ICE | ICE : Item Concept Embedding | Machine Learning library

You're missing an important thing:

Here is a complete example of what you are trying to accomplish. Notice that it also has code for a Google STUN server, but it is remarked out: https://owebio.github.io/serverless-webrtc-chat/.

That page uses two iframes:

Create: https://owebio.github.io/serverless-webrtc-chat/noserv.create.html

Join: https://owebio.github.io/serverless-webrtc-chat/noserv.join.html.

This should get you started.

Also, two libraries built on WebTorrent exist that can aid in discovering and connecting to peers using only the browser: Bugout, P2PT.

/(?=TITLE: )/g seems like a reasonable start. I'm not sure if the gutter of 2 characters whitespace is in your original text or not, but adding ^ or ^ to the front of the lookahead is nice to better avoid false-positives, i.e. /(?=^TITLE: )/mg, /(?=^ TITLE: )/mg or /(?=^ *TITLE: )/mg.

So, I can clearly see that there you haven't set any local description for the remote user who is going to answer this call.

TL;DR: Do you HAVE to use arrays? If not, use lists

Replace this:

Constructor constructor = dragonTypes[index].getConstructor(String.class, String.class);

With this:

Constructor constructor = dragonTypes.get(index).getConstructor(String.class, String.class);

And this:

private static final Class[] dragonTypes = {Dragon.class, Dragon.class};

With this:

private static final List> dragonTypes = Arrays.asList(Dragon.class, Dragon.class);

Turns out, this is my problem.

To quote from the SO answer "This problem is almost totally undocumented...you can't add ICE candidates without setting remote description..."

Call to addIceCandidate() should not happen before call to setRemoteDescription()

My solution is to cache all incoming ICE candidates from peer and only add them after RTCPeerConnection.signalingState turns to have-remote-offer which should occur after remote description have been set.

First, your TrieNode is using a List, which means you have to do a for-loop O(N) search for each char. It would be faster to use a Map.

(You could also use a 26D array, instead of a map, if you know that you'll only have English letters: [0] = 'A', [1] = 'B', ... [25] = 'Z')

Now I need to search using prefix so if the user searches for bur it'll show Burger. But if someone write Garlic Butter I need to Garlic Parmesan Butter. So, basically if the search query has multiple words I need to show the correct name.

bur is easy to do, as that's what a Trie data structure is for, but the garlic butter one is harder. You probably want to look into how to implement a fuzzy search or "did you mean...?" type algorithm:

• Fuzzy search algorithm (approximate string matching algorithm)

However, maybe this is more complex than you want.

Here are some alternatives I thought of:

Change your TrieNode to store a String variable stating the "standard" word. So the final TrieNode of garlic parmesan butter and garlic butter would both have an instance variable that stores garlic butter (the main standard/common word you want to use).

Your TrieNode would be like this:

I guess you are trying to use firebase as a signalling medium and want to use react-native-webrtc for the video calling.

Here is the sample code I have for the same solution with the latest libraries and react-native version.

Firebase Installation React Native.

Just set up ios and android using this above link and then use the below code for reference.

In the provided code, you are passing a FIRDocumentReference instance as a string to collection.document(). When you stringify an object instance without a description string, it becomes something like .

Try something like this instead: