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No commits in common. "main" and "v4.3.2" have entirely different histories.
48 changed files with 325 additions and 609 deletions
7
.github/workflows/build-everything-tgw.yml
vendored
7
.github/workflows/build-everything-tgw.yml
vendored
|
|
@ -41,13 +41,6 @@ jobs:
|
|||
version: ${{ inputs.version }}
|
||||
config: 'os:ubuntu-22.04'
|
||||
|
||||
build_release_rocm_windows:
|
||||
name: ROCm Windows
|
||||
uses: ./.github/workflows/build-portable-release-rocm.yml
|
||||
with:
|
||||
version: ${{ inputs.version }}
|
||||
config: 'os:windows-2022'
|
||||
|
||||
build_release_rocm_linux:
|
||||
name: ROCm Linux
|
||||
uses: ./.github/workflows/build-portable-release-rocm.yml
|
||||
|
|
|
|||
|
|
@ -102,8 +102,8 @@ jobs:
|
|||
VERSION_CLEAN="${{ inputs.version }}"
|
||||
VERSION_CLEAN="${VERSION_CLEAN#v}"
|
||||
cd ..
|
||||
cp -r text-generation-webui "text-generation-webui-ik-${VERSION_CLEAN}"
|
||||
cd "text-generation-webui-ik-${VERSION_CLEAN}"
|
||||
cp -r text-generation-webui "text-generation-webui-${VERSION_CLEAN}"
|
||||
cd "text-generation-webui-${VERSION_CLEAN}"
|
||||
|
||||
# Remove extensions that need additional requirements
|
||||
allowed=("character_bias" "gallery" "sd_api_pictures")
|
||||
|
|
@ -133,10 +133,10 @@ jobs:
|
|||
echo "Downloading Python for $PLATFORM..."
|
||||
curl -L -o python-build.tar.gz "$PYTHON_URL"
|
||||
tar -xzf python-build.tar.gz
|
||||
mv python "text-generation-webui-ik-${VERSION_CLEAN}/portable_env"
|
||||
mv python "text-generation-webui-${VERSION_CLEAN}/portable_env"
|
||||
|
||||
# 3. Prepare requirements file based on CUDA version
|
||||
cd "text-generation-webui-ik-${VERSION_CLEAN}"
|
||||
cd "text-generation-webui-${VERSION_CLEAN}"
|
||||
if [[ "$CUDA_VERSION" == "13.1" ]]; then
|
||||
REQ_FILE="requirements/portable/requirements_ik_cuda131.txt"
|
||||
else
|
||||
|
|
@ -158,11 +158,11 @@ jobs:
|
|||
if [[ "$RUNNER_OS" == "Windows" ]]; then
|
||||
ARCHIVE_NAME="textgen-portable-ik-${VERSION_CLEAN}-${PLATFORM}-cuda${CUDA_VERSION}.zip"
|
||||
echo "Creating archive: $ARCHIVE_NAME"
|
||||
powershell -Command "Compress-Archive -Path text-generation-webui-ik-${VERSION_CLEAN} -DestinationPath $ARCHIVE_NAME"
|
||||
powershell -Command "Compress-Archive -Path text-generation-webui-${VERSION_CLEAN} -DestinationPath $ARCHIVE_NAME"
|
||||
else
|
||||
ARCHIVE_NAME="textgen-portable-ik-${VERSION_CLEAN}-${PLATFORM}-cuda${CUDA_VERSION}.tar.gz"
|
||||
echo "Creating archive: $ARCHIVE_NAME"
|
||||
tar czf "$ARCHIVE_NAME" "text-generation-webui-ik-${VERSION_CLEAN}"
|
||||
tar czf "$ARCHIVE_NAME" "text-generation-webui-${VERSION_CLEAN}"
|
||||
fi
|
||||
|
||||
- name: Upload files to a GitHub release
|
||||
|
|
|
|||
12
.github/workflows/build-portable-release-ik.yml
vendored
12
.github/workflows/build-portable-release-ik.yml
vendored
|
|
@ -101,8 +101,8 @@ jobs:
|
|||
VERSION_CLEAN="${{ inputs.version }}"
|
||||
VERSION_CLEAN="${VERSION_CLEAN#v}"
|
||||
cd ..
|
||||
cp -r text-generation-webui "text-generation-webui-ik-${VERSION_CLEAN}"
|
||||
cd "text-generation-webui-ik-${VERSION_CLEAN}"
|
||||
cp -r text-generation-webui "text-generation-webui-${VERSION_CLEAN}"
|
||||
cd "text-generation-webui-${VERSION_CLEAN}"
|
||||
|
||||
# Remove extensions that need additional requirements
|
||||
allowed=("character_bias" "gallery" "sd_api_pictures")
|
||||
|
|
@ -131,10 +131,10 @@ jobs:
|
|||
cd ..
