diff --git a/.github/workflows/build.yml b/.github/workflows/build.yml index c02dd6a81..6841ba589 100644 --- a/.github/workflows/build.yml +++ b/.github/workflows/build.yml @@ -10,10 +10,10 @@ on: push: branches: - master - paths: ['.github/workflows/build.yml', '**/CMakeLists.txt', '**/Makefile', '**/*.h', '**/*.hpp', '**/*.c', '**/*.cpp', '**/*.cu', '**/*.cuh', '**/*.swift', '**/*.m', '**/*.metal'] + paths: ['.github/workflows/build.yml', '**/CMakeLists.txt', '**/Makefile', '**/*.h', '**/*.hpp', '**/*.c', '**/*.cpp', '**/*.cu', '**/*.cuh', '**/*.swift', '**/*.m', '**/*.metal', '**/*.comp'] pull_request: types: [opened, synchronize, reopened] - paths: ['.github/workflows/build.yml', '**/CMakeLists.txt', '**/Makefile', '**/*.h', '**/*.hpp', '**/*.c', '**/*.cpp', '**/*.cu', '**/*.cuh', '**/*.swift', '**/*.m', '**/*.metal'] + paths: ['.github/workflows/build.yml', '**/CMakeLists.txt', '**/Makefile', '**/*.h', '**/*.hpp', '**/*.c', '**/*.cpp', '**/*.cu', '**/*.cuh', '**/*.swift', '**/*.m', '**/*.metal', '**/*.comp'] concurrency: group: ${{ github.workflow }}-${{ github.head_ref && github.ref || github.run_id }} @@ -59,16 +59,14 @@ jobs: id: cmake_build run: | sysctl -a - mkdir build - cd build - cmake .. \ + cmake -B build \ -DCMAKE_BUILD_RPATH="@loader_path" \ -DLLAMA_FATAL_WARNINGS=ON \ -DLLAMA_CURL=ON \ -DGGML_METAL_USE_BF16=ON \ -DGGML_METAL_EMBED_LIBRARY=ON \ -DGGML_RPC=ON - cmake --build . --config Release -j $(sysctl -n hw.logicalcpu) + cmake --build build --config Release -j $(sysctl -n hw.logicalcpu) - name: Test id: cmake_test @@ -199,13 +197,11 @@ jobs: - name: Build id: cmake_build run: | - mkdir build - cd build - cmake .. \ + cmake -B build \ -DLLAMA_FATAL_WARNINGS=ON \ -DLLAMA_CURL=ON \ -DGGML_RPC=ON - cmake --build . --config Release -j $(nproc) + cmake --build build --config Release -j $(nproc) - name: Test id: cmake_test @@ -283,26 +279,52 @@ jobs: id: cmake_build if: ${{ matrix.sanitizer != 'THREAD' }} run: | - mkdir build - cd build - cmake .. \ + cmake -B build \ -DLLAMA_FATAL_WARNINGS=ON \ -DLLAMA_SANITIZE_${{ matrix.sanitizer }}=ON \ -DCMAKE_BUILD_TYPE=${{ matrix.build_type }} - cmake --build . --config ${{ matrix.build_type }} -j $(nproc) + cmake --build build --config ${{ matrix.build_type }} -j $(nproc) - name: Build (no OpenMP) id: cmake_build_no_openmp if: ${{ matrix.sanitizer == 'THREAD' }} run: | - mkdir build - cd build - cmake .. \ + cmake -B build \ -DLLAMA_FATAL_WARNINGS=ON \ -DLLAMA_SANITIZE_${{ matrix.sanitizer }}=ON \ -DCMAKE_BUILD_TYPE=${{ matrix.build_type }} \ -DGGML_OPENMP=OFF - cmake --build . --config ${{ matrix.build_type }} -j $(nproc) + cmake --build build --config ${{ matrix.build_type }} -j $(nproc) + + - name: Test + id: cmake_test + run: | + cd build + ctest -L main --verbose --timeout 900 + + ubuntu-latest-llguidance: + runs-on: ubuntu-latest + + steps: + - name: Clone + id: checkout + uses: actions/checkout@v4 + + - name: Dependencies + id: depends + run: | + sudo apt-get update + sudo apt-get install build-essential + + - name: Build + id: cmake_build + run: | + mkdir build + cd build + cmake .. \ + -DLLAMA_FATAL_WARNINGS=ON \ + -DLLAMA_LLGUIDANCE=ON + cmake --build . --config Release -j $(nproc) - name: Test id: cmake_test @@ -335,11 +357,9 @@ jobs: - name: Build id: cmake_build run: | - mkdir build - cd build - cmake .. \ + cmake -B build \ -DGGML_RPC=ON - cmake --build . --config Release -j $(nproc) + cmake --build build --config Release -j $(nproc) - name: Test id: cmake_test @@ -372,11 +392,9 @@ jobs: - name: Build id: cmake_build run: | - mkdir build - cd build - cmake .. \ + cmake -B build \ -DGGML_VULKAN=ON - cmake --build . --config Release -j $(nproc) + cmake --build build --config Release -j $(nproc) - name: Test id: cmake_test @@ -493,13 +511,11 @@ jobs: id: cmake_build run: | source /opt/intel/oneapi/setvars.sh - mkdir build - cd build - cmake .. \ + cmake -B build \ -DGGML_SYCL=ON \ -DCMAKE_C_COMPILER=icx \ -DCMAKE_CXX_COMPILER=icpx - cmake --build . --config Release -j $(nproc) + cmake --build build --config Release -j $(nproc) ubuntu-22-cmake-sycl-fp16: runs-on: ubuntu-22.04 @@ -543,14 +559,12 @@ jobs: id: cmake_build run: | source /opt/intel/oneapi/setvars.sh - mkdir build - cd build - cmake .. \ + cmake -B build \ -DGGML_SYCL=ON \ -DCMAKE_C_COMPILER=icx \ -DCMAKE_CXX_COMPILER=icpx \ -DGGML_SYCL_F16=ON - cmake --build . --config Release -j $(nproc) + cmake --build build --config Release -j $(nproc) macOS-latest-cmake-ios: runs-on: macos-latest @@ -576,9 +590,7 @@ jobs: id: cmake_build run: | sysctl -a - mkdir build - cd build - cmake -G Xcode .. \ + cmake -B build -G Xcode \ -DGGML_METAL_USE_BF16=ON \ -DGGML_METAL_EMBED_LIBRARY=ON \ -DLLAMA_BUILD_EXAMPLES=OFF \ @@ -587,7 +599,7 @@ jobs: -DCMAKE_SYSTEM_NAME=iOS \ -DCMAKE_OSX_DEPLOYMENT_TARGET=14.0 \ -DCMAKE_XCODE_ATTRIBUTE_DEVELOPMENT_TEAM=ggml - cmake --build . --config Release -j $(sysctl -n hw.logicalcpu) -- CODE_SIGNING_ALLOWED=NO + cmake --build build --config Release -j $(sysctl -n hw.logicalcpu) -- CODE_SIGNING_ALLOWED=NO macOS-latest-cmake-tvos: runs-on: macos-latest @@ -613,9 +625,7 @@ jobs: id: cmake_build run: | sysctl -a - mkdir build - cd build - cmake -G Xcode .. \ + cmake -B build -G Xcode \ -DGGML_METAL_USE_BF16=ON \ -DGGML_METAL_EMBED_LIBRARY=ON \ -DLLAMA_BUILD_EXAMPLES=OFF \ @@ -624,7 +634,7 @@ jobs: -DCMAKE_SYSTEM_NAME=tvOS \ -DCMAKE_OSX_DEPLOYMENT_TARGET=14.0 \ -DCMAKE_XCODE_ATTRIBUTE_DEVELOPMENT_TEAM=ggml - cmake --build . --config Release -j $(sysctl -n hw.logicalcpu) -- CODE_SIGNING_ALLOWED=NO + cmake --build build --config Release -j $(sysctl -n hw.logicalcpu) -- CODE_SIGNING_ALLOWED=NO macOS-latest-swift: runs-on: macos-latest @@ -654,17 +664,15 @@ jobs: id: cmake_build run: | sysctl -a - mkdir build - cd build - cmake -G Xcode .. \ + cmake -B build -G Xcode \ -DGGML_METAL_USE_BF16=ON \ -DGGML_METAL_EMBED_LIBRARY=ON \ -DLLAMA_BUILD_EXAMPLES=OFF \ -DLLAMA_BUILD_TESTS=OFF \ -DLLAMA_BUILD_SERVER=OFF \ -DCMAKE_OSX_ARCHITECTURES="arm64;x86_64" - cmake --build . --config Release -j $(sysctl -n hw.logicalcpu) - sudo cmake --install . --config Release + cmake --build build --config Release -j $(sysctl -n hw.logicalcpu) + sudo cmake --install build --config Release - name: xcodebuild for swift package id: xcodebuild @@ -689,6 +697,7 @@ jobs: uses: hendrikmuhs/ccache-action@v1.2.16 with: key: windows-msys2 + variant: sccache evict-old-files: 1d - name: Setup ${{ matrix.sys }} @@ -763,6 +772,7 @@ jobs: uses: hendrikmuhs/ccache-action@v1.2.16 with: key: windows-latest-cmake-${{ matrix.build }} + variant: sccache evict-old-files: 1d - name: Clone Kompute submodule @@ -804,21 +814,19 @@ jobs: run: | git clone https://github.com/KhronosGroup/OpenCL-Headers cd OpenCL-Headers - mkdir build && cd build - cmake .. ` + cmake -B build ` -DBUILD_TESTING=OFF ` -DOPENCL_HEADERS_BUILD_TESTING=OFF ` -DOPENCL_HEADERS_BUILD_CXX_TESTS=OFF ` -DCMAKE_INSTALL_PREFIX="$env:RUNNER_TEMP/opencl-arm64-release" - cmake --build . --target install + cmake --build build --target install git clone https://github.com/KhronosGroup/OpenCL-ICD-Loader cd OpenCL-ICD-Loader - mkdir build-arm64-release && cd build-arm64-release - cmake .. ` + cmake -B build-arm64-release ` -A arm64 ` -DCMAKE_PREFIX_PATH="$env:RUNNER_TEMP/opencl-arm64-release" ` -DCMAKE_INSTALL_PREFIX="$env:RUNNER_TEMP/opencl-arm64-release" - cmake --build . --target install --config release + cmake --build build-arm64-release --target install --config release - name: Build id: cmake_build @@ -949,6 +957,7 @@ jobs: uses: hendrikmuhs/ccache-action@v1.2.16 with: key: ${{ github.job }}-${{ matrix.cuda }}-${{ matrix.build }} + variant: sccache evict-old-files: 1d - name: Install Cuda Toolkit 11.7 @@ -1090,6 +1099,7 @@ jobs: uses: hendrikmuhs/ccache-action@v1.2.16 with: key: windows-latest-cmake-sycl + variant: sccache evict-old-files: 1d - name: Install @@ -1278,9 +1288,7 @@ jobs: id: cmake_build run: | sysctl -a - mkdir build - cd build - cmake -G Xcode .. \ + cmake -B build -G Xcode \ -DGGML_METAL_USE_BF16=ON \ -DGGML_METAL_EMBED_LIBRARY=ON \ -DLLAMA_BUILD_EXAMPLES=OFF \ @@ -1289,8 +1297,8 @@ jobs: -DCMAKE_SYSTEM_NAME=iOS \ -DCMAKE_OSX_DEPLOYMENT_TARGET=14.0 \ -DCMAKE_XCODE_ATTRIBUTE_DEVELOPMENT_TEAM=ggml - cmake --build . --config Release -j $(sysctl -n hw.logicalcpu) -- CODE_SIGNING_ALLOWED=NO - sudo cmake --install . --config Release + cmake --build build --config Release -j $(sysctl -n hw.logicalcpu) -- CODE_SIGNING_ALLOWED=NO + sudo cmake --install build --config Release - name: xcodebuild for swift package id: xcodebuild diff --git a/.github/workflows/close-issue.yml b/.github/workflows/close-issue.yml index f63860d14..276a217d4 100644 --- a/.github/workflows/close-issue.yml +++ b/.github/workflows/close-issue.yml @@ -17,7 +17,7 @@ jobs: steps: - uses: actions/stale@v5 with: - exempt-issue-labels: "refactor,help wanted,good first issue,research,bug" + exempt-issue-labels: "refactor,help wanted,good first issue,research,bug,roadmap" days-before-issue-stale: 30 days-before-issue-close: 14 stale-issue-label: "stale" diff --git a/.github/workflows/server.yml b/.github/workflows/server.yml index 0cbc3d640..3a29107d0 100644 --- a/.github/workflows/server.yml +++ b/.github/workflows/server.yml @@ -81,13 +81,36 @@ jobs: with: node-version: '22.11.0' + - name: WebUI - Install dependencies + id: webui_lint + run: | + cd examples/server/webui + npm ci + + - name: WebUI - Check code format + id: webui_format + run: | + git config --global --add safe.directory $(realpath .) + cd examples/server/webui + git status + + npm run format + git status + modified_files="$(git status -s)" + echo "Modified files: ${modified_files}" + if [ -n "${modified_files}" ]; then + echo "Files do not follow coding style. To fix: npm run format" + echo "${modified_files}" + exit 1 + fi + - name: Verify bundled index.html id: verify_server_index_html run: | git config --global --add safe.directory $(realpath .) cd examples/server/webui git status - npm ci + npm run build git status modified_files="$(git status -s)" diff --git a/AUTHORS b/AUTHORS index 2eb60806a..6796b2941 100644 --- a/AUTHORS +++ b/AUTHORS @@ -1,4 +1,4 @@ -# date: Thu Nov 28 20:46:15 EET 2024 +# date: Tue Feb 4 13:04:05 EET 2025 # this file is auto-generated by scripts/gen-authors.sh 0cc4m @@ -20,6 +20,8 @@ Adithya Balaji AdithyanI Adrian Adrian Hesketh +Adrien Gallouët +Adrien Gallouët Ahmad Tameem <113388789+Tameem-10xE@users.noreply.github.com> Ahmet Zeer AidanBeltonS <87009434+AidanBeltonS@users.noreply.github.com> @@ -55,6 +57,7 @@ Ananta Bastola Anas Ahouzi <112881240+aahouzi@users.noreply.github.com> András Salamon Andreas (Andi) Kunar +Andreas Kieslinger <47689530+aendk@users.noreply.github.com> Andrei Andrew Canis Andrew Downing @@ -91,13 +94,17 @@ Ben Siraphob Ben Williams Benjamin Findley <39356821+Kartoffelsaft@users.noreply.github.com> Benjamin Lecaillon <84293038+blecaillon@users.noreply.github.com> +Benson Wong Bernat Vadell +Bernhard M. Wiedemann Bert Wagner +Billel Mokeddem Bingan <70050083+binganao@users.noreply.github.com> Bjarke Viksøe <164612031+bviksoe@users.noreply.github.com> Bodo Graumann Bono Lv Borislav Stanimirov +Borislav Stanimirov Branden Butler Brandon Squizzato <35474886+bsquizz@users.noreply.github.com> Brian @@ -117,6 +124,7 @@ Casey Primozic Casey Primozic CausalLM <148736309+CausalLM@users.noreply.github.com> Cebtenzzre +CentricStorm Chad Brewbaker Changyeon Kim Chao Jiang @@ -131,12 +139,15 @@ Chris Kuehl Christian Demsar Christian Demsar Christian Falch <875252+chrfalch@users.noreply.github.com> +Christian Kastner Christian Kögler Christian Köhnenkamp Christian Zhou-Zheng <59622928+christianazinn@users.noreply.github.com> +Christopher Nielsen <62156882+mascguy@users.noreply.github.com> Clark Saben <76020733+csaben@users.noreply.github.com> Clint Herron Conrad Kramer +Corentin REGAL CrispStrobe <154636388+CrispStrobe@users.noreply.github.com> Csaba Kecskemeti Cuong Trinh Manh @@ -176,6 +187,7 @@ Dibakar Gope Didzis Gosko Diego Devesa Diogo Teles Sant'Anna +Djip007 <3705339+Djip007@users.noreply.github.com> Djip007 Don Mahurin DooWoong Lee (David) @@ -193,6 +205,7 @@ Edward Taylor Elaine Elbios <141279586+Elbios@users.noreply.github.com> Elton Kola +Emreerdog <34742675+Emreerdog@users.noreply.github.com> Engininja2 <139037756+Engininja2@users.noreply.github.com> Equim Eric Curtin @@ -233,6 +246,7 @@ Fred Douglas <43351173+fredlas@users.noreply.github.com> Frederik Vogel Gabe Goodhart Gabe Goodhart +Gaetan Bisson GainLee Galunid Gary Linscott @@ -249,6 +263,7 @@ Guillaume "Vermeille" Sanchez Guillaume Wenzek Guoliang Hua <32868157+nbcsm@users.noreply.github.com> Guoteng <32697156+SolenoidWGT@users.noreply.github.com> +Guspan Tanadi <36249910+guspan-tanadi@users.noreply.github.com> Gustavo Rocha Dias <91472747+gustrd@users.noreply.github.com> Haggai Nuchi Halalaluyafail3 <55773281+Halalaluyafail3@users.noreply.github.com> @@ -259,11 +274,13 @@ Haoxiang Fei Harald Fernengel Hatsune Miku <129688334+at8u@users.noreply.github.com> HatsuneMikuUwU33 <173229399+HatsuneMikuUwU33@users.noreply.github.com> +Haus1 Henk Poley Henri Vasserman Henrik Forstén Herman Semenov Hesen Peng +HimariO Hoang Nguyen Hong Bo PENG Hongyu Ouyang <96765450+casavaca@users.noreply.github.com> @@ -280,6 +297,7 @@ Icecream95 Ido S IgnacioFDM Igor Okulist +Ihar Hrachyshka Ikko Eltociear Ashimine Ilya Kurdyukov <59548320+ilyakurdyukov@users.noreply.github.com> Ionoclast Laboratories @@ -289,12 +307,14 @@ Ivan Ivan Filipov <159561759+vanaka11@users.noreply.github.com> Ivan Komarov Ivan Stepanov +JFLFY2255 JH23X <165871467+JH23X@users.noreply.github.com> Jack Mousseau Jack Mousseau JackJollimore <130917767+JackJollimore@users.noreply.github.com> Jaeden Amero Jaemin Son +Jafar Uruç Jag Chadha Jakub N James A Capozzoli <157492257+jac-jim@users.noreply.github.com> @@ -315,6 +335,7 @@ Jeffrey Morgan Jeffrey Quesnelle Jeroen Mostert Jesse Jojo Johnson +Jett Janiak Jeximo Jhen-Jie Hong Jiahao Li @@ -343,6 +364,7 @@ Josh Ramer Joyce Juan Calderon-Perez <835733+gaby@users.noreply.github.com> Judd +Juk Armstrong <69222624+jukofyork@users.noreply.github.com> Julius Arkenberg Jun Hee Yoo Jun Jie <71215065+junnjiee16@users.noreply.github.com> @@ -357,6 +379,7 @@ Justine Tunney Juuso Alasuutari KASR Kamil Tomšík +Karol Kontny <82021046+kkontny@users.noreply.github.com> Karsten Weiss Karthick Karthik Kumar Viswanathan <195178+guilt@users.noreply.github.com> @@ -376,6 +399,7 @@ Kolen Cheung Konstantin Herud Konstantin Zhuravlyov Kunshang Ji +Kyle Bruene Kyle Liang Kyle Mistele Kylin <56434533+KyL0N@users.noreply.github.com> @@ -394,6 +418,7 @@ Liu Jia LoganDark Loïc Carrère LostRuins <39025047+LostRuins@users.noreply.github.com> +LostRuins Concedo <39025047+LostRuins@users.noreply.github.com> Luciano Luo Tian Lyle Dean @@ -423,6 +448,7 @@ MasterYi1024 <39848311+MasterYi1024@users.noreply.github.com> Mateusz Charytoniuk Matheus C. França Matheus Gabriel Alves Silva +Mathieu Baudier Mathieu Geli Mathieu Nayrolles Mathijs Henquet @@ -444,6 +470,7 @@ Meng, Hengyu Mengqing Cao Merrick Christensen Michael Coppola +Michael Engel Michael Francis Michael Hueschen Michael Kesper @@ -452,7 +479,9 @@ Michael Podvitskiy Michael Potter Michael de Gans Michaël de Vries +Michał Moskal Michał Tuszyński +Michelle Tan <41475767+MichelleTanPY@users.noreply.github.com> Mihai Mike Mikko Juola @@ -477,6 +506,7 @@ Neo Zhang <14088817+arthw@users.noreply.github.com> Neo Zhang Neo Zhang Jianyu Neuman Vong +NeverLucky <92274250+nvrxq@users.noreply.github.com> Nexes the Old <124105151+Nexesenex@users.noreply.github.com> Nexesenex <124105151+Nexesenex@users.noreply.github.com> Niall Coates <1349685+Niall-@users.noreply.github.com> @@ -484,11 +514,15 @@ Nicholai Tukanov Nico Bosshard Nicolai Weitkemper Nicolás Pérez +Nicolò Scipione Nigel Bosch +Nikita Sarychev <42014488+sARY77@users.noreply.github.com> Niklas Korz NikolaiLyssogor <59844691+NikolaiLyssogor@users.noreply.github.com> +Nikolaos Pothitos Nikolas <127742645+nneubacher@users.noreply.github.com> Nindaleth +Nuno OSecret <135510162+OLSecret@users.noreply.github.com> Oleksandr Nikitin Oleksii Maryshchenko @@ -504,6 +538,7 @@ Pavel Zloi Pavol Rusnak Paweł Wodnicki <151604+32bitmicro@users.noreply.github.com> Pedro Cuenca +Peter Peter Sugihara Phil H <5756783+phiharri@users.noreply.github.com> Philip Taron @@ -529,9 +564,12 @@ Rand Xie Randall Fitzgerald Random Fly Reinforce-II +Rémy Oudompheng Ren Xuancheng Rene Leonhardt <65483435+reneleonhardt@users.noreply.github.com> +Reza Kakhki RhinoDevel +Riccardo Orlando Riceball LEE Rich Dougherty Richard Kiss @@ -544,6 +582,8 @@ Riley Stewart Rinne Rinne Robert Brisita <986796+rbrisita@users.noreply.github.com> +Robert Collins +Robert Ormandi <52251610+ormandi@users.noreply.github.com> Robert Sung-wook Shin Robey Holderith Robyn @@ -559,7 +599,9 @@ Roni Ronny Brendel Ronsor Rowan Hart +Ruan <47767371+ruanych@users.noreply.github.com> Ruchira Hasaranga +Rudi Servo Ruixin Huang <18860020911@163.com> Rune <43761327+Rune-AI@users.noreply.github.com> RunningLeon @@ -623,12 +665,14 @@ Steven Roussey Steward Garcia <57494570+FSSRepo@users.noreply.github.com> StrangeBytesDev <141275258+StrangeBytesDev@users.noreply.github.com> Suaj Carrot <72162667+SuajCarrot@users.noreply.github.com> +Sukriti Sharma SuperUserNameMan Sutou Kouhei Tai Duc Nguyen Taikono-Himazin Tameem <113388789+AhmadTameem@users.noreply.github.com> Tamotsu Takahashi +Tei Home Thái Hoàng Tâm <75922889+RoyalHeart@users.noreply.github.com> Thatcher Chamberlin Theia Vogel @@ -640,6 +684,7 @@ Tim Miller Tim Wang Timmy Knight Timothy Cronin <40186632+4imothy@users.noreply.github.com> +Ting Lou Ting Lou Ting Sun Tobias Lütke @@ -661,6 +706,7 @@ Uzo Nweke Vaibhav Srivastav Val Kharitonov Valentin Konovalov +Valentin Mamedov <45292985+Inf1delis@users.noreply.github.com> Valentyn Bezshapkin <61702053+valentynbez@users.noreply.github.com> Vali Malinoiu <0x4139@gmail.com> Victor Nogueira @@ -673,13 +719,17 @@ Vladimir Malyutin Vladimir Zorin VoidIsVoid <343750470@qq.com> Volodymyr Vitvitskyi <72226+signalpillar@users.noreply.github.com> +Wang Qin <37098874+wangqin0@users.noreply.github.com> +Wang Ran (汪然) WangHaoranRobin <56047610+WangHaoranRobin@users.noreply.github.com> Weird Constructor Welby Seely Wentai Zhang WillCorticesAI <150854901+WillCorticesAI@users.noreply.github.com> William Tambellini +William Tambellini Willy Tarreau +Woof Dog <197125663+woof-dog@users.noreply.github.com> Wouter <9594229+DifferentialityDevelopment@users.noreply.github.com> Wu Jian Ping Wu Jian Ping @@ -692,6 +742,7 @@ Xie Yanbo Xingchen Song(宋星辰) Xinpeng Dou <81913537+Dou-Git@users.noreply.github.com> Xuan Son Nguyen +Xuan-Son Nguyen Yaiko Yann Follet <131855179+YannFollet@users.noreply.github.com> Yaroslav @@ -702,7 +753,9 @@ Yoshi Suhara Yoshi Suhara Younes Belkada <49240599+younesbelkada@users.noreply.github.com> Yueh-Po Peng <94939112+y10ab1@users.noreply.github.com> +Yüg Yui +Yun Dou Yuri Khrustalev Yusuf Kağan Hanoğlu Yuval Peled <31162840+Yuval-Peled@users.noreply.github.com> @@ -714,18 +767,23 @@ Zhang Peiyuan Zheng.Deng <32841220+dengzheng-cloud@users.noreply.github.com> Zhenwei Jin <109658203+kylo5aby@users.noreply.github.com> Zhiyuan Li +Zhiyuan Li ZhouYuChen Ziad Ben Hadj-Alouane Ziang Wu <97337387+ZiangWu-77@users.noreply.github.com> Zsapi a-n-n-a-l-e-e <150648636+a-n-n-a-l-e-e@users.noreply.github.com> +a3sh <38979186+A3shTnT@users.noreply.github.com> adel boussaken afrideva <95653597+afrideva@users.noreply.github.com> +ag2s20150909 <19373730+ag2s20150909@users.noreply.github.com> agray3 akawrykow <142945436+akawrykow@users.noreply.github.com> +alek3y <44779186+alek3y@users.noreply.github.com> alexpinel <93524949+alexpinel@users.noreply.github.com> alonfaraj alwqx +amd-dwang amd-lalithnc amritahs-ibm andrijdavid @@ -737,6 +795,7 @@ arch-btw <57669023+arch-btw@users.noreply.github.com> arcrank ardfork <134447697+ardfork@users.noreply.github.com> arlo-phoenix <140345165+arlo-phoenix@users.noreply.github.com> +aryantandon01 <80969509+aryantandon01@users.noreply.github.com> at8u <129688334+at8u@users.noreply.github.com> automaticcat awatuna <23447591+awatuna@users.noreply.github.com> @@ -751,12 +810,14 @@ bryanSwk <93190252+bryanSwk@users.noreply.github.com> bsilvereagle bssrdf byte-6174 <88070277+byte-6174@users.noreply.github.com> +cduk <19917266+cduk@users.noreply.github.com> cebtenzzre chaihahaha chiranko <96988916+chiranko@users.noreply.github.com> clibdev <52199778+clibdev@users.noreply.github.com> clyang cocktailpeanut <121128867+cocktailpeanut@users.noreply.github.com> +codezjx coezbek comex compilade <113953597+compilade@users.noreply.github.com> @@ -780,14 +841,17 @@ drbh ds5t5 <145942675+ds5t5@users.noreply.github.com> dylan eastriver +ebraminio ebraminio eiery <19350831+eiery@users.noreply.github.com> eric8607242 fairydreaming <166155368+fairydreaming@users.noreply.github.com> fengerhu1 <2748250768@qq.com> +fj-y-saito <85871716+fj-y-saito@users.noreply.github.com> fraxy-v <65565042+fraxy-v@users.noreply.github.com> github-actions[bot] gliptic +gn64 goerch grahameth <96447521+grahameth@users.noreply.github.com> gtygo @@ -812,10 +876,12 @@ icppWorld <124377669+icppWorld@users.noreply.github.com> igarnier intelmatt <61025942+intelmatt@users.noreply.github.com> iohub +issixx <46835150+issixx@users.noreply.github.com> jacobi petrucciani <8117202+jpetrucciani@users.noreply.github.com> jaime-m-p <167997752+jaime-m-p@users.noreply.github.com> jameswu2014 <545426914@qq.com> jdomke <28772296+jdomke@users.noreply.github.com> +jiahao su jiez <373447296@qq.com> jneem joecryptotoo <80373433+joecryptotoo@users.noreply.github.com> @@ -828,6 +894,7 @@ junchao-loongson <68935141+junchao-loongson@users.noreply.github.com> jwj7140 <32943891+jwj7140@users.noreply.github.com> k.h.lai kaizau +kallewoof kalomaze <66376113+kalomaze@users.noreply.github.com> kang katsu560 <118887472+katsu560@users.noreply.github.com> @@ -835,6 +902,7 @@ kchro3 <62481661+kchro3@users.noreply.github.com> khimaros kiltyj klosax <131523366+klosax@users.noreply.github.com> +krystiancha kunal-vaishnavi <115581922+kunal-vaishnavi@users.noreply.github.com> kunnis kuronekosaiko @@ -847,6 +915,8 @@ ldwang le.chang leejet leo-pony +lexasub +lhez limitedAtonement liuwei-git <14815172+liuwei-git@users.noreply.github.com> lon <114724657+longregen@users.noreply.github.com> @@ -855,10 +925,13 @@ ltoniazzi <61414566+ltoniazzi@users.noreply.github.com> luoyu-intel m3ndax maddes8cht <55592906+maddes8cht@users.noreply.github.com> +mahorozte <41834471+mahorozte@users.noreply.github.com> makomk manikbhandari maor-ps <154728172+maor-ps@users.noreply.github.com> +mashdragon <122402293+mashdragon@users.noreply.github.com> matiaslin <45382001+matiaslin@users.noreply.github.com> +matt23654 matteo mdrokz mgroeber9110 <45620825+mgroeber9110@users.noreply.github.com> @@ -868,6 +941,7 @@ mmyjona momonga <115213907+mmnga@users.noreply.github.com> momonga <146910567+mmngays@users.noreply.github.com> moritzbrantner <31051084+moritzbrantner@users.noreply.github.com> +musoles <135031143+musoles@users.noreply.github.com> mzcu nanahi <130121847+na-na-hi@users.noreply.github.com> ngc92 <7938269+ngc92@users.noreply.github.com> @@ -885,6 +959,7 @@ oobabooga <112222186+oobabooga@users.noreply.github.com> opparco ostix360 <55257054+ostix360@users.noreply.github.com> pculliton +peidaqi pengxin99 perserk piDack <104877312+piDack@users.noreply.github.com> @@ -892,10 +967,12 @@ pmysl postmasters pudepiedj qingfengfenga <41416092+qingfengfenga@users.noreply.github.com> +qingy1337 qouoq qunash rabidcopy rankaiyx +redbeard rhjdvsgsgks <26178113+rhjdvsgsgks@users.noreply.github.com> rhuddleston rimoliga <53384203+rimoliga@users.noreply.github.com> @@ -912,6 +989,7 @@ sjxx <63994076+ylsdamxssjxxdd@users.noreply.github.com> slaren <2141330+slaren@users.noreply.github.com> slaren snadampal <87143774+snadampal@users.noreply.github.com> +someone13574 <81528246+someone13574@users.noreply.github.com> standby24x7 staviq stduhpf @@ -931,6 +1009,7 @@ uint256_t uint256_t unbounded uvos +uvos valiray <133289098+valiray@users.noreply.github.com> vb vik @@ -951,6 +1030,7 @@ xaedes xctan xloem <0xloem@gmail.com> yangli2 +ymcki <84055651+ymcki@users.noreply.github.com> yuiseki yuri@FreeBSD zakkor @@ -963,4 +1043,5 @@ zrm 杨朱 · Kiki 源文雨 <41315874+fumiama@users.noreply.github.com> 蕭澧邦 <45505768+shou692199@users.noreply.github.com> +谢乃闻 Нияз Гарифзянов <112617865+garrnizon@users.noreply.github.com> diff --git a/CMakeLists.txt b/CMakeLists.txt index 4c62d1788..7b2a1845e 100644 --- a/CMakeLists.txt +++ b/CMakeLists.txt @@ -80,6 +80,7 @@ option(LLAMA_BUILD_SERVER "llama: build server example" ${LLAMA_STANDALONE}) # 3rd party libs option(LLAMA_CURL "llama: use libcurl to download model from an URL" OFF) +option(LLAMA_LLGUIDANCE "llama-common: include LLGuidance library for structured output in common utils" OFF) # Required for relocatable CMake package include(${CMAKE_CURRENT_SOURCE_DIR}/cmake/build-info.cmake) @@ -232,4 +233,4 @@ configure_file(cmake/llama.pc.in @ONLY) install(FILES "${CMAKE_CURRENT_BINARY_DIR}/llama.pc" - DESTINATION lib/pkgconfig) + DESTINATION ${CMAKE_INSTALL_LIBDIR}/pkgconfig) diff --git a/Makefile b/Makefile index ef152d246..dc3de3cb1 100644 --- a/Makefile +++ b/Makefile @@ -596,7 +596,7 @@ ifdef GGML_RPC OBJ_GGML_EXT += ggml/src/ggml-rpc.o endif # GGML_RPC -OBJ_CUDA_TMPL = $(patsubst %.cu,%.o,$(wildcard ggml/src/ggml-cuda/template-instances/fattn-wmma*.cu)) +OBJ_CUDA_TMPL = $(patsubst %.cu,%.o,$(wildcard ggml/src/ggml-cuda/template-instances/fattn-mma*.cu)) OBJ_CUDA_TMPL += $(patsubst %.cu,%.o,$(wildcard ggml/src/ggml-cuda/template-instances/mmq*.cu)) ifdef GGML_CUDA_FA_ALL_QUANTS diff --git a/README.md b/README.md index d40309875..11f3d0286 100644 --- a/README.md +++ b/README.md @@ -96,7 +96,7 @@ Instructions for adding support for new models: [HOWTO-add-model.md](docs/develo - [x] [Bitnet b1.58 models](https://huggingface.co/1bitLLM) - [x] [Flan T5](https://huggingface.co/models?search=flan-t5) - [x] [Open Elm models](https://huggingface.co/collections/apple/openelm-instruct-models-6619ad295d7ae9f868b759ca) -- [x] [ChatGLM3-6b](https://huggingface.co/THUDM/chatglm3-6b) + [ChatGLM4-9b](https://huggingface.co/THUDM/glm-4-9b) +- [x] [ChatGLM3-6b](https://huggingface.co/THUDM/chatglm3-6b) + [ChatGLM4-9b](https://huggingface.co/THUDM/glm-4-9b) + [GLMEdge-1.5b](https://huggingface.co/THUDM/glm-edge-1.5b-chat) + [GLMEdge-4b](https://huggingface.co/THUDM/glm-edge-4b-chat) - [x] [SmolLM](https://huggingface.co/collections/HuggingFaceTB/smollm-6695016cad7167254ce15966) - [x] [EXAONE-3.0-7.8B-Instruct](https://huggingface.co/LGAI-EXAONE/EXAONE-3.0-7.8B-Instruct) - [x] [FalconMamba Models](https://huggingface.co/collections/tiiuae/falconmamba-7b-66b9a580324dd1598b0f6d4a) @@ -117,6 +117,7 @@ Instructions for adding support for new models: [HOWTO-add-model.md](docs/develo - [x] [Mini CPM](https://huggingface.co/models?search=MiniCPM) - [x] [Moondream](https://huggingface.co/vikhyatk/moondream2) - [x] [Bunny](https://github.com/BAAI-DCAI/Bunny) +- [x] [GLM-EDGE](https://huggingface.co/models?search=glm-edge) - [x] [Qwen2-VL](https://huggingface.co/collections/Qwen/qwen2-vl-66cee7455501d7126940800d) @@ -135,6 +136,7 @@ Instructions for adding support for new models: [HOWTO-add-model.md](docs/develo - Rust (more features): [edgenai/llama_cpp-rs](https://github.com/edgenai/llama_cpp-rs) - Rust (nicer API): [mdrokz/rust-llama.cpp](https://github.com/mdrokz/rust-llama.cpp) - Rust (more direct bindings): [utilityai/llama-cpp-rs](https://github.com/utilityai/llama-cpp-rs) +- Rust (automated build from crates.io): [ShelbyJenkins/llm_client](https://github.com/ShelbyJenkins/llm_client) - C#/.NET: [SciSharp/LLamaSharp](https://github.com/SciSharp/LLamaSharp) - C#/VB.NET (more features - community license): [LM-Kit.NET](https://docs.lm-kit.com/lm-kit-net/index.html) - Scala 3: [donderom/llm4s](https://github.com/donderom/llm4s) @@ -187,6 +189,7 @@ Instructions for adding support for new models: [HOWTO-add-model.md](docs/develo - [ramalama](https://github.com/containers/ramalama) (MIT) - [semperai/amica](https://github.com/semperai/amica) (MIT) - [withcatai/catai](https://github.com/withcatai/catai) (MIT) +- [Autopen](https://github.com/blackhole89/autopen) (GPL) diff --git a/cmake/llama.pc.in b/cmake/llama.pc.in index 0b2b6bcfa..6fb58b5f6 100644 --- a/cmake/llama.pc.in +++ b/cmake/llama.pc.in @@ -1,10 +1,10 @@ prefix=@CMAKE_INSTALL_PREFIX@ -exec_prefix=${prefix} -libdir=${exec_prefix}/lib -includedir=${prefix}/include +exec_prefix=@CMAKE_INSTALL_PREFIX@ +libdir=@CMAKE_INSTALL_FULL_LIBDIR@ +includedir=@CMAKE_INSTALL_FULL_INCLUDEDIR@ Name: llama Description: Port of Facebook's LLaMA model in C/C++ -Version: @PROJECT_VERSION@ -Libs: -L${libdir} -lggml -lggml-base -lllama +Version: @LLAMA_INSTALL_VERSION@ +Libs: -L${libdir} -lggml -lggml-base -lllama Cflags: -I${includedir} diff --git a/common/CMakeLists.txt b/common/CMakeLists.txt index 72f0915c1..e61015d2a 100644 --- a/common/CMakeLists.txt +++ b/common/CMakeLists.txt @@ -65,6 +65,7 @@ add_library(${TARGET} STATIC console.h json-schema-to-grammar.cpp json.hpp + llguidance.cpp log.cpp log.h minja.hpp @@ -91,6 +92,33 @@ if (LLAMA_CURL) set(LLAMA_COMMON_EXTRA_LIBS ${LLAMA_COMMON_EXTRA_LIBS} ${CURL_LIBRARY}) endif () +if (LLAMA_LLGUIDANCE) + include(ExternalProject) + set(LLGUIDANCE_SRC ${CMAKE_BINARY_DIR}/llguidance/source) + set(LLGUIDANCE_PATH ${LLGUIDANCE_SRC}/target/release) + ExternalProject_Add(llguidance_ext + GIT_REPOSITORY https://github.com/guidance-ai/llguidance + # v0.6.12: + GIT_TAG ced1c9023d47ec194fa977932d35ce65c2ebfc09 + PREFIX ${CMAKE_BINARY_DIR}/llguidance + SOURCE_DIR ${LLGUIDANCE_SRC} + BUILD_IN_SOURCE TRUE + CONFIGURE_COMMAND "" + BUILD_COMMAND cargo build --release + INSTALL_COMMAND "" + BUILD_BYPRODUCTS ${LLGUIDANCE_PATH}/libllguidance.a ${LLGUIDANCE_PATH}/llguidance.h + UPDATE_COMMAND "" + ) + target_compile_definitions(${TARGET} PUBLIC LLAMA_USE_LLGUIDANCE) + + add_library(llguidance STATIC IMPORTED) + set_target_properties(llguidance PROPERTIES IMPORTED_LOCATION ${LLGUIDANCE_PATH}/libllguidance.a) + add_dependencies(llguidance llguidance_ext) + + target_include_directories(${TARGET} PRIVATE ${LLGUIDANCE_PATH}) + set(LLAMA_COMMON_EXTRA_LIBS ${LLAMA_COMMON_EXTRA_LIBS} llguidance) +endif () + target_include_directories(${TARGET} PUBLIC .) target_compile_features (${TARGET} PUBLIC cxx_std_17) target_link_libraries (${TARGET} PRIVATE ${LLAMA_COMMON_EXTRA_LIBS} PUBLIC llama Threads::Threads) diff --git a/common/arg.cpp b/common/arg.cpp index f5e9b294f..152f671ab 100644 --- a/common/arg.cpp +++ b/common/arg.cpp @@ -1465,15 +1465,28 @@ common_params_context common_params_parser_init(common_params & params, llama_ex {"--list-devices"}, "print list of available devices and exit", [](common_params &) { - printf("Available devices:\n"); + std::vector rpc_devices; + std::vector all_devices; for (size_t i = 0; i < ggml_backend_dev_count(); ++i) { auto * dev = ggml_backend_dev_get(i); if (ggml_backend_dev_type(dev) == GGML_BACKEND_DEVICE_TYPE_GPU) { - size_t free, total; - ggml_backend_dev_memory(dev, &free, &total); - printf(" %s: %s (%zu MiB, %zu MiB free)\n", ggml_backend_dev_name(dev), ggml_backend_dev_description(dev), total / 1024 / 1024, free / 1024 / 1024); + ggml_backend_reg_t reg = ggml_backend_dev_backend_reg(dev); + if (ggml_backend_reg_name(reg) == std::string("RPC")) { + rpc_devices.push_back(dev); + } else { + all_devices.push_back(dev); + } } } + // insert RPC devices in front + all_devices.insert(all_devices.begin(), rpc_devices.begin(), rpc_devices.end()); + printf("Available devices:\n"); + for (size_t i = 0; i < all_devices.size(); ++i) { + auto * dev = all_devices[i]; + size_t free, total; + ggml_backend_dev_memory(dev, &free, &total); + printf(" %s: %s (%zu MiB, %zu MiB free)\n", ggml_backend_dev_name(dev), ggml_backend_dev_description(dev), total / 1024 / 1024, free / 1024 / 1024); + } exit(0); } )); @@ -2311,5 +2324,47 @@ common_params_context common_params_parser_init(common_params & params, llama_ex } ).set_examples({LLAMA_EXAMPLE_TTS})); + add_opt(common_arg( + {"--embd-bge-small-en-default"}, + string_format("use default bge-small-en-v1.5 model (note: can download weights from the internet)"), + [](common_params & params) { + params.hf_repo = "ggml-org/bge-small-en-v1.5-Q8_0-GGUF"; + params.hf_file = "bge-small-en-v1.5-q8_0.gguf"; + params.pooling_type = LLAMA_POOLING_TYPE_NONE; + params.embd_normalize = 2; + params.n_ctx = 512; + params.verbose_prompt = true; + params.embedding = true; + } + ).set_examples({LLAMA_EXAMPLE_EMBEDDING, LLAMA_EXAMPLE_SERVER})); + + add_opt(common_arg( + {"--embd-e5-small-en-default"}, + string_format("use default e5-small-v2 model (note: can download weights from the internet)"), + [](common_params & params) { + params.hf_repo = "ggml-org/e5-small-v2-Q8_0-GGUF"; + params.hf_file = "e5-small-v2-q8_0.gguf"; + params.pooling_type = LLAMA_POOLING_TYPE_NONE; + params.embd_normalize = 2; + params.n_ctx = 512; + params.verbose_prompt = true; + params.embedding = true; + } + ).set_examples({LLAMA_EXAMPLE_EMBEDDING, LLAMA_EXAMPLE_SERVER})); + + add_opt(common_arg( + {"--embd-gte-small-default"}, + string_format("use default gte-small model (note: can download weights from the internet)"), + [](common_params & params) { + params.hf_repo = "ggml-org/gte-small-Q8_0-GGUF"; + params.hf_file = "gte-small-q8_0.gguf"; + params.pooling_type = LLAMA_POOLING_TYPE_NONE; + params.embd_normalize = 2; + params.n_ctx = 512; + params.verbose_prompt = true; + params.embedding = true; + } + ).set_examples({LLAMA_EXAMPLE_EMBEDDING, LLAMA_EXAMPLE_SERVER})); + return ctx_arg; } diff --git a/common/chat-template.hpp b/common/chat-template.hpp index 75ba5d938..0e88fb361 100644 --- a/common/chat-template.hpp +++ b/common/chat-template.hpp @@ -33,6 +33,29 @@ struct chat_template_caps { bool requires_typed_content = false; }; +struct chat_template_inputs { + nlohmann::ordered_json messages; + nlohmann::ordered_json tools; + bool add_generation_prompt = true; + nlohmann::ordered_json extra_context; + std::chrono::system_clock::time_point now = std::chrono::system_clock::now(); +}; + +struct chat_template_options { + bool apply_polyfills = true; + bool use_bos_token = true; + bool use_eos_token = true; + bool define_strftime_now = true; + + bool polyfill_tools = true; + bool polyfill_tool_call_examples = true; + bool polyfill_tool_calls = true; + bool polyfill_tool_responses = true; + bool polyfill_system_role = true; + bool polyfill_object_arguments = true; + bool polyfill_typed_content = true; +}; + class chat_template { private: @@ -41,6 +64,7 @@ class chat_template { std::string bos_token_; std::string eos_token_; std::shared_ptr template_root_; + std::string tool_call_example_; std::string try_raw_render( const nlohmann::ordered_json & messages, @@ -49,7 +73,18 @@ class chat_template { const nlohmann::ordered_json & extra_context = nlohmann::ordered_json()) const { try { - auto prompt = apply(messages, tools, add_generation_prompt, extra_context, /* adjust_inputs= */ false); + chat_template_inputs inputs; + inputs.messages = messages; + inputs.tools = tools; + inputs.add_generation_prompt = add_generation_prompt; + inputs.extra_context = extra_context; + // Use fixed date for tests + inputs.now = std::chrono::system_clock::from_time_t(0); + + chat_template_options opts; + opts.apply_polyfills = false; + + auto prompt = apply(inputs, opts); // fprintf(stderr, "try_raw_render: %s\n", prompt.c_str()); return prompt; } catch (const std::exception & e) { @@ -176,6 +211,58 @@ class chat_template { caps_.supports_tool_responses = contains(out, "Some response!"); caps_.supports_tool_call_id = contains(out, "call_911_"); } + + try { + if (!caps_.supports_tools) { + const json user_msg { + {"role", "user"}, + {"content", "Hey"}, + }; + const json args { + {"arg1", "some_value"}, + }; + const json tool_call_msg { + {"role", "assistant"}, + {"content", nullptr}, + {"tool_calls", json::array({ + { + // TODO: detect if requires numerical id or fixed length == 6 like Nemo + {"id", "call_1___"}, + {"type", "function"}, + {"function", { + {"name", "tool_name"}, + {"arguments", (caps_.requires_object_arguments ? args : json(minja::Value(args).dump(-1, /* to_json= */ true)))}, + }}, + }, + })}, + }; + std::string prefix, full; + { + chat_template_inputs inputs; + inputs.messages = json::array({user_msg}); + inputs.add_generation_prompt = true; + prefix = apply(inputs); + } + { + chat_template_inputs inputs; + inputs.messages = json::array({user_msg, tool_call_msg}); + inputs.add_generation_prompt = false; + full = apply(inputs); + } + + if (full.find(prefix) != 0) { + if (prefix.rfind(eos_token_) == prefix.size() - eos_token_.size()) { + prefix = prefix.substr(0, prefix.size() - eos_token_.size()); + } + } + if (full.find(prefix) != 0) { + fprintf(stderr, "Failed to infer a tool call example (possible template bug)\n"); + } + tool_call_example_ = full.substr(prefix.size()); + } + } catch (const std::exception & e) { + fprintf(stderr, "Failed to generate tool call example: %s\n", e.what()); + } } const std::string & source() const { return source_; } @@ -183,28 +270,72 @@ class chat_template { const std::string & eos_token() const { return eos_token_; } const chat_template_caps & original_caps() const { return caps_; } + // Deprecated, please use the form with chat_template_inputs and chat_template_options std::string apply( const nlohmann::ordered_json & messages, const nlohmann::ordered_json & tools, bool add_generation_prompt, const nlohmann::ordered_json & extra_context = nlohmann::ordered_json(), - bool adjust_inputs = true) const + bool apply_polyfills = true) + { + fprintf(stderr, "[%s] Deprecated!\n", __func__); + chat_template_inputs inputs; + inputs.messages = messages; + inputs.tools = tools; + inputs.add_generation_prompt = add_generation_prompt; + inputs.extra_context = extra_context; + inputs.now = std::chrono::system_clock::now(); + + chat_template_options opts; + opts.apply_polyfills = apply_polyfills; + + return apply(inputs, opts); + } + + std::string apply( + const chat_template_inputs & inputs, + const chat_template_options & opts = chat_template_options()) const { json actual_messages; - auto needs_adjustments = adjust_inputs && (false - || !caps_.supports_system_role - || !caps_.supports_tools - || !caps_.supports_tool_responses - || !caps_.supports_tool_calls - || caps_.requires_object_arguments - || caps_.requires_typed_content + auto has_tools = inputs.tools.is_array() && !inputs.tools.empty(); + auto has_tool_calls = false; + auto has_tool_responses = false; + auto has_string_content = false; + for (const auto & message : inputs.messages) { + if (message.contains("tool_calls") && !message["tool_calls"].is_null()) { + has_tool_calls = true; + } + if (message.contains("role") && message["role"] == "tool") { + has_tool_responses = true; + } + if (message.contains("content") && message["content"].is_string()) { + has_string_content = true; + } + } + + auto polyfill_system_role = opts.polyfill_system_role && !caps_.supports_system_role; + auto polyfill_tools = opts.polyfill_tools && has_tools && !caps_.supports_tools; + auto polyfill_tool_call_example = polyfill_tools && opts.polyfill_tool_call_examples; + auto polyfill_tool_calls = opts.polyfill_tool_calls && has_tool_calls && !caps_.supports_tool_calls; + auto polyfill_tool_responses = opts.polyfill_tool_responses && has_tool_responses && !caps_.supports_tool_responses; + auto polyfill_object_arguments = opts.polyfill_object_arguments && has_tool_calls && caps_.requires_object_arguments; + auto polyfill_typed_content = opts.polyfill_typed_content && has_string_content && caps_.requires_typed_content; + + auto needs_polyfills = opts.apply_polyfills && (false + || polyfill_system_role + || polyfill_tools + || polyfill_tool_calls + || polyfill_tool_responses + || polyfill_object_arguments + || polyfill_typed_content ); - if (needs_adjustments) { + + if (needs_polyfills) { actual_messages = json::array(); auto add_message = [&](const json & msg) { - if (caps_.requires_typed_content && msg.contains("content") && !msg.at("content").is_null() && msg.at("content").is_string()) { + if (polyfill_typed_content && msg.contains("content") && !msg.at("content").is_null() && msg.at("content").is_string()) { actual_messages.push_back({ {"role", msg.at("role")}, {"content", {{ @@ -227,9 +358,17 @@ class chat_template { pending_system.clear(); } }; - auto needs_tools_in_system = !tools.is_null() && tools.size() > 0 && !caps_.supports_tools; - for (const auto & message_ : needs_tools_in_system ? add_system(messages, "Available tools: " + tools.dump(2)) : messages) { + json adjusted_messages; + if (polyfill_tools) { + adjusted_messages = add_system(inputs.messages, + "You can call any of the following tools to satisfy the user's requests: " + minja::Value(inputs.tools).dump(2, /* to_json= */ true) + + (!polyfill_tool_call_example || tool_call_example_.empty() ? "" : "\n\nExample tool call syntax:\n\n" + tool_call_example_)); + } else { + adjusted_messages = inputs.messages; + } + + for (const auto & message_ : adjusted_messages) { auto message = message_; if (!message.contains("role") || !message.contains("content")) { throw std::runtime_error("message must have 'role' and 'content' fields: " + message.dump()); @@ -237,7 +376,7 @@ class chat_template { std::string role = message.at("role"); if (message.contains("tool_calls")) { - if (caps_.requires_object_arguments || !caps_.supports_tool_calls) { + if (polyfill_object_arguments || polyfill_tool_calls) { for (auto & tool_call : message.at("tool_calls")) { if (tool_call["type"] == "function") { auto & function = tool_call.at("function"); @@ -252,7 +391,7 @@ class chat_template { } } } - if (!caps_.supports_tool_calls) { + if (polyfill_tool_calls) { auto content = message.at("content"); auto tool_calls = json::array(); for (const auto & tool_call : message.at("tool_calls")) { @@ -279,14 +418,16 @@ class chat_template { message.erase("tool_calls"); } } - if (!caps_.supports_tool_responses && role == "tool") { + if (polyfill_tool_responses && role == "tool") { message["role"] = "user"; auto obj = json { {"tool_response", { - {"tool", message.at("name")}, {"content", message.at("content")}, }}, }; + if (message.contains("name")) { + obj["tool_response"]["name"] = message.at("name"); + } if (message.contains("tool_call_id")) { obj["tool_response"]["tool_call_id"] = message.at("tool_call_id"); } @@ -294,7 +435,7 @@ class chat_template { message.erase("name"); } - if (!message["content"].is_null() && !caps_.supports_system_role) { + if (!message["content"].is_null() && polyfill_system_role) { std::string content = message.at("content"); if (role == "system") { if (!pending_system.empty()) pending_system += "\n"; @@ -313,28 +454,36 @@ class chat_template { } add_message(message); } - if (!caps_.supports_system_role) { - flush_sys(); - } + flush_sys(); } else { - actual_messages = messages; + actual_messages = inputs.messages; } auto context = minja::Context::make(json({ {"messages", actual_messages}, - {"add_generation_prompt", add_generation_prompt}, - {"bos_token", bos_token_}, - {"eos_token", eos_token_}, + {"add_generation_prompt", inputs.add_generation_prompt}, })); + context->set("bos_token", opts.use_bos_token ? bos_token_ : ""); + context->set("eos_token", opts.use_eos_token ? eos_token_ : ""); + if (opts.define_strftime_now) { + auto now = inputs.now; + context->set("strftime_now", Value::callable([now](const std::shared_ptr &, minja::ArgumentsValue & args) { + args.expectArgs("strftime_now", {1, 1}, {0, 0}); + auto format = args.args[0].get(); - if (!tools.is_null()) { - auto tools_val = minja::Value(tools); - context->set("tools", tools_val); + auto time = std::chrono::system_clock::to_time_t(now); + auto local_time = *std::localtime(&time); + std::ostringstream ss; + ss << std::put_time(&local_time, format.c_str()); + return ss.str(); + })); } - if (!extra_context.is_null()) { - for (auto & kv : extra_context.items()) { - minja::Value val(kv.value()); - context->set(kv.key(), val); + if (!inputs.tools.is_null()) { + context->set("tools", minja::Value(inputs.tools)); + } + if (!inputs.extra_context.is_null()) { + for (auto & kv : inputs.extra_context.items()) { + context->set(kv.key(), minja::Value(kv.value())); } } @@ -351,7 +500,7 @@ class chat_template { std::string existing_system = messages_with_system.at(0).at("content"); messages_with_system[0] = json { {"role", "system"}, - {"content", existing_system + "\n" + system_prompt}, + {"content", existing_system + "\n\n" + system_prompt}, }; } else { messages_with_system.insert(messages_with_system.begin(), json { diff --git a/common/chat.cpp b/common/chat.cpp index d9a654892..ef1c6fb3d 100644 --- a/common/chat.cpp +++ b/common/chat.cpp @@ -16,6 +16,7 @@ std::string common_chat_format_name(common_chat_format format) { case COMMON_CHAT_FORMAT_FUNCTIONARY_V3_2: return "Functionary v3.2"; case COMMON_CHAT_FORMAT_FUNCTIONARY_V3_1_LLAMA_3_1: return "Functionary v3.1 Llama 3.1"; case COMMON_CHAT_FORMAT_HERMES_2_PRO: return "Hermes 2 Pro"; + case COMMON_CHAT_FORMAT_COMMAND_R7B: return "Command R7B"; default: throw std::runtime_error("Unknown chat format"); } @@ -162,6 +163,28 @@ static void foreach_function(const json & tools, const std::function\" " + builder.add_schema("tool_calls", schema) + " \"<|END_ACTION|>\""); + }, grammar_options); + data.grammar_triggers.push_back({"<|START_ACTION|>", /* .at_start = */ false}); + data.preserved_tokens = { + "<|START_RESPONSE|>", + "<|END_RESPONSE|>", + "<|START_THINKING|>", + "<|END_THINKING|>", + "<|END_ACTION|>", + }; + data.prompt = apply(tmpl, inputs.messages, inputs.tools.empty() ? json() : inputs.tools, inputs.add_generation_prompt); + data.format = COMMON_CHAT_FORMAT_COMMAND_R7B; + return data; +} +static common_chat_msg common_chat_parse_command_r7b(const std::string & input) { + static std::regex response_regex("<\\|START_RESPONSE\\|>([\\s\\S\\n\\r]*?)<\\|END_RESPONSE\\|>"); + static std::regex thought_action_regex("<\\|START_THINKING\\|>([\\s\\S\\n\\r]*?)<\\|END_THINKING\\|><\\|START_ACTION\\|>([\\s\\S\\n\\r]*?)<\\|END_ACTION\\|>"); + std::smatch match; + + common_chat_msg result; + result.role = "assistant"; + if (std::regex_match(input, match, response_regex)) { + result.content = match[1].str(); + } else if (std::regex_match(input, match, thought_action_regex)) { + result.tool_plan = match[1].str(); + auto actions_str = match[2].str(); + auto actions = json::parse(actions_str); + for (const auto & action : actions) { + result.tool_calls.push_back({ + /* .name = */ action["tool_name"], + /* .arguments = */ action["parameters"].dump(), + /* .id = */ action["tool_call_id"], + }); + } + } else { + LOG_ERR("Failed to parse command_r output"); + result.content = input; + } + return result; +} + static void expect_tool_parameters(const std::string & name, const json & parameters, const std::vector & expected_properties) { if (!parameters.is_object() || !parameters.contains("type") || parameters["type"] != "object" || !parameters.contains("properties") || !parameters.contains("required")) { throw std::runtime_error("Parameters of tool " + name + " must be an object w/ required properties"); @@ -384,21 +480,26 @@ static common_chat_params common_chat_params_init_llama_3_1_tool_calls(const com tool_rules.push_back( builder.add_rule( name + "-call", - "\"{\" ( \"\\\"type\\\": \\\"function\\\", \" | space ) " + "\"{\" space " + "( \"\\\"type\\\":\" space \"\\\"function\\\",\" space )? " "\"\\\"name\\\": \\\"" + name + "\\\", \\\"parameters\\\": \" " + builder.add_schema(name + "-args", parameters) + " \"}\"")); data.grammar_triggers.push_back({"{\"name\": \"" + name + "\"", /* .at_start = */ true}); }); data.grammar_triggers.push_back({"{\"name\":", /* .at_start = */ true}); + data.grammar_triggers.push_back({"{\n \"name\":", /* .at_start = */ true}); + data.grammar_triggers.push_back({"{\n \"name\":", /* .at_start = */ true}); data.grammar_triggers.push_back({"{\"type\": \"function\"", /* .at_start = */ true}); + data.grammar_triggers.push_back({"{\n \"type\": \"function\"", /* .at_start = */ true}); + data.grammar_triggers.push_back({"{\n \"type\": \"function\"", /* .at_start = */ true}); if (!builtin_tools.empty()) { data.grammar_triggers.push_back({"<|python_tag|>", /* .at_start = */ false}); } builder.add_rule("root", string_join(tool_rules, " | ")); }, grammar_options); data.additional_stops.push_back("<|eom_id|>"); - data.prompt = tmpl.apply(inputs.messages, inputs.tools.empty() ? json() : inputs.tools, inputs.add_generation_prompt, { + data.prompt = apply(tmpl, inputs.messages, inputs.tools.empty() ? json() : inputs.tools, inputs.add_generation_prompt, { {"tools_in_user_message", false}, {"builtin_tools", builtin_tools.empty() ? json() : builtin_tools}, }); @@ -457,9 +558,14 @@ static common_chat_params common_chat_params_init_deepseek_r1(const common_chat_ "\"<｜tool▁call▁begin｜>function<｜tool▁sep｜>" + name + "\\n```json\\n\" " + args_rule + " \"```<｜tool▁call▁end｜>\"")); }); data.grammar_triggers.push_back({"<｜tool▁calls▁begin｜>", /* .at_start = */ false}); + data.preserved_tokens = { + "<｜tool▁sep｜>", + "<｜tool▁call▁end｜>", + }; builder.add_rule("root", "\"<｜tool▁calls▁begin｜>\" (" + string_join(tool_rules, " | ") + ")" + (inputs.parallel_tool_calls ? "*" : "") + " space"); }, grammar_options); - data.prompt = tmpl.apply(inputs.messages, inputs.tools.empty() ? json() : inputs.tools, inputs.add_generation_prompt); + auto prompt = apply(tmpl, inputs.messages, inputs.tools.empty() ? json() : inputs.tools, inputs.add_generation_prompt); + data.prompt = prompt; data.format = COMMON_CHAT_FORMAT_DEEPSEEK_R1; return data; } @@ -473,10 +579,10 @@ static common_chat_msg common_chat_parse_deepseek_r1(const std::string & input) static common_chat_params common_chat_params_init_firefunction_v2(const common_chat_template & tmpl, const struct common_chat_inputs & inputs) { fprintf(stderr, "%s\n", __func__); common_chat_params data; - data.prompt = tmpl.apply(inputs.messages, /* tools= */ nullptr, inputs.add_generation_prompt, { + data.prompt = apply(tmpl, inputs.messages, /* tools= */ nullptr, inputs.add_generation_prompt, { {"datetime", "Jan 29 2025 13:00:00 GMT"}, {"functions", json(inputs.tools.empty() ? "" : inputs.tools.dump(2))}, - }, /* adjust_inputs= */ false); + }); if (!inputs.tools.is_null() && !inputs.tools.empty()) { data.grammar_lazy = inputs.tool_choice != "required"; data.grammar = build_grammar([&](const common_grammar_builder & builder) { @@ -520,7 +626,7 @@ static common_chat_params common_chat_params_init_functionary_v3_2(const common_ // >>>all\nlet's call functions>>>fn1\n{"arg1": 1...}\n>>>fn2\n{"arg1": 1...}... // Using ">>>f1\n", ">>>f2\n"... as trigger words for the grammar common_chat_params data; - data.prompt = tmpl.apply(inputs.messages, inputs.tools.empty() ? json() : inputs.tools, inputs.add_generation_prompt); + data.prompt = apply(tmpl, inputs.messages, inputs.tools.empty() ? json() : inputs.tools, inputs.add_generation_prompt); data.format = COMMON_CHAT_FORMAT_FUNCTIONARY_V3_2; if (!inputs.tools.is_null() && !inputs.tools.empty()) { data.grammar_lazy = inputs.tool_choice != "required"; @@ -586,9 +692,17 @@ static common_chat_msg common_chat_parse_functionary_v3_2(const std::string & in } } // TODO: tighten & simplify. - auto res = parse_json_tool_calls(std::string(it, end), std::nullopt, function_regex, close_regex); - res.content = content; - return res; + try { + auto res = parse_json_tool_calls(std::string(it, end), std::nullopt, function_regex, close_regex); + res.content = content + res.content; + return res; + } catch (const std::exception & e) { + LOG_ERR("Failed to parse functionary v3.2 input: %s\n", e.what()); + common_chat_msg res; + res.role = "assistant"; + res.content = input; + return res; + } } static common_chat_params common_chat_params_init_functionary_v3_1_llama_3_1(const common_chat_template & tmpl, const struct common_chat_inputs & inputs) { @@ -639,7 +753,7 @@ static common_chat_params common_chat_params_init_functionary_v3_1_llama_3_1(con data.grammar_triggers.push_back({"\" space " + builder.add_rule("tool_call", string_join(tool_rules, " | ")) + " \"\" space"; builder.add_rule("root", inputs.parallel_tool_calls ? "(" + tool_call + ")+" : tool_call); data.grammar_triggers.push_back({"", /* .at_start = */ false}); - // Not really a trigger but need to print this special token to get a successful parse. - data.grammar_triggers.push_back({"", /* .at_start = */ false}); + data.preserved_tokens = { "" }; }, grammar_options); - data.prompt = tmpl.apply(inputs.messages, inputs.tools.empty() ? json() : inputs.tools, inputs.add_generation_prompt); + data.prompt = apply(tmpl, inputs.messages, inputs.tools.empty() ? json() : inputs.tools, inputs.add_generation_prompt); data.format = COMMON_CHAT_FORMAT_HERMES_2_PRO; return data; } @@ -756,7 +869,7 @@ static common_chat_msg common_chat_parse_hermes_2_pro(const std::string & input) static common_chat_params common_chat_params_init_without_tools(const common_chat_template & tmpl, const struct common_chat_inputs & inputs) { common_chat_params data; - data.prompt = tmpl.apply(inputs.messages, inputs.tools.empty() ? json() : inputs.tools, inputs.add_generation_prompt); + data.prompt = apply(tmpl, inputs.messages, inputs.tools.empty() ? json() : inputs.tools, inputs.add_generation_prompt); data.format = COMMON_CHAT_FORMAT_CONTENT_ONLY; data.grammar_lazy = false; if (!inputs.json_schema.is_null()) { @@ -809,6 +922,9 @@ common_chat_params common_chat_params_init(const common_chat_template & tmpl, co if (src.find("[TOOL_CALLS]") != std::string::npos) { return common_chat_params_init_mistral_nemo(tmpl, inputs); } + if (src.find("<|END_THINKING|><|START_ACTION|>") != std::string::npos) { + return common_chat_params_init_command_r7b(tmpl, inputs); + } return common_chat_params_init_generic(tmpl, inputs); } @@ -842,6 +958,8 @@ common_chat_msg common_chat_parse(const std::string & input, common_chat_format return common_chat_parse_hermes_2_pro(input); case COMMON_CHAT_FORMAT_FIREFUNCTION_V2: return common_chat_parse_firefunction_v2(input); + case COMMON_CHAT_FORMAT_COMMAND_R7B: + return common_chat_parse_command_r7b(input); default: throw std::runtime_error("Unsupported format: " + common_chat_format_name(format)); } diff --git a/common/chat.hpp b/common/chat.hpp index ca165aa13..33e64a430 100644 --- a/common/chat.hpp +++ b/common/chat.hpp @@ -32,6 +32,7 @@ enum common_chat_format { COMMON_CHAT_FORMAT_FUNCTIONARY_V3_2, COMMON_CHAT_FORMAT_FUNCTIONARY_V3_1_LLAMA_3_1, COMMON_CHAT_FORMAT_HERMES_2_PRO, + COMMON_CHAT_FORMAT_COMMAND_R7B, COMMON_CHAT_FORMAT_COUNT, // Not a format, just the # formats }; @@ -42,6 +43,7 @@ struct common_chat_params { std::string grammar; bool grammar_lazy = false; std::vector grammar_triggers; + std::vector preserved_tokens; std::vector additional_stops; }; diff --git a/common/common.cpp b/common/common.cpp index 6c81d18f9..8661e164a 100644 --- a/common/common.cpp +++ b/common/common.cpp @@ -1869,11 +1869,19 @@ std::string common_chat_format_example(const common_chat_template & tmpl, bool u return common_chat_apply_template(tmpl, msgs, true, use_jinja); } +#define CHATML_TEMPLATE_SRC \ + "{%- for message in messages -%}\n" \ + " {{- '<|im_start|>' + message.role + '\n' + message.content + '<|im_end|>\n' -}}\n" \ + "{%- endfor -%}\n" \ + "{%- if add_generation_prompt -%}\n" \ + " {{- '<|im_start|>assistant\n' -}}\n" \ + "{%- endif -%}" + common_chat_templates common_chat_templates_from_model(const struct llama_model * model, const std::string & chat_template_override) { - auto vocab = llama_model_get_vocab(model); - std::string default_template_src = chat_template_override; - std::string template_tool_use_src = chat_template_override; + std::string default_template_src; + std::string template_tool_use_src; + bool has_explicit_template = !chat_template_override.empty(); if (chat_template_override.empty()) { auto str = llama_model_chat_template(model, /* name */ nullptr); @@ -1886,21 +1894,17 @@ common_chat_templates common_chat_templates_from_model(const struct llama_model template_tool_use_src = str; has_explicit_template = true; } + } else { + default_template_src = chat_template_override; } if (default_template_src.empty() || default_template_src == "chatml") { if (!template_tool_use_src.empty()) { default_template_src = template_tool_use_src; } else { - default_template_src = R"( - {%- for message in messages -%} - {{- "<|im_start|>" + message.role + "\n" + message.content + "<|im_end|>\n" -}} - {%- endfor -%} - {%- if add_generation_prompt -%} - {{- "<|im_start|>assistant\n" -}} - {%- endif -%} - )"; + default_template_src = CHATML_TEMPLATE_SRC; } } + auto vocab = llama_model_get_vocab(model); const auto get_token = [&](llama_token token, const char * name, const char * jinja_variable_name) { if (token == LLAMA_TOKEN_NULL) { if (default_template_src.find(jinja_variable_name) != std::string::npos @@ -1914,13 +1918,22 @@ common_chat_templates common_chat_templates_from_model(const struct llama_model }; auto token_bos = get_token(llama_vocab_bos(vocab), "BOS", "bos_token"); auto token_eos = get_token(llama_vocab_eos(vocab), "EOS", "eos_token"); - return { - has_explicit_template, - std::make_unique(default_template_src, token_bos, token_eos), - template_tool_use_src.empty() - ? nullptr - : std::make_unique(template_tool_use_src, token_bos, token_eos) - }; + try { + return { + has_explicit_template, + std::make_unique(default_template_src, token_bos, token_eos), + template_tool_use_src.empty() + ? nullptr + : std::make_unique(template_tool_use_src, token_bos, token_eos), + }; + } catch (const std::exception & e) { + LOG_ERR("%s: failed to parse chat template: %s\n", __func__, e.what()); + return { + has_explicit_template, + std::make_unique(CHATML_TEMPLATE_SRC, token_bos, token_eos), + nullptr, + }; + } } // diff --git a/common/common.h b/common/common.h index 1b9920689..4eac8db5a 100644 --- a/common/common.h +++ b/common/common.h @@ -4,6 +4,7 @@ #include "llama-cpp.h" +#include #include #include #include @@ -163,6 +164,7 @@ struct common_params_sampling { bool grammar_lazy = false; std::vector grammar_trigger_words; // optional trigger words to trigger lazy grammar std::vector grammar_trigger_tokens; // optional trigger tokens to trigger lazy grammar and print trigger special tokens. + std::set preserved_tokens; std::vector logit_bias; // logit biases to apply @@ -621,6 +623,7 @@ struct common_chat_msg { std::string role; std::string content; std::vector tool_calls; + std::string tool_plan = ""; }; // Check if the template supplied via "--chat-template" is supported or not. Returns true if it's valid diff --git a/common/json-schema-to-grammar.cpp b/common/json-schema-to-grammar.cpp index 1f47e313e..3ebcc3d9f 100644 --- a/common/json-schema-to-grammar.cpp +++ b/common/json-schema-to-grammar.cpp @@ -991,7 +991,14 @@ public: } }; -std::string json_schema_to_grammar(const json & schema) { +std::string json_schema_to_grammar(const json & schema, bool force_gbnf) { +#ifdef LLAMA_USE_LLGUIDANCE + if (!force_gbnf) { + return "%llguidance {}\nstart: %json " + schema.dump(); + } +#else + (void)force_gbnf; +#endif // LLAMA_USE_LLGUIDANCE return build_grammar([&](const common_grammar_builder & callbacks) { auto copy = schema; callbacks.resolve_refs(copy); diff --git a/common/json-schema-to-grammar.h b/common/json-schema-to-grammar.h index ba4112cb9..62a3b0a44 100644 --- a/common/json-schema-to-grammar.h +++ b/common/json-schema-to-grammar.h @@ -5,7 +5,8 @@ #define JSON_ASSERT GGML_ASSERT #include "json.hpp" -std::string json_schema_to_grammar(const nlohmann::ordered_json & schema); +std::string json_schema_to_grammar(const nlohmann::ordered_json & schema, + bool force_gbnf = false); struct common_grammar_builder { std::function add_rule; diff --git a/common/llguidance.cpp b/common/llguidance.cpp new file mode 100644 index 000000000..2feeb93c8 --- /dev/null +++ b/common/llguidance.cpp @@ -0,0 +1,270 @@ +#include "sampling.h" +#include "log.h" + +#ifdef LLAMA_USE_LLGUIDANCE + +# include "llguidance.h" +# include + +struct llama_sampler_llg { + const llama_vocab * vocab; + std::string grammar_kind; + std::string grammar_data; + LlgTokenizer * tokenizer; + LlgConstraint * grammar; + LlgMaskResult llg_res; + bool has_llg_res; +}; + +static LlgConstraint * llama_sampler_llg_new(LlgTokenizer * tokenizer, const char * grammar_kind, + const char * grammar_data) { + LlgConstraintInit cinit; + llg_constraint_init_set_defaults(&cinit, tokenizer); + const char * log_level = getenv("LLGUIDANCE_LOG_LEVEL"); + if (log_level && *log_level) { + cinit.log_stderr_level = atoi(log_level); + } + auto c = llg_new_constraint_any(&cinit, grammar_kind, grammar_data); + if (llg_get_error(c)) { + LOG_ERR("llg error: %s\n", llg_get_error(c)); + llg_free_constraint(c); + return nullptr; + } + return c; +} + +static const char * llama_sampler_llg_name(const llama_sampler * /*smpl*/) { + return "llguidance"; +} + +static void llama_sampler_llg_accept_impl(llama_sampler * smpl, llama_token token) { + auto * ctx = (llama_sampler_llg *) smpl->ctx; + if (ctx->grammar) { + LlgCommitResult res; + llg_commit_token(ctx->grammar, token, &res); + ctx->has_llg_res = false; + } +} + +static void llama_sampler_llg_apply(llama_sampler * smpl, llama_token_data_array * cur_p) { + auto * ctx = (llama_sampler_llg *) smpl->ctx; + if (ctx->grammar) { + if (!ctx->has_llg_res) { + if (llg_compute_mask(ctx->grammar, &ctx->llg_res) == 0) { + ctx->has_llg_res = true; + } else { + LOG_ERR("llg error: %s\n", llg_get_error(ctx->grammar)); + llg_free_constraint(ctx->grammar); + ctx->grammar = nullptr; + } + } + if (ctx->has_llg_res) { + if (ctx->llg_res.is_stop) { + for (size_t i = 0; i < cur_p->size; ++i) { + if (!llama_vocab_is_eog(ctx->vocab, cur_p->data[i].id)) { + cur_p->data[i].logit = -INFINITY; + } + } + } else { + const uint32_t * mask = ctx->llg_res.sample_mask; + for (size_t i = 0; i < cur_p->size; ++i) { + auto token = cur_p->data[i].id; + if ((mask[token / 32] & (1 << (token % 32))) == 0) { + cur_p->data[i].logit = -INFINITY; + } + } + } + } + } +} + +static void llama_sampler_llg_reset(llama_sampler * smpl) { + auto * ctx = (llama_sampler_llg *) smpl->ctx; + if (!ctx->grammar) { + return; + } + + auto * grammar_new = llama_sampler_llg_new(ctx->tokenizer, ctx->grammar_kind.c_str(), ctx->grammar_data.c_str()); + llg_free_constraint(ctx->grammar); + ctx->grammar = grammar_new; + ctx->has_llg_res = false; +} + +static llama_sampler * llama_sampler_llg_clone(const llama_sampler * smpl) { + const auto * ctx = (const llama_sampler_llg *) smpl->ctx; + + auto * result = llama_sampler_init_llg(ctx->vocab, nullptr, nullptr); + + // copy the state + { + auto * result_ctx = (llama_sampler_llg *) result->ctx; + + if (ctx->grammar) { + result_ctx->grammar_kind = ctx->grammar_kind; + result_ctx->grammar_data = ctx->grammar_data; + result_ctx->grammar = llg_clone_constraint(ctx->grammar); + result_ctx->tokenizer = llg_clone_tokenizer(ctx->tokenizer); + } + } + + return result; +} + +static void llama_sampler_llg_free(llama_sampler * smpl) { + const auto * ctx = (llama_sampler_llg *) smpl->ctx; + + if (ctx->grammar) { + llg_free_constraint(ctx->grammar); + llg_free_tokenizer(ctx->tokenizer); + } + + delete ctx; +} + +static llama_sampler_i llama_sampler_llg_i = { + /* .name = */ llama_sampler_llg_name, + /* .accept = */ llama_sampler_llg_accept_impl, + /* .apply = */ llama_sampler_llg_apply, + /* .reset = */ llama_sampler_llg_reset, + /* .clone = */ llama_sampler_llg_clone, + /* .free = */ llama_sampler_llg_free, +}; + +static size_t llama_sampler_llg_tokenize_fn(const void * user_data, const uint8_t * bytes, size_t bytes_len, + uint32_t * output_tokens, size_t output_tokens_len) { + const llama_vocab * vocab = (const llama_vocab *) user_data; + int r = 0; + try { + r = llama_tokenize(vocab, (const char *) bytes, bytes_len, (int32_t *) output_tokens, output_tokens_len, false, + true); + } catch (const std::exception & e) { + GGML_ABORT("llama_tokenize failed: %s\n", e.what()); + } + if (r < 0) { + return -r; + } + return r; +} + +static LlgTokenizer * llama_sampler_llg_new_tokenizer(const llama_vocab * vocab) { + // TODO store the tokenizer in the vocab somehow + static const llama_vocab * vocab_cache; + static LlgTokenizer * tokenizer_cache; + + if (vocab_cache == vocab) { + return llg_clone_tokenizer(tokenizer_cache); + } + + auto tok_eos = llama_vocab_eot(vocab); + if (tok_eos == LLAMA_TOKEN_NULL) { + tok_eos = llama_vocab_eos(vocab); + } + + size_t vocab_size = llama_vocab_n_tokens(vocab); + + auto token_lens = new uint32_t[vocab_size]; + // we typically have ~7 bytes per token; let's go on the safe side here + auto token_bytes_size = vocab_size * 16 + 1024 * 1024; + auto token_bytes = new uint8_t[token_bytes_size]; + + size_t offset = 0; + for (size_t i = 0; i < vocab_size; i++) { + size_t max_token = 1024; + if (token_bytes_size - offset < max_token) { + GGML_ABORT("token_bytes buffer too small\n"); + } + + llama_token token = i; + auto dp = (char *) token_bytes + offset; + auto size = llama_detokenize(vocab, &token, 1, dp, max_token, false, false); + if (size < 0) { + GGML_ABORT("llama_detokenize failed\n"); + } + if (size == 0) { + size = llama_detokenize(vocab, &token, 1, dp + 1, max_token - 1, false, true); + if (size < 0) { + GGML_ABORT("llama_detokenize failed\n"); + } + if (size != 0) { + *dp = '\xff'; // special token prefix marker + size += 1; + } + } + + token_lens[i] = size; + offset += size; + } + + LlgTokenizerInit tinit = { + /* .vocab_size = */ (uint32_t) vocab_size, + /* .tok_eos = */ (uint32_t) tok_eos, + /* .token_lens = */ token_lens, + /* .token_bytes = */ token_bytes, + /* .tokenizer_json = */ nullptr, + /* .tokenize_assumes_string = */ true, + /* .tokenize_fn = */ llama_sampler_llg_tokenize_fn, + /* .use_approximate_greedy_tokenize_fn = */ false, + /* .tokenize_user_data = */ vocab, + }; + + char error_buffer[1024]; + LlgTokenizer * tokenizer = llg_new_tokenizer(&tinit, error_buffer, sizeof(error_buffer)); + + delete[] token_bytes; + delete[] token_lens; + + if (tokenizer == nullptr) { + LOG_ERR("llg tokenizer error: %s\n", error_buffer); + return tokenizer; + } + + if (tokenizer_cache) { + llg_free_tokenizer(tokenizer_cache); + } + vocab_cache = vocab; + tokenizer_cache = tokenizer; + + return llg_clone_tokenizer(tokenizer_cache); +} + +llama_sampler * llama_sampler_init_llg(const llama_vocab * vocab, const char * grammar_kind, + const char * grammar_data) { + auto * ctx = new llama_sampler_llg; + + if (grammar_kind != nullptr && grammar_kind[0] != '\0') { + auto tokenizer = llama_sampler_llg_new_tokenizer(vocab); + *ctx = { + /* .vocab = */ vocab, + /* .grammar_kind = */ grammar_kind, + /* .grammar_data = */ grammar_data, + /* .tokenizer = */ tokenizer, + /* .grammar = */ llama_sampler_llg_new(tokenizer, grammar_kind, grammar_data), + /* .llg_res = */ {}, + /* .has_llg_res = */ false, + }; + } else { + *ctx = { + /* .vocab = */ vocab, + /* .grammar_kind = */ {}, + /* .grammar_data = */ {}, + /* .tokenizer = */ nullptr, + /* .grammar = */ nullptr, + /* .llg_res = */ {}, + /* .has_llg_res = */ false, + }; + } + + return llama_sampler_init( + /* .iface = */ &llama_sampler_llg_i, + /* .ctx = */ ctx + ); +} + +#else + +llama_sampler * llama_sampler_init_llg(const llama_vocab *, const char *, const char *) { + LOG_WRN("llguidance (cmake -DLLAMA_LLGUIDANCE=ON) is not enabled"); + return nullptr; +} + +#endif // LLAMA_USE_LLGUIDANCE diff --git a/common/log.cpp b/common/log.cpp index 04c7c0ed1..4bfbecf15 100644 --- a/common/log.cpp +++ b/common/log.cpp @@ -14,16 +14,6 @@ void common_log_set_verbosity_thold(int verbosity) { common_log_verbosity_thold = verbosity; } -#define LOG_COL_DEFAULT "\033[0m" -#define LOG_COL_BOLD "\033[1m" -#define LOG_COL_RED "\033[31m" -#define LOG_COL_GREEN "\033[32m" -#define LOG_COL_YELLOW "\033[33m" -#define LOG_COL_BLUE "\033[34m" -#define LOG_COL_MAGENTA "\033[35m" -#define LOG_COL_CYAN "\033[36m" -#define LOG_COL_WHITE "\033[37m" - static int64_t t_us() { return std::chrono::duration_cast(std::chrono::system_clock::now().time_since_epoch()).count(); } @@ -206,6 +196,7 @@ public: vsnprintf(entry.msg.data(), entry.msg.size(), ss.str().c_str(), args_copy); } #endif + va_end(args_copy); } entry.level = level; diff --git a/common/log.h b/common/log.h index 66605cc69..4ebc6314b 100644 --- a/common/log.h +++ b/common/log.h @@ -2,6 +2,17 @@ #include "ggml.h" // for ggml_log_level +#define LOG_CLR_TO_EOL "\033[K\r" +#define LOG_COL_DEFAULT "\033[0m" +#define LOG_COL_BOLD "\033[1m" +#define LOG_COL_RED "\033[31m" +#define LOG_COL_GREEN "\033[32m" +#define LOG_COL_YELLOW "\033[33m" +#define LOG_COL_BLUE "\033[34m" +#define LOG_COL_MAGENTA "\033[35m" +#define LOG_COL_CYAN "\033[36m" +#define LOG_COL_WHITE "\033[37m" + #ifndef __GNUC__ # define LOG_ATTRIBUTE_FORMAT(...) #elif defined(__MINGW32__) diff --git a/common/minja.hpp b/common/minja.hpp index f0e80fd7c..c304b5c66 100644 --- a/common/minja.hpp +++ b/common/minja.hpp @@ -693,7 +693,7 @@ enum SpaceHandling { Keep, Strip, StripSpaces, StripNewline }; class TemplateToken { public: - enum class Type { Text, Expression, If, Else, Elif, EndIf, For, EndFor, Generation, EndGeneration, Set, EndSet, Comment, Macro, EndMacro, Filter, EndFilter }; + enum class Type { Text, Expression, If, Else, Elif, EndIf, For, EndFor, Generation, EndGeneration, Set, EndSet, Comment, Macro, EndMacro, Filter, EndFilter, Break, Continue }; static std::string typeToString(Type t) { switch (t) { @@ -714,6 +714,8 @@ public: case Type::EndFilter: return "endfilter"; case Type::Generation: return "generation"; case Type::EndGeneration: return "endgeneration"; + case Type::Break: return "break"; + case Type::Continue: return "continue"; } return "Unknown"; } @@ -815,6 +817,22 @@ struct CommentTemplateToken : public TemplateToken { CommentTemplateToken(const Location & location, SpaceHandling pre, SpaceHandling post, const std::string& t) : TemplateToken(Type::Comment, location, pre, post), text(t) {} }; +enum class LoopControlType { Break, Continue }; + +class LoopControlException : public std::runtime_error { +public: + LoopControlType control_type; + LoopControlException(const std::string & message, LoopControlType control_type) : std::runtime_error(message), control_type(control_type) {} + LoopControlException(LoopControlType control_type) + : std::runtime_error((control_type == LoopControlType::Continue ? "continue" : "break") + std::string(" outside of a loop")), + control_type(control_type) {} +}; + +struct LoopControlTemplateToken : public TemplateToken { + LoopControlType control_type; + LoopControlTemplateToken(const Location & location, SpaceHandling pre, SpaceHandling post, LoopControlType control_type) : TemplateToken(Type::Break, location, pre, post), control_type(control_type) {} +}; + class TemplateNode { Location location_; protected: @@ -825,6 +843,12 @@ public: void render(std::ostringstream & out, const std::shared_ptr & context) const { try { do_render(out, context); + } catch (const LoopControlException & e) { + // TODO: make stack creation lazy. Only needed if it was thrown outside of a loop. + std::ostringstream err; + err << e.what(); + if (location_.source) err << error_location_suffix(*location_.source, location_.pos); + throw LoopControlException(err.str(), e.control_type); } catch (const std::exception & e) { std::ostringstream err; err << e.what(); @@ -897,6 +921,15 @@ public: } }; +class LoopControlNode : public TemplateNode { + LoopControlType control_type_; + public: + LoopControlNode(const Location & location, LoopControlType control_type) : TemplateNode(location), control_type_(control_type) {} + void do_render(std::ostringstream &, const std::shared_ptr &) const override { + throw LoopControlException(control_type_); + } +}; + class ForNode : public TemplateNode { std::vector var_names; std::shared_ptr iterable; @@ -961,7 +994,12 @@ public: loop.set("last", i == (n - 1)); loop.set("previtem", i > 0 ? filtered_items.at(i - 1) : Value()); loop.set("nextitem", i < n - 1 ? filtered_items.at(i + 1) : Value()); - body->render(out, loop_context); + try { + body->render(out, loop_context); + } catch (const LoopControlException & e) { + if (e.control_type == LoopControlType::Break) break; + if (e.control_type == LoopControlType::Continue) continue; + } } } }; @@ -2156,10 +2194,10 @@ private: } TemplateTokenVector tokenize() { - static std::regex comment_tok(R"(\{#([-~]?)(.*?)([-~]?)#\})"); + static std::regex comment_tok(R"(\{#([-~]?)([\s\S\r\n]*?)([-~]?)#\})"); static std::regex expr_open_regex(R"(\{\{([-~])?)"); static std::regex block_open_regex(R"(^\{%([-~])?[\s\n\r]*)"); - static std::regex block_keyword_tok(R"((if|else|elif|endif|for|endfor|generation|endgeneration|set|endset|block|endblock|macro|endmacro|filter|endfilter)\b)"); + static std::regex block_keyword_tok(R"((if|else|elif|endif|for|endfor|generation|endgeneration|set|endset|block|endblock|macro|endmacro|filter|endfilter|break|continue)\b)"); static std::regex non_text_open_regex(R"(\{\{|\{%|\{#)"); static std::regex expr_close_regex(R"([\s\n\r]*([-~])?\}\})"); static std::regex block_close_regex(R"([\s\n\r]*([-~])?%\})"); @@ -2291,6 +2329,9 @@ private: } else if (keyword == "endfilter") { auto post_space = parseBlockClose(); tokens.push_back(std::make_unique(location, pre_space, post_space)); + } else if (keyword == "break" || keyword == "continue") { + auto post_space = parseBlockClose(); + tokens.push_back(std::make_unique(location, pre_space, post_space, keyword == "break" ? LoopControlType::Break : LoopControlType::Continue)); } else { throw std::runtime_error("Unexpected block: " + keyword); } @@ -2414,6 +2455,8 @@ private: children.emplace_back(std::make_shared(token->location, std::move(filter_token->filter), std::move(body))); } else if (dynamic_cast(token.get())) { // Ignore comments + } else if (auto ctrl_token = dynamic_cast(token.get())) { + children.emplace_back(std::make_shared(token->location, ctrl_token->control_type)); } else if (dynamic_cast(token.get()) || dynamic_cast(token.get()) || dynamic_cast(token.get()) @@ -2572,6 +2615,7 @@ inline std::shared_ptr Context::builtins() { })); globals.set("join", simple_function("join", { "items", "d" }, [](const std::shared_ptr &, Value & args) { auto do_join = [](Value & items, const std::string & sep) { + if (!items.is_array()) throw std::runtime_error("object is not iterable: " + items.dump()); std::ostringstream oss; auto first = true; for (size_t i = 0, n = items.size(); i < n; ++i) { @@ -2652,6 +2696,10 @@ inline std::shared_ptr Context::builtins() { return Value::callable([=](const std::shared_ptr & context, ArgumentsValue & args) { args.expectArgs(is_select ? "select" : "reject", {2, (std::numeric_limits::max)()}, {0, 0}); auto & items = args.args[0]; + if (items.is_null()) + return Value::array(); + if (!items.is_array()) throw std::runtime_error("object is not iterable: " + items.dump()); + auto filter_fn = context->get(args.args[1]); if (filter_fn.is_null()) throw std::runtime_error("Undefined filter: " + args.args[1].dump()); @@ -2729,6 +2777,7 @@ inline std::shared_ptr Context::builtins() { auto & items = args.args[0]; if (items.is_null()) return Value::array(); + if (!items.is_array()) throw std::runtime_error("object is not iterable: " + items.dump()); auto attr_name = args.args[1].get(); bool has_test = false; diff --git a/common/sampling.cpp b/common/sampling.cpp index bc7e49fdb..e4b21ca10 100644 --- a/common/sampling.cpp +++ b/common/sampling.cpp @@ -156,13 +156,25 @@ struct common_sampler * common_sampler_init(const struct llama_model * model, co for (const auto & str : params.grammar_trigger_words) { trigger_words.push_back(str.word.c_str()); } + + struct llama_sampler * grmr; + if (params.grammar.compare(0, 11, "%llguidance") == 0) { +#ifdef LLAMA_USE_LLGUIDANCE + grmr = llama_sampler_init_llg(vocab, "lark", params.grammar.c_str()); +#else + GGML_ABORT("llguidance (cmake -DLLAMA_LLGUIDANCE=ON) is not enabled"); +#endif // LLAMA_USE_LLGUIDANCE + } else { + grmr = params.grammar_lazy + ? llama_sampler_init_grammar_lazy(vocab, params.grammar.c_str(), "root", + trigger_words.data(), trigger_words.size(), + params.grammar_trigger_tokens.data(), params.grammar_trigger_tokens.size()) + : llama_sampler_init_grammar(vocab, params.grammar.c_str(), "root"); + } + auto * result = new common_sampler { /* .params = */ params, - /* .grmr = */ params.grammar_lazy - ? llama_sampler_init_grammar_lazy(vocab, params.grammar.c_str(), "root", - trigger_words.data(), trigger_words.size(), - params.grammar_trigger_tokens.data(), params.grammar_trigger_tokens.size()) - : llama_sampler_init_grammar(vocab, params.grammar.c_str(), "root"), + /* .grmr = */ grmr, /* .chain = */ llama_sampler_chain_init(lparams), /* .prev = */ ring_buffer(std::max(32, params.n_prev)), /* .cur = */ {}, diff --git a/common/sampling.h b/common/sampling.h index 348911b18..2064421db 100644 --- a/common/sampling.h +++ b/common/sampling.h @@ -102,3 +102,6 @@ std::string common_sampler_type_to_str(enum common_sampler_type cnstr); std::vector common_sampler_types_from_names(const std::vector & names, bool allow_alt_names); std::vector common_sampler_types_from_chars(const std::string & chars); + +llama_sampler * llama_sampler_init_llg(const llama_vocab * vocab, + const char * grammar_kind, const char * grammar_data); diff --git a/convert_hf_to_gguf.py b/convert_hf_to_gguf.py index 63b54a9cf..018a2a588 100755 --- a/convert_hf_to_gguf.py +++ b/convert_hf_to_gguf.py @@ -648,7 +648,7 @@ class Model: if chkhsh == "7967bfa498ade6b757b064f31e964dddbb80f8f9a4d68d4ba7998fcf281c531a": # ref: https://huggingface.co/jinaai/jina-embeddings-v2-base-code res = "jina-v2-code" - if chkhsh == "b6e8e1518dc4305be2fe39c313ed643381c4da5db34a98f6a04c093f8afbe99b": + if chkhsh == "b6e8e1518dc4305be2fe39c313ed643381c4da5db34a98f6a04c093f8afbe99b" or chkhsh == "81d72c7348a9f0ebe86f23298d37debe0a5e71149e29bd283904c02262b27516": # ref: https://huggingface.co/THUDM/glm-4-9b-chat res = "chatglm-bpe" if chkhsh == "7fc505bd3104ca1083b150b17d088b59534ede9bde81f0dd2090967d7fe52cee": @@ -4513,7 +4513,7 @@ class JaisModel(Model): self.gguf_writer.add_max_alibi_bias(self.max_alibi_bias) -@Model.register("ChatGLMModel", "ChatGLMForConditionalGeneration") +@Model.register("GlmForCausalLM", "ChatGLMModel", "ChatGLMForConditionalGeneration") class ChatGLMModel(Model): model_arch = gguf.MODEL_ARCH.CHATGLM @@ -4619,47 +4619,15 @@ class ChatGLMModel(Model): from transformers import AutoTokenizer tokenizer = AutoTokenizer.from_pretrained(dir_model, trust_remote_code=True) - vocab_size = hparams["padded_vocab_size"] + vocab_size = hparams.get("padded_vocab_size",hparams["vocab_size"]) assert max(tokenizer.get_vocab().values()) < vocab_size - tokpre = self.get_vocab_base_pre(tokenizer) - - merges = [] - vocab = {} - mergeable_ranks = tokenizer.mergeable_ranks - for token, rank in mergeable_ranks.items(): - vocab[ChatGLMModel.token_bytes_to_string(token)] = rank - if len(token) == 1: - continue - merged = ChatGLMModel.bpe(mergeable_ranks, token, max_rank=rank) - assert len(merged) >= 2 and len(merged) <= 7 - merges.append(' '.join(map(ChatGLMModel.token_bytes_to_string, merged))) - - # for this kind of tokenizer, added_vocab is not a subset of vocab, so they need to be combined - added_vocab = tokenizer.get_added_vocab() - reverse_vocab = {id_ : encoded_tok for encoded_tok, id_ in {**vocab, **added_vocab}.items()} - - for i in range(vocab_size): - if i not in reverse_vocab: - tokens.append(f"[PAD{i}]") - toktypes.append(gguf.TokenType.UNUSED) - elif reverse_vocab[i] in added_vocab: - tokens.append(reverse_vocab[i]) - if tokenizer.added_tokens_decoder[i].special: - toktypes.append(gguf.TokenType.CONTROL) - else: - toktypes.append(gguf.TokenType.USER_DEFINED) - else: - tokens.append(reverse_vocab[i]) - toktypes.append(gguf.TokenType.NORMAL) - + tokens, toktypes, tokpre = self.get_vocab_base() self.gguf_writer.add_tokenizer_model("gpt2") self.gguf_writer.add_tokenizer_pre(tokpre) self.gguf_writer.add_token_list(tokens) self.gguf_writer.add_token_types(toktypes) - - special_vocab = gguf.SpecialVocab(dir_model, load_merges=False) - special_vocab.merges = merges + special_vocab = gguf.SpecialVocab(self.dir_model, load_merges=True) # only add special tokens when they were not already loaded from config.json special_vocab._set_special_token("eos", tokenizer.get_added_vocab()["<|endoftext|>"]) special_vocab._set_special_token("eot", tokenizer.get_added_vocab()["<|user|>"]) @@ -4670,16 +4638,20 @@ class ChatGLMModel(Model): def set_gguf_parameters(self): n_embed = self.hparams.get("hidden_size", self.hparams.get("n_embed")) n_head = self.hparams.get("n_head", self.hparams.get("num_attention_heads")) - n_head_kv = self.hparams.get("multi_query_group_num", n_head) + n_head_kv = self.hparams.get("multi_query_group_num", self.hparams.get("num_key_value_heads", n_head)) self.gguf_writer.add_context_length(self.hparams.get("seq_length", n_embed)) self.gguf_writer.add_embedding_length(n_embed) - self.gguf_writer.add_feed_forward_length(self.hparams.get("ffn_hidden_size", 4 * n_embed)) - self.gguf_writer.add_block_count(self.hparams["num_layers"]) + self.gguf_writer.add_feed_forward_length(self.hparams.get("ffn_hidden_size", self.hparams.get("intermediate_size", 4 * n_embed))) + self.gguf_writer.add_block_count(self.hparams.get("num_layers", self.hparams["num_hidden_layers"])) self.gguf_writer.add_head_count(n_head) self.gguf_writer.add_head_count_kv(n_head_kv) - self.gguf_writer.add_layer_norm_rms_eps(self.hparams["layernorm_epsilon"]) + self.gguf_writer.add_layer_norm_rms_eps(self.hparams.get("layernorm_epsilon",1e-5)) self.gguf_writer.add_file_type(self.ftype) - self.gguf_writer.add_rope_dimension_count(64) + if "attention_dim" in self.hparams: + rope_dim = self.hparams["attention_dim"] + else: + rope_dim = self.hparams["hidden_size"] // self.hparams["num_attention_heads"] + self.gguf_writer.add_rope_dimension_count(int(rope_dim * self.hparams.get("partial_rotary_factor", 0.5))) self.gguf_writer.add_add_bos_token(False) rope_freq = 10000 if "rope_ratio" in self.hparams: @@ -4689,7 +4661,7 @@ class ChatGLMModel(Model): def modify_tensors(self, data_torch: Tensor, name: str, bid: int | None) -> Iterable[tuple[str, Tensor]]: del bid # unused - if name.endswith(".rotary_pos_emb.inv_freq"): + if name.endswith(".rotary_pos_emb.inv_freq") or name.startswith("model.vision."): return [] name = name.removeprefix("transformer.") diff --git a/docs/build.md b/docs/build.md index dd6495028..afb7a0402 100644 --- a/docs/build.md +++ b/docs/build.md @@ -125,21 +125,66 @@ For detailed info, please refer to [llama.cpp for SYCL](./backend/SYCL.md). ## CUDA -This provides GPU acceleration using an NVIDIA GPU. Make sure to have the CUDA toolkit installed. You can download it from your Linux distro's package manager (e.g. `apt install nvidia-cuda-toolkit`) or from the [NVIDIA developer site](https://developer.nvidia.com/cuda-downloads). +This provides GPU acceleration using an NVIDIA GPU. Make sure to have the [CUDA toolkit](https://developer.nvidia.com/cuda-toolkit) installed. -If you are using Fedora (using Fedora Workstation, or an 'Atomic' variant such as Silverblue), or would like to set up CUDA in a toolbox, please consider our [Fedora CUDA guide](./cuda-fedora.md). Unfortunately, the process is not as simple as one might expect. +#### Download directly from NVIDIA +You may find the official downloads here: [NVIDIA developer site](https://developer.nvidia.com/cuda-downloads). -- Using `CMake`: - ```bash - cmake -B build -DGGML_CUDA=ON - cmake --build build --config Release - ``` +#### Compile and run inside a Fedora Toolbox Container +We also have a [guide](./cuda-fedora.md) for setting up CUDA toolkit in a Fedora [toolbox container](https://containertoolbx.org/). -The environment variable [`CUDA_VISIBLE_DEVICES`](https://docs.nvidia.com/cuda/cuda-c-programming-guide/index.html#env-vars) can be used to specify which GPU(s) will be used. +**Recommended for:** + +- ***Particularly*** *convenient* for users of [Atomic Desktops for Fedora](https://fedoraproject.org/atomic-desktops/); such as: [Silverblue](https://fedoraproject.org/atomic-desktops/silverblue/) and [Kinoite](https://fedoraproject.org/atomic-desktops/kinoite/). +- Toolbox is installed by default: [Fedora Workstation](https://fedoraproject.org/workstation/) or [Fedora KDE Plasma Desktop](https://fedoraproject.org/spins/kde). +- *Optionally* toolbox packages are available: [Arch Linux](https://archlinux.org/), [Red Hat Enterprise Linux >= 8.5](https://www.redhat.com/en/technologies/linux-platforms/enterprise-linux), or [Ubuntu](https://ubuntu.com/download) + + +### Compilation +```bash +cmake -B build -DGGML_CUDA=ON +cmake --build build --config Release +``` + +### Override Compute Capability Specifications + +If `nvcc` cannot detect your gpu, you may get compile-warnings such as: + ```text +nvcc warning : Cannot find valid GPU for '-arch=native', default arch is used +``` + +To override the `native` GPU detection: + +#### 1. Take note of the `Compute Capability` of your NVIDIA devices: ["CUDA: Your GPU Compute > Capability"](https://developer.nvidia.com/cuda-gpus). + +```text +GeForce RTX 4090 8.9 +GeForce RTX 3080 Ti 8.6 +GeForce RTX 3070 8.6 +``` + +#### 2. Manually list each varying `Compute Capability` in the `CMAKE_CUDA_ARCHITECTURES` list. + +```bash +cmake -B build -DGGML_CUDA=ON -DCMAKE_CUDA_ARCHITECTURES="86;89" +``` + +### Runtime CUDA environmental variables + +You may set the [cuda environmental variables](https://docs.nvidia.com/cuda/cuda-c-programming-guide/index.html#env-vars) at runtime. + +```bash +# Use `CUDA_VISIBLE_DEVICES` to hide the first compute device. +CUDA_VISIBLE_DEVICES="-0" ./build/bin/llama-server --model /srv/models/llama.gguf +``` + +### Unified Memory The environment variable `GGML_CUDA_ENABLE_UNIFIED_MEMORY=1` can be used to enable unified memory in Linux. This allows swapping to system RAM instead of crashing when the GPU VRAM is exhausted. In Windows this setting is available in the NVIDIA control panel as `System Memory Fallback`. +### Performance Tuning + The following compilation options are also available to tweak performance: | Option | Legal values | Default | Description | diff --git a/docs/cuda-fedora.md b/docs/cuda-fedora.md index b993386c8..9c88b7694 100644 --- a/docs/cuda-fedora.md +++ b/docs/cuda-fedora.md @@ -1,17 +1,16 @@ # Setting Up CUDA on Fedora In this guide we setup [Nvidia CUDA](https://docs.nvidia.com/cuda/) in a toolbox container. This guide is applicable for: + - [Fedora Workstation](https://fedoraproject.org/workstation/) - [Atomic Desktops for Fedora](https://fedoraproject.org/atomic-desktops/) - [Fedora Spins](https://fedoraproject.org/spins) -- [Other Distributions](https://containertoolbx.org/distros/), including `Red Hat Enterprise Linux >= 8.