mirror of
https://github.com/RooVetGit/Roo-Code.git
synced 2026-09-07 08:26:51 +00:00
feat: add support for custom Anthropic-compatible models
- Allow custom model IDs in AnthropicModelId type - Update AnthropicHandler.getModel() to handle unknown models with sensible defaults - Modify createMessage() to support custom models with prompt caching - Add comprehensive tests for custom model support - Enables third-party Anthropic-compatible providers (MinMax, etc.) - Fixes #9093
This commit is contained in:
Roo Code
parent
6e3e8a96ef
commit
fbb95f0fd0
3 changed files with 273 additions and 104 deletions
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@ -2,8 +2,9 @@ import type { ModelInfo } from "../model.js"
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// https://docs.anthropic.com/en/docs/about-claude/models
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export type AnthropicModelId = keyof typeof anthropicModels
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export const anthropicDefaultModelId: AnthropicModelId = "claude-sonnet-4-5"
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// Allow custom model IDs in addition to known models
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export type AnthropicModelId = keyof typeof anthropicModels | string
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export const anthropicDefaultModelId = "claude-sonnet-4-5" as const
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export const anthropicModels = {
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"claude-sonnet-4-5": {
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@ -288,5 +288,105 @@ describe("AnthropicHandler", () => {
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expect(model.info.inputPrice).toBe(6.0)
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expect(model.info.outputPrice).toBe(22.5)
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})
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it("should handle custom model ID not in predefined list", () => {
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const handler = new AnthropicHandler({
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apiKey: "test-api-key",
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apiModelId: "custom-claude-model",
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})
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const model = handler.getModel()
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expect(model.id).toBe("custom-claude-model")
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expect(model.info).toBeDefined()
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// Should have sensible defaults
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expect(model.info.maxTokens).toBe(8192)
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expect(model.info.contextWindow).toBe(200000)
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expect(model.info.supportsImages).toBe(true)
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expect(model.info.supportsPromptCache).toBe(true)
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})
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it("should handle third-party Anthropic-compatible models", () => {
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const handler = new AnthropicHandler({
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apiKey: "test-api-key",
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apiModelId: "MinMax-M2",
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})
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const model = handler.getModel()
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expect(model.id).toBe("MinMax-M2")
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expect(model.info).toBeDefined()
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expect(model.info.maxTokens).toBe(8192)
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expect(model.info.contextWindow).toBe(200000)
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})
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it("should handle custom Claude model with hyphen format", () => {
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const handler = new AnthropicHandler({
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apiKey: "test-api-key",
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apiModelId: "claude-haiku-4-5",
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})
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const model = handler.getModel()
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expect(model.id).toBe("claude-haiku-4-5")
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expect(model.info).toBeDefined()
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expect(model.info.supportsPromptCache).toBe(true)
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})
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it("should handle custom Claude model with date suffix", () => {
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const handler = new AnthropicHandler({
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apiKey: "test-api-key",
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apiModelId: "claude-sonnet-4-5-20250929",
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})
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const model = handler.getModel()
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expect(model.id).toBe("claude-sonnet-4-5-20250929")
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expect(model.info).toBeDefined()
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expect(model.info.supportsImages).toBe(true)
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})
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})
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describe("createMessage with custom models", () => {
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const systemPrompt = "You are a helpful assistant."
