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https://github.com/ChatGPTNextWeb/ChatGPT-Next-Web.git
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1 Commits
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492c071cc7
| Author | SHA1 | Date | |
|---|---|---|---|
|
492c071cc7 |
@ -76,37 +76,9 @@ export async function handle(
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"Stream:",
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body.stream,
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"Messages count:",
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body.messages?.length || 0,
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body.messages.length,
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);
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// Add detailed logging for debugging
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if (body.messages && body.messages.length > 0) {
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body.messages.forEach((msg: any, index: number) => {
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console.log(`[Bedrock] Message ${index}:`, {
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role: msg.role,
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contentType: typeof msg.content,
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isArray: Array.isArray(msg.content),
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contentLength: Array.isArray(msg.content)
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? msg.content.length
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: typeof msg.content === "string"
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? msg.content.length
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: "unknown",
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});
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if (Array.isArray(msg.content)) {
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msg.content.forEach((item: any, itemIndex: number) => {
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console.log(`[Bedrock] Message ${index}, Item ${itemIndex}:`, {
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type: item.type,
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hasImageUrl: !!item.image_url?.url,
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urlPreview: item.image_url?.url
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? item.image_url.url.substring(0, 50) + "..."
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: null,
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});
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});
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}
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});
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}
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const {
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messages,
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model,
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@ -115,27 +87,6 @@ export async function handle(
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max_tokens,
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} = body;
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// --- Input Validation ---
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if (!model || typeof model !== "string") {
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return NextResponse.json(
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{
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error: true,
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msg: "Model parameter is required and must be a string",
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},
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{ status: 400 },
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);
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}
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if (!Array.isArray(messages) || messages.length === 0) {
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return NextResponse.json(
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{
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error: true,
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msg: "Messages parameter is required and must be a non-empty array",
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},
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{ status: 400 },
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);
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}
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// --- Payload formatting for Claude on Bedrock ---
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const isClaudeModel = model.includes("anthropic.claude");
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if (!isClaudeModel) {
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@ -150,298 +101,23 @@ export async function handle(
