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修改： app/api/[provider]/[...path]/route.ts
修改： app/api/auth.ts 新文件： app/api/bedrock.ts 新文件： app/api/bedrock/models.ts 新文件： app/api/bedrock/utils.ts 修改： app/client/api.ts 新文件： app/client/platforms/bedrock.ts 修改： app/components/settings.tsx 修改： app/config/server.ts 修改： app/constant.ts 修改： app/locales/cn.ts 修改： app/locales/en.ts 修改： app/store/access.ts 修改： app/utils.ts 修改： package.json
This commit is contained in:
glay
280
app/api/bedrock/models.ts
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280
app/api/bedrock/models.ts
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@@ -0,0 +1,280 @@
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import {
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Message,
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validateMessageOrder,
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processDocumentContent,
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BedrockTextBlock,
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BedrockImageBlock,
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BedrockDocumentBlock,
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} from "./utils";
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export interface ConverseRequest {
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modelId: string;
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messages: Message[];
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inferenceConfig?: {
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maxTokens?: number;
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temperature?: number;
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topP?: number;
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};
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system?: string;
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tools?: Array<{
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type: "function";
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function: {
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name: string;
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description: string;
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parameters: {
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type: string;
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properties: Record<string, any>;
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required: string[];
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};
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};
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}>;
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}
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interface ContentItem {
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type: string;
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text?: string;
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image_url?: {
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url: string;
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};
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document?: {
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format: string;
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name: string;
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source: {
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bytes: string;
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};
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};
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}
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type ProcessedContent =
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| ContentItem
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| BedrockTextBlock
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| BedrockImageBlock
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| BedrockDocumentBlock
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| {
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type: string;
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source: { type: string; media_type: string; data: string };
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};
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// Helper function to format request body based on model type
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export function formatRequestBody(request: ConverseRequest) {
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const baseModel = request.modelId;
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const messages = validateMessageOrder(request.messages).map((msg) => ({
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role: msg.role,
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content: Array.isArray(msg.content)
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? msg.content.map((item: ContentItem) => {
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if (item.type === "image_url" && item.image_url?.url) {
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// If it's a base64 image URL
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const base64Match = item.image_url.url.match(
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/^data:image\/([a-zA-Z]*);base64,([^"]*)$/,
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);
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if (base64Match) {
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return {
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type: "image",
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source: {
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type: "base64",
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media_type: `image/${base64Match[1]}`,
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data: base64Match[2],
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},
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};
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}
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// If it's not a base64 URL, return as is
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return item;
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}
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if ("document" in item) {
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try {
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return processDocumentContent(item);
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} catch (error) {
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console.error("Error processing document:", error);
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return {
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type: "text",
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text: `[Document: ${item.document?.name || "Unknown"}]`,
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};
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}
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}
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return { type: "text", text: item.text };
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})
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: [{ type: "text", text: msg.content }],
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}));
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const systemPrompt = request.system
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? [{ type: "text", text: request.system }]
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: undefined;
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const baseConfig = {
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max_tokens: request.inferenceConfig?.maxTokens || 2048,
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temperature: request.inferenceConfig?.temperature || 0.7,
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top_p: request.inferenceConfig?.topP || 0.9,
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};
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if (baseModel.startsWith("anthropic.claude")) {
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return {
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messages,
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system: systemPrompt,
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anthropic_version: "bedrock-2023-05-31",
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...baseConfig,
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...(request.tools && { tools: request.tools }),
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};
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} else if (
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baseModel.startsWith("meta.llama") ||
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baseModel.startsWith("mistral.")
