mirror of
https://github.com/AutoMaker-Org/automaker.git
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feat: implement modular provider architecture with Codex CLI support
Implements a flexible provider pattern that supports both Claude Agent SDK and OpenAI Codex CLI, enabling future expansion to other AI providers (Cursor, OpenCode, etc.) with minimal changes. ## Architecture Changes ### New Provider System - Created provider abstraction layer with BaseProvider interface - Model-based routing: model prefix determines provider - `gpt-*`, `o*` → CodexProvider (subprocess CLI) - `claude-*`, `opus/sonnet/haiku` → ClaudeProvider (SDK) - Providers implement common ExecuteOptions interface ### New Files Created - `providers/types.ts` - Shared interfaces (ExecuteOptions, ProviderMessage, etc.) - `providers/base-provider.ts` - Abstract base class - `providers/claude-provider.ts` - Claude Agent SDK wrapper - `providers/codex-provider.ts` - Codex CLI subprocess executor - `providers/codex-cli-detector.ts` - Installation & auth detection - `providers/codex-config-manager.ts` - TOML config management - `providers/provider-factory.ts` - Model-based provider routing - `lib/subprocess-manager.ts` - Reusable subprocess utilities ## Features Implemented ### Codex CLI Integration - Spawns Codex CLI as subprocess with JSONL output - Converts Codex events to Claude SDK-compatible format - Supports both `codex login` and OPENAI_API_KEY auth methods - Handles: reasoning, messages, commands, todos, file changes - Extracts text from content blocks for non-vision CLI ### Conversation History - Added conversationHistory support to ExecuteOptions - ClaudeProvider: yields previous messages to SDK - CodexProvider: prepends history as text context - Follow-up prompts maintain full conversation context ### Image Upload Support - Images embedded as base64 for vision models - Image paths appended to prompt text for Read tool access - Auto-mode: copies images to feature folder - Follow-up: combines original + new images - Updates feature.json with image metadata ### Session Model Persistence - Added `model` field to Session and SessionMetadata - Sessions remember model preference across interactions - API endpoints accept model parameter - Auto-mode respects feature's model setting ## Modified Files ### Services - `agent-service.ts`: - Added conversation history building - Uses ProviderFactory instead of direct SDK calls - Appends image paths to prompts - Added model parameter and persistence - `auto-mode-service.ts`: - Removed OpenAI model block restriction - Uses ProviderFactory for all models - Added image support in buildFeaturePrompt - Follow-up: loads context, copies images, updates feature.json - Returns to waiting_approval after follow-up ### Routes - `agent.ts`: Added model parameter to /send endpoint - `sessions.ts`: Added model field to create/update - `models.ts`: Added Codex models (gpt-5.2, gpt-5.1-codex*) ### Configuration - `.env.example`: Added OPENAI_API_KEY and CODEX_CLI_PATH - `.gitignore`: Added provider-specific ignores ## Bug Fixes - Fixed image path resolution (relative → absolute) - Fixed Codex empty prompt when images attached - Fixed follow-up status management (in_progress → waiting_approval) - Fixed follow-up images not appearing in prompt text - Removed OpenAI model restrictions in auto-mode ## Testing Notes - Codex CLI authentication verified with both methods - Image uploads work for both Claude (vision) and Codex (Read tool) - Follow-up prompts maintain full context - Conversation history persists across turns - Model switching works per-session 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
This commit is contained in:
Kacper
@@ -1,12 +1,14 @@
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/**
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* Agent Service - Runs Claude agents via the Claude Agent SDK
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* Agent Service - Runs AI agents via provider architecture
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* Manages conversation sessions and streams responses via WebSocket
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*/
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import { query, AbortError, type Options } from "@anthropic-ai/claude-agent-sdk";
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import { AbortError } from "@anthropic-ai/claude-agent-sdk";
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import path from "path";
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import fs from "fs/promises";
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import type { EventEmitter } from "../lib/events.js";
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import { ProviderFactory } from "../providers/provider-factory.js";
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import type { ExecuteOptions } from "../providers/types.js";
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interface Message {
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id: string;
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@@ -26,6 +28,7 @@ interface Session {
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isRunning: boolean;
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abortController: AbortController | null;
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workingDirectory: string;
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model?: string;
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}
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interface SessionMetadata {
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@@ -37,6 +40,7 @@ interface SessionMetadata {
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updatedAt: string;
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archived?: boolean;
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tags?: string[];
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model?: string;
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}
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export class AgentService {
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@@ -91,11 +95,13 @@ export class AgentService {
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message,
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workingDirectory,
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imagePaths,
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model,
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}: {
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sessionId: string;
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message: string;
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workingDirectory?: string;
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imagePaths?: string[];
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model?: string;
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}) {
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const session = this.sessions.get(sessionId);
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if (!session) {
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@@ -106,6 +112,12 @@ export class AgentService {
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throw new Error("Agent is already processing a message");
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}
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// Update session model if provided
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if (model) {
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session.model = model;
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await this.updateSession(sessionId, { model });
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}
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// Read images and convert to base64
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const images: Message["images"] = [];
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if (imagePaths && imagePaths.length > 0) {
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@@ -143,6 +155,12 @@ export class AgentService {
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timestamp: new Date().toISOString(),
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};
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// Build conversation history from existing messages BEFORE adding current message
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const conversationHistory = session.messages.map((msg) => ({
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role: msg.role,
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content: msg.content,
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}));
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session.messages.push(userMessage);
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session.isRunning = true;
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session.abortController = new AbortController();
