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68 Commits

Author SHA1 Message Date
Adam Treat
1bc16a2a4f Bump version to v3.0.0-rc4
Signed-off-by: Adam Treat <treat.adam@gmail.com>
2024-06-29 18:02:45 -04:00
AT
b5fdc4c05a Chatview and combobox UI fixes (#2489)
Chatview and combobox UI fixes (#2489)

Signed-off-by: Adam Treat <treat.adam@gmail.com>
2024-06-29 18:00:52 -04:00
AT
55858f93b0 Solve a bad performance problem in text processing that leads to hangs of the UI. (#2487)
Signed-off-by: Adam Treat <treat.adam@gmail.com>
2024-06-29 17:59:45 -04:00
Adam Treat
720ea5a147 Bump the version to rc3.
Signed-off-by: Adam Treat <treat.adam@gmail.com>
2024-06-28 20:34:17 -04:00
Jared Van Bortel
a191844a3f new UI fixes, part 5 (#2485)
additional new ui changes, part 5 (#2485)

Signed-off-by: Jared Van Bortel <jared@nomic.ai>
2024-06-28 20:34:03 -04:00
Jared Van Bortel
22396a6fa1 AddCollectionView: fix label colors (#2484)
Signed-off-by: Jared Van Bortel <jared@nomic.ai>
2024-06-28 17:50:12 -04:00
Jared Van Bortel
f2cad6abaa additional new ui changes, part 4 (#2481)
Signed-off-by: Jared Van Bortel <jared@nomic.ai>
2024-06-28 17:11:12 -04:00
Adam Treat
d893a6e5d6 Give it an empty string default.
Signed-off-by: Adam Treat <treat.adam@gmail.com>
2024-06-28 14:52:44 -04:00
Adam Treat
8fe73832a6 Fix up the loading default model to display the actual name as per Vincent.
Signed-off-by: Adam Treat <treat.adam@gmail.com>
2024-06-28 14:52:44 -04:00
John W. Parent
23e8b187a4 Add basic signing of app bundle and binaries (#2472)
Adds verification functionality to codesign script
Adds required context to enable XCode to perform the signing
Adds install time check + signing for all binaries
Adds instructions allowing macdeployqt to sign the finalized app bundle

Signed-off-by: John Parent <john.parent@kitware.com>
2024-06-28 14:21:18 -04:00
AT
dc6d01a0bb Change the name of this property to not conflict. (#2480)
Signed-off-by: Adam Treat <treat.adam@gmail.com>
2024-06-28 13:34:26 -04:00
Jared Van Bortel
2c8d634b5b UI and embedding device changes for GPT4All v3.0.0-rc3 (#2477)
Signed-off-by: Jared Van Bortel <jared@nomic.ai>
2024-06-28 12:57:57 -04:00
AT
426aa5eb47 Go ahead and try to handle links in the text by opening them externally. (#2479)
Handle links in the text by opening them externally.

Signed-off-by: Adam Treat <treat.adam@gmail.com>
2024-06-28 12:54:12 -04:00
Jared Van Bortel
81bbeef5b3 partially back out that change, I wasn't reading
Signed-off-by: Jared Van Bortel <jared@nomic.ai>
2024-06-28 11:49:12 -04:00
Jared Van Bortel
1712830228 chatviewtextprocessor: fix missing #include and simplify sort
Signed-off-by: Jared Van Bortel <jared@nomic.ai>
2024-06-28 11:49:12 -04:00
Adam Treat
f6f265f968 This allows support for markdown table display and <foo>
Signed-off-by: Adam Treat <treat.adam@gmail.com>
2024-06-28 11:49:12 -04:00
Adam Treat
6f52f602ef Improved markdown support:
* Correctly displays inline code blocks with syntax highlighting turned on
as well as markdown at the same time
* Adds a context menu item for toggling markdown on and off which also
which essentially turns on/off all text processing
* Uses QTextDocument::MarkdownNoHTML to handle markdown in QTextDocument
which allows display of html tags like normal, but unfortunately does not
allow display of markdown tables as markdown

Signed-off-by: Adam Treat <treat.adam@gmail.com>
2024-06-28 11:49:12 -04:00
Adam Treat
d92252cab1 Revert an incorrect renaming that slipped in.
Signed-off-by: Adam Treat <treat.adam@gmail.com>
2024-06-27 11:14:12 -04:00
Jared Van Bortel
6506ba161b UI tweaks for GPT4All v3.0.0-rc2 (#2474)
* clickable link to get API key with hand-style mouse cursor
* remove "Force Metal" setting
* allow typing incorrect API keys (but don't accept them), add placeholder text

Signed-off-by: Jared Van Bortel <jared@nomic.ai>
2024-06-27 11:08:32 -04:00
Adam Treat
bed92046d0 Set the 3.0.0-rc2 version.
Signed-off-by: Adam Treat <treat.adam@gmail.com>
2024-06-27 11:00:00 -04:00
Adam Treat
a1ec6f2150 Change the divider height and color to be more consistent.
Signed-off-by: Adam Treat <treat.adam@gmail.com>
2024-06-27 07:25:39 -04:00
Adam Treat
8d6e11fcad Change to just sources after multiple feedback advising same.
Signed-off-by: Adam Treat <treat.adam@gmail.com>
2024-06-27 07:25:39 -04:00
Adam Treat
fc5dc9dd1a Fix the scrollbar so it doesn't overlap content on chat view.
Signed-off-by: Adam Treat <treat.adam@gmail.com>
2024-06-27 07:25:39 -04:00
Adam Treat
d4494602e2 Markdown support.
Signed-off-by: Adam Treat <treat.adam@gmail.com>
2024-06-27 07:25:39 -04:00
AT
23e8f43c5a Change the way we're showing the localdocs sources. (#2475)
* Change the way we're showing the localdocs sources.

Signed-off-by: Adam Treat <treat.adam@gmail.com>
2024-06-26 22:00:48 -04:00
Adam Treat
31fa575c35 Place the antenna icon in the lower left right above nomic logo as per discussion.
Signed-off-by: Adam Treat <treat.adam@gmail.com>
2024-06-26 16:43:22 -04:00
Adam Treat
6d593d6ea1 Fix the thumbsdown dialog.
Signed-off-by: Adam Treat <treat.adam@gmail.com>
2024-06-26 16:37:01 -04:00
Jared Van Bortel
01870b4a46 chat: fix blank device in UI and improve Mixpanel reporting (#2409)
Also remove LLModel::hasGPUDevice.

Signed-off-by: Jared Van Bortel <jared@nomic.ai>
2024-06-26 15:26:27 -04:00
Adam Treat
53fc2d56f6 Add a tooltip to make clear what is going on with the antenna animation.
Signed-off-by: Adam Treat <treat.adam@gmail.com>
2024-06-26 15:20:09 -04:00
Adam Treat
e5d9936d04 Update the license.
Signed-off-by: Adam Treat <treat.adam@gmail.com>
2024-06-26 15:07:51 -04:00
Adam Treat
11823022e2 Add a fixme for combobox popups in general which is less than ideal right now.
Signed-off-by: Adam Treat <treat.adam@gmail.com>
2024-06-26 15:00:50 -04:00
Jared Van Bortel
da1823ed7a cmake: fix CMAKE_CUDA_ARCHITECTURES default (#2421)
Signed-off-by: Jared Van Bortel <jared@nomic.ai>
2024-06-26 14:48:18 -04:00
AT
3a61070f82 chat: fix incorrect file URIs for sources on Windows (#2469)
This was causing LocalDocs sources to not open correctly on Windows.

Signed-off-by: Adam Treat <treat.adam@gmail.com>
Signed-off-by: Jared Van Bortel <jared@nomic.ai>
Co-authored-by: Jared Van Bortel <jared@nomic.ai>
2024-06-26 14:48:02 -04:00
Adam Treat
c87ccf4124 Make the chatview combo scrollable.
Signed-off-by: Adam Treat <treat.adam@gmail.com>
2024-06-26 14:39:39 -04:00
Adam Treat
88f5face2b Change section headers to be lighter and smaller as per Vincent.
Signed-off-by: Adam Treat <treat.adam@gmail.com>
2024-06-26 13:48:02 -04:00
Adam Treat
f8a935d8a6 Decrease vertical size of search bar and spacing in add model view.
Signed-off-by: Adam Treat <treat.adam@gmail.com>
2024-06-26 13:00:01 -04:00
Adam Treat
029bd318e9 If huggingface search doesn't give this information, then display question mark.
Signed-off-by: Adam Treat <treat.adam@gmail.com>
2024-06-26 12:31:11 -04:00
Adam Treat
d5968f4ab2 Make the chatdrawer edit/delete icons smaller.
Signed-off-by: Adam Treat <treat.adam@gmail.com>
2024-06-26 12:19:02 -04:00
John W. Parent
30febbe3d2 Add basic Macos signing + notarizing workflow (#2319)
Adds basic CircleCI workflow to sign, notarize,
and staple MacOS app bundle and associated DMG,
then publishes signed binary in CircleCI artifacts

Signed-off-by: Adam Treat <treat.adam@gmail.com>
2024-06-25 20:31:51 -04:00
Jared Van Bortel
88d85be0f9 chat: fix build on Windows and Nomic Embed path on macOS (#2467)
* chat: remove unused oscompat source files

These files are no longer needed now that the hnswlib index is gone.
This fixes an issue with the Windows build as there was a compilation
error in oscompat.cpp.

Signed-off-by: Jared Van Bortel <jared@nomic.ai>

* llm: fix pragma to be recognized by MSVC

Replaces this MSVC warning:
C:\msys64\home\Jared\gpt4all\gpt4all-chat\llm.cpp(53,21): warning C4081: expected '('; found 'string'

With this:
C:\msys64\home\Jared\gpt4all\gpt4all-chat\llm.cpp : warning : offline installer build will not check for updates!

Signed-off-by: Jared Van Bortel <jared@nomic.ai>

* usearch: fork usearch to fix `CreateFile` build error

Signed-off-by: Jared Van Bortel <jared@nomic.ai>

* dlhandle: fix incorrect assertion on Windows

SetErrorMode returns the previous value of the error mode flags, not an
indicator of success.

Signed-off-by: Jared Van Bortel <jared@nomic.ai>

* llamamodel: fix UB in LLamaModel::embedInternal

It is undefined behavior to increment an STL iterator past the end of
the container. Use offsets to do the math instead.

Signed-off-by: Jared Van Bortel <jared@nomic.ai>

* cmake: install embedding model to bundle's Resources dir on macOS

Signed-off-by: Jared Van Bortel <jared@nomic.ai>

* ci: fix macOS build by explicitly installing Rosetta

Signed-off-by: Jared Van Bortel <jared@nomic.ai>

---------

Signed-off-by: Jared Van Bortel <jared@nomic.ai>
2024-06-25 17:22:51 -04:00
AT
bbf0c2f246 Update qa_checklist.md
Add the directories for each OS

Signed-off-by: AT <manyoso@users.noreply.github.com>
2024-06-25 13:50:19 -04:00
AT
9363ffb958 Update qa_checklist.md
Add another step for users to shutdown and retest with settings and so on from a previous version

Signed-off-by: AT <manyoso@users.noreply.github.com>
2024-06-25 13:15:29 -04:00
AT
8724572d61 Create qa_checklist.md
Add a checklist for QA testing

Signed-off-by: AT <manyoso@users.noreply.github.com>
2024-06-25 13:06:52 -04:00
Jared Van Bortel
1a00882276 embllm: fix use of llama ctx before loading (#2465)
This fixes a regression in PR #2396.

Signed-off-by: Jared Van Bortel <jared@nomic.ai>
2024-06-25 11:04:01 -04:00
AT
9273b49b62 chat: major UI redesign for v3.0.0 (#2396)
Signed-off-by: Adam Treat <treat.adam@gmail.com>
Signed-off-by: Jared Van Bortel <jared@nomic.ai>
Co-authored-by: Jared Van Bortel <jared@nomic.ai>
2024-06-24 18:49:23 -04:00
Adam Treat
1272b694ae Add a latest news markdown file for future version.
Signed-off-by: Adam Treat <treat.adam@gmail.com>
2024-06-24 13:57:12 -04:00
patcher9
986d9d9bb8 docs: add description of OpenLIT GPU monitoring (#2436)
Signed-off-by: patcher9 <patcher99@dokulabs.com>
2024-06-13 11:23:32 -04:00
dependabot[bot]
b999d07d93 typescript: update braces dep to 3.0.3 (#2432)
Signed-off-by: dependabot[bot] <support@github.com>
2024-06-12 17:14:47 -04:00
Jared Van Bortel
beaede03fb repo: remove bindings that have no maintainer (#2429)
The C#, Java, and Go bindings are now removed from the repo.

Signed-off-by: Jared Van Bortel <jared@nomic.ai>
2024-06-11 18:11:25 -04:00
Jared Van Bortel
41c9013fa4 chat: don't use incomplete types with signals/slots/Q_INVOKABLE (#2408)
Signed-off-by: Jared Van Bortel <jared@nomic.ai>
2024-06-06 11:59:28 -04:00
Markus Mayer
69f766cbbb ci: update checkout action to v4 in codespell workflow (#2414)
Signed-off-by: Markus Mayer <widemeadows@gmail.com>
2024-06-05 11:34:51 -04:00
patcher9
d43bfa0a53 docs: document OpenLIT integration (#2386)
Signed-off-by: patcher9 <patcher99@dokulabs.com>
Co-authored-by: Jared Van Bortel <jared@nomic.ai>
2024-06-05 11:05:21 -04:00
Jared Van Bortel
d3d777bc51 chat: fix #includes with include-what-you-use (#2401)
Also use qGuiApp instead of qApp.

Signed-off-by: Jared Van Bortel <jared@nomic.ai>
2024-06-04 14:47:11 -04:00
Jared Van Bortel
55d709862f Revert "typescript bindings maintenance (#2363)"
As discussed on Discord, this PR was not ready to be merged. CI fails on
it.

This reverts commit a602f7fde7.

Signed-off-by: Jared Van Bortel <jared@nomic.ai>
2024-06-03 17:26:19 -04:00
Andreas Obersteiner
a602f7fde7 typescript bindings maintenance (#2363)
* remove outdated comments

Signed-off-by: limez <limez@protonmail.com>

* simpler build from source

Signed-off-by: limez <limez@protonmail.com>

* update unix build script to create .so runtimes correctly

Signed-off-by: limez <limez@protonmail.com>

* configure ci build type, use RelWithDebInfo for dev build script

Signed-off-by: limez <limez@protonmail.com>

* add clean script

Signed-off-by: limez <limez@protonmail.com>

* fix streamed token decoding / emoji

Signed-off-by: limez <limez@protonmail.com>

* remove deprecated nCtx

Signed-off-by: limez <limez@protonmail.com>

* update typings

Signed-off-by: jacob <jacoobes@sern.dev>

update typings

Signed-off-by: jacob <jacoobes@sern.dev>

* readme,mspell

Signed-off-by: jacob <jacoobes@sern.dev>

* cuda/backend logic changes + name napi methods like their js counterparts

Signed-off-by: limez <limez@protonmail.com>

* convert llmodel example into a test, separate test suite that can run in ci

Signed-off-by: limez <limez@protonmail.com>

* update examples / naming

Signed-off-by: limez <limez@protonmail.com>

* update deps, remove the need for binding.ci.gyp, make node-gyp-build fallback easier testable

Signed-off-by: limez <limez@protonmail.com>

* make sure the assert-backend-sources.js script is published, but not the others

Signed-off-by: limez <limez@protonmail.com>

* build correctly on windows (regression on node-gyp-build)

Signed-off-by: Jacob Nguyen <76754747+jacoobes@users.noreply.github.com>

* codespell

Signed-off-by: limez <limez@protonmail.com>

* make sure dlhandle.cpp gets linked correctly

Signed-off-by: limez <limez@protonmail.com>

* add include for check_cxx_compiler_flag call during aarch64 builds

Signed-off-by: limez <limez@protonmail.com>

* x86 > arm64 cross compilation of runtimes and bindings

Signed-off-by: limez <limez@protonmail.com>

* default to cpu instead of kompute on arm64

Signed-off-by: limez <limez@protonmail.com>

* formatting, more minimal example

Signed-off-by: limez <limez@protonmail.com>

---------

Signed-off-by: limez <limez@protonmail.com>
Signed-off-by: jacob <jacoobes@sern.dev>
Signed-off-by: Jacob Nguyen <76754747+jacoobes@users.noreply.github.com>
Co-authored-by: Jacob Nguyen <76754747+jacoobes@users.noreply.github.com>
Co-authored-by: jacob <jacoobes@sern.dev>
2024-06-03 11:12:55 -05:00
woheller69
f001897a1a Fix path in Readme (#2339)
Signed-off-by: woheller69 <68678880+woheller69@users.noreply.github.com>
2024-05-31 17:20:41 -04:00
Jared Van Bortel
636307160e backend: fix #includes with include-what-you-use (#2371)
Also fix a PARENT_SCOPE warning when building the backend.

Signed-off-by: Jared Van Bortel <jared@nomic.ai>
2024-05-31 16:34:54 -04:00
Jared Van Bortel
8ba7ef4832 dlhandle: suppress DLL errors on Windows (#2389)
Signed-off-by: Jared Van Bortel <jared@nomic.ai>
2024-05-31 16:33:40 -04:00
Jared Van Bortel
4e89a9c44f backend: support non-ASCII characters in path to llmodel libs on Windows (#2388)
* backend: refactor dlhandle.h into oscompat.{cpp,h}

Signed-off-by: Jared Van Bortel <jared@nomic.ai>

* llmodel: alias std::filesystem

Signed-off-by: Jared Van Bortel <jared@nomic.ai>

* llmodel: use wide strings for paths on Windows

Using the native path representation allows us to manipulate paths and
call LoadLibraryEx without mangling non-ASCII characters.

Signed-off-by: Jared Van Bortel <jared@nomic.ai>

* llmodel: prefer built-in std::filesystem functionality

Signed-off-by: Jared Van Bortel <jared@nomic.ai>

* oscompat: fix string type error

Signed-off-by: Jared Van Bortel <jared@nomic.ai>

* backend: rename oscompat back to dlhandle

Signed-off-by: Jared Van Bortel <jared@nomic.ai>

* dlhandle: fix #includes

Signed-off-by: Jared Van Bortel <jared@nomic.ai>

* dlhandle: remove another #include

Signed-off-by: Jared Van Bortel <jared@nomic.ai>

* dlhandle: move dlhandle #include

Signed-off-by: Jared Van Bortel <jared@nomic.ai>

* dlhandle: remove #includes that are covered by dlhandle.h

Signed-off-by: Jared Van Bortel <jared@nomic.ai>

* llmodel: fix #include order

Signed-off-by: Jared Van Bortel <jared@nomic.ai>

---------

Signed-off-by: Jared Van Bortel <jared@nomic.ai>
2024-05-31 13:12:28 -04:00
Jared Van Bortel
8a70f770a2 ci: fix Python build after CUDA PR (#2373)
Build with -DCMAKE_BUILD_TYPE=Release, and use MSVC on Windows.

Signed-off-by: Jared Van Bortel <jared@nomic.ai>
2024-05-29 10:52:45 -04:00
Jared Van Bortel
e94177ee9a llamamodel: fix embedding crash for >512 tokens after #2310 (#2383)
Signed-off-by: Jared Van Bortel <jared@nomic.ai>
2024-05-29 10:51:00 -04:00
Jared Van Bortel
f047f383d0 llama.cpp: update submodule for "code" model crash workaround (#2382)
Signed-off-by: Jared Van Bortel <jared@nomic.ai>
2024-05-29 10:50:00 -04:00
Jared Van Bortel
f1b4092ca6 llamamodel: fix BERT tokenization after llama.cpp update (#2381)
Signed-off-by: Jared Van Bortel <jared@nomic.ai>
2024-05-28 13:11:57 -04:00
Jared Van Bortel
0b63ad5eff chat: add release notes for v2.8.0 and bump version (#2372)
Signed-off-by: Jared Van Bortel <jared@nomic.ai>
2024-05-23 10:29:25 -04:00
Jared Van Bortel
09dd3dc318 python: depend on offical NVIDIA CUDA packages (#2355)
Signed-off-by: Jared Van Bortel <jared@nomic.ai>
2024-05-20 18:06:27 -04:00
Jared Van Bortel
c779d8a32d python: init_gpu fixes (#2368)
* python: tweak GPU init failure message
* llama.cpp: update submodule for use-after-free fix

Signed-off-by: Jared Van Bortel <jared@nomic.ai>
2024-05-20 18:04:11 -04:00
Jared Van Bortel
e021fe130f installer script: fix detection of macOS on newer QtIFW (#2361)
Signed-off-by: Jared Van Bortel <jared@nomic.ai>
2024-05-17 12:28:46 -04:00
Jared Van Bortel
2025d2d15b llmodel: add CUDA to the DLL search path if CUDA_PATH is set (#2357)
Signed-off-by: Jared Van Bortel <jared@nomic.ai>
2024-05-16 17:39:49 -04:00
240 changed files with 10973 additions and 13899 deletions

View File

@@ -15,6 +15,5 @@ workflows:
gpt4all-backend/.* run-all-workflows true
gpt4all-bindings/python/.* run-python-workflow true
gpt4all-bindings/typescript/.* run-ts-workflow true
gpt4all-bindings/csharp/.* run-csharp-workflow true
gpt4all-chat/.* run-chat-workflow true
.* run-default-workflow true

View File

@@ -20,9 +20,6 @@ parameters:
run-ts-workflow:
type: boolean
default: false
run-csharp-workflow:
type: boolean
default: false
jobs:
default-job:
@@ -43,6 +40,9 @@ jobs:
- restore_cache: # this is the new step to restore cache
keys:
- macos-qt-cache-v3
- run:
name: Install Rosetta
command: softwareupdate --install-rosetta --agree-to-license # needed for QtIFW
- run:
name: Installing Qt
command: |
@@ -56,6 +56,15 @@ jobs:
key: macos-qt-cache-v3
paths:
- ~/Qt
- run:
name: Setup Keychain
command: |
echo $MAC_SIGNING_CERT | base64 --decode > cert.p12
security create-keychain -p "$MAC_KEYCHAIN_KEY" sign.keychain
security default-keychain -s sign.keychain
security unlock-keychain -p "$MAC_KEYCHAIN_KEY" sign.keychain
security import cert.p12 -k sign.keychain -P "$MAC_SIGNING_CERT_PWD" -T /usr/bin/codesign
security set-key-partition-list -S apple-tool:,apple:,codesign: -s -k "$MAC_KEYCHAIN_KEY" sign.keychain
- run:
name: Build
command: |
@@ -67,6 +76,7 @@ jobs:
-DBUILD_UNIVERSAL=ON \
-DMACDEPLOYQT=~/Qt/6.5.1/macos/bin/macdeployqt \
-DGPT4ALL_OFFLINE_INSTALLER=ON \
-DGPT4ALL_SIGN_INSTALL=ON \
-DCMAKE_BUILD_TYPE=Release \
-DCMAKE_PREFIX_PATH:PATH=~/Qt/6.5.1/macos/lib/cmake/Qt6 \
-DCMAKE_MAKE_PROGRAM:FILEPATH=~/Qt/Tools/Ninja/ninja \
@@ -77,8 +87,90 @@ jobs:
~/Qt/Tools/CMake/CMake.app/Contents/bin/cmake --build . --target package
mkdir upload
cp gpt4all-installer-* upload
# persist the unsigned installer
- store_artifacts:
path: build/upload
# add workspace so signing jobs can connect & obtain dmg
- persist_to_workspace:
root: build
# specify path to only include components we want to persist
# accross builds
paths:
- upload
sign-offline-chat-installer-macos:
macos:
xcode: 14.0.0
steps:
- checkout
# attach to a workspace containing unsigned dmg
- attach_workspace:
at: build
- run:
name: "Setup Keychain"
command: |
echo $MAC_SIGNING_CERT | base64 --decode > cert.p12
# cat \<<< "$MAC_SIGNING_CERT" > certs1.pem
# file certs1.pem
# iconv -c -f UTF8 -t ASCII certs1.pem > certs.pem
# openssl pkcs12 -legacy -export -out cert.p12 -in certs.pem -inkey certs.pem -passin pass:"$MAC_SIGNING_CERT_PWD" -passout pass:"$MAC_SIGNING_CERT_PWD"
security create-keychain -p "$MAC_KEYCHAIN_KEY" sign.keychain
security default-keychain -s sign.keychain
security unlock-keychain -p "$MAC_KEYCHAIN_KEY" sign.keychain
security import cert.p12 -k sign.keychain -P "$MAC_SIGNING_CERT_PWD" -T /usr/bin/codesign
security set-key-partition-list -S apple-tool:,apple:,codesign: -s -k "$MAC_KEYCHAIN_KEY" sign.keychain
rm cert.p12
- run:
name: "Sign App Bundle"
command: |
python3 -m pip install click
python3 gpt4all-chat/cmake/sign_dmg.py --input-dmg build/upload/gpt4all-installer-darwin.dmg --output-dmg build/upload/gpt4all-installer-darwin-signed.dmg --signing-identity "$MAC_SIGNING_CERT_NAME"
- run:
name: "Sign DMG"
command: |
codesign --options runtime --timestamp -s "$MAC_SIGNING_CERT_NAME" build/upload/gpt4all-installer-darwin-signed.dmg
# add workspace so signing jobs can connect & obtain dmg
- persist_to_workspace:
root: build
# specify path to only include components we want to persist
# accross builds
paths:
- upload
notarize-offline-chat-installer-macos:
macos:
xcode: 14.0.0
steps:
- checkout
- attach_workspace:
at: build
# - run:
# name: "Setup Notarize Keychain"
# command: |
# security create-keychain
# sudo xcrun notarytool store-credentials "notarytool-profile" --apple-id "$MAC_NOTARIZATION_ID" --team-id "$MAC_NOTARIZATION_TID" --password "$MAC_NOTARIZATION_KEY" --keychain /Library/Keychains/System.keychain
- run:
name: "Notarize"
command: |
xcrun notarytool submit build/upload/gpt4all-installer-darwin-signed.dmg --apple-id "$MAC_NOTARIZATION_ID" --team-id "$MAC_NOTARIZATION_TID" --password "$MAC_NOTARIZATION_KEY" --wait | tee notarize_log.txt
- run:
name: "Report Notarization Failure"
command: |
NID=`python3 .circleci/grab_notary_id.py notarize_log.txt` && export NID
xcrun notarytool log $NID --keychain-profile "notary-profile"
exit 1
when: on_fail
# - run:
# name: "Rename and move"
# command: |
# mv build/upload/gpt4all-installer-darwin-signed.dmg build/upload-signed/gpt4all-installer-darwin-signed.dmg
- run:
name: "Staple"
command: |
xcrun stapler staple build/upload/gpt4all-installer-darwin-signed.dmg
- store_artifacts:
path: build/upload
build-offline-chat-installer-linux:
machine:
image: ubuntu-2204:2023.04.2
@@ -328,6 +420,9 @@ jobs:
- restore_cache: # this is the new step to restore cache
keys:
- macos-qt-cache-v3
- run:
name: Install Rosetta
command: softwareupdate --install-rosetta --agree-to-license # needed for QtIFW
- run:
name: Installing Qt
command: |
@@ -421,7 +516,7 @@ jobs:
export PATH=$PATH:/usr/local/cuda/bin
git submodule update --init --recursive
cd gpt4all-backend
cmake -B build
cmake -B build -DCMAKE_BUILD_TYPE=Release
cmake --build build --parallel
- run:
name: Build wheel
@@ -451,7 +546,7 @@ jobs:
command: |
git submodule update --init # don't use --recursive because macOS doesn't use Kompute
cd gpt4all-backend
cmake -B build -DCMAKE_OSX_ARCHITECTURES="x86_64;arm64"
cmake -B build -DCMAKE_BUILD_TYPE=Release -DCMAKE_OSX_ARCHITECTURES="x86_64;arm64"
cmake --build build --parallel
- run:
name: Build wheel
@@ -466,13 +561,17 @@ jobs:
- "*.whl"
build-py-windows:
executor:
name: win/default
machine:
image: 'windows-server-2019-vs2019:2022.08.1'
resource_class: windows.large
shell: powershell.exe -ExecutionPolicy Bypass
steps:
- checkout
- run:
name: Install MinGW64
command: choco install -y mingw --force --no-progress
name: Update Submodules
command: |
git submodule sync
git submodule update --init --recursive
- run:
name: Install VulkanSDK
command: |
@@ -486,31 +585,40 @@ jobs:
- run:
name: Install dependencies
command:
choco install -y cmake --installargs 'ADD_CMAKE_TO_PATH=System'
choco install -y cmake ninja --installargs 'ADD_CMAKE_TO_PATH=System'
- run:
name: Install Python dependencies
command: pip install setuptools wheel cmake
- run:
name: Build C library
command: |
git submodule update --init --recursive
cd gpt4all-backend
$Env:Path += ";C:\ProgramData\mingw64\mingw64\bin"
$Env:Path += ";C:\VulkanSDK\1.3.261.1\bin"
# Visual Studio setup
# I would use Enter-VsDevShell but it causes cudafe++ to segfault
$Env:PATH += ";C:\Program Files (x86)\Windows Kits\10\bin\x64"
$Env:PATH += ";C:\Program Files (x86)\Windows Kits\10\bin\10.0.22000.0\x64"
$Env:PATH += ";C:\Program Files (x86)\Microsoft Visual Studio\2019\Community\VC\Tools\MSVC\14.29.30133\bin\HostX64\x64"
$Env:LIB = "C:\Program Files (x86)\Windows Kits\10\Lib\10.0.22000.0\ucrt\x64"
$Env:LIB += ";C:\Program Files (x86)\Windows Kits\10\Lib\10.0.22000.0\um\x64"
$Env:LIB += ";C:\Program Files (x86)\Microsoft Visual Studio\2019\Community\VC\Tools\MSVC\14.29.30133\lib\x64"
$Env:LIB += ";C:\Program Files (x86)\Microsoft Visual Studio\2019\Community\VC\Tools\MSVC\14.29.30133\ATLMFC\lib\x64"
$Env:INCLUDE = "C:\Program Files (x86)\Windows Kits\10\include\10.0.22000.0\ucrt"
$Env:INCLUDE += ";C:\Program Files (x86)\Windows Kits\10\include\10.0.22000.0\um"
$Env:INCLUDE += ";C:\Program Files (x86)\Windows Kits\10\include\10.0.22000.0\shared"
$Env:INCLUDE += ";C:\Program Files (x86)\Windows Kits\10\include\10.0.22000.0\winrt"
$Env:INCLUDE += ";C:\Program Files (x86)\Windows Kits\10\include\10.0.22000.0\cppwinrt"
$Env:INCLUDE += ";C:\Program Files (x86)\Microsoft Visual Studio\2019\Community\VC\Auxiliary\VS\include"
$Env:INCLUDE += ";C:\Program Files (x86)\Microsoft Visual Studio\2019\Community\VC\Tools\MSVC\14.29.30133\include"
$Env:INCLUDE += ";C:\Program Files (x86)\Microsoft Visual Studio\2019\Community\VC\Tools\MSVC\14.29.30133\ATLMFC\include"
$Env:PATH += ";C:\VulkanSDK\1.3.261.1\bin"
$Env:VULKAN_SDK = "C:\VulkanSDK\1.3.261.1"
cmake -G "MinGW Makefiles" -B build -DKOMPUTE_OPT_DISABLE_VULKAN_VERSION_CHECK=ON -DKOMPUTE_OPT_USE_BUILT_IN_VULKAN_HEADER=OFF
cd gpt4all-backend
cmake -G Ninja -B build -DCMAKE_BUILD_TYPE=Release -DKOMPUTE_OPT_DISABLE_VULKAN_VERSION_CHECK=ON
cmake --build build --parallel
- run:
name: Build wheel
# TODO: As part of this task, we need to move mingw64 binaries into package.
# This is terrible and needs a more robust solution eventually.
command: |
cd gpt4all-bindings/python
cd gpt4all
mkdir llmodel_DO_NOT_MODIFY
mkdir llmodel_DO_NOT_MODIFY/build/
cp 'C:\ProgramData\mingw64\mingw64\bin\*dll' 'llmodel_DO_NOT_MODIFY/build/'
cd ..
python setup.py bdist_wheel --plat-name=win_amd64
- store_artifacts:
path: gpt4all-bindings/python/dist
@@ -607,57 +715,6 @@ jobs:
- runtimes/osx-x64/*.metal
build-bindings-backend-windows:
executor:
name: win/default
size: large
shell: powershell.exe -ExecutionPolicy Bypass
steps:
- checkout
- run:
name: Update Submodules
command: |
git submodule sync
git submodule update --init --recursive
- run:
name: Install MinGW64
command: choco install -y mingw --force --no-progress
- run:
name: Install VulkanSDK
command: |
Invoke-WebRequest -Uri https://sdk.lunarg.com/sdk/download/1.3.261.1/windows/VulkanSDK-1.3.261.1-Installer.exe -OutFile VulkanSDK-1.3.261.1-Installer.exe
.\VulkanSDK-1.3.261.1-Installer.exe --accept-licenses --default-answer --confirm-command install
- run:
name: Install CUDA Toolkit
command: |
Invoke-WebRequest -Uri https://developer.download.nvidia.com/compute/cuda/12.4.1/network_installers/cuda_12.4.1_windows_network.exe -OutFile cuda_12.4.1_windows_network.exe
.\cuda_12.4.1_windows_network.exe -s cudart_12.4 nvcc_12.4 cublas_12.4 cublas_dev_12.4
- run:
name: Install dependencies
command: |
choco install -y cmake --installargs 'ADD_CMAKE_TO_PATH=System'
- run:
name: Build Libraries
command: |
$MinGWBin = "C:\ProgramData\mingw64\mingw64\bin"
$Env:Path += ";$MinGwBin"
$Env:Path += ";C:\Program Files\CMake\bin"
$Env:Path += ";C:\VulkanSDK\1.3.261.1\bin"
$Env:VULKAN_SDK = "C:\VulkanSDK\1.3.261.1"
cd gpt4all-backend
mkdir runtimes/win-x64
cd runtimes/win-x64
cmake -G "MinGW Makefiles" -DKOMPUTE_OPT_DISABLE_VULKAN_VERSION_CHECK=ON ../..
cmake --build . --parallel --config Release
cp "$MinGWBin\libgcc*.dll" .
cp "$MinGWBin\libstdc++*.dll" .
cp "$MinGWBin\libwinpthread*.dll" .
cp bin/*.dll .
- persist_to_workspace:
root: gpt4all-backend
paths:
- runtimes/win-x64/*.dll
build-bindings-backend-windows-msvc:
machine:
image: 'windows-server-2022-gui:2023.03.1'
resource_class: windows.large
@@ -700,182 +757,6 @@ jobs:
paths:
- runtimes/win-x64_msvc/*.dll
build-csharp-linux:
docker:
- image: mcr.microsoft.com/dotnet/sdk:8.0
steps:
- checkout
- attach_workspace:
at: /tmp/workspace
- run:
name: "Prepare Native Libs"
command: |
cd gpt4all-bindings/csharp
mkdir -p runtimes/linux-x64/native
cp /tmp/workspace/runtimes/linux-x64/*.so runtimes/linux-x64/native/
ls -R runtimes
- restore_cache:
keys:
- gpt4all-csharp-nuget-packages-nix
- run:
name: "Install project dependencies"
command: |
cd gpt4all-bindings/csharp
dotnet restore Gpt4All
- save_cache:
paths:
- ~/.nuget/packages
key: gpt4all-csharp-nuget-packages-nix
- run:
name: Build C# Project
command: |
cd gpt4all-bindings/csharp
dotnet build Gpt4All --configuration Release --nologo
- run:
name: "Run C# Tests"
command: |
cd gpt4all-bindings/csharp
dotnet test Gpt4All.Tests -v n -c Release --filter "SKIP_ON_CI!=True" --logger "trx"
- run:
name: Test results
command: |
cd gpt4all-bindings/csharp/Gpt4All.Tests
dotnet tool install -g trx2junit
export PATH="$PATH:$HOME/.dotnet/tools"
trx2junit TestResults/*.trx
- store_test_results:
path: gpt4all-bindings/csharp/Gpt4All.Tests/TestResults
build-csharp-windows:
executor:
name: win/default
size: large
shell: powershell.exe -ExecutionPolicy Bypass
steps:
- checkout
- restore_cache:
keys:
- gpt4all-csharp-nuget-packages-win
- attach_workspace:
at: C:\Users\circleci\workspace
- run:
name: "Install .NET"
command: |
choco install -y dotnet-8.0-sdk
- run:
name: "Prepare Native Libs"
command: |
cd gpt4all-bindings/csharp
mkdir -p runtimes\win-x64\native
cp C:\Users\circleci\workspace\runtimes\win-x64\*.dll runtimes\win-x64\native\
ls -R runtimes
- run:
name: "Install project dependencies"
command: |
cd gpt4all-bindings/csharp
dotnet.exe restore Gpt4All
- save_cache:
paths:
- C:\Users\circleci\.nuget\packages
key: gpt4all-csharp-nuget-packages-win
- run:
name: Build C# Project
command: |
cd gpt4all-bindings/csharp
dotnet.exe build Gpt4All --configuration Release --nologo
- run:
name: "Run C# Tests"
command: |
cd gpt4all-bindings/csharp
dotnet.exe test Gpt4All.Tests -v n -c Release --filter "SKIP_ON_CI!=True" --logger "trx"
- run:
name: Test results
command: |
cd gpt4all-bindings/csharp/Gpt4All.Tests
dotnet tool install -g trx2junit
$Env:Path += ";$Env:USERPROFILE\.dotnet\tools"
trx2junit TestResults/*.trx
- store_test_results:
path: gpt4all-bindings/csharp/Gpt4All.Tests/TestResults
build-csharp-macos:
macos:
xcode: "14.0.0"
steps:
- checkout
- restore_cache:
keys:
- gpt4all-csharp-nuget-packages-nix
- run:
name: Install dependencies
command: |
brew tap isen-ng/dotnet-sdk-versions
brew install --cask dotnet-sdk8-0-100
- attach_workspace:
at: /tmp/workspace
- run:
name: "Prepare Native Libs"
command: |
cd gpt4all-bindings/csharp
mkdir -p runtimes/osx/native
cp /tmp/workspace/runtimes/osx-x64/*.dylib runtimes/osx/native/
cp /tmp/workspace/runtimes/osx-x64/*.metal runtimes/osx/native/
ls -R runtimes
- run:
name: "Install project dependencies"
command: |
cd gpt4all-bindings/csharp
dotnet restore Gpt4All
- save_cache:
paths:
- ~/.nuget/packages
key: gpt4all-csharp-nuget-packages-nix
- run:
name: Build C# Project
command: |
cd gpt4all-bindings/csharp
dotnet build Gpt4All --configuration Release --nologo
- run:
name: "Run C# Tests"
command: |
cd gpt4all-bindings/csharp
dotnet test Gpt4All.Tests -v n -c Release --filter "SKIP_ON_CI!=True" --logger "trx"
- run:
name: Test results
command: |
cd gpt4all-bindings/csharp/Gpt4All.Tests
dotnet tool install -g trx2junit
export PATH="$PATH:$HOME/.dotnet/tools"
trx2junit TestResults/*.trx
- store_test_results:
path: gpt4all-bindings/csharp/Gpt4All.Tests/TestResults
store-and-upload-nupkgs:
docker:
- image: mcr.microsoft.com/dotnet/sdk:8.0
steps:
- attach_workspace:
at: /tmp/workspace
- checkout
- restore_cache:
keys:
- gpt4all-csharp-nuget-packages-nix
- run:
name: NuGet Pack
command: |
cd gpt4all-bindings/csharp
mkdir -p runtimes/linux-x64/native
cp /tmp/workspace/runtimes/linux-x64/*.so runtimes/linux-x64/native/
mkdir -p runtimes/win-x64/native
cp /tmp/workspace/runtimes/win-x64/*.dll runtimes/win-x64/native/
#mkdir -p runtimes/osx/native
#cp /tmp/workspace/runtimes/osx-x64/*.dylib runtimes/osx/native/
#cp /tmp/workspace/runtimes/osx-x64/*.metal runtimes/osx/native/
dotnet pack ./Gpt4All/Gpt4All.csproj -p:IncludeSymbols=true -p:SymbolPackageFormat=snupkg -c Release
dotnet nuget push ./Gpt4All/bin/Release/Gpt4All.*.nupkg -s $NUGET_URL -k $NUGET_TOKEN --skip-duplicate
- store_artifacts:
path: gpt4all-bindings/csharp/Gpt4All/bin/Release
build-nodejs-linux:
docker:
- image: cimg/base:stable
@@ -1059,6 +940,12 @@ workflows:
- build-offline-chat-installer-macos:
requires:
- hold
- sign-offline-chat-installer-macos:
requires:
- build-offline-chat-installer-macos
- notarize-offline-chat-installer-macos:
requires:
- sign-offline-chat-installer-macos
- build-offline-chat-installer-windows:
requires:
- hold
@@ -1140,13 +1027,10 @@ workflows:
or:
- << pipeline.parameters.run-all-workflows >>
- << pipeline.parameters.run-python-workflow >>
- << pipeline.parameters.run-csharp-workflow >>
- << pipeline.parameters.run-ts-workflow >>
jobs:
- hold:
type: approval
- csharp-hold:
type: approval
- nuget-hold:
type: approval
- nodejs-hold:
@@ -1171,12 +1055,6 @@ workflows:
only:
requires:
- hold
- build-bindings-backend-windows-msvc:
filters:
branches:
only:
requires:
- hold
# NodeJs Jobs
- prepare-npm-pkg:
@@ -1201,7 +1079,7 @@ workflows:
only:
requires:
- nodejs-hold
- build-bindings-backend-windows-msvc
- build-bindings-backend-windows
- build-nodejs-macos:
filters:
branches:
@@ -1209,36 +1087,3 @@ workflows:
requires:
- nodejs-hold
- build-bindings-backend-macos
# CSharp Jobs
- build-csharp-linux:
filters:
branches:
only:
requires:
- csharp-hold
- build-bindings-backend-linux
- build-csharp-windows:
filters:
branches:
only:
requires:
- csharp-hold
- build-bindings-backend-windows
- build-csharp-macos:
filters:
branches:
only:
requires:
- csharp-hold
- build-bindings-backend-macos
- store-and-upload-nupkgs:
filters:
branches:
only:
requires:
- nuget-hold
- build-csharp-windows
- build-csharp-linux
#- build-csharp-macos

