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92 Commits

Author SHA1 Message Date
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
Jared Van Bortel
a92d266cea cmake: fix Metal build after #2310 (#2350)
I don't understand why this is needed, but it works.

Signed-off-by: Jared Van Bortel <jared@nomic.ai>
2024-05-15 18:12:32 -04:00
Jared Van Bortel
d2a99d9bc6 support the llama.cpp CUDA backend (#2310)
* rebase onto llama.cpp commit ggerganov/llama.cpp@d46dbc76f
* support for CUDA backend (enabled by default)
* partial support for Occam's Vulkan backend (disabled by default)
* partial support for HIP/ROCm backend (disabled by default)
* sync llama.cpp.cmake with upstream llama.cpp CMakeLists.txt
* changes to GPT4All backend, bindings, and chat UI to handle choice of llama.cpp backend (Kompute or CUDA)
* ship CUDA runtime with installed version
* make device selection in the UI on macOS actually do something
* model whitelist: remove dbrx, mamba, persimmon, plamo; add internlm and starcoder2

Signed-off-by: Jared Van Bortel <jared@nomic.ai>
2024-05-15 15:27:50 -04:00
Jared Van Bortel
a618ca5699 readme: document difference between installers (#2336)
Signed-off-by: Jared Van Bortel <jared@nomic.ai>
2024-05-15 14:10:10 -04:00
Jared Van Bortel
fbbf810020 chat: fix issues with the initial "New Chat" (#2330)
* select the existing new chat if there already is one when "New Chat" is clicked
* scroll to the new chat when "New Chat" is clicked
* fix the "New Chat" being scrolled past the top of the chat list

Signed-off-by: Jared Van Bortel <jared@nomic.ai>
2024-05-15 14:09:32 -04:00
Jared Van Bortel
7e1e00f331 chat: fix issues with quickly switching between multiple chats (#2343)
* prevent load progress from getting out of sync with the current chat
* fix memory leak on exit if the LLModelStore contains a model
* do not report cancellation as a failure in console/Mixpanel
* show "waiting for model" separately from "switching context" in UI
* do not show lower "reload" button on error
* skip context switch if unload is pending
* skip unnecessary calls to LLModel::saveState

Signed-off-by: Jared Van Bortel <jared@nomic.ai>
2024-05-15 14:07:03 -04:00
Jared Van Bortel
7f1c3d4275 chatllm: fix model loading progress showing "Reload" sometimes (#2337)
Signed-off-by: Jared Van Bortel <jared@nomic.ai>
2024-05-15 13:57:53 -04:00
Jared Van Bortel
9f9d8e636f backend: do not crash if GGUF lacks general.architecture (#2346)
Signed-off-by: Jared Van Bortel <jared@nomic.ai>
2024-05-15 13:57:13 -04:00
Jared Van Bortel
6d8888b267 llamamodel: free the batch in embedInternal (#2348)
Signed-off-by: Jared Van Bortel <jared@nomic.ai>
2024-05-15 12:46:12 -04:00
AT
61cefcfd8a Fix destruction and tear down of the embedding thread. (#2328)
* Fix destruction and tear down of the embedding thread.

Signed-off-by: Adam Treat <treat.adam@gmail.com>

* Fix order of deletion to prevent use after free.

Signed-off-by: Adam Treat <treat.adam@gmail.com>

---------

Signed-off-by: Adam Treat <treat.adam@gmail.com>
2024-05-15 10:01:53 -04:00
Jared Van Bortel
1427ef7195 chat: fix window icon on Windows (#2321)
* chat: fix window icon on Windows

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

* chat: remove redundant copy of macOS app icon

This has been redundant since PR #2180.

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

---------

Signed-off-by: Jared Van Bortel <jared@nomic.ai>
2024-05-09 13:42:46 -04:00
Tim453
69720fedaa Update appdata.xml (#2307) 2024-05-09 12:51:38 -04:00
Jared Van Bortel
86560f3952 maint: remove Docker API server and related references (#2314)
Signed-off-by: Jared Van Bortel <jared@nomic.ai>
2024-05-09 12:50:26 -04:00
Jared Van Bortel
5fb9d17c00 chatllm: use a better prompt for the generated chat name (#2322)
Signed-off-by: Jared Van Bortel <jared@nomic.ai>
2024-05-09 09:38:19 -04:00
Jared Van Bortel
f26e8d0d87 chat: do not allow sending a message while the LLM is responding (#2323)
Signed-off-by: Jared Van Bortel <jared@nomic.ai>
2024-05-09 09:37:36 -04:00
Jared Van Bortel
d54e644d05 ChatView: make context menus more intuitive (#2324)
* ChatView: fix deprecation warning

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

* ChatView: make context menus more intuitive

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

---------

Signed-off-by: Jared Van Bortel <jared@nomic.ai>
2024-05-09 09:35:54 -04:00
Jared Van Bortel
cef74c2be2 readme: cleanup and modernization (#2308)
Signed-off-by: Jared Van Bortel <jared@nomic.ai>
2024-05-06 13:29:37 -04:00
Jared Van Bortel
26eaf598b4 chat: add release notes for v2.7.5 and bump version (#2300)
Signed-off-by: Jared Van Bortel <jared@nomic.ai>
2024-05-03 09:54:09 -04:00
Andriy Mulyar
d7c47fb6f7 Update README.md (#2301)
Signed-off-by: Andriy Mulyar <andriy.mulyar@gmail.com>
2024-05-02 20:02:19 -04:00
Jared Van Bortel
577ebd4826 mixpanel: report cpu_supports_avx2 on startup (#2299)
Signed-off-by: Jared Van Bortel <jared@nomic.ai>
2024-05-02 16:09:41 -04:00
Jared Van Bortel
855fd22417 localdocs: load model before checking which model is loaded (#2284)
* localdocs: load model before checking what we loaded

Fixes "WARNING: Request to generate sync embeddings for non-local model
invalid"

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

* fix inverted assertion

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

---------

Signed-off-by: Jared Van Bortel <jared@nomic.ai>
2024-05-02 09:30:36 -04:00
Jared Van Bortel
adaecb7a72 mixpanel: improved GPU device statistics (plus GPU sort order fix) (#2297)
Signed-off-by: Jared Van Bortel <jared@nomic.ai>
2024-05-01 16:15:48 -04:00
Jared Van Bortel
27c561aeb7 mixpanel: fix opt-out events after #2238 (#2296)
Signed-off-by: Jared Van Bortel <jared@nomic.ai>
2024-05-01 12:08:40 -04:00
Noofbiz
1b87aa2dbc fixed bindings to match new API (#2240)
* fixed bindings to match new API

Signed-off-by: Jerry Caligiure <jerry@noof.biz>

* added update to readme

Signed-off-by: Jerry Caligiure <jerry@noof.biz>

---------

Signed-off-by: Jerry Caligiure <jerry@noof.biz>
Co-authored-by: Jerry Caligiure <jerry@noof.biz>
2024-04-29 08:49:26 -04:00
Jared Van Bortel
6f38fde80b mixpanel: fix doc_collections_total of localdocs_startup (#2270)
Signed-off-by: Jared Van Bortel <jared@nomic.ai>
2024-04-26 14:05:47 -04:00
Jared Van Bortel
a14193623a chat: add release notes for v2.7.4 and bump version (#2269)
Signed-off-by: Jared Van Bortel <jared@nomic.ai>
2024-04-26 12:55:54 -04:00
Jared Van Bortel
4f3c9bbe3e network: fix use of GNU asm statement with MSVC (#2267)
Signed-off-by: Jared Van Bortel <jared@nomic.ai>
2024-04-26 11:22:24 -04:00
Jared Van Bortel
c622921894 improve mixpanel usage statistics (#2238)
Other changes:
- Always display first start dialog if privacy options are unset (e.g. if the user closed GPT4All without selecting them)
- LocalDocs scanQueue is now always deferred
- Fix a potential crash in magic_match
- LocalDocs indexing is now started after the first start dialog is dismissed so usage stats are included

Signed-off-by: Jared Van Bortel <jared@nomic.ai>
2024-04-25 13:16:52 -04:00
Jared Van Bortel
4193533154 models.json: add Phi-3 Mini Instruct (#2252)
Signed-off-by: Jared Van Bortel <jared@nomic.ai>
2024-04-23 18:53:09 -04:00
Ikko Eltociear Ashimine
baf1dfc5d7 docs: update README.md (#2250)
minor fix

Signed-off-by: Ikko Eltociear Ashimine <eltociear@gmail.com>
2024-04-23 13:26:47 -04:00
Jared Van Bortel
0b78b79b1c models.json: add Llama 3 Instruct 8B (#2242)
Other changes:
* fix 'requires' for models with %2 in template
* move Ghost 7B to the appropriate location in the file based on where it actually appears in the UI

Signed-off-by: Jared Van Bortel <jared@nomic.ai>
2024-04-19 13:09:44 -04:00
Jared Van Bortel
aac00d019a chat: temporarily revert some UI changes before next release (#2234)
* chat: revert PR #2187

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

* chat: revert PR #2148

This reverts commit f571e7e450.

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

---------

Signed-off-by: Jared Van Bortel <jared@nomic.ai>
2024-04-18 14:52:29 -04:00
Jared Van Bortel
ba53ab5da0 python: do not print GPU name with verbose=False, expose this info via properties (#2222)
* llamamodel: only print device used in verbose mode

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

* python: expose backend and device via GPT4All properties

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

* backend: const correctness fixes

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

* python: bump version

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

* python: typing fixups

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

* python: fix segfault with closed GPT4All

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

---------

Signed-off-by: Jared Van Bortel <jared@nomic.ai>
2024-04-18 14:52:02 -04:00
Jared Van Bortel
271d752701 localdocs: small but important fixes to local docs (#2236)
* chat: use .rmodel extension for Nomic Embed

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

* database: fix order of SQL arguments in updateDocument

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

---------

Signed-off-by: Jared Van Bortel <jared@nomic.ai>
2024-04-18 14:51:13 -04:00
Jared Van Bortel
be93ee75de responsetext : fix markdown code block trimming (#2232)
Signed-off-by: Jared Van Bortel <jared@nomic.ai>
2024-04-18 14:50:32 -04:00
Andriy Mulyar
4ebb0c6ac0 Remove town hall announcement from readme (#2237)
Signed-off-by: Andriy Mulyar <andriy.mulyar@gmail.com>
2024-04-18 12:54:50 -04:00
Andriy Mulyar
2c4c101b2e Roadmap update (#2230)
* Roadmap update

Signed-off-by: Andriy Mulyar <andriy.mulyar@gmail.com>

* Spelling error

Signed-off-by: Andriy Mulyar <andriy.mulyar@gmail.com>

* Update README.md

Signed-off-by: Andriy Mulyar <andriy.mulyar@gmail.com>

* Update README.md

Signed-off-by: Andriy Mulyar <andriy.mulyar@gmail.com>

---------

Signed-off-by: Andriy Mulyar <andriy.mulyar@gmail.com>
2024-04-17 12:19:57 -04:00
Jared Van Bortel
38cc778a0c models.json: use simpler system prompt for Mistral OpenOrca (#2220)
Signed-off-by: Jared Van Bortel <jared@nomic.ai>
2024-04-15 18:02:51 -04:00
Adam Treat
94a9943782 Change the behavior of show references setting for localdocs.
Signed-off-by: Adam Treat <treat.adam@gmail.com>
2024-04-15 14:30:26 -05:00
Adam Treat
e27653219b Fix bugs with the context link text for localdocs to make the context links
persistently work across application loads and fix scrolling bug with context
links.

Signed-off-by: Adam Treat <treat.adam@gmail.com>
2024-04-15 14:30:26 -05:00
Jared Van Bortel
ac498f79ac fix regressions in system prompt handling (#2219)
* python: fix system prompt being ignored
* fix unintended whitespace after system prompt

Signed-off-by: Jared Van Bortel <jared@nomic.ai>
2024-04-15 11:39:48 -04:00
dependabot[bot]
2273cf145e build(deps): bump tar in /gpt4all-bindings/typescript
Bumps [tar](https://github.com/isaacs/node-tar) from 6.2.0 to 6.2.1.
- [Release notes](https://github.com/isaacs/node-tar/releases)
- [Changelog](https://github.com/isaacs/node-tar/blob/main/CHANGELOG.md)
- [Commits](https://github.com/isaacs/node-tar/compare/v6.2.0...v6.2.1)

---
updated-dependencies:
- dependency-name: tar
  dependency-type: indirect
...