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@@ -156,11 +174,23 @@ export class AgentService {
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await this.saveSession(sessionId, session.messages);
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try {
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const options: Options = {
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model: "claude-opus-4-5-20251101",
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// Use session model, parameter model, or default
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const effectiveModel = model || session.model || "claude-opus-4-5-20251101";
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// Get provider for this model
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const provider = ProviderFactory.getProviderForModel(effectiveModel);
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console.log(
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`[AgentService] Using provider "${provider.getName()}" for model "${effectiveModel}"`
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);
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// Build options for provider
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const options: ExecuteOptions = {
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prompt: "", // Will be set below based on images
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model: effectiveModel,
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cwd: workingDirectory || session.workingDirectory,
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systemPrompt: this.getSystemPrompt(),
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maxTurns: 20,
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cwd: workingDirectory || session.workingDirectory,
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allowedTools: [
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"Read",
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"Write",
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@@ -171,23 +201,28 @@ export class AgentService {
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"WebSearch",
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"WebFetch",
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],
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permissionMode: "acceptEdits",
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sandbox: {
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enabled: true,
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autoAllowBashIfSandboxed: true,
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},
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abortController: session.abortController!,
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conversationHistory: conversationHistory.length > 0 ? conversationHistory : undefined,
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};
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// Build prompt content
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let promptContent: string | Array<{ type: string; text?: string; source?: object }> =
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message;
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// Append image paths to prompt text (like old implementation)
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if (imagePaths && imagePaths.length > 0) {
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let enhancedMessage = message;
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// Append image file paths to the message text
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enhancedMessage += "\n\nAttached images:\n";
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for (const imagePath of imagePaths) {
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enhancedMessage += `- ${imagePath}\n`;
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}
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const contentBlocks: Array<{ type: string; text?: string; source?: object }> = [];
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if (message && message.trim()) {
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contentBlocks.push({ type: "text", text: message });
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if (enhancedMessage && enhancedMessage.trim()) {
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contentBlocks.push({ type: "text", text: enhancedMessage });
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}
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for (const imagePath of imagePaths) {
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@@ -219,25 +254,16 @@ export class AgentService {
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if (contentBlocks.length > 1 || contentBlocks[0]?.type === "image") {
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promptContent = contentBlocks;
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} else {
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promptContent = enhancedMessage;
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}
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}
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// Build payload
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const promptPayload = Array.isArray(promptContent)
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? (async function* () {
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yield {
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type: "user" as const,
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session_id: "",
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message: {
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role: "user" as const,
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content: promptContent,
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},
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parent_tool_use_id: null,
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};
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})()
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: promptContent;
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// Set the prompt in options
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options.prompt = promptContent;
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const stream = query({ prompt: promptPayload, options });
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// Execute via provider
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const stream = provider.executeQuery(options);
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let currentAssistantMessage: Message | null = null;
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let responseText = "";
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@@ -245,7 +271,7 @@ export class AgentService {
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for await (const msg of stream) {
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if (msg.type === "assistant") {
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if (msg.message.content) {
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if (msg.message?.content) {
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for (const block of msg.message.content) {
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if (block.type === "text") {
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responseText += block.text;
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@@ -270,7 +296,7 @@ export class AgentService {
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});
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} else if (block.type === "tool_use") {
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const toolUse = {
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name: block.name,
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name: block.name || "unknown",
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input: block.input,
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};
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toolUses.push(toolUse);
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@@ -450,7 +476,8 @@ export class AgentService {
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async createSession(
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name: string,
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projectPath?: string,
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workingDirectory?: string
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workingDirectory?: string,
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model?: string
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): Promise<SessionMetadata> {
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const sessionId = this.generateId();
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const metadata = await this.loadMetadata();
