wip cloud

This commit is contained in:
Frank
2025-08-28 17:52:17 -04:00
parent 9b27d61fe8
commit 8a0e773add
3 changed files with 658 additions and 1 deletions

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@@ -0,0 +1,576 @@
import { Resource } from "sst"
import { Billing } from "@opencode/cloud-core/billing.js"
import type { APIEvent } from "@solidjs/start/server"
import { Database, eq, sql } from "@opencode/cloud-core/drizzle/index.js"
import { BillingTable, PaymentTable } from "@opencode/cloud-core/schema/billing.sql.js"
import { Identifier } from "@opencode/cloud-core/identifier.js"
import { centsToMicroCents } from "@opencode/cloud-core/util/price.js"
import { Actor } from "@opencode/cloud-core/actor.js"
import { KeyTable } from "@opencode/cloud-core/schema/key.sql.js"
const SUPPORTED_MODELS = {
// "anthropic/claude-sonnet-4": {
// input: 0.0000015,
// output: 0.000006,
// reasoning: 0.0000015,
// cacheRead: 0.0000001,
// cacheWrite: 0.0000001,
// model: () =>
// createAnthropic({
// apiKey: Resource.ANTHROPIC_API_KEY.value,
// })("claude-sonnet-4-20250514"),
// },
// "openai/gpt-4.1": {
// input: 0.0000015,
// output: 0.000006,
// reasoning: 0.0000015,
// cacheRead: 0.0000001,
// cacheWrite: 0.0000001,
// model: () =>
// createOpenAI({
// apiKey: Resource.OPENAI_API_KEY.value,
// })("gpt-4.1"),
// },
// "zhipuai/glm-4.5-flash": {
// input: 0,
// output: 0,
// reasoning: 0,
// cacheRead: 0,
// cacheWrite: 0,
// model: () =>
// createOpenAICompatible({
// name: "Zhipu AI",
// baseURL: "https://api.z.ai/api/paas/v4",
// apiKey: Resource.ZHIPU_API_KEY.value,
// })("glm-4.5-flash"),
// },
}
export async function POST(input: APIEvent) {
// Check auth header
const authHeader = input.request.headers.get("authorization")
if (!authHeader || !authHeader.startsWith("Bearer "))
return Response.json(
{
error: {
message: "Missing API key.",
type: "invalid_request_error",
param: null,
code: "unauthorized",
},
},
{ status: 401 },
)
const apiKey = authHeader.split(" ")[1]
// Check against KeyTable
const keyRecord = await Database.use((tx) =>
tx
.select({
id: KeyTable.id,
workspaceID: KeyTable.workspaceID,
})
.from(KeyTable)
.where(eq(KeyTable.key, apiKey))
.then((rows) => rows[0]),
)
if (!keyRecord)
return Response.json(
{
error: {
message: "Invalid API key.",
type: "invalid_request_error",
param: null,
code: "unauthorized",
},
},
{ status: 401 },
)
/*
return await Actor.provide("system", { workspaceID: keyRecord.workspaceID }, async () => {
try {
// Check balance
const customer = await Billing.get()
if (customer.balance <= 0) {
return Response.json(
{
error: {
message: "Insufficient balance",
type: "insufficient_quota",
param: null,
code: "insufficient_quota",
},
},
{ status: 401 },
)
}
const body = await input.request.json<ChatCompletionCreateParamsBase>()
const model = SUPPORTED_MODELS[body.model as keyof typeof SUPPORTED_MODELS]?.model()
if (!model) throw new Error(`Unsupported model: ${body.model}`)
const requestBody = transformOpenAIRequestToAiSDK()
return body.stream ? await handleStream() : await handleGenerate()
async function handleStream() {
const result = await model.doStream({
...requestBody,
})
const encoder = new TextEncoder()
const stream = new ReadableStream({
async start(controller) {
const id = `chatcmpl-${Date.now()}`
const created = Math.floor(Date.now() / 1000)
try {
for await (const chunk of result.stream) {
console.log("!!! CHUNK !!! : " + chunk.type)
switch (chunk.type) {
case "text-delta": {
const data = {
id,
object: "chat.completion.chunk",
created,
model: body.model,
choices: [
{
index: 0,
delta: {
content: chunk.delta,
},
finish_reason: null,
},
],
}
controller.enqueue(encoder.encode(`data: ${JSON.stringify(data)}\n\n`))
break
}
case "reasoning-delta": {
const data = {
id,
object: "chat.completion.chunk",
created,
model: body.model,
choices: [
{
index: 0,