Signed-off-by: dependabot[bot] <support@github.com>
2024-04-15 08:37:39 -05:00
248 changed files with 11916 additions and 15659 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: |
@@ -77,8 +77,90 @@ 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
@@ -97,7 +179,9 @@ jobs:
command: |
wget -qO- https://packages.lunarg.com/lunarg-signing-key-pub.asc | sudo tee /etc/apt/trusted.gpg.d/lunarg.asc
sudo wget -qO /etc/apt/sources.list.d/lunarg-vulkan-jammy.list http://packages.lunarg.com/vulkan/lunarg-vulkan-jammy.list
sudo apt update && sudo apt install -y libfontconfig1 libfreetype6 libx11-6 libx11-xcb1 libxext6 libxfixes3 libxi6 libxrender1 libxcb1 libxcb-cursor0 libxcb-glx0 libxcb-keysyms1 libxcb-image0 libxcb-shm0 libxcb-icccm4 libxcb-sync1 libxcb-xfixes0 libxcb-shape0 libxcb-randr0 libxcb-render-util0 libxcb-util1 libxcb-xinerama0 libxcb-xkb1 libxkbcommon0 libxkbcommon-x11-0 bison build-essential flex gperf python3 gcc g++ libgl1-mesa-dev libwayland-dev vulkan-sdk patchelf
wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64/cuda-keyring_1.1-1_all.deb
sudo dpkg -i cuda-keyring_1.1-1_all.deb
sudo apt update && sudo apt install -y libfontconfig1 libfreetype6 libx11-6 libx11-xcb1 libxext6 libxfixes3 libxi6 libxrender1 libxcb1 libxcb-cursor0 libxcb-glx0 libxcb-keysyms1 libxcb-image0 libxcb-shm0 libxcb-icccm4 libxcb-sync1 libxcb-xfixes0 libxcb-shape0 libxcb-randr0 libxcb-render-util0 libxcb-util1 libxcb-xinerama0 libxcb-xkb1 libxkbcommon0 libxkbcommon-x11-0 bison build-essential flex gperf python3 gcc g++ libgl1-mesa-dev libwayland-dev vulkan-sdk patchelf cuda-compiler-12-4 libcublas-dev-12-4 libnvidia-compute-550-server libmysqlclient21 libodbc2 libpq5
- run:
name: Installing Qt
command: |
@@ -121,6 +205,7 @@ jobs:
set -eo pipefail
export CMAKE_PREFIX_PATH=~/Qt/6.5.1/gcc_64/lib/cmake
export PATH=$PATH:$HOME/Qt/Tools/QtInstallerFramework/4.7/bin
export PATH=$PATH:/usr/local/cuda/bin
mkdir build
cd build
mkdir upload
@@ -162,6 +247,11 @@ jobs:
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: Build
command: |
@@ -218,7 +308,9 @@ jobs:
command: |
wget -qO- https://packages.lunarg.com/lunarg-signing-key-pub.asc | sudo tee /etc/apt/trusted.gpg.d/lunarg.asc
sudo wget -qO /etc/apt/sources.list.d/lunarg-vulkan-jammy.list http://packages.lunarg.com/vulkan/lunarg-vulkan-jammy.list
sudo apt update && sudo apt install -y libfontconfig1 libfreetype6 libx11-6 libx11-xcb1 libxext6 libxfixes3 libxi6 libxrender1 libxcb1 libxcb-cursor0 libxcb-glx0 libxcb-keysyms1 libxcb-image0 libxcb-shm0 libxcb-icccm4 libxcb-sync1 libxcb-xfixes0 libxcb-shape0 libxcb-randr0 libxcb-render-util0 libxcb-util1 libxcb-xinerama0 libxcb-xkb1 libxkbcommon0 libxkbcommon-x11-0 bison build-essential flex gperf python3 gcc g++ libgl1-mesa-dev libwayland-dev vulkan-sdk
wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64/cuda-keyring_1.1-1_all.deb
sudo dpkg -i cuda-keyring_1.1-1_all.deb
sudo apt update && sudo apt install -y libfontconfig1 libfreetype6 libx11-6 libx11-xcb1 libxext6 libxfixes3 libxi6 libxrender1 libxcb1 libxcb-cursor0 libxcb-glx0 libxcb-keysyms1 libxcb-image0 libxcb-shm0 libxcb-icccm4 libxcb-sync1 libxcb-xfixes0 libxcb-shape0 libxcb-randr0 libxcb-render-util0 libxcb-util1 libxcb-xinerama0 libxcb-xkb1 libxkbcommon0 libxkbcommon-x11-0 bison build-essential flex gperf python3 gcc g++ libgl1-mesa-dev libwayland-dev vulkan-sdk cuda-compiler-12-4 libcublas-dev-12-4 libnvidia-compute-550-server libmysqlclient21 libodbc2 libpq5
- run:
name: Installing Qt
command: |
@@ -235,6 +327,7 @@ jobs:
name: Build
command: |
export CMAKE_PREFIX_PATH=~/Qt/6.5.1/gcc_64/lib/cmake
export PATH=$PATH:/usr/local/cuda/bin
~/Qt/Tools/CMake/bin/cmake -DCMAKE_BUILD_TYPE=Release -S gpt4all-chat -B build
~/Qt/Tools/CMake/bin/cmake --build build --target all
@@ -269,6 +362,11 @@ jobs:
command: |
Invoke-WebRequest -Uri https://sdk.lunarg.com/sdk/download/1.3.261.1/windows/VulkanSDK-1.3.261.1-Installer.exe -OutFile VulkanSDK-1.3.261.1-Installer.exe
.\VulkanSDK-1.3.261.1-Installer.exe --accept-licenses --default-answer --confirm-command install
- run:
name: Install CUDA Toolkit
command: |
Invoke-WebRequest -Uri https://developer.download.nvidia.com/compute/cuda/12.4.1/network_installers/cuda_12.4.1_windows_network.exe -OutFile cuda_12.4.1_windows_network.exe
.\cuda_12.4.1_windows_network.exe -s cudart_12.4 nvcc_12.4 cublas_12.4 cublas_dev_12.4
- run:
name: Build
command: |
@@ -312,6 +410,9 @@ jobs:
- restore_cache: # this is the new step to restore cache
keys:
- macos-qt-cache-v3
- run:
name: Install Rosetta
command: softwareupdate --install-rosetta --agree-to-license # needed for QtIFW
- run:
name: Installing Qt
command: |
@@ -394,15 +495,18 @@ jobs:
command: |
wget -qO- https://packages.lunarg.com/lunarg-signing-key-pub.asc | sudo tee /etc/apt/trusted.gpg.d/lunarg.asc
sudo wget -qO /etc/apt/sources.list.d/lunarg-vulkan-jammy.list http://packages.lunarg.com/vulkan/lunarg-vulkan-jammy.list
wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64/cuda-keyring_1.1-1_all.deb
sudo dpkg -i cuda-keyring_1.1-1_all.deb
sudo apt-get update
sudo apt-get install -y cmake build-essential vulkan-sdk
sudo apt-get install -y cmake build-essential vulkan-sdk cuda-compiler-12-4 libcublas-dev-12-4 libnvidia-compute-550-server libmysqlclient21 libodbc2 libpq5
pip install setuptools wheel cmake
- run:
name: Build C library
command: |
export PATH=$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
@@ -432,7 +536,7 @@ 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
@@ -447,46 +551,64 @@ 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: |
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'
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"
$Env:VULKAN_SDK = "C:\VulkanSDK\1.3.261.1"
cmake -G "MinGW Makefiles" -B build -DKOMPUTE_OPT_DISABLE_VULKAN_VERSION_CHECK=ON -DKOMPUTE_OPT_USE_BUILT_IN_VULKAN_HEADER=OFF
cd gpt4all-backend
cmake -G Ninja -B build -DCMAKE_BUILD_TYPE=Release -DKOMPUTE_OPT_DISABLE_VULKAN_VERSION_CHECK=ON
cmake --build build --parallel
- run:
name: Build wheel
# TODO: As part of this task, we need to move mingw64 binaries into package.
# This is terrible and needs a more robust solution eventually.
command: |
cd gpt4all-bindings/python
cd gpt4all
mkdir llmodel_DO_NOT_MODIFY
mkdir llmodel_DO_NOT_MODIFY/build/
cp 'C:\ProgramData\mingw64\mingw64\bin\*dll' 'llmodel_DO_NOT_MODIFY/build/'
cd ..
python setup.py bdist_wheel --plat-name=win_amd64
- store_artifacts:
path: gpt4all-bindings/python/dist
@@ -530,11 +652,14 @@ jobs:
command: |
wget -qO- https://packages.lunarg.com/lunarg-signing-key-pub.asc | sudo tee /etc/apt/trusted.gpg.d/lunarg.asc
sudo wget -qO /etc/apt/sources.list.d/lunarg-vulkan-jammy.list http://packages.lunarg.com/vulkan/lunarg-vulkan-jammy.list
wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64/cuda-keyring_1.1-1_all.deb
sudo dpkg -i cuda-keyring_1.1-1_all.deb
sudo apt-get update
sudo apt-get install -y cmake build-essential vulkan-sdk
sudo apt-get install -y cmake build-essential vulkan-sdk cuda-compiler-12-4 libcublas-dev-12-4 libnvidia-compute-550-server libmysqlclient21 libodbc2 libpq5
- run:
name: Build Libraries
command: |
export PATH=$PATH:/usr/local/cuda/bin
cd gpt4all-backend
mkdir -p runtimes/build
cd runtimes/build
@@ -580,52 +705,6 @@ 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 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
@@ -642,6 +721,11 @@ jobs:
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: |
@@ -663,182 +747,6 @@ 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
@@ -1022,6 +930,12 @@ 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
@@ -1103,13 +1017,10 @@ 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:
@@ -1134,12 +1045,6 @@ workflows:
only:
requires:
- hold
- build-bindings-backend-windows-msvc:
filters:
branches:
only:
requires:
- hold
# NodeJs Jobs
- prepare-npm-pkg:
@@ -1164,7 +1069,7 @@ workflows:
only:
requires:
- nodejs-hold
- build-bindings-backend-windows-msvc
- build-bindings-backend-windows
- build-nodejs-macos:
filters:
branches:
@@ -1172,36 +1077,3 @@ 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

@@ -1,30 +0,0 @@
Software for Open Models License (SOM)
Version 1.0 dated August 30th, 2023
This license governs use of the accompanying Software. If you use the Software, you accept this license. If you do not accept the license, do not use the Software.
This license is intended to encourage open release of models created, modified, processed, or otherwise used via the Software under open licensing terms, and should be interpreted in light of that intent.
1. Definitions
The “Licensor” is the person or entity who is making the Software available under this license. “Software” is the software made available by Licensor under this license.
A “Model” is the output of a machine learning algorithm, and excludes the Software.
“Model Source Materials” must include the Model and model weights, and may include any input data, input data descriptions, documentation or training descriptions for the Model.
“Open Licensing Terms” means: (a) any open source license approved by the Open Source Initiative, or (b) any other terms that make the Model Source Materials publicly available free of charge, and allow recipients to use, modify and distribute the Model Source Materials. Terms described in (b) may include reasonable restrictions such as non-commercial or non-production limitations, or require use in compliance with law.
2. Grant of Rights. Subject to the conditions and limitations in section 3:
(A) Copyright Grant. Licensor grants you a non-exclusive, worldwide, royalty-free copyright license to copy, modify, and distribute the Software and any modifications of the Software you create under this license. The foregoing license includes without limitation the right to create, modify, and use Models using this Software.
(B) Patent Grant. Licensor grants you a non-exclusive, worldwide, royalty-free license, under any patents owned or controlled by Licensor, to make, have made, use, sell, offer for sale, import, or otherwise exploit the Software. No license is granted to patent rights that are not embodied in the operation of the Software in the form provided by Licensor.
3. Conditions and Limitations
(A) Model Licensing and Access. If you use the Software to create, modify, process, or otherwise use any Model, including usage to create inferences with a Model, whether or not you make the Model available to others, you must make that Model Source Materials publicly available under Open Licensing Terms.
(B) No Re-Licensing. If you redistribute the Software, or modifications to the Software made under the license granted above, you must make it available only under the terms of this license. You may offer additional terms such as warranties, maintenance and support, but You, and not Licensor, are responsible for performing such terms.
(C) No Trademark License. This license does not grant you rights to use the Licensors name, logo, or trademarks.
(D) If you assert in writing a claim against any person or entity alleging that the use of the Software infringes any patent, all of your licenses to the Software under Section 2 end automatically as of the date you asserted the claim.
(E) If you distribute any portion of the Software, you must retain all copyright, patent, trademark, and attribution notices that are present in the Software, and you must include a copy of this license.
(F) The Software is licensed “as-is.” You bear the entire risk of using it. Licensor gives You no express warranties, guarantees or conditions. You may have additional consumer rights under your local laws that this license cannot change. To the extent permitted under your local laws, the Licensor disclaims and excludes the implied warranties of merchantability, fitness for a particular purpose and non-infringement. To the extent this disclaimer is unlawful, you, and not Licensor, are responsible for any liability.