|
||||
curl -L -o python-build.tar.gz "$PYTHON_URL"
|
||||
tar -xzf python-build.tar.gz
|
||||
mv python "text-generation-webui-ik-${VERSION_CLEAN}/portable_env"
|
||||
mv python "text-generation-webui-${VERSION_CLEAN}/portable_env"
|
||||
|
||||
# 3. Prepare requirements file
|
||||
cd "text-generation-webui-ik-${VERSION_CLEAN}"
|
||||
cd "text-generation-webui-${VERSION_CLEAN}"
|
||||
REQ_FILE="requirements/portable/requirements_ik_cpu_only.txt"
|
||||
echo "Using requirements file: $REQ_FILE"
|
||||
|
||||
|
|
@ -153,11 +153,11 @@ jobs:
|
|||
if [[ "$RUNNER_OS" == "Windows" ]]; then
|
||||
ARCHIVE_NAME="textgen-portable-ik-${VERSION_CLEAN}-${PLATFORM}.zip"
|
||||
echo "Creating archive: $ARCHIVE_NAME"
|
||||
powershell -Command "Compress-Archive -Path text-generation-webui-ik-${VERSION_CLEAN} -DestinationPath $ARCHIVE_NAME"
|
||||
powershell -Command "Compress-Archive -Path text-generation-webui-${VERSION_CLEAN} -DestinationPath $ARCHIVE_NAME"
|
||||
else
|
||||
ARCHIVE_NAME="textgen-portable-ik-${VERSION_CLEAN}-${PLATFORM}.tar.gz"
|
||||
echo "Creating archive: $ARCHIVE_NAME"
|
||||
tar czf "$ARCHIVE_NAME" "text-generation-webui-ik-${VERSION_CLEAN}"
|
||||
tar czf "$ARCHIVE_NAME" "text-generation-webui-${VERSION_CLEAN}"
|
||||
fi
|
||||
|
||||
- name: Upload files to a GitHub release
|
||||
|
|
|
|||
|
|
@ -24,9 +24,9 @@ A Gradio web UI for running Large Language Models locally. 100% private and offl
|
|||
## Features
|
||||
|
||||
- **Easy setup**: [Portable builds](https://github.com/oobabooga/text-generation-webui/releases) (zero setup, just unzip and run) for GGUF models on Windows/Linux/macOS, or a one-click installer for the full feature set.
|
||||
- **Multiple backends**: [llama.cpp](https://github.com/ggerganov/llama.cpp), [ik_llama.cpp](https://github.com/ikawrakow/ik_llama.cpp), [Transformers](https://github.com/huggingface/transformers), [ExLlamaV3](https://github.com/turboderp-org/exllamav3), and [TensorRT-LLM](https://github.com/NVIDIA/TensorRT-LLM). Switch between backends and models without restarting.
|
||||
- **Multiple backends**: [llama.cpp](https://github.com/ggerganov/llama.cpp), [Transformers](https://github.com/huggingface/transformers), [ExLlamaV3](https://github.com/turboderp-org/exllamav3), and [TensorRT-LLM](https://github.com/NVIDIA/TensorRT-LLM). Switch between backends and models without restarting.
|
||||
- **OpenAI/Anthropic-compatible API**: Chat, Completions, and Messages endpoints with tool-calling support. Use as a local drop-in replacement for the OpenAI/Anthropic APIs ([examples](https://github.com/oobabooga/text-generation-webui/wiki/12-%E2%80%90-OpenAI-API#examples)).
|
||||
- **Tool-calling**: Models can call custom functions during chat — web search, page fetching, math, and more. Each tool is a single `.py` file. MCP servers are also supported ([tutorial](https://github.com/oobabooga/text-generation-webui/wiki/Tool-Calling-Tutorial)).
|
||||
- **Tool-calling**: Models can call custom functions during chat — web search, page fetching, math, and more. Each tool is a single `.py` file, easy to create and extend ([tutorial](https://github.com/oobabooga/text-generation-webui/wiki/Tool-Calling-Tutorial)).
|
||||
- **Vision (multimodal)**: Attach images to messages for visual understanding ([tutorial](https://github.com/oobabooga/text-generation-webui/wiki/Multimodal-Tutorial)).
|
||||
- **File attachments**: Upload text files, PDF documents, and .docx documents to talk about their contents.
|
||||
- **Training**: Fine-tune LoRAs on multi-turn chat or raw text datasets. Supports resuming interrupted runs ([tutorial](https://github.com/oobabooga/text-generation-webui/wiki/05-%E2%80%90-Training-Tab)).
|
||||
|
|
|
|||
|
|
@ -13,12 +13,21 @@
|
|||
line-height: 28px !important;
|
||||
}
|
||||
|
||||
.dark .chat .message-body :is(p,li),
|
||||
.dark .chat .message-body :is(p,li,h1,h2,h3,h4,h5,h6),
|
||||
.dark .chat .message-body em:not(:is(h1,h2,h3,h4,h5,h6,b,strong) em),
|
||||
.dark .chat .message-body q:not(:is(h1,h2,h3,h4,h5,h6,b,strong) q) {
|
||||
color: #d1d5db !important;
|
||||
}
|
||||
|
||||
.chat .message-body :is(th, td),
|
||||
.prose hr {
|
||||
border-color: #40404096 !important;
|
||||
}
|
||||
|
||||
.dark .chat .message-body :is(th, td),
|
||||
.dark .prose hr {
|
||||
border-color: rgb(255 255 255 / 30%) !important;
|
||||
}
|
||||
|
||||
.chat .message-body :is(p, ul, ol) {
|
||||
margin: 1.25em 0 !important;
|
||||
|
|
|
|||
177
css/main.css
177
css/main.css
|
|
@ -22,17 +22,6 @@
|
|||
font-style: italic;
|
||||
}
|
||||
|
||||
/* Hide spin buttons on number inputs (look bad on Windows) */
|
||||
input[type="number"]::-webkit-outer-spin-button,
|
||||
input[type="number"]::-webkit-inner-spin-button {
|
||||
-webkit-appearance: none;
|
||||
margin: 0;
|
||||
}
|
||||
|
||||
input[type="number"] {
|
||||
-moz-appearance: textfield;
|
||||
}
|
||||
|
||||
