opencode/packages/opencode/src/provider/transform.ts

import type { APICallError, ModelMessage } from "ai"
import { unique } from "remeda"
import type { JSONSchema } from "zod/v4/core"
import type { Provider } from "./provider"
import type { ModelsDev } from "./models"
import { iife } from "@/util/iife"

type Modality = NonNullable<ModelsDev.Model["modalities"]>["input"][number]

function mimeToModality(mime: string): Modality | undefined {
  if (mime.startsWith("image/")) return "image"
  if (mime.startsWith("audio/")) return "audio"
  if (mime.startsWith("video/")) return "video"
  if (mime === "application/pdf") return "pdf"
  return undefined
}

export namespace ProviderTransform {
  function isAzureAnthropic(model: Provider.Model): boolean {
    return (
      model.providerID === "azure-cognitive-services" &&
      (model.api.id.includes("claude") || model.api.id.includes("anthropic"))
    )
  }

  function usesAnthropicSDK(model: Provider.Model): boolean {
    return model.api.npm === "@ai-sdk/anthropic" || isAzureAnthropic(model)
  }

  function normalizeMessages(
    msgs: ModelMessage[],
    model: Provider.Model,
    options: Record<string, unknown>,
  ): ModelMessage[] {
    // Strip openai itemId metadata following what codex does
    if (model.api.npm === "@ai-sdk/openai" || options.store === false) {
      msgs = msgs.map((msg) => {
        if (msg.providerOptions) {
          for (const options of Object.values(msg.providerOptions)) {
            if (options && typeof options === "object") {
              delete options["itemId"]
            }
          }
        }
        if (!Array.isArray(msg.content)) {
          return msg
        }
        const content = msg.content.map((part) => {
          if (part.providerOptions) {
            for (const options of Object.values(part.providerOptions)) {
              if (options && typeof options === "object") {
                delete options["itemId"]
              }
            }
          }
          return part
        })
        return { ...msg, content } as typeof msg
      })
    }

    // Anthropic rejects messages with empty content - filter out empty string messages
    // and remove empty text/reasoning parts from array content
    if (usesAnthropicSDK(model)) {
      msgs = msgs
        .map((msg) => {
          if (typeof msg.content === "string") {
            if (msg.content === "") return undefined
            return msg
          }
          if (!Array.isArray(msg.content)) return msg
          const filtered = msg.content.filter((part) => {
            if (part.type === "text" || part.type === "reasoning") {
              return part.text !== ""
            }
            return true
          })
          if (filtered.length === 0) return undefined
          return { ...msg, content: filtered }
        })
        .filter((msg): msg is ModelMessage => msg !== undefined && msg.content !== "")
    }

    if (model.api.id.includes("claude")) {
      return msgs.map((msg) => {
        if ((msg.role === "assistant" || msg.role === "tool") && Array.isArray(msg.content)) {
          msg.content = msg.content.map((part) => {
            if ((part.type === "tool-call" || part.type === "tool-result") && "toolCallId" in part) {
              return {
                ...part,
                toolCallId: part.toolCallId.replace(/[^a-zA-Z0-9_-]/g, "_"),
              }
            }
            return part
          })
        }
        return msg
      })
    }
    if (model.providerID === "mistral" || model.api.id.toLowerCase().includes("mistral")) {
      const result: ModelMessage[] = []
      for (let i = 0; i < msgs.length; i++) {
        const msg = msgs[i]
        const nextMsg = msgs[i + 1]

        if ((msg.role === "assistant" || msg.role === "tool") && Array.isArray(msg.content)) {
          msg.content = msg.content.map((part) => {
            if ((part.type === "tool-call" || part.type === "tool-result") && "toolCallId" in part) {
              // Mistral requires alphanumeric tool call IDs with exactly 9 characters
              const normalizedId = part.toolCallId
                .replace(/[^a-zA-Z0-9]/g, "") // Remove non-alphanumeric characters
                .substring(0, 9) // Take first 9 characters
                .padEnd(9, "0") // Pad with zeros if less than 9 characters

              return {
                ...part,
                toolCallId: normalizedId,
              }
            }
            return part
          })
        }

        result.push(msg)