130
README.md
View File

@@ -1,82 +1,74 @@
<h1 align="center">GPT4All</h1>
<p align="center">Open-source large language models that run locally on your CPU and nearly any GPU</p>
<p align="center">Privacy-oriented software for chatting with large language models that run on your own computer.</p>
<p align="center">
Join the <a href="https://discord.gg/tyc74KNVK3?event=1227642051294658621">GPT4All 2024 Roadmap Townhall</a> on April 18, 2024 at 12pm EST
<a href="https://gpt4all.io">Official Website</a> &bull; <a href="https://docs.gpt4all.io">Documentation</a> &bull; <a href="https://discord.gg/mGZE39AS3e">Discord</a>
</p>
<p align="center">
<a href="https://gpt4all.io">GPT4All Website and Models</a> • <a href="https://docs.gpt4all.io">GPT4All Documentation</a> • <a href="https://discord.gg/mGZE39AS3e">Discord</a>
Official Download Links: <a href="https://gpt4all.io/installers/gpt4all-installer-win64.exe">Windows</a> &mdash; <a href="https://gpt4all.io/installers/gpt4all-installer-darwin.dmg">macOS</a> &mdash; <a href="https://gpt4all.io/installers/gpt4all-installer-linux.run">Ubuntu</a>
</p>
<p align="center">
<a href="https://python.langchain.com/en/latest/modules/models/llms/integrations/gpt4all.html">🦜️🔗 Official Langchain Backend</a>
<b>NEW:</b> <a href="https://forms.nomic.ai/gpt4all-release-notes-signup">Subscribe to our mailing list</a> for updates and news!
</p>
<p align="center">
GPT4All is made possible by our compute partner <a href="https://www.paperspace.com/">Paperspace</a>.
</p>
<p align="center">
<a href="https://www.phorm.ai/query?projectId=755eecd3-24ad-49cc-abf4-0ab84caacf63"><img src="https://img.shields.io/badge/Phorm-Ask_AI-%23F2777A.svg?&logo=data:image/svg+xml;base64,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" alt="phorm.ai"></a>
<a href="https://www.phorm.ai/query?projectId=755eecd3-24ad-49cc-abf4-0ab84caacf63"><img src="https://img.shields.io/badge/Phorm-Ask_AI-%23F2777A.svg" alt="phorm.ai"></a>
</p>
<p align="center">
<img width="600" height="365" src="https://user-images.githubusercontent.com/13879686/231876409-e3de1934-93bb-4b4b-9013-b491a969ebbc.gif">
<img width="auto" height="400" src="https://github.com/nomic-ai/gpt4all/assets/14168726/495fce3e-769b-4e5a-a394-99f072ac4d29">
</p>
<p align="center">
Run on an M1 macOS Device (not sped up!)
Run on an M2 MacBook Pro (not sped up!)
</p>
## GPT4All: An ecosystem of open-source on-edge large language models.
GPT4All is an ecosystem to run **powerful** and **customized** large language models that work locally on consumer grade CPUs and any GPU. Note that your CPU needs to support [AVX or AVX2 instructions](https://en.wikipedia.org/wiki/Advanced_Vector_Extensions).
## About GPT4All
GPT4All is an ecosystem to run **powerful** and **customized** large language models that work locally on consumer grade CPUs and NVIDIA and AMD GPUs. Note that your CPU needs to support [AVX instructions](https://en.wikipedia.org/wiki/Advanced_Vector_Extensions).
Learn more in the [documentation](https://docs.gpt4all.io).
A GPT4All model is a 3GB - 8GB file that you can download and plug into the GPT4All open-source ecosystem software. **Nomic AI** supports and maintains this software ecosystem to enforce quality and security alongside spearheading the effort to allow any person or enterprise to easily train and deploy their own on-edge large language models.
A GPT4All model is a 3GB - 8GB file that you can download and plug into the GPT4All software. **Nomic AI** supports and maintains this software ecosystem to enforce quality and security alongside spearheading the effort to allow any person or enterprise to easily deploy their own on-edge large language models.
### What's New ([Issue Tracker](https://github.com/orgs/nomic-ai/projects/2))
### Installation
The recommended way to install GPT4All is to use one of the online installers linked above in this README, which are also available at the [GPT4All website](https://gpt4all.io/). These require an internet connection at install time, are slightly easier to use on macOS due to code signing, and provide a version of GPT4All that can check for updates.
An alternative way to install GPT4All is to use one of the offline installers available on the [Releases page](https://github.com/nomic-ai/gpt4all/releases). These do not require an internet connection at install time, and can be used to install an older version of GPT4All if so desired. But using these requires acknowledging a security warning on macOS, and they provide a version of GPT4All that is unable to notify you of updates, so you should enable notifications for Releases on this repository (Watch > Custom > Releases) or sign up for announcements in our [Discord server](https://discord.gg/mGZE39AS3e).
### What's New
- **October 19th, 2023**: GGUF Support Launches with Support for:
- Mistral 7b base model, an updated model gallery on [gpt4all.io](https://gpt4all.io), several new local code models including Rift Coder v1.5
- [Nomic Vulkan](https://blog.nomic.ai/posts/gpt4all-gpu-inference-with-vulkan) support for Q4\_0 and Q4\_1 quantizations in GGUF.
- Offline build support for running old versions of the GPT4All Local LLM Chat Client.
- **September 18th, 2023**: [Nomic Vulkan](https://blog.nomic.ai/posts/gpt4all-gpu-inference-with-vulkan) launches supporting local LLM inference on AMD, Intel, Samsung, Qualcomm and NVIDIA GPUs.
- **August 15th, 2023**: GPT4All API launches allowing inference of local LLMs from docker containers.
- **July 2023**: Stable support for LocalDocs, a GPT4All Plugin that allows you to privately and locally chat with your data.
- **September 18th, 2023**: [Nomic Vulkan](https://blog.nomic.ai/posts/gpt4all-gpu-inference-with-vulkan) launches supporting local LLM inference on NVIDIA and AMD GPUs.
- **July 2023**: Stable support for LocalDocs, a feature that allows you to privately and locally chat with your data.
- **June 28th, 2023**: [Docker-based API server] launches allowing inference of local LLMs from an OpenAI-compatible HTTP endpoint.
[Docker-based API server]: https://github.com/nomic-ai/gpt4all/tree/cef74c2be20f5b697055d5b8b506861c7b997fab/gpt4all-api
### Chat Client
Run any GPT4All model natively on your home desktop with the auto-updating desktop chat client. See <a href="https://gpt4all.io">GPT4All Website</a> for a full list of open-source models you can run with this powerful desktop application.
### Building From Source
Direct Installer Links:
* Follow the instructions [here](gpt4all-chat/build_and_run.md) to build the GPT4All Chat UI from source.
* [macOS](https://gpt4all.io/installers/gpt4all-installer-darwin.dmg)
* [Windows](https://gpt4all.io/installers/gpt4all-installer-win64.exe)
* [Ubuntu](https://gpt4all.io/installers/gpt4all-installer-linux.run)
Find the most up-to-date information on the [GPT4All Website](https://gpt4all.io/)
### Chat Client building and running
* Follow the visual instructions on the chat client [build_and_run](gpt4all-chat/build_and_run.md) page
### Bindings
* <a href="https://github.com/nomic-ai/gpt4all/tree/main/gpt4all-bindings/python/README.md">:snake: Official Python Bindings</a> [![Downloads](https://static.pepy.tech/badge/gpt4all/week)](https://pepy.tech/project/gpt4all)
* <a href="https://github.com/nomic-ai/gpt4all/tree/main/gpt4all-bindings/typescript">:computer: Official Typescript Bindings</a>
* <a href="https://github.com/nomic-ai/gpt4all/tree/main/gpt4all-bindings/golang">:computer: Official GoLang Bindings</a>
* <a href="https://github.com/nomic-ai/gpt4all/tree/main/gpt4all-bindings/csharp">:computer: Official C# Bindings</a>
* <a href="https://github.com/nomic-ai/gpt4all/tree/main/gpt4all-bindings/java">:computer: Official Java Bindings</a>
* :snake: <a href="https://github.com/nomic-ai/gpt4all/tree/main/gpt4all-bindings/python">Official Python Bindings</a> [![Downloads](https://static.pepy.tech/badge/gpt4all/week)](https://pepy.tech/project/gpt4all)
* :computer: <a href="https://github.com/nomic-ai/gpt4all/tree/main/gpt4all-bindings/typescript">Typescript Bindings</a>
### Integrations
* 🗃️ [Weaviate Vector Database](https://github.com/weaviate/weaviate) - [module docs](https://weaviate.io/developers/weaviate/modules/retriever-vectorizer-modules/text2vec-gpt4all)
* :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
GPT4All welcomes contributions, involvement, and discussion from the open source community!
@@ -86,6 +78,59 @@ Check project discord, with project owners, or through existing issues/PRs to av
Please make sure to tag all of the above with relevant project identifiers or your contribution could potentially get lost.
Example tags: `backend`, `bindings`, `python-bindings`, `documentation`, etc.
## GPT4All 2024 Roadmap
To contribute to the development of any of the below roadmap items, make or find the corresponding issue and cross-reference the [in-progress task](https://github.com/orgs/nomic-ai/projects/2/views/1).
Each item should have an issue link below.
- Chat UI Language Localization (localize UI into the native languages of users)
- [ ] Chinese
- [ ] German
- [ ] French
- [ ] Portuguese
- [ ] Your native language here.
- UI Redesign: an internal effort at Nomic to improve the UI/UX of gpt4all for all users.
- [ ] Design new user interface and gather community feedback
- [ ] Implement the new user interface and experience.
- Installer and Update Improvements
- [ ] Seamless native installation and update process on OSX
- [ ] Seamless native installation and update process on Windows
- [ ] Seamless native installation and update process on Linux
- Model discoverability improvements:
- [x] Support huggingface model discoverability
- [ ] Support Nomic hosted model discoverability
- LocalDocs (towards a local perplexity)
- Multilingual LocalDocs Support
- [ ] Create a multilingual experience
- [ ] Incorporate a multilingual embedding model
- [ ] Specify a preferred multilingual LLM for localdocs
- Improved RAG techniques
- [ ] Query augmentation and re-writing
- [ ] Improved chunking and text extraction from arbitrary modalities
- [ ] Custom PDF extractor past the QT default (charts, tables, text)
- [ ] Faster indexing and local exact search with v1.5 hamming embeddings and reranking (skip ANN index construction!)
- Support queries like 'summarize X document'
- Multimodal LocalDocs support with Nomic Embed
- Nomic Dataset Integration with real-time LocalDocs
- [ ] Include an option to allow the export of private LocalDocs collections to Nomic Atlas for debugging data/chat quality
- [ ] Allow optional sharing of LocalDocs collections between users.
- [ ] Allow the import of a LocalDocs collection from an Atlas Datasets
- Chat with live version of Wikipedia, Chat with Pubmed, chat with the latest snapshot of world news.
- First class Multilingual LLM Support
- [ ] Recommend and set a default LLM for German
- [ ] Recommend and set a default LLM for English
- [ ] Recommend and set a default LLM for Chinese
- [ ] Recommend and set a default LLM for Spanish
- Server Mode improvements
- Improved UI and new requested features:
- [ ] Fix outstanding bugs and feature requests around networking configurations.
- [ ] Support Nomic Embed inferencing
- [ ] First class documentation
- [ ] Improving developer use and quality of server mode (e.g. support larger batches)
## Technical Reports
<p align="center">
@@ -100,6 +145,7 @@ Example tags: `backend`, `bindings`, `python-bindings`, `documentation`, etc.
<a href="https://s3.amazonaws.com/static.nomic.ai/gpt4all/2023_GPT4All_Technical_Report.pdf">:green_book: Technical Report 1: GPT4All</a>
</p>
## Citation
If you utilize this repository, models or data in a downstream project, please consider citing it with:

112
gpt4all-api/.gitignore vendored
View File

@@ -1,112 +0,0 @@
# Byte-compiled / optimized / DLL files
__pycache__/
app/__pycache__/
gpt4all_api/__pycache__/
gpt4all_api/app/api_v1/__pycache__/
*.py[cod]
*$py.class
# C extensions
*.so
# VS Code
.vscode/
# Distribution / packaging
.Python
build/
develop-eggs/
dist/
downloads/
eggs/
.eggs/
lib64/
parts/
sdist/
var/
wheels/
*.egg-info/
.installed.cfg
*.egg
MANIFEST
# PyInstaller
# Usually these files are written by a python script from a template
# before PyInstaller builds the exe, so as to inject date/other infos into it.
*.manifest
*.spec
# Installer logs
pip-log.txt
pip-delete-this-directory.txt
# Unit test / coverage reports
htmlcov/
.tox/
.coverage
.coverage.*
.cache
nosetests.xml
coverage.xml
*.cover
.hypothesis/
.pytest_cache/
# Translations
*.mo
*.pot
# Django stuff:
*.log
local_settings.py
db.sqlite3
# Flask stuff:
instance/
.webassets-cache
# Scrapy stuff:
.scrapy
# Sphinx documentation
docs/_build/
# PyBuilder
target/
# Jupyter Notebook
.ipynb_checkpoints
# pyenv
.python-version
# celery beat schedule file
celerybeat-schedule
# SageMath parsed files
*.sage.py
# Environments
.env
.venv
env/
venv/
ENV/
env.bak/
venv.bak/
# Spyder project settings
.spyderproject
.spyproject
# Rope project settings
.ropeproject
# mkdocs documentation
/site
# mypy
.mypy_cache/
*.lock
*.cache

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@@ -1,7 +0,0 @@
[settings]
known_third_party=geopy,nltk,np,numpy,pandas,pysbd,fire,torch
line_length=120
include_trailing_comma=True
multi_line_output=3
use_parentheses=True

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@@ -1,13 +0,0 @@
Copyright 2023 Nomic, Inc.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.

