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Requests with newer Anthropic beta headers silently lose functionality when proxied through LiteLLM's OAuth handler; developers unaware of silent feature loss Includes evidence for LiteLLM troubleshooting demand.
oauth handler overwrites anthropic-beta header — only oauth-2025-04-20 retained, newer beta features dropped (e.g. prompt caching) Debug why explicit timeout setting disappears when passing requests through LiteLLM's responses() wrapper, leading to indefinite hangs on slow providers Includes evidence for LiteLLM troubleshooting demand.
Timeout parameter silently dropped on completion transformation path (affects Anthropic, Bedrock, Vertex) causing unexpected request hangs Fix LiteLLM Router streaming fallback not triggering when provider fails mid-stream during aresponses(), losing graceful failover to backup models Includes evidence for LiteLLM troubleshooting demand.
MidStreamFallbackError not handled in Router.aresponses() causing unhandled streaming bypass during mid-call provider failure Understand why LiteLLM TPM rate limits don't aggregate across pods and how to enforce correct per-deployment token limits Includes evidence for LiteLLM troubleshooting demand.
tpm_limit × N_replica — deployment-level tokens-per-minute enforcement is per-pod, not cross-pod consistent Add Retry-After header support to LiteLLM rate limit errors so clients can implement proper exponential backoff Includes evidence for LiteLLM troubleshooting demand.
RouterRateLimitError: No Retry-After header returned when all deployments in cooldown period Fix OpenRouter API rate limiting or quota exhaustion when calling models through the platform; understand tier-based limits and how to implement proper retry/backoff for production workloads. Includes evidence for OpenRouter troubleshooting demand.
OpenRouter rate limit exceeded OR quota exhausted — model routing request rejected by proxy Distinguish between LiteLLM proxy rate limiting and underlying OpenAI quota exhaustion for faster fix Includes evidence for LiteLLM troubleshooting demand.
litellm.RateLimitError: RateLimitError: OpenAIException - Error code: 429 - { 'error' : {'message': 'You exceeded your current quota , please check your plan and billing details.'} Configure automatic fallback to secondary models when primary model group hits LiteLLM rate limits; avoid downtime on paid proxy tier Includes evidence for LiteLLM troubleshooting demand.
RateLimitError: Rate limit exceeded — LiteLLM proxy needs automatic fallback configuration for model groups to handle rate limit errors gracefully Fix LiteLLM hanging 600 seconds on Ollama connection timeout instead of raising proper error quickly; understand why stream_timeout and regular timeout settings don't work for watsonx/Ollama backends Includes evidence for LiteLLM troubleshooting demand.
ERROR :root: LiteLLM call failed: litellm.APIConnectionError: OllamaException - litellm.Timeout: Connection timed out after 600.0 seconds. Fix LiteLLM proxy rate limit error that leaks internal API key SHA-256 hash in error message body, exposing credentials Includes evidence for LiteLLM troubleshooting demand.
Error: { "message": "Rate limit exceeded for ...", ... } leaking full SHA-256 key in response body Fix LiteLLM hiding 429 rate limit errors from Vertex AI during streaming requests; clients see hung responses instead of actionable error Includes evidence for LiteLLM troubleshooting demand.
Vertex AI 429 rate limit error during streaming not surfaced to client — only visible in LiteLLM debug logs, causes silent streaming failures Fix or understand timeout errors occurring when LiteLLM proxy forwards requests to upstream LLM providers, causing cascading failures in production Includes evidence for LiteLLM troubleshooting demand.
TimeoutError / Timeout on upstream API provider calls through LiteLLM proxy Fix LiteLLM router not properly handling mid-stream model fallback when primary model fails during streaming — causes dropped responses instead of transparent failover Includes evidence for LiteLLM troubleshooting demand.
[Bug]: Router.aresponses streaming bypasses mid-stream fallback (MidStreamFallbackError not handled) Fix LiteLLM proxy TPM enforcement to be cluster-wide across all pods rather than per-instance; prevent quota bypass through horizontal scaling Includes evidence for LiteLLM troubleshooting demand.
tpm_limit × N_replica causes deployments with multiple replicas to exceed intended rate limits; per-pod enforcement bypasses aggregate billing controls Fix cascading rate limit errors in LiteLLM proxy when auto-fallback between model groups encounters its own RPM/TPM limits Includes evidence for LiteLLM troubleshooting demand.
RateLimitError / timeout in LiteLLM proxy when automatic model group fallback is triggered — fallback itself triggers another rate limit Fix MCP Python SDK where a single HTTP error in a concurrent JSON-RPC session causes all other in-flight requests to fail simultaneously Includes evidence for LiteLLM troubleshooting demand.
streamable_http_client: one concurrent request HTTPStatusError tears down sibling requests — transport task group disruption Developer configured max_parallel_requests on a LiteLLM API key to control concurrency, but requests still exceed rate limits because the setting is ignored Includes evidence for LiteLLM troubleshooting demand.
MaxParallelRequests do not limit concurrent requests from one API Key — rate limits hit despite config Developer running LiteLLM proxy hits provider rate limit (429) but sees misleading error 'No deployments available', leading them down wrong debugging path instead of fixing rate limits Includes evidence for LiteLLM troubleshooting demand.
Rate limit error reported as 'No deployments available' — incorrect error classification causes wrong troubleshooting path Developer encounters error where LiteLLM rate limit response body contains full SHA-256 secret key, potentially exposing credentials in logs and monitoring systems Includes evidence for LiteLLM troubleshooting demand.
Rate limit error message body leaks full SHA-256 hash of API key — security vulnerability exposed through error response Fix incorrect BudgetExceededError triggered by leaked Redis counters after upgrading LiteLLM, blocking AI proxy service Includes evidence for LiteLLM troubleshooting demand.
BudgetExceededError — phantom error despite downgrade to v1.83.10.dev.2; Redis spend counter leak in reserve_budget_for_request()