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commented
1 month ago Potential solution
To implement a peer-to-peer chat feature, we need to create a backend service to store and retrieve chat messages, update the frontend to interact with this backend, and manage the chat state effectively. The solution involves updating endpoints, removing mocked data, configuring Apollo Client, managing state with Jotai, and creating a backend service.
How to implement
Step 1: Update Endpoints
Update the requests/endpoints.ts file to include new endpoints for the chat service.
Updated Code for requests/endpoints.ts
export const httpEndpoint = 'https://bigshortbets.squids.live/bigsb-testnet/graphql';
export const wsEndpoint = 'wss://bigshortbets.squids.live/bigsb-testnet/graphql';
export const chatHttpEndpoint = 'https://bigshortbets.squids.live/bigsb-testnet/chat';
export const chatWsEndpoint = 'wss://bigshortbets.squids.live/bigsb-testnet/chat';Step 2: Remove Mocked Data
Remove the mocked data from components/Market/TradingHub/Chat/mockedData.ts.
Updated components/Market/TradingHub/Chat/mockedData.ts
export {};Step 3: Configure Apollo Client
Ensure Apollo Client is configured to use the new chat service endpoints in requests/graphql.ts.
Updated requests/graphql.ts
import { ApolloClient, HttpLink, InMemoryCache, split } from '@apollo/client';
import { GraphQLWsLink } from '@apollo/client/link/subscriptions';
import { httpEndpoint, wsEndpoint } from './endpoints';
import { createClient } from 'graphql-ws';
import { getMainDefinition } from '@apollo/client/utilities';
const httpLink = new HttpLink({
uri: httpEndpoint,
});
const wsLink = new GraphQLWsLink(
createClient({
url: wsEndpoint,
})
);
const splitLink = split(
({ query }) => {
const definition = getMainDefinition(query);
return (
definition.kind === 'OperationDefinition' &&
definition.operation === 'subscription'
);
},
wsLink,
httpLink
);
export const apolloClient = new ApolloClient({
link: splitLink,
cache: new InMemoryCache(),
connectToDevTools: true,
});Step 4: Manage State with Jotai
Add state management for chat messages in store/store.ts.
Updated store/store.ts
import { atom } from 'jotai';
import { TradingHubStateType } from '@/components/Market/TradingHub/TradingHub';
import { EnrichedMarketType } from '@/types/marketTypes';
export const marketsAtom = atom<EnrichedMarketType[]>([]);
export const chosenMarketAtom = atom<EnrichedMarketType | undefined>(undefined);
export const tradingHubStateAtom = atom<TradingHubStateType>('chart');
export const tradingHubPositionsCountAtom = atom<number>(0);
export const tradingHubOrdersCountAtom = atom<number>(0);
export const chosenInterlocutorAtom = atom<string>('0x26C494d6526Df0c43c01480Ee07a870d4Eb0B647');
interface ChatMessage {
id: string;
sender: string;
receiver: string;
content: string;
timestamp: number;
}
export const chatMessagesAtom = atom<ChatMessage[]>([]);
export const newMessageAtom = atom<string>('');Step 5: Create Backend Service
Create a backend service to store and retrieve chat messages in backend/chatService.js.
Updated backend/chatService.js
const express = require('express');
const mongoose = require('mongoose');
const bodyParser = require('body-parser');
mongoose.connect('mongodb://localhost:27017/chatDB', {
useNewUrlParser: true,
useUnifiedTopology: true,
});
const db = mongoose.connection;
db.on('error', console.error.bind(console, 'connection error:'));
db.once('open', function() {
console.log('Connected to MongoDB');
});
const messageSchema = new mongoose.Schema({
sender: String,
receiver: String,
content: String,
timestamp: { type: Date, default: Date.now },
});
const Message = mongoose.model('Message', messageSchema);
const app = express();
app.use(bodyParser.json());
app.post('/api/chat/messages', async (req, res) => {
const { sender, receiver, content } = req.body;
const newMessage = new Message({ sender, receiver, content });
try {
const savedMessage = await newMessage.save();
res.status(201).json(savedMessage);
} catch (error) {
res.status(400).json({ error: error.message });
}
});
app.get('/api/chat/messages', async (req, res) => {
const { sender, receiver } = req.query;
try {
const messages = await Message.find({
$or: [
{ sender, receiver },
{ sender: receiver, receiver: sender },
],
}).sort({ timestamp: 1 });
res.status(200).json(messages);
} catch (error) {
res.status(400).json({ error: error.message });
}
});
const PORT = process.env.PORT || 3000;
app.listen(PORT, () => {
console.log(`Server is running on port ${PORT}`);
});Step 6: Update ChatMessage Component
Ensure ChatMessage component correctly displays messages from the backend.
