Merge branch 'main' into pr/197

backends/c_transformers/__init__.py

@@ -0,0 +1,106 @@
+######
+# Project       : GPT4ALL-UI
+# File          : backend.py
+# Author        : ParisNeo with the help of the community
+# Underlying backend : Abdeladim's pygptj backend
+# Supported by Nomic-AI
+# Licence       : Apache 2.0
+# Description   : 
+# This is an interface class for GPT4All-ui backends.
+
+# This backend is a wrapper to marella's backend
+# Follow him on his github project : https://github.com/marella/ctransformers
+
+######
+from pathlib import Path
+from typing import Callable
+from gpt4all_api.backend import GPTBackend
+import yaml
+from ctransformers import AutoModelForCausalLM
+
+__author__ = "parisneo"
+__github__ = "https://github.com/nomic-ai/gpt4all-ui"
+__copyright__ = "Copyright 2023, "
+__license__ = "Apache 2.0"
+
+backend_name = "GPTJ"
+
+class GPTJ(GPTBackend):
+    file_extension='*.bin'
+    def __init__(self, config:dict) -> None:
+        """Builds a LLAMACPP backend
+
+        Args:
+            config (dict): The configuration file
+        """
+        super().__init__(config, False)
+        if 'gpt2' in self.config['model']:
+            model_type='gpt2'
+        elif 'gptj' in self.config['model']:
+            model_type='gptj'
+        elif 'gpt_neox' in self.config['model']:
+            model_type='gpt_neox'
+        elif 'dolly-v2' in self.config['model']:
+            model_type='dolly-v2'
+        elif 'starcoder' in self.config['model']:
+            model_type='starcoder'
+        else:
+            print("The model you are using is not supported by this backend")
+            return
+        
+        
+        if self.config["use_avx2"]:
+            self.model = AutoModelForCausalLM.from_pretrained(
+                    f"./models/c_transformers/{self.config['model']}", model_type=model_type
+                    )
+        else:
+            self.model = AutoModelForCausalLM.from_pretrained(
+                    f"./models/c_transformers/{self.config['model']}", model_type=model_type, lib = "avx"
+                    )
+
+    def generate(self, 
+                 prompt:str,                  
+                 n_predict: int = 128,
+                 new_text_callback: Callable[[str], None] = bool,
+                 verbose: bool = False,
+                 **gpt_params ):
+        """Generates text out of a prompt
+
+        Args:
+            prompt (str): The prompt to use for generation
+            n_predict (int, optional): Number of tokens to prodict. Defaults to 128.
+            new_text_callback (Callable[[str], None], optional): A callback function that is called everytime a new text element is generated. Defaults to None.
+            verbose (bool, optional): If true, the code will spit many informations about the generation process. Defaults to False.
+        """
+        try:
+            self.model.reset()
+            tokens = self.model.tokenize(prompt.encode())
+            for tok in self.model.generate(
+                                            tokens, 
+                                            seed=self.config['seed'],
+                                            n_threads=self.config['n_threads'],
+                                            n_predict=n_predict,
+                                            top_k=self.config['top_k'],
+                                            top_p=self.config['top_p'],
+                                            temp=self.config['temperature'],
+                                            repeat_penalty=self.config['repeat_penalty'],
+                                            repeat_last_n=self.config['repeat_last_n'],
+                                            n_batch=8,
+                                            reset=True,
+                                           ):
+                if not new_text_callback(self.model.detokenize(tok)):
+                    return
+        except Exception as ex:
+            print(ex)
+            
+            
+    @staticmethod
+    def get_available_models():
+        # Create the file path relative to the child class's directory
+        backend_path = Path(__file__).parent
+        file_path = backend_path/"models.yaml"
+
+        with open(file_path, 'r') as file:
+            yaml_data = yaml.safe_load(file)
+        
+        return yaml_data

backends/c_transformers/models.yaml

@@ -0,0 +1,7 @@
+- 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

backends/gpt_4all/__init__.py

@@ -6,6 +6,11 @@
 # Licence       : Apache 2.0
 # Description   : 
 # This is an interface class for GPT4All-ui backends.
+
+
+# This backend is a wrapper to gpt4all's official backend
+# Follow him on his github project : https://github.com/nomic-ai/gpt4all
+
 ######
 from pathlib import Path
 from typing import Callable