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it("should handle custom model with prompt caching", async () => {
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const customHandler = new AnthropicHandler({
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apiKey: "test-api-key",
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apiModelId: "custom-anthropic-model",
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})
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const stream = customHandler.createMessage(systemPrompt, [
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{
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role: "user",
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content: [{ type: "text" as const, text: "Test message" }],
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},
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])
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const chunks: any[] = []
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for await (const chunk of stream) {
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chunks.push(chunk)
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}
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// Should still process the stream correctly
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expect(chunks.length).toBeGreaterThan(0)
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expect(mockCreate).toHaveBeenCalledWith(
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expect.objectContaining({
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model: "custom-anthropic-model",
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stream: true,
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}),
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expect.objectContaining({
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headers: { "anthropic-beta": "prompt-caching-2024-07-31" },
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}),
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)
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})
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it("should use appropriate defaults for unknown model", async () => {
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const customHandler = new AnthropicHandler({
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apiKey: "test-api-key",
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apiModelId: "third-party-claude-compatible",
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})
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await customHandler.completePrompt("Test prompt")
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expect(mockCreate).toHaveBeenCalledWith(
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expect.objectContaining({
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model: "third-party-claude-compatible",
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max_tokens: 8192,
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}),
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)
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})
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})
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})
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@ -43,7 +43,7 @@ export class AnthropicHandler extends BaseProvider implements SingleCompletionHa
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): ApiStream {
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let stream: AnthropicStream<Anthropic.Messages.RawMessageStreamEvent>
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const cacheControl: CacheControlEphemeral = { type: "ephemeral" }
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let { id: modelId, betas = [], maxTokens, temperature, reasoning: thinking } = this.getModel()
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let { id: modelId, betas = [], maxTokens, temperature, reasoning: thinking, info } = this.getModel()
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// Add 1M context beta flag if enabled for Claude Sonnet 4 and 4.5
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if (
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@ -53,98 +53,144 @@ export class AnthropicHandler extends BaseProvider implements SingleCompletionHa
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betas.push("context-1m-2025-08-07")
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}
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switch (modelId) {
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case "claude-sonnet-4-5":
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case "claude-sonnet-4-20250514":
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case "claude-opus-4-1-20250805":
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case "claude-opus-4-20250514":
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case "claude-3-7-sonnet-20250219":
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case "claude-3-5-sonnet-20241022":
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case "claude-3-5-haiku-20241022":
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case "claude-3-opus-20240229":
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case "claude-haiku-4-5-20251001":
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case "claude-3-haiku-20240307": {
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/**
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* The latest message will be the new user message, one before
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* will be the assistant message from a previous request, and
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* the user message before that will be a previously cached user
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* message. So we need to mark the latest user message as
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* ephemeral to cache it for the next request, and mark the
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* second to last user message as ephemeral to let the server
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* know the last message to retrieve from the cache for the
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* current request.
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*/
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const userMsgIndices = messages.reduce(
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(acc, msg, index) => (msg.role === "user" ? [...acc, index] : acc),
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[] as number[],
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)
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// Check if this is a known model that supports prompt caching
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const supportsPromptCache = info.supportsPromptCache ?? false
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const lastUserMsgIndex = userMsgIndices[userMsgIndices.length - 1] ?? -1
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const secondLastMsgUserIndex = userMsgIndices[userMsgIndices.length - 2] ?? -1
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// For custom models, check if they support prompt caching
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if (supportsPromptCache) {
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switch (modelId) {
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case "claude-sonnet-4-5":
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case "claude-sonnet-4-20250514":
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case "claude-opus-4-1-20250805":
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case "claude-opus-4-20250514":
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case "claude-3-7-sonnet-20250219":
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case "claude-3-5-sonnet-20241022":
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case "claude-3-5-haiku-20241022":
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case "claude-3-opus-20240229":
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case "claude-haiku-4-5-20251001":
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case "claude-3-haiku-20240307": {
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/**
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* The latest message will be the new user message, one before
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* will be the assistant message from a previous request, and
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* the user message before that will be a previously cached user
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* message. So we need to mark the latest user message as
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* ephemeral to cache it for the next request, and mark the
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* second to last user message as ephemeral to let the server
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* know the last message to retrieve from the cache for the
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* current request.
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*/
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const userMsgIndices = messages.reduce(
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(acc, msg, index) => (msg.role === "user" ? [...acc, index] : acc),
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[] as number[],
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)
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stream = await this.client.messages.create(
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{
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model: modelId,
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max_tokens: maxTokens ?? ANTHROPIC_DEFAULT_MAX_TOKENS,
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temperature,
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thinking,
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// Setting cache breakpoint for system prompt so new tasks can reuse it.