.padded.svelte-12cmxck {
|
||||
padding: 3px 0;
|
||||
}
|
||||
|
|
@ -257,8 +246,8 @@ button {
|
|||
|
||||
.pretty_scrollbar::-webkit-scrollbar,
|
||||
#image-history-gallery > :nth-child(2)::-webkit-scrollbar {
|
||||
width: 7px;
|
||||
height: 7px;
|
||||
width: 8px;
|
||||
height: 8px;
|
||||
}
|
||||
|
||||
.pretty_scrollbar::-webkit-scrollbar-track,
|
||||
|
|
@ -271,7 +260,7 @@ button {
|
|||
#image-history-gallery > :nth-child(2)::-webkit-scrollbar-thumb,
|
||||
#image-history-gallery > :nth-child(2)::-webkit-scrollbar-thumb:hover {
|
||||
background: var(--neutral-300);
|
||||
border-radius: 9999px;
|
||||
border-radius: 30px;
|
||||
}
|
||||
|
||||
.dark .pretty_scrollbar::-webkit-scrollbar-thumb,
|
||||
|
|
@ -279,17 +268,18 @@ button {
|
|||
.dark #image-history-gallery > :nth-child(2)::-webkit-scrollbar-thumb,
|
||||
.dark #image-history-gallery > :nth-child(2)::-webkit-scrollbar-thumb:hover {
|
||||
background: rgb(255 255 255 / 6.25%);
|
||||
border-radius: 9999px;
|
||||
border-radius: 30px;
|
||||
}
|
||||
|
||||
.pretty_scrollbar::-webkit-resizer,
|
||||
#image-history-gallery > :nth-child(2)::-webkit-resizer {
|
||||
background: transparent;
|
||||
background: #d2d2d8;
|
||||
}
|
||||
|
||||
.dark .pretty_scrollbar::-webkit-resizer,
|
||||
.dark #image-history-gallery > :nth-child(2)::-webkit-resizer {
|
||||
background: transparent;
|
||||
background: rgb(255 255 255 / 10%);
|
||||
border-radius: 10px;
|
||||
}
|
||||
|
||||
.pretty_scrollbar::-webkit-scrollbar-corner,
|
||||
|
|
@ -446,25 +436,15 @@ audio {
|
|||
.dark .message-body h4,
|
||||
.dark .message-body h5,
|
||||
.dark .message-body h6 {
|
||||
color: #e8e8e8 !important;
|
||||
color: white !important;
|
||||
}
|
||||
|
||||
.message-body blockquote {
|
||||
border-left-width: 4px;
|
||||
border-left-color: var(--border-color-primary);
|
||||
}
|
||||
|
||||
.message-body h1,
|
||||
.message-body h2,
|
||||
.message-body h3,
|
||||
.message-body h4,
|
||||
.message-body h5,
|
||||
.message-body h6 {
|
||||
color: #1a1a1a;
|
||||
.dark .message-body blockquote {
|
||||
border-left-color: rgb(255 255 255 / 30%);
|
||||
}
|
||||
|
||||
.message-body h1 {
|
||||
font-weight: 700;
|
||||
font-weight: 800;
|
||||
font-size: 2.25em;
|
||||
margin-top: 0;
|
||||
margin-bottom: 0.8888889em;
|
||||
|
|
@ -496,13 +476,13 @@ audio {
|
|||
}
|
||||
|
||||
.message-body h5 {
|
||||
font-weight: 600;
|
||||
font-weight: normal;
|
||||
font-size: 1em;
|
||||
margin: 0;
|
||||
}
|
||||
|
||||
.message-body h6 {
|
||||
font-weight: 600;
|
||||
font-weight: normal;
|
||||
font-size: 1em;
|
||||
margin: 0;
|
||||
}
|
||||
|
|
@ -610,7 +590,7 @@ audio {
|
|||
}
|
||||
|
||||
#chat-input textarea::-webkit-scrollbar {
|
||||
width: 7px;
|
||||
width: 8px;
|
||||
}
|
||||
|
||||
#chat-input textarea::-webkit-scrollbar-track {
|
||||
|
|
@ -619,7 +599,7 @@ audio {
|
|||
|
||||
#chat-input textarea::-webkit-scrollbar-thumb {
|
||||
background: var(--neutral-300);
|
||||
border-radius: 9999px;
|
||||
border-radius: 30px;
|
||||
}
|
||||
|
||||
.dark #chat-input textarea::-webkit-scrollbar-thumb {
|
||||
|
|
@ -653,10 +633,6 @@ audio {
|
|||
background: transparent;
|
||||
}
|
||||
|
||||
#chat-input .thumbnails {
|
||||
padding-top: 3px;
|
||||
}
|
||||
|
||||
.chat-input-positioned {
|
||||
max-width: 54rem;
|
||||
left: 50%;
|
||||
|
|
@ -759,30 +735,7 @@ audio {
|
|||
|
||||
.hover-element {
|
||||
position: relative;
|
||||
padding-top: 4px;
|
||||
}
|
||||
|
||||
#hover-element-button {
|
||||
display: flex;
|
||||
align-items: center;
|
||||
justify-content: center;
|
||||
width: 32px;
|
||||
height: 32px;
|
||||
border-radius: 0.5rem;
|
||||
cursor: pointer;
|
||||
color: gray;
|
||||
}
|
||||
|
||||
#hover-element-button:hover {
|
||||
background-color: var(--background-fill-secondary);
|
||||
}
|
||||
|
||||
#hover-element-button svg {
|
||||
color: inherit;
|
||||
}
|
||||
|
||||
.dark #hover-element-button:hover {
|
||||
background-color: var(--selected-item-color-dark);
|
||||
font-size: 24px;
|
||||
}
|
||||
|
||||
.hover-menu {
|
||||
|
|
@ -790,40 +743,27 @@ audio {
|
|||
position: absolute;
|
||||
bottom: 100%;
|
||||
left: 0;
|
||||
background: white;
|
||||
border: 1px solid rgba(0, 0, 0, 0.1);
|
||||
box-shadow: 0 4px 16px rgb(0 0 0 / 12%), 0 1px 3px rgb(0 0 0 / 8%);
|
||||
border-radius: 0.75rem;
|
||||
box-shadow: 0 2px 12px rgb(0 0 0 / 15%);
|
||||
border-radius: 0.5rem;
|
||||
z-index: 10000;
|
||||
min-width: 330px;
|
||||
flex-direction: column;
|
||||
padding: 4px;
|
||||
}
|
||||
|
||||
.hover-menu::before {
|
||||
content: '';
|
||||
position: absolute;
|
||||
top: 100%;
|
||||
left: 0;
|
||||
width: 100%;
|
||||
height: 8px;
|
||||
}
|
||||
|
||||
.hover-menu > * {
|
||||
border: none !important;
|
||||
box-shadow: none !important;
|
||||
overflow: hidden;
|
||||
}
|
||||
|
||||
.hover-menu button {
|
||||
width: 100%;
|
||||