        // Fix message sequence: tool messages cannot be followed by user messages
        if (msg.role === "tool" && nextMsg?.role === "user") {
          result.push({
            role: "assistant",
            content: [
              {
                type: "text",
                text: "Done.",
              },
            ],
          })
        }
      }
      return result
    }

    if (
      model.capabilities.interleaved &&
      typeof model.capabilities.interleaved === "object" &&
      model.capabilities.interleaved.field === "reasoning_content"
    ) {
      return msgs.map((msg) => {
        if (msg.role === "assistant" && Array.isArray(msg.content)) {
          const reasoningParts = msg.content.filter((part: any) => part.type === "reasoning")
          const reasoningText = reasoningParts.map((part: any) => part.text).join("")

          // Filter out reasoning parts from content
          const filteredContent = msg.content.filter((part: any) => part.type !== "reasoning")

          // Include reasoning_content directly on the message for all assistant messages
          if (reasoningText) {
            return {
              ...msg,
              content: filteredContent,
              providerOptions: {
                ...msg.providerOptions,
                openaiCompatible: {
                  ...(msg.providerOptions as any)?.openaiCompatible,
                  reasoning_content: reasoningText,
                },
              },
            }
          }

          return {
            ...msg,
            content: filteredContent,
          }
        }

        return msg
      })
    }

    return msgs
  }

  function applyCaching(msgs: ModelMessage[], providerID: string): ModelMessage[] {
    const system = msgs.filter((msg) => msg.role === "system").slice(0, 2)
    const final = msgs.filter((msg) => msg.role !== "system").slice(-2)

    const providerOptions = {
      anthropic: {
        cacheControl: { type: "ephemeral" },
      },
      openrouter: {
        cacheControl: { type: "ephemeral" },
      },
      bedrock: {
        cachePoint: { type: "ephemeral" },
      },
      openaiCompatible: {
        cache_control: { type: "ephemeral" },
      },
    }

    for (const msg of unique([...system, ...final])) {
      const shouldUseContentOptions = providerID !== "anthropic" && Array.isArray(msg.content) && msg.content.length > 0

      if (shouldUseContentOptions) {
        const lastContent = msg.content[msg.content.length - 1]
        if (lastContent && typeof lastContent === "object") {
          lastContent.providerOptions = {
            ...lastContent.providerOptions,
            ...providerOptions,
          }
          continue
        }
      }

      msg.providerOptions = {
        ...msg.providerOptions,
        ...providerOptions,
      }
    }

    return msgs
  }

  function unsupportedParts(msgs: ModelMessage[], model: Provider.Model): ModelMessage[] {
    return msgs.map((msg) => {
      if (msg.role !== "user" || !Array.isArray(msg.content)) return msg

      const filtered = msg.content.map((part) => {
        if (part.type !== "file" && part.type !== "image") return part

        // Check for empty base64 image data
        if (part.type === "image") {
          const imageStr = part.image.toString()
          if (imageStr.startsWith("data:")) {
            const match = imageStr.match(/^data:([^;]+);base64,(.*)$/)
            if (match && (!match[2] || match[2].length === 0)) {
              return {
                type: "text" as const,
                text: "ERROR: Image file is empty or corrupted. Please provide a valid image.",
              }
            }
          }
        }

        const mime = part.type === "image" ? part.image.toString().split(";")[0].replace("data:", "") : part.mediaType
        const filename = part.type === "file" ? part.filename : undefined
        const modality = mimeToModality(mime)
        if (!modality) return part
        if (model.capabilities.input[modality]) return part

        const name = filename ? `"${filename}"` : modality
        return {
          type: "text" as const,
          text: `ERROR: Cannot read ${name} (this model does not support ${modality} input). Inform the user.`,
        }
      })

