* chore(electron): update mac build scripts for improved artifact handling - Modified the `electron:build:mac-arm64` script to rename the generated YAML file for better clarity. - Adjusted the `electron:build:mac-both` script to run builds sequentially without file renaming logic, ensuring consistent output. * chore(electron): enable notarization for macOS builds and update build workflow secrets - Added notarization support in `electron-builder.yml` for enhanced security. - Updated GitHub Actions workflow to include necessary Apple credentials for notarization. * chore(electron): add additional secrets for macOS notarization in build workflow - Included CSC_LINK and CSC_KEY_PASSWORD in the GitHub Actions workflow to support code signing for macOS builds. * feat(types): add ImageFitMode type and objectFit to ImageNode Support fill/fit/crop/tile image scaling modes, matching Figma's image fill behavior. Default is 'fill' (cover) for backward compat. * feat(canvas): render images per fill mode with native crop Add computeImageTransform helper supporting fill/fit/crop/tile modes. Fill/crop uses FabricImage native cropX/cropY instead of clipPath to avoid conflict with parent frame clipping. Tile mode creates a Rect with Pattern fill. Detect mode changes via __needsRecreation flag for object recreation when switching between tile and non-tile modes. * feat(panels): add image fit mode dropdown to property panel New ImageSection component with Fill/Fit/Crop/Tile dropdown for image nodes. Wired into PropertyPanel between icon and appearance sections. * feat(figma): preserve image scale mode from Figma import Map Figma imageScaleMode (FIT/FILL/TILE) to objectFit property on imported ImageNodes so fill mode is preserved across import. * fix(canvas): fix zoom-to-fit bounds inflated by clipped children computeDocBounds was recursing into frame children, inflating the bounding box beyond visible frame bounds. Now only recurses into groups. Also use double-RAF in Figma import for reliable timing. * feat(figma): implement Figma clipboard paste functionality - Added a new hook, useFigmaPaste, to handle pasting Figma clipboard data into the canvas. - Integrated clipboard data extraction and processing to convert Figma nodes into PenNodes. - Enhanced keyboard shortcuts to attempt reading Figma data from the system clipboard as a fallback. - Introduced utility functions for decoding and processing Figma clipboard HTML data. - Updated editor layout to utilize the new Figma paste functionality. * feat(figma): implement Figma clipboard support for pasting nodes - Added a new hook, `useFigmaPaste`, to handle Figma clipboard data extraction and processing. - Integrated Figma clipboard support into the editor layout and keyboard shortcuts for seamless pasting. - Updated README to reflect changes in file format from `.pen` to `.op`. - Refactored AI service methods to route to appropriate provider SDK based on the `provider` field, enhancing flexibility in AI interactions. * fix(figma): preserve imported node order and disable openpencil auto layout Prevent imported/generated nodes from being prepended in auto-layout containers, which could reverse visual order during progressive insertion. Hide the unfinished OpenPencil auto-layout path from the import dialog to avoid selecting a mode that is not ready yet. * fix(ai): enforce explicit provider and model routing Pass selected provider and model through design generation, orchestration, sub-agent, and validation flows. Disable provider/model fallback and remove model retry-without-selection behavior so requests fail fast instead of silently routing to Claude. * chore(package): bump version to 0.1.1 --------- Co-authored-by: Fini <fini.yang@gmail.com>
550 lines
20 KiB
TypeScript
550 lines
20 KiB
TypeScript
import { defineEventHandler, readBody, setResponseHeaders } from 'h3'
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import { readFile, writeFile, mkdtemp, rm } from 'node:fs/promises'
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import { tmpdir } from 'node:os'
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import { join } from 'node:path'
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import { resolveClaudeCli } from '../../utils/resolve-claude-cli'
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import { runCodexExec } from '../../utils/codex-client'
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import {
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buildClaudeAgentEnv,
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getClaudeAgentDebugFilePath,
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} from '../../utils/resolve-claude-agent-env'
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interface ChatAttachmentWire {
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name: string
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mediaType: string
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data: string // base64
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}
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interface ChatBody {
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system: string
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messages: Array<{ role: 'user' | 'assistant'; content: string; attachments?: ChatAttachmentWire[] }>
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model?: string
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provider?: 'anthropic' | 'openai' | 'opencode'
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thinkingMode?: 'adaptive' | 'disabled' | 'enabled'
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thinkingBudgetTokens?: number
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effort?: 'low' | 'medium' | 'high' | 'max'
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}
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async function readDebugTail(path?: string, maxLines = 40): Promise<string[] | undefined> {
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if (!path) return undefined
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try {
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const raw = await readFile(path, 'utf-8')
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const lines = raw.split('\n').filter((l) => l.trim().length > 0)
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return lines.slice(-maxLines)
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} catch {
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return undefined
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}