`, `Arch Linux`, and `Ubuntu`. - +- [Other Distributions](https://containertoolbx.org/distros/), including `Red Hat Enterprise Linux >= 8.5`, `Arch Linux`, and `Ubuntu`. ## Table of Contents - [Prerequisites](#prerequisites) -- [Monitoring NVIDIA CUDA Repositories](#monitoring-nvidia-cuda-repositories) -- [Using the Fedora 39 CUDA Repository](#using-the-fedora-39-cuda-repository) +- [Using the Fedora 41 CUDA Repository](#using-the-fedora-41-cuda-repository) - [Creating a Fedora Toolbox Environment](#creating-a-fedora-toolbox-environment) - [Installing Essential Development Tools](#installing-essential-development-tools) - [Adding the CUDA Repository](#adding-the-cuda-repository) @@ -29,44 +28,33 @@ In this guide we setup [Nvidia CUDA](https://docs.nvidia.com/cuda/) in a toolbox ## Prerequisites - **Toolbox Installed on the Host System** `Fedora Silverblue` and `Fedora Workstation` both have toolbox by default, other distributions may need to install the [toolbox package](https://containertoolbx.org/install/). -- **NVIDIA Drivers and Graphics Card installed on Host System (optional)** To run CUDA program, such as `llama.cpp`, the host should be setup to access your NVIDIA hardware. Fedora Hosts can use the [RPM Fusion Repository](https://rpmfusion.org/Howto/NVIDIA). +- **NVIDIA Drivers and Graphics Card installed on Host System (recommended)** To run CUDA program, such as `llama.cpp`, the host should be setup to access your NVIDIA hardware. Fedora Hosts can use the [RPM Fusion Repository](https://rpmfusion.org/Howto/NVIDIA). - **Internet connectivity** to download packages. -### Monitoring NVIDIA CUDA Repositories +### Using the Fedora 41 CUDA Repository -Before proceeding, it is advisable to check if NVIDIA has updated their CUDA repositories for your Fedora version. NVIDIA's repositories can be found at: +The latest release is 41. -- [Fedora 40 CUDA Repository](https://developer.download.nvidia.com/compute/cuda/repos/fedora40/x86_64/) - [Fedora 41 CUDA Repository](https://developer.download.nvidia.com/compute/cuda/repos/fedora41/x86_64/) -As of the latest update, these repositories do not contain the `cuda` meta-package or are missing essential components. - -### Using the Fedora 39 CUDA Repository - -Since the newer repositories are incomplete, we'll use the Fedora 39 repository: - -- [Fedora 39 CUDA Repository](https://developer.download.nvidia.com/compute/cuda/repos/fedora39/x86_64/) - -**Note:** Fedora 39 is no longer maintained, so we recommend using a toolbox environment to prevent system conflicts. +**Note:** We recommend using a toolbox environment to prevent system conflicts. ## Creating a Fedora Toolbox Environment -This guide focuses on Fedora hosts, but with small adjustments, it can work for other hosts. Using a Fedora 39 toolbox allows us to install the necessary packages without affecting the host system. +This guide focuses on Fedora hosts, but with small adjustments, it can work for other hosts. Using the Fedora Toolbox allows us to install the necessary packages without affecting the host system. **Note:** Toolbox is available for other systems, and even without Toolbox, it is possible to use Podman or Docker. -We do not recommend installing on the host system, as Fedora 39 is out-of-maintenance, and instead you should upgrade to a maintained version of Fedora for your host. - -1. **Create a Fedora 39 Toolbox:** +1. **Create a Fedora 41 Toolbox:** ```bash - toolbox create --image registry.fedoraproject.org/fedora-toolbox:39 --container fedora-toolbox-39-cuda + toolbox create --image registry.fedoraproject.org/fedora-toolbox:41 --container fedora-toolbox-41-cuda ``` 2. **Enter the Toolbox:** ```bash - toolbox enter --container fedora-toolbox-39-cuda + toolbox enter --container fedora-toolbox-41-cuda ``` Inside the toolbox, you have root privileges and can install packages without affecting the host system. @@ -85,7 +73,7 @@ We do not recommend installing on the host system, as Fedora 39 is out-of-mainte sudo dnf install vim-default-editor --allowerasing ``` - The `--allowerasing` flag resolves any package conflicts. + The `--allowerasing` flag will allow the removal of the conflicting `nano-default-editor` package. 3. **Install Development Tools and Libraries:** @@ -100,7 +88,7 @@ We do not recommend installing on the host system, as Fedora 39 is out-of-mainte Add the NVIDIA CUDA repository to your DNF configuration: ```bash -sudo dnf config-manager --add-repo https://developer.download.nvidia.com/compute/cuda/repos/fedora39/x86_64/cuda-fedora39.repo +sudo dnf config-manager addrepo --from-repofile=https://developer.download.nvidia.com/compute/cuda/repos/fedora41/x86_64/cuda-fedora41.repo ``` After adding the repository, synchronize the package manager again: @@ -109,106 +97,62 @@ After adding the repository, synchronize the package manager again: sudo dnf distro-sync ``` -## Installing `nvidia-driver-libs` +## Installing `nvidia-driver-libs` and `nvidia-driver-cuda-libs` -Attempt to install `nvidia-driver-libs`: +We need to detect if the host is supplying the [NVIDIA driver libraries into the toolbox](https://github.com/containers/toolbox/blob/main/src/pkg/nvidia/nvidia.go). ```bash -sudo dnf install nvidia-driver-libs +ls -la /usr/lib64/libcuda.so.1 ``` **Explanation:** -- `nvidia-driver-libs` contains necessary NVIDIA driver libraries required by CUDA. -- This step might fail due to conflicts with existing NVIDIA drivers on the host system. +- `nvidia-driver-libs` and `nvidia-driver-cuda-libs` contains necessary NVIDIA driver libraries required by CUDA, + on hosts with NVIDIA drivers installed the Fedora Container will supply the host libraries. -## Manually Resolving Package Conflicts +### Install Nvidia Driver Libraries on Guest (if `libcuda.so.1` was NOT found). + +```bash +sudo dnf install nvidia-driver-libs nvidia-driver-cuda-libs +``` + +### Manually Updating the RPM database for host-supplied NVIDIA drivers (if `libcuda.so.1` was found). If the installation fails due to conflicts, we'll manually download and install the required packages, excluding conflicting files. -### 1. Download the `nvidia-driver-libs` RPM +#### 1. Download `nvidia-driver-libs` and `nvidia-driver-cuda-libs` RPM's (with dependencies) ```bash -sudo dnf download --arch x86_64 nvidia-driver-libs +sudo dnf download --destdir=/tmp/nvidia-driver-libs --resolve --arch x86_64 nvidia-driver-libs nvidia-driver-cuda-libs ``` -You should see a file similar to: - -``` -nvidia-driver-libs-560.35.05-1.fc39.x86_64.rpm -``` - -### 2. Attempt to Install the RPM +#### 2. Update the RPM database to assume the installation of these packages. ```bash -sudo dnf install nvidia-driver-libs-560.35.05-1.fc39.x86_64.rpm -``` - -**Expected Error:** - -Installation may fail with errors pointing to conflicts with `egl-gbm` and `egl-wayland`. - -**Note: It is important to carefully read the error messages to identify the exact paths that need to be excluded.** - -### 3. Download Dependencies - -```bash -sudo dnf download --arch x86_64 egl-gbm egl-wayland -``` - -### 4. Install `egl-gbm` with Excluded Paths - -Exclude conflicting files during installation: - -```bash -sudo rpm --install --verbose --hash \ - --excludepath=/usr/lib64/libnvidia-egl-gbm.so.1.1.2 \ - --excludepath=/usr/share/egl/egl_external_platform.d/15_nvidia_gbm.json \ - egl-gbm-1.1.2^20240919gitb24587d-3.fc39.x86_64.rpm -``` - -**Explanation:** - -- The `--excludepath` option skips installing files that conflict with existing files. -- Adjust the paths based on the error messages you receive. - -### 5. Install `egl-wayland` with Excluded Paths - -```bash -sudo rpm --install --verbose --hash \ - --excludepath=/usr/share/egl/egl_external_platform.d/10_nvidia_wayland.json \ - egl-wayland-1.1.17^20241118giteeb29e1-5.fc39.x86_64.rpm -``` - -### 6. Install `nvidia-driver-libs` with Excluded Paths - -```bash -sudo rpm --install --verbose --hash \ - --excludepath=/usr/share/glvnd/egl_vendor.d/10_nvidia.json \ - --excludepath=/usr/share/nvidia/nvoptix.bin \ - nvidia-driver-libs-560.35.05-1.fc39.x86_64.rpm +sudo rpm --install --verbose --hash --justdb /tmp/nvidia-driver-libs/* ``` **Note:** -- Replace the paths with the ones causing conflicts in your installation if they differ. -- The `--verbose` and `--hash` options provide detailed output during installation. +- The `--justdb` option only updates the RPM database, without touching the filesystem. -## Finalizing the Installation of `nvidia-driver-libs` +#### Finalizing the Installation of `nvidia-driver-libs` and `nvidia-driver-cuda-libs` After manually installing the dependencies, run: ```bash -sudo dnf install nvidia-driver-libs +sudo dnf install nvidia-driver-libs nvidia-driver-cuda-libs ``` You should receive a message indicating the package is already installed: ``` -Package nvidia-driver-libs-3:560.35.05-1.fc39.x86_64 is already installed. -Dependencies resolved. +Updating and loading repositories: +Repositories loaded. +Package "nvidia-driver-libs-3:570.86.10-1.fc41.x86_64" is already installed. +Package "nvidia-driver-cuda-libs-3:570.86.10-1.fc41.x86_64" is already installed. + Nothing to do. -Complete! ``` ## Installing the CUDA Meta-Package @@ -233,7 +177,7 @@ To use CUDA, add its binary directory to your system's `PATH`. **Explanation:** - - We add to `/etc/profile.d/` as the `/etc/` folder is unique to this particular container, and is not shared with other containers or the host system. + - We add to `/etc/profile.d/` as the `/etc/` folder is unique to this particular container, and is not shared with other containers or the host system. - The backslash `\` before `$PATH` ensures the variable is correctly written into the script. 2. **Make the Script Executable:** @@ -262,26 +206,33 @@ You should see output similar to: ``` nvcc: NVIDIA (R) Cuda compiler driver -Copyright (c) 2005-2024 NVIDIA Corporation -Built on Tue_Oct_29_23:50:19_PDT_2024 -Cuda compilation tools, release 12.6, V12.6.85 -Build cuda_12.6.r12.6/compiler.35059454_0 +Copyright (c) 2005-2025 NVIDIA Corporation +Built on Wed_Jan_15_19:20:09_PST_2025 +Cuda compilation tools, release 12.8, V12.8.61 +Build cuda_12.8.r12.8/compiler.35404655_0 ``` This output confirms that the CUDA compiler is accessible and indicates the installed version. ## Conclusion -You have successfully set up CUDA on Fedora within a toolbox environment using the Fedora 39 CUDA repository. By manually resolving package conflicts and configuring the environment, you can develop CUDA applications without affecting your host system. +You have successfully set up CUDA on Fedora within a toolbox environment using the Fedora 41 CUDA repository. By manually updating the RPM db and configuring the environment, you can develop CUDA applications without affecting your host system. ## Troubleshooting - **Installation Failures:** - - If you encounter errors during installation, carefully read the error messages. They often indicate conflicting files or missing dependencies. - - Use the `--excludepath` option with `rpm` to exclude conflicting files during manual installations. -- **Driver Conflicts:** - - Since the host system may already have NVIDIA drivers installed, conflicts can arise. Using the toolbox environment helps isolate these issues. + - If you encounter errors during installation, carefully read the error messages. They often indicate conflicting files or missing dependencies. + - You may use the `--excludepath` option with `rpm` to exclude conflicting files during manual RPM installations. + +- **Rebooting the Container:** + + - Sometimes there may be a bug in the NVIDIA driver host passthrough (such as missing a shared library). Rebooting the container may solve this issue: + + ```bash + # on the host system + podman container restart --all + ``` - **Environment Variables Not Set:** - If `nvcc` is not found after installation, ensure that `/usr/local/cuda/bin` is in your `PATH`. @@ -291,10 +242,12 @@ You have successfully set up CUDA on Fedora within a toolbox environment using t ## Additional Notes - **Updating CUDA in the Future:** + - Keep an eye on the official NVIDIA repositories for updates to your Fedora version. - When an updated repository becomes available, adjust your `dnf` configuration accordingly. - **Building `llama.cpp`:** + - With CUDA installed, you can follow these [build instructions for `llama.cpp`](https://github.com/ggerganov/llama.cpp/blob/master/docs/build.md) to compile it with CUDA support. - Ensure that any CUDA-specific build flags or paths are correctly set in your build configuration. diff --git a/docs/llguidance.md b/docs/llguidance.md new file mode 100644 index 000000000..792d20704 --- /dev/null +++ b/docs/llguidance.md @@ -0,0 +1,51 @@ +# LLGuidance Support in llama.cpp + +[LLGuidance](https://github.com/guidance-ai/llguidance) is a library for constrained decoding (also called constrained sampling or structured outputs) for Large Language Models (LLMs). Initially developed as the backend for the [Guidance](https://github.com/guidance-ai/guidance) library, it can also be used independently. + +LLGuidance supports JSON Schemas and arbitrary context-free grammars (CFGs) written in a [variant](https://github.com/guidance-ai/llguidance/blob/main/docs/syntax.md) of Lark syntax. It is [very fast](https://github.com/guidance-ai/jsonschemabench/tree/main/maskbench) and has [excellent](https://github.com/guidance-ai/llguidance/blob/main/docs/json_schema.md) JSON Schema coverage but requires the Rust compiler, which complicates the llama.cpp build process. + +## Building + +To enable LLGuidance support, build llama.cpp with the `LLAMA_LLGUIDANCE` option: + +```sh +cmake -B build -DLLAMA_LLGUIDANCE=ON +make -C build -j +``` + +This requires the Rust compiler and the `cargo` tool to be [installed](https://www.rust-lang.org/tools/install). + +## Interface + +There are no new command-line arguments or modifications to `common_params`. When enabled, grammars starting with `%llguidance` are passed to LLGuidance instead of the [current](../grammars/README.md) llama.cpp grammars. Additionally, JSON Schema requests (e.g., using the `-j` argument in `llama-cli`) are also passed to LLGuidance. + +For your existing GBNF grammars, you can use [gbnf_to_lark.py script](https://github.com/guidance-ai/llguidance/blob/main/scripts/gbnf_to_lark.py) to convert them to LLGuidance Lark-like format. + +## Performance + +Computing a "token mask" (i.e., the set of allowed tokens) for a llama3 tokenizer with 128k tokens takes, on average, 50μs of single-core CPU time for the [JSON Schema Bench](https://github.com/guidance-ai/jsonschemabench). The p99 time is 0.5ms, and the p100 time is 20ms. These results are due to the lexer/parser split and several [optimizations](https://github.com/guidance-ai/llguidance/blob/main/docs/optimizations.md). + +## JSON Schema + +LLGuidance adheres closely to the JSON Schema specification. For example: + +- `additionalProperties` defaults to `true`, unlike current grammars, though you can set `"additionalProperties": false` if needed. +- any whitespace is allowed. +- The definition order in the `"properties": {}` object is maintained, regardless of whether properties are required (current grammars always puts required properties first). + +Unsupported schemas result in an error message—no keywords are silently ignored. + +## Why Not Reuse GBNF Format? + +GBNF lacks the concept of a lexer. + +Most programming languages, including JSON, use a two-step process: a lexer (built with regular expressions) converts a byte stream into lexemes, which are then processed by a CFG parser. This approach is faster because lexers are cheaper to evaluate, and there is ~10x fewer lexemes than bytes. +LLM tokens often align with lexemes, so the parser is engaged in under 0.5% of tokens, with the lexer handling the rest. + +However, the user has to provide the distinction between lexemes and CFG symbols. In [Lark](https://github.com/lark-parser/lark), lexeme names are uppercase, while CFG symbols are lowercase. +The [gbnf_to_lark.py script](https://github.com/guidance-ai/llguidance/blob/main/scripts/gbnf_to_lark.py) can often take care of this automatically. +See [LLGuidance syntax docs](https://github.com/guidance-ai/llguidance/blob/main/docs/syntax.md#terminals-vs-rules) for more details. + +## Error Handling + +Errors are currently printed to `stderr`, and generation continues. Improved error handling may be added in the future. diff --git a/examples/batched.swift/Sources/main.swift b/examples/batched.swift/Sources/main.swift index 371917b2e..55c31166c 100644 --- a/examples/batched.swift/Sources/main.swift +++ b/examples/batched.swift/Sources/main.swift @@ -31,6 +31,11 @@ defer { llama_model_free(model) } +guard let vocab = llama_model_get_vocab(model) else { + print("Failed to get vocab") + exit(1) +} + var tokens = tokenize(text: prompt, add_bos: true) let n_kv_req = UInt32(tokens.count) + UInt32((n_len - Int(tokens.count)) * n_parallel) @@ -41,7 +46,7 @@ context_params.n_batch = UInt32(max(n_len, n_parallel)) context_params.n_threads = 8 context_params.n_threads_batch = 8 -let context = llama_new_context_with_model(model, context_params) +let context = llama_init_from_model(model, context_params) guard context != nil else { print("Failed to initialize context") exit(1) @@ -141,7 +146,7 @@ while n_cur <= n_len { let new_token_id = llama_sampler_sample(smpl, context, i_batch[i]) // is it an end of stream? -> mark the stream as finished - if llama_vocab_is_eog(model, new_token_id) || n_cur == n_len { + if llama_vocab_is_eog(vocab, new_token_id) || n_cur == n_len { i_batch[i] = -1 // print("") if n_parallel > 1 { @@ -207,7 +212,7 @@ private func tokenize(text: String, add_bos: Bool) -> [llama_token] { let utf8Count = text.utf8.count let n_tokens = utf8Count + (add_bos ? 1 : 0) let tokens = UnsafeMutablePointer.allocate(capacity: n_tokens) - let tokenCount = llama_tokenize(model, text, Int32(utf8Count), tokens, Int32(n_tokens), add_bos, /*special tokens*/ false) + let tokenCount = llama_tokenize(vocab, text, Int32(utf8Count), tokens, Int32(n_tokens), add_bos, /*special tokens*/ false) var swiftTokens: [llama_token] = [] for i in 0 ..< tokenCount { swiftTokens.append(tokens[Int(i)]) @@ -218,12 +223,12 @@ private func tokenize(text: String, add_bos: Bool) -> [llama_token] { private func token_to_piece(token: llama_token, buffer: inout [CChar]) -> String? { var result = [CChar](repeating: 0, count: 8) - let nTokens = llama_token_to_piece(model, token, &result, Int32(result.count), 0, false) + let nTokens = llama_token_to_piece(vocab, token, &result, Int32(result.count), 0, false) if nTokens < 0 { let actualTokensCount = -Int(nTokens) result = .init(repeating: 0, count: actualTokensCount) let check = llama_token_to_piece( - model, + vocab, token, &result, Int32(result.count), diff --git a/examples/llama.swiftui/llama.cpp.swift/LibLlama.swift b/examples/llama.swiftui/llama.cpp.swift/LibLlama.swift index 477c3e6f2..ee7141a66 100644 --- a/examples/llama.swiftui/llama.cpp.swift/LibLlama.swift +++ b/examples/llama.swiftui/llama.cpp.swift/LibLlama.swift @@ -24,6 +24,7 @@ func llama_batch_add(_ batch: inout llama_batch, _ id: llama_token, _ pos: llama actor LlamaContext { private var model: OpaquePointer private var context: OpaquePointer + private var vocab: OpaquePointer private var sampling: UnsafeMutablePointer private var batch: llama_batch private var tokens_list: [llama_token] @@ -47,6 +48,7 @@ actor LlamaContext { self.sampling = llama_sampler_chain_init(sparams) llama_sampler_chain_add(self.sampling, llama_sampler_init_temp(0.4)) llama_sampler_chain_add(self.sampling, llama_sampler_init_dist(1234)) + vocab = llama_model_get_vocab(model) } deinit { @@ -79,7 +81,7 @@ actor LlamaContext { ctx_params.n_threads = Int32(n_threads) ctx_params.n_threads_batch = Int32(n_threads) - let context = llama_new_context_with_model(model, ctx_params) + let context = llama_init_from_model(model, ctx_params) guard let context else { print("Could not load context!") throw LlamaError.couldNotInitializeContext @@ -151,7 +153,7 @@ actor LlamaContext { new_token_id = llama_sampler_sample(sampling, context, batch.n_tokens - 1) - if llama_vocab_is_eog(model, new_token_id) || n_cur == n_len { + if llama_vocab_is_eog(vocab, new_token_id) || n_cur == n_len { print("\n") is_done = true let new_token_str = String(cString: temporary_invalid_cchars + [0]) @@ -297,7 +299,7 @@ actor LlamaContext { let utf8Count = text.utf8.count let n_tokens = utf8Count + (add_bos ? 1 : 0) + 1 let tokens = UnsafeMutablePointer.allocate(capacity: n_tokens) - let tokenCount = llama_tokenize(model, text, Int32(utf8Count), tokens, Int32(n_tokens), add_bos, false) + let tokenCount = llama_tokenize(vocab, text, Int32(utf8Count), tokens, Int32(n_tokens), add_bos, false) var swiftTokens: [llama_token] = [] for i in 0...allocate(capacity: Int(-nTokens)) @@ -324,7 +326,7 @@ actor LlamaContext { defer { newResult.deallocate() } - let nNewTokens = llama_token_to_piece(model, token, newResult, -nTokens, 0, false) + let nNewTokens = llama_token_to_piece(vocab, token, newResult, -nTokens, 0, false) let bufferPointer = UnsafeBufferPointer(start: newResult, count: Int(nNewTokens)) return Array(bufferPointer) } else { diff --git a/examples/llava/CMakeLists.txt b/examples/llava/CMakeLists.txt index 3ce0d60c8..319effd19 100644 --- a/examples/llava/CMakeLists.txt +++ b/examples/llava/CMakeLists.txt @@ -50,3 +50,10 @@ set_target_properties(${TARGET} PROPERTIES OUTPUT_NAME llama-qwen2vl-cli) install(TARGETS ${TARGET} RUNTIME) target_link_libraries(${TARGET} PRIVATE common llava ${CMAKE_THREAD_LIBS_INIT}) target_compile_features(${TARGET} PRIVATE cxx_std_17) + +set(TARGET llama-llava-clip-quantize-cli) +add_executable(${TARGET} clip-quantize-cli.cpp) +set_target_properties(${TARGET} PROPERTIES OUTPUT_NAME llama-llava-clip-quantize-cli) +install(TARGETS ${TARGET} RUNTIME) +target_link_libraries(${TARGET} PRIVATE common llava ${CMAKE_THREAD_LIBS_INIT}) +target_compile_features(${TARGET} PRIVATE cxx_std_17) diff --git a/examples/llava/README-glmedge.md b/examples/llava/README-glmedge.md new file mode 100644 index 000000000..603d01474 --- /dev/null +++ b/examples/llava/README-glmedge.md @@ -0,0 +1,43 @@ +# GLMV-EDGE + +Currently this implementation supports [glm-edge-v-2b](https://huggingface.co/THUDM/glm-edge-v-2b) and [glm-edge-v-5b](https://huggingface.co/THUDM/glm-edge-v-5b). + +## Usage +Build with cmake or run `make llama-llava-cli` to build it. + +After building, run: `./llama-llava-cli` to see the usage. For example: + +```sh +./llama-llava-cli -m model_path/ggml-model-f16.gguf --mmproj model_path/mmproj-model-f16.gguf --image img_path/image.jpg -p "<|system|>\n system prompt <|user|>\n prompt <|assistant|>\n" +``` + +**note**: A lower temperature like 0.1 is recommended for better quality. add `--temp 0.1` to the command to do so. +**note**: For GPU offloading ensure to use the `-ngl` flag just like usual + +## GGUF conversion + +1. Clone a GLMV-EDGE model ([2B](https://huggingface.co/THUDM/glm-edge-v-2b) or [5B](https://huggingface.co/THUDM/glm-edge-v-5b)). For example: + +```sh +git clone https://huggingface.co/THUDM/glm-edge-v-5b or https://huggingface.co/THUDM/glm-edge-v-2b +``` + +2. Use `glmedge-surgery.py` to split the GLMV-EDGE model to LLM and multimodel projector constituents: + +```sh +python ./examples/llava/glmedge-surgery.py -m ../model_path +``` + +4. Use `glmedge-convert-image-encoder-to-gguf.py` to convert the GLMV-EDGE image encoder to GGUF: + +```sh +python ./examples/llava/glmedge-convert-image-encoder-to-gguf.py -m ../model_path --llava-projector ../model_path/glm.projector --output-dir ../model_path +``` + +5. Use `examples/convert_hf_to_gguf.py` to convert the LLM part of GLMV-EDGE to GGUF: + +```sh +python convert_hf_to_gguf.py ../model_path +``` + +Now both the LLM part and the image encoder are in the `model_path` directory. diff --git a/examples/llava/README-quantize.md b/examples/llava/README-quantize.md new file mode 100644 index 000000000..b931513ab --- /dev/null +++ b/examples/llava/README-quantize.md @@ -0,0 +1,44 @@ +# Quantizing CLIP Visual Projector + +This is the tool for quantizing the CLIP visual projector model. Quantization reduces the precision of the model's weights, which can significantly decrease the model size and improve inference speed, often with minimal impact on performance. + +## Usage + +To quantize a CLIP visual projector model, use the following command: + +```sh +./bin/llama-llava-clip-quantize-cli /path/to/ggml-model-f32.gguf /path/to/ggml-model-quantized.gguf +``` + +After the quantization, the visual projector can be used freely with the existing LLAVA cli (LLAVA, Qwen2VL, etc). + +### Arguments + +- `/path/to/ggml-model-f32.gguf`: The path to the input model file in FP32 or FP16 format. +- `/path/to/ggml-model-quantized.gguf`: The path where the quantized model will be saved. +- ``: The quantization type to apply. This should be an integer corresponding to one of the quantization types defined in the `enum ggml_type`. + +### Quantization Types + +The following quantization types are supported, based on the `enum ggml_type` definition: + +- `2` - `q4_0`: 4-bit quantization with a single scale value. +- `3` - `q4_1`: 4-bit quantization with a separate scale value for each block. +- `6` - `q5_0`: 5-bit quantization with a single scale value. +- `7` - `q5_1`: 5-bit quantization with a separate scale value for each block. +- `8` - `q8_0`: 8-bit quantization with a single scale value. + +### Example + +To quantize a model using the `q4_0` quantization type, you would run: + +```sh +./bin/llama-llava-clip-quantize-cli /path/to/ggml-model-f32.gguf /path/to/ggml-model-quantized.gguf 2 +``` + +This command will generate a quantized model at `/path/to/ggml-model-quantized.gguf` using the `q4_0` quantization method. + +## Notes + +- Quantization can lead to a loss in model accuracy, depending on the chosen quantization type. It is recommended to evaluate the quantized model's performance on your specific task to ensure it meets your requirements. +- The quantized model will typically be smaller in size and faster to run, making it more suitable for deployment in resource-constrained environments. diff --git a/examples/llava/clip-quantize-cli.cpp b/examples/llava/clip-quantize-cli.cpp new file mode 100644 index 000000000..566506954 --- /dev/null +++ b/examples/llava/clip-quantize-cli.cpp @@ -0,0 +1,59 @@ +#include "arg.h" +#include "base64.hpp" +#include "log.h" +#include "common.h" +#include "sampling.h" +#include "clip.h" +#include "llava.h" +#include "llama.h" +#include "ggml.h" + +static void print_usage(int argc, char ** argv) { + (void) argc; + + fprintf(stderr, "usage: %s /path/to/ggml-model-f32.gguf /path/to/ggml-model-quantized.gguf type\n", argv[0]); + fprintf(stderr, " type = 2 - q4_0\n"); + fprintf(stderr, " type = 3 - q4_1\n"); + fprintf(stderr, " type = 6 - q5_0\n"); + fprintf(stderr, " type = 7 - q5_1\n"); + fprintf(stderr, " type = 8 - q8_0\n"); +} + +int main(int argc, char ** argv) { + if (argc != 4) { + print_usage(argc, argv); + return 1; + } + + const std::string fname_inp = argv[1]; + const std::string fname_out = argv[2]; + + const int itype = atoi(argv[3]); + + const int64_t t_main_start_us = ggml_time_us(); + + int64_t t_quantize_us = 0; + + // load the model + { + const int64_t t_start_us = ggml_time_us(); + + if (!clip_model_quantize(fname_inp.c_str(), fname_out.c_str(), itype)) { + fprintf(stderr, "%s: failed to quantize model from '%s'\n", __func__, fname_inp.c_str()); + return 1; + } + + t_quantize_us = ggml_time_us() - t_start_us; + } + + // report timing + { + const int64_t t_main_end_us = ggml_time_us(); + + printf("\n"); + printf("%s: quantize time = %8.2f ms\n", __func__, t_quantize_us / 1000.0f); + printf("%s: total time = %8.2f ms\n", __func__, (t_main_end_us - t_main_start_us) / 1000.0f); + } + + return 0; +} diff --git a/examples/llava/clip.cpp b/examples/llava/clip.cpp index 24073c5a9..271cf2a2a 100644 --- a/examples/llava/clip.cpp +++ b/examples/llava/clip.cpp @@ -102,6 +102,7 @@ static std::string format(const char * fmt, ...) { #define KEY_HAS_VIS_ENC "clip.has_vision_encoder" #define KEY_HAS_LLAVA_PROJ "clip.has_llava_projector" #define KEY_HAS_MINICPMV_PROJ "clip.has_minicpmv_projector" +#define KEY_HAS_GLM_PROJ "clip.has_glm_projector" #define KEY_MINICPMV_VERSION "clip.minicpmv_version" #define KEY_HAS_QWEN2VL_MERGER "clip.has_qwen2vl_merger" #define KEY_USE_GELU "clip.use_gelu" @@ -160,6 +161,15 @@ static std::string format(const char * fmt, ...) { #define TN_MINICPMV_ATTN "resampler.attn.