Merge db519e8e6c into 83397ebde2

packages/opencode/src/provider/sdk/openai-compatible/src/chat/convert-to-openai-compatible-chat-messages.ts

@@ -0,0 +1,153 @@
+import {
+  type LanguageModelV2Prompt,
+  type SharedV2ProviderMetadata,
+  UnsupportedFunctionalityError,
+} from '@ai-sdk/provider';
+import type { OpenAICompatibleChatPrompt } from './openai-compatible-api-types';
+import { convertToBase64 } from '@ai-sdk/provider-utils';
+import { Log } from '@/util/log';
+
+function getOpenAIMetadata(message: {
+  providerOptions?: SharedV2ProviderMetadata;
+}) {
+  return message?.providerOptions?.openaiCompatible ?? {};
+}
+
+export function convertToOpenAICompatibleChatMessages(
+  prompt: LanguageModelV2Prompt,
+): OpenAICompatibleChatPrompt {
+  const logger = Log.create();
+  const messages: OpenAICompatibleChatPrompt = [];
+  for (const { role, content, ...message } of prompt) {
+    const metadata = getOpenAIMetadata({ ...message });
+    switch (role) {
+      case 'system': {
+        messages.push({ role: 'system', content, ...metadata });
+        break;
+      }
+
+      case 'user': {
+        if (content.length === 1 && content[0].type === 'text') {
+          messages.push({
+            role: 'user',
+            content: content[0].text,
+            ...getOpenAIMetadata(content[0]),
+          });
+          break;
+        }
+
+        messages.push({
+          role: 'user',
+          content: content.map(part => {
+            const partMetadata = getOpenAIMetadata(part);
+            switch (part.type) {
+              case 'text': {
+                return { type: 'text', text: part.text, ...partMetadata };
+              }
+              case 'file': {
+                if (part.mediaType.startsWith('image/')) {
+                  const mediaType =
+                    part.mediaType === 'image/*'
+                      ? 'image/jpeg'
+                      : part.mediaType;
+
+                  return {
+                    type: 'image_url',
+                    image_url: {
+                      url:
+                        part.data instanceof URL
+                          ? part.data.toString()
+                          : `data:${mediaType};base64,${convertToBase64(part.data)}`,
+                    },
+                    ...partMetadata,
+                  };
+                } else {
+                  throw new UnsupportedFunctionalityError({
+                    functionality: `file part media type ${part.mediaType}`,
+                  });
+                }
+              }
+            }
+          }),
+          ...metadata,
+        });
+
+        break;
+      }
+
+      case 'assistant': {
+        let text = '';
+        const toolCalls: Array<{
+          id: string;
+          type: 'function';
+          function: { name: string; arguments: string };
+        }> = [];
+        for (const part of content) {
+          const partMetadata = getOpenAIMetadata(part);
+          switch (part.type) {
+            case 'text': {
+              text += part.text;
+              break;
+            }
+            case 'tool-call': {
+              toolCalls.push({
+                id: part.toolCallId,
+                type: 'function',
+                function: {
+                  name: part.toolName,
+                  arguments: JSON.stringify(part.input),
+                },
+                ...partMetadata,
+              });
+              break;
+            }
+          }
+        }
+
+        messages.push({
+          role: 'assistant',
+          content: text,
+          tool_calls: toolCalls.length > 0 ? toolCalls : undefined,
+          ...metadata,
+        });
+
+        break;
+      }
+
+      case 'tool': {
+        for (const toolResponse of content) {
+          const output = toolResponse.output;
+
+          let contentValue: string;
+          switch (output.type) {
+            case 'text':
+            case 'error-text':
+              contentValue = output.value;
+              break;
+            case 'content':
+            case 'json':
+            case 'error-json':
+              contentValue = JSON.stringify(output.value);
+              break;
+          }
+
+          const toolResponseMetadata = getOpenAIMetadata(toolResponse);
+          messages.push({
+            role: 'tool',
+            tool_call_id: toolResponse.toolCallId,
+            content: contentValue,
+            ...toolResponseMetadata,
+          });
+        }
+        break;
+      }
+
+      default: {
+        const _exhaustiveCheck: never = role;
+        throw new Error(`Unsupported role: ${_exhaustiveCheck}`);
+      }
+    }
+  }
+
+  return messages;
+}

packages/opencode/src/provider/sdk/openai-compatible/src/chat/get-response-metadata.ts

@@ -0,0 +1,15 @@
+export function getResponseMetadata({
+  id,
+  model,
+  created,
+}: {
+  id?: string | undefined | null;
+  created?: number | undefined | null;
+  model?: string | undefined | null;
+}) {
+  return {
+    id: id ?? undefined,
+    modelId: model ?? undefined,
+    timestamp: created != null ? new Date(created * 1000) : undefined,
+  };
+}

packages/opencode/src/provider/sdk/openai-compatible/src/chat/map-openai-compatible-finish-reason.ts

