Ardan Labs

Kronk AI: Building a Basic AI Chat Agent with Message History Pt. 1

The video walks through building a rudimentary chat agent in Go, leveraging Kronk AI’s model server and server‑side events (SSE) to exchange messages with an OpenAI‑compatible backend. It starts by defining constants for the model endpoint, then creates a simple stdin scanner to capture user input. A factory function builds an agent that wraps an SSE client, writes output to stdout, and maintains a slice of message maps as the conversation history. Each user turn is added with role = "user", packaged into a chat‑completion request, and sent with `stream:true` so the server streams partial tokens back. During execution the code prints colored chunks—regular content in default color and reasoning in red—demonstrating how to differentiate response parts. The presenter shows a live session: greeting the model, asking it to write a Go “Hello World”, then requesting the same in Rust, confirming that the stored history informs follow‑up answers. While the prototype successfully preserves context, the host notes that each request clears the KV cache, forcing full re‑decoding and degrading performance as the dialogue grows. This highlights the need for caching optimizations before scaling the agent to more complex tool‑calling scenarios.