mirror of
https://github.com/ParisNeo/lollms-webui.git
synced 2024-12-19 04:17:52 +00:00
Merge branch 'nomic-ai:main' into main
This commit is contained in:
tkocou
GitHub
commit
31eeef6ff6
@ -19,6 +19,7 @@ import threading
|
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import time
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import requests
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import urllib.request
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from tqdm import tqdm
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__author__ = "parisneo"
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__github__ = "https://github.com/nomic-ai/gpt4all-ui"
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@ -38,6 +39,7 @@ class ModelProcess:
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self.started_queue = mp.Queue()
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self.process = None
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self.is_generating = mp.Value('i', 0)
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self.model_ready = mp.Value('i', 0)
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self.ready = False
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def load_backend(self, backend_path):
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@ -103,6 +105,7 @@ class ModelProcess:
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model_file = Path("models")/self.config["backend"]/self.config["model"]
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print(f"Loading model : {model_file}")
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self.model = self.backend(self.config)
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self.model_ready.value = 1
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print("Model created successfully")
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except Exception as ex:
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print("Couldn't build model")
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@ -138,12 +141,15 @@ class ModelProcess:
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def _run(self):
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self._rebuild_model()
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self._rebuild_personality()
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if self.model_ready.value == 1:
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self._generate("I",0,1)
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print()
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print("Ready to receive data")
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print(f"Listening on :http://{self.config['host']}:{self.config['port']}")
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self.ready = True
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else:
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print("No model loaded. Waiting for new configuration instructions")
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self.ready = True
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print(f"Listening on :http://{self.config['host']}:{self.config['port']}")
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while True:
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try:
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self._check_set_config_queue()
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@ -312,7 +318,6 @@ class GPT4AllAPI():
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if installation_path.exists():
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print("Error: Model already exists")
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data.installing = False
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socketio.emit('install_progress',{'status': 'failed', 'error': 'model already exists'})
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socketio.emit('install_progress',{'status': 'progress', 'progress': progress})
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@ -342,6 +347,7 @@ class GPT4AllAPI():
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@socketio.on('generate_msg')
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def generate_msg(data):
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if self.process.model_ready.value==1:
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if self.current_discussion is None:
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if self.db.does_last_discussion_have_messages():
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self.current_discussion = self.db.create_discussion()
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@ -356,6 +362,18 @@ class GPT4AllAPI():
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self.current_user_message_id = message_id
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tpe = threading.Thread(target=self.start_message_generation, args=(message, message_id))
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tpe.start()
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else:
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self.socketio.emit('infos',
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{
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"status":'model_not_ready',
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"type": "input_message_infos",
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"bot": self.personality.name,
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"user": self.personality.user_name,
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"message":"",
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"user_message_id": self.current_user_message_id,
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"ai_message_id": self.current_ai_message_id,
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}
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)
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@socketio.on('generate_msg_from')
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def handle_connection(data):
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@ -390,23 +408,42 @@ class GPT4AllAPI():
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def download_file(self, url, installation_path, callback=None):
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"""
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Downloads a file from a URL and displays the download progress using tqdm.
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Downloads a file from a URL, reports the download progress using a callback function, and displays a progress bar.
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Args:
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url (str): The URL of the file to download.
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installation_path (str): The path where the file should be saved.
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callback (function, optional): A callback function to be called during the download
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with the progress percentage as an argument. Defaults to None.