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system: [{ text: systemPrompt, type: "text", cache_control: cacheControl }],
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messages: messages.map((message, index) => {
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if (index === lastUserMsgIndex || index === secondLastMsgUserIndex) {
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return {
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...message,
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content:
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typeof message.content === "string"
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? [{ type: "text", text: message.content, cache_control: cacheControl }]
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: message.content.map((content, contentIndex) =>
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contentIndex === message.content.length - 1
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? { ...content, cache_control: cacheControl }
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: content,
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),
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const lastUserMsgIndex = userMsgIndices[userMsgIndices.length - 1] ?? -1
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const secondLastMsgUserIndex = userMsgIndices[userMsgIndices.length - 2] ?? -1
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stream = await this.client.messages.create(
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{
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model: modelId,
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max_tokens: maxTokens ?? ANTHROPIC_DEFAULT_MAX_TOKENS,
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temperature,
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thinking,
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// Setting cache breakpoint for system prompt so new tasks can reuse it.
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system: [{ text: systemPrompt, type: "text", cache_control: cacheControl }],
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messages: messages.map((message, index) => {
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if (index === lastUserMsgIndex || index === secondLastMsgUserIndex) {
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return {
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...message,
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content:
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typeof message.content === "string"
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? [{ type: "text", text: message.content, cache_control: cacheControl }]
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: message.content.map((content, contentIndex) =>
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contentIndex === message.content.length - 1
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? { ...content, cache_control: cacheControl }
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: content,
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),
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}
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}
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}
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return message
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}),
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stream: true,
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},
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(() => {
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// prompt caching: https://x.com/alexalbert__/status/1823751995901272068
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// https://github.com/anthropics/anthropic-sdk-typescript?tab=readme-ov-file#default-headers
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// https://github.com/anthropics/anthropic-sdk-typescript/commit/c920b77fc67bd839bfeb6716ceab9d7c9bbe7393
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return message
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}),
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stream: true,
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},
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(() => {
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// prompt caching: https://x.com/alexalbert__/status/1823751995901272068
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// https://github.com/anthropics/anthropic-sdk-typescript?tab=readme-ov-file#default-headers
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// https://github.com/anthropics/anthropic-sdk-typescript/commit/c920b77fc67bd839bfeb6716ceab9d7c9bbe7393
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// Then check for models that support prompt caching
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switch (modelId) {
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case "claude-sonnet-4-5":
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case "claude-sonnet-4-20250514":
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case "claude-opus-4-1-20250805":
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case "claude-opus-4-20250514":
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case "claude-3-7-sonnet-20250219":
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case "claude-3-5-sonnet-20241022":
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case "claude-3-5-haiku-20241022":
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case "claude-3-opus-20240229":
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case "claude-haiku-4-5-20251001":
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case "claude-3-haiku-20240307":
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betas.push("prompt-caching-2024-07-31")
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return { headers: { "anthropic-beta": betas.join(",") } }
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default:
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return undefined
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}
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})(),
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)
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break
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}
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default: {
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stream = (await this.client.messages.create({
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model: modelId,
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max_tokens: maxTokens ?? ANTHROPIC_DEFAULT_MAX_TOKENS,
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temperature,
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system: [{ text: systemPrompt, type: "text" }],
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messages,
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stream: true,
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})) as any
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break
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// Then check for models that support prompt caching
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switch (modelId) {
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case "claude-sonnet-4-5":
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case "claude-sonnet-4-20250514":
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case "claude-opus-4-1-20250805":
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case "claude-opus-4-20250514":
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case "claude-3-7-sonnet-20250219":
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case "claude-3-5-sonnet-20241022":
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case "claude-3-5-haiku-20241022":
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case "claude-3-opus-20240229":
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case "claude-haiku-4-5-20251001":
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case "claude-3-haiku-20240307":
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betas.push("prompt-caching-2024-07-31")
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return { headers: { "anthropic-beta": betas.join(",") } }
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default:
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return undefined
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}
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})(),
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)
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break
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}
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default: {
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// Custom model with prompt caching support
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const userMsgIndices = messages.reduce(
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(acc, msg, index) => (msg.role === "user" ? [...acc, index] : acc),
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[] as number[],
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)
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const lastUserMsgIndex = userMsgIndices[userMsgIndices.length - 1] ?? -1
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const secondLastMsgUserIndex = userMsgIndices[userMsgIndices.length - 2] ?? -1
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stream = await this.client.messages.create(
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{
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model: modelId,
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max_tokens: maxTokens ?? ANTHROPIC_DEFAULT_MAX_TOKENS,
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temperature,
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thinking,
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// Setting cache breakpoint for system prompt so new tasks can reuse it.