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@@ -1,90 +0,0 @@
# GPT4All REST API
NOTICE: We are considering to deprecate this API as it has become challenging to maintain and test. If you have any interest in maintaining this or would like to takeover and adopt or discuss the future of this API please speak up in the discord channel.
This directory contains the source code to run and build docker images that run a FastAPI app
for serving inference from GPT4All models. The API matches the OpenAI API spec.
## Tutorial
The following tutorial assumes that you have checked out this repo and cd'd into it.
### Starting the app
First change your working directory to `gpt4all/gpt4all-api`.
Now you can build the FastAPI docker image. You only have to do this on initial build or when you add new dependencies to the requirements.txt file:
```bash
DOCKER_BUILDKIT=1 docker build -t gpt4all_api --progress plain -f gpt4all_api/Dockerfile.buildkit .
```
Then, start the backend with:
```bash
docker compose up --build
```
This will run both the API and locally hosted GPU inference server. If you want to run the API without the GPU inference server, you can run:
```bash
docker compose up --build gpt4all_api
```
To run the API with the GPU inference server, you will need to include environment variables (like the `MODEL_ID`). Edit the `.env` file and run
```bash
docker compose --env-file .env up --build
```
#### Spinning up your app
Run `docker compose up` to spin up the backend. Monitor the logs for errors in-case you forgot to set an environment variable above.
#### Development
Run
```bash
docker compose up --build
```
and edit files in the `app` directory. The api will hot-reload on changes.
You can run the unit tests with
```bash
make test
```
#### Viewing API documentation
Once the FastAPI ap is started you can access its documentation and test the search endpoint by going to:
```
localhost:80/docs
```
This documentation should match the OpenAI OpenAPI spec located at https://github.com/openai/openai-openapi/blob/master/openapi.yaml
#### Running inference
```python
import openai
openai.api_base = "http://localhost:4891/v1"
openai.api_key = "not needed for a local LLM"
def test_completion():
model = "gpt4all-j-v1.3-groovy"
prompt = "Who is Michael Jordan?"
response = openai.Completion.create(
model=model,
prompt=prompt,
max_tokens=50,
temperature=0.28,
top_p=0.95,
n=1,
echo=True,
stream=False
)
assert len(response['choices'][0]['text']) > len(prompt)
print(response)
```

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@@ -1,24 +0,0 @@
version: "3.8"
services:
gpt4all_gpu:
image: ghcr.io/huggingface/text-generation-inference:0.9.3
container_name: gpt4all_gpu
restart: always #restart on error (usually code compilation from save during bad state)
environment:
- HUGGING_FACE_HUB_TOKEN=token
- USE_FLASH_ATTENTION=false
- MODEL_ID=''
- NUM_SHARD=1
command: --model-id $MODEL_ID --num-shard $NUM_SHARD
volumes:
- ./:/data
ports:
- "8080:80"
shm_size: 1g
deploy:
resources:
reservations:
devices:
- driver: nvidia
capabilities: [gpu]

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@@ -1,22 +0,0 @@
version: "3.8"
services:
gpt4all_api:
image: gpt4all_api
container_name: gpt4all_api
restart: always #restart on error (usually code compilation from save during bad state)
ports:
- "4891:4891"
env_file:
- .env
environment:
- APP_ENVIRONMENT=dev
- WEB_CONCURRENCY=2
- LOGLEVEL=debug
- PORT=4891
- model=${MODEL_BIN} # using variable from .env file
- inference_mode=cpu
volumes:
- './gpt4all_api/app:/app'
- './gpt4all_api/models:/models' # models are mounted in the container
command: ["/start-reload.sh"]

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@@ -1,17 +0,0 @@
# syntax=docker/dockerfile:1.0.0-experimental
FROM tiangolo/uvicorn-gunicorn:python3.11
# Put first so anytime this file changes other cached layers are invalidated.
COPY gpt4all_api/requirements.txt /requirements.txt
RUN pip install --upgrade pip
# Run various pip install commands with ssh keys from host machine.
RUN --mount=type=ssh pip install -r /requirements.txt && \
rm -Rf /root/.cache && rm -Rf /tmp/pip-install*
# Finally, copy app and client.
COPY gpt4all_api/app /app
RUN mkdir -p /models

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@@ -1 +0,0 @@
# FastAPI app for serving GPT4All models

View File

@@ -1,9 +0,0 @@
from api_v1.routes import chat, completions, engines, health
from fastapi import APIRouter
router = APIRouter()
router.include_router(chat.router)
router.include_router(completions.router)
router.include_router(engines.router)
router.include_router(health.router)

View File

@@ -1,29 +0,0 @@
import logging
from api_v1.settings import settings
from fastapi import HTTPException
from fastapi.responses import JSONResponse
from starlette.requests import Request
log = logging.getLogger(__name__)
startup_msg_fmt = """
Starting up GPT4All API
"""
async def on_http_error(request: Request, exc: HTTPException):
return JSONResponse({'detail': exc.detail}, status_code=exc.status_code)
async def on_startup(app):
startup_msg = startup_msg_fmt.format(settings=settings)
log.info(startup_msg)
def startup_event_handler(app):
async def start_app() -> None:
await on_startup(app)
return start_app

View File

@@ -1,103 +0,0 @@
import logging
import time
from typing import List
from uuid import uuid4
from fastapi import APIRouter, HTTPException
from gpt4all import GPT4All
from pydantic import BaseModel, Field
from api_v1.settings import settings
from fastapi.responses import StreamingResponse
logger = logging.getLogger(__name__)
logger.setLevel(logging.DEBUG)
### This should follow https://github.com/openai/openai-openapi/blob/master/openapi.yaml
class ChatCompletionMessage(BaseModel):
role: str
content: str
class ChatCompletionRequest(BaseModel):
model: str = Field(settings.model, description='The model to generate a completion from.')
messages: List[ChatCompletionMessage] = Field(..., description='Messages for the chat completion.')
temperature: float = Field(settings.temp, description='Model temperature')
class ChatCompletionChoice(BaseModel):
message: ChatCompletionMessage
index: int
logprobs: float
finish_reason: str
class ChatCompletionUsage(BaseModel):
prompt_tokens: int
completion_tokens: int
total_tokens: int
class ChatCompletionResponse(BaseModel):
id: str
object: str = 'text_completion'
created: int
model: str
choices: List[ChatCompletionChoice]
usage: ChatCompletionUsage
router = APIRouter(prefix="/chat", tags=["Completions Endpoints"])
@router.post("/completions", response_model=ChatCompletionResponse)
async def chat_completion(request: ChatCompletionRequest):
'''
Completes a GPT4All model response based on the last message in the chat.
'''
# GPU is not implemented yet
if settings.inference_mode == "gpu":
raise HTTPException(status_code=400,
detail=f"Not implemented yet: Can only infer in CPU mode.")
# we only support the configured model
if request.model != settings.model:
raise HTTPException(status_code=400,
detail=f"The GPT4All inference server is booted to only infer: `{settings.model}`")
# run only of we have a message
if request.messages:
model = GPT4All(model_name=settings.model, model_path=settings.gpt4all_path)
# format system message and conversation history correctly
formatted_messages = ""
for message in request.messages:
formatted_messages += f"<|im_start|>{message.role}\n{message.content}<|im_end|>\n"
# the LLM will complete the response of the assistant
formatted_messages += "<|im_start|>assistant\n"
response = model.generate(
prompt=formatted_messages,
temp=request.temperature
)
# the LLM may continue to hallucinate the conversation, but we want only the first response
# so, cut off everything after first <|im_end|>
index = response.find("<|im_end|>")
response_content = response[:index].strip()
else:
response_content = "No messages received."
# Create a chat message for the response
response_message = ChatCompletionMessage(role="assistant", content=response_content)
# Create a choice object with the response message
response_choice = ChatCompletionChoice(
message=response_message,
index=0,
logprobs=-1.0, # Placeholder value
finish_reason="length" # Placeholder value
)
# Create the response object
chat_response = ChatCompletionResponse(
id=str(uuid4()),
created=int(time.time()),
model=request.model,
choices=[response_choice],
usage=ChatCompletionUsage(prompt_tokens=0, completion_tokens=0, total_tokens=0), # Placeholder values
)
return chat_response

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@@ -1,215 +0,0 @@
import json
from typing import List, Dict, Iterable, AsyncIterable
import logging
import time
from typing import Dict, List, Union, Optional
from uuid import uuid4
import aiohttp
import asyncio
from api_v1.settings import settings
from fastapi import APIRouter, Depends, Response, Security, status, HTTPException
from fastapi.responses import StreamingResponse
from gpt4all import GPT4All
from pydantic import BaseModel, Field
logger = logging.getLogger(__name__)
logger.setLevel(logging.DEBUG)
### This should follow https://github.com/openai/openai-openapi/blob/master/openapi.yaml
class CompletionRequest(BaseModel):
model: str = Field(settings.model, description='The model to generate a completion from.')
prompt: Union[List[str], str] = Field(..., description='The prompt to begin completing from.')
max_tokens: int = Field(None, description='Max tokens to generate')
temperature: float = Field(settings.temp, description='Model temperature')
top_p: Optional[float] = Field(settings.top_p, description='top_p')
top_k: Optional[int] = Field(settings.top_k, description='top_k')
n: int = Field(1, description='How many completions to generate for each prompt')
stream: bool = Field(False, description='Stream responses')
repeat_penalty: float = Field(settings.repeat_penalty, description='Repeat penalty')
class CompletionChoice(BaseModel):
text: str
index: int
logprobs: float
finish_reason: str
class CompletionUsage(BaseModel):
prompt_tokens: int
completion_tokens: int
total_tokens: int
class CompletionResponse(BaseModel):
id: str
object: str = 'text_completion'
created: int
model: str
choices: List[CompletionChoice]
usage: CompletionUsage
class CompletionStreamResponse(BaseModel):
id: str
object: str = 'text_completion'
created: int
model: str
choices: List[CompletionChoice]
router = APIRouter(prefix="/completions", tags=["Completion Endpoints"])
def stream_completion(output: Iterable, base_response: CompletionStreamResponse):
"""
Streams a GPT4All output to the client.
Args:
output: The output of GPT4All.generate(), which is an iterable of tokens.
base_response: The base response object, which is cloned and modified for each token.
Returns:
A Generator of CompletionStreamResponse objects, which are serialized to JSON Event Stream format.
"""
for token in output:
chunk = base_response.copy()
chunk.choices = [dict(CompletionChoice(
text=token,
index=0,
logprobs=-1,
finish_reason=''
))]
yield f"data: {json.dumps(dict(chunk))}\n\n"
async def gpu_infer(payload, header):
async with aiohttp.ClientSession() as session:
try:
async with session.post(
settings.hf_inference_server_host, headers=header, data=json.dumps(payload)
) as response:
resp = await response.json()
return resp
except aiohttp.ClientError as e:
# Handle client-side errors (e.g., connection error, invalid URL)
logger.error(f"Client error: {e}")
except aiohttp.ServerError as e:
# Handle server-side errors (e.g., internal server error)
logger.error(f"Server error: {e}")
except json.JSONDecodeError as e:
# Handle JSON decoding errors
logger.error(f"JSON decoding error: {e}")
except Exception as e:
# Handle other unexpected exceptions
logger.error(f"Unexpected error: {e}")
@router.post("/", response_model=CompletionResponse)
async def completions(request: CompletionRequest):
'''
Completes a GPT4All model response.
'''
if settings.inference_mode == "gpu":
params = request.dict(exclude={'model', 'prompt', 'max_tokens', 'n'})
params["max_new_tokens"] = request.max_tokens
params["num_return_sequences"] = request.n
header = {"Content-Type": "application/json"}
if isinstance(request.prompt, list):
tasks = []
for prompt in request.prompt:
payload = {"parameters": params}
payload["inputs"] = prompt
task = gpu_infer(payload, header)
tasks.append(task)
results = await asyncio.gather(*tasks)
choices = []
for response in results:
scores = response["scores"] if "scores" in response else -1.0
choices.append(
dict(
CompletionChoice(
text=response["generated_text"], index=0, logprobs=scores, finish_reason='stop'
)
)
)
return CompletionResponse(
id=str(uuid4()),
created=time.time(),
model=request.model,
choices=choices,
usage={'prompt_tokens': 0, 'completion_tokens': 0, 'total_tokens': 0},
)
else:
payload = {"parameters": params}
# If streaming, we need to return a StreamingResponse
payload["inputs"] = request.prompt
resp = await gpu_infer(payload, header)
output = resp["generated_text"]
# this returns all logprobs
scores = resp["scores"] if "scores" in resp else -1.0
return CompletionResponse(
id=str(uuid4()),
created=time.time(),
model=request.model,
choices=[dict(CompletionChoice(text=output, index=0, logprobs=scores, finish_reason='stop'))],
usage={'prompt_tokens': 0, 'completion_tokens': 0, 'total_tokens': 0},
)
else:
if request.model != settings.model:
raise HTTPException(status_code=400,
detail=f"The GPT4All inference server is booted to only infer: `{settings.model}`")
if isinstance(request.prompt, list):
if len(request.prompt) > 1:
raise HTTPException(status_code=400, detail="Can only infer one inference per request in CPU mode.")
else:
request.prompt = request.prompt[0]
model = GPT4All(model_name=settings.model, model_path=settings.gpt4all_path)
output = model.generate(prompt=request.prompt,
max_tokens=request.max_tokens,
streaming=request.stream,
top_k=request.top_k,
top_p=request.top_p,
temp=request.temperature,
)
# If streaming, we need to return a StreamingResponse
if request.stream:
base_chunk = CompletionStreamResponse(
id=str(uuid4()),
created=time.time(),
model=request.model,
choices=[]
)
return StreamingResponse((response for response in stream_completion(output, base_chunk)),
media_type="text/event-stream")
else:
return CompletionResponse(
id=str(uuid4()),
created=time.time(),
model=request.model,
choices=[dict(CompletionChoice(
text=output,
index=0,
logprobs=-1,
finish_reason='stop'
))],
usage={
'prompt_tokens': 0, # TODO how to compute this?
'completion_tokens': 0,
'total_tokens': 0
}
)

