feat(cli): one-shot terminal client (models, chat, --text/--file/--cwd/--conversation)

HTTP client of transport-contract; pure-core arg/render/ndjson + injected fetch/fs shell.
Docs: GLOSSARY (credential/key/model name/model catalog), tasks.md milestone, ORCHESTRATOR geography.

1 files changed, 164 insertions, 0 deletions

diff --git a/packages/cli/src/http.test.ts b/packages/cli/src/http.test.ts
new file mode 100644
index 0000000..becfdbb
--- /dev/null
+++ b/packages/cli/src/http.test.ts
@@ -0,0 +1,164 @@
+import type { AgentEvent } from "@dispatch/transport-contract";
+import { describe, expect, it } from "vitest";
+import { fetchModels, streamChat } from "./http.js";
+
+function ndjsonLines(...events: AgentEvent[]): string {
+	return `${events.map((e) => JSON.stringify(e)).join("\n")}\n`;
+}
+
+function makeFakeFetch(responseBody: string, headers?: Record<string, string>) {
+	const fn = async (_url: string | URL | Request, _init?: RequestInit): Promise<Response> => {
+		const encoder = new TextEncoder();
+		const chunks = responseBody.split("|||");
+		let i = 0;
+		const stream = new ReadableStream<Uint8Array>({
+			pull(controller) {
+				if (i < chunks.length) {
+					const chunk = chunks[i];
+					if (chunk !== undefined) controller.enqueue(encoder.encode(chunk));
+					i++;
+				} else {
+					controller.close();
+				}
+			},
+		});
+		return new Response(stream, {
+			status: 200,
+			headers: headers ?? {},
+		});
+	};
+	return fn as unknown as typeof fetch;
+}
+
+describe("streamChat", () => {
+	it("parses NDJSON events and returns conversationId", async () => {
+		const event1: AgentEvent = {
+			type: "text-delta",
+			conversationId: "c1",
+			turnId: "t1",
+			delta: "Hello",
+		};
+		const event2: AgentEvent = {
+			type: "done",
+			conversationId: "c1",
+			turnId: "t1",
+			reason: "completed",
+		};
+
+		const body = ndjsonLines(event1, event2);
+		const fakeFetch = makeFakeFetch(body, { "X-Conversation-Id": "c1" });
+
+		const { conversationId, events } = await streamChat(
+			{ fetchImpl: fakeFetch },
+			{
+				server: "http://localhost:24203",
+				request: { message: "hi", model: "openai/gpt-4" },
+			},
+		);
+
+		expect(conversationId).toBe("c1");
+
+		const collected: AgentEvent[] = [];
+		for await (const e of events) {
+			collected.push(e);
+		}
+
+		expect(collected).toEqual([event1, event2]);
+	});
+
+	it("handles NDJSON split across chunks", async () => {
+		const event1: AgentEvent = {
+			type: "text-delta",
+			conversationId: "c",
+			turnId: "t",
+			delta: "Hi",
+		};
+		const event2: AgentEvent = {
+			type: "usage",
+			conversationId: "c",
+			turnId: "t",
+			usage: { inputTokens: 10, outputTokens: 5 },
+		};
+
+		const fullNdjson = ndjsonLines(event1, event2);
+		// Split mid-line: after 20 chars
+		const mid = 20;
+		const chunk1 = fullNdjson.slice(0, mid);
+		const chunk2 = fullNdjson.slice(mid);
+
+		const fakeFetch = makeFakeFetch(`${chunk1}|||${chunk2}`, {
+			"X-Conversation-Id": "c",
+		});
+
+		const { events } = await streamChat(
+			{ fetchImpl: fakeFetch },
+			{
+				server: "http://localhost:24203",
+				request: { message: "hi" },
+			},
+		);
+
+		const collected: AgentEvent[] = [];
+		for await (const e of events) {
+			collected.push(e);
+		}
+
+		expect(collected).toEqual([event1, event2]);
+	});
+
+	it("throws on non-OK status", async () => {
+		const fakeFetch = (async (): Promise<Response> =>
+			new Response("not found", { status: 404 })) as unknown as typeof fetch;
+
+		await expect(
+			streamChat(
+				{ fetchImpl: fakeFetch },
+				{
+					server: "http://localhost:24203",
+					request: { message: "hi" },
+				},
+			),
+		).rejects.toThrow("POST /chat failed with status 404");
+	});
+
+	it("throws when response has no body", async () => {
+		const fakeFetch = (async (): Promise<Response> =>
+			new Response(null, { status: 200 })) as unknown as typeof fetch;
+
+		await expect(
+			streamChat(
+				{ fetchImpl: fakeFetch },
+				{
+					server: "http://localhost:24203",
+					request: { message: "hi" },
+				},
+			),
+		).rejects.toThrow("no body");
+	});
+});
+
+describe("fetchModels", () => {
+	it("returns ModelsResponse on success", async () => {
+		const models = { models: ["openai/gpt-4", "anthropic/claude-3"] };
+		const fakeFetch = (async (): Promise<Response> =>
+			new Response(JSON.stringify(models), {
+				status: 200,
+				headers: { "Content-Type": "application/json" },
+			})) as unknown as typeof fetch;
+
+		const result = await fetchModels(
+			{ fetchImpl: fakeFetch },
+			{ server: "http://localhost:24203" },
+		);
+		expect(result).toEqual(models);
+	});
+
+	it("throws on non-OK status", async () => {
+		const fakeFetch = (async (): Promise<Response> =>
+			new Response("server error", { status: 500 })) as unknown as typeof fetch;
+
+		await expect(
+			fetchModels({ fetchImpl: fakeFetch }, { server: "http://localhost:24203" }),
+		).rejects.toThrow("GET /models failed with status 500");
+	});
+});