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(msg: any) => msg.role !== "system",
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);
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// Validate we have non-system messages
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if (userAssistantMessages.length === 0) {
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return NextResponse.json(
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{
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error: true,
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msg: "At least one user or assistant message is required",
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},
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{ status: 400 },
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);
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}
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// Process messages and handle image fetching
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const processedMessages = await Promise.all(
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userAssistantMessages.map(async (msg: any) => {
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let content;
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if (Array.isArray(msg.content)) {
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const processedContent = await Promise.all(
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msg.content.map(async (item: any) => {
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if (item.type === "image_url") {
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console.log("[Bedrock] Processing image_url item:", item);
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// Adapt from OpenAI format to Bedrock's format
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const url = item.image_url?.url;
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if (!url) {
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console.warn(
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"[Bedrock] Image URL is missing in content item",
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);
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return null;
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}
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// Check if it's a data URL or regular URL
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const dataUrlMatch = url.match(
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/^data:(image\/[^;]+);base64,(.+)$/,
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);
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if (dataUrlMatch) {
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// Handle data URL (base64)
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const mediaType = dataUrlMatch[1];
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const base64Data = dataUrlMatch[2];
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if (!base64Data) {
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console.warn("[Bedrock] Empty base64 data in image URL");
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return null;
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}
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const bedrockImageItem = {
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type: "image",
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source: {
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type: "base64",
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media_type: mediaType,
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data: base64Data,
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},
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};
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console.log(
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"[Bedrock] Successfully converted data URL to Bedrock format:",
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{
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mediaType,
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dataLength: base64Data.length,
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},
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);
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return bedrockImageItem;
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} else if (
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url.startsWith("http://") ||
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url.startsWith("https://")
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) {
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// Handle HTTP URL - fetch directly and convert to base64
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console.log(
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"[Bedrock] HTTP URL detected, fetching directly:",
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url.substring(0, 50) + "...",
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);
