Create ombre_security_audit_openai.md#2648
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| # Adding Security and Audit Logging to OpenAI Apps with Ombre | |||
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This commit introduces a new cookbook document but does not register it in registry.yaml, so it will not be picked up by the cookbook publication pipeline and users will not see it on cookbook.openai.com. The repo review guidelines in AGENTS.md explicitly mark metadata sync for new content as a priority-0 requirement.
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| \```bash | ||
| pip install git+https://github.com/pypl0/Ombre.git | ||
| pip install openai | ||
| \``` |
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The snippet fences are written as escaped backticks (for example \```bash), which renders literal backticks instead of fenced code blocks in Markdown. That breaks formatting for every code sample in this guide and makes examples harder to read and copy correctly.
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| from ombre import Ombre | ||
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| # Initialize with your OpenAI key | ||
| ai = Ombre(openai_key="your-openai-key") |
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The examples initialize Ombre with a literal openai_key string, which encourages hard-coded credential usage when readers adapt the sample. This conflicts with the repo guidance to document environment-variable-based secrets handling and increases the risk of accidental key leakage in downstream code.
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Adds a practical guide showing how to add production-grade
security, hallucination detection, semantic caching, and
tamper-proof audit logging to OpenAI applications using
Ombre — an open source AI infrastructure layer.
Covers:
github.com/pypl0/Ombre