backends/gpt_j_a/__init__.py

@@ -7,6 +7,10 @@
 # Licence       : Apache 2.0
 # Description   : 
 # This is an interface class for GPT4All-ui backends.
+
+# This backend is a wrapper to abdeladim's backend
+# Follow him on his github project : https://github.com/abdeladim-s/pygptj
+
 ######
 from pathlib import Path
 from typing import Callable

backends/gpt_j_m/__init__.py

@@ -7,6 +7,10 @@
 # Licence       : Apache 2.0
 # Description   : 
 # This is an interface class for GPT4All-ui backends.
+
+# This backend is a wrapper to marella's backend
+# Follow him on his github project : https://github.com/marella/gpt4all-j 
+
 ######
 from pathlib import Path
 from typing import Callable

backends/hugging_face/models.yaml

@@ -1,72 +0,0 @@
-- 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

backends/llama_cpp/models.yaml

@@ -1,47 +0,0 @@
-- bestLlama: 'false'
-  description: The model who started it all
-  filename: gpt4all-lora-quantized-ggml.new.bin
-  md5sum: 91f886b68fbce697e9a3cd501951e455
-  server: https://huggingface.co/ParisNeo/GPT4All/resolve/main/
-- bestLlama: 'false'
-  description: The model who started it all (uncensored version)
-  filename: gpt4all-lora-unfiltered-quantized.new.bin
-  md5sum: 91f886b68fbce697e9a3cd501951e455
-  server: https://huggingface.co/ParisNeo/GPT4All/resolve/main/
-- 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
-  server: https://gpt4all.io/models/
-- 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
-  server: https://gpt4all.io/models/
-- 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
-  server: https://gpt4all.io/models/
-- 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
-  server: https://gpt4all.io/models/
-- 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
-  server: https://gpt4all.io/models/
-- 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
-  server: https://gpt4all.io/models/

backends/llama_cpp_official/__init__.py

@@ -6,38 +6,39 @@
 # Licence       : Apache 2.0
 # Description   : 
 # This is an interface class for GPT4All-ui backends.
+
+# This backend is a wrapper to the official llamacpp python bindings
+# Follow him on his github project : https://github.com/abetlen/llama-cpp-python
+
 ######
 from pathlib import Path
 from typing import Callable
-from accelerate import init_empty_weights
-from accelerate import load_checkpoint_and_dispatch
-from transformers import AutoTokenizer
-from transformers import AutoConfig, AutoModelForCausalLM
+from llama_cpp import Llama
 from gpt4all_api.backend import GPTBackend
-import torch
+import yaml
+import random
 
 __author__ = "parisneo"
-__github__ = "https://github.com/ParisNeo/GPTQ_backend"
+__github__ = "https://github.com/nomic-ai/gpt4all-ui"
 __copyright__ = "Copyright 2023, "
 __license__ = "Apache 2.0"
 
-backend_name = "HuggingFace"
+backend_name = "LLAMACPP"
 
-class HuggingFace(GPTBackend):
-    file_extension='*'
+class LLAMACPP(GPTBackend):
+    file_extension='*.bin'
     def __init__(self, config:dict) -> None:
-        """Builds a HuggingFace backend
+        """Builds a LLAMACPP backend
 
         Args:
             config (dict): The configuration file
         """
         super().__init__(config, False)
-
-
-        # load quantized model, currently only support cpu or single gpu
-        config_path = AutoConfig.from_pretrained(config["model"])
-        self.tokenizer = AutoTokenizer.from_pretrained(config["model"])
-        self.model = AutoModelForCausalLM.from_pretrained(config["model"], load_in_8bit=True, device_map='auto')
+        seed = config["seed"]
+        if seed <=0:
+            seed = random.randint(1, 2**31)
+            
+        self.model = Llama(model_path=f"./models/llama_cpp_official/{self.config['model']}", n_gpu_layers=40, seed=seed)
 