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"""
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def report_hook(count, block_size, total_size):
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if callback is not None:
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percentage = (count * block_size / total_size) * 100
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callback(percentage)
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try:
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response = requests.get(url, stream=True)
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urllib.request.urlretrieve(url, installation_path, reporthook=report_hook)
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# Get the file size from the response headers
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total_size = int(response.headers.get('content-length', 0))
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with open(installation_path, 'wb') as file:
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downloaded_size = 0
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with tqdm(total=total_size, unit='B', unit_scale=True, ncols=80) as progress_bar:
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for chunk in response.iter_content(chunk_size=8192):
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if chunk:
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file.write(chunk)
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downloaded_size += len(chunk)
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if callback is not None:
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percentage = (downloaded_size / total_size) * 100
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callback(percentage)
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progress_bar.update(len(chunk))
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if callback is not None:
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callback(100.0)
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print("File downloaded successfully")
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except Exception as e:
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print("Couldn't download file:", str(e))
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def load_backend(self, backend_path):
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# define the full absolute path to the module
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@ -544,6 +581,7 @@ class GPT4AllAPI():
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) # first the content is empty, but we'll fill it at the end
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self.socketio.emit('infos',
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{
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"status":'generation_started',
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"type": "input_message_infos",
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"bot": self.personality.name,
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"user": self.personality.user_name,
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@ -22,14 +22,24 @@ socket.on('disconnect', function() {
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console.log("Disconnected")
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});
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socket.on('infos', function(msg) {
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if(globals.user_msg){
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console.log(msg)
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if(msg["status"]=="generation_started"){
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if(globals.user_msg){
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globals.user_msg.setSender(msg.user);
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globals.user_msg.setMessage(msg.message);
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globals.user_msg.setID(msg.id);
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}
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globals.bot_msg.setSender(msg.bot);
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globals.bot_msg.setID(msg.ai_message_id);
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globals.bot_msg.messageTextElement.innerHTML = `Generating answer. Please stand by...`;
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}
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globals.bot_msg.setSender(msg.bot);
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globals.bot_msg.setID(msg.ai_message_id);
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globals.bot_msg.messageTextElement.innerHTML = `Generating answer. Please stand by...`;
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}
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else{
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globals.sendbtn.style.display="block";
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globals.waitAnimation.style.display="none";
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globals.stopGeneration.style.display = "none";
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globals.is_generating = false
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alert("It seems that no model has been loaded. Please download and install a model first, then try again.");
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}
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});
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socket.on('waiter', function(msg) {
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File diff suppressed because one or more lines are too long
File diff suppressed because one or more lines are too long
4
web/dist/index.html
vendored
4
web/dist/index.html
vendored
@ -6,8 +6,8 @@
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<meta name="viewport" content="width=device-width, initial-scale=1.0">
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<title>GPT4All - WEBUI</title>
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<script type="module" crossorigin src="/assets/index-afd2c992.js"></script>
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<link rel="stylesheet" href="/assets/index-98afc6c1.css">
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<script type="module" crossorigin src="/assets/index-8b53a73b.js"></script>
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<link rel="stylesheet" href="/assets/index-94947680.css">
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</head>
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<body>
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<div id="app"></div>
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@ -26,9 +26,9 @@
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<template v-if="installing">
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<div class="flex items-center space-x-2">
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<div class="h-2 w-20 bg-gray-300 rounded">
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<div :style="{ width: progress + '%' }" class="h-full bg-green-500"></div>
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<div :style="{ width: progress + '%'}" class="h-full bg-red-500 rounded"></div>
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</div>
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<span>Installing...</span>
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<span>Installing...{{ Math.floor(progress) }}%</span>
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</div>
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</template>
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<template v-else-if="uninstalling">
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@ -51,10 +51,6 @@
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import socket from '@/services/websocket.js'
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export default {
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props: {
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progress: {
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type: Number,
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default: 0