delta: {
reasoning_content: chunk.delta,
},
finish_reason: null,
},
],
}
controller.enqueue(encoder.encode(`data: ${JSON.stringify(data)}\n\n`))
break
}
case "tool-call": {
const data = {
id,
object: "chat.completion.chunk",
created,
model: body.model,
choices: [
{
index: 0,
delta: {
tool_calls: [
{
index: 0,
id: chunk.toolCallId,
type: "function",
function: {
name: chunk.toolName,
arguments: chunk.input,
},
},
],
},
finish_reason: null,
},
],
}
controller.enqueue(encoder.encode(`data: ${JSON.stringify(data)}\n\n`))
break
}
case "error": {
const data = {
id,
object: "chat.completion.chunk",
created,
model: body.model,
choices: [
{
index: 0,
delta: {},
finish_reason: "stop",
},
],
error: {
message: typeof chunk.error === "string" ? chunk.error : chunk.error,
type: "server_error",
},
}
controller.enqueue(encoder.encode(`data: ${JSON.stringify(data)}\n\n`))
controller.enqueue(encoder.encode("data: [DONE]\n\n"))
controller.close()
break
}
case "finish": {
const data = {
id,
object: "chat.completion.chunk",
created,
model: body.model,
choices: [
{
index: 0,
delta: {},
finish_reason:
{
stop: "stop",
length: "length",
"content-filter": "content_filter",
"tool-calls": "tool_calls",
error: "stop",
other: "stop",
unknown: "stop",
}[chunk.finishReason] || "stop",
},
],
usage: {
prompt_tokens: chunk.usage.inputTokens,
completion_tokens: chunk.usage.outputTokens,
total_tokens: chunk.usage.totalTokens,
completion_tokens_details: {
reasoning_tokens: chunk.usage.reasoningTokens,
},
prompt_tokens_details: {
cached_tokens: chunk.usage.cachedInputTokens,
},
},
}
await trackUsage(body.model, chunk.usage, chunk.providerMetadata)
controller.enqueue(encoder.encode(`data: ${JSON.stringify(data)}\n\n`))
controller.enqueue(encoder.encode("data: [DONE]\n\n"))
controller.close()
break
}
//case "stream-start":
//case "response-metadata":
case "text-start":
case "text-end":
case "reasoning-start":
case "reasoning-end":
case "tool-input-start":
case "tool-input-delta":
case "tool-input-end":
case "raw":
default:
// Log unknown chunk types for debugging
console.warn(`Unknown chunk type: ${(chunk as any).type}`)
break
}
}
} catch (error) {
controller.error(error)
}
},
})
return new Response(stream, {
headers: {
"Content-Type": "text/plain; charset=utf-8",
"Cache-Control": "no-cache",
Connection: "keep-alive",
},
})
}
async function handleGenerate() {
const response = await model.doGenerate({
...requestBody,
})
await trackUsage(body.model, response.usage, response.providerMetadata)
return c.json({
id: `chatcmpl-${Date.now()}`,
object: "chat.completion" as const,
created: Math.floor(Date.now() / 1000),
model: body.model,
choices: [
{
index: 0,
message: {
role: "assistant" as const,
content: response.content?.find((c) => c.type === "text")?.text ?? "",
reasoning_content: response.content?.find((c) => c.type === "reasoning")?.text,
tool_calls: response.content
?.filter((c) => c.type === "tool-call")
.map((toolCall) => ({
id: toolCall.toolCallId,
type: "function" as const,
function: {
name: toolCall.toolName,
arguments: toolCall.input,
},
})),
},
finish_reason:
(
{
stop: "stop",
length: "length",
"content-filter": "content_filter",
"tool-calls": "tool_calls",
error: "stop",
other: "stop",
unknown: "stop",
} as const
)[response.finishReason] || "stop",
},
],
usage: {
prompt_tokens: response.usage?.inputTokens,
completion_tokens: response.usage?.outputTokens,
total_tokens: response.usage?.totalTokens,
completion_tokens_details: {
reasoning_tokens: response.usage?.reasoningTokens,
},
prompt_tokens_details: {
cached_tokens: response.usage?.cachedInputTokens,
},
},
})
}
function transformOpenAIRequestToAiSDK() {
const prompt = transformMessages()
const tools = transformTools()
return {
prompt,
maxOutputTokens: body.max_tokens ?? body.max_completion_tokens ?? undefined,
temperature: body.temperature ?? undefined,