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try {
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const response = await fetch(url);
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console.log(
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"[Bedrock] Fetch response status:",
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response.status,
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response.statusText,
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);
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if (!response.ok) {
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console.error(
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"[Bedrock] Failed to fetch image:",
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response.status,
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response.statusText,
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);
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return null;
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}
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const blob = await response.blob();
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console.log("[Bedrock] Blob info:", {
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size: blob.size,
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type: blob.type,
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});
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if (blob.size === 0) {
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console.error(
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"[Bedrock] Fetched blob is empty - cache endpoint may not be working",
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);
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console.log(
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"[Bedrock] This might be a service worker cache issue - image was uploaded but cache retrieval failed",
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);
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return null;
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}
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const arrayBuffer = await blob.arrayBuffer();
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console.log(
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"[Bedrock] ArrayBuffer size:",
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arrayBuffer.byteLength,
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);
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if (arrayBuffer.byteLength === 0) {
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console.error("[Bedrock] ArrayBuffer is empty");
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return null;
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}
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const base64Data =
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Buffer.from(arrayBuffer).toString("base64");
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console.log("[Bedrock] Base64 conversion:", {
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originalSize: arrayBuffer.byteLength,
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base64Length: base64Data.length,
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isEmpty: !base64Data || base64Data.length === 0,
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firstChars: base64Data.substring(0, 20),
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});
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if (!base64Data || base64Data.length === 0) {
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console.error(
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"[Bedrock] Base64 data is empty after conversion",
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);
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return null;
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}
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const mediaType = blob.type || "image/jpeg";
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const bedrockImageItem = {
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type: "image",
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source: {
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type: "base64",
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media_type: mediaType,
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data: base64Data,
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},
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};
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console.log(
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"[Bedrock] Successfully converted HTTP URL to Bedrock format:",
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{
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url: url.substring(0, 50) + "...",
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mediaType,
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dataLength: base64Data.length,