background: transparent !important;
|
||||
border: none !important;
|
||||
border-radius: 0.5rem !important;
|
||||
background: white !important;
|
||||
border-radius: 0 !important;
|
||||
justify-content: space-between;
|
||||
margin: 0 !important;
|
||||
height: 36px;
|
||||
font-weight: 500;
|
||||
box-shadow: none !important;
|
||||
border-color: transparent !important;
|
||||
transition: background-color 0.15s ease;
|
||||
}
|
||||
|
||||
.hover-menu button:not(#clear-history-confirm) {
|
||||
border-bottom: 0 !important;
|
||||
}
|
||||
|
||||
.hover-menu button:hover {
|
||||
|
|
@ -835,26 +775,19 @@ audio {
|
|||
}
|
||||
|
||||
#show-controls {
|
||||
background-color: transparent;
|
||||
border: none !important;
|
||||
background-color: white;
|
||||
border-color: transparent !important;
|
||||
height: 36px;
|
||||
border-radius: 0.5rem;
|
||||
border-radius: 0;
|
||||
border-bottom: 0 !important;
|
||||
padding-top: 3px;
|
||||
padding-left: 4px;
|
||||
display: flex;
|
||||
font-weight: normal;
|
||||
}
|
||||
|
||||
#show-controls:hover {
|
||||
background-color: #dbeafe;
|
||||
}
|
||||
|
||||
.dark #show-controls {
|
||||
background-color: transparent;
|
||||
}
|
||||
|
||||
.dark #show-controls:hover {
|
||||
background-color: var(--selected-item-color-dark);
|
||||
background-color: var(--darker-gray);
|
||||
}
|
||||
|
||||
#show-controls label {
|
||||
|
|
@ -864,12 +797,12 @@ audio {
|
|||
width: 100%;
|
||||
padding-right: 12px;
|
||||
gap: 10px;
|
||||
font-weight: 500;
|
||||
font-weight: 600;
|
||||
color: var(--button-secondary-text-color);
|
||||
}
|
||||
|
||||
#show-controls label input {
|
||||
margin-top: 5px;
|
||||
margin-top: 4px;
|
||||
}
|
||||
|
||||
.transparent-substring {
|
||||
|
|
@ -909,7 +842,7 @@ audio {
|
|||
}
|
||||
|
||||
#chat-input-row {
|
||||
padding: 0.5rem 1rem 1rem;
|
||||
padding: 1rem;
|
||||
}
|
||||
|
||||
#chat-col {
|
||||
|
|
@ -1275,14 +1208,9 @@ audio {
|
|||
color: #9ca3af;
|
||||
}
|
||||
|
||||
.dark .hover-menu {
|
||||
background: var(--darker-gray);
|
||||
border-color: transparent;
|
||||
box-shadow: 0 4px 16px rgb(0 0 0 / 40%);
|
||||
}
|
||||
|
||||
.dark .hover-menu button {
|
||||
background-color: transparent !important;
|
||||
border-color: var(--border-color-primary);
|
||||
background-color: var(--darker-gray) !important;
|
||||
}
|
||||
|
||||
.dark #chat-controls,
|
||||
|
|
@ -1444,7 +1372,8 @@ audio {
|
|||
}
|
||||
|
||||
.footer-button svg {
|
||||
stroke: rgb(140 140 148);
|
||||
stroke: rgb(156 163 175);
|
||||
transition: stroke 0.2s;
|
||||
}
|
||||
|
||||
.footer-button:hover svg {
|
||||
|
|
@ -1459,12 +1388,12 @@ audio {
|
|||
stroke: rgb(209 213 219);
|
||||
}
|
||||
|
||||
.block:has(> .label-wrap) {
|
||||
.tgw-accordion {
|
||||
padding: 10px 12px !important;
|
||||
border: 1px solid #d2d2d8;
|
||||
}
|
||||
|
||||
.dark .block:has(> .label-wrap) {
|
||||
.dark .tgw-accordion {
|
||||
border: 1px solid var(--border-color-dark);
|
||||
}
|
||||
|
||||
|
|
@ -1974,24 +1903,14 @@ table, tr, td, th, thead {
|
|||
border: 0;
|
||||
}
|
||||
|
||||
.prose hr {
|
||||
border-color: var(--border-color-primary);
|
||||
}
|
||||
|
||||
td + td,
|
||||
th + th {
|
||||
border-left: 1px solid var(--border-color-primary) !important;
|
||||
}
|
||||
th + th { border-left: 1px solid; }
|
||||
|
||||
tr + tr td,
|
||||
tr + tr th {
|
||||
border-top: 1px solid var(--border-color-primary) !important;
|
||||
}
|
||||
tr + tr th { border-top: 1px solid; }
|
||||
|
||||
thead + tbody tr:first-child td,
|
||||
thead + tbody tr:first-child th {
|
||||
border-top: 1px solid var(--border-color-primary) !important;
|
||||
}
|
||||
thead + tbody tr:first-child th { border-top: 1px solid; }
|
||||
|
||||
/* ------------------------------------------------
|
||||
Tools CheckboxGroup - vertical DragDrop-like style
|
||||
|
|
@ -2023,8 +1942,8 @@ thead + tbody tr:first-child th {
|
|||
|
||||
/* Pretty scrollbar for the tools list */
|
||||
#tools-group .wrap::-webkit-scrollbar {
|
||||
width: 7px;
|
||||
height: 7px;
|
||||
width: 8px;
|
||||
height: 8px;
|
||||
}
|
||||
|
||||
#tools-group .wrap::-webkit-scrollbar-track {
|
||||
|
|
@ -2034,13 +1953,13 @@ thead + tbody tr:first-child th {
|
|||
#tools-group .wrap::-webkit-scrollbar-thumb,
|
||||
#tools-group .wrap::-webkit-scrollbar-thumb:hover {
|
||||
background: var(--neutral-300);
|
||||
border-radius: 9999px;
|
||||
border-radius: 30px;
|
||||
}
|
||||
|
||||
.dark #tools-group .wrap::-webkit-scrollbar-thumb,
|
||||
.dark #tools-group .wrap::-webkit-scrollbar-thumb:hover {
|
||||
background: rgb(255 255 255 / 6.25%);
|
||||
border-radius: 9999px;
|
||||
border-radius: 30px;
|
||||
}
|
||||
|
||||
#tools-group .wrap::-webkit-scrollbar-corner {
|
||||
|
|
|
|||
|
|
@ -232,17 +232,6 @@ curl -k http://127.0.0.1:5000/v1/internal/model/load \
|
|||
}'
|
||||
```
|
||||
|
||||