topP: body.top_p ?? undefined,
frequencyPenalty: body.frequency_penalty ?? undefined,
presencePenalty: body.presence_penalty ?? undefined,
providerOptions: body.reasoning_effort
? {
anthropic: {
reasoningEffort: body.reasoning_effort,
},
}
: undefined,
stopSequences: (typeof body.stop === "string" ? [body.stop] : body.stop) ?? undefined,
responseFormat: (() => {
if (!body.response_format) return { type: "text" as const }
if (body.response_format.type === "json_schema")
return {
type: "json" as const,
schema: body.response_format.json_schema.schema,
name: body.response_format.json_schema.name,
description: body.response_format.json_schema.description,
}
if (body.response_format.type === "json_object") return { type: "json" as const }
throw new Error("Unsupported response format")
})(),
seed: body.seed ?? undefined,
tools: tools.tools,
toolChoice: tools.toolChoice,
}
function transformTools() {
const { tools, tool_choice } = body
if (!tools || tools.length === 0) {
return { tools: undefined, toolChoice: undefined }
}
const aiSdkTools = tools.map((tool) => {
return {
type: tool.type,
name: tool.function.name,
description: tool.function.description,
inputSchema: tool.function.parameters!,
}
})
let aiSdkToolChoice
if (tool_choice == null) {
aiSdkToolChoice = undefined
} else if (tool_choice === "auto") {
aiSdkToolChoice = { type: "auto" as const }
} else if (tool_choice === "none") {
aiSdkToolChoice = { type: "none" as const }
} else if (tool_choice === "required") {
aiSdkToolChoice = { type: "required" as const }
} else if (tool_choice.type === "function") {
aiSdkToolChoice = {
type: "tool" as const,
toolName: tool_choice.function.name,
}
}
return { tools: aiSdkTools, toolChoice: aiSdkToolChoice }
}
function transformMessages() {
const { messages } = body
const prompt: LanguageModelV2Prompt = []
for (const message of messages) {
switch (message.role) {
case "system": {
prompt.push({
role: "system",
content: message.content as string,
})
break
}
case "user": {
if (typeof message.content === "string") {
prompt.push({
role: "user",
content: [{ type: "text", text: message.content }],
})
} else {
const content = message.content.map((part) => {
switch (part.type) {
case "text":
return { type: "text" as const, text: part.text }
case "image_url":
return {
type: "file" as const,
mediaType: "image/jpeg" as const,
data: part.image_url.url,
}
default:
throw new Error(`Unsupported content part type: ${(part as any).type}`)
}
})
prompt.push({
role: "user",
content,
})
}
break
}
case "assistant": {
const content: Array<
| { type: "text"; text: string }
| {
type: "tool-call"
toolCallId: string
toolName: string
input: any
}
> = []
if (message.content) {
content.push({
type: "text",
text: message.content as string,
})
}
if (message.tool_calls) {
for (const toolCall of message.tool_calls) {
content.push({
type: "tool-call",
toolCallId: toolCall.id,
toolName: toolCall.function.name,
input: JSON.parse(toolCall.function.arguments),
})
}
}
prompt.push({
role: "assistant",
content,
})
break
}
case "tool": {
prompt.push({
role: "tool",
content: [
{
type: "tool-result",
toolName: "placeholder",
toolCallId: message.tool_call_id,
output: {
type: "text",
value: message.content as string,
},
},
],
})
break
}
default: {
throw new Error(`Unsupported message role: ${message.role}`)
}
}
}
return prompt
}
}
async function trackUsage(model: string, usage: LanguageModelUsage, providerMetadata?: ProviderMetadata) {
const modelData = SUPPORTED_MODELS[model as keyof typeof SUPPORTED_MODELS]
if (!modelData) throw new Error(`Unsupported model: ${model}`)
const inputTokens = usage.inputTokens ?? 0
const outputTokens = usage.outputTokens ?? 0
const reasoningTokens = usage.reasoningTokens ?? 0
const cacheReadTokens = usage.cachedInputTokens ?? 0
const cacheWriteTokens =
providerMetadata?.["anthropic"]?.["cacheCreationInputTokens"] ??
