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fix: adjust GLM-4.6-turbo max output tokens to prevent context limit errors (#8822)

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Co-authored-by: Roo Code <roomote@roocode.com>
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roomote[bot] 2025-10-25 14:08:27 -04:00 • committed by GitHub
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commit 98b8d5b005
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4 changed files with 29 additions and 13 deletions
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16
packages/types/src/providers/chutes.ts
View file

@ -88,7 +88,8 @@ export const chutesModels = {
supportsPromptCache: false,
inputPrice: 0.23,
outputPrice: 0.9,
description: "DeepSeek‑V3.1‑Terminus is an update to V3.1 that improves language consistency by reducing CN/EN mix‑ups and eliminating random characters, while strengthening agent capabilities with notably better Code Agent and Search Agent performance.",
description:
"DeepSeek‑V3.1‑Terminus is an update to V3.1 that improves language consistency by reducing CN/EN mix‑ups and eliminating random characters, while strengthening agent capabilities with notably better Code Agent and Search Agent performance.",
},
"deepseek-ai/DeepSeek-V3.1-turbo": {
maxTokens: 32768,
@ -97,7 +98,8 @@ export const chutesModels = {
supportsPromptCache: false,
inputPrice: 1.0,
outputPrice: 3.0,
description: "DeepSeek-V3.1-turbo is an FP8, speculative-decoding turbo variant optimized for ultra-fast single-shot queries (~200 TPS), with outputs close to the originals and solid function calling/reasoning/structured output, priced at $1/M input and $3/M output tokens, using 2× quota per request and not intended for bulk workloads.",
description:
"DeepSeek-V3.1-turbo is an FP8, speculative-decoding turbo variant optimized for ultra-fast single-shot queries (~200 TPS), with outputs close to the originals and solid function calling/reasoning/structured output, priced at $1/M input and $3/M output tokens, using 2× quota per request and not intended for bulk workloads.",
},
"deepseek-ai/DeepSeek-V3.2-Exp": {
maxTokens: 163840,
@ -106,7 +108,8 @@ export const chutesModels = {
supportsPromptCache: false,
inputPrice: 0.25,
outputPrice: 0.35,
description: "DeepSeek-V3.2-Exp is an experimental LLM that introduces DeepSeek Sparse Attention to improve long‑context training and inference efficiency while maintaining performance comparable to V3.1‑Terminus.",
description:
"DeepSeek-V3.2-Exp is an experimental LLM that introduces DeepSeek Sparse Attention to improve long‑context training and inference efficiency while maintaining performance comparable to V3.1‑Terminus.",
},
"unsloth/Llama-3.3-70B-Instruct": {
maxTokens: 32768, // From Groq
@ -397,8 +400,9 @@ export const chutesModels = {
contextWindow: 262144,
supportsImages: true,
supportsPromptCache: false,
inputPrice: 0.1600,
outputPrice: 0.6500,
description: "Qwen3‑VL‑235B‑A22B‑Thinking is an open‑weight MoE vision‑language model (235B total, ~22B activated) optimized for deliberate multi‑step reasoning with strong text‑image‑video understanding and long‑context capabilities.",
inputPrice: 0.16,
outputPrice: 0.65,
description:
"Qwen3‑VL‑235B‑A22B‑Thinking is an open‑weight MoE vision‑language model (235B total, ~22B activated) optimized for deliberate multi‑step reasoning with strong text‑image‑video understanding and long‑context capabilities.",
},
} as const satisfies Record<string, ModelInfo>

5
src/api/providers/__tests__/chutes.spec.ts
View file

@ -460,10 +460,13 @@ describe("ChutesHandler", () => {
const messageGenerator = handlerWithModel.createMessage(systemPrompt, messages)
await messageGenerator.next()
// Centralized 20% cap should apply to OpenAI-compatible providers like Chutes
const expectedMaxTokens = Math.min(modelInfo.maxTokens, Math.ceil(modelInfo.contextWindow * 0.2))
expect(mockCreate).toHaveBeenCalledWith(
expect.objectContaining({
model: modelId,
max_tokens: modelInfo.maxTokens,
max_tokens: expectedMaxTokens,
temperature: 0.5,
messages: expect.arrayContaining([{ role: "system", content: systemPrompt }]),
stream: true,

5
src/api/providers/__tests__/zai.spec.ts
View file

@ -280,10 +280,13 @@ describe("ZAiHandler", () => {
const messageGenerator = handlerWithModel.createMessage(systemPrompt, messages)
await messageGenerator.next()
// Centralized 20% cap should apply to OpenAI-compatible providers like Z AI
const expectedMaxTokens = Math.min(modelInfo.maxTokens, Math.ceil(modelInfo.contextWindow * 0.2))
expect(mockCreate).toHaveBeenCalledWith(
expect.objectContaining({
model: modelId,
max_tokens: modelInfo.maxTokens,
max_tokens: expectedMaxTokens,
temperature: ZAI_DEFAULT_TEMPERATURE,
messages: expect.arrayContaining([{ role: "system", content: systemPrompt }]),
stream: true,

16
src/api/providers/base-openai-compatible-provider.ts
View file

@ -3,7 +3,7 @@ import OpenAI from "openai"
import type { ModelInfo } from "@roo-code/types"
import type { ApiHandlerOptions } from "../../shared/api"
import { type ApiHandlerOptions, getModelMaxOutputTokens } from "../../shared/api"
import { ApiStream } from "../transform/stream"
import { convertToOpenAiMessages } from "../transform/openai-format"
@ -69,10 +69,16 @@ export abstract class BaseOpenAiCompatibleProvider<ModelName extends string>
metadata?: ApiHandlerCreateMessageMetadata,
requestOptions?: OpenAI.RequestOptions,
) {
const {
id: model,
info: { maxTokens: max_tokens },
} = this.getModel()
const { id: model, info } = this.getModel()
// Centralized cap: clamp to 20% of the context window (unless provider-specific exceptions apply)
const max_tokens =
getModelMaxOutputTokens({
modelId: model,
model: info,
settings: this.options,
format: "openai",
}) ?? undefined
const temperature = this.options.modelTemperature ?? this.defaultTemperature