     def generate(self, 
                  prompt:str,                  
@@ -54,30 +55,31 @@ class HuggingFace(GPTBackend):
             verbose (bool, optional): If true, the code will spit many informations about the generation process. Defaults to False.
         """
         try:
-            tok = self.tokenizer.decode(self.model.generate(**self.tokenizer(prompt, return_tensors="pt").to("cuda:0"))[0])
-            new_text_callback(tok)
-            """
             self.model.reset()
-            for tok in self.model.generate(prompt, 
-                                           n_predict=n_predict,                                           
-                                            temp=self.config['temp'],
+            tokens = self.model.tokenize(prompt.encode())
+            count = 0
+            for tok in self.model.generate(tokens, 
+                                            temp=self.config['temperature'],
                                             top_k=self.config['top_k'],
                                             top_p=self.config['top_p'],
                                             repeat_penalty=self.config['repeat_penalty'],
-                                            repeat_last_n = self.config['repeat_last_n'],
-                                            n_threads=self.config['n_threads'],
                                            ):
-                if not new_text_callback(tok):
+                if count >= n_predict or (tok == self.model.token_eos()):
+                    break
+                word = self.model.detokenize([tok]).decode()
+                if not new_text_callback(word):
                     return
-            """
+                count += 1
         except Exception as ex:
             print(ex)
             
     @staticmethod
-    def list_models(config:dict):
-        """Lists the models for this backend
-        """
+    def get_available_models():
+        # Create the file path relative to the child class's directory
+        backend_path = Path(__file__).parent
+        file_path = backend_path/"models.yaml"
+
+        with open(file_path, 'r') as file:
+            yaml_data = yaml.safe_load(file)
         
-        return [
-            "EleutherAI/gpt-j-6B"
-        ]
+        return yaml_data

backends/llama_cpp_official/models.yaml

@@ -0,0 +1,29 @@
+- bestLlama: 'true'
+  license: Non commercial
+  description: The official open assistant 30B model finally here
+  filename: OpenAssistant-SFT-7-Llama-30B.ggml.q4_0.bin
+  sha256: 32fd44c685fbf429810db593e2db8aa42a7e1be2cd3571b6005d53b029acfcf5
+  server: https://huggingface.co/TheBloke/OpenAssistant-SFT-7-Llama-30B-GGML/resolve/main/
+
+- bestLlama: 'true'
+  license: Non commercial
+  description: The wizardVicuna model 13B
+  filename: wizard-vicuna-13B.ggml.q4_0.bin
+  sha256: 32fd44c685fbf429810db593e2db8aa42a7e1be2cd3571b6005d53b029acfcf5
+  server: https://huggingface.co/TheBloke/wizard-vicuna-13B-GGML/resolve/main/
+
+- bestLlama: 'true'
+  license: Non commercial
+  description: The wizardLM model 7B
+  filename: WizardLM-7B-uncensored.ggml.q4_0.bin
+  sha256: b1e53a3c3a9389b9c5d81e0813cfb90ebaff6acad1733fad08cd28974fa3ac30
+  server: https://huggingface.co/TheBloke/WizardLM-7B-uncensored-GGML/resolve/main/
+
+- bestLlama: 'true'
+  license: Non commercial
+  description: The wizardLM model uncensored
+  filename: WizardLM-7B-uncensored.ggml.q4_0.bin
+  md5sum: b1e53a3c3a9389b9c5d81e0813cfb90ebaff6acad1733fad08cd28974fa3ac30
+  server: https://huggingface.co/TheBloke/WizardLM-7B-uncensored-GGML/resolve/main/
+
+

backends/llama_cpp_official/requirements.txt

@@ -0,0 +1 @@
+llama-cpp-python

backends/py_llama_cpp/__init__.py

@@ -6,6 +6,10 @@
 # Licence       : Apache 2.0
 # Description   : 
 # This is an interface class for GPT4All-ui backends.
+
+# This backend is a wrapper to abdeladim's backend
+# Follow him on his github project : https://github.com/abdeladim-s/pyllamacpp
+
 ######
 from pathlib import Path
 from typing import Callable
@@ -18,9 +22,9 @@ __github__ = "https://github.com/nomic-ai/gpt4all-ui"
 __copyright__ = "Copyright 2023, "
 __license__ = "Apache 2.0"
 
