Merge commit gpt4all-chat into monorepo

This commit is contained in:
Adam Treat 2023-05-10 10:28:36 -04:00
commit a971831ed2
76 changed files with 11086 additions and 6 deletions

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.github/ISSUE_TEMPLATE/bug_report.md vendored Normal file
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---
name: Bug report
about: Create a report to help us improve
title: ''
labels: ''
assignees: ''
---
**Describe the bug**
A clear and concise description of what the bug is.
**To Reproduce**
Steps to reproduce the behavior:
1. Go to '...'
2. Click on '....'
3. Scroll down to '....'
4. See error
**Expected behavior**
A clear and concise description of what you expected to happen.
**Screenshots**
If applicable, add screenshots to help explain your problem.
**Desktop (please complete the following information):**
- OS: [e.g. iOS]
- Browser [e.g. chrome, safari]
- Version [e.g. 22]
**Smartphone (please complete the following information):**
- Device: [e.g. iPhone6]
- OS: [e.g. iOS8.1]
- Browser [e.g. stock browser, safari]
- Version [e.g. 22]
**Additional context**
Add any other context about the problem here.

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---
name: Feature request
about: Suggest an idea for this project
title: ''
labels: ''
assignees: ''
---
**Is your feature request related to a problem? Please describe.**
A clear and concise description of what the problem is. Ex. I'm always frustrated when [...]
**Describe the solution you'd like**
A clear and concise description of what you want to happen.
**Describe alternatives you've considered**
A clear and concise description of any alternative solutions or features you've considered.
**Additional context**
Add any other context or screenshots about the feature request here.

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.gitignore vendored
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@ -171,4 +171,9 @@ cython_debug/
.vscode .vscode
*.bin *.bin
.DS_Store .DS_Store
# gpt4all-chat
CMakeLists.txt.user
gpt4all-chat/meta/*
gpt4all-chat/models/*

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[submodule "peft"] [submodule "llama.cpp"]
path = peft path = gpt4all-chat/llmodel/llama.cpp
url = https://github.com/huggingface/peft.git url = https://github.com/manyoso/llama.cpp.git

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gpt4all-chat/CMakeLists.txt Normal file
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cmake_minimum_required(VERSION 3.16)
if(APPLE)
option(BUILD_UNIVERSAL "Build a Universal binary on macOS" OFF)
if(BUILD_UNIVERSAL)
# Build a Universal binary on macOS
# This requires that the found Qt library is compiled as Universal binaries.
set(CMAKE_OSX_ARCHITECTURES "arm64;x86_64" CACHE STRING "" FORCE)
else()
# Build for the host architecture on macOS
set(CMAKE_OSX_ARCHITECTURES "${CMAKE_HOST_SYSTEM_PROCESSOR}" CACHE STRING "" FORCE)
endif()
endif()
set(APP_VERSION_MAJOR 2)
set(APP_VERSION_MINOR 4)
set(APP_VERSION_PATCH 2)
set(APP_VERSION "${APP_VERSION_MAJOR}.${APP_VERSION_MINOR}.${APP_VERSION_PATCH}")
# Include the binary directory for the generated header file
include_directories("${CMAKE_CURRENT_BINARY_DIR}")
project(gpt4all VERSION ${APP_VERSION} LANGUAGES CXX C)
set(CMAKE_AUTOMOC ON)
set(CMAKE_AUTORCC ON)
set(CMAKE_CXX_STANDARD_REQUIRED ON)
option(GPT4ALL_LOCALHOST OFF "Build installer for localhost repo")
option(GPT4ALL_AVX_ONLY OFF "Build for avx only")
option(GPT4ALL_OFFLINE_INSTALLER "Build an offline installer" OFF)
# Generate a header file with the version number
configure_file(
"${CMAKE_CURRENT_SOURCE_DIR}/cmake/config.h.in"
"${CMAKE_CURRENT_BINARY_DIR}/config.h"
)
find_package(Qt6 6.2 COMPONENTS Core Quick QuickDialogs2 Svg REQUIRED)
# Get the Qt6Core target properties
get_target_property(Qt6Core_INCLUDE_DIRS Qt6::Core INTERFACE_INCLUDE_DIRECTORIES)
get_target_property(Qt6Core_LIBRARY_RELEASE Qt6::Core LOCATION_RELEASE)
# Find the qmake binary
find_program(QMAKE_EXECUTABLE NAMES qmake qmake6 PATHS ${Qt6Core_INCLUDE_DIRS}/../.. NO_DEFAULT_PATH)
# Get the Qt 6 root directory
get_filename_component(Qt6_ROOT_DIR "${Qt6Core_LIBRARY_RELEASE}" DIRECTORY)
get_filename_component(Qt6_ROOT_DIR "${Qt6_ROOT_DIR}/.." ABSOLUTE)
message(STATUS "qmake binary: ${QMAKE_EXECUTABLE}")
message(STATUS "Qt 6 root directory: ${Qt6_ROOT_DIR}")
add_subdirectory(llmodel)
set (CMAKE_RUNTIME_OUTPUT_DIRECTORY ${CMAKE_BINARY_DIR}/bin)
qt_add_executable(chat
main.cpp
chat.h chat.cpp
chatllm.h chatllm.cpp
chatmodel.h chatlistmodel.h chatlistmodel.cpp
download.h download.cpp
network.h network.cpp
llm.h llm.cpp
sysinfo.h
)
qt_add_qml_module(chat
URI gpt4all
VERSION 1.0
QML_FILES
main.qml
qml/ChatDrawer.qml
qml/ModelDownloaderDialog.qml
qml/NetworkDialog.qml
qml/NewVersionDialog.qml
qml/ThumbsDownDialog.qml
qml/SettingsDialog.qml
qml/StartupDialog.qml
qml/PopupDialog.qml
qml/AboutDialog.qml
qml/Theme.qml
RESOURCES
icons/send_message.svg
icons/stop_generating.svg
icons/regenerate.svg
icons/copy.svg
icons/settings.svg
icons/edit.svg
icons/trash.svg
icons/network.svg
icons/thumbs_up.svg
icons/thumbs_down.svg
icons/logo.svg
icons/logo-32.png
icons/logo-48.png
icons/favicon.ico
icons/favicon.icns
)
set_target_properties(chat PROPERTIES
MACOSX_BUNDLE_GUI_IDENTIFIER gpt4all
MACOSX_BUNDLE_BUNDLE_VERSION ${PROJECT_VERSION}
MACOSX_BUNDLE_SHORT_VERSION_STRING ${PROJECT_VERSION_MAJOR}.${PROJECT_VERSION_MINOR}
MACOSX_BUNDLE TRUE
WIN32_EXECUTABLE TRUE
MACOSX_BUNDLE_ICON_FILE "favicon.icns"
)
if(${CMAKE_SYSTEM_NAME} MATCHES Darwin)
set_target_properties(chat PROPERTIES
OUTPUT_NAME gpt4all
)
endif()
target_compile_definitions(chat
PRIVATE $<$<OR:$<CONFIG:Debug>,$<CONFIG:RelWithDebInfo>>:QT_QML_DEBUG>)
target_link_libraries(chat
PRIVATE Qt6::Quick Qt6::Svg)
target_link_libraries(chat
PRIVATE llmodel)
set(COMPONENT_NAME_MAIN ${PROJECT_NAME})
set(CMAKE_INSTALL_PREFIX ${CMAKE_BINARY_DIR}/install)
if(NOT (CMAKE_HOST_SYSTEM_NAME STREQUAL "Darwin" AND CMAKE_HOST_SYSTEM_PROCESSOR STREQUAL "arm64"))
add_executable(test_hw test_hw.cpp)
install(TARGETS test_hw DESTINATION bin COMPONENT ${COMPONENT_NAME_MAIN})
endif()
install(TARGETS chat DESTINATION bin COMPONENT ${COMPONENT_NAME_MAIN})
install(TARGETS llmodel DESTINATION lib COMPONENT ${COMPONENT_NAME_MAIN})
install(TARGETS llama DESTINATION lib COMPONENT ${COMPONENT_NAME_MAIN})
set(CPACK_GENERATOR "IFW")
set(CPACK_VERBATIM_VARIABLES YES)
set(CPACK_IFW_VERBOSE ON)
if(${CMAKE_SYSTEM_NAME} MATCHES Linux)
set(LINUXDEPLOYQT "$ENV{HOME}/dev/linuxdeployqt/build/tools/linuxdeployqt/linuxdeployqt")
configure_file("${CMAKE_CURRENT_SOURCE_DIR}/cmake/deploy-qt-linux.cmake.in"
"${CMAKE_BINARY_DIR}/cmake/deploy-qt-linux.cmake" @ONLY)
set(CPACK_PRE_BUILD_SCRIPTS ${CMAKE_BINARY_DIR}/cmake/deploy-qt-linux.cmake)
set(CPACK_IFW_ROOT "~/Qt/Tools/QtInstallerFramework/4.5")
set(CPACK_PACKAGE_FILE_NAME "${COMPONENT_NAME_MAIN}-installer-linux")
set(CPACK_IFW_TARGET_DIRECTORY "@HomeDir@/${COMPONENT_NAME_MAIN}")
elseif(${CMAKE_SYSTEM_NAME} MATCHES Windows)
find_program(WINDEPLOYQT windeployqt HINTS ${_qt_bin_dir})
configure_file("${CMAKE_CURRENT_SOURCE_DIR}/cmake/deploy-qt-windows.cmake.in"
"${CMAKE_BINARY_DIR}/cmake/deploy-qt-windows.cmake" @ONLY)
set(CPACK_PRE_BUILD_SCRIPTS ${CMAKE_BINARY_DIR}/cmake/deploy-qt-windows.cmake)
set(CPACK_IFW_ROOT "C:/Qt/Tools/QtInstallerFramework/4.5")
set(CPACK_IFW_PACKAGE_ICON "${CMAKE_CURRENT_SOURCE_DIR}/icons/favicon.ico")
set(CPACK_PACKAGE_FILE_NAME "${COMPONENT_NAME_MAIN}-installer-win64")
set(CPACK_IFW_TARGET_DIRECTORY "@HomeDir@\\${COMPONENT_NAME_MAIN}")
elseif(${CMAKE_SYSTEM_NAME} MATCHES Darwin)
find_program(MACDEPLOYQT macdeployqt HINTS ${_qt_bin_dir})
configure_file("${CMAKE_CURRENT_SOURCE_DIR}/cmake/deploy-qt-mac.cmake.in"
"${CMAKE_BINARY_DIR}/cmake/deploy-qt-mac.cmake" @ONLY)
set(CPACK_PRE_BUILD_SCRIPTS ${CMAKE_BINARY_DIR}/cmake/deploy-qt-mac.cmake)
set(CPACK_IFW_ROOT "~/Qt/Tools/QtInstallerFramework/4.5")
set(CPACK_IFW_PACKAGE_ICON "${CMAKE_CURRENT_SOURCE_DIR}/icons/favicon.icns")
set(CPACK_PACKAGE_FILE_NAME "${COMPONENT_NAME_MAIN}-installer-darwin")
set(CPACK_IFW_TARGET_DIRECTORY "@ApplicationsDir@/${COMPONENT_NAME_MAIN}")
set(CPACK_BUNDLE_NAME ${COMPONENT_NAME_MAIN})
set(CPACK_BUNDLE_ICON "${CMAKE_CURRENT_SOURCE_DIR}/icons/favicon.icns")
endif()
set(CPACK_PACKAGE_INSTALL_DIRECTORY ${COMPONENT_NAME_MAIN})
set(CPACK_PACKAGE_VERSION_MAJOR ${PROJECT_VERSION_MAJOR})
set(CPACK_PACKAGE_VERSION_MINOR ${PROJECT_VERSION_MINOR})
SET(CPACK_PACKAGE_VERSION_PATCH ${PROJECT_VERSION_PATCH})
set(CPACK_PACKAGE_HOMEPAGE_URL "https://gpt4all.io")
set(CPACK_PACKAGE_ICON "${CMAKE_CURRENT_SOURCE_DIR}/icons/logo-48.png")
set(CPACK_RESOURCE_FILE_LICENSE ${CMAKE_CURRENT_SOURCE_DIR}/LICENSE)
set(CPACK_RESOURCE_FILE_README ${CMAKE_CURRENT_SOURCE_DIR}/README.md)
set(CPACK_PACKAGE_EXECUTABLES "GPT4All")
set(CPACK_CREATE_DESKTOP_LINKS "GPT4All")
set(CPACK_IFW_PACKAGE_NAME "GPT4All")
set(CPACK_IFW_PACKAGE_TITLE "GPT4All Installer")
set(CPACK_IFW_PACKAGE_PUBLISHER "Nomic, Inc.")
set(CPACK_IFW_PRODUCT_URL "https://gpt4all.io")
set(CPACK_IFW_PACKAGE_WIZARD_STYLE "Aero")
set(CPACK_IFW_PACKAGE_LOGO "${CMAKE_CURRENT_SOURCE_DIR}/icons/logo-48.png")
set(CPACK_IFW_PACKAGE_WINDOW_ICON "${CMAKE_CURRENT_SOURCE_DIR}/icons/logo-32.png")
set(CPACK_IFW_PACKAGE_WIZARD_SHOW_PAGE_LIST OFF)
include(InstallRequiredSystemLibraries)
include(CPack)
include(CPackIFW)
cpack_add_component(${COMPONENT_NAME_MAIN} DOWNLOADED)
cpack_ifw_configure_component(${COMPONENT_NAME_MAIN} ESSENTIAL FORCED_INSTALLATION)
cpack_ifw_configure_component(${COMPONENT_NAME_MAIN} VERSION ${APP_VERSION})
cpack_ifw_configure_component(${COMPONENT_NAME_MAIN} LICENSES "MIT LICENSE" ${CPACK_RESOURCE_FILE_LICENSE})
cpack_ifw_configure_component(${COMPONENT_NAME_MAIN} SCRIPT "${CMAKE_CURRENT_SOURCE_DIR}/cmake/installerscript.qs")
cpack_ifw_configure_component(${COMPONENT_NAME_MAIN} REPLACES "gpt4all-chat") #Was used in very earliest prototypes
if (GPT4ALL_LOCALHOST)
cpack_ifw_add_repository("GPT4AllRepository" URL "http://localhost/repository")
elseif(GPT4ALL_OFFLINE_INSTALLER)
cpack_ifw_add_repository("GPT4AllRepository" URL "file://${CMAKE_BINARY_DIR}/packages")
else()
if(${CMAKE_SYSTEM_NAME} MATCHES Linux)
if (GPT4ALL_AVX_ONLY)
cpack_ifw_add_repository("GPT4AllRepository" URL "https://gpt4all.io/installer_repos/avx_only/linux/repository")
else()
cpack_ifw_add_repository("GPT4AllRepository" URL "https://gpt4all.io/installer_repos/linux/repository")
endif()
elseif(${CMAKE_SYSTEM_NAME} MATCHES Windows)
#To sign the target on windows have to create a batch script add use it as a custom target and then use CPACK_IFW_EXTRA_TARGETS to set this extra target
if (GPT4ALL_AVX_ONLY)
cpack_ifw_add_repository("GPT4AllRepository" URL "https://gpt4all.io/installer_repos/avx_only/windows/repository")
else()
cpack_ifw_add_repository("GPT4AllRepository" URL "https://gpt4all.io/installer_repos/windows/repository")
endif()
elseif(${CMAKE_SYSTEM_NAME} MATCHES Darwin)
if (GPT4ALL_AVX_ONLY)
cpack_ifw_add_repository("GPT4AllRepository" URL "https://gpt4all.io/installer_repos/avx_only/mac/repository")
else()
cpack_ifw_add_repository("GPT4AllRepository" URL "https://gpt4all.io/installer_repos/mac/repository")
endif()
endif()
endif()

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Copyright 2023 Nomic, Inc., Aaron Miller
Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the “Software”), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
ADDENDUM:
Any LLM models that are loaded and used by the application are not themselves
subject to this license if indeed they are even copyrightable. The terms of
this license apply only to the application software and its accompanying
documentation and do not extend to any LLM models, whether created by the
author of the application or obtained from third-party sources.

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# GPT4All Chat # gpt4all-chat
This directory will contain the code to build out the QT chat GUI.
Cross platform Qt based GUI for GPT4All versions with GPT-J as the base
model. NOTE: The model seen in the screenshot is actually a preview of a
new training run for GPT4All based on GPT-J. The GPT4All project is busy
at work getting ready to release this model including installers for all
three major OS's. In the meantime, you can try this UI out with the original
GPT-J model by following build instructions below.
![image](https://user-images.githubusercontent.com/50458173/231464085-da9edff6-a593-410e-8f38-7513f75c8aab.png)
## Install
One click installers for macOS, Linux, and Windows at https://gpt4all.io
## Features
* Cross-platform (Linux, Windows, MacOSX)
* Fast CPU based inference using ggml for GPT-J based models
* The UI is made to look and feel like you've come to expect from a chatty gpt
* Check for updates so you can alway stay fresh with latest models
* Easy to install with precompiled binaries available for all three major desktop platforms
* Multi-modal - Ability to load more than one model and switch between them
* Supports both llama.cpp and gptj.cpp style models
* Model downloader in GUI featuring many popular open source models
* Settings dialog to change temp, top_p, top_k, threads, etc
* Copy your conversation to clipboard
* Check for updates to get the very latest GUI
## Feature wishlist
* Multi-chat - a list of current and past chats and the ability to save/delete/export and switch between
* Text to speech - have the AI response with voice
* Speech to text - give the prompt with your voice
* Python bindings
* Typescript bindings
* Plugin support for langchain other developer tools
* Save your prompt/responses to disk
* Upload prompt/respones manually/automatically to nomic.ai to aid future training runs
* Syntax highlighting support for programming languages, etc.
* REST API with a built-in webserver in the chat gui itself with a headless operation mode as well
* Advanced settings for changing temperature, topk, etc. (DONE)
* YOUR IDEA HERE
## Building and running
* Follow the visual instructions on the [build_and_run](build_and_run.md) page
## Getting the latest
If you've already checked out the source code and/or built the program make sure when you do a git fetch to get the latest changes and that you also do ```git submodule update --init --recursive``` to update the submodules.
## Manual download of models
* https://gpt4all.io/models/ggml-mpt-7b-chat.bin (default) (md5sum 756249d3d6abe23bde3b1ae272628640) Current best non-commercially licensable chat model based on MPT and trained by Mosaic ML.
* https://gpt4all.io/models/ggml-gpt4all-j-v1.3-groovy.bin (default) (md5sum 81a09a0ddf89690372fc296ff7f625af) Current best commercially licensable model based on GPT-J and trained by Nomic AI on the latest curated GPT4All dataset.
* https://gpt4all.io/models/ggml-gpt4all-l13b-snoozy.bin (md5sum 91f886b68fbce697e9a3cd501951e455) Current best non-commercially licensable model based on Llama 13b and trained by Nomic AI on the latest curated GPT4All dataset.
* https://gpt4all.io/models/ggml-gpt4all-j-v1.2-jazzy.bin (md5sum 879344aaa9d62fdccbda0be7a09e7976) An commercially licensable model based on GPT-J and trained by Nomic AI on the v2 GPT4All dataset.
* https://gpt4all.io/models/ggml-gpt4all-j-v1.1-breezy.bin (md5sum 61d48a82cb188cceb14ebb8082bfec37) An commercially licensable model based on GPT-J and trained by Nomic AI on the v1 GPT4All dataset.
* https://gpt4all.io/models/ggml-gpt4all-j.bin (md5sum 5b5a3f9b858d33b29b52b89692415595) An commercially licensable model based on GPT-J and trained by Nomic AI on the v0 GPT4All dataset.
* https://gpt4all.io/models/ggml-vicuna-7b-1.1-q4_2.bin (md5sum 29119f8fa11712704c6b22ac5ab792ea) An non-commercially licensable model based on Llama 7b and trained by teams from UC Berkeley, CMU, Stanford, MBZUAI, and UC San Diego.
* https://gpt4all.io/models/ggml-vicuna-13b-1.1-q4_2.bin (md5sum 95999b7b0699e2070af63bf5d34101a8) An non-commercially licensable model based on Llama 13b and trained by teams from UC Berkeley, CMU, Stanford, MBZUAI, and UC San Diego.
* https://gpt4all.io/models/ggml-wizardLM-7B.q4_2.bin (md5sum 99e6d129745a3f1fb1121abed747b05a) An non-commercially licensable model based on Llama 7b and trained by Microsoft and Peking University.
* https://gpt4all.io/models/ggml-stable-vicuna-13B.q4_2.bin (md5sum 6cb4ee297537c9133bddab9692879de0) An non-commercially licensable model based on Llama 13b and RLHF trained by Stable AI.
* https://gpt4all.io/models/ggml-mpt-7b-base.bin (md5sum 120c32a51d020066288df045ef5d52b9) A commercially licensable model base pre-trained by Mosaic ML.
## Terminal Only Interface with no Qt dependency
Check out https://github.com/kuvaus/LlamaGPTJ-chat which is using the llmodel backend so it is compliant with our ecosystem and all models downloaded above should work with it.
## Contributing
* Pull requests welcome. See the feature wish list for ideas :)
## License
The source code of this chat interface is currently under a MIT license. The underlying GPT4All-j model is released under non-restrictive open-source Apache 2 License.
The GPT4All-J license allows for users to use generated outputs as they see fit. Users take responsibility for ensuring their content meets applicable requirements for publication in a given context or region.

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# Install Qt 6.x and setup/build gpt4all-chat from source
Depending upon your operating system, there are many ways that Qt is distributed.
Here is the recommended method for getting the Qt dependency installed to setup and build
gpt4all-chat from source.
## Create a [Qt account](https://login.qt.io/register)
![image](https://github.com/nomic-ai/gpt4all-chat/assets/10168/d1e44cab-4245-4144-a91c-7b02267df2b2)
## Go to the Qt open source [download page](https://www.qt.io/download-qt-installer-oss)
![image](https://github.com/nomic-ai/gpt4all-chat/assets/10168/d68f5f45-cca3-4fe9-acf4-cabdcb95f669)
## Start the installer and sign in
![image](https://github.com/nomic-ai/gpt4all-chat/assets/10168/899b1422-51ae-4bb5-acc9-b9027a8e9b19)
## After some screens about license, select custom
![image](https://github.com/nomic-ai/gpt4all-chat/assets/10168/2290031a-fdb0-4f47-a7f1-d77ad5451068)
## Select the following
![image](https://github.com/nomic-ai/gpt4all-chat/assets/10168/c6e999e5-cc8a-4dfc-8065-b59139e8c7ae)
NOTE: This is for macOS. For Linux it is similar, but you need ming64 for Windows, not the MSVC install
## Open up QtCreator
![image](https://github.com/nomic-ai/gpt4all-chat/assets/10168/a34978f4-a220-459c-af66-e901d7ccd7bb)
## Clone the git repo for gpt4all-chat
```
git clone --recurse-submodules https://github.com/nomic-ai/gpt4all-chat
```
## Open the gpt4all-chat project in QtCreator
![image](https://github.com/nomic-ai/gpt4all-chat/assets/10168/3d3e2743-2a1d-43d6-9e55-62f7f4306de7)
NOTE: File->Open File or Project and navigate to the gpt4all-chat repo and choose the CMakeLists.txt
## Configure project
![image](https://github.com/nomic-ai/gpt4all-chat/assets/10168/44d5aafb-a95d-434b-ba2a-a3138c0e49a0)
## Build project
![image](https://github.com/nomic-ai/gpt4all-chat/assets/10168/43cd7b42-32f0-4efa-9612-d51f85637103)
## Run project
![image](https://github.com/nomic-ai/gpt4all-chat/assets/10168/611ea795-bdcd-4feb-a466-eb1c2e936e7e)

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#include "chat.h"
#include "llm.h"
#include "network.h"
#include "download.h"
Chat::Chat(QObject *parent)
: QObject(parent)
, m_id(Network::globalInstance()->generateUniqueId())
, m_name(tr("New Chat"))
, m_chatModel(new ChatModel(this))
, m_responseInProgress(false)
, m_creationDate(QDateTime::currentSecsSinceEpoch())
, m_llmodel(new ChatLLM(this))
{
// Should be in same thread
connect(Download::globalInstance(), &Download::modelListChanged, this, &Chat::modelListChanged, Qt::DirectConnection);
connect(this, &Chat::modelNameChanged, this, &Chat::modelListChanged, Qt::DirectConnection);
// Should be in different threads
connect(m_llmodel, &ChatLLM::isModelLoadedChanged, this, &Chat::isModelLoadedChanged, Qt::QueuedConnection);
connect(m_llmodel, &ChatLLM::responseChanged, this, &Chat::handleResponseChanged, Qt::QueuedConnection);
connect(m_llmodel, &ChatLLM::responseStarted, this, &Chat::responseStarted, Qt::QueuedConnection);
connect(m_llmodel, &ChatLLM::responseStopped, this, &Chat::responseStopped, Qt::QueuedConnection);
connect(m_llmodel, &ChatLLM::modelNameChanged, this, &Chat::handleModelNameChanged, Qt::QueuedConnection);
connect(m_llmodel, &ChatLLM::modelLoadingError, this, &Chat::modelLoadingError, Qt::QueuedConnection);
connect(m_llmodel, &ChatLLM::recalcChanged, this, &Chat::handleRecalculating, Qt::QueuedConnection);
connect(m_llmodel, &ChatLLM::generatedNameChanged, this, &Chat::generatedNameChanged, Qt::QueuedConnection);
connect(this, &Chat::promptRequested, m_llmodel, &ChatLLM::prompt, Qt::QueuedConnection);
connect(this, &Chat::modelNameChangeRequested, m_llmodel, &ChatLLM::modelNameChangeRequested, Qt::QueuedConnection);
connect(this, &Chat::loadDefaultModelRequested, m_llmodel, &ChatLLM::loadDefaultModel, Qt::QueuedConnection);
connect(this, &Chat::loadModelRequested, m_llmodel, &ChatLLM::loadModel, Qt::QueuedConnection);
connect(this, &Chat::unloadModelRequested, m_llmodel, &ChatLLM::unloadModel, Qt::QueuedConnection);
connect(this, &Chat::reloadModelRequested, m_llmodel, &ChatLLM::reloadModel, Qt::QueuedConnection);
connect(this, &Chat::generateNameRequested, m_llmodel, &ChatLLM::generateName, Qt::QueuedConnection);
// The following are blocking operations and will block the gui thread, therefore must be fast
// to respond to
connect(this, &Chat::regenerateResponseRequested, m_llmodel, &ChatLLM::regenerateResponse, Qt::BlockingQueuedConnection);
connect(this, &Chat::resetResponseRequested, m_llmodel, &ChatLLM::resetResponse, Qt::BlockingQueuedConnection);
connect(this, &Chat::resetContextRequested, m_llmodel, &ChatLLM::resetContext, Qt::BlockingQueuedConnection);
}
void Chat::reset()
{
stopGenerating();
// Erase our current on disk representation as we're completely resetting the chat along with id
LLM::globalInstance()->chatListModel()->removeChatFile(this);
emit resetContextRequested(); // blocking queued connection
m_id = Network::globalInstance()->generateUniqueId();
emit idChanged();
// NOTE: We deliberately do no reset the name or creation date to indictate that this was originally
// an older chat that was reset for another purpose. Resetting this data will lead to the chat
// name label changing back to 'New Chat' and showing up in the chat model list as a 'New Chat'
// further down in the list. This might surprise the user. In the future, we me might get rid of
// the "reset context" button in the UI. Right now, by changing the model in the combobox dropdown
// we effectively do a reset context. We *have* to do this right now when switching between different
// types of models. The only way to get rid of that would be a very long recalculate where we rebuild
// the context if we switch between different types of models. Probably the right way to fix this
// is to allow switching models but throwing up a dialog warning users if we switch between types
// of models that a long recalculation will ensue.
m_chatModel->clear();
}
bool Chat::isModelLoaded() const
{
return m_llmodel->isModelLoaded();
}
void Chat::prompt(const QString &prompt, const QString &prompt_template, int32_t n_predict,
int32_t top_k, float top_p, float temp, int32_t n_batch, float repeat_penalty,
int32_t repeat_penalty_tokens)
{
emit promptRequested(prompt, prompt_template, n_predict, top_k, top_p, temp, n_batch,
repeat_penalty, repeat_penalty_tokens, LLM::globalInstance()->threadCount());
}
void Chat::regenerateResponse()
{
emit regenerateResponseRequested(); // blocking queued connection
}
void Chat::stopGenerating()
{
m_llmodel->stopGenerating();
}
QString Chat::response() const
{
return m_llmodel->response();
}
void Chat::handleResponseChanged()
{
const int index = m_chatModel->count() - 1;
m_chatModel->updateValue(index, response());
emit responseChanged();
}
void Chat::responseStarted()
{
m_responseInProgress = true;
emit responseInProgressChanged();
}
void Chat::responseStopped()
{
m_responseInProgress = false;
emit responseInProgressChanged();
if (m_llmodel->generatedName().isEmpty())
emit generateNameRequested();
if (chatModel()->count() < 3)
Network::globalInstance()->sendChatStarted();
}
QString Chat::modelName() const
{
return m_llmodel->modelName();
}
void Chat::setModelName(const QString &modelName)
{
// doesn't block but will unload old model and load new one which the gui can see through changes
// to the isModelLoaded property
emit modelNameChangeRequested(modelName);
}
void Chat::newPromptResponsePair(const QString &prompt)
{
m_chatModel->appendPrompt(tr("Prompt: "), prompt);
m_chatModel->appendResponse(tr("Response: "), prompt);
emit resetResponseRequested(); // blocking queued connection
}
bool Chat::isRecalc() const
{
return m_llmodel->isRecalc();
}
void Chat::loadDefaultModel()
{
emit loadDefaultModelRequested();
}
void Chat::loadModel(const QString &modelName)
{
emit loadModelRequested(modelName);
}
void Chat::unloadModel()
{
stopGenerating();
emit unloadModelRequested();
}
void Chat::reloadModel()
{
emit reloadModelRequested(m_savedModelName);
}
void Chat::generatedNameChanged()
{
// Only use the first three words maximum and remove newlines and extra spaces
QString gen = m_llmodel->generatedName().simplified();
QStringList words = gen.split(' ', Qt::SkipEmptyParts);
int wordCount = qMin(3, words.size());
m_name = words.mid(0, wordCount).join(' ');
emit nameChanged();
}
void Chat::handleRecalculating()
{
Network::globalInstance()->sendRecalculatingContext(m_chatModel->count());
emit recalcChanged();
}
void Chat::handleModelNameChanged()
{
m_savedModelName = modelName();
emit modelNameChanged();
}
bool Chat::serialize(QDataStream &stream, int version) const
{
stream << m_creationDate;
stream << m_id;
stream << m_name;
stream << m_userName;
stream << m_savedModelName;
if (!m_llmodel->serialize(stream, version))
return false;
if (!m_chatModel->serialize(stream, version))
return false;
return stream.status() == QDataStream::Ok;
}
bool Chat::deserialize(QDataStream &stream, int version)
{
stream >> m_creationDate;
stream >> m_id;
emit idChanged();
stream >> m_name;
stream >> m_userName;
emit nameChanged();
stream >> m_savedModelName;
// Prior to version 2 gptj models had a bug that fixed the kv_cache to F32 instead of F16 so
// unfortunately, we cannot deserialize these
if (version < 2 && m_savedModelName.contains("gpt4all-j"))
return false;
if (!m_llmodel->deserialize(stream, version))
return false;
if (!m_chatModel->deserialize(stream, version))
return false;
emit chatModelChanged();
return stream.status() == QDataStream::Ok;
}
QList<QString> Chat::modelList() const
{
// Build a model list from exepath and from the localpath
QList<QString> list;
QString exePath = QCoreApplication::applicationDirPath() + QDir::separator();
QString localPath = Download::globalInstance()->downloadLocalModelsPath();
{
QDir dir(exePath);
dir.setNameFilters(QStringList() << "ggml-*.bin");
QStringList fileNames = dir.entryList();
for (QString f : fileNames) {
QString filePath = exePath + f;
QFileInfo info(filePath);
QString name = info.completeBaseName().remove(0, 5);
if (info.exists()) {
if (name == modelName())
list.prepend(name);
else
list.append(name);
}
}
}
if (localPath != exePath) {
QDir dir(localPath);
dir.setNameFilters(QStringList() << "ggml-*.bin");
QStringList fileNames = dir.entryList();
for (QString f : fileNames) {
QString filePath = localPath + f;
QFileInfo info(filePath);
QString name = info.completeBaseName().remove(0, 5);
if (info.exists() && !list.contains(name)) { // don't allow duplicates
if (name == modelName())
list.prepend(name);
else
list.append(name);
}
}
}
if (list.isEmpty()) {
if (exePath != localPath) {
qWarning() << "ERROR: Could not find any applicable models in"
<< exePath << "nor" << localPath;
} else {
qWarning() << "ERROR: Could not find any applicable models in"
<< exePath;
}
return QList<QString>();
}
return list;
}

