Merge branch 'main' into chat-box

api/__init__.py

@@ -368,7 +368,10 @@ class ModelProcess:
         return output
 
     def _callback(self, text, text_type=0):
-        print(text,end="", flush=True)
+        try:
+            print(str(text),end="", flush=True)
+        except:
+            print(".")
         self.curent_text += text
         detected_anti_prompt = False
         anti_prompt_to_remove=""
@@ -501,7 +504,10 @@ class GPT4AllAPI():
                 def callback(progress):
                     socketio.emit('install_progress',{'status': 'progress', 'progress': progress})
                     
-                self.download_file(model_path, installation_path, callback)
+                if hasattr(self.binding, "download_model"):
+                    self.binding.download_model(model_path, installation_path, callback)
+                else:
+                    self.download_file(model_path, installation_path, callback)
                 socketio.emit('install_progress',{'status': 'succeeded', 'error': ''})
             tpe = threading.Thread(target=install_model_, args=())
             tpe.start()

api/db.py

@@ -274,6 +274,36 @@ class DiscussionsDB:
                 )
             discussions.append(discussion)
         return discussions
+    
+    def import_from_json(self, json_data):
+        discussions = []
+        data = json_data
+        for discussion_data in data:
+            discussion_id = discussion_data.get("id")
+            discussion_title = discussion_data.get("title")
+            messages_data = discussion_data.get("messages", [])
+            discussion = {"id": discussion_id, "title": discussion_title, "messages": []}
+
+            # Insert discussion into the database
+            self.insert("INSERT INTO discussion (id, title) VALUES (?, ?)", (discussion_id, discussion_title))
+
+            for message_data in messages_data:
+                sender = message_data.get("sender")
+                content = message_data.get("content")
+                content_type = message_data.get("type")
+                rank = message_data.get("rank")
+                parent = message_data.get("parent")
+                discussion["messages"].append(
+                    {"sender": sender, "content": content, "type": content_type, "rank": rank, "parent": parent}
+                )
+
+                # Insert message into the database
+                self.insert("INSERT INTO message (sender, content, type, rank, parent, discussion_id) VALUES (?, ?, ?, ?, ?, ?)",
+                            (sender, content, content_type, rank, parent, discussion_id))
+
+            discussions.append(discussion)
+
+        return discussions
 
 class Discussion:
     def __init__(self, discussion_id, discussions_db:DiscussionsDB):

api/langchain.py

@@ -1 +1,84 @@
-# TODO : implement
+try:
+    from langchain.llms.base import LLM
+except ImportError:
+    raise ImportError(
+        'To use the ctransformers.langchain module, please install the '
+        '`langchain` python package: `pip install langchain`')
+
+from typing import Any, Dict, Optional, Sequence
+
+from pydantic import root_validator
+from langchain.callbacks.manager import CallbackManagerForLLMRun
+
+from api.binding import LLMBinding
+
+
+class GenericBinding(LLM):
+    """Wrapper around All compatible LLM interfaces.
+     Thanks to Marella for providing the base for this work.
+     To follow him, here is his github profile:
+     
+     To use, you should have the `langchain` python package installed.
+    """
+
+    client: Any  #: :meta private:
+
+    model: str
+    """The path to a model file or directory or the name of a Hugging Face Hub
+    model repo."""
+
+    model_type: Optional[str] = None
+    """The model type."""
+
+    model_file: Optional[str] = None
+    """The name of the model file in repo or directory."""
+
+    config: Optional[Dict[str, Any]] = None
+    """The config parameters."""
+
+    lib: Optional[Any] = None
+    """The path to a shared library or one of `avx2`, `avx`, `basic`."""
+
+    @property
+    def _identifying_params(self) -> Dict[str, Any]:
+        """Get the identifying parameters."""
+        return {
+            'model': self.model,
+            'model_type': self.model_type,
+            'model_file': self.model_file,
+            'config': self.config,
+        }
+
+    @property
+    def _llm_type(self) -> str:
+        """Return type of llm."""
+        return 'generic_binding'
+
+    @root_validator()
+    def validate_environment(cls, values: Dict) -> Dict:
+        """Validate and load model from a local file or remote repo."""
+        config = values['config'] or {}
+        values['client'] = LLMBinding(config, True)
+        return values
+
+    def _call(
+        self,
+        prompt: str,
+        stop: Optional[Sequence[str]] = None,
+        run_manager: Optional[CallbackManagerForLLMRun] = None,
+    ) -> str:
+        """Generate text from a prompt.
+
+        Args:
+            prompt: The prompt to generate text from.
+            stop: A list of sequences to stop generation when encountered.
+
+        Returns:
+            The generated text.
+        """
+        text = []
+        for chunk in self.client(prompt, stop=stop, stream=True):
+            text.append(chunk)
+            if run_manager:
+                run_manager.on_llm_new_token(chunk, verbose=self.verbose)
+        return ''.join(text)

