- Support thinkingMode/effort params in chat and generate endpoints - Add Codex (OpenAI) provider streaming via codex-client utility - Forward thinking config to both Anthropic SDK and Agent SDK paths
417 lines
14 KiB
TypeScript
417 lines
14 KiB
TypeScript
import { defineEventHandler, readBody, setResponseHeaders } from 'h3'
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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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interface ChatBody {
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system: string
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messages: Array<{ role: 'user' | 'assistant'; content: string }>
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model?: string
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provider?: string
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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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/**
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* Streaming chat endpoint.
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* Tries ANTHROPIC_API_KEY first (via Anthropic SDK);
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* falls back to local Claude Code (via Agent SDK, uses OAuth login).
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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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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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// Explicit provider routing
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if (body.provider === 'opencode') {
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return streamViaOpenCode(body, body.model)
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}
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if (body.provider === 'openai') {
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return streamViaCodex(body, body.model)
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}
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// Default: existing behavior (backward-compatible)
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const apiKey = process.env.ANTHROPIC_API_KEY
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if (apiKey) {
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try {
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return await streamViaAnthropicSDK(apiKey, body, body.model)
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} catch {
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// SDK not installed or failed — fall back to Agent SDK
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}
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}
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return streamViaAgentSDK(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 getAnthropicThinkingConfig(body: ChatBody):
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| { type: 'adaptive' | 'disabled' }
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| { type: 'enabled'; budget_tokens: 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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const budget = Math.max(1024, body.thinkingBudgetTokens ?? 1024)
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return { type: 'enabled', budget_tokens: budget }
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}
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return { type: body.thinkingMode }
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}
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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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/** Stream via Anthropic SDK (when API key is available) */
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async function streamViaAnthropicSDK(apiKey: string, body: ChatBody, model?: string) {
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const { default: Anthropic } = await import('@anthropic-ai/sdk')
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const client = new Anthropic({ apiKey })
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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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try {
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const thinking = getAnthropicThinkingConfig(body)
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const messageStream = client.messages.stream({
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model: model || 'claude-sonnet-4-5-20250929',
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max_tokens: 16384,
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system: body.system,
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messages: body.messages,
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...(body.effort ? { effort: body.effort } : {}),
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...(thinking ? { thinking } : {}),
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})
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for await (const ev of messageStream) {
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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.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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}
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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 msg = error instanceof Error ? error.message : 'Unknown error'
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controller.enqueue(
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encoder.encode(`data: ${JSON.stringify({ type: 'error', content: msg })}\n\n`),
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)
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} finally {
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clearInterval(pingTimer)
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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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/** 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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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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// Remove CLAUDECODE env to allow running from within a CC terminal
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const env = { ...process.env } as Record<string, string | undefined>
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delete env.CLAUDECODE
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const claudePath = resolveClaudeCli()
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const thinking = getAgentThinkingConfig(body)
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const q = query({
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prompt,
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options: {
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systemPrompt: body.system,
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model: model || 'claude-sonnet-4-6',
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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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...(claudePath ? { pathToClaudeCodeExecutable: claudePath } : {}),
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},
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})
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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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if (message.subtype !== 'success') {
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const errors = 'errors' in message ? (message.errors as string[]) : []
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const content = errors.join('; ') || `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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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 content = error instanceof Error ? error.message : 'Unknown error'
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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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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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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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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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})
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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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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 content = error instanceof Error ? error.message : 'Unknown error'
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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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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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/** Stream via OpenCode SDK (connects to a running OpenCode server) */
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function streamViaOpenCode(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 ocServer: { close(): void } | undefined
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try {
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const { getOpencodeClient } = await import('../../utils/opencode-client')
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const oc = await getOpencodeClient()
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const ocClient = oc.client
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ocServer = oc.server
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// Create a session for this conversation
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const { data: session, error: sessionError } = await ocClient.session.create({
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title: 'OpenPencil Chat',
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})
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if (sessionError || !session) {
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throw new Error('Failed to create OpenCode session')
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}
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// Inject system prompt as context (no AI reply)
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await ocClient.session.prompt({
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sessionID: session.id,
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noReply: true,
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parts: [{ type: 'text', text: body.system }],
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})
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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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const prompt = lastUserMsg?.content ?? ''
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const parsed = parseOpenCodeModel(model)
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// Send prompt and await full response
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const promptPayload: Record<string, unknown> = {
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sessionID: session.id,
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...(parsed ? { model: parsed } : {}),
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parts: [{ type: 'text', text: prompt }],
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}
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const { data: result, error: promptError } = await promptOpenCodeWithThinking(
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ocClient,
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promptPayload,
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body,
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)
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if (promptError) {
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throw new Error('OpenCode prompt failed')
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}
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// Extract text from response parts
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clearInterval(pingTimer)
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if (result?.parts) {
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for (const part of result.parts) {
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if (part.type === 'text' && 'text' in part) {
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const data = JSON.stringify({ type: 'text', content: part.text })
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controller.enqueue(encoder.encode(`data: ${data}\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) {
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const content = error instanceof Error ? error.message : 'Unknown error'
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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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const { releaseOpencodeServer } = await import('../../utils/opencode-client')
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releaseOpencodeServer(ocServer)
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clearInterval(pingTimer)
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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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