openclaw/extensions/opencode-go/provider-catalog.ts

import type { ModelCatalogEntry } from "openclaw/plugin-sdk/agent-runtime";
import type { ProviderRuntimeModel } from "openclaw/plugin-sdk/plugin-entry";
import { normalizeModelCompat } from "openclaw/plugin-sdk/provider-model-shared";

const PROVIDER_ID = "opencode-go";

const OPENCODE_GO_OPENAI_BASE_URL = "https://opencode.ai/zen/go/v1";
const OPENCODE_GO_ANTHROPIC_BASE_URL = "https://opencode.ai/zen/go";
const OPENCODE_GO_KIMI_NO_REASONING_MODEL_IDS = new Set(["kimi-k2.5", "kimi-k2.6"]);

const OPENCODE_GO_MODELS = (
  [
    {
      id: "deepseek-v4-pro",
      name: "DeepSeek V4 Pro",
      api: "openai-completions",
      provider: PROVIDER_ID,
      baseUrl: OPENCODE_GO_OPENAI_BASE_URL,
      reasoning: true,
      input: ["text"],
      cost: {
        input: 1.74,
        output: 3.48,
        cacheRead: 0.145,
        cacheWrite: 0,
      },
      contextWindow: 1_000_000,
      maxTokens: 384_000,
      compat: {
        supportsUsageInStreaming: true,
        supportsReasoningEffort: true,
        maxTokensField: "max_tokens",
      },
    },
    {
      id: "deepseek-v4-flash",
      name: "DeepSeek V4 Flash",
      api: "openai-completions",
      provider: PROVIDER_ID,
      baseUrl: OPENCODE_GO_OPENAI_BASE_URL,
      reasoning: true,
      input: ["text"],
      cost: {
        input: 0.14,
        output: 0.28,
        cacheRead: 0.028,
        cacheWrite: 0,
      },
      contextWindow: 1_000_000,
      maxTokens: 384_000,
      compat: {
        supportsUsageInStreaming: true,
        supportsReasoningEffort: true,
        maxTokensField: "max_tokens",
      },
    },
    {
      id: "glm-5",
      name: "GLM-5",
      api: "openai-completions",
      provider: PROVIDER_ID,
      baseUrl: OPENCODE_GO_OPENAI_BASE_URL,
      reasoning: true,
      input: ["text"],
      cost: {
        input: 1,
        output: 3.2,
        cacheRead: 0.2,
        cacheWrite: 0,
      },
      contextWindow: 202_752,
      maxTokens: 32_768,
    },
    {
      id: "glm-5.1",
      name: "GLM-5.1",
      api: "openai-completions",
      provider: PROVIDER_ID,
      baseUrl: OPENCODE_GO_OPENAI_BASE_URL,
      reasoning: true,
      input: ["text"],
      cost: {
        input: 1.4,
        output: 4.4,
        cacheRead: 0.26,
        cacheWrite: 0,
      },
      contextWindow: 202_752,
      maxTokens: 32_768,
    },
    {
      id: "kimi-k2.5",
      name: "Kimi K2.5",
      api: "openai-completions",
      provider: PROVIDER_ID,
      baseUrl: OPENCODE_GO_OPENAI_BASE_URL,
      reasoning: true,
      input: ["text", "image"],
      cost: {
        input: 0.6,
        output: 3,
        cacheRead: 0.1,
        cacheWrite: 0,
      },
      contextWindow: 262_144,
      maxTokens: 65_536,
    },
    {
      id: "kimi-k2.6",
      name: "Kimi K2.6",
      api: "openai-completions",
      provider: PROVIDER_ID,
      baseUrl: OPENCODE_GO_OPENAI_BASE_URL,
      reasoning: true,
      input: ["text", "image"],
      cost: {
        input: 0.95,
        output: 4,
        cacheRead: 0.16,
        cacheWrite: 0,
      },
      contextWindow: 262_144,
      maxTokens: 65_536,
    },
    {
      id: "mimo-v2.5",
      name: "MiMo V2.5",
      api: "openai-completions",
      provider: PROVIDER_ID,
      baseUrl: OPENCODE_GO_OPENAI_BASE_URL,
      reasoning: true,
      input: ["text", "image"],
      cost: {
        input: 0.4,
        output: 2,
        cacheRead: 0.08,
        cacheWrite: 0,
      },
      contextWindow: 1_000_000,
      maxTokens: 128_000,
    },
    {
      id: "mimo-v2.5-pro",
      name: "MiMo V2.5 Pro",
      api: "openai-completions",
      provider: PROVIDER_ID,
      baseUrl: OPENCODE_GO_OPENAI_BASE_URL,
      reasoning: true,
      input: ["text"],
      cost: {
        input: 1,
        output: 3,
        cacheRead: 0.2,
        cacheWrite: 0,
      },
      contextWindow: 1_048_576,
      maxTokens: 128_000,
    },
    {
      id: "minimax-m2.5",
      name: "MiniMax M2.5",
      api: "anthropic-messages",
      provider: PROVIDER_ID,
      baseUrl: OPENCODE_GO_ANTHROPIC_BASE_URL,
      reasoning: true,
      input: ["text"],
      cost: {
        input: 0.3,
        output: 1.2,
        cacheRead: 0.03,
        cacheWrite: 0,
      },
      contextWindow: 204_800,
      maxTokens: 65_536,
    },
    {
      id: "minimax-m2.7",
      name: "MiniMax M2.7",
      api: "openai-completions",
      provider: PROVIDER_ID,
      baseUrl: OPENCODE_GO_OPENAI_BASE_URL,
      reasoning: true,
      input: ["text"],
      cost: {
        input: 0.3,
        output: 1.2,
        cacheRead: 0.06,
        cacheWrite: 0,
      },
      contextWindow: 204_800,
      maxTokens: 131_072,
    },
    {
      id: "qwen3.5-plus",
      name: "Qwen3.5 Plus",
      api: "openai-completions",
      provider: PROVIDER_ID,
      baseUrl: OPENCODE_GO_OPENAI_BASE_URL,
      compat: { thinkingFormat: "qwen" },
      reasoning: true,
      input: ["text", "image"],
      cost: {
        input: 0.2,
        output: 1.2,
        cacheRead: 0.02,
        cacheWrite: 0.25,
      },
      contextWindow: 262_144,
      maxTokens: 65_536,
    },
    {
      id: "qwen3.6-plus",
      name: "Qwen3.6 Plus",
      api: "openai-completions",
      provider: PROVIDER_ID,
      baseUrl: OPENCODE_GO_OPENAI_BASE_URL,
      compat: { thinkingFormat: "qwen" },
      reasoning: true,
      input: ["text", "image"],
      cost: {
        input: 0.5,
        output: 3,
        cacheRead: 0.05,
        cacheWrite: 0.625,
      },
      contextWindow: 262_144,
      maxTokens: 65_536,
    },
  ] satisfies ProviderRuntimeModel[]
).map((model) => normalizeModelCompat(model));

