LiteLLM / LiteLLM
LiteLLM Proxy 'No module named proxy_server' Error After Update
Fix 'No module named proxy_server' error after updating LiteLLM to 1.72.x Includes evidence for LiteLLM troubleshooting demand.
- Category
- LiteLLM
- Error signature
No module named 'proxy_server'- Quick fix
- Compare the failing environment with a known working setup, then change one configuration value at a time.
- Updated
What this error means
No module named 'proxy_server' is a LiteLLM failure pattern reported for developers trying to fix ‘no module named proxy_server’ error after updating litellm to 1.72.x. Based on the imported evidence, treat this as a tool-specific troubleshooting page rather than a generic API error.
Why this happens
After updating to LiteLLM 1.72.7 or 1.72.8, proxy server fails with ‘No module named proxy_server’. Workaround: pip install litellm[proxy]. Affects enterprise users running LiteLLM as AI gateway for 100+ LLM APIs.
Common causes
- After updating LiteLLM to versions 1.72.7 or 1.72.8, users encounter ‘No module named proxy_server’ on startup and LiteLLM proxy crashes. Fix requires pip install litellm[proxy] but many users don’t know this.
- After updating to LiteLLM 1.72.7 or 1.72.8, proxy server fails with ‘No module named proxy_server’. Workaround: pip install litellm[proxy]. Affects enterprise users running LiteLLM as AI gateway for 100+ LLM APIs.
Quick fixes
- Confirm the exact error signature matches
No module named 'proxy_server'. - Check the LiteLLM account, local tool state, and provider configuration involved in the failing workflow.
- 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
- Capture the exact error message and the command, editor action, or request that triggered it.
- Check whether the failure is account/auth, quota/rate, model/provider, local runtime, or deployment configuration.
- Review the source evidence below and compare it with your environment.
- Apply one change at a time and rerun the smallest failing action.
- 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.
Sources checked
Evidence note: After updating to LiteLLM 1.72.7 or 1.72.8, proxy server fails with ‘No module named proxy_server’. Workaround: pip install litellm[proxy]. Affects enterprise users running LiteLLM as AI gateway for 100+ LLM APIs.
Related errors
- LiteLLM proxy fails to start with Prisma NotConnectedError
- LiteLLM proxy startup TypeError in check_view_exists
FAQ
What should I check first?
Start with the exact No module named 'proxy_server' text and the smallest action that reproduces it.
Can I ignore this error?
No. Treat it as a failed LiteLLM workflow until the root cause is understood.
Is this guaranteed to have one fix?
No. The imported evidence supports the troubleshooting path above, but tool behavior can vary by account, plan, version, provider, and local configuration.
How do I know the fix worked?
Rerun the same command, editor action, or request. The fix is working when that action completes without No module named 'proxy_server'.