diff --git a/.github/workflows/build-portable-release-cuda.yml b/.github/workflows/build-portable-release-cuda.yml index fb9e61b0..571cbac0 100644 --- a/.github/workflows/build-portable-release-cuda.yml +++ b/.github/workflows/build-portable-release-cuda.yml @@ -102,6 +102,8 @@ jobs: shell: bash run: | rm -rf .git cmd* update_wizard* Colab-TextGen-GPU.ipynb docker + allowed=("character_bias" "gallery" "openai" "sd_api_pictures") + find extensions/ -mindepth 1 -maxdepth 1 -type d | grep -v -E "$(printf '%s|' "${allowed[@]}" | sed 's/|$//')" | xargs rm -rf # Define common variables CUDA_VERSION="${{ matrix.cuda }}" diff --git a/.github/workflows/build-portable-release-vulkan.yml b/.github/workflows/build-portable-release-vulkan.yml index 8de29791..4e88d4d9 100644 --- a/.github/workflows/build-portable-release-vulkan.yml +++ b/.github/workflows/build-portable-release-vulkan.yml @@ -101,6 +101,8 @@ jobs: shell: bash run: | rm -rf .git cmd* update_wizard* Colab-TextGen-GPU.ipynb docker + allowed=("character_bias" "gallery" "openai" "sd_api_pictures") + find extensions/ -mindepth 1 -maxdepth 1 -type d | grep -v -E "$(printf '%s|' "${allowed[@]}" | sed 's/|$//')" | xargs rm -rf # Define common variables AVX_SUPPORT="${{ matrix.avx }}" diff --git a/.github/workflows/build-portable-release.yml b/.github/workflows/build-portable-release.yml index bdf96cec..6910ce2c 100644 --- a/.github/workflows/build-portable-release.yml +++ b/.github/workflows/build-portable-release.yml @@ -101,6 +101,8 @@ jobs: shell: bash run: | rm -rf .git cmd* update_wizard* Colab-TextGen-GPU.ipynb docker + allowed=("character_bias" "gallery" "openai" "sd_api_pictures") + find extensions/ -mindepth 1 -maxdepth 1 -type d | grep -v -E "$(printf '%s|' "${allowed[@]}" | sed 's/|$//')" | xargs rm -rf # Define common variables AVX_SUPPORT="${{ matrix.avx }}" diff --git a/README.md b/README.md index 4b541b9e..0833f9b0 100644 --- a/README.md +++ b/README.md @@ -22,7 +22,7 @@ Its goal is to become the [AUTOMATIC1111/stable-diffusion-webui](https://github. - Free-form text generation in the Default/Notebook tabs without being limited to chat turns. You can send formatted conversations from the Chat tab to these. - Multiple sampling parameters and generation options for sophisticated text generation control. - Switch between different models easily in the UI without restarting, with fine control over settings. -- OpenAI-compatible API with Chat and Completions endpoints – see [examples](https://github.com/oobabooga/text-generation-webui/wiki/12-%E2%80%90-OpenAI-API#examples). +- OpenAI-compatible API with Chat and Completions endpoints, including tool-calling support – see [examples](https://github.com/oobabooga/text-generation-webui/wiki/12-%E2%80%90-OpenAI-API#examples). - 100% offline and private, with zero telemetry, external resources, or remote update requests. - Extension support, with numerous built-in and user-contributed extensions available. See the [wiki](https://github.com/oobabooga/text-generation-webui/wiki/07-%E2%80%90-Extensions) and [extensions directory](https://github.com/oobabooga/text-generation-webui-extensions) for details. @@ -44,7 +44,7 @@ Download from: https://github.com/oobabooga/text-generation-webui/releases To restart the web UI later, just run the same `start_` script. If you need to reinstall, delete the `installer_files` folder created during setup and run the script again. -You can use command-line flags, like `./start_linux.sh --help`, or add them to `user_data/CMD_FLAGS.txt` (such as `--api` to enable API use). To update the project, run `update_wizard_linux.sh`, `update_wizard_windows.bat`, `update_wizard_macos.sh`, or `update_wizard_wsl.bat`. +You can use command-line flags, like `./start_linux.sh --help`, or add them to `user_data/CMD_FLAGS.txt` (such as `--api` to enable API use). To update the project, run `update_wizard_linux.sh`, `update_wizard_windows.bat`, or `update_wizard_macos.sh`.
@@ -55,12 +55,12 @@ Setup details and information about installing manually The script uses Miniconda to set up a Conda environment in the `installer_files` folder. -If you ever need to install something manually in the `installer_files` environment, you can launch an interactive shell using the cmd script: `cmd_linux.sh`, `cmd_windows.bat`, `cmd_macos.sh`, or `cmd_wsl.bat`. +If you ever need to install something manually in the `installer_files` environment, you can launch an interactive shell using the cmd script: `cmd_linux.sh`, `cmd_windows.bat`, or `cmd_macos.sh`. * There is no need to run any of those scripts (`start_`, `update_wizard_`, or `cmd_`) as admin/root. * To install the requirements for extensions, you can use the `extensions_reqs` script for your OS. At the end, this script will install the main requirements for the project to make sure that they take precedence in case of version conflicts. * For additional instructions about AMD and WSL setup, consult [the documentation](https://github.com/oobabooga/text-generation-webui/wiki). -* For automated installation, you can use the `GPU_CHOICE`, `USE_CUDA118`, `LAUNCH_AFTER_INSTALL`, and `INSTALL_EXTENSIONS` environment variables. For instance: `GPU_CHOICE=A USE_CUDA118=FALSE LAUNCH_AFTER_INSTALL=FALSE INSTALL_EXTENSIONS=TRUE ./start_linux.sh`. +* For automated installation, you can use the `GPU_CHOICE`, `LAUNCH_AFTER_INSTALL`, and `INSTALL_EXTENSIONS` environment variables. For instance: `GPU_CHOICE=A LAUNCH_AFTER_INSTALL=FALSE INSTALL_EXTENSIONS=TRUE ./start_linux.sh`. ### Manual installation using Conda @@ -90,7 +90,7 @@ conda activate textgen |--------|---------|---------| | Linux/WSL | NVIDIA | `pip3 install torch==2.6.0 torchvision==0.21.0 torchaudio==2.6.0 --index-url https://download.pytorch.org/whl/cu124` | | Linux/WSL | CPU only | `pip3 install torch==2.6.0 torchvision==0.21.0 torchaudio==2.6.0 --index-url https://download.pytorch.org/whl/cpu` | -| Linux | AMD | `pip3 install torch==2.6.0 torchvision==0.21.0 torchaudio==2.6.0 --index-url https://download.pytorch.org/whl/rocm6.1` | +| Linux | AMD | `pip3 install torch==2.6.0 torchvision==0.21.0 torchaudio==2.6.0 --index-url https://download.pytorch.org/whl/rocm6.2.4` | | MacOS + MPS | Any | `pip3 install torch==2.6.0 torchvision==0.21.0 torchaudio==2.6.0` | | Windows | NVIDIA | `pip3 install torch==2.6.0 torchvision==0.21.0 torchaudio==2.6.0 --index-url https://download.pytorch.org/whl/cu124` | | Windows | CPU only | `pip3 install torch==2.6.0 torchvision==0.21.0 torchaudio==2.6.0` | diff --git a/css/chat_style-Dark.css b/css/chat_style-Dark.css index 368a2a16..1ad46bc0 100644 --- a/css/chat_style-Dark.css +++ b/css/chat_style-Dark.css @@ -1,7 +1,9 @@ .message { display: grid; + align-items: start; grid-template-columns: 60px minmax(0, 1fr); - padding-bottom: 28px; + padding-bottom: 14px; + padding-top: 14px; font-size: 18px; font-family: Roboto, Arial, sans-serif; /* Modern font */ line-height: 1.5; @@ -102,6 +104,7 @@ @media screen and (width <= 688px) { .message { display: grid; + align-items: start; grid-template-columns: 60px minmax(0, 1fr); padding-bottom: 25px; font-size: 15px; diff --git a/css/chat_style-TheEncrypted777.css b/css/chat_style-TheEncrypted777.css index 6404f41d..9e1230b7 100644 --- a/css/chat_style-TheEncrypted777.css +++ b/css/chat_style-TheEncrypted777.css @@ -2,8 +2,10 @@ .message { display: grid; + align-items: start; grid-template-columns: 60px minmax(0, 1fr); - padding-bottom: 28px; + padding-bottom: 14px; + padding-top: 14px; font-size: 18px; font-family: 'Noto Sans', Arial, sans-serif; line-height: 1.428571429; @@ -100,6 +102,7 @@ @media screen and (width <= 688px) { .message { display: grid; + align-items: start; grid-template-columns: 60px minmax(0, 1fr); padding-bottom: 25px; font-size: 15px; diff --git a/css/chat_style-cai-chat-square.css b/css/chat_style-cai-chat-square.css index 854fff60..015f6927 100644 --- a/css/chat_style-cai-chat-square.css +++ b/css/chat_style-cai-chat-square.css @@ -16,6 +16,7 @@ } .message { - padding-bottom: 2em; + padding-bottom: 1em; + padding-top: 1em; grid-template-columns: 70px minmax(0, 1fr); } diff --git a/css/chat_style-cai-chat.css b/css/chat_style-cai-chat.css index 93276bd3..0e91101f 100644 --- a/css/chat_style-cai-chat.css +++ b/css/chat_style-cai-chat.css @@ -1,7 +1,9 @@ .message { display: grid; + align-items: start; grid-template-columns: 60px minmax(0, 1fr); - padding-bottom: 2em; + padding-bottom: 1em; + padding-top: 1em; font-size: 15px; font-family: 'Noto Sans', Helvetica, Arial, sans-serif; line-height: 22.5px !important; diff --git a/css/chat_style-messenger.css b/css/chat_style-messenger.css index f0fd1578..6518d6ca 100644 --- a/css/chat_style-messenger.css +++ b/css/chat_style-messenger.css @@ -1,5 +1,6 @@ .message { - padding-bottom: 25px; + padding-bottom: 12.5px; + padding-top: 12.5px; font-size: 15px; font-family: 'Noto Sans', Helvetica, Arial, sans-serif; line-height: 1.428571429; diff --git a/css/chat_style-wpp.css b/css/chat_style-wpp.css index 30ca61f3..1442dd0a 100644 --- a/css/chat_style-wpp.css +++ b/css/chat_style-wpp.css @@ -1,5 +1,6 @@ .message { - padding-bottom: 25px; + padding-bottom: 12.5px; + padding-top: 12.5px; font-size: 15px; font-family: 'Noto Sans', Helvetica, Arial, sans-serif; line-height: 1.428571429; diff --git a/css/html_instruct_style.css b/css/html_instruct_style.css index 4613b380..6ad250aa 100644 --- a/css/html_instruct_style.css +++ b/css/html_instruct_style.css @@ -8,10 +8,6 @@ padding-top: 0 !important; } -.chat > .messages > :last-child { - margin-bottom: 1.7rem !important; -} - .chat .message-body p, .chat .message-body li { font-size: 1rem !important; line-height: 28px !important; @@ -46,7 +42,7 @@ } .chat .user-message { - background: #f5f5f5; + background: #f3f4f6; padding: 1.5rem 1rem; padding-bottom: 2rem; border-radius: 0; @@ -61,16 +57,16 @@ } .dark .chat .user-message { - background: transparent; + background: var(--light-gray); } .dark .chat .assistant-message { - background: var(--light-gray); + background: transparent; } .chat .user-message .text, .chat .assistant-message .text { - max-width: 645px; + max-width: 700px; margin-left: auto; margin-right: auto; } diff --git a/css/main.css b/css/main.css index d6e5ac83..0902b184 100644 --- a/css/main.css +++ b/css/main.css @@ -2,7 +2,7 @@ --darker-gray: #202123; --dark-gray: #343541; --light-gray: #444654; - --light-theme-gray: #f5f5f5; + --light-theme-gray: #f9fbff; --border-color-dark: #525252; --header-width: 112px; --selected-item-color-dark: #32333e; @@ -389,7 +389,7 @@ div.svelte-362y77>*, div.svelte-362y77>.form>* { .chat { margin-left: auto; margin-right: auto; - min-height: var(--chat-height); + flex: 1; overflow-y: auto; display: flex; flex-direction: column; @@ -401,10 +401,9 @@ div.svelte-362y77>*, div.svelte-362y77>.form>* { } .chat-parent { - height: calc(100dvh - 98px - var(--input-delta)); + flex: 1; overflow: auto !important; border-radius: 0 !important; - margin-bottom: var(--input-delta) !important; } .chat-parent .prose { @@ -421,13 +420,13 @@ div.svelte-362y77>*, div.svelte-362y77>.form>* { } .chat-parent.bigchat { - height: calc(100dvh - 98px - var(--input-delta)) !important; - margin-bottom: var(--input-delta) !important; + flex: 1; } .chat > .messages { display: flex; flex-direction: column; + min-height: calc(100vh - 102px); } .chat > .messages > :first-child { @@ -546,7 +545,7 @@ div.svelte-362y77>*, div.svelte-362y77>.form>* { border-radius: 5px; font-size: 82%; padding: 1px 3px; - background: white !important; + background: #f3f4f6 !important; color: #1f2328; } @@ -560,18 +559,17 @@ div.svelte-362y77>*, div.svelte-362y77>.form>* { padding: 15px; } -.message-body :not(pre) > code::before { - content: "`"; -} - -.message-body :not(pre) > code::after { - content: "`"; -} - .message-body :not(pre) > code { white-space: normal !important; font-weight: bold; - font-family: unset; + font-size: 0.95em; + font-family: Menlo,"Roboto Mono","Courier New",Courier,monospace,Inter,sans-serif; + padding: .15rem .3rem; + background-color: #ececec; +} + +.dark .message-body :not(pre) > code { + background-color: rgb(255 255 255 / 10%); } #chat-input { @@ -582,7 +580,10 @@ div.svelte-362y77>*, div.svelte-362y77>.form>* { } #chat-input textarea { + background: #f3f4f6; padding: 0.65rem 2.5rem; + border: 0; + box-shadow: 0; } #chat-input textarea::placeholder { @@ -603,8 +604,6 @@ div.svelte-362y77>*, div.svelte-362y77>.form>* { } .chat-input-positioned { - position: absolute; - bottom: 0; max-width: 54rem; left: 50%; transform: translateX(-50%); @@ -744,7 +743,7 @@ div.svelte-362y77>*, div.svelte-362y77>.form>* { .hover-menu button { width: 100%; - background: transparent !important; + background: white !important; border-radius: 0 !important; justify-content: space-between; margin: 0 !important; @@ -760,7 +759,11 @@ div.svelte-362y77>*, div.svelte-362y77>.form>* { } .hover-menu button:hover { - background: var(--button-secondary-background-fill-hover) !important; + background: #dbeafe !important; +} + +.dark .hover-menu button:hover { + background: var(--selected-item-color-dark) !important; } .transparent-substring { @@ -789,6 +792,8 @@ div.svelte-362y77>*, div.svelte-362y77>.form>* { } #chat-input-container { + display: flex; + flex-direction: column; min-width: 0 !important; } @@ -798,9 +803,8 @@ div.svelte-362y77>*, div.svelte-362y77>.form>* { } #chat-input-row { - padding-bottom: 1.5em; - padding-left: 1rem; - padding-right: 1rem; + padding: 1rem; + padding-top: 0; } #chat-input-row.bigchat { @@ -808,22 +812,17 @@ div.svelte-362y77>*, div.svelte-362y77>.form>* { } #chat-col { - padding-bottom: 100px; + height: 100dvh; + display: flex; + flex-direction: column; + padding-bottom: 0; + gap: 0; } @media screen and (width <= 924px) { #chat-col { - padding-bottom: 100px; margin-top: 32px; - position: relative; /* Ensure positioning for the pseudo-element */ - } - - .chat-parent { - height: calc(100dvh - 98px - var(--input-delta) - 32px); - } - - .chat-parent.bigchat { - height: calc(100dvh - 98px - var(--input-delta) - 32px) !important; + height: calc(100dvh - 32px); } } @@ -985,6 +984,11 @@ div.svelte-362y77>*, div.svelte-362y77>.form>* { cursor: pointer; } +#past-chats .selected, +#past-chats label:hover { + background-color: #dbeafe !important; +} + #past-chats-buttons, #delete-chat-row, #rename-row { @@ -993,7 +997,6 @@ div.svelte-362y77>*, div.svelte-362y77>.form>* { gap: 9px; } - #past-chats-row, #chat-controls { width: 260px; @@ -1111,12 +1114,9 @@ div.svelte-362y77>*, div.svelte-362y77>.form>* { color: #9ca3af; } -.dark .hover-menu { - background-color: var(--darker-gray); -} - .dark .hover-menu button { border-color: var(--border-color-primary); + background-color: var(--darker-gray) !important; } .dark #chat-controls, @@ -1125,8 +1125,8 @@ div.svelte-362y77>*, div.svelte-362y77>.form>* { border: 0 !important; } -.dark #past-chats .selected, -.dark #past-chats label:hover { +.dark gradio-app .gradio-container.gradio-container-4-37-2 .contain #past-chats .selected, +.dark gradio-app .gradio-container.gradio-container-4-37-2 .contain #past-chats label:hover { background-color: var(--selected-item-color-dark) !important; } @@ -1163,7 +1163,7 @@ div.svelte-362y77>*, div.svelte-362y77>.form>* { } .header_bar button.selected { - background: #E0E0E0; + background: #dbeafe; } #chat-controls, @@ -1382,3 +1382,19 @@ div.svelte-362y77>*, div.svelte-362y77>.form>* { 50% { opacity: 1; } 100% { opacity: 0.6; } } + +strong { + font-weight: bold; +} + +.min.svelte-1ybaih5 { + min-height: 0; +} + +#vram-info .value { + color: #008d00; +} + +.dark #vram-info .value { + color: #07ff07; +} diff --git a/docker/amd/docker-compose.yml b/docker/amd/docker-compose.yml index 4709ae94..8866e9ed 100644 --- a/docker/amd/docker-compose.yml +++ b/docker/amd/docker-compose.yml @@ -22,7 +22,7 @@ services: TORCH_CUDA_ARCH_LIST: ${TORCH_CUDA_ARCH_LIST:-7.5} BUILD_EXTENSIONS: ${BUILD_EXTENSIONS:-} APP_GID: ${APP_GID:-6972} - APP_UID: ${APP_UID-6972} + APP_UID: ${APP_UID:-6972} env_file: .env user: "${APP_RUNTIME_UID:-6972}:${APP_RUNTIME_GID:-6972}" ports: diff --git a/docker/cpu/docker-compose.yml b/docker/cpu/docker-compose.yml index c9d415ae..9aba314a 100644 --- a/docker/cpu/docker-compose.yml +++ b/docker/cpu/docker-compose.yml @@ -22,7 +22,7 @@ services: TORCH_CUDA_ARCH_LIST: ${TORCH_CUDA_ARCH_LIST:-7.5} BUILD_EXTENSIONS: ${BUILD_EXTENSIONS:-} APP_GID: ${APP_GID:-6972} - APP_UID: ${APP_UID-6972} + APP_UID: ${APP_UID:-6972} env_file: .env user: "${APP_RUNTIME_UID:-6972}:${APP_RUNTIME_GID:-6972}" ports: diff --git a/docker/intel/docker-compose.yml b/docker/intel/docker-compose.yml index 31e9dde0..78e06698 100644 --- a/docker/intel/docker-compose.yml +++ b/docker/intel/docker-compose.yml @@ -22,7 +22,7 @@ services: TORCH_CUDA_ARCH_LIST: ${TORCH_CUDA_ARCH_LIST:-7.5} BUILD_EXTENSIONS: ${BUILD_EXTENSIONS:-} APP_GID: ${APP_GID:-6972} - APP_UID: ${APP_UID-6972} + APP_UID: ${APP_UID:-6972} env_file: .env user: "${APP_RUNTIME_UID:-6972}:${APP_RUNTIME_GID:-6972}" ports: diff --git a/docker/nvidia/Dockerfile b/docker/nvidia/Dockerfile index 900a4329..82594a26 100644 --- a/docker/nvidia/Dockerfile +++ b/docker/nvidia/Dockerfile @@ -14,7 +14,7 @@ WORKDIR /home/app/ RUN git clone https://github.com/oobabooga/text-generation-webui.git WORKDIR /home/app/text-generation-webui RUN GPU_CHOICE=A LAUNCH_AFTER_INSTALL=FALSE INSTALL_EXTENSIONS=TRUE ./start_linux.sh --verbose -COPY CMD_FLAGS.txt /home/app/text-generation-webui/ +COPY /user_data/CMD_FLAGS.txt /home/app/text-generation-webui/user_data EXPOSE ${CONTAINER_PORT:-7860} ${CONTAINER_API_PORT:-5000} ${CONTAINER_API_STREAM_PORT:-5005} WORKDIR /home/app/text-generation-webui # set umask to ensure group read / write at runtime diff --git a/docker/nvidia/docker-compose.yml b/docker/nvidia/docker-compose.yml index 835dd838..23d5cacc 100644 --- a/docker/nvidia/docker-compose.yml +++ b/docker/nvidia/docker-compose.yml @@ -22,7 +22,7 @@ services: TORCH_CUDA_ARCH_LIST: ${TORCH_CUDA_ARCH_LIST:-7.5} BUILD_EXTENSIONS: ${BUILD_EXTENSIONS:-} APP_GID: ${APP_GID:-6972} - APP_UID: ${APP_UID-6972} + APP_UID: ${APP_UID:-6972} env_file: .env user: "${APP_RUNTIME_UID:-6972}:${APP_RUNTIME_GID:-6972}" ports: @@ -31,17 +31,7 @@ services: stdin_open: true tty: true volumes: - - ./cache:/home/app/text-generation-webui/cache - - ./characters:/home/app/text-generation-webui/characters - - ./extensions:/home/app/text-generation-webui/extensions - - ./loras:/home/app/text-generation-webui/loras - - ./logs:/home/app/text-generation-webui/logs - - ./models:/home/app/text-generation-webui/models - - ./presets:/home/app/text-generation-webui/presets - - ./prompts:/home/app/text-generation-webui/prompts - - ./softprompts:/home/app/text-generation-webui/softprompts - - ./training:/home/app/text-generation-webui/training - - ./cloudflared:/etc/cloudflared + - ./user_data:/home/app/text-generation-webui/user_data deploy: resources: reservations: diff --git a/docs/12 - OpenAI API.md b/docs/12 - OpenAI API.md index 364c6b09..db9befed 100644 --- a/docs/12 - OpenAI API.md +++ b/docs/12 - OpenAI API.md @@ -257,6 +257,85 @@ headers = { in any of the examples above. +#### Tool/Function Calling Example + +You need to use a model with tools support. The prompt will be automatically formatted using the model's Jinja2 template. + +Request: + +``` +curl http://127.0.0.1:5000/v1/chat/completions \ + -H "Content-Type: application/json" \ + -d '{ + "messages": [ + { + "role": "system", + "content": "You are a helpful assistant." + }, + { + "role": "user", + "content": "What time is it currently in New York City?" + } + ], + "tools": [ + { + "type": "function", + "function": { + "name": "get_current_time", + "description": "Get current time in a specific timezones", + "parameters": { + "type": "object", + "required": ["timezone"], + "properties": { + "timezone": { + "type": "string", + "description": "IANA timezone name (e.g., America/New_York, Europe/London). Use Europe/Berlin as local timezone if no timezone provided by the user." + } + } + } + } + } + ] + }' +``` + +Sample response: + +``` +{ + "id": "chatcmpl-1746532051477984256", + "object": "chat.completion", + "created": 1746532051, + "model": "qwen2.5-coder-14b-instruct-q4_k_m.gguf", + "choices": [ + { + "index": 0, + "finish_reason": "tool_calls", + "message": { + "role": "assistant", + "content": "```xml\n\n{\n \"name\": \"get_current_time\",\n \"arguments\": {\n \"timezone\": \"America/New_York\"\n }\n}\n\n```" + }, + "tool_calls": [ + { + "type": "function", + "function": { + "name": "get_current_time", + "arguments": "{\"timezone\": \"America/New_York\"}" + }, + "id": "call_52ij07mh", + "index": "0" + } + ] + } + ], + "usage": { + "prompt_tokens": 224, + "completion_tokens": 38, + "total_tokens": 262 + } +} +``` + ### Environment variables The following environment variables can be used (they take precedence over everything else): diff --git a/extensions/openai/completions.py b/extensions/openai/completions.py index 75e2cc11..5181b18b 100644 --- a/extensions/openai/completions.py +++ b/extensions/openai/completions.py @@ -1,16 +1,14 @@ -import base64 import copy -import re +import json import time from collections import deque -from io import BytesIO -import requests import tiktoken -from PIL import Image +from pydantic import ValidationError from extensions.openai.errors import InvalidRequestError -from extensions.openai.utils import debug_msg +from extensions.openai.typing import ToolDefinition +from extensions.openai.utils import debug_msg, getToolCallId, parseToolCall from modules import shared from modules.chat import ( generate_chat_prompt, @@ -96,72 +94,32 @@ def convert_history(history): user_input_last = True system_message = "" - # Multimodal: convert OpenAI format to multimodal extension format - if any('content' in entry and isinstance(entry['content'], list) for entry in history): - new_history = [] - for entry in history: - if isinstance(entry['content'], list): - for item in entry['content']: - if not isinstance(item, dict): - continue - - image_url = None - content = None - if item['type'] == 'image_url' and isinstance(item['image_url'], dict): - image_url = item['image_url']['url'] - elif item['type'] == 'text' and isinstance(item['text'], str): - content = item['text'] - if image_url: - new_history.append({"image_url": image_url, "role": "user"}) - if content: - new_history.append({"content": content, "role": "user"}) - else: - new_history.append(entry) - - history = new_history - for entry in history: - if "image_url" in entry: - image_url = entry['image_url'] - if "base64" in image_url: - image_url = re.sub('^data:image/.+;base64,', '', image_url) - img = Image.open(BytesIO(base64.b64decode(image_url))) - else: - try: - my_res = requests.get(image_url) - img = Image.open(BytesIO(my_res.content)) - except Exception: - raise 'Image cannot be loaded from the URL!' - - buffered = BytesIO() - if img.mode in ("RGBA", "P"): - img = img.convert("RGB") - - img.save(buffered, format="JPEG") - img_str = base64.b64encode(buffered.getvalue()).decode('utf-8') - content = f'' - else: - content = entry["content"] - + content = entry["content"] role = entry["role"] if role == "user": user_input = content user_input_last = True if current_message: - chat_dialogue.append([current_message, '']) + chat_dialogue.append([current_message, '', '']) current_message = "" current_message = content elif role == "assistant": + if "tool_calls" in entry and isinstance(entry["tool_calls"], list) and len(entry["tool_calls"]) > 0 and content.strip() == "": + continue # skip tool calls current_reply = content user_input_last = False if current_message: - chat_dialogue.append([current_message, current_reply]) + chat_dialogue.append([current_message, current_reply, '']) current_message = "" current_reply = "" else: - chat_dialogue.append(['', current_reply]) + chat_dialogue.append(['', current_reply, '']) + elif role == "tool": + user_input_last = False + chat_dialogue.append(['', '', content]) elif role == "system": system_message += f"\n{content}" if system_message else content @@ -181,6 +139,10 @@ def chat_completions_common(body: dict, is_legacy: bool = False, stream=False, p if 'messages' not in body: raise InvalidRequestError(message="messages is required", param='messages') + tools = None + if 'tools' in body and body['tools'] is not None and isinstance(body['tools'], list) and len(body['tools']) > 0: + tools = validateTools(body['tools']) # raises InvalidRequestError if validation fails + messages = body['messages'] for m in messages: if 'role' not in m: @@ -238,6 +200,7 @@ def chat_completions_common(body: dict, is_legacy: bool = False, stream=False, p 'custom_system_message': custom_system_message, 'chat_template_str': chat_template_str, 'chat-instruct_command': chat_instruct_command, + 'tools': tools, 'history': history, 'stream': stream }) @@ -250,7 +213,7 @@ def chat_completions_common(body: dict, is_legacy: bool = False, stream=False, p requested_model = generate_params.pop('model') logprob_proc = generate_params.pop('logprob_proc', None) - def chat_streaming_chunk(content): + def chat_streaming_chunk(content, chunk_tool_calls=None): # begin streaming chunk = { "id": cmpl_id, @@ -260,7 +223,7 @@ def chat_completions_common(body: dict, is_legacy: bool = False, stream=False, p resp_list: [{ "index": 0, "finish_reason": None, - "delta": {'role': 'assistant', 'content': content}, + "delta": {'role': 'assistant', 'content': content, 'tool_calls': chunk_tool_calls}, }], } @@ -269,6 +232,7 @@ def chat_completions_common(body: dict, is_legacy: bool = False, stream=False, p chunk[resp_list][0]["logprobs"] = {'top_logprobs': [top_logprobs]} # else: # chunk[resp_list][0]["logprobs"] = None + return chunk # generate reply ####################################### @@ -277,8 +241,6 @@ def chat_completions_common(body: dict, is_legacy: bool = False, stream=False, p yield {'prompt': prompt} return - debug_msg({'prompt': prompt, 'generate_params': generate_params}) - if stream: yield chat_streaming_chunk('') @@ -288,8 +250,23 @@ def chat_completions_common(body: dict, is_legacy: bool = False, stream=False, p answer = '' seen_content = '' + tool_calls = [] + end_last_tool_call = 0 + supported_tools = [x["function"]["name"] for x in tools] if tools is not None else None + for a in generator: answer = a['internal'][-1][1] + + if supported_tools is not None: + tool_call = parseToolCall(answer[end_last_tool_call:], supported_tools) if len(answer) > 0 else [] + if len(tool_call) > 0: + for tc in tool_call: + tc["id"] = getToolCallId() + tc["index"] = str(len(tool_calls)) + tc["function"]["arguments"] = json.dumps(tc["function"]["arguments"]) + tool_calls.append(tc) + end_last_tool_call = len(answer) + if stream: len_seen = len(seen_content) new_content = answer[len_seen:] @@ -297,18 +274,25 @@ def chat_completions_common(body: dict, is_legacy: bool = False, stream=False, p if not new_content or chr(0xfffd) in new_content: # partial unicode character, don't send it yet. continue - seen_content = answer chunk = chat_streaming_chunk(new_content) + + seen_content = answer yield chunk + # stop generation if tool_calls were generated previously + if len(tool_calls) > 0: + break + token_count = len(encode(prompt)[0]) completion_token_count = len(encode(answer)[0]) stop_reason = "stop" + if len(tool_calls) > 0: + stop_reason = "tool_calls" if token_count + completion_token_count >= generate_params['truncation_length'] or completion_token_count >= generate_params['max_new_tokens']: stop_reason = "length" if stream: - chunk = chat_streaming_chunk('') + chunk = chat_streaming_chunk('', tool_calls) chunk[resp_list][0]['finish_reason'] = stop_reason chunk['usage'] = { "prompt_tokens": token_count, @@ -326,7 +310,8 @@ def chat_completions_common(body: dict, is_legacy: bool = False, stream=False, p resp_list: [{ "index": 0, "finish_reason": stop_reason, - "message": {"role": "assistant", "content": answer} + "message": {"role": "assistant", "content": answer}, + "tool_calls": tool_calls }], "usage": { "prompt_tokens": token_count, @@ -515,3 +500,19 @@ def completions(body: dict, is_legacy: bool = False) -> dict: def stream_completions(body: dict, is_legacy: bool = False): for resp in completions_common(body, is_legacy, stream=True): yield resp + + +def validateTools(tools: list[dict]): + # Validate each tool definition in the JSON array + valid_tools = None + for idx in range(len(tools)): + tool = tools[idx] + try: + tool_definition = ToolDefinition(**tool) + if valid_tools is None: + valid_tools = [] + valid_tools.append(tool) + except ValidationError: + raise InvalidRequestError(message=f"Invalid tool specification at index {idx}.", param='tools') + + return valid_tools diff --git a/extensions/openai/script.py b/extensions/openai/script.py index a995da9d..2c98ee78 100644 --- a/extensions/openai/script.py +++ b/extensions/openai/script.py @@ -14,6 +14,7 @@ from fastapi.requests import Request from fastapi.responses import JSONResponse from pydub import AudioSegment from sse_starlette import EventSourceResponse +from starlette.concurrency import iterate_in_threadpool import extensions.openai.completions as OAIcompletions import extensions.openai.images as OAIimages @@ -115,7 +116,7 @@ async def openai_completions(request: Request, request_data: CompletionRequest): async def generator(): async with streaming_semaphore: response = OAIcompletions.stream_completions(to_dict(request_data), is_legacy=is_legacy) - for resp in response: + async for resp in iterate_in_threadpool(response): disconnected = await request.is_disconnected() if disconnected: break @@ -125,7 +126,12 @@ async def openai_completions(request: Request, request_data: CompletionRequest): return EventSourceResponse(generator()) # SSE streaming else: - response = OAIcompletions.completions(to_dict(request_data), is_legacy=is_legacy) + response = await asyncio.to_thread( + OAIcompletions.completions, + to_dict(request_data), + is_legacy=is_legacy + ) + return JSONResponse(response) @@ -138,7 +144,7 @@ async def openai_chat_completions(request: Request, request_data: ChatCompletion async def generator(): async with streaming_semaphore: response = OAIcompletions.stream_chat_completions(to_dict(request_data), is_legacy=is_legacy) - for resp in response: + async for resp in iterate_in_threadpool(response): disconnected = await request.is_disconnected() if disconnected: break @@ -148,7 +154,12 @@ async def openai_chat_completions(request: Request, request_data: ChatCompletion return EventSourceResponse(generator()) # SSE streaming else: - response = OAIcompletions.chat_completions(to_dict(request_data), is_legacy=is_legacy) + response = await asyncio.to_thread( + OAIcompletions.chat_completions, + to_dict(request_data), + is_legacy=is_legacy + ) + return JSONResponse(response) @@ -436,7 +447,7 @@ def run_server(): # Start server logging.getLogger("uvicorn.error").propagate = False - uvicorn.run(app, host=server_addrs, port=port, ssl_certfile=ssl_certfile, ssl_keyfile=ssl_keyfile) + uvicorn.run(app, host=server_addrs, port=port, ssl_certfile=ssl_certfile, ssl_keyfile=ssl_keyfile, access_log=False) def setup(): diff --git a/extensions/openai/typing.py b/extensions/openai/typing.py index b1979cbc..b28ebb4e 100644 --- a/extensions/openai/typing.py +++ b/extensions/openai/typing.py @@ -1,8 +1,8 @@ import json import time -from typing import Dict, List +from typing import Dict, List, Optional -from pydantic import BaseModel, Field +from pydantic import BaseModel, Field, validator class GenerationOptions(BaseModel): @@ -54,6 +54,48 @@ class GenerationOptions(BaseModel): grammar_string: str = "" +class ToolDefinition(BaseModel): + function: 'ToolFunction' + type: str + + +class ToolFunction(BaseModel): + description: str + name: str + parameters: 'ToolParameters' + + +class ToolParameters(BaseModel): + properties: Optional[Dict[str, 'ToolProperty']] = None + required: Optional[list[str]] = None + type: str + description: Optional[str] = None + + +class ToolProperty(BaseModel): + description: Optional[str] = None + type: Optional[str] = None # we are faced with definitions like anyOf, e.g. {'type': 'function', 'function': {'name': 'git_create_branch', 'description': 'Creates a new branch from an optional base branch', 'parameters': {'type': 'object', 'properties': {'repo_path': {'title': 'Repo Path', 'type': 'string'}, 'branch_name': {'title': 'Branch Name', 'type': 'string'}, 'base_branch': {'anyOf': [{'type': 'string'}, {'type': 'null'}], 'default': None, 'title': 'Base Branch'}}, 'required': ['repo_path', 'branch_name'], 'title': 'GitCreateBranch'}}} + + +class FunctionCall(BaseModel): + name: str + arguments: Optional[str] = None + parameters: Optional[str] = None + + @validator('arguments', allow_reuse=True) + def checkPropertyArgsOrParams(cls, v, values, **kwargs): + if not v and not values.get('parameters'): + raise ValueError("At least one of 'arguments' or 'parameters' must be provided as