export function listOpencodeGoModelCatalogEntries(): ModelCatalogEntry[] {
  return OPENCODE_GO_MODELS.map((model) => ({
    provider: model.provider,
    id: model.id,
    name: model.name,
    reasoning: model.reasoning,
    input: model.input,
    contextWindow: model.contextWindow,
  }));
}

export function resolveOpencodeGoModel(modelId: string): ProviderRuntimeModel | undefined {
  const normalizedModelId = modelId.trim().toLowerCase();
  return OPENCODE_GO_MODELS.find((model) => model.id === normalizedModelId);
}

export function isOpencodeGoKimiNoReasoningModelId(modelId: unknown): boolean {
  return (
    typeof modelId === "string" &&
    OPENCODE_GO_KIMI_NO_REASONING_MODEL_IDS.has(modelId.trim().toLowerCase())
  );
}

export function normalizeOpencodeGoResolvedModel(
  model: ProviderRuntimeModel,
): ProviderRuntimeModel | undefined {
  if (!isOpencodeGoKimiNoReasoningModelId(model.id)) {
    return undefined;
  }
  const compat =
    model.compat && typeof model.compat === "object" && !Array.isArray(model.compat)
      ? model.compat
      : undefined;
  if (!model.reasoning && !compat?.supportsReasoningEffort) {
    return undefined;
  }
  return {
    ...model,
    reasoning: false,
    compat: {
      ...compat,
      supportsReasoningEffort: false,
    },
  };
}

function normalizeBaseUrl(baseUrl: string | undefined): string {
  return (baseUrl ?? "").trim().replace(/\/+$/, "");
}

export function normalizeOpencodeGoBaseUrl(params: {
  api?: string | null;
  baseUrl?: string;
}): string | undefined {
  const normalized = normalizeBaseUrl(params.baseUrl);
  if (!normalized) {
    return undefined;
  }
  if (normalized === OPENCODE_GO_OPENAI_BASE_URL) {
    return OPENCODE_GO_OPENAI_BASE_URL;
  }
  if (normalized === OPENCODE_GO_ANTHROPIC_BASE_URL) {
    return OPENCODE_GO_ANTHROPIC_BASE_URL;
  }
  if (normalized === "https://opencode.ai/go") {
    return OPENCODE_GO_ANTHROPIC_BASE_URL;
  }
  if (normalized === "https://opencode.ai/go/v1") {
    return params.api === "anthropic-messages"
      ? OPENCODE_GO_ANTHROPIC_BASE_URL
      : OPENCODE_GO_OPENAI_BASE_URL;
  }
  return undefined;
}