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}
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function buildClaudeExitHint(rawError: string, debugTail?: string[]): string | undefined {
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if (!/process exited with code 1/i.test(rawError)) return undefined
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if (!debugTail || debugTail.length === 0) return undefined
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const text = debugTail.join('\n')
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const hints: string[] = []
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if (/Failed to save config with lock: Error: EPERM|operation not permitted, .*\.claude\.json/i.test(text)) {
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hints.push('Claude Code cannot write ~/.claude.json in the current runtime (permission denied).')
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}
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if (/Connection error|Could not resolve host|Failed to connect/i.test(text)) {
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hints.push('Upstream API connection failed (check proxy/DNS/network reachability to your ANTHROPIC_BASE_URL).')
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}
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if (/ANTHROPIC_CUSTOM_HEADERS present: false, has Authorization header: false/i.test(text)) {
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hints.push('No API auth header detected by Claude runtime; verify token/header env mapping.')
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}
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if (hints.length === 0) return undefined
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return `${rawError}\n${hints.join(' ')}`
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}
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/**
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* Streaming chat endpoint.
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* Routes to the appropriate provider SDK based on the `provider` field.
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* Requires explicit provider and model; no fallback routing.
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*/
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export default defineEventHandler(async (event) => {
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const body = await readBody<ChatBody>(event)
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if (!body?.messages || !body?.system) {
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setResponseHeaders(event, { 'Content-Type': 'application/json' })
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return { error: 'Missing required fields: system, messages' }
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}
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if (!body.provider) {
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setResponseHeaders(event, { 'Content-Type': 'application/json' })
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return { error: 'Missing provider. Provider fallback is disabled.' }
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}
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if (!body.model?.trim()) {
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setResponseHeaders(event, { 'Content-Type': 'application/json' })
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return { error: 'Missing model. Model fallback is disabled.' }
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}
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if (body.provider !== 'anthropic' && body.provider !== 'openai' && body.provider !== 'opencode') {
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setResponseHeaders(event, { 'Content-Type': 'application/json' })
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return { error: 'Missing or unsupported provider. Provider fallback is disabled.' }
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}
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setResponseHeaders(event, {
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'Content-Type': 'text/event-stream',
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'Cache-Control': 'no-cache',
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Connection: 'keep-alive',
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})
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if (body.provider === 'anthropic') return streamViaAgentSDK(body, body.model)
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if (body.provider === 'opencode') return streamViaOpenCode(body, body.model)
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return streamViaCodex(body, body.model)
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})
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// Keep-alive ping interval (ms) — prevents client timeout while waiting for API TTFT
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const KEEPALIVE_INTERVAL_MS = 15_000
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function getAgentThinkingConfig(body: ChatBody):
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| { type: 'adaptive' | 'disabled' }
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| { type: 'enabled'; budgetTokens?: number }
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| undefined {
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if (!body.thinkingMode) return undefined
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if (body.thinkingMode === 'enabled') {
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return { type: 'enabled', budgetTokens: body.thinkingBudgetTokens }
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}
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return { type: body.thinkingMode }
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}
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/**
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* Save base64 attachments to temp files. Returns { tempDir, files[] } — caller must clean up tempDir.
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*
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* When `insideProject` is true, files are saved under `.openpencil-tmp/` in the
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* current working directory so that Claude Code Agent SDK (which restricts reads
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* to the project directory in plan mode) can access them.
