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Track multi-turn conversations with a chatbot or assistant using sessions

Sessions enable tracking and organizing related traces across multi-turn conversations with your AI application. When building conversational AI, maintaining context between interactions is critical - Sessions make this possible from an observability perspective. With Sessions in Phoenix, you can:
  • Track the entire history of a conversation in a single thread
  • View conversations in a chatbot-like UI showing inputs and outputs of each turn
  • Search through sessions to find specific interactions
  • Track token usage and latency per conversation
This feature is particularly valuable for applications where context builds over time, like chatbots, virtual assistants, or any other multi-turn interaction. By tagging spans with a consistent session ID, you create a connected view that reveals how your application performs across an entire user journey.

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