Principle:Confident ai Deepeval API Key Management

Overview

API Key Management is the principle of managing API keys securely for cloud-based evaluation services. In the context of DeepEval and Confident AI, this involves handling sensitive credentials -- such as API keys for LLM providers and the Confident AI platform -- in a manner that prevents accidental exposure, ensures proper isolation from regular configuration, and supports environment-based configuration patterns.

Core Concept

When working with cloud-based LLM evaluation services, applications must authenticate with multiple external providers. Each provider requires its own API key or secret token. The principle of API Key Management dictates that:

Secrets must be separated from regular configuration -- API keys and tokens are fundamentally different from non-sensitive settings (e.g., model names, thresholds). They require distinct handling throughout their lifecycle: storage, transmission, and display.
SecretStr protection -- Sensitive values should be wrapped in types such as Pydantic's SecretStr, which prevents accidental logging or serialization of the raw secret value. This ensures that even if configuration objects are printed or logged, the actual key values remain hidden.
Credential isolation -- API keys should never be co-mingled with application logic or persisted alongside non-sensitive data without explicit safeguards. A dedicated handler should manage the read/write lifecycle of credentials.
Environment-based configuration -- Keys should be resolvable from environment variables, dedicated key files, or secure vaults, allowing different deployment environments (development, staging, production) to maintain their own credential sets without code changes.

Theoretical Basis

This principle draws from several established practices in software security and configuration management:

Secret management -- The discipline of storing, accessing, and rotating sensitive credentials using dedicated infrastructure (e.g., secret managers, encrypted key files, environment variables).
Credential isolation -- The architectural pattern of ensuring secrets are handled through a narrow, well-audited interface rather than scattered throughout the codebase.
Environment-based configuration -- The twelve-factor app methodology's recommendation that configuration, especially secrets, be stored in the environment rather than in code.

Why It Matters

Improper API key management leads to:

Accidental exposure in logs, error messages, or version control
Security breaches when keys are stored in plaintext configuration files committed to repositories
Operational failures when keys cannot be rotated without code changes
Compliance violations when audit trails cannot demonstrate proper secret handling

By adhering to this principle, DeepEval ensures that users' API keys for OpenAI, Azure, Anthropic, and Confident AI itself are handled with appropriate security guarantees.

Relationship to Implementation

This principle is realized through a dedicated key file handler that manages the persistence and retrieval of API keys via a hidden configuration file, with explicit protections against persisting SecretStr-annotated values.

Implementation:Confident_ai_Deepeval_KeyFileHandler

Related Pages

Metadata

DeepEval Tracing Observability LLM_Evaluation 2026-02-14 09:00 GMT

Page Connections

Double-click a node to navigate. Hold to expand connections.

Principle

Implementation

Heuristic

Environment