diff --git a/templates/types/streaming/express/src/controllers/chat.controller.ts b/templates/types/streaming/express/src/controllers/chat.controller.ts
index beb8d7f173a32b37e71e7bdbfc8217d35458b973..f88397919c8c0ae55a5b610fcca53f41665070f3 100644
--- a/templates/types/streaming/express/src/controllers/chat.controller.ts
+++ b/templates/types/streaming/express/src/controllers/chat.controller.ts
@@ -2,11 +2,7 @@ import { Message, StreamData, streamToResponse } from "ai";
import { Request, Response } from "express";
import { ChatMessage, Settings } from "llamaindex";
import { createChatEngine } from "./engine/chat";
-import {
- DataParserOptions,
- LlamaIndexStream,
- convertMessageContent,
-} from "./llamaindex-stream";
+import { LlamaIndexStream, convertMessageContent } from "./llamaindex-stream";
import { createCallbackManager, createStreamTimeout } from "./stream-helper";
export const chat = async (req: Request, res: Response) => {
@@ -14,10 +10,7 @@ export const chat = async (req: Request, res: Response) => {
const vercelStreamData = new StreamData();
const streamTimeout = createStreamTimeout(vercelStreamData);
try {
- const {
- messages,
- data,
- }: { messages: Message[]; data: DataParserOptions | undefined } = req.body;
+ const { messages }: { messages: Message[] } = req.body;
const userMessage = messages.pop();
if (!messages || !userMessage || userMessage.role !== "user") {
return res.status(400).json({
@@ -28,8 +21,24 @@ export const chat = async (req: Request, res: Response) => {
const chatEngine = await createChatEngine();
+ let annotations = userMessage.annotations;
+ if (!annotations) {
+ // the user didn't send any new annotations with the last message
+ // so use the annotations from the last user message that has annotations
+ // REASON: GPT4 doesn't consider MessageContentDetail from previous messages, only strings
+ annotations = messages
+ .slice()
+ .reverse()
+ .find(
+ (message) => message.role === "user" && message.annotations,
+ )?.annotations;
+ }
+
// Convert message content from Vercel/AI format to LlamaIndex/OpenAI format
- const userMessageContent = convertMessageContent(userMessage.content, data);
+ const userMessageContent = convertMessageContent(
+ userMessage.content,
+ annotations,
+ );
// Setup callbacks
const callbackManager = createCallbackManager(vercelStreamData);
@@ -44,12 +53,7 @@ export const chat = async (req: Request, res: Response) => {
});
// Return a stream, which can be consumed by the Vercel/AI client
- const stream = LlamaIndexStream(response, vercelStreamData, {
- parserOptions: {
- imageUrl: data?.imageUrl,
- csvFiles: data?.csvFiles,
- },
- });
+ const stream = LlamaIndexStream(response, vercelStreamData);
return streamToResponse(stream, res, {}, vercelStreamData);
} catch (error) {
diff --git a/templates/types/streaming/express/src/controllers/llamaindex-stream.ts b/templates/types/streaming/express/src/controllers/llamaindex-stream.ts
index a8c055a4538409ba8400fe4c29a765ac4f6fe470..f2f4b5a33f60aedb4fb8598e3e2757328280af7c 100644
--- a/templates/types/streaming/express/src/controllers/llamaindex-stream.ts
+++ b/templates/types/streaming/express/src/controllers/llamaindex-stream.ts
@@ -1,4 +1,5 @@
import {
+ JSONValue,
StreamData,
createCallbacksTransformer,
createStreamDataTransformer,
@@ -7,6 +8,7 @@ import {
} from "ai";
import {
MessageContent,
+ MessageContentDetail,
Metadata,
NodeWithScore,
Response,
@@ -20,42 +22,66 @@ type LlamaIndexResponse =
| AgentStreamChatResponse<ToolCallLLMMessageOptions>
| Response;
-export type DataParserOptions = {
- imageUrl?: string;
- csvFiles?: CsvFile[];
-};
-
export const convertMessageContent = (
- textMessage: string,
- additionalData?: DataParserOptions,
+ content: string,
+ annotations?: JSONValue[],
): MessageContent => {
- if (!additionalData) return textMessage;
- const content: MessageContent = [
