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Here’s a detailed breakdown of the goals as AI prompts, written as if you're feeding them to another AI (e.g., an AI software engineer). These prompts request the full application to be built, specifying the behavior, components, and architecture step-by-step.

Build a Python application using the aiortc library that connects to other WebRTC peers using RTCDataChannel. Each peer should be uniquely identified with a generated ID. When the client starts, it should contact a central signaling server (see next prompt) and receive a list of all other online peers. It should then initiate a WebRTC connection to every peer on the list, creating a full mesh. If any connection drops or fails, it should attempt to reconnect periodically.

Build a lightweight signaling server in PHP at https://secupgrade.com/webapi/meshntwrk/index.php. The server should:

• Accept POST requests with the following JSON payload: { "id": "<peer_id>", "peers": [<peer_ids>] }
• Store each peer’s IP address and timestamp
• Clean up inactive peers (offline for 60+ seconds)
• Respond to each request with the full current list of online peers
• Optionally include a “status” boolean (online: true/false) for each peer

In the Python client, after retrieving the peer list from the signaling server, automatically:

• Iterate over every listed peer
• Create an RTCPeerConnection
• Establish a RTCDataChannel for messaging
• Maintain a connection table ({peer_id: connection}) and ping each connection every 10 seconds
• If a peer becomes unreachable, log it, remove it from the local list, and retry on the next sync

Make sure all WebRTC connections are encrypted using DTLS (WebRTC does this by default). Optionally, add an extra layer of AES encryption to all messages passed over the data channel. Each peer can generate a symmetric key and share it in the first message with each connected peer.

Add an online status indicator in the client. Each time the peer list is fetched from the server:

• Show which peers are online (have checked in within 60 seconds)
• Label the local node with a marker such as “(you)”
• Display any nodes that have gone offline as "unreachable"

The Python client should send an updated list of connected peers to the signaling server every 10–30 seconds.

• If a new node joins, it should appear in the list and the client should connect to it immediately
• If a peer disappears (not in server response), disconnect from it and remove it from the connection list

Create a text-based messaging interface over the mesh network.

• Messages should be sent from one peer to all others via the RTCDataChannel
• Optionally, add a command prefix (like /ping, /id, or /msg <id> <message>)
• All incoming messages should include the sender’s peer ID

Test the system with simulated failures:

• Randomly shut down nodes
• Ensure the system detects disconnections
• Observe whether the mesh dynamically repairs itself when the node returns

Package the entire application as:

• A Python script that can run on any OS (Windows, Linux, macOS)
• A sample .env file or config for specifying the peer ID (or allow random generation)
• Optional support for Dockerizing both the client and PHP signaling server

Leave hooks or function placeholders for future features, including:

• File transfer between nodes over WebRTC
• Distributed computing tasks
• Integration with a GUI (e.g., Flask or Tkinter)
• Adding TURN/STUN support for NAT traversal
• Decentralized authentication using cryptographic signatures

Let me know if you'd like all these prompts combined into one long “super prompt” or a script that auto-feeds them to another AI for step-by-step development. I can also provide mockups, folder structure, or example output logs.