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#ifndef CHAT_H
#define CHAT_H
#include <QObject>
#include <QtQml>
#include <QDataStream>
#include "chatllm.h"
#include "chatmodel.h"
class Chat : public QObject
{
Q_OBJECT
Q_PROPERTY(QString id READ id NOTIFY idChanged)
Q_PROPERTY(QString name READ name WRITE setName NOTIFY nameChanged)
Q_PROPERTY(ChatModel *chatModel READ chatModel NOTIFY chatModelChanged)
Q_PROPERTY(bool isModelLoaded READ isModelLoaded NOTIFY isModelLoadedChanged)
Q_PROPERTY(QString response READ response NOTIFY responseChanged)
Q_PROPERTY(QString modelName READ modelName WRITE setModelName NOTIFY modelNameChanged)
Q_PROPERTY(bool responseInProgress READ responseInProgress NOTIFY responseInProgressChanged)
Q_PROPERTY(bool isRecalc READ isRecalc NOTIFY recalcChanged)
Q_PROPERTY(QList<QString> modelList READ modelList NOTIFY modelListChanged)
QML_ELEMENT
QML_UNCREATABLE("Only creatable from c++!")
public:
explicit Chat(QObject *parent = nullptr);
QString id() const { return m_id; }
QString name() const { return m_userName.isEmpty() ? m_name : m_userName; }
void setName(const QString &name)
{
m_userName = name;
emit nameChanged();
}
ChatModel *chatModel() { return m_chatModel; }
Q_INVOKABLE void reset();
Q_INVOKABLE bool isModelLoaded() const;
Q_INVOKABLE void prompt(const QString &prompt, const QString &prompt_template, int32_t n_predict,
int32_t top_k, float top_p, float temp, int32_t n_batch, float repeat_penalty, int32_t repeat_penalty_tokens);
Q_INVOKABLE void regenerateResponse();
Q_INVOKABLE void stopGenerating();
Q_INVOKABLE void newPromptResponsePair(const QString &prompt);
QString response() const;
bool responseInProgress() const { return m_responseInProgress; }
QString modelName() const;
void setModelName(const QString &modelName);
bool isRecalc() const;
void loadDefaultModel();
void loadModel(const QString &modelName);
void unloadModel();
void reloadModel();
qint64 creationDate() const { return m_creationDate; }
bool serialize(QDataStream &stream, int version) const;
bool deserialize(QDataStream &stream, int version);
QList<QString> modelList() const;
Q_SIGNALS:
void idChanged();
void nameChanged();
void chatModelChanged();
void isModelLoadedChanged();
void responseChanged();
void responseInProgressChanged();
void promptRequested(const QString &prompt, const QString &prompt_template, int32_t n_predict,
int32_t top_k, float top_p, float temp, int32_t n_batch, float repeat_penalty, int32_t repeat_penalty_tokens,
int32_t n_threads);
void regenerateResponseRequested();
void resetResponseRequested();
void resetContextRequested();
void modelNameChangeRequested(const QString &modelName);
void modelNameChanged();
void recalcChanged();
void loadDefaultModelRequested();
void loadModelRequested(const QString &modelName);
void unloadModelRequested();
void reloadModelRequested(const QString &modelName);
void generateNameRequested();
void modelListChanged();
void modelLoadingError(const QString &error);
private Q_SLOTS:
void handleResponseChanged();
void responseStarted();
void responseStopped();
void generatedNameChanged();
void handleRecalculating();
void handleModelNameChanged();
private:
QString m_id;
QString m_name;
QString m_userName;
QString m_savedModelName;
ChatModel *m_chatModel;
bool m_responseInProgress;
qint64 m_creationDate;
ChatLLM *m_llmodel;
};
#endif // CHAT_H

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#include "chatlistmodel.h"
#include "download.h"
#include <QFile>
#include <QDataStream>
#define CHAT_FORMAT_MAGIC 0xF5D553CC
#define CHAT_FORMAT_VERSION 2
ChatListModel::ChatListModel(QObject *parent)
: QAbstractListModel(parent)
, m_newChat(nullptr)
, m_dummyChat(nullptr)
, m_currentChat(nullptr)
, m_shouldSaveChats(false)
{
addDummyChat();
ChatsRestoreThread *thread = new ChatsRestoreThread;
connect(thread, &ChatsRestoreThread::chatRestored, this, &ChatListModel::restoreChat);
connect(thread, &ChatsRestoreThread::finished, this, &ChatListModel::chatsRestoredFinished);
connect(thread, &ChatsRestoreThread::finished, thread, &QObject::deleteLater);
thread->start();
}
bool ChatListModel::shouldSaveChats() const
{
return m_shouldSaveChats;
}
void ChatListModel::setShouldSaveChats(bool b)
{
if (m_shouldSaveChats == b)
return;
m_shouldSaveChats = b;
emit shouldSaveChatsChanged();
}
void ChatListModel::removeChatFile(Chat *chat) const
{
const QString savePath = Download::globalInstance()->downloadLocalModelsPath();
QFile file(savePath + "/gpt4all-" + chat->id() + ".chat");
if (!file.exists())
return;
bool success = file.remove();
if (!success)
qWarning() << "ERROR: Couldn't remove chat file:" << file.fileName();
}
void ChatListModel::saveChats() const
{
if (!m_shouldSaveChats)
return;
QElapsedTimer timer;
timer.start();
const QString savePath = Download::globalInstance()->downloadLocalModelsPath();
for (Chat *chat : m_chats) {
QString fileName = "gpt4all-" + chat->id() + ".chat";
QFile file(savePath + "/" + fileName);
bool success = file.open(QIODevice::WriteOnly);
if (!success) {
qWarning() << "ERROR: Couldn't save chat to file:" << file.fileName();
continue;
}
QDataStream out(&file);
out << (quint32)CHAT_FORMAT_MAGIC;
out << (qint32)CHAT_FORMAT_VERSION;
out.setVersion(QDataStream::Qt_6_2);
qDebug() << "serializing chat" << fileName;
if (!chat->serialize(out, CHAT_FORMAT_VERSION)) {
qWarning() << "ERROR: Couldn't serialize chat to file:" << file.fileName();
file.remove();
}
file.close();
}
qint64 elapsedTime = timer.elapsed();
qDebug() << "serializing chats took:" << elapsedTime << "ms";
}
void ChatsRestoreThread::run()
{
QElapsedTimer timer;
timer.start();
struct FileInfo {
bool oldFile;
qint64 creationDate;
QString file;
};
QList<FileInfo> files;
{
// Look for any files in the original spot which was the settings config directory
QSettings settings;
QFileInfo settingsInfo(settings.fileName());
QString settingsPath = settingsInfo.absolutePath();
QDir dir(settingsPath);
dir.setNameFilters(QStringList() << "gpt4all-*.chat");
QStringList fileNames = dir.entryList();
for (QString f : fileNames) {
QString filePath = settingsPath + "/" + f;
QFile file(filePath);
bool success = file.open(QIODevice::ReadOnly);
if (!success) {
qWarning() << "ERROR: Couldn't restore chat from file:" << file.fileName();
continue;
}
QDataStream in(&file);
FileInfo info;
info.oldFile = true;
info.file = filePath;
in >> info.creationDate;
files.append(info);
file.close();
}
}
{
const QString savePath = Download::globalInstance()->downloadLocalModelsPath();
QDir dir(savePath);
dir.setNameFilters(QStringList() << "gpt4all-*.chat");
QStringList fileNames = dir.entryList();
for (QString f : fileNames) {
QString filePath = savePath + "/" + f;
QFile file(filePath);
bool success = file.open(QIODevice::ReadOnly);
if (!success) {
qWarning() << "ERROR: Couldn't restore chat from file:" << file.fileName();
continue;
}
QDataStream in(&file);
// Read and check the header
quint32 magic;
in >> magic;
if (magic != CHAT_FORMAT_MAGIC) {
qWarning() << "ERROR: Chat file has bad magic:" << file.fileName();
continue;
}
// Read the version
qint32 version;
in >> version;
if (version < 1) {
qWarning() << "ERROR: Chat file has non supported version:" << file.fileName();
continue;
}
if (version <= 1)
in.setVersion(QDataStream::Qt_6_2);
FileInfo info;
info.oldFile = false;
info.file = filePath;
in >> info.creationDate;
files.append(info);
file.close();
}
}
std::sort(files.begin(), files.end(), [](const FileInfo &a, const FileInfo &b) {
return a.creationDate > b.creationDate;
});
for (FileInfo &f : files) {
QFile file(f.file);
bool success = file.open(QIODevice::ReadOnly);
if (!success) {
qWarning() << "ERROR: Couldn't restore chat from file:" << file.fileName();
continue;
}
QDataStream in(&file);
qint32 version = 0;
if (!f.oldFile) {
// Read and check the header
quint32 magic;
in >> magic;
if (magic != CHAT_FORMAT_MAGIC) {
qWarning() << "ERROR: Chat file has bad magic:" << file.fileName();
continue;
}
// Read the version
in >> version;
if (version < 1) {
qWarning() << "ERROR: Chat file has non supported version:" << file.fileName();
continue;
}
if (version <= 1)
in.setVersion(QDataStream::Qt_6_2);
}
qDebug() << "deserializing chat" << f.file;
Chat *chat = new Chat;
chat->moveToThread(qApp->thread());
if (!chat->deserialize(in, version)) {
qWarning() << "ERROR: Couldn't deserialize chat from file:" << file.fileName();
file.remove();
} else {
emit chatRestored(chat);
}
if (f.oldFile)
file.remove(); // No longer storing in this directory
file.close();
}
qint64 elapsedTime = timer.elapsed();
qDebug() << "deserializing chats took:" << elapsedTime << "ms";
}
void ChatListModel::restoreChat(Chat *chat)
{
chat->setParent(this);
connect(chat, &Chat::nameChanged, this, &ChatListModel::nameChanged);
connect(chat, &Chat::modelLoadingError, this, &ChatListModel::handleModelLoadingError);
if (m_dummyChat) {
beginResetModel();
m_chats = QList<Chat*>({chat});
setCurrentChat(chat);
delete m_dummyChat;
m_dummyChat = nullptr;
endResetModel();
} else {
beginInsertRows(QModelIndex(), m_chats.size(), m_chats.size());
m_chats.append(chat);
endInsertRows();
}
}
void ChatListModel::chatsRestoredFinished()
{
if (m_dummyChat) {
beginResetModel();
Chat *dummy = m_dummyChat;
m_dummyChat = nullptr;
m_chats.clear();
addChat();
delete dummy;
endResetModel();
}
if (m_chats.isEmpty())
addChat();
}

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#ifndef CHATLISTMODEL_H
#define CHATLISTMODEL_H
#include <QAbstractListModel>
#include "chat.h"
class ChatsRestoreThread : public QThread
{
Q_OBJECT
public:
void run() override;
Q_SIGNALS:
void chatRestored(Chat *chat);
};
class ChatListModel : public QAbstractListModel
{
Q_OBJECT
Q_PROPERTY(int count READ count NOTIFY countChanged)
Q_PROPERTY(Chat *currentChat READ currentChat WRITE setCurrentChat NOTIFY currentChatChanged)
Q_PROPERTY(bool shouldSaveChats READ shouldSaveChats WRITE setShouldSaveChats NOTIFY shouldSaveChatsChanged)
public:
explicit ChatListModel(QObject *parent = nullptr);
enum Roles {
IdRole = Qt::UserRole + 1,
NameRole
};
int rowCount(const QModelIndex &parent = QModelIndex()) const override
{
Q_UNUSED(parent)
return m_chats.size();
}
QVariant data(const QModelIndex &index, int role = Qt::DisplayRole) const override
{
if (!index.isValid() || index.row() < 0 || index.row() >= m_chats.size())
return QVariant();
const Chat *item = m_chats.at(index.row());
switch (role) {
case IdRole:
return item->id();
case NameRole:
return item->name();
}
return QVariant();
}
QHash<int, QByteArray> roleNames() const override
{
QHash<int, QByteArray> roles;
roles[IdRole] = "id";
roles[NameRole] = "name";
return roles;
}
bool shouldSaveChats() const;
void setShouldSaveChats(bool b);
Q_INVOKABLE void addChat()
{
// Don't add a new chat if we already have one
if (m_newChat || m_dummyChat)
return;
// Create a new chat pointer and connect it to determine when it is populated
m_newChat = new Chat(this);
connect(m_newChat->chatModel(), &ChatModel::countChanged,
this, &ChatListModel::newChatCountChanged);
connect(m_newChat, &Chat::nameChanged,
this, &ChatListModel::nameChanged);
beginInsertRows(QModelIndex(), 0, 0);
m_chats.prepend(m_newChat);
endInsertRows();
emit countChanged();
setCurrentChat(m_newChat);
}
Q_INVOKABLE void addDummyChat()
{
// Create a new dummy chat pointer and don't connect it
m_dummyChat = new Chat(this);
beginInsertRows(QModelIndex(), 0, 0);
m_chats.prepend(m_dummyChat);
endInsertRows();
emit countChanged();
m_currentChat = m_dummyChat;
emit currentChatChanged();
}
void setNewChat(Chat* chat)
{
// Don't add a new chat if we already have one
if (m_newChat)
return;
m_newChat = chat;
connect(m_newChat->chatModel(), &ChatModel::countChanged,
this, &ChatListModel::newChatCountChanged);
connect(m_newChat, &Chat::nameChanged,
this, &ChatListModel::nameChanged);
connect(m_newChat, &Chat::modelLoadingError,
this, &ChatListModel::handleModelLoadingError);
setCurrentChat(m_newChat);
}
Q_INVOKABLE void removeChat(Chat* chat)
{
if (!m_chats.contains(chat)) {
qWarning() << "WARNING: Removing chat failed with id" << chat->id();
return;
}
removeChatFile(chat);
if (chat == m_newChat) {
m_newChat->disconnect(this);
m_newChat = nullptr;
}
const int index = m_chats.indexOf(chat);
if (m_chats.count() < 2) {
addChat();
} else {
int nextIndex;
if (index == m_chats.count() - 1)
nextIndex = index - 1;
else
nextIndex = index + 1;
Chat *nextChat = get(nextIndex);
Q_ASSERT(nextChat);
setCurrentChat(nextChat);
}
const int newIndex = m_chats.indexOf(chat);
beginRemoveRows(QModelIndex(), newIndex, newIndex);
m_chats.removeAll(chat);
endRemoveRows();
delete chat;
}
Chat *currentChat() const
{
return m_currentChat;
}
void setCurrentChat(Chat *chat)
{
if (!m_chats.contains(chat)) {
qWarning() << "ERROR: Setting current chat failed with id" << chat->id();
return;
}
if (m_currentChat && m_currentChat->isModelLoaded())
m_currentChat->unloadModel();
m_currentChat = chat;
if (!m_currentChat->isModelLoaded())
m_currentChat->reloadModel();
emit currentChatChanged();
}
Q_INVOKABLE Chat* get(int index)
{
if (index < 0 || index >= m_chats.size()) return nullptr;
return m_chats.at(index);
}
int count() const { return m_chats.size(); }
void removeChatFile(Chat *chat) const;
void saveChats() const;
void restoreChat(Chat *chat);
void chatsRestoredFinished();
Q_SIGNALS:
void countChanged();
void currentChatChanged();
void shouldSaveChatsChanged();
private Q_SLOTS:
void newChatCountChanged()
{
Q_ASSERT(m_newChat && m_newChat->chatModel()->count());
m_newChat->chatModel()->disconnect(this);
m_newChat = nullptr;
}
void nameChanged()
{
Chat *chat = qobject_cast<Chat *>(sender());
if (!chat)
return;
int row = m_chats.indexOf(chat);
if (row < 0 || row >= m_chats.size())
return;
QModelIndex index = createIndex(row, 0);
emit dataChanged(index, index, {NameRole});
}
void handleModelLoadingError(const QString &error)
{
Chat *chat = qobject_cast<Chat *>(sender());
qWarning() << "ERROR:" << qPrintable(error) << "id" << chat->id();
removeChat(chat);
}
void printChats()
{
for (auto c : m_chats) {
qDebug() << c->name()
<< (c == m_currentChat ? "currentChat: true" : "currentChat: false")
<< (c == m_newChat ? "newChat: true" : "newChat: false");
}
}
private:
bool m_shouldSaveChats;
Chat* m_newChat;
Chat* m_dummyChat;
Chat* m_currentChat;
QList<Chat*> m_chats;
};
#endif // CHATITEMMODEL_H

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#include "chatllm.h"
#include "chat.h"
#include "download.h"
#include "network.h"
#include "llmodel/gptj.h"
#include "llmodel/llamamodel.h"
#include "llmodel/mpt.h"
#include <QCoreApplication>
#include <QDir>
#include <QFile>
#include <QProcess>
#include <QResource>
#include <QSettings>
#include <fstream>
//#define DEBUG
#define MPT_INTERNAL_STATE_VERSION 0
#define GPTJ_INTERNAL_STATE_VERSION 0
#define LLAMA_INTERNAL_STATE_VERSION 0
static QString modelFilePath(const QString &modelName)
{
QString appPath = QCoreApplication::applicationDirPath()
+ "/ggml-" + modelName + ".bin";
QFileInfo infoAppPath(appPath);
if (infoAppPath.exists())
return appPath;
QString downloadPath = Download::globalInstance()->downloadLocalModelsPath()
+ "/ggml-" + modelName + ".bin";
QFileInfo infoLocalPath(downloadPath);
if (infoLocalPath.exists())
return downloadPath;
return QString();
}
ChatLLM::ChatLLM(Chat *parent)
: QObject{nullptr}
, m_llmodel(nullptr)
, m_promptResponseTokens(0)
, m_responseLogits(0)
, m_isRecalc(false)
, m_chat(parent)
{
moveToThread(&m_llmThread);
connect(this, &ChatLLM::sendStartup, Network::globalInstance(), &Network::sendStartup);
connect(this, &ChatLLM::sendModelLoaded, Network::globalInstance(), &Network::sendModelLoaded);
connect(m_chat, &Chat::idChanged, this, &ChatLLM::handleChatIdChanged);
m_llmThread.setObjectName(m_chat->id());
m_llmThread.start();
}
bool ChatLLM::loadDefaultModel()
{
const QList<QString> models = m_chat->modelList();
if (models.isEmpty()) {
// try again when we get a list of models
connect(Download::globalInstance(), &Download::modelListChanged, this,
&ChatLLM::loadDefaultModel, Qt::SingleShotConnection);
return false;
}
QSettings settings;
settings.sync();
// The user default model can be set by the user in the settings dialog. The "default" user
// default model is "Application default" which signals we should use the default model that was
// specified by the models.json file.
QString defaultModel = settings.value("userDefaultModel").toString();
if (defaultModel.isEmpty() || !models.contains(defaultModel) || defaultModel == "Application default")
defaultModel = settings.value("defaultModel").toString();
if (defaultModel.isEmpty() || !models.contains(defaultModel))
defaultModel = models.first();
return loadModel(defaultModel);
}
bool ChatLLM::loadModel(const QString &modelName)
{
if (isModelLoaded() && m_modelName == modelName)
return true;
if (isModelLoaded()) {
resetContextPrivate();
delete m_llmodel;
m_llmodel = nullptr;
emit isModelLoadedChanged();
}
bool isGPTJ = false;
bool isMPT = false;
QString filePath = modelFilePath(modelName);
QFileInfo info(filePath);
if (info.exists()) {
auto fin = std::ifstream(filePath.toStdString(), std::ios::binary);
uint32_t magic;
fin.read((char *) &magic, sizeof(magic));
fin.seekg(0);
fin.close();
isGPTJ = magic == 0x67676d6c;
isMPT = magic == 0x67676d6d;
if (isGPTJ) {
m_modelType = ModelType::GPTJ_;
m_llmodel = new GPTJ;
m_llmodel->loadModel(filePath.toStdString());
} else if (isMPT) {
m_modelType = ModelType::MPT_;
m_llmodel = new MPT;
m_llmodel->loadModel(filePath.toStdString());
} else {
m_modelType = ModelType::LLAMA_;
m_llmodel = new LLamaModel;
m_llmodel->loadModel(filePath.toStdString());
}
restoreState();
#if defined(DEBUG)
qDebug() << "chatllm modelLoadedChanged" << m_chat->id();
fflush(stdout);
#endif
emit isModelLoadedChanged();
static bool isFirstLoad = true;
if (isFirstLoad) {
emit sendStartup();
isFirstLoad = false;
} else
emit sendModelLoaded();
} else {
const QString error = QString("Could not find model %1").arg(modelName);
emit modelLoadingError(error);
}
if (m_llmodel)
setModelName(info.completeBaseName().remove(0, 5)); // remove the ggml- prefix
return m_llmodel;
}
bool ChatLLM::isModelLoaded() const
{
return m_llmodel && m_llmodel->isModelLoaded();
}
void ChatLLM::regenerateResponse()
{
m_ctx.n_past -= m_promptResponseTokens;
m_ctx.n_past = std::max(0, m_ctx.n_past);
// FIXME: This does not seem to be needed in my testing and llama models don't to it. Remove?
m_ctx.logits.erase(m_ctx.logits.end() -= m_responseLogits, m_ctx.logits.end());
m_ctx.tokens.erase(m_ctx.tokens.end() -= m_promptResponseTokens, m_ctx.tokens.end());
m_promptResponseTokens = 0;
m_responseLogits = 0;
m_response = std::string();
emit responseChanged();
}
void ChatLLM::resetResponse()
{
m_promptResponseTokens = 0;
m_responseLogits = 0;
m_response = std::string();
emit responseChanged();
}
void ChatLLM::resetContext()
{
resetContextPrivate();
emit sendResetContext();
}
void ChatLLM::resetContextPrivate()
{
regenerateResponse();
m_ctx = LLModel::PromptContext();
}
std::string remove_leading_whitespace(const std::string& input) {
auto first_non_whitespace = std::find_if(input.begin(), input.end(), [](unsigned char c) {
return !std::isspace(c);
});
return std::string(first_non_whitespace, input.end());
}
std::string trim_whitespace(const std::string& input) {
auto first_non_whitespace = std::find_if(input.begin(), input.end(), [](unsigned char c) {
return !std::isspace(c);
});
auto last_non_whitespace = std::find_if(input.rbegin(), input.rend(), [](unsigned char c) {
return !std::isspace(c);
}).base();
return std::string(first_non_whitespace, last_non_whitespace);
}
QString ChatLLM::response() const
{
return QString::fromStdString(remove_leading_whitespace(m_response));
}
QString ChatLLM::modelName() const
{
return m_modelName;
}
void ChatLLM::setModelName(const QString &modelName)
{
m_modelName = modelName;
emit modelNameChanged();
}
void ChatLLM::modelNameChangeRequested(const QString &modelName)
{
if (!loadModel(modelName))
qWarning() << "ERROR: Could not load model" << modelName;
}
bool ChatLLM::handlePrompt(int32_t token)
{
// m_promptResponseTokens and m_responseLogits are related to last prompt/response not
// the entire context window which we can reset on regenerate prompt
#if defined(DEBUG)
qDebug() << "chatllm prompt process" << m_chat->id() << token;
#endif
++m_promptResponseTokens;
return !m_stopGenerating;
}
bool ChatLLM::handleResponse(int32_t token, const std::string &response)
{
#if defined(DEBUG)
printf("%s", response.c_str());
fflush(stdout);
#endif
// check for error
if (token < 0) {
m_response.append(response);
emit responseChanged();
return false;
}
// m_promptResponseTokens and m_responseLogits are related to last prompt/response not
// the entire context window which we can reset on regenerate prompt
++m_promptResponseTokens;
Q_ASSERT(!response.empty());
m_response.append(response);
emit responseChanged();
return !m_stopGenerating;
}
bool ChatLLM::handleRecalculate(bool isRecalc)
{
if (m_isRecalc != isRecalc) {
m_isRecalc = isRecalc;
emit recalcChanged();
}
return !m_stopGenerating;
}
bool ChatLLM::prompt(const QString &prompt, const QString &prompt_template, int32_t n_predict, int32_t top_k,
float top_p, float temp, int32_t n_batch, float repeat_penalty, int32_t repeat_penalty_tokens, int n_threads)
{
if (!isModelLoaded())
return false;
QString instructPrompt = prompt_template.arg(prompt);
m_stopGenerating = false;
auto promptFunc = std::bind(&ChatLLM::handlePrompt, this, std::placeholders::_1);
auto responseFunc = std::bind(&ChatLLM::handleResponse, this, std::placeholders::_1,
std::placeholders::_2);
auto recalcFunc = std::bind(&ChatLLM::handleRecalculate, this, std::placeholders::_1);
emit responseStarted();
qint32 logitsBefore = m_ctx.logits.size();
m_ctx.n_predict = n_predict;
m_ctx.top_k = top_k;
m_ctx.top_p = top_p;
m_ctx.temp = temp;
m_ctx.n_batch = n_batch;
m_ctx.repeat_penalty = repeat_penalty;
m_ctx.repeat_last_n = repeat_penalty_tokens;
m_llmodel->setThreadCount(n_threads);
#if defined(DEBUG)
printf("%s", qPrintable(instructPrompt));
fflush(stdout);
#endif
m_llmodel->prompt(instructPrompt.toStdString(), promptFunc, responseFunc, recalcFunc, m_ctx);
#if defined(DEBUG)
printf("\n");
fflush(stdout);
#endif
m_responseLogits += m_ctx.logits.size() - logitsBefore;
std::string trimmed = trim_whitespace(m_response);
if (trimmed != m_response) {
m_response = trimmed;
emit responseChanged();
}
emit responseStopped();
return true;
}
void ChatLLM::unloadModel()
{
#if defined(DEBUG)
qDebug() << "chatllm unloadModel" << m_chat->id();
#endif
saveState();
delete m_llmodel;
m_llmodel = nullptr;
emit isModelLoadedChanged();
}
void ChatLLM::reloadModel(const QString &modelName)
{
#if defined(DEBUG)
qDebug() << "chatllm reloadModel" << m_chat->id();
#endif
if (modelName.isEmpty()) {
loadDefaultModel();
} else {
loadModel(modelName);
}
}
void ChatLLM::generateName()
{
Q_ASSERT(isModelLoaded());
if (!isModelLoaded())
return;
QString instructPrompt("### Instruction:\n"
"Describe response above in three words.\n"
"### Response:\n");
auto promptFunc = std::bind(&ChatLLM::handleNamePrompt, this, std::placeholders::_1);
auto responseFunc = std::bind(&ChatLLM::handleNameResponse, this, std::placeholders::_1,
std::placeholders::_2);
auto recalcFunc = std::bind(&ChatLLM::handleNameRecalculate, this, std::placeholders::_1);
LLModel::PromptContext ctx = m_ctx;
#if defined(DEBUG)
printf("%s", qPrintable(instructPrompt));
fflush(stdout);
#endif
m_llmodel->prompt(instructPrompt.toStdString(), promptFunc, responseFunc, recalcFunc, ctx);
#if defined(DEBUG)
printf("\n");
fflush(stdout);
#endif
std::string trimmed = trim_whitespace(m_nameResponse);
if (trimmed != m_nameResponse) {
m_nameResponse = trimmed;
emit generatedNameChanged();
}
}
void ChatLLM::handleChatIdChanged()
{
m_llmThread.setObjectName(m_chat->id());
}
bool ChatLLM::handleNamePrompt(int32_t token)
{
Q_UNUSED(token);
qt_noop();
return true;
}
bool ChatLLM::handleNameResponse(int32_t token, const std::string &response)
{
Q_UNUSED(token);
m_nameResponse.append(response);
emit generatedNameChanged();
QString gen = QString::fromStdString(m_nameResponse).simplified();
QStringList words = gen.split(' ', Qt::SkipEmptyParts);
int wordCount = words.size();
return words.size() <= 3;
}
bool ChatLLM::handleNameRecalculate(bool isRecalc)
{
Q_UNUSED(isRecalc);
Q_UNREACHABLE();
return true;
}
bool ChatLLM::serialize(QDataStream &stream, int version)
{
if (version > 1) {
stream << m_modelType;
switch (m_modelType) {
case MPT_: stream << MPT_INTERNAL_STATE_VERSION; break;
case GPTJ_: stream << GPTJ_INTERNAL_STATE_VERSION; break;
case LLAMA_: stream << LLAMA_INTERNAL_STATE_VERSION; break;
default: Q_UNREACHABLE();
}
}
stream << response();
stream << generatedName();
stream << m_promptResponseTokens;
stream << m_responseLogits;
stream << m_ctx.n_past;
stream << quint64(m_ctx.logits.size());
stream.writeRawData(reinterpret_cast<const char*>(m_ctx.logits.data()), m_ctx.logits.size() * sizeof(float));
stream << quint64(m_ctx.tokens.size());
stream.writeRawData(reinterpret_cast<const char*>(m_ctx.tokens.data()), m_ctx.tokens.size() * sizeof(int));
saveState();
QByteArray compressed = qCompress(m_state);
stream << compressed;
#if defined(DEBUG)
qDebug() << "chatllm serialize" << m_chat->id() << m_state.size();
#endif
return stream.status() == QDataStream::Ok;
}
bool ChatLLM::deserialize(QDataStream &stream, int version)
{
if (version > 1) {
int internalStateVersion;
stream >> m_modelType;
stream >> internalStateVersion; // for future use
}
QString response;
stream >> response;
m_response = response.toStdString();
QString nameResponse;
stream >> nameResponse;
m_nameResponse = nameResponse.toStdString();
stream >> m_promptResponseTokens;
stream >> m_responseLogits;
stream >> m_ctx.n_past;
quint64 logitsSize;
stream >> logitsSize;
m_ctx.logits.resize(logitsSize);
stream.readRawData(reinterpret_cast<char*>(m_ctx.logits.data()), logitsSize * sizeof(float));
quint64 tokensSize;
stream >> tokensSize;
m_ctx.tokens.resize(tokensSize);
stream.readRawData(reinterpret_cast<char*>(m_ctx.tokens.data()), tokensSize * sizeof(int));
if (version > 0) {
QByteArray compressed;
stream >> compressed;
m_state = qUncompress(compressed);
} else {
stream >> m_state;
}
#if defined(DEBUG)
qDebug() << "chatllm deserialize" << m_chat->id();
#endif
return stream.status() == QDataStream::Ok;
}
void ChatLLM::saveState()
{
if (!isModelLoaded())
return;
const size_t stateSize = m_llmodel->stateSize();
m_state.resize(stateSize);
#if defined(DEBUG)
qDebug() << "chatllm saveState" << m_chat->id() << "size:" << m_state.size();
#endif
m_llmodel->saveState(static_cast<uint8_t*>(reinterpret_cast<void*>(m_state.data())));
}
void ChatLLM::restoreState()
{
if (!isModelLoaded() || m_state.isEmpty())
return;
#if defined(DEBUG)
qDebug() << "chatllm restoreState" << m_chat->id() << "size:" << m_state.size();
#endif
m_llmodel->restoreState(static_cast<const uint8_t*>(reinterpret_cast<void*>(m_state.data())));
m_state.clear();
m_state.resize(0);
}

