Build extensible agent harness with interactive chat loop

src/model/openai.ts

@@ -0,0 +1,60 @@
+import OpenAI from "openai";
+import type {
+  AgentMessage,
+  ModelClient,
+  ModelTurn,
+  ToolCall,
+  ToolDefinition
+} from "../types.js";
+import type { EventBus } from "../events.js";
+
+export class OpenAIResponsesClient implements ModelClient {
+  private readonly client = new OpenAI();
+
+  constructor(
+    private readonly model = "gpt-5",
+    private readonly instructions?: string,
+    private readonly events?: EventBus
+  ) {}
+
+  async respond(input: AgentMessage[], tools: ToolDefinition[]): Promise<ModelTurn> {
+    await this.events?.emit("model.request", {
+      model: this.model,
+      messages: input.length,
+      tools: tools.map((tool) => tool.name)
+    });
+
+    const response = await this.client.responses.create({
+      model: this.model,
+      instructions: this.instructions,
+      input,
+      tools: tools.map((tool) => ({
+        type: "function",
+        name: tool.name,
+        description: tool.description,
+        parameters: tool.parameters,
+        strict: true
+      }))
+    });
+
+    const toolCalls: ToolCall[] = response.output
+      .filter((item): item is OpenAI.Responses.ResponseFunctionToolCall => item.type === "function_call")
+      .map((item) => ({
+        id: item.call_id,
+        name: item.name,
+        arguments: item.arguments
+      }));
+
+    await this.events?.emit("model.response", {
+      outputItems: response.output.length,
+      toolCalls: toolCalls.map((toolCall) => toolCall.name),
+      hasText: response.output_text.length > 0
+    });
+
+    return {
+      output: response.output,
+      outputText: response.output_text,
+      toolCalls
+    };
+  }
+}