Giving Your Agent a Memory — Multi-Turn Conversations with NVIDIA NIM

Short summary

Add persistent conversation memory to multi-turn agents by moving message history from a local variable into a session object. Trim old context by user-message boundaries, not arbitrarily, to avoid orphaning tool-call responses. This pattern works with any OpenAI-compatible LLM API like NVIDIA NIM.

• •Session objects persist agent message history across turns, enabling true multi-turn conversations
• •Naive context trimming breaks tool-call bookkeeping; always trim at user-message boundaries to keep tool calls paired with their results
• •Low temperature settings become critical with persistent memory to prevent hallucinations from accumulated context

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