// @ts-expect-error
providerMetadata?.["bedrock"]?.["usage"]?.["cacheWriteInputTokens"] ??
0
const inputCost = modelData.input * inputTokens
const outputCost = modelData.output * outputTokens
const reasoningCost = modelData.reasoning * reasoningTokens
const cacheReadCost = modelData.cacheRead * cacheReadTokens
const cacheWriteCost = modelData.cacheWrite * cacheWriteTokens
const costInCents = (inputCost + outputCost + reasoningCost + cacheReadCost + cacheWriteCost) * 100
await Billing.consume({
model,
inputTokens,
outputTokens,
reasoningTokens,
cacheReadTokens,
cacheWriteTokens,
costInCents,
})
await Database.use((tx) =>
tx
.update(KeyTable)
.set({ timeUsed: sql`now()` })
.where(eq(KeyTable.id, keyRecord.id)),
)
}
} catch (error: any) {
return Response.json({ error: { message: error.message } }, { status: 500 })
}
})
*/
}

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@@ -0,0 +1,73 @@
import { Resource } from "sst"
import { Billing } from "@opencode/cloud-core/billing.js"
import type { APIEvent } from "@solidjs/start/server"
import { Database, eq, sql } from "@opencode/cloud-core/drizzle/index.js"
import { BillingTable, PaymentTable } from "@opencode/cloud-core/schema/billing.sql.js"
import { Identifier } from "@opencode/cloud-core/identifier.js"
import { centsToMicroCents } from "@opencode/cloud-core/util/price.js"
import { Actor } from "@opencode/cloud-core/actor.js"
export async function POST(input: APIEvent) {
const body = await Billing.stripe().webhooks.constructEventAsync(
await input.request.text(),
input.request.headers.get("stripe-signature")!,
Resource.STRIPE_WEBHOOK_SECRET.value,
)
console.log(body.type, JSON.stringify(body, null, 2))
if (body.type === "checkout.session.completed") {
const workspaceID = body.data.object.metadata?.workspaceID
const customerID = body.data.object.customer as string
const paymentID = body.data.object.payment_intent as string
const amount = body.data.object.amount_total
if (!workspaceID) throw new Error("Workspace ID not found")
if (!customerID) throw new Error("Customer ID not found")
if (!amount) throw new Error("Amount not found")
if (!paymentID) throw new Error("Payment ID not found")
await Actor.provide("system", { workspaceID }, async () => {
const customer = await Billing.get()
if (customer?.customerID && customer.customerID !== customerID) throw new Error("Customer ID mismatch")
// set customer metadata
if (!customer?.customerID) {
await Billing.stripe().customers.update(customerID, {
metadata: {
workspaceID,
},
})
}
// get payment method for the payment intent
const paymentIntent = await Billing.stripe().paymentIntents.retrieve(paymentID, {
expand: ["payment_method"],
})
const paymentMethod = paymentIntent.payment_method
if (!paymentMethod || typeof paymentMethod === "string") throw new Error("Payment method not expanded")
await Database.transaction(async (tx) => {
await tx
.update(BillingTable)
.set({
balance: sql`${BillingTable.balance} + ${centsToMicroCents(amount)}`,
customerID,
paymentMethodID: paymentMethod.id,
paymentMethodLast4: paymentMethod.card!.last4,
})
.where(eq(BillingTable.workspaceID, workspaceID))
await tx.insert(PaymentTable).values({
workspaceID,
id: Identifier.create("payment"),
amount: centsToMicroCents(amount),
paymentID,
customerID,
})
})
})
}
console.log("finished handling")
return Response.json("ok", { status: 200 })
}

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@@ -123,7 +123,15 @@ export const console = new sst.cloudflare.x.StaticSite("Console", {
*/
new sst.x.DevCommand("Solid", {
link: [database],
link: [
database,
AUTH_API_URL,
STRIPE_WEBHOOK_SECRET,
STRIPE_SECRET_KEY,
ANTHROPIC_API_KEY,
OPENAI_API_KEY,
ZHIPU_API_KEY,
],
dev: {
directory: "cloud/app",
command: "bun dev",