property in FunctionCall type") + return v + + +class ToolCall(BaseModel): + id: str + index: int + type: str + function: FunctionCall + + class CompletionRequestParams(BaseModel): model: str | None = Field(default=None, description="Unused parameter. To change the model, use the /v1/internal/model/load endpoint.") prompt: str | List[str] @@ -92,6 +134,7 @@ class ChatCompletionRequestParams(BaseModel): frequency_penalty: float | None = 0 function_call: str | dict | None = Field(default=None, description="Unused parameter.") functions: List[dict] | None = Field(default=None, description="Unused parameter.") + tools: List[dict] | None = Field(default=None, description="Tools signatures passed via MCP.") logit_bias: dict | None = None max_tokens: int | None = None n: int | None = Field(default=1, description="Unused parameter.") diff --git a/extensions/openai/utils.py b/extensions/openai/utils.py index 2b414769..9a1de2e7 100644 --- a/extensions/openai/utils.py +++ b/extensions/openai/utils.py @@ -1,5 +1,8 @@ import base64 +import json import os +import random +import re import time import traceback from typing import Callable, Optional @@ -52,3 +55,94 @@ def _start_cloudflared(port: int, tunnel_id: str, max_attempts: int = 3, on_star time.sleep(3) raise Exception('Could not start cloudflared.') + + +def getToolCallId() -> str: + letter_bytes = "abcdefghijklmnopqrstuvwxyz0123456789" + b = [random.choice(letter_bytes) for _ in range(8)] + return "call_" + "".join(b).lower() + + +def checkAndSanitizeToolCallCandidate(candidate_dict: dict, tool_names: list[str]): + # check if property 'function' exists and is a dictionary, otherwise adapt dict + if 'function' not in candidate_dict and 'name' in candidate_dict and isinstance(candidate_dict['name'], str): + candidate_dict = {"type": "function", "function": candidate_dict} + if 'function' in candidate_dict and isinstance(candidate_dict['function'], str): + candidate_dict['name'] = candidate_dict['function'] + del candidate_dict['function'] + candidate_dict = {"type": "function", "function": candidate_dict} + if 'function' in candidate_dict and isinstance(candidate_dict['function'], dict): + # check if 'name' exists within 'function' and is part of known tools + if 'name' in candidate_dict['function'] and candidate_dict['function']['name'] in tool_names: + candidate_dict["type"] = "function" # ensure required property 'type' exists and has the right value + # map property 'parameters' used by some older models to 'arguments' + if "arguments" not in candidate_dict["function"] and "parameters" in candidate_dict["function"]: + candidate_dict["function"]["arguments"] = candidate_dict["function"]["parameters"] + del candidate_dict["function"]["parameters"] + return candidate_dict + return None + + +def parseToolCall(answer: str, tool_names: list[str]): + matches = [] + + # abort on very short answers to save computation cycles + if len(answer) < 10: + return matches + + # Define the regex pattern to find the JSON content wrapped in , , , and other tags observed from various models + patterns = [r"(```[^\n]*)\n(.*?)```", r"<([^>]+)>(.*?)"] + + for pattern in patterns: + for match in re.finditer(pattern, answer, re.DOTALL): + # print(match.group(2)) + if match.group(2) is None: + continue + # remove backtick wraps if present + candidate = re.sub(r"^```(json|xml|python[^\n]*)\n", "", match.group(2).strip()) + candidate = re.sub(r"```$", "", candidate.strip()) + # unwrap inner tags + candidate = re.sub(pattern, r"\2", candidate.strip(), flags=re.DOTALL) + # llm might have generated multiple json objects separated by linebreaks, check for this pattern and try parsing each object individually + if re.search(r"\}\s*\n\s*\{", candidate) is not None: + candidate = re.sub(r"\}\s*\n\s*\{", "},\n{", candidate) + if not candidate.strip().startswith("["): + candidate = "[" + candidate + "]" + + candidates = [] + try: + # parse the candidate JSON into a dictionary + candidates = json.loads(candidate) + if not isinstance(candidates, list): + candidates = [candidates] + except json.JSONDecodeError: + # Ignore invalid JSON silently + continue + + for candidate_dict in candidates: + checked_candidate = checkAndSanitizeToolCallCandidate(candidate_dict, tool_names) + if checked_candidate is not None: + matches.append(checked_candidate) + + # last resort if nothing has been mapped: LLM might have produced plain json tool call without xml-like tags + if len(matches) == 0: + try: + candidate = answer + # llm might have generated multiple json objects separated by linebreaks, check for this pattern and try parsing each object individually + if re.search(r"\}\s*\n\s*\{", candidate) is not None: + candidate = re.sub(r"\}\s*\n\s*\{", "},\n{", candidate) + if not candidate.strip().startswith("["): + candidate = "[" + candidate + "]" + # parse the candidate JSON into a dictionary + candidates = json.loads(candidate) + if not isinstance(candidates, list): + candidates = [candidates] + for candidate_dict in candidates: + checked_candidate = checkAndSanitizeToolCallCandidate(candidate_dict, tool_names) + if checked_candidate is not None: + matches.append(checked_candidate) + except json.JSONDecodeError: + # Ignore invalid JSON silently + pass + + return matches diff --git a/extensions/superboogav2/chromadb.py b/extensions/superboogav2/chromadb.py index 6e93dd92..9344e25c 100644 --- a/extensions/superboogav2/chromadb.py +++ b/extensions/superboogav2/chromadb.py @@ -1,10 +1,11 @@ import math import random import threading -import torch + import chromadb import numpy as np import posthog +import torch from chromadb.config import Settings from chromadb.utils import embedding_functions @@ -292,6 +293,8 @@ class ChromaCollector(): for doc in documents: doc_tokens = encode(doc)[0] + if isinstance(doc_tokens, np.ndarray): + doc_tokens = doc_tokens.tolist() doc_token_count = len(doc_tokens) if current_token_count + doc_token_count > max_token_count: # If adding this document would exceed the max token count, diff --git a/js/main.js b/js/main.js index 33b7d6bd..205cf88e 100644 --- a/js/main.js +++ b/js/main.js @@ -150,6 +150,16 @@ const observer = new MutationObserver(function(mutations) { if (!isScrolled && targetElement.scrollTop !== targetElement.scrollHeight) { targetElement.scrollTop = targetElement.scrollHeight; } + + const chatElement = document.getElementById("chat"); + if (chatElement) { + const messagesContainer = chatElement.querySelector(".messages"); + const lastChild = messagesContainer?.lastElementChild; + const prevSibling = lastChild?.previousElementSibling; + if (lastChild && prevSibling) { + lastChild.style.minHeight = `calc(max(70vh, 100vh - ${prevSibling.offsetHeight}px - 102px))`; + } + } }); // Configure the observer to watch for changes in the subtree and attributes @@ -442,12 +452,6 @@ function updateCssProperties() { // Check if the chat container is visible if (chatContainer.clientHeight > 0) { - const chatContainerParentHeight = chatContainer.parentNode.clientHeight; - const newChatHeight = `${chatContainerParentHeight - chatInputHeight - 80}px`; - - document.documentElement.style.setProperty("--chat-height", newChatHeight); - document.documentElement.style.setProperty("--input-delta", `${chatInputHeight - 40}px`); - // Adjust scrollTop based on input height change if (chatInputHeight !== currentChatInputHeight) { const deltaHeight = chatInputHeight - currentChatInputHeight; @@ -720,7 +724,7 @@ function isMobile() { // Function to initialize sidebars function initializeSidebars() { const isOnMobile = isMobile(); - + if (isOnMobile) { // Mobile state: Hide sidebars and set closed states [pastChatsRow, chatControlsRow, headerBar].forEach(el => { diff --git a/modules/chat.py b/modules/chat.py index 98913d5c..b83c4bfe 100644 --- a/modules/chat.py +++ b/modules/chat.py @@ -5,6 +5,7 @@ import html import json import pprint import re +import time from datetime import datetime from functools import partial from pathlib import Path @@ -145,7 +146,7 @@ def generate_chat_prompt(user_input, state, **kwargs): instruct_renderer = partial( instruction_template.render, builtin_tools=None, - tools=None, + tools=state['tools'] if 'tools' in state else None, tools_in_user_message=False, add_generation_prompt=False ) @@ -171,9 +172,13 @@ def generate_chat_prompt(user_input, state, **kwargs): messages.append({"role": "system", "content": context}) insert_pos = len(messages) - for user_msg, assistant_msg in reversed(history): - user_msg = user_msg.strip() - assistant_msg = assistant_msg.strip() + for entry in reversed(history): + user_msg = entry[0].strip() + assistant_msg = entry[1].strip() + tool_msg = entry[2].strip() if len(entry) > 2 else '' + + if tool_msg: + messages.insert(insert_pos, {"role": "tool", "content": tool_msg}) if assistant_msg: messages.insert(insert_pos, {"role": "assistant", "content": assistant_msg}) @@ -394,16 +399,13 @@ def chatbot_wrapper(text, state, regenerate=False, _continue=False, loading_mess # Extract the reply if state['mode'] in ['chat', 'chat-instruct']: - visible_reply = re.sub("(||{{user}})", state['name1'], reply + '▍') + visible_reply = re.sub("(||{{user}})", state['name1'], reply) else: - visible_reply = reply + '▍' + visible_reply = reply visible_reply = html.escape(visible_reply) if shared.stop_everything: - if output['visible'][-1][1].endswith('▍'): - output['visible'][-1][1] = output['visible'][-1][1][:-1] - output['visible'][-1][1] = apply_extensions('output', output['visible'][-1][1], state, is_chat=True) yield output return @@ -419,9 +421,6 @@ def chatbot_wrapper(text, state, regenerate=False, _continue=False, loading_mess if is_stream: yield output - if output['visible'][-1][1].endswith('▍'): - output['visible'][-1][1] = output['visible'][-1][1][:-1] - output['visible'][-1][1] = apply_extensions('output', output['visible'][-1][1], state, is_chat=True) yield output @@ -481,9 +480,17 @@ def generate_chat_reply_wrapper(text, state, regenerate=False, _continue=False): send_dummy_reply(state['start_with'], state) history = state['history'] + last_save_time = time.monotonic() + save_interval = 8 for i, history in enumerate(generate_chat_reply(text, state, regenerate, _continue, loading_message=True, for_ui=True)): yield chat_html_wrapper(history, state['name1'], state['name2'], state['mode'], state['chat_style'], state['character_menu']), history + current_time = time.monotonic() + # Save on first iteration or if save_interval seconds have passed + if i == 0 or (current_time - last_save_time) >= save_interval: + save_history(history, state['unique_id'], state['character_menu'], state['mode']) + last_save_time = current_time + save_history(history, state['unique_id'], state['character_menu'], state['mode']) diff --git a/modules/exllamav3_hf.py b/modules/exllamav3_hf.py index 12b22f64..417df473 100644 --- a/modules/exllamav3_hf.py +++ b/modules/exllamav3_hf.py @@ -119,7 +119,7 @@ class Exllamav3HF(PreTrainedModel, GenerationMixin): reset = True # Maximum number of tokens to process in a single forward pass - max_chunk_size = 2048 + max_chunk_size = 256 # Make the forward call if labels is None: diff --git a/modules/llama_cpp_server.py b/modules/llama_cpp_server.py index d9187db8..d695c74e 100644 --- a/modules/llama_cpp_server.py +++ b/modules/llama_cpp_server.py @@ -66,7 +66,7 @@ class LlamaServer: "top_k": state["top_k"], "top_p": state["top_p"], "min_p": state["min_p"], - "tfs_z": state["tfs"], + "top_n_sigma": state["top_n_sigma"] if state["top_n_sigma"] > 0 else -1, "typical_p": state["typical_p"], "repeat_penalty": state["repetition_penalty"], "repeat_last_n": state["repetition_penalty_range"], @@ -102,8 +102,10 @@ class LlamaServer: penalty_found = False for s in samplers: - if s.strip() in ["dry", "top_k", "typ_p", "top_p", "min_p", "xtc", "temperature"]: + if s.strip() in ["dry", "top_k", "top_p", "top_n_sigma", "min_p", "temperature", "xtc"]: filtered_samplers.append(s.strip()) + elif s.strip() == "typical_p": + filtered_samplers.append("typ_p") elif not penalty_found and s.strip() == "repetition_penalty": filtered_samplers.append("penalties") penalty_found = True @@ -144,8 +146,9 @@ class LlamaServer: pprint.PrettyPrinter(indent=4, sort_dicts=False).pprint(printable_payload) print() - # Make a direct request with streaming enabled using a context manager - with self.session.post(url, json=payload, stream=True) as response: + # Make the generation request + response = self.session.post(url, json=payload, stream=True) + try: response.raise_for_status() # Raise an exception for HTTP errors full_text = "" @@ -182,6 +185,8 @@ class LlamaServer: print(f"JSON decode error: {e}") print(f"Problematic line: {line}") continue + finally: + response.close() def generate(self, prompt, state): output = "" @@ -210,14 +215,15 @@ class LlamaServer: pprint.PrettyPrinter(indent=4, sort_dicts=False).pprint(printable_payload) print() - response = self.session.post(url, json=payload) - result = response.json() + for retry in range(5): + response = self.session.post(url, json=payload) + result = response.json() - if "completion_probabilities" in result: - if use_samplers: - return result["completion_probabilities"][0]["top_probs"] - else: - return result["completion_probabilities"][0]["top_logprobs"] + if "completion_probabilities" in result: + if use_samplers: + return result["completion_probabilities"][0]["top_probs"] + else: + return result["completion_probabilities"][0]["top_logprobs"] else: raise Exception(f"Unexpected response format: 'completion_probabilities' not found in {result}") @@ -255,9 +261,10 @@ class LlamaServer: self.server_path, "--model", self.model_path, "--ctx-size", str(shared.args.ctx_size), - "--n-gpu-layers", str(shared.args.n_gpu_layers), + "--gpu-layers", str(shared.args.gpu_layers), "--batch-size", str(shared.args.batch_size), "--port", str(self.port), + "--no-webui", ] if shared.args.flash_attn: @@ -278,8 +285,10 @@ class LlamaServer: cmd.append("--no-kv-offload") if shared.args.row_split: cmd += ["--split-mode", "row"] + cache_type = "fp16" if shared.args.cache_type != "fp16" and shared.args.cache_type in llamacpp_valid_cache_types: cmd += ["--cache-type-k", shared.args.cache_type, "--cache-type-v", shared.args.cache_type] + cache_type = shared.args.cache_type if shared.args.compress_pos_emb != 1: cmd += ["--rope-freq-scale", str(1.0 / shared.args.compress_pos_emb)] if shared.args.rope_freq_base > 0: @@ -316,9 +325,15 @@ class LlamaServer: for flag_item in extra_flags.split(','): if '=' in flag_item: flag, value = flag_item.split('=', 1) - cmd += [f"--{flag}", value] + if len(flag) <= 3: + cmd += [f"-{flag}", value] + else: + cmd += [f"--{flag}", value] else: - cmd.append(f"--{flag_item}") + if len(flag_item) <= 3: + cmd.append(f"-{flag_item}") + else: + cmd.append(f"--{flag_item}") env = os.environ.copy() if os.name == 'posix': @@ -333,6 +348,7 @@ class LlamaServer: print(' '.join(str(item) for item in cmd[1:])) print() + logger.info(f"Using gpu_layers={shared.args.gpu_layers} | ctx_size={shared.args.ctx_size} | cache_type={cache_type}") # Start the server with pipes for output self.process = subprocess.Popen( cmd, diff --git a/modules/loaders.py b/modules/loaders.py index 738198b1..79a7a4a3 100644 --- a/modules/loaders.py +++ b/modules/loaders.py @@ -5,7 +5,7 @@ import gradio as gr loaders_and_params = OrderedDict({ 'llama.cpp': [ - 'n_gpu_layers', + 'gpu_layers', 'threads', 'threads_batch', 'batch_size', @@ -28,6 +28,7 @@ loaders_and_params = OrderedDict({ 'device_draft', 'ctx_size_draft', 'speculative_decoding_accordion', + 'vram_info', ], 'Transformers': [ 'gpu_split', @@ -84,7 +85,6 @@ loaders_and_params = OrderedDict({ 'no_flash_attn', 'no_xformers', 'no_sdpa', - 'exllamav2_info', 'model_draft', 'draft_max', 'ctx_size_draft', @@ -299,7 +299,7 @@ loaders_samplers = { 'typical_p', 'xtc_threshold', 'xtc_probability', - 'tfs', + 'top_n_sigma', 'dry_multiplier', 'dry_allowed_length', 'dry_base', diff --git a/modules/logits.py b/modules/logits.py index 32aef7ae..56a20572 100644 --- a/modules/logits.py +++ b/modules/logits.py @@ -7,6 +7,7 @@ from modules import models, shared from modules.logging_colors import logger from modules.models import load_model from modules.text_generation import generate_reply +from modules.utils import check_model_loaded global_scores = None @@ -33,9 +34,9 @@ def get_next_logits(*args, **kwargs): def _get_next_logits(prompt, state, use_samplers, previous, top_logits=25, return_dict=False): - if shared.model is None: - logger.error("No model is loaded! Select one in the Model tab.") - return 'Error: No model is loaded1 Select one in the Model tab.', previous + model_is_loaded, error_message = check_model_loaded() + if not model_is_loaded: + return error_message, previous # llama.cpp case if shared.model.