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@@ -462,6 +489,7 @@ export class AgentService {
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workingDirectory: workingDirectory || projectPath || process.cwd(),
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createdAt: new Date().toISOString(),
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updatedAt: new Date().toISOString(),
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model,
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};
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metadata[sessionId] = session;
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@@ -470,6 +498,16 @@ export class AgentService {
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return session;
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}
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async setSessionModel(sessionId: string, model: string): Promise<boolean> {
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const session = this.sessions.get(sessionId);
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if (session) {
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session.model = model;
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await this.updateSession(sessionId, { model });
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return true;
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}
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return false;
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}
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async updateSession(
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sessionId: string,
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updates: Partial<SessionMetadata>
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@@ -9,7 +9,9 @@
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* - Verification and merge workflows
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*/
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import { query, AbortError, type Options } from "@anthropic-ai/claude-agent-sdk";
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import { AbortError } from "@anthropic-ai/claude-agent-sdk";
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import { ProviderFactory } from "../providers/provider-factory.js";
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import type { ExecuteOptions } from "../providers/types.js";
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import { exec } from "child_process";
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import { promisify } from "util";
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import path from "path";
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@@ -33,6 +35,7 @@ interface Feature {
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priority?: number;
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spec?: string;
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model?: string; // Model to use for this feature
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imagePaths?: Array<string | { path: string; filename?: string; mimeType?: string; [key: string]: unknown }>;
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}
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/**
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@@ -237,12 +240,17 @@ export class AutoModeService {
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// Build the prompt
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const prompt = this.buildFeaturePrompt(feature);
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// Extract image paths from feature
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const imagePaths = feature.imagePaths?.map((img) =>
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typeof img === "string" ? img : img.path
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);
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// Get model from feature
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const model = getModelString(feature);
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console.log(`[AutoMode] Executing feature ${featureId} with model: ${model}`);
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// Run the agent with the feature's model
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await this.runAgent(workDir, featureId, prompt, abortController, undefined, model);
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// Run the agent with the feature's model and images
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await this.runAgent(workDir, featureId, prompt, abortController, imagePaths, model);
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// Mark as waiting_approval for user review
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await this.updateFeatureStatus(projectPath, featureId, "waiting_approval");
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@@ -377,7 +385,126 @@ export class AutoModeService {
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const model = feature ? getModelString(feature) : MODEL_MAP.opus;
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console.log(`[AutoMode] Follow-up for feature ${featureId} using model: ${model}`);
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await this.runAgent(workDir, featureId, prompt, abortController, imagePaths, model);
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// Update feature status to in_progress
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await this.updateFeatureStatus(projectPath, featureId, "in_progress");
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// Copy follow-up images to feature folder
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const copiedImagePaths: string[] = [];
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if (imagePaths && imagePaths.length > 0) {
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const featureImagesDir = path.join(
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projectPath,
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".automaker",
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"features",
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featureId,
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"images"
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);
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await fs.mkdir(featureImagesDir, { recursive: true });
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for (const imagePath of imagePaths) {
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try {
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// Get the filename from the path
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const filename = path.basename(imagePath);
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const destPath = path.join(featureImagesDir, filename);
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// Copy the image
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await fs.copyFile(imagePath, destPath);
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// Store the relative path (like FeatureLoader does)
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const relativePath = path.join(
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".automaker",
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"features",
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featureId,
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"images",
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filename
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);
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copiedImagePaths.push(relativePath);
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} catch (error) {
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console.error(`[AutoMode] Failed to copy follow-up image ${imagePath}:`, error);
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}
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}
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}
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// Update feature object with new follow-up images BEFORE building prompt
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if (copiedImagePaths.length > 0 && feature) {
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const currentImagePaths = feature.imagePaths || [];
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const newImagePaths = copiedImagePaths.map((p) => ({
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path: p,
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filename: path.basename(p),
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mimeType: "image/png", // Default, could be improved
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}));
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feature.imagePaths = [...currentImagePaths, ...newImagePaths];