-backend_name = "LLAMACPP"
+backend_name = "PyLLAMACPP"
 
-class LLAMACPP(GPTBackend):
+class PyLLAMACPP(GPTBackend):
     file_extension='*.bin'
     def __init__(self, config:dict) -> None:
         """Builds a LLAMACPP backend
@@ -31,7 +35,7 @@ class LLAMACPP(GPTBackend):
         super().__init__(config, False)
         
         self.model = Model(
-                model_path=f"./models/llama_cpp/{self.config['model']}",
+                model_path=f"./models/py_llama_cpp/{self.config['model']}",
                 prompt_context="", prompt_prefix="", prompt_suffix="",
                 n_ctx=self.config['ctx_size'], 
                 seed=self.config['seed'],

backends/py_llama_cpp/models.yaml

@@ -0,0 +1,11 @@
+- bestLlama: 'true'
+  description: The official open assistant 30B model finally here
+  filename: OpenAssistant-SFT-7-Llama-30B.ggml.q4_0.bin
+  md5sum: 91f886b68fbce697e9a3cd501951e455
+  server: https://huggingface.co/TheBloke/OpenAssistant-SFT-7-Llama-30B-GGML/resolve/main/
+
+- bestLlama: 'true'
+  description: Stable vicuna 13B
+  filename: stable-vicuna-13B.ggml.q5_1.bin
+  md5sum: 91f886b68fbce697e9a3cd501951e455
+  server: https://huggingface.co/TheBloke/stable-vicuna-13B-GGML/resolve/main/

backends/py_llama_cpp/requirements.txt

@@ -0,0 +1 @@
+pyllamacpp

configs/default.yaml

@@ -7,7 +7,7 @@ n_threads: 8
 host: localhost
 language: en-US
 # Supported backends are llamacpp and gpt-j
-backend: llama_cpp
+backend: llama_cpp_official
 model: null
 n_predict: 1024
 nb_messages_to_remember: 5

docs/dev/new_ui_dev.md

@@ -36,27 +36,29 @@ This will update `/dist/` folder with all the files. Also the build will show yo
 Here we keep track of things to implement and stuff we need to do.
 ## Todo's
 
-- Add ability to select multiple discussions to export or delete [WIP]
+- Add ability to select multiple discussions to export [WIP]
 - Add toast messages for errors and successes
-- Populate settings with settings controls [WIP]
-- Connect Settings to backend, ability to save changes
 - Add DB switcher (im thinking in the settings view)
 - Make the UI work good on mobile
-- Scroll to bottom
-- Scroll to top
 - Need to fix colors for `<input />` fields
 - Create status bar for backend to display if something is generating on the backend
-- Create stop generating button
-- Fix the generated message formatting - add line breaks, also for user input messages.
 - Add ability for users to style the whole UI, either changing Hue or changing every color manually.
-- Maybe try to set the chatbox to float to the bottom (always on the bottom of the screen)
 - Create a panel in the Settings tab to create new personalities
-- Need to fix when user inputs message it shows up in the discussion array and then add new message for bot that is typing.
 - Need to investigate performance of websocket when message is being streamed back to the UI
 - On first launch of the UI force users to create "User" personality, to be used as "User" for any or all input messages.
-- Connect delete / export discussions to backend functions.
-- Need to fix when deleting multiple discussions to not loose loading animation for each discussion when list gets updated
-- Need to add loading feedback for when a new discussion is being created
+- Add drag n drop files into messages, images gets parsed as images, ability to load images from messages from DB.
+- Send files to backend - images, other files for parsing data.
+- Ability to reorder Discussions, add tags, categories
+- Export whole DB
+- Reset whole DB
+- Add text to speech to messages and chatbox
+- Add indicator to messages when non-comercial model was used. 
+- Ability to export messages that are for commercial use or open source model messages Only.
+- Ability to hide non commercial model messages.
+- Feature - bot council where you add multiple bots to discussion, give them a topic and maybe max message count or something and they ponder about the topic then summerize it all.
+- Feature voice chat with bot and voice output from bot - whisper + bard?
+- Feature under selected discussion show more options to select and add more bots, select model per discussion or per bot, tweak settings per bot or per model.
+- Easy share personality via export to a file, then drag and drop on to the webui and youre done.
 