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#ifndef CHATLLM_H
#define CHATLLM_H
#include <QObject>
#include <QThread>
#include "llmodel/llmodel.h"
class Chat;
class ChatLLM : public QObject
{
Q_OBJECT
Q_PROPERTY(bool isModelLoaded READ isModelLoaded NOTIFY isModelLoadedChanged)
Q_PROPERTY(QString response READ response NOTIFY responseChanged)
Q_PROPERTY(QString modelName READ modelName WRITE setModelName NOTIFY modelNameChanged)
Q_PROPERTY(bool isRecalc READ isRecalc NOTIFY recalcChanged)
Q_PROPERTY(QString generatedName READ generatedName NOTIFY generatedNameChanged)
public:
enum ModelType {
MPT_,
GPTJ_,
LLAMA_
};
ChatLLM(Chat *parent);
bool isModelLoaded() const;
void regenerateResponse();
void resetResponse();
void resetContext();
void stopGenerating() { m_stopGenerating = true; }
QString response() const;
QString modelName() const;
void setModelName(const QString &modelName);
bool isRecalc() const { return m_isRecalc; }
QString generatedName() const { return QString::fromStdString(m_nameResponse); }
bool serialize(QDataStream &stream, int version);
bool deserialize(QDataStream &stream, int version);
public Q_SLOTS:
bool prompt(const QString &prompt, const QString &prompt_template, int32_t n_predict,
int32_t top_k, float top_p, float temp, int32_t n_batch, float repeat_penalty, int32_t repeat_penalty_tokens,
int32_t n_threads);
bool loadDefaultModel();
bool loadModel(const QString &modelName);
void modelNameChangeRequested(const QString &modelName);
void unloadModel();
void reloadModel(const QString &modelName);
void generateName();
void handleChatIdChanged();
Q_SIGNALS:
void isModelLoadedChanged();
void modelLoadingError(const QString &error);
void responseChanged();
void responseStarted();
void responseStopped();
void modelNameChanged();
void recalcChanged();
void sendStartup();
void sendModelLoaded();
void sendResetContext();
void generatedNameChanged();
void stateChanged();
private:
void resetContextPrivate();
bool handlePrompt(int32_t token);
bool handleResponse(int32_t token, const std::string &response);
bool handleRecalculate(bool isRecalc);
bool handleNamePrompt(int32_t token);
bool handleNameResponse(int32_t token, const std::string &response);
bool handleNameRecalculate(bool isRecalc);
void saveState();
void restoreState();
private:
LLModel::PromptContext m_ctx;
LLModel *m_llmodel;
std::string m_response;
std::string m_nameResponse;
quint32 m_promptResponseTokens;
quint32 m_responseLogits;
QString m_modelName;
ModelType m_modelType;
Chat *m_chat;
QByteArray m_state;
QThread m_llmThread;
std::atomic<bool> m_stopGenerating;
bool m_isRecalc;
};
#endif // CHATLLM_H

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#ifndef CHATMODEL_H
#define CHATMODEL_H
#include <QAbstractListModel>
#include <QtQml>
#include <QDataStream>
struct ChatItem
{
Q_GADGET
Q_PROPERTY(int id MEMBER id)
Q_PROPERTY(QString name MEMBER name)
Q_PROPERTY(QString value MEMBER value)
Q_PROPERTY(QString prompt MEMBER prompt)
Q_PROPERTY(QString newResponse MEMBER newResponse)
Q_PROPERTY(bool currentResponse MEMBER currentResponse)
Q_PROPERTY(bool stopped MEMBER stopped)
Q_PROPERTY(bool thumbsUpState MEMBER thumbsUpState)
Q_PROPERTY(bool thumbsDownState MEMBER thumbsDownState)
public:
int id = 0;
QString name;
QString value;
QString prompt;
QString newResponse;
bool currentResponse = false;
bool stopped = false;
bool thumbsUpState = false;
bool thumbsDownState = false;
};
Q_DECLARE_METATYPE(ChatItem)
class ChatModel : public QAbstractListModel
{
Q_OBJECT
Q_PROPERTY(int count READ count NOTIFY countChanged)
public:
explicit ChatModel(QObject *parent = nullptr) : QAbstractListModel(parent) {}
enum Roles {
IdRole = Qt::UserRole + 1,
NameRole,
ValueRole,
PromptRole,
NewResponseRole,
CurrentResponseRole,
StoppedRole,
ThumbsUpStateRole,
ThumbsDownStateRole
};
int rowCount(const QModelIndex &parent = QModelIndex()) const override
{
Q_UNUSED(parent)
return m_chatItems.size();
}
QVariant data(const QModelIndex &index, int role = Qt::DisplayRole) const override
{
if (!index.isValid() || index.row() < 0 || index.row() >= m_chatItems.size())
return QVariant();
const ChatItem &item = m_chatItems.at(index.row());
switch (role) {
case IdRole:
return item.id;
case NameRole:
return item.name;
case ValueRole:
return item.value;
case PromptRole:
return item.prompt;
case NewResponseRole:
return item.newResponse;
case CurrentResponseRole:
return item.currentResponse;
case StoppedRole:
return item.stopped;
case ThumbsUpStateRole:
return item.thumbsUpState;
case ThumbsDownStateRole:
return item.thumbsDownState;
}
return QVariant();
}
QHash<int, QByteArray> roleNames() const override
{
QHash<int, QByteArray> roles;
roles[IdRole] = "id";
roles[NameRole] = "name";
roles[ValueRole] = "value";
roles[PromptRole] = "prompt";
roles[NewResponseRole] = "newResponse";
roles[CurrentResponseRole] = "currentResponse";
roles[StoppedRole] = "stopped";
roles[ThumbsUpStateRole] = "thumbsUpState";
roles[ThumbsDownStateRole] = "thumbsDownState";
return roles;
}
void appendPrompt(const QString &name, const QString &value)
{
ChatItem item;
item.name = name;
item.value = value;
beginInsertRows(QModelIndex(), m_chatItems.size(), m_chatItems.size());
m_chatItems.append(item);
endInsertRows();
emit countChanged();
}
void appendResponse(const QString &name, const QString &prompt)
{
ChatItem item;
item.id = m_chatItems.count(); // This is only relevant for responses
item.name = name;
item.prompt = prompt;
item.currentResponse = true;
beginInsertRows(QModelIndex(), m_chatItems.size(), m_chatItems.size());
m_chatItems.append(item);
endInsertRows();
emit countChanged();
}
Q_INVOKABLE void clear()
{
if (m_chatItems.isEmpty()) return;
beginResetModel();
m_chatItems.clear();
endResetModel();
emit countChanged();
}
Q_INVOKABLE ChatItem get(int index)
{
if (index < 0 || index >= m_chatItems.size()) return ChatItem();
return m_chatItems.at(index);
}
Q_INVOKABLE void updateCurrentResponse(int index, bool b)
{
if (index < 0 || index >= m_chatItems.size()) return;
ChatItem &item = m_chatItems[index];
if (item.currentResponse != b) {
item.currentResponse = b;
emit dataChanged(createIndex(index, 0), createIndex(index, 0), {CurrentResponseRole});
}
}
Q_INVOKABLE void updateStopped(int index, bool b)
{
if (index < 0 || index >= m_chatItems.size()) return;
ChatItem &item = m_chatItems[index];
if (item.stopped != b) {
item.stopped = b;
emit dataChanged(createIndex(index, 0), createIndex(index, 0), {StoppedRole});
}
}
Q_INVOKABLE void updateValue(int index, const QString &value)
{
if (index < 0 || index >= m_chatItems.size()) return;
ChatItem &item = m_chatItems[index];
if (item.value != value) {
item.value = value;
emit dataChanged(createIndex(index, 0), createIndex(index, 0), {ValueRole});
}
}
Q_INVOKABLE void updateThumbsUpState(int index, bool b)
{
if (index < 0 || index >= m_chatItems.size()) return;
ChatItem &item = m_chatItems[index];
if (item.thumbsUpState != b) {
item.thumbsUpState = b;
emit dataChanged(createIndex(index, 0), createIndex(index, 0), {ThumbsUpStateRole});
}
}
Q_INVOKABLE void updateThumbsDownState(int index, bool b)
{
if (index < 0 || index >= m_chatItems.size()) return;
ChatItem &item = m_chatItems[index];
if (item.thumbsDownState != b) {
item.thumbsDownState = b;
emit dataChanged(createIndex(index, 0), createIndex(index, 0), {ThumbsDownStateRole});
}
}
Q_INVOKABLE void updateNewResponse(int index, const QString &newResponse)
{
if (index < 0 || index >= m_chatItems.size()) return;
ChatItem &item = m_chatItems[index];
if (item.newResponse != newResponse) {
item.newResponse = newResponse;
emit dataChanged(createIndex(index, 0), createIndex(index, 0), {NewResponseRole});
}
}
int count() const { return m_chatItems.size(); }
bool serialize(QDataStream &stream, int version) const
{
stream << count();
for (auto c : m_chatItems) {
stream << c.id;
stream << c.name;
stream << c.value;
stream << c.prompt;
stream << c.newResponse;
stream << c.currentResponse;
stream << c.stopped;
stream << c.thumbsUpState;
stream << c.thumbsDownState;
}
return stream.status() == QDataStream::Ok;
}
bool deserialize(QDataStream &stream, int version)
{
int size;
stream >> size;
for (int i = 0; i < size; ++i) {
ChatItem c;
stream >> c.id;
stream >> c.name;
stream >> c.value;
stream >> c.prompt;
stream >> c.newResponse;
stream >> c.currentResponse;
stream >> c.stopped;
stream >> c.thumbsUpState;
stream >> c.thumbsDownState;
beginInsertRows(QModelIndex(), m_chatItems.size(), m_chatItems.size());
m_chatItems.append(c);
endInsertRows();
}
emit countChanged();
return stream.status() == QDataStream::Ok;
}
Q_SIGNALS:
void countChanged();
private:
QList<ChatItem> m_chatItems;
};
#endif // CHATMODEL_H

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#ifndef CONFIG_H
#define CONFIG_H
#define APP_VERSION "@APP_VERSION@"
#define GPT4ALL_AVX_ONLY "@GPT4ALL_AVX_ONLY@"
#endif // CONFIG_H

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@ -0,0 +1,12 @@
set(LINUXDEPLOYQT "@LINUXDEPLOYQT@")
set(COMPONENT_NAME_MAIN "@COMPONENT_NAME_MAIN@")
set(CMAKE_CURRENT_SOURCE_DIR "@CMAKE_CURRENT_SOURCE_DIR@")
set(DATA_DIR ${CPACK_TEMPORARY_INSTALL_DIRECTORY}/packages/${COMPONENT_NAME_MAIN}/data)
set(BIN_DIR ${DATA_DIR}/bin)
set(Qt6_ROOT_DIR "@Qt6_ROOT_DIR@")
set(ENV{LD_LIBRARY_PATH} "${BIN_DIR}:${Qt6_ROOT_DIR}/../lib/")
execute_process(COMMAND ${LINUXDEPLOYQT} ${BIN_DIR}/chat -qmldir=${CMAKE_CURRENT_SOURCE_DIR} -bundle-non-qt-libs -qmake=${Qt6_ROOT_DIR}/bin/qmake -verbose=2)
file(COPY "${CMAKE_CURRENT_SOURCE_DIR}/icons/logo-32.png"
DESTINATION ${DATA_DIR})
file(COPY "${CMAKE_CURRENT_SOURCE_DIR}/icons/logo-48.png"
DESTINATION ${DATA_DIR})

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@ -0,0 +1,16 @@
set(MACDEPLOYQT "@MACDEPLOYQT@")
set(COMPONENT_NAME_MAIN "@COMPONENT_NAME_MAIN@")
set(CMAKE_CURRENT_SOURCE_DIR "@CMAKE_CURRENT_SOURCE_DIR@")
execute_process(COMMAND ${MACDEPLOYQT} ${CPACK_TEMPORARY_INSTALL_DIRECTORY}/packages/${COMPONENT_NAME_MAIN}/data/bin/gpt4all.app -qmldir=${CMAKE_CURRENT_SOURCE_DIR} -verbose=2)
file(COPY ${CPACK_TEMPORARY_INSTALL_DIRECTORY}/packages/${COMPONENT_NAME_MAIN}/data/lib/libllama.dylib
DESTINATION ${CPACK_TEMPORARY_INSTALL_DIRECTORY}/packages/${COMPONENT_NAME_MAIN}/data/bin/gpt4all.app/Contents/Frameworks)
file(COPY ${CPACK_TEMPORARY_INSTALL_DIRECTORY}/packages/${COMPONENT_NAME_MAIN}/data/lib/libllmodel.dylib
DESTINATION ${CPACK_TEMPORARY_INSTALL_DIRECTORY}/packages/${COMPONENT_NAME_MAIN}/data/bin/gpt4all.app/Contents/Frameworks)
file(COPY "${CMAKE_CURRENT_SOURCE_DIR}/icons/favicon.icns"
DESTINATION ${CPACK_TEMPORARY_INSTALL_DIRECTORY}/packages/${COMPONENT_NAME_MAIN}/data/bin/gpt4all.app/Contents/Resources)
file(COPY "${CMAKE_CURRENT_SOURCE_DIR}/icons/logo-32.png"
DESTINATION ${CPACK_TEMPORARY_INSTALL_DIRECTORY}/packages/${COMPONENT_NAME_MAIN}/data)
file(COPY "${CMAKE_CURRENT_SOURCE_DIR}/icons/logo-48.png"
DESTINATION ${CPACK_TEMPORARY_INSTALL_DIRECTORY}/packages/${COMPONENT_NAME_MAIN}/data)
file(COPY "${CMAKE_CURRENT_SOURCE_DIR}/icons/favicon.icns"
DESTINATION ${CPACK_TEMPORARY_INSTALL_DIRECTORY}/packages/${COMPONENT_NAME_MAIN}/data)

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@ -0,0 +1,14 @@
set(WINDEPLOYQT "@WINDEPLOYQT@")
set(COMPONENT_NAME_MAIN "@COMPONENT_NAME_MAIN@")
set(CMAKE_CURRENT_SOURCE_DIR "@CMAKE_CURRENT_SOURCE_DIR@")
execute_process(COMMAND ${WINDEPLOYQT} --qmldir ${CMAKE_CURRENT_SOURCE_DIR} ${CPACK_TEMPORARY_INSTALL_DIRECTORY}/packages/${COMPONENT_NAME_MAIN}/data/bin)
file(COPY ${CPACK_TEMPORARY_INSTALL_DIRECTORY}/packages/${COMPONENT_NAME_MAIN}/data/lib/libllama.dll
DESTINATION ${CPACK_TEMPORARY_INSTALL_DIRECTORY}/packages/${COMPONENT_NAME_MAIN}/data/bin)
file(COPY ${CPACK_TEMPORARY_INSTALL_DIRECTORY}/packages/${COMPONENT_NAME_MAIN}/data/lib/libllmodel.dll
DESTINATION ${CPACK_TEMPORARY_INSTALL_DIRECTORY}/packages/${COMPONENT_NAME_MAIN}/data/bin)
file(COPY "${CMAKE_CURRENT_SOURCE_DIR}/icons/logo-32.png"
DESTINATION ${CPACK_TEMPORARY_INSTALL_DIRECTORY}/packages/${COMPONENT_NAME_MAIN}/data)
file(COPY "${CMAKE_CURRENT_SOURCE_DIR}/icons/logo-48.png"
DESTINATION ${CPACK_TEMPORARY_INSTALL_DIRECTORY}/packages/${COMPONENT_NAME_MAIN}/data)
file(COPY "${CMAKE_CURRENT_SOURCE_DIR}/icons/favicon.ico"
DESTINATION ${CPACK_TEMPORARY_INSTALL_DIRECTORY}/packages/${COMPONENT_NAME_MAIN}/data)

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function Component() {
}
var targetDirectory;
Component.prototype.beginInstallation = function() {
targetDirectory = installer.value("TargetDir");
};
Component.prototype.createOperations = function()
{
try {
// call the base create operations function
component.createOperations();
if (systemInfo.productType === "windows") {
try {
var userProfile = installer.environmentVariable("USERPROFILE");
installer.setValue("UserProfile", userProfile);
component.addOperation("CreateShortcut",
targetDirectory + "/bin/chat.exe",
"@UserProfile@/Desktop/GPT4All.lnk",
"workingDirectory=" + targetDirectory + "/bin",
"iconPath=" + targetDirectory + "/favicon.ico",
"iconId=0", "description=Open GPT4All");
} catch (e) {
print("ERROR: creating desktop shortcut" + e);
}
component.addOperation("CreateShortcut",
targetDirectory + "/bin/chat.exe",
"@StartMenuDir@/GPT4All.lnk",
"workingDirectory=" + targetDirectory + "/bin",
"iconPath=" + targetDirectory + "/favicon.ico",
"iconId=0", "description=Open GPT4All");
} else if (systemInfo.productType === "osx") {
var gpt4allAppPath = targetDirectory + "/bin/gpt4all.app";
var symlinkPath = targetDirectory + "/../GPT4All.app";
// Remove the symlink if it already exists
component.addOperation("Execute", "rm", "-f", symlinkPath);
// Create the symlink
component.addOperation("Execute", "ln", "-s", gpt4allAppPath, symlinkPath);
} else { // linux
var homeDir = installer.environmentVariable("HOME");
if (!installer.fileExists(homeDir + "/Desktop/GPT4All.desktop")) {
component.addOperation("CreateDesktopEntry",
homeDir + "/Desktop/GPT4All.desktop",
"Type=Application\nTerminal=false\nExec=\"" + targetDirectory +
"/bin/chat\"\nName=GPT4All\nIcon=" + targetDirectory +
"/logo-48.png\nName[en_US]=GPT4All");
}
}
} catch (e) {
print("ERROR: running post installscript.qs" + e);
}
}
Component.prototype.createOperationsForArchive = function(archive)
{
component.createOperationsForArchive(archive);
if (systemInfo.productType === "osx") {
var uninstallTargetDirectory = installer.value("TargetDir");
var symlinkPath = uninstallTargetDirectory + "/../GPT4All.app";
// Remove the symlink during uninstallation
if (installer.isUninstaller()) {
component.addOperation("Execute", "rm", "-f", symlinkPath, "UNDOEXECUTE");
}
}
}

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import os
import subprocess
import tempfile
import shutil
import click
from typing import Optional
# Requires click
# pip install click
# Example usage
# python sign_dmg.py --input-dmg /path/to/your/input.dmg --output-dmg /path/to/your/output.dmg --signing-identity "Developer ID Application: YOUR_NAME (TEAM_ID)"
# NOTE: This script assumes that you have the necessary Developer ID Application certificate in your
# Keychain Access and that the codesign and hdiutil command-line tools are available on your system.
@click.command()
@click.option('--input-dmg', required=True, help='Path to the input DMG file.')
@click.option('--output-dmg', required=True, help='Path to the output signed DMG file.')
@click.option('--sha1-hash', help='SHA-1 hash of the Developer ID Application certificate')
@click.option('--signing-identity', default=None, help='Common name of the Developer ID Application certificate')
def sign_dmg(input_dmg: str, output_dmg: str, signing_identity: Optional[str] = None, sha1_hash: Optional[str] = None) -> None:
if not signing_identity and not sha1_hash:
print("Error: Either --signing-identity or --sha1-hash must be provided.")
exit(1)
# Mount the input DMG
mount_point = tempfile.mkdtemp()
subprocess.run(['hdiutil', 'attach', input_dmg, '-mountpoint', mount_point])
# Copy the contents of the DMG to a temporary folder
temp_dir = tempfile.mkdtemp()
shutil.copytree(mount_point, os.path.join(temp_dir, 'contents'))
subprocess.run(['hdiutil', 'detach', mount_point])
# Find the .app bundle in the temporary folder
app_bundle = None
for item in os.listdir(os.path.join(temp_dir, 'contents')):
if item.endswith('.app'):
app_bundle = os.path.join(temp_dir, 'contents', item)
break
if not app_bundle:
print('No .app bundle found in the DMG.')
exit(1)
# Sign the .app bundle
try:
subprocess.run([
'codesign',
'--deep',
'--force',
'--verbose',
'--options', 'runtime',
'--timestamp',
'--sign', sha1_hash or signing_identity,
app_bundle
], check=True)
except subprocess.CalledProcessError as e:
print(f"Error during codesign: {e}")
# Clean up temporary directories
shutil.rmtree(temp_dir)
shutil.rmtree(mount_point)
exit(1)
# Create a new DMG containing the signed .app bundle
subprocess.run([
'hdiutil', 'create',
'-volname', os.path.splitext(os.path.basename(input_dmg))[0],
'-srcfolder', os.path.join(temp_dir, 'contents'),
'-ov',
'-format', 'UDZO',
output_dmg
])
# Clean up temporary directories
shutil.rmtree(temp_dir)
shutil.rmtree(mount_point)
if __name__ == '__main__':
sign_dmg()

600
gpt4all-chat/download.cpp Normal file
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#include "download.h"
#include "network.h"
#include <QCoreApplication>
#include <QNetworkRequest>
#include <QNetworkAccessManager>
#include <QJsonDocument>
#include <QJsonObject>
#include <QJsonArray>
#include <QUrl>
#include <QDir>
#include <QStandardPaths>
#include <QSettings>
class MyDownload: public Download { };
Q_GLOBAL_STATIC(MyDownload, downloadInstance)
Download *Download::globalInstance()
{
return downloadInstance();
}
Download::Download()
: QObject(nullptr)
, m_hashAndSave(new HashAndSaveFile)
{
connect(this, &Download::requestHashAndSave, m_hashAndSave,
&HashAndSaveFile::hashAndSave, Qt::QueuedConnection);
connect(m_hashAndSave, &HashAndSaveFile::hashAndSaveFinished, this,
&Download::handleHashAndSaveFinished, Qt::QueuedConnection);
connect(&m_networkManager, &QNetworkAccessManager::sslErrors, this,
&Download::handleSslErrors);
connect(this, &Download::downloadLocalModelsPathChanged, this, &Download::updateModelList);
updateModelList();
updateReleaseNotes();
QSettings settings;
settings.sync();
m_downloadLocalModelsPath = settings.value("modelPath",
defaultLocalModelsPath()).toString();
m_startTime = QDateTime::currentDateTime();
}
bool operator==(const ModelInfo& lhs, const ModelInfo& rhs) {
return lhs.filename == rhs.filename && lhs.md5sum == rhs.md5sum;
}
bool operator==(const ReleaseInfo& lhs, const ReleaseInfo& rhs) {
return lhs.version == rhs.version;
}
bool compareVersions(const QString &a, const QString &b) {
QStringList aParts = a.split('.');
QStringList bParts = b.split('.');
for (int i = 0; i < std::min(aParts.size(), bParts.size()); ++i) {
int aInt = aParts[i].toInt();
int bInt = bParts[i].toInt();
if (aInt > bInt) {
return true;
} else if (aInt < bInt) {
return false;
}
}
return aParts.size() > bParts.size();
}
QList<ModelInfo> Download::modelList() const
{
// We make sure the default model is listed first
QList<ModelInfo> values = m_modelMap.values();
ModelInfo defaultInfo;
ModelInfo bestGPTJInfo;
ModelInfo bestLlamaInfo;
ModelInfo bestMPTInfo;
QList<ModelInfo> filtered;
for (ModelInfo v : values) {
if (v.isDefault)
defaultInfo = v;
if (v.bestGPTJ)
bestGPTJInfo = v;
if (v.bestLlama)
bestLlamaInfo = v;
if (v.bestMPT)
bestMPTInfo = v;
filtered.append(v);
}
Q_ASSERT(defaultInfo == bestGPTJInfo || defaultInfo == bestLlamaInfo || defaultInfo == bestMPTInfo);
if (bestLlamaInfo.bestLlama) {
filtered.removeAll(bestLlamaInfo);
filtered.prepend(bestLlamaInfo);
}
if (bestGPTJInfo.bestGPTJ) {
filtered.removeAll(bestGPTJInfo);
filtered.prepend(bestGPTJInfo);
}
if (bestMPTInfo.bestMPT) {
filtered.removeAll(bestMPTInfo);
filtered.prepend(bestMPTInfo);
}
return filtered;
}
ReleaseInfo Download::releaseInfo() const
{
const QString currentVersion = QCoreApplication::applicationVersion();
if (m_releaseMap.contains(currentVersion))
return m_releaseMap.value(currentVersion);
return ReleaseInfo();
}
bool Download::hasNewerRelease() const
{
const QString currentVersion = QCoreApplication::applicationVersion();
QList<QString> versions = m_releaseMap.keys();
std::sort(versions.begin(), versions.end(), compareVersions);
if (versions.isEmpty())
return false;
return compareVersions(versions.first(), currentVersion);
}
QString Download::downloadLocalModelsPath() const {
return m_downloadLocalModelsPath;
}
void Download::setDownloadLocalModelsPath(const QString &modelPath) {
QString filePath = (modelPath.startsWith("file://") ?
QUrl(modelPath).toLocalFile() : modelPath);
QString canonical = QFileInfo(filePath).canonicalFilePath() + "/";
if (m_downloadLocalModelsPath != canonical) {
m_downloadLocalModelsPath = canonical;
emit downloadLocalModelsPathChanged();
}
}
bool Download::isFirstStart() const
{
QSettings settings;
settings.sync();
QString lastVersionStarted = settings.value("download/lastVersionStarted").toString();
bool first = lastVersionStarted != QCoreApplication::applicationVersion();
settings.setValue("download/lastVersionStarted", QCoreApplication::applicationVersion());
settings.sync();
return first;
}
QString Download::incompleteDownloadPath(const QString &modelFile) {
QString downloadPath = downloadLocalModelsPath() + "incomplete-" +
modelFile;
return downloadPath;
}
QString Download::defaultLocalModelsPath() const
{
QString localPath = QStandardPaths::writableLocation(QStandardPaths::AppLocalDataLocation)
+ "/";
QString testWritePath = localPath + QString("test_write.txt");
QString canonicalLocalPath = QFileInfo(localPath).canonicalFilePath() + "/";
QDir localDir(localPath);
if (!localDir.exists()) {
if (!localDir.mkpath(localPath)) {
qWarning() << "ERROR: Local download directory can't be created:" << canonicalLocalPath;
return canonicalLocalPath;
}
}
if (QFileInfo::exists(testWritePath))
return canonicalLocalPath;
QFile testWriteFile(testWritePath);
if (testWriteFile.open(QIODeviceBase::ReadWrite)) {
testWriteFile.close();
return canonicalLocalPath;
}
qWarning() << "ERROR: Local download path appears not writeable:" << canonicalLocalPath;
return canonicalLocalPath;
}
void Download::updateModelList()
{
QUrl jsonUrl("http://gpt4all.io/models/models.json");
QNetworkRequest request(jsonUrl);
QSslConfiguration conf = request.sslConfiguration();
conf.setPeerVerifyMode(QSslSocket::VerifyNone);
request.setSslConfiguration(conf);
QNetworkReply *jsonReply = m_networkManager.get(request);
connect(jsonReply, &QNetworkReply::finished, this, &Download::handleModelsJsonDownloadFinished);
}
void Download::updateReleaseNotes()
{
QUrl jsonUrl("http://gpt4all.io/meta/release.json");
QNetworkRequest request(jsonUrl);
QSslConfiguration conf = request.sslConfiguration();
conf.setPeerVerifyMode(QSslSocket::VerifyNone);
request.setSslConfiguration(conf);
QNetworkReply *jsonReply = m_networkManager.get(request);
connect(jsonReply, &QNetworkReply::finished, this, &Download::handleReleaseJsonDownloadFinished);
}
void Download::downloadModel(const QString &modelFile)
{
QFile *tempFile = new QFile(incompleteDownloadPath(modelFile));
QDateTime modTime = tempFile->fileTime(QFile::FileModificationTime);
bool success = tempFile->open(QIODevice::WriteOnly | QIODevice::Append);
qWarning() << "Opening temp file for writing:" << tempFile->fileName();
if (!success) {
qWarning() << "ERROR: Could not open temp file:"
<< tempFile->fileName() << modelFile;
return;
}
size_t incomplete_size = tempFile->size();
if (incomplete_size > 0) {
if (modTime < m_startTime) {
qWarning() << "File last modified before app started, rewinding by 1MB";
if (incomplete_size >= 1024 * 1024) {
incomplete_size -= 1024 * 1024;
} else {
incomplete_size = 0;
}
}
tempFile->seek(incomplete_size);
}
Network::globalInstance()->sendDownloadStarted(modelFile);
QNetworkRequest request("http://gpt4all.io/models/" + modelFile);
request.setRawHeader("range", QString("bytes=%1-").arg(incomplete_size).toUtf8());
QSslConfiguration conf = request.sslConfiguration();
conf.setPeerVerifyMode(QSslSocket::VerifyNone);
request.setSslConfiguration(conf);
QNetworkReply *modelReply = m_networkManager.get(request);
connect(modelReply, &QNetworkReply::downloadProgress, this, &Download::handleDownloadProgress);
connect(modelReply, &QNetworkReply::finished, this, &Download::handleModelDownloadFinished);
connect(modelReply, &QNetworkReply::readyRead, this, &Download::handleReadyRead);
m_activeDownloads.insert(modelReply, tempFile);
}
void Download::cancelDownload(const QString &modelFile)
{
for (int i = 0; i < m_activeDownloads.size(); ++i) {
QNetworkReply *modelReply = m_activeDownloads.keys().at(i);
QUrl url = modelReply->request().url();
if (url.toString().endsWith(modelFile)) {
Network::globalInstance()->sendDownloadCanceled(modelFile);
// Disconnect the signals
disconnect(modelReply, &QNetworkReply::downloadProgress, this, &Download::handleDownloadProgress);
disconnect(modelReply, &QNetworkReply::finished, this, &Download::handleModelDownloadFinished);
modelReply->abort(); // Abort the download
modelReply->deleteLater(); // Schedule the reply for deletion
QFile *tempFile = m_activeDownloads.value(modelReply);
tempFile->deleteLater();
m_activeDownloads.remove(modelReply);
// Emit downloadFinished signal for cleanup
emit downloadFinished(modelFile);
break;
}
}
}
void Download::handleSslErrors(QNetworkReply *reply, const QList<QSslError> &errors)
{
QUrl url = reply->request().url();
for (auto e : errors)
qWarning() << "ERROR: Received ssl error:" << e.errorString() << "for" << url;
}
void Download::handleModelsJsonDownloadFinished()
{
#if 0
QByteArray jsonData = QString(""
"["
" {"
" \"md5sum\": \"61d48a82cb188cceb14ebb8082bfec37\","
" \"filename\": \"ggml-gpt4all-j-v1.1-breezy.bin\","
" \"filesize\": \"3785248281\""
" },"
" {"
" \"md5sum\": \"879344aaa9d62fdccbda0be7a09e7976\","
" \"filename\": \"ggml-gpt4all-j-v1.2-jazzy.bin\","
" \"filesize\": \"3785248281\","
" \"isDefault\": \"true\""
" },"
" {"
" \"md5sum\": \"5b5a3f9b858d33b29b52b89692415595\","
" \"filesize\": \"3785248281\","
" \"filename\": \"ggml-gpt4all-j.bin\""
" }"
"]"
).toUtf8();
printf("%s\n", jsonData.toStdString().c_str());
fflush(stdout);
#else
QNetworkReply *jsonReply = qobject_cast<QNetworkReply *>(sender());
if (!jsonReply)
return;
QByteArray jsonData = jsonReply->readAll();
jsonReply->deleteLater();
#endif
parseModelsJsonFile(jsonData);
}
void Download::parseModelsJsonFile(const QByteArray &jsonData)
{
QJsonParseError err;
QJsonDocument document = QJsonDocument::fromJson(jsonData, &err);
if (err.error != QJsonParseError::NoError) {
qDebug() << "ERROR: Couldn't parse: " << jsonData << err.errorString();
return;
}
QString defaultModel;
QJsonArray jsonArray = document.array();
const QString currentVersion = QCoreApplication::applicationVersion();
m_modelMap.clear();
for (const QJsonValue &value : jsonArray) {
QJsonObject obj = value.toObject();
QString modelFilename = obj["filename"].toString();
QString modelFilesize = obj["filesize"].toString();
QString requires = obj["requires"].toString();
QByteArray modelMd5sum = obj["md5sum"].toString().toLatin1().constData();
bool isDefault = obj.contains("isDefault") && obj["isDefault"] == QString("true");
bool bestGPTJ = obj.contains("bestGPTJ") && obj["bestGPTJ"] == QString("true");
bool bestLlama = obj.contains("bestLlama") && obj["bestLlama"] == QString("true");
bool bestMPT = obj.contains("bestMPT") && obj["bestMPT"] == QString("true");
QString description = obj["description"].toString();
if (!requires.isEmpty()
&& requires != currentVersion
&& compareVersions(requires, currentVersion)) {
continue;
}
if (isDefault)
defaultModel = modelFilename;
quint64 sz = modelFilesize.toULongLong();
if (sz < 1024) {
modelFilesize = QString("%1 bytes").arg(sz);
} else if (sz < 1024 * 1024) {
modelFilesize = QString("%1 KB").arg(qreal(sz) / 1024, 0, 'g', 3);
} else if (sz < 1024 * 1024 * 1024) {
modelFilesize = QString("%1 MB").arg(qreal(sz) / (1024 * 1024), 0, 'g', 3);
} else {
modelFilesize = QString("%1 GB").arg(qreal(sz) / (1024 * 1024 * 1024), 0, 'g', 3);
}
QString filePath = downloadLocalModelsPath() + modelFilename;
QFileInfo info(filePath);
ModelInfo modelInfo;
modelInfo.filename = modelFilename;
modelInfo.filesize = modelFilesize;
modelInfo.md5sum = modelMd5sum;
modelInfo.installed = info.exists();
modelInfo.isDefault = isDefault;
modelInfo.bestGPTJ = bestGPTJ;
modelInfo.bestLlama = bestLlama;
modelInfo.bestMPT = bestMPT;
modelInfo.description = description;
modelInfo.requires = requires;
m_modelMap.insert(modelInfo.filename, modelInfo);
}
// remove ggml- prefix and .bin suffix
Q_ASSERT(defaultModel.startsWith("ggml-"));
defaultModel = defaultModel.remove(0, 5);
Q_ASSERT(defaultModel.endsWith(".bin"));
defaultModel.chop(4);
QSettings settings;
settings.sync();
settings.setValue("defaultModel", defaultModel);
settings.sync();
emit modelListChanged();
}
void Download::handleReleaseJsonDownloadFinished()
{
QNetworkReply *jsonReply = qobject_cast<QNetworkReply *>(sender());
if (!jsonReply)
return;
QByteArray jsonData = jsonReply->readAll();
jsonReply->deleteLater();
parseReleaseJsonFile(jsonData);
}
void Download::parseReleaseJsonFile(const QByteArray &jsonData)
{
QJsonParseError err;
QJsonDocument document = QJsonDocument::fromJson(jsonData, &err);
if (err.error != QJsonParseError::NoError) {
qDebug() << "ERROR: Couldn't parse: " << jsonData << err.errorString();
return;
}
QJsonArray jsonArray = document.array();
m_releaseMap.clear();
for (const QJsonValue &value : jsonArray) {
QJsonObject obj = value.toObject();
QString version = obj["version"].toString();
QString notes = obj["notes"].toString();
QString contributors = obj["contributors"].toString();
ReleaseInfo releaseInfo;
releaseInfo.version = version;
releaseInfo.notes = notes;
releaseInfo.contributors = contributors;
m_releaseMap.insert(version, releaseInfo);
}
emit hasNewerReleaseChanged();
emit releaseInfoChanged();
}
void Download::handleErrorOccurred(QNetworkReply::NetworkError code)
{
QNetworkReply *modelReply = qobject_cast<QNetworkReply *>(sender());
if (!modelReply)
return;
QString modelFilename = modelReply->url().fileName();
qWarning() << "ERROR: Network error occurred attempting to download"
<< modelFilename
<< "code:" << code
<< "errorString" << modelReply->errorString();
Network::globalInstance()->sendDownloadError(modelFilename, (int)code, modelReply->errorString());
cancelDownload(modelFilename);
}
void Download::handleDownloadProgress(qint64 bytesReceived, qint64 bytesTotal)
{
QNetworkReply *modelReply = qobject_cast<QNetworkReply *>(sender());
if (!modelReply)
return;
QFile *tempFile = m_activeDownloads.value(modelReply);
if (!tempFile)
return;
QString contentRange = modelReply->rawHeader("content-range");
if (contentRange.contains("/")) {
QString contentTotalSize = contentRange.split("/").last();
bytesTotal = contentTotalSize.toLongLong();
}
QString modelFilename = modelReply->url().fileName();
emit downloadProgress(tempFile->pos(), bytesTotal, modelFilename);
}
HashAndSaveFile::HashAndSaveFile()
: QObject(nullptr)
{
moveToThread(&m_hashAndSaveThread);
m_hashAndSaveThread.setObjectName("hashandsave thread");
m_hashAndSaveThread.start();
}
void HashAndSaveFile::hashAndSave(const QString &expectedHash, const QString &saveFilePath,
QFile *tempFile, QNetworkReply *modelReply)
{
Q_ASSERT(!tempFile->isOpen());
QString modelFilename = modelReply->url().fileName();
// Reopen the tempFile for hashing
if (!tempFile->open(QIODevice::ReadOnly)) {
qWarning() << "ERROR: Could not open temp file for hashing:"
<< tempFile->fileName() << modelFilename;
emit hashAndSaveFinished(false, tempFile, modelReply);
return;
}
QCryptographicHash hash(QCryptographicHash::Md5);
while(!tempFile->atEnd())
hash.addData(tempFile->read(16384));
if (hash.result().toHex() != expectedHash) {
tempFile->close();
qWarning() << "ERROR: Download error MD5SUM did not match:"
<< hash.result().toHex()
<< "!=" << expectedHash << "for" << modelFilename;
tempFile->remove();
emit hashAndSaveFinished(false, tempFile, modelReply);
return;
}
// The file save needs the tempFile closed
tempFile->close();
// Attempt to *move* the verified tempfile into place - this should be atomic
// but will only work if the destination is on the same filesystem
if (tempFile->rename(saveFilePath)) {
emit hashAndSaveFinished(true, tempFile, modelReply);
return;
}
// Reopen the tempFile for copying
if (!tempFile->open(QIODevice::ReadOnly)) {
qWarning() << "ERROR: Could not open temp file at finish:"
<< tempFile->fileName() << modelFilename;
emit hashAndSaveFinished(false, tempFile, modelReply);
return;
}
// Save the model file to disk
QFile file(saveFilePath);
if (file.open(QIODevice::WriteOnly)) {
QByteArray buffer;
while (!tempFile->atEnd()) {
buffer = tempFile->read(16384);
file.write(buffer);
}
file.close();
tempFile->close();
emit hashAndSaveFinished(true, tempFile, modelReply);
} else {
QFile::FileError error = file.error();
qWarning() << "ERROR: Could not save model to location:"
<< saveFilePath
<< "failed with code" << error;
tempFile->close();
emit hashAndSaveFinished(false, tempFile, modelReply);
return;
}
}
void Download::handleModelDownloadFinished()
{
QNetworkReply *modelReply = qobject_cast<QNetworkReply *>(sender());
if (!modelReply)
return;
QString modelFilename = modelReply->url().fileName();
QFile *tempFile = m_activeDownloads.value(modelReply);
m_activeDownloads.remove(modelReply);
if (modelReply->error()) {
qWarning() << "ERROR: downloading:" << modelReply->errorString();
modelReply->deleteLater();
tempFile->deleteLater();
emit downloadFinished(modelFilename);
return;
}
// The hash and save needs the tempFile closed
tempFile->close();
// Notify that we are calculating hash
ModelInfo info = m_modelMap.value(modelFilename);
info.calcHash = true;
m_modelMap.insert(modelFilename, info);
emit modelListChanged();
const QString saveFilePath = downloadLocalModelsPath() + modelFilename;
emit requestHashAndSave(info.md5sum, saveFilePath, tempFile, modelReply);
}
void Download::handleHashAndSaveFinished(bool success,
QFile *tempFile, QNetworkReply *modelReply)
{
// The hash and save should send back with tempfile closed
Q_ASSERT(!tempFile->isOpen());
QString modelFilename = modelReply->url().fileName();
Network::globalInstance()->sendDownloadFinished(modelFilename, success);
ModelInfo info = m_modelMap.value(modelFilename);
info.calcHash = false;
info.installed = success;
m_modelMap.insert(modelFilename, info);
emit modelListChanged();
modelReply->deleteLater();
tempFile->deleteLater();
emit downloadFinished(modelFilename);
}
void Download::handleReadyRead()
{
QNetworkReply *modelReply = qobject_cast<QNetworkReply *>(sender());
if (!modelReply)
return;
QString modelFilename = modelReply->url().fileName();
QFile *tempFile = m_activeDownloads.value(modelReply);
QByteArray buffer;
while (!modelReply->atEnd()) {
buffer = modelReply->read(16384);
tempFile->write(buffer);
}
tempFile->flush();
}

