What this error means

OpenTelemetry integration crashes with 'unhashable type: ''list'' when guardrail mode is a list' is a LiteLLM failure pattern reported for developers trying to fix crash in litellm opentelemetry guardrail integration when guardrail mode is configured as a python list instead of single value. Based on the imported evidence, treat this as a tool-specific troubleshooting page rather than a generic API error.

Why this happens

GitHub issue #28486 on BerriAI/litellm opened May 22, 2026 by kenany. Passguardrails_mode as list causes Python TypeError crash ('unhashable type: list') in OpenTelemetry instrumentation path. bug + llm translation + proxy labels. Directly impacts observability setups for production LLM proxies. Clean, specific error signature with reproduction path. Not in covered errors list.

Common causes

  • GitHub issue #28486 on BerriAI/litellm opened May 22, 2026 by kenany. Passguardrails_mode as list causes Python TypeError crash ('unhashable type: list') in OpenTelemetry instrumentation path. bug + llm translation + proxy labels. Directly impacts observability setups for production LLM proxies. Clean, specific error signature with reproduction path. Not in covered errors list.

Quick fixes

  1. Confirm the exact error signature matches OpenTelemetry integration crashes with 'unhashable type: ''list'' when guardrail mode is a list'.
  2. Check the LiteLLM account, local tool state, and provider configuration involved in the failing workflow.
  3. Compare the failing environment with a known working setup, then change one configuration value at a time.

Platform/tool-specific checks

  • Verify the command, editor, extension, or API client that produced the error.
  • Compare local settings with CI, deployment, or editor-level settings when the error appears in only one environment.
  • Avoid deleting credentials, local model data, or project settings until the failing scope is clear.

Step-by-step troubleshooting

  1. Capture the exact error message and the command, editor action, or request that triggered it.
  2. Check whether the failure is account/auth, quota/rate, model/provider, local runtime, or deployment configuration.
  3. Review the source evidence below and compare it with your environment.
  4. Apply one change at a time and rerun the smallest failing action.
  5. Keep the working fix documented for the team or deployment environment.

How to prevent it

  • Keep provider/tool configuration documented.
  • Record non-secret diagnostics such as tool version, provider name, model name, and command path.
  • Add a lightweight check before CI or production workflows depend on the tool.