **Use the OpenAI Dashboard**: Create a vector store directly in the [OpenAI Dashboard](https://platform.openai.com/storage/vector_stores/). * 3. **Follow OpenAI Documentation**: Refer to the "Create a vector store and upload a file" section of the [File Search documentation](https://platform.openai.com/docs/guides/tools-file-search) for detailed instructions. * 4. **Use the provided utility script**: Use the `create_vector_store.py` script provided in the [repo](https://github.com/OpenAI-Early-Access/guardrails/blob/main/guardrails/src/guardrails/utils/create_vector_store.py) to create a vector store from local files or directories.