%s.%s" #define TN_MINICPMV_LN "resampler.ln_%s.%s" +#define TN_GLM_ADAPER_CONV "adapter.conv.%s" +#define TN_GLM_ADAPTER_LINEAR "adapter.linear.linear.%s" +#define TN_GLM_ADAPTER_NORM_1 "adapter.linear.norm1.%s" +#define TN_GLM_ADAPTER_D_H_2_4H "adapter.linear.dense_h_to_4h.%s" +#define TN_GLM_ADAPTER_GATE "adapter.linear.gate.%s" +#define TN_GLM_ADAPTER_D_4H_2_H "adapter.linear.dense_4h_to_h.%s" +#define TN_GLM_BOI_W "adapter.boi" +#define TN_GLM_EOI_W "adapter.eoi" + enum projector_type { PROJECTOR_TYPE_MLP, @@ -167,6 +177,7 @@ enum projector_type { PROJECTOR_TYPE_LDP, PROJECTOR_TYPE_LDPV2, PROJECTOR_TYPE_RESAMPLER, + PROJECTOR_TYPE_GLM_EDGE, PROJECTOR_TYPE_MERGER, PROJECTOR_TYPE_UNKNOWN, }; @@ -176,6 +187,7 @@ static std::map PROJECTOR_TYPE_NAMES = { { PROJECTOR_TYPE_LDP, "ldp" }, { PROJECTOR_TYPE_LDPV2, "ldpv2"}, { PROJECTOR_TYPE_RESAMPLER, "resampler"}, + { PROJECTOR_TYPE_GLM_EDGE, "adapter"}, { PROJECTOR_TYPE_MERGER, "qwen2vl_merger"}, }; @@ -500,6 +512,12 @@ struct clip_vision_model { struct ggml_tensor * mm_4_w = NULL; struct ggml_tensor * mm_4_b = NULL; + //GLMV-Edge projection + struct ggml_tensor * mm_model_adapter_conv_w; + struct ggml_tensor * mm_model_adapter_conv_b; + struct ggml_tensor * boi_w; + struct ggml_tensor * eoi_w; + // MobileVLM projection struct ggml_tensor * mm_model_mlp_1_w; struct ggml_tensor * mm_model_mlp_1_b; @@ -560,6 +578,7 @@ struct clip_ctx { bool has_vision_encoder = false; bool has_llava_projector = false; bool has_minicpmv_projector = false; + bool has_glm_projector = false; bool has_qwen2vl_merger = false; int minicpmv_version = 2; @@ -638,7 +657,7 @@ static ggml_cgraph * clip_image_build_graph(clip_ctx * ctx, const clip_image_f32 const int batch_size = imgs->size; - if (ctx->has_llava_projector || ctx->has_minicpmv_projector) { + if (ctx->has_llava_projector || ctx->has_minicpmv_projector || ctx->has_glm_projector) { GGML_ASSERT(batch_size == 1); } @@ -734,8 +753,7 @@ static ggml_cgraph * clip_image_build_graph(clip_ctx * ctx, const clip_image_f32 } // loop over layers - if (ctx->has_minicpmv_projector || ctx->has_qwen2vl_merger) { - // TODO: figure out why we doing thing in this way ??? + if (ctx->has_minicpmv_projector || ctx->has_glm_projector || ctx->has_qwen2vl_merger) { n_layer += 1; } for (int il = 0; il < n_layer - 1; il++) { @@ -1095,7 +1113,33 @@ static ggml_cgraph * clip_image_build_graph(clip_ctx * ctx, const clip_image_f32 GGML_ASSERT(false); } } - else if (ctx->proj_type == PROJECTOR_TYPE_MERGER) { + // glm projector + else if (ctx->has_glm_projector) { + if (ctx->proj_type == PROJECTOR_TYPE_GLM_EDGE) { + size_t gridsz = (size_t)sqrt(embeddings->ne[1]); + embeddings = ggml_cont(ctx0, ggml_permute(ctx0,embeddings,1,0,2,3)); + embeddings = ggml_reshape_3d(ctx0, embeddings, gridsz, gridsz, embeddings->ne[1]); + embeddings = ggml_conv_2d(ctx0, model.mm_model_adapter_conv_w, embeddings, 2, 2, 0, 0, 1, 1); + embeddings = ggml_reshape_3d(ctx0, embeddings,embeddings->ne[0]*embeddings->ne[1] , embeddings->ne[2], batch_size); + embeddings = ggml_cont(ctx0, ggml_permute(ctx0,embeddings, 1, 0, 2, 3)); + embeddings = ggml_add(ctx0, embeddings, model.mm_model_adapter_conv_b); + //GLU + { + embeddings = ggml_mul_mat(ctx0, model.mm_model_mlp_0_w, embeddings); + embeddings = ggml_norm(ctx0, embeddings, eps); + embeddings = ggml_add(ctx0, ggml_mul(ctx0, embeddings, model.mm_model_ln_q_w), model.mm_model_ln_q_b); + embeddings = ggml_gelu_inplace(ctx0, embeddings); + struct ggml_tensor * x = embeddings; + embeddings = ggml_mul_mat(ctx0, model.mm_model_mlp_2_w, embeddings); + x = ggml_mul_mat(ctx0, model.mm_model_mlp_1_w,x); + embeddings = ggml_silu_inplace(ctx0, embeddings); + embeddings = ggml_mul(ctx0, embeddings,x); + embeddings = ggml_mul_mat(ctx0, model.mm_model_mlp_3_w, embeddings); + } + } else { + GGML_ABORT("fatel error"); + } + } else if (ctx->proj_type == PROJECTOR_TYPE_MERGER) { embeddings = ggml_reshape_3d(ctx0, embeddings, hidden_size * 4, num_positions / 4, batch_size); embeddings = ggml_mul_mat(ctx0, model.mm_0_w, embeddings); @@ -1284,6 +1328,11 @@ struct clip_ctx * clip_model_load(const char * fname, const int verbosity = 1) { new_clip->minicpmv_version = gguf_get_val_i32(ctx, idx); } + idx = gguf_find_key(ctx, KEY_HAS_GLM_PROJ); + if (idx != -1) { + new_clip->has_glm_projector = gguf_get_val_bool(ctx, idx); + } + idx = gguf_find_key(ctx, KEY_HAS_QWEN2VL_MERGER); if (idx != -1) { new_clip->has_qwen2vl_merger = gguf_get_val_bool(ctx, idx); @@ -1308,6 +1357,7 @@ struct clip_ctx * clip_model_load(const char * fname, const int verbosity = 1) { LOG_INF("%s: vision_encoder: %d\n", __func__, new_clip->has_vision_encoder); LOG_INF("%s: llava_projector: %d\n", __func__, new_clip->has_llava_projector); LOG_INF("%s: minicpmv_projector: %d\n", __func__, new_clip->has_minicpmv_projector); + LOG_INF("%s: glm_projector: %d\n", __func__, new_clip->has_glm_projector); LOG_INF("%s: model size: %.2f MB\n", __func__, model_size / 1024.0 / 1024.0); LOG_INF("%s: metadata size: %.2f MB\n", __func__, ggml_get_mem_size(meta) / 1024.0 / 1024.0); } @@ -1575,6 +1625,18 @@ struct clip_ctx * clip_model_load(const char * fname, const int verbosity = 1) { vision_model.mm_model_ln_post_w = get_tensor(new_clip->ctx_data, format(TN_MINICPMV_LN, "post", "weight")); vision_model.mm_model_ln_post_b = get_tensor(new_clip->ctx_data, format(TN_MINICPMV_LN, "post", "bias")); } + else if (new_clip->proj_type == PROJECTOR_TYPE_GLM_EDGE) { + vision_model.mm_model_adapter_conv_w = get_tensor(new_clip->ctx_data, format(TN_GLM_ADAPER_CONV, "weight")); + vision_model.mm_model_adapter_conv_b = get_tensor(new_clip->ctx_data, format(TN_GLM_ADAPER_CONV, "bias")); + vision_model.mm_model_mlp_0_w = get_tensor(new_clip->ctx_data, format(TN_GLM_ADAPTER_LINEAR,"weight")); + vision_model.mm_model_ln_q_w = get_tensor(new_clip->ctx_data, format(TN_GLM_ADAPTER_NORM_1,"weight")); + vision_model.mm_model_ln_q_b = get_tensor(new_clip->ctx_data, format(TN_GLM_ADAPTER_NORM_1,"bias")); + vision_model.mm_model_mlp_1_w = get_tensor(new_clip->ctx_data, format(TN_GLM_ADAPTER_D_H_2_4H,"weight")); + vision_model.mm_model_mlp_2_w = get_tensor(new_clip->ctx_data, format(TN_GLM_ADAPTER_GATE,"weight")); + vision_model.mm_model_mlp_3_w = get_tensor(new_clip->ctx_data, format(TN_GLM_ADAPTER_D_4H_2_H,"weight")); + vision_model.boi_w = get_tensor(new_clip->ctx_data, TN_GLM_BOI_W); + vision_model.eoi_w = get_tensor(new_clip->ctx_data, TN_GLM_EOI_W); + } else if (new_clip->proj_type == PROJECTOR_TYPE_MERGER) { vision_model.mm_0_w = get_tensor(new_clip->ctx_data, format(TN_LLAVA_PROJ, 0, "weight")); vision_model.mm_0_b = get_tensor(new_clip->ctx_data, format(TN_LLAVA_PROJ, 0, "bias")); @@ -2115,6 +2177,20 @@ bool clip_image_preprocess(struct clip_ctx * ctx, const clip_image_u8 * img, cli return true; } + if (ctx->has_glm_projector) { + res_imgs->size = 1; + res_imgs->data = new clip_image_f32[res_imgs->size]; + clip_image_u8 resized_image; + int32_t sz=ctx->vision_model.hparams.image_size; + bicubic_resize(*img, resized_image,sz,sz); + clip_image_f32 * res = clip_image_f32_init(); + //clip_image_save_to_bmp(resized_image, "resized.bmp"); + normalize_image_u8_to_f32(&resized_image, res, ctx->image_mean, ctx->image_std); + res_imgs->data[0] = *res; + clip_image_f32_free(res); + return true; + } + bool pad_to_square = true; if (!ctx->has_vision_encoder) { LOG_ERR("This gguf file seems to have no vision encoder\n"); @@ -2300,7 +2376,8 @@ void clip_free(clip_ctx * ctx) { } size_t clip_embd_nbytes(const struct clip_ctx * ctx) { - return clip_n_patches(ctx) * clip_n_mmproj_embd(ctx) * sizeof(float); + int extra_tokens = ctx->has_glm_projector ? 2 : 0; + return (clip_n_patches(ctx) + extra_tokens) * clip_n_mmproj_embd(ctx) * sizeof(float); } size_t clip_embd_nbytes_by_img(const struct clip_ctx * ctx, int img_h, int img_w) { @@ -2342,7 +2419,7 @@ int clip_n_patches_by_img(const struct clip_ctx * ctx, struct clip_image_f32 * i int n_patches = (params.image_size / params.patch_size) * (params.image_size / params.patch_size); - if (ctx->proj_type == PROJECTOR_TYPE_LDP || ctx->proj_type == PROJECTOR_TYPE_LDPV2) { + if (ctx->proj_type == PROJECTOR_TYPE_LDP || ctx->proj_type == PROJECTOR_TYPE_LDPV2 || ctx->proj_type == PROJECTOR_TYPE_GLM_EDGE) { n_patches /= 4; } else if (ctx->proj_type == PROJECTOR_TYPE_RESAMPLER) { if (ctx->minicpmv_version == 2) { @@ -2475,6 +2552,12 @@ bool clip_image_batch_encode(clip_ctx * ctx, const int n_threads, const clip_ima if (ctx->has_minicpmv_projector) { GGML_ASSERT(batch_size == 1); } + if (ctx->has_glm_projector) { + GGML_ASSERT(batch_size == 1); + ggml_tensor * boi = ctx->vision_model.boi_w; + ggml_backend_tensor_get(boi,vec,0,ggml_nbytes(boi)); + vec = (float*)(vec+ggml_nelements(boi)); //offset for boi + } // build the inference graph ggml_cgraph * gf = clip_image_build_graph(ctx, imgs, ctx->load_image_size, true); @@ -2627,7 +2710,7 @@ bool clip_image_batch_encode(clip_ctx * ctx, const int n_threads, const clip_ima ggml_backend_tensor_set(positions, positions_data, 0, ggml_nbytes(positions)); free(positions_data); - { + if (!ctx->has_glm_projector) { struct ggml_tensor * patches = ggml_graph_get_tensor(gf, "patches"); int* patches_data = (int*)malloc(ggml_nbytes(patches)); for (int i = 0; i < num_patches; i++) { @@ -2651,14 +2734,19 @@ bool clip_image_batch_encode(clip_ctx * ctx, const int n_threads, const clip_ima // copy the embeddings to the location passed by the user ggml_backend_tensor_get(embeddings, vec, 0, ggml_nbytes(embeddings)); + if (ctx->has_glm_projector) { + //eoi + ggml_tensor * eoi = ctx->vision_model.eoi_w; + int offset = ggml_nelements(embeddings); + ggml_backend_tensor_get(eoi, vec+offset, 0, ggml_nbytes(eoi)); + } + return true; } bool clip_model_quantize(const char * fname_inp, const char * fname_out, const int itype) { - ggml_type type = GGML_TYPE_Q4_1; - assert(itype < GGML_TYPE_COUNT); - type = static_cast(itype); + ggml_type type = static_cast(itype); auto * ctx_clip = clip_model_load(fname_inp, 2); @@ -2711,8 +2799,8 @@ bool clip_model_quantize(const char * fname_inp, const char * fname_out, const i } } - // quantize only 2D tensors - quantize &= (ggml_n_dims(cur) == 2); + // quantize only 2D tensors and bigger than block size + quantize &= (ggml_n_dims(cur) == 2) && cur->ne[0] > ggml_blck_size(type); if (quantize) { new_type = type; @@ -2812,6 +2900,9 @@ int clip_n_mmproj_embd(const struct clip_ctx * ctx) { return 3584; } } + if (ctx->proj_type == PROJECTOR_TYPE_GLM_EDGE){ + return ctx->vision_model.mm_model_mlp_3_w->ne[1]; + } if (ctx->proj_type == PROJECTOR_TYPE_MERGER) { return ctx->vision_model.mm_1_b->ne[0]; } @@ -2827,6 +2918,9 @@ int clip_is_minicpmv(const struct clip_ctx * ctx) { return 0; } +bool clip_is_glm(const struct clip_ctx * ctx) { + return ctx->has_glm_projector; +} bool clip_is_qwen2vl(const struct clip_ctx * ctx) { return ctx->has_qwen2vl_merger; } diff --git a/examples/llava/clip.h b/examples/llava/clip.h index 1603edd26..841b4f6f9 100644 --- a/examples/llava/clip.h +++ b/examples/llava/clip.h @@ -93,6 +93,8 @@ CLIP_API bool clip_is_qwen2vl(const struct clip_ctx * ctx); CLIP_API bool clip_encode_float_image (struct clip_ctx * ctx, int n_threads, float * img, int h, int w, float * vec); +CLIP_API bool clip_is_glm(const struct clip_ctx * ctx); + #ifdef __cplusplus } #endif diff --git a/examples/llava/glmedge-convert-image-encoder-to-gguf.py b/examples/llava/glmedge-convert-image-encoder-to-gguf.py new file mode 100644 index 000000000..848ef1cf3 --- /dev/null +++ b/examples/llava/glmedge-convert-image-encoder-to-gguf.py @@ -0,0 +1,280 @@ +import argparse +import os +import json +import re + +import torch +import numpy as np +from gguf import * + +TEXT = "clip.text" +VISION = "clip.vision" +from transformers import SiglipVisionModel, SiglipVisionConfig + +def k(raw_key: str, arch: str) -> str: + return raw_key.format(arch=arch) + + +def should_skip_tensor(name: str, has_text: bool, has_vision: bool, has_llava: bool) -> bool: + if name in ( + "logit_scale", + "text_model.embeddings.position_ids", + "vision_model.embeddings.position_ids", + ): + return True + + if name in ( + "vision_model.head.probe", + "vision_model.head.attention.in_proj_weight", + "vision_model.head.attention.in_proj_bias", + "vision_model.head.attention.out_proj.weight", + "vision_model.head.attention.out_proj.bias", + "vision_model.head.layernorm.weight", + "vision_model.head.layernorm.bias", + "vision_model.head.mlp.fc1.weight", + "vision_model.head.mlp.fc1.bias", + "vision_model.head.mlp.fc2.weight", + "vision_model.head.mlp.fc2.bias" + ): + return True + + if name.startswith("v") and not has_vision: + return True + + if name.startswith("t") and not has_text: + return True + + return False + + +def get_tensor_name(name: str) -> str: + if "projection" in name: + return name + if "mm_projector" in name: + name = name.replace("model.mm_projector", "mm") + name = re.sub(r'mm\.mlp\.mlp', 'mm.model.mlp', name, count=1) + name = re.sub(r'mm\.peg\.peg', 'mm.model.peg', name, count=1) + return name + + return name.replace("text_model", "t").replace("vision_model", "v").replace("encoder.layers", "blk").replace("embeddings.", "").replace("_proj", "").replace("self_attn.", "attn_").replace("layer_norm", "ln").replace("layernorm", "ln").replace("mlp.fc1", "ffn_down").replace("mlp.fc2", "ffn_up").replace("embedding", "embd").replace("final", "post").replace("layrnorm", "ln") + + +def bytes_to_unicode(): + """ + Returns list of utf-8 byte and a corresponding list of unicode strings. + The reversible bpe codes work on unicode strings. + This means you need a large # of unicode characters in your vocab if you want to avoid UNKs. + When you're at something like a 10B token dataset you end up needing around 5K for decent coverage. + This is a significant percentage of your normal, say, 32K bpe vocab. + To avoid that, we want lookup tables between utf-8 bytes and unicode strings. + And avoids mapping to whitespace/control characters the bpe code barfs on. + """ + bs = ( + list(range(ord("!"), ord("~") + 1)) + + list(range(ord("¡"), ord("¬") + 1)) + + list(range(ord("®"), ord("ÿ") + 1)) + ) + cs = bs[:] + n = 0 + for b in range(2**8): + if b not in bs: + bs.append(b) + cs.append(2**8 + n) + n += 1 + cs = [chr(n) for n in cs] + return dict(zip(bs, cs)) + + +ap = argparse.ArgumentParser() +ap.add_argument("-m", "--model-dir", help="Path to model directory cloned from HF Hub", required=True) +ap.add_argument("--use-f32", action="store_true", default=False, help="Use f32 instead of f16") +ap.add_argument("--text-only", action="store_true", required=False, + help="Save a text-only model. It can't be used to encode images") +ap.add_argument("--vision-only", action="store_true", required=False, + help="Save a vision-only model. It can't be used to encode texts") +ap.add_argument("--clip-model-is-vision", action="store_true", required=False, + help="The clip model is a pure vision model (ShareGPT4V vision extract for example)") +ap.add_argument("--clip-model-is-openclip", action="store_true", required=False, + help="The clip model is from openclip (for ViT-SO400M type))") +ap.add_argument("--llava-projector", help="Path to llava.projector file. If specified, save an image encoder for LLaVA models.") +ap.add_argument("--projector-type", help="Type of projector. Possible values: mlp, ldp, ldpv2", choices=["mlp", "ldp", "ldpv2","adapter"], default="adapter") +ap.add_argument("-o", "--output-dir", help="Directory to save GGUF files. Default is the original model directory", default=None) +# Example --image_mean 0.48145466 0.4578275 0.40821073 --image_std 0.26862954 0.26130258 0.27577711 +# Example --image_mean 0.5 0.5 0.5 --image_std 0.5 0.5 0.5 +default_image_mean = [0.5, 0.5, 0.5] +default_image_std = [0.5, 0.5, 0.5] +ap.add_argument('--image-mean', type=float, nargs='+', help='Mean of the images for normalization (overrides processor) ', default=None) +ap.add_argument('--image-std', type=float, nargs='+', help='Standard deviation of the images for normalization (overrides processor)', default=None) + +# with proper +args = ap.parse_args() + + +if args.text_only and args.vision_only: + print("--text-only and --image-only arguments cannot be specified at the same time.") + exit(1) + +if args.use_f32: + print("WARNING: Weights for the convolution op is always saved in f16, as the convolution op in GGML does not support 32-bit kernel weights yet.") + +# output in the same directory as the model if output_dir is None +dir_model = args.model_dir + +if args.clip_model_is_vision or not os.path.exists(dir_model + "/vocab.json") or args.clip_model_is_openclip: + vocab = None + tokens = None +else: + with open(dir_model + "/vocab.json", "r", encoding="utf-8") as f: + vocab = json.load(f) + tokens = [key for key in vocab] + +with open(dir_model + "/config.json", "r", encoding="utf-8") as f: + config = json.load(f) + if args.clip_model_is_vision: + v_hparams = config + t_hparams = None + else: + v_hparams = config["vision_config"] + t_hparams = None + +# possible data types +# ftype == 0 -> float32 +# ftype == 1 -> float16 +# +# map from ftype to string +ftype_str = ["f32", "f16"] + +ftype = 1 +if args.use_f32: + ftype = 0 + +vision_config = SiglipVisionConfig(**v_hparams) +model = SiglipVisionModel(vision_config) +model.load_state_dict(torch.load(os.path.join(dir_model, "glm.clip"))) + +fname_middle = None +has_text_encoder = False +has_vision_encoder = True +has_glm_projector = True +if args.text_only: + fname_middle = "text-" + has_vision_encoder = False +elif args.llava_projector is not None: + fname_middle = "mmproj-" + has_text_encoder = False + has_glm_projector = True +elif args.vision_only: + fname_middle = "vision-" + has_text_encoder = False +else: + fname_middle = "" + +output_dir = args.output_dir if args.output_dir is not None else dir_model +os.makedirs(output_dir, exist_ok=True) +output_prefix = os.path.basename(output_dir).replace("ggml_", "") +fname_out = os.path.join(output_dir, f"{fname_middle}model-{ftype_str[ftype]}.gguf") +fout = GGUFWriter(path=fname_out, arch="clip") + +fout.add_bool("clip.has_text_encoder", has_text_encoder) +fout.add_bool("clip.has_vision_encoder", has_vision_encoder) +fout.add_bool("clip.has_glm_projector", has_glm_projector) +fout.add_file_type(ftype) +model_name = config["_name_or_path"] if "_name_or_path" in config else os.path.basename(dir_model) +fout.add_name(model_name) +if has_glm_projector: + fout.add_description("image encoder for glm4v") + fout.add_string("clip.projector_type", "adapter") +else: + fout.add_description("two-tower CLIP model") + +if has_text_encoder: + assert t_hparams is not None + assert tokens is not None + # text_model hparams + fout.add_uint32(k(KEY_CONTEXT_LENGTH, TEXT), t_hparams["max_position_embeddings"]) + fout.add_uint32(k(KEY_EMBEDDING_LENGTH, TEXT), t_hparams["hidden_size"]) + fout.add_uint32(k(KEY_FEED_FORWARD_LENGTH, TEXT), t_hparams["intermediate_size"]) + fout.add_uint32("clip.text.projection_dim", t_hparams.get("projection_dim", config["projection_dim"])) + fout.add_uint32(k(KEY_ATTENTION_HEAD_COUNT, TEXT), t_hparams["num_attention_heads"]) + fout.add_float32(k(KEY_ATTENTION_LAYERNORM_EPS, TEXT), t_hparams["layer_norm_eps"]) + fout.add_uint32(k(KEY_BLOCK_COUNT, TEXT), t_hparams["num_hidden_layers"]) + fout.add_token_list(tokens) + +if has_vision_encoder: + # vision_model hparams + fout.add_uint32("clip.vision.image_size", v_hparams["image_size"]) + fout.add_uint32("clip.vision.patch_size", v_hparams["patch_size"]) + fout.add_uint32(k(KEY_EMBEDDING_LENGTH, VISION), v_hparams["hidden_size"]) + fout.add_uint32(k(KEY_FEED_FORWARD_LENGTH, VISION), v_hparams["intermediate_size"]) + fout.add_uint32("clip.vision.projection_dim", 0) + fout.add_uint32(k(KEY_ATTENTION_HEAD_COUNT, VISION), v_hparams["num_attention_heads"]) + fout.add_float32(k(KEY_ATTENTION_LAYERNORM_EPS, VISION), 1e-6) + fout.add_uint32(k(KEY_BLOCK_COUNT, VISION), v_hparams["num_hidden_layers"]) + + image_mean = args.image_mean if args.image_mean is not None else default_image_mean + image_std = args.image_std if args.image_std is not None else default_image_std + fout.add_array("clip.vision.image_mean", image_mean) + fout.add_array("clip.vision.image_std", image_std) + +fout.add_bool("clip.use_gelu", True) + + +if has_glm_projector: + # model.vision_model.encoder.layers.pop(-1) # pyright: ignore[reportAttributeAccessIssue] + projector = torch.load(args.llava_projector) + for name, data in projector.items(): + name = get_tensor_name(name) + # pw and dw conv ndim==4 + if data.ndim == 2 or data.ndim == 4: + data = data.squeeze().numpy().astype(np.float16) + else: + data = data.squeeze().numpy().astype(np.float32) + if name.startswith("vision."): + name=name.replace("vision.","") + fout.add_tensor(name, data) + print(f"Projector {name} - {data.dtype} - shape = {data.shape}") + # print(f"Projector {name} tensors added\n") + +state_dict = model.state_dict() # pyright: ignore[reportAttributeAccessIssue] +for name, data in state_dict.items(): + if should_skip_tensor(name, has_text_encoder, has_vision_encoder, has_glm_projector): + # we don't need this + print(f"skipping parameter: {name}") + continue + + name = get_tensor_name(name) + data = data.squeeze().numpy() + + n_dims = len(data.shape) + + # ftype == 0 -> float32, ftype == 1 -> float16 + ftype_cur = 0 + if n_dims == 4: + print(f"tensor {name} is always saved in f16") + data = data.astype(np.float16) + ftype_cur = 1 + elif ftype == 1: + if name[-7:] == ".weight" and n_dims == 2: + # print(" Converting to float16") + data = data.astype(np.float16) + ftype_cur = 1 + else: + # print(" Converting to float32") + data = data.astype(np.float32) + ftype_cur = 0 + else: + if data.dtype != np.float32: + # print(" Converting to float32") + data = data.astype(np.float32) + ftype_cur = 0 + print(f"siglip {name} - {data.dtype} - shape = {data.shape}") + # print(f"{name} - {ftype_str[ftype_cur]} - shape = {data.shape}") + fout.add_tensor(name, data) + + +fout.write_header_to_file() +fout.write_kv_data_to_file() +fout.write_tensors_to_file() +fout.close() + +print("Done. Output file: " + fname_out) diff --git a/examples/llava/glmedge-surgery.py b/examples/llava/glmedge-surgery.py new file mode 100644 index 000000000..16bb915d0 --- /dev/null +++ b/examples/llava/glmedge-surgery.py @@ -0,0 +1,33 @@ +import argparse +import os +import torch +from transformers import AutoModel + +ap = argparse.ArgumentParser() +ap.add_argument("-m", "--model", help="Path to GLM model") +args = ap.parse_args() + +# find the model part that includes the the multimodal projector weights +model = AutoModel.from_pretrained(args.model, trust_remote_code=True, local_files_only=True) +checkpoint = model.state_dict() + +# get a list of mm tensor names +mm_tensors = [k for k, v in checkpoint.items() if k.startswith("vision.adapter.")] + +# store these tensors in a new dictionary and torch.save them +projector = {name: checkpoint[name].float() for name in mm_tensors} +torch.save(projector, f"{args.model}/glm.projector") + +clip_tensors = [k for k, v in checkpoint.items() if k.startswith("vision.vit.model.vision_model.")] +if len(clip_tensors) > 0: + clip = {name.replace("vision.vit.model.", ""): checkpoint[name].float() for name in clip_tensors} + torch.save(clip, f"{args.model}/glm.clip") + + # added tokens should be removed to be able to convert Mistral models + if os.path.exists(f"{args.model}/added_tokens.json"): + with open(f"{args.model}/added_tokens.json", "w") as f: + f.write("{}\n") + +print("Done!") +print(f"Now you can convert {args.model} to a regular LLaMA GGUF file.") +print(f"Also, use {args.model}glm.projector to prepare a glm-encoder.gguf file.") diff --git a/examples/llava/llava.cpp b/examples/llava/llava.cpp index 2cac7933d..300714045 100644 --- a/examples/llava/llava.cpp +++ b/examples/llava/llava.cpp @@ -311,6 +311,20 @@ static bool encode_image_with_clip(clip_ctx * ctx_clip, int n_threads, const cli img_res_v.size = 0; img_res_v.data = nullptr; } + else if (clip_is_glm(ctx_clip)){ + struct clip_image_size * load_image_size = clip_image_size_init(); + load_image_size->width = img_res_v.data[0].nx; + load_image_size->height = img_res_v.data[0].ny; + clip_add_load_image_size(ctx_clip, load_image_size); + + bool encoded = clip_image_encode(ctx_clip, n_threads, &img_res_v.data[0], image_embd); + int pos = int(load_image_size->width/clip_patch_size(ctx_clip)/2); + *n_img_pos = (pos * pos + 2); + if (!encoded){ + LOG_ERR("Unable to encode image \n"); + return false; + } + } else if (strcmp(mm_patch_merge_type, "spatial_unpad") != 0) { // flat / default llava-1.5 type embedding *n_img_pos = clip_n_patches(ctx_clip); @@ -395,6 +409,9 @@ bool llava_image_embed_make_with_clip_img(clip_ctx * ctx_clip, int n_threads, co if (clip_is_minicpmv(ctx_clip)) { num_max_patches = 10; } + if (clip_is_glm(ctx_clip)) { + num_max_patches = 1; + } float * image_embd; if (clip_is_qwen2vl(ctx_clip)) { // qwen2vl don't split image into chunks, so `num_max_patches` is not needed. diff --git a/examples/run/run.cpp b/examples/run/run.cpp index 