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@@ -1,65 +0,0 @@
from typing import List, Union
from fastapi import APIRouter
from api_v1.settings import settings
from gpt4all import Embed4All
from pydantic import BaseModel, Field
### This should follow https://github.com/openai/openai-openapi/blob/master/openapi.yaml
class EmbeddingRequest(BaseModel):
model: str = Field(
settings.model, description="The model to generate an embedding from."
)
input: Union[str, List[str], List[int], List[List[int]]] = Field(
..., description="Input text to embed, encoded as a string or array of tokens."
)
class EmbeddingUsage(BaseModel):
prompt_tokens: int = 0
total_tokens: int = 0
class Embedding(BaseModel):
index: int = 0
object: str = "embedding"
embedding: List[float]
class EmbeddingResponse(BaseModel):
object: str = "list"
model: str
data: List[Embedding]
usage: EmbeddingUsage
router = APIRouter(prefix="/embeddings", tags=["Embedding Endpoints"])
embedder = Embed4All()
def get_embedding(data: EmbeddingRequest) -> EmbeddingResponse:
"""
Calculates the embedding for the given input using a specified model.
Args:
data (EmbeddingRequest): An EmbeddingRequest object containing the input data
and model name.
Returns:
EmbeddingResponse: An EmbeddingResponse object encapsulating the calculated embedding,
usage info, and the model name.
"""
embedding = embedder.embed(data.input)
return EmbeddingResponse(
data=[Embedding(embedding=embedding)], usage=EmbeddingUsage(), model=data.model
)
@router.post("/", response_model=EmbeddingResponse)
def embeddings(data: EmbeddingRequest):
"""
Creates a GPT4All embedding
"""
return get_embedding(data)

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@@ -1,39 +0,0 @@
import requests
from fastapi import APIRouter, HTTPException
from pydantic import BaseModel, Field
from typing import List, Dict
# Define the router for the engines module
router = APIRouter(prefix="/engines", tags=["Search Endpoints"])
# Define the models for the engines module
class ListEnginesResponse(BaseModel):
data: List[Dict] = Field(..., description="All available models.")
class EngineResponse(BaseModel):
data: List[Dict] = Field(..., description="All available models.")
# Define the routes for the engines module
@router.get("/", response_model=ListEnginesResponse)
async def list_engines():
try:
response = requests.get('https://raw.githubusercontent.com/nomic-ai/gpt4all/main/gpt4all-chat/metadata/models2.json')
response.raise_for_status() # This will raise an HTTPError if the HTTP request returned an unsuccessful status code
engines = response.json()
return ListEnginesResponse(data=engines)
except requests.RequestException as e:
logger.error(f"Error fetching engine list: {e}")
raise HTTPException(status_code=500, detail="Error fetching engine list")
# Define the routes for the engines module
@router.get("/{engine_id}", response_model=EngineResponse)
async def retrieve_engine(engine_id: str):
try:
# Implement logic to fetch a specific engine's details
# This is a placeholder, replace with your actual data retrieval logic
engine_details = {"id": engine_id, "name": "Engine Name", "description": "Engine Description"}
return EngineResponse(data=[engine_details])
except Exception as e:
logger.error(f"Error fetching engine details: {e}")
raise HTTPException(status_code=500, detail=f"Error fetching details for engine {engine_id}")

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@@ -1,13 +0,0 @@
import logging
from fastapi import APIRouter
from fastapi.responses import JSONResponse
log = logging.getLogger(__name__)
router = APIRouter(prefix="/health", tags=["Health"])
@router.get('/', response_class=JSONResponse)
async def health_check():
"""Runs a health check on this instance of the API."""
return JSONResponse({'status': 'ok'}, headers={'Access-Control-Allow-Origin': '*'})

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@@ -1,19 +0,0 @@
from pydantic import BaseSettings
class Settings(BaseSettings):
app_environment = 'dev'
model: str = 'ggml-mpt-7b-chat.bin'
gpt4all_path: str = '/models'
inference_mode: str = "cpu"
hf_inference_server_host: str = "http://gpt4all_gpu:80/generate"
sentry_dns: str = None
temp: float = 0.18
top_p: float = 1.0
top_k: int = 50
repeat_penalty: float = 1.18
settings = Settings()

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@@ -1,3 +0,0 @@
desc = 'GPT4All API'
endpoint_paths = {'health': '/health'}

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@@ -1,84 +0,0 @@
import logging
import os
import docs
from api_v1 import events
from api_v1.api import router as v1_router
from api_v1.settings import settings
from fastapi import FastAPI, HTTPException, Request
from fastapi.logger import logger as fastapi_logger
from starlette.middleware.cors import CORSMiddleware
logger = logging.getLogger(__name__)
app = FastAPI(title='GPT4All API', description=docs.desc)
# CORS Configuration (in-case you want to deploy)
app.add_middleware(
CORSMiddleware,
allow_origins=["*"],
allow_credentials=True,
allow_methods=["GET", "POST", "OPTIONS"],
allow_headers=["*"],
)
logger.info('Adding v1 endpoints..')
# add v1
app.include_router(v1_router, prefix='/v1')
app.add_event_handler('startup', events.startup_event_handler(app))
app.add_exception_handler(HTTPException, events.on_http_error)
@app.on_event("startup")
async def startup():
global model
if settings.inference_mode == "cpu":
logger.info(f"Downloading/fetching model: {os.path.join(settings.gpt4all_path, settings.model)}")
from gpt4all import GPT4All
model = GPT4All(model_name=settings.model, model_path=settings.gpt4all_path)
logger.info(f"GPT4All API is ready to infer from {settings.model} on CPU.")
else:
# is it possible to do this once the server is up?
## TODO block until HF inference server is up.
logger.info(f"GPT4All API is ready to infer from {settings.model} on CPU.")
@app.on_event("shutdown")
async def shutdown():
logger.info("Shutting down API")
if settings.sentry_dns is not None:
import sentry_sdk
def traces_sampler(sampling_context):
if 'health' in sampling_context['transaction_context']['name']:
return False
sentry_sdk.init(
dsn=settings.sentry_dns, traces_sample_rate=0.1, traces_sampler=traces_sampler, send_default_pii=False
)
# This is needed to get logs to show up in the app
if "gunicorn" in os.environ.get("SERVER_SOFTWARE", ""):
gunicorn_error_logger = logging.getLogger("gunicorn.error")
gunicorn_logger = logging.getLogger("gunicorn")
root_logger = logging.getLogger()
fastapi_logger.setLevel(gunicorn_logger.level)
fastapi_logger.handlers = gunicorn_error_logger.handlers
root_logger.setLevel(gunicorn_logger.level)
uvicorn_logger = logging.getLogger("uvicorn.access")
uvicorn_logger.handlers = gunicorn_error_logger.handlers
else:
# https://github.com/tiangolo/fastapi/issues/2019
LOG_FORMAT2 = (
"[%(asctime)s %(process)d:%(threadName)s] %(name)s - %(levelname)s - %(message)s | %(filename)s:%(lineno)d"
)
logging.basicConfig(level=logging.INFO, format=LOG_FORMAT2)

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@@ -1,93 +0,0 @@
"""
Use the OpenAI python API to test gpt4all models.
"""
from typing import List, get_args
import os
from dotenv import load_dotenv
import openai
openai.api_base = "http://localhost:4891/v1"
openai.api_key = "not needed for a local LLM"
# Load the .env file
env_path = 'gpt4all-api/gpt4all_api/.env'
load_dotenv(dotenv_path=env_path)
# Fetch MODEL_ID from .env file
model_id = os.getenv('MODEL_BIN', 'default_model_id')
embedding = os.getenv('EMBEDDING', 'default_embedding_model_id')
print (model_id)
print (embedding)
def test_completion():
model = model_id
prompt = "Who is Michael Jordan?"
response = openai.Completion.create(
model=model, prompt=prompt, max_tokens=50, temperature=0.28, top_p=0.95, n=1, echo=True, stream=False
)
assert len(response['choices'][0]['text']) > len(prompt)
def test_streaming_completion():
model = model_id
prompt = "Who is Michael Jordan?"
tokens = []
for resp in openai.Completion.create(
model=model,
prompt=prompt,
max_tokens=50,
temperature=0.28,
top_p=0.95,
n=1,
echo=True,
stream=True):
tokens.append(resp.choices[0].text)
assert (len(tokens) > 0)
assert (len("".join(tokens)) > len(prompt))
# Modified test batch, problems with keyerror in response
def test_batched_completion():
model = model_id # replace with your specific model ID
prompt = "Who is Michael Jordan?"
responses = []
# Loop to create completions one at a time
for _ in range(3):
response = openai.Completion.create(
model=model, prompt=prompt, max_tokens=50, temperature=0.28, top_p=0.95, n=1, echo=True, stream=False
)
responses.append(response)
# Assertions to check the responses
for response in responses:
assert len(response['choices'][0]['text']) > len(prompt)
assert len(responses) == 3
def test_embedding():
model = embedding
prompt = "Who is Michael Jordan?"
response = openai.Embedding.create(model=model, input=prompt)
output = response["data"][0]["embedding"]
args = get_args(List[float])
assert response["model"] == model
assert isinstance(output, list)
assert all(isinstance(x, args) for x in output)
def test_chat_completion():
model = model_id
response = openai.ChatCompletion.create(
model=model,
messages=[
{"role": "system", "content": "You are a helpful assistant."},
{"role": "user", "content": "Knock knock."},
{"role": "assistant", "content": "Who's there?"},
{"role": "user", "content": "Orange."},
]
)
assert response.choices[0].message.role == "assistant"
assert len(response.choices[0].message.content) > 0

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@@ -1,3 +0,0 @@
# Add your GGUF compatible model LLM here. ie: MODEL_BIN="mistral-7b-instruct-v0.1.Q4_0", rename file ".env"
# Make sure this LLM matches the model you placed inside the models folder
MODEL_BIN=""

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@@ -1 +0,0 @@
### Drop GGUF compatible models here, make sure it matches MODEL_BIN on your .env file

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@@ -1,13 +0,0 @@
aiohttp>=3.6.2
aiofiles
pydantic>=1.4.0,<2.0.0
requests>=2.24.0
ujson>=2.0.2
fastapi>=0.95.0
Jinja2>=3.0
gpt4all>=1.0.0
pytest
openai==0.28.0
black
isort
python-dotenv

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@@ -1,46 +0,0 @@
ROOT_DIR:=$(shell dirname $(realpath $(lastword $(MAKEFILE_LIST))))
APP_NAME:=gpt4all_api
PYTHON:=python3.8
SHELL := /bin/bash
all: dependencies
fresh: clean dependencies
testenv: clean_testenv test_build
docker compose -f docker-compose.yaml up --build
testenv_gpu: clean_testenv test_build
docker compose -f docker-compose.yaml -f docker-compose.gpu.yaml up --build
testenv_d: clean_testenv test_build
docker compose env up --build -d
test:
docker compose exec $(APP_NAME) pytest -svv --disable-warnings -p no:cacheprovider /app/tests
test_build:
DOCKER_BUILDKIT=1 docker build -t $(APP_NAME) --progress plain -f $(APP_NAME)/Dockerfile.buildkit .
clean_testenv:
docker compose down -v
fresh_testenv: clean_testenv testenv
venv:
if [ ! -d $(ROOT_DIR)/venv ]; then $(PYTHON) -m venv $(ROOT_DIR)/venv; fi
dependencies: venv
source $(ROOT_DIR)/venv/bin/activate; $(PYTHON) -m pip install -r $(ROOT_DIR)/$(APP_NAME)/requirements.txt
clean: clean_testenv
# Remove existing environment
rm -rf $(ROOT_DIR)/venv;
rm -rf $(ROOT_DIR)/$(APP_NAME)/*.pyc;
black:
source $(ROOT_DIR)/venv/bin/activate; black -l 120 -S --target-version py38 $(APP_NAME)
isort:
source $(ROOT_DIR)/venv/bin/activate; isort --ignore-whitespace --atomic -w 120 $(APP_NAME)