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*/
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async function saveAttachmentsToTempFiles(
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attachments: ChatAttachmentWire[],
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insideProject = false,
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): Promise<{ tempDir: string; files: string[] }> {
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let tempDir: string
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if (insideProject) {
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const { mkdirSync } = await import('node:fs')
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const baseDir = join(process.cwd(), '.openpencil-tmp')
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mkdirSync(baseDir, { recursive: true })
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tempDir = await mkdtemp(join(baseDir, 'attach-'))
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} else {
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tempDir = await mkdtemp(join(tmpdir(), 'openpencil-attach-'))
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}
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const files: string[] = []
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for (const att of attachments) {
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const ext = att.mediaType.split('/')[1] || 'png'
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const filePath = join(tempDir, `${files.length}.${ext}`)
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await writeFile(filePath, Buffer.from(att.data, 'base64'))
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files.push(filePath)
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}
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return { tempDir, files }
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}
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/** Collect all attachments from the last user message */
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function getLastUserAttachments(body: ChatBody): ChatAttachmentWire[] {
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const lastUser = [...body.messages].reverse().find((m) => m.role === 'user')
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return lastUser?.attachments ?? []
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}
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/**
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* Strip "NEVER use tools" and similar instructions from system prompt
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* when we need Claude Code Agent SDK to use its Read tool for image analysis.
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*/
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function stripNoToolsRestriction(systemPrompt: string): string {
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return systemPrompt
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.replace(/^.*NEVER use tools.*$/gim, '')
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.replace(/\n{3,}/g, '\n\n')
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}
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/** Stream via Claude Agent SDK (uses local Claude Code OAuth login, no API key needed) */
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function streamViaAgentSDK(body: ChatBody, model?: string) {
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const stream = new ReadableStream({
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async start(controller) {
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const encoder = new TextEncoder()
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// Send keep-alive pings until the first real chunk arrives
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const pingTimer = setInterval(() => {
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try {
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controller.enqueue(encoder.encode(`data: ${JSON.stringify({ type: 'ping', content: '' })}\n\n`))
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} catch { /* stream already closed */ }
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}, KEEPALIVE_INTERVAL_MS)
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let debugFile: string | undefined
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let attachTempDir: string | undefined
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try {
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const { query } = await import('@anthropic-ai/claude-agent-sdk')
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// Build prompt from the last user message
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const lastUserMsg = [...body.messages].reverse().find((m) => m.role === 'user')
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let prompt = lastUserMsg?.content ?? ''
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// If the last user message has image attachments, save to temp files
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// inside the project directory so Claude Code has read permission.
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const attachments = getLastUserAttachments(body)
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const hasImageAttachments = attachments.length > 0
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if (hasImageAttachments) {
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const saved = await saveAttachmentsToTempFiles(attachments, true)
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attachTempDir = saved.tempDir
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const imageRefs = saved.files.map((f) =>
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`First, use the Read tool to read the image file at "${f}". Then analyze it and respond to the user.`,
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).join('\n')
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prompt = imageRefs + '\n\n' + (prompt || 'Describe what you see in the image.')
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}
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// Remove CLAUDECODE env to allow running from within a CC terminal
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const env = buildClaudeAgentEnv()
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debugFile = getClaudeAgentDebugFilePath()
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const claudePath = resolveClaudeCli()
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const thinking = getAgentThinkingConfig(body)
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// When images are attached, strip the "NEVER use tools" restriction from
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// the system prompt so Claude Code will use its Read tool to view images.
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const effectiveSystemPrompt = hasImageAttachments
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? stripNoToolsRestriction(body.system)
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: body.system
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// When images are attached, use result-based flow (like validate.ts):
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// let Claude Code read the image via its Read tool internally, then
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// only emit the final result text. This avoids streaming intermediate
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// tool-use preamble like "I need to read the file first".