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hasValidData: !!base64Data && base64Data.length > 0,
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},
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);
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return bedrockImageItem;
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} catch (error) {
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console.error("[Bedrock] Error fetching image:", error);
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return null;
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}
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} else {
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console.warn(
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"[Bedrock] Invalid URL format:",
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url.substring(0, 50) + "...",
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);
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return null;
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}
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} else {
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// Handle text content
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return item;
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}
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}),
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);
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// Filter out nulls and ensure we have content
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content = processedContent.filter(Boolean);
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// Additional validation: ensure no image objects have empty data
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content = content.filter((item: any) => {
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if (item.type === "image") {
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const hasValidData =
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item.source?.data && item.source.data.length > 0;
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if (!hasValidData) {
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console.error(
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||||
"[Bedrock] Filtering out image with empty data:",
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{
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hasSource: !!item.source,
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hasData: !!item.source?.data,
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dataLength: item.source?.data?.length || 0,
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||||
},
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||||
);
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return false;
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||||
}
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||||
}
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return true;
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||||
});
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if (content.length === 0) {
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console.warn(
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"[Bedrock] All content items were filtered out, adding empty text",
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);
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content = [{ type: "text", text: "" }];
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}
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console.log(
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"[Bedrock] Processed content for message:",
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content.length,
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"items",
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);
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} else if (typeof msg.content === "string") {
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content = [{ type: "text", text: msg.content }];
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||||
} else {
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||||
console.warn("[Bedrock] Unknown content type:", typeof msg.content);
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content = [{ type: "text", text: "" }];
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||||
}
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return {
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role: msg.role,
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content: content,
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||||
};
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}),
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);
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const payload = {
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anthropic_version: "bedrock-2023-05-31",