+ if (!annotations) return content;
+ return [
{
type: "text",
- text: textMessage,
+ text: content,
},
+ ...convertAnnotations(annotations),
];
- if (additionalData?.imageUrl) {
- content.push({
- type: "image_url",
- image_url: {
- url: additionalData?.imageUrl,
- },
- });
- }
+};
- if (additionalData?.csvFiles?.length) {
- const rawContents = additionalData.csvFiles.map((csv) => {
- return "```csv\n" + csv.content + "\n```";
- });
- const csvContent =
- "Use data from following CSV raw contents:\n" + rawContents.join("\n\n");
- content.push({
- type: "text",
- text: `${csvContent}\n\n${textMessage}`,
- });
- }
+const convertAnnotations = (
+ annotations: JSONValue[],
+): MessageContentDetail[] => {
+ const content: MessageContentDetail[] = [];
+ annotations.forEach((annotation: JSONValue) => {
+ // first skip invalid annotation
+ if (
+ !(
+ annotation &&
+ typeof annotation === "object" &&
+ "type" in annotation &&
+ "data" in annotation &&
+ annotation.data &&
+ typeof annotation.data === "object"
+ )
+ ) {
+ console.log(
+ "Client sent invalid annotation. Missing data and type",
+ annotation,
+ );
+ return;
+ }
+ const { type, data } = annotation;
+ // convert image
+ if (type === "image" && "url" in data && typeof data.url === "string") {
+ content.push({
+ type: "image_url",
+ image_url: {
+ url: data.url,
+ },
+ });
+ }
+ // convert CSV files to text
+ if (type === "csv" && "csvFiles" in data && Array.isArray(data.csvFiles)) {
+ const rawContents = data.csvFiles.map((csv) => {
+ return "```csv\n" + (csv as CsvFile).content + "\n```";
+ });
+ const csvContent =
+ "Use data from following CSV raw contents:\n" +
+ rawContents.join("\n\n");
+ content.push({
+ type: "text",
+ text: csvContent,
+ });
+ }
+ });
return content;
};
@@ -63,7 +89,6 @@ export const convertMessageContent = (
function createParser(
res: AsyncIterable<LlamaIndexResponse>,
data: StreamData,
- opts?: DataParserOptions,
) {
const it = res[Symbol.asyncIterator]();
const trimStartOfStream = trimStartOfStreamHelper();
@@ -106,10 +131,9 @@ export function LlamaIndexStream(
data: StreamData,
opts?: {
callbacks?: AIStreamCallbacksAndOptions;
- parserOptions?: DataParserOptions;
},
): ReadableStream<Uint8Array> {
- return createParser(response, data, opts?.parserOptions)
+ return createParser(response, data)
.pipeThrough(createCallbacksTransformer(opts?.callbacks))
.pipeThrough(createStreamDataTransformer());
}
diff --git a/templates/types/streaming/fastapi/app/api/routers/models.py b/templates/types/streaming/fastapi/app/api/routers/models.py
index 5b1ebca5bb6b3f8b040c47237b2e49b002ddb359..d870b091453b517181a27bfa552492f92a2fda70 100644
--- a/templates/types/streaming/fastapi/app/api/routers/models.py
+++ b/templates/types/streaming/fastapi/app/api/routers/models.py
@@ -10,11 +10,6 @@ from llama_index.core.llms import ChatMessage, MessageRole
logger = logging.getLogger("uvicorn")
-class Message(BaseModel):
- role: MessageRole
- content: str
-
-
class CsvFile(BaseModel):
content: str
filename: str
@@ -23,7 +18,7 @@ class CsvFile(BaseModel):
type: str
-class DataParserOptions(BaseModel):
+class AnnotationData(BaseModel):
csv_files: List[CsvFile] | None = Field(
default=None,
description="List of CSV files",
@@ -47,15 +42,23 @@ class DataParserOptions(BaseModel):
def to_raw_content(self) -> str:
if self.csv_files is not None and len(self.csv_files) > 0:
- return "Use data from following CSV raw contents" + "\n".join(
+ return "Use data from following CSV raw contents\n" + "\n".join(
[f"```csv\n{csv_file.content}\n```" for csv_file in self.csv_files]
)
+class Annotation(BaseModel):
+ type: str
+ data: AnnotationData
+
+
+class Message(BaseModel):
+ role: MessageRole
+ content: str
+ annotations: List[Annotation] | None = None
+
+
class ChatData(BaseModel):
- data: DataParserOptions | None = Field(
- default=None,
- )