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if (hasImageAttachments) {
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const runImageQuery = async (): Promise<string> => {
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const q = query({
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prompt,
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options: {
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systemPrompt: effectiveSystemPrompt,
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...(model ? { model } : {}),
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maxTurns: 3,
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plugins: [],
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permissionMode: 'plan',
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persistSession: false,
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...(body.effort ? { effort: body.effort } : {}),
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...(thinking ? { thinking } : {}),
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env,
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...(debugFile ? { debugFile } : {}),
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...(claudePath ? { pathToClaudeCodeExecutable: claudePath } : {}),
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},
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})
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try {
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for await (const message of q) {
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if (message.type === 'result') {
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const isErrorResult = 'is_error' in message && Boolean((message as { is_error?: boolean }).is_error)
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if (message.subtype === 'success' && !isErrorResult) {
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return message.result ?? ''
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}
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const errors = 'errors' in message ? (message.errors as string[]) : []
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const resultText = 'result' in message ? String(message.result ?? '') : ''
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const errContent = errors.join('; ') || resultText || `Query ended with: ${message.subtype}`
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throw new Error(errContent)
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}
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}
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return ''
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} finally {
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q.close()
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}
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}
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const resultText = await runImageQuery()
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clearInterval(pingTimer)
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if (resultText) {
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controller.enqueue(
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encoder.encode(`data: ${JSON.stringify({ type: 'text', content: resultText })}\n\n`),
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)
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}
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} else {
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// Normal text-only chat: stream partial messages as before
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const runQuery = async () => {
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const q = query({
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prompt,
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options: {
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systemPrompt: effectiveSystemPrompt,
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...(model ? { model } : {}),
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maxTurns: 1,
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includePartialMessages: true,
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tools: [],
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plugins: [],
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permissionMode: 'plan',
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persistSession: false,
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...(body.effort ? { effort: body.effort } : {}),
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...(thinking ? { thinking } : {}),
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env,
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...(debugFile ? { debugFile } : {}),
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...(claudePath ? { pathToClaudeCodeExecutable: claudePath } : {}),
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},
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})
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try {
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for await (const message of q) {
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if (message.type === 'stream_event') {
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const ev = message.event
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if (ev.type === 'content_block_delta') {
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if (ev.delta.type === 'text_delta') {
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clearInterval(pingTimer)
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const data = JSON.stringify({ type: 'text', content: ev.delta.text })
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controller.enqueue(encoder.encode(`data: ${data}\n\n`))
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} else if (ev.delta.type === 'thinking_delta') {
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// Keep pings alive during thinking — only stop on text output
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const data = JSON.stringify({ type: 'thinking', content: (ev.delta as any).thinking })
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controller.enqueue(encoder.encode(`data: ${data}\n\n`))
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}
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}
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} else if (message.type === 'result') {
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const isErrorResult = 'is_error' in message && Boolean((message as { is_error?: boolean }).is_error)
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if (message.subtype !== 'success' || isErrorResult) {
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const errors = 'errors' in message ? (message.errors as string[]) : []
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const resultText = 'result' in message ? String(message.result ?? '') : ''