@@ -0,0 +1,19 @@
+import type { LanguageModelV2FinishReason } from '@ai-sdk/provider';
+
+export function mapOpenAICompatibleFinishReason(
+  finishReason: string | null | undefined,
+): LanguageModelV2FinishReason {
+  switch (finishReason) {
+    case 'stop':
+      return 'stop';
+    case 'length':
+      return 'length';
+    case 'content_filter':
+      return 'content-filter';
+    case 'function_call':
+    case 'tool_calls':
+      return 'tool-calls';
+    default:
+      return 'unknown';
+  }
+}

packages/opencode/src/provider/sdk/openai-compatible/src/chat/openai-compatible-api-types.ts

@@ -0,0 +1,63 @@
+import { type JSONValue } from '@ai-sdk/provider';
+
+export type OpenAICompatibleChatPrompt = Array<OpenAICompatibleMessage>;
+
+export type OpenAICompatibleMessage =
+  | OpenAICompatibleSystemMessage
+  | OpenAICompatibleUserMessage
+  | OpenAICompatibleAssistantMessage
+  | OpenAICompatibleToolMessage;
+
+// Allow for arbitrary additional properties for general purpose
+// provider-metadata-specific extensibility.
+type JsonRecord<T = never> = Record<
+  string,
+  JSONValue | JSONValue[] | T | T[] | undefined
+>;
+
+export interface OpenAICompatibleSystemMessage extends JsonRecord {
+  role: 'system';
+  content: string;
+}
+
+export interface OpenAICompatibleUserMessage
+  extends JsonRecord<OpenAICompatibleContentPart> {
+  role: 'user';
+  content: string | Array<OpenAICompatibleContentPart>;
+}
+
+export type OpenAICompatibleContentPart =
+  | OpenAICompatibleContentPartText
+  | OpenAICompatibleContentPartImage;
+
+export interface OpenAICompatibleContentPartImage extends JsonRecord {
+  type: 'image_url';
+  image_url: { url: string };
+}
+
+export interface OpenAICompatibleContentPartText extends JsonRecord {
+  type: 'text';
+  text: string;
+}
+
+export interface OpenAICompatibleAssistantMessage
+  extends JsonRecord<OpenAICompatibleMessageToolCall> {
+  role: 'assistant';
+  content?: string | null;
+  tool_calls?: Array<OpenAICompatibleMessageToolCall>;
+}
+
+export interface OpenAICompatibleMessageToolCall extends JsonRecord {
+  type: 'function';
+  id: string;
+  function: {
+    arguments: string;
+    name: string;
+  };
+}
+
+export interface OpenAICompatibleToolMessage extends JsonRecord {
+  role: 'tool';
+  content: string;
+  tool_call_id: string;
+}

packages/opencode/src/provider/sdk/openai-compatible/src/chat/openai-compatible-chat-language-model.ts