You can also set a default instruction template for all subsequent API requests by passing `instruction_template` (a template name from `user_data/instruction-templates/`) or `instruction_template_str` (a raw Jinja2 string):
|
||||
|
||||
```shell
|
||||
curl -k http://127.0.0.1:5000/v1/internal/model/load \
|
||||
-H "Content-Type: application/json" \
|
||||
-d '{
|
||||
"model_name": "Qwen_Qwen3-0.6B-Q4_K_M.gguf",
|
||||
"instruction_template": "Alpaca"
|
||||
}'
|
||||
```
|
||||
|
||||
#### Python chat example
|
||||
|
||||
```python
|
||||
|
|
|
|||
|
|
@ -80,19 +80,6 @@ def execute(arguments):
|
|||
|
||||
You can open the built-in tools in `user_data/tools/` for more examples.
|
||||
|
||||
## MCP servers
|
||||
|
||||
You can connect to remote [MCP (Model Context Protocol)](https://modelcontextprotocol.io/) servers to use their tools alongside local ones.
|
||||
|
||||
In the chat sidebar, open the **MCP servers** accordion and enter one server URL per line. For servers that require authentication, append headers after the URL separated by commas:
|
||||
|
||||
```
|
||||
https://example.com/mcp
|
||||
https://other.com/mcp,Authorization: Bearer sk-xxx
|
||||
```
|
||||
|
||||
All tools from the configured servers are automatically discovered and made available to the model during generation. If an MCP tool has the same name as a selected local tool, the local tool takes priority.
|
||||
|
||||
## Tool calling over the API
|
||||
|
||||
Tool calling over the API follows the [OpenAI API](https://platform.openai.com/docs/guides/function-calling) convention. Define your tools, send them with your messages, and handle tool calls in a loop until the model gives a final answer.
|
||||
|
|
|
|||
44
js/main.js
44
js/main.js
|
|
@ -309,19 +309,18 @@ for (let i = 0; i < slimDropdownElements.length; i++) {
|
|||
// https://github.com/SillyTavern/SillyTavern/blob/6c8bd06308c69d51e2eb174541792a870a83d2d6/public/script.js
|
||||
//------------------------------------------------
|
||||
var buttonsInChat = document.querySelectorAll("#chat-tab #chat-buttons button, #chat-tab #chat-buttons #show-controls");
|
||||
var hoverContainer = document.getElementById("gr-hover-container");
|
||||
var button = document.getElementById("hover-element-button");
|
||||
var menu = document.getElementById("hover-menu");
|
||||
var istouchscreen = (navigator.maxTouchPoints > 0) || "ontouchstart" in document.documentElement;
|
||||
|
||||
function showMenu() {
|
||||
menu.style.display = "flex";
|
||||
menu.style.display = "flex"; // Show the menu
|
||||
}
|
||||
|
||||
function hideMenu() {
|
||||
menu.style.display = "none";
|
||||
menu.style.display = "none"; // Hide the menu
|
||||
if (!istouchscreen) {
|
||||
document.querySelector("#chat-input textarea").focus();
|
||||
document.querySelector("#chat-input textarea").focus(); // Focus on the chat input
|
||||
}
|
||||
}
|
||||
|
||||
|
|
@ -330,6 +329,7 @@ if (buttonsInChat.length > 0) {
|
|||
const thisButton = buttonsInChat[i];
|
||||
menu.appendChild(thisButton);
|
||||
|
||||
// Only apply transformations to button elements
|
||||
if (thisButton.tagName.toLowerCase() === "button") {
|
||||
thisButton.addEventListener("click", () => {
|
||||
hideMenu();
|
||||
|
|
@ -339,6 +339,7 @@ if (buttonsInChat.length > 0) {
|
|||
const matches = buttonText.match(/(\(.*?\))/);
|
||||
|
||||
if (matches && matches.length > 1) {
|
||||
// Apply the transparent-substring class to the matched substring
|
||||
const substring = matches[1];
|
||||
const newText = buttonText.replace(substring, ` <span class="transparent-substring">${substring.slice(1, -1)}</span>`);
|
||||
thisButton.innerHTML = newText;
|
||||
|
|
@ -347,19 +348,16 @@ if (buttonsInChat.length > 0) {
|
|||
}
|
||||
}
|
||||
|
||||
var menuInteracting = false;
|
||||
function isMouseOverButtonOrMenu() {
|
||||
return menu.matches(":hover") || button.matches(":hover");
|
||||
}
|
||||
|
||||
hoverContainer.addEventListener("mouseenter", function () {
|
||||
button.addEventListener("mouseenter", function () {
|
||||
if (!istouchscreen) {
|
||||
showMenu();
|
||||
}
|
||||
});
|
||||
|
||||
hoverContainer.addEventListener("mousedown", function () {
|
||||
menuInteracting = true;
|
||||
setTimeout(function () { menuInteracting = false; }, 300);
|
||||
});
|
||||
|
||||
button.addEventListener("click", function () {
|
||||
if (menu.style.display === "flex") {
|
||||
hideMenu();
|
||||
|
|
@ -369,20 +367,24 @@ button.addEventListener("click", function () {
|
|||
}
|
||||
});
|
||||
|
||||
hoverContainer.addEventListener("mouseleave", function () {
|
||||
if (!istouchscreen) {
|
||||
setTimeout(function () {
|
||||
if (!hoverContainer.matches(":hover") && !menu.matches(":hover")) {
|
||||
hideMenu();
|
||||
}
|
||||
}, 50);
|
||||
}
|
||||
});
|
||||
// Delay to prevent menu hiding when the mouse leaves the button or menu
|
||||
function delayedHideMenu() {
|
||||
setTimeout(function () {