messages: List[Message]
class Config:
@@ -78,11 +81,22 @@ class ChatData(BaseModel):
def get_last_message_content(self) -> str:
"""
- Get the content of the last message along with the data content if available
+ Get the content of the last message along with the data content if available. Fallback to use data content from previous messages
"""
- message_content = self.messages[-1].content
- if self.data:
- message_content += "\n" + self.data.to_raw_content()
+ if len(self.messages) == 0:
+ raise ValueError("There is not any message in the chat")
+ last_message = self.messages[-1]
+ message_content = last_message.content
+ for message in reversed(self.messages):
+ if message.role == MessageRole.USER and message.annotations is not None:
+ annotation_text = "\n".join(
+ [
+ annotation.data.to_raw_content()
+ for annotation in message.annotations
+ ]
+ )
+ message_content = f"{message_content}\n{annotation_text}"
+ break
return message_content
def get_history_messages(self) -> List[Message]:
diff --git a/templates/types/streaming/nextjs/app/api/chat/llamaindex-stream.ts b/templates/types/streaming/nextjs/app/api/chat/llamaindex-stream.ts
index a8c055a4538409ba8400fe4c29a765ac4f6fe470..f2f4b5a33f60aedb4fb8598e3e2757328280af7c 100644
--- a/templates/types/streaming/nextjs/app/api/chat/llamaindex-stream.ts
+++ b/templates/types/streaming/nextjs/app/api/chat/llamaindex-stream.ts
@@ -1,4 +1,5 @@
import {
+ JSONValue,
StreamData,
createCallbacksTransformer,
createStreamDataTransformer,
@@ -7,6 +8,7 @@ import {
} from "ai";
import {
MessageContent,
+ MessageContentDetail,
Metadata,
NodeWithScore,
Response,
@@ -20,42 +22,66 @@ type LlamaIndexResponse =
| AgentStreamChatResponse<ToolCallLLMMessageOptions>
| Response;
-export type DataParserOptions = {
- imageUrl?: string;
- csvFiles?: CsvFile[];
-};
-
export const convertMessageContent = (
- textMessage: string,
- additionalData?: DataParserOptions,
+ content: string,
+ annotations?: JSONValue[],
): MessageContent => {
- if (!additionalData) return textMessage;
- const content: MessageContent = [
+ if (!annotations) return content;
+ return [
{
type: "text",
- text: textMessage,
+ text: content,
},
+ ...convertAnnotations(annotations),
];
- if (additionalData?.imageUrl) {
- content.push({
- type: "image_url",
- image_url: {
- url: additionalData?.imageUrl,
- },
- });
- }
+};
- if (additionalData?.csvFiles?.length) {
- const rawContents = additionalData.csvFiles.map((csv) => {
- return "```csv\n" + csv.content + "\n```";
- });
- const csvContent =
- "Use data from following CSV raw contents:\n" + rawContents.join("\n\n");
- content.push({
- type: "text",
- text: `${csvContent}\n\n${textMessage}`,
- });
- }
+const convertAnnotations = (
+ annotations: JSONValue[],
+): MessageContentDetail[] => {
+ const content: MessageContentDetail[] = [];
+ annotations.forEach((annotation: JSONValue) => {
+ // first skip invalid annotation
+ if (
+ !(
+ annotation &&
+ typeof annotation === "object" &&
+ "type" in annotation &&
+ "data" in annotation &&
+ annotation.data &&
+ typeof annotation.data === "object"
+ )
+ ) {
+ console.log(
+ "Client sent invalid annotation. Missing data and type",
+ annotation,
+ );
+ return;
+ }
+ const { type, data } = annotation;
+ // convert image
+ if (type === "image" && "url" in data && typeof data.url === "string") {
+ content.push({
+ type: "image_url",
+ image_url: {
+ url: data.url,
+ },
+ });
+ }
+ // convert CSV files to text
+ if (type === "csv" && "csvFiles" in data && Array.isArray(data.csvFiles)) {
+ const rawContents = data.csvFiles.map((csv) => {
+ return "```csv\n" + (csv as CsvFile).content + "\n```";
+ });
+ const csvContent =
+ "Use data from following CSV raw contents:\n" +
+ rawContents.join("\n\n");
+ content.push({
+ type: "text",
+ text: csvContent,
+ });
+ }
+ });
return content;
};
@@ -63,7 +89,6 @@ export const convertMessageContent = (