Updated components/Market/TradingHub/Chat/ChatMessage.tsx
export interface ChatMessageProps {
author: MessageAuthorType;
message: string;
}
export const ChatMessage = ({ author, message }: ChatMessageProps) => {
return (
<div
className={`flex w-full ${author === 'user' && 'justify-end'} ${
author === 'interlocutor' && 'justify-start'
}`}
>
<div
className={`max-w-[50%] break-normal px-[16px] py-[8px]
mb-[16px] ${
author === 'user' &&
'rounded-bl-2xl rounded-tl-2xl rounded-tr-2xl bg-[#87DAA4]'
} ${
author === 'interlocutor' &&
'rounded-br-2xl rounded-tr-2xl rounded-tl-2xl bg-[#23252E]'
}`}
>
<p
className={`break-words text-xs ${
author === 'user' ? 'text-black' : 'text-tetriary'
}`}
>
{message}
</p>
</div>
</div>
);
};Step 7: Update ChatContainer Component
Integrate the new backend chat service into ChatContainer.tsx.
Updated components/Market/TradingHub/Chat/ChatContainer.tsx
import React, { useEffect, useRef, useState } from 'react';
import { IoSend } from 'react-icons/io5';
import { ChatMessage, ChatMessageProps } from './ChatMessage';
import { useAccount } from 'wagmi';
import { truncateAddress } from '@/utils/truncateAddress';
import { FaSearch } from 'react-icons/fa';
import { useAtom } from 'jotai';
import { chosenInterlocutorAtom } from '@/store/store';
import { fetchMessages, sendMessage } from '@/services/chatService';
export const ChatContainer = () => {
const [messages, setMessages] = useState<ChatMessageProps[]>([]);
const [inputVal, setInputVal] = useState<string>('');
const [chosenInterlocutor, setChosenInterlocutor] = useAtom(chosenInterlocutorAtom);
const messagesEndRef = useRef<HTMLDivElement>(null);
const { address } = useAccount();
useEffect(() => {
const loadMessages = async () => {
if (chosenInterlocutor) {
const fetchedMessages = await fetchMessages(chosenInterlocutor);
setMessages(fetchedMessages);
}
};
loadMessages();
}, [chosenInterlocutor]);
const handleSendMessage = async () => {
if (inputVal.trim() !== '') {
const message: ChatMessageProps = { author: address, message: inputVal };
const newMessage = await sendMessage({ ...message, interlocutor: chosenInterlocutor });
setMessages((prevMessages) => [...prevMessages, newMessage]);
setInputVal('');
}
};
const handleKeyPress = (event: React.KeyboardEvent<HTMLInputElement>) => {
if (event.key === 'Enter') {
handleSendMessage();
}
};
return (
<div className='w-full h-full flex pt-4' style={{ height: 'calc(100vh - 229px)' }}>
<div className='w-[200px] h-full border-r border-[#444650] border-t'>
<div className='w-full px-2 my-4'>
<div className='w-full bg-[#23252E] h-[32px] rounded-[100px] flex justify-between items-center mb-3'>
<input
placeholder='Search'
type='text'
className='w-[85%] outline-none bg-[#23252E] h-full rounded-[100px] pl-3 text-xs text-tetriary'
/>
<div className='pr-3 text-tetriary text-sm'>
<FaSearch />
</div>
</div>
</div>
<div className='mb-3'>
<p className='text-[10px] text-tetriary px-2'>All messages</p>
</div>
</div>
<div className='flex-grow h-full border-t border-[#444650] flex flex-col justify-between'>
<div className='flex flex-col justify-between h-full'>
<div className='h-[56px] border-b border-[#444650] flex items-center justify-between px-3'>
<div className='flex items-center gap-1.5'>
<div className='h-4 w-4 rounded-full bg-white'></div>
<p className='text-tetriary text-sm'>
{truncateAddress(chosenInterlocutor)}
</p>
</div>
<div>
<p className='text-[10px] text-tetriary'>
PnL with Opponent:{' '}
<span className='font-bold text-[#87DAA4]'>
+400.50 $DOLLARS
</span>
</p>
</div>
</div>
<div className='flex-1 overflow-auto pb-[16px] no-scrollbar'>
<div className=' flex flex-col p-3 first:mt-2'>
{messages.map((message, key) => (
<ChatMessage
author={message.author}
key={key}
message={message.message}
/>
))}
</div>
</div>
<div className='w-full px-3'>
<div className='w-full bg-[#23252E] h-[42px] rounded-[100px] flex justify-between items-center mb-3'>
<input
onChange={(e) => setInputVal(e.target.value)}