View File

@@ -0,0 +1,17 @@
import re
import sys
ID_REG = r"id: (.*)"
def main() -> None:
notary_log = sys.argv[1]
with open(notary_log, "r") as f:
notary_output = f.read()
id_m = re.search(ID_REG, notary_output)
if id_m:
print(id_m.group(1))
else:
raise RuntimeError("Unable to parse ID from notarization logs")
if __name__ == "__main__":
main()

View File

@@ -14,6 +14,6 @@ jobs:
steps:
- name: Checkout
uses: actions/checkout@v3
uses: actions/checkout@v4
- name: Codespell
uses: codespell-project/actions-codespell@v2

3
.gitmodules vendored
View File

@@ -2,3 +2,6 @@
path = gpt4all-backend/llama.cpp-mainline
url = https://github.com/nomic-ai/llama.cpp.git
branch = master
[submodule "gpt4all-chat/usearch"]
path = gpt4all-chat/usearch
url = https://github.com/nomic-ai/usearch.git

View File

@@ -67,6 +67,7 @@ An alternative way to install GPT4All is to use one of the offline installers av
* :parrot::link: [Langchain](https://python.langchain.com/en/latest/modules/models/llms/integrations/gpt4all.html)
* :card_file_box: [Weaviate Vector Database](https://github.com/weaviate/weaviate) - [module docs](https://weaviate.io/developers/weaviate/modules/retriever-vectorizer-modules/text2vec-gpt4all)
* :telescope: [OpenLIT (OTel-native Monitoring)](https://github.com/openlit/openlit) - [Docs](https://docs.openlit.io/latest/integrations/gpt4all)
## Contributing

View File

@@ -1,4 +1,4 @@
cmake_minimum_required(VERSION 3.16)
cmake_minimum_required(VERSION 3.21) # for PROJECT_IS_TOP_LEVEL
set(CMAKE_WINDOWS_EXPORT_ALL_SYMBOLS ON)
set(CMAKE_EXPORT_COMPILE_COMMANDS ON)
@@ -65,6 +65,10 @@ if (LLMODEL_VULKAN)
list(APPEND BUILD_VARIANTS vulkan vulkan-avxonly)
endif()
if (LLMODEL_CUDA)
if (DEFINED CMAKE_CUDA_ARCHITECTURES)
set(GGML_CUDA_ARCHITECTURES "${CMAKE_CUDA_ARCHITECTURES}")
endif()
include(CheckLanguage)
check_language(CUDA)
if (NOT CMAKE_CUDA_COMPILER)
@@ -141,7 +145,7 @@ foreach(BUILD_VARIANT IN LISTS BUILD_VARIANTS)
prepare_target(gptj llama-mainline)
endif()
if (BUILD_VARIANT STREQUAL cuda)
if (NOT PROJECT_IS_TOP_LEVEL AND BUILD_VARIANT STREQUAL cuda)
set(CUDAToolkit_BIN_DIR ${CUDAToolkit_BIN_DIR} PARENT_SCOPE)
endif()
endforeach()
@@ -149,7 +153,7 @@ endforeach()
add_library(llmodel
llmodel.h llmodel.cpp llmodel_shared.cpp
llmodel_c.h llmodel_c.cpp
dlhandle.h
dlhandle.cpp
)
target_compile_definitions(llmodel PRIVATE LIB_FILE_EXT="${CMAKE_SHARED_LIBRARY_SUFFIX}")

View File

@@ -0,0 +1,73 @@
#include "dlhandle.h"
#include <string>
#ifndef _WIN32
# include <dlfcn.h>
#else
# include <cassert>
# include <sstream>
# define WIN32_LEAN_AND_MEAN
# ifndef NOMINMAX
# define NOMINMAX
# endif
# include <windows.h>
#endif
using namespace std::string_literals;
namespace fs = std::filesystem;
#ifndef _WIN32
Dlhandle::Dlhandle(const fs::path &fpath)
{
chandle = dlopen(fpath.c_str(), RTLD_LAZY | RTLD_LOCAL);
if (!chandle) {
throw Exception("dlopen: "s + dlerror());
}
}
Dlhandle::~Dlhandle()
{
if (chandle) dlclose(chandle);
}
void *Dlhandle::get_internal(const char *symbol) const
{
return dlsym(chandle, symbol);
}
#else // defined(_WIN32)
Dlhandle::Dlhandle(const fs::path &fpath)
{
fs::path afpath = fs::absolute(fpath);
// Suppress the "Entry Point Not Found" dialog, caused by outdated nvcuda.dll from the GPU driver
UINT lastErrorMode = GetErrorMode();
SetErrorMode(lastErrorMode | SEM_FAILCRITICALERRORS);
chandle = LoadLibraryExW(afpath.c_str(), NULL, LOAD_LIBRARY_SEARCH_DEFAULT_DIRS | LOAD_LIBRARY_SEARCH_DLL_LOAD_DIR);
SetErrorMode(lastErrorMode);
if (!chandle) {
DWORD err = GetLastError();
std::ostringstream ss;
ss << "LoadLibraryExW failed with error 0x" << std::hex << err;
throw Exception(ss.str());
}
}
Dlhandle::~Dlhandle()
{
if (chandle) FreeLibrary(HMODULE(chandle));
}
void *Dlhandle::get_internal(const char *symbol) const
{
return GetProcAddress(HMODULE(chandle), symbol);
}
#endif // defined(_WIN32)

View File

@@ -1,73 +1,15 @@
#ifndef DLHANDLE_H
#define DLHANDLE_H
#ifndef _WIN32
#include <string>
#include <stdexcept>
#include <utility>
#include <dlfcn.h>
#pragma once
class Dlhandle {
void *chandle;
public:
class Exception : public std::runtime_error {
public:
using std::runtime_error::runtime_error;
};
Dlhandle() : chandle(nullptr) {}
Dlhandle(const std::string& fpath, int flags = RTLD_LAZY | RTLD_LOCAL) {
chandle = dlopen(fpath.c_str(), flags);
if (!chandle) {
throw Exception("dlopen(\""+fpath+"\"): "+dlerror());
}
}
Dlhandle(const Dlhandle& o) = delete;
Dlhandle(Dlhandle&& o) : chandle(o.chandle) {
o.chandle = nullptr;
}
~Dlhandle() {
if (chandle) dlclose(chandle);
}
auto operator =(Dlhandle&& o) {
chandle = std::exchange(o.chandle, nullptr);
}
bool is_valid() const {
return chandle != nullptr;
}
operator bool() const {
return is_valid();
}
template<typename T>
T* get(const std::string& fname) const {
auto fres = reinterpret_cast<T*>(dlsym(chandle, fname.c_str()));
return (dlerror()==NULL)?fres:nullptr;
}
auto get_fnc(const std::string& fname) const {
return get<void*(...)>(fname);
}
};
#else
#include <algorithm>
#include <filesystem>
#include <string>
#include <exception>
#include <stdexcept>
#ifndef NOMINMAX
#define NOMINMAX
#endif
#include <windows.h>
#include <libloaderapi.h>
#include <string>
#include <utility>
namespace fs = std::filesystem;
class Dlhandle {
HMODULE chandle;
void *chandle = nullptr;
public:
class Exception : public std::runtime_error {
@@ -75,34 +17,31 @@ public:
using std::runtime_error::runtime_error;
};
Dlhandle() : chandle(nullptr) {}
Dlhandle(const std::string& fpath) {
std::string afpath = std::filesystem::absolute(fpath).string();
std::replace(afpath.begin(), afpath.end(), '/', '\\');
chandle = LoadLibraryExA(afpath.c_str(), NULL, LOAD_LIBRARY_SEARCH_DEFAULT_DIRS | LOAD_LIBRARY_SEARCH_DLL_LOAD_DIR);
if (!chandle) {
throw Exception("dlopen(\""+fpath+"\"): Error");
}
}
Dlhandle(const Dlhandle& o) = delete;
Dlhandle(Dlhandle&& o) : chandle(o.chandle) {
Dlhandle() = default;
Dlhandle(const fs::path &fpath);
Dlhandle(const Dlhandle &o) = delete;
Dlhandle(Dlhandle &&o)
: chandle(o.chandle)
{
o.chandle = nullptr;
}
~Dlhandle() {
if (chandle) FreeLibrary(chandle);
~Dlhandle();
Dlhandle &operator=(Dlhandle &&o) {
chandle = std::exchange(o.chandle, nullptr);
return *this;
}
bool is_valid() const {
return chandle != nullptr;
template <typename T>
T *get(const std::string &symbol) const {
return reinterpret_cast<T *>(get_internal(symbol.c_str()));
}
template<typename T>
T* get(const std::string& fname) const {
return reinterpret_cast<T*>(GetProcAddress(chandle, fname.c_str()));
}
auto get_fnc(const std::string& fname) const {
return get<void*(...)>(fname);
auto get_fnc(const std::string &symbol) const {
return get<void*(...)>(symbol);
}
private:
void *get_internal(const char *symbol) const;
};
#endif
#endif // DLHANDLE_H

View File

@@ -1,33 +1,28 @@
#define GPTJ_H_I_KNOW_WHAT_I_AM_DOING_WHEN_INCLUDING_THIS_FILE
#include "gptj_impl.h"
#include "utils.h"
#include "llmodel.h"
#include "llmodel_shared.h"
#include "utils.h"
#include <ggml.h>
#include <algorithm>
#include <cassert>
#include <cinttypes>
#include <cmath>
#include <cstdio>
#include <cstring>
#include <map>
#include <string>
#include <vector>
#include <ctime>
#include <iostream>
#if defined(_WIN32) && defined(_MSC_VER)
#define WIN32_LEAN_AND_MEAN
#ifndef NOMINMAX
#define NOMINMAX
#endif
#include <windows.h>
#include <io.h>
#include <stdio.h>
#else
#include <unistd.h>
#endif
#include <map>
#include <memory>
#include <random>
#include <sstream>
#include <unordered_set>
#include <ggml.h>
#include <stdexcept>
#include <string>
#include <thread>
#include <vector>
namespace {
const char *modelType_ = "GPT-J";
@@ -128,7 +123,8 @@ static bool kv_cache_init(
}
// load the model's weights from a file path
bool gptj_model_load(const std::string &fname, gptj_model & model, gpt_vocab & vocab, size_t * mem_req = nullptr) {
bool gptj_model_load(const std::string &fname, gptj_model & model, gpt_vocab & vocab, size_t * mem_req = nullptr)
{
printf("%s: loading model from '%s' - please wait ...\n", __func__, fname.c_str());
if(mem_req != nullptr) {
*mem_req = 0;
@@ -672,7 +668,8 @@ GPTJ::GPTJ()
d_ptr->modelLoaded = false;
}
size_t GPTJ::requiredMem(const std::string &modelPath, int n_ctx, int ngl) {
size_t GPTJ::requiredMem(const std::string &modelPath, int n_ctx, int ngl)
{
(void)n_ctx;
(void)ngl;
gptj_model dummy_model;
@@ -682,7 +679,8 @@ size_t GPTJ::requiredMem(const std::string &modelPath, int n_ctx, int ngl) {
return mem_req;
}
bool GPTJ::loadModel(const std::string &modelPath, int n_ctx, int ngl) {
bool GPTJ::loadModel(const std::string &modelPath, int n_ctx, int ngl)
{
(void)n_ctx;
(void)ngl;
d_ptr->modelLoaded = false;
@@ -703,7 +701,8 @@ bool GPTJ::loadModel(const std::string &modelPath, int n_ctx, int ngl) {
return true;
}
void GPTJ::setThreadCount(int32_t n_threads) {
void GPTJ::setThreadCount(int32_t n_threads)
{
d_ptr->n_threads = n_threads;
}
@@ -785,7 +784,8 @@ const std::vector<LLModel::Token> &GPTJ::endTokens() const
return fres;
}
const char *get_arch_name(gguf_context *ctx_gguf) {
const char *get_arch_name(gguf_context *ctx_gguf)
{
const int kid = gguf_find_key(ctx_gguf, "general.architecture");
if (kid == -1)
throw std::runtime_error("key not found in model: general.architecture");
@@ -804,19 +804,23 @@ const char *get_arch_name(gguf_context *ctx_gguf) {
#endif
extern "C" {
DLL_EXPORT bool is_g4a_backend_model_implementation() {
DLL_EXPORT bool is_g4a_backend_model_implementation()
{
return true;
}
DLL_EXPORT const char *get_model_type() {
DLL_EXPORT const char *get_model_type()
{
return modelType_;
}
DLL_EXPORT const char *get_build_variant() {
DLL_EXPORT const char *get_build_variant()
{
return GGML_BUILD_VARIANT;
}
DLL_EXPORT char *get_file_arch(const char *fname) {
DLL_EXPORT char *get_file_arch(const char *fname)
{
struct ggml_context * ctx_meta = NULL;
struct gguf_init_params params = {
/*.no_alloc = */ true,
@@ -837,11 +841,13 @@ DLL_EXPORT char *get_file_arch(const char *fname) {
return arch;
}
DLL_EXPORT bool is_arch_supported(const char *arch) {
DLL_EXPORT bool is_arch_supported(const char *arch)
{
return !strcmp(arch, "gptj");
}
DLL_EXPORT LLModel *construct() {
DLL_EXPORT LLModel *construct()
{
return new GPTJ;
}
}

View File

@@ -4,11 +4,12 @@
#ifndef GPTJ_H
#define GPTJ_H
#include <string>
#include <functional>
#include <vector>
#include "llmodel.h"
#include <functional>
#include <string>
#include <vector>
struct GPTJPrivate;
class GPTJ : public LLModel {
public:

View File

@@ -371,6 +371,20 @@ function(include_ggml SUFFIX)
find_package(CUDAToolkit REQUIRED)
set(CUDAToolkit_BIN_DIR ${CUDAToolkit_BIN_DIR} PARENT_SCOPE)
if (NOT DEFINED GGML_CUDA_ARCHITECTURES)
# 52 == lowest CUDA 12 standard
# 60 == f16 CUDA intrinsics
# 61 == integer CUDA intrinsics
# 70 == compute capability at which unrolling a loop in mul_mat_q kernels is faster
if (LLAMA_CUDA_F16 OR LLAMA_CUDA_DMMV_F16)
set(GGML_CUDA_ARCHITECTURES "60;61;70") # needed for f16 CUDA intrinsics
else()
set(GGML_CUDA_ARCHITECTURES "52;61;70") # lowest CUDA 12 standard + lowest for integer intrinsics
#set(GGML_CUDA_ARCHITECTURES "OFF") # use this to compile much faster, but only F16 models work
endif()
endif()
message(STATUS "Using CUDA architectures: ${GGML_CUDA_ARCHITECTURES}")
set(GGML_HEADERS_CUDA ${DIRECTORY}/ggml-cuda.h)
file(GLOB GGML_SOURCES_CUDA "${DIRECTORY}/ggml-cuda/*.cu")
@@ -406,22 +420,6 @@ function(include_ggml SUFFIX)
endif()
set(LLAMA_EXTRA_LIBS ${LLAMA_EXTRA_LIBS} CUDA::cuda_driver)
if (DEFINED CMAKE_CUDA_ARCHITECTURES)
set(GGML_CUDA_ARCHITECTURES "${CMAKE_CUDA_ARCHITECTURES}")
else()
# 52 == lowest CUDA 12 standard
# 60 == f16 CUDA intrinsics
# 61 == integer CUDA intrinsics
# 70 == compute capability at which unrolling a loop in mul_mat_q kernels is faster
if (LLAMA_CUDA_F16 OR LLAMA_CUDA_DMMV_F16)
set(GGML_CUDA_ARCHITECTURES "60;61;70") # needed for f16 CUDA intrinsics
else()
set(GGML_CUDA_ARCHITECTURES "52;61;70") # lowest CUDA 12 standard + lowest for integer intrinsics
#set(GGML_CUDA_ARCHITECTURES "") # use this to compile much faster, but only F16 models work
endif()
endif()
message(STATUS "Using CUDA architectures: ${GGML_CUDA_ARCHITECTURES}")
endif()
if (LLAMA_CLBLAST)