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const content = errors.join('; ') || resultText || `Query ended with: ${message.subtype}`
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controller.enqueue(
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encoder.encode(`data: ${JSON.stringify({ type: 'error', content })}\n\n`),
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)
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}
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}
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}
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} finally {
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q.close()
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}
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}
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await runQuery()
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}
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controller.enqueue(
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encoder.encode(`data: ${JSON.stringify({ type: 'done', content: '' })}\n\n`),
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)
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} catch (error) {
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const rawContent = error instanceof Error ? error.message : 'Unknown error'
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const tail = await readDebugTail(debugFile)
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const hintedContent = buildClaudeExitHint(rawContent, tail)
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const content = hintedContent ?? rawContent
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controller.enqueue(
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encoder.encode(`data: ${JSON.stringify({ type: 'error', content })}\n\n`),
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)
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} finally {
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clearInterval(pingTimer)
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if (attachTempDir) {
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rm(attachTempDir, { recursive: true, force: true }).catch(() => {})
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}
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controller.close()
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}
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},
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})
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return new Response(stream)
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}
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/** Parse an OpenCode model string ("providerID/modelID") into its parts */
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function parseOpenCodeModel(model?: string): { providerID: string; modelID: string } | undefined {
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if (!model || !model.includes('/')) return undefined
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const idx = model.indexOf('/')
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return { providerID: model.slice(0, idx), modelID: model.slice(idx + 1) }
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}
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function mapOpenCodeEffort(
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effort?: 'low' | 'medium' | 'high' | 'max',
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): 'low' | 'medium' | 'high' | undefined {
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if (!effort) return undefined
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if (effort === 'max') return 'high'
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return effort
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}
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function buildOpenCodeReasoning(
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body: ChatBody,
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): Record<string, unknown> | undefined {
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const reasoning: Record<string, unknown> = {}
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const effort = mapOpenCodeEffort(body.effort)
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if (effort) {
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reasoning.effort = effort
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}
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if (body.thinkingMode === 'enabled') {
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reasoning.enabled = true
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} else if (body.thinkingMode === 'disabled') {
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reasoning.enabled = false
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}
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if (typeof body.thinkingBudgetTokens === 'number' && body.thinkingBudgetTokens > 0) {
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reasoning.budgetTokens = body.thinkingBudgetTokens
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}
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return Object.keys(reasoning).length > 0 ? reasoning : undefined
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}
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async function promptOpenCodeWithThinking(
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ocClient: any,
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basePayload: Record<string, unknown>,
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body: ChatBody,
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): Promise<{ data: any; error: any }> {
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const reasoning = buildOpenCodeReasoning(body)
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if (!reasoning) {
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return await ocClient.session.prompt(basePayload)
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}
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const enhanced = { ...basePayload, reasoning }
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const firstTry = await ocClient.session.prompt(enhanced)
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if (!firstTry.error) {
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return firstTry
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}
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console.warn('[AI] OpenCode reasoning options rejected, retrying without reasoning.')
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return await ocClient.session.prompt(basePayload)
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}
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function streamViaCodex(body: ChatBody, model?: string) {
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const stream = new ReadableStream({
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async start(controller) {