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#ifndef DOWNLOAD_H
#define DOWNLOAD_H
#include <QObject>
#include <QNetworkAccessManager>
#include <QNetworkReply>
#include <QFile>
#include <QVariant>
#include <QTemporaryFile>
#include <QThread>
struct ModelInfo {
Q_GADGET
Q_PROPERTY(QString filename MEMBER filename)
Q_PROPERTY(QString filesize MEMBER filesize)
Q_PROPERTY(QByteArray md5sum MEMBER md5sum)
Q_PROPERTY(bool calcHash MEMBER calcHash)
Q_PROPERTY(bool installed MEMBER installed)
Q_PROPERTY(bool isDefault MEMBER isDefault)
Q_PROPERTY(bool bestGPTJ MEMBER bestGPTJ)
Q_PROPERTY(bool bestLlama MEMBER bestLlama)
Q_PROPERTY(bool bestMPT MEMBER bestMPT)
Q_PROPERTY(QString description MEMBER description)
Q_PROPERTY(QString requires MEMBER requires)
public:
QString filename;
QString filesize;
QByteArray md5sum;
bool calcHash = false;
bool installed = false;
bool isDefault = false;
bool bestGPTJ = false;
bool bestLlama = false;
bool bestMPT = false;
QString description;
QString requires;
};
Q_DECLARE_METATYPE(ModelInfo)
struct ReleaseInfo {
Q_GADGET
Q_PROPERTY(QString version MEMBER version)
Q_PROPERTY(QString notes MEMBER notes)
Q_PROPERTY(QString contributors MEMBER contributors)
public:
QString version;
QString notes;
QString contributors;
};
class HashAndSaveFile : public QObject
{
Q_OBJECT
public:
HashAndSaveFile();
public Q_SLOTS:
void hashAndSave(const QString &hash, const QString &saveFilePath,
QFile *tempFile, QNetworkReply *modelReply);
Q_SIGNALS:
void hashAndSaveFinished(bool success,
QFile *tempFile, QNetworkReply *modelReply);
private:
QThread m_hashAndSaveThread;
};
class Download : public QObject
{
Q_OBJECT
Q_PROPERTY(QList<ModelInfo> modelList READ modelList NOTIFY modelListChanged)
Q_PROPERTY(bool hasNewerRelease READ hasNewerRelease NOTIFY hasNewerReleaseChanged)
Q_PROPERTY(ReleaseInfo releaseInfo READ releaseInfo NOTIFY releaseInfoChanged)
Q_PROPERTY(QString downloadLocalModelsPath READ downloadLocalModelsPath
WRITE setDownloadLocalModelsPath
NOTIFY downloadLocalModelsPathChanged)
public:
static Download *globalInstance();
QList<ModelInfo> modelList() const;
ReleaseInfo releaseInfo() const;
bool hasNewerRelease() const;
Q_INVOKABLE void updateModelList();
Q_INVOKABLE void updateReleaseNotes();
Q_INVOKABLE void downloadModel(const QString &modelFile);
Q_INVOKABLE void cancelDownload(const QString &modelFile);
Q_INVOKABLE QString defaultLocalModelsPath() const;
Q_INVOKABLE QString downloadLocalModelsPath() const;
Q_INVOKABLE void setDownloadLocalModelsPath(const QString &modelPath);
Q_INVOKABLE bool isFirstStart() const;
private Q_SLOTS:
void handleSslErrors(QNetworkReply *reply, const QList<QSslError> &errors);
void handleModelsJsonDownloadFinished();
void handleReleaseJsonDownloadFinished();
void handleErrorOccurred(QNetworkReply::NetworkError code);
void handleDownloadProgress(qint64 bytesReceived, qint64 bytesTotal);
void handleModelDownloadFinished();
void handleHashAndSaveFinished(bool success,
QFile *tempFile, QNetworkReply *modelReply);
void handleReadyRead();
Q_SIGNALS:
void downloadProgress(qint64 bytesReceived, qint64 bytesTotal, const QString &modelFile);
void downloadFinished(const QString &modelFile);
void modelListChanged();
void releaseInfoChanged();
void hasNewerReleaseChanged();
void downloadLocalModelsPathChanged();
void requestHashAndSave(const QString &hash, const QString &saveFilePath,
QFile *tempFile, QNetworkReply *modelReply);
private:
void parseModelsJsonFile(const QByteArray &jsonData);
void parseReleaseJsonFile(const QByteArray &jsonData);
QString incompleteDownloadPath(const QString &modelFile);
HashAndSaveFile *m_hashAndSave;
QMap<QString, ModelInfo> m_modelMap;
QMap<QString, ReleaseInfo> m_releaseMap;
QNetworkAccessManager m_networkManager;
QMap<QNetworkReply*, QFile*> m_activeDownloads;
QString m_downloadLocalModelsPath;
QDateTime m_startTime;
private:
explicit Download();
~Download() {}
friend class MyDownload;
};
#endif // DOWNLOAD_H

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79
gpt4all-chat/llm.cpp Normal file
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#include "llm.h"
#include "config.h"
#include "download.h"
#include "network.h"
#include <QCoreApplication>
#include <QDir>
#include <QFile>
#include <QProcess>
#include <QResource>
#include <QSettings>
#include <fstream>
class MyLLM: public LLM { };
Q_GLOBAL_STATIC(MyLLM, llmInstance)
LLM *LLM::globalInstance()
{
return llmInstance();
}
LLM::LLM()
: QObject{nullptr}
, m_chatListModel(new ChatListModel(this))
, m_threadCount(std::min(4, (int32_t) std::thread::hardware_concurrency()))
, m_compatHardware(true)
{
connect(QCoreApplication::instance(), &QCoreApplication::aboutToQuit,
this, &LLM::aboutToQuit);
#if defined(__x86_64__) || defined(__i386__)
if (QString(GPT4ALL_AVX_ONLY) == "OFF") {
const bool avx(__builtin_cpu_supports("avx"));
const bool avx2(__builtin_cpu_supports("avx2"));
const bool fma(__builtin_cpu_supports("fma"));
m_compatHardware = avx && avx2 && fma;
emit compatHardwareChanged();
}
#endif
}
bool LLM::checkForUpdates() const
{
Network::globalInstance()->sendCheckForUpdates();
#if defined(Q_OS_LINUX)
QString tool("maintenancetool");
#elif defined(Q_OS_WINDOWS)
QString tool("maintenancetool.exe");
#elif defined(Q_OS_DARWIN)
QString tool("../../../maintenancetool.app/Contents/MacOS/maintenancetool");
#endif
QString fileName = QCoreApplication::applicationDirPath()
+ "/../" + tool;
if (!QFileInfo::exists(fileName)) {
qDebug() << "Couldn't find tool at" << fileName << "so cannot check for updates!";
return false;
}
return QProcess::startDetached(fileName);
}
int32_t LLM::threadCount() const
{
return m_threadCount;
}
void LLM::setThreadCount(int32_t n_threads)
{
if (n_threads <= 0)
n_threads = std::min(4, (int32_t) std::thread::hardware_concurrency());
m_threadCount = n_threads;
emit threadCountChanged();
}
void LLM::aboutToQuit()
{
m_chatListModel->saveChats();
}

44
gpt4all-chat/llm.h Normal file
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#ifndef LLM_H
#define LLM_H
#include <QObject>
#include "chatlistmodel.h"
class LLM : public QObject
{
Q_OBJECT
Q_PROPERTY(ChatListModel *chatListModel READ chatListModel NOTIFY chatListModelChanged)
Q_PROPERTY(int32_t threadCount READ threadCount WRITE setThreadCount NOTIFY threadCountChanged)
Q_PROPERTY(bool compatHardware READ compatHardware NOTIFY compatHardwareChanged)
public:
static LLM *globalInstance();
ChatListModel *chatListModel() const { return m_chatListModel; }
int32_t threadCount() const;
void setThreadCount(int32_t n_threads);
bool compatHardware() const { return m_compatHardware; }
Q_INVOKABLE bool checkForUpdates() const;
Q_SIGNALS:
void chatListModelChanged();
void threadCountChanged();
void compatHardwareChanged();
private Q_SLOTS:
void aboutToQuit();
private:
ChatListModel *m_chatListModel;
int32_t m_threadCount;
bool m_compatHardware;
private:
explicit LLM();
~LLM() {}
friend class MyLLM;
};
#endif // LLM_H

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cmake_minimum_required(VERSION 3.16)
if(APPLE)
option(BUILD_UNIVERSAL "Build a Universal binary on macOS" ON)
if(BUILD_UNIVERSAL)
# Build a Universal binary on macOS
# This requires that the found Qt library is compiled as Universal binaries.
set(CMAKE_OSX_ARCHITECTURES "arm64;x86_64" CACHE STRING "" FORCE)
else()
# Build for the host architecture on macOS
set(CMAKE_OSX_ARCHITECTURES "${CMAKE_HOST_SYSTEM_PROCESSOR}" CACHE STRING "" FORCE)
endif()
endif()
# Include the binary directory for the generated header file
include_directories("${CMAKE_CURRENT_BINARY_DIR}")
project(llmodel VERSION ${APP_VERSION} LANGUAGES CXX C)
set(CMAKE_CXX_STANDARD_REQUIRED ON)
set(LLAMA_BUILD_EXAMPLES ON CACHE BOOL "llama: build examples" FORCE)
set(BUILD_SHARED_LIBS ON FORCE)
set(CMAKE_VERBOSE_MAKEFILE ON)
if (GPT4ALL_AVX_ONLY)
set(LLAMA_AVX2 OFF CACHE BOOL "llama: enable AVX2" FORCE)
set(LLAMA_F16C OFF CACHE BOOL "llama: enable F16C" FORCE)
set(LLAMA_FMA OFF CACHE BOOL "llama: enable FMA" FORCE)
endif()
add_subdirectory(llama.cpp)
add_library(llmodel
gptj.h gptj.cpp
llamamodel.h llamamodel.cpp
llama.cpp/examples/common.cpp
llmodel.h llmodel_c.h llmodel_c.cpp
mpt.h mpt.cpp
utils.h utils.cpp
)
target_link_libraries(llmodel
PRIVATE llama)
set(COMPONENT_NAME_MAIN ${PROJECT_NAME})
set(CMAKE_INSTALL_PREFIX ${CMAKE_BINARY_DIR}/install)

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#ifndef GPTJ_H
#define GPTJ_H
#include <string>
#include <functional>
#include <vector>
#include "llmodel.h"
class GPTJPrivate;
class GPTJ : public LLModel {
public:
GPTJ();
~GPTJ();
bool loadModel(const std::string &modelPath) override;
bool isModelLoaded() const override;
size_t stateSize() const override;
size_t saveState(uint8_t *dest) const override;
size_t restoreState(const uint8_t *src) override;
void prompt(const std::string &prompt,
std::function<bool(int32_t)> promptCallback,
std::function<bool(int32_t, const std::string&)> responseCallback,
std::function<bool(bool)> recalculateCallback,
PromptContext &ctx) override;
void setThreadCount(int32_t n_threads) override;
int32_t threadCount() override;
protected:
void recalculateContext(PromptContext &promptCtx,
std::function<bool(bool)> recalculate) override;
private:
GPTJPrivate *d_ptr;
};
#endif // GPTJ_H

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#include "llamamodel.h"
#include "llama.cpp/examples/common.h"
#include "llama.cpp/llama.h"
#include "llama.cpp/ggml.h"
#include <cassert>
#include <cmath>
#include <cstdio>
#include <cstring>
#include <fstream>
#include <map>
#include <string>
#include <vector>
#include <iostream>
#include <unistd.h>
#include <random>
#include <thread>
#include <unordered_set>
struct LLamaPrivate {
const std::string modelPath;
bool modelLoaded;
llama_context *ctx = nullptr;
llama_context_params params;
int64_t n_threads = 0;
};
LLamaModel::LLamaModel()
: d_ptr(new LLamaPrivate) {
d_ptr->modelLoaded = false;
}
bool LLamaModel::loadModel(const std::string &modelPath)
{
// load the model
d_ptr->params = llama_context_default_params();
gpt_params params;
d_ptr->params.n_ctx = 2048;
d_ptr->params.n_parts = params.n_parts;
d_ptr->params.seed = params.seed;
d_ptr->params.f16_kv = params.memory_f16;
d_ptr->params.use_mmap = params.use_mmap;
d_ptr->params.use_mlock = params.use_mlock;
d_ptr->ctx = llama_init_from_file(modelPath.c_str(), d_ptr->params);
if (!d_ptr->ctx) {
std::cerr << "LLAMA ERROR: failed to load model from " << modelPath << std::endl;
return false;
}
d_ptr->n_threads = std::min(4, (int32_t) std::thread::hardware_concurrency());
d_ptr->modelLoaded = true;
fflush(stderr);
return true;
}
void LLamaModel::setThreadCount(int32_t n_threads) {
d_ptr->n_threads = n_threads;
}
int32_t LLamaModel::threadCount() {
return d_ptr->n_threads;
}
LLamaModel::~LLamaModel()
{
llama_free(d_ptr->ctx);
}
bool LLamaModel::isModelLoaded() const
{
return d_ptr->modelLoaded;
}
size_t LLamaModel::stateSize() const
{
return llama_get_state_size(d_ptr->ctx);
}
size_t LLamaModel::saveState(uint8_t *dest) const
{
return llama_copy_state_data(d_ptr->ctx, dest);
}
size_t LLamaModel::restoreState(const uint8_t *src)
{
return llama_set_state_data(d_ptr->ctx, src);
}
void LLamaModel::prompt(const std::string &prompt,
std::function<bool(int32_t)> promptCallback,
std::function<bool(int32_t, const std::string&)> responseCallback,
std::function<bool(bool)> recalculateCallback,
PromptContext &promptCtx) {
if (!isModelLoaded()) {
std::cerr << "LLAMA ERROR: prompt won't work with an unloaded model!\n";
return;
}
gpt_params params;
params.prompt = prompt;
// Add a space in front of the first character to match OG llama tokenizer behavior
params.prompt.insert(0, 1, ' ');
// tokenize the prompt
auto embd_inp = ::llama_tokenize(d_ptr->ctx, params.prompt, false);
// save the context size
promptCtx.n_ctx = llama_n_ctx(d_ptr->ctx);
if ((int) embd_inp.size() > promptCtx.n_ctx - 4) {
responseCallback(-1, "The prompt size exceeds the context window size and cannot be processed.");
std::cerr << "LLAMA ERROR: The prompt is" << embd_inp.size() <<
"tokens and the context window is" << promptCtx.n_ctx << "!\n";
return;
}
promptCtx.n_predict = std::min(promptCtx.n_predict, promptCtx.n_ctx - (int) embd_inp.size());
promptCtx.n_past = std::min(promptCtx.n_past, promptCtx.n_ctx);
// number of tokens to keep when resetting context
params.n_keep = (int)embd_inp.size();
// process the prompt in batches
size_t i = 0;
const int64_t t_start_prompt_us = ggml_time_us();
while (i < embd_inp.size()) {
size_t batch_end = std::min(i + promptCtx.n_batch, embd_inp.size());
std::vector<llama_token> batch(embd_inp.begin() + i, embd_inp.begin() + batch_end);
// Check if the context has run out...
if (promptCtx.n_past + batch.size() > promptCtx.n_ctx) {
const int32_t erasePoint = promptCtx.n_ctx * promptCtx.contextErase;
// Erase the first percentage of context from the tokens...
std::cerr << "LLAMA: reached the end of the context window so resizing\n";
promptCtx.tokens.erase(promptCtx.tokens.begin(), promptCtx.tokens.begin() + erasePoint);
promptCtx.n_past = promptCtx.tokens.size();
recalculateContext(promptCtx, recalculateCallback);
assert(promptCtx.n_past + batch.size() <= promptCtx.n_ctx);
}
if (llama_eval(d_ptr->ctx, batch.data(), batch.size(), promptCtx.n_past, d_ptr->n_threads)) {
std::cerr << "LLAMA ERROR: Failed to process prompt\n";
return;
}
size_t tokens = batch_end - i;
for (size_t t = 0; t < tokens; ++t) {
if (promptCtx.tokens.size() == promptCtx.n_ctx)
promptCtx.tokens.erase(promptCtx.tokens.begin());
promptCtx.tokens.push_back(batch.at(t));
if (!promptCallback(batch.at(t)))
return;
}
promptCtx.n_past += batch.size();
i = batch_end;
}
std::string cachedResponse;
std::vector<llama_token> cachedTokens;
std::unordered_set<std::string> reversePrompts
= { "### Instruction", "### Prompt", "### Response", "### Human", "### Assistant" };
// predict next tokens
int32_t totalPredictions = 0;
for (int i = 0; i < promptCtx.n_predict; i++) {
// sample next token
llama_token id = llama_sample_top_p_top_k(d_ptr->ctx,
promptCtx.tokens.data() + promptCtx.n_ctx - promptCtx.repeat_last_n,
promptCtx.repeat_last_n, promptCtx.top_k, promptCtx.top_p, promptCtx.temp,
promptCtx.repeat_penalty);
// Check if the context has run out...
if (promptCtx.n_past + 1 > promptCtx.n_ctx) {
const int32_t erasePoint = promptCtx.n_ctx * promptCtx.contextErase;
// Erase the first percentage of context from the tokens...
std::cerr << "LLAMA: reached the end of the context window so resizing\n";
promptCtx.tokens.erase(promptCtx.tokens.begin(), promptCtx.tokens.begin() + erasePoint);
promptCtx.n_past = promptCtx.tokens.size();
recalculateContext(promptCtx, recalculateCallback);
assert(promptCtx.n_past + 1 <= promptCtx.n_ctx);
}
if (llama_eval(d_ptr->ctx, &id, 1, promptCtx.n_past, d_ptr->n_threads)) {
std::cerr << "LLAMA ERROR: Failed to predict next token\n";
return;
}
promptCtx.n_past += 1;
// display text
++totalPredictions;
if (id == llama_token_eos())
return;
const std::string str = llama_token_to_str(d_ptr->ctx, id);
// Check if the provided str is part of our reverse prompts
bool foundPartialReversePrompt = false;
const std::string completed = cachedResponse + str;
if (reversePrompts.find(completed) != reversePrompts.end()) {
return;
}
// Check if it partially matches our reverse prompts and if so, cache
for (auto s : reversePrompts) {
if (s.compare(0, completed.size(), completed) == 0) {
foundPartialReversePrompt = true;
cachedResponse = completed;
break;
}
}
// Regardless the token gets added to our cache
cachedTokens.push_back(id);
// Continue if we have found a partial match
if (foundPartialReversePrompt)
continue;
// Empty the cache
for (auto t : cachedTokens) {
if (promptCtx.tokens.size() == promptCtx.n_ctx)
promptCtx.tokens.erase(promptCtx.tokens.begin());
promptCtx.tokens.push_back(t);
if (!responseCallback(t, llama_token_to_str(d_ptr->ctx, t)))
return;
}
cachedTokens.clear();
}
}
void LLamaModel::recalculateContext(PromptContext &promptCtx, std::function<bool(bool)> recalculate)
{
size_t i = 0;
promptCtx.n_past = 0;
while (i < promptCtx.tokens.size()) {
size_t batch_end = std::min(i + promptCtx.n_batch, promptCtx.tokens.size());
std::vector<llama_token> batch(promptCtx.tokens.begin() + i, promptCtx.tokens.begin() + batch_end);
assert(promptCtx.n_past + batch.size() <= promptCtx.n_ctx);
if (llama_eval(d_ptr->ctx, batch.data(), batch.size(), promptCtx.n_past, d_ptr->n_threads)) {
std::cerr << "LLAMA ERROR: Failed to process prompt\n";
goto stop_generating;
}
promptCtx.n_past += batch.size();
if (!recalculate(true))
goto stop_generating;
i = batch_end;
}
assert(promptCtx.n_past == promptCtx.tokens.size());
stop_generating:
recalculate(false);
}

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#ifndef LLAMAMODEL_H
#define LLAMAMODEL_H
#include <string>
#include <functional>
#include <vector>
#include "llmodel.h"
class LLamaPrivate;
class LLamaModel : public LLModel {
public:
LLamaModel();
~LLamaModel();
bool loadModel(const std::string &modelPath) override;
bool isModelLoaded() const override;
size_t stateSize() const override;
size_t saveState(uint8_t *dest) const override;
size_t restoreState(const uint8_t *src) override;
void prompt(const std::string &prompt,
std::function<bool(int32_t)> promptCallback,
std::function<bool(int32_t, const std::string&)> responseCallback,
std::function<bool(bool)> recalculateCallback,
PromptContext &ctx) override;
void setThreadCount(int32_t n_threads) override;
int32_t threadCount() override;
protected:
void recalculateContext(PromptContext &promptCtx,
std::function<bool(bool)> recalculate) override;
private:
LLamaPrivate *d_ptr;
};
#endif // LLAMAMODEL_H

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#ifndef LLMODEL_H
#define LLMODEL_H
#include <string>
#include <functional>
#include <vector>
#include <cstdint>
class LLModel {
public:
explicit LLModel() {}
virtual ~LLModel() {}
virtual bool loadModel(const std::string &modelPath) = 0;
virtual bool isModelLoaded() const = 0;
virtual size_t stateSize() const { return 0; }
virtual size_t saveState(uint8_t *dest) const { return 0; }
virtual size_t restoreState(const uint8_t *src) { return 0; }
struct PromptContext {
std::vector<float> logits; // logits of current context
std::vector<int32_t> tokens; // current tokens in the context window
int32_t n_past = 0; // number of tokens in past conversation
int32_t n_ctx = 0; // number of tokens possible in context window
int32_t n_predict = 200;
int32_t top_k = 40;
float top_p = 0.9f;
float temp = 0.9f;
int32_t n_batch = 9;
float repeat_penalty = 1.10f;
int32_t repeat_last_n = 64; // last n tokens to penalize
float contextErase = 0.75f; // percent of context to erase if we exceed the context
// window
};
virtual void prompt(const std::string &prompt,
std::function<bool(int32_t)> promptCallback,
std::function<bool(int32_t, const std::string&)> responseCallback,
std::function<bool(bool)> recalculateCallback,
PromptContext &ctx) = 0;
virtual void setThreadCount(int32_t n_threads) {}
virtual int32_t threadCount() { return 1; }
protected:
virtual void recalculateContext(PromptContext &promptCtx,
std::function<bool(bool)> recalculate) = 0;
};
#endif // LLMODEL_H