9cecae48c..9362da220 100644 --- a/examples/run/run.cpp +++ b/examples/run/run.cpp @@ -24,15 +24,16 @@ #include #include +#include "chat-template.hpp" #include "common.h" #include "json.hpp" #include "linenoise.cpp/linenoise.h" #include "llama-cpp.h" -#include "chat-template.hpp" +#include "log.h" #if defined(__unix__) || (defined(__APPLE__) && defined(__MACH__)) || defined(_WIN32) [[noreturn]] static void sigint_handler(int) { - printf("\n\033[0m"); + printf("\n" LOG_COL_DEFAULT); exit(0); // not ideal, but it's the only way to guarantee exit in all cases } #endif @@ -65,6 +66,13 @@ static int printe(const char * fmt, ...) { return ret; } +static std::string strftime_fmt(const char * fmt, const std::tm & tm) { + std::ostringstream oss; + oss << std::put_time(&tm, fmt); + + return oss.str(); +} + class Opt { public: int init(int argc, const char ** argv) { @@ -338,7 +346,7 @@ class HttpClient { if (!output_file.empty()) { output_file_partial = output_file + ".partial"; if (!out.open(output_file_partial, "ab")) { - printe("Failed to open file\n"); + printe("Failed to open file for writing\n"); return 1; } @@ -527,8 +535,7 @@ class HttpClient { static void print_progress(const std::string & progress_prefix, const std::string & progress_bar, const std::string & progress_suffix) { - printe("\r%*s\r%s%s| %s", get_terminal_width(), " ", progress_prefix.c_str(), progress_bar.c_str(), - progress_suffix.c_str()); + printe("\r" LOG_CLR_TO_EOL "%s%s| %s", progress_prefix.c_str(), progress_bar.c_str(), progress_suffix.c_str()); } // Function to write data to a file static size_t write_data(void * ptr, size_t size, size_t nmemb, void * stream) { @@ -698,6 +705,39 @@ class LlamaData { return download(url, bn, true); } + int s3_dl(const std::string & model, const std::string & bn) { + const size_t slash_pos = model.find('/'); + if (slash_pos == std::string::npos) { + return 1; + } + + const std::string bucket = model.substr(0, slash_pos); + const std::string key = model.substr(slash_pos + 1); + const char * access_key = std::getenv("AWS_ACCESS_KEY_ID"); + const char * secret_key = std::getenv("AWS_SECRET_ACCESS_KEY"); + if (!access_key || !secret_key) { + printe("AWS credentials not found in environment\n"); + return 1; + } + + // Generate AWS Signature Version 4 headers + // (Implementation requires HMAC-SHA256 and date handling) + // Get current timestamp + const time_t now = time(nullptr); + const tm tm = *gmtime(&now); + const std::string date = strftime_fmt("%Y%m%d", tm); + const std::string datetime = strftime_fmt("%Y%m%dT%H%M%SZ", tm); + const std::vector headers = { + "Authorization: AWS4-HMAC-SHA256 Credential=" + std::string(access_key) + "/" + date + + "/us-east-1/s3/aws4_request", + "x-amz-content-sha256: UNSIGNED-PAYLOAD", "x-amz-date: " + datetime + }; + + const std::string url = "https://" + bucket + ".s3.amazonaws.com/" + key; + + return download(url, bn, true, headers); + } + std::string basename(const std::string & path) { const size_t pos = path.find_last_of("/\\"); if (pos == std::string::npos) { @@ -738,6 +778,9 @@ class LlamaData { rm_until_substring(model_, "github:"); rm_until_substring(model_, "://"); ret = github_dl(model_, bn); + } else if (string_starts_with(model_, "s3://")) { + rm_until_substring(model_, "://"); + ret = s3_dl(model_, bn); } else { // ollama:// or nothing rm_until_substring(model_, "ollama.com/library/"); rm_until_substring(model_, "://"); @@ -753,16 +796,13 @@ class LlamaData { llama_model_ptr initialize_model(Opt & opt) { ggml_backend_load_all(); resolve_model(opt.model_); - printe( - "\r%*s" - "\rLoading model", - get_terminal_width(), " "); + printe("\r" LOG_CLR_TO_EOL "Loading model"); llama_model_ptr model(llama_model_load_from_file(opt.model_.c_str(), opt.model_params)); if (!model) { printe("%s: error: unable to load model from file: %s\n", __func__, opt.model_.c_str()); } - printe("\r%*s\r", static_cast(sizeof("Loading model")), " "); + printe("\r" LOG_CLR_TO_EOL); return model; } @@ -804,7 +844,15 @@ static int apply_chat_template(const common_chat_template & tmpl, LlamaData & ll }); } try { - auto result = tmpl.apply(messages, /* tools= */ json(), append); + minja::chat_template_inputs tmpl_inputs; + tmpl_inputs.messages = messages; + tmpl_inputs.add_generation_prompt = append; + + minja::chat_template_options tmpl_opts; + tmpl_opts.use_bos_token = false; + tmpl_opts.use_eos_token = false; + + auto result = tmpl.apply(tmpl_inputs, tmpl_opts); llama_data.fmtted.resize(result.size() + 1); memcpy(llama_data.fmtted.data(), result.c_str(), result.size() + 1); return result.size(); @@ -847,7 +895,7 @@ static int check_context_size(const llama_context_ptr & ctx, const llama_batch & const int n_ctx = llama_n_ctx(ctx.get()); const int n_ctx_used = llama_get_kv_cache_used_cells(ctx.get()); if (n_ctx_used + batch.n_tokens > n_ctx) { - printf("\033[0m\n"); + printf(LOG_COL_DEFAULT "\n"); printe("context size exceeded\n"); return 1; } @@ -910,17 +958,14 @@ static int generate(LlamaData & llama_data, const std::string & prompt, std::str batch = llama_batch_get_one(&new_token_id, 1); } - printf("\033[0m"); + printf(LOG_COL_DEFAULT); return 0; } static int read_user_input(std::string & user_input) { static const char * prompt_prefix = "> "; #ifdef WIN32 - printf( - "\r%*s" - "\r\033[0m%s", - get_terminal_width(), " ", prompt_prefix); + printf("\r" LOG_CLR_TO_EOL LOG_COL_DEFAULT "%s", prompt_prefix); std::getline(std::cin, user_input); if (std::cin.eof()) { @@ -956,7 +1001,7 @@ static int generate_response(LlamaData & llama_data, const std::string & prompt, const bool stdout_a_terminal) { // Set response color if (stdout_a_terminal) { - printf("\033[33m"); + printf(LOG_COL_YELLOW); } if (generate(llama_data, prompt, response)) { @@ -965,7 +1010,7 @@ static int generate_response(LlamaData & llama_data, const std::string & prompt, } // End response with color reset and newline - printf("\n%s", stdout_a_terminal ? "\033[0m" : ""); + printf("\n%s", stdout_a_terminal ? LOG_COL_DEFAULT : ""); return 0; } diff --git a/examples/server/README.md b/examples/server/README.md index ce1ae8858..d0b262f0e 100644 --- a/examples/server/README.md +++ b/examples/server/README.md @@ -126,7 +126,7 @@ The project is under active development, and we are [looking for feedback and co | `--grammar GRAMMAR` | BNF-like grammar to constrain generations (see samples in grammars/ dir) (default: '') | | `--grammar-file FNAME` | file to read grammar from | | `-j, --json-schema SCHEMA` | JSON schema to constrain generations (https://json-schema.org/), e.g. `{}` for any JSON object
For schemas w/ external $refs, use --grammar + example/json_schema_to_grammar.py instead | -| `--jinja` | Enable experimental Jinja templating engine (needed for tool use) | +| `--jinja` | Enable experimental Jinja templating engine (required for tool use) | **Example-specific params** @@ -220,7 +220,7 @@ services: The project includes a web-based user interface that enables interaction with the model through the `/chat/completions` endpoint. The web UI is developed using: -- `vue` framework for frontend development +- `react` framework for frontend development - `tailwindcss` and `daisyui` for styling - `vite` for build tooling @@ -1069,7 +1069,7 @@ Given a ChatML-formatted json description in `messages`, it returns the predicte *Options:* -See [OpenAI Chat Completions API documentation](https://platform.openai.com/docs/api-reference/chat). While some OpenAI-specific features such as function calling aren't supported, llama.cpp `/completion`-specific features such as `mirostat` are supported. +See [OpenAI Chat Completions API documentation](https://platform.openai.com/docs/api-reference/chat). llama.cpp `/completion`-specific features such as `mirostat` are also supported. The `response_format` parameter supports both plain JSON output (e.g. `{"type": "json_object"}`) and schema-constrained JSON (e.g. `{"type": "json_object", "schema": {"type": "string", "minLength": 10, "maxLength": 100}}` or `{"type": "json_schema", "schema": {"properties": { "name": { "title": "Name", "type": "string" }, "date": { "title": "Date", "type": "string" }, "participants": { "items": {"type: "string" }, "title": "Participants", "type": "string" } } } }`), similar to other OpenAI-inspired API providers. @@ -1117,17 +1117,119 @@ curl http://localhost:8080/v1/chat/completions \ }' ``` -... and even tool usage (needs `--jinja` flag): +*Tool call support* + +[Function calling](https://platform.openai.com/docs/guides/function-calling) is supported for all models (see https://github.com/ggerganov/llama.cpp/pull/9639): + +- Requires `--jinja` flag +- Native tool call formats supported: + - Llama 3.1 / 3.3 (including builtin tools support - tool names for `wolfram_alpha`, `web_search` / `brave_search`, `code_interpreter`), Llama 3.2 + - Functionary v3.1 / v3.2 + - Hermes 2/3, Qwen 2.5 + - Mistral Nemo + - Firefunction v2 + - Command R7B + - DeepSeek R1 (WIP / seems reluctant to call any tools?) + +
+ Show some common templates and which format handler they use + + | Template | Format | + |----------|--------| + | CohereForAI-c4ai-command-r-plus-default.jinja | generic tool calls | + | CohereForAI-c4ai-command-r-plus-rag.jinja | generic tool calls | + | CohereForAI-c4ai-command-r-plus-tool_use.jinja | generic tool calls | + | MiniMaxAI-MiniMax-Text-01.jinja | generic tool calls | + | NexaAIDev-Octopus-v2.jinja | generic tool calls | + | NousResearch-Hermes-2-Pro-Llama-3-8B-default.jinja | generic tool calls | + | NousResearch-Hermes-2-Pro-Llama-3-8B-tool_use.jinja | hermes 2 pro tool calls | + | NousResearch-Hermes-2-Pro-Mistral-7B-default.jinja | generic tool calls | + | NousResearch-Hermes-2-Pro-Mistral-7B-tool_use.jinja | hermes 2 pro tool calls | + | NousResearch-Hermes-3-Llama-3.1-70B-default.jinja | generic tool calls | + | NousResearch-Hermes-3-Llama-3.1-70B-tool_use.jinja | hermes 2 pro tool calls | + | OrionStarAI-Orion-14B-Chat.jinja | generic tool calls | + | Qwen-QwQ-32B-Preview.jinja | hermes 2 pro tool calls | + | Qwen-Qwen2-7B-Instruct.jinja | generic tool calls | + | Qwen-Qwen2-VL-7B-Instruct.jinja | generic tool calls | + | Qwen-Qwen2.5-7B-Instruct.jinja | hermes 2 pro tool calls | + | Qwen-Qwen2.5-Math-7B-Instruct.jinja | hermes 2 pro tool calls | + | TheBloke-FusionNet_34Bx2_MoE-AWQ.jinja | generic tool calls | + | abacusai-Fewshot-Metamath-OrcaVicuna-Mistral.jinja | generic tool calls | + | bofenghuang-vigogne-2-70b-chat.jinja | generic tool calls | + | databricks-dbrx-instruct.jinja | generic tool calls | + | deepseek-ai-DeepSeek-Coder-V2-Instruct.jinja | generic tool calls | + | deepseek-ai-DeepSeek-R1-Distill-Llama-8B.jinja | deepseek r1 tool calls | + | deepseek-ai-DeepSeek-R1-Distill-Qwen-32B.jinja | deepseek r1 tool calls | + | deepseek-ai-DeepSeek-R1-Distill-Qwen-7B.jinja | deepseek r1 tool calls | + | deepseek-ai-DeepSeek-V2.5.jinja | deepseek r1 tool calls | + | deepseek-ai-deepseek-coder-33b-instruct.jinja | generic tool calls | + | google-gemma-2-2b-it.jinja | generic tool calls | + | google-gemma-7b-it.jinja | generic tool calls | + | indischepartij-MiniCPM-3B-OpenHermes-2.5-v2.jinja | generic tool calls | + | mattshumer-Reflection-Llama-3.1-70B.jinja | generic tool calls | + | meetkai-functionary-medium-v3.2.jinja | functionary v3.2 tool calls | + | meta-llama-Llama-3.1-8B-Instruct.jinja | llama 3.x tool calls (w/ builtin tools) | + | meta-llama-Llama-3.2-3B-Instruct.jinja | llama 3.x tool calls | + | meta-llama-Llama-3.3-70B-Instruct.jinja | llama 3.x tool calls (w/ builtin tools) | + | meta-llama-Meta-Llama-3.1-8B-Instruct.jinja | llama 3.x tool calls (w/ builtin tools) | + | microsoft-Phi-3-medium-4k-instruct.jinja | generic tool calls | + | microsoft-Phi-3-mini-4k-instruct.jinja | generic tool calls | + | microsoft-Phi-3-small-8k-instruct.jinja | generic tool calls | + | microsoft-Phi-3.5-mini-instruct.jinja | generic tool calls | + | microsoft-Phi-3.5-vision-instruct.jinja | generic tool calls | + | mistralai-Mistral-7B-Instruct-v0.2.jinja | generic tool calls | + | mistralai-Mistral-Large-Instruct-2407.jinja | mistral nemo tool calls | + | mistralai-Mistral-Large-Instruct-2411.jinja | generic tool calls | + | mistralai-Mistral-Nemo-Instruct-2407.jinja | mistral nemo tool calls | + | mistralai-Mixtral-8x7B-Instruct-v0.1.jinja | generic tool calls | + | mlabonne-AlphaMonarch-7B.jinja | generic tool calls | + | nvidia-Llama-3.1-Nemotron-70B-Instruct-HF.jinja | llama 3.x tool calls (w/ builtin tools) | + | openchat-openchat-3.5-0106.jinja | generic tool calls | + | teknium-OpenHermes-2.5-Mistral-7B.jinja | generic tool calls | + + This table can be generated with: + + ```bash + ./build/bin/test-chat ../minja/build/tests/*.jinja 2>/dev/null + +
+ +- Generic tool call is supported when the template isn't recognized by native format handlers (you'll see `Chat format: Generic` in the logs). + - Use `--chat-template-file` to override the template when appropriate (see examples below) + - Generic support may consume more tokens and be less efficient than a model's native format. + +- Run with: ```shell - llama-server --jinja -hfr lmstudio-community/Meta-Llama-3.1-8B-Instruct-GGUF -hff Meta-Llama-3.1-8B-Instruct-Q5_K_M.gguf -fa + # Native support: + llama-server --jinja -fa -hf bartowski/Qwen2.5-7B-Instruct-GGUF:Q4_K_M + llama-server --jinja -fa -hf bartowski/Mistral-Nemo-Instruct-2407-GGUF:Q6_K_L + llama-server --jinja -fa -hf bartowski/functionary-small-v3.2-GGUF:Q4_K_M + llama-server --jinja -fa -hf bartowski/Llama-3.3-70B-Instruct-GGUF:Q4_K_M - # https://huggingface.co/meetkai/functionary-medium-v3.2 - llama-server --jinja -hfr bartowski/functionary-medium-v3.2-GGUF -hff functionary-medium-v3.2-IQ4_XS.gguf -fa + # Native support requires the right template for these GGUFs: - # https://huggingface.co/meetkai/functionary-medium-v3.1 - llama-server --jinja -hfr meetkai/functionary-medium-v3.1-GGUF -hff functionary-medium-llama-3.1.Q4_0.gguf -fa + llama-server --jinja -fa -hf bartowski/Hermes-2-Pro-Llama-3-8B-GGUF:Q4_K_M \ + --chat-template-file <( python scripts/get_chat_template.py NousResearch/Hermes-2-Pro-Llama-3-8B tool_use ) + llama-server --jinja -fa -hf bartowski/Hermes-3-Llama-3.1-8B-GGUF:Q4_K_M \ + --chat-template-file <( python scripts/get_chat_template.py NousResearch/Hermes-3-Llama-3.1-8B tool_use ) + + llama-server --jinja -fa -hf bartowski/firefunction-v2-GGUF -hff firefunction-v2-IQ1_M.gguf \ + --chat-template-file <( python scripts/get_chat_template.py fireworks-ai/llama-3-firefunction-v2 tool_use ) + + llama-server --jinja -fa -hf bartowski/c4ai-command-r7b-12-2024-GGUF:Q6_K_L \ + --chat-template-file <( python scripts/get_chat_template.py CohereForAI/c4ai-command-r7b-12-2024 tool_use ) + + # Generic format support + llama-server --jinja -fa -hf bartowski/phi-4-GGUF:Q4_0 + llama-server --jinja -fa -hf bartowski/gemma-2-2b-it-GGUF:Q8_0 + llama-server --jinja -fa -hf bartowski/c4ai-command-r-v01-GGUF:Q2_K + ``` + +- Test in CLI: + + ```bash curl http://localhost:8080/v1/chat/completions -d '{ "model": "gpt-3.5-turbo", "tools": [ diff --git a/examples/server/public/index.html.gz b/examples/server/public/index.html.gz index 582ccc0d3..141e80920 100644 Binary files a/examples/server/public/index.html.gz and b/examples/server/public/index.html.gz differ diff --git a/examples/server/server.cpp b/examples/server/server.cpp index d1ea343dd..0718806c8 100644 --- a/examples/server/server.cpp +++ b/examples/server/server.cpp @@ -131,6 +131,11 @@ struct slot_params { lora.push_back({{"id", i}, {"scale", this->lora[i].scale}}); } + std::vector grammar_trigger_words; + for (const auto & trigger : sampling.grammar_trigger_words) { + grammar_trigger_words.push_back(trigger.word); + } + return json { {"n_predict", n_predict}, // Server configured n_predict {"seed", sampling.seed}, @@ -165,8 +170,9 @@ struct slot_params { {"n_probs", sampling.n_probs}, {"min_keep", sampling.min_keep}, {"grammar", sampling.grammar}, - // {"grammar_trigger_words", sampling.grammar_trigger_words}, + {"grammar_trigger_words", grammar_trigger_words}, {"grammar_trigger_tokens", sampling.grammar_trigger_tokens}, + {"preserved_tokens", sampling.preserved_tokens}, {"samplers", samplers}, {"speculative.n_max", speculative.n_max}, {"speculative.n_min", speculative.n_min}, @@ -328,24 +334,24 @@ struct server_task { if (data.contains("json_schema") && !data.contains("grammar")) { try { auto schema = json_value(data, "json_schema", json::object()); - LOG_DBG("JSON schema: %s\n", schema.dump(2).c_str()); + SRV_DBG("JSON schema: %s\n", schema.dump(2).c_str()); params.sampling.grammar = json_schema_to_grammar(schema); - LOG_DBG("Converted grammar: %s\n", params.sampling.grammar.c_str()); + SRV_DBG("Converted grammar: %s\n", params.sampling.grammar.c_str()); } catch (const std::exception & e) { throw std::runtime_error(std::string("\"json_schema\": ") + e.what()); } } else { params.sampling.grammar = json_value(data, "grammar", defaults.sampling.grammar); - LOG_DBG("Grammar: %s\n", params.sampling.grammar.c_str()); + SRV_DBG("Grammar: %s\n", params.sampling.grammar.c_str()); params.sampling.grammar_lazy = json_value(data, "grammar_lazy", defaults.sampling.grammar_lazy); - LOG_DBG("Grammar lazy: %s\n", params.sampling.grammar_lazy ? "true" : "false"); + SRV_DBG("Grammar lazy: %s\n", params.sampling.grammar_lazy ? "true" : "false"); } { auto it = data.find("chat_format"); if (it != data.end()) { params.oaicompat_chat_format = static_cast(it->get()); - LOG_DBG("Chat format: %s\n", common_chat_format_name(params.oaicompat_chat_format).c_str()); + SRV_INF("Chat format: %s\n", common_chat_format_name(params.oaicompat_chat_format).c_str()); } else { params.oaicompat_chat_format = defaults.oaicompat_chat_format; } @@ -361,14 +367,28 @@ struct server_task { auto ids = common_tokenize(vocab, trigger.word, /* add_special= */ false, /* parse_special= */ true); if (ids.size() == 1) { - LOG_DBG("Grammar trigger token: %d (`%s`)\n", ids[0], trigger.word.c_str()); + SRV_DBG("Grammar trigger token: %d (`%s`)\n", ids[0], trigger.word.c_str()); params.sampling.grammar_trigger_tokens.push_back(ids[0]); + params.sampling.preserved_tokens.insert(ids[0]); continue; } - LOG_DBG("Grammar trigger word: `%s`\n", trigger.word.c_str()); + SRV_DBG("Grammar trigger word: `%s`\n", trigger.word.c_str()); params.sampling.grammar_trigger_words.push_back(trigger); } } + const auto preserved_tokens = data.find("preserved_tokens"); + if (preserved_tokens != data.end()) { + for (const auto & t : *preserved_tokens) { + auto ids = common_tokenize(vocab, t.get(), /* add_special= */ false, /* parse_special= */ true); + if (ids.size() == 1) { + SRV_DBG("Preserved token: %d\n", ids[0]); + params.sampling.preserved_tokens.insert(ids[0]); + } else { + // This may happen when using a tool call style meant for a model with special tokens to preserve on a model without said tokens. + SRV_WRN("Not preserved because more than 1 token (wrong chat template override?): %s\n", t.get().c_str()); + } + } + } if (params.sampling.grammar_lazy) { GGML_ASSERT(params.sampling.grammar_trigger_tokens.size() > 0 || params.sampling.grammar_trigger_words.size() > 0); } @@ -695,37 +715,43 @@ struct server_task_result_cmpl_final : server_task_result { json to_json_oaicompat_chat() { std::string finish_reason = "length"; - common_chat_msg message; + common_chat_msg msg; if (stop == STOP_TYPE_WORD || stop == STOP_TYPE_EOS) { - message = common_chat_parse(content, oaicompat_chat_format); - finish_reason = message.tool_calls.empty() ? "stop" : "tool_calls"; + SRV_DBG("Parsing chat message: %s\n", content.c_str()); + msg = common_chat_parse(content, oaicompat_chat_format); + finish_reason = msg.tool_calls.empty() ? "stop" : "tool_calls"; } else { - message.content = content; + msg.content = content; } json tool_calls; - if (!message.tool_calls.empty()) { + if (!msg.tool_calls.empty()) { tool_calls = json::array(); - for (const auto & tc : message.tool_calls) { + for (const auto & tc : msg.tool_calls) { tool_calls.push_back({ {"type", "function"}, {"function", { {"name", tc.name}, {"arguments", tc.arguments}, }}, - {"id", tc.id.empty() ? json() : json(tc.id)}, + {"id", tc.id}, }); } } + json message { + {"content", msg.content}, + {"tool_calls", tool_calls}, + {"role", "assistant"}, + }; + if (!msg.tool_plan.empty()) { + message["tool_plan"] = msg.tool_plan; + } + json choice { {"finish_reason", finish_reason}, {"index", 0}, - {"message", json { - {"content", message.content}, - {"tool_calls", tool_calls}, - {"role", "assistant"}, - }}, + {"message", message}, }; if (!stream && probs_output.size() > 0) { @@ -1858,7 +1884,12 @@ struct server_context { llama_init_dft.context.reset(); } - chat_templates = common_chat_templates_from_model(model, params_base.chat_template); + if (params_base.chat_template.empty() && !validate_builtin_chat_template(params.use_jinja)) { + SRV_WRN("%s: The chat template that comes with this model is not yet supported, falling back to chatml. This may cause the model to output suboptimal responses\n", __func__); + chat_templates = common_chat_templates_from_model(model, "chatml"); + } else { + chat_templates = common_chat_templates_from_model(model, params_base.chat_template); + } GGML_ASSERT(chat_templates.template_default.get() != nullptr); return true; @@ -2827,8 +2858,7 @@ struct server_context { server_slot * slot_batched = nullptr; auto accept_special_token = [&](server_slot & slot, llama_token token) { - const auto & trigger_tokens = slot.params.sampling.grammar_trigger_tokens; - return params_base.special || std::find(trigger_tokens.begin(), trigger_tokens.end(), token) != trigger_tokens.end(); + return params_base.special || slot.params.sampling.preserved_tokens.find(token) != slot.params.sampling.preserved_tokens.end(); }; // frist, add sampled tokens from any ongoing sequences @@ -3323,10 +3353,12 @@ static void log_server_request(const httplib::Request & req, const httplib::Resp return; } - LOG_INF("request: %s %s %s %d\n", req.method.c_str(), req.path.c_str(), req.remote_addr.c_str(), res.status); + // reminder: this function is not covered by httplib's exception handler; if someone does more complicated stuff, think about wrapping it in try-catch - LOG_DBG("request: %s\n", req.body.c_str()); - LOG_DBG("response: %s\n", res.body.c_str()); + SRV_INF("request: %s %s %s %d\n", req.method.c_str(), req.path.c_str(), req.remote_addr.c_str(), res.status); + + SRV_DBG("request: %s\n", req.body.c_str()); + SRV_DBG("response: %s\n", res.body.c_str()); } std::function shutdown_handler; @@ -3409,9 +3441,13 @@ int main(int argc, char ** argv) { message = "Unknown Exception"; } - json formatted_error = format_error_response(message, ERROR_TYPE_SERVER); - LOG_WRN("got exception: %s\n", formatted_error.dump().c_str()); - res_error(res, formatted_error); + try { + json formatted_error = format_error_response(message, ERROR_TYPE_SERVER); + LOG_WRN("got exception: %s\n", formatted_error.dump().c_str()); + res_error(res, formatted_error); + } catch (const std::exception & e) { + LOG_ERR("got another exception: %s | while hanlding exception: %s\n", e.what(), message.c_str()); + } }); svr->set_error_handler([&res_error](const httplib::Request &, httplib::Response & res) { @@ -3633,11 +3669,11 @@ int main(int argc, char ** argv) { {"value", (uint64_t) res_metrics->kv_cache_tokens_count} },{ {"name", "requests_processing"}, - {"help", "Number of request processing."}, + {"help", "Number of requests processing."}, {"value", (uint64_t) res_metrics->n_processing_slots} },{ {"name", "requests_deferred"}, - {"help", "Number of request deferred."}, + {"help", "Number of requests deferred."}, {"value", (uint64_t) res_metrics->n_tasks_deferred} }}} }; @@ -3824,7 +3860,9 @@ int main(int argc, char ** argv) { try { const auto & prompt = data.at("prompt"); - LOG_DBG("Prompt: %s\n", prompt.is_string() ? prompt.get().c_str() : prompt.dump(2).c_str()); + // TODO: this log can become very long, put it behind a flag or think about a more compact format + //SRV_DBG("Prompt: %s\n", prompt.is_string() ? prompt.get().c_str() : prompt.dump(2).c_str()); + std::vector tokenized_prompts = tokenize_input_prompts(ctx_server.vocab, prompt, true, true); tasks.reserve(tokenized_prompts.size()); for (size_t i = 0; i < tokenized_prompts.size(); i++) { @@ -4340,6 +4378,9 @@ int main(int argc, char ** argv) { res.set_content("Error: gzip is not supported by this browser", "text/plain"); } else { res.set_header("Content-Encoding", "gzip"); + // COEP and COOP headers, required by pyodide (python interpreter) + res.set_header("Cross-Origin-Embedder-Policy", "require-corp"); + res.set_header("Cross-Origin-Opener-Policy", "same-origin"); res.set_content(reinterpret_cast(index_html_gz), index_html_gz_len, "text/html; charset=utf-8"); } return false; @@ -4435,14 +4476,6 @@ int main(int argc, char ** argv) { LOG_INF("%s: model loaded\n", __func__); - // if a custom chat template is not supplied, we will use the one that comes with the model (if any) - if (params.chat_template.empty()) { - if (!ctx_server.validate_builtin_chat_template(params.use_jinja)) { - LOG_WRN("%s: The chat template that comes with this model is not yet supported, falling back to chatml. This may cause the model to output suboptimal responses\n", __func__); - params.chat_template = "chatml"; - } - } - // print sample chat example to make it clear which template is used LOG_INF("%s: chat template, chat_template: %s, example_format: '%s'\n", __func__, ctx_server.chat_templates.template_default->source().c_str(), diff --git a/examples/server/tests/unit/test_chat_completion.py b/examples/server/tests/unit/test_chat_completion.py index 0be04bab5..f23d5cff4 100644 --- a/examples/server/tests/unit/test_chat_completion.py +++ b/examples/server/tests/unit/test_chat_completion.py @@ -13,12 +13,14 @@ def create_server(): @pytest.mark.parametrize( "model,system_prompt,user_prompt,max_tokens,re_content,n_prompt,n_predicted,finish_reason,jinja,chat_template", [ + (None, "Book", "Hey", 8, "But she couldn't", 69, 8, "length", False, None), + (None, "Book", "Hey", 8, "But she couldn't", 69, 8, "length", True, None), (None, "Book", "What is the best book", 8, "(Suddenly)+|\\{ \" Sarax.", 77, 8, "length", False, None), + (None, "Book", "What is the best book", 8, "(Suddenly)+|\\{ \" Sarax.", 77, 8, "length", True, None), + (None, "Book", "What is the best book", 8, "(Suddenly)+|\\{ \" Sarax.", 77, 8, "length", True, 'chatml'), + (None, "Book", "What is the best book", 8, "^ blue", 23, 8, "length", True, "This is not a chat template, it is"), ("codellama70b", "You are a coding assistant.", "Write the fibonacci function in c++.", 128, "(Aside|she|felter|alonger)+", 104, 64, "length", False, None), - # TODO: fix testing of non-tool jinja mode - # (None, "Book", "What is the best book", 8, "(Suddenly)+|\\{ \" Sarax.", 77, 8, "length", True, None), - # (None, "Book", "What is the best book", 8, "I want to play with", 23, 8, "length", True, "This is not a chat template, it is"), - # ("codellama70b", "You are a coding assistant.", "Write the fibonacci function in c++.", 128, "(Aside|she|felter|alonger)+", 104, 64, "length", True, None), + ("codellama70b", "You are a coding assistant.", "Write the fibonacci function in c++.", 128, "(Aside|she|felter|alonger)+", 104, 64, "length", True, None), ] ) def test_chat_completion(model, system_prompt, user_prompt, max_tokens, re_content, n_prompt, n_predicted, finish_reason, jinja, chat_template): diff --git a/examples/server/tests/unit/test_tool_call.py b/examples/server/tests/unit/test_tool_call.py index e6ed9c9be..4a551404f 100644 --- a/examples/server/tests/unit/test_tool_call.py +++ b/examples/server/tests/unit/test_tool_call.py @@ -67,8 +67,8 @@ WEATHER_TOOL = { def do_test_completion_with_required_tool_tiny(template_name: str, tool: dict, argument_key: str | None): - n_predict = 512 global server + n_predict = 512 # server = ServerPreset.stories15m_moe() server.jinja = True server.n_predict = n_predict @@ -139,29 +139,49 @@ def test_completion_with_required_tool_tiny_slow(template_name: str, tool: dict, @pytest.mark.parametrize("tool,argument_key,hf_repo,template_override", [ (TEST_TOOL, "success", "bartowski/Meta-Llama-3.1-8B-Instruct-GGUF:Q4_K_M", None), (PYTHON_TOOL, "code", "bartowski/Meta-Llama-3.1-8B-Instruct-GGUF:Q4_K_M", None), + (PYTHON_TOOL, "code", "bartowski/Meta-Llama-3.1-8B-Instruct-GGUF:Q4_K_M", "chatml"), + + # Note: gemma-2-2b-it knows itself as "model", not "assistant", so we don't test the ill-suited chatml on it. (TEST_TOOL, "success", "bartowski/gemma-2-2b-it-GGUF:Q4_K_M", None), (PYTHON_TOOL, "code", "bartowski/gemma-2-2b-it-GGUF:Q4_K_M", None), + (TEST_TOOL, "success", "bartowski/Phi-3.5-mini-instruct-GGUF:Q4_K_M", None), (PYTHON_TOOL, "code", "bartowski/Phi-3.5-mini-instruct-GGUF:Q4_K_M", None), + (PYTHON_TOOL, "code", "bartowski/Phi-3.5-mini-instruct-GGUF:Q4_K_M", "chatml"), + (TEST_TOOL, "success", "bartowski/Qwen2.5-7B-Instruct-GGUF:Q4_K_M", None), (PYTHON_TOOL, "code", "bartowski/Qwen2.5-7B-Instruct-GGUF:Q4_K_M", None), + (PYTHON_TOOL, "code", "bartowski/Qwen2.5-7B-Instruct-GGUF:Q4_K_M", "chatml"), + (TEST_TOOL, "success", "bartowski/Hermes-2-Pro-Llama-3-8B-GGUF:Q4_K_M", ("NousResearch/Hermes-2-Pro-Llama-3-8B", "tool_use")), (PYTHON_TOOL, "code", "bartowski/Hermes-2-Pro-Llama-3-8B-GGUF:Q4_K_M", ("NousResearch/Hermes-2-Pro-Llama-3-8B", "tool_use")), + (PYTHON_TOOL, "code", "bartowski/Hermes-2-Pro-Llama-3-8B-GGUF:Q4_K_M", "chatml"), + (TEST_TOOL, "success", "bartowski/Hermes-3-Llama-3.1-8B-GGUF:Q4_K_M", ("NousResearch/Hermes-3-Llama-3.1-8B", "tool_use")), (PYTHON_TOOL, "code", "bartowski/Hermes-3-Llama-3.1-8B-GGUF:Q4_K_M", ("NousResearch/Hermes-3-Llama-3.1-8B", "tool_use")), + (PYTHON_TOOL, "code", "bartowski/Hermes-3-Llama-3.1-8B-GGUF:Q4_K_M", "chatml"), + (TEST_TOOL, "success", "bartowski/Mistral-Nemo-Instruct-2407-GGUF:Q4_K_M", None), (PYTHON_TOOL, "code", "bartowski/Mistral-Nemo-Instruct-2407-GGUF:Q4_K_M", None), - (TEST_TOOL, "success", "bartowski/functionary-small-v3.2-GGUF:Q8_0", ("meetkai/functionary-medium-v3.2", None)), - (PYTHON_TOOL, "code", "bartowski/functionary-small-v3.2-GGUF:Q8_0", ("meetkai/functionary-medium-v3.2", None)), + (PYTHON_TOOL, "code", "bartowski/Mistral-Nemo-Instruct-2407-GGUF:Q4_K_M", "chatml"), + + (TEST_TOOL, "success", "bartowski/functionary-small-v3.2-GGUF:Q4_K_M", ("meetkai/functionary-medium-v3.2", None)), + (PYTHON_TOOL, "code", "bartowski/functionary-small-v3.2-GGUF:Q4_K_M", ("meetkai/functionary-medium-v3.2", None)), + (PYTHON_TOOL, "code", "bartowski/functionary-small-v3.2-GGUF:Q4_K_M", "chatml"), + (TEST_TOOL, "success", "bartowski/Llama-3.2-3B-Instruct-GGUF:Q4_K_M", ("meta-llama/Llama-3.2-3B-Instruct", None)), (PYTHON_TOOL, "code", "bartowski/Llama-3.2-3B-Instruct-GGUF:Q4_K_M", ("meta-llama/Llama-3.2-3B-Instruct", None)), + (PYTHON_TOOL, "code", "bartowski/Llama-3.2-3B-Instruct-GGUF:Q4_K_M", "chatml"), + (TEST_TOOL, "success", "bartowski/Llama-3.2-1B-Instruct-GGUF:Q4_K_M", ("meta-llama/Llama-3.2-3B-Instruct", None)), (PYTHON_TOOL, "code", "bartowski/Llama-3.2-1B-Instruct-GGUF:Q4_K_M", ("meta-llama/Llama-3.2-3B-Instruct", None)), + (PYTHON_TOOL, "code", "bartowski/Llama-3.2-1B-Instruct-GGUF:Q4_K_M", "chatml"), # TODO: fix these # (TEST_TOOL, "success", "bartowski/DeepSeek-R1-Distill-Qwen-7B-GGUF:Q4_K_M", None), # (PYTHON_TOOL, "code", "bartowski/DeepSeek-R1-Distill-Qwen-7B-GGUF:Q4_K_M", None), ]) -def test_completion_with_required_tool_real_model(tool: dict, argument_key: str | None, hf_repo: str, template_override: Tuple[str, str | None] | None): +def test_completion_with_required_tool_real_model(tool: dict, argument_key: str | None, hf_repo: str, template_override: str | Tuple[str, str | None] | None): + global server n_predict = 512 server.n_slots = 1 server.jinja = True @@ -169,10 +189,12 @@ def test_completion_with_required_tool_real_model(tool: dict, argument_key: str server.n_predict = n_predict server.model_hf_repo = hf_repo server.model_hf_file = None - if template_override: + if isinstance(template_override, tuple): (template_hf_repo, template_variant) = template_override server.chat_template_file = f"../../../models/templates/{template_hf_repo.replace('/', '-') + ('-' + template_variant if template_variant else '')}.jinja" assert os.path.exists(server.chat_template_file), f"Template file {server.chat_template_file} does not exist. Run `python scripts/get_chat_template.py {template_hf_repo} {template_variant} > {server.chat_template_file}` to download the template." + elif isinstance(template_override, str): + server.chat_template = template_override server.start(timeout_seconds=TIMEOUT_SERVER_START) res = server.make_request("POST", "/chat/completions", data={ "max_tokens": n_predict, @@ -251,33 +273,55 @@ def test_completion_without_tool_call_slow(template_name: str, n_predict: int, t @pytest.mark.slow @pytest.mark.parametrize("hf_repo,template_override", [ + ("bartowski/c4ai-command-r7b-12-2024-GGUF:Q4_K_M", ("CohereForAI/c4ai-command-r7b-12-2024", "tool_use")), ("bartowski/Meta-Llama-3.1-8B-Instruct-GGUF:Q4_K_M", None), - ("bartowski/gemma-2-2b-it-GGUF:Q4_K_M", None), + ("bartowski/Meta-Llama-3.1-8B-Instruct-GGUF:Q4_K_M", "chatml"), + ("bartowski/Phi-3.5-mini-instruct-GGUF:Q4_K_M", None), + ("bartowski/Phi-3.5-mini-instruct-GGUF:Q4_K_M", "chatml"), + ("bartowski/Qwen2.5-7B-Instruct-GGUF:Q4_K_M", None), - ("bartowski/Hermes-2-Pro-Llama-3-8B-GGUF:Q4_K_M", ("NousResearch/Hermes-2-Pro-Llama-3-8B", "tool_use")), - ("bartowski/Hermes-3-Llama-3.1-8B-GGUF:Q4_K_M", ("NousResearch/Hermes-3-Llama-3.1-8B", "tool_use")), + ("bartowski/Qwen2.5-7B-Instruct-GGUF:Q4_K_M", "chatml"), + + ("bartowski/Hermes-2-Pro-Llama-3-8B-GGUF:Q4_K_M", ("NousResearch/Hermes-2-Pro-Llama-3-8B", "tool_use")), + ("bartowski/Hermes-2-Pro-Llama-3-8B-GGUF:Q4_K_M", "chatml"), + + ("bartowski/Hermes-3-Llama-3.1-8B-GGUF:Q4_K_M", ("NousResearch/Hermes-3-Llama-3.1-8B", "tool_use")), + ("bartowski/Hermes-3-Llama-3.1-8B-GGUF:Q4_K_M", "chatml"), + ("bartowski/Mistral-Nemo-Instruct-2407-GGUF:Q4_K_M", None), + ("bartowski/Mistral-Nemo-Instruct-2407-GGUF:Q4_K_M", "chatml"), + ("bartowski/functionary-small-v3.2-GGUF:Q8_0", ("meetkai/functionary-medium-v3.2", None)), + ("bartowski/functionary-small-v3.2-GGUF:Q8_0", "chatml"), + ("bartowski/Llama-3.2-3B-Instruct-GGUF:Q4_K_M", ("meta-llama/Llama-3.2-3B-Instruct", None)), + ("bartowski/Llama-3.2-3B-Instruct-GGUF:Q4_K_M", "chatml"), + + # Note: gemma-2-2b-it knows itself as "model", not "assistant", so we don't test the ill-suited chatml on it. + ("bartowski/gemma-2-2b-it-GGUF:Q4_K_M", None), + # ("bartowski/Llama-3.2-1B-Instruct-GGUF:Q4_K_M", ("meta-llama/Llama-3.2-3B-Instruct", None)), # ("bartowski/DeepSeek-R1-Distill-Qwen-7B-GGUF:Q4_K_M", None), ]) -def test_weather_tool_call(hf_repo: str, template_override: Tuple[str, str | None] | None): +def test_weather(hf_repo: str, template_override: Tuple[str, str | None] | None): global server + n_predict = 512 server.n_slots = 1 server.jinja = True server.n_ctx = 8192 - server.n_predict = 512 + server.n_predict = n_predict server.model_hf_repo = hf_repo server.model_hf_file = None - if template_override: + if isinstance(template_override, tuple): (template_hf_repo, template_variant) = template_override server.chat_template_file = f"../../../models/templates/{template_hf_repo.replace('/', '-') + ('-' + template_variant if template_variant else '')}.jinja" assert os.path.exists(server.chat_template_file), f"Template file {server.chat_template_file} does not exist. Run `python scripts/get_chat_template.py {template_hf_repo} {template_variant} > {server.chat_template_file}` to download the template." + elif isinstance(template_override, str): + server.chat_template = template_override server.start(timeout_seconds=TIMEOUT_SERVER_START) res = server.make_request("POST", "/chat/completions", data={ - "max_tokens": 256, + "max_tokens": n_predict, "messages": [ {"role": "user", "content": "What is the weather in Istanbul?"}, ], @@ -298,19 +342,39 @@ def test_weather_tool_call(hf_repo: str, template_override: Tuple[str, str | Non @pytest.mark.slow @pytest.mark.parametrize("expected_arguments_override,hf_repo,template_override", [ - (None, "bartowski/gemma-2-2b-it-GGUF:Q4_K_M", None), (None, "bartowski/Phi-3.5-mini-instruct-GGUF:Q4_K_M", None), + (None, "bartowski/Phi-3.5-mini-instruct-GGUF:Q4_K_M", "chatml"), + (None, "bartowski/functionary-small-v3.2-GGUF:Q8_0", ("meetkai-functionary-medium-v3.2", None)), - ('{"code":"print("}', "bartowski/Meta-Llama-3.1-8B-Instruct-GGUF:Q4_K_M", None), - (None, "bartowski/Llama-3.2-1B-Instruct-GGUF:Q4_K_M", ("meta-llama-Llama-3.2-3B-Instruct", None)), + (None, "bartowski/functionary-small-v3.2-GGUF:Q8_0", "chatml"), + + (None, "bartowski/Meta-Llama-3.1-8B-Instruct-GGUF:Q4_K_M", None), + ('{"code":"print("}', "bartowski/Meta-Llama-3.1-8B-Instruct-GGUF:Q4_K_M", "chatml"), + + ('{"code":"print("}', "bartowski/Llama-3.2-1B-Instruct-GGUF:Q4_K_M", ("meta-llama-Llama-3.2-3B-Instruct", None)), + (None, "bartowski/Llama-3.2-1B-Instruct-GGUF:Q4_K_M", "chatml"), + ('{"code":"print("}', "bartowski/Llama-3.2-3B-Instruct-GGUF:Q4_K_M", ("meta-llama-Llama-3.2-3B-Instruct", None)), + ('{"code":"print("}', "bartowski/Llama-3.2-3B-Instruct-GGUF:Q4_K_M", "chatml"), + (None, "bartowski/Qwen2.5-7B-Instruct-GGUF:Q4_K_M", None), - (None, "bartowski/Hermes-2-Pro-Llama-3-8B-GGUF:Q4_K_M", ("NousResearch/Hermes-2-Pro-Llama-3-8B", "tool_use")), - (None, "bartowski/Hermes-3-Llama-3.1-8B-GGUF:Q4_K_M", ("NousResearch-Hermes-3-Llama-3.1-8B", "tool_use")), + (None, "bartowski/Qwen2.5-7B-Instruct-GGUF:Q4_K_M", "chatml"), + + (None, "bartowski/Hermes-2-Pro-Llama-3-8B-GGUF:Q4_K_M", ("NousResearch/Hermes-2-Pro-Llama-3-8B", "tool_use")), + (None, "bartowski/Hermes-2-Pro-Llama-3-8B-GGUF:Q4_K_M", "chatml"), + + (None, "bartowski/Hermes-3-Llama-3.1-8B-GGUF:Q4_K_M", ("NousResearch-Hermes-3-Llama-3.1-8B", "tool_use")), + (None, "bartowski/Hermes-3-Llama-3.1-8B-GGUF:Q4_K_M", "chatml"), + (None, "bartowski/Mistral-Nemo-Instruct-2407-GGUF:Q4_K_M", None), + (None, "bartowski/Mistral-Nemo-Instruct-2407-GGUF:Q4_K_M", "chatml"), + + # Note: gemma-2-2b-it knows itself as "model", not "assistant", so we don't test the ill-suited chatml on it. + (None, "bartowski/gemma-2-2b-it-GGUF:Q4_K_M", None), + # (None, "bartowski/DeepSeek-R1-Distill-Qwen-7B-GGUF:Q4_K_M", None), ]) -def test_hello_world_tool_call(expected_arguments_override: str | None, hf_repo: str, template_override: Tuple[str, str | None] | None): +def test_hello_world_tool_call(expected_arguments_override: str | None, hf_repo: str, template_override: str | Tuple[str, str | None] | None): global server server.n_slots = 1 server.jinja = True @@ -318,10 +382,12 @@ def test_hello_world_tool_call(expected_arguments_override: str | None, hf_repo: server.n_predict = 128 server.model_hf_repo = hf_repo server.model_hf_file = None - if template_override: + if isinstance(template_override, tuple): (template_hf_repo, template_variant) = template_override server.chat_template_file = f"../../../models/templates/{template_hf_repo.replace('/', '-') + ('-' + template_variant if template_variant else '')}.jinja" assert os.path.exists(server.chat_template_file), f"Template file {server.chat_template_file} does not exist. Run `python scripts/get_chat_template.py {template_hf_repo} {template_variant} > {server.chat_template_file}` to download the template." + elif isinstance(template_override, str): + server.chat_template = template_override server.start(timeout_seconds=TIMEOUT_SERVER_START) res = server.make_request("POST", "/chat/completions", data={ "max_tokens": 256, diff --git a/examples/server/utils.hpp b/examples/server/utils.hpp index 3d2c04666..5f97df5fd 100644 --- a/examples/server/utils.hpp +++ b/examples/server/utils.hpp @@ -5,10 +5,6 @@ #include "llama.h" #include "common/base64.hpp" -#ifndef NDEBUG -// crash the server in debug mode, otherwise send an http 500 error -#define CPPHTTPLIB_NO_EXCEPTIONS 1 -#endif // increase max payload length to allow use of larger context size #define CPPHTTPLIB_FORM_URL_ENCODED_PAYLOAD_MAX_LENGTH 1048576 #include "httplib.h" @@ -484,13 +480,14 @@ static bool ends_with(const std::string & str, const std::string & suffix) { static size_t find_partial_stop_string(const std::string &stop, const std::string &text) { if (!text.empty() && !stop.empty()) { - auto it = std::find(stop.rbegin(), stop.rend(), text.back()); - while (it != stop.rend()) { - size_t length = std::distance(it, stop.rend()); - if (text.length() >= length && 0 == text.compare(text.length() - length, length, stop)) { - return text.length() - length; + const char text_last_char = text.back(); + for (int64_t char_index = stop.size() - 1; char_index >= 0; char_index--) { + if (stop[char_index] == text_last_char) { + const std::string current_partial = stop.substr(0, char_index + 1); + if (ends_with(text, current_partial)) { + return text.size() - char_index - 1; + } } - it = std::find(std::next(it), stop.rend(), text.back()); } } @@ -640,9 +637,13 @@ static json oaicompat_completion_params_parse( inputs.tools = tools; inputs.tool_choice = tool_choice; inputs.parallel_tool_calls = json_value(body, "parallel_tool_calls", false); + if (inputs.parallel_tool_calls && !tmpl.original_caps().supports_parallel_tool_calls) { + LOG_DBG("Disabling parallel_tool_calls because the template does not support it\n"); + inputs.parallel_tool_calls = false; + } inputs.stream = stream; // TODO: support mixing schema w/ tools beyond generic format. - inputs.json_schema = json_value(llama_params, "json_schema", json::object()); + inputs.json_schema = json_value(llama_params, "json_schema", json()); auto chat_params = common_chat_params_init(tmpl, inputs); llama_params["chat_format"] = static_cast(chat_params.format); @@ -657,6 +658,7 @@ static json oaicompat_completion_params_parse( }); } llama_params["grammar_triggers"] = grammar_triggers; + llama_params["preserved_tokens"] = chat_params.preserved_tokens; for (const auto & stop : chat_params.additional_stops) { llama_params["stop"].push_back(stop); } diff --git a/examples/server/webui/.gitignore b/examples/server/webui/.gitignore new file mode 100644 index 000000000..a547bf36d --- /dev/null +++ b/examples/server/webui/.gitignore @@ -0,0 +1,24 @@ +# Logs +logs +*.log +npm-debug.log* +yarn-debug.log* +yarn-error.log* +pnpm-debug.log* +lerna-debug.log* + +node_modules +dist +dist-ssr +*.local + +# Editor directories and files +.vscode/* +!.vscode/extensions.json +.idea +.DS_Store +*.suo +*.ntvs* +*.njsproj +*.sln +*.sw? diff --git a/examples/server/webui/.prettierignore b/examples/server/webui/.prettierignore new file mode 100644 index 000000000..c0cb165b3 --- /dev/null +++ b/examples/server/webui/.prettierignore @@ -0,0 +1,10 @@ +**/.vscode +**/.github +**/.git +**/.svn +**/.hg +**/node_modules +**/dist +**/build + +*.config.js diff --git a/examples/server/webui/eslint.config.js b/examples/server/webui/eslint.config.js new file mode 100644 index 000000000..7c0d39b89 --- /dev/null +++ b/examples/server/webui/eslint.config.js @@ -0,0 +1,26 @@ +import js from '@eslint/js' +import globals from 'globals' +import reactHooks from 'eslint-plugin-react-hooks' +import reactRefresh from 'eslint-plugin-react-refresh' +import tseslint from 'typescript-eslint' + +export default tseslint.config( + { ignores: ['dist'] }, + { + extends: [js.configs.recommended, ...tseslint.configs.recommended], + files: ['**/*.{ts,tsx}'], + languageOptions: { + ecmaVersion: 2020, + globals: globals.browser, + }, + plugins: { + 'react-hooks': reactHooks, + 'react-refresh': reactRefresh, + }, + rules: { + ...reactHooks.configs.recommended.rules, + 'react-refresh/only-export-components': 'off', + '@typescript-eslint/no-unused-vars': 'off', + }, + }, +) diff --git a/examples/server/webui/index.html b/examples/server/webui/index.html index d3893ea4e..471f46b3a 100644 --- a/examples/server/webui/index.html +++ b/examples/server/webui/index.html @@ -1,343 +1,16 @@ - + - - - - - 🦙 llama.cpp - chat - - - -
-
- - - -
- -
-
-

Conversations

- - - -
- - -
- + New conversation -
-
- {{ conv.messages[0].content }} -
-
- Conversations are saved to browser's localStorage -
-
-
- - -
- -
- - - -
llama.cpp
- - -
-
- - - - -
-
- -
- - -
-
-
- - - -
-
    -
  • - -
    • -
  • - -
    • -
-
-
-
-
- - -
-
- - {{ messages.length === 0 ? 'Send a message to start' : '' }} -
-
- -
- - -
- -
-
- - -
- - - -
-
- -
- - - - -
-

Settings

-
-

Settings below are saved in browser's localStorage

- - - - - -
- Other sampler settings -
- - - - -
-
- -
- Penalties settings -
- -
-
- -
- Reasoning models -
-
- - Expand though process by default for generating message -
-
- - Exclude thought process when sending request to API (Recommended for DeepSeek-R1) -
-
-
- -
- Advanced config -
-
- - -
-
- - Show tokens per second -
- -
-
-
- - -
- - - -
-
- - -
- - - - - - - - - - - - + + + + + 🦙 llama.cpp - chat + + +
+ + diff --git a/examples/server/webui/package-lock.json b/examples/server/webui/package-lock.json index bbebccbf2..c6c5de3c0 100644 --- a/examples/server/webui/package-lock.json +++ b/examples/server/webui/package-lock.json @@ -8,22 +8,43 @@ "name": "webui", "version": "0.0.0", "dependencies": { + "@heroicons/react": "^2.2.0", "@sec-ant/readable-stream": "^0.6.0", "@vscode/markdown-it-katex": "^1.1.1", "autoprefixer": "^10.4.20", "daisyui": "^4.12.14", "highlight.js": "^11.10.0", "katex": "^0.16.15", - "markdown-it": "^14.1.0", "postcss": "^8.4.49", + "react": "^18.3.1", + "react-dom": "^18.3.1", + "react-markdown": "^9.0.3", + "react-router": "^7.1.5", + "rehype-highlight": "^7.0.2", + "rehype-katex": "^7.0.1", + "remark-breaks": "^4.0.0", + "remark-gfm": "^4.0.0", + "remark-math": "^6.0.0", "tailwindcss": "^3.4.15", "textlinestream": "^1.1.1", - "vite-plugin-singlefile": "^2.0.3", - "vue": "^3.5.13" + "vite-plugin-singlefile": "^2.0.3" }, "devDependencies": { - "sass-embedded": "^1.83.0", - "vite": "^5.4.10" + "@eslint/js": "^9.17.0", + "@types/markdown-it": "^14.1.2", + "@types/node": "^22.13.1", + "@types/react": "^18.3.18", + "@types/react-dom": "^18.3.5", + "@vitejs/plugin-react": "^4.3.4", + "eslint": "^9.17.0", + "eslint-plugin-react-hooks": "^5.0.0", + "eslint-plugin-react-refresh": "^0.4.16", + "globals": "^15.14.0", + "prettier": "^3.4.2", + "sass-embedded": "^1.83.4", + "typescript": "~5.6.2", + "typescript-eslint": "^8.18.2", + "vite": "^6.0.5" } }, "node_modules/@alloc/quick-lru": { @@ -38,6 +59,302 @@ "url": "https://github.com/sponsors/sindresorhus" } }, + "node_modules/@ampproject/remapping": { + "version": "2.3.0", + "resolved": "https://registry.npmjs.org/@ampproject/remapping/-/remapping-2.3.0.tgz", + "integrity": "sha512-30iZtAPgz+LTIYoeivqYo853f02jBYSd5uGnGpkFV0M3xOt9aN73erkgYAmZU43x4VfqcnLxW9Kpg3R5LC4YYw==", + "dev": true, + "license": "Apache-2.0", + "dependencies": { + "@jridgewell/gen-mapping": "^0.3.5", + "@jridgewell/trace-mapping": 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"sha512-bXE4cR/kVZhKZX/RjPEflHaKVhUVl85noU3v6b8apfQEc1x4A+zBxjZ4lN8LqGd6WZ3dl98pY4o717VFmoPp+A==", + "license": "MIT", + "funding": { + "type": "github", + "url": "https://github.com/sponsors/wooorm" } } } diff --git a/examples/server/webui/package.json b/examples/server/webui/package.json index 2836cce00..3be2b14de 100644 --- a/examples/server/webui/package.json +++ b/examples/server/webui/package.json @@ -5,26 +5,55 @@ "type": "module", "scripts": { "dev": "vite", - "build": "vite build", - "preview": "vite preview", - "analyze": "ANALYZE=1 npx vite-bundle-visualizer" - }, - "devDependencies": { - "sass-embedded": "^1.83.0", - "vite": "^5.4.10" + "build": "tsc -b && vite build", + "format": "eslint . && prettier --write .", + "lint": "eslint .", + "preview": "vite preview" }, "dependencies": { + "@heroicons/react": "^2.2.0", "@sec-ant/readable-stream": "^0.6.0", "@vscode/markdown-it-katex": "^1.1.1", "autoprefixer": "^10.4.20", "daisyui": "^4.12.14", "highlight.js": "^11.10.0", "katex": "^0.16.15", - "markdown-it": "^14.1.0", "postcss": "^8.4.49", + "react": "^18.3.1", + "react-dom": "^18.3.1", + "react-markdown": "^9.0.3", + "react-router": "^7.1.5", + "rehype-highlight": "^7.0.2", + "rehype-katex": "^7.0.1", + "remark-breaks": "^4.0.0", + "remark-gfm": "^4.0.0", + "remark-math": "^6.0.0", "tailwindcss": "^3.4.15", "textlinestream": "^1.1.1", - "vite-plugin-singlefile": "^2.0.3", - "vue": "^3.5.13" + "vite-plugin-singlefile": "^2.0.3" + }, + "devDependencies": { + "@eslint/js": "^9.17.0", + "@types/markdown-it": "^14.1.2", + "@types/node": "^22.13.1", + "@types/react": "^18.3.18", + "@types/react-dom": "^18.3.5", + "@vitejs/plugin-react": "^4.3.4", + "eslint": "^9.17.0", + "eslint-plugin-react-hooks": "^5.0.0", + "eslint-plugin-react-refresh": "^0.4.16", + "globals": "^15.14.0", + "prettier": "^3.4.2", + "sass-embedded": "^1.83.4", + "typescript": "~5.6.2", + "typescript-eslint": "^8.18.2", + "vite": "^6.0.5" + }, + "prettier": { + "trailingComma": "es5", + "tabWidth": 2, + "semi": true, + "singleQuote": true, + "bracketSameLine": false } } diff --git a/examples/server/webui/public/demo-conversation.json b/examples/server/webui/public/demo-conversation.json index 75ab599dd..338b4aea5 100644 --- a/examples/server/webui/public/demo-conversation.json +++ b/examples/server/webui/public/demo-conversation.json @@ -11,7 +11,7 @@ { "id": 1734087548327, "role": "assistant", - "content": "This is the formula:\n\n$\\frac{e^{x_i}}{\\sum_{j=1}^{n}e^{x_j}}$\n\nGiven an input vector \\(\\mathbf{x} = [x_1, x_2, \\ldots, x_n]\\)\n\n\\[\ny_i = \\frac{e^{x_i}}{\\sum_{j=1}^n e^{x_j}}\n\\]\n\nCode block latex:\n```latex\n\\frac{e^{x_i}}{\\sum_{j=1}^{n}e^{x_j}}\n```\n\nTest dollar sign: $1234 $4567\n\nInvalid latex syntax: $E = mc^$ and $$E = mc^$$", + "content": "This is the formula:\n\n$\\frac{e^{x_i}}{\\sum_{j=1}^{n}e^{x_j}}$\n\nGiven an input vector \\(\\mathbf{x} = [x_1, x_2, \\ldots, x_n]\\)\n\n\\[\ny_i = \\frac{e^{x_i}}{\\sum_{j=1}^n e^{x_j}}\n\\]\n\n$2x + y = z$\n\nCode block latex:\n```latex\n\\frac{e^{x_i}}{\\sum_{j=1}^{n}e^{x_j}}\n```\n\nTest dollar sign: $1234 $4567\n\nInvalid latex syntax: $E = mc^$ and $$E = mc^$$", "timings": { "prompt_n": 1, "prompt_ms": 28.923, diff --git a/examples/server/webui/src/App.tsx b/examples/server/webui/src/App.tsx new file mode 100644 index 000000000..2ce734682 --- /dev/null +++ b/examples/server/webui/src/App.tsx @@ -0,0 +1,47 @@ +import { HashRouter, Outlet, Route, Routes } from 'react-router'; +import Header from './components/Header'; +import Sidebar from './components/Sidebar'; +import { AppContextProvider, useAppContext } from './utils/app.context'; +import ChatScreen from './components/ChatScreen'; +import SettingDialog from './components/SettingDialog'; + +function App() { + return ( + +
+ + + }> + } /> + } /> + + + +
+ + ); +} + +function AppLayout() { + const { showSettings, setShowSettings } = useAppContext(); + return ( + <> + +
+
+ +
+ { + setShowSettings(false)} + /> + } + + ); +} + +export default App; diff --git a/examples/server/webui/src/Config.ts b/examples/server/webui/src/Config.ts new file mode 100644 index 000000000..779ed9bf7 --- /dev/null +++ b/examples/server/webui/src/Config.ts @@ -0,0 +1,92 @@ +import daisyuiThemes from 'daisyui/src/theming/themes'; +import { isNumeric } from './utils/misc'; + +export const isDev = import.meta.env.MODE === 'development'; + +// constants +export const BASE_URL = new URL('.', document.baseURI).href + .toString() + .replace(/\/$/, ''); + +export const CONFIG_DEFAULT = { + // Note: in order not to introduce breaking changes, please keep the same data type (number, string, etc) if you want to change the default value. Do not use null or undefined for default value. + // Do not use nested objects, keep it single level. Prefix the key if you need to group them. + apiKey: '', + systemMessage: 'You are a helpful assistant.', + showTokensPerSecond: false, + showThoughtInProgress: false, + excludeThoughtOnReq: true, + // make sure these default values are in sync with `common.h` + samplers: 'edkypmxt', + temperature: 0.8, + dynatemp_range: 0.0, + dynatemp_exponent: 1.0, + top_k: 40, + top_p: 0.95, + min_p: 0.05, + xtc_probability: 0.0, + xtc_threshold: 0.1, + typical_p: 1.0, + repeat_last_n: 64, + repeat_penalty: 1.0, + presence_penalty: 0.0, + frequency_penalty: 0.0, + dry_multiplier: 0.0, + dry_base: 1.75, + dry_allowed_length: 2, + dry_penalty_last_n: -1, + max_tokens: -1, + custom: '', // custom json-stringified object + // experimental features + pyIntepreterEnabled: false, +}; +export const CONFIG_INFO: Record = { + apiKey: 'Set the API Key if you are using --api-key option for the server.', + systemMessage: 'The starting message that defines how model should behave.', + samplers: + 'The order at which samplers are applied, in simplified way. Default is "dkypmxt": dry->top_k->typ_p->top_p->min_p->xtc->temperature', + temperature: + 'Controls the randomness of the generated text by affecting the probability distribution of the output tokens. Higher = more random, lower = more focused.', + dynatemp_range: + 'Addon for the temperature sampler. The added value to the range of dynamic temperature, which adjusts probabilities by entropy of tokens.', + dynatemp_exponent: + 'Addon for the temperature sampler. Smoothes out the probability redistribution based on the most probable token.', + top_k: 'Keeps only k top tokens.', + top_p: + 'Limits tokens to those that together have a cumulative probability of at least p', + min_p: + 'Limits tokens based on the minimum probability for a token to be considered, relative to the probability of the most likely token.', + xtc_probability: + 'XTC sampler cuts out top tokens; this parameter controls the chance of cutting tokens at all. 0 disables XTC.', + xtc_threshold: + 'XTC sampler cuts out top tokens; this parameter controls the token probability that is required to cut that token.', + typical_p: + 'Sorts and limits tokens based on the difference between log-probability and entropy.', + repeat_last_n: 'Last n tokens to consider for penalizing repetition', + repeat_penalty: + 'Controls the repetition of token sequences in the generated text', + presence_penalty: + 'Limits tokens based on whether they appear in the output or not.', + frequency_penalty: + 'Limits tokens based on how often they appear in the output.', + dry_multiplier: + 'DRY sampling reduces repetition in generated text even across long contexts. This parameter sets the DRY sampling multiplier.', + dry_base: + 'DRY sampling reduces repetition in generated text even across long contexts. This parameter sets the DRY sampling base value.', + dry_allowed_length: + 'DRY sampling reduces repetition in generated text even across long contexts. This parameter sets the allowed length for DRY sampling.', + dry_penalty_last_n: + 'DRY sampling reduces repetition in generated text even across long contexts. This parameter sets DRY penalty for the last n tokens.', + max_tokens: 'The maximum number of token per output.', + custom: '', // custom json-stringified object +}; +// config keys having numeric value (i.e. temperature, top_k, top_p, etc) +export const CONFIG_NUMERIC_KEYS = Object.entries(CONFIG_DEFAULT) + .filter((e) => isNumeric(e[1])) + .map((e) => e[0]); +// list of themes supported by daisyui +export const THEMES = ['light', 'dark'] + // make sure light & dark are always at the beginning + .concat( + Object.keys(daisyuiThemes).filter((t) => t !== 'light' && t !== 'dark') + ); diff --git a/examples/server/webui/src/components/CanvasPyInterpreter.tsx b/examples/server/webui/src/components/CanvasPyInterpreter.tsx new file mode 100644 index 000000000..c2707fe20 --- /dev/null +++ b/examples/server/webui/src/components/CanvasPyInterpreter.tsx @@ -0,0 +1,195 @@ +import { useEffect, useState } from 'react'; +import { useAppContext } from '../utils/app.context'; +import { OpenInNewTab, XCloseButton } from '../utils/common'; +import { CanvasType } from '../utils/types'; +import { PlayIcon, StopIcon } from '@heroicons/react/24/outline'; +import StorageUtils from '../utils/storage'; + +const canInterrupt = typeof SharedArrayBuffer === 'function'; + +// adapted from https://pyodide.org/en/stable/usage/webworker.html +const WORKER_CODE = ` +importScripts("https://cdn.jsdelivr.net/pyodide/v0.27.2/full/pyodide.js"); + +let stdOutAndErr = []; + +let pyodideReadyPromise = loadPyodide({ + stdout: (data) => stdOutAndErr.push(data), + stderr: (data) => stdOutAndErr.push(data), +}); + +let alreadySetBuff = false; + +self.onmessage = async (event) => { + stdOutAndErr = []; + + // make sure loading is done + const pyodide = await pyodideReadyPromise; + const { id, python, context, interruptBuffer } = event.data; + + if (interruptBuffer && !alreadySetBuff) { + pyodide.setInterruptBuffer(interruptBuffer); + alreadySetBuff = true; + } + + // Now load any packages we need, run the code, and send the result back. + await pyodide.loadPackagesFromImports(python); + + // make a Python dictionary with the data from content + const dict = pyodide.globals.get("dict"); + const globals = dict(Object.entries(context)); + try { + self.postMessage({ id, running: true }); + // Execute the python code in this context + const result = pyodide.runPython(python, { globals }); + self.postMessage({ result, id, stdOutAndErr }); + } catch (error) { + self.postMessage({ error: error.message, id }); + } + interruptBuffer[0] = 0; +}; +`; + +let worker: Worker; +const interruptBuffer = canInterrupt + ? new Uint8Array(new SharedArrayBuffer(1)) + : null; + +const startWorker = () => { + if (!worker) { + worker = new Worker( + URL.createObjectURL(new Blob([WORKER_CODE], { type: 'text/javascript' })) + ); + } +}; + +if (StorageUtils.getConfig().pyIntepreterEnabled) { + startWorker(); +} + +const runCodeInWorker = ( + pyCode: string, + callbackRunning: () => void +): { + donePromise: Promise; + interrupt: () => void; +} => { + startWorker(); + const id = Math.random() * 1e8; + const context = {}; + if (interruptBuffer) { + interruptBuffer[0] = 0; + } + + const donePromise = new Promise((resolve) => { + worker.onmessage = (event) => { + const { error, stdOutAndErr, running } = event.data; + if (id !== event.data.id) return; + if (running) { + callbackRunning(); + return; + } else if (error) { + resolve(error.toString()); + } else { + resolve(stdOutAndErr.join('\n')); + } + }; + worker.postMessage({ id, python: pyCode, context, interruptBuffer }); + }); + + const interrupt = () => { + console.log('Interrupting...'); + console.trace(); + if (interruptBuffer) { + interruptBuffer[0] = 2; + } + }; + + return { donePromise, interrupt }; +}; + +export default function CanvasPyInterpreter() { + const { canvasData, setCanvasData } = useAppContext(); + + const [code, setCode] = useState(canvasData?.content ?? ''); // copy to avoid direct mutation + const [running, setRunning] = useState(false); + const [output, setOutput] = useState(''); + const [interruptFn, setInterruptFn] = useState<() => void>(); + const [showStopBtn, setShowStopBtn] = useState(false); + + const runCode = async (pycode: string) => { + interruptFn?.(); + setRunning(true); + setOutput('Loading Pyodide...'); + const { donePromise, interrupt } = runCodeInWorker(pycode, () => { + setOutput('Running...'); + setShowStopBtn(canInterrupt); + }); + setInterruptFn(() => interrupt); + const out = await donePromise; + setOutput(out); + setRunning(false); + setShowStopBtn(false); + }; + + // run code on mount + useEffect(() => { + setCode(canvasData?.content ?? ''); + runCode(canvasData?.content ?? ''); + // eslint-disable-next-line react-hooks/exhaustive-deps + }, [canvasData?.content]); + + if (canvasData?.type !== CanvasType.PY_INTERPRETER) { + return null; + } + + return ( +
