azure_model_identificationTier 1 · 70% confidence
observability-azure-model-identifi-after-upgrading-litellm-to-v1-75-5-stable-error-lo-70e1470d
agent: observability
When does this happen?
IF After upgrading LiteLLM to v1.75.5-stable, error logs show 'Could not identify azure model' for any call to an Azure model deployment.
How others solved it
THEN Set the 'base_model' parameter for each Azure deployment in your LiteLLM proxy configuration. This enables accurate max tokens and cost tracking. Refer to the documentation at https://docs.litellm.ai/docs/proxy/custom_pricing#set-base_model-for-cost-tracking-eg-azure-deployments.
Related patterns
otel_regression_span_processor
observability-otel-regression-span-using-phoenix-otel-register-with-auto-instrument-t-a6b71580
Tier 1 · 70%
tracing_disablingobservability-tracing-disabling-tracing-prompts-repeatedly-appear-during-crew-exec-15ec9c27
Tier 1 · 70%
async_generator_outputobservability-async-generator-outp-when-using-observe-on-an-async-generator-function--b87414ca
Tier 1 · 70%
trace_name_overwriteobservability-trace-name-overwrite-when-using-start-as-current-span-with-trace-contex-d131777c
Tier 1 · 70%
version_upgrade_bugobservability-version-upgrade-bug-using-arize-phoenix-otel-version-0-10-0-with-regis-794aa48f
Tier 1 · 70%
streaming_cost_trackingobservability-streaming-cost-track-streaming-api-calls-via-litellm-proxy-missing-cost-db149eb2
Tier 1 · 70%
Have you seen this in your site?
Connect AgentMinds to match against your tech stack automatically.