function createParser(
res: AsyncIterable<LlamaIndexResponse>,
data: StreamData,
- opts?: DataParserOptions,
) {
const it = res[Symbol.asyncIterator]();
const trimStartOfStream = trimStartOfStreamHelper();
@@ -106,10 +131,9 @@ export function LlamaIndexStream(
data: StreamData,
opts?: {
callbacks?: AIStreamCallbacksAndOptions;
- parserOptions?: DataParserOptions;
},
): ReadableStream<Uint8Array> {
- return createParser(response, data, opts?.parserOptions)
+ return createParser(response, data)
.pipeThrough(createCallbacksTransformer(opts?.callbacks))
.pipeThrough(createStreamDataTransformer());
}
diff --git a/templates/types/streaming/nextjs/app/api/chat/route.ts b/templates/types/streaming/nextjs/app/api/chat/route.ts
index 223917bc251b2cf58c1dacec888ad192f4f18fa8..d18b3fdb6bcf03e8db512cf998500620a7e9861e 100644
--- a/templates/types/streaming/nextjs/app/api/chat/route.ts
+++ b/templates/types/streaming/nextjs/app/api/chat/route.ts
@@ -4,11 +4,7 @@ import { ChatMessage, Settings } from "llamaindex";
import { NextRequest, NextResponse } from "next/server";
import { createChatEngine } from "./engine/chat";
import { initSettings } from "./engine/settings";
-import {
- DataParserOptions,
- LlamaIndexStream,
- convertMessageContent,
-} from "./llamaindex-stream";
+import { LlamaIndexStream, convertMessageContent } from "./llamaindex-stream";
import { createCallbackManager, createStreamTimeout } from "./stream-helper";
initObservability();
@@ -24,10 +20,7 @@ export async function POST(request: NextRequest) {
try {
const body = await request.json();
- const {
- messages,
- data,
- }: { messages: Message[]; data: DataParserOptions | undefined } = body;
+ const { messages }: { messages: Message[] } = body;
const userMessage = messages.pop();
if (!messages || !userMessage || userMessage.role !== "user") {
return NextResponse.json(
@@ -41,8 +34,24 @@ export async function POST(request: NextRequest) {
const chatEngine = await createChatEngine();
+ let annotations = userMessage.annotations;
+ if (!annotations) {
+ // the user didn't send any new annotations with the last message
+ // so use the annotations from the last user message that has annotations
+ // REASON: GPT4 doesn't consider MessageContentDetail from previous messages, only strings
+ annotations = messages
+ .slice()
+ .reverse()
+ .find(
+ (message) => message.role === "user" && message.annotations,
+ )?.annotations;
+ }
+
// Convert message content from Vercel/AI format to LlamaIndex/OpenAI format
- const userMessageContent = convertMessageContent(userMessage.content, data);
+ const userMessageContent = convertMessageContent(
+ userMessage.content,
+ annotations,
+ );
// Setup callbacks
const callbackManager = createCallbackManager(vercelStreamData);
@@ -57,12 +66,7 @@ export async function POST(request: NextRequest) {
});
// Transform LlamaIndex stream to Vercel/AI format
- const stream = LlamaIndexStream(response, vercelStreamData, {
- parserOptions: {
- imageUrl: data?.imageUrl,
- csvFiles: data?.csvFiles,
- },
- });
+ const stream = LlamaIndexStream(response, vercelStreamData);
// Return a StreamingTextResponse, which can be consumed by the Vercel/AI client
return new StreamingTextResponse(stream, {}, vercelStreamData);
diff --git a/templates/types/streaming/nextjs/app/components/ui/chat/chat-input.tsx b/templates/types/streaming/nextjs/app/components/ui/chat/chat-input.tsx
index 531361beffa0ef2d1f3f4f5ef97ba37970b06b20..8ee4ec3740d0ec089abf9fd592da3449542ee30e 100644
--- a/templates/types/streaming/nextjs/app/components/ui/chat/chat-input.tsx
+++ b/templates/types/streaming/nextjs/app/components/ui/chat/chat-input.tsx
@@ -1,5 +1,4 @@
import { JSONValue } from "ai";
-import { Loader2 } from "lucide-react";
import { useState } from "react";
import { v4 as uuidv4 } from "uuid";
import { MessageAnnotation, MessageAnnotationType } from ".";