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max_tokens:
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typeof max_tokens === "number" && max_tokens > 0 ? max_tokens : 4096,
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temperature:
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typeof temperature === "number" && temperature >= 0 && temperature <= 1
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? temperature
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: 0.7, // Bedrock Claude accepts 0-1 range
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messages: processedMessages,
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max_tokens: max_tokens || 4096,
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temperature: temperature,
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messages: userAssistantMessages.map((msg: any) => ({
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role: msg.role, // 'user' or 'assistant'
|
||||
content:
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typeof msg.content === "string"
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? [{ type: "text", text: msg.content }]
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: msg.content, // Assuming MultimodalContent format is compatible
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})),
|
||||
...(systemPrompts.length > 0 && {
|
||||
system: systemPrompts
|
||||
.map((msg: any) => {
|
||||
if (typeof msg.content === "string") {
|
||||
return msg.content;
|
||||
} else if (Array.isArray(msg.content)) {
|
||||
// Handle multimodal system prompts by extracting text
|
||||
return msg.content
|
||||
.filter((item: any) => item.type === "text")
|
||||
.map((item: any) => item.text)
|
||||
.join(" ");
|
||||
}
|
||||
return String(msg.content); // Fallback conversion
|
||||
})
|
||||
.filter(Boolean)
|
||||
.join("\n"),
|
||||
system: systemPrompts.map((msg: any) => msg.content).join("\n"),
|
||||
}),
|
||||
};
|
||||
// --- End Payload Formatting ---
|
||||
|
||||
// Log the final payload structure (without base64 data to avoid huge logs)
|
||||
console.log("[Bedrock] Final payload structure:", {
|
||||
anthropic_version: payload.anthropic_version,
|
||||
max_tokens: payload.max_tokens,
|
||||
temperature: payload.temperature,
|
||||
messageCount: payload.messages.length,
|
||||
messages: payload.messages.map((msg: any, index: number) => ({
|
||||
index,
|
||||
role: msg.role,
|
||||
contentItems: msg.content.map((item: any) => ({
|
||||
type: item.type,
|
||||
hasData: item.type === "image" ? !!item.source?.data : !!item.text,
|
||||
mediaType: item.source?.media_type || null,
|
||||
textLength: item.text?.length || null,
|
||||
dataLength: item.source?.data?.length || null,
|
||||
})),
|
||||
})),
|
||||
hasSystem: !!(payload as any).system,
|
||||
});
|
||||
|
||||
// Final validation: check for any empty images
|
||||
const hasEmptyImages = payload.messages.some((msg: any) =>
|
||||
msg.content.some(
|
||||
(item: any) =>
|
||||
item.type === "image" &&
|
||||
(!item.source?.data || item.source.data.length === 0),
|
||||
),
|
||||
);
|
||||
|
||||
if (hasEmptyImages) {
|
||||
console.error(
|
||||
"[Bedrock] Payload contains empty images, this will cause Bedrock to fail",
|
||||
);
|
||||
return NextResponse.json(
|
||||
{
|
||||
error: true,
|
||||
msg: "Image processing failed: empty image data detected",
|
||||
},
|
||||
{ status: 400 },
|
||||
);
|
||||
}
|
||||
|
||||
if (stream) {
|
||||
const command = new InvokeModelWithResponseStreamCommand({
|
||||
modelId: model,
|
||||
@ -463,23 +139,13 @@ export async function handle(
|
||||
try {
|
||||
for await (const event of responseBody) {
|
||||
if (event.chunk?.bytes) {
|
||||
let chunkData;
|
||||
try {
|
||||
chunkData = JSON.parse(decoder.decode(event.chunk.bytes));
|
||||
} catch (parseError) {
|
||||
console.error(
|
||||
"[Bedrock] Failed to parse chunk JSON:",
|
||||
parseError,
|
||||
);
|
||||
continue; // Skip malformed chunks
|
||||
}
|
||||
|
||||
const chunkData = JSON.parse(decoder.decode(event.chunk.bytes));
|
||||
let responseText = "";
|
||||
let finishReason: string | null = null;
|
||||
|
||||
if (
|
||||
chunkData.type === "content_block_delta" &&
|
||||
chunkData.delta?.type === "text_delta"
|
||||
chunkData.delta.type === "text_delta"
|
||||
) {
|
||||
responseText = chunkData.delta.text || "";
|
||||
} else if (chunkData.type === "message_stop") {
|
||||
@ -490,68 +156,35 @@ export async function handle(
|
||||
: "length"; // Example logic
|
||||
}
|
||||
|
||||
// Only send non-empty responses or finish signals
|
||||
if (responseText || finishReason) {
|
||||
// Format as OpenAI SSE chunk
|
||||
const sseData = {
|
||||
id: `chatcmpl-${nanoid()}`,
|
||||
object: "chat.completion.chunk",
|
||||
created: Math.floor(Date.now() / 1000),
|
||||
model: model,
|
||||
choices: [
|
||||
{
|
||||
index: 0,
|
||||
delta: { content: responseText },
|
||||
finish_reason: finishReason,
|
||||
},
|
||||
],
|
||||
};
|
||||
|
||||
try {
|
||||
controller.enqueue(
|
||||