      return { ...msg, content: filtered }
    })
  }

  export function message(msgs: ModelMessage[], model: Provider.Model, options: Record<string, unknown>) {
    msgs = unsupportedParts(msgs, model)
    msgs = normalizeMessages(msgs, model, options)
    if (
      model.providerID === "anthropic" ||
      model.api.id.includes("anthropic") ||
      model.api.id.includes("claude") ||
      usesAnthropicSDK(model)
    ) {
      msgs = applyCaching(msgs, model.providerID)
    }

    return msgs
  }

  export function temperature(model: Provider.Model) {
    const id = model.id.toLowerCase()
    if (id.includes("qwen")) return 0.55
    if (id.includes("claude")) return undefined
    if (id.includes("gemini")) return 1.0
    if (id.includes("glm-4.6")) return 1.0
    if (id.includes("glm-4.7")) return 1.0
    if (id.includes("minimax-m2")) return 1.0
    if (id.includes("kimi-k2")) {
      if (id.includes("thinking")) return 1.0
      return 0.6
    }
    return undefined
  }

  export function topP(model: Provider.Model) {
    const id = model.id.toLowerCase()
    if (id.includes("qwen")) return 1
    if (id.includes("minimax-m2")) {
      return 0.95
    }
    if (id.includes("gemini")) return 0.95
    return undefined
  }

  export function topK(model: Provider.Model) {
    const id = model.id.toLowerCase()
    if (id.includes("minimax-m2")) {
      if (id.includes("m2.1")) return 40
      return 20
    }
    if (id.includes("gemini")) return 64
    return undefined
  }

  const WIDELY_SUPPORTED_EFFORTS = ["low", "medium", "high"]
  const OPENAI_EFFORTS = ["none", "minimal", ...WIDELY_SUPPORTED_EFFORTS, "xhigh"]

  export function variants(model: Provider.Model): Record<string, Record<string, any>> {
    if (!model.capabilities.reasoning) return {}

    const id = model.id.toLowerCase()
    if (id.includes("deepseek") || id.includes("minimax") || id.includes("glm") || id.includes("mistral")) return {}

    if (isAzureAnthropic(model)) {
      return {
        high: {
          thinking: {
            type: "enabled",
            budgetTokens: 16000,
          },
        },
        max: {
          thinking: {
            type: "enabled",
            budgetTokens: 31999,
          },
        },
      }
    }

    switch (model.api.npm) {
      case "@openrouter/ai-sdk-provider":
        if (!model.id.includes("gpt") && !model.id.includes("gemini-3") && !model.id.includes("grok-4")) return {}
        return Object.fromEntries(OPENAI_EFFORTS.map((effort) => [effort, { reasoning: { effort } }]))

      // TODO: YOU CANNOT SET max_tokens if this is set!!!
      case "@ai-sdk/gateway":
        return Object.fromEntries(OPENAI_EFFORTS.map((effort) => [effort, { reasoningEffort: effort }]))

      case "@ai-sdk/cerebras":
      // https://v5.ai-sdk.dev/providers/ai-sdk-providers/cerebras
      case "@ai-sdk/togetherai":
      // https://v5.ai-sdk.dev/providers/ai-sdk-providers/togetherai
      case "@ai-sdk/xai":
      // https://v5.ai-sdk.dev/providers/ai-sdk-providers/xai
      case "@ai-sdk/deepinfra":
      // https://v5.ai-sdk.dev/providers/ai-sdk-providers/deepinfra
      case "@ai-sdk/openai-compatible":
        return Object.fromEntries(WIDELY_SUPPORTED_EFFORTS.map((effort) => [effort, { reasoningEffort: effort }]))