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}
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// Load previous agent output for context
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const outputPath = path.join(
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workDir,
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".automaker",
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"features",
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featureId,
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"agent-output.md"
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);
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let previousContext = "";
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try {
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previousContext = await fs.readFile(outputPath, "utf-8");
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} catch {
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// No previous context
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}
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// Build follow-up prompt with context (feature now includes new images)
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let followUpPrompt = prompt;
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if (previousContext) {
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followUpPrompt = `## Follow-up Request
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${this.buildFeaturePrompt(feature!)}
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## Previous Work
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The following is the output from the previous implementation:
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${previousContext}
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---
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## New Instructions
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${prompt}
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Please continue from where you left off and address the new instructions above.`;
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}
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// Combine original feature images with new follow-up images
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const allImagePaths: string[] = [];
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// Add all images from feature (now includes both original and new)
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if (feature?.imagePaths) {
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const allPaths = feature.imagePaths.map((img) =>
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typeof img === "string" ? img : img.path
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);
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allImagePaths.push(...allPaths);
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}
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// Save updated feature.json with new images
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if (copiedImagePaths.length > 0 && feature) {
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const featurePath = path.join(
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projectPath,
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".automaker",
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"features",
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featureId,
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"feature.json"
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);
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try {
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await fs.writeFile(featurePath, JSON.stringify(feature, null, 2));
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} catch (error) {
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console.error(`[AutoMode] Failed to save feature.json:`, error);
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}
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}
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await this.runAgent(workDir, featureId, followUpPrompt, abortController, allImagePaths.length > 0 ? allImagePaths : undefined, model);
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// Mark as waiting_approval for user review
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await this.updateFeatureStatus(projectPath, featureId, "waiting_approval");
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this.emitAutoModeEvent("auto_mode_feature_complete", {
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featureId,
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@@ -544,23 +671,25 @@ export class AutoModeService {
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Format your response as a structured markdown document.`;
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try {
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const options: Options = {
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const provider = ProviderFactory.getProviderForModel("claude-sonnet-4-20250514");
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const options: ExecuteOptions = {
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prompt,
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model: "claude-sonnet-4-20250514",
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maxTurns: 5,
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cwd: projectPath,
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allowedTools: ["Read", "Glob", "Grep"],
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permissionMode: "acceptEdits",
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abortController,
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};
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const stream = query({ prompt, options });
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const stream = provider.executeQuery(options);
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let analysisResult = "";
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for await (const msg of stream) {
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if (msg.type === "assistant" && msg.message.content) {
|
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if (msg.type === "assistant" && msg.message?.content) {
|
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for (const block of msg.message.content) {
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if (block.type === "text") {
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analysisResult = block.text;
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analysisResult = block.text || "";
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this.emitAutoModeEvent("auto_mode_progress", {
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featureId: analysisFeatureId,
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content: block.text,
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@@ -736,6 +865,27 @@ ${feature.spec}
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`;
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}
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// Add images note (like old implementation)
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if (feature.imagePaths && feature.imagePaths.length > 0) {
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const imagesList = feature.imagePaths
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.map((img, idx) => {
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const path = typeof img === "string" ? img : img.path;
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const filename = typeof img === "string" ? path.split("/").pop() : img.filename || path.split("/").pop();
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const mimeType = typeof img === "string" ? "image/*" : img.mimeType || "image/*";
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return ` ${idx + 1}. ${filename} (${mimeType})\n Path: ${path}`;
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})
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.join("\n");
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prompt += `
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**📎 Context Images Attached:**
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The user has attached ${feature.imagePaths.length} image(s) for context. These images are provided both visually (in the initial message) and as files you can read:
|
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|
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${imagesList}
|
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|
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You can use the Read tool to view these images at any time during implementation. Review them carefully before implementing.