app.py

@@ -232,6 +232,11 @@ class Gpt4AllWebUI(GPT4AllAPI):
         self.add_endpoint(
             "/export_multiple_discussions", "export_multiple_discussions", self.export_multiple_discussions, methods=["POST"]
         )      
+        self.add_endpoint(
+            "/import_multiple_discussions", "import_multiple_discussions", self.import_multiple_discussions, methods=["POST"]
+        )      
+
+        
         
     def export_multiple_discussions(self):
         data = request.get_json()
@@ -239,6 +244,10 @@ class Gpt4AllWebUI(GPT4AllAPI):
         discussions = self.db.export_discussions_to_json(discussion_ids)
         return jsonify(discussions)
           
+    def import_multiple_discussions(self):
+        data = request.get_json()
+        discussions = data
+        return jsonify(discussions)
         
     def reset(self):
         os.kill(os.getpid(), signal.SIGINT)  # Send the interrupt signal to the current process

bindings/gpt_4all/__init__.py

@@ -24,6 +24,7 @@ __copyright__ = "Copyright 2023, "
 __license__ = "Apache 2.0"
 
 binding_name = "GPT4ALL"
+from gpt4all import GPT4All
 
 class GPT4ALL(LLMBinding):
     file_extension='*.bin'
@@ -64,6 +65,8 @@ class GPT4ALL(LLMBinding):
             str: The detokenized text as a string.
         """
         return None
+    
+
     def generate(self, 
                  prompt:str,                  
                  n_predict: int = 128,
@@ -79,8 +82,19 @@ class GPT4ALL(LLMBinding):
             verbose (bool, optional): If true, the code will spit many informations about the generation process. Defaults to False.
         """
         try:
-            output = ""
-            for tok in self.model.generate(prompt, 
+            response_tokens = []
+            def local_callback(token_id, response):
+                decoded_token = response.decode('utf-8')
+                response_tokens.append( decoded_token );
+                if new_text_callback is not None:
+                    if not new_text_callback(''.join(response_tokens)):
+                        return False
+
+                # Do whatever you want with decoded_token here.
+
+                return True
+            self.model._response_callback = local_callback
+            self.model.generate(prompt, 
                                            n_predict=n_predict,                                           
                                             temp=self.config['temperature'],
                                             top_k=self.config['top_k'],
@@ -88,15 +102,11 @@ class GPT4ALL(LLMBinding):
                                             repeat_penalty=self.config['repeat_penalty'],
                                             repeat_last_n = self.config['repeat_last_n'],
                                             # n_threads=self.config['n_threads'],
-                                            streaming=True,
-                                           ):
-                output += tok
-                if new_text_callback is not None:
-                    if not new_text_callback(tok):
-                        return output
+                                            streaming=False,
+                                           )
         except Exception as ex:
             print(ex)
-        return output
+        return ''.join(response_tokens)
 
     @staticmethod
     def get_available_models():

bindings/gpt_4all/install.py

@@ -32,7 +32,7 @@ class Install:
             subprocess.run(["pip", "install", "--no-cache-dir", "-r", str(requirements_file)])
             