@@ -0,0 +1,728 @@
+import {
+  APICallError,
+  InvalidResponseDataError,
+  type LanguageModelV2,
+  type LanguageModelV2CallWarning,
+  type LanguageModelV2Content,
+  type LanguageModelV2FinishReason,
+  type LanguageModelV2StreamPart,
+  type SharedV2ProviderMetadata,
+} from "@ai-sdk/provider"
+
+import {
+  combineHeaders,
+  createEventSourceResponseHandler,
+  createJsonErrorResponseHandler,
+  createJsonResponseHandler,
+  type FetchFunction,
+  generateId,
+  isParsableJson,
+  parseProviderOptions,
+  type ParseResult,
+  postJsonToApi,
+  type ResponseHandler,
+} from "@ai-sdk/provider-utils"
+import { z } from "zod/v4"
+import { convertToOpenAICompatibleChatMessages } from "./convert-to-openai-compatible-chat-messages"
+import { getResponseMetadata } from "./get-response-metadata"
+import { mapOpenAICompatibleFinishReason } from "./map-openai-compatible-finish-reason"
+import {
+  type OpenAICompatibleChatModelId,
+  openaiCompatibleProviderOptions,
+  type OpenAICompatibleProviderOptions,
+} from "./openai-compatible-chat-options"
+import { defaultOpenAICompatibleErrorStructure } from "../openai-compatible-error"
+import type { ProviderErrorStructure } from "@ai-sdk/openai-compatible"
+import type { MetadataExtractor } from "./openai-compatible-metadata-extractor"
+import { prepareTools } from "./openai-compatible-prepare-tools"
+import { Log } from "@/util/log"
+
+export type OpenAICompatibleChatConfig = {
+  provider: string
+  headers: () => Record<string, string | undefined>
+  url: (options: { modelId: string; path: string }) => string
+  fetch?: FetchFunction
+  includeUsage?: boolean
+  errorStructure?: ProviderErrorStructure<any>
+  metadataExtractor?: MetadataExtractor
+
+  /**
+   * Whether the model supports structured outputs.
+   */
+  supportsStructuredOutputs?: boolean
+
+  /**
+   * The supported URLs for the model.
+   */
+  supportedUrls?: () => LanguageModelV2["supportedUrls"]
+}
+
+export class OpenAICompatibleChatLanguageModel implements LanguageModelV2 {
+  readonly specificationVersion = "v2"
+
+  readonly supportsStructuredOutputs: boolean
+
+  readonly modelId: OpenAICompatibleChatModelId
+  private readonly config: OpenAICompatibleChatConfig
+  private readonly failedResponseHandler: ResponseHandler<APICallError>
+  private readonly chunkSchema // type inferred via constructor
+
+  constructor(modelId: OpenAICompatibleChatModelId, config: OpenAICompatibleChatConfig) {
+    this.modelId = modelId
+    this.config = config
+
+    // initialize error handling:
+    const errorStructure = config.errorStructure ?? defaultOpenAICompatibleErrorStructure
+    this.chunkSchema = createOpenAICompatibleChatChunkSchema(errorStructure.errorSchema)
+    this.failedResponseHandler = createJsonErrorResponseHandler(errorStructure)
+
+    this.supportsStructuredOutputs = config.supportsStructuredOutputs ?? false
+  }
+
+  get provider(): string {
+    return this.config.provider
+  }
+
+  private get providerOptionsName(): string {
+    return this.config.provider.split(".")[0].trim()
+  }
+
+  get supportedUrls() {
+    return this.config.supportedUrls?.() ?? {}
+  }
+
+  private async getArgs({
+    prompt,
+    maxOutputTokens,
+    temperature,
+    topP,
+    topK,
+    frequencyPenalty,
+    presencePenalty,
+    providerOptions,
+    stopSequences,
+    responseFormat,
+    seed,
+    toolChoice,
+    tools,
+  }: Parameters<LanguageModelV2["doGenerate"]>[0]) {
+    const warnings: LanguageModelV2CallWarning[] = []
+
+    // Parse provider options
+    const compatibleOptions = Object.assign(
+      (await parseProviderOptions({
+        provider: "openai-compatible",
+        providerOptions,
+        schema: openaiCompatibleProviderOptions,
+      })) ?? {},
+      (await parseProviderOptions({
+        provider: this.providerOptionsName,
+        providerOptions,
+        schema: openaiCompatibleProviderOptions,
+      })) ?? {},
+    )
+
+    if (topK != null) {
+      warnings.push({ type: "unsupported-setting", setting: "topK" })
+    }
+
+    if (responseFormat?.type === "json" && responseFormat.schema != null && !this.supportsStructuredOutputs) {
+      warnings.push({
+        type: "unsupported-setting",
+        setting: "responseFormat",
+        details: "JSON response format schema is only supported with structuredOutputs",
+      })
+    }
+
+    const {
+      tools: openaiTools,
+      toolChoice: openaiToolChoice,
+      toolWarnings,
+    } = prepareTools({
+      tools,
+      toolChoice,
+    })
+
+    return {
+      args: {
+        // model id:
+        model: this.modelId,
+
+        // model specific settings:
+        user: compatibleOptions.user,
+
+        // standardized settings:
+        max_tokens: maxOutputTokens,
+        temperature,
+        top_p: topP,
+        frequency_penalty: frequencyPenalty,
+        presence_penalty: presencePenalty,
+        response_format:
+          responseFormat?.type === "json"
+            ? this.supportsStructuredOutputs === true && responseFormat.schema != null
+              ? {
+                  type: "json_schema",
+                  json_schema: {
+                    schema: responseFormat.schema,
+                    name: responseFormat.name ?? "response",
+                    description: responseFormat.description,
+                  },
+                }
+              : { type: "json_object" }
+            : undefined,
+
+        stop: stopSequences,
+        seed,
+        ...Object.fromEntries(
+          Object.entries(providerOptions?.[this.providerOptionsName] ?? {}).filter(
+            ([key]) => !Object.keys(openaiCompatibleProviderOptions.shape).includes(key),
+          ),
+        ),
+
+        reasoning_effort: compatibleOptions.reasoningEffort,
+
+        // messages:
+        messages: convertToOpenAICompatibleChatMessages(prompt),
+
+        // tools:
+        tools: openaiTools,
+        tool_choice: openaiToolChoice,
+      },
+      warnings: [...warnings, ...toolWarnings],
+    }
+  }
+
+  async doGenerate(
+    options: Parameters<LanguageModelV2["doGenerate"]>[0],
+  ): Promise<Awaited<ReturnType<LanguageModelV2["doGenerate"]>>> {
+    const { args, warnings } = await this.getArgs({ ...options })
+
+    const body = JSON.stringify(args)
+
+    const {
+      responseHeaders,