View File

@@ -1,26 +1,33 @@
#define LLAMAMODEL_H_I_KNOW_WHAT_I_AM_DOING_WHEN_INCLUDING_THIS_FILE
#include "llamamodel_impl.h"
#include "llmodel.h"
#include <ggml.h>
#include <llama.h>
#include <algorithm>
#include <cassert>
#include <cmath>
#include <cstdint>
#include <cstdio>
#include <cstdlib>
#include <cstring>
#include <fstream>
#include <functional>
#include <initializer_list>
#include <iomanip>
#include <iostream>
#include <map>
#include <iterator>
#include <memory>
#include <numeric>
#include <random>
#include <optional>
#include <sstream>
#include <stdexcept>
#include <string>
#include <thread>
#include <unordered_set>
#include <vector>
#include <llama.h>
#include <ggml.h>
#ifdef GGML_USE_KOMPUTE
# include <ggml-kompute.h>
#elif GGML_USE_VULKAN
@@ -31,6 +38,7 @@
using namespace std::string_literals;
// Maximum supported GGUF version
static constexpr int GGUF_VER_MAX = 3;
@@ -76,16 +84,19 @@ static const std::vector<const char *> EMBEDDING_ARCHES {
"bert", "nomic-bert",
};
static bool is_embedding_arch(const std::string &arch) {
static bool is_embedding_arch(const std::string &arch)
{
return std::find(EMBEDDING_ARCHES.begin(), EMBEDDING_ARCHES.end(), arch) < EMBEDDING_ARCHES.end();
}
static bool llama_verbose() {
static bool llama_verbose()
{
const char* var = getenv("GPT4ALL_VERBOSE_LLAMACPP");
return var && *var;
}
static void llama_log_callback(enum ggml_log_level level, const char *text, void *userdata) {
static void llama_log_callback(enum ggml_log_level level, const char *text, void *userdata)
{
(void)userdata;
if (llama_verbose() || level <= GGML_LOG_LEVEL_ERROR) {
fputs(text, stderr);
@@ -139,7 +150,8 @@ static int llama_sample_top_p_top_k(
return llama_sample_token(ctx, &candidates_p);
}
const char *get_arch_name(gguf_context *ctx_gguf) {
const char *get_arch_name(gguf_context *ctx_gguf)
{
const int kid = gguf_find_key(ctx_gguf, "general.architecture");
if (kid == -1)
throw std::runtime_error("key not found in model: general.architecture");
@@ -151,7 +163,8 @@ const char *get_arch_name(gguf_context *ctx_gguf) {
return gguf_get_val_str(ctx_gguf, kid);
}
static gguf_context *load_gguf(const char *fname) {
static gguf_context *load_gguf(const char *fname)
{
struct gguf_init_params params = {
/*.no_alloc = */ true,
/*.ctx = */ nullptr,
@@ -172,7 +185,8 @@ static gguf_context *load_gguf(const char *fname) {
return ctx;
}
static int32_t get_arch_key_u32(std::string const &modelPath, std::string const &archKey) {
static int32_t get_arch_key_u32(std::string const &modelPath, std::string const &archKey)
{
int32_t value = -1;
std::string arch;
@@ -229,7 +243,8 @@ struct llama_file_hparams {
enum llama_ftype ftype = LLAMA_FTYPE_MOSTLY_F16;
};
size_t LLamaModel::requiredMem(const std::string &modelPath, int n_ctx, int ngl) {
size_t LLamaModel::requiredMem(const std::string &modelPath, int n_ctx, int ngl)
{
// TODO(cebtenzzre): update to GGUF
(void)ngl; // FIXME(cetenzzre): use this value
auto fin = std::ifstream(modelPath, std::ios::binary);
@@ -253,7 +268,8 @@ size_t LLamaModel::requiredMem(const std::string &modelPath, int n_ctx, int ngl)
return filesize + est_kvcache_size;
}
bool LLamaModel::isModelBlacklisted(const std::string &modelPath) const {
bool LLamaModel::isModelBlacklisted(const std::string &modelPath) const
{
auto * ctx = load_gguf(modelPath.c_str());
if (!ctx) {
std::cerr << __func__ << ": failed to load " << modelPath << "\n";
@@ -289,7 +305,8 @@ bool LLamaModel::isModelBlacklisted(const std::string &modelPath) const {
return res;
}
bool LLamaModel::isEmbeddingModel(const std::string &modelPath) const {
bool LLamaModel::isEmbeddingModel(const std::string &modelPath) const
{
bool result = false;
std::string arch;
@@ -354,6 +371,11 @@ bool LLamaModel::loadModel(const std::string &modelPath, int n_ctx, int ngl)
d_ptr->model_params.main_gpu = d_ptr->device;
d_ptr->model_params.n_gpu_layers = ngl;
d_ptr->model_params.split_mode = LLAMA_SPLIT_MODE_NONE;
} else {
#ifdef GGML_USE_CUDA
std::cerr << "Llama ERROR: CUDA loadModel was called without a device\n";
return false;
#endif // GGML_USE_CUDA
}
#elif defined(GGML_USE_METAL)
(void)ngl;
@@ -366,15 +388,17 @@ bool LLamaModel::loadModel(const std::string &modelPath, int n_ctx, int ngl)
// always fully offload on Metal
// TODO(cebtenzzre): use this parameter to allow using more than 53% of system RAM to load a model
d_ptr->model_params.n_gpu_layers = 100;
#else
#else // !KOMPUTE && !VULKAN && !CUDA && !METAL
(void)ngl;
#endif
d_ptr->model = llama_load_model_from_file_gpt4all(modelPath.c_str(), &d_ptr->model_params);
d_ptr->model = llama_load_model_from_file(modelPath.c_str(), d_ptr->model_params);
if (!d_ptr->model) {
fflush(stdout);
#ifndef GGML_USE_CUDA
d_ptr->device = -1;
d_ptr->deviceName.clear();
#endif
std::cerr << "LLAMA ERROR: failed to load model from " << modelPath << std::endl;
return false;
}
@@ -386,7 +410,8 @@ bool LLamaModel::loadModel(const std::string &modelPath, int n_ctx, int ngl)
bool isEmbedding = is_embedding_arch(llama_model_arch(d_ptr->model));
const int n_ctx_train = llama_n_ctx_train(d_ptr->model);
if (isEmbedding) {
d_ptr->ctx_params.n_batch = n_ctx;
d_ptr->ctx_params.n_batch = n_ctx;
d_ptr->ctx_params.n_ubatch = n_ctx;
} else {
if (n_ctx > n_ctx_train) {
std::cerr << "warning: model was trained on only " << n_ctx_train << " context tokens ("
@@ -416,8 +441,10 @@ bool LLamaModel::loadModel(const std::string &modelPath, int n_ctx, int ngl)
std::cerr << "LLAMA ERROR: failed to init context for model " << modelPath << std::endl;
llama_free_model(d_ptr->model);
d_ptr->model = nullptr;
#ifndef GGML_USE_CUDA
d_ptr->device = -1;
d_ptr->deviceName.clear();
#endif
return false;
}
@@ -444,12 +471,14 @@ bool LLamaModel::loadModel(const std::string &modelPath, int n_ctx, int ngl)
return true;
}
void LLamaModel::setThreadCount(int32_t n_threads) {
void LLamaModel::setThreadCount(int32_t n_threads)
{
d_ptr->n_threads = n_threads;
llama_set_n_threads(d_ptr->ctx, n_threads, n_threads);
}
int32_t LLamaModel::threadCount() const {
int32_t LLamaModel::threadCount() const
{
return d_ptr->n_threads;
}
@@ -572,7 +601,8 @@ int32_t LLamaModel::layerCount(std::string const &modelPath) const
}
#ifdef GGML_USE_VULKAN
static const char *getVulkanVendorName(uint32_t vendorID) {
static const char *getVulkanVendorName(uint32_t vendorID)
{
switch (vendorID) {
case 0x10DE: return "nvidia";
case 0x1002: return "amd";
@@ -702,41 +732,30 @@ bool LLamaModel::initializeGPUDevice(int device, std::string *unavail_reason) co
#endif
}
bool LLamaModel::hasGPUDevice() const
{
#if defined(GGML_USE_KOMPUTE) || defined(GGML_USE_VULKAN) || defined(GGML_USE_CUDA)
return d_ptr->device != -1;
#else
return false;
#endif
}
bool LLamaModel::usingGPUDevice() const
{
bool hasDevice;
if (!d_ptr->model)
return false;
bool usingGPU = llama_model_using_gpu(d_ptr->model);
#ifdef GGML_USE_KOMPUTE
hasDevice = hasGPUDevice() && d_ptr->model_params.n_gpu_layers > 0;
assert(!hasDevice || ggml_vk_has_device());
#elif defined(GGML_USE_VULKAN) || defined(GGML_USE_CUDA)
hasDevice = hasGPUDevice() && d_ptr->model_params.n_gpu_layers > 0;
#elif defined(GGML_USE_METAL)
hasDevice = true;
#else
hasDevice = false;
assert(!usingGPU || ggml_vk_has_device());
#endif
return hasDevice;
return usingGPU;
}
const char *LLamaModel::backendName() const {
const char *LLamaModel::backendName() const
{
return d_ptr->backend_name;
}
const char *LLamaModel::gpuDeviceName() const {
const char *LLamaModel::gpuDeviceName() const
{
if (usingGPUDevice()) {
#if defined(GGML_USE_KOMPUTE) || defined(GGML_USE_VULKAN) || defined(GGML_USE_CUDA)
return d_ptr->deviceName.c_str();
#elif defined(GGML_USE_METAL)
return "Metal";
#endif
}
return nullptr;
@@ -759,13 +778,15 @@ void llama_batch_add(
batch.n_tokens++;
}
static void batch_add_seq(llama_batch &batch, const std::vector<LLModel::Token> &tokens, int seq_id) {
static void batch_add_seq(llama_batch &batch, const std::vector<LLModel::Token> &tokens, int seq_id)
{
for (unsigned i = 0; i < tokens.size(); i++) {
llama_batch_add(batch, tokens[i], i, { seq_id }, i == tokens.size() - 1);
}
}
size_t LLamaModel::embeddingSize() const {
size_t LLamaModel::embeddingSize() const
{
return llama_n_embd(d_ptr->model);
}
@@ -885,12 +906,14 @@ void LLamaModel::embed(
// MD5 hash of "nomic empty"
static const char EMPTY_PLACEHOLDER[] = "24df574ea1c998de59d5be15e769658e";
auto product(double a) -> std::function<double(double)> {
auto product(double a) -> std::function<double(double)>
{
return [a](double b) { return a * b; };
}
template <typename T>
double getL2NormScale(T *start, T *end) {
double getL2NormScale(T *start, T *end)
{
double magnitude = std::sqrt(std::inner_product(start, end, start, 0.0));
return 1.0 / std::max(magnitude, 1e-12);
}
@@ -920,11 +943,11 @@ void LLamaModel::embedInternal(
int32_t n_tokens = llama_tokenize(d_ptr->model, text.c_str(), text.length(), tokens.data(), tokens.size(), wantBOS, false);
if (n_tokens) {
(void)eos_token;
assert(useEOS == (eos_token != -1 && tokens[n_tokens - 1] == eos_token));
tokens.resize(n_tokens - useEOS); // erase EOS/SEP
} else {
tokens.clear();
assert((useEOS && wantBOS) == (eos_token != -1 && tokens[n_tokens - 1] == eos_token));
if (useEOS && wantBOS)
n_tokens--; // erase EOS/SEP
}
tokens.resize(n_tokens);
};
// tokenize the texts
@@ -976,14 +999,14 @@ void LLamaModel::embedInternal(
size_t totalTokens = 0;
for (unsigned i = 0; i < inputs.size(); i++) {
auto &input = inputs[i];
for (auto it = input.begin(); it < input.end(); it += max_len) {
if (it > input.begin()) { it -= chunkOverlap; }
auto end = std::min(it + max_len, input.end());
for (unsigned j = 0; j < input.size(); j += max_len) {
if (j) { j -= chunkOverlap; }
unsigned end = std::min(j + max_len, unsigned(input.size()));
batches.push_back({ i, {} });
auto &batch = batches.back().batch;
batch = prefixTokens;
batch.insert(batch.end(), it, end);
totalTokens += end - it;
batch.insert(batch.end(), input.begin() + j, input.begin() + end);
totalTokens += end - j;
batch.push_back(eos_token);
if (!doMean) { break; /* limit text to one chunk */ }
}
@@ -1098,19 +1121,23 @@ void LLamaModel::embedInternal(
#endif
extern "C" {
DLL_EXPORT bool is_g4a_backend_model_implementation() {
DLL_EXPORT bool is_g4a_backend_model_implementation()
{
return true;
}
DLL_EXPORT const char *get_model_type() {
DLL_EXPORT const char *get_model_type()
{
return modelType_;
}
DLL_EXPORT const char *get_build_variant() {
DLL_EXPORT const char *get_build_variant()
{
return GGML_BUILD_VARIANT;
}
DLL_EXPORT char *get_file_arch(const char *fname) {
DLL_EXPORT char *get_file_arch(const char *fname)
{
char *arch = nullptr;
std::string archStr;
@@ -1135,11 +1162,13 @@ cleanup:
return arch;
}
DLL_EXPORT bool is_arch_supported(const char *arch) {
DLL_EXPORT bool is_arch_supported(const char *arch)
{
return std::find(KNOWN_ARCHES.begin(), KNOWN_ARCHES.end(), std::string(arch)) < KNOWN_ARCHES.end();
}
DLL_EXPORT LLModel *construct() {
DLL_EXPORT LLModel *construct()
{
llama_log_set(llama_log_callback, nullptr);
return new LLamaModel;
}

View File

@@ -4,11 +4,12 @@
#ifndef LLAMAMODEL_H
#define LLAMAMODEL_H
#include "llmodel.h"
#include <functional>
#include <memory>
#include <string>
#include <vector>
#include "llmodel.h"
struct LLamaPrivate;
struct EmbModelSpec;
@@ -33,7 +34,6 @@ public:
std::vector<GPUDevice> availableGPUDevices(size_t memoryRequired = 0) const override;
bool initializeGPUDevice(size_t memoryRequired, const std::string &name) const override;
bool initializeGPUDevice(int device, std::string *unavail_reason = nullptr) const override;
bool hasGPUDevice() const override;
bool usingGPUDevice() const override;
const char *backendName() const override;
const char *gpuDeviceName() const override;

View File

@@ -1,12 +1,13 @@
#include "llmodel.h"
#include "dlhandle.h"
#include "sysinfo.h"
#include <cassert>
#include <cstdlib>
#include <filesystem>
#include <fstream>
#include <iostream>
#include <iterator>
#include <memory>
#include <optional>
#include <regex>
@@ -15,10 +16,24 @@
#include <unordered_map>
#include <vector>
#ifdef _MSC_VER
#include <intrin.h>
#ifdef _WIN32
# define WIN32_LEAN_AND_MEAN
# ifndef NOMINMAX
# define NOMINMAX
# endif
# include <windows.h>
#endif
#ifdef _MSC_VER
# include <intrin.h>
#endif
#if defined(__APPLE__) && defined(__aarch64__)
# include "sysinfo.h" // for getSystemTotalRAMInBytes
#endif
namespace fs = std::filesystem;
#ifndef __APPLE__
static const std::string DEFAULT_BACKENDS[] = {"kompute", "cpu"};
#elif defined(__aarch64__)
@@ -77,15 +92,33 @@ LLModel::Implementation::Implementation(Implementation &&o)
o.m_dlhandle = nullptr;
}
LLModel::Implementation::~Implementation() {
LLModel::Implementation::~Implementation()
{
delete m_dlhandle;
}
static bool isImplementation(const Dlhandle &dl) {
static bool isImplementation(const Dlhandle &dl)
{
return dl.get<bool(uint32_t)>("is_g4a_backend_model_implementation");
}
const std::vector<LLModel::Implementation> &LLModel::Implementation::implementationList() {
// Add the CUDA Toolkit to the DLL search path on Windows.
// This is necessary for chat.exe to find CUDA when started from Qt Creator.
static void addCudaSearchPath()
{
#ifdef _WIN32
if (const auto *cudaPath = _wgetenv(L"CUDA_PATH")) {
auto libDir = std::wstring(cudaPath) + L"\\bin";
if (!AddDllDirectory(libDir.c_str())) {
auto err = GetLastError();
std::wcerr << L"AddDllDirectory(\"" << libDir << L"\") failed with error 0x" << std::hex << err << L"\n";
}
}
#endif
}
const std::vector<LLModel::Implementation> &LLModel::Implementation::implementationList()
{
if (cpu_supports_avx() == 0) {
throw std::runtime_error("CPU does not support AVX");
}
@@ -95,6 +128,8 @@ const std::vector<LLModel::Implementation> &LLModel::Implementation::implementat
static auto* libs = new std::vector<Implementation>([] () {
std::vector<Implementation> fres;
addCudaSearchPath();
std::string impl_name_re = "(gptj|llamamodel-mainline)-(cpu|metal|kompute|vulkan|cuda)";
if (cpu_supports_avx2() == 0) {
impl_name_re += "-avxonly";
@@ -105,21 +140,27 @@ const std::vector<LLModel::Implementation> &LLModel::Implementation::implementat
std::string path;
// Split the paths string by the delimiter and process each path.
while (std::getline(ss, path, ';')) {
std::filesystem::path fs_path(path);
std::u8string u8_path(path.begin(), path.end());
// Iterate over all libraries
for (const auto& f : std::filesystem::directory_iterator(fs_path)) {
const std::filesystem::path& p = f.path();
for (const auto &f : fs::directory_iterator(u8_path)) {
const fs::path &p = f.path();
if (p.extension() != LIB_FILE_EXT) continue;
if (!std::regex_search(p.stem().string(), re)) continue;
// Add to list if model implementation
Dlhandle dl;
try {
Dlhandle dl(p.string());
if (!isImplementation(dl))
continue;
fres.emplace_back(Implementation(std::move(dl)));
} catch (...) {}
dl = Dlhandle(p);
} catch (const Dlhandle::Exception &e) {
std::cerr << "Failed to load " << p.filename().string() << ": " << e.what() << "\n";
continue;
}
if (!isImplementation(dl)) {
std::cerr << "Not an implementation: " << p.filename().string() << "\n";
continue;
}
fres.emplace_back(Implementation(std::move(dl)));
}
}
};
@@ -132,14 +173,16 @@ const std::vector<LLModel::Implementation> &LLModel::Implementation::implementat
return *libs;
}
static std::string applyCPUVariant(const std::string &buildVariant) {
static std::string applyCPUVariant(const std::string &buildVariant)
{
if (buildVariant != "metal" && cpu_supports_avx2() == 0) {
return buildVariant + "-avxonly";
}
return buildVariant;
}
const LLModel::Implementation* LLModel::Implementation::implementation(const char *fname, const std::string& buildVariant) {
const LLModel::Implementation* LLModel::Implementation::implementation(const char *fname, const std::string& buildVariant)
{
bool buildVariantMatched = false;
std::optional<std::string> archName;
for (const auto& i : implementationList()) {
@@ -163,7 +206,8 @@ const LLModel::Implementation* LLModel::Implementation::implementation(const cha
throw BadArchError(std::move(*archName));
}
LLModel *LLModel::Implementation::construct(const std::string &modelPath, const std::string &backend, int n_ctx) {
LLModel *LLModel::Implementation::construct(const std::string &modelPath, const std::string &backend, int n_ctx)
{
std::vector<std::string> desiredBackends;
if (backend != "auto") {
desiredBackends.push_back(backend);
@@ -203,7 +247,8 @@ LLModel *LLModel::Implementation::construct(const std::string &modelPath, const
throw MissingImplementationError("Could not find any implementations for backend: " + backend);
}
LLModel *LLModel::Implementation::constructGlobalLlama(const std::optional<std::string> &backend) {
LLModel *LLModel::Implementation::constructGlobalLlama(const std::optional<std::string> &backend)
{
static std::unordered_map<std::string, std::unique_ptr<LLModel>> implCache;
const std::vector<Implementation> *impls;
@@ -247,7 +292,8 @@ LLModel *LLModel::Implementation::constructGlobalLlama(const std::optional<std::
return nullptr;
}
std::vector<LLModel::GPUDevice> LLModel::Implementation::availableGPUDevices(size_t memoryRequired) {
std::vector<LLModel::GPUDevice> LLModel::Implementation::availableGPUDevices(size_t memoryRequired)
{
std::vector<LLModel::GPUDevice> devices;
#ifndef __APPLE__
static const std::string backends[] = {"kompute", "cuda"};
@@ -262,33 +308,40 @@ std::vector<LLModel::GPUDevice> LLModel::Implementation::availableGPUDevices(siz
return devices;
}
int32_t LLModel::Implementation::maxContextLength(const std::string &modelPath) {
int32_t LLModel::Implementation::maxContextLength(const std::string &modelPath)
{
auto *llama = constructGlobalLlama();
return llama ? llama->maxContextLength(modelPath) : -1;
}
int32_t LLModel::Implementation::layerCount(const std::string &modelPath) {
int32_t LLModel::Implementation::layerCount(const std::string &modelPath)
{
auto *llama = constructGlobalLlama();
return llama ? llama->layerCount(modelPath) : -1;
}
bool LLModel::Implementation::isEmbeddingModel(const std::string &modelPath) {
bool LLModel::Implementation::isEmbeddingModel(const std::string &modelPath)
{
auto *llama = constructGlobalLlama();
return llama && llama->isEmbeddingModel(modelPath);
}
void LLModel::Implementation::setImplementationsSearchPath(const std::string& path) {
void LLModel::Implementation::setImplementationsSearchPath(const std::string& path)
{
s_implementations_search_path = path;
}
const std::string& LLModel::Implementation::implementationsSearchPath() {
const std::string& LLModel::Implementation::implementationsSearchPath()
{
return s_implementations_search_path;
}
bool LLModel::Implementation::hasSupportedCPU() {
bool LLModel::Implementation::hasSupportedCPU()
{
return cpu_supports_avx() != 0;
}
int LLModel::Implementation::cpuSupportsAVX2() {
int LLModel::Implementation::cpuSupportsAVX2()
{
return cpu_supports_avx2();
}

View File

@@ -2,14 +2,16 @@
#define LLMODEL_H
#include <algorithm>
#include <cassert>
#include <cstddef>
#include <cstdint>
#include <fstream>
#include <functional>
#include <limits>
#include <optional>
#include <stdexcept>
#include <string>
#include <string_view>
#include <unordered_map>
#include <utility>
#include <vector>
using namespace std::string_literals;
@@ -56,23 +58,30 @@ public:
backend(backend), index(index), type(type), heapSize(heapSize), name(std::move(name)),
vendor(std::move(vendor)) {}
std::string selectionName() const { return m_backendNames.at(backend) + ": " + name; }
std::string reportedName() const { return name + " (" + m_backendNames.at(backend) + ")"; }
std::string selectionName() const
{
assert(backend == "cuda"s || backend == "kompute"s);
return backendName() + ": " + name;
}
std::string backendName() const { return backendIdToName(backend); }
static std::string backendIdToName(const std::string &backend) { return s_backendNames.at(backend); }
static std::string updateSelectionName(const std::string &name) {
if (name == "Auto" || name == "CPU" || name == "Metal")
return name;
auto it = std::find_if(m_backendNames.begin(), m_backendNames.end(), [&name](const auto &entry) {
auto it = std::find_if(s_backendNames.begin(), s_backendNames.end(), [&name](const auto &entry) {
return name.starts_with(entry.second + ": ");
});
if (it != m_backendNames.end())
if (it != s_backendNames.end())
return name;
return "Vulkan: " + name; // previously, there were only Vulkan devices
}
private:
static inline const std::unordered_map<std::string, std::string> m_backendNames {
{"cuda", "CUDA"}, {"kompute", "Vulkan"},
static inline const std::unordered_map<std::string, std::string> s_backendNames {
{"cpu", "CPU"}, {"metal", "Metal"}, {"cuda", "CUDA"}, {"kompute", "Vulkan"},
};
};
@@ -195,7 +204,6 @@ public:
return false;
}
virtual bool hasGPUDevice() const { return false; }
virtual bool usingGPUDevice() const { return false; }
virtual const char *backendName() const { return "cpu"; }
virtual const char *gpuDeviceName() const { return nullptr; }

View File

@@ -1,12 +1,18 @@
#include "llmodel_c.h"
#include "llmodel.h"
#include <cerrno>
#include <algorithm>
#include <cstdio>
#include <cstdlib>
#include <cstring>
#include <exception>
#include <functional>
#include <iostream>
#include <memory>
#include <optional>
#include <utility>
#include <string>
#include <vector>
struct LLModelWrapper {
LLModel *llModel = nullptr;
@@ -14,7 +20,8 @@ struct LLModelWrapper {
~LLModelWrapper() { delete llModel; }
};
llmodel_model llmodel_model_create(const char *model_path) {
llmodel_model llmodel_model_create(const char *model_path)
{
const char *error;
auto fres = llmodel_model_create2(model_path, "auto", &error);
if (!fres) {
@@ -23,7 +30,8 @@ llmodel_model llmodel_model_create(const char *model_path) {
return fres;
}
static void llmodel_set_error(const char **errptr, const char *message) {
static void llmodel_set_error(const char **errptr, const char *message)
{
thread_local static std::string last_error_message;
if (errptr) {
last_error_message = message;
@@ -31,7 +39,8 @@ static void llmodel_set_error(const char **errptr, const char *message) {
}
}
llmodel_model llmodel_model_create2(const char *model_path, const char *backend, const char **error) {
llmodel_model llmodel_model_create2(const char *model_path, const char *backend, const char **error)
{
LLModel *llModel;
try {
llModel = LLModel::Implementation::construct(model_path, backend);
@@ -45,7 +54,8 @@ llmodel_model llmodel_model_create2(const char *model_path, const char *backend,
return wrapper;
}
void llmodel_model_destroy(llmodel_model model) {
void llmodel_model_destroy(llmodel_model model)
{
delete static_cast<LLModelWrapper *>(model);
}
@@ -277,12 +287,6 @@ bool llmodel_gpu_init_gpu_device_by_int(llmodel_model model, int device)
return wrapper->llModel->initializeGPUDevice(device);
}
bool llmodel_has_gpu_device(llmodel_model model)
{
const auto *wrapper = static_cast<LLModelWrapper *>(model);
return wrapper->llModel->hasGPUDevice();
}
const char *llmodel_model_backend_name(llmodel_model model)
{
const auto *wrapper = static_cast<LLModelWrapper *>(model);

View File

@@ -1,9 +1,9 @@
#ifndef LLMODEL_C_H
#define LLMODEL_C_H
#include <stdint.h>
#include <stddef.h>
#include <stdbool.h>
#include <stddef.h>
#include <stdint.h>
#ifdef __GNUC__
#define DEPRECATED __attribute__ ((deprecated))
@@ -291,11 +291,6 @@ bool llmodel_gpu_init_gpu_device_by_struct(llmodel_model model, const llmodel_gp
*/
bool llmodel_gpu_init_gpu_device_by_int(llmodel_model model, int device);
/**
* @return True if a GPU device is successfully initialized, false otherwise.
*/
bool llmodel_has_gpu_device(llmodel_model model);
/**
* @return The name of the llama.cpp backend currently in use. One of "cpu", "kompute", or "metal".
*/

View File

@@ -1,13 +1,21 @@
#include "llmodel.h"
#include <algorithm>
#include <cassert>
#include <cstddef>
#include <cstdint>
#include <functional>
#include <iostream>
#include <optional>
#include <regex>
#include <stdexcept>
#include <string>
#include <unordered_set>
#include <vector>
// TODO(cebtenzzre): replace this with llama_kv_cache_seq_shift for llamamodel (GPT-J needs this as-is)
void LLModel::recalculateContext(PromptContext &promptCtx, std::function<bool(bool)> recalculate) {
void LLModel::recalculateContext(PromptContext &promptCtx, std::function<bool(bool)> recalculate)
{
int n_keep = shouldAddBOS();
const int32_t n_discard = (promptCtx.n_ctx - n_keep) * promptCtx.contextErase;
@@ -36,7 +44,8 @@ stop_generating:
recalculate(false);
}
static bool parsePromptTemplate(const std::string &tmpl, std::vector<std::smatch> &placeholders, std::string &err) {
static bool parsePromptTemplate(const std::string &tmpl, std::vector<std::smatch> &placeholders, std::string &err)
{
static const std::regex placeholderRegex(R"(%[1-2](?![0-9]))");
auto it = std::sregex_iterator(tmpl.begin(), tmpl.end(), placeholderRegex);

View File

@@ -1,9 +1,11 @@
#pragma once
#include <cstdint>
#include <cstddef>
#include <vector>
#include <ggml.h>
#include <cstddef>
#include <cstdint>
#include <vector>
struct llm_buffer {
uint8_t * addr = NULL;
size_t size = 0;
@@ -36,7 +38,8 @@ struct llm_kv_cache {
}
};
inline void ggml_graph_compute_g4a(llm_buffer& buf, ggml_cgraph * graph, int n_threads) {
inline void ggml_graph_compute_g4a(llm_buffer& buf, ggml_cgraph * graph, int n_threads)
{
struct ggml_cplan plan = ggml_graph_plan(graph, n_threads);
if (plan.work_size > 0) {
buf.resize(plan.work_size);

View File

@@ -2,17 +2,21 @@
#define SYSINFO_H
#include <fstream>
#include <string>
#include <sstream>
#include <iomanip>
#include <sstream>
#include <string>
#if defined(__linux__)
#include <unistd.h>
# include <unistd.h>
#elif defined(__APPLE__)
#include <sys/types.h>
#include <sys/sysctl.h>
# include <sys/types.h>
# include <sys/sysctl.h>
#elif defined(_WIN32)
#include <windows.h>
# define WIN32_LEAN_AND_MEAN
# ifndef NOMINMAX
# define NOMINMAX
# endif
# include <windows.h>
#endif
static long long getSystemTotalRAMInBytes()

View File

@@ -1,9 +1,15 @@
#include "utils.h"
#include <cmath>
#include <cstdio>
#include <cstdlib>
#include <fstream>
#include <iterator>
#include <regex>
#include <utility>
void replace(std::string & str, const std::string & needle, const std::string & replacement) {
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);
@@ -11,7 +17,8 @@ void replace(std::string & str, const std::string & needle, const std::string &
}
}
std::map<std::string, int32_t> json_parse(const std::string & fname) {
std::map<std::string, int32_t> json_parse(const std::string & fname)
{
std::map<std::string, int32_t> result;
// read file into string
@@ -102,7 +109,8 @@ std::map<std::string, int32_t> json_parse(const std::string & fname) {
return result;
}
std::vector<gpt_vocab::id> gpt_tokenize_inner(const gpt_vocab & vocab, const std::string & text) {
std::vector<gpt_vocab::id> gpt_tokenize_inner(const gpt_vocab & vocab, const std::string & text)
{
std::vector<std::string> words;
// first split the text into words
@@ -157,12 +165,14 @@ std::vector<gpt_vocab::id> gpt_tokenize_inner(const gpt_vocab & vocab, const std
return tokens;
}
std::string regex_escape(const std::string &s) {
std::string regex_escape(const std::string &s)
{
static const std::regex metacharacters(R"([\.\^\$\-\+\(\)\[\]\{\}\|\?\*])");
return std::regex_replace(s, metacharacters, "\\$&");
}
std::vector<gpt_vocab::id> gpt_tokenize(const gpt_vocab & vocab, const std::string & text) {
std::vector<gpt_vocab::id> gpt_tokenize(const gpt_vocab & vocab, const std::string & text)
{
// Generate the subpattern from the special_tokens vector if it's not empty
if (!vocab.special_tokens.empty()) {
std::vector<gpt_vocab::id> out;
@@ -198,7 +208,8 @@ std::vector<gpt_vocab::id> gpt_tokenize(const gpt_vocab & vocab, const std::stri
}
bool gpt_vocab_init(const std::string & fname, gpt_vocab & vocab) {
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);
@@ -325,4 +336,4 @@ gpt_vocab::id gpt_sample_top_k_top_p(
int idx = dist(rng);
return logits_id[idx].second;
}
}

View File

@@ -2,16 +2,20 @@
#pragma once
#include <string>
#include <algorithm>
#include <cstddef>
#include <cstdint>
#include <map>
#include <vector>
#include <random>
#include <string>
#include <thread>
#include <vector>
//
// General purpose inline functions
//
constexpr inline unsigned long long operator ""_MiB(unsigned long long bytes) {
constexpr inline unsigned long long operator ""_MiB(unsigned long long bytes)
{
return bytes*1024*1024;
}

View File

@@ -1,3 +1,21 @@
# GPT4All Bindings
This directory will contain language specific bindings on top of the C/C++ model backends.
We will have one directory per language binding (e.g. Python, Typescript, Golang, etc.).
# GPT4All Language Bindings
These are the language bindings for the GPT4All backend. They provide functionality to load GPT4All models (and other llama.cpp models), generate text, and (in the case of the Python bindings) embed text as a vector representation.
See their respective folders for language-specific documentation.
### Languages
- [Python](https://github.com/nomic-ai/gpt4all/tree/main/gpt4all-bindings/python) (Nomic official, maintained by [@cebtenzzre](https://github.com/cebtenzzre))
- [Node.js/Typescript](https://github.com/nomic-ai/gpt4all/tree/main/gpt4all-bindings/typescript) (community, maintained by [@jacoobes](https://github.com/jacoobes) and [@iimez](https://github.com/iimez))
<br/>
<br/>
<details><summary><b>Archived Bindings</b></summary>
<br/>
The following bindings have been removed from this repository due to lack of maintenance. If adopted, they can be brought back&mdash;feel free to message a developer on Dicsord if you are interested in maintaining one of them. Below are links to their last available version (not necessarily the last working version).
- C#: [41c9013f](https://github.com/nomic-ai/gpt4all/tree/41c9013fa46a194b3e4fee6ced1b9d1b65e177ac/gpt4all-bindings/csharp)
- Java: [41c9013f](https://github.com/nomic-ai/gpt4all/tree/41c9013fa46a194b3e4fee6ced1b9d1b65e177ac/gpt4all-bindings/java)
- Go: [41c9013f](https://github.com/nomic-ai/gpt4all/tree/41c9013fa46a194b3e4fee6ced1b9d1b65e177ac/gpt4all-bindings/golang)
</details>