type='text'
value={inputVal}
onKeyPress={handleKeyPress}
placeholder='Your message here'
className='w-[85%] outline-none bg-[#23252E] h-full rounded-[100px] pl-3 text-xs text-tetriary'
/>
<button
className='pr-3 text-tetriary'
onClick={handleSendMessage}
>
<IoSend />
</button>
</div>
</div>
</div>
</div>
</div>
);
};Click here to create a Pull Request with the proposed solution
Files used for this task:
Changes on requests/endpoints.ts
To address the feature request for a peer-to-peer chat system, we need to add new endpoints for the chat service to handle message storage and retrieval. Here's a concrete plan for updating the `requests/endpoints.ts` file: ### Plan for `requests/endpoints.ts` 1. **Define New Endpoints**: Add new HTTP and WebSocket endpoints specifically for the chat service. 2. **Ensure Compatibility**: Make sure these endpoints are compatible with the existing infrastructure. ### Updated Code for `requests/endpoints.ts` ```typescript // Existing GraphQL endpoints export const httpEndpoint = 'https://bigshortbets.squids.live/bigsb-testnet/graphql'; export const wsEndpoint = 'wss://bigshortbets.squids.live/bigsb-testnet/graphql'; // New endpoints for chat service export const chatHttpEndpoint = 'https://bigshortbets.squids.live/bigsb-testnet/chat'; export const chatWsEndpoint = 'wss://bigshortbets.squids.live/bigsb-testnet/chat'; ``` ### Explanation - **chatHttpEndpoint**: This will be used for HTTP requests related to storing and retrieving chat messages. - **chatWsEndpoint**: This will be used for WebSocket connections to handle real-time chat functionalities. By adding these new endpoints, the frontend components and state management can now interact with the backend chat service to store and retrieve messages, enabling the peer-to-peer chat feature. If there are no further changes required for this file, this should be sufficient to support the new chat functionality.Changes on components/Market/TradingHub/Chat/mockedData.ts
To address the task for the `components/Market/TradingHub/Chat/mockedData.ts` file, you need to remove or replace the mocked data with actual data fetched from the backend service. Here’s a concrete plan to achieve this: 1. **Remove Mocked Data**: Since the data will now be fetched from the backend, you can remove the existing mocked data. 2. **Fetch Data from Backend**: Instead of using static data, you will fetch the chat messages from the backend service. This will likely involve making an API call to the backend service that you will implement. Here’s how you can modify the file: ### Updated `components/Market/TradingHub/Chat/mockedData.ts` ```typescript // This file is no longer needed as we will fetch data from the backend service. // You can safely delete this file or leave it empty. export {}; ``` ### Additional Steps 1. **Update Chat Container**: Ensure that the `ChatContainer.tsx` is updated to fetch messages from the backend service. This will involve making an API call to the backend and updating the state with the fetched messages. 2. **API Integration**: Ensure that the API endpoints for fetching and storing messages are correctly set up in `requests/endpoints.ts` and `requests/graphql.ts`. 3. **State Management**: Update the state management in `store/store.ts` to handle real-time updates and storage of chat messages. By following these steps, you will successfully transition from using mocked data to fetching actual data from the backend service, thereby enabling real-time peer-to-peer chat functionality.Changes on requests/graphql.ts