|
||||
`;
|
||||
}
|
||||
|
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prompt += `
|
||||
## Instructions
|
||||
|
||||
@@ -761,17 +911,62 @@ When done, summarize what you implemented and any notes for the developer.`;
|
||||
): Promise<void> {
|
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const finalModel = model || MODEL_MAP.opus;
|
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console.log(`[AutoMode] runAgent called for feature ${featureId} with model: ${finalModel}`);
|
||||
|
||||
// Check if this is an OpenAI/Codex model - Claude Agent SDK doesn't support these
|
||||
if (finalModel.startsWith("gpt-") || finalModel.startsWith("o")) {
|
||||
const errorMessage = `OpenAI/Codex models (like "${finalModel}") are not yet supported in server mode. ` +
|
||||
`Please use a Claude model (opus, sonnet, or haiku) instead. ` +
|
||||
`OpenAI/Codex models are only supported in the Electron app.`;
|
||||
console.error(`[AutoMode] ${errorMessage}`);
|
||||
throw new Error(errorMessage);
|
||||
|
||||
// Get provider for this model
|
||||
const provider = ProviderFactory.getProviderForModel(finalModel);
|
||||
|
||||
console.log(
|
||||
`[AutoMode] Using provider "${provider.getName()}" for model "${finalModel}"`
|
||||
);
|
||||
|
||||
// Build prompt content with images (like AgentService)
|
||||
let promptContent: string | Array<{ type: string; text?: string; source?: object }> = prompt;
|
||||
|
||||
if (imagePaths && imagePaths.length > 0) {
|
||||
const contentBlocks: Array<{ type: string; text?: string; source?: object }> = [];
|
||||
|
||||
// Add text block first
|
||||
contentBlocks.push({ type: "text", text: prompt });
|
||||
|
||||
// Add image blocks (for vision models)
|
||||
for (const imagePath of imagePaths) {
|
||||
try {
|
||||
// Make path absolute by prepending workDir if it's relative
|
||||
const absolutePath = path.isAbsolute(imagePath)
|
||||
? imagePath
|
||||
: path.join(workDir, imagePath);
|
||||
|
||||
const imageBuffer = await fs.readFile(absolutePath);
|
||||
const base64Data = imageBuffer.toString("base64");
|
||||
const ext = path.extname(imagePath).toLowerCase();
|
||||
const mimeTypeMap: Record<string, string> = {
|
||||
".jpg": "image/jpeg",
|
||||
".jpeg": "image/jpeg",
|
||||
".png": "image/png",
|
||||
".gif": "image/gif",
|
||||
".webp": "image/webp",
|
||||
};
|
||||
const mediaType = mimeTypeMap[ext] || "image/png";
|
||||
|
||||
contentBlocks.push({
|
||||
type: "image",
|
||||
source: {
|
||||
type: "base64",
|
||||
media_type: mediaType,
|
||||
data: base64Data,
|
||||
},
|
||||
});
|
||||
|
||||
} catch (error) {
|
||||
console.error(`[AutoMode] Failed to load image ${imagePath}:`, error);
|
||||
}
|
||||
}
|
||||
|
||||
promptContent = contentBlocks;
|
||||
}
|
||||
|
||||
const options: Options = {
|
||||
|
||||
const options: ExecuteOptions = {
|
||||
prompt: promptContent,
|
||||
model: finalModel,
|
||||
maxTurns: 50,
|
||||
cwd: workDir,