 ## Done
 
@@ -66,4 +68,16 @@ Here we keep track of things to implement and stuff we need to do.
 - Add clear filter button to search input field [DONE]
 - Add modal to ask user if you sure about to delete [DONE but in different way]
 - Fix up the discussion array to filter out the messages by type not by count. (conditionner and )[DONE]
-- Add title of current discussion to page [DONE]
+- Add title of current discussion to page [DONE]
+- Populate settings with settings controls [DONE]
+- Connect Settings to backend, ability to save changes [DONE]
+- Scroll to bottom [SCROLLBAR]
+- Scroll to top [SCROLLBAR]
+- Create stop generating button [DONE]
+- Fix the generated message formatting - add line breaks, also for user input messages. [DONE]
+- Maybe try to set the chatbox to float to the bottom (always on the bottom of the screen) [DONE]
+- Need to fix when user inputs message it shows up in the discussion array and then add new message for bot that is typing. [DONE]
+- Connect delete / export discussions to backend functions.[DONE]
+- Need to fix when deleting multiple discussions to not loose loading animation for each discussion when list gets updated [DONE]
+- Need to add loading feedback for when a new discussion is being created [DONE]
+- Add ability to select multiple discussions to delete [DONE]

gpt4all_api/api.py

@@ -28,6 +28,58 @@ __license__ = "Apache 2.0"
 
 
 
+import subprocess
+import pkg_resources
+
+
+# ===========================================================
+# Manage automatic install scripts
+
+def is_package_installed(package_name):
+    try:
+        dist = pkg_resources.get_distribution(package_name)
+        return True
+    except pkg_resources.DistributionNotFound:
+        return False
+
+
+def install_package(package_name):
+    try:
+        # Check if the package is already installed
+        __import__(package_name)
+        print(f"{package_name} is already installed.")
+    except ImportError:
+        print(f"{package_name} is not installed. Installing...")
+        
+        # Install the package using pip
+        subprocess.check_call(["pip", "install", package_name])
+        
+        print(f"{package_name} has been successfully installed.")
+
+
+def parse_requirements_file(requirements_path):
+    with open(requirements_path, 'r') as f:
+        for line in f:
+            line = line.strip()
+            if not line or line.startswith('#'):
+                # Skip empty and commented lines
+                continue
+            package_name, _, version_specifier = line.partition('==')
+            package_name, _, version_specifier = line.partition('>=')
+            if is_package_installed(package_name):
+                # The package is already installed
+                print(f"{package_name} is already installed.")
+            else:
+                # The package is not installed, install it
+                if version_specifier:
+                    install_package(f"{package_name}{version_specifier}")
+                else:
+                    install_package(package_name)
+
+
+# ===========================================================
+
+
 class ModelProcess:
     def __init__(self, config=None):
         self.config = config
@@ -42,7 +94,11 @@ class ModelProcess:
         self.model_ready  = mp.Value('i', 0)
         self.ready = False
             
-    def load_backend(self, backend_path):
+    def load_backend(self, backend_path:Path):
+        # first find out if there is a requirements.txt file
+        requirements_file = backend_path/"requirements.txt"
+        if requirements_file.exists():
+            parse_requirements_file(requirements_file)        
 
         # define the full absolute path to the module
         absolute_path = backend_path.resolve()
@@ -88,6 +144,7 @@ class ModelProcess:
     
     def rebuild_backend(self, config):
         try:
+            
             backend = self.load_backend(Path("backends")/config["backend"])
             print("Backend loaded successfully")
         except Exception as ex:
@@ -106,7 +163,7 @@ class ModelProcess:
                 print(f"Loading model : {model_file}")
                 self.model = self.backend(self.config)
                 self.model_ready.value = 1
-                print("Model created successfully")
+                print("Model created successfully\ntesting the model, please wait ...")
             except Exception as ex:
                 print("Couldn't build model")
                 print(ex)
@@ -239,6 +296,7 @@ class ModelProcess:
         while not self.set_config_queue.empty():
             config = self.set_config_queue.get()
             if config is not None:
+                print("Inference process : Setting configuration")
                 self._set_config(config)
 