      case "@ai-sdk/azure":
        // https://v5.ai-sdk.dev/providers/ai-sdk-providers/azure
        if (id === "o1-mini") return {}
        const azureEfforts = ["low", "medium", "high"]
        if (id.includes("gpt-5-") || id === "gpt-5") {
          azureEfforts.unshift("minimal")
        }
        return Object.fromEntries(
          azureEfforts.map((effort) => [
            effort,
            {
              reasoningEffort: effort,
              reasoningSummary: "auto",
              include: ["reasoning.encrypted_content"],
            },
          ]),
        )
      case "@ai-sdk/openai":
        // https://v5.ai-sdk.dev/providers/ai-sdk-providers/openai
        if (id === "gpt-5-pro") return {}
        const openaiEfforts = iife(() => {
          if (id.includes("codex")) {
            if (id.includes("5.2")) return [...WIDELY_SUPPORTED_EFFORTS, "xhigh"]
            return WIDELY_SUPPORTED_EFFORTS
          }
          const arr = [...WIDELY_SUPPORTED_EFFORTS]
          if (id.includes("gpt-5-") || id === "gpt-5") {
            arr.unshift("minimal")
          }
          if (model.release_date >= "2025-11-13") {
            arr.unshift("none")
          }
          if (model.release_date >= "2025-12-04") {
            arr.push("xhigh")
          }
          return arr
        })
        return Object.fromEntries(
          openaiEfforts.map((effort) => [
            effort,
            {
              reasoningEffort: effort,
              reasoningSummary: "auto",
              include: ["reasoning.encrypted_content"],
            },
          ]),
        )

      case "@ai-sdk/anthropic":
        // https://v5.ai-sdk.dev/providers/ai-sdk-providers/anthropic
        return {
          high: {
            thinking: {
              type: "enabled",
              budgetTokens: 16000,
            },
          },
          max: {
            thinking: {
              type: "enabled",
              budgetTokens: 31999,
            },
          },
        }

      case "@ai-sdk/amazon-bedrock":
        // https://v5.ai-sdk.dev/providers/ai-sdk-providers/amazon-bedrock
        // For Anthropic models on Bedrock, use reasoningConfig with budgetTokens
        if (model.api.id.includes("anthropic")) {
          return {
            high: {
              reasoningConfig: {
                type: "enabled",
                budgetTokens: 16000,
              },
            },
            max: {
              reasoningConfig: {
                type: "enabled",
                budgetTokens: 31999,
              },
            },
          }
        }

        // For Amazon Nova models, use reasoningConfig with maxReasoningEffort
        return Object.fromEntries(
          WIDELY_SUPPORTED_EFFORTS.map((effort) => [
            effort,
            {
              reasoningConfig: {
                type: "enabled",
                maxReasoningEffort: effort,
              },
            },
          ]),
        )

      case "@ai-sdk/google-vertex":
      // https://v5.ai-sdk.dev/providers/ai-sdk-providers/google-vertex
      case "@ai-sdk/google":
        // https://v5.ai-sdk.dev/providers/ai-sdk-providers/google-generative-ai
        if (id.includes("2.5")) {
          return {
            high: {
              thinkingConfig: {
                includeThoughts: true,
                thinkingBudget: 16000,
              },
            },
            max: {
              thinkingConfig: {
                includeThoughts: true,
                thinkingBudget: 24576,
              },
            },
          }
        }
        return Object.fromEntries(
          ["low", "high"].map((effort) => [
            effort,
            {
              includeThoughts: true,
              thinkingLevel: effort,
            },
          ]),
        )

      case "@ai-sdk/mistral":
        // https://v5.ai-sdk.dev/providers/ai-sdk-providers/mistral
        return {}

      case "@ai-sdk/cohere":
        // https://v5.ai-sdk.dev/providers/ai-sdk-providers/cohere
        return {}

      case "@ai-sdk/groq":
        // https://v5.ai-sdk.dev/providers/ai-sdk-providers/groq
        const groqEffort = ["none", ...WIDELY_SUPPORTED_EFFORTS]
        return Object.fromEntries(
          groqEffort.map((effort) => [
            effort,
            {
              includeThoughts: true,
              thinkingLevel: effort,
            },
          ]),
        )

      case "@ai-sdk/perplexity":
        // https://v5.ai-sdk.dev/providers/ai-sdk-providers/perplexity
        return {}
    }
    return {}
  }

  export function options(input: {
    model: Provider.Model
    sessionID: string
    providerOptions?: Record<string, any>
  }): Record<string, any> {
    const result: Record<string, any> = {}