View File

@@ -1,348 +0,0 @@
# EditorConfig is awesome: https://EditorConfig.org
# top-most EditorConfig file
root = true
# Don't use tabs for indentation.
[*]
indent_style = space
# (Please don't specify an indent_size here; that has too many unintended consequences.)
# Code files
[*.{cs,csx,vb,vbx}]
indent_size = 4
insert_final_newline = true
charset = utf-8-bom
# XML project files
[*.{csproj,vbproj,vcxproj,vcxproj.filters,proj,projitems,shproj}]
indent_size = 4
# XML config files
[*.{props,targets,ruleset,config,nuspec,resx,vsixmanifest,vsct}]
indent_size = 2
# JSON files
[*.json]
indent_size = 2
# Powershell files
[*.ps1]
indent_size = 2
# Shell script files
[*.sh]
end_of_line = lf
indent_size = 2
insert_final_newline = true
# Dotnet code style settings:
[*.{cs,vb}]
# IDE0055: Fix formatting
dotnet_diagnostic.IDE0055.severity = error
dotnet_diagnostic.CS1573.severity = suggestion
dotnet_diagnostic.CS1591.severity = suggestion
# Sort using and Import directives with System.* appearing first
dotnet_sort_system_directives_first = true
dotnet_separate_import_directive_groups = false
# Avoid "this." and "Me." if not necessary
dotnet_style_qualification_for_field = false:suggestion
dotnet_style_qualification_for_property = false:suggestion
dotnet_style_qualification_for_method = false:suggestion
dotnet_style_qualification_for_event = false:suggestion
# Use language keywords instead of framework type names for type references
dotnet_style_predefined_type_for_locals_parameters_members = true:warning
dotnet_style_predefined_type_for_member_access = true:warning
# Suggest more modern language features when available
dotnet_style_object_initializer = true:suggestion
dotnet_style_collection_initializer = true:suggestion
dotnet_style_coalesce_expression = true:suggestion
dotnet_style_null_propagation = true:suggestion
dotnet_style_explicit_tuple_names = true:suggestion
# Whitespace options
dotnet_style_allow_multiple_blank_lines_experimental = false
# Private fields are camelCase with '_' prefix
dotnet_naming_rule.private_members_with_underscore.symbols = private_fields
dotnet_naming_rule.private_members_with_underscore.style = prefix_underscore
dotnet_naming_rule.private_members_with_underscore.severity = error
dotnet_naming_symbols.private_fields.applicable_kinds = field
dotnet_naming_symbols.private_fields.applicable_accessibilities = private
dotnet_naming_style.prefix_underscore.capitalization = camel_case
dotnet_naming_style.prefix_underscore.required_prefix = _
# Non-private static fields are PascalCase
dotnet_naming_rule.non_private_static_fields_should_be_pascal_case.severity = suggestion
dotnet_naming_rule.non_private_static_fields_should_be_pascal_case.symbols = non_private_static_fields
dotnet_naming_rule.non_private_static_fields_should_be_pascal_case.style = non_private_static_field_style
dotnet_naming_symbols.non_private_static_fields.applicable_kinds = field
dotnet_naming_symbols.non_private_static_fields.applicable_accessibilities = public, protected, internal, protected_internal, private_protected
dotnet_naming_symbols.non_private_static_fields.required_modifiers = static
dotnet_naming_style.non_private_static_field_style.capitalization = pascal_case
# Non-private readonly fields are PascalCase
dotnet_naming_rule.non_private_readonly_fields_should_be_pascal_case.severity = suggestion
dotnet_naming_rule.non_private_readonly_fields_should_be_pascal_case.symbols = non_private_readonly_fields
dotnet_naming_rule.non_private_readonly_fields_should_be_pascal_case.style = non_private_static_field_style
dotnet_naming_symbols.non_private_readonly_fields.applicable_kinds = field
dotnet_naming_symbols.non_private_readonly_fields.applicable_accessibilities = public, protected, internal, protected_internal, private_protected
dotnet_naming_symbols.non_private_readonly_fields.required_modifiers = readonly
dotnet_naming_style.non_private_readonly_field_style.capitalization = pascal_case
# Constants are PascalCase
dotnet_naming_rule.constants_should_be_pascal_case.severity = suggestion
dotnet_naming_rule.constants_should_be_pascal_case.symbols = constants
dotnet_naming_rule.constants_should_be_pascal_case.style = non_private_static_field_style
dotnet_naming_symbols.constants.applicable_kinds = field, local
dotnet_naming_symbols.constants.required_modifiers = const
dotnet_naming_style.constant_style.capitalization = pascal_case
# Static fields are camelCase and start with s_
dotnet_naming_rule.static_fields_should_be_camel_case.severity = none
dotnet_naming_rule.static_fields_should_be_camel_case.symbols = static_fields
dotnet_naming_rule.static_fields_should_be_camel_case.style = static_field_style
dotnet_naming_symbols.static_fields.applicable_kinds = field
dotnet_naming_symbols.static_fields.required_modifiers = static
dotnet_naming_style.static_field_style.capitalization = camel_case
dotnet_naming_style.static_field_style.required_prefix = s_
# Instance fields are camelCase and start with _
dotnet_naming_rule.instance_fields_should_be_camel_case.severity = none
dotnet_naming_rule.instance_fields_should_be_camel_case.symbols = instance_fields
dotnet_naming_rule.instance_fields_should_be_camel_case.style = instance_field_style
dotnet_naming_symbols.instance_fields.applicable_kinds = field
dotnet_naming_style.instance_field_style.capitalization = camel_case
dotnet_naming_style.instance_field_style.required_prefix = _
# Locals and parameters are camelCase
dotnet_naming_rule.locals_should_be_camel_case.severity = suggestion
dotnet_naming_rule.locals_should_be_camel_case.symbols = locals_and_parameters
dotnet_naming_rule.locals_should_be_camel_case.style = camel_case_style
dotnet_naming_symbols.locals_and_parameters.applicable_kinds = parameter, local
dotnet_naming_style.camel_case_style.capitalization = camel_case
# Local functions are PascalCase
dotnet_naming_rule.local_functions_should_be_pascal_case.severity = suggestion
dotnet_naming_rule.local_functions_should_be_pascal_case.symbols = local_functions
dotnet_naming_rule.local_functions_should_be_pascal_case.style = non_private_static_field_style
dotnet_naming_symbols.local_functions.applicable_kinds = local_function
dotnet_naming_style.local_function_style.capitalization = pascal_case
# By default, name items with PascalCase
dotnet_naming_rule.members_should_be_pascal_case.severity = suggestion
dotnet_naming_rule.members_should_be_pascal_case.symbols = all_members
dotnet_naming_rule.members_should_be_pascal_case.style = non_private_static_field_style
dotnet_naming_symbols.all_members.applicable_kinds = *
dotnet_naming_style.pascal_case_style.capitalization = pascal_case
# error RS2008: Enable analyzer release tracking for the analyzer project containing rule '{0}'
dotnet_diagnostic.RS2008.severity = none
# IDE0073: File header
dotnet_diagnostic.IDE0073.severity = none
#file_header_template = Licensed to the .NET Foundation under one or more agreements.\nThe .NET Foundation licenses this file to you under the MIT license.\nSee the LICENSE file in the project root for more information.
# IDE0035: Remove unreachable code
dotnet_diagnostic.IDE0035.severity = warning
# IDE0036: Order modifiers
dotnet_diagnostic.IDE0036.severity = warning
# IDE0043: Format string contains invalid placeholder
dotnet_diagnostic.IDE0043.severity = warning
# IDE0044: Make field readonly
dotnet_diagnostic.IDE0044.severity = warning
# IDE1006: Naming rule violation
#dotnet_diagnostic.IDE1006.severity = none
# RS0016: Only enable if API files are present
dotnet_public_api_analyzer.require_api_files = true
dotnet_style_operator_placement_when_wrapping = beginning_of_line
tab_width = 4
end_of_line = crlf
dotnet_style_prefer_is_null_check_over_reference_equality_method = true:suggestion
dotnet_style_prefer_auto_properties = true:silent
dotnet_style_prefer_simplified_boolean_expressions = true:suggestion
dotnet_style_prefer_conditional_expression_over_assignment = true:silent
dotnet_style_prefer_conditional_expression_over_return = true:silent
dotnet_style_prefer_inferred_tuple_names = true:suggestion
dotnet_style_prefer_inferred_anonymous_type_member_names = true:suggestion
dotnet_style_prefer_compound_assignment = true:suggestion
dotnet_style_prefer_simplified_interpolation = true:suggestion
dotnet_style_namespace_match_folder = true:suggestion
# CSharp code style settings:
[*.cs]
# Newline settings
csharp_new_line_before_open_brace = all
csharp_new_line_before_else = true
csharp_new_line_before_catch = true
csharp_new_line_before_finally = true
csharp_new_line_before_members_in_object_initializers = true
csharp_new_line_before_members_in_anonymous_types = true
csharp_new_line_between_query_expression_clauses = true
# Indentation preferences
csharp_indent_block_contents = true
csharp_indent_braces = false
csharp_indent_case_contents = true
csharp_indent_case_contents_when_block = true
csharp_indent_switch_labels = true
csharp_indent_labels = flush_left
# Whitespace options
csharp_style_allow_embedded_statements_on_same_line_experimental = false
csharp_style_allow_blank_lines_between_consecutive_braces_experimental = false
csharp_style_allow_blank_line_after_colon_in_constructor_initializer_experimental = false
# Prefer "var" everywhere
csharp_style_var_for_built_in_types = true:suggestion
csharp_style_var_when_type_is_apparent = true:suggestion
csharp_style_var_elsewhere = true:suggestion
# Prefer method-like constructs to have a block body
csharp_style_expression_bodied_methods = false:none
csharp_style_expression_bodied_constructors = false:none
csharp_style_expression_bodied_operators = false:none
# Prefer property-like constructs to have an expression-body
csharp_style_expression_bodied_properties = true:none
csharp_style_expression_bodied_indexers = true:none
csharp_style_expression_bodied_accessors = true:none
# Suggest more modern language features when available
csharp_style_pattern_matching_over_is_with_cast_check = true:suggestion
csharp_style_pattern_matching_over_as_with_null_check = true:suggestion
csharp_style_inlined_variable_declaration = true:suggestion
csharp_style_throw_expression = true:suggestion
csharp_style_conditional_delegate_call = true:suggestion
# Space preferences
csharp_space_after_cast = false
csharp_space_after_colon_in_inheritance_clause = true
csharp_space_after_comma = true
csharp_space_after_dot = false
csharp_space_after_keywords_in_control_flow_statements = true
csharp_space_after_semicolon_in_for_statement = true
csharp_space_around_binary_operators = before_and_after
csharp_space_around_declaration_statements = do_not_ignore
csharp_space_before_colon_in_inheritance_clause = true
csharp_space_before_comma = false
csharp_space_before_dot = false
csharp_space_before_open_square_brackets = false
csharp_space_before_semicolon_in_for_statement = false
csharp_space_between_empty_square_brackets = false
csharp_space_between_method_call_empty_parameter_list_parentheses = false
csharp_space_between_method_call_name_and_opening_parenthesis = false
csharp_space_between_method_call_parameter_list_parentheses = false
csharp_space_between_method_declaration_empty_parameter_list_parentheses = false
csharp_space_between_method_declaration_name_and_open_parenthesis = false
csharp_space_between_method_declaration_parameter_list_parentheses = false
csharp_space_between_parentheses = false
csharp_space_between_square_brackets = false
# Blocks are allowed
csharp_prefer_braces = true:silent
csharp_preserve_single_line_blocks = true
csharp_preserve_single_line_statements = true
# Target-type new expressio
csharp_style_implicit_object_creation_when_type_is_apparent = true:suggestion
# Currently only enabled for C# due to crash in VB analyzer. VB can be enabled once
# https://github.com/dotnet/roslyn/pull/54259 has been published.
dotnet_style_allow_statement_immediately_after_block_experimental = false
dotnet_diagnostic.RCS0003.severity=warning
dotnet_diagnostic.RCS1036.severity=error
dotnet_diagnostic.IDE0005.severity=warning
dotnet_diagnostic.IDE0007.severity=error
csharp_using_directive_placement = outside_namespace:silent
csharp_prefer_simple_using_statement = true:suggestion
csharp_style_namespace_declarations = block_scoped:silent
csharp_style_expression_bodied_lambdas = true:silent
csharp_style_expression_bodied_local_functions = false:silent
csharp_style_prefer_null_check_over_type_check = true:suggestion
dotnet_diagnostic.RCS1075.severity = suggestion
[src/CodeStyle/**.{cs,vb}]
# warning RS0005: Do not use generic CodeAction.Create to create CodeAction
dotnet_diagnostic.RS0005.severity = none
[src/{Analyzers,CodeStyle,Features,Workspaces,EditorFeatures,VisualStudio}/**/*.{cs,vb}]
# IDE0011: Add braces
csharp_prefer_braces = when_multiline:warning
# NOTE: We need the below severity entry for Add Braces due to https://github.com/dotnet/roslyn/issues/44201
dotnet_diagnostic.IDE0011.severity = warning
# IDE0040: Add accessibility modifiers
dotnet_diagnostic.IDE0040.severity = warning
# CONSIDER: Are IDE0051 and IDE0052 too noisy to be warnings for IDE editing scenarios? Should they be made build-only warnings?
# IDE0051: Remove unused private member
dotnet_diagnostic.IDE0051.severity = warning
# IDE0052: Remove unread private member
dotnet_diagnostic.IDE0052.severity = warning
# IDE0059: Unnecessary assignment to a value
dotnet_diagnostic.IDE0059.severity = warning
# IDE0060: Remove unused parameter
dotnet_diagnostic.IDE0060.severity = warning
# CA1012: Abstract types should not have public constructors
dotnet_diagnostic.CA1012.severity = warning
# CA1822: Make member static
dotnet_diagnostic.CA1822.severity = warning
# Prefer "var" everywhere
dotnet_diagnostic.IDE0007.severity = warning
csharp_style_var_for_built_in_types = true:warning
csharp_style_var_when_type_is_apparent = true:warning
csharp_style_var_elsewhere = true:warning
# dotnet_style_allow_multiple_blank_lines_experimental
dotnet_diagnostic.IDE2000.severity = warning
# csharp_style_allow_embedded_statements_on_same_line_experimental
dotnet_diagnostic.IDE2001.severity = warning
# csharp_style_allow_blank_lines_between_consecutive_braces_experimental
dotnet_diagnostic.IDE2002.severity = warning
# dotnet_style_allow_statement_immediately_after_block_experimental
dotnet_diagnostic.IDE2003.severity = warning
# csharp_style_allow_blank_line_after_colon_in_constructor_initializer_experimental
dotnet_diagnostic.IDE2004.severity = warning
[src/{VisualStudio}/**/*.{cs,vb}]
# CA1822: Make member static
# There is a risk of accidentally breaking an internal API that partners rely on though IVT.
dotnet_code_quality.CA1822.api_surface = private

View File

@@ -1,379 +0,0 @@
## Ignore Visual Studio temporary files, build results, and
## files generated by popular Visual Studio add-ons.
##
## Get latest from https://github.com/github/gitignore/blob/master/VisualStudio.gitignore
runtimes
**/*nuget
*.zip
include/
*.exp
*.lib
*.dll
# User-specific files
*.rsuser
*.suo
*.user
*.userosscache
*.sln.docstates
# User-specific files (MonoDevelop/Xamarin Studio)
*.userprefs
# Mono auto generated files
mono_crash.*
Tests/**/launchSettings.json
# Build results
[Dd]ebug/
[Dd]ebugPublic/
[Rr]elease/
[Rr]eleases/
x64/
x86/
[Ww][Ii][Nn]32/
[Aa][Rr][Mm]/
[Aa][Rr][Mm]64/
bld/
[Bb]in/
[Oo]bj/
[Oo]ut/
[Ll]og/
[Ll]ogs/
# Visual Studio 2015/2017 cache/options directory
.vs/
# Uncomment if you have tasks that create the project's static files in wwwroot
#wwwroot/
# Visual Studio 2017 auto generated files
Generated\ Files/
# MSTest test Results
[Tt]est[Rr]esult*/
[Bb]uild[Ll]og.*
# NUnit
*.VisualState.xml
TestResult.xml
nunit-*.xml
# Build Results of an ATL Project
[Dd]ebugPS/
[Rr]eleasePS/
dlldata.c
# Benchmark Results
BenchmarkDotNet.Artifacts/
# .NET Core
project.lock.json
project.fragment.lock.json
artifacts/
# ASP.NET Scaffolding
ScaffoldingReadMe.txt
# StyleCop
StyleCopReport.xml
# Files built by Visual Studio
*_i.c
*_p.c
*_h.h
*.ilk
*.meta
*.obj
*.iobj
*.pch
*.pdb
*.ipdb
*.pgc
*.pgd
*.rsp
*.sbr
*.tlb
*.tli
*.tlh
*.tmp
*.tmp_proj
*_wpftmp.csproj
*.log
*.vspscc
*.vssscc
.builds
*.pidb
*.svclog
*.scc
# Chutzpah Test files
_Chutzpah*
# Visual C++ cache files
ipch/
*.aps
*.ncb
*.opendb
*.opensdf
*.sdf
*.cachefile
*.VC.db
*.VC.VC.opendb
# Visual Studio profiler
*.psess
*.vsp
*.vspx
*.sap
# Visual Studio Trace Files
*.e2e
# TFS 2012 Local Workspace
$tf/
# Guidance Automation Toolkit
*.gpState
# ReSharper is a .NET coding add-in
_ReSharper*/
*.[Rr]e[Ss]harper
*.DotSettings.user
# TeamCity is a build add-in
_TeamCity*
# DotCover is a Code Coverage Tool
*.dotCover
# AxoCover is a Code Coverage Tool
.axoCover/*
!.axoCover/settings.json
# Coverlet is a free, cross platform Code Coverage Tool
coverage*.json
coverage*.xml
coverage*.info
# Visual Studio code coverage results
*.coverage
*.coveragexml
# NCrunch
_NCrunch_*
.*crunch*.local.xml
nCrunchTemp_*
# MightyMoose
*.mm.*
AutoTest.Net/
# Web workbench (sass)
.sass-cache/
# Installshield output folder
[Ee]xpress/
# DocProject is a documentation generator add-in
DocProject/buildhelp/
DocProject/Help/*.HxT
DocProject/Help/*.HxC
DocProject/Help/*.hhc
DocProject/Help/*.hhk
DocProject/Help/*.hhp
DocProject/Help/Html2
DocProject/Help/html
# Click-Once directory
publish/
# Publish Web Output
*.[Pp]ublish.xml
*.azurePubxml
# Note: Comment the next line if you want to checkin your web deploy settings,
# but database connection strings (with potential passwords) will be unencrypted
*.pubxml
*.publishproj
# Microsoft Azure Web App publish settings. Comment the next line if you want to
# checkin your Azure Web App publish settings, but sensitive information contained
# in these scripts will be unencrypted
PublishScripts/
# NuGet Packages
*.nupkg
# NuGet Symbol Packages
*.snupkg
# The packages folder can be ignored because of Package Restore
**/[Pp]ackages/*
# except build/, which is used as an MSBuild target.
!**/[Pp]ackages/build/
# Uncomment if necessary however generally it will be regenerated when needed
#!**/[Pp]ackages/repositories.config
# NuGet v3's project.json files produces more ignorable files
*.nuget.props
*.nuget.targets
# Microsoft Azure Build Output
csx/
*.build.csdef
# Microsoft Azure Emulator
ecf/
rcf/
# Windows Store app package directories and files
AppPackages/
BundleArtifacts/
Package.StoreAssociation.xml
_pkginfo.txt
*.appx
*.appxbundle
*.appxupload
# Visual Studio cache files
# files ending in .cache can be ignored
*.[Cc]ache
# but keep track of directories ending in .cache
!?*.[Cc]ache/
# Others
ClientBin/
~$*
*~
*.dbmdl
*.dbproj.schemaview
*.jfm
*.pfx
*.publishsettings
orleans.codegen.cs
# Including strong name files can present a security risk
# (https://github.com/github/gitignore/pull/2483#issue-259490424)
#*.snk
# Since there are multiple workflows, uncomment next line to ignore bower_components
# (https://github.com/github/gitignore/pull/1529#issuecomment-104372622)
#bower_components/
# RIA/Silverlight projects
Generated_Code/
# Backup & report files from converting an old project file
# to a newer Visual Studio version. Backup files are not needed,
# because we have git ;-)
_UpgradeReport_Files/
Backup*/
UpgradeLog*.XML
UpgradeLog*.htm
ServiceFabricBackup/
*.rptproj.bak
# SQL Server files
*.mdf
*.ldf
*.ndf
# Business Intelligence projects
*.rdl.data
*.bim.layout
*.bim_*.settings
*.rptproj.rsuser
*- [Bb]ackup.rdl
*- [Bb]ackup ([0-9]).rdl
*- [Bb]ackup ([0-9][0-9]).rdl
# Microsoft Fakes
FakesAssemblies/
# GhostDoc plugin setting file
*.GhostDoc.xml
# Node.js Tools for Visual Studio
.ntvs_analysis.dat
node_modules/
# Visual Studio 6 build log
*.plg
# Visual Studio 6 workspace options file
*.opt
# Visual Studio 6 auto-generated workspace file (contains which files were open etc.)
*.vbw
# Visual Studio LightSwitch build output
**/*.HTMLClient/GeneratedArtifacts
**/*.DesktopClient/GeneratedArtifacts
**/*.DesktopClient/ModelManifest.xml
**/*.Server/GeneratedArtifacts
**/*.Server/ModelManifest.xml
_Pvt_Extensions
# Paket dependency manager
.paket/paket.exe
paket-files/
# FAKE - F# Make
.fake/
# CodeRush personal settings
.cr/personal
# Python Tools for Visual Studio (PTVS)
__pycache__/
*.pyc
# Cake - Uncomment if you are using it
# tools/**
# !tools/packages.config
# Tabs Studio
*.tss
# Telerik's JustMock configuration file
*.jmconfig
# BizTalk build output
*.btp.cs
*.btm.cs
*.odx.cs
*.xsd.cs
# OpenCover UI analysis results
OpenCover/
# Azure Stream Analytics local run output
ASALocalRun/
# MSBuild Binary and Structured Log
*.binlog
# NVidia Nsight GPU debugger configuration file
*.nvuser
# MFractors (Xamarin productivity tool) working folder
.mfractor/
# Local History for Visual Studio
.localhistory/
# BeatPulse healthcheck temp database
healthchecksdb
# Backup folder for Package Reference Convert tool in Visual Studio 2017
MigrationBackup/
# Ionide (cross platform F# VS Code tools) working folder
.ionide/
# Fody - auto-generated XML schema
FodyWeavers.xsd
# JetBrains Rider
.idea
# Visual Studio Code
.vscode

View File

@@ -1,44 +0,0 @@
<?xml version="1.0" encoding="utf-8"?>
<Project>
<PropertyGroup>
<Company></Company>
<Copyright></Copyright>
<NeutralLanguage>en-US</NeutralLanguage>
<Version>0.6.4-alpha</Version>
<VersionSuffix>$(VersionSuffix)</VersionSuffix>
<Version Condition=" '$(VersionSuffix)' != '' ">$(Version)$(VersionSuffix)</Version>
<TreatWarningsAsErrors>true</TreatWarningsAsErrors>
<RepositoryUrl></RepositoryUrl>
<RepositoryType>git</RepositoryType>
<IncludeSymbols>true</IncludeSymbols>
<IncludeSource>true</IncludeSource>
<AnalysisLevel>latest-minimum</AnalysisLevel>
<EnforceCodeStyleInBuild>true</EnforceCodeStyleInBuild>
</PropertyGroup>
<ItemGroup>
<Using Include="System"/>
</ItemGroup>
<PropertyGroup>
<LangVersion>preview</LangVersion>
<Features>strict</Features>
</PropertyGroup>
<ItemGroup>
<PackageReference Include="Roslynator.Analyzers" Version="4.2.0">
<PrivateAssets>all</PrivateAssets>
<IncludeAssets>runtime; build; native; contentfiles; analyzers</IncludeAssets>
</PackageReference>
<PackageReference Include="Roslynator.CodeAnalysis.Analyzers" Version="4.2.0">
<PrivateAssets>all</PrivateAssets>
<IncludeAssets>runtime; build; native; contentfiles; analyzers</IncludeAssets>
</PackageReference>
<PackageReference Include="Roslynator.Formatting.Analyzers" Version="4.2.0">
<PrivateAssets>all</PrivateAssets>
<IncludeAssets>runtime; build; native; contentfiles; analyzers</IncludeAssets>
</PackageReference>
</ItemGroup>
</Project>

View File

@@ -1,33 +0,0 @@
<Project Sdk="Microsoft.NET.Sdk">
<PropertyGroup>
<OutputType>Exe</OutputType>
<TargetFramework>net8.0</TargetFramework>
<ImplicitUsings>enable</ImplicitUsings>
<Nullable>enable</Nullable>
<GenerateDocumentationFile>true</GenerateDocumentationFile>
</PropertyGroup>
<ItemGroup>
<ProjectReference Include="..\Gpt4All\Gpt4All.csproj" />
</ItemGroup>
<ItemGroup>
<!-- Windows -->
<None Include="..\runtimes\win-x64\native\*.dll" Pack="true" PackagePath="runtimes\win-x64\native\%(Filename)%(Extension)" />
<!-- Linux -->
<None Include="..\runtimes\linux-x64\native\*.so" Pack="true" PackagePath="runtimes\linux-x64\native\%(Filename)%(Extension)" />
<!-- MacOS -->
<None Include="..\runtimes\osx\native\*.dylib" Pack="true" PackagePath="runtimes\osx\native\%(Filename)%(Extension)" />
</ItemGroup>
<ItemGroup>
<!-- Windows -->
<None Condition="$([MSBuild]::IsOSPlatform('Windows'))" Include="..\runtimes\win-x64\native\*.dll" Visible="False" CopyToOutputDirectory="PreserveNewest" />
<!-- Linux -->
<None Condition="$([MSBuild]::IsOSPlatform('Linux'))" Include="..\runtimes\linux-x64\native\*.so" Visible="False" CopyToOutputDirectory="PreserveNewest" />
<!-- MacOS -->
<None Condition="$([MSBuild]::IsOSPlatform('OSX'))" Include="..\runtimes\osx\native\*.dylib" Visible="False" CopyToOutputDirectory="PreserveNewest" />
<Content Condition="$([MSBuild]::IsOSPlatform('OSX'))" Include="..\runtimes\osx\native\*.metal" Visible="False" CopyToOutputDirectory="PreserveNewest" />
</ItemGroup>
</Project>

View File

@@ -1,22 +0,0 @@
using Gpt4All;
var modelFactory = new Gpt4AllModelFactory();
if (args.Length < 2)
{
Console.WriteLine($"Usage: Gpt4All.Samples <model-path> <prompt>");
return;
}
var modelPath = args[0];
var prompt = args[1];
using var model = modelFactory.LoadModel(modelPath);
var result = await model.GetStreamingPredictionAsync(
prompt,
PredictRequestOptions.Defaults);
await foreach (var token in result.GetPredictionStreamingAsync())
{
Console.Write(token);
}

View File

@@ -1,9 +0,0 @@
namespace Gpt4All.Tests;
public static class Constants
{
public const string MODELS_BASE_DIR = "../../../models";
public const string LLAMA_MODEL_PATH = $"{MODELS_BASE_DIR}/ggml-gpt4all-l13b-snoozy.bin";
public const string GPTJ_MODEL_PATH = $"{MODELS_BASE_DIR}/ggml-gpt4all-j-v1.3-groovy.bin";
public const string MPT_MODEL_PATH = $"{MODELS_BASE_DIR}/ggml-mpt-7b-chat.bin";
}

View File

@@ -1,60 +0,0 @@
<Project Sdk="Microsoft.NET.Sdk">
<PropertyGroup>
<TargetFramework>net8.0</TargetFramework>
<Nullable>enable</Nullable>
<IsPackable>false</IsPackable>
<GenerateDocumentationFile>true</GenerateDocumentationFile>
</PropertyGroup>
<ItemGroup>
<PackageReference Include="Microsoft.NET.Test.Sdk" Version="17.6.2" />
<PackageReference Include="xunit" Version="2.4.2" />
<PackageReference Include="xunit.runner.visualstudio" Version="2.4.5">
<IncludeAssets>runtime; build; native; contentfiles; analyzers; buildtransitive</IncludeAssets>
<PrivateAssets>all</PrivateAssets>
</PackageReference>
<PackageReference Include="coverlet.collector" Version="6.0.0">
<IncludeAssets>runtime; build; native; contentfiles; analyzers; buildtransitive</IncludeAssets>
<PrivateAssets>all</PrivateAssets>
</PackageReference>
</ItemGroup>
<ItemGroup>
<ProjectReference Include="..\Gpt4All\Gpt4All.csproj" />
</ItemGroup>
<ItemGroup>
<!-- Windows -->
<None Include="..\runtimes\win-x64\native\*.dll" Pack="true" PackagePath="runtimes\win-x64\native\%(Filename)%(Extension)" />
<!-- Linux -->
<None Include="..\runtimes\linux-x64\native\*.so" Pack="true" PackagePath="runtimes\linux-x64\native\%(Filename)%(Extension)" />
<!-- MacOS -->
<None Include="..\runtimes\osx\native\*.dylib" Pack="true" PackagePath="runtimes\osx\native\%(Filename)%(Extension)" />
</ItemGroup>
<ItemGroup>
<!-- Windows -->
<None Condition="$([MSBuild]::IsOSPlatform('Windows'))" Include="..\runtimes\win-x64\native\*.dll" Visible="False" CopyToOutputDirectory="PreserveNewest" />
<!-- Linux -->
<None Condition="$([MSBuild]::IsOSPlatform('Linux'))" Include="..\runtimes\linux-x64\native\*.so" Visible="False" CopyToOutputDirectory="PreserveNewest" />
<!-- MacOS -->
<None Condition="$([MSBuild]::IsOSPlatform('OSX'))" Include="..\runtimes\osx\native\*.dylib" Visible="False" CopyToOutputDirectory="PreserveNewest" />
</ItemGroup>
<ItemGroup>
<PackageReference Update="Roslynator.Analyzers" Version="4.3.0">
<PrivateAssets>all</PrivateAssets>
<IncludeAssets>runtime; build; native; contentfiles; analyzers</IncludeAssets>
</PackageReference>
<PackageReference Update="Roslynator.CodeAnalysis.Analyzers" Version="4.3.0">
<PrivateAssets>all</PrivateAssets>
<IncludeAssets>runtime; build; native; contentfiles; analyzers</IncludeAssets>
</PackageReference>
<PackageReference Update="Roslynator.Formatting.Analyzers" Version="4.3.0">
<PrivateAssets>all</PrivateAssets>
<IncludeAssets>runtime; build; native; contentfiles; analyzers</IncludeAssets>
</PackageReference>
</ItemGroup>
</Project>

View File

@@ -1,34 +0,0 @@
using Xunit;
namespace Gpt4All.Tests;
public class ModelFactoryTests
{
private readonly Gpt4AllModelFactory _modelFactory;
public ModelFactoryTests()
{
_modelFactory = new Gpt4AllModelFactory();
}
[Fact]
[Trait(Traits.SkipOnCI, "True")]
public void CanLoadLlamaModel()
{
using var model = _modelFactory.LoadModel(Constants.LLAMA_MODEL_PATH);
}
[Fact]
[Trait(Traits.SkipOnCI, "True")]
public void CanLoadGptjModel()
{
using var model = _modelFactory.LoadModel(Constants.GPTJ_MODEL_PATH);
}
[Fact]
[Trait(Traits.SkipOnCI, "True")]
public void CanLoadMptModel()
{
using var model = _modelFactory.LoadModel(Constants.MPT_MODEL_PATH);
}
}

View File

@@ -1,56 +0,0 @@
using System.IO;
using Gpt4All.LibraryLoader;
using Xunit;
namespace Gpt4All.Tests;
public class NativeLibraryLoaderTests
{
[Fact]
public void NativeLibraryShouldLoad()
{
var result = NativeLibraryLoader.LoadNativeLibrary(bypassLoading: false);
Assert.True(result.IsSuccess);
}
private const string LLModelLib = "libllmodel.{0}";
[PlatformSpecificFact(Platforms.Windows)]
public void NativeLibraryShouldLoad_Windows()
{
var libraryLoader = new WindowsLibraryLoader();
var libraryPath = Path.Combine(
Environment.CurrentDirectory,
string.Format(LLModelLib, "dll"));
var result = libraryLoader.OpenLibrary(libraryPath);
Assert.True(result.IsSuccess);
}
[PlatformSpecificFact(Platforms.Linux)]
public void NativeLibraryShouldLoad_Linux()
{
var libraryLoader = new LinuxLibraryLoader();
var libraryPath = Path.Combine(
Environment.CurrentDirectory,
string.Format(LLModelLib, "so"));
var result = libraryLoader.OpenLibrary(libraryPath);
Assert.True(result.IsSuccess);
}
[PlatformSpecificFact(Platforms.MacOS)]
public void NativeLibraryShouldLoad_MacOS()
{
var libraryLoader = new MacOsLibraryLoader();
var libraryPath = Path.Combine(
Environment.CurrentDirectory,
string.Format(LLModelLib, "dylib"));
var result = libraryLoader.OpenLibrary(libraryPath);
Assert.True(result.IsSuccess);
}
}

View File

@@ -1,27 +0,0 @@
using Xunit;
namespace Gpt4All.Tests;
public static class Platforms
{
public const string Windows = "windows";
public const string Linux = "linux";
public const string MacOS = "macOS";
}
/// <summary>
/// This attribute ensures the Fact is only run on the specified platform.
/// </summary>
/// <remarks>
/// <see cref="OperatingSystem.IsOSPlatform(string)"/> for info about the platform string.
/// </remarks>
public class PlatformSpecificFactAttribute : FactAttribute
{
public PlatformSpecificFactAttribute(string platform)
{
if (!OperatingSystem.IsOSPlatform(platform))
{
Skip = $"Test only runs on {platform}.";
}
}
}

View File

@@ -1,6 +0,0 @@
namespace Gpt4All.Tests;
public static class Traits
{
public const string SkipOnCI = "SKIP_ON_CI";
}

View File

@@ -1,47 +0,0 @@

Microsoft Visual Studio Solution File, Format Version 12.00
# Visual Studio Version 17
VisualStudioVersion = 17.5.33516.290
MinimumVisualStudioVersion = 10.0.40219.1
Project("{9A19103F-16F7-4668-BE54-9A1E7A4F7556}") = "Gpt4All.Samples", "Gpt4All.Samples\Gpt4All.Samples.csproj", "{59864AE8-E45D-42F7-A7C0-1308EF185F39}"
EndProject
Project("{2150E333-8FDC-42A3-9474-1A3956D46DE8}") = "Solution Items", "Solution Items", "{DA396C11-CEAD-4368-8234-FB12255A30D2}"
ProjectSection(SolutionItems) = preProject
.gitignore = .gitignore
build_linux.sh = build_linux.sh
build_win-mingw.ps1 = build_win-mingw.ps1
build_win-msvc.ps1 = build_win-msvc.ps1
docs\gpt4all_csharp.md = docs\gpt4all_csharp.md
README.md = README.md
EndProjectSection
EndProject
Project("{9A19103F-16F7-4668-BE54-9A1E7A4F7556}") = "Gpt4All", "Gpt4All\Gpt4All.csproj", "{6015C62B-2008-426B-A334-740D6F1FE38B}"
EndProject
Project("{FAE04EC0-301F-11D3-BF4B-00C04F79EFBC}") = "Gpt4All.Tests", "Gpt4All.Tests\Gpt4All.Tests.csproj", "{33A72341-52C1-4EAE-878B-A98BC77F686A}"
EndProject
Global
GlobalSection(SolutionConfigurationPlatforms) = preSolution
Debug|Any CPU = Debug|Any CPU
Release|Any CPU = Release|Any CPU
EndGlobalSection
GlobalSection(ProjectConfigurationPlatforms) = postSolution
{59864AE8-E45D-42F7-A7C0-1308EF185F39}.Debug|Any CPU.ActiveCfg = Debug|Any CPU
{59864AE8-E45D-42F7-A7C0-1308EF185F39}.Debug|Any CPU.Build.0 = Debug|Any CPU
{59864AE8-E45D-42F7-A7C0-1308EF185F39}.Release|Any CPU.ActiveCfg = Release|Any CPU
{59864AE8-E45D-42F7-A7C0-1308EF185F39}.Release|Any CPU.Build.0 = Release|Any CPU
{6015C62B-2008-426B-A334-740D6F1FE38B}.Debug|Any CPU.ActiveCfg = Debug|Any CPU
{6015C62B-2008-426B-A334-740D6F1FE38B}.Debug|Any CPU.Build.0 = Debug|Any CPU
{6015C62B-2008-426B-A334-740D6F1FE38B}.Release|Any CPU.ActiveCfg = Release|Any CPU
{6015C62B-2008-426B-A334-740D6F1FE38B}.Release|Any CPU.Build.0 = Release|Any CPU
{33A72341-52C1-4EAE-878B-A98BC77F686A}.Debug|Any CPU.ActiveCfg = Debug|Any CPU
{33A72341-52C1-4EAE-878B-A98BC77F686A}.Debug|Any CPU.Build.0 = Debug|Any CPU
{33A72341-52C1-4EAE-878B-A98BC77F686A}.Release|Any CPU.ActiveCfg = Release|Any CPU
{33A72341-52C1-4EAE-878B-A98BC77F686A}.Release|Any CPU.Build.0 = Release|Any CPU
EndGlobalSection
GlobalSection(SolutionProperties) = preSolution
HideSolutionNode = FALSE
EndGlobalSection
GlobalSection(ExtensibilityGlobals) = postSolution
SolutionGuid = {17632027-F4C2-4903-B88F-310CE3DE386B}
EndGlobalSection
EndGlobal