     def _cancel_generation(self):
@@ -472,6 +530,8 @@ class GPT4AllAPI():
             )
         
             self.current_ai_message_id = message_id
+        else:
+            message_id = 0
         return message_id
 
     def prepare_reception(self):
@@ -492,12 +552,23 @@ class GPT4AllAPI():
         messages = self.current_discussion.get_messages()
         self.full_message_list = []
         for message in messages:
-            if message["id"]<= message_id or message_id==-1: 
+            if message["id"]< message_id or message_id==-1: 
                 if message["type"]==self.db.MSG_TYPE_NORMAL:
                     if message["sender"]==self.personality.name:
                         self.full_message_list.append(self.personality.ai_message_prefix+message["content"])
                     else:
                         self.full_message_list.append(self.personality.user_message_prefix + message["content"])
+            else:
+                break
+        if self.personality.processor is not None:
+            preprocessed_prompt = self.personality.processor.process_model_input(message["content"])
+        else:
+            preprocessed_prompt = message["content"]
+        if preprocessed_prompt is not None:
+            self.full_message_list.append(self.personality.user_message_prefix+preprocessed_prompt+self.personality.link_text+self.personality.ai_message_prefix)
+        else:
+            self.full_message_list.append(self.personality.user_message_prefix+preprocessed_prompt+self.personality.link_text+self.personality.ai_message_prefix)
+
 
         link_text = self.personality.link_text
 

requirements.txt

@@ -4,7 +4,6 @@ nomic
 pytest
 pyyaml
 markdown
-pyllamacpp==2.1.1
 gpt4all-j
 pygptj
 gpt4all
@@ -16,4 +15,5 @@ transformers
 accelerate
 gevent
 gevent-websocket
-pyaipersonality>=0.0.11
+pyaipersonality>=0.0.12
+ctransformers

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-536b56d7.js"></script>
-    <link rel="stylesheet" href="/assets/index-8f995011.css">
+    <script type="module" crossorigin src="/assets/index-9b4a79fd.js"></script>
+    <link rel="stylesheet" href="/assets/index-e783286d.css">
   </head>
   <body>
     <div id="app"></div>

web/src/views/SettingsView.vue

@@ -13,6 +13,7 @@
                     <i data-feather="check"></i>
                 </button>
 
+
             </div>
             <!-- SAVE AND RESET -->
             <div v-if="!showConfirmation" class="flex gap-3 flex-1 items-center ">
@@ -24,6 +25,10 @@
                     @click="reset_configuration()">
                     <i data-feather="refresh-ccw"></i>
                 </button>
+                <button class="text-2xl hover:text-secondary duration-75 active:scale-90" title="Collapse / Expand all panels"
+                    type="button" @click.stop="all_collapsed=!all_collapsed">
+                    <i data-feather="list"></i>
+                </button>
             </div>
 
         </div>
@@ -68,23 +73,23 @@
             </div>
         </div>
         <div
-            class="flex flex-col mb-2 p-3 rounded-lg bg-bg-light-tone dark:bg-bg-dark-tone hover:bg-bg-light-tone-panel hover:dark:bg-bg-dark-tone-panel duration-150 shadow-lg">
-            <div class="flex flex-row ">
+            class="flex flex-col mb-2  rounded-lg bg-bg-light-tone dark:bg-bg-dark-tone hover:bg-bg-light-tone-panel hover:dark:bg-bg-dark-tone-panel duration-150 shadow-lg">
+            <div class="flex flex-row p-3">
                 <button @click.stop="mzc_collapsed = !mzc_collapsed"
                     class="text-2xl hover:text-primary duration-75  p-2 -m-2 w-full text-left active:translate-y-1">
-                    <!-- <i data-feather="chevron-right"></i> -->
+                  
 