encoder.encode(`data: ${JSON.stringify(sseData)}\n\n`),
|
||||
);
|
||||
} catch (enqueueError) {
|
||||
console.error(
|
||||
"[Bedrock] Failed to enqueue data:",
|
||||
enqueueError,
|
||||
);
|
||||
break; // Stop processing if client disconnected
|
||||
}
|
||||
}
|
||||
// Format as OpenAI SSE chunk
|
||||
const sseData = {
|
||||
id: `chatcmpl-${nanoid()}`,
|
||||
object: "chat.completion.chunk",
|
||||
created: Math.floor(Date.now() / 1000),
|
||||
model: model,
|
||||
choices: [
|
||||
{
|
||||
index: 0,
|
||||
delta: { content: responseText },
|
||||
finish_reason: finishReason,
|
||||
},
|
||||
],
|
||||
};
|
||||
controller.enqueue(
|
||||
encoder.encode(`data: ${JSON.stringify(sseData)}\n\n`),
|
||||
);
|
||||
|
||||
if (finishReason) {
|
||||
try {
|
||||
controller.enqueue(encoder.encode("data: [DONE]\n\n"));
|
||||
} catch (enqueueError) {
|
||||
console.error(
|
||||
"[Bedrock] Failed to enqueue [DONE]:",
|
||||
enqueueError,
|
||||
);
|
||||
}
|
||||
controller.enqueue(encoder.encode("data: [DONE]\n\n"));
|
||||
break; // Exit loop after stop message
|
||||
}
|
||||
}
|
||||
}
|
||||
} catch (error) {
|
||||
console.error("[Bedrock] Streaming error:", error);
|
||||
try {
|
||||
controller.error(error);
|
||||
} catch (controllerError) {
|
||||
console.error(
|
||||
"[Bedrock] Failed to signal controller error:",
|
||||
controllerError,
|
||||
);
|
||||
}
|
||||
controller.error(error);
|
||||
} finally {
|
||||
try {
|
||||
controller.close();
|
||||
} catch (closeError) {
|
||||
console.error(
|
||||
"[Bedrock] Failed to close controller:",
|
||||
closeError,
|
||||
);
|
||||
}
|
||||
controller.close();
|
||||
}
|
||||
},
|
||||
});
|
||||
@ -572,28 +205,7 @@ export async function handle(
|
||||
body: JSON.stringify(payload),
|
||||
});
|
||||
const response = await client.send(command);
|
||||
|
||||
if (!response.body) {
|
||||
throw new Error("Empty response body from Bedrock");
|
||||
}
|
||||
|
||||
let responseBody;
|
||||
try {
|
||||
responseBody = JSON.parse(new TextDecoder().decode(response.body));
|
||||
} catch (parseError) {
|
||||
console.error("[Bedrock] Failed to parse response JSON:", parseError);
|
||||
throw new Error("Invalid JSON response from Bedrock");
|
||||
}
|
||||
|
||||
// Validate response structure
|
||||
if (
|
||||
!responseBody.content ||
|
||||
!Array.isArray(responseBody.content) ||
|
||||
responseBody.content.length === 0
|
||||
) {
|
||||
console.error("[Bedrock] Invalid response structure:", responseBody);
|
||||
throw new Error("Invalid response structure from Bedrock");
|
||||
}
|
||||
const responseBody = JSON.parse(new TextDecoder().decode(response.body));
|
||||
|
||||
// Format response to match OpenAI
|
||||
const formattedResponse = {
|
||||
|
||||
@ -366,57 +366,31 @@ export function getClientApi(provider: ServiceProvider | string): ClientApi {
|
||||
provider,
|
||||
"| Type:",
|
||||
typeof provider,
|
||||
"| Browser:",
|
||||
navigator.userAgent.includes("Edge")
|
||||
? "Edge"
|
||||
: navigator.userAgent.includes("Safari")
|
||||
? "Safari"
|
||||
: "Other",
|
||||
);
|
||||
|
||||
// Standardize the provider name to match Enum case (TitleCase)
|
||||
let standardizedProvider: ServiceProvider | string;
|
||||
if (typeof provider === "string") {
|
||||
console.log(
|
||||
"[getClientApi] Provider is string, attempting to standardize:",
|
||||
provider,
|
||||
);
|
||||
// Convert known lowercase versions to their Enum equivalent
|
||||
switch (provider.toLowerCase()) {
|
||||
case "bedrock":
|
||||
standardizedProvider = ServiceProvider.Bedrock;
|
||||
console.log(
|
||||
"[getClientApi] Converted 'bedrock' string to ServiceProvider.Bedrock",
|
||||
);
|
||||
break;
|
||||
case "openai":
|
||||
standardizedProvider = ServiceProvider.OpenAI;
|
||||
console.log(
|
||||
"[getClientApi] Converted 'openai' string to ServiceProvider.OpenAI",
|
||||
);
|
||||
break;
|
||||
case "google":
|
||||
standardizedProvider = ServiceProvider.Google;
|
||||
break;
|
||||
// Add other potential lowercase strings if needed
|
||||
default:
|
||||
console.log(
|
||||
"[getClientApi] Unknown string provider, keeping as-is:",
|
||||
provider,
|
||||
);
|
||||
standardizedProvider = provider; // Keep unknown strings as is
|
||||
}
|
||||
} else {
|
||||
console.log("[getClientApi] Provider is already enum value:", provider);
|
||||
standardizedProvider = provider; // Already an Enum value
|
||||
}
|
||||
|
||||
console.log(
|
||||
"[getClientApi] Final Standardized Provider:",
|
||||
standardizedProvider,
|
||||
"| Enum check:",
|
||||
standardizedProvider === ServiceProvider.Bedrock,
|
||||
);
|
||||
console.log("[getClientApi] Standardized Provider:", standardizedProvider);
|
||||
|
||||
switch (standardizedProvider) {
|
||||
case ServiceProvider.Google:
|
||||
@ -457,18 +431,6 @@ export function getClientApi(provider: ServiceProvider | string): ClientApi {
|
||||
console.log(
|
||||
`[getClientApi] Provider '${provider}' (Standardized: '${standardizedProvider}') not matched, returning default GPT.`,
|
||||
);
|
||||
|
||||