View File

@@ -1,16 +1,24 @@
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)
if(APPLE)
option(BUILD_UNIVERSAL "Build a Universal binary on macOS" ON)
if(BUILD_UNIVERSAL)
if (APPLE)
option(BUILD_UNIVERSAL "Build a Universal binary on macOS" ON)
else()
option(LLMODEL_KOMPUTE "llmodel: use Kompute" ON)
option(LLMODEL_VULKAN "llmodel: use Vulkan" OFF)
option(LLMODEL_CUDA "llmodel: use CUDA" ON)
option(LLMODEL_ROCM "llmodel: use ROCm" OFF)
endif()
if (APPLE)
if (BUILD_UNIVERSAL)
# Build a Universal binary on macOS
# This requires that the found Qt library is compiled as Universal binaries.
set(CMAKE_OSX_ARCHITECTURES "arm64;x86_64" CACHE STRING "" FORCE)
else()
# Build for the host architecture on macOS
if(NOT CMAKE_OSX_ARCHITECTURES)
if (NOT CMAKE_OSX_ARCHITECTURES)
set(CMAKE_OSX_ARCHITECTURES "${CMAKE_HOST_SYSTEM_PROCESSOR}" CACHE STRING "" FORCE)
endif()
endif()
@@ -39,11 +47,39 @@ else()
message(STATUS "Interprocedural optimization support detected")
endif()
set(DIRECTORY llama.cpp-mainline)
include(llama.cpp.cmake)
set(BUILD_VARIANTS default avxonly)
if (${CMAKE_SYSTEM_NAME} MATCHES "Darwin")
set(BUILD_VARIANTS ${BUILD_VARIANTS} metal)
set(BUILD_VARIANTS)
set(GPTJ_BUILD_VARIANT cpu)
if (APPLE)
list(APPEND BUILD_VARIANTS metal)
endif()
if (LLMODEL_KOMPUTE)
list(APPEND BUILD_VARIANTS kompute kompute-avxonly)
set(GPTJ_BUILD_VARIANT kompute)
else()
list(PREPEND BUILD_VARIANTS cpu cpu-avxonly)
endif()
if (LLMODEL_VULKAN)
list(APPEND BUILD_VARIANTS vulkan vulkan-avxonly)
endif()
if (LLMODEL_CUDA)
if (DEFINED CMAKE_CUDA_ARCHITECTURES)
set(GGML_CUDA_ARCHITECTURES "${CMAKE_CUDA_ARCHITECTURES}")
endif()
include(CheckLanguage)
check_language(CUDA)
if (NOT CMAKE_CUDA_COMPILER)
message(WARNING "CUDA Toolkit not found. To build without CUDA, use -DLLMODEL_CUDA=OFF.")
endif()
enable_language(CUDA)
list(APPEND BUILD_VARIANTS cuda cuda-avxonly)
endif()
if (LLMODEL_ROCM)
enable_language(HIP)
list(APPEND BUILD_VARIANTS rocm rocm-avxonly)
endif()
set(CMAKE_VERBOSE_MAKEFILE ON)
@@ -51,24 +87,34 @@ set(CMAKE_VERBOSE_MAKEFILE ON)
# Go through each build variant
foreach(BUILD_VARIANT IN LISTS BUILD_VARIANTS)
# Determine flags
if (BUILD_VARIANT STREQUAL avxonly)
set(GPT4ALL_ALLOW_NON_AVX NO)
if (BUILD_VARIANT MATCHES avxonly)
set(GPT4ALL_ALLOW_NON_AVX OFF)
else()
set(GPT4ALL_ALLOW_NON_AVX YES)
set(GPT4ALL_ALLOW_NON_AVX ON)
endif()
set(LLAMA_AVX2 ${GPT4ALL_ALLOW_NON_AVX})
set(LLAMA_F16C ${GPT4ALL_ALLOW_NON_AVX})
set(LLAMA_FMA ${GPT4ALL_ALLOW_NON_AVX})
if (BUILD_VARIANT STREQUAL metal)
set(LLAMA_METAL YES)
else()
set(LLAMA_METAL NO)
set(LLAMA_METAL OFF)
set(LLAMA_KOMPUTE OFF)
set(LLAMA_VULKAN OFF)
set(LLAMA_CUDA OFF)
set(LLAMA_ROCM OFF)
if (BUILD_VARIANT MATCHES metal)
set(LLAMA_METAL ON)
elseif (BUILD_VARIANT MATCHES kompute)
set(LLAMA_KOMPUTE ON)
elseif (BUILD_VARIANT MATCHES vulkan)
set(LLAMA_VULKAN ON)
elseif (BUILD_VARIANT MATCHES cuda)
set(LLAMA_CUDA ON)
elseif (BUILD_VARIANT MATCHES rocm)
set(LLAMA_HIPBLAS ON)
endif()
# Include GGML
set(LLAMA_K_QUANTS YES)
include_ggml(llama.cpp-mainline -mainline-${BUILD_VARIANT} ON)
include_ggml(-mainline-${BUILD_VARIANT})
# Function for preparing individual implementations
function(prepare_target TARGET_NAME BASE_LIB)
@@ -93,17 +139,21 @@ foreach(BUILD_VARIANT IN LISTS BUILD_VARIANTS)
LLAMA_VERSIONS=>=3 LLAMA_DATE=999999)
prepare_target(llamamodel-mainline llama-mainline)
if (NOT LLAMA_METAL)
if (BUILD_VARIANT MATCHES ${GPTJ_BUILD_VARIANT})
add_library(gptj-${BUILD_VARIANT} SHARED
gptj.cpp utils.h utils.cpp llmodel_shared.cpp llmodel_shared.h)
prepare_target(gptj llama-mainline)
endif()
if (NOT PROJECT_IS_TOP_LEVEL AND BUILD_VARIANT STREQUAL cuda)
set(CUDAToolkit_BIN_DIR ${CUDAToolkit_BIN_DIR} PARENT_SCOPE)
endif()
endforeach()
add_library(llmodel
llmodel.h llmodel.cpp llmodel_shared.cpp
llmodel_c.h llmodel_c.cpp
dlhandle.h
dlhandle.cpp
)
target_compile_definitions(llmodel PRIVATE LIB_FILE_EXT="${CMAKE_SHARED_LIBRARY_SUFFIX}")

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@@ -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)

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@@ -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

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@@ -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;
}
@@ -785,13 +784,16 @@ const std::vector<LLModel::Token> &GPTJ::endTokens() const
return fres;
}
std::string get_arch_name(gguf_context *ctx_gguf) {
std::string arch_name;
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");
enum gguf_type ktype = gguf_get_kv_type(ctx_gguf, kid);
if (ktype != GGUF_TYPE_STRING) {
throw std::runtime_error("ERROR: Can't get general architecture from gguf file.");
}
if (ktype != GGUF_TYPE_STRING)
throw std::runtime_error("key general.architecture has wrong type");
return gguf_get_val_str(ctx_gguf, kid);
}
@@ -802,36 +804,50 @@ std::string 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 bool magic_match(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,
/*.ctx = */ &ctx_meta,
};
gguf_context *ctx_gguf = gguf_init_from_file(fname, params);
if (!ctx_gguf)
return false;
bool isValid = gguf_get_version(ctx_gguf) <= 3;
isValid = isValid && get_arch_name(ctx_gguf) == "gptj";
char *arch = nullptr;
if (ctx_gguf && gguf_get_version(ctx_gguf) <= 3) {
try {
arch = strdup(get_arch_name(ctx_gguf));
} catch (const std::runtime_error &) {
// cannot read key -> return null
}
}
gguf_free(ctx_gguf);
return isValid;
return arch;
}
DLL_EXPORT LLModel *construct() {
DLL_EXPORT bool is_arch_supported(const char *arch)
{
return !strcmp(arch, "gptj");
}
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:

File diff suppressed because it is too large Load Diff

View File

@@ -1,56 +1,102 @@
#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>
# include <ggml-kompute.h>
#elif GGML_USE_VULKAN
# include <ggml-vulkan.h>
#elif GGML_USE_CUDA
# include <ggml-cuda.h>
#endif
using namespace std::string_literals;
// Maximum supported GGUF version
static constexpr int GGUF_VER_MAX = 3;
static const char * const modelType_ = "LLaMA";
// note: same order as LLM_ARCH_NAMES in llama.cpp
static const std::vector<const char *> KNOWN_ARCHES {
"baichuan", "bert", "bloom", "codeshell", "falcon", "gemma", "gpt2", "llama", "mpt", "nomic-bert", "orion",
"persimmon", "phi2", "plamo", "qwen", "qwen2", "refact", "stablelm", "starcoder"
"llama",
"falcon",
// "grok", -- 314B parameters
"gpt2",
// "gptj", -- no inference code
// "gptneox", -- no inference code
"mpt",
"baichuan",
"starcoder",
// "persimmon", -- CUDA generates garbage
"refact",
"bert",
"nomic-bert",
"bloom",
"stablelm",
"qwen",
"qwen2",
"qwen2moe",
"phi2",
"phi3",
// "plamo", -- https://github.com/ggerganov/llama.cpp/issues/5669
"codeshell",
"orion",
"internlm2",
// "minicpm", -- CUDA generates garbage
"gemma",
"starcoder2",
// "mamba", -- CUDA missing SSM_CONV
"xverse",
"command-r",
// "dbrx", -- 16x12B parameters
"olmo",
};
static const std::vector<const char *> EMBEDDING_ARCHES {
"bert", "nomic-bert"
"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);
@@ -104,17 +150,21 @@ static int llama_sample_top_p_top_k(
return llama_sample_token(ctx, &candidates_p);
}
std::string get_arch_name(gguf_context *ctx_gguf) {
std::string arch_name;
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");
enum gguf_type ktype = gguf_get_kv_type(ctx_gguf, kid);
if (ktype != (GGUF_TYPE_STRING)) {
throw std::runtime_error("ERROR: Can't get general architecture from gguf file.");
}
if (ktype != GGUF_TYPE_STRING)
throw std::runtime_error("key general.architecture has wrong type");
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,
@@ -135,14 +185,22 @@ 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;
auto * ctx = load_gguf(modelPath.c_str());
if (!ctx)
return -1;
std::string arch = get_arch_name(ctx);
goto cleanup;
int32_t value = -1;
if (ctx) {
try {
arch = get_arch_name(ctx);
} catch (const std::runtime_error &) {
goto cleanup; // cannot read key
}
{
auto key = arch + "." + archKey;
int keyidx = gguf_find_key(ctx, key.c_str());
if (keyidx != -1) {
@@ -152,6 +210,7 @@ static int32_t get_arch_key_u32(std::string const &modelPath, std::string const
}
}
cleanup:
gguf_free(ctx);
return value;
}
@@ -160,6 +219,7 @@ struct LLamaPrivate {
const std::string modelPath;
bool modelLoaded = false;
int device = -1;
std::string deviceName;
llama_model *model = nullptr;
llama_context *ctx = nullptr;
llama_model_params model_params;
@@ -183,7 +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);
@@ -207,7 +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";
@@ -243,16 +305,28 @@ 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;
auto *ctx_gguf = load_gguf(modelPath.c_str());
if (!ctx_gguf) {
std::cerr << __func__ << ": failed to load GGUF from " << modelPath << "\n";
return false;
goto cleanup;
}
std::string arch = get_arch_name(ctx_gguf);
try {
arch = get_arch_name(ctx_gguf);
} catch (const std::runtime_error &) {
goto cleanup; // cannot read key
}
result = is_embedding_arch(arch);
cleanup:
gguf_free(ctx_gguf);
return is_embedding_arch(arch);
return result;
}
bool LLamaModel::loadModel(const std::string &modelPath, int n_ctx, int ngl)
@@ -292,10 +366,16 @@ bool LLamaModel::loadModel(const std::string &modelPath, int n_ctx, int ngl)
d_ptr->backend_name = "cpu"; // default
#ifdef GGML_USE_KOMPUTE
#if defined(GGML_USE_KOMPUTE) || defined(GGML_USE_VULKAN) || defined(GGML_USE_CUDA)
if (d_ptr->device != -1) {
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;
@@ -308,14 +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;
}
@@ -327,7 +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 ("
@@ -357,18 +441,27 @@ 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;
}
d_ptr->end_tokens = {llama_token_eos(d_ptr->model)};
if (usingGPUDevice()) {
#ifdef GGML_USE_KOMPUTE
if (usingGPUDevice() && ggml_vk_has_device()) {
std::cerr << "llama.cpp: using Vulkan on " << ggml_vk_current_device().name << std::endl;
if (llama_verbose()) {
std::cerr << "llama.cpp: using Vulkan on " << d_ptr->deviceName << std::endl;
}
d_ptr->backend_name = "kompute";
}
#elif defined(GGML_USE_VULKAN)
d_ptr->backend_name = "vulkan";
#elif defined(GGML_USE_CUDA)
d_ptr->backend_name = "cuda";
#endif
}
m_supportsEmbedding = isEmbedding;
m_supportsCompletion = !isEmbedding;
@@ -378,12 +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;
}
@@ -429,7 +524,18 @@ std::vector<LLModel::Token> LLamaModel::tokenize(PromptContext &ctx, const std::
std::string LLamaModel::tokenToString(Token id) const
{
return llama_token_to_piece(d_ptr->ctx, id);
std::vector<char> result(8, 0);
const int n_tokens = llama_token_to_piece(d_ptr->model, id, result.data(), result.size(), false);
if (n_tokens < 0) {
result.resize(-n_tokens);
int check = llama_token_to_piece(d_ptr->model, id, result.data(), result.size(), false);
GGML_ASSERT(check == -n_tokens);
}
else {
result.resize(n_tokens);
}
return std::string(result.data(), result.size());
}
LLModel::Token LLamaModel::sampleToken(PromptContext &promptCtx) const
@@ -494,34 +600,78 @@ int32_t LLamaModel::layerCount(std::string const &modelPath) const
return get_arch_key_u32(modelPath, "block_count");
}
#ifdef GGML_USE_VULKAN
static const char *getVulkanVendorName(uint32_t vendorID)
{
switch (vendorID) {
case 0x10DE: return "nvidia";
case 0x1002: return "amd";
case 0x8086: return "intel";
default: return "unknown";
}
}
#endif
std::vector<LLModel::GPUDevice> LLamaModel::availableGPUDevices(size_t memoryRequired) const
{
#ifdef GGML_USE_KOMPUTE
#if defined(GGML_USE_KOMPUTE) || defined(GGML_USE_VULKAN) || defined(GGML_USE_CUDA)
size_t count = 0;
auto * vkDevices = ggml_vk_available_devices(memoryRequired, &count);
if (vkDevices) {
#ifdef GGML_USE_KOMPUTE
auto *lcppDevices = ggml_vk_available_devices(memoryRequired, &count);
#elif defined(GGML_USE_VULKAN)
(void)memoryRequired; // hasn't been used since GGUF was added
auto *lcppDevices = ggml_vk_available_devices(&count);
#else // defined(GGML_USE_CUDA)
(void)memoryRequired;
auto *lcppDevices = ggml_cuda_available_devices(&count);
#endif
if (lcppDevices) {
std::vector<LLModel::GPUDevice> devices;
devices.reserve(count);
for (size_t i = 0; i < count; ++i) {
auto & dev = vkDevices[i];
auto & dev = lcppDevices[i];
devices.emplace_back(
#ifdef GGML_USE_KOMPUTE
/* backend = */ "kompute",
/* index = */ dev.index,
/* type = */ dev.type,
/* heapSize = */ dev.heapSize,
/* name = */ dev.name,
/* vendor = */ dev.vendor
#elif defined(GGML_USE_VULKAN)
/* backend = */ "vulkan",
/* index = */ dev.index,
/* type = */ dev.type,
/* heapSize = */ dev.heapSize,
/* name = */ dev.name,
/* vendor = */ getVulkanVendorName(dev.vendorID)
#else // defined(GGML_USE_CUDA)
/* backend = */ "cuda",
/* index = */ dev.index,
/* type = */ 2, // vk::PhysicalDeviceType::eDiscreteGpu
/* heapSize = */ dev.heapSize,
/* name = */ dev.name,
/* vendor = */ "nvidia"
#endif
);
#ifndef GGML_USE_CUDA
ggml_vk_device_destroy(&dev);
#else
ggml_cuda_device_destroy(&dev);
#endif
}
free(vkDevices);
free(lcppDevices);
return devices;
}
#else
(void)memoryRequired;
std::cerr << __func__ << ": built without Kompute\n";
std::cerr << __func__ << ": built without a GPU backend\n";
#endif
return {};
@@ -529,11 +679,32 @@ std::vector<LLModel::GPUDevice> LLamaModel::availableGPUDevices(size_t memoryReq
bool LLamaModel::initializeGPUDevice(size_t memoryRequired, const std::string &name) const
{
#if defined(GGML_USE_KOMPUTE)
#if defined(GGML_USE_VULKAN) || defined(GGML_USE_CUDA)
auto devices = availableGPUDevices(memoryRequired);
auto dev_it = devices.begin();
#ifndef GGML_USE_CUDA
if (name == "amd" || name == "nvidia" || name == "intel") {
dev_it = std::find_if(dev_it, devices.end(), [&name](auto &dev) { return dev.vendor == name; });
} else
#endif
if (name != "gpu") {
dev_it = std::find_if(dev_it, devices.end(), [&name](auto &dev) { return dev.name == name; });
}
if (dev_it < devices.end()) {
d_ptr->device = dev_it->index;
d_ptr->deviceName = dev_it->name;
return true;
}
return false;
#elif defined(GGML_USE_KOMPUTE)
ggml_vk_device device;
bool ok = ggml_vk_get_device(&device, memoryRequired, name.c_str());
if (ok) {
d_ptr->device = device.index;
d_ptr->deviceName = device.name;
ggml_vk_device_destroy(&device);
return true;
}
#else
@@ -545,37 +716,49 @@ bool LLamaModel::initializeGPUDevice(size_t memoryRequired, const std::string &n
bool LLamaModel::initializeGPUDevice(int device, std::string *unavail_reason) const
{
#if defined(GGML_USE_KOMPUTE)
#if defined(GGML_USE_KOMPUTE) || defined(GGML_USE_VULKAN) || defined(GGML_USE_CUDA)
(void)unavail_reason;
auto devices = availableGPUDevices();
auto it = std::find_if(devices.begin(), devices.end(), [device](auto &dev) { return dev.index == device; });
d_ptr->device = device;
d_ptr->deviceName = it < devices.end() ? it->name : "(unknown)";
return true;
#else
(void)device;
if (unavail_reason) {
*unavail_reason = "built without Kompute";
*unavail_reason = "built without a GPU backend";
}
return false;
#endif
}
bool LLamaModel::hasGPUDevice()
bool LLamaModel::usingGPUDevice() const
{
#if defined(GGML_USE_KOMPUTE)
return d_ptr->device != -1;
#else
return false;
if (!d_ptr->model)
return false;
bool usingGPU = llama_model_using_gpu(d_ptr->model);
#ifdef GGML_USE_KOMPUTE
assert(!usingGPU || ggml_vk_has_device());
#endif
return usingGPU;
}
bool LLamaModel::usingGPUDevice()
const char *LLamaModel::backendName() const
{
#if defined(GGML_USE_KOMPUTE)
return hasGPUDevice() && d_ptr->model_params.n_gpu_layers > 0;
return d_ptr->backend_name;
}
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 true;
#else
return false;
return "Metal";
#endif
}
return nullptr;
}
void llama_batch_add(
@@ -595,13 +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);
}
@@ -721,12 +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);
}
@@ -755,11 +942,12 @@ void LLamaModel::embedInternal(
tokens.resize(text.length()+4);
int32_t n_tokens = llama_tokenize(d_ptr->model, text.c_str(), text.length(), tokens.data(), tokens.size(), wantBOS, false);
if (n_tokens) {
assert(useEOS == (eos_token != -1 && tokens[n_tokens - 1] == eos_token));
tokens.resize(n_tokens - useEOS); // erase EOS/SEP
} else {
tokens.clear();
(void)eos_token;
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
@@ -811,14 +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 */ }
}
@@ -922,6 +1110,8 @@ void LLamaModel::embedInternal(
}
if (tokenCount) { *tokenCount = totalTokens; }
llama_batch_free(batch);
}
#if defined(_WIN32)
@@ -931,40 +1121,54 @@ 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 bool magic_match(const char *fname) {
auto * ctx = load_gguf(fname);
std::string arch = get_arch_name(ctx);
DLL_EXPORT char *get_file_arch(const char *fname)
{
char *arch = nullptr;
std::string archStr;
bool valid = true;
auto *ctx = load_gguf(fname);
if (!ctx)
goto cleanup;
if (std::find(KNOWN_ARCHES.begin(), KNOWN_ARCHES.end(), arch) == KNOWN_ARCHES.end()) {
// not supported by this version of llama.cpp
if (arch != "gptj") { // we support this via another module
std::cerr << __func__ << ": unsupported model architecture: " << arch << "\n";
}
valid = false;
try {
archStr = get_arch_name(ctx);
} catch (const std::runtime_error &) {
goto cleanup; // cannot read key
}
if (valid && is_embedding_arch(arch) && gguf_find_key(ctx, (arch + ".pooling_type").c_str()) < 0)
valid = false; // old pre-llama.cpp embedding model, e.g. all-MiniLM-L6-v2-f16.gguf
if (is_embedding_arch(archStr) && gguf_find_key(ctx, (archStr + ".pooling_type").c_str()) < 0) {
// old bert.cpp embedding model
} else {
arch = strdup(archStr.c_str());
}
cleanup:
gguf_free(ctx);
return valid;
return arch;
}
DLL_EXPORT LLModel *construct() {
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()
{
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;
@@ -30,11 +31,12 @@ public:
size_t restoreState(const uint8_t *src) override;
void setThreadCount(int32_t n_threads) override;
int32_t threadCount() const override;
std::vector<GPUDevice> availableGPUDevices(size_t memoryRequired) const override;
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() override;
bool usingGPUDevice() override;
bool usingGPUDevice() const override;
const char *backendName() const override;
const char *gpuDeviceName() const override;
size_t embeddingSize() const override;
// user-specified prefix