__class__.__name__ == 'LlamaServer': diff --git a/modules/models.py b/modules/models.py index d0b0402a..9ecee803 100644 --- a/modules/models.py +++ b/modules/models.py @@ -71,7 +71,6 @@ def llama_cpp_server_loader(model_name): else: model_file = sorted(Path(f'{shared.args.model_dir}/{model_name}').glob('*.gguf'))[0] - logger.info(f"llama.cpp weights detected: \"{model_file}\"") try: model = LlamaServer(model_file) return model, model diff --git a/modules/models_settings.py b/modules/models_settings.py index ae589bb3..3fdf3c84 100644 --- a/modules/models_settings.py +++ b/modules/models_settings.py @@ -1,7 +1,11 @@ +import functools import json import re +import subprocess +from math import exp from pathlib import Path +import gradio as gr import yaml from modules import chat, loaders, metadata_gguf, shared, ui @@ -54,7 +58,7 @@ def get_model_metadata(model): else: model_file = list(path.glob('*.gguf'))[0] - metadata = metadata_gguf.load_metadata(model_file) + metadata = load_gguf_metadata_with_cache(model_file) for k in metadata: if k.endswith('context_length'): @@ -67,7 +71,7 @@ def get_model_metadata(model): elif k.endswith('rope.scaling.factor'): model_settings['compress_pos_emb'] = metadata[k] elif k.endswith('block_count'): - model_settings['n_gpu_layers'] = metadata[k] + 1 + model_settings['gpu_layers'] = metadata[k] + 1 if 'tokenizer.chat_template' in metadata: template = metadata['tokenizer.chat_template'] @@ -209,15 +213,27 @@ def apply_model_settings_to_state(model, state): model_settings = get_model_metadata(model) if 'loader' in model_settings: loader = model_settings.pop('loader') - - # If the user is using an alternative loader for the same model type, let them keep using it if not (loader == 'ExLlamav2_HF' and state['loader'] in ['ExLlamav2']): state['loader'] = loader for k in model_settings: - if k in state: + if k in state and k != 'gpu_layers': # Skip gpu_layers, handle separately state[k] = model_settings[k] + # Handle GPU layers and VRAM update for llama.cpp + if state['loader'] == 'llama.cpp' and 'gpu_layers' in model_settings: + vram_info, gpu_layers_update = update_gpu_layers_and_vram( + state['loader'], + model, + model_settings['gpu_layers'], + state['ctx_size'], + state['cache_type'], + auto_adjust=True + ) + + state['gpu_layers'] = gpu_layers_update + state['vram_info'] = vram_info + return state @@ -277,3 +293,186 @@ def save_instruction_template(model, template): yield (f"Instruction template for `{model}` unset in `{p}`, as the value for template was `{template}`.") else: yield (f"Instruction template for `{model}` saved to `{p}` as `{template}`.") + + +@functools.lru_cache(maxsize=1) +def load_gguf_metadata_with_cache(model_file): + return metadata_gguf.load_metadata(model_file) + + +def get_model_size_mb(model_file: Path) -> float: + filename = model_file.name + + # Check for multipart pattern + match = re.match(r'(.+)-\d+-of-\d+\.gguf$', filename) + + if match: + # It's a multipart file, find all matching parts + base_pattern = match.group(1) + part_files = sorted(model_file.parent.glob(f'{base_pattern}-*-of-*.gguf')) + total_size = sum(p.stat().st_size for p in part_files) + else: + # Single part + total_size = model_file.stat().st_size + + return total_size / (1024 ** 2) # Return size in MB + + +def estimate_vram(gguf_file, gpu_layers, ctx_size, cache_type): + model_file = Path(f'{shared.args.model_dir}/{gguf_file}') + metadata = load_gguf_metadata_with_cache(model_file) + size_in_mb = get_model_size_mb(model_file) + + # Extract values from metadata + n_layers = None + n_kv_heads = None + embedding_dim = None + context_length = None + feed_forward_dim = None + + for key, value in metadata.items(): + if key.endswith('.block_count'): + n_layers = value + elif key.endswith('.attention.head_count_kv'): + n_kv_heads = value + elif key.endswith('.embedding_length'): + embedding_dim = value + elif key.endswith('.context_length'): + context_length = value + elif key.endswith('.feed_forward_length'): + feed_forward_dim = value + + if gpu_layers > n_layers: + gpu_layers = n_layers + + # Convert cache_type to numeric + if cache_type == 'q4_0': + cache_type = 4 + elif cache_type == 'q8_0': + cache_type = 8 + else: + cache_type = 16 + + # Derived features + size_per_layer = size_in_mb / max(n_layers, 1e-6) + context_per_layer = context_length / max(n_layers, 1e-6) + ffn_per_embedding = feed_forward_dim / max(embedding_dim, 1e-6) + kv_cache_factor = n_kv_heads * cache_type * ctx_size + + # Helper function for smaller + def smaller(x, y): + return 1 if x < y else 0 + + # Calculate VRAM using the model + # Details: https://oobabooga.github.io/blog/posts/gguf-vram-formula/ + vram = ( + (size_per_layer - 21.19195204848197) + * exp(0.0001047328491557063 * size_in_mb * smaller(ffn_per_embedding, 2.671096993407845)) + + 0.0006621544775632052 * context_per_layer + + 3.34664386576376e-05 * kv_cache_factor + ) * (1.363306170123392 + gpu_layers) + 1255.163594536052 + + return vram + + +def get_nvidia_free_vram(): + """ + Calculates the total free VRAM across all NVIDIA GPUs by parsing nvidia-smi output. + + Returns: + int: The total free VRAM in MiB summed across all detected NVIDIA GPUs. + Returns -1 if nvidia-smi command fails (not found, error, etc.). + Returns 0 if nvidia-smi succeeds but no GPU memory info found. + """ + try: + # Execute nvidia-smi command + result = subprocess.run( + ['nvidia-smi'], + capture_output=True, + text=True, + check=False + ) + + # Check if nvidia-smi returned an error + if result.returncode != 0: + return -1 + + # Parse the output for memory usage patterns + output = result.stdout + + # Find memory usage like "XXXXMiB / YYYYMiB" + # Captures used and total memory for each GPU + matches = re.findall(r"(\d+)\s*MiB\s*/\s*(\d+)\s*MiB", output) + + if not matches: + # No GPUs found in expected format + return 0 + + total_free_vram_mib = 0 + for used_mem_str, total_mem_str in matches: + try: + used_mib = int(used_mem_str) + total_mib = int(total_mem_str) + total_free_vram_mib += (total_mib - used_mib) + except ValueError: + # Skip malformed entries + pass + + return total_free_vram_mib + + except FileNotFoundError: + # nvidia-smi not found (likely no NVIDIA drivers installed) + return -1 + except Exception: + # Handle any other unexpected exceptions + return -1 + + +def update_gpu_layers_and_vram(loader, model, gpu_layers, ctx_size, cache_type, auto_adjust=False, for_ui=True): + """ + Unified function to handle GPU layers and VRAM updates. + + Args: + for_ui: If True, returns Gradio updates. If False, returns raw values. + + Returns: + - If for_ui=True: (vram_info_update, gpu_layers_update) or just vram_info_update + - If for_ui=False: (vram_usage, adjusted_layers) or just vram_usage + """ + if loader != 'llama.cpp' or model in ["None", None] or not model.endswith(".gguf"): + vram_info = "
Estimated VRAM to load the model:" + if for_ui: + return (vram_info, gr.update()) if auto_adjust else vram_info + else: + return (0, gpu_layers) if auto_adjust else 0 + + current_layers = gpu_layers + max_layers = gpu_layers + + if auto_adjust: + # Get max layers from model metadata + model_settings = get_model_metadata(model) + max_layers = model_settings.get('gpu_layers', gpu_layers) + + # Auto-adjust based on available VRAM + available_vram = get_nvidia_free_vram() + if available_vram > 0: + tolerance = 906 + current_layers = max_layers + while current_layers > 0 and estimate_vram(model, current_layers, ctx_size, cache_type) > available_vram - tolerance: + current_layers -= 1 + + # Calculate VRAM with current layers + vram_usage = estimate_vram(model, current_layers, ctx_size, cache_type) + + if for_ui: + vram_info = f"
Estimated VRAM to load the model: {vram_usage:.0f} MiB" + if auto_adjust: + return vram_info, gr.update(value=current_layers, maximum=max_layers) + else: + return vram_info + else: + if auto_adjust: + return vram_usage, current_layers + else: + return vram_usage diff --git a/modules/presets.py b/modules/presets.py index a432bf52..cf706605 100644 --- a/modules/presets.py +++ b/modules/presets.py @@ -11,7 +11,7 @@ from modules.logging_colors import logger def default_preset(): - return { + result = { 'temperature': 1, 'dynatemp_low': 1, 'dynatemp_high': 1, @@ -46,10 +46,17 @@ def default_preset(): 'do_sample': True, 'dynamic_temperature': False, 'temperature_last': False, - 'sampler_priority': 'repetition_penalty\npresence_penalty\nfrequency_penalty\ndry\ntemperature\ndynamic_temperature\nquadratic_sampling\ntop_n_sigma\ntop_k\ntop_p\ntypical_p\nepsilon_cutoff\neta_cutoff\ntfs\ntop_a\nmin_p\nmirostat\nxtc\nencoder_repetition_penalty\nno_repeat_ngram', + 'sampler_priority': 'repetition_penalty\npresence_penalty\nfrequency_penalty\ndry\ntop_n_sigma\ntemperature\ndynamic_temperature\nquadratic_sampling\ntop_k\ntop_p\ntypical_p\nepsilon_cutoff\neta_cutoff\ntfs\ntop_a\nmin_p\nmirostat\nxtc\nencoder_repetition_penalty\nno_repeat_ngram', 'dry_sequence_breakers': '"\\n", ":", "\\"", "*"', } + if shared.args.portable: + samplers = result['sampler_priority'].split('\n') + samplers = [sampler for sampler in samplers if sampler in ["dry", "top_k", "top_p", "top_n_sigma", "min_p", "temperature", "xtc", "typical_p", "repetition_penalty"]] + result['sampler_priority'] = '\n'.join(samplers) + + return result + def presets_params(): return [k for k in default_preset()] diff --git a/modules/shared.py b/modules/shared.py index fb10c014..4e0a20db 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -47,7 +47,6 @@ settings = { 'max_new_tokens_max': 4096, 'prompt_lookup_num_tokens': 0, 'max_tokens_second': 0, - 'max_updates_second': 12, 'auto_max_new_tokens': True, 'ban_eos_token': False, 'add_bos_token': True, @@ -60,7 +59,6 @@ settings = { 'custom_stopping_strings': '', 'custom_token_bans': '', 'negative_prompt': '', - 'autoload_model': False, 'dark_theme': True, 'default_extensions': [], 'instruction_template_str': "{%- set ns = namespace(found=false) -%}\n{%- for message in messages -%}\n {%- if message['role'] == 'system' -%}\n {%- set ns.found = true -%}\n {%- endif -%}\n{%- endfor -%}\n{%- if not ns.found -%}\n {{- '' + 'Below is an instruction that describes a task. Write a response that appropriately completes the request.' + '\\n\\n' -}}\n{%- endif %}\n{%- for message in messages %}\n {%- if message['role'] == 'system' -%}\n {{- '' + message['content'] + '\\n\\n' -}}\n {%- else -%}\n {%- if message['role'] == 'user' -%}\n {{-'### Instruction:\\n' + message['content'] + '\\n\\n'-}}\n {%- else -%}\n {{-'### Response:\\n' + message['content'] + '\\n\\n' -}}\n {%- endif -%}\n {%- endif -%}\n{%- endfor -%}\n{%- if add_generation_prompt -%}\n {{-'### Response:\\n'-}}\n{%- endif -%}", @@ -121,7 +119,7 @@ group.add_argument('--threads-batch', type=int, default=0, help='Number of threa group.add_argument('--batch-size', type=int, default=256, help='Maximum number of prompt tokens to batch together when calling llama_eval.') group.add_argument('--no-mmap', action='store_true', help='Prevent mmap from being used.') group.add_argument('--mlock', action='store_true', help='Force the system to keep the model in RAM.') -group.add_argument('--n-gpu-layers', type=int, default=0, help='Number of layers to offload to the GPU.') +group.add_argument('--gpu-layers', '--n-gpu-layers', type=int, default=256, metavar='N', help='Number of layers to offload to the GPU.') group.add_argument('--tensor-split', type=str, default=None, help='Split the model across multiple GPUs. Comma-separated list of proportions. Example: 60,40.') group.add_argument('--numa', action='store_true', help='Activate NUMA task allocation for llama.cpp.') group.add_argument('--no-kv-offload', action='store_true', help='Do not offload the K, Q, V to the GPU. This saves VRAM but reduces the performance.') @@ -130,9 +128,9 @@ group.add_argument('--extra-flags', type=str, default=None, help='Extra flags to group.add_argument('--streaming-llm', action='store_true', help='Activate StreamingLLM to avoid re-evaluating the entire prompt when old messages are removed.') # Cache -group = parser.add_argument_group('Context and cache management') +group = parser.add_argument_group('Context and cache') group.add_argument('--ctx-size', '--n_ctx', '--max_seq_len', type=int, default=8192, metavar='N', help='Context size in tokens.') -group.add_argument('--cache_type', type=str, default='fp16', help='KV cache type; valid options: llama.cpp - fp16, q8_0, q4_0; ExLlamaV2 - fp16, fp8, q8, q6, q4; ExLlamaV3 - fp16, q2 to q8 (can specify k_bits and v_bits separately, e.g. q4_q8).') +group.add_argument('--cache-type', '--cache_type', type=str, default='fp16', metavar='N', help='KV cache type; valid options: llama.cpp - fp16, q8_0, q4_0; ExLlamaV2 - fp16, fp8, q8, q6, q4; ExLlamaV3 - fp16, q2 to q8 (can specify k_bits and v_bits separately, e.g. q4_q8).') # Speculative decoding group = parser.add_argument_group('Speculative decoding') @@ -161,10 +159,6 @@ group.add_argument('--hqq-backend', type=str, default='PYTORCH_COMPILE', help='B group = parser.add_argument_group('TensorRT-LLM') group.add_argument('--cpp-runner', action='store_true', help='Use the ModelRunnerCpp runner, which is faster than the default ModelRunner but doesn\'t support streaming yet.') -# Cache -group = parser.add_argument_group('Cache') -group.add_argument('--cache_type', type=str, default='fp16', help='KV cache type; valid options: llama.cpp - fp16, q8_0, q4_0; ExLlamaV2 - fp16, fp8, q8, q6, q4.') - # DeepSpeed group = parser.add_argument_group('DeepSpeed') group.add_argument('--deepspeed', action='store_true', help='Enable the use of DeepSpeed ZeRO-3 for inference via the Transformers integration.') @@ -190,6 +184,7 @@ group.add_argument('--ssl-keyfile', type=str, help='The path to the SSL certific group.add_argument('--ssl-certfile', type=str, help='The path to the SSL certificate cert file.', default=None) group.add_argument('--subpath', type=str, help='Customize the subpath for gradio, use with reverse proxy') group.add_argument('--old-colors', action='store_true', help='Use the legacy Gradio colors, before the December/2024 update.') +group.add_argument('--portable', action='store_true', help='Hide features not available in portable mode like training.') # API group = parser.add_argument_group('API') @@ -311,11 +306,13 @@ if args.api or args.public_api: add_extension('openai', last=True) # Load model-specific settings -with Path(f'{args.model_dir}/config.yaml') as p: - if p.exists(): - model_config = yaml.safe_load(open(p, 'r').read()) - else: - model_config = {} +p = Path(f'{args.model_dir}/config.yaml') +if p.exists(): + model_config = yaml.safe_load(open(p, 'r').read()) +else: + model_config = {} +del p + # Load custom model-specific settings user_config = load_user_config() diff --git a/modules/tensorrt_llm.py b/modules/tensorrt_llm.py index 73178c39..0527d493 100644 --- a/modules/tensorrt_llm.py +++ b/modules/tensorrt_llm.py @@ -1,15 +1,15 @@ from pathlib import Path -import torch - import tensorrt_llm +import torch +from tensorrt_llm.runtime import ModelRunner, ModelRunnerCpp + from modules import shared from modules.logging_colors import logger from modules.text_generation import ( get_max_prompt_length, get_reply_from_output_ids ) -from tensorrt_llm.runtime import ModelRunner, ModelRunnerCpp class TensorRTLLMModel: diff --git a/modules/text_generation.py b/modules/text_generation.py index 8d091868..00b9275a 100644 --- a/modules/text_generation.py +++ b/modules/text_generation.py @@ -14,6 +14,7 @@ from modules.callbacks import Iteratorize from modules.extensions import apply_extensions from modules.html_generator import generate_basic_html from modules.logging_colors import logger +from modules.utils import check_model_loaded def generate_reply(*args, **kwargs): @@ -34,8 +35,8 @@ def _generate_reply(question, state, stopping_strings=None, is_chat=False, escap # Find the appropriate generation function generate_func = apply_extensions('custom_generate_reply') if generate_func is None: - if shared.model_name == 'None' or shared.model is None: - logger.error("No model is loaded! Select one in the Model tab.") + model_is_loaded, error_message = check_model_loaded() + if not model_is_loaded: yield '' return @@ -64,41 +65,39 @@ def _generate_reply(question, state, stopping_strings=None, is_chat=False, escap all_stop_strings += st shared.stop_everything = False - last_update = -1 reply = '' is_stream = state['stream'] if len(all_stop_strings) > 0 and not state['stream']: state = copy.deepcopy(state) state['stream'] = True - min_update_interval = 0 - if state.get('max_updates_second', 0) > 0: - min_update_interval = 1 / state['max_updates_second'] - # Generate + last_update = -1 + latency_threshold = 1 / 1000 for reply in generate_func(question, original_question, state, stopping_strings, is_chat=is_chat): + cur_time = time.monotonic() reply, stop_found = apply_stopping_strings(reply, all_stop_strings) if escape_html: reply = html.escape(reply) if is_stream: - cur_time = time.time() - # Limit number of tokens/second to make text readable in real time if state['max_tokens_second'] > 0: diff = 1 / state['max_tokens_second'] - (cur_time - last_update) if diff > 0: time.sleep(diff) - last_update = time.time() + last_update = time.monotonic() yield reply # Limit updates to avoid lag in the Gradio UI # API updates are not limited else: - if cur_time - last_update > min_update_interval: - last_update = cur_time + # If 'generate_func' takes less than 0.001 seconds to yield the next token + # (equivalent to more than 1000 tok/s), assume that the UI is lagging behind and skip yielding + if (cur_time - last_update) > latency_threshold: yield reply + last_update = time.monotonic() if stop_found or (state['max_tokens_second'] > 0 and shared.stop_everything): break @@ -471,7 +470,7 @@ def generate_reply_HF(question, original_question, state, stopping_strings=None, t1 = time.time() original_tokens = len(original_input_ids[0]) new_tokens = len(output) - (original_tokens if not shared.is_seq2seq else 0) - print(f'Output generated in {(t1-t0):.2f} seconds ({new_tokens/(t1-t0):.2f} tokens/s, {new_tokens} tokens, context {original_tokens}, seed {seed})') + logger.info(f'Output generated in {(t1-t0):.2f} seconds ({new_tokens/(t1-t0):.2f} tokens/s, {new_tokens} tokens, context {original_tokens}, seed {seed})') return @@ -480,7 +479,7 @@ def generate_reply_custom(question, original_question, state, stopping_strings=N For models that do not use the transformers library for sampling """ - seed = set_manual_seed(state['seed']) + state['seed'] = set_manual_seed(state['seed']) t0 = time.time() reply = '' try: @@ -500,7 +499,7 @@ def generate_reply_custom(question, original_question, state, stopping_strings=N t1 = time.time() original_tokens = len(encode(original_question)[0]) new_tokens = len(encode(original_question + reply)[0]) - original_tokens - print(f'Output generated in {(t1-t0):.2f} seconds ({new_tokens/(t1-t0):.2f} tokens/s, {new_tokens} tokens, context {original_tokens}, seed {seed})') + logger.info(f'Output generated in {(t1-t0):.2f} seconds ({new_tokens/(t1-t0):.2f} tokens/s, {new_tokens} tokens, context {original_tokens}, seed {state["seed"]})') return diff --git a/modules/ui.py b/modules/ui.py index fb016f87..eeb6ce92 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -61,7 +61,7 @@ if not shared.args.old_colors: background_fill_primary_dark='var(--darker-gray)', body_background_fill="white", block_background_fill="transparent", - body_text_color="#333", + body_text_color='rgb(64, 64, 64)', button_secondary_background_fill="#f4f4f4", button_secondary_border_color="var(--border-color-primary)", @@ -105,7 +105,7 @@ def list_model_elements(): 'filter_by_loader', 'loader', 'cpu_memory', - 'n_gpu_layers', + 'gpu_layers', 'threads', 'threads_batch', 'batch_size', @@ -192,7 +192,6 @@ def list_interface_input_elements(): 'max_new_tokens', 'prompt_lookup_num_tokens', 'max_tokens_second', - 'max_updates_second', 'do_sample', 'dynamic_temperature', 'temperature_last', diff --git a/modules/ui_chat.py b/modules/ui_chat.py index 0d588549..0856cfab 100644 --- a/modules/ui_chat.py +++ b/modules/ui_chat.py @@ -46,8 +46,8 @@ def create_ui(): with gr.Row(): with gr.Column(elem_id='chat-col'): - shared.gradio['html_display'] = gr.HTML(value=chat_html_wrapper({'internal': [], 'visible': []}, '', '', 'chat', 'cai-chat', '')['html'], visible=True) shared.gradio['display'] = gr.JSON(value={}, visible=False) # Hidden buffer + shared.gradio['html_display'] = gr.HTML(value=chat_html_wrapper({'internal': [], 'visible': []}, '', '', 'chat', 'cai-chat', '')['html'], visible=True) with gr.Row(elem_id="chat-input-row"): with gr.Column(scale=1, elem_id='gr-hover-container'): gr.HTML(value='
☰
', elem_id='gr-hover') diff --git a/modules/ui_model_menu.py b/modules/ui_model_menu.py index d13bcff7..59bb6759 100644 --- a/modules/ui_model_menu.py +++ b/modules/ui_model_menu.py @@ -14,6 +14,7 @@ from modules.models_settings import ( get_model_metadata, save_instruction_template, save_model_settings, + update_gpu_layers_and_vram, update_model_parameters ) from modules.utils import gradio @@ -26,71 +27,36 @@ def create_ui(): with gr.Row(): with gr.Column(): with gr.Row(): - with gr.Column(): - with gr.Row(): - shared.gradio['model_menu'] = gr.Dropdown(choices=utils.get_available_models(), value=lambda: shared.model_name, label='Model', elem_classes='slim-dropdown', interactive=not mu) - ui.create_refresh_button(shared.gradio['model_menu'], lambda: None, lambda: {'choices': utils.get_available_models()}, 'refresh-button', interactive=not mu) - shared.gradio['load_model'] = gr.Button("Load", visible=not shared.settings['autoload_model'], elem_classes='refresh-button', interactive=not mu) - shared.gradio['unload_model'] = gr.Button("Unload", elem_classes='refresh-button', interactive=not mu) - shared.gradio['save_model_settings'] = gr.Button("Save settings", elem_classes='refresh-button', interactive=not mu) + shared.gradio['model_menu'] = gr.Dropdown(choices=utils.get_available_models(), value=lambda: shared.model_name, label='Model', elem_classes='slim-dropdown', interactive=not mu) + ui.create_refresh_button(shared.gradio['model_menu'], lambda: None, lambda: {'choices': utils.get_available_models()}, 'refresh-button', interactive=not mu) + shared.gradio['load_model'] = gr.Button("Load", elem_classes='refresh-button', interactive=not mu) + shared.gradio['unload_model'] = gr.Button("Unload", elem_classes='refresh-button', interactive=not mu) + shared.gradio['save_model_settings'] = gr.Button("Save settings", elem_classes='refresh-button', interactive=not mu) - with gr.Column(): - with gr.Row(): - shared.gradio['lora_menu'] = gr.Dropdown(multiselect=True, choices=utils.get_available_loras(), value=shared.lora_names, label='LoRA(s)', elem_classes='slim-dropdown', interactive=not mu) - ui.create_refresh_button(shared.gradio['lora_menu'], lambda: None, lambda: {'choices': utils.get_available_loras(), 'value': shared.lora_names}, 'refresh-button', interactive=not mu) - shared.gradio['lora_menu_apply'] = gr.Button(value='Apply LoRAs', elem_classes='refresh-button', interactive=not mu) - - with gr.Row(): - with gr.Column(): - shared.gradio['loader'] = gr.Dropdown(label="Model loader", choices=loaders.loaders_and_params.keys(), value=None) + shared.gradio['loader'] = gr.Dropdown(label="Model loader", choices=loaders.loaders_and_params.keys() if not shared.args.portable else ['llama.cpp'], value=None) with gr.Blocks(): + gr.Markdown("## Main options") with gr.Row(): with gr.Column(): - shared.gradio['n_gpu_layers'] = gr.Slider(label="n-gpu-layers", minimum=0, maximum=256, value=shared.args.n_gpu_layers, info='Must be greater than 0 for the GPU to be used. ⚠️ Lower this value if you can\'t load the model.') - shared.gradio['threads'] = gr.Slider(label="threads", minimum=0, step=1, maximum=256, value=shared.args.threads) - shared.gradio['threads_batch'] = gr.Slider(label="threads_batch", minimum=0, step=1, maximum=256, value=shared.args.threads_batch) - shared.gradio['batch_size'] = gr.Slider(label="batch_size", minimum=1, maximum=4096, step=1, value=shared.args.batch_size) - shared.gradio['hqq_backend'] = gr.Dropdown(label="hqq_backend", choices=["PYTORCH", "PYTORCH_COMPILE", "ATEN"], value=shared.args.hqq_backend) - shared.gradio['ctx_size'] = gr.Number(label='ctx-size', precision=0, step=256, value=shared.args.ctx_size, info='Context length. ⚠️ Lower this value if you can\'t load the model. Common values: 2048, 4096, 8192, 16384, 32768, 65536.') - shared.gradio['cache_type'] = gr.Dropdown(label="cache_type", choices=['fp16', 'q8_0', 'q4_0', 'fp8', 'q8', 'q7', 'q6', 'q5', 'q4', 'q3', 'q2'], value=shared.args.cache_type, allow_custom_value=True, info='Valid options: llama.cpp - fp16, q8_0, q4_0; ExLlamaV2 - fp16, fp8, q8, q6, q4; ExLlamaV3 - fp16, q2 to q8. For ExLlamaV3, you can type custom combinations for separate k/v bits (e.g. q4_q8).') - shared.gradio['tensor_split'] = gr.Textbox(label='tensor_split', info='List of proportions to split the model across multiple GPUs. Example: 60,40') + shared.gradio['gpu_layers'] = gr.Slider(label="gpu-layers", minimum=0, maximum=get_initial_gpu_layers_max(), step=1, value=shared.args.gpu_layers, info='Must be greater than 0 for the GPU to be used. ⚠️ Lower this value if you can\'t load the model.') + shared.gradio['ctx_size'] = gr.Slider(label='ctx-size', minimum=256, maximum=131072, step=256, value=shared.args.ctx_size, info='Context length. ⚠️ Lower this value if you can\'t load the model.') shared.gradio['gpu_split'] = gr.Textbox(label='gpu-split', info='Comma-separated list of VRAM (in GB) to use per GPU. Example: 20,7,7') - shared.gradio['extra_flags'] = gr.Textbox(label='extra-flags', info='Additional flags to pass to llama-server. Format: "flag1=value1,flag2,flag3=value3". Example: "override-tensor=exps=CPU"', value=shared.args.extra_flags) - shared.gradio['cpu_memory'] = gr.Number(label="Maximum CPU memory in GiB. Use this for CPU offloading.", value=shared.args.cpu_memory) - shared.gradio['alpha_value'] = gr.Number(label='alpha_value', value=shared.args.alpha_value, precision=2, info='Positional embeddings alpha factor for NTK RoPE scaling. Recommended values (NTKv1): 1.75 for 1.5x context, 2.5 for 2x context. Use either this or compress_pos_emb, not both.') - shared.gradio['rope_freq_base'] = gr.Number(label='rope_freq_base', value=shared.args.rope_freq_base, precision=0, info='Positional embeddings frequency base for NTK RoPE scaling. Related to alpha_value by rope_freq_base = 10000 * alpha_value ^ (64 / 63). 0 = from model.') - shared.gradio['compress_pos_emb'] = gr.Number(label='compress_pos_emb', value=shared.args.compress_pos_emb, precision=2, info='Positional embeddings compression factor. Should be set to (context length) / (model\'s original context length). Equal to 1/rope_freq_scale.') - shared.gradio['compute_dtype'] = gr.Dropdown(label="compute_dtype", choices=["bfloat16", "float16", "float32"], value=shared.args.compute_dtype, info='Used by load-in-4bit.') - shared.gradio['quant_type'] = gr.Dropdown(label="quant_type", choices=["nf4", "fp4"], value=shared.args.quant_type, info='Used by load-in-4bit.') - shared.gradio['num_experts_per_token'] = gr.Number(label="Number of experts per token", value=shared.args.num_experts_per_token, info='Only applies to MoE models like Mixtral.') + shared.gradio['cache_type'] = gr.Dropdown(label="cache-type", choices=['fp16', 'q8_0', 'q4_0', 'fp8', 'q8', 'q7', 'q6', 'q5', 'q4', 'q3', 'q2'], value=shared.args.cache_type, allow_custom_value=True, info='Valid options: llama.cpp - fp16, q8_0, q4_0; ExLlamaV2 - fp16, fp8, q8, q6, q4; ExLlamaV3 - fp16, q2 to q8. For ExLlamaV3, you can type custom combinations for separate k/v bits (e.g. q4_q8).') + shared.gradio['hqq_backend'] = gr.Dropdown(label="hqq_backend", choices=["PYTORCH", "PYTORCH_COMPILE", "ATEN"], value=shared.args.hqq_backend) with gr.Column(): + shared.gradio['vram_info'] = gr.HTML(value=get_initial_vram_info()) + shared.gradio['flash_attn'] = gr.Checkbox(label="flash-attn", value=shared.args.flash_attn, info='Use flash-attention.') + shared.gradio['streaming_llm'] = gr.Checkbox(label="streaming-llm", value=shared.args.streaming_llm, info='Activate StreamingLLM to avoid re-evaluating the entire prompt when old messages are removed.') shared.gradio['load_in_8bit'] = gr.Checkbox(label="load-in-8bit", value=shared.args.load_in_8bit) shared.gradio['load_in_4bit'] = gr.Checkbox(label="load-in-4bit", value=shared.args.load_in_4bit) shared.gradio['torch_compile'] = gr.Checkbox(label="torch-compile", value=shared.args.torch_compile, info='Compile the model with torch.compile for improved performance.') - shared.gradio['flash_attn'] = gr.Checkbox(label="flash_attn", value=shared.args.flash_attn, info='Use flash-attention.') shared.gradio['use_flash_attention_2'] = gr.Checkbox(label="use_flash_attention_2", value=shared.args.use_flash_attention_2, info='Set use_flash_attention_2=True while loading the model.') - shared.gradio['streaming_llm'] = gr.Checkbox(label="streaming_llm", value=shared.args.streaming_llm, info='Activate StreamingLLM to avoid re-evaluating the entire prompt when old messages are removed.') - shared.gradio['cpu'] = gr.Checkbox(label="cpu", value=shared.args.cpu, info='llama.cpp: Use llama-cpp-python compiled without GPU acceleration. Transformers: use PyTorch in CPU mode.') - shared.gradio['disk'] = gr.Checkbox(label="disk", value=shared.args.disk) - shared.gradio['row_split'] = gr.Checkbox(label="row_split", value=shared.args.row_split, info='Split the model by rows across GPUs. This may improve multi-gpu performance.') - shared.gradio['no_kv_offload'] = gr.Checkbox(label="no_kv_offload", value=shared.args.no_kv_offload, info='Do not offload the K, Q, V to the GPU. This saves VRAM but reduces the performance.') - shared.gradio['no_mmap'] = gr.Checkbox(label="no-mmap", value=shared.args.no_mmap) - shared.gradio['mlock'] = gr.Checkbox(label="mlock", value=shared.args.mlock) - shared.gradio['numa'] = gr.Checkbox(label="numa", value=shared.args.numa, info='NUMA support can help on some systems with non-uniform memory access.') shared.gradio['use_double_quant'] = gr.Checkbox(label="use_double_quant", value=shared.args.use_double_quant, info='Used by load-in-4bit.') - shared.gradio['use_eager_attention'] = gr.Checkbox(label="use_eager_attention", value=shared.args.use_eager_attention, info='Set attn_implementation= eager while loading the model.') - shared.gradio['bf16'] = gr.Checkbox(label="bf16", value=shared.args.bf16) shared.gradio['autosplit'] = gr.Checkbox(label="autosplit", value=shared.args.autosplit, info='Automatically split the model tensors across the available GPUs.') shared.gradio['enable_tp'] = gr.Checkbox(label="enable_tp", value=shared.args.enable_tp, info='Enable Tensor Parallelism (TP).') - shared.gradio['no_flash_attn'] = gr.Checkbox(label="no_flash_attn", value=shared.args.no_flash_attn) - shared.gradio['no_xformers'] = gr.Checkbox(label="no_xformers", value=shared.args.no_xformers) - shared.gradio['no_sdpa'] = gr.Checkbox(label="no_sdpa", value=shared.args.no_sdpa) - shared.gradio['cfg_cache'] = gr.Checkbox(label="cfg-cache", value=shared.args.cfg_cache, info='Necessary to use CFG with this loader.') shared.gradio['cpp_runner'] = gr.Checkbox(label="cpp-runner", value=shared.args.cpp_runner, info='Enable inference with ModelRunnerCpp, which is faster than the default ModelRunner.') shared.gradio['trust_remote_code'] = gr.Checkbox(label="trust-remote-code", value=shared.args.trust_remote_code, info='Set trust_remote_code=True while loading the tokenizer/model. To enable this option, start the web UI with the --trust-remote-code flag.', interactive=shared.args.trust_remote_code) - shared.gradio['no_use_fast'] = gr.Checkbox(label="no_use_fast", value=shared.args.no_use_fast, info='Set use_fast=False while loading the tokenizer.') - shared.gradio['exllamav2_info'] = gr.Markdown("ExLlamav2_HF is recommended over ExLlamav2 for better integration with extensions and more consistent sampling behavior across loaders.") shared.gradio['tensorrt_llm_info'] = gr.Markdown('* TensorRT-LLM has to be installed manually in a separate Python 3.10 environment at the moment. For a guide, consult the description of [this PR](https://github.com/oobabooga/text-generation-webui/pull/5715). \n\n* `ctx_size` is only used when `cpp-runner` is checked.