             # Create ther models folder
-            models_folder = Path("./models/c_transformers")
+            models_folder = Path("./models/gpt_4all")
             models_folder.mkdir(exist_ok=True, parents=True)
             
             #Create the install file 

bindings/gptq/__init__.py

@@ -14,6 +14,15 @@ from auto_gptq import AutoGPTQForCausalLM, BaseQuantizeConfig
 from api.binding import LLMBinding
 import torch
 import yaml
+import requests
+from tqdm import tqdm
+import os
+import requests
+from tqdm import tqdm
+from bs4 import BeautifulSoup
+import concurrent.futures
+import wget
+
 
 __author__ = "parisneo"
 __github__ = "https://github.com/ParisNeo/GPTQ_binding"
@@ -33,10 +42,14 @@ class GPTQ(LLMBinding):
         super().__init__(config, False)
         
         self.model_dir = f'{config["model"]}'
+        pretrained_model_dir = "facebook/opt-125m"
+        quantized_model_dir = "opt-125m-4bit"
+
+
+        self.tokenizer = AutoTokenizer.from_pretrained(pretrained_model_dir, use_fast=True)
+        # load quantized model to the first GPU
+        self.model = AutoGPTQForCausalLM.from_quantized(self.model_dir)
 
-        # load quantized model, currently only support cpu or single gpu
-        self.model = AutoGPTQForCausalLM.from_pretrained(self.model_dir, BaseQuantizeConfig())
-        self.tokenizer = AutoTokenizer.from_pretrained(self.model_dir, use_fast=True    )
     def tokenize(self, prompt):
         """
         Tokenizes the given prompt using the model's tokenizer.
@@ -47,7 +60,7 @@ class GPTQ(LLMBinding):
         Returns:
             list: A list of tokens representing the tokenized prompt.
         """
-        return None
+        return self.tokenizer.tokenize(prompt)
 
     def detokenize(self, tokens_list):
         """
@@ -59,7 +72,7 @@ class GPTQ(LLMBinding):
         Returns:
             str: The detokenized text as a string.
         """
-        return None
+        return self.tokenizer.decode(tokens_list)
     def generate(self, 
                  prompt:str,                  
                  n_predict: int = 128,
@@ -82,7 +95,7 @@ class GPTQ(LLMBinding):
             """
             self.model.reset()
             for tok in self.model.generate(prompt, 
-                                           n_predict=n_predict,                                           
+                                            n_predict=n_predict,                                           
                                             temp=self.config['temp'],
                                             top_k=self.config['top_k'],
                                             top_p=self.config['top_p'],
@@ -96,7 +109,59 @@ class GPTQ(LLMBinding):
         except Exception as ex:
             print(ex)
         return output
-            
+
+    def download_model(self, repo, base_folder, callback=None):
+        """
+        Downloads a folder from a Hugging Face repository URL, reports the download progress using a callback function,
+        and displays a progress bar.
+
+        Args:
+            repo (str): The name of the Hugging Face repository.
+            base_folder (str): The base folder where the repository should be saved.
+            installation_path (str): The path where the folder 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.
+        """
+        dont_download = [".gitattributes"]
+
+        url = f"https://huggingface.co/{repo}/tree/main"
+        response = requests.get(url)
+        html_content = response.text
+        soup = BeautifulSoup(html_content, 'html.parser')
+
+        file_names = []
+
+        for a_tag in soup.find_all('a', {'class': 'group'}):
+            span_tag = a_tag.find('span', {'class': 'truncate'})
+            if span_tag:
+                file_name = span_tag.text
+                if file_name not in dont_download:
+                    file_names.append(file_name)
+
+        print(f"Repo: {repo}")
+        print("Found files:")
+        for file in file_names:
+            print(" ", file)
+
+        dest_dir = Path(base_folder) / repo.replace("/", "_")
+        dest_dir.mkdir(parents=True, exist_ok=True)
+        os.chdir(dest_dir)
+
+        def download_file(get_file):
+            filename = f"https://huggingface.co/{repo}/resolve/main/{get_file}"
+            print(f"\nDownloading {filename}")
+            wget.download(filename, out=str(dest_dir), bar=callback)
+
+        with concurrent.futures.ThreadPoolExecutor() as executor:
+            executor.map(download_file, file_names)
+
+        os.chdir(base_folder)
+
+        installation_path = Path(installation_path)
+        installation_path.parent.mkdir(parents=True, exist_ok=True)
+        dest_dir.rename(installation_path)
+
+        print("Done")
     @staticmethod
     def list_models(config:dict):
         """Lists the models for this binding