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#include "llmodel_c.h"
#include "gptj.h"
#include "llamamodel.h"
#include "mpt.h"
struct LLModelWrapper {
LLModel *llModel = nullptr;
LLModel::PromptContext promptContext;
};
llmodel_model llmodel_gptj_create()
{
LLModelWrapper *wrapper = new LLModelWrapper;
wrapper->llModel = new GPTJ;
return reinterpret_cast<void*>(wrapper);
}
void llmodel_gptj_destroy(llmodel_model gptj)
{
LLModelWrapper *wrapper = reinterpret_cast<LLModelWrapper*>(gptj);
delete wrapper->llModel;
delete wrapper;
}
llmodel_model llmodel_mpt_create()
{
LLModelWrapper *wrapper = new LLModelWrapper;
wrapper->llModel = new MPT;
return reinterpret_cast<void*>(wrapper);
}
void llmodel_mpt_destroy(llmodel_model mpt)
{
LLModelWrapper *wrapper = reinterpret_cast<LLModelWrapper*>(mpt);
delete wrapper->llModel;
delete wrapper;
}
llmodel_model llmodel_llama_create()
{
LLModelWrapper *wrapper = new LLModelWrapper;
wrapper->llModel = new LLamaModel;
return reinterpret_cast<void*>(wrapper);
}
void llmodel_llama_destroy(llmodel_model llama)
{
LLModelWrapper *wrapper = reinterpret_cast<LLModelWrapper*>(llama);
delete wrapper->llModel;
delete wrapper;
}
bool llmodel_loadModel(llmodel_model model, const char *model_path)
{
LLModelWrapper *wrapper = reinterpret_cast<LLModelWrapper*>(model);
return wrapper->llModel->loadModel(model_path);
}
bool llmodel_isModelLoaded(llmodel_model model)
{
LLModelWrapper *wrapper = reinterpret_cast<LLModelWrapper*>(model);
return wrapper->llModel->isModelLoaded();
}
uint64_t llmodel_get_state_size(llmodel_model model)
{
LLModelWrapper *wrapper = reinterpret_cast<LLModelWrapper*>(model);
return wrapper->llModel->stateSize();
}
uint64_t llmodel_save_state_data(llmodel_model model, uint8_t *dest)
{
LLModelWrapper *wrapper = reinterpret_cast<LLModelWrapper*>(model);
return wrapper->llModel->saveState(dest);
}
uint64_t llmodel_restore_state_data(llmodel_model model, const uint8_t *src)
{
LLModelWrapper *wrapper = reinterpret_cast<LLModelWrapper*>(model);
return wrapper->llModel->restoreState(src);
}
// Wrapper functions for the C callbacks
bool prompt_wrapper(int32_t token_id, void *user_data) {
llmodel_prompt_callback callback = reinterpret_cast<llmodel_prompt_callback>(user_data);
return callback(token_id);
}
bool response_wrapper(int32_t token_id, const std::string &response, void *user_data) {
llmodel_response_callback callback = reinterpret_cast<llmodel_response_callback>(user_data);
return callback(token_id, response.c_str());
}
bool recalculate_wrapper(bool is_recalculating, void *user_data) {
llmodel_recalculate_callback callback = reinterpret_cast<llmodel_recalculate_callback>(user_data);
return callback(is_recalculating);
}
void llmodel_prompt(llmodel_model model, const char *prompt,
llmodel_response_callback prompt_callback,
llmodel_response_callback response_callback,
llmodel_recalculate_callback recalculate_callback,
llmodel_prompt_context *ctx)
{
LLModelWrapper *wrapper = reinterpret_cast<LLModelWrapper*>(model);
// Create std::function wrappers that call the C function pointers
std::function<bool(int32_t)> prompt_func =
std::bind(&prompt_wrapper, std::placeholders::_1, reinterpret_cast<void*>(prompt_callback));
std::function<bool(int32_t, const std::string&)> response_func =
std::bind(&response_wrapper, std::placeholders::_1, std::placeholders::_2, reinterpret_cast<void*>(response_callback));
std::function<bool(bool)> recalc_func =
std::bind(&recalculate_wrapper, std::placeholders::_1, reinterpret_cast<void*>(recalculate_callback));
// Copy the C prompt context
wrapper->promptContext.n_past = ctx->n_past;
wrapper->promptContext.n_ctx = ctx->n_ctx;
wrapper->promptContext.n_predict = ctx->n_predict;
wrapper->promptContext.top_k = ctx->top_k;
wrapper->promptContext.top_p = ctx->top_p;
wrapper->promptContext.temp = ctx->temp;
wrapper->promptContext.n_batch = ctx->n_batch;
wrapper->promptContext.repeat_penalty = ctx->repeat_penalty;
wrapper->promptContext.repeat_last_n = ctx->repeat_last_n;
wrapper->promptContext.contextErase = ctx->context_erase;
// Call the C++ prompt method
wrapper->llModel->prompt(prompt, prompt_func, response_func, recalc_func, wrapper->promptContext);
// Update the C context by giving access to the wrappers raw pointers to std::vector data
// which involves no copies
ctx->logits = wrapper->promptContext.logits.data();
ctx->logits_size = wrapper->promptContext.logits.size();
ctx->tokens = wrapper->promptContext.tokens.data();
ctx->tokens_size = wrapper->promptContext.tokens.size();
// Update the rest of the C prompt context
ctx->n_past = wrapper->promptContext.n_past;
ctx->n_ctx = wrapper->promptContext.n_ctx;
ctx->n_predict = wrapper->promptContext.n_predict;
ctx->top_k = wrapper->promptContext.top_k;
ctx->top_p = wrapper->promptContext.top_p;
ctx->temp = wrapper->promptContext.temp;
ctx->n_batch = wrapper->promptContext.n_batch;
ctx->repeat_penalty = wrapper->promptContext.repeat_penalty;
ctx->repeat_last_n = wrapper->promptContext.repeat_last_n;
ctx->context_erase = wrapper->promptContext.contextErase;
}
void llmodel_setThreadCount(llmodel_model model, int32_t n_threads)
{
LLModelWrapper *wrapper = reinterpret_cast<LLModelWrapper*>(model);
wrapper->llModel->setThreadCount(n_threads);
}
int32_t llmodel_threadCount(llmodel_model model)
{
LLModelWrapper *wrapper = reinterpret_cast<LLModelWrapper*>(model);
return wrapper->llModel->threadCount();
}

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#ifndef LLMODEL_C_H
#define LLMODEL_C_H
#include <stdint.h>
#include <stddef.h>
#include <stdbool.h>
#ifdef __cplusplus
extern "C" {
#endif
/**
* Opaque pointer to the underlying model.
*/
typedef void *llmodel_model;
/**
* llmodel_prompt_context structure for holding the prompt context.
* NOTE: The implementation takes care of all the memory handling of the raw logits pointer and the
* raw tokens pointer. Attempting to resize them or modify them in any way can lead to undefined
* behavior.
*/
typedef struct {
float *logits; // logits of current context
size_t logits_size; // the size of the raw logits vector
int32_t *tokens; // current tokens in the context window
size_t tokens_size; // the size of the raw tokens vector
int32_t n_past; // number of tokens in past conversation
int32_t n_ctx; // number of tokens possible in context window
int32_t n_predict; // number of tokens to predict
int32_t top_k; // top k logits to sample from
float top_p; // nucleus sampling probability threshold
float temp; // temperature to adjust model's output distribution
int32_t n_batch; // number of predictions to generate in parallel
float repeat_penalty; // penalty factor for repeated tokens
int32_t repeat_last_n; // last n tokens to penalize
float context_erase; // percent of context to erase if we exceed the context window
} llmodel_prompt_context;
/**
* Callback type for prompt processing.
* @param token_id The token id of the prompt.
* @return a bool indicating whether the model should keep processing.
*/
typedef bool (*llmodel_prompt_callback)(int32_t token_id);
/**
* Callback type for response.
* @param token_id The token id of the response.
* @param response The response string. NOTE: a token_id of -1 indicates the string is an error string.
* @return a bool indicating whether the model should keep generating.
*/
typedef bool (*llmodel_response_callback)(int32_t token_id, const char *response);
/**
* Callback type for recalculation of context.
* @param whether the model is recalculating the context.
* @return a bool indicating whether the model should keep generating.
*/
typedef bool (*llmodel_recalculate_callback)(bool is_recalculating);
/**
* Create a GPTJ instance.
* @return A pointer to the GPTJ instance.
*/
llmodel_model llmodel_gptj_create();
/**
* Destroy a GPTJ instance.
* @param gptj A pointer to the GPTJ instance.
*/
void llmodel_gptj_destroy(llmodel_model gptj);
/**
* Create a MPT instance.
* @return A pointer to the MPT instance.
*/
llmodel_model llmodel_mpt_create();
/**
* Destroy a MPT instance.
* @param gptj A pointer to the MPT instance.
*/
void llmodel_mpt_destroy(llmodel_model mpt);
/**
* Create a LLAMA instance.
* @return A pointer to the LLAMA instance.
*/
llmodel_model llmodel_llama_create();
/**
* Destroy a LLAMA instance.
* @param llama A pointer to the LLAMA instance.
*/
void llmodel_llama_destroy(llmodel_model llama);
/**
* Load a model from a file.
* @param model A pointer to the llmodel_model instance.
* @param model_path A string representing the path to the model file.
* @return true if the model was loaded successfully, false otherwise.
*/
bool llmodel_loadModel(llmodel_model model, const char *model_path);
/**
* Check if a model is loaded.
* @param model A pointer to the llmodel_model instance.
* @return true if the model is loaded, false otherwise.
*/
bool llmodel_isModelLoaded(llmodel_model model);
/**
* Get the size of the internal state of the model.
* NOTE: This state data is specific to the type of model you have created.
* @param model A pointer to the llmodel_model instance.
* @return the size in bytes of the internal state of the model
*/
uint64_t llmodel_get_state_size(llmodel_model model);
/**
* Saves the internal state of the model to the specified destination address.
* NOTE: This state data is specific to the type of model you have created.
* @param model A pointer to the llmodel_model instance.
* @param dest A pointer to the destination.
* @return the number of bytes copied
*/
uint64_t llmodel_save_state_data(llmodel_model model, uint8_t *dest);
/**
* Restores the internal state of the model using data from the specified address.
* NOTE: This state data is specific to the type of model you have created.
* @param model A pointer to the llmodel_model instance.
* @param src A pointer to the src.
* @return the number of bytes read
*/
uint64_t llmodel_restore_state_data(llmodel_model model, const uint8_t *src);
/**
* Generate a response using the model.
* @param model A pointer to the llmodel_model instance.
* @param prompt A string representing the input prompt.
* @param prompt_callback A callback function for handling the processing of prompt.
* @param response_callback A callback function for handling the generated response.
* @param recalculate_callback A callback function for handling recalculation requests.
* @param ctx A pointer to the llmodel_prompt_context structure.
*/
void llmodel_prompt(llmodel_model model, const char *prompt,
llmodel_response_callback prompt_callback,
llmodel_response_callback response_callback,
llmodel_recalculate_callback recalculate_callback,
llmodel_prompt_context *ctx);
/**
* Set the number of threads to be used by the model.
* @param model A pointer to the llmodel_model instance.
* @param n_threads The number of threads to be used.
*/
void llmodel_setThreadCount(llmodel_model model, int32_t n_threads);
/**
* Get the number of threads currently being used by the model.
* @param model A pointer to the llmodel_model instance.
* @return The number of threads currently being used.
*/
int32_t llmodel_threadCount(llmodel_model model);
#ifdef __cplusplus
}
#endif
#endif // LLMODEL_C_H

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#ifndef MPT_H
#define MPT_H
#include <string>
#include <functional>
#include <vector>
#include "llmodel.h"
class MPTPrivate;
class MPT : public LLModel {
public:
MPT();
~MPT();
bool loadModel(const std::string &modelPath) override;
bool isModelLoaded() const override;
size_t stateSize() const override;
size_t saveState(uint8_t *dest) const override;
size_t restoreState(const uint8_t *src) override;
void prompt(const std::string &prompt,
std::function<bool(int32_t)> promptCallback,
std::function<bool(int32_t, const std::string&)> responseCallback,
std::function<bool(bool)> recalculateCallback,
PromptContext &ctx) override;
void setThreadCount(int32_t n_threads) override;
int32_t threadCount() override;
protected:
void recalculateContext(PromptContext &promptCtx,
std::function<bool(bool)> recalculate) override;
private:
MPTPrivate *d_ptr;
};
#endif // MPT_H

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# Convert Hugging Face fine-tuned bloom-like models to ggml format
#
# Usage:
#
# python3 models/convert-h5-to-ggml.py
#
# This script is similar to "convert-pt-to-ggml.py"
#
import io
import os
import sys
import struct
import json
import code
import torch
import numpy as np
from transformers import AutoTokenizer, AutoModelForCausalLM, AutoConfig, BloomForCausalLM
# ref: https://github.com/openai/gpt-2/blob/master/src/encoder.py
def bytes_to_unicode():
"""
Returns list of utf-8 byte and a corresponding list of unicode strings.
The reversible bpe codes work on unicode strings.
This means you need a large # of unicode characters in your vocab if you want to avoid UNKs.
When you're at something like a 10B token dataset you end up needing around 5K for decent coverage.
This is a significant percentage of your normal, say, 32K bpe vocab.
To avoid that, we want lookup tables between utf-8 bytes and unicode strings.
And avoids mapping to whitespace/control characters the bpe code barfs on.
"""
bs = list(range(ord("!"), ord("~")+1))+list(range(ord("¡"), ord("¬")+1))+list(range(ord("®"), ord("ÿ")+1))
cs = bs[:]
n = 0
for b in range(2**8):
if b not in bs:
bs.append(b)
cs.append(2**8+n)
n += 1
cs = [chr(n) for n in cs]
return dict(zip(bs, cs))
if len(sys.argv) < 3:
print("Usage: python convert-hf-to-ggml.py model_name dir-output [use-f32]")
print(" model_name: name of the model to convert. Example: 'bigscience/bloomz-560m'")
print(" dir-output: directory where the output file will be written")
print(" use-f32: if present, use float32 instead of float16")
sys.exit(1)
model_name = sys.argv[1]
dir_out = sys.argv[2]
# make sure the output directory exists
os.makedirs(dir_out, exist_ok=True)
# possible data types
# ftype == 0 -> float32
# ftype == 1 -> float16
#
# map from ftype to string
ftype_str = ["f32", "f16"]
ftype = 1
if len(sys.argv) > 3:
ftype = 0
tokenizer = AutoTokenizer.from_pretrained(model_name, trust_remote_code=True)
config = AutoConfig.from_pretrained(model_name, trust_remote_code=True)
hparams = config.to_dict()
print("Loading model: ", model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, trust_remote_code=True, config=config, torch_dtype=torch.float16 if ftype == 1 else torch.float32, low_cpu_mem_usage=True)
print("Model loaded: ", model_name)
fname_out = dir_out + f"/ggml-model-{model_name.split('/')[-1]}-{ftype_str[ftype]}.bin"
fout = open(fname_out, "wb")
vocab = tokenizer.vocab
hparams["multiple_of"] = 1
fout.write(struct.pack("i", 0x67676d6d)) # magic: ggml in hex
fout.write(struct.pack("i", hparams["vocab_size"]))
fout.write(struct.pack("i", hparams["max_seq_len"]))
fout.write(struct.pack("i", hparams["d_model"]))
fout.write(struct.pack("i", hparams["n_heads"]))
fout.write(struct.pack("i", hparams["n_layers"]))
# n_rot (unused)
fout.write(struct.pack("i", 0))
fout.write(struct.pack("i", ftype))
# # Is this correct??
# dot_token = tokenizer.encode(".")[0]
# write tokens to ggml file
fout.write(struct.pack("i", hparams["vocab_size"]))
for i in range(hparams["vocab_size"]):
text = tokenizer.decode([i]).encode('utf-8')
fout.write(struct.pack("i", len(text)))
fout.write(text)
list_vars = model.state_dict()
for name in list_vars.keys():
data = list_vars[name].squeeze().numpy()
print("Processing variable: " + name + " with shape: ", data.shape)
# we don't need these
if name.endswith("attn.masked_bias") or name.endswith(".attn.bias"):
print(" Skipping variable: " + name)
continue
if "Wqkv.weight" in name:
# chunk qkv
query, key, value = np.split(data, 3, axis=0)
new_name = name.split("Wqkv.weight")[0]
for (data, name) in [(query, new_name + "q_proj.weight"), (key, new_name + "k_proj.weight"), (value, new_name + "v_proj.weight")]:
print(f"Processing variable: {name} with shape: {data.shape}")
n_dims = len(data.shape);
# ftype == 0 -> float32, ftype == 1 -> float16
ftype_cur = 0;
if ftype != 0:
print(" Converting to float16")
data = data.astype(np.float16)
ftype_cur = 1
else:
if data.dtype != np.float32:
print(" Converting to float32")
data = data.astype(np.float32)
ftype_cur = 0
# header
str = name.encode('utf-8')
fout.write(struct.pack("iii", n_dims, len(str), ftype_cur))
for i in range(n_dims):
fout.write(struct.pack("i", data.shape[n_dims - 1 - i]))
fout.write(str);
# data
data.tofile(fout)
else:
n_dims = len(data.shape);
# ftype == 0 -> float32, ftype == 1 -> float16
ftype_cur = 0;
if ftype != 0:
if name[-7:] == ".weight" and n_dims == 2:
print(" Converting to float16")
data = data.astype(np.float16)
ftype_cur = 1
else:
print(" Converting to float32")
data = data.astype(np.float32)
ftype_cur = 0
else:
if data.dtype != np.float32:
print(" Converting to float32")
data = data.astype(np.float32)
ftype_cur = 0
# header
str = name.encode('utf-8')
fout.write(struct.pack("iii", n_dims, len(str), ftype_cur))
for i in range(n_dims):
fout.write(struct.pack("i", data.shape[n_dims - 1 - i]))
fout.write(str);
# data
data.tofile(fout)
fout.close()
print("Done. Output file: " + fname_out)
print("")

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#include "utils.h"
#include <fstream>
#include <regex>
void replace(std::string & str, const std::string & needle, const std::string & replacement) {
size_t pos = 0;
while ((pos = str.find(needle, pos)) != std::string::npos) {
str.replace(pos, needle.length(), replacement);
pos += replacement.length();
}
}
std::map<std::string, int32_t> json_parse(const std::string & fname) {
std::map<std::string, int32_t> result;
// read file into string
std::string json;
{
std::ifstream ifs(fname);
if (!ifs) {
fprintf(stderr, "Failed to open %s\n", fname.c_str());
exit(1);
}
json = std::string((std::istreambuf_iterator<char>(ifs)),
(std::istreambuf_iterator<char>()));
}
if (json[0] != '{') {
return result;
}
// parse json
{
bool has_key = false;
bool in_token = false;
std::string str_key = "";
std::string str_val = "";
int n = json.size();
for (int i = 1; i < n; ++i) {
if (!in_token) {
if (json[i] == ' ') continue;
if (json[i] == '"') {
in_token = true;
continue;
}
} else {
if (json[i] == '\\' && i+1 < n) {
if (has_key == false) {
str_key += json[i];
} else {
str_val += json[i];
}
++i;
} else if (json[i] == '"') {
if (has_key == false) {
has_key = true;
++i;
while (json[i] == ' ') ++i;
++i; // :
while (json[i] == ' ') ++i;
if (json[i] != '\"') {
while (json[i] != ',' && json[i] != '}') {
str_val += json[i++];
}
has_key = false;
} else {
in_token = true;
continue;
}
} else {
has_key = false;
}
::replace(str_key, "\\u0120", " " ); // \u0120 -> space
::replace(str_key, "\\u010a", "\n"); // \u010a -> new line
::replace(str_key, "\\\"", "\""); // \\\" -> "
try {
result[str_key] = std::stoi(str_val);
} catch (...) {
//fprintf(stderr, "%s: ignoring key '%s' with value '%s'\n", fname.c_str(), str_key.c_str(), str_val.c_str());
}
str_key = "";
str_val = "";
in_token = false;
continue;
}
if (has_key == false) {
str_key += json[i];
} else {
str_val += json[i];
}
}
}
}
return result;
}
std::vector<gpt_vocab::id> gpt_tokenize(const gpt_vocab & vocab, const std::string & text) {
std::vector<std::string> words;
// first split the text into words
{
std::string str = text;
std::string pat = R"('s|'t|'re|'ve|'m|'ll|'d| ?[[:alpha:]]+| ?[[:digit:]]+| ?[^\s[:alpha:][:digit:]]+|\s+(?!\S)|\s+)";
std::regex re(pat);
std::smatch m;
while (std::regex_search(str, m, re)) {
for (auto x : m) {
words.push_back(x);
}
str = m.suffix();
}
}
// find the longest tokens that form the words:
std::vector<gpt_vocab::id> tokens;
for (const auto & word : words) {
if (word.size() == 0) continue;
int i = 0;
int n = word.size();
while (i < n) {
int j = n;
while (j > i) {
auto it = vocab.token_to_id.find(word.substr(i, j-i));
if (it != vocab.token_to_id.end()) {
tokens.push_back(it->second);
i = j;
break;
}
--j;
}
if (i == n) {
break;
}
if (j == i) {
auto sub = word.substr(i, 1);
if (vocab.token_to_id.find(sub) != vocab.token_to_id.end()) {
tokens.push_back(vocab.token_to_id.at(sub));
} else {
fprintf(stderr, "%s: unknown token '%s'\n", __func__, sub.data());
}
++i;
}
}
}
return tokens;
}
bool gpt_vocab_init(const std::string & fname, gpt_vocab & vocab) {
printf("%s: loading vocab from '%s'\n", __func__, fname.c_str());
vocab.token_to_id = ::json_parse(fname);
for (const auto & kv : vocab.token_to_id) {
vocab.id_to_token[kv.second] = kv.first;
}
printf("%s: vocab size = %d\n", __func__, (int) vocab.token_to_id.size());
// print the vocabulary
//for (auto kv : vocab.token_to_id) {
// printf("'%s' -> %d\n", kv.first.data(), kv.second);
//}
return true;
}
gpt_vocab::id gpt_sample_top_k_top_p(
const gpt_vocab & vocab,
const int32_t * last_n_tokens_data,
int last_n_tokens_size,
const std::vector<float> logits,
int top_k,
double top_p,
double temp,
float repeat_penalty,
std::mt19937 & rng) {
int n_logits = vocab.id_to_token.size();
const auto last_n_tokens = std::vector<int32_t>(last_n_tokens_data, last_n_tokens_data + last_n_tokens_size);
const auto * plogits = logits.data() + logits.size() - n_logits;
std::vector<std::pair<double, gpt_vocab::id>> logits_id;
logits_id.reserve(n_logits);
{
const float scale = 1.0f/temp;
for (int i = 0; i < n_logits; ++i) {
// repetition penalty from ctrl paper (https://arxiv.org/abs/1909.05858)
// credit https://github.com/facebookresearch/llama/compare/main...shawwn:llama:main
if (std::find(last_n_tokens.begin(), last_n_tokens.end(), i) != last_n_tokens.end()) {
// if score < 0 then repetition penalty has to multiplied to reduce the previous token probability
if (plogits[i] < 0.0f) {
logits_id.push_back(std::make_pair(plogits[i]*scale*repeat_penalty, i));
} else {
logits_id.push_back(std::make_pair(plogits[i]*scale/repeat_penalty, i));
}
} else {
logits_id.push_back(std::make_pair(plogits[i]*scale, i));
}
}
}
// find the top K tokens
std::partial_sort(
logits_id.begin(),
logits_id.begin() + top_k, logits_id.end(),
[](const std::pair<double, gpt_vocab::id> & a, const std::pair<double, gpt_vocab::id> & b) {
return a.first > b.first;
});
logits_id.resize(top_k);
double maxl = -INFINITY;
for (const auto & kv : logits_id) {
maxl = std::max(maxl, kv.first);
}
// compute probs for the top K tokens
std::vector<double> probs;
probs.reserve(logits_id.size());
double sum = 0.0;
for (const auto & kv : logits_id) {
double p = exp(kv.first - maxl);
probs.push_back(p);
sum += p;
}
// normalize the probs
for (auto & p : probs) {
p /= sum;
}
if (top_p < 1.0f) {
double cumsum = 0.0f;
for (int i = 0; i < top_k; i++) {
cumsum += probs[i];
if (cumsum >= top_p) {
top_k = i + 1;
probs.resize(top_k);
logits_id.resize(top_k);
break;
}
}
cumsum = 1.0/cumsum;
for (int i = 0; i < (int) probs.size(); i++) {
probs[i] *= cumsum;
}
}
//printf("\n");
//for (int i = 0; i < (int) probs.size(); i++) {
// printf("%d: '%s' %f\n", i, vocab.id_to_token.at(logits_id[i].second).c_str(), probs[i]);
//}
//exit(0);
std::discrete_distribution<> dist(probs.begin(), probs.end());
int idx = dist(rng);
return logits_id[idx].second;
}

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// Various helper functions and utilities
#pragma once
#include <string>
#include <map>
#include <vector>
#include <random>
#include <thread>
//
// CLI argument parsing
//
struct gpt_params {
int32_t seed = -1; // RNG seed
int32_t n_threads = std::min(4, (int32_t) std::thread::hardware_concurrency());
int32_t n_predict = 200; // new tokens to predict
// sampling parameters
int32_t top_k = 40;
float top_p = 0.9f;
float temp = 0.9f;
int32_t n_batch = 8; // batch size for prompt processing
std::string model = "models/gpt-2-117M/ggml-model.bin"; // model path
std::string prompt;
};
bool gpt_params_parse(int argc, char ** argv, gpt_params & params);
void gpt_print_usage(int argc, char ** argv, const gpt_params & params);
std::string gpt_random_prompt(std::mt19937 & rng);
//
// Vocab utils
//
struct gpt_vocab {
using id = int32_t;
using token = std::string;
std::map<token, id> token_to_id;
std::map<id, token> id_to_token;
};
void replace(std::string & str, const std::string & needle, const std::string & replacement);
// poor-man's JSON parsing
std::map<std::string, int32_t> json_parse(const std::string & fname);
// split text into tokens
//
// ref: https://github.com/openai/gpt-2/blob/a74da5d99abaaba920de8131d64da2862a8f213b/src/encoder.py#L53
//
// Regex (Python):
// r"""'s|'t|'re|'ve|'m|'ll|'d| ?\p{L}+| ?\p{N}+| ?[^\s\p{L}\p{N}]+|\s+(?!\S)|\s+"""
//
// Regex (C++):
// R"('s|'t|'re|'ve|'m|'ll|'d| ?[[:alpha:]]+| ?[[:digit:]]+| ?[^\s[:alpha:][:digit:]]+|\s+(?!\S)|\s+)"
//
std::vector<gpt_vocab::id> gpt_tokenize(const gpt_vocab & vocab, const std::string & text);
// load the tokens from encoder.json
bool gpt_vocab_init(const std::string & fname, gpt_vocab & vocab);
// sample next token given probabilities for each embedding
//
// - consider only the top K tokens
// - from them, consider only the top tokens with cumulative probability > P
//
// TODO: not sure if this implementation is correct
//
gpt_vocab::id gpt_sample_top_k_top_p(
const gpt_vocab & vocab,
const int32_t * last_n_tokens_data,
int last_n_tokens_size,
const std::vector<float> logits,
int top_k,
double top_p,
double temp,
float repeat_penalty,
std::mt19937 & rng);

43
gpt4all-chat/main.cpp Normal file
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#include <QGuiApplication>
#include <QQmlApplicationEngine>
#include <QQmlContext>
#include <QDirIterator>
#include <QSettings>
#include "llm.h"
#include "download.h"
#include "network.h"
#include "config.h"
int main(int argc, char *argv[])
{
QCoreApplication::setOrganizationName("nomic.ai");
QCoreApplication::setOrganizationDomain("gpt4all.io");
QCoreApplication::setApplicationName("GPT4All");
QCoreApplication::setApplicationVersion(APP_VERSION);
QSettings::setDefaultFormat(QSettings::IniFormat);
QGuiApplication app(argc, argv);
QQmlApplicationEngine engine;
qmlRegisterSingletonInstance("llm", 1, 0, "LLM", LLM::globalInstance());
qmlRegisterSingletonInstance("download", 1, 0, "Download", Download::globalInstance());
qmlRegisterSingletonInstance("network", 1, 0, "Network", Network::globalInstance());
const QUrl url(u"qrc:/gpt4all/main.qml"_qs);
QObject::connect(&engine, &QQmlApplicationEngine::objectCreated,
&app, [url](QObject *obj, const QUrl &objUrl) {
if (!obj && url == objUrl)
QCoreApplication::exit(-1);
}, Qt::QueuedConnection);
engine.load(url);
#if 0
QDirIterator it("qrc:", QDirIterator::Subdirectories);
while (it.hasNext()) {
qDebug() << it.next();
}
#endif
return app.exec();
}