\n\n* `cpp_runner` does not support streaming at the moment.') # Speculative decoding @@ -99,15 +65,50 @@ def create_ui(): shared.gradio['model_draft'] = gr.Dropdown(label="model-draft", choices=utils.get_available_models(), value=lambda: shared.args.model_draft, elem_classes='slim-dropdown', info='Draft model. Speculative decoding only works with models sharing the same vocabulary (e.g., same model family).', interactive=not mu) ui.create_refresh_button(shared.gradio['model_draft'], lambda: None, lambda: {'choices': utils.get_available_models()}, 'refresh-button', interactive=not mu) - shared.gradio['draft_max'] = gr.Number(label="draft-max", precision=0, step=1, value=shared.args.draft_max, info='Number of tokens to draft for speculative decoding.') shared.gradio['gpu_layers_draft'] = gr.Slider(label="gpu-layers-draft", minimum=0, maximum=256, value=shared.args.gpu_layers_draft, info='Number of layers to offload to the GPU for the draft model.') + shared.gradio['draft_max'] = gr.Number(label="draft-max", precision=0, step=1, value=shared.args.draft_max, info='Number of tokens to draft for speculative decoding. Recommended value: 4.') shared.gradio['device_draft'] = gr.Textbox(label="device-draft", value=shared.args.device_draft, info='Comma-separated list of devices to use for offloading the draft model. Example: CUDA0,CUDA1') shared.gradio['ctx_size_draft'] = gr.Number(label="ctx-size-draft", precision=0, step=256, value=shared.args.ctx_size_draft, info='Size of the prompt context for the draft model. If 0, uses the same as the main model.') - with gr.Column(): - with gr.Row(): - shared.gradio['autoload_model'] = gr.Checkbox(value=shared.settings['autoload_model'], label='Autoload the model', info='Whether to load the model as soon as it is selected in the Model dropdown.', interactive=not mu) + gr.Markdown("## Other options") + with gr.Accordion("See more options", open=False, elem_classes='tgw-accordion'): + with gr.Row(): + with gr.Column(): + shared.gradio['threads'] = gr.Slider(label="threads", minimum=0, step=1, maximum=256, value=shared.args.threads) + shared.gradio['threads_batch'] = gr.Slider(label="threads_batch", minimum=0, step=1, maximum=256, value=shared.args.threads_batch) + shared.gradio['batch_size'] = gr.Slider(label="batch_size", minimum=1, maximum=4096, step=1, value=shared.args.batch_size) + shared.gradio['tensor_split'] = gr.Textbox(label='tensor_split', info='List of proportions to split the model across multiple GPUs. Example: 60,40') + shared.gradio['extra_flags'] = gr.Textbox(label='extra-flags', info='Additional flags to pass to llama-server. Format: "flag1=value1,flag2,flag3=value3". Example: "override-tensor=exps=CPU"', value=shared.args.extra_flags) + shared.gradio['cpu_memory'] = gr.Number(label="Maximum CPU memory in GiB. Use this for CPU offloading.", value=shared.args.cpu_memory) + shared.gradio['alpha_value'] = gr.Number(label='alpha_value', value=shared.args.alpha_value, precision=2, info='Positional embeddings alpha factor for NTK RoPE scaling. Recommended values (NTKv1): 1.75 for 1.5x context, 2.5 for 2x context. Use either this or compress_pos_emb, not both.') + shared.gradio['rope_freq_base'] = gr.Number(label='rope_freq_base', value=shared.args.rope_freq_base, precision=0, info='Positional embeddings frequency base for NTK RoPE scaling. Related to alpha_value by rope_freq_base = 10000 * alpha_value ^ (64 / 63). 0 = from model.') + shared.gradio['compress_pos_emb'] = gr.Number(label='compress_pos_emb', value=shared.args.compress_pos_emb, precision=2, info='Positional embeddings compression factor. Should be set to (context length) / (model\'s original context length). Equal to 1/rope_freq_scale.') + shared.gradio['compute_dtype'] = gr.Dropdown(label="compute_dtype", choices=["bfloat16", "float16", "float32"], value=shared.args.compute_dtype, info='Used by load-in-4bit.') + shared.gradio['quant_type'] = gr.Dropdown(label="quant_type", choices=["nf4", "fp4"], value=shared.args.quant_type, info='Used by load-in-4bit.') + shared.gradio['num_experts_per_token'] = gr.Number(label="Number of experts per token", value=shared.args.num_experts_per_token, info='Only applies to MoE models like Mixtral.') + with gr.Column(): + shared.gradio['cpu'] = gr.Checkbox(label="cpu", value=shared.args.cpu, info='llama.cpp: Use llama-cpp-python compiled without GPU acceleration. Transformers: use PyTorch in CPU mode.') + shared.gradio['disk'] = gr.Checkbox(label="disk", value=shared.args.disk) + shared.gradio['row_split'] = gr.Checkbox(label="row_split", value=shared.args.row_split, info='Split the model by rows across GPUs. This may improve multi-gpu performance.') + shared.gradio['no_kv_offload'] = gr.Checkbox(label="no_kv_offload", value=shared.args.no_kv_offload, info='Do not offload the K, Q, V to the GPU. This saves VRAM but reduces the performance.') + shared.gradio['no_mmap'] = gr.Checkbox(label="no-mmap", value=shared.args.no_mmap) + shared.gradio['mlock'] = gr.Checkbox(label="mlock", value=shared.args.mlock) + shared.gradio['numa'] = gr.Checkbox(label="numa", value=shared.args.numa, info='NUMA support can help on some systems with non-uniform memory access.') + shared.gradio['use_eager_attention'] = gr.Checkbox(label="use_eager_attention", value=shared.args.use_eager_attention, info='Set attn_implementation= eager while loading the model.') + shared.gradio['bf16'] = gr.Checkbox(label="bf16", value=shared.args.bf16) + shared.gradio['no_flash_attn'] = gr.Checkbox(label="no_flash_attn", value=shared.args.no_flash_attn) + shared.gradio['no_xformers'] = gr.Checkbox(label="no_xformers", value=shared.args.no_xformers) + shared.gradio['no_sdpa'] = gr.Checkbox(label="no_sdpa", value=shared.args.no_sdpa) + shared.gradio['cfg_cache'] = gr.Checkbox(label="cfg-cache", value=shared.args.cfg_cache, info='Necessary to use CFG with this loader.') + shared.gradio['no_use_fast'] = gr.Checkbox(label="no_use_fast", value=shared.args.no_use_fast, info='Set use_fast=False while loading the tokenizer.') + if not shared.args.portable: + with gr.Row(): + shared.gradio['lora_menu'] = gr.Dropdown(multiselect=True, choices=utils.get_available_loras(), value=shared.lora_names, label='LoRA(s)', elem_classes='slim-dropdown', interactive=not mu) + ui.create_refresh_button(shared.gradio['lora_menu'], lambda: None, lambda: {'choices': utils.get_available_loras(), 'value': shared.lora_names}, 'refresh-button', interactive=not mu) + shared.gradio['lora_menu_apply'] = gr.Button(value='Apply LoRAs', elem_classes='refresh-button', interactive=not mu) + + with gr.Column(): with gr.Tab("Download"): shared.gradio['custom_model_menu'] = gr.Textbox(label="Download model or LoRA", info="Enter the Hugging Face username/model path, for instance: facebook/galactica-125m. To specify a branch, add it at the end after a \":\" character like this: facebook/galactica-125m:main. To download a single file, enter its name in the second box.", interactive=not mu) shared.gradio['download_specific_file'] = gr.Textbox(placeholder="File name (for GGUF models)", show_label=False, max_lines=1, interactive=not mu) @@ -132,11 +133,10 @@ def create_event_handlers(): # In this event handler, the interface state is read and updated # with the model defaults (if any), and then the model is loaded - # unless "autoload_model" is unchecked shared.gradio['model_menu'].change( ui.gather_interface_values, gradio(shared.input_elements), gradio('interface_state')).then( handle_load_model_event_initial, gradio('model_menu', 'interface_state'), gradio(ui.list_interface_input_elements()) + gradio('interface_state'), show_progress=False).then( - load_model_wrapper, gradio('model_menu', 'loader', 'autoload_model'), gradio('model_status'), show_progress=True).success( + partial(load_model_wrapper, autoload=False), gradio('model_menu', 'loader'), gradio('model_status'), show_progress=True).success( handle_load_model_event_final, gradio('truncation_length', 'loader', 'interface_state'), gradio('truncation_length', 'filter_by_loader'), show_progress=False) shared.gradio['load_model'].click( @@ -145,15 +145,31 @@ def create_event_handlers(): partial(load_model_wrapper, autoload=True), gradio('model_menu', 'loader'), gradio('model_status'), show_progress=True).success( handle_load_model_event_final, gradio('truncation_length', 'loader', 'interface_state'), gradio('truncation_length', 'filter_by_loader'), show_progress=False) - shared.gradio['unload_model'].click(handle_unload_model_click, None, gradio('model_status'), show_progress=False) + shared.gradio['unload_model'].click(handle_unload_model_click, None, gradio('model_status'), show_progress=False).then( + partial(update_gpu_layers_and_vram, auto_adjust=True), gradio('loader', 'model_menu', 'gpu_layers', 'ctx_size', 'cache_type'), gradio('vram_info', 'gpu_layers'), show_progress=False) + shared.gradio['save_model_settings'].click( ui.gather_interface_values, gradio(shared.input_elements), gradio('interface_state')).then( save_model_settings, gradio('model_menu', 'interface_state'), gradio('model_status'), show_progress=False) - shared.gradio['lora_menu_apply'].click(load_lora_wrapper, gradio('lora_menu'), gradio('model_status'), show_progress=False) + # For ctx_size and cache_type - auto-adjust GPU layers + for param in ['ctx_size', 'cache_type']: + shared.gradio[param].change( + partial(update_gpu_layers_and_vram, auto_adjust=True), + gradio('loader', 'model_menu', 'gpu_layers', 'ctx_size', 'cache_type'), + gradio('vram_info', 'gpu_layers'), show_progress=False) + + # For manual gpu_layers changes - only update VRAM + shared.gradio['gpu_layers'].change( + partial(update_gpu_layers_and_vram, auto_adjust=False), + gradio('loader', 'model_menu', 'gpu_layers', 'ctx_size', 'cache_type'), + gradio('vram_info'), show_progress=False) + + if not shared.args.portable: + shared.gradio['lora_menu_apply'].click(load_lora_wrapper, gradio('lora_menu'), gradio('model_status'), show_progress=False) + shared.gradio['download_model_button'].click(download_model_wrapper, gradio('custom_model_menu', 'download_specific_file'), gradio('model_status'), show_progress=True) shared.gradio['get_file_list'].click(partial(download_model_wrapper, return_links=True), gradio('custom_model_menu', 'download_specific_file'), gradio('model_status'), show_progress=True) - shared.gradio['autoload_model'].change(lambda x: gr.update(visible=not x), gradio('autoload_model'), gradio('load_model')) shared.gradio['customized_template_submit'].click(save_instruction_template, gradio('model_menu', 'customized_template'), gradio('model_status'), show_progress=True) @@ -192,6 +208,26 @@ def load_lora_wrapper(selected_loras): def download_model_wrapper(repo_id, specific_file, progress=gr.Progress(), return_links=False, check=False): try: + # Handle direct GGUF URLs + if repo_id.startswith("https://") and ("huggingface.co" in repo_id) and (repo_id.endswith(".gguf") or repo_id.endswith(".gguf?download=true")): + try: + path = repo_id.split("huggingface.co/")[1] + + # Extract the repository ID (first two parts of the path) + parts = path.split("/") + if len(parts) >= 2: + extracted_repo_id = f"{parts[0]}/{parts[1]}" + + # Extract the filename (last part of the path) + filename = repo_id.split("/")[-1] + if "?download=true" in filename: + filename = filename.replace("?download=true", "") + + repo_id = extracted_repo_id + specific_file = filename + except: + pass + if repo_id == "": yield ("Please enter a model path") return @@ -205,6 +241,18 @@ def download_model_wrapper(repo_id, specific_file, progress=gr.Progress(), retur yield ("Getting the download links from Hugging Face") links, sha256, is_lora, is_llamacpp = downloader.get_download_links_from_huggingface(model, branch, text_only=False, specific_file=specific_file) + + # Check for multiple GGUF files + gguf_files = [link for link in links if link.lower().endswith('.gguf')] + if len(gguf_files) > 1 and not specific_file: + output = "Multiple GGUF files found. Please copy one of the following filenames to the 'File name' field:\n\n```\n" + for link in gguf_files: + output += f"{Path(link).name}\n" + + output += "```" + yield output + return + if return_links: output = "```\n" for link in links: @@ -252,10 +300,34 @@ def update_truncation_length(current_length, state): return current_length +def get_initial_vram_info(): + if shared.model_name != 'None' and shared.args.loader == 'llama.cpp': + return update_gpu_layers_and_vram( + shared.args.loader, + shared.model_name, + shared.args.gpu_layers, + shared.args.ctx_size, + shared.args.cache_type, + auto_adjust=False, + for_ui=True + ) + + return "
Estimated VRAM to load the model:" + + +def get_initial_gpu_layers_max(): + if shared.model_name != 'None' and shared.args.loader == 'llama.cpp': + model_settings = get_model_metadata(shared.model_name) + return model_settings.get('gpu_layers', 256) + + return 256 + + def handle_load_model_event_initial(model, state): state = apply_model_settings_to_state(model, state) output = ui.apply_interface_values(state) - update_model_parameters(state) + update_model_parameters(state) # This updates the command-line flags + return output + [state] diff --git a/modules/ui_parameters.py b/modules/ui_parameters.py index 3f609d71..84f9fbfc 100644 --- a/modules/ui_parameters.py +++ b/modules/ui_parameters.py @@ -21,7 +21,7 @@ def create_ui(default_preset): shared.gradio['random_preset'] = gr.Button('🎲', elem_classes='refresh-button') with gr.Column(): - shared.gradio['filter_by_loader'] = gr.Dropdown(label="Filter by loader", choices=["All"] + list(loaders.loaders_and_params.keys()), value="All", elem_classes='slim-dropdown') + shared.gradio['filter_by_loader'] = gr.Dropdown(label="Filter by loader", choices=["All"] + list(loaders.loaders_and_params.keys()) if not shared.args.portable else ['llama.cpp'], value="All", elem_classes='slim-dropdown') with gr.Row(): with gr.Column(): @@ -71,8 +71,6 @@ def create_ui(default_preset): shared.gradio['max_new_tokens'] = gr.Slider(minimum=shared.settings['max_new_tokens_min'], maximum=shared.settings['max_new_tokens_max'], value=shared.settings['max_new_tokens'], step=1, label='max_new_tokens', info='⚠️ Setting this too high can cause prompt truncation.') shared.gradio['prompt_lookup_num_tokens'] = gr.Slider(value=shared.settings['prompt_lookup_num_tokens'], minimum=0, maximum=10, step=1, label='prompt_lookup_num_tokens', info='Activates Prompt Lookup Decoding.') shared.gradio['max_tokens_second'] = gr.Slider(value=shared.settings['max_tokens_second'], minimum=0, maximum=20, step=1, label='Maximum tokens/second', info='To make text readable in real time.') - shared.gradio['max_updates_second'] = gr.Slider(value=shared.settings['max_updates_second'], minimum=0, maximum=24, step=1, label='Maximum UI updates/second', info='Set this if you experience lag in the UI during streaming.') - with gr.Column(): with gr.Row(): with gr.Column(): @@ -82,7 +80,7 @@ def create_ui(default_preset): shared.gradio['auto_max_new_tokens'] = gr.Checkbox(value=shared.settings['auto_max_new_tokens'], label='auto_max_new_tokens', info='Expand max_new_tokens to the available context length.') shared.gradio['ban_eos_token'] = gr.Checkbox(value=shared.settings['ban_eos_token'], label='Ban the eos_token', info='Forces the model to never end the generation prematurely.') shared.gradio['add_bos_token'] = gr.Checkbox(value=shared.settings['add_bos_token'], label='Add the bos_token to the beginning of prompts', info='Disabling this can make the replies more creative.') - shared.gradio['enable_thinking'] = gr.Checkbox(value=shared.settings['enable_thinking'], label='enable_thinking', info='Used by Qwen3 to toggle mode.') + shared.gradio['enable_thinking'] = gr.Checkbox(value=shared.settings['enable_thinking'], label='Enable thinking', info='Used by Qwen3 to toggle mode.') shared.gradio['skip_special_tokens'] = gr.Checkbox(value=shared.settings['skip_special_tokens'], label='Skip special tokens', info='Some specific models need this unset.') shared.gradio['stream'] = gr.Checkbox(value=shared.settings['stream'], label='Activate text streaming') shared.gradio['static_cache'] = gr.Checkbox(value=shared.settings['static_cache'], label='Static KV cache', info='Use a static cache for improved performance.') diff --git a/modules/ui_session.py b/modules/ui_session.py index 7cf9f6e6..a4eba667 100644 --- a/modules/ui_session.py +++ b/modules/ui_session.py @@ -23,11 +23,15 @@ def create_ui(): shared.gradio['bool_menu'] = gr.CheckboxGroup(choices=get_boolean_arguments(), value=get_boolean_arguments(active=True), label="Boolean command-line flags", elem_classes='checkboxgroup-table') with gr.Column(): - extension_name = gr.Textbox(lines=1, label='Install or update an extension', info='Enter the GitHub URL below and press Enter. For a list of extensions, see: https://github.com/oobabooga/text-generation-webui-extensions ⚠️ WARNING ⚠️ : extensions can execute arbitrary code. Make sure to inspect their source code before activating them.', interactive=not mu) - extension_status = gr.Markdown() + if not shared.args.portable: + extension_name = gr.Textbox(lines=1, label='Install or update an extension', info='Enter the GitHub URL below and press Enter. For a list of extensions, see: https://github.com/oobabooga/text-generation-webui-extensions ⚠️ WARNING ⚠️ : extensions can execute arbitrary code. Make sure to inspect their source code before activating them.', interactive=not mu) + extension_status = gr.Markdown() + else: + pass shared.gradio['theme_state'] = gr.Textbox(visible=False, value='dark' if shared.settings['dark_theme'] else 'light') - extension_name.submit(clone_or_pull_repository, extension_name, extension_status, show_progress=False) + if not shared.args.portable: + extension_name.submit(clone_or_pull_repository, extension_name, extension_status, show_progress=False) # Reset interface event shared.gradio['reset_interface'].click( diff --git a/modules/utils.py b/modules/utils.py index 77324139..0e390d08 100644 --- a/modules/utils.py +++ b/modules/utils.py @@ -72,6 +72,20 @@ def natural_keys(text): return [atoi(c) for c in re.split(r'(\d+)', text)] +def check_model_loaded(): + if shared.model_name == 'None' or shared.model is None: + if len(get_available_models()) <= 1: + error_msg = "No model is loaded.