+      value: responseBody,
+      rawValue: rawResponse,
+    } = await postJsonToApi({
+      url: this.config.url({
+        path: "/chat/completions",
+        modelId: this.modelId,
+      }),
+      headers: combineHeaders(this.config.headers(), options.headers),
+      body: args,
+      failedResponseHandler: this.failedResponseHandler,
+      successfulResponseHandler: createJsonResponseHandler(OpenAICompatibleChatResponseSchema),
+      abortSignal: options.abortSignal,
+      fetch: this.config.fetch,
+    })
+    const log = Log.create()
+    log.info("responseBody", responseBody)
+    const choice = responseBody.choices[0]
+    const content: Array<LanguageModelV2Content> = []
+
+    // text content:
+    const text = choice.message.content
+    if (text != null && text.length > 0) {
+      content.push({ type: "text", text })
+    }
+
+    // reasoning content:
+    const reasoning = choice.message.reasoning_content ?? choice.message.reasoning ?? choice.message.reasoning_text
+    if (reasoning != null && reasoning.length > 0) {
+      content.push({
+        type: "reasoning",
+        text: reasoning,
+      })
+    }
+
+    // tool calls:
+    if (choice.message.tool_calls != null) {
+      for (const toolCall of choice.message.tool_calls) {
+        content.push({
+          type: "tool-call",
+          toolCallId: toolCall.id ?? generateId(),
+          toolName: toolCall.function.name,
+          input: toolCall.function.arguments!,
+        })
+      }
+    }
+
+    // provider metadata:
+    const providerMetadata: SharedV2ProviderMetadata = {
+      [this.providerOptionsName]: {},
+      ...(await this.config.metadataExtractor?.extractMetadata?.({
+        parsedBody: rawResponse,
+      })),
+    }
+    const completionTokenDetails = responseBody.usage?.completion_tokens_details
+    if (completionTokenDetails?.accepted_prediction_tokens != null) {
+      providerMetadata[this.providerOptionsName].acceptedPredictionTokens =
+        completionTokenDetails?.accepted_prediction_tokens
+    }
+    if (completionTokenDetails?.rejected_prediction_tokens != null) {
+      providerMetadata[this.providerOptionsName].rejectedPredictionTokens =
+        completionTokenDetails?.rejected_prediction_tokens
+    }
+
+    return {
+      content,
+      finishReason: mapOpenAICompatibleFinishReason(choice.finish_reason),
+      usage: {
+        inputTokens: responseBody.usage?.prompt_tokens ?? undefined,
+        outputTokens: responseBody.usage?.completion_tokens ?? undefined,
+        totalTokens: responseBody.usage?.total_tokens ?? undefined,
+        reasoningTokens: responseBody.usage?.completion_tokens_details?.reasoning_tokens ?? undefined,
+        cachedInputTokens: responseBody.usage?.prompt_tokens_details?.cached_tokens ?? undefined,
+      },
+      providerMetadata,
+      request: { body },
+      response: {
+        ...getResponseMetadata(responseBody),
+        headers: responseHeaders,
+        body: rawResponse,
+      },
+      warnings,
+    }
+  }
+
+  async doStream(
+    options: Parameters<LanguageModelV2["doStream"]>[0],
+  ): Promise<Awaited<ReturnType<LanguageModelV2["doStream"]>>> {
+    const { args, warnings } = await this.getArgs({ ...options })
+
+    const body = {
+      ...args,
+      stream: true,
+
+      // only include stream_options when in strict compatibility mode:
+      stream_options: this.config.includeUsage ? { include_usage: true } : undefined,
+    }
+
+    const metadataExtractor = this.config.metadataExtractor?.createStreamExtractor()
+
+    const { responseHeaders, value: response } = await postJsonToApi({
+      url: this.config.url({
+        path: "/chat/completions",
+        modelId: this.modelId,
+      }),
+      headers: combineHeaders(this.config.headers(), options.headers),
+      body,
+      failedResponseHandler: this.failedResponseHandler,
+      successfulResponseHandler: createEventSourceResponseHandler(this.chunkSchema),
+      abortSignal: options.abortSignal,
+      fetch: this.config.fetch,
+    })
+
+    const toolCalls: Array<{
+      id: string
+      type: "function"
+      function: {
+        name: string
+        arguments: string
+      }
+      hasFinished: boolean
+    }> = []
+
+    let finishReason: LanguageModelV2FinishReason = "unknown"
+    const usage: {
+      completionTokens: number | undefined
+      completionTokensDetails: {
+        reasoningTokens: number | undefined
+        acceptedPredictionTokens: number | undefined
+        rejectedPredictionTokens: number | undefined
+      }
+      promptTokens: number | undefined
+      promptTokensDetails: {
+        cachedTokens: number | undefined
+      }
+      totalTokens: number | undefined
+    } = {
+      completionTokens: undefined,
+      completionTokensDetails: {
+        reasoningTokens: undefined,
+        acceptedPredictionTokens: undefined,
+        rejectedPredictionTokens: undefined,
+      },
+      promptTokens: undefined,
+      promptTokensDetails: {
+        cachedTokens: undefined,
+      },
+      totalTokens: undefined,
+    }
+    let isFirstChunk = true
+    const providerOptionsName = this.providerOptionsName
+    let isActiveReasoning = false
+    let isActiveText = false
+
+    return {
+      stream: response.pipeThrough(
+        new TransformStream<ParseResult<z.infer<typeof this.chunkSchema>>, LanguageModelV2StreamPart>({
+          start(controller) {
+            controller.enqueue({ type: "stream-start", warnings })
+          },
+
+          // TODO we lost type safety on Chunk, most likely due to the error schema. MUST FIX
+          transform(chunk, controller) {
+            // Emit raw chunk if requested (before anything else)
+            if (options.includeRawChunks) {
+              controller.enqueue({ type: "raw", rawValue: chunk.rawValue })
+            }
+
+            // handle failed chunk parsing / validation:
+            if (!chunk.success) {
+              finishReason = "error"
+              controller.enqueue({ type: "error", error: chunk.error })
+              return
+            }
+            const value = chunk.value
+
+            metadataExtractor?.processChunk(chunk.rawValue)
+
+            // handle error chunks:
+            if ("error" in value) {
+              finishReason = "error"