// Edge browser fallback: check if this is a Bedrock model by name
|
||||
if (
|
||||
typeof provider === "string" &&
|
||||
provider.includes("anthropic.claude")
|
||||
) {
|
||||
console.log(
|
||||
"[getClientApi] Edge fallback: Detected Bedrock model by name, routing to Bedrock",
|
||||
);
|
||||
return new ClientApi(ModelProvider.Bedrock);
|
||||
}
|
||||
|
||||
return new ClientApi(ModelProvider.GPT);
|
||||
}
|
||||
}
|
||||
|
||||
@ -31,7 +31,7 @@ export class BedrockApi implements LLMApi {
|
||||
messages,
|
||||
temperature: modelConfig.temperature,
|
||||
stream: !!modelConfig.stream,
|
||||
max_tokens: (modelConfig as any).max_tokens || 4096, // Cast to access max_tokens from ModelConfig
|
||||
max_tokens: 4096, // Example: You might want to make this configurable
|
||||
}),
|
||||
signal: controller.signal,
|
||||
headers: getHeaders(), // getHeaders should handle Bedrock (no auth needed)
|
||||
|
||||
@ -77,6 +77,8 @@ import {
|
||||
showPlugins,
|
||||
} from "../utils";
|
||||
|
||||
import { uploadImage as uploadImageRemote } from "@/app/utils/chat";
|
||||
|
||||
import dynamic from "next/dynamic";
|
||||
|
||||
import { ChatControllerPool } from "../client/controller";
|
||||
@ -1151,15 +1153,6 @@ function _Chat() {
|
||||
|
||||
const doSubmit = (userInput: string) => {
|
||||
if (userInput.trim() === "" && isEmpty(attachImages)) return;
|
||||
|
||||
console.log("[doSubmit] Called with:", {
|
||||
userInput: userInput?.substring(0, 50) + "...",
|
||||
hasAttachImages: !!attachImages,
|
||||
attachImagesCount: attachImages?.length || 0,
|
||||
attachImagesPreview:
|
||||
attachImages?.map((img) => img?.substring(0, 50) + "...") || [],
|
||||
});
|
||||
|
||||
const matchCommand = chatCommands.match(userInput);
|
||||
if (matchCommand.matched) {
|
||||
setUserInput("");
|
||||
@ -1583,27 +1576,13 @@ function _Chat() {
|
||||
...(await new Promise<string[]>((res, rej) => {
|
||||
setUploading(true);
|
||||
const imagesData: string[] = [];
|
||||
// Use compressImage directly to bypass cache issues
|
||||
import("@/app/utils/chat")
|
||||
.then(({ compressImage }) => compressImage(file, 256 * 1024))
|
||||
uploadImageRemote(file)
|
||||
.then((dataUrl) => {
|
||||
console.log("[uploadImage] Compressed image:", {
|
||||
fileSize: file.size,
|
||||
fileName: file.name,
|
||||
dataUrlLength: dataUrl.length,
|
||||
isDataUrl: dataUrl.startsWith("data:"),
|
||||
});
|
||||
imagesData.push(dataUrl);
|
||||
if (
|
||||
imagesData.length === 3 ||
|
||||
imagesData.length === 1 // Only one file in this context
|
||||
) {
|
||||
setUploading(false);
|
||||
res(imagesData);
|
||||
}
|
||||
setUploading(false);
|
||||
res(imagesData);
|
||||
})
|
||||
.catch((e) => {
|
||||
console.error("[uploadImage] Compression failed:", e);
|
||||
setUploading(false);
|
||||
rej(e);
|
||||
});
|
||||
@ -1639,16 +1618,8 @@ function _Chat() {
|
||||
const imagesData: string[] = [];
|
||||
for (let i = 0; i < files.length; i++) {
|
||||
const file = event.target.files[i];
|
||||
// Use compressImage directly to bypass cache issues
|
||||
import("@/app/utils/chat")
|
||||
.then(({ compressImage }) => compressImage(file, 256 * 1024))
|
||||
uploadImageRemote(file)
|
||||
.then((dataUrl) => {
|
||||
console.log("[uploadImage] Compressed image:", {
|
||||
fileSize: file.size,
|
||||
fileName: file.name,
|
||||
dataUrlLength: dataUrl.length,
|
||||
isDataUrl: dataUrl.startsWith("data:"),
|
||||
});
|
||||
imagesData.push(dataUrl);
|
||||
if (
|
||||
imagesData.length === 3 ||
|
||||
@ -1659,7 +1630,6 @@ function _Chat() {
|
||||
}
|
||||
})
|
||||
.catch((e) => {
|
||||
console.error("[uploadImage] Compression failed:", e);
|
||||
setUploading(false);
|
||||
rej(e);
|
||||
});
|
||||
|
||||
@ -475,7 +475,6 @@ export const VISION_MODEL_REGEXES = [
|
||||
/gpt-4o/,
|
||||
/gpt-4\.1/,
|
||||
/claude-3/,
|
||||
/anthropic\.claude-3/,
|
||||
/gemini-1\.5/,
|
||||
/gemini-exp/,
|
||||
/gemini-2\.0/,
|
||||
@ -679,24 +678,6 @@ const siliconflowModels = [
|
||||
"Pro/deepseek-ai/DeepSeek-V3",
|
||||
];
|
||||
|
||||
const bedrockModels = [
|
||||
"anthropic.claude-3-opus-20240229-v1:0",
|
||||
"anthropic.claude-3-sonnet-20240229-v1:0",
|
||||
"anthropic.claude-3-haiku-20240307-v1:0",
|
||||
"anthropic.claude-3-5-sonnet-20240620-v1:0",
|
||||
"anthropic.claude-3-5-sonnet-20241022-v1:0",
|
||||
"anthropic.claude-3-5-haiku-20241022-v1:0",
|
||||
"anthropic.claude-instant-v1",
|
||||
"amazon.titan-text-express-v1",
|
||||
"amazon.titan-text-lite-v1",
|
||||
"cohere.command-text-v14",
|
||||
"cohere.command-light-text-v14",
|
||||
"ai21.j2-ultra-v1",
|
||||
"ai21.j2-mid-v1",
|
||||
"meta.llama2-13b-chat-v1",
|
||||
"meta.llama2-70b-chat-v1",
|
||||
];
|
||||
|
||||
let seq = 1000; // 内置的模型序号生成器从1000开始
|
||||
export const DEFAULT_MODELS = [
|
||||
...openaiModels.map((name) => ({
|
||||
@ -853,17 +834,6 @@ export const DEFAULT_MODELS = [
|
||||
sorted: 14,
|
||||
},
|
||||
})),
|
||||
...bedrockModels.map((name) => ({
|
||||
name,
|
||||
available: true,
|
||||
sorted: seq++,
|
||||
provider: {
|
||||
id: "bedrock",
|
