[jira] [Resolved] (CAMEL-23861) camel-langchain4j - Add OpenTelemetry and Micrometer observability for AI/LLM usage

["Claus Ibsen (Jira)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/CAMEL-23861?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Claus Ibsen resolved CAMEL-23861.
---------------------------------
    Resolution: Fixed

Merged via PR https://github.com/apache/camel/pull/25491

> camel-langchain4j - Add OpenTelemetry and Micrometer observability for AI/LLM usage
> -----------------------------------------------------------------------------------
>
>                 Key: CAMEL-23861
>                 URL: https://issues.apache.org/jira/browse/CAMEL-23861
>             Project: Camel
>          Issue Type: Improvement
>          Components: camel-langchain4j-agent, camel-langchain4j-chat, camel-langchain4j-embeddings, camel-langchain4j-tools
>            Reporter: Claus Ibsen
>            Assignee: Omar Atie
>            Priority: Major
>              Labels: ai, observability
>             Fix For: 4.23.0
>
>
> The camel-langchain4j components currently have no observability integration for AI/LLM-specific metrics and tracing. Token usage, model name, finish reason, and latency are not captured.
> Spring AI exposes this data through the Micrometer Observation API (which produces both metrics and traces) following the OpenTelemetry Semantic Conventions for GenAI (https://opentelemetry.io/docs/specs/semconv/gen-ai/). This enables dashboards showing token consumption, costs, model distribution, and conversation tracking.
> Camel should follow the same approach. When camel-micrometer or camel-opentelemetry2 is active, the langchain4j producers should capture:
> *OpenTelemetry span attributes (GenAI semantic conventions):*
> - gen_ai.system (e.g. openai, anthropic)
> - gen_ai.request.model
> - gen_ai.response.model
> - gen_ai.usage.input_tokens
> - gen_ai.usage.output_tokens
> - gen_ai.response.finish_reasons
> *Micrometer metrics:*
> - Token counters (input/output/total) with model tag
> - Request counters per model/operation
> - Latency timers/histograms
> - Error counters
> This would allow standard observability tooling (Grafana, Jaeger, Prometheus, etc.) and Camel TUI to visualize AI/LLM usage across routes.
> See also CAMEL-23860 which adds token data as exchange headers - this ticket is about propagating that data into the observability layer for monitoring and dashboards.



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