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},
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title: String,
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icon: String,
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path: String,
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@ -67,6 +63,7 @@ export default {
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},
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data() {
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return {
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progress: 0,
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installing: false,
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uninstalling: false
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};
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@ -5,6 +5,16 @@
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role="alert">
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<div class="flex flex-row">
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<slot>
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<div v-if="success"
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class="inline-flex items-center justify-center flex-shrink-0 w-8 h-8 text-green-500 bg-green-100 rounded-lg dark:bg-green-800 dark:text-green-200">
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<i data-feather="check"></i>
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<span class="sr-only">Check icon</span>
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</div>
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<div v-if="!success" class="inline-flex items-center justify-center flex-shrink-0 w-8 h-8 text-red-500 bg-red-100 rounded-lg dark:bg-red-800 dark:text-red-200">
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<i data-feather="x"></i>
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<span class="sr-only">Cross icon</span>
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</div>
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<div class="ml-3 text-sm font-normal">{{ message }}</div>
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</slot>
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</div>
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@ -19,6 +29,7 @@
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clip-rule="evenodd"></path>
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</svg>
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</button>
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</div>
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</div>
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</template>
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@ -34,12 +45,23 @@ export default {
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data() {
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return {
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show: false,
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success: true,
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message: ''
|
||||
};
|
||||
},
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methods: {
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close() {
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this.$emit('close')
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this.show = false
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},
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showToast(message, duration_s=3, success= true){
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this.success = success;
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this.message = message;
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this.show = true;
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||||
setTimeout(() => {
|
||||
this.$emit('close')
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this.show = false
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}, duration_s*1000);
|
||||
}
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},
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watch: {
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@ -131,13 +131,7 @@
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</div>
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</div>
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<Toast :showProp="isCopiedToClipboard" @close="isCopiedToClipboard = false">
|
||||
<div
|
||||
class="inline-flex items-center justify-center flex-shrink-0 w-8 h-8 text-green-500 bg-green-100 rounded-lg dark:bg-green-800 dark:text-green-200">
|
||||
<i data-feather="check"></i>
|
||||
<span class="sr-only">Check icon</span>
|
||||
</div>
|
||||
<div class="ml-3 text-sm font-normal">Message content copied to clipboard!</div>
|
||||
<Toast ref="toast">
|
||||
</Toast>
|
||||
|
||||
</template>
|
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@ -166,7 +160,7 @@ export default {
|
||||
isSelectAll: false,
|
||||
showConfirmation: false,
|
||||
chime: new Audio("chime_aud.wav"),
|
||||
isCopiedToClipboard: false,
|
||||
showToast: false,
|
||||
isSearch: false,
|
||||
isDiscussionBottom: false,
|
||||
}
|
||||
@ -427,14 +421,15 @@ export default {
|
||||
// Update previous message with reponse user data
|
||||
//
|
||||
// msgObj
|
||||
//
|
||||
// "status": "if the model is not ready this will inform the user that he can't promt the model"
|
||||
// "type": "input_message_infos",
|
||||
// "bot": self.personality.name,
|
||||
// "user": self.personality.user_name,
|
||||
// "message":message,#markdown.markdown(message),
|
||||
// "user_message_id": self.current_user_message_id,
|
||||
// "ai_message_id": self.current_ai_message_id,
|
||||
|
||||
console.log(msgObj);
|
||||
if(msgObj["status"]=="generation_started"){
|
||||
this.updateLastUserMsg(msgObj)
|
||||
// Create response message
|
||||
let responseMessage = {
|
||||
@ -461,6 +456,13 @@ export default {
|
||||
}
|
||||
}
|
||||
console.log("infos", msgObj)
|
||||
}
|
||||
else{
|
||||
this.$refs.toast.showToast("It seems that no model has been loaded. Please download and install a model first, then try again.",4, false)
|
||||
this.isGenerating = false
|
||||
this.setDiscussionLoading(this.currentDiscussion.id, this.isGenerating)
|
||||
this.chime.play()
|
||||
}
|
||||
},
|
||||
sendMsg(msg) {
|
||||
// Sends message to backend
|
||||
@ -746,15 +748,14 @@ export default {
|
||||
this.chime.play()
|
||||
},
|
||||
copyToClipBoard(content) {
|
||||
|
||||
this.isCopiedToClipboard = true
|
||||
this.$refs.toast.showToast("Copied to clipboard successfully")
|
||||
nextTick(() => {
|
||||
feather.replace()
|
||||
|
||||
})
|
||||
},
|
||||
closeToast() {
|
||||
this.isCopiedToClipboard = false
|
||||
this.showToast = false
|
||||
},
|
||||
|
||||
|
||||
|
||||
@ -360,7 +360,7 @@ export default {
|
||||
console.log("received something");
|
||||
if (response.status === 'progress') {
|
||||
console.log(`Progress = ${response.progress}`);
|
||||
this.progress = response.progress;
|
||||
model_object.progress = response.progress
|
||||
} else if (response.status === 'succeeded') {
|
||||
socket.off('install_progress', progressListener);
|
||||
// Update the isInstalled property of the corresponding model
|
||||
@ -373,7 +373,7 @@ export default {
|
||||
// Installation failed or encountered an error
|
||||
model_object.installing = false;
|
||||
this.showProgress = false;
|
||||
console.error('Installation failed:', message.error);
|
||||
console.error('Installation failed:', response.error);
|
||||
}
|
||||
};
|
||||
|
||||
@ -385,7 +385,7 @@ export default {
|
||||
console.log("uninstalling model...")
|
||||
const progressListener = (response) => {
|
||||
if (response.status === 'progress') {
|
||||
this.progress = message.progress;
|
||||
this.progress = response.progress;
|
||||
} else if (response.status === 'succeeded') {
|
||||
console.log(model_object)
|
||||
// Installation completed
|
||||
|
||||
@ -1,88 +0,0 @@
|
||||
[
|
||||
{
|
||||
"md5sum": "81a09a0ddf89690372fc296ff7f625af",
|
||||
"filename": "ggml-gpt4all-j-v1.3-groovy.bin",
|
||||
"filesize": "3785248281",
|
||||
"isDefault": "true",
|
||||
"bestGPTJ": "true",
|
||||
"description": "Current best commercially licensable model based on GPT-J and trained by Nomic AI on the latest curated GPT4All dataset."