|
||||
if (!isMouseOverButtonOrMenu()) {
|
||||
hideMenu();
|
||||
}
|
||||
}, 100);
|
||||
}
|
||||
|
||||
// Add event listener for mouseleave on the button
|
||||
button.addEventListener("mouseleave", delayedHideMenu);
|
||||
// Add event listener for mouseleave on the menu
|
||||
menu.addEventListener("mouseleave", delayedHideMenu);
|
||||
|
||||
// Add event listener for click anywhere in the document
|
||||
document.addEventListener("click", function (event) {
|
||||
// Check if the click is outside the button/menu and the menu is visible
|
||||
if (!menuInteracting && !event.target.closest("#gr-hover-container") && menu.style.display === "flex") {
|
||||
if (!isMouseOverButtonOrMenu() && menu.style.display === "flex") {
|
||||
hideMenu();
|
||||
}
|
||||
|
||||
|
|
|
|||
|
|
@ -6,7 +6,6 @@ from transformers import AutoModel
|
|||
from .errors import ServiceUnavailableError
|
||||
from .utils import debug_msg, float_list_to_base64
|
||||
from modules.logging_colors import logger
|
||||
from modules import shared
|
||||
|
||||
embeddings_params_initialized = False
|
||||
|
||||
|
|
@ -42,7 +41,7 @@ def load_embedding_model(model: str):
|
|||
try:
|
||||
logger.info(f"Try embedding model: {model} on {embeddings_device}")
|
||||
if 'jina-embeddings' in model:
|
||||
embeddings_model = AutoModel.from_pretrained(model, trust_remote_code=shared.args.trust_remote_code)
|
||||
embeddings_model = AutoModel.from_pretrained(model, trust_remote_code=True) # trust_remote_code is needed to use the encode method
|
||||
embeddings_model = embeddings_model.to(embeddings_device)
|
||||
else:
|
||||
embeddings_model = SentenceTransformer(model, device=embeddings_device)
|
||||
|
|
|
|||
|
|
@ -4,11 +4,8 @@ OpenAI-compatible image generation using local diffusion models.
|
|||
|
||||
import base64
|
||||
import io
|
||||
import json
|
||||
import time
|
||||
|
||||
from PIL.PngImagePlugin import PngInfo
|
||||
|
||||
from .errors import ServiceUnavailableError
|
||||
from modules import shared
|
||||
|
||||
|
|
@ -18,7 +15,7 @@ def generations(request):
|
|||
Generate images using the loaded diffusion model.
|
||||
Returns dict with 'created' timestamp and 'data' list of images.
|
||||
"""
|
||||
from modules.ui_image_generation import build_generation_metadata, generate
|
||||
from modules.ui_image_generation import generate
|
||||
|
||||
if shared.image_model is None:
|
||||
raise ServiceUnavailableError("No image model loaded. Load a model via the UI first.")
|
||||
|
|
@ -49,18 +46,10 @@ def generations(request):
|
|||
if not images:
|
||||
raise ServiceUnavailableError("Image generation failed or produced no images.")
|
||||
|
||||
# Build response with per-batch metadata (seed increments per batch)
|
||||
base_seed = state.get('image_seed_resolved', state['image_seed'])
|
||||
batch_size = int(state['image_batch_size'])
|
||||
|
||||
# Build response
|
||||
resp = {'created': int(time.time()), 'data': []}
|
||||
for idx, img in enumerate(images):
|
||||
batch_seed = base_seed + idx // batch_size
|
||||
metadata = build_generation_metadata(state, batch_seed)
|
||||
metadata_json = json.dumps(metadata, ensure_ascii=False)
|
||||
png_info = PngInfo()
|
||||
png_info.add_text("image_gen_settings", metadata_json)
|
||||
b64 = _image_to_base64(img, png_info)
|
||||
for img in images:
|
||||
b64 = _image_to_base64(img)
|
||||
|
||||
image_obj = {'revised_prompt': request.prompt}
|
||||
|
||||
|
|
@ -74,7 +63,7 @@ def generations(request):
|
|||
return resp
|
||||
|
||||
|
||||
def _image_to_base64(image, png_info=None) -> str:
|
||||
def _image_to_base64(image) -> str:
|
||||
buffered = io.BytesIO()
|
||||
image.save(buffered, format="PNG", pnginfo=png_info)
|
||||
image.save(buffered, format="PNG")
|
||||
return base64.b64encode(buffered.getvalue()).decode('utf-8')
|
||||
|
|
|
|||
|
|
@ -2,7 +2,7 @@ from modules import loaders, shared
|
|||
from modules.logging_colors import logger
|
||||
from modules.LoRA import add_lora_to_model
|
||||
from modules.models import load_model, unload_model
|
||||
from modules.models_settings import get_model_metadata, load_instruction_template, update_model_parameters
|
||||
from modules.models_settings import get_model_metadata, update_model_parameters
|
||||
from modules.utils import get_available_loras, get_available_models
|
||||
|
||||
|
||||
|
|
@ -42,10 +42,12 @@ def model_info_dict(model_name: str) -> dict:
|
|||
|
||||
def _load_model(data):
|
||||
model_name = data["model_name"]
|
||||
args = data.get("args")
|
||||
args = data["args"]
|
||||
settings = data["settings"]
|
||||
|
||||
unload_model()
|
||||
model_settings = get_model_metadata(model_name)
|
||||
update_model_parameters(model_settings)
|
||||
|
||||
# Update shared.args with custom model loading settings
|
||||
# Security: only allow keys that correspond to model loading
|
||||
|
|
@ -53,16 +55,6 @@ def _load_model(data):
