openAgent
gitlabThe open source UNIVERSAL agent.
clone
https://gitlab.com/bitzzdev/openAgent.gitAIagentautomationopen-sourceuniversal-agent
import { describe, expect, test } from "bun:test"import {createSession,sessionHistory,sessionVariant,type RunSession,type SessionMessages,} from "@/cli/cmd/run/session.shared"type Message = SessionMessages[number]type Part = Message["parts"][number]type TextPart = Extract<Part, { type: "text" }>type AgentPart = Extract<Part, { type: "agent" }>type FilePart = Extract<Part, { type: "file" }>const model = {providerID: "openai",modelID: "gpt-5",}function userMessage(id: string, parts: Message["parts"], variant = "high"): Message {return {info: {id,sessionID: "session-1",role: "user",time: {created: 1,},agent: "build",model: {...model,variant,},},parts,}}function assistantMessage(id: string, parts: Message["parts"]): Message {return {info: {id,sessionID: "session-1",role: "assistant",time: {created: 1,},parentID: "msg-user-1",modelID: "gpt-5",providerID: "openai",mode: "chat",agent: "build",path: {cwd: "/tmp",root: "/tmp",},cost: 0,tokens: {input: 1,output: 1,reasoning: 0,cache: {read: 0,write: 0,},},},parts,}}function textPart(id: string, messageID: string, text: string, input: Partial<TextPart> = {}): TextPart {return {id,sessionID: "session-1",messageID,type: "text",text,synthetic: input.synthetic,}}function agentPart(id: string, messageID: string, name: string, source?: AgentPart["source"]): AgentPart {return {id,sessionID: "session-1",messageID,type: "agent",name,source,}}function filePart(id: string, messageID: string, url: string, input: Partial<FilePart> = {}): FilePart {return {id,sessionID: "session-1",messageID,type: "file",mime: input.mime ?? "text/plain",filename: input.filename,url,source: input.source,}}describe("run session shared", () => {test("builds user prompt text from text, file, and agent parts", () => {const msgs: SessionMessages = [assistantMessage("msg-assistant-1", [textPart("txt-assistant-1", "msg-assistant-1", "ignore me")]),userMessage("msg-user-1", [textPart("txt-user-1", "msg-user-1", "look @scan"),textPart("txt-user-2", "msg-user-1", "hidden", { synthetic: true }),agentPart("agent-user-1", "msg-user-1", "scan", {start: 5,end: 10,value: "@scan",}),filePart("file-user-1", "msg-user-1", "file:///tmp/note.ts"),]),]const out = createSession(msgs)expect(out.first).toBe(false)expect(out.turns).toHaveLength(1)expect(out.turns[0]?.prompt.text).toBe("look @scan @note.ts")expect(out.turns[0]?.prompt.parts).toEqual([{type: "agent",name: "scan",source: {start: 5,end: 10,value: "@scan",},},{type: "file",mime: "text/plain",filename: undefined,url: "file:///tmp/note.ts",source: {type: "file",path: "file:///tmp/note.ts",text: {start: 11,end: 19,value: "@note.ts",},},},])})test("reuses existing mentions when file and agent parts have no source", () => {const out = createSession([userMessage("msg-user-1", [textPart("txt-user-1", "msg-user-1", "look @scan @note.ts"),agentPart("agent-user-1", "msg-user-1", "scan"),filePart("file-user-1", "msg-user-1", "file:///tmp/note.ts"),]),])expect(out.turns[0]?.prompt).toEqual({text: "look @scan @note.ts",parts: [{type: "agent",name: "scan",source: {start: 5,end: 10,value: "@scan",},},{type: "file",mime: "text/plain",filename: undefined,url: "file:///tmp/note.ts",source: {type: "file",path: "file:///tmp/note.ts",text: {start: 11,end: 19,value: "@note.ts",},},},],})})test("dedupes consecutive history entries, drops blanks, and copies prompt parts", () => {const parts = [{type: "agent" as const,name: "scan",source: {start: 0,end: 5,value: "@scan",},},]const session: RunSession = {first: false,turns: [{ prompt: { text: "one", parts }, provider: "openai", model: "gpt-5", variant: "high" },{ prompt: { text: "one", parts: structuredClone(parts) }, provider: "openai", model: "gpt-5", variant: "high" },{ prompt: { text: " ", parts: [] }, provider: "openai", model: "gpt-5", variant: "high" },{ prompt: { text: "two", parts: [] }, provider: "openai", model: "gpt-5", variant: undefined },],}const out = sessionHistory(session)expect(out.map((item) => item.text)).toEqual(["one", "two"])expect(out[0]?.parts).toEqual(parts)expect(out[0]?.parts).not.toBe(parts)expect(out[0]?.parts[0]).not.toBe(parts[0])})test("returns the latest matching variant for the active model", () => {const session: RunSession = {first: false,turns: [{ prompt: { text: "one", parts: [] }, provider: "openai", model: "gpt-5", variant: "high" },{ prompt: { text: "two", parts: [] }, provider: "anthropic", model: "sonnet", variant: "max" },{ prompt: { text: "three", parts: [] }, provider: "openai", model: "gpt-5", variant: undefined },],}expect(sessionVariant(session, model)).toBeUndefined()session.turns.push({prompt: { text: "four", parts: [] },provider: "openai",model: "gpt-5",variant: "minimal",})expect(sessionVariant(session, model)).toBe("minimal")})})