+              controller.enqueue({ type: "error", error: value.error.message })
+              return
+            }
+
+            if (isFirstChunk) {
+              isFirstChunk = false
+
+              controller.enqueue({
+                type: "response-metadata",
+                ...getResponseMetadata(value),
+              })
+            }
+
+            if (value.usage != null) {
+              const {
+                prompt_tokens,
+                completion_tokens,
+                total_tokens,
+                prompt_tokens_details,
+                completion_tokens_details,
+              } = value.usage
+
+              usage.promptTokens = prompt_tokens ?? undefined
+              usage.completionTokens = completion_tokens ?? undefined
+              usage.totalTokens = total_tokens ?? undefined
+              if (completion_tokens_details?.reasoning_tokens != null) {
+                usage.completionTokensDetails.reasoningTokens = completion_tokens_details?.reasoning_tokens
+              }
+              if (completion_tokens_details?.accepted_prediction_tokens != null) {
+                usage.completionTokensDetails.acceptedPredictionTokens =
+                  completion_tokens_details?.accepted_prediction_tokens
+              }
+              if (completion_tokens_details?.rejected_prediction_tokens != null) {
+                usage.completionTokensDetails.rejectedPredictionTokens =
+                  completion_tokens_details?.rejected_prediction_tokens
+              }
+              if (prompt_tokens_details?.cached_tokens != null) {
+                usage.promptTokensDetails.cachedTokens = prompt_tokens_details?.cached_tokens
+              }
+            }
+
+            const choice = value.choices[0]
+
+            if (choice?.finish_reason != null) {
+              finishReason = mapOpenAICompatibleFinishReason(choice.finish_reason)
+            }
+
+            if (choice?.delta == null) {
+              return
+            }
+
+            const delta = choice.delta
+
+            // enqueue reasoning before text deltas:
+            const reasoningContent = delta.reasoning_content ?? delta.reasoning ?? delta.reasoning_text
+            if (reasoningContent) {
+              if (!isActiveReasoning) {
+                controller.enqueue({
+                  type: "reasoning-start",
+                  id: "reasoning-0",
+                })
+                isActiveReasoning = true
+              }
+
+              controller.enqueue({
+                type: "reasoning-delta",
+                id: "reasoning-0",
+                delta: reasoningContent,
+              })
+            }
+
+            if (delta.content) {
+              if (!isActiveText) {
+                controller.enqueue({ type: "text-start", id: "txt-0" })
+                isActiveText = true
+              }
+
+              controller.enqueue({
+                type: "text-delta",
+                id: "txt-0",
+                delta: delta.content,
+              })
+            }
+
+            if (delta.tool_calls != null) {
+              for (const toolCallDelta of delta.tool_calls) {
+                const index = toolCallDelta.index
+
+                if (toolCalls[index] == null) {
+                  if (toolCallDelta.id == null) {
+                    throw new InvalidResponseDataError({
+                      data: toolCallDelta,
+                      message: `Expected 'id' to be a string.`,
+                    })
+                  }
+
+                  if (toolCallDelta.function?.name == null) {
+                    throw new InvalidResponseDataError({
+                      data: toolCallDelta,
+                      message: `Expected 'function.name' to be a string.`,
+                    })
+                  }
+
+                  controller.enqueue({
+                    type: "tool-input-start",
+                    id: toolCallDelta.id,
+                    toolName: toolCallDelta.function.name,
+                  })
+
+                  toolCalls[index] = {
+                    id: toolCallDelta.id,
+                    type: "function",
+                    function: {
+                      name: toolCallDelta.function.name,
+                      arguments: toolCallDelta.function.arguments ?? "",
+                    },
+                    hasFinished: false,
+                  }
+
+                  const toolCall = toolCalls[index]
+
+                  if (toolCall.function?.name != null && toolCall.function?.arguments != null) {
+                    // send delta if the argument text has already started:
+                    if (toolCall.function.arguments.length > 0) {
+                      controller.enqueue({
+                        type: "tool-input-delta",
+                        id: toolCall.id,
+                        delta: toolCall.function.arguments,
+                      })
+                    }
+
+                    // check if tool call is complete
+                    // (some providers send the full tool call in one chunk):
+                    if (isParsableJson(toolCall.function.arguments)) {
+                      controller.enqueue({
+                        type: "tool-input-end",
+                        id: toolCall.id,
+                      })
+
+                      controller.enqueue({
+                        type: "tool-call",
+                        toolCallId: toolCall.id ?? generateId(),
+                        toolName: toolCall.function.name,
+                        input: toolCall.function.arguments,
+                      })
+                      toolCall.hasFinished = true
+                    }
+                  }
+
+                  continue
+                }
+
+                // existing tool call, merge if not finished
+                const toolCall = toolCalls[index]
+
+                if (toolCall.hasFinished) {
+                  continue
+                }
+
+                if (toolCallDelta.function?.arguments != null) {
+                  toolCall.function!.arguments += toolCallDelta.function?.arguments ?? ""
+                }
+
+                // send delta
+                controller.enqueue({
+                  type: "tool-input-delta",
+                  id: toolCall.id,
+                  delta: toolCallDelta.function.arguments ?? "",
+                })
+
+                // check if tool call is complete
+                if (
+                  toolCall.function?.name != null &&
+                  toolCall.function?.arguments != null &&
+                  isParsableJson(toolCall.function.arguments)
+                ) {
+                  controller.enqueue({
+                    type: "tool-input-end",
+                    id: toolCall.id,
+                  })
+
+                  controller.enqueue({
+                    type: "tool-call",
+                    toolCallId: toolCall.id ?? generateId(),
+                    toolName: toolCall.function.name,
+                    input: toolCall.function.arguments,
+                  })
+                  toolCall.hasFinished = true
+                }
+              }
+            }
+          },
+
+          flush(controller) {
+            if (isActiveReasoning) {
+              controller.enqueue({ type: "reasoning-end", id: "reasoning-0" })
+            }
+
+            if (isActiveText) {
+              controller.enqueue({ type: "text-end", id: "txt-0" })
+            }
+
+            // go through all tool calls and send the ones that are not finished
+            for (const toolCall of toolCalls.filter((toolCall) => !toolCall.hasFinished)) {
+              controller.enqueue({
+                type: "tool-input-end",
+                id: toolCall.id,
+              })
+
+              controller.enqueue({
+                type: "tool-call",
+                toolCallId: toolCall.id ?? generateId(),
+                toolName: toolCall.function.name,
+                input: toolCall.function.arguments,
+              })
+            }
+
+            const providerMetadata: SharedV2ProviderMetadata = {
+              ...metadataExtractor?.buildMetadata(),
+            }
+            const log = Log.create()
+            log.error(`provider metadata = ${JSON.stringify(providerMetadata)}`)
+            if (usage.completionTokensDetails.acceptedPredictionTokens != null) {
+              providerMetadata[providerOptionsName].acceptedPredictionTokens =
+                usage.completionTokensDetails.acceptedPredictionTokens
+            }
+            if (usage.completionTokensDetails.rejectedPredictionTokens != null) {
+              providerMetadata[providerOptionsName].rejectedPredictionTokens =
+                usage.completionTokensDetails.rejectedPredictionTokens
+            }
+
+            controller.enqueue({
+              type: "finish",
+              finishReason,
+              usage: {
+                inputTokens: usage.promptTokens ?? undefined,
+                outputTokens: usage.completionTokens ?? undefined,
+                totalTokens: usage.totalTokens ?? undefined,
+                reasoningTokens: usage.completionTokensDetails.reasoningTokens ?? undefined,
+                cachedInputTokens: usage.promptTokensDetails.cachedTokens ?? undefined,
+              },
+              providerMetadata,
+            })
+          },
+        }),
+      ),
+      request: { body },
+      response: { headers: responseHeaders },
+    }
+  }
+}
+
+const openaiCompatibleTokenUsageSchema = z
+  .object({
+    prompt_tokens: z.number().nullish(),
+    completion_tokens: z.number().nullish(),
+    total_tokens: z.number().nullish(),
+    prompt_tokens_details: z
+      .object({
+        cached_tokens: z.number().nullish(),
+      })
+      .nullish(),
+    completion_tokens_details: z
+      .object({
+        reasoning_tokens: z.number().nullish(),
+        accepted_prediction_tokens: z.number().nullish(),
+        rejected_prediction_tokens: z.number().nullish(),
+      })
+      .nullish(),
+  })
+  .nullish()
+
+// limited version of the schema, focussed on what is needed for the implementation
+// this approach limits breakages when the API changes and increases efficiency
+const OpenAICompatibleChatResponseSchema = z.object({
+  id: z.string().nullish(),
+  created: z.number().nullish(),
+  model: z.string().nullish(),
+  choices: z.array(
+    z.object({
+      message: z.object({
+        role: z.literal("assistant").nullish(),
+        content: z.string().nullish(),
+        reasoning_text: z.string().nullish(),
+        reasoning_content: z.string().nullish(),
+        reasoning: z.string().nullish(),
+        tool_calls: z
+          .array(
+            z.object({
+              id: z.string().nullish(),
+              function: z.object({
+                name: z.string(),
+                arguments: z.string(),
+              }),
+            }),
+          )
+          .nullish(),
+      }),
+      finish_reason: z.string().nullish(),
+    }),
+  ),
+  usage: openaiCompatibleTokenUsageSchema,
+})
+
+// limited version of the schema, focussed on what is needed for the implementation
+// this approach limits breakages when the API changes and increases efficiency
+const createOpenAICompatibleChatChunkSchema = <ERROR_SCHEMA extends z.core.$ZodType>(errorSchema: ERROR_SCHEMA) =>
+  z.union([
+    z.object({
+      id: z.string().nullish(),
+      created: z.number().nullish(),
+      model: z.string().nullish(),
+      choices: z.array(
+        z.object({
+          delta: z
+            .object({
+              role: z.enum(["assistant"]).nullish(),
+              content: z.string().nullish(),
+              // Most openai-compatible models set `reasoning_content`, but some
+              // providers serving `gpt-oss` set `reasoning`. See #7866
+              reasoning_content: z.string().nullish(),
+              reasoning: z.string().nullish(),
+              // Copilot sets `reasoning_text`
+              reasoning_text: z.string().nullish(),
+              tool_calls: z
+                .array(
+                  z.object({
+                    index: z.number(),
+                    id: z.string().nullish(),
+                    function: z.object({
+                      name: z.string().nullish(),
+                      arguments: z.string().nullish(),
+                    }),
+                  }),
+                )
+                .nullish(),
+            })
+            .nullish(),
+          finish_reason: z.string().nullish(),
+        }),
+      ),
+      usage: openaiCompatibleTokenUsageSchema,
+    }),
+    errorSchema,
+  ])