|
|||
# flags like trust_remote_code or extra_flags to be set via the API.
|
||||
blocked_keys = {'extra_flags'}
|
||||
allowed_keys = set(loaders.list_model_elements()) - blocked_keys
|
||||
|
||||
# Reset all loader args to their startup values before applying new ones,
|
||||
# so settings from a previous API load don't leak into this one.
|
||||
# Include blocked keys in the reset (safe: restores startup value, not API-controlled).
|
||||
for k in allowed_keys | blocked_keys:
|
||||
if hasattr(shared.args, k) and hasattr(shared.original_args, k):
|
||||
setattr(shared.args, k, getattr(shared.original_args, k))
|
||||
|
||||
update_model_parameters(model_settings)
|
||||
|
||||
if args:
|
||||
for k in args:
|
||||
if k in allowed_keys and hasattr(shared.args, k):
|
||||
|
|
@ -70,12 +62,15 @@ def _load_model(data):
|
|||
|
||||
shared.model, shared.tokenizer = load_model(model_name)
|
||||
|
||||
if data.get("instruction_template_str") is not None:
|
||||
shared.settings['instruction_template_str'] = data["instruction_template_str"]
|
||||
logger.info("INSTRUCTION TEMPLATE: set to custom Jinja2 string")
|
||||
elif data.get("instruction_template") is not None:
|
||||
shared.settings['instruction_template_str'] = load_instruction_template(data["instruction_template"])
|
||||
logger.info(f"INSTRUCTION TEMPLATE: {data['instruction_template']}")
|
||||
# Update shared.settings with custom generation defaults
|
||||
if settings:
|
||||
for k in settings:
|
||||
if k in shared.settings:
|
||||
shared.settings[k] = settings[k]
|
||||
if k == 'truncation_length':
|
||||
logger.info(f"CONTEXT LENGTH (UPDATED): {shared.settings['truncation_length']}")
|
||||
elif k == 'instruction_template':
|
||||
logger.info(f"INSTRUCTION TEMPLATE (UPDATED): {shared.settings['instruction_template']}")
|
||||
|
||||
|
||||
def list_loras():
|
||||
|
|
|
|||
|
|
@ -475,8 +475,10 @@ async def handle_list_models():
|
|||
@app.post("/v1/internal/model/load", dependencies=check_admin_key)
|
||||
async def handle_load_model(request_data: LoadModelRequest):
|
||||
'''
|
||||
The "args" parameter can be used to modify loader flags before loading
|
||||
a model. Example:
|
||||
This endpoint is experimental and may change in the future.
|
||||
|
||||
The "args" parameter can be used to modify flags like "--load-in-4bit"
|
||||
or "--n-gpu-layers" before loading a model. Example:
|
||||
|
||||
```
|
||||
"args": {
|
||||
|
|
@ -485,13 +487,18 @@ async def handle_load_model(request_data: LoadModelRequest):
|
|||
}
|
||||
```
|
||||
|
||||
Loader args are reset to their startup defaults between loads, so
|
||||
settings from a previous load do not leak into the next one.
|
||||
Note that those settings will remain after loading the model. So you
|
||||
may need to change them back to load a second model.
|
||||
|
||||
The "instruction_template" parameter sets the default instruction
|
||||
template by name (from user_data/instruction-templates/). The
|
||||
"instruction_template_str" parameter sets it as a raw Jinja2 string
|
||||
and takes precedence over "instruction_template".
|
||||
The "settings" parameter is also a dict but with keys for the
|
||||
shared.settings object. It can be used to modify the default instruction
|
||||
template like this:
|
||||
|
||||
```
|
||||
"settings": {
|
||||
"instruction_template": "Alpaca"
|
||||
}
|
||||
```
|
||||
'''
|
||||
|
||||
try:
|
||||
|
|
@ -537,8 +544,8 @@ async def handle_unload_loras():
|
|||
def find_available_port(starting_port):
|
||||
"""Try the starting port, then find an available one if it's taken."""
|
||||
try:
|
||||
# Try to create a socket with the starting port
|
||||
with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as s:
|
||||
s.setsockopt(socket.SOL_SOCKET, socket.SO_REUSEADDR, 1)
|
||||
s.bind(('', starting_port))
|
||||
return starting_port
|
||||
except OSError:
|
||||
|
|
@ -563,7 +570,7 @@ def run_server():
|
|||
server_addrs.append(shared.args.listen_host)
|
||||
else:
|
||||
if os.environ.get('OPENEDAI_ENABLE_IPV6', shared.args.api_enable_ipv6):
|
||||
server_addrs.append('::' if shared.args.listen else '::1')
|
||||
server_addrs.append('[::]' if shared.args.listen else '[::1]')
|
||||
if not os.environ.get('OPENEDAI_DISABLE_IPV4', shared.args.api_disable_ipv4):
|
||||
server_addrs.append('0.0.0.0' if shared.args.listen else '127.0.0.1')
|
||||
|
||||
|
|
@ -580,7 +587,7 @@ def run_server():
|
|||
)
|
||||
else:
|
||||
url_proto = 'https://' if (ssl_certfile and ssl_keyfile) else 'http://'
|
||||
urls = [f'{url_proto}[{addr}]:{port}/v1' if ':' in addr else f'{url_proto}{addr}:{port}/v1' for addr in server_addrs]
|
||||
urls = [f'{url_proto}{addr}:{port}/v1' for addr in server_addrs]
|
||||
if len(urls) > 1:
|
||||
logger.info('OpenAI/Anthropic-compatible API URLs:\n\n' + '\n'.join(urls) + '\n')
|
||||
else:
|
||||
|
|
|
|||
|
|
@ -271,8 +271,7 @@ class ModelListResponse(BaseModel):
|
|||
class LoadModelRequest(BaseModel):
|
||||
model_name: str
|
||||
args: dict | None = None
|
||||
instruction_template: str | None = Field(default=None, description="An instruction template defined under text-generation-webui/user_data/instruction-templates. Sets the default template for all subsequent API requests.")
