Merge branch 'nomic-ai:main' into main

gpt4all_api/api.py

@@ -19,6 +19,7 @@ import threading
 import time
 import requests
 import urllib.request
+from tqdm import tqdm 
 
 __author__ = "parisneo"
 __github__ = "https://github.com/nomic-ai/gpt4all-ui"
@@ -38,6 +39,7 @@ class ModelProcess:
         self.started_queue = mp.Queue()
         self.process = None
         self.is_generating  = mp.Value('i', 0)
+        self.model_ready  = mp.Value('i', 0)
         self.ready = False
             
     def load_backend(self, backend_path):
@@ -103,6 +105,7 @@ class ModelProcess:
                 model_file = Path("models")/self.config["backend"]/self.config["model"]
                 print(f"Loading model : {model_file}")
                 self.model = self.backend(self.config)
+                self.model_ready.value = 1
                 print("Model created successfully")
             except Exception as ex:
                 print("Couldn't build model")
@@ -138,12 +141,15 @@ class ModelProcess:
     def _run(self):        
         self._rebuild_model()
         self._rebuild_personality()
+        if self.model_ready.value == 1:
             self._generate("I",0,1)
             print()
             print("Ready to receive data")
-        print(f"Listening on :http://{self.config['host']}:{self.config['port']}")
+        else:
-        self.ready = True
+            print("No model loaded. Waiting for new configuration instructions")
                     
+        self.ready = True
+        print(f"Listening on :http://{self.config['host']}:{self.config['port']}")
         while True:
             try:
                 self._check_set_config_queue()
@@ -312,7 +318,6 @@ class GPT4AllAPI():
 
                 if installation_path.exists():
                     print("Error: Model already exists")
-                    data.installing = False
                     socketio.emit('install_progress',{'status': 'failed', 'error': 'model already exists'})
                 
                 socketio.emit('install_progress',{'status': 'progress', 'progress': progress})
@@ -342,6 +347,7 @@ class GPT4AllAPI():
         
         @socketio.on('generate_msg')
         def generate_msg(data):
+            if self.process.model_ready.value==1:
                 if self.current_discussion is None:
                     if self.db.does_last_discussion_have_messages():
                         self.current_discussion = self.db.create_discussion()
@@ -356,6 +362,18 @@ class GPT4AllAPI():
                 self.current_user_message_id = message_id
                 tpe = threading.Thread(target=self.start_message_generation, args=(message, message_id))
                 tpe.start()
+            else:
+                self.socketio.emit('infos',
+                        {
+                            "status":'model_not_ready',
+                            "type": "input_message_infos",
+                            "bot": self.personality.name,
+                            "user": self.personality.user_name,
+                            "message":"",
+                            "user_message_id": self.current_user_message_id,
+                            "ai_message_id": self.current_ai_message_id,
+                        }
+                )
 
         @socketio.on('generate_msg_from')
         def handle_connection(data):
@@ -390,23 +408,42 @@ class GPT4AllAPI():
 
     def download_file(self, url, installation_path, callback=None):
         """
-        Downloads a file from a URL and displays the download progress using tqdm.
+        Downloads a file from a URL, reports the download progress using a callback function, and displays a progress bar.
 
         Args:
             url (str): The URL of the file to download.
+            installation_path (str): The path where the file should be saved.
             callback (function, optional): A callback function to be called during the download
                 with the progress percentage as an argument. Defaults to None.
         """
-        def report_hook(count, block_size, total_size):
+        try:
-            if callback is not None:
+            response = requests.get(url, stream=True)
-                percentage = (count * block_size / total_size) * 100
-                callback(percentage)
 
-        urllib.request.urlretrieve(url, installation_path, reporthook=report_hook)
+            # Get the file size from the response headers
+            total_size = int(response.headers.get('content-length', 0))
+
+            with open(installation_path, 'wb') as file:
+                downloaded_size = 0
+                with tqdm(total=total_size, unit='B', unit_scale=True, ncols=80) as progress_bar:
+                    for chunk in response.iter_content(chunk_size=8192):
+                        if chunk:
+                            file.write(chunk)
+                            downloaded_size += len(chunk)
+                            if callback is not None:
+                                percentage = (downloaded_size / total_size) * 100
+                                callback(percentage)
+                            progress_bar.update(len(chunk))
 
             if callback is not None:
                 callback(100.0)
 
+            print("File downloaded successfully")
+        except Exception as e:
+            print("Couldn't download file:", str(e))
+
+
+
+            
     def load_backend(self, backend_path):
 