+
+
+ Python Interpreter + setCanvasData(null)} + /> +
+
+ +
+
+ + {showStopBtn && ( + + )} + + + Report a bug + + +
+ +
+
+
+
+ ); +} diff --git a/examples/server/webui/src/components/ChatMessage.tsx b/examples/server/webui/src/components/ChatMessage.tsx new file mode 100644 index 000000000..ec72196ba --- /dev/null +++ b/examples/server/webui/src/components/ChatMessage.tsx @@ -0,0 +1,235 @@ +import { useMemo, useState } from 'react'; +import { useAppContext } from '../utils/app.context'; +import { Message, PendingMessage } from '../utils/types'; +import { classNames } from '../utils/misc'; +import MarkdownDisplay, { CopyButton } from './MarkdownDisplay'; + +interface SplitMessage { + content: PendingMessage['content']; + thought?: string; + isThinking?: boolean; +} + +export default function ChatMessage({ + msg, + id, + scrollToBottom, + isPending, +}: { + msg: Message | PendingMessage; + id?: string; + scrollToBottom: (requiresNearBottom: boolean) => void; + isPending?: boolean; +}) { + const { viewingConversation, replaceMessageAndGenerate, config } = + useAppContext(); + const [editingContent, setEditingContent] = useState(null); + const timings = useMemo( + () => + msg.timings + ? { + ...msg.timings, + prompt_per_second: + (msg.timings.prompt_n / msg.timings.prompt_ms) * 1000, + predicted_per_second: + (msg.timings.predicted_n / msg.timings.predicted_ms) * 1000, + } + : null, + [msg.timings] + ); + + // for reasoning model, we split the message into content and thought + // TODO: implement this as remark/rehype plugin in the future + const { content, thought, isThinking }: SplitMessage = useMemo(() => { + if (msg.content === null || msg.role !== 'assistant') { + return { content: msg.content }; + } + let actualContent = ''; + let thought = ''; + let isThinking = false; + let thinkSplit = msg.content.split('', 2); + actualContent += thinkSplit[0]; + while (thinkSplit[1] !== undefined) { + // tag found + thinkSplit = thinkSplit[1].split('', 2); + thought += thinkSplit[0]; + isThinking = true; + if (thinkSplit[1] !== undefined) { + // closing tag found + isThinking = false; + thinkSplit = thinkSplit[1].split('', 2); + actualContent += thinkSplit[0]; + } + } + return { content: actualContent, thought, isThinking }; + }, [msg]); + + if (!viewingConversation) return null; + + const regenerate = async () => { + replaceMessageAndGenerate(viewingConversation.id, msg.id, undefined, () => + scrollToBottom(true) + ); + }; + + return ( +
+
+
+ {/* textarea for editing message */} + {editingContent !== null && ( + <> + +
+ + + + )} + {/* not editing content, render message */} + {editingContent === null && ( + <> + {content === null ? ( + <> + {/* show loading dots for pending message */} + + + ) : ( + <> + {/* render message as markdown */} +
+ {thought && ( +
+ + {isPending && isThinking ? ( + + + Thinking + + ) : ( + Thought Process + )} + +
+ +
+
+ )} + +
+ + )} + {/* render timings if enabled */} + {timings && config.showTokensPerSecond && ( +
+
+ Speed: {timings.predicted_per_second.toFixed(1)} t/s +
+
+ Prompt +
- Tokens: {timings.prompt_n} +
- Time: {timings.prompt_ms} ms +
- Speed: {timings.prompt_per_second.toFixed(1)} t/s +
+ Generation +
- Tokens: {timings.predicted_n} +
- Time: {timings.predicted_ms} ms +
- Speed: {timings.predicted_per_second.toFixed(1)} t/s +
+
+
+ )} + + )} +
+
+ + {/* actions for each message */} + {msg.content !== null && ( +
+ {/* user message */} + {msg.role === 'user' && ( + + )} + {/* assistant message */} + {msg.role === 'assistant' && ( + <> + {!isPending && ( + + )} + + + )} +
+ )} +
+ ); +} diff --git a/examples/server/webui/src/components/ChatScreen.tsx b/examples/server/webui/src/components/ChatScreen.tsx new file mode 100644 index 000000000..dbc683ed1 --- /dev/null +++ b/examples/server/webui/src/components/ChatScreen.tsx @@ -0,0 +1,146 @@ +import { useEffect, useState } from 'react'; +import { useAppContext } from '../utils/app.context'; +import StorageUtils from '../utils/storage'; +import { useNavigate } from 'react-router'; +import ChatMessage from './ChatMessage'; +import { CanvasType, PendingMessage } from '../utils/types'; +import { classNames } from '../utils/misc'; +import CanvasPyInterpreter from './CanvasPyInterpreter'; + +export default function ChatScreen() { + const { + viewingConversation, + sendMessage, + isGenerating, + stopGenerating, + pendingMessages, + canvasData, + } = useAppContext(); + const [inputMsg, setInputMsg] = useState(''); + const navigate = useNavigate(); + + const currConvId = viewingConversation?.id ?? ''; + const pendingMsg: PendingMessage | undefined = pendingMessages[currConvId]; + + const scrollToBottom = (requiresNearBottom: boolean) => { + const mainScrollElem = document.getElementById('main-scroll'); + if (!mainScrollElem) return; + const spaceToBottom = + mainScrollElem.scrollHeight - + mainScrollElem.scrollTop - + mainScrollElem.clientHeight; + if (!requiresNearBottom || spaceToBottom < 50) { + setTimeout( + () => mainScrollElem.scrollTo({ top: mainScrollElem.scrollHeight }), + 1 + ); + } + }; + + // scroll to bottom when conversation changes + useEffect(() => { + scrollToBottom(false); + }, [viewingConversation?.id]); + + const sendNewMessage = async () => { + if (inputMsg.trim().length === 0 || isGenerating(currConvId)) return; + const convId = viewingConversation?.id ?? StorageUtils.getNewConvId(); + const lastInpMsg = inputMsg; + setInputMsg(''); + if (!viewingConversation) { + // if user is creating a new conversation, redirect to the new conversation + navigate(`/chat/${convId}`); + } + scrollToBottom(false); + // auto scroll as message is being generated + const onChunk = () => scrollToBottom(true); + if (!(await sendMessage(convId, inputMsg, onChunk))) { + // restore the input message if failed + setInputMsg(lastInpMsg); + } + }; + + const hasCanvas = !!canvasData; + + return ( +
+
+ {/* chat messages */} +
+
+ {/* placeholder to shift the message to the bottom */} + {viewingConversation ? '' : 'Send a message to start'} +
+ {viewingConversation?.messages.map((msg) => ( + + ))} + + {pendingMsg && ( + + )} +
+ + {/* chat input */} +
+ + {isGenerating(currConvId) ? ( + + ) : ( + + )} +
+
+
+ {canvasData?.type === CanvasType.PY_INTERPRETER && ( + + )} +
+
+ ); +} diff --git a/examples/server/webui/src/components/Header.tsx b/examples/server/webui/src/components/Header.tsx new file mode 100644 index 000000000..505350313 --- /dev/null +++ b/examples/server/webui/src/components/Header.tsx @@ -0,0 +1,176 @@ +import { useEffect, useState } from 'react'; +import StorageUtils from '../utils/storage'; +import { useAppContext } from '../utils/app.context'; +import { classNames } from '../utils/misc'; +import daisyuiThemes from 'daisyui/src/theming/themes'; +import { THEMES } from '../Config'; +import { useNavigate } from 'react-router'; + +export default function Header() { + const navigate = useNavigate(); + const [selectedTheme, setSelectedTheme] = useState(StorageUtils.getTheme()); + const { setShowSettings } = useAppContext(); + + const setTheme = (theme: string) => { + StorageUtils.setTheme(theme); + setSelectedTheme(theme); + }; + + useEffect(() => { + document.body.setAttribute('data-theme', selectedTheme); + document.body.setAttribute( + 'data-color-scheme', + // @ts-expect-error daisyuiThemes complains about index type, but it should work + daisyuiThemes[selectedTheme]?.['color-scheme'] ?? 'auto' + ); + }, [selectedTheme]); + + const { isGenerating, viewingConversation } = useAppContext(); + const isCurrConvGenerating = isGenerating(viewingConversation?.id ?? ''); + + const removeConversation = () => { + if (isCurrConvGenerating || !viewingConversation) return; + const convId = viewingConversation.id; + if (window.confirm('Are you sure to delete this conversation?')) { + StorageUtils.remove(convId); + navigate('/'); + } + }; + + const downloadConversation = () => { + if (isCurrConvGenerating || !viewingConversation) return; + const convId = viewingConversation.id; + const conversationJson = JSON.stringify(viewingConversation, null, 2); + const blob = new Blob([conversationJson], { type: 'application/json' }); + const url = URL.createObjectURL(blob); + const a = document.createElement('a'); + a.href = url; + a.download = `conversation_${convId}.json`; + document.body.appendChild(a); + a.click(); + document.body.removeChild(a); + URL.revokeObjectURL(url); + }; + + return ( +
+ {/* open sidebar button */} + + +
llama.cpp
+ + {/* action buttons (top right) */} +
+
+ {/* "..." button */} + + {/* dropdown menu */} + +
+
+ +
+ + {/* theme controller is copied from https://daisyui.com/components/theme-controller/ */} +
+
+
+ + + +
+
    +
  • + +
    • + {THEMES.map((theme) => ( +
  • + e.target.checked && setTheme(theme)} + /> +
    • + ))} +
+
+
+
+
+ ); +} diff --git a/examples/server/webui/src/components/MarkdownDisplay.tsx b/examples/server/webui/src/components/MarkdownDisplay.tsx new file mode 100644 index 000000000..5b7a72591 --- /dev/null +++ b/examples/server/webui/src/components/MarkdownDisplay.tsx @@ -0,0 +1,310 @@ +import React, { useMemo, useState } from 'react'; +import Markdown, { ExtraProps } from 'react-markdown'; +import remarkGfm from 'remark-gfm'; +import rehypeHightlight from 'rehype-highlight'; +import rehypeKatex from 'rehype-katex'; +import remarkMath from 'remark-math'; +import remarkBreaks from 'remark-breaks'; +import 'katex/dist/katex.min.css'; +import { classNames, copyStr } from '../utils/misc'; +import { ElementContent, Root } from 'hast'; +import { visit } from 'unist-util-visit'; +import { useAppContext } from '../utils/app.context'; +import { CanvasType } from '../utils/types'; + +export default function MarkdownDisplay({ + content, + isGenerating, +}: { + content: string; + isGenerating?: boolean; +}) { + const preprocessedContent = useMemo( + () => preprocessLaTeX(content), + [content] + ); + return ( + ( + + ), + // note: do not use "pre", "p" or other basic html elements here, it will cause the node to re-render when the message is being generated (this should be a bug with react-markdown, not sure how to fix it) + }} + > + {preprocessedContent} + + ); +} + +const CodeBlockButtons: React.ElementType< + React.ClassAttributes & + React.HTMLAttributes & + ExtraProps & { origContent: string; isGenerating?: boolean } +> = ({ node, origContent, isGenerating }) => { + const { config } = useAppContext(); + const startOffset = node?.position?.start.offset ?? 0; + const endOffset = node?.position?.end.offset ?? 0; + + const copiedContent = useMemo( + () => + origContent + .substring(startOffset, endOffset) + .replace(/^```[^\n]+\n/g, '') + .replace(/```$/g, ''), + [origContent, startOffset, endOffset] + ); + + const codeLanguage = useMemo( + () => + origContent + .substring(startOffset, startOffset + 10) + .match(/^```([^\n]+)\n/)?.[1] ?? '', + [origContent, startOffset] + ); + + const canRunCode = + !isGenerating && + config.pyIntepreterEnabled && + codeLanguage.startsWith('py'); + + return ( +
+ + {canRunCode && ( + + )} +
+ ); +}; + +export const CopyButton = ({ + content, + className, +}: { + content: string; + className?: string; +}) => { + const [copied, setCopied] = useState(false); + return ( + + ); +}; + +export const RunPyCodeButton = ({ + content, + className, +}: { + content: string; + className?: string; +}) => { + const { setCanvasData } = useAppContext(); + return ( + <> + + + ); +}; + +/** + * This injects the "button" element before each "pre" element. + * The actual button will be replaced with a react component in the MarkdownDisplay. + * We don't replace "pre" node directly because it will cause the node to re-render, which causes this bug: https://github.com/ggerganov/llama.cpp/issues/9608 + */ +function rehypeCustomCopyButton() { + return function (tree: Root) { + visit(tree, 'element', function (node) { + if (node.tagName === 'pre' && !node.properties.visited) { + const preNode = { ...node }; + // replace current node + preNode.properties.visited = 'true'; + node.tagName = 'div'; + node.properties = {}; + // add node for button + const btnNode: ElementContent = { + type: 'element', + tagName: 'button', + properties: {}, + children: [], + position: node.position, + }; + node.children = [btnNode, preNode]; + } + }); + }; +} + +/** + * The part below is copied and adapted from: + * https://github.com/danny-avila/LibreChat/blob/main/client/src/utils/latex.ts + * (MIT License) + */ + +// Regex to check if the processed content contains any potential LaTeX patterns +const containsLatexRegex = + /\\\(.*?\\\)|\\\[.*?\\\]|\$.*?\$|\\begin\{equation\}.*?\\end\{equation\}/; + +// Regex for inline and block LaTeX expressions +const inlineLatex = new RegExp(/\\\((.+?)\\\)/, 'g'); +const blockLatex = new RegExp(/\\\[(.*?[^\\])\\\]/, 'gs'); + +// Function to restore code blocks +const restoreCodeBlocks = (content: string, codeBlocks: string[]) => { + return content.replace( + /<>/g, + (_, index) => codeBlocks[index] + ); +}; + +// Regex to identify code blocks and inline code +const codeBlockRegex = /(```[\s\S]*?```|`.*?`)/g; + +export const processLaTeX = (_content: string) => { + let content = _content; + // Temporarily replace code blocks and inline code with placeholders + const codeBlocks: string[] = []; + let index = 0; + content = content.replace(codeBlockRegex, (match) => { + codeBlocks[index] = match; + return `<>`; + }); + + // Escape dollar signs followed by a digit or space and digit + let processedContent = content.replace(/(\$)(?=\s?\d)/g, '\\$'); + + // If no LaTeX patterns are found, restore code blocks and return the processed content + if (!containsLatexRegex.test(processedContent)) { + return restoreCodeBlocks(processedContent, codeBlocks); + } + + // Convert LaTeX expressions to a markdown compatible format + processedContent = processedContent + .replace(inlineLatex, (_: string, equation: string) => `$${equation}$`) // Convert inline LaTeX + .replace(blockLatex, (_: string, equation: string) => `$$${equation}$$`); // Convert block LaTeX + + // Restore code blocks + return restoreCodeBlocks(processedContent, codeBlocks); +}; + +/** + * Preprocesses LaTeX content by replacing delimiters and escaping certain characters. + * + * @param content The input string containing LaTeX expressions. + * @returns The processed string with replaced delimiters and escaped characters. + */ +export function preprocessLaTeX(content: string): string { + // Step 1: Protect code blocks + const codeBlocks: string[] = []; + content = content.replace(/(```[\s\S]*?```|`[^`\n]+`)/g, (_, code) => { + codeBlocks.push(code); + return `<>`; + }); + + // Step 2: Protect existing LaTeX expressions + const latexExpressions: string[] = []; + + // Protect block math ($$...$$), \[...\], and \(...\) as before. + content = content.replace( + /(\$\$[\s\S]*?\$\$|\\\[[\s\S]*?\\\]|\\\(.*?\\\))/g, + (match) => { + latexExpressions.push(match); + return `<>`; + } + ); + + // Protect inline math ($...$) only if it does NOT match a currency pattern. + // We assume a currency pattern is one where the inner content is purely numeric (with optional decimals). + content = content.replace(/\$([^$]+)\$/g, (match, inner) => { + if (/^\s*\d+(?:\.\d+)?\s*$/.test(inner)) { + // This looks like a currency value (e.g. "$123" or "$12.34"), + // so don't protect it. + return match; + } else { + // Otherwise, treat it as a LaTeX expression. + latexExpressions.push(match); + return `<>`; + } + }); + + // Step 3: Escape dollar signs that are likely currency indicators. + // (Now that inline math is protected, this will only escape dollars not already protected) + content = content.replace(/\$(?=\d)/g, '\\$'); + + // Step 4: Restore LaTeX expressions + content = content.replace( + /<>/g, + (_, index) => latexExpressions[parseInt(index)] + ); + + // Step 5: Restore code blocks + content = content.replace( + /<>/g, + (_, index) => codeBlocks[parseInt(index)] + ); + + // Step 6: Apply additional escaping functions + content = escapeBrackets(content); + content = escapeMhchem(content); + + return content; +} + +export function escapeBrackets(text: string): string { + const pattern = + /(```[\S\s]*?```|`.*?`)|\\\[([\S\s]*?[^\\])\\]|\\\((.*?)\\\)/g; + return text.replace( + pattern, + ( + match: string, + codeBlock: string | undefined, + squareBracket: string | undefined, + roundBracket: string | undefined + ): string => { + if (codeBlock != null) { + return codeBlock; + } else if (squareBracket != null) { + return `$$${squareBracket}$$`; + } else if (roundBracket != null) { + return `$${roundBracket}$`; + } + return match; + } + ); +} + +export function escapeMhchem(text: string) { + return text.replaceAll('$\\ce{', '$\\\\ce{').replaceAll('$\\pu{', '$\\\\pu{'); +} diff --git a/examples/server/webui/src/components/SettingDialog.tsx b/examples/server/webui/src/components/SettingDialog.tsx new file mode 100644 index 000000000..592b93fa3 --- /dev/null +++ b/examples/server/webui/src/components/SettingDialog.tsx @@ -0,0 +1,536 @@ +import { useState } from 'react'; +import { useAppContext } from '../utils/app.context'; +import { CONFIG_DEFAULT, CONFIG_INFO } from '../Config'; +import { isDev } from '../Config'; +import StorageUtils from '../utils/storage'; +import { classNames, isBoolean, isNumeric, isString } from '../utils/misc'; +import { + BeakerIcon, + ChatBubbleOvalLeftEllipsisIcon, + Cog6ToothIcon, + FunnelIcon, + HandRaisedIcon, + SquaresPlusIcon, +} from '@heroicons/react/24/outline'; +import { OpenInNewTab } from '../utils/common'; + +type SettKey = keyof typeof CONFIG_DEFAULT; + +const BASIC_KEYS: SettKey[] = [ + 'temperature', + 'top_k', + 'top_p', + 'min_p', + 'max_tokens', +]; +const SAMPLER_KEYS: SettKey[] = [ + 'dynatemp_range', + 'dynatemp_exponent', + 'typical_p', + 'xtc_probability', + 'xtc_threshold', +]; +const PENALTY_KEYS: SettKey[] = [ + 'repeat_last_n', + 'repeat_penalty', + 'presence_penalty', + 'frequency_penalty', + 'dry_multiplier', + 'dry_base', + 'dry_allowed_length', + 'dry_penalty_last_n', +]; + +enum SettingInputType { + SHORT_INPUT, + LONG_INPUT, + CHECKBOX, + CUSTOM, +} + +interface SettingFieldInput { + type: Exclude; + label: string | React.ReactElement; + help?: string | React.ReactElement; + key: SettKey; +} + +interface SettingFieldCustom { + type: SettingInputType.CUSTOM; + key: SettKey; + component: + | string + | React.FC<{ + value: string | boolean | number; + onChange: (value: string) => void; + }>; +} + +interface SettingSection { + title: React.ReactElement; + fields: (SettingFieldInput | SettingFieldCustom)[]; +} + +const ICON_CLASSNAME = 'w-4 h-4 mr-1 inline'; + +const SETTING_SECTIONS: SettingSection[] = [ + { + title: ( + <> + + General + + ), + fields: [ + { + type: SettingInputType.SHORT_INPUT, + label: 'API Key', + key: 'apiKey', + }, + { + type: SettingInputType.LONG_INPUT, + label: 'System Message (will be disabled if left empty)', + key: 'systemMessage', + }, + ...BASIC_KEYS.map( + (key) => + ({ + type: SettingInputType.SHORT_INPUT, + label: key, + key, + }) as SettingFieldInput + ), + ], + }, + { + title: ( + <> + + Samplers + + ), + fields: [ + { + type: SettingInputType.SHORT_INPUT, + label: 'Samplers queue', + key: 'samplers', + }, + ...SAMPLER_KEYS.map( + (key) => + ({ + type: SettingInputType.SHORT_INPUT, + label: key, + key, + }) as SettingFieldInput + ), + ], + }, + { + title: ( + <> + + Penalties + + ), + fields: PENALTY_KEYS.map((key) => ({ + type: SettingInputType.SHORT_INPUT, + label: key, + key, + })), + }, + { + title: ( + <> + + Reasoning + + ), + fields: [ + { + type: SettingInputType.CHECKBOX, + label: 'Expand though process by default for generating message', + key: 'showThoughtInProgress', + }, + { + type: SettingInputType.CHECKBOX, + label: + 'Exclude thought process when sending request to API (Recommended for DeepSeek-R1)', + key: 'excludeThoughtOnReq', + }, + ], + }, + { + title: ( + <> + + Advanced + + ), + fields: [ + { + type: SettingInputType.CUSTOM, + key: 'custom', // dummy key, won't be used + component: () => { + const debugImportDemoConv = async () => { + const res = await fetch('/demo-conversation.json'); + const demoConv = await res.json(); + StorageUtils.remove(demoConv.id); + for (const msg of demoConv.messages) { + StorageUtils.appendMsg(demoConv.id, msg); + } + }; + return ( + + ); + }, + }, + { + type: SettingInputType.CHECKBOX, + label: 'Show tokens per second', + key: 'showTokensPerSecond', + }, + { + type: SettingInputType.LONG_INPUT, + label: ( + <> + Custom JSON config (For more info, refer to{' '} + + server documentation + + ) + + ), + key: 'custom', + }, + ], + }, + { + title: ( + <> + + Experimental + + ), + fields: [ + { + type: SettingInputType.CUSTOM, + key: 'custom', // dummy key, won't be used + component: () => ( + <> +

+ Experimental features are not guaranteed to work correctly. +
+
+ If you encounter any problems, create a{' '} + + Bug (misc.) + {' '} + report on Github. Please also specify webui/experimental on + the report title and include screenshots. +
+
+ Some features may require packages downloaded from CDN, so they + need internet connection. +

+ + ), + }, + { + type: SettingInputType.CHECKBOX, + label: ( + <> + Enable Python interpreter +
+ + This feature uses{' '} + pyodide, + downloaded from CDN. To use this feature, ask the LLM to generate + python code inside a markdown code block. You will see a "Run" + button on the code block, near the "Copy" button. + + + ), + key: 'pyIntepreterEnabled', + }, + ], + }, +]; + +export default function SettingDialog({ + show, + onClose, +}: { + show: boolean; + onClose: () => void; +}) { + const { config, saveConfig } = useAppContext(); + const [sectionIdx, setSectionIdx] = useState(0); + + // clone the config object to prevent direct mutation + const [localConfig, setLocalConfig] = useState( + JSON.parse(JSON.stringify(config)) + ); + + const resetConfig = () => { + if (window.confirm('Are you sure to reset all settings?')) { + setLocalConfig(CONFIG_DEFAULT); + } + }; + + const handleSave = () => { + // copy the local config to prevent direct mutation + const newConfig: typeof CONFIG_DEFAULT = JSON.parse( + JSON.stringify(localConfig) + ); + // validate the config + for (const key in newConfig) { + const value = newConfig[key as SettKey]; + const mustBeBoolean = isBoolean(CONFIG_DEFAULT[key as SettKey]); + const mustBeString = isString(CONFIG_DEFAULT[key as SettKey]); + const mustBeNumeric = isNumeric(CONFIG_DEFAULT[key as SettKey]); + if (mustBeString) { + if (!isString(value)) { + alert(`Value for ${key} must be string`); + return; + } + } else if (mustBeNumeric) { + const trimedValue = value.toString().trim(); + const numVal = Number(trimedValue); + if (isNaN(numVal) || !isNumeric(numVal) || trimedValue.length === 0) { + alert(`Value for ${key} must be numeric`); + return; + } + // force conversion to number + // @ts-expect-error this is safe + newConfig[key] = numVal; + } else if (mustBeBoolean) { + if (!isBoolean(value)) { + alert(`Value for ${key} must be boolean`); + return; + } + } else { + console.error(`Unknown default type for key ${key}`); + } + } + if (isDev) console.log('Saving config', newConfig); + saveConfig(newConfig); + onClose(); + }; + + const onChange = (key: SettKey) => (value: string | boolean) => { + // note: we do not perform validation here, because we may get incomplete value as user is still typing it + setLocalConfig({ ...localConfig, [key]: value }); + }; + + return ( + +
+

Settings

+
+ {/* Left panel, showing sections - Desktop version */} +
+ {SETTING_SECTIONS.map((section, idx) => ( +
setSectionIdx(idx)} + dir="auto" + > + {section.title} +
+ ))} +
+ + {/* Left panel, showing sections - Mobile version */} +
+
+ + {SETTING_SECTIONS[sectionIdx].title} + +
    + {SETTING_SECTIONS.map((section, idx) => ( +
    setSectionIdx(idx)} + dir="auto" + > + {section.title} +
    + ))} +
+
+
+ + {/* Right panel, showing setting fields */} +
+ {SETTING_SECTIONS[sectionIdx].fields.map((field, idx) => { + const key = `${sectionIdx}-${idx}`; + if (field.type === SettingInputType.SHORT_INPUT) { + return ( + + ); + } else if (field.type === SettingInputType.LONG_INPUT) { + return ( + + ); + } else if (field.type === SettingInputType.CHECKBOX) { + return ( + + ); + } else if (field.type === SettingInputType.CUSTOM) { + return ( +
+ {typeof field.component === 'string' + ? field.component + : field.component({ + value: localConfig[field.key], + onChange: onChange(field.key), + })} +
+ ); + } + })} + +

+ Settings are saved in browser's localStorage +

+
+
+ +
+ + + +
+
+ + ); +} + +function SettingsModalLongInput({ + configKey, + value, + onChange, + label, +}: { + configKey: SettKey; + value: string; + onChange: (value: string) => void; + label?: string; +}) { + return ( +