|
||||
},
|
||||
{
|
||||
"md5sum": "91f886b68fbce697e9a3cd501951e455",
|
||||
"filename": "ggml-gpt4all-l13b-snoozy.bin",
|
||||
"filesize": "8136770688",
|
||||
"bestLlama": "true",
|
||||
"description": "Current best non-commercially licensable model based on Llama 13b and trained by Nomic AI on the latest curated GPT4All dataset."
|
||||
},
|
||||
{
|
||||
"md5sum": "756249d3d6abe23bde3b1ae272628640",
|
||||
"filename": "ggml-mpt-7b-chat.bin",
|
||||
"filesize": "4854401050",
|
||||
"isDefault": "true",
|
||||
"bestMPT": "true",
|
||||
"requires": "2.4.1",
|
||||
"description": "Current best non-commercially licensable chat model based on MPT and trained by Mosaic ML."
|
||||
},
|
||||
{
|
||||
"md5sum": "879344aaa9d62fdccbda0be7a09e7976",
|
||||
"filename": "ggml-gpt4all-j-v1.2-jazzy.bin",
|
||||
"filesize": "3785248281",
|
||||
"description": "A commercially licensable model based on GPT-J and trained by Nomic AI on the v2 GPT4All dataset."
|
||||
},
|
||||
{
|
||||
"md5sum": "61d48a82cb188cceb14ebb8082bfec37",
|
||||
"filename": "ggml-gpt4all-j-v1.1-breezy.bin",
|
||||
"filesize": "3785248281",
|
||||
"description": "A commercially licensable model based on GPT-J and trained by Nomic AI on the v1 GPT4All dataset."
|
||||
},
|
||||
{
|
||||
"md5sum": "5b5a3f9b858d33b29b52b89692415595",
|
||||
"filename": "ggml-gpt4all-j.bin",
|
||||
"filesize": "3785248281",
|
||||
"description": "A commercially licensable model based on GPT-J and trained by Nomic AI on the v0 GPT4All dataset."
|
||||
},
|
||||
{
|
||||
"md5sum": "29119f8fa11712704c6b22ac5ab792ea",
|
||||
"filename": "ggml-vicuna-7b-1.1-q4_2.bin",
|
||||
"filesize": "4212859520",
|
||||
"description": "A non-commercially licensable model based on Llama 7b and trained by teams from UC Berkeley, CMU, Stanford, MBZUAI, and UC San Diego."
|
||||
},
|
||||
{
|
||||
"md5sum": "95999b7b0699e2070af63bf5d34101a8",
|
||||
"filename": "ggml-vicuna-13b-1.1-q4_2.bin",
|
||||
"filesize": "8136770688",
|
||||
"description": "A non-commercially licensable model based on Llama 13b and trained by teams from UC Berkeley, CMU, Stanford, MBZUAI, and UC San Diego."
|
||||
},
|
||||
{
|
||||
"md5sum": "99e6d129745a3f1fb1121abed747b05a",
|
||||
"filename": "ggml-wizardLM-7B.q4_2.bin",
|
||||
"filesize": "4212864640",
|
||||
"description": "A non-commercially licensable model based on Llama 7b and trained by Microsoft and Peking University."
|
||||
},
|
||||
{
|
||||
"md5sum": "6cb4ee297537c9133bddab9692879de0",
|
||||
"filename": "ggml-stable-vicuna-13B.q4_2.bin",
|
||||
"filesize": "8136777088",
|
||||
"description": "A non-commercially licensable model based on Llama 13b and RLHF trained by Stable AI."
|
||||
},
|
||||
{
|
||||
"md5sum": "120c32a51d020066288df045ef5d52b9",
|
||||
"filename": "ggml-mpt-7b-base.bin",
|
||||
"filesize": "4854401028",
|
||||
"requires": "2.4.1",
|
||||
"description": "A commercially licensable model base pre-trained by Mosaic ML."
|
||||
},
|
||||
{
|
||||
"md5sum": "d5eafd5b0bd0d615cfd5fd763f642dfe",
|
||||
"filename": "ggml-nous-gpt4-vicuna-13b.bin",
|
||||
"filesize": "8136777088",
|
||||
"description": "A non-commercially licensable model based on Vicuna 13b, fine-tuned on ~180,000 instructions, trained by Nous Research."
|
||||
},
|
||||
{
|
||||
"md5sum": "1cfa4958f489f0a0d1ffdf6b37322809",
|
||||
"filename": "ggml-mpt-7b-instruct.bin",
|
||||
"filesize": "4854401028",
|
||||
"requires": "2.4.1",
|
||||
"description": "A commericially licensable instruct model based on MPT and trained by Mosaic ML."
|
||||
}
|
||||
]
|
||||
Loading…
Reference in New Issue
Block a user