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const encoder = new TextEncoder()
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const pingTimer = setInterval(() => {
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try {
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controller.enqueue(encoder.encode(`data: ${JSON.stringify({ type: 'ping', content: '' })}\n\n`))
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} catch { /* stream already closed */ }
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}, KEEPALIVE_INTERVAL_MS)
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let attachTempDir: string | undefined
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try {
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const lastUserMsg = [...body.messages].reverse().find((m) => m.role === 'user')
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const prompt = lastUserMsg?.content ?? ''
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|
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// Save image attachments to temp files for Codex CLI
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const attachments = getLastUserAttachments(body)
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let imageFiles: string[] | undefined
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if (attachments.length > 0) {
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const saved = await saveAttachmentsToTempFiles(attachments)
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attachTempDir = saved.tempDir
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imageFiles = saved.files
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}
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const result = await runCodexExec(prompt, {
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model,
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systemPrompt: body.system,
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thinkingMode: body.thinkingMode,
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thinkingBudgetTokens: body.thinkingBudgetTokens,
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effort: body.effort,
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imageFiles,
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})
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|
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clearInterval(pingTimer)
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if (result.error) {
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|
controller.enqueue(
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encoder.encode(`data: ${JSON.stringify({ type: 'error', content: result.error })}\n\n`),
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)
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return
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}
|
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|
|
if (result.text) {
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controller.enqueue(
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encoder.encode(`data: ${JSON.stringify({ type: 'text', content: result.text })}\n\n`),
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)
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}
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|
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controller.enqueue(
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encoder.encode(`data: ${JSON.stringify({ type: 'done', content: '' })}\n\n`),
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)
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|
} catch (error) {
|
|
const content = error instanceof Error ? error.message : 'Unknown error'
|
|
controller.enqueue(
|
|
encoder.encode(`data: ${JSON.stringify({ type: 'error', content })}\n\n`),
|
|
)
|
|
} finally {
|
|
clearInterval(pingTimer)
|
|
if (attachTempDir) {
|
|
rm(attachTempDir, { recursive: true, force: true }).catch(() => {})
|
|
}
|
|
controller.close()
|
|
}
|
|
},
|
|
})
|
|
|
|
return new Response(stream)
|
|
}
|
|
|
|
/** Stream via OpenCode SDK (connects to a running OpenCode server) */
|
|
function streamViaOpenCode(body: ChatBody, model?: string) {
|
|
const stream = new ReadableStream({
|
|
async start(controller) {
|
|
const encoder = new TextEncoder()
|
|
const pingTimer = setInterval(() => {
|
|
try {
|
|
controller.enqueue(encoder.encode(`data: ${JSON.stringify({ type: 'ping', content: '' })}\n\n`))
|
|
} catch { /* stream already closed */ }
|
|
}, KEEPALIVE_INTERVAL_MS)
|
|
|
|
let ocServer: { close(): void } | undefined
|
|
try {
|
|
const { getOpencodeClient } = await import('../../utils/opencode-client')
|
|
const oc = await getOpencodeClient()
|
|
const ocClient = oc.client
|
|
ocServer = oc.server
|
|
|
|
// Create a session for this conversation
|
|
const { data: session, error: sessionError } = await ocClient.session.create({
|
|
title: 'OpenPencil Chat',
|
|
})
|
|
if (sessionError || !session) {
|
|
throw new Error('Failed to create OpenCode session')
|
|
}
|
|
|
|
// Inject system prompt as context (no AI reply)
|
|
await ocClient.session.prompt({
|
|
sessionID: session.id,
|
|
noReply: true,
|
|
parts: [{ type: 'text', text: body.system }],
|
|
})
|
|
|
|
// Build prompt from the last user message
|
|
const lastUserMsg = [...body.messages].reverse().find((m) => m.role === 'user')
|
|
const prompt = lastUserMsg?.content ?? ''
|
|
|
|
const parsed = parseOpenCodeModel(model)
|
|
|
|
// Build parts array, adding image attachments if present
|
|
const attachments = getLastUserAttachments(body)
|
|
const parts: Array<Record<string, unknown>> = [
|
|
...attachments.map((a) => ({
|
|
type: 'image',
|
|
url: `data:${a.mediaType};base64,${a.data}`,
|
|
})),
|
|
{ type: 'text', text: prompt || 'Analyze these images.' },
|
|
]
|
|
|
|
// Send prompt and await full response
|
|
const promptPayload: Record<string, unknown> = {
|
|
sessionID: session.id,
|
|
...(parsed ? { model: parsed } : {}),
|
|
parts,
|
|
}
|
|
|
|
const { data: result, error: promptError } = await promptOpenCodeWithThinking(
|
|
ocClient,
|
|
promptPayload,
|
|
body,
|
|
)
|
|
|
|
if (promptError) {
|
|
throw new Error('OpenCode prompt failed')
|
|
}
|
|
|
|
// Extract text from response parts
|
|
clearInterval(pingTimer)
|
|
if (result?.parts) {
|
|
for (const part of result.parts) {
|
|
if (part.type === 'text' && 'text' in part) {
|
|
const data = JSON.stringify({ type: 'text', content: part.text })
|
|
controller.enqueue(encoder.encode(`data: ${data}\n\n`))
|
|
}
|
|
}
|
|
}
|
|
|
|
controller.enqueue(
|
|
encoder.encode(`data: ${JSON.stringify({ type: 'done', content: '' })}\n\n`),
|
|
)
|
|
} catch (error) {
|
|
const content = error instanceof Error ? error.message : 'Unknown error'
|
|
controller.enqueue(
|
|
encoder.encode(`data: ${JSON.stringify({ type: 'error', content })}\n\n`),
|
|
)
|
|
} finally {
|
|
const { releaseOpencodeServer } = await import('../../utils/opencode-client')
|
|
releaseOpencodeServer(ocServer)
|
|
clearInterval(pingTimer)
|
|
controller.close()
|
|
}
|
|
},
|
|
})
|
|
|
|
return new Response(stream)
|
|
}
|