@@ -26,12 +25,10 @@ export default function ChatInput(
>,
) {
const [imageUrl, setImageUrl] = useState<string | null>(null);
- const { files, uploadNew, removeFile, resetUploadedFiles } = useCsv(
- props.messages,
- );
+ const { files: csvFiles, upload, remove, reset } = useCsv();
- const getAttachments = () => {
- if (!imageUrl && files.length === 0) return undefined;
+ const getAnnotations = () => {
+ if (!imageUrl && csvFiles.length === 0) return undefined;
const annotations: MessageAnnotation[] = [];
if (imageUrl) {
annotations.push({
@@ -39,16 +36,15 @@ export default function ChatInput(
data: { url: imageUrl },
});
}
- if (files.length > 0) {
+ if (csvFiles.length > 0) {
annotations.push({
type: MessageAnnotationType.CSV,
data: {
- csvFiles: files.map((file) => ({
+ csvFiles: csvFiles.map((file) => ({
id: file.id,
content: file.content,
filename: file.filename,
filesize: file.filesize,
- type: "available",
})),
},
});
@@ -58,31 +54,26 @@ export default function ChatInput(
// default submit function does not handle including annotations in the message
// so we need to use append function to submit new message with annotations
- const submitWithAttachment = (
+ const handleSubmitWithAnnotations = (
e: React.FormEvent<HTMLFormElement>,
- attachments: JSONValue[] | undefined,
+ annotations: JSONValue[] | undefined,
) => {
e.preventDefault();
- props.append!(
- {
- content: props.input,
- role: "user",
- createdAt: new Date(),
- annotations: attachments,
- },
- {
- data: { imageUrl, csvFiles: files },
- },
- );
- setImageUrl(null);
- resetUploadedFiles();
+ props.append!({
+ content: props.input,
+ role: "user",
+ createdAt: new Date(),
+ annotations,
+ });
props.setInput!("");
};
const onSubmit = (e: React.FormEvent<HTMLFormElement>) => {
- const attachments = getAttachments();
- if (attachments) {
- submitWithAttachment(e, attachments);
+ const annotations = getAnnotations();
+ if (annotations) {
+ handleSubmitWithAnnotations(e, annotations);
+ imageUrl && setImageUrl(null);
+ csvFiles.length && reset();
return;
}
props.handleSubmit(e);
@@ -107,7 +98,7 @@ export default function ChatInput(
reader.onload = () => resolve(reader.result as string);
reader.onerror = (error) => reject(error);
});
- const isSuccess = uploadNew({
+ const isSuccess = upload({
id: uuidv4(),
content,
filename: file.name,
@@ -124,7 +115,7 @@ export default function ChatInput(
return await handleUploadImageFile(file);
}
if (file.type === "text/csv") {
- if (files.length > 0) {
+ if (csvFiles.length > 0) {
alert("You can only upload one csv file at a time.");
return;
}
@@ -144,27 +135,17 @@ export default function ChatInput(
{imageUrl && (
<UploadImagePreview url={imageUrl} onRemove={onRemovePreviewImage} />
)}
- {files.length > 0 && (
+ {csvFiles.length > 0 && (
<div className="flex gap-4 w-full overflow-auto py-2">
- {props.isLoading ? (
- <div className="flex gap-2 items-center">
- <Loader2 className="h-4 w-4 animate-spin" />{" "}
- <span>Handling csv files...</span>
- </div>
- ) : (
- <>
- {files.map((csv) => {
- return (
- <UploadCsvPreview
- key={csv.id}
- csv={csv}
- onRemove={() => removeFile(csv)}
- isNew={csv.type === "new_upload"}
- />
- );
- })}
- </>
- )}
+ {csvFiles.map((csv) => {
+ return (
+ <UploadCsvPreview
+ key={csv.id}
+ csv={csv}
+ onRemove={() => remove(csv)}
+ />
+ );
+ })}
</div>
)}
<div className="flex w-full items-start justify-between gap-4 ">
diff --git a/templates/types/streaming/nextjs/app/components/ui/chat/use-csv.ts b/templates/types/streaming/nextjs/app/components/ui/chat/use-csv.ts
index 7c51f444574d632eadf855359a3402bd612a699b..afdbacaa3458405938924db8bc76d56670c7953d 100644
--- a/templates/types/streaming/nextjs/app/components/ui/chat/use-csv.ts
+++ b/templates/types/streaming/nextjs/app/components/ui/chat/use-csv.ts
@@ -1,31 +1,10 @@
"use client";