View File

@@ -1,29 +0,0 @@
namespace Gpt4All.Bindings;
/// <summary>
/// Represents the interface exposed by the universal wrapper for GPT4All language models built around llmodel C-API.
/// </summary>
public interface ILLModel : IDisposable
{
ulong GetStateSizeBytes();
int GetThreadCount();
void SetThreadCount(int threadCount);
bool IsLoaded();
bool Load(string modelPath);
void Prompt(
string text,
LLModelPromptContext context,
Func<ModelPromptEventArgs, bool>? promptCallback = null,
Func<ModelResponseEventArgs, bool>? responseCallback = null,
Func<ModelRecalculatingEventArgs, bool>? recalculateCallback = null,
CancellationToken cancellationToken = default);
unsafe ulong RestoreStateData(byte* destination);
unsafe ulong SaveStateData(byte* source);
}

View File

@@ -1,212 +0,0 @@
using Microsoft.Extensions.Logging;
using Microsoft.Extensions.Logging.Abstractions;
namespace Gpt4All.Bindings;
/// <summary>
/// Arguments for the response processing callback
/// </summary>
/// <param name="TokenId">The token id of the response</param>
/// <param name="Response"> The response string. NOTE: a token_id of -1 indicates the string is an error string</param>
/// <return>
/// A bool indicating whether the model should keep generating
/// </return>
public record ModelResponseEventArgs(int TokenId, string Response)
{
public bool IsError => TokenId == -1;
}
/// <summary>
/// Arguments for the prompt processing callback
/// </summary>
/// <param name="TokenId">The token id of the prompt</param>
/// <return>
/// A bool indicating whether the model should keep processing
/// </return>
public record ModelPromptEventArgs(int TokenId)
{
}
/// <summary>
/// Arguments for the recalculating callback
/// </summary>
/// <param name="IsRecalculating"> whether the model is recalculating the context.</param>
/// <return>
/// A bool indicating whether the model should keep generating
/// </return>
public record ModelRecalculatingEventArgs(bool IsRecalculating);
/// <summary>
/// Base class and universal wrapper for GPT4All language models built around llmodel C-API.
/// </summary>
public class LLModel : ILLModel
{
protected readonly IntPtr _handle;
private readonly ILogger _logger;
private bool _disposed;
internal LLModel(IntPtr handle, ILogger? logger = null)
{
_handle = handle;
_logger = logger ?? NullLogger.Instance;
}
/// <summary>
/// Create a new model from a pointer
/// </summary>
/// <param name="handle">Pointer to underlying model</param>
public static LLModel Create(IntPtr handle, ILogger? logger = null)
{
return new LLModel(handle, logger: logger);
}
/// <summary>
/// Generate a response using the model
/// </summary>
/// <param name="text">The input promp</param>
/// <param name="context">The context</param>
/// <param name="promptCallback">A callback function for handling the processing of prompt</param>
/// <param name="responseCallback">A callback function for handling the generated response</param>
/// <param name="recalculateCallback">A callback function for handling recalculation requests</param>
/// <param name="cancellationToken"></param>
public void Prompt(
string text,
LLModelPromptContext context,
Func<ModelPromptEventArgs, bool>? promptCallback = null,
Func<ModelResponseEventArgs, bool>? responseCallback = null,
Func<ModelRecalculatingEventArgs, bool>? recalculateCallback = null,
CancellationToken cancellationToken = default)
{
GC.KeepAlive(promptCallback);
GC.KeepAlive(responseCallback);
GC.KeepAlive(recalculateCallback);
GC.KeepAlive(cancellationToken);
_logger.LogInformation("Prompt input='{Prompt}' ctx={Context}", text, context.Dump());
NativeMethods.llmodel_prompt(
_handle,
text,
(tokenId) =>
{
if (cancellationToken.IsCancellationRequested) return false;
if (promptCallback == null) return true;
var args = new ModelPromptEventArgs(tokenId);
return promptCallback(args);
},
(tokenId, response) =>
{
if (cancellationToken.IsCancellationRequested)
{
_logger.LogDebug("ResponseCallback evt=CancellationRequested");
return false;
}
if (responseCallback == null) return true;
var args = new ModelResponseEventArgs(tokenId, response);
return responseCallback(args);
},
(isRecalculating) =>
{
if (cancellationToken.IsCancellationRequested) return false;
if (recalculateCallback == null) return true;
var args = new ModelRecalculatingEventArgs(isRecalculating);
return recalculateCallback(args);
},
ref context.UnderlyingContext
);
}
/// <summary>
/// Set the number of threads to be used by the model.
/// </summary>
/// <param name="threadCount">The new thread count</param>
public void SetThreadCount(int threadCount)
{
NativeMethods.llmodel_setThreadCount(_handle, threadCount);
}
/// <summary>
/// Get the number of threads used by the model.
/// </summary>
/// <returns>the number of threads used by the model</returns>
public int GetThreadCount()
{
return NativeMethods.llmodel_threadCount(_handle);
}
/// <summary>
/// Get the size of the internal state of the model.
/// </summary>
/// <remarks>
/// This state data is specific to the type of model you have created.
/// </remarks>
/// <returns>the size in bytes of the internal state of the model</returns>
public ulong GetStateSizeBytes()
{
return NativeMethods.llmodel_get_state_size(_handle);
}
/// <summary>
/// Saves the internal state of the model to the specified destination address.
/// </summary>
/// <param name="source">A pointer to the src</param>
/// <returns>The number of bytes copied</returns>
public unsafe ulong SaveStateData(byte* source)
{
return NativeMethods.llmodel_save_state_data(_handle, source);
}
/// <summary>
/// Restores the internal state of the model using data from the specified address.
/// </summary>
/// <param name="destination">A pointer to destination</param>
/// <returns>the number of bytes read</returns>
public unsafe ulong RestoreStateData(byte* destination)
{
return NativeMethods.llmodel_restore_state_data(_handle, destination);
}
/// <summary>
/// Check if the model is loaded.
/// </summary>
/// <returns>true if the model was loaded successfully, false otherwise.</returns>
public bool IsLoaded()
{
return NativeMethods.llmodel_isModelLoaded(_handle);
}
/// <summary>
/// Load the model from a file.
/// </summary>
/// <param name="modelPath">The path to the model file.</param>
/// <returns>true if the model was loaded successfully, false otherwise.</returns>
public bool Load(string modelPath)
{
return NativeMethods.llmodel_loadModel(_handle, modelPath, 2048, 100);
}
protected void Destroy()
{
NativeMethods.llmodel_model_destroy(_handle);
}
protected virtual void Dispose(bool disposing)
{
if (_disposed) return;
if (disposing)
{
// dispose managed state
}
Destroy();
_disposed = true;
}
public void Dispose()
{
Dispose(disposing: true);
GC.SuppressFinalize(this);
}
}

View File

@@ -1,147 +0,0 @@
namespace Gpt4All.Bindings;
/// <summary>
/// Wrapper around the llmodel_prompt_context structure for holding the prompt context.
/// </summary>
/// <remarks>
/// 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
/// </remarks>
public unsafe class LLModelPromptContext
{
private llmodel_prompt_context _ctx;
internal ref llmodel_prompt_context UnderlyingContext => ref _ctx;
public LLModelPromptContext()
{
_ctx = new();
}
/// <summary>
/// logits of current context
/// </summary>
public Span<float> Logits => new(_ctx.logits, (int)_ctx.logits_size);
/// <summary>
/// the size of the raw logits vector
/// </summary>
public nuint LogitsSize
{
get => _ctx.logits_size;
set => _ctx.logits_size = value;
}
/// <summary>
/// current tokens in the context window
/// </summary>
public Span<int> Tokens => new(_ctx.tokens, (int)_ctx.tokens_size);
/// <summary>
/// the size of the raw tokens vector
/// </summary>
public nuint TokensSize
{
get => _ctx.tokens_size;
set => _ctx.tokens_size = value;
}
/// <summary>
/// top k logits to sample from
/// </summary>
public int TopK
{
get => _ctx.top_k;
set => _ctx.top_k = value;
}
/// <summary>
/// nucleus sampling probability threshold
/// </summary>
public float TopP
{
get => _ctx.top_p;
set => _ctx.top_p = value;
}
/// <summary>
/// min p sampling probability threshold
/// </summary>
public float MinP
{
get => _ctx.min_p;
set => _ctx.min_p = value;
}
/// <summary>
/// temperature to adjust model's output distribution
/// </summary>
public float Temperature
{
get => _ctx.temp;
set => _ctx.temp = value;
}
/// <summary>
/// number of tokens in past conversation
/// </summary>
public int PastNum
{
get => _ctx.n_past;
set => _ctx.n_past = value;
}
/// <summary>
/// number of predictions to generate in parallel
/// </summary>
public int Batches
{
get => _ctx.n_batch;
set => _ctx.n_batch = value;
}
/// <summary>
/// number of tokens to predict
/// </summary>
public int TokensToPredict
{
get => _ctx.n_predict;
set => _ctx.n_predict = value;
}
/// <summary>
/// penalty factor for repeated tokens
/// </summary>
public float RepeatPenalty
{
get => _ctx.repeat_penalty;
set => _ctx.repeat_penalty = value;
}
/// <summary>
/// last n tokens to penalize
/// </summary>
public int RepeatLastN
{
get => _ctx.repeat_last_n;
set => _ctx.repeat_last_n = value;
}
/// <summary>
/// number of tokens possible in context window
/// </summary>
public int ContextSize
{
get => _ctx.n_ctx;
set => _ctx.n_ctx = value;
}
/// <summary>
/// percent of context to erase if we exceed the context window
/// </summary>
public float ContextErase
{
get => _ctx.context_erase;
set => _ctx.context_erase = value;
}
}

View File

@@ -1,112 +0,0 @@
using System.Runtime.InteropServices;
namespace Gpt4All.Bindings;
public unsafe partial struct llmodel_prompt_context
{
public float* logits;
[NativeTypeName("size_t")]
public nuint logits_size;
[NativeTypeName("int32_t *")]
public int* tokens;
[NativeTypeName("size_t")]
public nuint tokens_size;
[NativeTypeName("int32_t")]
public int n_past;
[NativeTypeName("int32_t")]
public int n_ctx;
[NativeTypeName("int32_t")]
public int n_predict;
[NativeTypeName("int32_t")]
public int top_k;
public float top_p;
public float min_p;
public float temp;
[NativeTypeName("int32_t")]
public int n_batch;
public float repeat_penalty;
[NativeTypeName("int32_t")]
public int repeat_last_n;
public float context_erase;
}
#pragma warning disable CA2101
internal static unsafe partial class NativeMethods
{
[UnmanagedFunctionPointer(CallingConvention.Cdecl)]
[return: MarshalAs(UnmanagedType.I1)]
public delegate bool LlmodelResponseCallback(int token_id, [MarshalAs(UnmanagedType.LPUTF8Str)] string response);
[UnmanagedFunctionPointer(CallingConvention.Cdecl)]
[return: MarshalAs(UnmanagedType.I1)]
public delegate bool LlmodelPromptCallback(int token_id);
[UnmanagedFunctionPointer(CallingConvention.Cdecl)]
[return: MarshalAs(UnmanagedType.I1)]
public delegate bool LlmodelRecalculateCallback(bool isRecalculating);
[DllImport("libllmodel", CallingConvention = CallingConvention.Cdecl, ExactSpelling = true, BestFitMapping = false, ThrowOnUnmappableChar = true)]
[return: NativeTypeName("llmodel_model")]
public static extern IntPtr llmodel_model_create2(
[NativeTypeName("const char *")][MarshalAs(UnmanagedType.LPUTF8Str)] string model_path,
[NativeTypeName("const char *")][MarshalAs(UnmanagedType.LPUTF8Str)] string build_variant,
out IntPtr error);
[DllImport("libllmodel", CallingConvention = CallingConvention.Cdecl, ExactSpelling = true)]
public static extern void llmodel_model_destroy([NativeTypeName("llmodel_model")] IntPtr model);
[DllImport("libllmodel", CallingConvention = CallingConvention.Cdecl, ExactSpelling = true, BestFitMapping = false, ThrowOnUnmappableChar = true)]
[return: MarshalAs(UnmanagedType.I1)]
public static extern bool llmodel_loadModel(
[NativeTypeName("llmodel_model")] IntPtr model,
[NativeTypeName("const char *")][MarshalAs(UnmanagedType.LPUTF8Str)] string model_path,
[NativeTypeName("int32_t")] int n_ctx,
[NativeTypeName("int32_t")] int ngl);
[DllImport("libllmodel", CallingConvention = CallingConvention.Cdecl, ExactSpelling = true)]
[return: MarshalAs(UnmanagedType.I1)]
public static extern bool llmodel_isModelLoaded([NativeTypeName("llmodel_model")] IntPtr model);
[DllImport("libllmodel", CallingConvention = CallingConvention.Cdecl, ExactSpelling = true)]
[return: NativeTypeName("uint64_t")]
public static extern ulong llmodel_get_state_size([NativeTypeName("llmodel_model")] IntPtr model);
[DllImport("libllmodel", CallingConvention = CallingConvention.Cdecl, ExactSpelling = true)]
[return: NativeTypeName("uint64_t")]
public static extern ulong llmodel_save_state_data([NativeTypeName("llmodel_model")] IntPtr model, [NativeTypeName("uint8_t *")] byte* dest);
[DllImport("libllmodel", CallingConvention = CallingConvention.Cdecl, ExactSpelling = true)]
[return: NativeTypeName("uint64_t")]
public static extern ulong llmodel_restore_state_data([NativeTypeName("llmodel_model")] IntPtr model, [NativeTypeName("const uint8_t *")] byte* src);
[DllImport("libllmodel", CallingConvention = CallingConvention.Cdecl, ExactSpelling = true, BestFitMapping = false, ThrowOnUnmappableChar = true)]
public static extern void llmodel_prompt(
[NativeTypeName("llmodel_model")] IntPtr model,
[NativeTypeName("const char *")][MarshalAs(UnmanagedType.LPUTF8Str)] string prompt,
LlmodelPromptCallback prompt_callback,
LlmodelResponseCallback response_callback,
LlmodelRecalculateCallback recalculate_callback,
ref llmodel_prompt_context ctx);
[DllImport("libllmodel", CallingConvention = CallingConvention.Cdecl, ExactSpelling = true)]
public static extern void llmodel_setThreadCount([NativeTypeName("llmodel_model")] IntPtr model, [NativeTypeName("int32_t")] int n_threads);
[DllImport("libllmodel", CallingConvention = CallingConvention.Cdecl, ExactSpelling = true)]
[return: NativeTypeName("int32_t")]
public static extern int llmodel_threadCount([NativeTypeName("llmodel_model")] IntPtr model);
}
#pragma warning restore CA2101

View File

@@ -1,21 +0,0 @@
using System.Diagnostics;
namespace Gpt4All.Bindings;
/// <summary>Defines the type of a member as it was used in the native signature.</summary>
[AttributeUsage(AttributeTargets.Struct | AttributeTargets.Enum | AttributeTargets.Property | AttributeTargets.Field | AttributeTargets.Parameter | AttributeTargets.ReturnValue, AllowMultiple = false, Inherited = true)]
[Conditional("DEBUG")]
internal sealed partial class NativeTypeNameAttribute : Attribute
{
private readonly string _name;
/// <summary>Initializes a new instance of the <see cref="NativeTypeNameAttribute" /> class.</summary>
/// <param name="name">The name of the type that was used in the native signature.</param>
public NativeTypeNameAttribute(string name)
{
_name = name;
}
/// <summary>Gets the name of the type that was used in the native signature.</summary>
public string Name => _name;
}

View File

@@ -1,27 +0,0 @@
using Gpt4All.Bindings;
namespace Gpt4All;
internal static class LLPromptContextExtensions
{
public static string Dump(this LLModelPromptContext context)
{
var ctx = context.UnderlyingContext;
return @$"
{{
logits_size = {ctx.logits_size}
tokens_size = {ctx.tokens_size}
n_past = {ctx.n_past}
n_ctx = {ctx.n_ctx}
n_predict = {ctx.n_predict}
top_k = {ctx.top_k}
top_p = {ctx.top_p}
min_p = {ctx.min_p}
temp = {ctx.temp}
n_batch = {ctx.n_batch}
repeat_penalty = {ctx.repeat_penalty}
repeat_last_n = {ctx.repeat_last_n}
context_erase = {ctx.context_erase}
}}";
}
}

View File

@@ -1,26 +0,0 @@
using Gpt4All.Bindings;
namespace Gpt4All;
public static class PredictRequestOptionsExtensions
{
public static LLModelPromptContext ToPromptContext(this PredictRequestOptions opts)
{
return new LLModelPromptContext
{
LogitsSize = opts.LogitsSize,
TokensSize = opts.TokensSize,
TopK = opts.TopK,
TopP = opts.TopP,
MinP = opts.MinP,
PastNum = opts.PastConversationTokensNum,
RepeatPenalty = opts.RepeatPenalty,
Temperature = opts.Temperature,
RepeatLastN = opts.RepeatLastN,
Batches = opts.Batches,
ContextErase = opts.ContextErase,
ContextSize = opts.ContextSize,
TokensToPredict = opts.TokensToPredict
};
}
}

View File

@@ -1,21 +0,0 @@
--config
exclude-funcs-with-body
--with-access-specifier
*=Public
--include-directory
..\..\..\gpt4all-backend\
--file
..\..\..\gpt4all-backend\llmodel_c.h
--libraryPath
libllmodel
--remap
sbyte*=IntPtr
void*=IntPtr
--namespace
Gpt4All.Bindings
--methodClassName
NativeMethods
--output
.\Bindings\NativeMethods.cs
--output-mode
CSharp

View File

@@ -1,135 +0,0 @@
using System.Diagnostics;
using System.Runtime.CompilerServices;
using Gpt4All.Bindings;
using Microsoft.Extensions.Logging;
using Microsoft.Extensions.Logging.Abstractions;
[assembly: InternalsVisibleTo("Gpt4All.Tests")]
namespace Gpt4All;
public class Gpt4All : IGpt4AllModel
{
private readonly ILLModel _model;
private readonly ILogger _logger;
private const string ResponseErrorMessage =
"The model reported an error during token generation error={ResponseError}";
/// <inheritdoc/>
public IPromptFormatter? PromptFormatter { get; set; }
internal Gpt4All(ILLModel model, ILogger? logger = null)
{
_model = model;
_logger = logger ?? NullLogger.Instance;
PromptFormatter = new DefaultPromptFormatter();
}
private string FormatPrompt(string prompt)
{
if (PromptFormatter == null) return prompt;
return PromptFormatter.FormatPrompt(prompt);
}
public Task<ITextPredictionResult> GetPredictionAsync(string text, PredictRequestOptions opts, CancellationToken cancellationToken = default)
{
ArgumentNullException.ThrowIfNull(text);
return Task.Run(() =>
{
_logger.LogInformation("Start prediction task");
var sw = Stopwatch.StartNew();
var result = new TextPredictionResult();
var context = opts.ToPromptContext();
var prompt = FormatPrompt(text);
try
{
_model.Prompt(prompt, context, responseCallback: e =>
{
if (e.IsError)
{
_logger.LogWarning(ResponseErrorMessage, e.Response);
result.Success = false;
result.ErrorMessage = e.Response;
return false;
}
result.Append(e.Response);
return true;
}, cancellationToken: cancellationToken);
}
catch (Exception e)
{
_logger.LogError(e, "Prompt error");
result.Success = false;
}
sw.Stop();
_logger.LogInformation("Prediction task completed elapsed={Elapsed}s", sw.Elapsed.TotalSeconds);
return (ITextPredictionResult)result;
}, CancellationToken.None);
}
public Task<ITextPredictionStreamingResult> GetStreamingPredictionAsync(string text, PredictRequestOptions opts, CancellationToken cancellationToken = default)
{
ArgumentNullException.ThrowIfNull(text);
var result = new TextPredictionStreamingResult();
_ = Task.Run(() =>
{
_logger.LogInformation("Start streaming prediction task");
var sw = Stopwatch.StartNew();
try
{
var context = opts.ToPromptContext();
var prompt = FormatPrompt(text);
_model.Prompt(prompt, context, responseCallback: e =>
{
if (e.IsError)
{
_logger.LogWarning(ResponseErrorMessage, e.Response);
result.Success = false;
result.ErrorMessage = e.Response;
return false;
}
result.Append(e.Response);
return true;
}, cancellationToken: cancellationToken);
}
catch (Exception e)
{
_logger.LogError(e, "Prompt error");
result.Success = false;
}
finally
{
result.Complete();
sw.Stop();
_logger.LogInformation("Prediction task completed elapsed={Elapsed}s", sw.Elapsed.TotalSeconds);
}
}, CancellationToken.None);
return Task.FromResult((ITextPredictionStreamingResult)result);
}
protected virtual void Dispose(bool disposing)
{
if (disposing)
{
_model.Dispose();
}
}
public void Dispose()
{
Dispose(true);
GC.SuppressFinalize(this);
}
}

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@@ -1,23 +0,0 @@
<Project Sdk="Microsoft.NET.Sdk">
<PropertyGroup>
<ImplicitUsings>enable</ImplicitUsings>
<Nullable>enable</Nullable>
<AllowUnsafeBlocks>true</AllowUnsafeBlocks>
<GenerateDocumentationFile>true</GenerateDocumentationFile>
<TargetFramework>net8.0</TargetFramework>
</PropertyGroup>
<ItemGroup>
<!-- Windows -->
<None Include="..\runtimes\win-x64\native\*.dll" Pack="true" PackagePath="runtimes\win-x64\native\%(Filename)%(Extension)" />
<!-- Linux -->
<None Include="..\runtimes\linux-x64\native\*.so" Pack="true" PackagePath="runtimes\linux-x64\native\%(Filename)%(Extension)" />
<!-- MacOS -->
<None Include="..\runtimes\osx\native\*.dylib" Pack="true" PackagePath="runtimes\osx\native\%(Filename)%(Extension)" />
<Content Include="..\runtimes\osx\native\*.metal" Pack="true" PackagePath="contentFiles\any\any;content">
<PackageCopyToOutput>true</PackageCopyToOutput>
</Content>
</ItemGroup>
<ItemGroup>
<PackageReference Include="Microsoft.Extensions.Logging.Abstractions" Version="7.0.0" />
</ItemGroup>
</Project>

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@@ -1,6 +0,0 @@
namespace Gpt4All.LibraryLoader;
public interface ILibraryLoader
{
LoadResult OpenLibrary(string? fileName);
}

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@@ -1,53 +0,0 @@
using System.Runtime.InteropServices;
namespace Gpt4All.LibraryLoader;
internal class LinuxLibraryLoader : ILibraryLoader
{
#pragma warning disable CA2101
[DllImport("libdl.so", ExactSpelling = true, CharSet = CharSet.Auto, EntryPoint = "dlopen")]
#pragma warning restore CA2101
public static extern IntPtr NativeOpenLibraryLibdl(string? filename, int flags);
#pragma warning disable CA2101
[DllImport("libdl.so.2", ExactSpelling = true, CharSet = CharSet.Auto, EntryPoint = "dlopen")]
#pragma warning restore CA2101
public static extern IntPtr NativeOpenLibraryLibdl2(string? filename, int flags);
[DllImport("libdl.so", ExactSpelling = true, CharSet = CharSet.Auto, EntryPoint = "dlerror")]
public static extern IntPtr GetLoadError();
[DllImport("libdl.so.2", ExactSpelling = true, CharSet = CharSet.Auto, EntryPoint = "dlerror")]
public static extern IntPtr GetLoadError2();
public LoadResult OpenLibrary(string? fileName)
{
IntPtr loadedLib;
try
{
// open with rtls lazy flag
loadedLib = NativeOpenLibraryLibdl2(fileName, 0x00001);
}
catch (DllNotFoundException)
{
loadedLib = NativeOpenLibraryLibdl(fileName, 0x00001);
}
if (loadedLib == IntPtr.Zero)
{
string errorMessage;
try
{
errorMessage = Marshal.PtrToStringAnsi(GetLoadError2()) ?? "Unknown error";
}
catch (DllNotFoundException)
{
errorMessage = Marshal.PtrToStringAnsi(GetLoadError()) ?? "Unknown error";
}
return LoadResult.Failure(errorMessage);
}
return LoadResult.Success;
}
}

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@@ -1,20 +0,0 @@
namespace Gpt4All.LibraryLoader;
public class LoadResult
{
private LoadResult(bool isSuccess, string? errorMessage)
{
IsSuccess = isSuccess;
ErrorMessage = errorMessage;
}
public static LoadResult Success { get; } = new(true, null);
public static LoadResult Failure(string errorMessage)
{
return new(false, errorMessage);
}
public bool IsSuccess { get; }
public string? ErrorMessage { get; }
}

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@@ -1,28 +0,0 @@
using System.Runtime.InteropServices;
namespace Gpt4All.LibraryLoader;
internal class MacOsLibraryLoader : ILibraryLoader
{
#pragma warning disable CA2101
[DllImport("libdl.dylib", ExactSpelling = true, CharSet = CharSet.Auto, EntryPoint = "dlopen")]
#pragma warning restore CA2101
public static extern IntPtr NativeOpenLibraryLibdl(string? filename, int flags);
[DllImport("libdl.dylib", ExactSpelling = true, CharSet = CharSet.Auto, EntryPoint = "dlerror")]
public static extern IntPtr GetLoadError();
public LoadResult OpenLibrary(string? fileName)
{
var loadedLib = NativeOpenLibraryLibdl(fileName, 0x00001);
if (loadedLib == IntPtr.Zero)
{
var errorMessage = Marshal.PtrToStringAnsi(GetLoadError()) ?? "Unknown error";
return LoadResult.Failure(errorMessage);
}
return LoadResult.Success;
}
}

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@@ -1,81 +0,0 @@
#if !IOS && !MACCATALYST && !TVOS && !ANDROID
using System.Runtime.InteropServices;
#endif
namespace Gpt4All.LibraryLoader;
public static class NativeLibraryLoader
{
private static ILibraryLoader? defaultLibraryLoader;
/// <summary>
/// Sets the library loader used to load the native libraries. Overwrite this only if you want some custom loading.
/// </summary>
/// <param name="libraryLoader">The library loader to be used.</param>
public static void SetLibraryLoader(ILibraryLoader libraryLoader)
{
defaultLibraryLoader = libraryLoader;
}
internal static LoadResult LoadNativeLibrary(string? path = default, bool bypassLoading = true)
{
// If the user has handled loading the library themselves, we don't need to do anything.
if (bypassLoading)
{
return LoadResult.Success;
}
var architecture = RuntimeInformation.OSArchitecture switch
{
Architecture.X64 => "x64",
Architecture.X86 => "x86",
Architecture.Arm => "arm",
Architecture.Arm64 => "arm64",
_ => throw new PlatformNotSupportedException(
$"Unsupported OS platform, architecture: {RuntimeInformation.OSArchitecture}")
};
var (platform, extension) = Environment.OSVersion.Platform switch
{
_ when RuntimeInformation.IsOSPlatform(OSPlatform.Windows) => ("win", "dll"),
_ when RuntimeInformation.IsOSPlatform(OSPlatform.Linux) => ("linux", "so"),
_ when RuntimeInformation.IsOSPlatform(OSPlatform.OSX) => ("osx", "dylib"),
_ => throw new PlatformNotSupportedException(
$"Unsupported OS platform, architecture: {RuntimeInformation.OSArchitecture}")
};
// If the user hasn't set the path, we'll try to find it ourselves.
if (string.IsNullOrEmpty(path))
{
var libraryName = "libllmodel";
var assemblySearchPath = new[]
{
AppDomain.CurrentDomain.RelativeSearchPath,
Path.GetDirectoryName(typeof(NativeLibraryLoader).Assembly.Location),
Path.GetDirectoryName(Environment.GetCommandLineArgs()[0])
}.FirstOrDefault(it => !string.IsNullOrEmpty(it));
// Search for the library dll within the assembly search path. If it doesn't exist, for whatever reason, use the default path.
path = Directory.EnumerateFiles(assemblySearchPath ?? string.Empty, $"{libraryName}.{extension}", SearchOption.AllDirectories).FirstOrDefault() ?? Path.Combine("runtimes", $"{platform}-{architecture}", $"{libraryName}.{extension}");
}
if (defaultLibraryLoader != null)
{
return defaultLibraryLoader.OpenLibrary(path);
}
if (!File.Exists(path))
{
throw new FileNotFoundException($"Native Library not found in path {path}. " +
$"Verify you have have included the native Gpt4All library in your application.");
}
ILibraryLoader libraryLoader = platform switch
{
"win" => new WindowsLibraryLoader(),
"osx" => new MacOsLibraryLoader(),
"linux" => new LinuxLibraryLoader(),
_ => throw new PlatformNotSupportedException($"Currently {platform} platform is not supported")
};
return libraryLoader.OpenLibrary(path);
}
}

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@@ -1,24 +0,0 @@
using System.ComponentModel;
using System.Runtime.InteropServices;
namespace Gpt4All.LibraryLoader;
internal class WindowsLibraryLoader : ILibraryLoader
{
public LoadResult OpenLibrary(string? fileName)
{
var loadedLib = LoadLibrary(fileName);
if (loadedLib == IntPtr.Zero)
{
var errorCode = Marshal.GetLastWin32Error();
var errorMessage = new Win32Exception(errorCode).Message;
return LoadResult.Failure(errorMessage);
}
return LoadResult.Success;
}
[DllImport("kernel32", SetLastError = true, CharSet = CharSet.Auto)]
private static extern IntPtr LoadLibrary([MarshalAs(UnmanagedType.LPWStr)] string? lpFileName);
}

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@@ -1,16 +0,0 @@
namespace Gpt4All;
public class DefaultPromptFormatter : IPromptFormatter
{
public string FormatPrompt(string prompt)
{
return $"""
### Instruction:
The prompt below is a question to answer, a task to complete, or a conversation
to respond to; decide which and write an appropriate response.
### Prompt:
{prompt}
### Response:
""";
}
}

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@@ -1,62 +0,0 @@
using System.Diagnostics;
using Microsoft.Extensions.Logging.Abstractions;
using Microsoft.Extensions.Logging;
using Gpt4All.Bindings;
using Gpt4All.LibraryLoader;
using System.Runtime.InteropServices;
namespace Gpt4All;
public class Gpt4AllModelFactory : IGpt4AllModelFactory
{
private readonly ILoggerFactory _loggerFactory;
private readonly ILogger _logger;
private static bool bypassLoading;
private static string? libraryPath;
private static readonly Lazy<LoadResult> libraryLoaded = new(() =>
{
return NativeLibraryLoader.LoadNativeLibrary(Gpt4AllModelFactory.libraryPath, Gpt4AllModelFactory.bypassLoading);
}, true);
public Gpt4AllModelFactory(string? libraryPath = default, bool bypassLoading = true, ILoggerFactory? loggerFactory = null)
{
_loggerFactory = loggerFactory ?? NullLoggerFactory.Instance;
_logger = _loggerFactory.CreateLogger<Gpt4AllModelFactory>();
Gpt4AllModelFactory.libraryPath = libraryPath;
Gpt4AllModelFactory.bypassLoading = bypassLoading;
if (!libraryLoaded.Value.IsSuccess)
{
throw new Exception($"Failed to load native gpt4all library. Error: {libraryLoaded.Value.ErrorMessage}");
}
}
private Gpt4All CreateModel(string modelPath)
{
_logger.LogInformation("Creating model path={ModelPath}", modelPath);
IntPtr error;
var handle = NativeMethods.llmodel_model_create2(modelPath, "auto", out error);
if (error != IntPtr.Zero)
{
throw new Exception(Marshal.PtrToStringAnsi(error));
}
_logger.LogDebug("Model created handle=0x{ModelHandle:X8}", handle);
_logger.LogInformation("Model loading started");
var loadedSuccessfully = NativeMethods.llmodel_loadModel(handle, modelPath, 2048, 100);
_logger.LogInformation("Model loading completed success={ModelLoadSuccess}", loadedSuccessfully);
if (!loadedSuccessfully)
{
throw new Exception($"Failed to load model: '{modelPath}'");
}
var logger = _loggerFactory.CreateLogger<LLModel>();
var underlyingModel = LLModel.Create(handle, logger: logger);
Debug.Assert(underlyingModel.IsLoaded());
return new Gpt4All(underlyingModel, logger: logger);
}
public IGpt4AllModel LoadModel(string modelPath) => CreateModel(modelPath);
}

