To group multi-turn conversations in Lemma, useDocumentation Index
Fetch the complete documentation index at: https://docs.uselemma.ai/llms.txt
Use this file to discover all available pages before exploring further.
lemma.thread_id as the canonical thread attribute across related traces.
Use the same thread ID value for every turn in the same conversation. When your framework telemetry accepts OpenTelemetry-style metadata keys, set lemma.thread_id exactly.
When you also set gen_ai.agent.name, use snake_case, CamelCase, or kebab-case by semantic convention, such as support_agent, SupportAgent, or support-agent.
Langfuse framework telemetry
For greenfield apps, set thread metadata where the Langfuse framework integration emits spans. For the Vercel AI SDK, that isexperimental_telemetry.metadata:
Langfuse SDK propagation
Use Langfuse propagation when you create spans or wrap functions directly with the Langfuse SDK. This keeps the thread/session context attached to child observations created inside the scope.- TypeScript
- Python
lemma.thread_id is the canonical Lemma key when emitted as OpenTelemetry metadata. Langfuse SDK metadata fields are useful for propagation and filtering in Langfuse; use the exact lemma.thread_id key in framework telemetry hooks that support OpenTelemetry-style metadata keys.