View File

@@ -1,20 +1,45 @@
#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>
#include <sstream>
#include <string>
#include <unordered_map>
#include <vector>
#ifdef _WIN32
# define WIN32_LEAN_AND_MEAN
# ifndef NOMINMAX
# define NOMINMAX
# endif
# include <windows.h>
#endif
#ifdef _MSC_VER
#include <intrin.h>
# 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__)
static const std::string DEFAULT_BACKENDS[] = {"metal", "cpu"};
#else
static const std::string DEFAULT_BACKENDS[] = {"cpu"};
#endif
std::string s_implementations_search_path = ".";
@@ -32,13 +57,13 @@ std::string s_implementations_search_path = ".";
}
// AVX via EAX=1: Processor Info and Feature Bits, bit 28 of ECX
#define cpu_supports_avx() (get_cpu_info(1, 2) & (1 << 28))
#define cpu_supports_avx() !!(get_cpu_info(1, 2) & (1 << 28))
// AVX2 via EAX=7, ECX=0: Extended Features, bit 5 of EBX
#define cpu_supports_avx2() (get_cpu_info(7, 1) & (1 << 5))
#define cpu_supports_avx2() !!(get_cpu_info(7, 1) & (1 << 5))
#else
// gcc/clang
#define cpu_supports_avx() __builtin_cpu_supports("avx")
#define cpu_supports_avx2() __builtin_cpu_supports("avx2")
#define cpu_supports_avx() !!__builtin_cpu_supports("avx")
#define cpu_supports_avx2() !!__builtin_cpu_supports("avx2")
#endif
LLModel::Implementation::Implementation(Dlhandle &&dlhandle_)
@@ -49,14 +74,17 @@ LLModel::Implementation::Implementation(Dlhandle &&dlhandle_)
auto get_build_variant = m_dlhandle->get<const char *()>("get_build_variant");
assert(get_build_variant);
m_buildVariant = get_build_variant();
m_magicMatch = m_dlhandle->get<bool(const char*)>("magic_match");
assert(m_magicMatch);
m_getFileArch = m_dlhandle->get<char *(const char *)>("get_file_arch");
assert(m_getFileArch);
m_isArchSupported = m_dlhandle->get<bool(const char *)>("is_arch_supported");
assert(m_isArchSupported);
m_construct = m_dlhandle->get<LLModel *()>("construct");
assert(m_construct);
}
LLModel::Implementation::Implementation(Implementation &&o)
: m_magicMatch(o.m_magicMatch)
: m_getFileArch(o.m_getFileArch)
, m_isArchSupported(o.m_isArchSupported)
, m_construct(o.m_construct)
, m_modelType(o.m_modelType)
, m_buildVariant(o.m_buildVariant)
@@ -64,15 +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");
}
@@ -82,11 +128,11 @@ const std::vector<LLModel::Implementation> &LLModel::Implementation::implementat
static auto* libs = new std::vector<Implementation>([] () {
std::vector<Implementation> fres;
std::string impl_name_re = "(gptj|llamamodel-mainline)";
addCudaSearchPath();
std::string impl_name_re = "(gptj|llamamodel-mainline)-(cpu|metal|kompute|vulkan|cuda)";
if (cpu_supports_avx2() == 0) {
impl_name_re += "-avxonly";
} else {
impl_name_re += "-(default|metal)";
}
std::regex re(impl_name_re);
auto search_in_directory = [&](const std::string& paths) {
@@ -94,21 +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)));
}
}
};
@@ -121,127 +173,175 @@ const std::vector<LLModel::Implementation> &LLModel::Implementation::implementat
return *libs;
}
const LLModel::Implementation* LLModel::Implementation::implementation(const char *fname, 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)
{
bool buildVariantMatched = false;
std::optional<std::string> archName;
for (const auto& i : implementationList()) {
if (buildVariant != i.m_buildVariant) continue;
buildVariantMatched = true;
if (!i.m_magicMatch(fname)) continue;
return &i;
char *arch = i.m_getFileArch(fname);
if (!arch) continue;
archName = arch;
bool archSupported = i.m_isArchSupported(arch);
free(arch);
if (archSupported) return &i;
}
if (!buildVariantMatched)
throw std::runtime_error("Could not find any implementations for build variant: " + buildVariant);
return nullptr;
if (!archName)
throw UnsupportedModelError("Unsupported file format");
return nullptr; // unsupported model format
throw BadArchError(std::move(*archName));
}
LLModel *LLModel::Implementation::construct(const std::string &modelPath, std::string buildVariant, int n_ctx) {
// Get correct implementation
const Implementation* impl = nullptr;
#if defined(__APPLE__) && defined(__arm64__) // FIXME: See if metal works for intel macs
if (buildVariant == "auto") {
size_t total_mem = getSystemTotalRAMInBytes();
impl = implementation(modelPath.c_str(), "metal");
if(impl) {
LLModel* metalimpl = impl->m_construct();
metalimpl->m_implementation = impl;
/* TODO(cebtenzzre): after we fix requiredMem, we should change this to happen at
* load time, not construct time. right now n_ctx is incorrectly hardcoded 2048 in
* most (all?) places where this is called, causing underestimation of required
* memory. */
size_t req_mem = metalimpl->requiredMem(modelPath, n_ctx, 100);
float req_to_total = (float) req_mem / (float) total_mem;
// on a 16GB M2 Mac a 13B q4_0 (0.52) works for me but a 13B q4_K_M (0.55) does not
if (req_to_total >= 0.53) {
delete metalimpl;
impl = nullptr;
} else {
return metalimpl;
}
}
}
#else
(void)n_ctx;
#endif
if (!impl) {
//TODO: Auto-detect CUDA/OpenCL
if (buildVariant == "auto") {
if (cpu_supports_avx2() == 0) {
buildVariant = "avxonly";
} else {
buildVariant = "default";
}
}
impl = implementation(modelPath.c_str(), buildVariant);
if (!impl) return nullptr;
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);
} else {
desiredBackends.insert(desiredBackends.end(), DEFAULT_BACKENDS, std::end(DEFAULT_BACKENDS));
}
// Construct and return llmodel implementation
auto fres = impl->m_construct();
fres->m_implementation = impl;
return fres;
for (const auto &desiredBackend: desiredBackends) {
const auto *impl = implementation(modelPath.c_str(), applyCPUVariant(desiredBackend));
if (impl) {
// Construct llmodel implementation
auto *fres = impl->m_construct();
fres->m_implementation = impl;
#if defined(__APPLE__) && defined(__aarch64__) // FIXME: See if metal works for intel macs
/* TODO(cebtenzzre): after we fix requiredMem, we should change this to happen at
* load time, not construct time. right now n_ctx is incorrectly hardcoded 2048 in
* most (all?) places where this is called, causing underestimation of required
* memory. */
if (backend == "auto" && desiredBackend == "metal") {
// on a 16GB M2 Mac a 13B q4_0 (0.52) works for me but a 13B q4_K_M (0.55) does not
size_t req_mem = fres->requiredMem(modelPath, n_ctx, 100);
if (req_mem >= size_t(0.53f * getSystemTotalRAMInBytes())) {
delete fres;
continue;
}
}
#else
(void)n_ctx;
#endif
return fres;
}
}
throw MissingImplementationError("Could not find any implementations for backend: " + backend);
}
LLModel *LLModel::Implementation::constructDefaultLlama() {
static std::unique_ptr<LLModel> llama([]() -> LLModel * {
const std::vector<LLModel::Implementation> *impls;
try {
impls = &implementationList();
} catch (const std::runtime_error &e) {
std::cerr << __func__ << ": implementationList failed: " << e.what() << "\n";
return nullptr;
}
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;
try {
impls = &implementationList();
} catch (const std::runtime_error &e) {
std::cerr << __func__ << ": implementationList failed: " << e.what() << "\n";
return nullptr;
}
std::vector<std::string> desiredBackends;
if (backend) {
desiredBackends.push_back(backend.value());
} else {
desiredBackends.insert(desiredBackends.end(), DEFAULT_BACKENDS, std::end(DEFAULT_BACKENDS));
}
const Implementation *impl = nullptr;
for (const auto &desiredBackend: desiredBackends) {
auto cacheIt = implCache.find(desiredBackend);
if (cacheIt != implCache.end())
return cacheIt->second.get(); // cached
const LLModel::Implementation *impl = nullptr;
for (const auto &i: *impls) {
if (i.m_buildVariant == "metal" || i.m_modelType != "LLaMA") continue;
impl = &i;
}
if (!impl) {
std::cerr << __func__ << ": could not find llama.cpp implementation\n";
return nullptr;
if (i.m_modelType == "LLaMA" && i.m_buildVariant == applyCPUVariant(desiredBackend)) {
impl = &i;
break;
}
}
auto fres = impl->m_construct();
fres->m_implementation = impl;
return fres;
}());
return llama.get();
if (impl) {
auto *fres = impl->m_construct();
fres->m_implementation = impl;
implCache[desiredBackend] = std::unique_ptr<LLModel>(fres);
return fres;
}
}
std::cerr << __func__ << ": could not find Llama implementation for backend: " << backend.value_or("default") << "\n";
return nullptr;
}
std::vector<LLModel::GPUDevice> LLModel::Implementation::availableGPUDevices(size_t memoryRequired) {
auto *llama = constructDefaultLlama();
if (llama) { return llama->availableGPUDevices(memoryRequired); }
return {};
std::vector<LLModel::GPUDevice> LLModel::Implementation::availableGPUDevices(size_t memoryRequired)
{
std::vector<LLModel::GPUDevice> devices;
#ifndef __APPLE__
static const std::string backends[] = {"kompute", "cuda"};
for (const auto &backend: backends) {
auto *llama = constructGlobalLlama(backend);
if (llama) {
auto backendDevs = llama->availableGPUDevices(memoryRequired);
devices.insert(devices.end(), backendDevs.begin(), backendDevs.end());
}
}
#endif
return devices;
}
int32_t LLModel::Implementation::maxContextLength(const std::string &modelPath) {
auto *llama = constructDefaultLlama();
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) {
auto *llama = constructDefaultLlama();
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) {
auto *llama = constructDefaultLlama();
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()
{
return cpu_supports_avx2();
}

View File

@@ -1,15 +1,21 @@
#ifndef LLMODEL_H
#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;
#define LLMODEL_MAX_PROMPT_BATCH 128
class Dlhandle;
@@ -17,15 +23,66 @@ class LLModel {
public:
using Token = int32_t;
class BadArchError: public std::runtime_error {
public:
BadArchError(std::string arch)
: runtime_error("Unsupported model architecture: " + arch)
, m_arch(std::move(arch))
{}
const std::string &arch() const noexcept { return m_arch; }
private:
std::string m_arch;
};
class MissingImplementationError: public std::runtime_error {
public:
using std::runtime_error::runtime_error;
};
class UnsupportedModelError: public std::runtime_error {
public:
using std::runtime_error::runtime_error;
};
struct GPUDevice {
const char *backend;
int index;
int type;
size_t heapSize;
std::string name;
std::string vendor;
GPUDevice(int index, int type, size_t heapSize, std::string name, std::string vendor):
index(index), type(type), heapSize(heapSize), name(std::move(name)), vendor(std::move(vendor)) {}
GPUDevice(const char *backend, int index, int type, size_t heapSize, std::string name, std::string vendor):
backend(backend), index(index), type(type), heapSize(heapSize), name(std::move(name)),
vendor(std::move(vendor)) {}
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(s_backendNames.begin(), s_backendNames.end(), [&name](const auto &entry) {
return name.starts_with(entry.second + ": ");
});
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> s_backendNames {
{"cpu", "CPU"}, {"metal", "Metal"}, {"cuda", "CUDA"}, {"kompute", "Vulkan"},
};
};
class Implementation {
@@ -37,7 +94,7 @@ public:
std::string_view modelType() const { return m_modelType; }
std::string_view buildVariant() const { return m_buildVariant; }
static LLModel *construct(const std::string &modelPath, std::string buildVariant = "auto", int n_ctx = 2048);
static LLModel *construct(const std::string &modelPath, const std::string &backend = "auto", int n_ctx = 2048);
static std::vector<GPUDevice> availableGPUDevices(size_t memoryRequired = 0);
static int32_t maxContextLength(const std::string &modelPath);
static int32_t layerCount(const std::string &modelPath);
@@ -45,15 +102,18 @@ public:
static void setImplementationsSearchPath(const std::string &path);
static const std::string &implementationsSearchPath();
static bool hasSupportedCPU();
// 0 for no, 1 for yes, -1 for non-x86_64
static int cpuSupportsAVX2();
private:
Implementation(Dlhandle &&);
static const std::vector<Implementation> &implementationList();
static const Implementation *implementation(const char *fname, const std::string &buildVariant);
static LLModel *constructDefaultLlama();
static LLModel *constructGlobalLlama(const std::optional<std::string> &backend = std::nullopt);
bool (*m_magicMatch)(const char *fname);
char *(*m_getFileArch)(const char *fname);
bool (*m_isArchSupported)(const char *arch);
LLModel *(*m_construct)();
std::string_view m_modelType;
@@ -144,8 +204,9 @@ public:
return false;
}
virtual bool hasGPUDevice() { return false; }
virtual bool usingGPUDevice() { return false; }
virtual bool usingGPUDevice() const { return false; }
virtual const char *backendName() const { return "cpu"; }
virtual const char *gpuDeviceName() const { return nullptr; }
void setProgressCallback(ProgressCallback callback) { m_progressCallback = callback; }

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;
@@ -31,26 +39,23 @@ static void llmodel_set_error(const char **errptr, const char *message) {
}
}
llmodel_model llmodel_model_create2(const char *model_path, const char *build_variant, 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, build_variant);
llModel = LLModel::Implementation::construct(model_path, backend);
} catch (const std::exception& e) {
llmodel_set_error(error, e.what());
return nullptr;
}
if (!llModel) {
llmodel_set_error(error, "Model format not supported (no matching implementation found)");
return nullptr;
}
auto wrapper = new LLModelWrapper;
wrapper->llModel = llModel;
return wrapper;
}
void llmodel_model_destroy(llmodel_model model) {
void llmodel_model_destroy(llmodel_model model)
{
delete static_cast<LLModelWrapper *>(model);
}
@@ -253,6 +258,7 @@ struct llmodel_gpu_device *llmodel_available_gpu_devices(size_t memoryRequired,
for (unsigned i = 0; i < devices.size(); i++) {
const auto &dev = devices[i];
auto &cdev = c_devices[i];
cdev.backend = dev.backend;
cdev.index = dev.index;
cdev.type = dev.type;
cdev.heapSize = dev.heapSize;
@@ -281,8 +287,14 @@ 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 char *llmodel_model_backend_name(llmodel_model model)
{
auto *wrapper = static_cast<LLModelWrapper *>(model);
return wrapper->llModel->hasGPUDevice();
const auto *wrapper = static_cast<LLModelWrapper *>(model);
return wrapper->llModel->backendName();
}
const char *llmodel_model_gpu_device_name(llmodel_model model)
{
const auto *wrapper = static_cast<LLModelWrapper *>(model);
return wrapper->llModel->gpuDeviceName();
}

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))
@@ -48,6 +48,7 @@ struct llmodel_prompt_context {
};
struct llmodel_gpu_device {
const char * backend;
int index;
int type; // same as VkPhysicalDeviceType
size_t heapSize;
@@ -86,7 +87,7 @@ typedef bool (*llmodel_recalculate_callback)(bool is_recalculating);
* Embedding cancellation callback for use with llmodel_embed.
* @param batch_sizes The number of tokens in each batch that will be embedded.
* @param n_batch The number of batches that will be embedded.
* @param backend The backend that will be used for embedding. One of "cpu", "kompute", or "metal".
* @param backend The backend that will be used for embedding. One of "cpu", "kompute", "cuda", or "metal".
* @return True to cancel llmodel_embed, false to continue.
*/
typedef bool (*llmodel_emb_cancel_callback)(unsigned *batch_sizes, unsigned n_batch, const char *backend);
@@ -103,11 +104,11 @@ DEPRECATED llmodel_model llmodel_model_create(const char *model_path);
* Create a llmodel instance.
* Recognises correct model type from file at model_path
* @param model_path A string representing the path to the model file; will only be used to detect model type.
* @param build_variant A string representing the implementation to use (auto, default, avxonly, ...),
* @param backend A string representing the implementation to use. One of 'auto', 'cpu', 'metal', 'kompute', or 'cuda'.
* @param error A pointer to a string; will only be set on error.
* @return A pointer to the llmodel_model instance; NULL on error.
*/
llmodel_model llmodel_model_create2(const char *model_path, const char *build_variant, const char **error);
llmodel_model llmodel_model_create2(const char *model_path, const char *backend, const char **error);
/**
* Destroy a llmodel instance.
@@ -291,9 +292,14 @@ 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.
* @return The name of the llama.cpp backend currently in use. One of "cpu", "kompute", or "metal".
*/
bool llmodel_has_gpu_device(llmodel_model model);
const char *llmodel_model_backend_name(llmodel_model model);
/**
* @return The name of the GPU device currently in use, or NULL for backends other than Kompute.
*/
const char *llmodel_model_gpu_device_name(llmodel_model model);
#ifdef __cplusplus
}

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
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dotnet_naming_style.camel_case_style.capitalization = camel_case
# Local functions are PascalCase
dotnet_naming_rule.local_functions_should_be_pascal_case.severity = suggestion
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dotnet_naming_style.local_function_style.capitalization = pascal_case
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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
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dotnet_diagnostic.IDE0043.severity = warning
# IDE0044: Make field readonly
dotnet_diagnostic.IDE0044.severity = warning
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#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
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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
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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);
}
}

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@@ -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;
}
}

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@@ -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);
}
}

View File

@@ -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>

View File

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

View File

@@ -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;
}
}

View File

@@ -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; }
}

View File

@@ -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;
}
}

View File

@@ -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

View File

@@ -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/

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@@ -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
```

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@@ -1,106 +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, 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,
lambda_prompt,
lambda_response,
lambda_recalculate,
prompt_context );
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

@@ -1,18 +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, 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

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@@ -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
}

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