    // openai and providers using openai package should set store to false by default.
    if (input.model.providerID === "openai" || input.model.api.npm === "@ai-sdk/openai") {
      result["store"] = false
    }

    if (input.model.api.npm === "@openrouter/ai-sdk-provider") {
      result["usage"] = {
        include: true,
      }
      if (input.model.api.id.includes("gemini-3")) {
        result["reasoning"] = { effort: "high" }
      }
    }

    if (
      input.model.providerID === "baseten" ||
      (input.model.providerID === "opencode" && ["kimi-k2-thinking", "glm-4.6"].includes(input.model.api.id))
    ) {
      result["chat_template_args"] = { enable_thinking: true }
    }

    if (["zai", "zhipuai"].includes(input.model.providerID) && input.model.api.npm === "@ai-sdk/openai-compatible") {
      result["thinking"] = {
        type: "enabled",
        clear_thinking: false,
      }
    }

    if (input.model.providerID === "openai" || input.providerOptions?.setCacheKey) {
      result["promptCacheKey"] = input.sessionID
    }

    if (input.model.api.npm === "@ai-sdk/google" || input.model.api.npm === "@ai-sdk/google-vertex") {
      result["thinkingConfig"] = {
        includeThoughts: true,
      }
      if (input.model.api.id.includes("gemini-3")) {
        result["thinkingConfig"]["thinkingLevel"] = "high"
      }
    }

    if (input.model.api.id.includes("gpt-5") && !input.model.api.id.includes("gpt-5-chat")) {
      if (input.model.providerID.includes("codex")) {
        result["store"] = false
      }

      if (!input.model.api.id.includes("codex") && !input.model.api.id.includes("gpt-5-pro")) {
        result["reasoningEffort"] = "medium"
      }

      if (input.model.api.id.endsWith("gpt-5.") && input.model.providerID !== "azure") {
        result["textVerbosity"] = "low"
      }

      if (input.model.providerID.startsWith("opencode")) {
        result["promptCacheKey"] = input.sessionID
        result["include"] = ["reasoning.encrypted_content"]
        result["reasoningSummary"] = "auto"
      }
    }
    return result
  }

  export function smallOptions(model: Provider.Model) {
    if (model.providerID === "openai" || model.api.id.includes("gpt-5")) {
      if (model.api.id.includes("5.")) {
        return { reasoningEffort: "low" }
      }
      return { reasoningEffort: "minimal" }
    }
    if (model.providerID === "google") {
      // gemini-3 uses thinkingLevel, gemini-2.5 uses thinkingBudget
      if (model.api.id.includes("gemini-3")) {
        return { thinkingConfig: { thinkingLevel: "minimal" } }
      }
      return { thinkingConfig: { thinkingBudget: 0 } }
    }
    if (model.providerID === "openrouter") {
      if (model.api.id.includes("google")) {
        return { reasoning: { enabled: false } }
      }
      return { reasoningEffort: "minimal" }
    }
    return {}
  }

  export function providerOptions(model: Provider.Model, options: { [x: string]: any }) {
    if (isAzureAnthropic(model)) {
      return { ["anthropic" as string]: options }
    }
    switch (model.api.npm) {
      case "@ai-sdk/github-copilot":
      case "@ai-sdk/openai":
      case "@ai-sdk/azure":
        return {
          ["openai" as string]: options,
        }
      case "@ai-sdk/amazon-bedrock":
        return {
          ["bedrock" as string]: options,
        }
      case "@ai-sdk/anthropic":
        return {
          ["anthropic" as string]: options,
        }
      case "@ai-sdk/google-vertex":
      case "@ai-sdk/google":
        return {
          ["google" as string]: options,
        }
      case "@ai-sdk/gateway":
        return {
          ["gateway" as string]: options,
        }
      case "@openrouter/ai-sdk-provider":
        return {
          ["openrouter" as string]: options,
        }
      default:
        return {
          [model.providerID]: options,
        }
    }
  }