|
||||
@@ -783,35 +978,24 @@ When done, summarize what you implemented and any notes for the developer.`;
|
||||
"Grep",
|
||||
"Bash",
|
||||
],
|
||||
permissionMode: "acceptEdits",
|
||||
sandbox: {
|
||||
enabled: true,
|
||||
autoAllowBashIfSandboxed: true,
|
||||
},
|
||||
abortController,
|
||||
};
|
||||
|
||||
// Build prompt - include image paths for the agent to read
|
||||
let finalPrompt = prompt;
|
||||
|
||||
if (imagePaths && imagePaths.length > 0) {
|
||||
finalPrompt = `${prompt}\n\n## Reference Images\nThe following images are available for reference. Use the Read tool to view them:\n${imagePaths.map((p) => `- ${p}`).join("\n")}`;
|
||||
}
|
||||
|
||||
const stream = query({ prompt: finalPrompt, options });
|
||||
// Execute via provider
|
||||
const stream = provider.executeQuery(options);
|
||||
let responseText = "";
|
||||
const outputPath = path.join(workDir, ".automaker", "features", featureId, "agent-output.md");
|
||||
|
||||
for await (const msg of stream) {
|
||||
if (msg.type === "assistant" && msg.message.content) {
|
||||
if (msg.type === "assistant" && msg.message?.content) {
|
||||
for (const block of msg.message.content) {
|
||||
if (block.type === "text") {
|
||||
responseText = block.text;
|
||||
responseText = block.text || "";
|
||||
|
||||
// Check for authentication errors in the response
|
||||
if (block.text.includes("Invalid API key") ||
|
||||
if (block.text && (block.text.includes("Invalid API key") ||
|
||||
block.text.includes("authentication_failed") ||
|
||||
block.text.includes("Fix external API key")) {
|
||||
block.text.includes("Fix external API key"))) {
|
||||
throw new Error(
|
||||
"Authentication failed: Invalid or expired API key. " +
|
||||
"Please check your ANTHROPIC_API_KEY or run 'claude login' to re-authenticate."
|
||||
@@ -830,20 +1014,10 @@ When done, summarize what you implemented and any notes for the developer.`;
|
||||
});
|
||||
}
|
||||
}
|
||||
} else if (msg.type === "assistant" && (msg as { error?: string }).error === "authentication_failed") {
|
||||
// Handle authentication error from the SDK
|
||||
throw new Error(
|
||||
"Authentication failed: Invalid or expired API key. " +
|
||||
"Please set a valid ANTHROPIC_API_KEY environment variable or run 'claude login' to authenticate."
|
||||
);
|
||||
} else if (msg.type === "error") {
|
||||
// Handle error messages
|
||||
throw new Error(msg.error || "Unknown error");
|
||||
} else if (msg.type === "result" && msg.subtype === "success") {
|
||||
// Check if result indicates an error
|
||||
if (msg.is_error && msg.result?.includes("Invalid API key")) {
|
||||
throw new Error(
|
||||
"Authentication failed: Invalid or expired API key. " +
|
||||
"Please set a valid ANTHROPIC_API_KEY environment variable or run 'claude login' to authenticate."
|
||||
);
|
||||
}
|
||||
responseText = msg.result || responseText;
|
||||
}
|
||||
}
|
||||
|
||||
Reference in New Issue
Block a user