bindings/gptq/binding_card.yaml

@@ -0,0 +1,6 @@
+name: AutoGPTQ
+author: PanQiWei
+version: 1.0
+link: https://github.com/PanQiWei/AutoGPTQ
+description: 'Python bindings for the GPTQ type of files
+    '

bindings/gptq/install.py

@@ -15,7 +15,6 @@ class Install:
             print("This is the first time you are using this binding.")
             print("Installing ...")
             # Example of installing py torche
-            """
             try:
                 print("Checking pytorch")
                 import torch
@@ -27,7 +26,6 @@ class Install:
                     self.reinstall_pytorch_with_cuda()
             except Exception as ex:
                 self.reinstall_pytorch_with_cuda()
-            """
 
             # Step 2: Install dependencies using pip from requirements.txt
             requirements_file = current_dir / "requirements.txt"

bindings/gptq/models.yaml

@@ -1,72 +1,8 @@
-- bestGPTJ: 'true'
-  description: Current best commercially licensable model based on GPT-J and trained
-    by Nomic AI on the latest curated GPT4All dataset.
-  filename: ggml-gpt4all-j-v1.3-groovy.bin
-  filesize: '3785248281'
-  isDefault: 'true'
-  md5sum: 81a09a0ddf89690372fc296ff7f625af
-- bestLlama: 'true'
-  description: Current best non-commercially licensable model based on Llama 13b and
-    trained by Nomic AI on the latest curated GPT4All dataset.
-  filename: ggml-gpt4all-l13b-snoozy.bin
-  filesize: '8136770688'
-  md5sum: 91f886b68fbce697e9a3cd501951e455
-- bestMPT: 'true'
-  description: Current best non-commercially licensable chat model based on MPT and
-    trained by Mosaic ML.
-  filename: ggml-mpt-7b-chat.bin
-  filesize: '4854401050'
-  isDefault: 'true'
-  md5sum: 756249d3d6abe23bde3b1ae272628640
-  requires: 2.4.1
-- description: A commercially licensable model based on GPT-J and trained by Nomic
-    AI on the v2 GPT4All dataset.
-  filename: ggml-gpt4all-j-v1.2-jazzy.bin
-  filesize: '3785248281'
-  md5sum: 879344aaa9d62fdccbda0be7a09e7976
-- description: A commercially licensable model based on GPT-J and trained by Nomic
-    AI on the v1 GPT4All dataset.
-  filename: ggml-gpt4all-j-v1.1-breezy.bin
-  filesize: '3785248281'
-  md5sum: 61d48a82cb188cceb14ebb8082bfec37
-- description: A commercially licensable model based on GPT-J and trained by Nomic