To ensure that the Apollo Client is configured to interact with the new chat service endpoints, you need to make sure that the `httpLink` and `wsLink` are correctly set up to point to the new backend chat service endpoints. Here’s a step-by-step plan to achieve this: 1. **Update Endpoints**: Ensure that the `httpEndpoint` and `wsEndpoint` in the `endpoints.ts` file are correctly pointing to the new chat service endpoints. 2. **Modify the Apollo Client Configuration**: Ensure that the Apollo Client is correctly configured to use these endpoints for both HTTP and WebSocket connections. ### Step-by-Step Implementation 1. **Update `endpoints.ts`**: - Ensure that the `httpEndpoint` and `wsEndpoint` are updated to point to the new chat service endpoints. ```typescript // requests/endpoints.ts export const httpEndpoint = 'https://your-chat-service.com/graphql'; export const wsEndpoint = 'wss://your-chat-service.com/graphql'; ``` 2. **Modify `graphql.ts`**: - Ensure that the `httpLink` and `wsLink` are correctly set up to use the new endpoints. - The current configuration in `graphql.ts` already sets up the Apollo Client to use both HTTP and WebSocket links, so you just need to ensure the endpoints are correct. ```typescript import { ApolloClient, HttpLink, InMemoryCache, split } from '@apollo/client'; import { GraphQLWsLink } from '@apollo/client/link/subscriptions'; import { httpEndpoint, wsEndpoint } from './endpoints'; import { createClient } from 'graphql-ws'; import { getMainDefinition } from '@apollo/client/utilities'; const httpLink = new HttpLink({ uri: httpEndpoint, }); const wsLink = new GraphQLWsLink( createClient({ url: wsEndpoint, }) ); const splitLink = split( ({ query }) => { const definition = getMainDefinition(query); return ( definition.kind === 'OperationDefinition' && definition.operation === 'subscription' ); }, wsLink, httpLink ); export const apolloClient = new ApolloClient({ link: splitLink, cache: new InMemoryCache(), connectToDevTools: true, }); ``` ### Summary - Ensure that the `httpEndpoint` and `wsEndpoint` in `endpoints.ts` are correctly pointing to the new chat service. - The existing configuration in `graphql.ts` should work as long as the endpoints are correct. This should enable the Apollo Client to interact with the new chat service endpoints for both HTTP and WebSocket connections. If the endpoints are already correct, no further changes are needed in this file.Changes on store/store.ts
To handle the task of adding state management for chat messages in `store/store.ts`, we need to create atoms that will manage the chat messages and their real-time updates. Here's a step-by-step plan: 1. **Define Chat Message Type**: First, we need to define the structure of a chat message. 2. **Create Atoms for Chat Messages**: We will create atoms to store the list of chat messages and any other necessary state for real-time updates. 3. **Update the Store**: Integrate these atoms into the existing store. ### Step-by-Step Implementation 1. **Define Chat Message Type**: Define a TypeScript interface for the chat message to ensure type safety. ```typescript interface ChatMessage { id: string; sender: string; receiver: string; content: string; timestamp: number; } ``` 2. **Create Atoms for Chat Messages**: Add atoms to manage the list of chat messages and any other necessary state. ```typescript import { atom } from 'jotai'; import { TradingHubStateType } from '@/components/Market/TradingHub/TradingHub'; import { EnrichedMarketType } from '@/types/marketTypes'; // Existing atoms... /* CHAT */ export const chosenInterlocutorAtom = atomChanges on backend/chatService.js
To implement the feature request for peer-to-peer chat functionality, we need to create a backend service that can store and retrieve chat messages. Here's a concrete plan for the `backend/chatService.js` file: ### Plan for `backend/chatService.js` 1. **Set Up Database Connection**: Establish a connection to a database (e.g., MongoDB, PostgreSQL) to store chat messages. 