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system: [{ text: systemPrompt, type: "text", cache_control: cacheControl }],
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messages: messages.map((message, index) => {
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if (index === lastUserMsgIndex || index === secondLastMsgUserIndex) {
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return {
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...message,
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content:
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typeof message.content === "string"
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? [{ type: "text", text: message.content, cache_control: cacheControl }]
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: message.content.map((content, contentIndex) =>
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contentIndex === message.content.length - 1
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? { ...content, cache_control: cacheControl }
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: content,
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),
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}
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}
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return message
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}),
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stream: true,
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},
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{ headers: { "anthropic-beta": "prompt-caching-2024-07-31" } },
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)
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break
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}
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}
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} else {
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// Models without prompt caching support (or unknown custom models without the flag)
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stream = (await this.client.messages.create({
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model: modelId,
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max_tokens: maxTokens ?? ANTHROPIC_DEFAULT_MAX_TOKENS,
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temperature,
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thinking,
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system: [{ text: systemPrompt, type: "text" }],
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messages,
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stream: true,
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})) as any
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}
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let inputTokens = 0
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@ -249,23 +295,45 @@ export class AnthropicHandler extends BaseProvider implements SingleCompletionHa
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getModel() {
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const modelId = this.options.apiModelId
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let id = modelId && modelId in anthropicModels ? (modelId as AnthropicModelId) : anthropicDefaultModelId
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let info: ModelInfo = anthropicModels[id]
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let id: string
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let info: ModelInfo
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// If 1M context beta is enabled for Claude Sonnet 4 or 4.5, update the model info
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if ((id === "claude-sonnet-4-20250514" || id === "claude-sonnet-4-5") && this.options.anthropicBeta1MContext) {
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// Use the tier pricing for 1M context
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const tier = info.tiers?.[0]
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if (tier) {
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info = {
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...info,
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contextWindow: tier.contextWindow,
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inputPrice: tier.inputPrice,
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outputPrice: tier.outputPrice,
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cacheWritesPrice: tier.cacheWritesPrice,
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cacheReadsPrice: tier.cacheReadsPrice,
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// Check if modelId is a known model
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if (modelId && modelId in anthropicModels) {
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id = modelId as AnthropicModelId
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info = anthropicModels[id as keyof typeof anthropicModels]
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// If 1M context beta is enabled for Claude Sonnet 4 or 4.5, update the model info
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if (
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(id === "claude-sonnet-4-20250514" || id === "claude-sonnet-4-5") &&
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this.options.anthropicBeta1MContext
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) {
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// Use the tier pricing for 1M context
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const tier = info.tiers?.[0]
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if (tier) {
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info = {
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...info,
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contextWindow: tier.contextWindow,
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inputPrice: tier.inputPrice,
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outputPrice: tier.outputPrice,
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cacheWritesPrice: tier.cacheWritesPrice,
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cacheReadsPrice: tier.cacheReadsPrice,
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}
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}
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}
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} else if (modelId) {
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// Custom model - use sensible defaults
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id = modelId
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info = {
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maxTokens: ANTHROPIC_DEFAULT_MAX_TOKENS,
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contextWindow: 200_000, // Default Anthropic context window
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supportsImages: true, // Assume modern capabilities
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supportsPromptCache: true, // Most Anthropic-compatible APIs support caching
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}
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} else {
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// No model specified - use default
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id = anthropicDefaultModelId
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info = anthropicModels[anthropicDefaultModelId]
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}
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const params = getModelParams({
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