-    AI on the v0 GPT4All dataset.
-  filename: ggml-gpt4all-j.bin
-  filesize: '3785248281'
-  md5sum: 5b5a3f9b858d33b29b52b89692415595
-- description: A non-commercially licensable model based on Llama 7b and trained by
-    teams from UC Berkeley, CMU, Stanford, MBZUAI, and UC San Diego.
-  filename: ggml-vicuna-7b-1.1-q4_2.bin
-  filesize: '4212859520'
-  md5sum: 29119f8fa11712704c6b22ac5ab792ea
-- description: A non-commercially licensable model based on Llama 13b and trained
-    by teams from UC Berkeley, CMU, Stanford, MBZUAI, and UC San Diego.
-  filename: ggml-vicuna-13b-1.1-q4_2.bin
-  filesize: '8136770688'
-  md5sum: 95999b7b0699e2070af63bf5d34101a8
-- description: A non-commercially licensable model based on Llama 7b and trained by
-    Microsoft and Peking University.
-  filename: ggml-wizardLM-7B.q4_2.bin
-  filesize: '4212864640'
-  md5sum: 99e6d129745a3f1fb1121abed747b05a
-- description: A non-commercially licensable model based on Llama 13b and RLHF trained
-    by Stable AI.
-  filename: ggml-stable-vicuna-13B.q4_2.bin
-  filesize: '8136777088'
-  md5sum: 6cb4ee297537c9133bddab9692879de0
-- description: A commercially licensable model base pre-trained by Mosaic ML.
-  filename: ggml-mpt-7b-base.bin
-  filesize: '4854401028'
-  md5sum: 120c32a51d020066288df045ef5d52b9
-  requires: 2.4.1
-- description: A non-commercially licensable model based on Vicuna 13b, fine-tuned
-    on ~180,000 instructions, trained by Nous Research.
-  filename: ggml-nous-gpt4-vicuna-13b.bin
-  filesize: '8136777088'
-  md5sum: d5eafd5b0bd0d615cfd5fd763f642dfe
-- description: A commericially licensable instruct model based on MPT and trained
-    by Mosaic ML.
-  filename: ggml-mpt-7b-instruct.bin
-  filesize: '4854401028'
-  md5sum: 1cfa4958f489f0a0d1ffdf6b37322809
-  requires: 2.4.1
+-   description: GGML format model files for the original LLaMa
+  icon : https://aeiljuispo.cloudimg.io/v7/https://s3.amazonaws.com/moonup/production/uploads/6426d3f3a7723d62b53c259b/tvPikpAzKTKGN5wrpadOJ.jpeg?w=200&h=200&f=face
+  filename: Samantha-7B-GPTQ
+  license: Non commercial
+  owner_link: https://huggingface.co/TheBloke/
+  owner: TheBloke
+  server: Samantha-7B-GPTQ
+  sha256: ec2f2d1f0dfb73b72a4cbac7fa121abbe04c37ab327125a38248f930c0f09ddf

