First version copilot:

- basic llm call that can perform CRUD actions over dummy workflow json files

apps/cli/src/application/assistant/chat.ts

@@ -0,0 +1,105 @@
+import readline from "readline";
+import { z } from "zod";
+import { openai } from "@ai-sdk/openai";
+import { generateObject } from "ai";
+import { Workflow } from "../../application/entities/workflow.js";
+import { listWorkflows, getWorkflow, upsertWorkflow, deleteWorkflow } from "./workflows/service.js";
+
+const ChatCommand = z.object({
+  action: z.enum([
+    "help",
+    "list_workflows",
+    "get_workflow",
+    "create_workflow",
+    "update_workflow",
+    "delete_workflow",
+    "unknown",
+  ]),
+  id: z.string().optional(),
+  updates: Workflow.partial().optional(),
+});
+
+type ChatCommandT = z.infer<typeof ChatCommand>;
+
+const systemPrompt = `
+You are a CLI assistant that converts the user's natural language into a JSON command for managing workflows.
+
+Rules:
+- Only output JSON matching the provided schema. No extra commentary.
+- Choose the most appropriate action from: help, list_workflows, get_workflow, create_workflow, update_workflow, delete_workflow, unknown.
+- For actions that need an id (get/update/delete/create), set "id" to the workflow identifier (e.g. "example_workflow").
+- For create/update, include only provided fields in "updates". If not provided, omit.
+- Workflow shape reminder: { name: string, description: string, steps: Step[] } where Step is either { type: "function", id: string } or { type: "agent", id: string }.
+- If the request is ambiguous, set action to "unknown".
+`;
+
+async function interpret(input: string): Promise<ChatCommandT> {
+  const { object } = await generateObject({
+    model: openai("gpt-4.1"),
+    system: systemPrompt,
+    prompt: input,
+    schema: ChatCommand,
+  });
+  return object;
+}
+
+async function execute(cmd: ChatCommandT): Promise<unknown> {
+  switch (cmd.action) {
+    case "help":
+      return {
+        usage: [
+          "Examples:",
+          "- list workflows",
+          "- show workflow example_workflow",
+          "- create workflow demo with one step calling function get_date",
+          "- update workflow demo: add agent step default_assistant",
+          "- delete workflow demo",
+        ],
+      };
+    case "list_workflows":
+      return { items: listWorkflows() };
+    case "get_workflow":
+      if (!cmd.id) return { error: "id required" };
+      return getWorkflow(cmd.id) ?? null;
+    case "create_workflow":
+      if (!cmd.id) return { error: "id required" };
+      return upsertWorkflow(cmd.id, { ...(cmd.updates ?? {}) });
+    case "update_workflow":
+      if (!cmd.id) return { error: "id required" };
+      return upsertWorkflow(cmd.id, { ...(cmd.updates ?? {}) });
+    case "delete_workflow":
+      if (!cmd.id) return { error: "id required" };
+      return { deleted: deleteWorkflow(cmd.id) };
+    case "unknown":
+      return { error: "Could not determine intent. Try again or ask for help." };
+  }
+}
+
+export async function startCopilot(): Promise<void> {
+  if (!process.env.OPENAI_API_KEY) {
+    console.error("OPENAI_API_KEY is not set. Please export it to use chat.");
+    process.exitCode = 1;
+    return;
+  }
+
+  const rl = readline.createInterface({ input: process.stdin, output: process.stdout });
+  console.log("Rowboat Copilot (type 'exit' to quit)");
+
+  const ask = () => rl.question("> ", async (line) => {
+    if (!line || line.trim().toLowerCase() === "exit") {
+      rl.close();
+      return;
+    }
+    try {
+      const cmd = await interpret(line);
+      console.log("\n=== Parsed Command ===\n" + JSON.stringify(cmd, null, 2));
+      const result = await execute(cmd);
+      console.log("\n=== Result ===\n" + JSON.stringify(result, null, 2) + "\n");
+    } catch (err) {
+      console.error("Error:", (err as Error).message);
+    }
+    ask();
+  });
+
+  ask();
+}