                     <h3 class="text-lg font-semibold cursor-pointer select-none "
                         @click.stop="mzc_collapsed = !mzc_collapsed">
                         Models zoo</h3>
                 </button>
             </div>
-            <div :class="{ 'hidden': mzc_collapsed }" class="flex flex-col mb-2 p-2">
-                <div v-if="models.length > 0" class="my-2">
+            <div :class="{ 'hidden': mzc_collapsed }" class="flex flex-col mb-2 px-3 pb-0">
+                <div v-if="models.length > 0" class="mb-2">
                     <label for="model" class="block ml-2 mb-2 text-sm font-medium text-gray-900 dark:text-white">
                         Install more models:
                     </label>
-                    <div class="overflow-y-auto max-h-96 no-scrollbar p-2">
+                    <div ref="modelZoo" class="overflow-y-auto no-scrollbar p-2 pb-0" :class="mzl_collapsed ? '':'max-h-96'">
                         <model-entry v-for="(model, index) in models" :key="index" :title="model.title" :icon="model.icon"
                             :path="model.path" :description="model.description" :is-installed="model.isInstalled"
                             :on-install="onInstall"
@@ -92,7 +97,17 @@
                             :on-selected="onSelected" />
                     </div>
                 </div>
+                 <!-- EXPAND / COLLAPSE BUTTON -->
+                <button v-if="mzl_collapsed" class="text-2xl hover:text-secondary duration-75 flex justify-center  hover:bg-bg-light-tone hover:dark:bg-bg-dark-tone rounded-lg " title="Collapse"
+                    type="button" @click="mzl_collapsed = !mzl_collapsed">
+                    <i  data-feather="chevron-up" ></i>  
+                </button>
+                <button v-else class="text-2xl hover:text-secondary duration-75 flex justify-center  hover:bg-bg-light-tone hover:dark:bg-bg-dark-tone rounded-lg " title="Expand"
+                    type="button" @click="mzl_collapsed = !mzl_collapsed">
+                    <i  data-feather="chevron-down" ></i>  
+                </button>
             </div>
+
         </div>
         <!-- PERSONALITY -->
         <div
@@ -361,12 +376,16 @@ export default {
             // Models zoo installer stuff
             models: [],
             personalities:[],
-            // Accordeon stuff     
+            // Accordeon stuff 
+            collapsedArr:[],
+            all_collapsed:true,    
             bec_collapsed: true,
             mzc_collapsed: true, // models zoo
             pzc_collapsed: true, // personalities zoo
             pc_collapsed: true,
             mc_collapsed: true,
+            // Zoo accordeoon
+            mzl_collapsed:false,
             // Settings stuff
             backendsArr: [],
             modelsArr: [],
@@ -382,6 +401,13 @@ export default {
     created() {
         this.fetchModels();
     }, methods: {
+        collapseAll(val){
+            this.bec_collapsed=val
+            this.mzc_collapsed=val
+            this.pzc_collapsed=val
+            this.pc_collapsed=val
+            this.mc_collapsed=val
+        },
         fetchModels() {
             axios.get('/get_available_models')
                 .then(response => {
@@ -460,14 +486,16 @@ export default {
         },
         // Refresh stuff
         refresh() {
+            
+            console.log("Refreshing")
             // No need to refresh all lists because they never change during using application. 
             // On settings change only config file chnages.
             //
             //this.api_get_req("list_backends").then(response => { this.backendsArr = response })
-            //this.api_get_req("list_models").then(response => { this.modelsArr = response })
+            this.api_get_req("list_models").then(response => { this.modelsArr = response })
             //this.api_get_req("list_personalities_languages").then(response => { this.persLangArr = response })
-            //this.api_get_req("list_personalities_categories").then(response => { this.persCatgArr = response })
-            //this.api_get_req("list_personalities").then(response => { this.persArr = response })
+            this.api_get_req("list_personalities_categories").then(response => { this.persCatgArr = response })
+            this.api_get_req("list_personalities").then(response => { this.persArr = response })
             //this.api_get_req("list_languages").then(response => { this.langArr = response })
             this.api_get_req("get_config").then(response => { 
                 this.configFile = response 
@@ -615,8 +643,23 @@ export default {
             nextTick(() => {
                 feather.replace()
 
+            })
+        },
+        mzl_collapsed() {
+            
+            nextTick(() => {
+                feather.replace()
+
+            })
+        },
+        all_collapsed(val) {
+            this.collapseAll(val)
+            nextTick(() => {
+                feather.replace()
+
             })
         }
+
     }
 }
 </script>