2. **Define Message Schema**: Create a schema for chat messages that includes fields like sender, receiver, message content, timestamp, etc. 3. **Create API Routes**: Implement API endpoints for storing and retrieving chat messages. ### Implementation Steps 1. **Install Required Packages**: - If using MongoDB: `mongoose` - If using PostgreSQL: `pg`, `sequelize` - Express for creating API routes: `express` 2. **Set Up Database Connection**: - For MongoDB: ```javascript const mongoose = require('mongoose'); mongoose.connect('mongodb://localhost:27017/chatDB', { useNewUrlParser: true, useUnifiedTopology: true, }); const db = mongoose.connection; db.on('error', console.error.bind(console, 'connection error:')); db.once('open', function() { console.log('Connected to MongoDB'); }); ``` - For PostgreSQL: ```javascript const { Sequelize } = require('sequelize'); const sequelize = new Sequelize('database', 'username', 'password', { host: 'localhost', dialect: 'postgres', }); sequelize.authenticate() .then(() => { console.log('Connection has been established successfully.'); }) .catch(err => { console.error('Unable to connect to the database:', err); }); ``` 3. **Define Message Schema**: - For MongoDB: ```javascript const mongoose = require('mongoose'); const messageSchema = new mongoose.Schema({ sender: String, receiver: String, content: String, timestamp: { type: Date, default: Date.now }, }); const Message = mongoose.model('Message', messageSchema); ``` - For PostgreSQL: ```javascript const { Sequelize, DataTypes } = require('sequelize'); const sequelize = new Sequelize('database', 'username', 'password', { host: 'localhost', dialect: 'postgres', }); const Message = sequelize.define('Message', { sender: { type: DataTypes.STRING, allowNull: false, }, receiver: { type: DataTypes.STRING, allowNull: false, }, content: { type: DataTypes.STRING, allowNull: false, }, timestamp: { type: DataTypes.DATE, defaultValue: Sequelize.NOW, }, }); Message.sync(); ``` 4. **Create API Routes**: ```javascript const express = require('express'); const router = express.Router(); // Endpoint to store a new message router.post('/messages', async (req, res) => { const { sender, receiver, content } = req.body; const newMessage = new Message({ sender, receiver, content, }); try { const savedMessage = await newMessage.save(); res.status(201).json(savedMessage); } catch (error) { res.status(400).json({ error: error.message }); } }); // Endpoint to retrieve messages between two users router.get('/messages', async (req, res) => { const { sender, receiver } = req.query; try { const messages = await Message.find({ $or: [ { sender, receiver }, { sender: receiver, receiver: sender }, ], }).sort({ timestamp: 1 }); res.status(200).json(messages); } catch (error) { res.status(400).json({ error: error.message }); } }); module.exports = router; ``` 5. **Integrate with Main Server**: ```javascript const express = require('express'); const bodyParser = require('body-parser'); const chatService = require('./chatService'); const app = express(); app.use(bodyParser.json()); app.use('/api/chat', chatService); const PORT = process.env.PORT || 3000; app.listen(PORT, () => { console.log(`Server is running on port ${PORT}`); }); ``` By following these steps, you will have a backend service capable of storing and retrieving chat messages, which can then be integrated with the frontend components to provide the desired peer-to-peer chat functionality.Changes on components/Market/TradingHub/Chat/ChatMessage.tsx
To ensure that the `ChatMessage` component correctly displays messages retrieved from the backend service, you need to make sure that it can handle the data structure returned by the backend and render it appropriately. Here’s a concrete plan to achieve this: ### Plan for `ChatMessage.tsx` 1. **Verify Data Structure**: Ensure that the data structure of the messages retrieved from the backend matches the expected `ChatMessageProps` interface. If necessary, adjust the interface to match the backend data. 2. **Update Component Props**: Ensure that the `ChatMessage` component receives the correct props from its parent component. This involves verifying that the parent component (`ChatContainer.tsx`) correctly passes the data fetched from the backend. 