||||
providerName: "Bedrock",
|
||||
providerType: "bedrock",
|
||||
sorted: 15,
|
||||
},
|
||||
})),
|
||||
] as const;
|
||||
|
||||
export const CHAT_PAGE_SIZE = 15;
|
||||
|
||||
@ -412,24 +412,12 @@ export const useChatStore = createPersistStore(
|
||||
const session = get().currentSession();
|
||||
const modelConfig = session.mask.modelConfig;
|
||||
|
||||
console.log("[onUserInput] Starting with:", {
|
||||
content: content?.substring(0, 50) + "...",
|
||||
hasAttachImages: !!attachImages,
|
||||
attachImagesCount: attachImages?.length || 0,
|
||||
isMcpResponse,
|
||||
});
|
||||
|
||||
// MCP Response no need to fill template
|
||||
let mContent: string | MultimodalContent[] = isMcpResponse
|
||||
? content
|
||||
: fillTemplateWith(content, modelConfig);
|
||||
|
||||
if (!isMcpResponse && attachImages && attachImages.length > 0) {
|
||||
console.log("[onUserInput] Processing attached images:", {
|
||||
imageCount: attachImages.length,
|
||||
firstImagePreview: attachImages[0]?.substring(0, 50) + "...",
|
||||
});
|
||||
|
||||
mContent = [
|
||||
...(content ? [{ type: "text" as const, text: content }] : []),
|
||||
...attachImages.map((url) => ({
|
||||
@ -437,14 +425,6 @@ export const useChatStore = createPersistStore(
|
||||
image_url: { url },
|
||||
})),
|
||||
];
|
||||
|
||||
console.log("[onUserInput] Created multimodal content:", {
|
||||
isArray: Array.isArray(mContent),
|
||||
contentLength: Array.isArray(mContent) ? mContent.length : "N/A",
|
||||
contentTypes: Array.isArray(mContent)
|
||||
? mContent.map((item) => item.type)
|
||||
: "N/A",
|
||||
});
|
||||
}
|
||||
|
||||
let userMessage: ChatMessage = createMessage({
|
||||
@ -490,106 +470,12 @@ export const useChatStore = createPersistStore(
|
||||
"| Model:",
|
||||
modelConfig.model,
|
||||
);
|
||||
|
||||
// Add detailed browser and session logging
|
||||
console.log("[onUserInput] Browser:", navigator.userAgent);
|
||||
console.log(
|
||||
"[onUserInput] Full modelConfig:",
|
||||
JSON.stringify(modelConfig, null, 2),
|
||||
);
|
||||
console.log(
|
||||
"[onUserInput] Session mask:",
|
||||
JSON.stringify(session.mask, null, 2),
|
||||
);
|
||||
|
||||
// --- 日志结束 ---
|
||||
|
||||
// 使用从配置中获取的 providerName，并提供默认值
|
||||
const api: ClientApi = getClientApi(
|
||||
providerNameFromConfig ?? ServiceProvider.OpenAI,
|
||||
);
|
||||
|
||||
// Edge browser workaround: if we're using a Bedrock model but got wrong API, force Bedrock
|
||||
if (
|
||||
modelConfig.model?.includes("anthropic.claude") &&
|
||||
!api.llm.constructor.name.includes("Bedrock")
|
||||
) {
|
||||
console.warn(
|
||||
"[onUserInput] Edge workaround: Detected Bedrock model but wrong API class:",
|
||||
api.llm.constructor.name,
|
||||
"- forcing Bedrock",
|
||||
);
|
||||
const bedrockApi = getClientApi(ServiceProvider.Bedrock);
|
||||
bedrockApi.llm.chat({
|
||||
messages: sendMessages,
|
||||
config: { ...modelConfig, stream: true },
|
||||
onUpdate(message) {
|
||||
botMessage.streaming = true;
|
||||
if (message) {
|
||||
botMessage.content = message;
|
||||
}
|
||||
get().updateTargetSession(session, (session) => {
|
||||
session.messages = session.messages.concat();
|
||||
});
|
||||
},
|
||||
async onFinish(message) {
|
||||
botMessage.streaming = false;
|
||||
if (message) {
|
||||
botMessage.content = message;
|
||||
botMessage.date = new Date().toLocaleString();
|
||||
get().onNewMessage(botMessage, session);
|
||||
}
|
||||
ChatControllerPool.remove(session.id, botMessage.id);
|
||||
},
|
||||
onBeforeTool(tool: ChatMessageTool) {
|
||||
(botMessage.tools = botMessage?.tools || []).push(tool);
|
||||
get().updateTargetSession(session, (session) => {
|
||||
session.messages = session.messages.concat();
|
||||
});
|
||||
},
|
||||
onAfterTool(tool: ChatMessageTool) {
|
||||
botMessage?.tools?.forEach((t, i, tools) => {
|
||||
if (tool.id == t.id) {
|
||||
tools[i] = { ...tool };
|
||||
}
|
||||
});
|
||||
get().updateTargetSession(session, (session) => {
|
||||
session.messages = session.messages.concat();
|
||||
});
|
||||
},
|
||||
onError(error) {
|
||||
const isAborted = error.message?.includes?.("aborted");
|
||||
botMessage.content +=
|
||||
"\n\n" +
|
||||
prettyObject({
|
||||
error: true,
|
||||
message: error.message,
|
||||
});
|
||||
botMessage.streaming = false;
|
||||
userMessage.isError = !isAborted;
|
||||
botMessage.isError = !isAborted;
|
||||
get().updateTargetSession(session, (session) => {
|
||||
session.messages = session.messages.concat();
|
||||
});
|
||||
ChatControllerPool.remove(
|
||||
session.id,
|
||||
botMessage.id ?? messageIndex,
|
||||
);
|
||||
|
||||
console.error("[Chat] failed ", error);
|
||||
},
|
||||
onController(controller) {
|
||||
// collect controller for stop/retry
|
||||
ChatControllerPool.addController(
|
||||
session.id,
|
||||
botMessage.id ?? messageIndex,
|
||||
controller,
|
||||
);
|
||||
},
|
||||
});
|
||||
return;
|
||||
}
|
||||
|
||||
// make request
|
||||
api.llm.chat({
|
||||
messages: sendMessages,
|
||||
|
||||
Loading…
Reference in New Issue
Block a user