         # define the full absolute path to the module
@@ -544,6 +581,7 @@ class GPT4AllAPI():
             )  # first the content is empty, but we'll fill it at the end
             self.socketio.emit('infos',
                     {
+                        "status":'generation_started',
                         "type": "input_message_infos",
                         "bot": self.personality.name,
                         "user": self.personality.user_name,

static/js/websocket.js

@@ -22,6 +22,8 @@ socket.on('disconnect', function() {
 console.log("Disconnected")
 });
 socket.on('infos', function(msg) {
+    console.log(msg)
+    if(msg["status"]=="generation_started"){
         if(globals.user_msg){
             globals.user_msg.setSender(msg.user);
             globals.user_msg.setMessage(msg.message);
@@ -30,6 +32,14 @@ if(globals.user_msg){
         globals.bot_msg.setSender(msg.bot);
         globals.bot_msg.setID(msg.ai_message_id);
         globals.bot_msg.messageTextElement.innerHTML    = `Generating answer. Please stand by...`;    
+    }
+    else{
+        globals.sendbtn.style.display="block";
+        globals.waitAnimation.style.display="none";
+        globals.stopGeneration.style.display = "none";
+        globals.is_generating = false         
+        alert("It seems that no model has been loaded. Please download and install a model first, then try again.");
+    }
 });
 
 socket.on('waiter', function(msg) {

web/dist/index.html

@@ -6,8 +6,8 @@
     
     <meta name="viewport" content="width=device-width, initial-scale=1.0">
     <title>GPT4All - WEBUI</title>
-    <script type="module" crossorigin src="/assets/index-afd2c992.js"></script>
+    <script type="module" crossorigin src="/assets/index-8b53a73b.js"></script>
-    <link rel="stylesheet" href="/assets/index-98afc6c1.css">
+    <link rel="stylesheet" href="/assets/index-94947680.css">
   </head>
   <body>
     <div id="app"></div>

web/src/components/ModelEntry.vue

@@ -26,9 +26,9 @@
         <template v-if="installing">
           <div class="flex items-center space-x-2">
             <div class="h-2 w-20 bg-gray-300 rounded">
-              <div :style="{ width: progress + '%' }" class="h-full bg-green-500"></div>
+              <div :style="{ width: progress + '%'}" class="h-full bg-red-500 rounded"></div>
             </div>
-            <span>Installing...</span>
+            <span>Installing...{{ Math.floor(progress) }}%</span>
           </div>
         </template>
         <template v-else-if="uninstalling">
@@ -51,10 +51,6 @@
 import socket from '@/services/websocket.js'
 export default {
   props: {
-    progress: {
-      type: Number,
-      default: 0
-    },
     title: String,
     icon: String,
     path: String,
@@ -67,6 +63,7 @@ export default {
   },
   data() {
     return {
+      progress: 0,
       installing: false,
       uninstalling: false
     };

web/src/components/Toast.vue

@@ -5,6 +5,16 @@
             role="alert">
             <div class="flex flex-row">
                 <slot>
+                <div v-if="success"
+                    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 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">
+                    <i data-feather="x"></i>
+                    <span class="sr-only">Cross icon</span>
+                </div>             
+                <div class="ml-3 text-sm font-normal">{{ message }}</div>
 
                 </slot>
             </div>
@@ -19,6 +29,7 @@
                         clip-rule="evenodd"></path>
                 </svg>
             </button>
+
         </div>
     </div>
 </template>
@@ -34,12 +45,23 @@ export default {
     data() {
         return {
             show: false,
+            success: true,
+            message: ''
         };
     },
     methods: {
         close() {
             this.$emit('close')
             this.show = false
+        },
+        showToast(message, duration_s=3, success= true){
+            this.success = success;
+            this.message = message;
+            this.show = true;
+            setTimeout(() => {
+                    this.$emit('close')
+                    this.show = false
+                }, duration_s*1000);            
         }
     },
     watch: {

web/src/views/DiscussionsView.vue

@@ -131,13 +131,7 @@
         </div>
 
     </div>
-    <Toast :showProp="isCopiedToClipboard" @close="isCopiedToClipboard = false">
+    <Toast  ref="toast">
-        <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>
     
 </template>
@@ -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.$refs.toast.showToast("It seems that no model has been loaded. Please download and install a model first, then try again.",4, false)
+                this.isGenerating = false
+                this.setDiscussionLoading(this.currentDiscussion.id, this.isGenerating)
+                this.chime.play()
+            }
         },
         sendMsg(msg) {
             // Sends message to backend
@@ -746,15 +748,14 @@ export default {
             this.chime.play()
         },
         copyToClipBoard(content) {
-
+            this.$refs.toast.showToast("Copied to clipboard successfully")
-            this.isCopiedToClipboard = true
             nextTick(() => {
                 feather.replace()
 
             })
         },
         closeToast() {
-            this.isCopiedToClipboard = false
+            this.showToast = false
         },
         
         

web/src/views/SettingsView.vue

@@ -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

zoos/gpt4all_models_zoo.json

@@ -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."
-    }
-  ]