3. **Styling and Display**: Ensure that the styling and display logic correctly differentiate between messages from the user and the interlocutor. ### Steps to Implement 1. **Verify and Adjust Data Structure**: - Ensure that the backend returns messages in a format that includes an `author` and `value` field. - If the backend data structure is different, adjust the `ChatMessageProps` interface accordingly. 2. **Update Parent Component**: - Ensure that `ChatContainer.tsx` correctly fetches messages from the backend and passes them to `ChatMessage` as props. 3. **Styling and Display**: - Verify that the current styling logic correctly applies based on the `author` prop. - Test the component with different message data to ensure it displays correctly. ### Example Code Adjustments If the backend returns messages in the following format: ```json { "author": "user", "message": "Hello, how are you?" } ``` You might need to adjust the `ChatMessageProps` interface and the component to match this structure: ```typescript export interface ChatMessageProps { author: MessageAuthorType; message: string; // Adjusted from 'value' to 'message' } export const ChatMessage = ({ author, message }: ChatMessageProps) => { return ({message} {/* Adjusted from 'value' to 'message' */}
Changes on components/Market/TradingHub/Chat/ChatContainer.tsx
To integrate the new backend chat service into the `ChatContainer.tsx` file, you will need to update the logic to send and retrieve messages from the backend instead of using mocked data. Here is a step-by-step plan to achieve this: 1. **Set Up API Calls**: - Create functions to handle API calls for sending and retrieving messages. 2. **Update State Management**: - Modify the state management to handle messages fetched from the backend. 3. **Fetch Initial Messages**: - Fetch the initial set of messages when the component mounts. 4. **Send Messages to Backend**: - Update the `handleSendMessage` function to send messages to the backend. 5. **Real-Time Updates**: - Optionally, set up real-time updates using WebSockets or polling. ### Step-by-Step Implementation #### 1. Set Up API Calls Create a new file `chatService.js` (or use an existing service file) to handle API calls: ```javascript // chatService.js import axios from 'axios'; const API_URL = 'https://your-backend-url.com/api/chat'; export const fetchMessages = async (interlocutor) => { const response = await axios.get(`${API_URL}/messages`, { params: { interlocutor }, }); return response.data; }; export const sendMessage = async (message) => { const response = await axios.post(`${API_URL}/messages`, message); return response.data; }; ``` #### 2. Update State Management Modify the state management in `ChatContainer.tsx` to handle messages fetched from the backend: ```javascript import React, { useEffect, useRef, useState } from 'react'; import { IoSend } from 'react-icons/io5'; import { ChatMessage, ChatMessageProps } from './ChatMessage'; import { useAccount } from 'wagmi'; import { truncateAddress } from '@/utils/truncateAddress'; import { FaSearch } from 'react-icons/fa'; import { useAtom } from 'jotai'; import { chosenInterlocutorAtom } from '@/store/store'; import { fetchMessages, sendMessage } from '@/services/chatService'; // Import the service export const ChatContainer = () => { const [messages, setMessages] = useStateAll messages
{truncateAddress(chosenInterlocutor)}
PnL with Opponent:{' '} +400.50 $DOLLARS
{messages.map((message, key) => (
setInputVal(e.target.value)}
type='text'
value={inputVal}
onKeyPress={handleKeyPress}
placeholder='Your message here'
className='w-[85%] outline-none bg-[#23252E] h-full rounded-[100px] pl-3 text-xs text-tetriary'
/>
Is your feature request related to a problem? Please describe. I want to add feature that will allow users to chat peer to peer whenever they have position pair. graphql doesnt store messages can you create some backend to store it?