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@@ -1,10 +0,0 @@
namespace Gpt4All;
public interface IGpt4AllModel : ITextPrediction, IDisposable
{
/// <summary>
/// The prompt formatter used to format the prompt before
/// feeding it to the model, if null no transformation is applied
/// </summary>
IPromptFormatter? PromptFormatter { get; set; }
}

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@@ -1,6 +0,0 @@
namespace Gpt4All;
public interface IGpt4AllModelFactory
{
IGpt4AllModel LoadModel(string modelPath);
}

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@@ -1,14 +0,0 @@
namespace Gpt4All;
/// <summary>
/// Formats a prompt
/// </summary>
public interface IPromptFormatter
{
/// <summary>
/// Format the provided prompt
/// </summary>
/// <param name="prompt">the input prompt</param>
/// <returns>The formatted prompt</returns>
string FormatPrompt(string prompt);
}

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@@ -1,6 +0,0 @@
namespace Gpt4All;
public record ModelOptions
{
public int Threads { get; init; } = 4;
}

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@@ -1,31 +0,0 @@
namespace Gpt4All;
/// <summary>
/// Interface for text prediction services
/// </summary>
public interface ITextPrediction
{
/// <summary>
/// Get prediction results for the prompt and provided options.
/// </summary>
/// <param name="text">The text to complete</param>
/// <param name="opts">The prediction settings</param>
/// <param name="cancellation">The <see cref="CancellationToken"/> for cancellation requests. The default is <see cref="CancellationToken.None"/>.</param>
/// <returns>The prediction result generated by the model</returns>
Task<ITextPredictionResult> GetPredictionAsync(
string text,
PredictRequestOptions opts,
CancellationToken cancellation = default);
/// <summary>
/// Get streaming prediction results for the prompt and provided options.
/// </summary>
/// <param name="text">The text to complete</param>
/// <param name="opts">The prediction settings</param>
/// <param name="cancellationToken">The <see cref="CancellationToken"/> for cancellation requests. The default is <see cref="CancellationToken.None"/>.</param>
/// <returns>The prediction result generated by the model</returns>
Task<ITextPredictionStreamingResult> GetStreamingPredictionAsync(
string text,
PredictRequestOptions opts,
CancellationToken cancellationToken = default);
}

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@@ -1,10 +0,0 @@
namespace Gpt4All;
public interface ITextPredictionResult
{
bool Success { get; }
string? ErrorMessage { get; }
Task<string> GetPredictionAsync(CancellationToken cancellationToken = default);
}

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@@ -1,6 +0,0 @@
namespace Gpt4All;
public interface ITextPredictionStreamingResult : ITextPredictionResult
{
IAsyncEnumerable<string> GetPredictionStreamingAsync(CancellationToken cancellationToken = default);
}

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@@ -1,32 +0,0 @@
namespace Gpt4All;
public record PredictRequestOptions
{
public nuint LogitsSize { get; init; } = 0;
public nuint TokensSize { get; init; } = 0;
public int PastConversationTokensNum { get; init; } = 0;
public int ContextSize { get; init; } = 1024;
public int TokensToPredict { get; init; } = 128;
public int TopK { get; init; } = 40;
public float TopP { get; init; } = 0.9f;
public float MinP { get; init; } = 0.0f;
public float Temperature { get; init; } = 0.1f;
public int Batches { get; init; } = 8;
public float RepeatPenalty { get; init; } = 1.2f;
public int RepeatLastN { get; init; } = 10;
public float ContextErase { get; init; } = 0.5f;
public static readonly PredictRequestOptions Defaults = new();
}

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@@ -1,27 +0,0 @@
using System.Text;
namespace Gpt4All;
public record TextPredictionResult : ITextPredictionResult
{
private readonly StringBuilder _result;
public bool Success { get; internal set; } = true;
public string? ErrorMessage { get; internal set; }
internal TextPredictionResult()
{
_result = new StringBuilder();
}
internal void Append(string token)
{
_result.Append(token);
}
public Task<string> GetPredictionAsync(CancellationToken cancellationToken = default)
{
return Task.FromResult(_result.ToString());
}
}

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@@ -1,49 +0,0 @@
using System.Text;
using System.Threading.Channels;
namespace Gpt4All;
public record TextPredictionStreamingResult : ITextPredictionStreamingResult
{
private readonly Channel<string> _channel;
public bool Success { get; internal set; } = true;
public string? ErrorMessage { get; internal set; }
public Task Completion => _channel.Reader.Completion;
internal TextPredictionStreamingResult()
{
_channel = Channel.CreateUnbounded<string>();
}
internal bool Append(string token)
{
return _channel.Writer.TryWrite(token);
}
internal void Complete()
{
_channel.Writer.Complete();
}
public async Task<string> GetPredictionAsync(CancellationToken cancellationToken = default)
{
var sb = new StringBuilder();
var tokens = GetPredictionStreamingAsync(cancellationToken).ConfigureAwait(false);
await foreach (var token in tokens)
{
sb.Append(token);
}
return sb.ToString();
}
public IAsyncEnumerable<string> GetPredictionStreamingAsync(CancellationToken cancellationToken = default)
{
return _channel.Reader.ReadAllAsync(cancellationToken);
}
}

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@@ -1 +0,0 @@
ClangSharpPInvokeGenerator @(Get-Content .\GenLLModelBindings.rsp)

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@@ -1,124 +0,0 @@
# C# GPT4All
This package contains a set of C# bindings around the `llmodel` C-API.
## Documentation
TBD
## Installation
Windows and Linux builds are available on NuGet: https://www.nuget.org/packages/Gpt4All
macOS is WIP due to code signing issues, contributions are welcome.
## Project Structure
```
gpt4all-bindings/
└── csharp
   ├── Gpt4All // .NET Bindigs
   ├── Gpt4All.Samples // Sample project
├── build_win-msvc.ps1 // Native build scripts
├── build_win-mingw.ps1
├── build_linux.sh
└── runtimes // [POST-BUILD] Platform-specific native libraries
├── win-x64
├── ...
└── linux-x64
```
## Prerequisites
On Windows and Linux, building GPT4All requires the complete Vulkan SDK. You may download it from here: https://vulkan.lunarg.com/sdk/home
macOS users do not need Vulkan, as GPT4All will use Metal instead.
## Local Build Instructions
> **Note**
> Tested On:
> - Windows 11 22H + VS2022 (CE) x64
> - Linux Ubuntu x64
> - Linux Ubuntu (WSL2) x64
1. Setup the repository
2. Build the native libraries for the platform of choice (see below)
3. Build the C# Bindings (NET6+ SDK is required)
```
git clone --recurse-submodules https://github.com/nomic-ai/gpt4all
cd gpt4all/gpt4all-bindings/csharp
```
### Linux
1. Setup build environment and install NET6+ SDK with the appropriate procedure for your distribution
```
sudo apt-get update
sudo apt-get install -y cmake build-essential
chmod +x ./build_linux.sh
```
2. `./build_linux.sh`
3. The native libraries should be present at `.\native\linux-x64`
### Windows - MinGW64
#### Additional requirements
- [MinGW64](https://www.mingw-w64.org/)
- CMAKE
1. Setup
```
choco install mingw
$env:Path += ";C:\ProgramData\mingw64\mingw64\bin"
choco install -y cmake --installargs 'ADD_CMAKE_TO_PATH=System'
```
2. Run the `./build_win-mingw.ps1` build script
3. The native libraries should be present at `.\native\win-x64`
### Windows - MSVC
#### Additional requirements
- Visual Studio 2022
1. Open a terminal using the `x64 Native Tools Command Prompt for VS 2022` (`vcvars64.bat`)
2. Run the `./build_win-msvc.ps1` build script
3. `libllmodel.dll` and `libllama.dll` should be present at `.\native\win-x64`
> **Warning**
> If the build fails with: '**error C7555: use of designated initializers requires at least '/std:c++20'**'
>
> Modify `cd gpt4all/gpt4all-backends/CMakeLists.txt` adding `CXX_STANDARD_20` to `llmodel` properties.
> ```cmake
> set_target_properties(llmodel PROPERTIES
> VERSION ${PROJECT_VERSION}
> CXX_STANDARD 20 # <---- ADD THIS -----------------------
> SOVERSION ${PROJECT_VERSION_MAJOR})
> ```
## C# Bindings Build Instructions
Build the `Gpt4All` (or `Gpt4All.Samples`) projects from within VisualStudio.
### Try the bindings
```csharp
using Gpt4All;
// load the model
var modelFactory = new ModelFactory();
using var model = modelFactory.LoadModel("./path/to/ggml-gpt4all-j-v1.3-groovy.bin");
var input = "Name 3 Colors";
// request a prediction
var result = await model.GetStreamingPredictionAsync(
input,
PredictRequestOptions.Defaults);
// asynchronously print the tokens as soon as they are produces by the model
await foreach(var token in result.GetPredictionStreamingAsync())
{
Console.Write(token);
}
```
Output:
```
gptj_model_load: loading model from 'ggml-gpt4all-j-v1.3-groovy.bin' - please wait ...
gptj_model_load: n_vocab = 50400
[...TRUNCATED...]
gptj_model_load: ggml ctx size = 5401.45 MB
gptj_model_load: kv self size = 896.00 MB
gptj_model_load: ................................... done
gptj_model_load: model size = 3609.38 MB / num tensors = 285
Black, Blue and White
```

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@@ -1,10 +0,0 @@
#!/bin/sh
mkdir -p runtimes
rm -rf runtimes/linux-x64
mkdir -p runtimes/linux-x64/native
mkdir runtimes/linux-x64/build
cmake -S ../../gpt4all-backend -B runtimes/linux-x64/build
cmake --build runtimes/linux-x64/build --parallel --config Release
cp runtimes/linux-x64/build/libllmodel.so runtimes/linux-x64/native/libllmodel.so
cp runtimes/linux-x64/build/libgptj*.so runtimes/linux-x64/native/
cp runtimes/linux-x64/build/libllama*.so runtimes/linux-x64/native/

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@@ -1,16 +0,0 @@
$ROOT_DIR = '.\runtimes\win-x64'
$BUILD_DIR = '.\runtimes\win-x64\build\mingw'
$LIBS_DIR = '.\runtimes\win-x64\native'
# cleanup env
Remove-Item -Force -Recurse $ROOT_DIR -ErrorAction SilentlyContinue | Out-Null
mkdir $BUILD_DIR | Out-Null
mkdir $LIBS_DIR | Out-Null
# build
cmake -G "MinGW Makefiles" -S ..\..\gpt4all-backend -B $BUILD_DIR
cmake --build $BUILD_DIR --parallel --config Release
# copy native dlls
cp "C:\ProgramData\mingw64\mingw64\bin\*dll" $LIBS_DIR
cp "$BUILD_DIR\bin\*.dll" $LIBS_DIR

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@@ -1,6 +0,0 @@
Remove-Item -Force -Recurse .\runtimes\win-x64\msvc -ErrorAction SilentlyContinue
mkdir .\runtimes\win-x64\msvc\build | Out-Null
cmake -G "Visual Studio 17 2022" -A X64 -S ..\..\gpt4all-backend -B .\runtimes\win-x64\msvc\build
cmake --build .\runtimes\win-x64\msvc\build --parallel --config Release
cp .\runtimes\win-x64\msvc\build\bin\Release\*.dll .\runtimes\win-x64
mv .\runtimes\win-x64\llmodel.dll .\runtimes\win-x64\libllmodel.dll

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@@ -1 +0,0 @@
# GPT4All C# API

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@@ -1,163 +0,0 @@
INCLUDE_PATH := $(abspath ./)
LIBRARY_PATH := $(abspath ./)
CMAKEFLAGS=
ifndef UNAME_S
UNAME_S := $(shell uname -s)
endif
ifndef UNAME_P
UNAME_P := $(shell uname -p)
endif
ifndef UNAME_M
UNAME_M := $(shell uname -m)
endif
CCV := $(shell $(CC) --version | head -n 1)
CXXV := $(shell $(CXX) --version | head -n 1)
# Mac OS + Arm can report x86_64
# ref: https://github.com/ggerganov/whisper.cpp/issues/66#issuecomment-1282546789
ifeq ($(UNAME_S),Darwin)
ifneq ($(UNAME_P),arm)
SYSCTL_M := $(shell sysctl -n hw.optional.arm64 2>/dev/null)
ifeq ($(SYSCTL_M),1)
# UNAME_P := arm
# UNAME_M := arm64
warn := $(warning Your arch is announced as x86_64, but it seems to actually be ARM64. Not fixing that can lead to bad performance. For more info see: https://github.com/ggerganov/whisper.cpp/issues/66\#issuecomment-1282546789)
endif
endif
endif
#
# Compile flags
#
# keep standard at C11 and C++11
CFLAGS = -I. -I../../gpt4all-backend/llama.cpp -I../../gpt4all-backend -I -O3 -DNDEBUG -std=c11 -fPIC
CXXFLAGS = -I. -I../../gpt4all-backend/llama.cpp -I../../gpt4all-backend -O3 -DNDEBUG -std=c++17 -fPIC
LDFLAGS =
# warnings
CFLAGS += -Wall -Wextra -Wpedantic -Wcast-qual -Wdouble-promotion -Wshadow -Wstrict-prototypes -Wpointer-arith -Wno-unused-function
CXXFLAGS += -Wall -Wextra -Wpedantic -Wcast-qual -Wno-unused-function -Wno-multichar
# OS specific
# TODO: support Windows
ifeq ($(UNAME_S),Linux)
CFLAGS += -pthread
CXXFLAGS += -pthread
endif
ifeq ($(UNAME_S),Darwin)
CFLAGS += -pthread
CXXFLAGS += -pthread
endif
ifeq ($(UNAME_S),FreeBSD)
CFLAGS += -pthread
CXXFLAGS += -pthread
endif
ifeq ($(UNAME_S),NetBSD)
CFLAGS += -pthread
CXXFLAGS += -pthread
endif
ifeq ($(UNAME_S),OpenBSD)
CFLAGS += -pthread
CXXFLAGS += -pthread
endif
ifeq ($(UNAME_S),Haiku)
CFLAGS += -pthread
CXXFLAGS += -pthread
endif
# Architecture specific
# TODO: probably these flags need to be tweaked on some architectures
# feel free to update the Makefile for your architecture and send a pull request or issue
ifeq ($(UNAME_M),$(filter $(UNAME_M),x86_64 i686))
# Use all CPU extensions that are available:
CFLAGS += -march=native -mtune=native
CXXFLAGS += -march=native -mtune=native
endif
ifneq ($(filter ppc64%,$(UNAME_M)),)
POWER9_M := $(shell grep "POWER9" /proc/cpuinfo)
ifneq (,$(findstring POWER9,$(POWER9_M)))
CFLAGS += -mcpu=power9
CXXFLAGS += -mcpu=power9
endif
# Require c++23's std::byteswap for big-endian support.
ifeq ($(UNAME_M),ppc64)
CXXFLAGS += -std=c++23 -DGGML_BIG_ENDIAN
endif
endif
ifndef LLAMA_NO_ACCELERATE
# Mac M1 - include Accelerate framework.
# `-framework Accelerate` works on Mac Intel as well, with negliable performance boost (as of the predict time).
ifeq ($(UNAME_S),Darwin)
CFLAGS += -DGGML_USE_ACCELERATE
LDFLAGS += -framework Accelerate
endif
endif
ifdef LLAMA_OPENBLAS
CFLAGS += -DGGML_USE_OPENBLAS -I/usr/local/include/openblas
LDFLAGS += -lopenblas
endif
ifdef LLAMA_GPROF
CFLAGS += -pg
CXXFLAGS += -pg
endif
ifneq ($(filter aarch64%,$(UNAME_M)),)
CFLAGS += -mcpu=native
CXXFLAGS += -mcpu=native
endif
ifneq ($(filter armv6%,$(UNAME_M)),)
# Raspberry Pi 1, 2, 3
CFLAGS += -mfpu=neon-fp-armv8 -mfp16-format=ieee -mno-unaligned-access
endif
ifneq ($(filter armv7%,$(UNAME_M)),)
# Raspberry Pi 4
CFLAGS += -mfpu=neon-fp-armv8 -mfp16-format=ieee -mno-unaligned-access -funsafe-math-optimizations
endif
ifneq ($(filter armv8%,$(UNAME_M)),)
# Raspberry Pi 4
CFLAGS += -mfp16-format=ieee -mno-unaligned-access
endif
#
# Print build information
#
$(info I go-gpt4all build info: )
$(info I UNAME_S: $(UNAME_S))
$(info I UNAME_P: $(UNAME_P))
$(info I UNAME_M: $(UNAME_M))
$(info I CFLAGS: $(CFLAGS))
$(info I CXXFLAGS: $(CXXFLAGS))
$(info I LDFLAGS: $(LDFLAGS))
$(info I CMAKEFLAGS: $(CMAKEFLAGS))
$(info I CC: $(CCV))
$(info I CXX: $(CXXV))
$(info )
llmodel.o:
[ -e buildllm ] || mkdir buildllm
cd buildllm && cmake ../../../gpt4all-backend/ $(CMAKEFLAGS) && make
cd buildllm && cp -rf CMakeFiles/llmodel.dir/llmodel_c.cpp.o ../llmodel_c.o
cd buildllm && cp -rf CMakeFiles/llmodel.dir/llmodel.cpp.o ../llmodel.o
clean:
rm -f *.o
rm -f *.a
rm -rf buildllm
rm -rf example/main
binding.o: binding.cpp binding.h
$(CXX) $(CXXFLAGS) binding.cpp -o binding.o -c $(LDFLAGS)
libgpt4all.a: binding.o llmodel.o
ar src libgpt4all.a llmodel.o binding.o
test: libgpt4all.a
@C_INCLUDE_PATH=${INCLUDE_PATH} LIBRARY_PATH=${LIBRARY_PATH} go test -v ./...
example/main: libgpt4all.a
C_INCLUDE_PATH=$(INCLUDE_PATH) LIBRARY_PATH=$(INCLUDE_PATH) go build -o example/main ./example/

View File

@@ -1,59 +0,0 @@
# GPT4All Golang bindings
The golang bindings have been tested on:
- MacOS
- Linux
### Usage
```
import (
"github.com/nomic-ai/gpt4all/gpt4all-bindings/golang"
)
func main() {
// Load the model
model, err := gpt4all.New("model.bin", gpt4all.SetModelType(gpt4all.GPTJType))
if err != nil {
panic(err)
}
defer model.Free()
model.SetTokenCallback(func(s string) bool {
fmt.Print(s)
return true
})
_, err = model.Predict("Here are 4 steps to create a website:", "", "", gpt4all.SetTemperature(0.1))
if err != nil {
panic(err)
}
}
```
## Building
In order to use the bindings you will need to build `libgpt4all.a`:
```
git clone --recurse-submodules https://github.com/nomic-ai/gpt4all
cd gpt4all/gpt4all-bindings/golang
make libgpt4all.a
```
To use the bindings in your own software:
- Import `github.com/nomic-ai/gpt4all/gpt4all-bindings/golang`;
- Compile `libgpt4all.a` (you can use `make libgpt4all.a` in the bindings/go directory);
- Link your go binary by setting the environment variables `C_INCLUDE_PATH` and `LIBRARY_PATH` to point to the `binding.h` file directory and `libgpt4all.a` file directory respectively.
- Note: you need to have *.so/*.dynlib/*.dll files of the implementation nearby the binary produced by the binding in order to make this to work
## Testing
To run tests, run `make test`:
```
git clone https://github.com/nomic-ai/gpt4all
cd gpt4all/gpt4all-bindings/golang
make test
```

View File

@@ -1,107 +0,0 @@
#include "../../gpt4all-backend/llmodel_c.h"
#include "../../gpt4all-backend/llmodel.h"
#include "../../gpt4all-backend/llmodel_c.cpp"
#include "binding.h"
#include <cassert>
#include <cmath>
#include <cstddef>
#include <cstdio>
#include <cstring>
#include <fstream>
#include <map>
#include <string>
#include <vector>
#include <iostream>
#include <unistd.h>
void* load_model(const char *fname, int n_threads) {
// load the model
const char *new_error;
auto model = llmodel_model_create2(fname, "auto", &new_error);
if (model == nullptr) {
fprintf(stderr, "%s: error '%s'\n", __func__, new_error);
return nullptr;
}
if (!llmodel_loadModel(model, fname, 2048, 100)) {
llmodel_model_destroy(model);
return nullptr;
}
llmodel_setThreadCount(model, n_threads);
return model;
}
std::string res = "";
void * mm;
void model_prompt(const char *prompt, const char *prompt_template, int special, const char *fake_reply,
void *m, char* result, int repeat_last_n, float repeat_penalty, int n_ctx, int tokens,
int top_k, float top_p, float min_p, float temp, int n_batch,float ctx_erase)
{
llmodel_model* model = (llmodel_model*) m;
// std::string res = "";
auto lambda_prompt = [](int token_id) {
return true;
};
mm=model;
res="";
auto lambda_response = [](int token_id, const char *responsechars) {
res.append((char*)responsechars);
return !!getTokenCallback(mm, (char*)responsechars);
};
auto lambda_recalculate = [](bool is_recalculating) {
// You can handle recalculation requests here if needed
return is_recalculating;
};
llmodel_prompt_context* prompt_context = new llmodel_prompt_context{
.logits = NULL,
.logits_size = 0,
.tokens = NULL,
.tokens_size = 0,
.n_past = 0,
.n_ctx = 1024,
.n_predict = 50,
.top_k = 10,
.top_p = 0.9,
.min_p = 0.0,
.temp = 1.0,
.n_batch = 1,
.repeat_penalty = 1.2,
.repeat_last_n = 10,
.context_erase = 0.5
};
prompt_context->n_predict = tokens;
prompt_context->repeat_last_n = repeat_last_n;
prompt_context->repeat_penalty = repeat_penalty;
prompt_context->n_ctx = n_ctx;
prompt_context->top_k = top_k;
prompt_context->context_erase = ctx_erase;
prompt_context->top_p = top_p;
prompt_context->min_p = min_p;
prompt_context->temp = temp;
prompt_context->n_batch = n_batch;
llmodel_prompt(model, prompt, prompt_template,
lambda_prompt,
lambda_response,
lambda_recalculate,
prompt_context, special, fake_reply);
strcpy(result, res.c_str());
free(prompt_context);
}
void free_model(void *state_ptr) {
llmodel_model* ctx = (llmodel_model*) state_ptr;
llmodel_model_destroy(*ctx);
}

View File

@@ -1,19 +0,0 @@
#ifdef __cplusplus
extern "C" {
#endif
#include <stdbool.h>
void* load_model(const char *fname, int n_threads);
void model_prompt(const char *prompt, const char *prompt_template, int special, const char *fake_reply,
void *m, char* result, int repeat_last_n, float repeat_penalty, int n_ctx, int tokens,
int top_k, float top_p, float min_p, float temp, int n_batch,float ctx_erase);
void free_model(void *state_ptr);
extern unsigned char getTokenCallback(void *, char *);
#ifdef __cplusplus
}
#endif

View File

@@ -1,82 +0,0 @@
package main
import (
"bufio"
"flag"
"fmt"
"io"
"os"
"runtime"
"strings"
gpt4all "github.com/nomic-ai/gpt4all/gpt4all-bindings/golang"
)
var (
threads = 4
tokens = 128
)
func main() {
var model string
flags := flag.NewFlagSet(os.Args[0], flag.ExitOnError)
flags.StringVar(&model, "m", "./models/7B/ggml-model-q4_0.bin", "path to q4_0.bin model file to load")
flags.IntVar(&threads, "t", runtime.NumCPU(), "number of threads to use during computation")
flags.IntVar(&tokens, "n", 512, "number of tokens to predict")
err := flags.Parse(os.Args[1:])
if err != nil {
fmt.Printf("Parsing program arguments failed: %s", err)
os.Exit(1)
}
l, err := gpt4all.New(model, gpt4all.SetThreads(threads))
if err != nil {
fmt.Println("Loading the model failed:", err.Error())
os.Exit(1)
}
fmt.Printf("Model loaded successfully.\n")
l.SetTokenCallback(func(token string) bool {
fmt.Print(token)
return true
})
reader := bufio.NewReader(os.Stdin)
for {
text := readMultiLineInput(reader)
_, err := l.Predict(text, "", "", gpt4all.SetTokens(tokens), gpt4all.SetTopK(90), gpt4all.SetTopP(0.86))
if err != nil {
panic(err)
}
fmt.Printf("\n\n")
}
}
// readMultiLineInput reads input until an empty line is entered.
func readMultiLineInput(reader *bufio.Reader) string {
var lines []string
fmt.Print(">>> ")
for {
line, err := reader.ReadString('\n')
if err != nil {
if err == io.EOF {
os.Exit(0)
}
fmt.Printf("Reading the prompt failed: %s", err)
os.Exit(1)
}
if len(strings.TrimSpace(line)) == 0 {
break
}
lines = append(lines, line)
}
text := strings.Join(lines, "")
return text
}

View File

@@ -1,20 +0,0 @@
module github.com/nomic-ai/gpt4all/gpt4all-bindings/golang
go 1.19
require (
github.com/onsi/ginkgo/v2 v2.9.4
github.com/onsi/gomega v1.27.6
)
require (
github.com/go-logr/logr v1.2.4 // indirect
github.com/go-task/slim-sprig v0.0.0-20230315185526-52ccab3ef572 // indirect
github.com/google/go-cmp v0.5.9 // indirect
github.com/google/pprof v0.0.0-20210407192527-94a9f03dee38 // indirect
golang.org/x/net v0.9.0 // indirect
golang.org/x/sys v0.7.0 // indirect
golang.org/x/text v0.9.0 // indirect
golang.org/x/tools v0.8.0 // indirect
gopkg.in/yaml.v3 v3.0.1 // indirect
)

View File

@@ -1,40 +0,0 @@
github.com/chzyer/logex v1.1.10/go.mod h1:+Ywpsq7O8HXn0nuIou7OrIPyXbp3wmkHB+jjWRnGsAI=
github.com/chzyer/readline v0.0.0-20180603132655-2972be24d48e/go.mod h1:nSuG5e5PlCu98SY8svDHJxuZscDgtXS6KTTbou5AhLI=
github.com/chzyer/test v0.0.0-20180213035817-a1ea475d72b1/go.mod h1:Q3SI9o4m/ZMnBNeIyt5eFwwo7qiLfzFZmjNmxjkiQlU=
github.com/davecgh/go-spew v1.1.0/go.mod h1:J7Y8YcW2NihsgmVo/mv3lAwl/skON4iLHjSsI+c5H38=
github.com/davecgh/go-spew v1.1.1 h1:vj9j/u1bqnvCEfJOwUhtlOARqs3+rkHYY13jYWTU97c=
github.com/davecgh/go-spew v1.1.1/go.mod h1:J7Y8YcW2NihsgmVo/mv3lAwl/skON4iLHjSsI+c5H38=
github.com/go-logr/logr v1.2.4 h1:g01GSCwiDw2xSZfjJ2/T9M+S6pFdcNtFYsp+Y43HYDQ=
github.com/go-logr/logr v1.2.4/go.mod h1:jdQByPbusPIv2/zmleS9BjJVeZ6kBagPoEUsqbVz/1A=
github.com/go-task/slim-sprig v0.0.0-20230315185526-52ccab3ef572 h1:tfuBGBXKqDEevZMzYi5KSi8KkcZtzBcTgAUUtapy0OI=
github.com/go-task/slim-sprig v0.0.0-20230315185526-52ccab3ef572/go.mod h1:9Pwr4B2jHnOSGXyyzV8ROjYa2ojvAY6HCGYYfMoC3Ls=
github.com/golang/protobuf v1.5.3 h1:KhyjKVUg7Usr/dYsdSqoFveMYd5ko72D+zANwlG1mmg=
github.com/google/go-cmp v0.5.9 h1:O2Tfq5qg4qc4AmwVlvv0oLiVAGB7enBSJ2x2DqQFi38=
github.com/google/go-cmp v0.5.9/go.mod h1:17dUlkBOakJ0+DkrSSNjCkIjxS6bF9zb3elmeNGIjoY=
github.com/google/pprof v0.0.0-20210407192527-94a9f03dee38 h1:yAJXTCF9TqKcTiHJAE8dj7HMvPfh66eeA2JYW7eFpSE=
github.com/google/pprof v0.0.0-20210407192527-94a9f03dee38/go.mod h1:kpwsk12EmLew5upagYY7GY0pfYCcupk39gWOCRROcvE=
github.com/ianlancetaylor/demangle v0.0.0-20200824232613-28f6c0f3b639/go.mod h1:aSSvb/t6k1mPoxDqO4vJh6VOCGPwU4O0C2/Eqndh1Sc=
github.com/onsi/ginkgo/v2 v2.9.4 h1:xR7vG4IXt5RWx6FfIjyAtsoMAtnc3C/rFXBBd2AjZwE=
github.com/onsi/ginkgo/v2 v2.9.4/go.mod h1:gCQYp2Q+kSoIj7ykSVb9nskRSsR6PUj4AiLywzIhbKM=
github.com/onsi/gomega v1.27.6 h1:ENqfyGeS5AX/rlXDd/ETokDz93u0YufY1Pgxuy/PvWE=
github.com/onsi/gomega v1.27.6/go.mod h1:PIQNjfQwkP3aQAH7lf7j87O/5FiNr+ZR8+ipb+qQlhg=
github.com/pmezard/go-difflib v1.0.0 h1:4DBwDE0NGyQoBHbLQYPwSUPoCMWR5BEzIk/f1lZbAQM=
github.com/pmezard/go-difflib v1.0.0/go.mod h1:iKH77koFhYxTK1pcRnkKkqfTogsbg7gZNVY4sRDYZ/4=
github.com/stretchr/objx v0.1.0/go.mod h1:HFkY916IF+rwdDfMAkV7OtwuqBVzrE8GR6GFx+wExME=
github.com/stretchr/testify v1.6.1 h1:hDPOHmpOpP40lSULcqw7IrRb/u7w6RpDC9399XyoNd0=
github.com/stretchr/testify v1.6.1/go.mod h1:6Fq8oRcR53rry900zMqJjRRixrwX3KX962/h/Wwjteg=
golang.org/x/net v0.9.0 h1:aWJ/m6xSmxWBx+V0XRHTlrYrPG56jKsLdTFmsSsCzOM=
golang.org/x/net v0.9.0/go.mod h1:d48xBJpPfHeWQsugry2m+kC02ZBRGRgulfHnEXEuWns=
golang.org/x/sys v0.0.0-20191204072324-ce4227a45e2e/go.mod h1:h1NjWce9XRLGQEsW7wpKNCjG9DtNlClVuFLEZdDNbEs=
golang.org/x/sys v0.7.0 h1:3jlCCIQZPdOYu1h8BkNvLz8Kgwtae2cagcG/VamtZRU=
golang.org/x/sys v0.7.0/go.mod h1:oPkhp1MJrh7nUepCBck5+mAzfO9JrbApNNgaTdGDITg=
golang.org/x/text v0.9.0 h1:2sjJmO8cDvYveuX97RDLsxlyUxLl+GHoLxBiRdHllBE=
golang.org/x/text v0.9.0/go.mod h1:e1OnstbJyHTd6l/uOt8jFFHp6TRDWZR/bV3emEE/zU8=
golang.org/x/tools v0.8.0 h1:vSDcovVPld282ceKgDimkRSC8kpaH1dgyc9UMzlt84Y=
golang.org/x/tools v0.8.0/go.mod h1:JxBZ99ISMI5ViVkT1tr6tdNmXeTrcpVSD3vZ1RsRdN4=
google.golang.org/protobuf v1.28.0 h1:w43yiav+6bVFTBQFZX0r7ipe9JQ1QsbMgHwbBziscLw=
gopkg.in/check.v1 v0.0.0-20161208181325-20d25e280405 h1:yhCVgyC4o1eVCa2tZl7eS0r+SDo693bJlVdllGtEeKM=
gopkg.in/check.v1 v0.0.0-20161208181325-20d25e280405/go.mod h1:Co6ibVJAznAaIkqp8huTwlJQCZ016jof/cbN4VW5Yz0=
gopkg.in/yaml.v3 v3.0.0-20200313102051-9f266ea9e77c/go.mod h1:K4uyk7z7BCEPqu6E+C64Yfv1cQ7kz7rIZviUmN+EgEM=
gopkg.in/yaml.v3 v3.0.1 h1:fxVm/GzAzEWqLHuvctI91KS9hhNmmWOoWu0XTYJS7CA=
gopkg.in/yaml.v3 v3.0.1/go.mod h1:K4uyk7z7BCEPqu6E+C64Yfv1cQ7kz7rIZviUmN+EgEM=