894
gpt4all-chat/main.qml Normal file
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import QtCore
import QtQuick
import QtQuick.Controls
import QtQuick.Controls.Basic
import QtQuick.Layouts
import llm
import download
import network
Window {
id: window
width: 1280
height: 720
visible: true
title: qsTr("GPT4All v") + Qt.application.version
Theme {
id: theme
}
property var currentChat: LLM.chatListModel.currentChat
property var chatModel: currentChat.chatModel
color: theme.textColor
// Startup code
Component.onCompleted: {
if (!LLM.compatHardware) {
Network.sendNonCompatHardware();
errorCompatHardware.open();
} else
startupDialogs();
}
Connections {
target: firstStartDialog
function onClosed() {
startupDialogs();
}
}
Connections {
target: downloadNewModels
function onClosed() {
startupDialogs();
}
}
Connections {
target: Download
function onHasNewerReleaseChanged() {
startupDialogs();
}
}
Connections {
target: currentChat
function onResponseInProgressChanged() {
if (Network.isActive && !currentChat.responseInProgress)
Network.sendConversation(currentChat.id, getConversationJson());
}
}
function startupDialogs() {
// check for first time start of this version
if (Download.isFirstStart()) {
firstStartDialog.open();
return;
}
// check for any current models and if not, open download dialog
if (currentChat.modelList.length === 0 && !firstStartDialog.opened) {
downloadNewModels.open();
return;
}
// check for new version
if (Download.hasNewerRelease && !firstStartDialog.opened && !downloadNewModels.opened) {
newVersionDialog.open();
return;
}
}
PopupDialog {
id: errorCompatHardware
anchors.centerIn: parent
shouldTimeOut: false
shouldShowBusy: false
closePolicy: Popup.NoAutoClose
modal: true
text: qsTr("Incompatible hardware detected. Please try the avx-only installer on https://gpt4all.io")
}
StartupDialog {
id: firstStartDialog
anchors.centerIn: parent
}
NewVersionDialog {
id: newVersionDialog
anchors.centerIn: parent
}
AboutDialog {
id: aboutDialog
anchors.centerIn: parent
}
Item {
Accessible.role: Accessible.Window
Accessible.name: title
}
Rectangle {
id: header
anchors.left: parent.left
anchors.right: parent.right
anchors.top: parent.top
height: 100
color: theme.backgroundDarkest
Item {
anchors.centerIn: parent
height: childrenRect.height
visible: currentChat.isModelLoaded
Label {
id: modelLabel
color: theme.textColor
padding: 20
font.pixelSize: theme.fontSizeLarger
text: ""
background: Rectangle {
color: theme.backgroundDarkest
}
horizontalAlignment: TextInput.AlignRight
}
ComboBox {
id: comboBox
width: 350
anchors.top: modelLabel.top
anchors.bottom: modelLabel.bottom
anchors.horizontalCenter: parent.horizontalCenter
font.pixelSize: theme.fontSizeLarge
spacing: 0
model: currentChat.modelList
Accessible.role: Accessible.ComboBox
Accessible.name: qsTr("ComboBox for displaying/picking the current model")
Accessible.description: qsTr("Use this for picking the current model to use; the first item is the current model")
contentItem: Text {
anchors.horizontalCenter: parent.horizontalCenter
leftPadding: 10
rightPadding: 10
text: comboBox.displayText
font: comboBox.font
color: theme.textColor
verticalAlignment: Text.AlignVCenter
horizontalAlignment: Text.AlignHCenter
elide: Text.ElideRight
}
delegate: ItemDelegate {
width: comboBox.width
contentItem: Text {
text: modelData
color: theme.textColor
font: comboBox.font
elide: Text.ElideRight
verticalAlignment: Text.AlignVCenter
}
background: Rectangle {
color: highlighted ? theme.backgroundLight : theme.backgroundDark
}
highlighted: comboBox.highlightedIndex === index
}
popup: Popup {
y: comboBox.height - 1
width: comboBox.width
implicitHeight: contentItem.implicitHeight
padding: 0
contentItem: ListView {
clip: true
implicitHeight: contentHeight
model: comboBox.popup.visible ? comboBox.delegateModel : null
currentIndex: comboBox.highlightedIndex
ScrollIndicator.vertical: ScrollIndicator { }
}
background: Rectangle {
color: theme.backgroundDark
}
}
background: Rectangle {
color: theme.backgroundDark
}
onActivated: {
currentChat.stopGenerating()
currentChat.reset();
currentChat.modelName = comboBox.currentText
}
}
}
BusyIndicator {
anchors.centerIn: parent
visible: !currentChat.isModelLoaded
running: !currentChat.isModelLoaded
Accessible.role: Accessible.Animation
Accessible.name: qsTr("Busy indicator")
Accessible.description: qsTr("Displayed when the model is loading")
}
}
SettingsDialog {
id: settingsDialog
anchors.centerIn: parent
width: Math.min(1024, window.width - (window.width * .2))
height: Math.min(600, window.height - (window.height * .2))
}
Button {
id: drawerButton
anchors.left: parent.left
anchors.top: parent.top
anchors.topMargin: 30
anchors.leftMargin: 30
width: 40
height: 40
z: 200
padding: 15
Accessible.role: Accessible.ButtonMenu
Accessible.name: qsTr("Hamburger button")
Accessible.description: qsTr("Hamburger button that reveals a drawer on the left of the application")
background: Item {
anchors.centerIn: parent
width: 30
height: 30
Rectangle {
id: bar1
color: theme.backgroundLightest
width: parent.width
height: 6
radius: 2
antialiasing: true
}
Rectangle {
id: bar2
anchors.centerIn: parent
color: theme.backgroundLightest
width: parent.width
height: 6
radius: 2
antialiasing: true
}
Rectangle {
id: bar3
anchors.bottom: parent.bottom
color: theme.backgroundLightest
width: parent.width
height: 6
radius: 2
antialiasing: true
}
}
onClicked: {
drawer.visible = !drawer.visible
}
}
NetworkDialog {
id: networkDialog
anchors.centerIn: parent
width: Math.min(1024, window.width - (window.width * .2))
height: Math.min(600, window.height - (window.height * .2))
Item {
Accessible.role: Accessible.Dialog
Accessible.name: qsTr("Network dialog")
Accessible.description: qsTr("Dialog for opt-in to sharing feedback/conversations")
}
}
Button {
id: networkButton
anchors.right: parent.right
anchors.top: parent.top
anchors.topMargin: 30
anchors.rightMargin: 30
width: 40
height: 40
z: 200
padding: 15
Accessible.role: Accessible.Button
Accessible.name: qsTr("Network button")
Accessible.description: qsTr("Reveals a dialogue where you can opt-in for sharing data over network")
background: Item {
anchors.fill: parent
Rectangle {
anchors.fill: parent
color: "transparent"
visible: Network.isActive
border.color: theme.backgroundLightest
border.width: 1
radius: 10
}
Image {
anchors.centerIn: parent
width: 30
height: 30
source: "qrc:/gpt4all/icons/network.svg"
}
}
onClicked: {
if (Network.isActive) {
Network.isActive = false
Network.sendNetworkToggled(false);
} else
networkDialog.open()
}
}
Connections {
target: Network
function onHealthCheckFailed(code) {
healthCheckFailed.open();
}
}
Button {
id: settingsButton
anchors.right: networkButton.left
anchors.top: parent.top
anchors.topMargin: 30
anchors.rightMargin: 30
width: 40
height: 40
z: 200
padding: 15
background: Item {
anchors.fill: parent
Image {
anchors.centerIn: parent
width: 30
height: 30
source: "qrc:/gpt4all/icons/settings.svg"
}
}
Accessible.role: Accessible.Button
Accessible.name: qsTr("Settings button")
Accessible.description: qsTr("Reveals a dialogue where you can change various settings")
onClicked: {
settingsDialog.open()
}
}
PopupDialog {
id: copyMessage
anchors.centerIn: parent
text: qsTr("Conversation copied to clipboard.")
}
PopupDialog {
id: healthCheckFailed
anchors.centerIn: parent
text: qsTr("Connection to datalake failed.")
}
PopupDialog {
id: recalcPopup
anchors.centerIn: parent
shouldTimeOut: false
shouldShowBusy: true
text: qsTr("Recalculating context.")
Connections {
target: currentChat
function onRecalcChanged() {
if (currentChat.isRecalc)
recalcPopup.open()
else
recalcPopup.close()
}
}
}
Button {
id: copyButton
anchors.right: settingsButton.left
anchors.top: parent.top
anchors.topMargin: 30
anchors.rightMargin: 30
width: 40
height: 40
z: 200
padding: 15
Accessible.role: Accessible.Button
Accessible.name: qsTr("Copy button")
Accessible.description: qsTr("Copy the conversation to the clipboard")
background: Item {
anchors.fill: parent
Image {
anchors.centerIn: parent
width: 30
height: 30
source: "qrc:/gpt4all/icons/copy.svg"
}
}
TextEdit{
id: copyEdit
visible: false
}
onClicked: {
var conversation = getConversation()
copyEdit.text = conversation
copyEdit.selectAll()
copyEdit.copy()
copyMessage.open()
}
}
function getConversation() {
var conversation = "";
for (var i = 0; i < chatModel.count; i++) {
var item = chatModel.get(i)
var string = item.name;
var isResponse = item.name === qsTr("Response: ")
string += chatModel.get(i).value
if (isResponse && item.stopped)
string += " <stopped>"
string += "\n"
conversation += string
}
return conversation
}
function getConversationJson() {
var str = "{\"conversation\": [";
for (var i = 0; i < chatModel.count; i++) {
var item = chatModel.get(i)
var isResponse = item.name === qsTr("Response: ")
str += "{\"content\": ";
str += JSON.stringify(item.value)
str += ", \"role\": \"" + (isResponse ? "assistant" : "user") + "\"";
if (isResponse && item.thumbsUpState !== item.thumbsDownState)
str += ", \"rating\": \"" + (item.thumbsUpState ? "positive" : "negative") + "\"";
if (isResponse && item.newResponse !== "")
str += ", \"edited_content\": " + JSON.stringify(item.newResponse);
if (isResponse && item.stopped)
str += ", \"stopped\": \"true\""
if (!isResponse)
str += "},"
else
str += ((i < chatModel.count - 1) ? "}," : "}")
}
return str + "]}"
}
Button {
id: resetContextButton
anchors.right: copyButton.left
anchors.top: parent.top
anchors.topMargin: 30
anchors.rightMargin: 30
width: 40
height: 40
z: 200
padding: 15
Accessible.role: Accessible.Button
Accessible.name: text
Accessible.description: qsTr("Reset the context which erases current conversation")
background: Item {
anchors.fill: parent
Image {
anchors.centerIn: parent
width: 30
height: 30
source: "qrc:/gpt4all/icons/regenerate.svg"
}
}
onClicked: {
Network.sendResetContext(chatModel.count)
currentChat.reset();
}
}
Dialog {
id: checkForUpdatesError
anchors.centerIn: parent
modal: false
opacity: 0.9
padding: 20
Text {
horizontalAlignment: Text.AlignJustify
text: qsTr("ERROR: Update system could not find the MaintenanceTool used<br>
to check for updates!<br><br>
Did you install this application using the online installer? If so,<br>
the MaintenanceTool executable should be located one directory<br>
above where this application resides on your filesystem.<br><br>
If you can't start it manually, then I'm afraid you'll have to<br>
reinstall.")
color: theme.textColor
Accessible.role: Accessible.Dialog
Accessible.name: text
Accessible.description: qsTr("Dialog indicating an error")
}
background: Rectangle {
anchors.fill: parent
color: theme.backgroundDarkest
border.width: 1
border.color: theme.dialogBorder
radius: 10
}
}
ModelDownloaderDialog {
id: downloadNewModels
anchors.centerIn: parent
width: Math.min(1024, window.width - (window.width * .2))
height: Math.min(600, window.height - (window.height * .2))
Item {
Accessible.role: Accessible.Dialog
Accessible.name: qsTr("Download new models dialog")
Accessible.description: qsTr("Dialog for downloading new models")
}
}
ChatDrawer {
id: drawer
y: header.height
width: 0.3 * window.width
height: window.height - y
onDownloadClicked: {
downloadNewModels.open()
}
onAboutClicked: {
aboutDialog.open()
}
}
Rectangle {
id: conversation
color: theme.backgroundLight
anchors.left: parent.left
anchors.right: parent.right
anchors.bottom: parent.bottom
anchors.top: header.bottom
ScrollView {
id: scrollView
anchors.left: parent.left
anchors.right: parent.right
anchors.top: parent.top
anchors.bottom: textInputView.top
anchors.bottomMargin: 30
ScrollBar.vertical.policy: ScrollBar.AlwaysOn
Rectangle {
anchors.fill: parent
color: theme.backgroundLighter
ListView {
id: listView
anchors.fill: parent
model: chatModel
Accessible.role: Accessible.List
Accessible.name: qsTr("List of prompt/response pairs")
Accessible.description: qsTr("This is the list of prompt/response pairs comprising the actual conversation with the model")
delegate: TextArea {
text: value
width: listView.width
color: theme.textColor
wrapMode: Text.WordWrap
focus: false
readOnly: true
font.pixelSize: theme.fontSizeLarge
cursorVisible: currentResponse ? currentChat.responseInProgress : false
cursorPosition: text.length
background: Rectangle {
color: name === qsTr("Response: ") ? theme.backgroundLighter : theme.backgroundLight
}
Accessible.role: Accessible.Paragraph
Accessible.name: name
Accessible.description: name === qsTr("Response: ") ? "The response by the model" : "The prompt by the user"
topPadding: 20
bottomPadding: 20
leftPadding: 100
rightPadding: 100
BusyIndicator {
anchors.left: parent.left
anchors.leftMargin: 90
anchors.top: parent.top
anchors.topMargin: 5
visible: (currentResponse ? true : false) && value === "" && currentChat.responseInProgress
running: (currentResponse ? true : false) && value === "" && currentChat.responseInProgress
Accessible.role: Accessible.Animation
Accessible.name: qsTr("Busy indicator")
Accessible.description: qsTr("Displayed when the model is thinking")
}
Rectangle {
anchors.left: parent.left
anchors.top: parent.top
anchors.leftMargin: 20
anchors.topMargin: 20
width: 30
height: 30
radius: 5
color: name === qsTr("Response: ") ? theme.assistantColor : theme.userColor
Text {
anchors.centerIn: parent
text: name === qsTr("Response: ") ? "R" : "P"
color: "white"
}
}
ThumbsDownDialog {
id: thumbsDownDialog
property point globalPoint: mapFromItem(window,
window.width / 2 - width / 2,
window.height / 2 - height / 2)
x: globalPoint.x
y: globalPoint.y
property string text: value
response: newResponse === undefined || newResponse === "" ? text : newResponse
onAccepted: {
var responseHasChanged = response !== text && response !== newResponse
if (thumbsDownState && !thumbsUpState && !responseHasChanged)
return
chatModel.updateNewResponse(index, response)
chatModel.updateThumbsUpState(index, false)
chatModel.updateThumbsDownState(index, true)
Network.sendConversation(currentChat.id, getConversationJson());
}
}
Column {
visible: name === qsTr("Response: ") &&
(!currentResponse || !currentChat.responseInProgress) && Network.isActive
anchors.right: parent.right
anchors.rightMargin: 20
anchors.top: parent.top
anchors.topMargin: 20
spacing: 10
Item {
width: childrenRect.width
height: childrenRect.height
Button {
id: thumbsUp
width: 30
height: 30
opacity: thumbsUpState || thumbsUpState == thumbsDownState ? 1.0 : 0.2
background: Image {
anchors.fill: parent
source: "qrc:/gpt4all/icons/thumbs_up.svg"
}
onClicked: {
if (thumbsUpState && !thumbsDownState)
return
chatModel.updateNewResponse(index, "")
chatModel.updateThumbsUpState(index, true)
chatModel.updateThumbsDownState(index, false)
Network.sendConversation(currentChat.id, getConversationJson());
}
}
Button {
id: thumbsDown
anchors.top: thumbsUp.top
anchors.topMargin: 10
anchors.left: thumbsUp.right
anchors.leftMargin: 2
width: 30
height: 30
checked: thumbsDownState
opacity: thumbsDownState || thumbsUpState == thumbsDownState ? 1.0 : 0.2
transform: [
Matrix4x4 {
matrix: Qt.matrix4x4(-1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1)
},
Translate {
x: thumbsDown.width
}
]
background: Image {
anchors.fill: parent
source: "qrc:/gpt4all/icons/thumbs_down.svg"
}
onClicked: {
thumbsDownDialog.open()
}
}
}
}
}
property bool shouldAutoScroll: true
property bool isAutoScrolling: false
Connections {
target: currentChat
function onResponseChanged() {
if (listView.shouldAutoScroll) {
listView.isAutoScrolling = true
listView.positionViewAtEnd()
listView.isAutoScrolling = false
}
}
}
onContentYChanged: {
if (!isAutoScrolling)
shouldAutoScroll = atYEnd
}
Component.onCompleted: {
shouldAutoScroll = true
positionViewAtEnd()
}
footer: Item {
id: bottomPadding
width: parent.width
height: 60
}
}
}
}
Button {
visible: chatModel.count
Image {
anchors.verticalCenter: parent.verticalCenter
anchors.left: parent.left
anchors.leftMargin: 15
source: currentChat.responseInProgress ? "qrc:/gpt4all/icons/stop_generating.svg" : "qrc:/gpt4all/icons/regenerate.svg"
}
leftPadding: 50
onClicked: {
var index = Math.max(0, chatModel.count - 1);
var listElement = chatModel.get(index);
if (currentChat.responseInProgress) {
listElement.stopped = true
currentChat.stopGenerating()
} else {
currentChat.regenerateResponse()
if (chatModel.count) {
if (listElement.name === qsTr("Response: ")) {
chatModel.updateCurrentResponse(index, true);
chatModel.updateStopped(index, false);
chatModel.updateThumbsUpState(index, false);
chatModel.updateThumbsDownState(index, false);
chatModel.updateNewResponse(index, "");
currentChat.prompt(listElement.prompt, settingsDialog.promptTemplate,
settingsDialog.maxLength,
settingsDialog.topK, settingsDialog.topP,
settingsDialog.temperature,
settingsDialog.promptBatchSize,
settingsDialog.repeatPenalty,
settingsDialog.repeatPenaltyTokens)
}
}
}
}
anchors.bottom: textInputView.top
anchors.horizontalCenter: textInputView.horizontalCenter
anchors.bottomMargin: 40
padding: 15
contentItem: Text {
text: currentChat.responseInProgress ? qsTr("Stop generating") : qsTr("Regenerate response")
color: theme.textColor
Accessible.role: Accessible.Button
Accessible.name: text
Accessible.description: qsTr("Controls generation of the response")
}
background: Rectangle {
opacity: .5
border.color: theme.backgroundLightest
border.width: 1
radius: 10
color: theme.backgroundLight
}
}
ScrollView {
id: textInputView
anchors.left: parent.left
anchors.right: parent.right
anchors.bottom: parent.bottom
anchors.margins: 30
height: Math.min(contentHeight, 200)
TextArea {
id: textInput
color: theme.textColor
padding: 20
rightPadding: 40
enabled: currentChat.isModelLoaded
wrapMode: Text.WordWrap
font.pixelSize: theme.fontSizeLarge
placeholderText: qsTr("Send a message...")
placeholderTextColor: theme.backgroundLightest
background: Rectangle {
color: theme.backgroundLighter
radius: 10
}
Accessible.role: Accessible.EditableText
Accessible.name: placeholderText
Accessible.description: qsTr("Textfield for sending messages/prompts to the model")
Keys.onReturnPressed: (event)=> {
if (event.modifiers & Qt.ControlModifier || event.modifiers & Qt.ShiftModifier)
event.accepted = false;
else {
editingFinished();
sendMessage()
}
}
function sendMessage() {
if (textInput.text === "")
return
currentChat.stopGenerating()
if (chatModel.count) {
var index = Math.max(0, chatModel.count - 1);
var listElement = chatModel.get(index);
chatModel.updateCurrentResponse(index, false);
}
currentChat.newPromptResponsePair(textInput.text);
currentChat.prompt(textInput.text, settingsDialog.promptTemplate,
settingsDialog.maxLength,
settingsDialog.topK,
settingsDialog.topP,
settingsDialog.temperature,
settingsDialog.promptBatchSize,
settingsDialog.repeatPenalty,
settingsDialog.repeatPenaltyTokens)
textInput.text = ""
}
}
}
Button {
anchors.right: textInputView.right
anchors.verticalCenter: textInputView.verticalCenter
anchors.rightMargin: 15
width: 30
height: 30
background: Image {
anchors.centerIn: parent
source: "qrc:/gpt4all/icons/send_message.svg"
}
Accessible.role: Accessible.Button
Accessible.name: qsTr("Send the message button")
Accessible.description: qsTr("Sends the message/prompt contained in textfield to the model")
onClicked: {
textInput.sendMessage()
}
}
}
}

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gpt4all-chat/network.cpp Normal file
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#include "network.h"
#include "llm.h"
#include "sysinfo.h"
#include <QCoreApplication>
#include <QGuiApplication>
#include <QUuid>
#include <QJsonDocument>
#include <QJsonArray>
#include <QJsonObject>
#include <QSettings>
#include <QNetworkRequest>
#include <QScreen>
//#define DEBUG
#if defined(Q_OS_MAC)
#include <sys/sysctl.h>
std::string getCPUModel() {
char buffer[256];
size_t bufferlen = sizeof(buffer);
sysctlbyname("machdep.cpu.brand_string", &buffer, &bufferlen, NULL, 0);
return std::string(buffer);
}
#endif
class MyNetwork: public Network { };
Q_GLOBAL_STATIC(MyNetwork, networkInstance)
Network *Network::globalInstance()
{
return networkInstance();
}
Network::Network()
: QObject{nullptr}
, m_isActive(false)
, m_usageStatsActive(false)
, m_shouldSendStartup(false)
{
QSettings settings;
settings.sync();
m_uniqueId = settings.value("uniqueId", generateUniqueId()).toString();
settings.setValue("uniqueId", m_uniqueId);
settings.sync();
m_isActive = settings.value("network/isActive", false).toBool();
if (m_isActive)
sendHealth();
m_usageStatsActive = settings.value("network/usageStatsActive", false).toBool();
if (m_usageStatsActive)
sendIpify();
connect(&m_networkManager, &QNetworkAccessManager::sslErrors, this,
&Network::handleSslErrors);
}
void Network::setActive(bool b)
{
QSettings settings;
settings.setValue("network/isActive", b);
settings.sync();
m_isActive = b;
emit activeChanged();
if (m_isActive)
sendHealth();
}
void Network::setUsageStatsActive(bool b)
{
QSettings settings;
settings.setValue("network/usageStatsActive", b);
settings.sync();
m_usageStatsActive = b;
emit usageStatsActiveChanged();
if (!m_usageStatsActive)
sendOptOut();
else {
// model might be loaded already when user opt-in for first time
sendStartup();
sendIpify();
}
}
QString Network::generateUniqueId() const
{
return QUuid::createUuid().toString(QUuid::WithoutBraces);
}
bool Network::packageAndSendJson(const QString &ingestId, const QString &json)
{
if (!m_isActive)
return false;
QJsonParseError err;
QJsonDocument doc = QJsonDocument::fromJson(json.toUtf8(), &err);
if (err.error != QJsonParseError::NoError) {
qDebug() << "Couldn't parse: " << json << err.errorString();
return false;
}
Q_ASSERT(doc.isObject());
Q_ASSERT(LLM::globalInstance()->chatListModel()->currentChat());
QJsonObject object = doc.object();
object.insert("source", "gpt4all-chat");
object.insert("agent_id", LLM::globalInstance()->chatListModel()->currentChat()->modelName());
object.insert("submitter_id", m_uniqueId);
object.insert("ingest_id", ingestId);
QSettings settings;
settings.sync();
QString attribution = settings.value("network/attribution", QString()).toString();
if (!attribution.isEmpty())
object.insert("network/attribution", attribution);
QJsonDocument newDoc;
newDoc.setObject(object);
#if defined(DEBUG)
printf("%s\n", qPrintable(newDoc.toJson(QJsonDocument::Indented)));
fflush(stdout);
#endif
QUrl jsonUrl("https://api.gpt4all.io/v1/ingest/chat");
QNetworkRequest request(jsonUrl);
QSslConfiguration conf = request.sslConfiguration();
conf.setPeerVerifyMode(QSslSocket::VerifyNone);
request.setSslConfiguration(conf);
QByteArray body(newDoc.toJson());
request.setHeader(QNetworkRequest::ContentTypeHeader, "application/json");
QNetworkReply *jsonReply = m_networkManager.post(request, body);
connect(jsonReply, &QNetworkReply::finished, this, &Network::handleJsonUploadFinished);
m_activeUploads.append(jsonReply);
return true;
}
void Network::handleJsonUploadFinished()
{
QNetworkReply *jsonReply = qobject_cast<QNetworkReply *>(sender());
if (!jsonReply)
return;
m_activeUploads.removeAll(jsonReply);
QVariant response = jsonReply->attribute(QNetworkRequest::HttpStatusCodeAttribute);
Q_ASSERT(response.isValid());
bool ok;
int code = response.toInt(&ok);
if (!ok)
qWarning() << "ERROR: ingest invalid response.";
if (code != 200) {
qWarning() << "ERROR: ingest response != 200 code:" << code;
sendHealth();
}
QByteArray jsonData = jsonReply->readAll();
QJsonParseError err;
QJsonDocument document = QJsonDocument::fromJson(jsonData, &err);
if (err.error != QJsonParseError::NoError) {
qDebug() << "ERROR: Couldn't parse: " << jsonData << err.errorString();
return;
}
#if defined(DEBUG)
printf("%s\n", qPrintable(document.toJson(QJsonDocument::Indented)));
fflush(stdout);
#endif
jsonReply->deleteLater();
}
void Network::handleSslErrors(QNetworkReply *reply, const QList<QSslError> &errors)
{
QUrl url = reply->request().url();
for (auto e : errors)
qWarning() << "ERROR: Received ssl error:" << e.errorString() << "for" << url;
}
void Network::sendOptOut()
{
QJsonObject properties;
properties.insert("token", "ce362e568ddaee16ed243eaffb5860a2");
properties.insert("time", QDateTime::currentSecsSinceEpoch());
properties.insert("distinct_id", m_uniqueId);
properties.insert("$insert_id", generateUniqueId());
QJsonObject event;
event.insert("event", "opt_out");
event.insert("properties", properties);
QJsonArray array;
array.append(event);
QJsonDocument doc;
doc.setArray(array);
sendMixpanel(doc.toJson(), true /*isOptOut*/);
#if defined(DEBUG)
printf("%s %s\n", qPrintable("opt_out"), qPrintable(doc.toJson(QJsonDocument::Indented)));
fflush(stdout);
#endif
}
void Network::sendModelLoaded()
{
if (!m_usageStatsActive)
return;
sendMixpanelEvent("model_load");
}
void Network::sendResetContext(int conversationLength)
{
if (!m_usageStatsActive)
return;
KeyValue kv;
kv.key = QString("length");
kv.value = QJsonValue(conversationLength);
sendMixpanelEvent("reset_context", QVector<KeyValue>{kv});
}
void Network::sendStartup()
{
if (!m_usageStatsActive)
return;
m_shouldSendStartup = true;
if (m_ipify.isEmpty())
return; // when it completes it will send
sendMixpanelEvent("startup");
}
void Network::sendCheckForUpdates()
{
if (!m_usageStatsActive)
return;
sendMixpanelEvent("check_for_updates");
}
void Network::sendModelDownloaderDialog()
{
if (!m_usageStatsActive)
return;
sendMixpanelEvent("download_dialog");
}
void Network::sendDownloadStarted(const QString &model)
{
if (!m_usageStatsActive)
return;
KeyValue kv;
kv.key = QString("model");
kv.value = QJsonValue(model);
sendMixpanelEvent("download_started", QVector<KeyValue>{kv});
}
void Network::sendDownloadCanceled(const QString &model)
{
if (!m_usageStatsActive)
return;
KeyValue kv;
kv.key = QString("model");
kv.value = QJsonValue(model);
sendMixpanelEvent("download_canceled", QVector<KeyValue>{kv});
}
void Network::sendDownloadError(const QString &model, int code, const QString &errorString)
{
if (!m_usageStatsActive)
return;
KeyValue kv;
kv.key = QString("model");
kv.value = QJsonValue(model);
KeyValue kvCode;
kvCode.key = QString("code");
kvCode.value = QJsonValue(code);
KeyValue kvError;
kvError.key = QString("error");
kvError.value = QJsonValue(errorString);
sendMixpanelEvent("download_error", QVector<KeyValue>{kv, kvCode, kvError});
}
void Network::sendDownloadFinished(const QString &model, bool success)
{
if (!m_usageStatsActive)
return;
KeyValue kv;
kv.key = QString("model");
kv.value = QJsonValue(model);
KeyValue kvSuccess;
kvSuccess.key = QString("success");
kvSuccess.value = QJsonValue(success);
sendMixpanelEvent("download_finished", QVector<KeyValue>{kv, kvSuccess});
}
void Network::sendSettingsDialog()
{
if (!m_usageStatsActive)
return;
sendMixpanelEvent("settings_dialog");
}
void Network::sendNetworkToggled(bool isActive)
{
if (!m_usageStatsActive)
return;
KeyValue kv;
kv.key = QString("isActive");
kv.value = QJsonValue(isActive);
sendMixpanelEvent("network_toggled", QVector<KeyValue>{kv});
}
void Network::sendSaveChatsToggled(bool isActive)
{
if (!m_usageStatsActive)
return;
KeyValue kv;
kv.key = QString("isActive");
kv.value = QJsonValue(isActive);
sendMixpanelEvent("savechats_toggled", QVector<KeyValue>{kv});
}
void Network::sendNewChat(int count)
{
if (!m_usageStatsActive)
return;
KeyValue kv;
kv.key = QString("number_of_chats");
kv.value = QJsonValue(count);
sendMixpanelEvent("new_chat", QVector<KeyValue>{kv});
}
void Network::sendRemoveChat()
{
if (!m_usageStatsActive)
return;
sendMixpanelEvent("remove_chat");
}
void Network::sendRenameChat()
{
if (!m_usageStatsActive)
return;
sendMixpanelEvent("rename_chat");
}
void Network::sendChatStarted()
{
if (!m_usageStatsActive)
return;
sendMixpanelEvent("chat_started");
}
void Network::sendRecalculatingContext(int conversationLength)
{
if (!m_usageStatsActive)
return;
KeyValue kv;
kv.key = QString("length");
kv.value = QJsonValue(conversationLength);
sendMixpanelEvent("recalc_context", QVector<KeyValue>{kv});
}
void Network::sendNonCompatHardware()
{
if (!m_usageStatsActive)
return;
sendMixpanelEvent("noncompat_hardware");
}
void Network::sendMixpanelEvent(const QString &ev, const QVector<KeyValue> &values)
{
if (!m_usageStatsActive)
return;
Q_ASSERT(LLM::globalInstance()->chatListModel()->currentChat());
QJsonObject properties;
properties.insert("token", "ce362e568ddaee16ed243eaffb5860a2");
properties.insert("time", QDateTime::currentSecsSinceEpoch());
properties.insert("distinct_id", m_uniqueId);
properties.insert("$insert_id", generateUniqueId());
properties.insert("$os", QSysInfo::prettyProductName());
if (!m_ipify.isEmpty())
properties.insert("ip", m_ipify);
properties.insert("name", QCoreApplication::applicationName() + " v"
+ QCoreApplication::applicationVersion());
properties.insert("model", LLM::globalInstance()->chatListModel()->currentChat()->modelName());
// Some additional startup information
if (ev == "startup") {
const QSize display = QGuiApplication::primaryScreen()->size();
properties.insert("display", QString("%1x%2").arg(display.width()).arg(display.height()));
properties.insert("ram", getSystemTotalRAM());
#if defined(__x86_64__) || defined(__i386__)
properties.insert("avx", bool(__builtin_cpu_supports("avx")));
properties.insert("avx2", bool(__builtin_cpu_supports("avx2")));
properties.insert("fma", bool(__builtin_cpu_supports("fma")));
#endif
#if defined(Q_OS_MAC)
properties.insert("cpu", QString::fromStdString(getCPUModel()));
#endif
}
for (auto p : values)
properties.insert(p.key, p.value);
QJsonObject event;
event.insert("event", ev);
event.insert("properties", properties);
QJsonArray array;
array.append(event);
QJsonDocument doc;
doc.setArray(array);
sendMixpanel(doc.toJson());
#if defined(DEBUG)
printf("%s %s\n", qPrintable(ev), qPrintable(doc.toJson(QJsonDocument::Indented)));
fflush(stdout);
#endif
}
void Network::sendIpify()
{
if (!m_usageStatsActive || !m_ipify.isEmpty())
return;
QUrl ipifyUrl("https://api.ipify.org");
QNetworkRequest request(ipifyUrl);
QSslConfiguration conf = request.sslConfiguration();
conf.setPeerVerifyMode(QSslSocket::VerifyNone);
request.setSslConfiguration(conf);
QNetworkReply *reply = m_networkManager.get(request);
connect(reply, &QNetworkReply::finished, this, &Network::handleIpifyFinished);
}
void Network::sendMixpanel(const QByteArray &json, bool isOptOut)
{
if (!m_usageStatsActive && !isOptOut)
return;
QUrl trackUrl("https://api.mixpanel.com/track");
QNetworkRequest request(trackUrl);
QSslConfiguration conf = request.sslConfiguration();
conf.setPeerVerifyMode(QSslSocket::VerifyNone);
request.setSslConfiguration(conf);
request.setHeader(QNetworkRequest::ContentTypeHeader, "application/json");
QNetworkReply *trackReply = m_networkManager.post(request, json);
connect(trackReply, &QNetworkReply::finished, this, &Network::handleMixpanelFinished);
}
void Network::handleIpifyFinished()
{
Q_ASSERT(m_usageStatsActive);
QNetworkReply *reply = qobject_cast<QNetworkReply *>(sender());
if (!reply)
return;
QVariant response = reply->attribute(QNetworkRequest::HttpStatusCodeAttribute);
Q_ASSERT(response.isValid());
bool ok;
int code = response.toInt(&ok);
if (!ok)
qWarning() << "ERROR: ipify invalid response.";
if (code != 200)
qWarning() << "ERROR: ipify response != 200 code:" << code;
m_ipify = qPrintable(reply->readAll());
#if defined(DEBUG)
printf("ipify finished %s\n", m_ipify.toLatin1().constData());
fflush(stdout);
#endif
reply->deleteLater();
if (m_shouldSendStartup)
sendStartup();
}
void Network::handleMixpanelFinished()
{
QNetworkReply *reply = qobject_cast<QNetworkReply *>(sender());
if (!reply)
return;
QVariant response = reply->attribute(QNetworkRequest::HttpStatusCodeAttribute);
Q_ASSERT(response.isValid());
bool ok;
int code = response.toInt(&ok);
if (!ok)
qWarning() << "ERROR: track invalid response.";
if (code != 200)
qWarning() << "ERROR: track response != 200 code:" << code;
#if defined(DEBUG)
printf("mixpanel finished %s\n", qPrintable(reply->readAll()));
fflush(stdout);
#endif
reply->deleteLater();
}
bool Network::sendConversation(const QString &ingestId, const QString &conversation)
{
return packageAndSendJson(ingestId, conversation);
}
void Network::sendHealth()
{
QUrl healthUrl("https://api.gpt4all.io/v1/health");
QNetworkRequest request(healthUrl);
QSslConfiguration conf = request.sslConfiguration();
conf.setPeerVerifyMode(QSslSocket::VerifyNone);
request.setSslConfiguration(conf);
QNetworkReply *healthReply = m_networkManager.get(request);
connect(healthReply, &QNetworkReply::finished, this, &Network::handleHealthFinished);
}
void Network::handleHealthFinished()
{
QNetworkReply *healthReply = qobject_cast<QNetworkReply *>(sender());
if (!healthReply)
return;
QVariant response = healthReply->attribute(QNetworkRequest::HttpStatusCodeAttribute);
Q_ASSERT(response.isValid());
bool ok;
int code = response.toInt(&ok);
if (!ok)
qWarning() << "ERROR: health invalid response.";
if (code != 200) {
qWarning() << "ERROR: health response != 200 code:" << code;
emit healthCheckFailed(code);
setActive(false);
}
healthReply->deleteLater();
}

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gpt4all-chat/network.h Normal file
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#ifndef NETWORK_H
#define NETWORK_H
#include <QObject>
#include <QNetworkAccessManager>
#include <QNetworkReply>
#include <QJsonValue>
struct KeyValue {
QString key;
QJsonValue value;
};
class Network : public QObject
{
Q_OBJECT
Q_PROPERTY(bool isActive READ isActive WRITE setActive NOTIFY activeChanged)
Q_PROPERTY(bool usageStatsActive READ usageStatsActive WRITE setUsageStatsActive NOTIFY usageStatsActiveChanged)
public:
static Network *globalInstance();
bool isActive() const { return m_isActive; }
void setActive(bool b);
bool usageStatsActive() const { return m_usageStatsActive; }
void setUsageStatsActive(bool b);
Q_INVOKABLE QString generateUniqueId() const;
Q_INVOKABLE bool sendConversation(const QString &ingestId, const QString &conversation);
Q_SIGNALS:
void activeChanged();
void usageStatsActiveChanged();
void healthCheckFailed(int code);
public Q_SLOTS:
void sendOptOut();
void sendModelLoaded();
void sendStartup();
void sendCheckForUpdates();
Q_INVOKABLE void sendModelDownloaderDialog();
Q_INVOKABLE void sendResetContext(int conversationLength);
void sendDownloadStarted(const QString &model);
void sendDownloadCanceled(const QString &model);
void sendDownloadError(const QString &model, int code, const QString &errorString);
void sendDownloadFinished(const QString &model, bool success);
Q_INVOKABLE void sendSettingsDialog();
Q_INVOKABLE void sendNetworkToggled(bool active);
Q_INVOKABLE void sendSaveChatsToggled(bool active);
Q_INVOKABLE void sendNewChat(int count);
Q_INVOKABLE void sendRemoveChat();
Q_INVOKABLE void sendRenameChat();
Q_INVOKABLE void sendNonCompatHardware();
void sendChatStarted();
void sendRecalculatingContext(int conversationLength);
private Q_SLOTS:
void handleIpifyFinished();
void handleHealthFinished();
void handleJsonUploadFinished();
void handleSslErrors(QNetworkReply *reply, const QList<QSslError> &errors);
void handleMixpanelFinished();
private:
void sendHealth();
void sendIpify();
void sendMixpanelEvent(const QString &event, const QVector<KeyValue> &values = QVector<KeyValue>());
void sendMixpanel(const QByteArray &json, bool isOptOut = false);
bool packageAndSendJson(const QString &ingestId, const QString &json);
private:
bool m_shouldSendStartup;
bool m_isActive;
bool m_usageStatsActive;
QString m_ipify;
QString m_uniqueId;
QNetworkAccessManager m_networkManager;
QVector<QNetworkReply*> m_activeUploads;
private:
explicit Network();
~Network() {}
friend class MyNetwork;
};
#endif // LLM_H