\n\nTo get started:\n1) Place a GGUF file in your user_data/models folder\n2) Go to the Model tab and select it" + logger.error(error_msg) + return False, error_msg + else: + error_msg = "No model is loaded. Please select one in the Model tab." + logger.error(error_msg) + return False, error_msg + + return True, None + + def get_available_models(): # Get all GGUF files gguf_files = get_available_ggufs() diff --git a/one_click.py b/one_click.py index 065afd99..482a6aa9 100644 --- a/one_click.py +++ b/one_click.py @@ -126,7 +126,7 @@ def check_env(): sys.exit(1) # Ensure this is a new environment and not the base environment - if os.environ["CONDA_DEFAULT_ENV"] == "base": + if os.environ.get("CONDA_DEFAULT_ENV", "") == "base": print("Create an environment for this project and activate it. Exiting...") sys.exit(1) @@ -222,7 +222,7 @@ def update_pytorch_and_python(): if "+cu" in torver: install_cmd = f"{base_cmd} --index-url https://download.pytorch.org/whl/cu124" elif "+rocm" in torver: - install_cmd = f"{base_cmd} --index-url https://download.pytorch.org/whl/rocm6.1" + install_cmd = f"{base_cmd} --index-url https://download.pytorch.org/whl/rocm6.2.4" elif "+cpu" in torver: install_cmd = f"{base_cmd} --index-url https://download.pytorch.org/whl/cpu" elif "+cxx11" in torver: @@ -273,7 +273,7 @@ def install_webui(): "What is your GPU?", { 'A': 'NVIDIA - CUDA 12.4', - 'B': 'AMD - Linux/macOS only, requires ROCm 6.1', + 'B': 'AMD - Linux/macOS only, requires ROCm 6.2.4', 'C': 'Apple M Series', 'D': 'Intel Arc (beta)', 'N': 'CPU mode' @@ -314,7 +314,7 @@ def install_webui(): if selected_gpu == "NVIDIA": install_pytorch += "--index-url https://download.pytorch.org/whl/cu124" elif selected_gpu == "AMD": - install_pytorch += "--index-url https://download.pytorch.org/whl/rocm6.1" + install_pytorch += "--index-url https://download.pytorch.org/whl/rocm6.2.4" elif selected_gpu in ["APPLE", "NONE"]: install_pytorch += "--index-url https://download.pytorch.org/whl/cpu" elif selected_gpu == "INTEL": diff --git a/requirements/full/requirements.txt b/requirements/full/requirements.txt index 6f265eba..af5f7d8a 100644 --- a/requirements/full/requirements.txt +++ b/requirements/full/requirements.txt @@ -30,12 +30,12 @@ sse-starlette==1.6.5 tiktoken # CUDA wheels -https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.8.0/llama_cpp_binaries-0.8.0+cu124-py3-none-win_amd64.whl; platform_system == "Windows" and python_version == "3.11" -https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.8.0/llama_cpp_binaries-0.8.0+cu124-py3-none-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.11" -https://github.com/oobabooga/exllamav3/releases/download/v0.0.1a6/exllamav3-0.0.1a6+cu124.torch2.6.0-cp311-cp311-win_amd64.whl; platform_system == "Windows" and python_version == "3.11" -https://github.com/oobabooga/exllamav3/releases/download/v0.0.1a6/exllamav3-0.0.1a6+cu124.torch2.6.0-cp311-cp311-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.11" -https://github.com/oobabooga/exllamav2/releases/download/v0.2.9/exllamav2-0.2.9+cu124.torch2.6.0-cp311-cp311-win_amd64.whl; platform_system == "Windows" and python_version == "3.11" -https://github.com/oobabooga/exllamav2/releases/download/v0.2.9/exllamav2-0.2.9+cu124.torch2.6.0-cp311-cp311-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.11" -https://github.com/oobabooga/exllamav2/releases/download/v0.2.9/exllamav2-0.2.9-py3-none-any.whl; platform_system == "Linux" and platform_machine != "x86_64" +https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.12.0/llama_cpp_binaries-0.12.0+cu124-py3-none-win_amd64.whl; platform_system == "Windows" and python_version == "3.11" +https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.12.0/llama_cpp_binaries-0.12.0+cu124-py3-none-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.11" +https://github.com/oobabooga/exllamav3/releases/download/v0.0.1a9/exllamav3-0.0.1a9+cu124.torch2.6.0-cp311-cp311-win_amd64.whl; platform_system == "Windows" and python_version == "3.11" +https://github.com/oobabooga/exllamav3/releases/download/v0.0.1a9/exllamav3-0.0.1a9+cu124.torch2.6.0-cp311-cp311-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.11" +https://github.com/turboderp-org/exllamav2/releases/download/v0.2.9/exllamav2-0.2.9+cu124.torch2.6.0-cp311-cp311-win_amd64.whl; platform_system == "Windows" and python_version == "3.11" +https://github.com/turboderp-org/exllamav2/releases/download/v0.2.9/exllamav2-0.2.9+cu124.torch2.6.0-cp311-cp311-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.11" +https://github.com/turboderp-org/exllamav2/releases/download/v0.2.9/exllamav2-0.2.9-py3-none-any.whl; platform_system == "Linux" and platform_machine != "x86_64" https://github.com/oobabooga/flash-attention/releases/download/v2.7.4.post1/flash_attn-2.7.4.post1+cu124torch2.6.0cxx11abiFALSE-cp311-cp311-win_amd64.whl; platform_system == "Windows" and python_version == "3.11" https://github.com/Dao-AILab/flash-attention/releases/download/v2.7.4.post1/flash_attn-2.7.4.post1+cu12torch2.6cxx11abiFALSE-cp311-cp311-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.11" diff --git a/requirements/full/requirements_amd.txt b/requirements/full/requirements_amd.txt index c8e75ee7..4e011989 100644 --- a/requirements/full/requirements_amd.txt +++ b/requirements/full/requirements_amd.txt @@ -29,6 +29,7 @@ sse-starlette==1.6.5 tiktoken # AMD wheels -https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.8.0/llama_cpp_binaries-0.8.0+rocm6.1.2-py3-none-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.11" -https://github.com/oobabooga/exllamav2/releases/download/v0.2.9/exllamav2-0.2.9+rocm6.1.torch2.6.0-cp311-cp311-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.11" -https://github.com/oobabooga/exllamav2/releases/download/v0.2.9/exllamav2-0.2.9-py3-none-any.whl; platform_system != "Darwin" and platform_machine != "x86_64" +https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.12.0/llama_cpp_binaries-0.12.0+vulkan-py3-none-win_amd64.whl; platform_system == "Windows" +https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.12.0/llama_cpp_binaries-0.12.0+vulkan-py3-none-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" +https://github.com/turboderp-org/exllamav2/releases/download/v0.2.9/exllamav2-0.2.9+rocm6.2.4.torch2.6.0-cp311-cp311-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.11" +https://github.com/turboderp-org/exllamav2/releases/download/v0.2.9/exllamav2-0.2.9-py3-none-any.whl; platform_system != "Darwin" and platform_machine != "x86_64" diff --git a/requirements/full/requirements_amd_noavx2.txt b/requirements/full/requirements_amd_noavx2.txt index e54d6d9c..a3bd1350 100644 --- a/requirements/full/requirements_amd_noavx2.txt +++ b/requirements/full/requirements_amd_noavx2.txt @@ -29,6 +29,7 @@ sse-starlette==1.6.5 tiktoken # AMD wheels -https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.8.0/llama_cpp_binaries-0.8.0+rocm6.1.2avx-py3-none-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.11" -https://github.com/oobabooga/exllamav2/releases/download/v0.2.9/exllamav2-0.2.9+rocm6.1.torch2.6.0-cp311-cp311-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.11" -https://github.com/oobabooga/exllamav2/releases/download/v0.2.9/exllamav2-0.2.9-py3-none-any.whl; platform_system != "Darwin" and platform_machine != "x86_64" +https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.12.0/llama_cpp_binaries-0.12.0+vulkanavx-py3-none-win_amd64.whl; platform_system == "Windows" +https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.12.0/llama_cpp_binaries-0.12.0+vulkanavx-py3-none-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" +https://github.com/turboderp-org/exllamav2/releases/download/v0.2.9/exllamav2-0.2.9+rocm6.2.4.torch2.6.0-cp311-cp311-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.11" +https://github.com/turboderp-org/exllamav2/releases/download/v0.2.9/exllamav2-0.2.9-py3-none-any.whl; platform_system != "Darwin" and platform_machine != "x86_64" diff --git a/requirements/full/requirements_apple_intel.txt b/requirements/full/requirements_apple_intel.txt index d714ea3d..363365bf 100644 --- a/requirements/full/requirements_apple_intel.txt +++ b/requirements/full/requirements_apple_intel.txt @@ -29,7 +29,7 @@ sse-starlette==1.6.5 tiktoken # Mac wheels -https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.8.0/llama_cpp_binaries-0.8.0-py3-none-macosx_15_0_x86_64.whl; platform_system == "Darwin" and platform_release >= "24.0.0" and platform_release < "25.0.0" and python_version == "3.11" -https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.8.0/llama_cpp_binaries-0.8.0-py3-none-macosx_14_0_x86_64.whl; platform_system == "Darwin" and platform_release >= "23.0.0" and platform_release < "24.0.0" and python_version == "3.11" -https://github.com/oobabooga/exllamav3/releases/download/v0.0.1a6/exllamav3-0.0.1a6-py3-none-any.whl -https://github.com/oobabooga/exllamav2/releases/download/v0.2.9/exllamav2-0.2.9-py3-none-any.whl +https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.12.0/llama_cpp_binaries-0.12.0-py3-none-macosx_15_0_x86_64.whl; platform_system == "Darwin" and platform_release >= "24.0.0" and platform_release < "25.0.0" and python_version == "3.11" +https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.12.0/llama_cpp_binaries-0.12.0-py3-none-macosx_14_0_x86_64.whl; platform_system == "Darwin" and platform_release >= "23.0.0" and platform_release < "24.0.0" and python_version == "3.11" +https://github.com/oobabooga/exllamav3/releases/download/v0.0.1a9/exllamav3-0.0.1a9-py3-none-any.whl +https://github.com/turboderp-org/exllamav2/releases/download/v0.2.9/exllamav2-0.2.9-py3-none-any.whl diff --git a/requirements/full/requirements_apple_silicon.txt b/requirements/full/requirements_apple_silicon.txt index 89f4f576..2843fed2 100644 --- a/requirements/full/requirements_apple_silicon.txt +++ b/requirements/full/requirements_apple_silicon.txt @@ -29,8 +29,8 @@ sse-starlette==1.6.5 tiktoken # Mac wheels -https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.8.0/llama_cpp_binaries-0.8.0-py3-none-macosx_15_0_arm64.whl; platform_system == "Darwin" and platform_release >= "24.0.0" and platform_release < "25.0.0" and python_version == "3.11" -https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.8.0/llama_cpp_binaries-0.8.0-py3-none-macosx_14_0_arm64.whl; platform_system == "Darwin" and platform_release >= "23.0.0" and platform_release < "24.0.0" and python_version == "3.11" -https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.8.0/llama_cpp_binaries-0.8.0-py3-none-macosx_13_0_arm64.whl; platform_system == "Darwin" and platform_release >= "22.0.0" and platform_release < "23.0.0" and python_version == "3.11" -https://github.com/oobabooga/exllamav3/releases/download/v0.0.1a6/exllamav3-0.0.1a6-py3-none-any.whl -https://github.com/oobabooga/exllamav2/releases/download/v0.2.9/exllamav2-0.2.9-py3-none-any.whl +https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.12.0/llama_cpp_binaries-0.12.0-py3-none-macosx_15_0_arm64.whl; platform_system == "Darwin" and platform_release >= "24.0.0" and platform_release < "25.0.0" and python_version == "3.11" +https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.12.0/llama_cpp_binaries-0.12.0-py3-none-macosx_14_0_arm64.whl; platform_system == "Darwin" and platform_release >= "23.0.0" and platform_release < "24.0.0" and python_version == "3.11" +https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.12.0/llama_cpp_binaries-0.12.0-py3-none-macosx_13_0_arm64.whl; platform_system == "Darwin" and platform_release >= "22.0.0" and platform_release < "23.0.0" and python_version == "3.11" +https://github.com/oobabooga/exllamav3/releases/download/v0.0.1a9/exllamav3-0.0.1a9-py3-none-any.whl +https://github.com/turboderp-org/exllamav2/releases/download/v0.2.9/exllamav2-0.2.9-py3-none-any.whl diff --git a/requirements/full/requirements_cpu_only.txt b/requirements/full/requirements_cpu_only.txt index 47ad5759..bd7c4a4f 100644 --- a/requirements/full/requirements_cpu_only.txt +++ b/requirements/full/requirements_cpu_only.txt @@ -29,5 +29,5 @@ sse-starlette==1.6.5 tiktoken # llama.cpp (CPU only, AVX2) -https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.8.0/llama_cpp_binaries-0.8.0+cpuavx2-py3-none-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.11" -https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.8.0/llama_cpp_binaries-0.8.0+cpuavx2-py3-none-win_amd64.whl; platform_system == "Windows" and python_version == "3.11" +https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.12.0/llama_cpp_binaries-0.12.0+cpuavx2-py3-none-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.11" +https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.12.0/llama_cpp_binaries-0.12.0+cpuavx2-py3-none-win_amd64.whl; platform_system == "Windows" and python_version == "3.11" diff --git a/requirements/full/requirements_cpu_only_noavx2.txt b/requirements/full/requirements_cpu_only_noavx2.txt index 334f11df..b5aa1cf7 100644 --- a/requirements/full/requirements_cpu_only_noavx2.txt +++ b/requirements/full/requirements_cpu_only_noavx2.txt @@ -29,5 +29,5 @@ sse-starlette==1.6.5 tiktoken # llama.cpp (CPU only, no AVX2) -https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.8.0/llama_cpp_binaries-0.8.0+cpuavx-py3-none-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.11" -https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.8.0/llama_cpp_binaries-0.8.0+cpuavx-py3-none-win_amd64.whl; platform_system == "Windows" and python_version == "3.11" +https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.12.0/llama_cpp_binaries-0.12.0+cpuavx-py3-none-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.11" +https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.12.0/llama_cpp_binaries-0.12.0+cpuavx-py3-none-win_amd64.whl; platform_system == "Windows" and python_version == "3.11" diff --git a/requirements/full/requirements_noavx2.txt b/requirements/full/requirements_noavx2.txt index e216c9cd..89947cbe 100644 --- a/requirements/full/requirements_noavx2.txt +++ b/requirements/full/requirements_noavx2.txt @@ -30,12 +30,12 @@ sse-starlette==1.6.5 tiktoken # CUDA wheels -https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.8.0/llama_cpp_binaries-0.8.0+cu124avx-py3-none-win_amd64.whl; platform_system == "Windows" and python_version == "3.11" -https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.8.0/llama_cpp_binaries-0.8.0+cu124avx-py3-none-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.11" -https://github.com/oobabooga/exllamav3/releases/download/v0.0.1a6/exllamav3-0.0.1a6+cu124.torch2.6.0-cp311-cp311-win_amd64.whl; platform_system == "Windows" and python_version == "3.11" -https://github.com/oobabooga/exllamav3/releases/download/v0.0.1a6/exllamav3-0.0.1a6+cu124.torch2.6.0-cp311-cp311-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.11" -https://github.com/oobabooga/exllamav2/releases/download/v0.2.9/exllamav2-0.2.9+cu124.torch2.6.0-cp311-cp311-win_amd64.whl; platform_system == "Windows" and python_version == "3.11" -https://github.com/oobabooga/exllamav2/releases/download/v0.2.9/exllamav2-0.2.9+cu124.torch2.6.0-cp311-cp311-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.11" -https://github.com/oobabooga/exllamav2/releases/download/v0.2.9/exllamav2-0.2.9-py3-none-any.whl; platform_system == "Linux" and platform_machine != "x86_64" +https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.12.0/llama_cpp_binaries-0.12.0+cu124avx-py3-none-win_amd64.whl; platform_system == "Windows" and python_version == "3.11" +https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.12.0/llama_cpp_binaries-0.12.0+cu124avx-py3-none-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.11" +https://github.com/oobabooga/exllamav3/releases/download/v0.0.1a9/exllamav3-0.0.1a9+cu124.torch2.6.0-cp311-cp311-win_amd64.whl; platform_system == "Windows" and python_version == "3.11" +https://github.com/oobabooga/exllamav3/releases/download/v0.0.1a9/exllamav3-0.0.1a9+cu124.torch2.6.0-cp311-cp311-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.11" +https://github.com/turboderp-org/exllamav2/releases/download/v0.2.9/exllamav2-0.2.9+cu124.torch2.6.0-cp311-cp311-win_amd64.whl; platform_system == "Windows" and python_version == "3.11" +https://github.com/turboderp-org/exllamav2/releases/download/v0.2.9/exllamav2-0.2.9+cu124.torch2.6.0-cp311-cp311-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.11" +https://github.com/turboderp-org/exllamav2/releases/download/v0.2.9/exllamav2-0.2.9-py3-none-any.whl; platform_system == "Linux" and platform_machine != "x86_64" https://github.com/oobabooga/flash-attention/releases/download/v2.7.4.post1/flash_attn-2.7.4.post1+cu124torch2.6.0cxx11abiFALSE-cp311-cp311-win_amd64.whl; platform_system == "Windows" and python_version == "3.11" https://github.com/Dao-AILab/flash-attention/releases/download/v2.7.4.post1/flash_attn-2.7.4.post1+cu12torch2.6cxx11abiFALSE-cp311-cp311-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.11" diff --git a/requirements/portable/requirements.txt b/requirements/portable/requirements.txt index c720daa7..79959398 100644 --- a/requirements/portable/requirements.txt +++ b/requirements/portable/requirements.txt @@ -15,5 +15,5 @@ sse-starlette==1.6.5 tiktoken # CUDA wheels -https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.8.0/llama_cpp_binaries-0.8.0+cu124-py3-none-win_amd64.whl; platform_system == "Windows" -https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.8.0/llama_cpp_binaries-0.8.0+cu124-py3-none-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" +https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.12.0/llama_cpp_binaries-0.12.0+cu124-py3-none-win_amd64.whl; platform_system == "Windows" +https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.12.0/llama_cpp_binaries-0.12.0+cu124-py3-none-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" diff --git a/requirements/portable/requirements_amd.txt b/requirements/portable/requirements_amd.txt deleted file mode 100644 index 7d9c00c0..00000000 --- a/requirements/portable/requirements_amd.txt +++ /dev/null @@ -1,18 +0,0 @@ -fastapi==0.112.4 -gradio==4.37.* -jinja2==3.1.6 -markdown -numpy==1.26.* -pydantic==2.8.2 -pyyaml -requests -rich -tqdm - -# API -flask_cloudflared==0.0.14 -sse-starlette==1.6.5 -tiktoken - -# AMD wheels -https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.8.0/llama_cpp_binaries-0.8.0+rocm6.1.2-py3-none-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" diff --git a/requirements/portable/requirements_amd_noavx2.txt b/requirements/portable/requirements_amd_noavx2.txt deleted file mode 100644 index d718c1b1..00000000 --- a/requirements/portable/requirements_amd_noavx2.txt +++ /dev/null @@ -1,18 +0,0 @@ -fastapi==0.112.4 -gradio==4.37.* -jinja2==3.1.6 -markdown -numpy==1.26.* -pydantic==2.8.2 -pyyaml -requests -rich -tqdm - -# API -flask_cloudflared==0.0.14 -sse-starlette==1.6.5 -tiktoken - -# AMD wheels -https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.8.0/llama_cpp_binaries-0.8.0+rocm6.1.2avx-py3-none-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" diff --git a/requirements/portable/requirements_apple_intel.txt b/requirements/portable/requirements_apple_intel.txt index 9e184b53..ca16e4c7 100644 --- a/requirements/portable/requirements_apple_intel.txt +++ b/requirements/portable/requirements_apple_intel.txt @@ -15,5 +15,5 @@ sse-starlette==1.6.5 tiktoken # Mac wheels -https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.8.0/llama_cpp_binaries-0.8.0-py3-none-macosx_15_0_x86_64.whl; platform_system == "Darwin" and platform_release >= "24.0.0" and platform_release < "25.0.0" -https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.8.0/llama_cpp_binaries-0.8.0-py3-none-macosx_14_0_x86_64.whl; platform_system == "Darwin" and platform_release >= "23.0.0" and platform_release < "24.0.0" +https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.12.0/llama_cpp_binaries-0.12.0-py3-none-macosx_15_0_x86_64.whl; platform_system == "Darwin" and platform_release >= "24.0.0" and platform_release < "25.0.0" +https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.12.0/llama_cpp_binaries-0.12.0-py3-none-macosx_14_0_x86_64.whl; platform_system == "Darwin" and platform_release >= "23.0.0" and platform_release < "24.0.0" diff --git a/requirements/portable/requirements_apple_silicon.txt b/requirements/portable/requirements_apple_silicon.txt index ec059716..18e1c506 100644 --- a/requirements/portable/requirements_apple_silicon.txt +++ b/requirements/portable/requirements_apple_silicon.txt @@ -15,6 +15,6 @@ sse-starlette==1.6.5 tiktoken # Mac wheels -https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.8.0/llama_cpp_binaries-0.8.0-py3-none-macosx_15_0_arm64.whl; platform_system == "Darwin" and platform_release >= "24.0.0" and platform_release < "25.0.0" -https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.8.0/llama_cpp_binaries-0.8.0-py3-none-macosx_14_0_arm64.whl; platform_system == "Darwin" and platform_release >= "23.0.0" and platform_release < "24.0.0" -https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.8.0/llama_cpp_binaries-0.8.0-py3-none-macosx_13_0_arm64.whl; platform_system == "Darwin" and platform_release >= "22.0.0" and platform_release < "23.0.0" +https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.12.0/llama_cpp_binaries-0.12.0-py3-none-macosx_15_0_arm64.whl; platform_system == "Darwin" and platform_release >= "24.0.0" and platform_release < "25.0.0" +https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.12.0/llama_cpp_binaries-0.12.0-py3-none-macosx_14_0_arm64.whl; platform_system == "Darwin" and platform_release >= "23.0.0" and platform_release < "24.0.0" +https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.12.0/llama_cpp_binaries-0.12.0-py3-none-macosx_13_0_arm64.whl; platform_system == "Darwin" and platform_release >= "22.0.0" and platform_release < "23.0.0" diff --git a/requirements/portable/requirements_cpu_only.txt b/requirements/portable/requirements_cpu_only.txt index d473b824..693f4712 100644 --- a/requirements/portable/requirements_cpu_only.txt +++ b/requirements/portable/requirements_cpu_only.txt @@ -15,5 +15,5 @@ sse-starlette==1.6.5 tiktoken # llama.cpp (CPU only, AVX2) -https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.8.0/llama_cpp_binaries-0.8.0+cpuavx2-py3-none-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" -https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.8.0/llama_cpp_binaries-0.8.0+cpuavx2-py3-none-win_amd64.whl; platform_system == "Windows" +https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.12.0/llama_cpp_binaries-0.12.0+cpuavx2-py3-none-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" +https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.12.0/llama_cpp_binaries-0.12.0+cpuavx2-py3-none-win_amd64.whl; platform_system == "Windows" diff --git a/requirements/portable/requirements_cpu_only_noavx2.txt b/requirements/portable/requirements_cpu_only_noavx2.txt index d3fffb43..8635d11e 100644 --- a/requirements/portable/requirements_cpu_only_noavx2.txt +++ b/requirements/portable/requirements_cpu_only_noavx2.txt @@ -15,5 +15,5 @@ sse-starlette==1.6.5 tiktoken # llama.cpp (CPU only, no AVX2) -https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.8.0/llama_cpp_binaries-0.8.0+cpuavx-py3-none-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" -https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.8.0/llama_cpp_binaries-0.8.0+cpuavx-py3-none-win_amd64.whl; platform_system == "Windows" +https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.12.0/llama_cpp_binaries-0.12.0+cpuavx-py3-none-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" +https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.12.0/llama_cpp_binaries-0.12.0+cpuavx-py3-none-win_amd64.whl; platform_system == "Windows" diff --git a/requirements/portable/requirements_noavx2.txt b/requirements/portable/requirements_noavx2.txt index cdfa6a01..e844596e 100644 --- a/requirements/portable/requirements_noavx2.txt +++ b/requirements/portable/requirements_noavx2.txt @@ -15,5 +15,5 @@ sse-starlette==1.6.5 tiktoken # CUDA wheels -https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.8.0/llama_cpp_binaries-0.8.0+cu124avx-py3-none-win_amd64.whl; platform_system == "Windows" -https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.8.0/llama_cpp_binaries-0.8.0+cu124avx-py3-none-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" +https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.12.0/llama_cpp_binaries-0.12.0+cu124avx-py3-none-win_amd64.whl; platform_system == "Windows" +https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.12.0/llama_cpp_binaries-0.12.0+cu124avx-py3-none-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" diff --git a/requirements/portable/requirements_vulkan.txt b/requirements/portable/requirements_vulkan.txt index 1a7ce6ed..9b7435d1 100644 --- a/requirements/portable/requirements_vulkan.txt +++ b/requirements/portable/requirements_vulkan.txt @@ -15,5 +15,5 @@ sse-starlette==1.6.5 tiktoken # CUDA wheels -https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.8.0/llama_cpp_binaries-0.8.0+vulkan-py3-none-win_amd64.whl; platform_system == "Windows" -https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.8.0/llama_cpp_binaries-0.8.0+vulkan-py3-none-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" +https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.12.0/llama_cpp_binaries-0.12.0+vulkan-py3-none-win_amd64.whl; platform_system == "Windows" +https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.12.0/llama_cpp_binaries-0.12.0+vulkan-py3-none-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" diff --git a/requirements/portable/requirements_vulkan_noavx2.txt b/requirements/portable/requirements_vulkan_noavx2.txt index 4737321d..513b7a15 100644 --- a/requirements/portable/requirements_vulkan_noavx2.txt +++ b/requirements/portable/requirements_vulkan_noavx2.txt @@ -15,5 +15,5 @@ sse-starlette==1.6.5 tiktoken # CUDA wheels -https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.8.0/llama_cpp_binaries-0.8.0+vulkanavx-py3-none-win_amd64.whl; platform_system == "Windows" -https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.8.0/llama_cpp_binaries-0.8.0+vulkanavx-py3-none-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" +https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.12.0/llama_cpp_binaries-0.12.0+vulkanavx-py3-none-win_amd64.whl; platform_system == "Windows" +https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.12.0/llama_cpp_binaries-0.12.0+vulkanavx-py3-none-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" diff --git a/server.py b/server.py index 169578a5..c22ed1f1 100644 --- a/server.py +++ b/server.py @@ -51,6 +51,7 @@ from modules.models import load_model, unload_model_if_idle from modules.models_settings import ( get_fallback_settings, get_model_metadata, + update_gpu_layers_and_vram, update_model_parameters ) from modules.shared import do_cmd_flags_warnings @@ -90,7 +91,7 @@ def create_interface(): 'instruction_template_str': shared.settings['instruction_template_str'], 'prompt_menu-default': shared.settings['prompt-default'], 'prompt_menu-notebook': shared.settings['prompt-notebook'], - 'filter_by_loader': shared.args.loader or 'All' + 'filter_by_loader': (shared.args.loader or 'All') if not shared.args.portable else 'llama.cpp' }) if Path("user_data/cache/pfp_character.png").exists(): @@ -127,7 +128,8 @@ def create_interface(): ui_parameters.create_ui(shared.settings['preset']) # Parameters tab ui_model_menu.create_ui() # Model tab - training.create_ui() # Training tab + if not shared.args.portable: + training.create_ui() # Training tab ui_session.create_ui() # Session tab # Generation events @@ -247,6 +249,20 @@ if __name__ == "__main__": model_settings = get_model_metadata(model_name) update_model_parameters(model_settings, initial=True) # hijack the command-line arguments + # Auto-adjust GPU layers if not provided by user and it's a llama.cpp model + if 'gpu_layers' not in shared.provided_arguments and shared.args.loader == 'llama.cpp' and 'gpu_layers' in model_settings: + vram_usage, adjusted_layers = update_gpu_layers_and_vram( + shared.args.loader, + model_name, + model_settings['gpu_layers'], + shared.args.ctx_size, + shared.args.cache_type, + auto_adjust=True, + for_ui=False + ) + + shared.args.gpu_layers = adjusted_layers + # Load the model shared.model, shared.tokenizer = load_model(model_name) if shared.args.lora: diff --git a/start_linux.sh b/start_linux.sh index 00082f07..e2b00558 100755 --- a/start_linux.sh +++ b/start_linux.sh @@ -1,10 +1,15 @@ #!/usr/bin/env bash +# environment isolation +export PYTHONNOUSERSITE=1 +unset PYTHONPATH +unset PYTHONHOME + cd "$(dirname "${BASH_SOURCE[0]}")" # Portable install case if [ -d "portable_env" ]; then - ./portable_env/bin/python3 server.py --api --auto-launch "$@" + ./portable_env/bin/python3 server.py --portable --api --auto-launch "$@" exit $? fi @@ -61,10 +66,6 @@ if [ ! -e "$INSTALL_ENV_DIR/bin/python" ]; then exit fi -# environment isolation -export PYTHONNOUSERSITE=1 -unset PYTHONPATH -unset PYTHONHOME export CUDA_PATH="$INSTALL_ENV_DIR" export CUDA_HOME="$CUDA_PATH" diff --git a/start_macos.sh b/start_macos.sh index 628f59cc..bff11bc1 100755 --- a/start_macos.sh +++ b/start_macos.sh @@ -1,10 +1,15 @@ #!/bin/bash +# environment isolation +export PYTHONNOUSERSITE=1 +unset PYTHONPATH +unset PYTHONHOME + cd "$(dirname "${BASH_SOURCE[0]}")" # Portable install case if [ -d "portable_env" ]; then - ./portable_env/bin/python3 server.py --api --auto-launch --api-port 5005 "$@" + ./portable_env/bin/python3 server.py --portable --api --auto-launch --api-port 5005 "$@" exit $? fi @@ -61,10 +66,6 @@ if [ ! -e "$INSTALL_ENV_DIR/bin/python" ]; then exit fi -# environment isolation -export PYTHONNOUSERSITE=1 -unset PYTHONPATH -unset PYTHONHOME export CUDA_PATH="$INSTALL_ENV_DIR" export CUDA_HOME="$CUDA_PATH" diff --git a/start_windows.bat b/start_windows.bat index 451b85e0..f5e66ec2 100755 --- a/start_windows.bat +++ b/start_windows.bat @@ -1,11 +1,16 @@ @echo off setlocal enabledelayedexpansion +@rem environment isolation +set PYTHONNOUSERSITE=1 +set PYTHONPATH= +set PYTHONHOME= + cd /D "%~dp0" @rem Portable install case if exist "portable_env" ( - .\portable_env\python.exe server.py --api --auto-launch %* + .\portable_env\python.exe server.py --portable --api --auto-launch %* exit /b %errorlevel% ) @@ -87,10 +92,6 @@ if not exist "%INSTALL_ENV_DIR%" ( @rem check if conda environment was actually created if not exist "%INSTALL_ENV_DIR%\python.exe" ( echo. && echo Conda environment is empty. && goto end ) -@rem environment isolation -set PYTHONNOUSERSITE=1 -set PYTHONPATH= -set PYTHONHOME= set "CUDA_PATH=%INSTALL_ENV_DIR%" set "CUDA_HOME=%CUDA_PATH%" diff --git a/user_data/settings-template.yaml b/user_data/settings-template.yaml index 20896da3..db481e84 100644 --- a/user_data/settings-template.yaml +++ b/user_data/settings-template.yaml @@ -18,7 +18,6 @@ max_new_tokens_min: 1 max_new_tokens_max: 4096 prompt_lookup_num_tokens: 0 max_tokens_second: 0 -max_updates_second: 12 auto_max_new_tokens: true ban_eos_token: false add_bos_token: true @@ -31,7 +30,6 @@ seed: -1 custom_stopping_strings: '' custom_token_bans: '' negative_prompt: '' -autoload_model: false dark_theme: true default_extensions: [] instruction_template_str: |-