packages/opencode/src/provider/sdk/openai-compatible/src/chat/openai-compatible-chat-options.ts

@@ -0,0 +1,20 @@
+import { z } from 'zod/v4';
+
+export type OpenAICompatibleChatModelId = string;
+
+export const openaiCompatibleProviderOptions = z.object({
+  /**
+   * A unique identifier representing your end-user, which can help the provider to
+   * monitor and detect abuse.
+   */
+  user: z.string().optional(),
+
+  /**
+   * Reasoning effort for reasoning models. Defaults to `medium`.
+   */
+  reasoningEffort: z.string().optional(),
+});
+
+export type OpenAICompatibleProviderOptions = z.infer<
+  typeof openaiCompatibleProviderOptions
+>;

packages/opencode/src/provider/sdk/openai-compatible/src/chat/openai-compatible-metadata-extractor.ts

@@ -0,0 +1,48 @@
+import type { SharedV2ProviderMetadata } from '@ai-sdk/provider';
+
+/**
+Extracts provider-specific metadata from API responses.
+Used to standardize metadata handling across different LLM providers while allowing
+provider-specific metadata to be captured.
+*/
+export type MetadataExtractor = {
+  /**
+   * Extracts provider metadata from a complete, non-streaming response.
+   *
+   * @param parsedBody - The parsed response JSON body from the provider's API.
+   *
+   * @returns Provider-specific metadata or undefined if no metadata is available.
+   *          The metadata should be under a key indicating the provider id.
+   */
+  extractMetadata: ({
+    parsedBody,
+  }: {
+    parsedBody: unknown;
+  }) => Promise<SharedV2ProviderMetadata | undefined>;
+
+  /**
+   * Creates an extractor for handling streaming responses. The returned object provides
+   * methods to process individual chunks and build the final metadata from the accumulated
+   * stream data.
+   *
+   * @returns An object with methods to process chunks and build metadata from a stream
+   */
+  createStreamExtractor: () => {
+    /**
+     * Process an individual chunk from the stream. Called for each chunk in the response stream
+     * to accumulate metadata throughout the streaming process.
+     *
+     * @param parsedChunk - The parsed JSON response chunk from the provider's API
+     */
+    processChunk(parsedChunk: unknown): void;
+
+    /**
+     * Builds the metadata object after all chunks have been processed.
+     * Called at the end of the stream to generate the complete provider metadata.
+     *
+     * @returns Provider-specific metadata or undefined if no metadata is available.
+     *          The metadata should be under a key indicating the provider id.
+     */
+    buildMetadata(): SharedV2ProviderMetadata | undefined;
+  };
+};

packages/opencode/src/provider/sdk/openai-compatible/src/chat/openai-compatible-prepare-tools.ts