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import QtCore
import QtQuick
import QtQuick.Controls
import QtQuick.Controls.Basic
import QtQuick.Layouts
import download
import network
import llm
Dialog {
id: abpoutDialog
anchors.centerIn: parent
modal: false
opacity: 0.9
padding: 20
width: 1024
height: column.height + 40
Theme {
id: theme
}
Column {
id: column
spacing: 20
Item {
width: childrenRect.width
height: childrenRect.height
Image {
id: img
anchors.top: parent.top
anchors.left: parent.left
width: 60
height: 60
source: "qrc:/gpt4all/icons/logo.svg"
}
Text {
anchors.left: img.right
anchors.leftMargin: 30
anchors.verticalCenter: img.verticalCenter
text: qsTr("About GPT4All")
color: theme.textColor
}
}
ScrollView {
clip: true
height: 200
width: 1024 - 40
ScrollBar.vertical.policy: ScrollBar.AlwaysOn
ScrollBar.horizontal.policy: ScrollBar.AlwaysOff
TextArea {
id: welcome
wrapMode: Text.Wrap
width: 1024 - 40
padding: 20
textFormat: TextEdit.MarkdownText
text: qsTr("### Release notes\n")
+ Download.releaseInfo.notes
+ qsTr("### Contributors\n")
+ Download.releaseInfo.contributors
color: theme.textColor
focus: false
readOnly: true
Accessible.role: Accessible.Paragraph
Accessible.name: qsTr("Release notes")
Accessible.description: qsTr("Release notes for this version")
background: Rectangle {
color: theme.backgroundLight
radius: 10
}
}
}
Label {
id: discordLink
width: parent.width
textFormat: Text.RichText
wrapMode: Text.WordWrap
text: qsTr("Check out our discord channel <a href=\"https://discord.gg/4M2QFmTt2k\">https://discord.gg/4M2QFmTt2k</a>")
onLinkActivated: { Qt.openUrlExternally("https://discord.gg/4M2QFmTt2k") }
color: theme.textColor
linkColor: theme.linkColor
Accessible.role: Accessible.Link
Accessible.name: qsTr("Discord link")
}
Label {
id: nomicProps
width: parent.width
textFormat: Text.RichText
wrapMode: Text.WordWrap
text: qsTr("Thank you to <a href=\"https://home.nomic.ai\">Nomic AI</a> and the community for contributing so much great data, code, ideas, and energy to the growing open source AI ecosystem!")
onLinkActivated: { Qt.openUrlExternally("https://home.nomic.ai") }
color: theme.textColor
linkColor: theme.linkColor
Accessible.role: Accessible.Paragraph
Accessible.name: qsTr("Thank you blurb")
Accessible.description: qsTr("Contains embedded link to https://home.nomic.ai")
}
}
background: Rectangle {
anchors.fill: parent
color: theme.backgroundDarkest
border.width: 1
border.color: theme.dialogBorder
radius: 10
}
}

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import QtCore
import QtQuick
import QtQuick.Controls
import QtQuick.Controls.Basic
import QtQuick.Layouts
import llm
import download
import network
Drawer {
id: chatDrawer
modal: false
opacity: 0.9
Theme {
id: theme
}
signal downloadClicked
signal aboutClicked
background: Rectangle {
height: parent.height
color: theme.backgroundDarkest
}
Item {
anchors.fill: parent
anchors.margins: 10
Accessible.role: Accessible.Pane
Accessible.name: qsTr("Drawer on the left of the application")
Accessible.description: qsTr("Drawer that is revealed by pressing the hamburger button")
Button {
id: newChat
anchors.left: parent.left
anchors.right: parent.right
padding: 15
font.pixelSize: theme.fontSizeLarger
background: Rectangle {
color: theme.backgroundDarkest
opacity: .5
border.color: theme.backgroundLightest
border.width: 1
radius: 10
}
contentItem: Text {
text: qsTr("New chat")
horizontalAlignment: Text.AlignHCenter
color: theme.textColor
Accessible.role: Accessible.Button
Accessible.name: text
Accessible.description: qsTr("Use this to launch an external application that will check for updates to the installer")
}
onClicked: {
LLM.chatListModel.addChat();
Network.sendNewChat(LLM.chatListModel.count)
}
}
ScrollView {
anchors.left: parent.left
anchors.right: parent.right
anchors.rightMargin: -10
anchors.topMargin: 10
anchors.top: newChat.bottom
anchors.bottom: checkForUpdatesButton.top
anchors.bottomMargin: 10
ScrollBar.vertical.policy: ScrollBar.AlwaysOn
ListView {
id: conversationList
anchors.fill: parent
anchors.rightMargin: 10
model: LLM.chatListModel
delegate: Rectangle {
id: chatRectangle
width: conversationList.width
height: chatName.height
opacity: 0.9
property bool isCurrent: LLM.chatListModel.currentChat === LLM.chatListModel.get(index)
property bool trashQuestionDisplayed: false
z: isCurrent ? 199 : 1
color: index % 2 === 0 ? theme.backgroundLight : theme.backgroundLighter
border.width: isCurrent
border.color: chatName.readOnly ? theme.assistantColor : theme.userColor
TextField {
id: chatName
anchors.left: parent.left
anchors.right: buttons.left
color: theme.textColor
padding: 15
focus: false
readOnly: true
wrapMode: Text.NoWrap
hoverEnabled: false // Disable hover events on the TextArea
selectByMouse: false // Disable text selection in the TextArea
font.pixelSize: theme.fontSizeLarger
text: readOnly ? metrics.elidedText : name
horizontalAlignment: TextInput.AlignLeft
opacity: trashQuestionDisplayed ? 0.5 : 1.0
TextMetrics {
id: metrics
font: chatName.font
text: name
elide: Text.ElideRight
elideWidth: chatName.width - 25
}
background: Rectangle {
color: "transparent"
}
onEditingFinished: {
// Work around a bug in qml where we're losing focus when the whole window
// goes out of focus even though this textfield should be marked as not
// having focus
if (chatName.readOnly)
return;
changeName();
Network.sendRenameChat()
}
function changeName() {
LLM.chatListModel.get(index).name = chatName.text
chatName.focus = false
chatName.readOnly = true
chatName.selectByMouse = false
}
TapHandler {
onTapped: {
if (isCurrent)
return;
LLM.chatListModel.currentChat = LLM.chatListModel.get(index);
}
}
Accessible.role: Accessible.Button
Accessible.name: qsTr("Select the current chat")
Accessible.description: qsTr("Provides a button to select the current chat or edit the chat when in edit mode")
}
Row {
id: buttons
anchors.verticalCenter: chatName.verticalCenter
anchors.right: chatRectangle.right
anchors.rightMargin: 10
spacing: 10
Button {
id: editButton
width: 30
height: 30
visible: isCurrent
opacity: trashQuestionDisplayed ? 0.5 : 1.0
background: Image {
width: 30
height: 30
source: "qrc:/gpt4all/icons/edit.svg"
}
onClicked: {
chatName.focus = true
chatName.readOnly = false
chatName.selectByMouse = true
}
Accessible.role: Accessible.Button
Accessible.name: qsTr("Edit the chat name")
Accessible.description: qsTr("Provides a button to edit the chat name")
}
Button {
id: c
width: 30
height: 30
visible: isCurrent
background: Image {
width: 30
height: 30
source: "qrc:/gpt4all/icons/trash.svg"
}
onClicked: {
trashQuestionDisplayed = true
timer.start()
}
Accessible.role: Accessible.Button
Accessible.name: qsTr("Delete of the chat")
Accessible.description: qsTr("Provides a button to delete the chat")
}
}
Rectangle {
id: trashSureQuestion
anchors.top: buttons.bottom
anchors.topMargin: 10
anchors.right: buttons.right
width: childrenRect.width
height: childrenRect.height
color: chatRectangle.color
visible: isCurrent && trashQuestionDisplayed
opacity: 1.0
radius: 10
z: 200
Row {
spacing: 10
Button {
id: checkMark
width: 30
height: 30
contentItem: Text {
color: theme.textErrorColor
text: "\u2713"
font.pixelSize: theme.fontSizeLarger
horizontalAlignment: Text.AlignHCenter
verticalAlignment: Text.AlignVCenter
}
background: Rectangle {
width: 30
height: 30
color: "transparent"
}
onClicked: {
LLM.chatListModel.removeChat(LLM.chatListModel.get(index))
Network.sendRemoveChat()
}
Accessible.role: Accessible.Button
Accessible.name: qsTr("Confirm delete of the chat")
Accessible.description: qsTr("Provides a button to confirm delete of the chat")
}
Button {
id: cancel
width: 30
height: 30
contentItem: Text {
color: theme.textColor
text: "\u2715"
font.pixelSize: theme.fontSizeLarger
horizontalAlignment: Text.AlignHCenter
verticalAlignment: Text.AlignVCenter
}
background: Rectangle {
width: 30
height: 30
color: "transparent"
}
onClicked: {
trashQuestionDisplayed = false
}
Accessible.role: Accessible.Button
Accessible.name: qsTr("Cancel the delete of the chat")
Accessible.description: qsTr("Provides a button to cancel delete of the chat")
}
}
}
Timer {
id: timer
interval: 3000; running: false; repeat: false
onTriggered: trashQuestionDisplayed = false
}
}
Accessible.role: Accessible.List
Accessible.name: qsTr("List of chats")
Accessible.description: qsTr("List of chats in the drawer dialog")
}
}
Button {
id: checkForUpdatesButton
anchors.left: parent.left
anchors.right: parent.right
anchors.bottom: downloadButton.top
anchors.bottomMargin: 10
padding: 15
contentItem: Text {
text: qsTr("Updates")
horizontalAlignment: Text.AlignHCenter
color: theme.textColor
Accessible.role: Accessible.Button
Accessible.name: text
Accessible.description: qsTr("Use this to launch an external application that will check for updates to the installer")
}
background: Rectangle {
opacity: .5
border.color: theme.backgroundLightest
border.width: 1
radius: 10
color: theme.backgroundLight
}
onClicked: {
if (!LLM.checkForUpdates())
checkForUpdatesError.open()
}
}
Button {
id: downloadButton
anchors.left: parent.left
anchors.right: parent.right
anchors.bottom: aboutButton.top
anchors.bottomMargin: 10
padding: 15
contentItem: Text {
text: qsTr("Downloads")
horizontalAlignment: Text.AlignHCenter
color: theme.textColor
Accessible.role: Accessible.Button
Accessible.name: text
Accessible.description: qsTr("Use this to launch a dialog to download new models")
}
background: Rectangle {
opacity: .5
border.color: theme.backgroundLightest
border.width: 1
radius: 10
color: theme.backgroundLight
}
onClicked: {
downloadClicked()
}
}
Button {
id: aboutButton
anchors.left: parent.left
anchors.right: parent.right
anchors.bottom: parent.bottom
padding: 15
contentItem: Text {
text: qsTr("About")
horizontalAlignment: Text.AlignHCenter
color: theme.textColor
Accessible.role: Accessible.Button
Accessible.name: text
Accessible.description: qsTr("Use this to launch a dialog to show the about page")
}
background: Rectangle {
opacity: .5
border.color: theme.backgroundLightest
border.width: 1
radius: 10
color: theme.backgroundLight
}
onClicked: {
aboutClicked()
}
}
}
}

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import QtCore
import QtQuick
import QtQuick.Controls
import QtQuick.Controls.Basic
import QtQuick.Dialogs
import QtQuick.Layouts
import download
import llm
import network
Dialog {
id: modelDownloaderDialog
modal: true
opacity: 0.9
closePolicy: LLM.chatListModel.currentChat.modelList.length === 0 ? Popup.NoAutoClose : (Popup.CloseOnEscape | Popup.CloseOnPressOutside)
background: Rectangle {
anchors.fill: parent
anchors.margins: -20
color: theme.backgroundDarkest
border.width: 1
border.color: theme.dialogBorder
radius: 10
}
onOpened: {
Network.sendModelDownloaderDialog();
}
property string defaultModelPath: Download.defaultLocalModelsPath()
property alias modelPath: settings.modelPath
Settings {
id: settings
property string modelPath: modelDownloaderDialog.defaultModelPath
}
Component.onCompleted: {
Download.downloadLocalModelsPath = settings.modelPath
}
Component.onDestruction: {
settings.sync()
}
ColumnLayout {
anchors.fill: parent
anchors.margins: 20
spacing: 30
Label {
id: listLabel
text: "Available Models:"
Layout.alignment: Qt.AlignLeft
Layout.fillWidth: true
color: theme.textColor
}
ScrollView {
id: scrollView
ScrollBar.vertical.policy: ScrollBar.AlwaysOn
Layout.fillWidth: true
Layout.fillHeight: true
clip: true
ListView {
id: modelList
model: Download.modelList
boundsBehavior: Flickable.StopAtBounds
delegate: Item {
id: delegateItem
width: modelList.width
height: modelName.height + modelName.padding
+ description.height + description.padding
objectName: "delegateItem"
property bool downloading: false
Rectangle {
anchors.fill: parent
color: index % 2 === 0 ? theme.backgroundLight : theme.backgroundLighter
}
Text {
id: modelName
objectName: "modelName"
property string filename: modelData.filename
text: filename.slice(5, filename.length - 4)
padding: 20
anchors.top: parent.top
anchors.left: parent.left
font.bold: modelData.isDefault || modelData.bestGPTJ || modelData.bestLlama || modelData.bestMPT
color: theme.assistantColor
Accessible.role: Accessible.Paragraph
Accessible.name: qsTr("Model file")
Accessible.description: qsTr("Model file to be downloaded")
}
Text {
id: description
text: " - " + modelData.description
leftPadding: 20
rightPadding: 20
anchors.top: modelName.bottom
anchors.left: modelName.left
anchors.right: parent.right
wrapMode: Text.WordWrap
color: theme.textColor
Accessible.role: Accessible.Paragraph
Accessible.name: qsTr("Description")
Accessible.description: qsTr("The description of the file")
}
Text {
id: isDefault
text: qsTr("(default)")
visible: modelData.isDefault
anchors.top: modelName.top
anchors.left: modelName.right
padding: 20
color: theme.textColor
Accessible.role: Accessible.Paragraph
Accessible.name: qsTr("Default file")
Accessible.description: qsTr("Whether the file is the default model")
}
Text {
text: modelData.filesize
anchors.top: modelName.top
anchors.left: isDefault.visible ? isDefault.right : modelName.right
padding: 20
color: theme.textColor
Accessible.role: Accessible.Paragraph
Accessible.name: qsTr("File size")
Accessible.description: qsTr("The size of the file")
}
Label {
id: speedLabel
anchors.top: modelName.top
anchors.right: itemProgressBar.left
padding: 20
objectName: "speedLabel"
color: theme.textColor
text: ""
visible: downloading
Accessible.role: Accessible.Paragraph
Accessible.name: qsTr("Download speed")
Accessible.description: qsTr("Download speed in bytes/kilobytes/megabytes per second")
}
ProgressBar {
id: itemProgressBar
objectName: "itemProgressBar"
anchors.top: modelName.top
anchors.right: downloadButton.left
anchors.topMargin: 20
anchors.rightMargin: 20
width: 100
visible: downloading
background: Rectangle {
implicitWidth: 200
implicitHeight: 30
color: theme.backgroundDarkest
radius: 3
}
contentItem: Item {
implicitWidth: 200
implicitHeight: 25
Rectangle {
width: itemProgressBar.visualPosition * parent.width
height: parent.height
radius: 2
color: theme.assistantColor
}
}
Accessible.role: Accessible.ProgressBar
Accessible.name: qsTr("Download progressBar")
Accessible.description: qsTr("Shows the progress made in the download")
}
Item {
visible: modelData.calcHash
anchors.top: modelName.top
anchors.right: parent.right
Label {
id: calcHashLabel
anchors.right: busyCalcHash.left
padding: 20
objectName: "calcHashLabel"
color: theme.textColor
text: qsTr("Calculating MD5...")
Accessible.role: Accessible.Paragraph
Accessible.name: text
Accessible.description: qsTr("Whether the file hash is being calculated")
}
BusyIndicator {
id: busyCalcHash
anchors.right: parent.right
padding: 20
running: modelData.calcHash
Accessible.role: Accessible.Animation
Accessible.name: qsTr("Busy indicator")
Accessible.description: qsTr("Displayed when the file hash is being calculated")
}
}
Label {
id: installedLabel
anchors.top: modelName.top
anchors.right: parent.right
padding: 20
objectName: "installedLabel"
color: theme.textColor
text: qsTr("Already installed")
visible: modelData.installed
Accessible.role: Accessible.Paragraph
Accessible.name: text
Accessible.description: qsTr("Whether the file is already installed on your system")
}
Button {
id: downloadButton
contentItem: Text {
color: theme.textColor
text: downloading ? "Cancel" : "Download"
}
anchors.top: modelName.top
anchors.right: parent.right
anchors.topMargin: 15
anchors.rightMargin: 20
visible: !modelData.installed && !modelData.calcHash
onClicked: {
if (!downloading) {
downloading = true;
Download.downloadModel(modelData.filename);
} else {
downloading = false;
Download.cancelDownload(modelData.filename);
}
}
background: Rectangle {
opacity: .5
border.color: theme.backgroundLightest
border.width: 1
radius: 10
color: theme.backgroundLight
}
Accessible.role: Accessible.Button
Accessible.name: text
Accessible.description: qsTr("Cancel/Download button to stop/start the download")
}
}
Component.onCompleted: {
Download.downloadProgress.connect(updateProgress);
Download.downloadFinished.connect(resetProgress);
}
property var lastUpdate: ({})
function updateProgress(bytesReceived, bytesTotal, modelName) {
let currentTime = new Date().getTime();
for (let i = 0; i < modelList.contentItem.children.length; i++) {
let delegateItem = modelList.contentItem.children[i];
if (delegateItem.objectName === "delegateItem") {
let modelNameText = delegateItem.children.find(child => child.objectName === "modelName").filename;
if (modelNameText === modelName) {
let progressBar = delegateItem.children.find(child => child.objectName === "itemProgressBar");
progressBar.value = bytesReceived / bytesTotal;
// Calculate the download speed
if (lastUpdate[modelName] && lastUpdate[modelName].timestamp) {
let timeDifference = currentTime - lastUpdate[modelName].timestamp;
let bytesDifference = bytesReceived - lastUpdate[modelName].bytesReceived;
let speed = (bytesDifference / timeDifference) * 1000; // bytes per second
delegateItem.downloading = true
// Update the speed label
let speedLabel = delegateItem.children.find(child => child.objectName === "speedLabel");
if (speed < 1024) {
speedLabel.text = speed.toFixed(2) + " B/s";
} else if (speed < 1024 * 1024) {
speedLabel.text = (speed / 1024).toFixed(2) + " KB/s";
} else {
speedLabel.text = (speed / (1024 * 1024)).toFixed(2) + " MB/s";
}
}
// Update the lastUpdate object for the current model
lastUpdate[modelName] = {"timestamp": currentTime, "bytesReceived": bytesReceived};
break;
}
}
}
}
function resetProgress(modelName) {
for (let i = 0; i < modelList.contentItem.children.length; i++) {
let delegateItem = modelList.contentItem.children[i];
if (delegateItem.objectName === "delegateItem") {
let modelNameText = delegateItem.children.find(child => child.objectName === "modelName").filename;
if (modelNameText === modelName) {
let progressBar = delegateItem.children.find(child => child.objectName === "itemProgressBar");
progressBar.value = 0;
delegateItem.downloading = false;
// Remove speed label text
let speedLabel = delegateItem.children.find(child => child.objectName === "speedLabel");
speedLabel.text = "";
// Remove the lastUpdate object for the canceled model
delete lastUpdate[modelName];
break;
}
}
}
}
}
}
RowLayout {
Layout.alignment: Qt.AlignCenter
Layout.fillWidth: true
spacing: 20
FolderDialog {
id: modelPathDialog
title: "Please choose a directory"
currentFolder: Download.downloadLocalModelsPath
onAccepted: {
Download.downloadLocalModelsPath = selectedFolder
settings.modelPath = Download.downloadLocalModelsPath
settings.sync()
}
}
Label {
id: modelPathLabel
text: qsTr("Download path:")
color: theme.textColor
Layout.row: 1
Layout.column: 0
}
TextField {
id: modelPathDisplayLabel
text: Download.downloadLocalModelsPath
readOnly: true
color: theme.textColor
Layout.fillWidth: true
ToolTip.text: qsTr("Path where model files will be downloaded to")
ToolTip.visible: hovered
Accessible.role: Accessible.ToolTip
Accessible.name: modelPathDisplayLabel.text
Accessible.description: ToolTip.text
background: Rectangle {
color: theme.backgroundLighter
radius: 10
}
}
Button {
text: qsTr("Browse")
contentItem: Text {
text: qsTr("Browse")
horizontalAlignment: Text.AlignHCenter
color: theme.textColor
Accessible.role: Accessible.Button
Accessible.name: text
Accessible.description: qsTr("Opens a folder picker dialog to choose where to save model files")
}
background: Rectangle {
opacity: .5
border.color: theme.backgroundLightest
border.width: 1
radius: 10
color: theme.backgroundLight
}
onClicked: modelPathDialog.open()
}
}
}
}

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import QtCore
import QtQuick
import QtQuick.Controls
import QtQuick.Controls.Basic
import QtQuick.Layouts
import download
import network
import llm
Dialog {
id: networkDialog
anchors.centerIn: parent
modal: true
opacity: 0.9
padding: 20
Theme {
id: theme
}
Settings {
id: settings
category: "network"
property string attribution: ""
}
Component.onDestruction: {
settings.sync()
}
Column {
id: column
spacing: 20
Item {
width: childrenRect.width
height: childrenRect.height
Image {
id: img
anchors.top: parent.top
anchors.left: parent.left
width: 60
height: 60
source: "qrc:/gpt4all/icons/logo.svg"
}
Text {
anchors.left: img.right
anchors.leftMargin: 30
anchors.verticalCenter: img.verticalCenter
text: qsTr("Contribute data to the GPT4All Opensource Datalake.")
color: theme.textColor
}
}
ScrollView {
clip: true
height: 300
width: 1024 - 40
ScrollBar.vertical.policy: ScrollBar.AlwaysOn
ScrollBar.horizontal.policy: ScrollBar.AlwaysOff
TextArea {
id: textOptIn
wrapMode: Text.Wrap
width: 1024 - 40
padding: 20
text: qsTr("By enabling this feature, you will be able to participate in the democratic process of training a large language model by contributing data for future model improvements.
When a GPT4All model responds to you and you have opted-in, your conversation will be sent to the GPT4All Open Source Datalake. Additionally, you can like/dislike its response. If you dislike a response, you can suggest an alternative response. This data will be collected and aggregated in the GPT4All Datalake.
NOTE: By turning on this feature, you will be sending your data to the GPT4All Open Source Datalake. You should have no expectation of chat privacy when this feature is enabled. You should; however, have an expectation of an optional attribution if you wish. Your chat data will be openly available for anyone to download and will be used by Nomic AI to improve future GPT4All models. Nomic AI will retain all attribution information attached to your data and you will be credited as a contributor to any GPT4All model release that uses your data!")
color: theme.textColor
focus: false
readOnly: true
Accessible.role: Accessible.Paragraph
Accessible.name: qsTr("Terms for opt-in")
Accessible.description: qsTr("Describes what will happen when you opt-in")
background: Rectangle {
color: theme.backgroundLight
radius: 10
}
}
}
TextField {
id: attribution
color: theme.textColor
padding: 20
width: parent.width
text: settings.attribution
font.pixelSize: theme.fontSizeLarge
placeholderText: qsTr("Please provide a name for attribution (optional)")
placeholderTextColor: theme.backgroundLightest
background: Rectangle {
color: theme.backgroundLighter
radius: 10
}
Accessible.role: Accessible.EditableText
Accessible.name: qsTr("Attribution (optional)")
Accessible.description: qsTr("Textfield for providing attribution")
onEditingFinished: {
settings.attribution = attribution.text;
settings.sync();
}
}
}
background: Rectangle {
anchors.fill: parent
color: theme.backgroundDarkest
border.width: 1
border.color: theme.dialogBorder
radius: 10
}
footer: DialogButtonBox {
id: dialogBox
padding: 20
alignment: Qt.AlignRight
spacing: 10
Button {
contentItem: Text {
color: theme.textColor
text: qsTr("Enable")
}
background: Rectangle {
border.color: theme.backgroundLightest
border.width: 1
radius: 10
color: theme.backgroundLight
}
Accessible.role: Accessible.Button
Accessible.name: text
Accessible.description: qsTr("Enable opt-in button")
padding: 15
DialogButtonBox.buttonRole: DialogButtonBox.AcceptRole
}
Button {
contentItem: Text {
color: theme.textColor
text: qsTr("Cancel")
}
background: Rectangle {
border.color: theme.backgroundLightest
border.width: 1
radius: 10
color: theme.backgroundLight
}
Accessible.role: Accessible.Button
Accessible.name: text
Accessible.description: qsTr("Cancel opt-in button")
padding: 15
DialogButtonBox.buttonRole: DialogButtonBox.RejectRole
}
background: Rectangle {
color: "transparent"
}
}
onAccepted: {
if (Network.isActive)
return
Network.isActive = true;
Network.sendNetworkToggled(true);
}
onRejected: {
if (!Network.isActive)
return
Network.isActive = false;
Network.sendNetworkToggled(false);
}
}

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import QtCore
import QtQuick
import QtQuick.Controls
import QtQuick.Controls.Basic
import QtQuick.Layouts
import download
import network
import llm
Dialog {
id: newVerionDialog
anchors.centerIn: parent
modal: true
opacity: 0.9
width: contentItem.width
height: contentItem.height
padding: 20
Theme {
id: theme
}
background: Rectangle {
anchors.fill: parent
color: theme.backgroundDarkest
border.width: 1
border.color: theme.dialogBorder
radius: 10
}
Item {
id: contentItem
width: childrenRect.width + 40
height: childrenRect.height + 40
Label {
id: label
anchors.top: parent.top
anchors.left: parent.left
topPadding: 20
bottomPadding: 20
text: qsTr("New version is available:")
color: theme.textColor
}
Button {
id: button
anchors.left: label.right
anchors.leftMargin: 10
anchors.verticalCenter: label.verticalCenter
padding: 20
contentItem: Text {
text: qsTr("Update")
horizontalAlignment: Text.AlignHCenter
color: theme.textColor
Accessible.role: Accessible.Button
Accessible.name: text
Accessible.description: qsTr("Use this to launch an external application that will check for updates to the installer")
}
background: Rectangle {
opacity: .5
border.color: theme.backgroundLightest
border.width: 1
radius: 10
color: theme.backgroundLight
}
onClicked: {
if (!LLM.checkForUpdates())
checkForUpdatesError.open()
}
}
}
}

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import QtCore
import QtQuick
import QtQuick.Controls
import QtQuick.Controls.Basic
import QtQuick.Layouts
Dialog {
id: popupDialog
anchors.centerIn: parent
opacity: 0.9
padding: 20
property alias text: textField.text
property bool shouldTimeOut: true
property bool shouldShowBusy: false
modal: shouldShowBusy
closePolicy: shouldShowBusy ? Popup.NoAutoClose : (Popup.CloseOnEscape | Popup.CloseOnPressOutside)
Theme {
id: theme
}
Row {
anchors.centerIn: parent
width: childrenRect.width
height: childrenRect.height
spacing: 20
Text {
id: textField
anchors.verticalCenter: busyIndicator.verticalCenter
horizontalAlignment: Text.AlignJustify
color: theme.textColor
Accessible.role: Accessible.HelpBalloon
Accessible.name: text
Accessible.description: qsTr("Reveals a shortlived help balloon")
}
BusyIndicator {
id: busyIndicator
visible: shouldShowBusy
running: shouldShowBusy
Accessible.role: Accessible.Animation
Accessible.name: qsTr("Busy indicator")
Accessible.description: qsTr("Displayed when the popup is showing busy")
}
}
background: Rectangle {
anchors.fill: parent
color: theme.backgroundDarkest
border.width: 1
border.color: theme.dialogBorder
radius: 10
}
exit: Transition {
NumberAnimation { duration: 500; property: "opacity"; from: 1.0; to: 0.0 }
}
onOpened: {
if (shouldTimeOut)
timer.start()
}
Timer {
id: timer
interval: 500; running: false; repeat: false
onTriggered: popupDialog.close()
}
}