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) {
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return {
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messages: messages.map((m) => ({
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role: m.role,
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content: Array.isArray(m.content)
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? m.content.map((c: ProcessedContent) => {
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if ("text" in c) return { type: "text", text: c.text || "" };
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if ("image_url" in c)
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return {
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type: "text",
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text: `[Image: ${c.image_url?.url || "URL not provided"}]`,
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};
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if ("document" in c)
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return {
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type: "text",
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text: `[Document: ${c.document?.name || "Unknown"}]`,
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};
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return { type: "text", text: "" };
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})
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: [{ type: "text", text: m.content }],
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})),
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...baseConfig,
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stop_sequences: ["\n\nHuman:", "\n\nAssistant:"],
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};
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} else if (baseModel.startsWith("amazon.titan")) {
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const formattedText = messages.map((m) => ({
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role: m.role,
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content: [
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{
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type: "text",
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text: `${m.role === "user" ? "Human" : "Assistant"}: ${
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Array.isArray(m.content)
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? m.content
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.map((c: ProcessedContent) => {
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if ("text" in c) return c.text || "";
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if ("image_url" in c)
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return `[Image: ${
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c.image_url?.url || "URL not provided"
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}]`;
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if ("document" in c)
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return `[Document: ${c.document?.name || "Unknown"}]`;
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return "";
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})
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.join("")
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: m.content
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}`,
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},
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],
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}));
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return {
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messages: formattedText,
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textGenerationConfig: {
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maxTokenCount: baseConfig.max_tokens,
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temperature: baseConfig.temperature,
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topP: baseConfig.top_p,
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stopSequences: ["Human:", "Assistant:"],
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},
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};
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}
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throw new Error(`Unsupported model: ${baseModel}`);
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}
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// Helper function to parse and format response based on model type
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export function parseModelResponse(responseBody: string, modelId: string): any {
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const baseModel = modelId;
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try {
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const response = JSON.parse(responseBody);
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// Common response format for all models
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const formatResponse = (content: string | any[]) => ({
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role: "assistant",
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content: Array.isArray(content)
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? content.map((item) => {
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if (typeof item === "string") {
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return { type: "text", text: item };
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}
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// Handle different content types
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if ("text" in item) {
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return { type: "text", text: item.text || "" };
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}
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if ("image" in item) {
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return {
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type: "image_url",
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image_url: {
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url: `data:image/${
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item.source?.media_type || "image/png"
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};base64,${item.source?.data || ""}`,
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},
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};
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}
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// Document responses are converted to text
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if ("document" in item) {
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return {
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type: "text",
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text: `[Document Content]\n${item.text || ""}`,
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};
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}
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return { type: "text", text: item.text || "" };
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})
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: [{ type: "text", text: content }],
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stop_reason: response.stop_reason || response.stopReason || "end_turn",
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usage: response.usage || {
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input_tokens: 0,
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output_tokens: 0,
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total_tokens: 0,
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},
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});
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if (baseModel.startsWith("anthropic.claude")) {
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// Handle the new Converse API response format
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if (response.output?.message) {
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return {
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role: response.output.message.role,
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content: response.output.message.content.map((item: any) => {
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if ("text" in item) return { type: "text", text: item.text || "" };
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if ("image" in item) {
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return {
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type: "image_url",
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image_url: {
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url: `data:${item.source?.media_type || "image/png"};base64,${
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item.source?.data || ""
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}`,
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},
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};
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}
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return { type: "text", text: item.text || "" };
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}),
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stop_reason: response.stopReason,
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usage: response.usage,
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};
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}
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// Fallback for older format
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return formatResponse(
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response.content ||
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(response.completion
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? [{ type: "text", text: response.completion }]
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: []),
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);
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} else if (baseModel.startsWith("meta.llama")) {
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return formatResponse(response.generation || response.completion || "");
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} else if (baseModel.startsWith("amazon.titan")) {
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return formatResponse(response.results?.[0]?.outputText || "");
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} else if (baseModel.startsWith("mistral.")) {
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return formatResponse(
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response.outputs?.[0]?.text || response.response || "",
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);
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}
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throw new Error(`Unsupported model: ${baseModel}`);
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} catch (e) {
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console.error("[Bedrock] Failed to parse response:", e);
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// Return raw text as fallback
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return {
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role: "assistant",
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content: [{ type: "text", text: responseBody }],
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};
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}
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}
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218
app/api/bedrock/utils.ts
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218
app/api/bedrock/utils.ts
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@@ -0,0 +1,218 @@
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import { MultimodalContent } from "../../client/api";
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export interface Message {
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role: string;
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content: string | MultimodalContent[];
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}
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export interface ImageSource {
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bytes: string; // base64 encoded image bytes
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}
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export interface DocumentSource {
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bytes: string; // base64 encoded document bytes
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}
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export interface BedrockImageBlock {
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image: {
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format: "png" | "jpeg" | "gif" | "webp";
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source: ImageSource;
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};
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}
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export interface BedrockDocumentBlock {
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document: {
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format:
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| "pdf"
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| "csv"
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| "doc"
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| "docx"
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| "xls"
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| "xlsx"
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| "html"
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| "txt"
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| "md";
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name: string;
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source: DocumentSource;
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};
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}
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export interface BedrockTextBlock {
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text: string;
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}
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export type BedrockContentBlock =
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| BedrockTextBlock
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| BedrockImageBlock
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| BedrockDocumentBlock;
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export interface BedrockResponse {
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content?: any[];
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completion?: string;
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stop_reason?: string;
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usage?: {
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input_tokens: number;
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output_tokens: number;
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total_tokens: number;
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};
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tool_calls?: any[];
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}
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// Helper function to get the base model type from modelId
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export function getModelType(modelId: string): string {
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if (modelId.includes("inference-profile")) {
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const match = modelId.match(/us\.(meta\.llama.+?)$/);
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if (match) return match[1];
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}
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return modelId;
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}
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// Helper function to validate model ID
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export function validateModelId(modelId: string): string | null {
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// Check if model requires inference profile
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if (
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modelId.startsWith("meta.llama") &&
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!modelId.includes("inference-profile")
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) {
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return "Llama models require an inference profile. Please use the full inference profile ARN.";
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}
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return null;
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}
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// Helper function to process document content for Bedrock
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export function processDocumentContent(content: any): BedrockContentBlock {
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if (
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!content?.document?.format ||
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!content?.document?.name ||
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!content?.document?.source?.bytes
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) {
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throw new Error("Invalid document content format");
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}
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const format = content.document.format.toLowerCase();
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if (
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!["pdf", "csv", "doc", "docx", "xls", "xlsx", "html", "txt", "md"].includes(
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format,
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)
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) {
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throw new Error(`Unsupported document format: ${format}`);
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}
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return {
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document: {
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format: format as BedrockDocumentBlock["document"]["format"],
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name: sanitizeDocumentName(content.document.name),
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source: {
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bytes: content.document.source.bytes,
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},
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},
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};
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}
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// Helper function to format content for Bedrock
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export function formatContent(
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content: string | MultimodalContent[],
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): BedrockContentBlock[] {
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if (typeof content === "string") {
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return [{ text: content }];
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}
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const formattedContent: BedrockContentBlock[] = [];
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for (const item of content) {
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if (item.type === "text" && item.text) {
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formattedContent.push({ text: item.text });
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} else if (item.type === "image_url" && item.image_url?.url) {
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// Extract base64 data from data URL
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const base64Match = item.image_url.url.match(
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/^data:image\/([a-zA-Z]*);base64,([^"]*)$/,
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);
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if (base64Match) {
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const format = base64Match[1].toLowerCase();
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if (["png", "jpeg", "gif", "webp"].includes(format)) {
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formattedContent.push({
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image: {
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format: format as "png" | "jpeg" | "gif" | "webp",
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source: {
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bytes: base64Match[2],
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},
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},
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});
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}
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}
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} else if ("document" in item) {
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try {
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formattedContent.push(processDocumentContent(item));
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} catch (error) {
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console.error("Error processing document:", error);
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// Convert document to text as fallback
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formattedContent.push({
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text: `[Document: ${(item as any).document?.name || "Unknown"}]`,
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});
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}
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}
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}
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return formattedContent;
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}
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// Helper function to ensure messages alternate between user and assistant
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export function validateMessageOrder(messages: Message[]): Message[] {
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const validatedMessages: Message[] = [];
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let lastRole = "";
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for (const message of messages) {
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if (message.role === lastRole) {
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// Skip duplicate roles to maintain alternation
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continue;
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}
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validatedMessages.push(message);
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lastRole = message.role;
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}
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return validatedMessages;
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}
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// Helper function to sanitize document names according to Bedrock requirements
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function sanitizeDocumentName(name: string): string {
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// Remove any characters that aren't alphanumeric, whitespace, hyphens, or parentheses
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let sanitized = name.replace(/[^a-zA-Z0-9\s\-\(\)\[\]]/g, "");
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// Replace multiple whitespace characters with a single space
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sanitized = sanitized.replace(/\s+/g, " ");
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// Trim whitespace from start and end
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return sanitized.trim();
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}
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// Helper function to convert Bedrock response back to MultimodalContent format
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export function convertBedrockResponseToMultimodal(
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response: BedrockResponse,
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): string | MultimodalContent[] {
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if (response.completion) {
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return response.completion;
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}
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if (!response.content) {
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return "";
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}
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return response.content.map((block) => {
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if ("text" in block) {
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return {
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type: "text",
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text: block.text,
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};
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} else if ("image" in block) {
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return {
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type: "image_url",
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image_url: {
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url: `data:image/${block.image.format};base64,${block.image.source.bytes}`,
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},
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};
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}
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// Document responses are converted to text content
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return {
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type: "text",
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text: block.text || "",
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};
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});
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}
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