View File

@@ -1,112 +0,0 @@
package gpt4all
// #cgo CFLAGS: -I${SRCDIR}../../gpt4all-backend/ -I${SRCDIR}../../gpt4all-backend/llama.cpp -I./
// #cgo CXXFLAGS: -std=c++17 -I${SRCDIR}../../gpt4all-backend/ -I${SRCDIR}../../gpt4all-backend/llama.cpp -I./
// #cgo darwin LDFLAGS: -framework Accelerate
// #cgo darwin CXXFLAGS: -std=c++17
// #cgo LDFLAGS: -lgpt4all -lm -lstdc++ -ldl
// void* load_model(const char *fname, int n_threads);
// void model_prompt( const char *prompt, const char *prompt_template, int special, const char *fake_reply, void *m, char* result, int repeat_last_n, float repeat_penalty, int n_ctx, int tokens, int top_k,
// float top_p, float min_p, float temp, int n_batch,float ctx_erase);
// void free_model(void *state_ptr);
// extern unsigned char getTokenCallback(void *, char *);
// void llmodel_set_implementation_search_path(const char *path);
import "C"
import (
"fmt"
"runtime"
"strings"
"sync"
"unsafe"
)
// The following code is https://github.com/go-skynet/go-llama.cpp with small adaptations
type Model struct {
state unsafe.Pointer
}
func New(model string, opts ...ModelOption) (*Model, error) {
ops := NewModelOptions(opts...)
if ops.LibrarySearchPath != "" {
C.llmodel_set_implementation_search_path(C.CString(ops.LibrarySearchPath))
}
state := C.load_model(C.CString(model), C.int(ops.Threads))
if state == nil {
return nil, fmt.Errorf("failed loading model")
}
gpt := &Model{state: state}
// set a finalizer to remove any callbacks when the struct is reclaimed by the garbage collector.
runtime.SetFinalizer(gpt, func(g *Model) {
setTokenCallback(g.state, nil)
})
return gpt, nil
}
func (l *Model) Predict(text, template, fakeReplyText string, opts ...PredictOption) (string, error) {
po := NewPredictOptions(opts...)
input := C.CString(text)
if po.Tokens == 0 {
po.Tokens = 99999999
}
templateInput := C.CString(template)
fakeReplyInput := C.CString(fakeReplyText)
out := make([]byte, po.Tokens)
C.model_prompt(input, templateInput, C.int(po.Special), fakeReplyInput, l.state, (*C.char)(unsafe.Pointer(&out[0])),
C.int(po.RepeatLastN), C.float(po.RepeatPenalty), C.int(po.ContextSize), C.int(po.Tokens),
C.int(po.TopK), C.float(po.TopP), C.float(po.MinP), C.float(po.Temperature), C.int(po.Batch),
C.float(po.ContextErase))
res := C.GoString((*C.char)(unsafe.Pointer(&out[0])))
res = strings.TrimPrefix(res, " ")
res = strings.TrimPrefix(res, text)
res = strings.TrimPrefix(res, "\n")
res = strings.TrimSuffix(res, "<|endoftext|>")
return res, nil
}
func (l *Model) Free() {
C.free_model(l.state)
}
func (l *Model) SetTokenCallback(callback func(token string) bool) {
setTokenCallback(l.state, callback)
}
var (
m sync.Mutex
callbacks = map[uintptr]func(string) bool{}
)
//export getTokenCallback
func getTokenCallback(statePtr unsafe.Pointer, token *C.char) bool {
m.Lock()
defer m.Unlock()
if callback, ok := callbacks[uintptr(statePtr)]; ok {
return callback(C.GoString(token))
}
return true
}
// setCallback can be used to register a token callback for LLama. Pass in a nil callback to
// remove the callback.
func setTokenCallback(statePtr unsafe.Pointer, callback func(string) bool) {
m.Lock()
defer m.Unlock()
if callback == nil {
delete(callbacks, uintptr(statePtr))
} else {
callbacks[uintptr(statePtr)] = callback
}
}

View File

@@ -1,13 +0,0 @@
package gpt4all_test
import (
"testing"
. "github.com/onsi/ginkgo/v2"
. "github.com/onsi/gomega"
)
func TestGPT(t *testing.T) {
RegisterFailHandler(Fail)
RunSpecs(t, "go-gpt4all-j test suite")
}

View File

@@ -1,17 +0,0 @@
package gpt4all_test
import (
. "github.com/nomic-ai/gpt4all/gpt4all-bindings/golang"
. "github.com/onsi/ginkgo/v2"
. "github.com/onsi/gomega"
)
var _ = Describe("LLama binding", func() {
Context("Declaration", func() {
It("fails with no model", func() {
model, err := New("not-existing")
Expect(err).To(HaveOccurred())
Expect(model).To(BeNil())
})
})
})

View File

@@ -1,138 +0,0 @@
package gpt4all
type PredictOptions struct {
ContextSize, RepeatLastN, Tokens, TopK, Batch, Special int
TopP, MinP, Temperature, ContextErase, RepeatPenalty float64
}
type PredictOption func(p *PredictOptions)
var DefaultOptions PredictOptions = PredictOptions{
Tokens: 200,
TopK: 10,
TopP: 0.90,
MinP: 0.0,
Temperature: 0.96,
Batch: 1,
Special: 0,
ContextErase: 0.55,
ContextSize: 1024,
RepeatLastN: 10,
RepeatPenalty: 1.2,
}
var DefaultModelOptions ModelOptions = ModelOptions{
Threads: 4,
}
type ModelOptions struct {
Threads int
LibrarySearchPath string
}
type ModelOption func(p *ModelOptions)
// SetTokens sets the number of tokens to generate.
func SetTokens(tokens int) PredictOption {
return func(p *PredictOptions) {
p.Tokens = tokens
}
}
// SetTopK sets the value for top-K sampling.
func SetTopK(topk int) PredictOption {
return func(p *PredictOptions) {
p.TopK = topk
}
}
// SetTopP sets the value for nucleus sampling.
func SetTopP(topp float64) PredictOption {
return func(p *PredictOptions) {
p.TopP = topp
}
}
// SetMinP sets the value for min p sampling
func SetMinP(minp float64) PredictOption {
return func(p *PredictOptions) {
p.MinP = minp
}
}
// SetRepeatPenalty sets the repeat penalty.
func SetRepeatPenalty(ce float64) PredictOption {
return func(p *PredictOptions) {
p.RepeatPenalty = ce
}
}
// SetRepeatLastN sets the RepeatLastN.
func SetRepeatLastN(ce int) PredictOption {
return func(p *PredictOptions) {
p.RepeatLastN = ce
}
}
// SetContextErase sets the context erase %.
func SetContextErase(ce float64) PredictOption {
return func(p *PredictOptions) {
p.ContextErase = ce
}
}
// SetTemperature sets the temperature value for text generation.
func SetTemperature(temp float64) PredictOption {
return func(p *PredictOptions) {
p.Temperature = temp
}
}
// SetBatch sets the batch size.
func SetBatch(size int) PredictOption {
return func(p *PredictOptions) {
p.Batch = size
}
}
// SetSpecial is true if special tokens in the prompt should be processed, false otherwise.
func SetSpecial(special bool) PredictOption {
return func(p *PredictOptions) {
if special {
p.Special = 1
} else {
p.Special = 0
}
}
}
// Create a new PredictOptions object with the given options.
func NewPredictOptions(opts ...PredictOption) PredictOptions {
p := DefaultOptions
for _, opt := range opts {
opt(&p)
}
return p
}
// SetThreads sets the number of threads to use for text generation.
func SetThreads(c int) ModelOption {
return func(p *ModelOptions) {
p.Threads = c
}
}
// SetLibrarySearchPath sets the dynamic libraries used by gpt4all for the various ggml implementations.
func SetLibrarySearchPath(t string) ModelOption {
return func(p *ModelOptions) {
p.LibrarySearchPath = t
}
}
// Create a new PredictOptions object with the given options.
func NewModelOptions(opts ...ModelOption) ModelOptions {
p := DefaultModelOptions
for _, opt := range opts {
opt(&p)
}
return p
}

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@@ -1,5 +0,0 @@
# Make sure native directory never gets commited to git for the project.
/src/main/resources/native
# IntelliJ project file
*.iml

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@@ -1,80 +0,0 @@
# Java Bindings Developer documents.
This document is meant to anyone looking to build the Java bindings from source, test a build locally and perform a release.
## Building locally
Maven is the build tool used by the project. Maven version of 3.8 or higher is recommended. Make sure the **mvn**
is available on the command path.
The project builds to Java version 11 target so make sure that a JDK at version 11 or newer is installed.
### Setting up location of native shared libraries
The property **native.libs.location** in pom.xml may need to be set:
```
<properties>
...
<native.libs.location>C:\Users\felix\dev\gpt4all_java_bins\release_1_1_3_Jun22_2023</native.libs.location>
</properties>
```
All the native shared libraries bundled with the Java binding jar will be copied from this location.
The directory structure is **native/linux**, **native/macos**, **native/windows**. These directories are copied
into the **src/main/resources** folder during the build process.
For the purposes of local testing, none of these directories have to be present or just one OS type may be present.
If none of the native libraries are present in **native.libs.location** the shared libraries will be searched for
in location path set by **LLModel.LIBRARY_SEARCH_PATH** static variable in Java source code that is using the bindings.
Alternately you can copy the shared libraries into the **src/resources/native/linux** before
you build, but note **src/main/resources/native** is on the .gitignore, so it will not be committed to sources.
### Building
To package the bindings jar run:
```
mvn package
```
This will build two jars. One has only the Java bindings and the other is a fat jar that will have required dependencies included as well.
To package and install the Java bindings to your local maven repository run:
```
mvn install
```
### Using in a sample application
You can check out a sample project that uses the java bindings here:
https://github.com/felix-zaslavskiy/gpt4all-java-bindings-sample.git
1. First, update the dependency of java bindings to whatever you have installed in local repository such as **1.1.4-SNAPSHOT**
2. Second, update **Main.java** and set **baseModelPath** to the correct location of model weight files.
3. To make a runnable jar run:
```
mvn package
```
A fat jar is also created which is easy to run from command line:
```
java -jar target/gpt4all-java-bindings-sample-1.0-SNAPSHOT-jar-with-dependencies.jar
```
### Publish a public release.
For publishing a new version to maven central repository requires password and signing keys which F.Z. currently maintains, so
he is responsible for making a public release.
The procedure is as follows:
For a snapshot release
Run:
```
mvn deploy -P signing-profile
```
For a non-snapshot release
Run:
```
mvn clean deploy -P signing-profile,release
```

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@@ -1,126 +0,0 @@
# Java bindings
Java bindings let you load a gpt4all library into your Java application and execute text
generation using an intuitive and easy to use API. No GPU is required because gpt4all executes on the CPU.
The gpt4all models are quantized to easily fit into system RAM and use about 4 to 7GB of system RAM.
## Getting Started
You can add Java bindings into your Java project by adding the following dependency to your project:
**Maven**
```
<dependency>
<groupId>com.hexadevlabs</groupId>
<artifactId>gpt4all-java-binding</artifactId>
<version>1.1.5</version>
</dependency>
```
**Gradle**
```
implementation 'com.hexadevlabs:gpt4all-java-binding:1.1.5'
```
To add the library dependency for another build system see [Maven Central Java bindings](https://central.sonatype.com/artifact/com.hexadevlabs/gpt4all-java-binding/).
To download model binary weights file use a URL such as [`https://gpt4all.io/models/gguf/gpt4all-13b-snoozy-q4_0.gguf`](https://gpt4all.io/models/gguf/gpt4all-13b-snoozy-q4_0.gguf).
For information about other models available see the [model file list](https://github.com/nomic-ai/gpt4all/tree/main/gpt4all-chat#manual-download-of-models).
### Sample code
```java
public class Example {
public static void main(String[] args) {
String prompt = "### Human:\nWhat is the meaning of life\n### Assistant:";
// Replace the hardcoded path with the actual path where your model file resides
String modelFilePath = "C:\\Users\\felix\\AppData\\Local\\nomic.ai\\GPT4All\\ggml-gpt4all-j-v1.3-groovy.bin";
try (LLModel model = new LLModel(Path.of(modelFilePath))) {
// May generate up to 4096 tokens but generally stops early
LLModel.GenerationConfig config = LLModel.config()
.withNPredict(4096).build();
// Will also stream to standard output
String fullGeneration = model.generate(prompt, config, true);
} catch (Exception e) {
// Exceptions generally may happen if the model file fails to load
// for a number of reasons such as a file not found.
// It is possible that Java may not be able to dynamically load the native shared library or
// the llmodel shared library may not be able to dynamically load the backend
// implementation for the model file you provided.
//
// Once the LLModel class is successfully loaded into memory the text generation calls
// generally should not throw exceptions.
e.printStackTrace(); // Printing here but in a production system you may want to take some action.
}
}
}
```
For a Maven-based sample project that uses this library see this [sample project](https://github.com/felix-zaslavskiy/gpt4all-java-bindings-sample)
### Additional considerations
#### Logger warnings
The Java bindings library may produce a warning if you don't have a SLF4J binding included in your project:
```
SLF4J: Failed to load class "org.slf4j.impl.StaticLoggerBinder".
SLF4J: Defaulting to no-operation (NOP) logger implementation
SLF4J: See http://www.slf4j.org/codes.html#StaticLoggerBinder for further details.
```
The Java bindings only use logging for informational
purposes, so a logger is not essential to correctly use the library. You can ignore this warning if you don't have SLF4J bindings
in your project.
To add a simple logger using a Maven dependency you may use:
```
<dependency>
<groupId>org.slf4j</groupId>
<artifactId>slf4j-simple</artifactId>
<version>1.7.36</version>
</dependency>
```
#### Loading your native libraries
1. the Java bindings package JAR comes bundled with a native library files for Windows, macOS and Linux. These library files are
copied to a temporary directory and loaded at runtime. For advanced users who may want to package shared libraries into Docker containers
or want to use a custom build of the shared libraries and ignore the once bundled with the Java package they have option
to load libraries from your local directory by setting a static property to the location of library files.
There are no guarantees of compatibility if used in such a way so be careful if you really want to do it.
For example:
```java
class Example {
public static void main(String[] args) {
// gpt4all native shared libraries location
LLModel.LIBRARY_SEARCH_PATH = "C:\\Users\\felix\\gpt4all\\lib\\";
// ... use the library normally
}
}
```
2. Not every AVX-only shared library is bundled with the JAR right now to reduce size. Only libgptj-avx is included.
If you are running into issues please let us know using the [gpt4all project issue tracker](https://github.com/nomic-ai/gpt4all/issues).
3. For Windows the native library included in jar depends on specific Microsoft C and C++ (MSVC) runtime libraries which may not be installed on your system.
If this is the case you can easily download and install the latest x64 Microsoft Visual C++ Redistributable package from https://learn.microsoft.com/en-us/cpp/windows/latest-supported-vc-redist?view=msvc-170
4. When running Java in a Docker container it is advised to use eclipse-temurin:17-jre parent image. Alpine based parent images don't work due to the native library dependencies.
## Version history
1. Version **1.1.2**:
- Java bindings is compatible with gpt4ll version 2.4.6
- Initial stable release with the initial feature set
2. Version **1.1.3**:
- Java bindings is compatible with gpt4all version 2.4.8
- Add static GPT4ALL_VERSION to signify gpt4all version of the bindings
- Add PromptIsTooLongException for prompts that are longer than context size.
- Replit model support to include Metal Mac hardware support.
3. Version **1.1.4**:
- Java bindings is compatible with gpt4all version 2.4.11
- Falcon model support included.
4. Version **1.1.5**:
- Add a check for model file readability before loading model.

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@@ -1,6 +0,0 @@
## Needed
1. Integrate with circleci build pipeline like the C# binding.
## These are just ideas
1. Better Chat completions function.
2. Chat completion that returns result in OpenAI compatible format.

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@@ -1,216 +0,0 @@
<?xml version="1.0" encoding="UTF-8"?>
<project xmlns="http://maven.apache.org/POM/4.0.0"
xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
<modelVersion>4.0.0</modelVersion>
<groupId>com.hexadevlabs</groupId>
<artifactId>gpt4all-java-binding</artifactId>
<version>1.1.5</version>
<packaging>jar</packaging>
<properties>
<maven.compiler.source>11</maven.compiler.source>
<maven.compiler.target>11</maven.compiler.target>
<project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
<native.libs.location>C:\Users\felix\dev\gpt4all_java_bins\release_1_1_4_July8_2023</native.libs.location>
</properties>
<name>${project.groupId}:${project.artifactId}</name>
<description>Java bindings for GPT4ALL LLM</description>
<url>https://github.com/nomic-ai/gpt4all</url>
<licenses>
<license>
<name>The Apache License, Version 2.0</name>
<url>https://github.com/nomic-ai/gpt4all/blob/main/LICENSE.txt</url>
</license>
</licenses>
<developers>
<developer>
<name>Felix Zaslavskiy</name>
<email>felixz@hexadevlabs.com</email>
<organizationUrl>https://github.com/felix-zaslavskiy/</organizationUrl>
</developer>
</developers>
<scm>
<connection>scm:git:git://github.com/nomic-ai/gpt4all.git</connection>
<developerConnection>scm:git:ssh://github.com/nomic-ai/gpt4all.git</developerConnection>
<url>https://github.com/nomic-ai/gpt4all/tree/main</url>
</scm>
<dependencies>
<dependency>
<groupId>com.github.jnr</groupId>
<artifactId>jnr-ffi</artifactId>
<version>2.2.13</version>
</dependency>
<dependency>
<groupId>org.slf4j</groupId>
<artifactId>slf4j-api</artifactId>
<version>1.7.36</version>
</dependency>
<dependency>
<groupId>org.junit.jupiter</groupId>
<artifactId>junit-jupiter-api</artifactId>
<version>5.9.2</version>
<scope>test</scope>
</dependency>
<dependency>
<groupId>org.mockito</groupId>
<artifactId>mockito-junit-jupiter</artifactId>
<version>5.4.0</version>
<scope>test</scope>
</dependency>
<dependency>
<groupId>org.mockito</groupId>
<artifactId>mockito-core</artifactId>
<version>5.4.0</version>
<scope>test</scope>
</dependency>
</dependencies>
<distributionManagement>
<snapshotRepository>
<id>ossrh</id>
<url>https://s01.oss.sonatype.org/content/repositories/snapshots</url>
</snapshotRepository>
<repository>
<id>ossrh</id>
<url>https://s01.oss.sonatype.org/service/local/staging/deploy/maven2/</url>
</repository>
</distributionManagement>
<build>
<resources>
<resource>
<directory>src/main/resources</directory>
</resource>
<resource>
<directory>${project.build.directory}/generated-resources</directory>
</resource>
</resources>
<plugins>
<plugin>
<groupId>org.apache.maven.plugins</groupId>
<artifactId>maven-surefire-plugin</artifactId>
<version>3.0.0</version>
<configuration>
<forkCount>0</forkCount>
</configuration>
</plugin>
<plugin>
<groupId>org.apache.maven.plugins</groupId>
<artifactId>maven-resources-plugin</artifactId>
<version>3.3.1</version>
<executions>
<execution>
<id>copy-resources</id>
<!-- Here the phase you need -->
<phase>validate</phase>
<goals>
<goal>copy-resources</goal>
</goals>
<configuration>
<outputDirectory>${project.build.directory}/generated-resources</outputDirectory>
<resources>
<resource>
<directory>${native.libs.location}</directory>
</resource>
</resources>
</configuration>
</execution>
</executions>
</plugin>
<plugin>
<groupId>org.sonatype.plugins</groupId>
<artifactId>nexus-staging-maven-plugin</artifactId>
<version>1.6.13</version>
<extensions>true</extensions>
<configuration>
<serverId>ossrh</serverId>
<nexusUrl>https://s01.oss.sonatype.org/</nexusUrl>
<autoReleaseAfterClose>true</autoReleaseAfterClose>
</configuration>
</plugin>
<plugin>
<groupId>org.apache.maven.plugins</groupId>
<artifactId>maven-source-plugin</artifactId>
<version>2.2.1</version>
<executions>
<execution>
<id>attach-sources</id>
<goals>
<goal>jar-no-fork</goal>
</goals>
</execution>
</executions>
</plugin>
<plugin>
<groupId>org.apache.maven.plugins</groupId>
<artifactId>maven-javadoc-plugin</artifactId>
<version>3.5.0</version>
<executions>
<execution>
<id>attach-javadocs</id>
<goals>
<goal>jar</goal>
</goals>
</execution>
</executions>
</plugin>
<plugin>
<groupId>org.apache.maven.plugins</groupId>
<artifactId>maven-assembly-plugin</artifactId>
<version>3.6.0</version>
<configuration>
<descriptorRefs>
<descriptorRef>jar-with-dependencies</descriptorRef>
</descriptorRefs>
</configuration>
<executions>
<execution>
<id>make-assembly</id>
<phase>package</phase>
<goals>
<goal>single</goal>
</goals>
</execution>
</executions>
</plugin>
</plugins>
</build>
<profiles>
<profile>
<id>signing-profile</id>
<!-- activation conditions here, if any -->
<build>
<plugins>
<plugin>
<groupId>org.apache.maven.plugins</groupId>
<artifactId>maven-gpg-plugin</artifactId>
<version>3.1.0</version>
<executions>
<execution>
<id>sign-artifacts</id>
<phase>verify</phase>
<goals>
<goal>sign</goal>
</goals>
</execution>
</executions>
</plugin>
</plugins>
</build>
</profile>
</profiles>
</project>

View File

@@ -1,641 +0,0 @@
package com.hexadevlabs.gpt4all;
import jnr.ffi.Pointer;
import jnr.ffi.byref.PointerByReference;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import java.io.ByteArrayOutputStream;
import java.nio.charset.StandardCharsets;
import java.nio.file.Files;
import java.nio.file.Path;
import java.util.*;
import java.util.stream.Collectors;
public class LLModel implements AutoCloseable {
/**
* Config used for how to decode LLM outputs.
* High temperature closer to 1 gives more creative outputs
* while low temperature closer to 0 produce more precise outputs.
* <p>
* Use builder to set settings you want.
*/
public static class GenerationConfig extends LLModelLibrary.LLModelPromptContext {
private GenerationConfig() {
super(jnr.ffi.Runtime.getSystemRuntime());
logits_size.set(0);
tokens_size.set(0);
n_past.set(0);
n_ctx.set(1024);
n_predict.set(128);
top_k.set(40);
top_p.set(0.95);
min_p.set(0.0);
temp.set(0.28);
n_batch.set(8);
repeat_penalty.set(1.1);
repeat_last_n.set(10);
context_erase.set(0.55);
}
public static class Builder {
private final GenerationConfig configToBuild;
public Builder() {
configToBuild = new GenerationConfig();
}
public Builder withNPast(int n_past) {
configToBuild.n_past.set(n_past);
return this;
}
public Builder withNCtx(int n_ctx) {
configToBuild.n_ctx.set(n_ctx);
return this;
}
public Builder withNPredict(int n_predict) {
configToBuild.n_predict.set(n_predict);
return this;
}
public Builder withTopK(int top_k) {
configToBuild.top_k.set(top_k);
return this;
}
public Builder withTopP(float top_p) {
configToBuild.top_p.set(top_p);
return this;
}
public Builder withMinP(float min_p) {
configToBuild.min_p.set(min_p);
return this;
}
public Builder withTemp(float temp) {
configToBuild.temp.set(temp);
return this;
}
public Builder withNBatch(int n_batch) {
configToBuild.n_batch.set(n_batch);
return this;
}
public Builder withRepeatPenalty(float repeat_penalty) {
configToBuild.repeat_penalty.set(repeat_penalty);
return this;
}
public Builder withRepeatLastN(int repeat_last_n) {
configToBuild.repeat_last_n.set(repeat_last_n);
return this;
}
public Builder withContextErase(float context_erase) {
configToBuild.context_erase.set(context_erase);
return this;
}
/**
*
* @return GenerationConfig build instance of the config
*/
public GenerationConfig build() {
return configToBuild;
}
}
}
/**
* Shortcut for making GenerativeConfig builder.
*
* @return GenerationConfig.Builder - builder that can be used to make a GenerationConfig
*/
public static GenerationConfig.Builder config(){
return new GenerationConfig.Builder();
}
/**
* This may be set before any Model instance classes are instantiated to
* set where the native shared libraries are to be found.
* <p>
* This may be needed if setting library search path by standard means is not available
* or the libraries loaded from the temp folder bundled with the binding jar is not desirable.
*/
public static String LIBRARY_SEARCH_PATH;
/**
* Generally for debugging purposes only. Will print
* the numerical tokens as they are generated instead of the string representations.
* Will also print out the processed input tokens as numbers to standard out.
*/
public static boolean OUTPUT_DEBUG = false;
private static final Logger logger = LoggerFactory.getLogger(LLModel.class);
/**
* Which version of GPT4ALL that this binding is built for.
* The binding is guaranteed to work with this version of
* GPT4ALL native libraries. The binding may work for older
* versions but that is not guaranteed.
*/
public static final String GPT4ALL_VERSION = "2.4.11";
protected static LLModelLibrary library;
protected Pointer model;
protected String modelName;
/**
* Package private default constructor, for testing purposes.
*/
LLModel(){
}
public LLModel(Path modelPath) {
logger.info("Java bindings for gpt4all version: " + GPT4ALL_VERSION);
if(library==null) {
if (LIBRARY_SEARCH_PATH != null){
library = Util.loadSharedLibrary(LIBRARY_SEARCH_PATH);
library.llmodel_set_implementation_search_path(LIBRARY_SEARCH_PATH);
} else {
// Copy system libraries to Temp folder
Path tempLibraryDirectory = Util.copySharedLibraries();
library = Util.loadSharedLibrary(tempLibraryDirectory.toString());
library.llmodel_set_implementation_search_path(tempLibraryDirectory.toString() );
}
}
// modelType = type;
modelName = modelPath.getFileName().toString();
String modelPathAbs = modelPath.toAbsolutePath().toString();
PointerByReference error = new PointerByReference();
// Check if model file exists
if(!Files.exists(modelPath)){
throw new IllegalStateException("Model file does not exist: " + modelPathAbs);
}
// Check if file is Readable
if(!Files.isReadable(modelPath)){
throw new IllegalStateException("Model file cannot be read: " + modelPathAbs);
}
// Create Model Struct. Will load dynamically the correct backend based on model type
model = library.llmodel_model_create2(modelPathAbs, "auto", error);
if(model == null) {
throw new IllegalStateException("Could not load, gpt4all backend returned error: " + error.getValue().getString(0));
}
library.llmodel_loadModel(model, modelPathAbs, 2048, 100);
if(!library.llmodel_isModelLoaded(model)){
throw new IllegalStateException("The model " + modelName + " could not be loaded");
}
}
public void setThreadCount(int nThreads) {
library.llmodel_setThreadCount(this.model, nThreads);
}
public int threadCount() {
return library.llmodel_threadCount(this.model);
}
/**
* Generate text after the prompt
*
* @param prompt The text prompt to complete
* @param generationConfig What generation settings to use while generating text
* @return String The complete generated text
*/
public String generate(String prompt, GenerationConfig generationConfig) {
return generate(prompt, generationConfig, false);
}
/**
* Generate text after the prompt
*
* @param prompt The text prompt to complete
* @param generationConfig What generation settings to use while generating text
* @param streamToStdOut Should the generation be streamed to standard output. Useful for troubleshooting.
* @return String The complete generated text
*/
public String generate(String prompt, GenerationConfig generationConfig, boolean streamToStdOut) {
ByteArrayOutputStream bufferingForStdOutStream = new ByteArrayOutputStream();
ByteArrayOutputStream bufferingForWholeGeneration = new ByteArrayOutputStream();
LLModelLibrary.ResponseCallback responseCallback = getResponseCallback(streamToStdOut, bufferingForStdOutStream, bufferingForWholeGeneration);
library.llmodel_prompt(this.model,
prompt,
(int tokenID) -> {
if(LLModel.OUTPUT_DEBUG)
System.out.println("token " + tokenID);
return true; // continue processing
},
responseCallback,
(boolean isRecalculating) -> {
if(LLModel.OUTPUT_DEBUG)
System.out.println("recalculating");
return isRecalculating; // continue generating
},
generationConfig);
return bufferingForWholeGeneration.toString(StandardCharsets.UTF_8);
}
/**
* Callback method to be used by prompt method as text is generated.
*
* @param streamToStdOut Should send generated text to standard out.
* @param bufferingForStdOutStream Output stream used for buffering bytes for standard output.
* @param bufferingForWholeGeneration Output stream used for buffering a complete generation.
* @return LLModelLibrary.ResponseCallback lambda function that is invoked by response callback.
*/
static LLModelLibrary.ResponseCallback getResponseCallback(boolean streamToStdOut, ByteArrayOutputStream bufferingForStdOutStream, ByteArrayOutputStream bufferingForWholeGeneration) {
return (int tokenID, Pointer response) -> {
if(LLModel.OUTPUT_DEBUG)
System.out.print("Response token " + tokenID + " " );
// For all models if input sequence in tokens is longer then model context length
// the error is generated.
if(tokenID==-1){
throw new PromptIsTooLongException(response.getString(0, 1000, StandardCharsets.UTF_8));
}
long len = 0;
byte nextByte;
do{
try {
nextByte = response.getByte(len);
} catch(IndexOutOfBoundsException e){
// Not sure if this can ever happen but just in case
// the generation does not terminate in a Null (0) value.
throw new RuntimeException("Empty array or not null terminated");
}
len++;
if(nextByte!=0) {
bufferingForWholeGeneration.write(nextByte);
if(streamToStdOut){
bufferingForStdOutStream.write(nextByte);
// Test if Buffer is UTF8 valid string.
byte[] currentBytes = bufferingForStdOutStream.toByteArray();
String validString = Util.getValidUtf8(currentBytes);
if(validString!=null){ // is valid string
System.out.print(validString);
// reset the buffer for next utf8 sequence to buffer
bufferingForStdOutStream.reset();
}
}
}
} while(nextByte != 0);
return true; // continue generating
};
}
/**
* The array of messages for the conversation.
*/
public static class Messages {
private final List<PromptMessage> messages = new ArrayList<>();
public Messages(PromptMessage...messages) {
this.messages.addAll(Arrays.asList(messages));
}
public Messages(List<PromptMessage> messages) {
this.messages.addAll(messages);
}
public Messages addPromptMessage(PromptMessage promptMessage) {
this.messages.add(promptMessage);
return this;
}
List<PromptMessage> toList() {
return Collections.unmodifiableList(this.messages);
}
List<Map<String, String>> toListMap() {
return messages.stream()
.map(PromptMessage::toMap).collect(Collectors.toList());
}
}
/**
* A message in the conversation, identical to OpenAI's chat message.
*/
public static class PromptMessage {
private static final String ROLE = "role";
private static final String CONTENT = "content";
private final Map<String, String> message = new HashMap<>();
public PromptMessage() {
}
public PromptMessage(Role role, String content) {
addRole(role);
addContent(content);
}
public PromptMessage addRole(Role role) {
return this.addParameter(ROLE, role.type());
}
public PromptMessage addContent(String content) {
return this.addParameter(CONTENT, content);
}
public PromptMessage addParameter(String key, String value) {
this.message.put(key, value);
return this;
}
public String content() {
return this.parameter(CONTENT);
}
public Role role() {
String role = this.parameter(ROLE);
return Role.from(role);
}
public String parameter(String key) {
return this.message.get(key);
}
Map<String, String> toMap() {
return Collections.unmodifiableMap(this.message);
}
}
public enum Role {
SYSTEM("system"), ASSISTANT("assistant"), USER("user");
private final String type;
String type() {
return this.type;
}
static Role from(String type) {
if (type == null) {
return null;
}
switch (type) {
case "system": return SYSTEM;
case "assistant": return ASSISTANT;
case "user": return USER;
default: throw new IllegalArgumentException(
String.format("You passed %s type but only %s are supported",
type, Arrays.toString(Role.values())
)
);
}
}
Role(String type) {
this.type = type;
}
@Override
public String toString() {
return type();
}
}
/**
* The result of the completion, similar to OpenAI's format.
*/
public static class CompletionReturn {
private String model;
private Usage usage;
private Choices choices;
public CompletionReturn(String model, Usage usage, Choices choices) {
this.model = model;
this.usage = usage;
this.choices = choices;
}
public Choices choices() {
return choices;
}
public String model() {
return model;
}
public Usage usage() {
return usage;
}
}
/**
* The generated completions.
*/
public static class Choices {
private final List<CompletionChoice> choices = new ArrayList<>();
public Choices(List<CompletionChoice> choices) {
this.choices.addAll(choices);
}
public Choices(CompletionChoice...completionChoices){
this.choices.addAll(Arrays.asList(completionChoices));
}
public Choices addCompletionChoice(CompletionChoice completionChoice) {
this.choices.add(completionChoice);
return this;
}
public CompletionChoice first() {
return this.choices.get(0);
}
public int totalChoices() {
return this.choices.size();
}
public CompletionChoice get(int index) {
return this.choices.get(index);
}
public List<CompletionChoice> choices() {
return Collections.unmodifiableList(choices);
}
}
/**
* A completion choice, similar to OpenAI's format.
*/
public static class CompletionChoice extends PromptMessage {
public CompletionChoice(Role role, String content) {
super(role, content);
}
}
public static class ChatCompletionResponse {
public String model;
public Usage usage;
public List<Map<String, String>> choices;
// Getters and setters
}
public static class Usage {
public int promptTokens;
public int completionTokens;
public int totalTokens;
// Getters and setters
}
public CompletionReturn chatCompletionResponse(Messages messages,
GenerationConfig generationConfig) {
return chatCompletion(messages, generationConfig, false, false);
}
/**
* chatCompletion formats the existing chat conversation into a template to be
* easier to process for chat UIs. It is not absolutely necessary as generate method
* may be directly used to make generations with gpt models.
*
* @param messages object to create theMessages to send to GPT model
* @param generationConfig How to decode/process the generation.
* @param streamToStdOut Send tokens as they are calculated Standard output.
* @param outputFullPromptToStdOut Should full prompt built out of messages be sent to Standard output.
* @return CompletionReturn contains stats and generated Text.
*/
public CompletionReturn chatCompletion(Messages messages,
GenerationConfig generationConfig, boolean streamToStdOut,
boolean outputFullPromptToStdOut) {
String fullPrompt = buildPrompt(messages.toListMap());
if(outputFullPromptToStdOut)
System.out.print(fullPrompt);
String generatedText = generate(fullPrompt, generationConfig, streamToStdOut);
final CompletionChoice promptMessage = new CompletionChoice(Role.ASSISTANT, generatedText);
final Choices choices = new Choices(promptMessage);
final Usage usage = getUsage(fullPrompt, generatedText);
return new CompletionReturn(this.modelName, usage, choices);
}
public ChatCompletionResponse chatCompletion(List<Map<String, String>> messages,
GenerationConfig generationConfig) {
return chatCompletion(messages, generationConfig, false, false);
}
/**
* chatCompletion formats the existing chat conversation into a template to be
* easier to process for chat UIs. It is not absolutely necessary as generate method
* may be directly used to make generations with gpt models.
*
* @param messages List of Maps "role"-&gt;"user", "content"-&gt;"...", "role"-&gt; "assistant"-&gt;"..."
* @param generationConfig How to decode/process the generation.
* @param streamToStdOut Send tokens as they are calculated Standard output.
* @param outputFullPromptToStdOut Should full prompt built out of messages be sent to Standard output.
* @return ChatCompletionResponse contains stats and generated Text.
*/
public ChatCompletionResponse chatCompletion(List<Map<String, String>> messages,
GenerationConfig generationConfig, boolean streamToStdOut,
boolean outputFullPromptToStdOut) {
String fullPrompt = buildPrompt(messages);
if(outputFullPromptToStdOut)
System.out.print(fullPrompt);
String generatedText = generate(fullPrompt, generationConfig, streamToStdOut);
ChatCompletionResponse response = new ChatCompletionResponse();
response.model = this.modelName;
response.usage = getUsage(fullPrompt, generatedText);
Map<String, String> message = new HashMap<>();
message.put("role", "assistant");
message.put("content", generatedText);
response.choices = List.of(message);
return response;
}
private Usage getUsage(String fullPrompt, String generatedText) {
Usage usage = new Usage();
usage.promptTokens = fullPrompt.length();
usage.completionTokens = generatedText.length();
usage.totalTokens = fullPrompt.length() + generatedText.length();
return usage;
}
protected static String buildPrompt(List<Map<String, String>> messages) {
StringBuilder fullPrompt = new StringBuilder();
for (Map<String, String> message : messages) {
if ("system".equals(message.get("role"))) {
String systemMessage = message.get("content") + "\n";
fullPrompt.append(systemMessage);
}
}
fullPrompt.append("### Instruction: \n" +
"The prompt below is a question to answer, a task to complete, or a conversation to respond to; decide which and write an appropriate response.\n" +
"### Prompt: ");
for (Map<String, String> message : messages) {
if ("user".equals(message.get("role"))) {
String userMessage = "\n" + message.get("content");
fullPrompt.append(userMessage);
}
if ("assistant".equals(message.get("role"))) {
String assistantMessage = "\n### Response: " + message.get("content");
fullPrompt.append(assistantMessage);
}
}
fullPrompt.append("\n### Response:");
return fullPrompt.toString();
}
@Override
public void close() throws Exception {
library.llmodel_model_destroy(model);
}
}