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import QtCore
import QtQuick
import QtQuick.Controls
import QtQuick.Controls.Basic
import QtQuick.Dialogs
import QtQuick.Layouts
import download
import network
import llm
Dialog {
id: settingsDialog
modal: true
opacity: 0.9
background: Rectangle {
anchors.fill: parent
anchors.margins: -20
color: theme.backgroundDarkest
border.width: 1
border.color: theme.dialogBorder
radius: 10
}
onOpened: {
Network.sendSettingsDialog();
}
property var currentChat: LLM.chatListModel.currentChat
Theme {
id: theme
}
property real defaultTemperature: 0.28
property real defaultTopP: 0.95
property int defaultTopK: 40
property int defaultMaxLength: 4096
property int defaultPromptBatchSize: 9
property real defaultRepeatPenalty: 1.10
property int defaultRepeatPenaltyTokens: 64
property int defaultThreadCount: 0
property bool defaultSaveChats: false
property string defaultPromptTemplate: "### Human:
%1
### Assistant:\n"
property string defaultModelPath: Download.defaultLocalModelsPath()
property string defaultUserDefaultModel: "Application default"
property alias temperature: settings.temperature
property alias topP: settings.topP
property alias topK: settings.topK
property alias maxLength: settings.maxLength
property alias promptBatchSize: settings.promptBatchSize
property alias promptTemplate: settings.promptTemplate
property alias repeatPenalty: settings.repeatPenalty
property alias repeatPenaltyTokens: settings.repeatPenaltyTokens
property alias threadCount: settings.threadCount
property alias saveChats: settings.saveChats
property alias modelPath: settings.modelPath
property alias userDefaultModel: settings.userDefaultModel
Settings {
id: settings
property real temperature: settingsDialog.defaultTemperature
property real topP: settingsDialog.defaultTopP
property int topK: settingsDialog.defaultTopK
property int maxLength: settingsDialog.defaultMaxLength
property int promptBatchSize: settingsDialog.defaultPromptBatchSize
property int threadCount: settingsDialog.defaultThreadCount
property bool saveChats: settingsDialog.defaultSaveChats
property real repeatPenalty: settingsDialog.defaultRepeatPenalty
property int repeatPenaltyTokens: settingsDialog.defaultRepeatPenaltyTokens
property string promptTemplate: settingsDialog.defaultPromptTemplate
property string modelPath: settingsDialog.defaultModelPath
property string userDefaultModel: settingsDialog.defaultUserDefaultModel
}
function restoreGenerationDefaults() {
settings.temperature = defaultTemperature
settings.topP = defaultTopP
settings.topK = defaultTopK
settings.maxLength = defaultMaxLength
settings.promptBatchSize = defaultPromptBatchSize
settings.promptTemplate = defaultPromptTemplate
settings.repeatPenalty = defaultRepeatPenalty
settings.repeatPenaltyTokens = defaultRepeatPenaltyTokens
settings.sync()
}
function restoreApplicationDefaults() {
settings.modelPath = settingsDialog.defaultModelPath
settings.threadCount = defaultThreadCount
settings.saveChats = defaultSaveChats
settings.userDefaultModel = defaultUserDefaultModel
Download.downloadLocalModelsPath = settings.modelPath
LLM.threadCount = settings.threadCount
LLM.chatListModel.shouldSaveChats = settings.saveChats
settings.sync()
}
Component.onCompleted: {
LLM.threadCount = settings.threadCount
LLM.chatListModel.shouldSaveChats = settings.saveChats
Download.downloadLocalModelsPath = settings.modelPath
}
Connections {
target: settingsDialog
function onClosed() {
settings.sync()
}
}
Item {
Accessible.role: Accessible.Dialog
Accessible.name: qsTr("Settings dialog")
Accessible.description: qsTr("Dialog containing various application settings")
}
TabBar {
id: settingsTabBar
width: parent.width / 1.5
TabButton {
id: genSettingsButton
contentItem: IconLabel {
color: theme.textColor
font.bold: genSettingsButton.checked
font.pixelSize: genSettingsButton.checked ? theme.fontSizeLarger : theme.fontSizeLarge
text: qsTr("Generation")
}
background: Rectangle {
color: genSettingsButton.checked ? theme.backgroundDarkest : theme.backgroundLight
border.color: theme.tabBorder
border.width: 1 ? genSettingsButton.checked : 0
}
Accessible.role: Accessible.Button
Accessible.name: qsTr("Generation settings")
Accessible.description: qsTr("Settings related to how the model generates text")
}
TabButton {
id: appSettingsButton
contentItem: IconLabel {
color: theme.textColor
font.bold: appSettingsButton.checked
font.pixelSize: appSettingsButton.checked ? theme.fontSizeLarger : theme.fontSizeLarge
text: qsTr("Application")
}
background: Rectangle {
color: appSettingsButton.checked ? theme.backgroundDarkest : theme.backgroundLight
border.color: theme.tabBorder
border.width: 1 ? appSettingsButton.checked : 0
}
Accessible.role: Accessible.Button
Accessible.name: qsTr("Application settings")
Accessible.description: qsTr("Settings related to general behavior of the application")
}
}
StackLayout {
anchors.top: settingsTabBar.bottom
width: parent.width
height: availableHeight
currentIndex: settingsTabBar.currentIndex
Item {
id: generationSettingsTab
ScrollView {
background: Rectangle {
color: 'transparent'
border.color: theme.tabBorder
border.width: 1
radius: 2
}
padding: 10
width: parent.width
height: parent.height - 30
contentWidth: availableWidth - 20
contentHeight: generationSettingsTabInner.implicitHeight + 40
ScrollBar.vertical.policy: ScrollBar.AlwaysOn
GridLayout {
id: generationSettingsTabInner
anchors.margins: 10
columns: 2
rowSpacing: 10
columnSpacing: 10
anchors.fill: parent
Label {
id: tempLabel
text: qsTr("Temperature:")
color: theme.textColor
Layout.row: 0
Layout.column: 0
}
TextField {
text: settings.temperature.toString()
color: theme.textColor
background: Rectangle {
implicitWidth: 150
color: theme.backgroundLighter
radius: 10
}
padding: 10
ToolTip.text: qsTr("Temperature increases the chances of choosing less likely tokens - higher temperature gives more creative but less predictable outputs")
ToolTip.visible: hovered
Layout.row: 0
Layout.column: 1
validator: DoubleValidator {
locale: "C"
}
onEditingFinished: {
var val = parseFloat(text)
if (!isNaN(val)) {
settings.temperature = val
settings.sync()
focus = false
} else {
text = settings.temperature.toString()
}
}
Accessible.role: Accessible.EditableText
Accessible.name: tempLabel.text
Accessible.description: ToolTip.text
}
Label {
id: topPLabel
text: qsTr("Top P:")
color: theme.textColor
Layout.row: 1
Layout.column: 0
}
TextField {
text: settings.topP.toString()
color: theme.textColor
background: Rectangle {
implicitWidth: 150
color: theme.backgroundLighter
radius: 10
}
padding: 10
ToolTip.text: qsTr("Only the most likely tokens up to a total probability of top_p can be chosen, prevents choosing highly unlikely tokens, aka Nucleus Sampling")
ToolTip.visible: hovered
Layout.row: 1
Layout.column: 1
validator: DoubleValidator {
locale: "C"
}
onEditingFinished: {
var val = parseFloat(text)
if (!isNaN(val)) {
settings.topP = val
settings.sync()
focus = false
} else {
text = settings.topP.toString()
}
}
Accessible.role: Accessible.EditableText
Accessible.name: topPLabel.text
Accessible.description: ToolTip.text
}
Label {
id: topKLabel
text: qsTr("Top K:")
color: theme.textColor
Layout.row: 2
Layout.column: 0
}
TextField {
text: settings.topK.toString()
color: theme.textColor
background: Rectangle {
implicitWidth: 150
color: theme.backgroundLighter
radius: 10
}
padding: 10
ToolTip.text: qsTr("Only the top K most likely tokens will be chosen from")
ToolTip.visible: hovered
Layout.row: 2
Layout.column: 1
validator: IntValidator {
bottom: 1
}
onEditingFinished: {
var val = parseInt(text)
if (!isNaN(val)) {
settings.topK = val
settings.sync()
focus = false
} else {
text = settings.topK.toString()
}
}
Accessible.role: Accessible.EditableText
Accessible.name: topKLabel.text
Accessible.description: ToolTip.text
}
Label {
id: maxLengthLabel
text: qsTr("Max Length:")
color: theme.textColor
Layout.row: 3
Layout.column: 0
}
TextField {
text: settings.maxLength.toString()
color: theme.textColor
background: Rectangle {
implicitWidth: 150
color: theme.backgroundLighter
radius: 10
}
padding: 10
ToolTip.text: qsTr("Maximum length of response in tokens")
ToolTip.visible: hovered
Layout.row: 3
Layout.column: 1
validator: IntValidator {
bottom: 1
}
onEditingFinished: {
var val = parseInt(text)
if (!isNaN(val)) {
settings.maxLength = val
settings.sync()
focus = false
} else {
text = settings.maxLength.toString()
}
}
Accessible.role: Accessible.EditableText
Accessible.name: maxLengthLabel.text
Accessible.description: ToolTip.text
}
Label {
id: batchSizeLabel
text: qsTr("Prompt Batch Size:")
color: theme.textColor
Layout.row: 4
Layout.column: 0
}
TextField {
text: settings.promptBatchSize.toString()
color: theme.textColor
background: Rectangle {
implicitWidth: 150
color: theme.backgroundLighter
radius: 10
}
padding: 10
ToolTip.text: qsTr("Amount of prompt tokens to process at once, higher values can speed up reading prompts but will use more RAM")
ToolTip.visible: hovered
Layout.row: 4
Layout.column: 1
validator: IntValidator {
bottom: 1
}
onEditingFinished: {
var val = parseInt(text)
if (!isNaN(val)) {
settings.promptBatchSize = val
settings.sync()
focus = false
} else {
text = settings.promptBatchSize.toString()
}
}
Accessible.role: Accessible.EditableText
Accessible.name: batchSizeLabel.text
Accessible.description: ToolTip.text
}
Label {
id: repeatPenaltyLabel
text: qsTr("Repeat Penalty:")
color: theme.textColor
Layout.row: 5
Layout.column: 0
}
TextField {
text: settings.repeatPenalty.toString()
color: theme.textColor
background: Rectangle {
implicitWidth: 150
color: theme.backgroundLighter
radius: 10
}
padding: 10
ToolTip.text: qsTr("Amount to penalize repetitiveness of the output")
ToolTip.visible: hovered
Layout.row: 5
Layout.column: 1
validator: DoubleValidator {
locale: "C"
}
onEditingFinished: {
var val = parseFloat(text)
if (!isNaN(val)) {
settings.repeatPenalty = val
settings.sync()
focus = false
} else {
text = settings.repeatPenalty.toString()
}
}
Accessible.role: Accessible.EditableText
Accessible.name: repeatPenaltyLabel.text
Accessible.description: ToolTip.text
}
Label {
id: repeatPenaltyTokensLabel
text: qsTr("Repeat Penalty Tokens:")
color: theme.textColor
Layout.row: 6
Layout.column: 0
}
TextField {
text: settings.repeatPenaltyTokens.toString()
color: theme.textColor
background: Rectangle {
implicitWidth: 150
color: theme.backgroundLighter
radius: 10
}
padding: 10
ToolTip.text: qsTr("How far back in output to apply repeat penalty")
ToolTip.visible: hovered
Layout.row: 6
Layout.column: 1
validator: IntValidator {
bottom: 1
}
onEditingFinished: {
var val = parseInt(text)
if (!isNaN(val)) {
settings.repeatPenaltyTokens = val
settings.sync()
focus = false
} else {
text = settings.repeatPenaltyTokens.toString()
}
}
Accessible.role: Accessible.EditableText
Accessible.name: repeatPenaltyTokensLabel.text
Accessible.description: ToolTip.text
}
Label {
id: promptTemplateLabel
text: qsTr("Prompt Template:")
color: theme.textColor
Layout.row: 7
Layout.column: 0
}
Rectangle {
Layout.row: 7
Layout.column: 1
Layout.fillWidth: true
height: 200
color: "transparent"
clip: true
Label {
id: promptTemplateLabelHelp
visible: settings.promptTemplate.indexOf(
"%1") === -1
font.bold: true
color: theme.textErrorColor
text: qsTr("Prompt template must contain %1 to be replaced with the user's input.")
anchors.fill: templateScrollView
z: 200
padding: 10
wrapMode: TextArea.Wrap
Accessible.role: Accessible.EditableText
Accessible.name: text
}
ScrollView {
id: templateScrollView
anchors.fill: parent
TextArea {
text: settings.promptTemplate
color: theme.textColor
background: Rectangle {
implicitWidth: 150
color: theme.backgroundLighter
radius: 10
}
padding: 10
wrapMode: TextArea.Wrap
onTextChanged: {
settings.promptTemplate = text
settings.sync()
}
bottomPadding: 10
Accessible.role: Accessible.EditableText
Accessible.name: promptTemplateLabel.text
Accessible.description: promptTemplateLabelHelp.text
}
}
}
Button {
Layout.row: 8
Layout.column: 1
Layout.fillWidth: true
padding: 10
contentItem: Text {
text: qsTr("Restore Defaults")
horizontalAlignment: Text.AlignHCenter
color: theme.textColor
Accessible.role: Accessible.Button
Accessible.name: text
Accessible.description: qsTr("Restores the settings dialog to a default state")
}
background: Rectangle {
opacity: .5
border.color: theme.backgroundLightest
border.width: 1
radius: 10
color: theme.backgroundLight
}
onClicked: {
settingsDialog.restoreGenerationDefaults()
}
}
}
}
}
Item {
id: applicationSettingsTab
ScrollView {
background: Rectangle {
color: 'transparent'
border.color: theme.tabBorder
border.width: 1
radius: 2
}
padding: 10
width: parent.width
height: parent.height - 30
contentWidth: availableWidth - 20
ScrollBar.vertical.policy: ScrollBar.AlwaysOn
GridLayout {
anchors.margins: 10
columns: 3
rowSpacing: 10
columnSpacing: 10
anchors.fill: parent
Label {
id: defaultModelLabel
text: qsTr("Default model:")
color: theme.textColor
Layout.row: 1
Layout.column: 0
}
ComboBox {
id: comboBox
Layout.row: 1
Layout.column: 1
Layout.minimumWidth: 350
font.pixelSize: theme.fontSizeLarge
spacing: 0
padding: 10
model: modelList
Accessible.role: Accessible.ComboBox
Accessible.name: qsTr("ComboBox for displaying/picking the default model")
Accessible.description: qsTr("Use this for picking the default model to use; the first item is the current default model")
function updateModel(newModelList) {
var newArray = Array.from(newModelList);
newArray.unshift('Application default');
comboBox.model = newArray;
settings.sync();
comboBox.currentIndex = comboBox.indexOfValue(settingsDialog.userDefaultModel);
}
Component.onCompleted: {
comboBox.updateModel(currentChat.modelList)
}
Connections {
target: settings
function onUserDefaultModelChanged() {
comboBox.updateModel(currentChat.modelList)
}
}
Connections {
target: currentChat
function onModelListChanged() {
comboBox.updateModel(currentChat.modelList)
}
}
contentItem: Text {
anchors.horizontalCenter: parent.horizontalCenter
leftPadding: 10
rightPadding: 10
text: comboBox.displayText
font: comboBox.font
color: theme.textColor
verticalAlignment: Text.AlignVCenter
horizontalAlignment: Text.AlignHCenter
elide: Text.ElideRight
}
delegate: ItemDelegate {
width: comboBox.width
contentItem: Text {
text: modelData
color: theme.textColor
font: comboBox.font
elide: Text.ElideRight
verticalAlignment: Text.AlignVCenter
}
background: Rectangle {
color: highlighted ? theme.backgroundLight : theme.backgroundDark
}
highlighted: comboBox.highlightedIndex === index
}
popup: Popup {
y: comboBox.height - 1
width: comboBox.width
implicitHeight: contentItem.implicitHeight
padding: 0
contentItem: ListView {
clip: true
implicitHeight: contentHeight
model: comboBox.popup.visible ? comboBox.delegateModel : null
currentIndex: comboBox.highlightedIndex
ScrollIndicator.vertical: ScrollIndicator { }
}
background: Rectangle {
color: theme.backgroundDark
}
}
background: Rectangle {
color: theme.backgroundDark
border.width: 1
border.color: theme.backgroundLightest
radius: 10
}
onActivated: {
settingsDialog.userDefaultModel = comboBox.currentText
settings.sync()
}
}
FolderDialog {
id: modelPathDialog
title: "Please choose a directory"
currentFolder: Download.downloadLocalModelsPath
onAccepted: {
Download.downloadLocalModelsPath = selectedFolder
settings.modelPath = Download.downloadLocalModelsPath
settings.sync()
}
}
Label {
id: modelPathLabel
text: qsTr("Download path:")
color: theme.textColor
Layout.row: 2
Layout.column: 0
}
TextField {
id: modelPathDisplayLabel
text: Download.downloadLocalModelsPath
readOnly: true
color: theme.textColor
implicitWidth: 300
padding: 10
Layout.row: 2
Layout.column: 1
Layout.fillWidth: true
ToolTip.text: qsTr("Path where model files will be downloaded to")
ToolTip.visible: hovered
Accessible.role: Accessible.ToolTip
Accessible.name: modelPathDisplayLabel.text
Accessible.description: ToolTip.text
background: Rectangle {
color: theme.backgroundLighter
radius: 10
}
}
Button {
Layout.row: 2
Layout.column: 2
text: qsTr("Browse")
contentItem: Text {
text: qsTr("Browse")
horizontalAlignment: Text.AlignHCenter
color: theme.textColor
Accessible.role: Accessible.Button
Accessible.name: text
Accessible.description: qsTr("Opens a folder picker dialog to choose where to save model files")
}
background: Rectangle {
opacity: .5
border.color: theme.backgroundLightest
border.width: 1
radius: 10
color: theme.backgroundLight
}
onClicked: modelPathDialog.open()
}
Label {
id: nThreadsLabel
text: qsTr("CPU Threads:")
color: theme.textColor
Layout.row: 3
Layout.column: 0
}
TextField {
text: settingsDialog.threadCount.toString()
color: theme.textColor
background: Rectangle {
implicitWidth: 150
color: theme.backgroundLighter
radius: 10
}
padding: 10
ToolTip.text: qsTr("Amount of processing threads to use, a setting of 0 will use the lesser of 4 or your number of CPU threads")
ToolTip.visible: hovered
Layout.row: 3
Layout.column: 1
validator: IntValidator {
bottom: 1
}
onEditingFinished: {
var val = parseInt(text)
if (!isNaN(val)) {
settingsDialog.threadCount = val
LLM.threadCount = val
settings.sync()
focus = false
} else {
text = settingsDialog.threadCount.toString()
}
}
Accessible.role: Accessible.EditableText
Accessible.name: nThreadsLabel.text
Accessible.description: ToolTip.text
}
Label {
id: saveChatsLabel
text: qsTr("Save chats to disk:")
color: theme.textColor
Layout.row: 4
Layout.column: 0
}
CheckBox {
id: saveChatsBox
Layout.row: 4
Layout.column: 1
checked: settingsDialog.saveChats
onClicked: {
Network.sendSaveChatsToggled(saveChatsBox.checked);
settingsDialog.saveChats = saveChatsBox.checked
LLM.chatListModel.shouldSaveChats = saveChatsBox.checked
settings.sync()
}
ToolTip.text: qsTr("WARNING: Saving chats to disk can be ~2GB per chat")
ToolTip.visible: hovered
background: Rectangle {
color: "transparent"
}
indicator: Rectangle {
implicitWidth: 26
implicitHeight: 26
x: saveChatsBox.leftPadding
y: parent.height / 2 - height / 2
border.color: theme.dialogBorder
color: "transparent"
Rectangle {
width: 14
height: 14
x: 6
y: 6
color: theme.textColor
visible: saveChatsBox.checked
}
}
contentItem: Text {
text: saveChatsBox.text
font: saveChatsBox.font
opacity: enabled ? 1.0 : 0.3
color: theme.textColor
verticalAlignment: Text.AlignVCenter
leftPadding: saveChatsBox.indicator.width + saveChatsBox.spacing
}
}
Button {
Layout.row: 5
Layout.column: 1
Layout.fillWidth: true
padding: 10
contentItem: Text {
text: qsTr("Restore Defaults")
horizontalAlignment: Text.AlignHCenter
color: theme.textColor
Accessible.role: Accessible.Button
Accessible.name: text
Accessible.description: qsTr("Restores the settings dialog to a default state")
}
background: Rectangle {
opacity: .5
border.color: theme.backgroundLightest
border.width: 1
radius: 10
color: theme.backgroundLight
}
onClicked: {
settingsDialog.restoreApplicationDefaults()
}
}
}
}
}
}
}

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import QtCore
import QtQuick
import QtQuick.Controls
import QtQuick.Controls.Basic
import QtQuick.Layouts
import download
import network
import llm
Dialog {
id: startupDialog
anchors.centerIn: parent
modal: true
opacity: 0.9
padding: 20
width: 1024
height: column.height + 40
closePolicy: !optInStatisticsRadio.choiceMade || !optInNetworkRadio.choiceMade ? Popup.NoAutoClose : (Popup.CloseOnEscape | Popup.CloseOnPressOutside)
Theme {
id: theme
}
Column {
id: column
spacing: 20
Item {
width: childrenRect.width
height: childrenRect.height
Image {
id: img
anchors.top: parent.top
anchors.left: parent.left
width: 60
height: 60
source: "qrc:/gpt4all/icons/logo.svg"
}
Text {
anchors.left: img.right
anchors.leftMargin: 30
anchors.verticalCenter: img.verticalCenter
text: qsTr("Welcome!")
color: theme.textColor
}
}
ScrollView {
clip: true
height: 200
width: 1024 - 40
ScrollBar.vertical.policy: ScrollBar.AlwaysOn
ScrollBar.horizontal.policy: ScrollBar.AlwaysOff
TextArea {
id: welcome
wrapMode: Text.Wrap
width: 1024 - 40
padding: 20
textFormat: TextEdit.MarkdownText
text: qsTr("### Release notes\n")
+ Download.releaseInfo.notes
+ qsTr("### Contributors\n")
+ Download.releaseInfo.contributors
color: theme.textColor
focus: false
readOnly: true
Accessible.role: Accessible.Paragraph
Accessible.name: qsTr("Release notes")
Accessible.description: qsTr("Release notes for this version")
background: Rectangle {
color: theme.backgroundLight
radius: 10
}
}
}
ScrollView {
clip: true
height: 150
width: 1024 - 40
ScrollBar.vertical.policy: ScrollBar.AlwaysOn
ScrollBar.horizontal.policy: ScrollBar.AlwaysOff
TextArea {
id: optInTerms
wrapMode: Text.Wrap
width: 1024 - 40
padding: 20
textFormat: TextEdit.MarkdownText
text: qsTr(
"### Opt-ins for anonymous usage analytics and datalake
By enabling these features, you will be able to participate in the democratic process of training a
large language model by contributing data for future model improvements.
When a GPT4All model responds to you and you have opted-in, your conversation will be sent to the GPT4All
Open Source Datalake. Additionally, you can like/dislike its response. If you dislike a response, you
can suggest an alternative response. This data will be collected and aggregated in the GPT4All Datalake.
NOTE: By turning on this feature, you will be sending your data to the GPT4All Open Source Datalake.
You should have no expectation of chat privacy when this feature is enabled. You should; however, have
an expectation of an optional attribution if you wish. Your chat data will be openly available for anyone
to download and will be used by Nomic AI to improve future GPT4All models. Nomic AI will retain all
attribution information attached to your data and you will be credited as a contributor to any GPT4All
model release that uses your data!")
color: theme.textColor
focus: false
readOnly: true
Accessible.role: Accessible.Paragraph
Accessible.name: qsTr("Terms for opt-in")
Accessible.description: qsTr("Describes what will happen when you opt-in")
background: Rectangle {
color: theme.backgroundLight
radius: 10
}
}
}
GridLayout {
columns: 2
rowSpacing: 10
columnSpacing: 10
anchors.right: parent.right
Label {
id: optInStatistics
text: "Opt-in to anonymous usage analytics used to improve GPT4All"
Layout.row: 0
Layout.column: 0
color: theme.textColor
Accessible.role: Accessible.Paragraph
Accessible.name: qsTr("Opt-in for anonymous usage statistics")
Accessible.description: qsTr("Label for opt-in")
}
ButtonGroup {
buttons: optInStatisticsRadio.children
onClicked: {
Network.usageStatsActive = optInStatisticsRadio.checked
if (optInNetworkRadio.choiceMade && optInStatisticsRadio.choiceMade)
startupDialog.close();
}
}
RowLayout {
id: optInStatisticsRadio
Layout.alignment: Qt.AlignVCenter
Layout.row: 0
Layout.column: 1
property bool defaultChecked: Network.usageStatsActive
property alias checked: optInStatisticsRadioYes.checked
property bool choiceMade: optInStatisticsRadioYes.checked || optInStatisticsRadioNo.checked
RadioButton {
id: optInStatisticsRadioYes
checked: optInStatisticsRadio.defaultChecked
text: qsTr("Yes")
Accessible.role: Accessible.RadioButton
Accessible.name: qsTr("Opt-in for anonymous usage statistics")
Accessible.description: qsTr("Radio button to allow opt-in for anonymous usage statistics")
background: Rectangle {
color: "transparent"
}
indicator: Rectangle {
implicitWidth: 26
implicitHeight: 26
x: optInStatisticsRadioYes.leftPadding
y: parent.height / 2 - height / 2
radius: 13
border.color: theme.dialogBorder
color: "transparent"
Rectangle {
width: 14
height: 14
x: 6
y: 6
radius: 7
color: theme.textColor
visible: optInStatisticsRadioYes.checked
}
}
contentItem: Text {
text: optInStatisticsRadioYes.text
font: optInStatisticsRadioYes.font
opacity: enabled ? 1.0 : 0.3
color: theme.textColor
verticalAlignment: Text.AlignVCenter
leftPadding: optInStatisticsRadioYes.indicator.width + optInStatisticsRadioYes.spacing
}
}
RadioButton {
id: optInStatisticsRadioNo
text: qsTr("No")
Accessible.role: Accessible.RadioButton
Accessible.name: qsTr("Opt-out for anonymous usage statistics")
Accessible.description: qsTr("Radio button to allow opt-out for anonymous usage statistics")
background: Rectangle {
color: "transparent"
}
indicator: Rectangle {
implicitWidth: 26
implicitHeight: 26
x: optInStatisticsRadioNo.leftPadding
y: parent.height / 2 - height / 2
radius: 13
border.color: theme.dialogBorder
color: "transparent"
Rectangle {
width: 14
height: 14
x: 6
y: 6
radius: 7
color: theme.textColor
visible: optInStatisticsRadioNo.checked
}
}
contentItem: Text {
text: optInStatisticsRadioNo.text
font: optInStatisticsRadioNo.font
opacity: enabled ? 1.0 : 0.3
color: theme.textColor
verticalAlignment: Text.AlignVCenter
leftPadding: optInStatisticsRadioNo.indicator.width + optInStatisticsRadioNo.spacing
}
}
}
Label {
id: optInNetwork
text: "Opt-in to anonymous sharing of chats to the GPT4All Datalake"
Layout.row: 1
Layout.column: 0
color: theme.textColor
Accessible.role: Accessible.Paragraph
Accessible.name: qsTr("Opt-in for network")
Accessible.description: qsTr("Checkbox to allow opt-in for network")
}
ButtonGroup {
buttons: optInNetworkRadio.children
onClicked: {
Network.isActive = optInNetworkRadio.checked
if (optInNetworkRadio.choiceMade && optInStatisticsRadio.choiceMade)
startupDialog.close();
}
}
RowLayout {
id: optInNetworkRadio
Layout.alignment: Qt.AlignVCenter
Layout.row: 1
Layout.column: 1
property bool defaultChecked: Network.isActive
property alias checked: optInNetworkRadioYes.checked
property bool choiceMade: optInNetworkRadioYes.checked || optInNetworkRadioNo.checked
RadioButton {
id: optInNetworkRadioYes
checked: optInNetworkRadio.defaultChecked
text: qsTr("Yes")
Accessible.role: Accessible.RadioButton
Accessible.name: qsTr("Opt-in for network")
Accessible.description: qsTr("Radio button to allow opt-in anonymous sharing of chats to the GPT4All Datalake")
background: Rectangle {
color: "transparent"
}
indicator: Rectangle {
implicitWidth: 26
implicitHeight: 26
x: optInNetworkRadioYes.leftPadding
y: parent.height / 2 - height / 2
radius: 13
border.color: theme.dialogBorder
color: "transparent"
Rectangle {
width: 14
height: 14
x: 6
y: 6
radius: 7
color: theme.textColor
visible: optInNetworkRadioYes.checked
}
}
contentItem: Text {
text: optInNetworkRadioYes.text
font: optInNetworkRadioYes.font
opacity: enabled ? 1.0 : 0.3
color: theme.textColor
verticalAlignment: Text.AlignVCenter
leftPadding: optInNetworkRadioYes.indicator.width + optInNetworkRadioYes.spacing
}
}
RadioButton {
id: optInNetworkRadioNo
text: qsTr("No")
Accessible.role: Accessible.RadioButton
Accessible.name: qsTr("Opt-out for network")
Accessible.description: qsTr("Radio button to allow opt-out anonymous sharing of chats to the GPT4All Datalake")
background: Rectangle {
color: "transparent"
}
indicator: Rectangle {
implicitWidth: 26
implicitHeight: 26
x: optInNetworkRadioNo.leftPadding
y: parent.height / 2 - height / 2
radius: 13
border.color: theme.dialogBorder
color: "transparent"
Rectangle {
width: 14
height: 14
x: 6
y: 6
radius: 7
color: theme.textColor
visible: optInNetworkRadioNo.checked
}
}
contentItem: Text {
text: optInNetworkRadioNo.text
font: optInNetworkRadioNo.font
opacity: enabled ? 1.0 : 0.3
color: theme.textColor
verticalAlignment: Text.AlignVCenter
leftPadding: optInNetworkRadioNo.indicator.width + optInNetworkRadioNo.spacing
}
}
}
}
}
background: Rectangle {
anchors.fill: parent
color: theme.backgroundDarkest
border.width: 1
border.color: theme.dialogBorder
radius: 10
}
}

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import QtCore
import QtQuick
import QtQuick.Controls.Basic
QtObject {
property color textColor: "#d1d5db"
property color textErrorColor: "red"
property color backgroundDarkest: "#202123"
property color backgroundDark: "#242528"
property color backgroundLight: "#343541"
property color backgroundLighter: "#444654"
property color backgroundLightest: "#7d7d8e"
property color dialogBorder: "#d1d5db"
property color userColor: "#ec86bf"
property color assistantColor: "#10a37f"
property color linkColor: "white"
property color tabBorder: "#aaa"
property real fontSizeLarge: Qt.application.font.pixelSize
property real fontSizeLarger: Qt.application.font.pixelSize + 2
}

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import QtCore
import QtQuick
import QtQuick.Controls
import QtQuick.Controls.Basic
import QtQuick.Layouts
import download
import network
import llm
Dialog {
id: thumbsDownDialog
modal: true
opacity: 0.9
padding: 20
Theme {
id: theme
}
property alias response: thumbsDownNewResponse.text
Column {
anchors.fill: parent
spacing: 20
Item {
width: childrenRect.width
height: childrenRect.height
Image {
id: img
anchors.top: parent.top
anchors.left: parent.left
width: 60
height: 60
source: "qrc:/gpt4all/icons/thumbs_down.svg"
}
Text {
anchors.left: img.right
anchors.leftMargin: 30
anchors.verticalCenter: img.verticalCenter
text: qsTr("Please edit the text below to provide a better response. (optional)")
color: theme.textColor
}
}
ScrollView {
clip: true
height: 300
width: parent.width
ScrollBar.vertical.policy: ScrollBar.AlwaysOn
ScrollBar.horizontal.policy: ScrollBar.AlwaysOff
TextArea {
id: thumbsDownNewResponse
color: theme.textColor
padding: 20
wrapMode: Text.Wrap
font.pixelSize: theme.fontSizeLarge
placeholderText: qsTr("Please provide a better response...")
placeholderTextColor: theme.backgroundLightest
background: Rectangle {
color: theme.backgroundLighter
radius: 10
}
}
}
}
background: Rectangle {
anchors.fill: parent
color: theme.backgroundDarkest
border.width: 1
border.color: theme.dialogBorder
radius: 10
}
footer: DialogButtonBox {
padding: 20
alignment: Qt.AlignRight
spacing: 10
Button {
contentItem: Text {
color: theme.textColor
text: qsTr("Submit")
}
background: Rectangle {
border.color: theme.backgroundLightest
border.width: 1
radius: 10
color: theme.backgroundLight
}
padding: 15
DialogButtonBox.buttonRole: DialogButtonBox.AcceptRole
}
Button {
contentItem: Text {
color: theme.textColor
text: qsTr("Cancel")
}
background: Rectangle {
border.color: theme.backgroundLightest
border.width: 1
radius: 10
color: theme.backgroundLight
}
padding: 15
DialogButtonBox.buttonRole: DialogButtonBox.RejectRole
}
background: Rectangle {
color: "transparent"
}
}
}

48
gpt4all-chat/sysinfo.h Normal file
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#include <QtCore/QCoreApplication>
#include <QDebug>
#include <QFile>
#include <QTextStream>
#include <QRegularExpression>
#if defined(Q_OS_MAC)
#include <sys/types.h>
#include <sys/sysctl.h>
#endif
#if defined(Q_OS_WIN)
#include <Windows.h>
#endif
QString getSystemTotalRAM()
{
qint64 totalRAM = 0;
#if defined(Q_OS_LINUX)
QFile file("/proc/meminfo");
if (file.open(QIODevice::ReadOnly | QIODevice::Text)) {
QTextStream in(&file);
QString line = in.readLine();
while (!line.isNull()) {
if (line.startsWith("MemTotal")) {
QStringList parts = line.split(QRegularExpression("\\s+"));
totalRAM = parts[1].toLongLong() * 1024; // Convert from KB to bytes
break;
}
line = in.readLine();
}
file.close();
}
#elif defined(Q_OS_MAC)
int mib[2] = {CTL_HW, HW_MEMSIZE};
size_t length = sizeof(totalRAM);
sysctl(mib, 2, &totalRAM, &length, NULL, 0);
#elif defined(Q_OS_WIN)
MEMORYSTATUSEX memoryStatus;
memoryStatus.dwLength = sizeof(memoryStatus);
GlobalMemoryStatusEx(&memoryStatus);
totalRAM = memoryStatus.ullTotalPhys;
#endif
double totalRAM_GB = static_cast<double>(totalRAM) / (1024 * 1024 * 1024);
return QString::number(totalRAM_GB, 'f', 2) + " GB";
}

29
gpt4all-chat/test_hw.cpp Normal file
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#include <stdio.h>
#include <string>
int main(int argc, char *argv[])
{
static bool avx = __builtin_cpu_supports("avx");
static bool avx2 = __builtin_cpu_supports("avx2");
static bool fma = __builtin_cpu_supports("fma");
static bool sse3 = __builtin_cpu_supports("sse3");
static std::string s;
s = "gpt4all hardware test results:\n";
s += " AVX = " + std::to_string(avx) + "\n";
s += " AVX2 = " + std::to_string(avx2) + "\n";
s += " FMA = " + std::to_string(fma) + "\n";
s += " SSE3 = " + std::to_string(sse3) + "\n";
fprintf(stderr, "%s", s.c_str());
fprintf(stderr, "your hardware supports the \"");
fflush(stderr);
if (avx2)
printf("full");
else if (avx && fma)
printf("avx_only");
else
printf("bare_minimum");
fflush(stdout);
fprintf(stderr, "\" version of gpt4all.\n");
fflush(stderr);
return 0;
}