  export function maxOutputTokens(model: Provider.Model, options: Record<string, any>, globalLimit: number): number
  export function maxOutputTokens(
    npm: string,
    options: Record<string, any>,
    modelLimit: number,
    globalLimit: number,
  ): number
  export function maxOutputTokens(
    arg1: Provider.Model | string,
    options: Record<string, any>,
    arg3: number,
    arg4?: number,
  ): number {
    const model = typeof arg1 === "object" ? arg1 : null
    const npm = model ? model.api.npm : (arg1 as string)
    const modelLimit = model ? model.limit.output : arg3
    const globalLimit = model ? arg3 : arg4!
    const modelCap = modelLimit || globalLimit
    const standardLimit = Math.min(modelCap, globalLimit)

    if (model ? usesAnthropicSDK(model) : npm === "@ai-sdk/anthropic") {
      const thinking = options?.["thinking"]
      const budgetTokens = typeof thinking?.["budgetTokens"] === "number" ? thinking["budgetTokens"] : 0
      const enabled = thinking?.["type"] === "enabled"
      if (enabled && budgetTokens > 0) {
        // Return text tokens so that text + thinking <= model cap, preferring 32k text when possible.
        if (budgetTokens + standardLimit <= modelCap) {
          return standardLimit
        }
        return modelCap - budgetTokens
      }
    }

    return standardLimit
  }

  export function schema(model: Provider.Model, schema: JSONSchema.BaseSchema) {
    /*
    if (["openai", "azure"].includes(providerID)) {
      if (schema.type === "object" && schema.properties) {
        for (const [key, value] of Object.entries(schema.properties)) {
          if (schema.required?.includes(key)) continue
          schema.properties[key] = {
            anyOf: [
              value as JSONSchema.JSONSchema,
              {
                type: "null",
              },
            ],
          }
        }
      }
    }
    */

    // Convert integer enums to string enums for Google/Gemini
    if (model.providerID === "google" || model.api.id.includes("gemini")) {
      const sanitizeGemini = (obj: any): any => {
        if (obj === null || typeof obj !== "object") {
          return obj
        }

        if (Array.isArray(obj)) {
          return obj.map(sanitizeGemini)
        }

        const result: any = {}
        for (const [key, value] of Object.entries(obj)) {
          if (key === "enum" && Array.isArray(value)) {
            // Convert all enum values to strings
            result[key] = value.map((v) => String(v))
            // If we have integer type with enum, change type to string
            if (result.type === "integer" || result.type === "number") {
              result.type = "string"
            }
          } else if (typeof value === "object" && value !== null) {
            result[key] = sanitizeGemini(value)
          } else {
            result[key] = value
          }
        }

        // Filter required array to only include fields that exist in properties
        if (result.type === "object" && result.properties && Array.isArray(result.required)) {
          result.required = result.required.filter((field: any) => field in result.properties)
        }

        if (result.type === "array" && result.items == null) {
          result.items = {}
        }

        return result
      }

      schema = sanitizeGemini(schema)
    }

    return schema
  }

  export function error(providerID: string, error: APICallError) {
    let message = error.message
    if (providerID.includes("github-copilot") && error.statusCode === 403) {
      return "Please reauthenticate with the copilot provider to ensure your credentials work properly with OpenCode."
    }
    if (providerID.includes("github-copilot") && message.includes("The requested model is not supported")) {
      return (
        message +
        "\n\nMake sure the model is enabled in your copilot settings: https://github.com/settings/copilot/features"
      )
    }

    return message
  }
}