@@ -0,0 +1,92 @@
+import {
+  type LanguageModelV2CallOptions,
+  type LanguageModelV2CallWarning,
+  UnsupportedFunctionalityError,
+} from '@ai-sdk/provider';
+
+export function prepareTools({
+  tools,
+  toolChoice,
+}: {
+  tools: LanguageModelV2CallOptions['tools'];
+  toolChoice?: LanguageModelV2CallOptions['toolChoice'];
+}): {
+  tools:
+    | undefined
+    | Array<{
+        type: 'function';
+        function: {
+          name: string;
+          description: string | undefined;
+          parameters: unknown;
+        };
+      }>;
+  toolChoice:
+    | { type: 'function'; function: { name: string } }
+    | 'auto'
+    | 'none'
+    | 'required'
+    | undefined;
+  toolWarnings: LanguageModelV2CallWarning[];
+} {
+  // when the tools array is empty, change it to undefined to prevent errors:
+  tools = tools?.length ? tools : undefined;
+
+  const toolWarnings: LanguageModelV2CallWarning[] = [];
+
+  if (tools == null) {
+    return { tools: undefined, toolChoice: undefined, toolWarnings };
+  }
+
+  const openaiCompatTools: Array<{
+    type: 'function';
+    function: {
+      name: string;
+      description: string | undefined;
+      parameters: unknown;
+    };
+  }> = [];
+
+  for (const tool of tools) {
+    if (tool.type === 'provider-defined') {
+      toolWarnings.push({ type: 'unsupported-tool', tool });
+    } else {
+      openaiCompatTools.push({
+        type: 'function',
+        function: {
+          name: tool.name,
+          description: tool.description,
+          parameters: tool.inputSchema,
+        },
+      });
+    }
+  }
+
+  if (toolChoice == null) {
+    return { tools: openaiCompatTools, toolChoice: undefined, toolWarnings };
+  }
+
+  const type = toolChoice.type;
+
+  switch (type) {
+    case 'auto':
+    case 'none':
+    case 'required':
+      return { tools: openaiCompatTools, toolChoice: type, toolWarnings };
+    case 'tool':
+      return {
+        tools: openaiCompatTools,
+        toolChoice: {
+          type: 'function',
+          function: { name: toolChoice.toolName },
+        },
+        toolWarnings,
+      };
+    default: {
+      const _exhaustiveCheck: never = type;
+      throw new UnsupportedFunctionalityError({
+        functionality: `tool choice type: ${_exhaustiveCheck}`,
+      });
+    }
+  }
+}

packages/opencode/src/provider/sdk/openai-compatible/src/openai-compatible-error.ts

@@ -0,0 +1,30 @@
+import { z, ZodType } from 'zod/v4';
+
+export const openaiCompatibleErrorDataSchema = z.object({
+  error: z.object({
+    message: z.string(),
+
+    // The additional information below is handled loosely to support
+    // OpenAI-compatible providers that have slightly different error
+    // responses:
+    type: z.string().nullish(),
+    param: z.any().nullish(),
+    code: z.union([z.string(), z.number()]).nullish(),
+  }),
+});
+
+export type OpenAICompatibleErrorData = z.infer<
+  typeof openaiCompatibleErrorDataSchema
+>;
+
+export type ProviderErrorStructure<T> = {
+  errorSchema: ZodType<T>;
+  errorToMessage: (error: T) => string;
+  isRetryable?: (response: Response, error?: T) => boolean;
+};
+
+export const defaultOpenAICompatibleErrorStructure: ProviderErrorStructure<OpenAICompatibleErrorData> =
+  {
+    errorSchema: openaiCompatibleErrorDataSchema,
+    errorToMessage: data => data.error.message,
+  };

packages/opencode/src/provider/sdk/openai-compatible/src/openai-compatible-provider.ts

@@ -1,8 +1,8 @@
 import type { LanguageModelV2 } from "@ai-sdk/provider"
-import { OpenAICompatibleChatLanguageModel } from "@ai-sdk/openai-compatible"
 import { type FetchFunction, withoutTrailingSlash, withUserAgentSuffix } from "@ai-sdk/provider-utils"
 import { OpenAIResponsesLanguageModel } from "./responses/openai-responses-language-model"
-
+import { OpenAICompatibleChatLanguageModel } from "./chat/openai-compatible-chat-language-model"
+import { Log } from "@/util/log"
 // Import the version or define it
 const VERSION = "0.1.0"