bindings/gptq/requirements.txt

@@ -1 +1 @@
-gptq
+auto-gptq

docs/dev/ful_endpoints_lis.md

@@ -0,0 +1,468 @@
+# Flask Backend API Documentation
+
+This documentation provides an overview of the endpoints available in the Flask backend API.
+
+## Introduction
+
+The Flask backend API exposes various endpoints to interact with the application. Each endpoint performs a specific function and supports different HTTP methods. The following sections describe each endpoint along with their parameters and expected outputs.
+
+## Endpoints
+
+### Endpoint: /disk_usage (GET)
+
+**Description**: Retrieves the disk usage of the system.
+
+**Parameters**: None
+
+**Output**: Returns the disk usage information.
+
+---
+
+### Endpoint: /list_bindings (GET)
+
+**Description**: Lists the available bindings.
+
+**Parameters**: None
+
+**Output**: Returns a list of available bindings.
+
+---
+
+### Endpoint: /list_models (GET)
+
+**Description**: Lists the available models.
+
+**Parameters**: None
+
+**Output**: Returns a list of available models.
+
+---
+
+### Endpoint: /list_personalities_languages (GET)
+
+**Description**: Lists the languages supported by personalities.
+
+**Parameters**: None
+
+**Output**: Returns a list of languages supported by personalities.
+
+---
+
+### Endpoint: /list_personalities_categories (GET)
+
+**Description**: Lists the categories of personalities.
+
+**Parameters**: None
+
+**Output**: Returns a list of personality categories.
+
+---
+
+### Endpoint: /list_personalities (GET)
+
+**Description**: Lists the available personalities.
+
+**Parameters**: None
+
+**Output**: Returns a list of available personalities.
+
+---
+
+### Endpoint: /list_languages (GET)
+
+**Description**: Lists the available languages.
+
+**Parameters**: None
+
+**Output**: Returns a list of available languages.
+
+---
+
+### Endpoint: /list_discussions (GET)
+
+**Description**: Lists the discussions.
+
+**Parameters**: None
+
+**Output**: Returns a list of discussions.
+
+---
+
+### Endpoint: /set_personality (GET)
+
+**Description**: Sets the active personality.
+
+**Parameters**: None
+
+**Output**: Sets the active personality.
+
+---
+
+### Endpoint: /delete_personality (GET)
+
+**Description**: Deletes a personality.
+
+**Parameters**: None
+
+**Output**: Deletes the specified personality.
+
+---
+
+### Endpoint: / (GET)
+
+**Description**: Returns the index page.
+
+**Parameters**: None
+
+**Output**: Returns the index page.
+
+---
+
+### Endpoint: /<path:filename> (GET)
+
+**Description**: Serves static files.
+
+**Parameters**: `filename` - The path to the static file.
+
+**Output**: Returns the requested static file.
+
+---
+
+### Endpoint: /personalities/<path:filename> (GET)
+
+**Description**: Serves personality files.
+
+**Parameters**: `filename` - The path to the personality file.
+
+**Output**: Returns the requested personality file.
+
+---
+
+### Endpoint: /outputs/<path:filename> (GET)
+
+**Description**: Serves output files.
+
+**Parameters**: `filename` - The path to the output file.
+
+**Output**: Returns the requested output file.
+
+---
+
+### Endpoint: /export_discussion (GET)
+
+**Description**: Exports a discussion.
+
+**Parameters**: None
+
+**Output**: Exports the specified discussion.
+
+---
+
+### Endpoint: /export (GET)
+
+**Description**: Exports data.
+
+**Parameters**: None
+
+**Output**: Exports the specified data.
+
+---
+
+### Endpoint: /new_discussion (GET)
+
+**Description**: Creates a new discussion.
+
+**Parameters**: None
+
+**Output**: Creates a new discussion.
+
+---
+
+### Endpoint: /stop_gen (GET)
+
+**Description**: Stops the generation process.
+
+**Parameters**: None
+
+**Output**: Stops the generation process.
+
+---
+
+### Endpoint: /rename (POST)
+
+**Description**: Renames a resource.
+
+**Parameters**: None
+
+**Output**: Renames the specified resource.
+
+---
+
+### Endpoint: /edit_title (POST)
+
+**Description**: Edits the title of a resource.
+
+**Parameters**: None
+
+**Output**: Edits the title of the specified resource.
+
+---
+
+### Endpoint: /load_discussion (POST)
+
+**Description**: Loads a discussion.
+
+**Parameters**: None
+
+**Output**: Loads the specified discussion.
+
+---
+
+### Endpoint: /delete_discussion (POST)
+
+**Description**: Deletes a discussion.
+