-import { Message } from "ai";
-import { useEffect, useMemo, useState } from "react";
-import {
- CsvData,
- CsvFile,
- MessageAnnotation,
- MessageAnnotationType,
- getAnnotationData,
-} from ".";
+import { useState } from "react";
+import { CsvFile } from ".";
-interface FrontendCSVData extends CsvFile {
- type: "available" | "new_upload";
-}
-
-export function useCsv(messages: Message[]) {
- const [availableFiles, setAvailableFiles] = useState<FrontendCSVData[]>([]);
- const [uploadedFiles, setUploadedFiles] = useState<FrontendCSVData[]>([]);
-
- const files = useMemo(() => {
- return [...availableFiles, ...uploadedFiles];
- }, [availableFiles, uploadedFiles]);
-
- useEffect(() => {
- const items = getAvailableCsvFiles(messages);
- setAvailableFiles(items.map((data) => ({ ...data, type: "available" })));
- }, [messages]);
+export function useCsv() {
+ const [files, setFiles] = useState<CsvFile[]>([]);
const csvEqual = (a: CsvFile, b: CsvFile) => {
if (a.id === b.id) return true;
@@ -33,53 +12,22 @@ export function useCsv(messages: Message[]) {
return false;
};
- // Get available csv files from annotations chat history
- // returns the unique csv files by id
- const getAvailableCsvFiles = (messages: Message[]): Array<CsvFile> => {
- const docHash: Record<string, CsvFile> = {};
- messages.forEach((message) => {
- if (message.annotations) {
- const csvData = getAnnotationData<CsvData>(
- message.annotations as MessageAnnotation[],
- MessageAnnotationType.CSV,
- );
- csvData.forEach((data) => {
- data.csvFiles.forEach((file) => {
- if (!docHash[file.id]) {
- docHash[file.id] = file;
- }
- });
- });
- }
- });
- return Object.values(docHash);
- };
-
- const uploadNew = (file: CsvFile) => {
+ const upload = (file: CsvFile) => {
const existedCsv = files.find((f) => csvEqual(f, file));
if (!existedCsv) {
- setUploadedFiles((prev) => [...prev, { ...file, type: "new_upload" }]);
+ setFiles((prev) => [...prev, file]);
return true;
}
return false;
};
- const removeFile = (file: FrontendCSVData) => {
- if (file.type === "new_upload") {
- setUploadedFiles((prev) => prev.filter((f) => f.id !== file.id));
- } else {
- setAvailableFiles((prev) => prev.filter((f) => f.id !== file.id));
- }
+ const remove = (file: CsvFile) => {
+ setFiles((prev) => prev.filter((f) => f.id !== file.id));
};
- const resetUploadedFiles = () => {
- setUploadedFiles([]);
+ const reset = () => {
+ setFiles([]);
};
- return {
- files,
- uploadNew,
- removeFile,
- resetUploadedFiles,
- };
+ return { files, upload, remove, reset };
}
diff --git a/templates/types/streaming/nextjs/app/components/ui/upload-csv-preview.tsx b/templates/types/streaming/nextjs/app/components/ui/upload-csv-preview.tsx
index 767ed63c3a0f352345c5eda08021aa32aaabd70b..db540975ce2913a34e6b4aff2e7a6e1132e095ef 100644
--- a/templates/types/streaming/nextjs/app/components/ui/upload-csv-preview.tsx
+++ b/templates/types/streaming/nextjs/app/components/ui/upload-csv-preview.tsx
@@ -17,7 +17,6 @@ import { cn } from "./lib/utils";
export interface UploadCsvPreviewProps {
csv: CsvFile;
onRemove?: () => void;
- isNew?: boolean;
}
export default function UploadCsvPreview(props: UploadCsvPreviewProps) {
@@ -52,7 +51,7 @@ export default function UploadCsvPreview(props: UploadCsvPreviewProps) {
}
function CSVSummaryCard(props: UploadCsvPreviewProps) {
- const { onRemove, isNew, csv } = props;
+ const { onRemove, csv } = props;
return (
<div className="p-2 w-60 max-w-60 bg-secondary rounded-lg text-sm relative cursor-pointer">
<div className="flex flex-row items-center gap-2">
@@ -70,11 +69,6 @@ function CSVSummaryCard(props: UploadCsvPreviewProps) {
</div>
<div className="truncate text-token-text-tertiary flex items-center gap-2">
<span>Spreadsheet</span>
- {isNew && (
- <span className="px-2 py-0.5 bg-red-400 text-white text-xs rounded-2xl">
- new
- </span>
- )}
</div>
</div>
</div>