View File

@@ -1,81 +0,0 @@
package com.hexadevlabs.gpt4all;
import jnr.ffi.Pointer;
import jnr.ffi.byref.PointerByReference;
import jnr.ffi.Struct;
import jnr.ffi.annotations.Delegate;
import jnr.ffi.annotations.Encoding;
import jnr.ffi.annotations.In;
import jnr.ffi.annotations.Out;
import jnr.ffi.types.u_int64_t;
/**
* The basic Native library interface the provides all the LLM functions.
*/
public interface LLModelLibrary {
interface PromptCallback {
@Delegate
boolean invoke(int token_id);
}
interface ResponseCallback {
@Delegate
boolean invoke(int token_id, Pointer response);
}
interface RecalculateCallback {
@Delegate
boolean invoke(boolean is_recalculating);
}
class LLModelError extends Struct {
public final Struct.AsciiStringRef message = new Struct.AsciiStringRef();
public final int32_t status = new int32_t();
public LLModelError(jnr.ffi.Runtime runtime) {
super(runtime);
}
}
class LLModelPromptContext extends Struct {
public final Pointer logits = new Pointer();
public final ssize_t logits_size = new ssize_t();
public final Pointer tokens = new Pointer();
public final ssize_t tokens_size = new ssize_t();
public final int32_t n_past = new int32_t();
public final int32_t n_ctx = new int32_t();
public final int32_t n_predict = new int32_t();
public final int32_t top_k = new int32_t();
public final Float top_p = new Float();
public final Float min_p = new Float();
public final Float temp = new Float();
public final int32_t n_batch = new int32_t();
public final Float repeat_penalty = new Float();
public final int32_t repeat_last_n = new int32_t();
public final Float context_erase = new Float();
public LLModelPromptContext(jnr.ffi.Runtime runtime) {
super(runtime);
}
}
Pointer llmodel_model_create2(String model_path, String build_variant, PointerByReference error);
void llmodel_model_destroy(Pointer model);
boolean llmodel_loadModel(Pointer model, String model_path, int n_ctx, int ngl);
boolean llmodel_isModelLoaded(Pointer model);
@u_int64_t long llmodel_get_state_size(Pointer model);
@u_int64_t long llmodel_save_state_data(Pointer model, Pointer dest);
@u_int64_t long llmodel_restore_state_data(Pointer model, Pointer src);
void llmodel_set_implementation_search_path(String path);
// ctx was an @Out ... without @Out crash
void llmodel_prompt(Pointer model, @Encoding("UTF-8") String prompt,
PromptCallback prompt_callback,
ResponseCallback response_callback,
RecalculateCallback recalculate_callback,
@In LLModelPromptContext ctx);
void llmodel_setThreadCount(Pointer model, int n_threads);
int llmodel_threadCount(Pointer model);
}

View File

@@ -1,7 +0,0 @@
package com.hexadevlabs.gpt4all;
public class PromptIsTooLongException extends RuntimeException {
public PromptIsTooLongException(String message) {
super(message);
}
}

View File

@@ -1,160 +0,0 @@
package com.hexadevlabs.gpt4all;
import jnr.ffi.LibraryLoader;
import jnr.ffi.LibraryOption;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import java.io.IOException;
import java.io.InputStream;
import java.nio.ByteBuffer;
import java.nio.charset.CharacterCodingException;
import java.nio.charset.CharsetDecoder;
import java.nio.charset.StandardCharsets;
import java.nio.file.Files;
import java.nio.file.Path;
import java.nio.file.StandardCopyOption;
import java.util.Comparator;
import java.util.HashMap;
import java.util.List;
import java.util.Map;
public class Util {
private static final Logger logger = LoggerFactory.getLogger(Util.class);
private static final CharsetDecoder cs = StandardCharsets.UTF_8.newDecoder();
public static LLModelLibrary loadSharedLibrary(String librarySearchPath){
String libraryName = "llmodel";
Map<LibraryOption, Object> libraryOptions = new HashMap<>();
libraryOptions.put(LibraryOption.LoadNow, true); // load immediately instead of lazily (ie on first use)
libraryOptions.put(LibraryOption.IgnoreError, false); // calls shouldn't save last errno after call
if(librarySearchPath!=null) {
Map<String, List<String>> searchPaths = new HashMap<>();
searchPaths.put(libraryName, List.of(librarySearchPath));
return LibraryLoader.loadLibrary(LLModelLibrary.class,
libraryOptions,
searchPaths,
libraryName
);
}else {
return LibraryLoader.loadLibrary(LLModelLibrary.class,
libraryOptions,
libraryName
);
}
}
/**
* Copy over shared library files from resource package to
* target Temp directory.
*
* @return Path path to the temp directory holding the shared libraries
*/
public static Path copySharedLibraries() {
try {
// Identify the OS and architecture
String osName = System.getProperty("os.name").toLowerCase();
boolean isWindows = osName.startsWith("windows");
boolean isMac = osName.startsWith("mac os x");
boolean isLinux = osName.startsWith("linux");
if(isWindows) osName = "windows";
if(isMac) osName = "macos";
if(isLinux) osName = "linux";
//String osArch = System.getProperty("os.arch");
// Create a temporary directory
Path tempDirectory = Files.createTempDirectory("nativeLibraries");
tempDirectory.toFile().deleteOnExit();
String[] libraryNames = {
"gptj-default",
"gptj-avxonly",
"llmodel",
"mpt-default",
"llamamodel-230511-default",
"llamamodel-230519-default",
"llamamodel-mainline-default",
"llamamodel-mainline-metal",
"replit-mainline-default",
"replit-mainline-metal",
"ggml-metal.metal",
"falcon-default"
};
for (String libraryName : libraryNames) {
if(!isMac && (
libraryName.equals("replit-mainline-metal")
|| libraryName.equals("llamamodel-mainline-metal")
|| libraryName.equals("ggml-metal.metal"))
) continue;
if(isWindows){
libraryName = libraryName + ".dll";
} else if(isMac){
if(!libraryName.equals("ggml-metal.metal"))
libraryName = "lib" + libraryName + ".dylib";
} else if(isLinux) {
libraryName = "lib"+ libraryName + ".so";
}
// Construct the resource path based on the OS and architecture
String nativeLibraryPath = "/native/" + osName + "/" + libraryName;
// Get the library resource as a stream
InputStream in = Util.class.getResourceAsStream(nativeLibraryPath);
if (in == null) {
throw new RuntimeException("Unable to find native library: " + nativeLibraryPath);
}
// Create a file in the temporary directory with the original library name
Path tempLibraryPath = tempDirectory.resolve(libraryName);
// Use Files.copy to copy the library to the temporary file
Files.copy(in, tempLibraryPath, StandardCopyOption.REPLACE_EXISTING);
// Close the input stream
in.close();
}
// Add shutdown hook to delete tempDir on JVM exit
// On Windows deleting dll files that are loaded into memory is not possible.
if(!isWindows) {
Runtime.getRuntime().addShutdownHook(new Thread(() -> {
try {
Files.walk(tempDirectory)
.sorted(Comparator.reverseOrder())
.map(Path::toFile)
.forEach(file -> {
try {
Files.delete(file.toPath());
} catch (IOException e) {
logger.error("Deleting temp library file", e);
}
});
} catch (IOException e) {
logger.error("Deleting temp directory for libraries", e);
}
}));
}
return tempDirectory;
} catch (IOException e) {
throw new RuntimeException("Failed to load native libraries", e);
}
}
public static String getValidUtf8(byte[] bytes) {
try {
return cs.decode(ByteBuffer.wrap(bytes)).toString();
} catch (CharacterCodingException e) {
return null;
}
}
}

View File

@@ -1,182 +0,0 @@
package com.hexadevlabs.gpt4all;
import jnr.ffi.Memory;
import jnr.ffi.Pointer;
import jnr.ffi.Runtime;
import org.junit.jupiter.api.Test;
import org.junit.jupiter.api.extension.ExtendWith;
import org.mockito.Mockito;
import org.mockito.junit.jupiter.MockitoExtension;
import java.io.ByteArrayOutputStream;
import java.nio.charset.StandardCharsets;
import java.util.List;
import java.util.Map;
import static org.junit.jupiter.api.Assertions.*;
import static org.mockito.ArgumentMatchers.anyString;
import static org.mockito.Mockito.*;
/**
* These tests only test the Java implementation as the underlying backend can't be mocked.
* These tests do serve the purpose of validating the java bits that do
* not directly have to do with the function of the underlying gp4all library.
*/
@ExtendWith(MockitoExtension.class)
public class BasicTests {
@Test
public void simplePromptWithObject(){
LLModel model = Mockito.spy(new LLModel());
LLModel.GenerationConfig config =
LLModel.config()
.withNPredict(20)
.build();
// The generate method will return "4"
doReturn("4").when( model ).generate(anyString(), eq(config), eq(true));
LLModel.PromptMessage promptMessage1 = new LLModel.PromptMessage(LLModel.Role.SYSTEM, "You are a helpful assistant");
LLModel.PromptMessage promptMessage2 = new LLModel.PromptMessage(LLModel.Role.USER, "Add 2+2");
LLModel.Messages messages = new LLModel.Messages(promptMessage1, promptMessage2);
LLModel.CompletionReturn response = model.chatCompletion(
messages, config, true, true);
assertTrue( response.choices().first().content().contains("4") );
// Verifies the prompt and response are certain length.
assertEquals( 224 , response.usage().totalTokens );
}
@Test
public void simplePrompt(){
LLModel model = Mockito.spy(new LLModel());
LLModel.GenerationConfig config =
LLModel.config()
.withNPredict(20)
.build();
// The generate method will return "4"
doReturn("4").when( model ).generate(anyString(), eq(config), eq(true));
LLModel.ChatCompletionResponse response= model.chatCompletion(
List.of(Map.of("role", "system", "content", "You are a helpful assistant"),
Map.of("role", "user", "content", "Add 2+2")), config, true, true);
assertTrue( response.choices.get(0).get("content").contains("4") );
// Verifies the prompt and response are certain length.
assertEquals( 224 , response.usage.totalTokens );
}
@Test
public void testResponseCallback(){
ByteArrayOutputStream bufferingForStdOutStream = new ByteArrayOutputStream();
ByteArrayOutputStream bufferingForWholeGeneration = new ByteArrayOutputStream();
LLModelLibrary.ResponseCallback responseCallback = LLModel.getResponseCallback(false, bufferingForStdOutStream, bufferingForWholeGeneration);
// Get the runtime instance
Runtime runtime = Runtime.getSystemRuntime();
// Allocate memory for the byte array. Has to be null terminated
// UTF-8 Encoding of the character: 0xF0 0x9F 0x92 0xA9
byte[] utf8ByteArray = {(byte) 0xF0, (byte) 0x9F, (byte) 0x92, (byte) 0xA9, 0x00}; // Adding null termination
// Optional: Converting the byte array back to a String to print the character
String decodedString = new String(utf8ByteArray, 0, utf8ByteArray.length - 1, java.nio.charset.StandardCharsets.UTF_8);
Pointer pointer = Memory.allocateDirect(runtime, utf8ByteArray.length);
// Copy the byte array to the allocated memory
pointer.put(0, utf8ByteArray, 0, utf8ByteArray.length);
responseCallback.invoke(1, pointer);
String result = bufferingForWholeGeneration.toString(StandardCharsets.UTF_8);
assertEquals(decodedString, result);
}
@Test
public void testResponseCallbackTwoTokens(){
ByteArrayOutputStream bufferingForStdOutStream = new ByteArrayOutputStream();
ByteArrayOutputStream bufferingForWholeGeneration = new ByteArrayOutputStream();
LLModelLibrary.ResponseCallback responseCallback = LLModel.getResponseCallback(false, bufferingForStdOutStream, bufferingForWholeGeneration);
// Get the runtime instance
Runtime runtime = Runtime.getSystemRuntime();
// Allocate memory for the byte array. Has to be null terminated
// UTF-8 Encoding of the character: 0xF0 0x9F 0x92 0xA9
byte[] utf8ByteArray = { (byte) 0xF0, (byte) 0x9F, 0x00}; // Adding null termination
byte[] utf8ByteArray2 = { (byte) 0x92, (byte) 0xA9, 0x00}; // Adding null termination
// Optional: Converting the byte array back to a String to print the character
Pointer pointer = Memory.allocateDirect(runtime, utf8ByteArray.length);
// Copy the byte array to the allocated memory
pointer.put(0, utf8ByteArray, 0, utf8ByteArray.length);
responseCallback.invoke(1, pointer);
// Copy the byte array to the allocated memory
pointer.put(0, utf8ByteArray2, 0, utf8ByteArray2.length);
responseCallback.invoke(2, pointer);
String result = bufferingForWholeGeneration.toString(StandardCharsets.UTF_8);
assertEquals("\uD83D\uDCA9", result);
}
@Test
public void testResponseCallbackExpectError(){
ByteArrayOutputStream bufferingForStdOutStream = new ByteArrayOutputStream();
ByteArrayOutputStream bufferingForWholeGeneration = new ByteArrayOutputStream();
LLModelLibrary.ResponseCallback responseCallback = LLModel.getResponseCallback(false, bufferingForStdOutStream, bufferingForWholeGeneration);
// Get the runtime instance
Runtime runtime = Runtime.getSystemRuntime();
// UTF-8 Encoding of the character: 0xF0 0x9F 0x92 0xA9
byte[] utf8ByteArray = {(byte) 0xF0, (byte) 0x9F, (byte) 0x92, (byte) 0xA9}; // No null termination
Pointer pointer = Memory.allocateDirect(runtime, utf8ByteArray.length);
// Copy the byte array to the allocated memory
pointer.put(0, utf8ByteArray, 0, utf8ByteArray.length);
Exception exception = assertThrows(RuntimeException.class, () -> responseCallback.invoke(1, pointer));
assertEquals("Empty array or not null terminated", exception.getMessage());
// With empty array
utf8ByteArray = new byte[0];
pointer.put(0, utf8ByteArray, 0, utf8ByteArray.length);
Exception exceptionN = assertThrows(RuntimeException.class, () -> responseCallback.invoke(1, pointer));
assertEquals("Empty array or not null terminated", exceptionN.getMessage());
}
}

View File

@@ -1,30 +0,0 @@
package com.hexadevlabs.gpt4all;
import java.nio.file.Path;
import java.util.List;
import java.util.Map;
/**
* GPTJ chat completion, multiple messages
*/
public class Example1 {
public static void main(String[] args) {
// Optionally in case override to location of shared libraries is necessary
//LLModel.LIBRARY_SEARCH_PATH = "C:\\Users\\felix\\gpt4all\\lib\\";
try ( LLModel gptjModel = new LLModel(Path.of("C:\\Users\\felix\\AppData\\Local\\nomic.ai\\GPT4All\\ggml-gpt4all-j-v1.3-groovy.bin")) ){
LLModel.GenerationConfig config = LLModel.config()
.withNPredict(4096).build();
gptjModel.chatCompletion(
List.of(Map.of("role", "user", "content", "Add 2+2"),
Map.of("role", "assistant", "content", "4"),
Map.of("role", "user", "content", "Multiply 4 * 5")), config, true, true);
} catch (Exception e) {
throw new RuntimeException(e);
}
}
}

View File

@@ -1,31 +0,0 @@
package com.hexadevlabs.gpt4all;
import java.nio.file.Path;
/**
* Generation with MPT model
*/
public class Example2 {
public static void main(String[] args) {
String prompt = "### Human:\nWhat is the meaning of life\n### Assistant:";
// Optionally in case override to location of shared libraries is necessary
//LLModel.LIBRARY_SEARCH_PATH = "C:\\Users\\felix\\gpt4all\\lib\\";
try (LLModel mptModel = new LLModel(Path.of("C:\\Users\\felix\\AppData\\Local\\nomic.ai\\GPT4All\\ggml-mpt-7b-instruct.bin"))) {
LLModel.GenerationConfig config =
LLModel.config()
.withNPredict(4096)
.withRepeatLastN(64)
.build();
mptModel.generate(prompt, config, true);
} catch (Exception e) {
throw new RuntimeException(e);
}
}
}

View File

@@ -1,33 +0,0 @@
package com.hexadevlabs.gpt4all;
import jnr.ffi.LibraryLoader;
import java.nio.file.Path;
import java.util.List;
import java.util.Map;
/**
* GPTJ chat completion with system message
*/
public class Example3 {
public static void main(String[] args) {
// Optionally in case override to location of shared libraries is necessary
//LLModel.LIBRARY_SEARCH_PATH = "C:\\Users\\felix\\gpt4all\\lib\\";
try ( LLModel gptjModel = new LLModel(Path.of("C:\\Users\\felix\\AppData\\Local\\nomic.ai\\GPT4All\\ggml-gpt4all-j-v1.3-groovy.bin")) ){
LLModel.GenerationConfig config = LLModel.config()
.withNPredict(4096).build();
// String result = gptjModel.generate(prompt, config, true);
gptjModel.chatCompletion(
List.of(Map.of("role", "system", "content", "You are a helpful assistant"),
Map.of("role", "user", "content", "Add 2+2")), config, true, true);
} catch (Exception e) {
throw new RuntimeException(e);
}
}
}

View File

@@ -1,43 +0,0 @@
package com.hexadevlabs.gpt4all;
import java.nio.file.Path;
public class Example4 {
public static void main(String[] args) {
String prompt = "### Human:\nWhat is the meaning of life\n### Assistant:";
// The emoji is poop emoji. The Unicode character is encoded as surrogate pair for Java string.
// LLM should correctly identify it as poop emoji in the description
//String prompt = "### Human:\nDescribe the meaning of this emoji \uD83D\uDCA9\n### Assistant:";
//String prompt = "### Human:\nOutput the unicode character of smiley face emoji\n### Assistant:";
// Optionally in case override to location of shared libraries is necessary
//LLModel.LIBRARY_SEARCH_PATH = "C:\\Users\\felix\\gpt4all\\lib\\";
String model = "ggml-vicuna-7b-1.1-q4_2.bin";
//String model = "ggml-gpt4all-j-v1.3-groovy.bin";
//String model = "ggml-mpt-7b-instruct.bin";
String basePath = "C:\\Users\\felix\\AppData\\Local\\nomic.ai\\GPT4All\\";
//String basePath = "/Users/fzaslavs/Library/Application Support/nomic.ai/GPT4All/";
try (LLModel mptModel = new LLModel(Path.of(basePath + model))) {
LLModel.GenerationConfig config =
LLModel.config()
.withNPredict(4096)
.withRepeatLastN(64)
.build();
String result = mptModel.generate(prompt, config, true);
System.out.println("Code points:");
result.codePoints().forEach(System.out::println);
} catch (Exception e) {
throw new RuntimeException(e);
}
}
}

View File

@@ -1,47 +0,0 @@
package com.hexadevlabs.gpt4all;
import java.nio.file.Path;
public class Example5 {
public static void main(String[] args) {
// String prompt = "### Human:\nWhat is the meaning of life\n### Assistant:";
// The emoji is poop emoji. The Unicode character is encoded as surrogate pair for Java string.
// LLM should correctly identify it as poop emoji in the description
//String prompt = "### Human:\nDescribe the meaning of this emoji \uD83D\uDCA9\n### Assistant:";
//String prompt = "### Human:\nOutput the unicode character of smiley face emoji\n### Assistant:";
// Optionally in case override to location of shared libraries is necessary
//LLModel.LIBRARY_SEARCH_PATH = "C:\\Users\\felix\\gpt4all\\lib\\";
StringBuffer b = new StringBuffer();
b.append("The ".repeat(2060));
String prompt = b.toString();
String model = "ggml-vicuna-7b-1.1-q4_2.bin";
//String model = "ggml-gpt4all-j-v1.3-groovy.bin";
//String model = "ggml-mpt-7b-instruct.bin";
String basePath = "C:\\Users\\felix\\AppData\\Local\\nomic.ai\\GPT4All\\";
//String basePath = "/Users/fzaslavs/Library/Application Support/nomic.ai/GPT4All/";
try (LLModel mptModel = new LLModel(Path.of(basePath + model))) {
LLModel.GenerationConfig config =
LLModel.config()
.withNPredict(4096)
.withRepeatLastN(64)
.build();
String result = mptModel.generate(prompt, config, true);
System.out.println("Code points:");
result.codePoints().forEach(System.out::println);
} catch (Exception e) {
System.out.println(e.getMessage());
throw new RuntimeException(e);
}
}
}

View File

@@ -53,7 +53,7 @@ cmake --build build --parallel
2. Install the Python package:
```
cd ../../gpt4all-bindings/python
cd ../gpt4all-bindings/python
pip install -e .
```

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@@ -0,0 +1,70 @@
# Monitoring
Leverage OpenTelemetry to perform real-time monitoring of your LLM application and GPUs using [OpenLIT](https://github.com/openlit/openlit). This tool helps you easily collect data on user interactions, performance metrics, along with GPU Performance metrics, which can assist in enhancing the functionality and dependability of your GPT4All based LLM application.
## How it works?
OpenLIT adds automatic OTel instrumentation to the GPT4All SDK. It covers the `generate` and `embedding` functions, helping to track LLM usage by gathering inputs and outputs. This allows users to monitor and evaluate the performance and behavior of their LLM application in different environments. OpenLIT also provides OTel auto-instrumentation for monitoring GPU metrics like utilization, temperature, power usage, and memory usage.
Additionally, you have the flexibility to view and analyze the generated traces and metrics either in the OpenLIT UI or by exporting them to widely used observability tools like Grafana and DataDog for more comprehensive analysis and visualization.
## Getting Started
Heres a straightforward guide to help you set up and start monitoring your application:
### 1. Install the OpenLIT SDK
Open your terminal and run:
```shell
pip install openlit
```
### 2. Setup Monitoring for your Application
In your application, initiate OpenLIT as outlined below:
```python
from gpt4all import GPT4All
import openlit
openlit.init() # Initialize OpenLIT monitoring
model = GPT4All(model_name='orca-mini-3b-gguf2-q4_0.gguf')
# Start a chat session and send queries
with model.chat_session():
response1 = model.generate(prompt='hello', temp=0)
response2 = model.generate(prompt='write me a short poem', temp=0)
response3 = model.generate(prompt='thank you', temp=0)
print(model.current_chat_session)
```
This setup wraps your gpt4all model interactions, capturing valuable data about each request and response.
### 3. (Optional) Enable GPU Monitoring
If your application runs on NVIDIA GPUs, you can enable GPU stats collection in the OpenLIT SDK by adding `collect_gpu_stats=True`. This collects GPU metrics like utilization, temperature, power usage, and memory-related performance metrics. The collected metrics are OpenTelemetry gauges.
```python
from gpt4all import GPT4All
import openlit
openlit.init(collect_gpu_stats=True) # Initialize OpenLIT monitoring
model = GPT4All(model_name='orca-mini-3b-gguf2-q4_0.gguf')
# Start a chat session and send queries
with model.chat_session():
response1 = model.generate(prompt='hello', temp=0)
response2 = model.generate(prompt='write me a short poem', temp=0)
response3 = model.generate(prompt='thank you', temp=0)
print(model.current_chat_session)
```
### Visualize
Once you've set up data collection with [OpenLIT](https://github.com/openlit/openlit), you can visualize and analyze this information to better understand your application's performance:
- **Using OpenLIT UI:** Connect to OpenLIT's UI to start exploring performance metrics. Visit the OpenLIT [Quickstart Guide](https://docs.openlit.io/latest/quickstart) for step-by-step details.
- **Integrate with existing Observability Tools:** If you use tools like Grafana or DataDog, you can integrate the data collected by OpenLIT. For instructions on setting up these connections, check the OpenLIT [Connections Guide](https://docs.openlit.io/latest/connections/intro).

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@@ -28,6 +28,27 @@ if TYPE_CHECKING:
EmbeddingsType = TypeVar('EmbeddingsType', bound='list[Any]')
# Find CUDA libraries from the official packages
cuda_found = False
if platform.system() in ('Linux', 'Windows'):
try:
from nvidia import cuda_runtime, cublas
except ImportError:
pass # CUDA is optional
else:
if platform.system() == 'Linux':
cudalib = 'lib/libcudart.so.12'
cublaslib = 'lib/libcublas.so.12'
else: # Windows
cudalib = r'bin\cudart64_12.dll'
cublaslib = r'bin\cublas64_12.dll'
# preload the CUDA libs so the backend can find them
ctypes.CDLL(os.path.join(cuda_runtime.__path__[0], cudalib), mode=ctypes.RTLD_GLOBAL)
ctypes.CDLL(os.path.join(cublas.__path__[0], cublaslib), mode=ctypes.RTLD_GLOBAL)
cuda_found = True
# TODO: provide a config file to make this more robust
MODEL_LIB_PATH = importlib_resources.files("gpt4all") / "llmodel_DO_NOT_MODIFY" / "build"
@@ -156,9 +177,6 @@ llmodel.llmodel_gpu_init_gpu_device_by_struct.restype = ctypes.c_bool
llmodel.llmodel_gpu_init_gpu_device_by_int.argtypes = [ctypes.c_void_p, ctypes.c_int32]
llmodel.llmodel_gpu_init_gpu_device_by_int.restype = ctypes.c_bool
llmodel.llmodel_has_gpu_device.argtypes = [ctypes.c_void_p]
llmodel.llmodel_has_gpu_device.restype = ctypes.c_bool
llmodel.llmodel_model_backend_name.argtypes = [ctypes.c_void_p]
llmodel.llmodel_model_backend_name.restype = ctypes.c_char_p
@@ -218,7 +236,16 @@ class LLModel:
model = llmodel.llmodel_model_create2(self.model_path, backend.encode(), ctypes.byref(err))
if model is None:
s = err.value
raise RuntimeError(f"Unable to instantiate model: {'null' if s is None else s.decode()}")
errmsg = 'null' if s is None else s.decode()
if (
backend == 'cuda'
and not cuda_found
and errmsg.startswith('Could not find any implementations for backend')
):
print('WARNING: CUDA runtime libraries not found. Try `pip install "gpt4all[cuda]"`\n', file=sys.stderr)
raise RuntimeError(f"Unable to instantiate model: {errmsg}")
self.model: ctypes.c_void_p | None = model
def __del__(self, llmodel=llmodel):
@@ -274,11 +301,12 @@ class LLModel:
all_gpus = self.list_gpus()
available_gpus = self.list_gpus(mem_required)
unavailable_gpus = set(all_gpus).difference(available_gpus)
unavailable_gpus = [g for g in all_gpus if g not in available_gpus]
error_msg = "Unable to initialize model on GPU: {!r}".format(device)
error_msg += "\nAvailable GPUs: {}".format(available_gpus)
error_msg += "\nUnavailable GPUs due to insufficient memory or features: {}".format(unavailable_gpus)
error_msg = (f"Unable to initialize model on GPU: {device!r}" +
f"\nAvailable GPUs: {available_gpus}")
if unavailable_gpus:
error_msg += f"\nUnavailable GPUs due to insufficient memory: {unavailable_gpus}"
raise ValueError(error_msg)
def load_model(self) -> bool:

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