+**Parameters**: None
+
+**Output**: Deletes the specified discussion.
+
+---
+
+### Endpoint: /update_message (GET)
+
+**Description**: Updates a message.
+
+**Parameters**: None
+
+**Output**: Updates the specified message.
+
+---
+
+### Endpoint: /message_rank_up (GET)
+
+**Description**: Increases the rank of a message.
+
+**Parameters**: None
+
+**Output**: Increases the rank of the specified message.
+
+---
+
+### Endpoint: /message_rank_down (GET)
+
+**Description**: Decreases the rank of a message.
+
+**Parameters**: None
+
+**Output**: Decreases the rank of the specified message.
+
+---
+
+### Endpoint: /delete_message (GET)
+
+**Description**: Deletes a message.
+
+**Parameters**: None
+
+**Output**: Deletes the specified message.
+
+---
+
+### Endpoint: /set_binding (POST)
+
+**Description**: Sets a binding.
+
+**Parameters**: None
+
+**Output**: Sets the specified binding.
+
+---
+
+### Endpoint: /set_model (POST)
+
+**Description**: Sets a model.
+
+**Parameters**: None
+
+**Output**: Sets the specified model.
+
+---
+
+### Endpoint: /update_model_params (POST)
+
+**Description**: Updates model parameters.
+
+**Parameters**: None
+
+**Output**: Updates the specified model parameters.
+
+---
+
+### Endpoint: /get_config (GET)
+
+**Description**: Retrieves the configuration.
+
+**Parameters**: None
+
+**Output**: Returns the configuration.
+
+---
+
+### Endpoint: /get_available_models (GET)
+
+**Description**: Retrieves the available models.
+
+**Parameters**: None
+
+**Output**: Returns a list of available models.
+
+---
+
+### Endpoint: /extensions (GET)
+
+**Description**: Retrieves the extensions.
+
+**Parameters**: None
+
+**Output**: Returns the extensions.
+
+---
+
+### Endpoint: /training (GET)
+
+**Description**: Performs training.
+
+**Parameters**: None
+
+**Output**: Performs the training process.
+
+---
+
+### Endpoint: /main (GET)
+
+**Description**: Returns the main page.
+
+**Parameters**: None
+
+**Output**: Returns the main page.
+
+---
+
+### Endpoint: /settings (GET)
+
+**Description**: Returns the settings page.
+
+**Parameters**: None
+
+**Output**: Returns the settings page.
+
+---
+
+### Endpoint: /help (GET)
+
+**Description**: Returns the help page.
+
+**Parameters**: None
+
+**Output**: Returns the help page.
+
+---
+
+### Endpoint: /get_generation_status (GET)
+
+**Description**: Retrieves the generation status.
+
+**Parameters**: None
+
+**Output**: Returns the generation status.
+
+---
+
+### Endpoint: /update_setting (POST)
+
+**Description**: Updates a setting.
+
+**Parameters**: None
+
+**Output**: Updates the specified setting.
+
+---
+
+### Endpoint: /apply_settings (POST)
+
+**Description**: Applies the settings.
+
+**Parameters**: None
+
+**Output**: Applies the specified settings.
+
+---
+
+### Endpoint: /save_settings (POST)
+
+**Description**: Saves the settings.
+
+**Parameters**: None
+
+**Output**: Saves the specified settings.
+
+---
+
+### Endpoint: /get_current_personality (GET)
+
+**Description**: Retrieves the current personality.
+
+**Parameters**: None
+
+**Output**: Returns the current personality.
+
+---
+
+### Endpoint: /get_all_personalities (GET)
+
+**Description**: Retrieves all personalities.
+
+**Parameters**: None
+
+**Output**: Returns a list of all personalities.
+
+---
+
+### Endpoint: /get_personality (GET)
+
+**Description**: Retrieves a specific personality.
+
+**Parameters**: None
+
+**Output**: Returns the specified personality.
+
+---
+
+### Endpoint: /reset (GET)
+
+**Description**: Resets the system.
+
+**Parameters**: None
+
+**Output**: Resets the system.
+
+---
+
+### Endpoint: /export_multiple_discussions (POST)
+
+**Description**: Exports multiple discussions.
+
+**Parameters**: None
+
+**Output**: Exports the specified discussions.
+
+---
+
+### Endpoint: /import_multiple_discussions (POST)
+
+**Description**: Imports multiple discussions.
+
+**Parameters**: None
+
+**Output**: Imports the specified discussions.
+

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-0e9c5983.js"></script>
-    <link rel="stylesheet" href="/assets/index-c9ce79a4.css">
+    <script type="module" crossorigin src="/assets/index-9deab5e4.js"></script>
+    <link rel="stylesheet" href="/assets/index-86ec2b95.css">
   </head>
   <body>
     <div id="app"></div>