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Summary of Changes

Hello @XinyueDu, I'm Gemini Code Assist1! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed!

This pull request introduces a new playground demo application designed to showcase conversational chart generation. It provides a user-friendly chat interface where users can describe their desired charts using natural language. The system leverages an underlying LLM to interpret these requests and interact with an MCP Server Chart, which then generates the appropriate chart configurations. These configurations are rendered visually using @antv/gpt-vis, offering a seamless experience for creating data visualizations through conversation. The main project documentation has also been updated to reflect these new capabilities and output formats.

Highlights

  • New Conversational Chart Generation Playground: A new playground directory has been added, featuring a demo application that enables users to generate various charts through natural language conversations.
  • LLM Integration for Natural Language Processing: The playground integrates with Large Language Models (LLMs) such as Aliyun Bailian and OpenAI, allowing the system to understand user requests and trigger appropriate chart generation tools.
  • MCP Server Chart and GPT-Vis Integration: The demo seamlessly connects to an MCP Server Chart for chart configuration generation and utilizes @antv/gpt-vis for rendering rich, interactive data visualizations.
  • Updated Documentation: The main README.md now includes a new section detailing the standard output format for chart responses and a link to the newly added playground.
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Code Review

This pull request introduces a new playground application, which serves as an excellent interactive demo for the MCP server's chart generation capabilities. The implementation using React, Vite, and Ant Design is solid. My review includes suggestions to fix an incorrect command in the documentation, improve the robustness of unique ID generation in both the React components and the MCP client, enhance type safety, and ensure documentation consistency.

Comment on lines +182 to +190
const userMessage: Message = {
id: Date.now().toString(),
role: 'user',
content: text,
status: 'success',
};

// 添加用户消息和加载中的助手消息
const loadingMessageId = (Date.now() + 1).toString();

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high

Using Date.now() to generate ids for messages is not robust. If handleSend is called multiple times within the same millisecond, it could result in duplicate keys for React components, leading to unpredictable UI behavior and potential bugs. It's better to use a more reliable method for generating unique IDs, such as crypto.randomUUID().

Suggested change
const userMessage: Message = {
id: Date.now().toString(),
role: 'user',
content: text,
status: 'success',
};
// 添加用户消息和加载中的助手消息
const loadingMessageId = (Date.now() + 1).toString();
const userMessage: Message = {
id: crypto.randomUUID(),
role: 'user',
content: text,
status: 'success',
};
// 添加用户消息和加载中的助手消息
const loadingMessageId = crypto.randomUUID();

await this.connect();
}

const requestId = Date.now();

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high

Using Date.now() for requestId is not guaranteed to be unique. If callTool or listTools are called in rapid succession within the same millisecond, it could lead to request ID collisions. This would cause responses to be routed to the wrong caller, leading to incorrect behavior. A simple incrementing counter would be a more robust solution for generating unique request IDs within the client's session.

You should add a private requestIdCounter = 0; field to the MCPClient class and then use it here. The same applies to the listTools method.

Suggested change
const requestId = Date.now();
const requestId = this.requestIdCounter++;

await this.connect();
}

const requestId = Date.now();

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high

As with callTool, using Date.now() for the requestId is not robust. Please use an incrementing counter here as well to prevent potential request ID collisions.

Suggested change
const requestId = Date.now();
const requestId = this.requestIdCounter++;

### 1. Install Dependencies

```bash
cd demo

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medium

The command cd demo appears to be incorrect. Based on the project structure where this README.md and the package.json are located, the directory should be playground.

Suggested change
cd demo
cd playground

export class LLMService {
private client: OpenAI;
private mcpClient: MCPClient;
private conversationHistory: Array<{ role: string; content: string }> = [];

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medium

The type for conversationHistory is Array<{ role: string; content: string }>, which is too generic. The role property has a specific set of allowed values (e.g., 'system', 'user', 'assistant'). Using a more specific type would improve type safety and code clarity, aligning it with the OpenAI API's expectations.

Suggested change
private conversationHistory: Array<{ role: string; content: string }> = [];
private conversationHistory: Array<{ role: 'system' | 'user' | 'assistant'; content: string }> = [];

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3 participants