|
||||
instruction_template_str: str | None = Field(default=None, description="A Jinja2 instruction template string. If set, takes precedence over instruction_template.")
|
||||
settings: dict | None = None
|
||||
|
||||
|
||||
class LoraListResponse(BaseModel):
|
||||
|
|
|
|||
|
|
@ -568,24 +568,13 @@ def generate_chat_prompt(user_input, state, **kwargs):
|
|||
encoded_length = get_encoded_length(prompt)
|
||||
while len(messages) > 0 and encoded_length > max_length:
|
||||
|
||||
# Remove old message, save system message
|
||||
if len(messages) > 2 and messages[0]['role'] == 'system':
|
||||
pop_idx = 1
|
||||
messages.pop(1)
|
||||
|
||||
# Remove old message when no system message is present
|
||||
elif len(messages) > 1 and messages[0]['role'] != 'system':
|
||||
pop_idx = 0
|
||||
else:
|
||||
pop_idx = None
|
||||
|
||||
if pop_idx is not None:
|
||||
messages.pop(pop_idx)
|
||||
|
||||
# Remove orphaned tool-call/tool-result messages that
|
||||
# would be invalid without their partner.
|
||||
while pop_idx < len(messages):
|
||||
msg = messages[pop_idx]
|
||||
if msg.get('role') == 'tool' or (msg.get('role') == 'assistant' and msg.get('tool_calls')):
|
||||
messages.pop(pop_idx)
|
||||
else:
|
||||
break
|
||||
messages.pop(0)
|
||||
|
||||
# Resort to truncating the user input
|
||||
else:
|
||||
|
|
@ -705,7 +694,7 @@ def get_stopping_strings(state):
|
|||
# Find positions of each message content
|
||||
first_user_end = prompt.find("first user message") + len("first user message")
|
||||
first_assistant_start = prompt.find("first assistant message")
|
||||
first_assistant_end = first_assistant_start + len("first assistant message")
|
||||
first_assistant_end = prompt.find("first assistant message") + len("first assistant message")
|
||||
second_user_start = prompt.find("second user message")
|
||||
second_assistant_end = prompt.find("second assistant message") + len("second assistant message")
|
||||
|
||||
|
|
@ -1194,7 +1183,7 @@ def chatbot_wrapper(text, state, regenerate=False, _continue=False, loading_mess
|
|||
# visible text from before buffering started so raw markup doesn't flash
|
||||
# in the UI. The internal text is left intact so the caller can still
|
||||
# parse tool calls from it.
|
||||
if is_stream and _check_tool_markers and streaming_tool_buffer_check(output['internal'][-1][1], markers=_streaming_markers, tool_names=_tool_names, check_bare_names=_check_bare_names, partial_match=False):
|
||||
if is_stream and _check_tool_markers and streaming_tool_buffer_check(output['internal'][-1][1], markers=_streaming_markers, tool_names=_tool_names, check_bare_names=_check_bare_names):
|
||||
output['visible'][-1][1] = _last_visible_before_tool_buffer or ''
|
||||
|
||||
yield output
|
||||
|
|
@ -1275,23 +1264,14 @@ def generate_chat_reply_wrapper(text, state, regenerate=False, _continue=False):
|
|||
|
||||
# Load tools if any are selected
|
||||
selected = state.get('selected_tools', [])
|
||||
mcp_servers = state.get('mcp_servers', '')
|
||||
parse_tool_call = None
|
||||
_tool_parsers = None
|
||||
if selected or mcp_servers:
|
||||
from modules.tool_use import load_tools, load_mcp_tools, execute_tool
|
||||
if selected:
|
||||
from modules.tool_use import load_tools, execute_tool
|
||||
from modules.tool_parsing import parse_tool_call, get_tool_call_id, detect_tool_call_format
|
||||
|
||||
if selected:
|
||||
tool_defs, tool_executors = load_tools(selected)
|
||||
if mcp_servers:
|
||||
mcp_defs, mcp_executors = load_mcp_tools(mcp_servers)
|
||||
for td in mcp_defs:
|
||||
fn = td['function']['name']
|
||||
if fn in tool_executors:
|
||||
logger.warning(f'MCP tool "{fn}" conflicts with a local tool. Skipping.')
|
||||
continue
|
||||
tool_defs.append(td)
|
||||
tool_executors[fn] = mcp_executors[fn]
|
||||
state['tools'] = tool_defs
|
||||
tool_func_names = [t['function']['name'] for t in tool_defs]
|
||||
_template_str = state.get('instruction_template_str', '') if state.get('mode') == 'instruct' else state.get('chat_template_str', '')
|
||||
|
|
@ -1839,8 +1819,7 @@ def load_history(unique_id, character, mode):
|
|||
if not p.exists():
|
||||
return {'internal': [], 'visible': [], 'metadata': {}}
|
||||
|
||||
with open(p, 'rb') as fh:
|
||||
f = json.loads(fh.read())
|
||||
f = json.loads(open(p, 'rb').read())
|
||||
if 'internal' in f and 'visible' in f:
|
||||
history = f
|
||||
else:
|
||||
|
|
@ -1904,17 +1883,19 @@ def generate_pfp_cache(character):
|
|||
if not cache_folder.exists():
|
||||
cache_folder.mkdir()
|
||||
|
||||
for extension in ['png', 'jpg', 'jpeg']:
|
||||
path = shared.user_data_dir / 'characters' / f"{character}.{extension}"
|
||||
for path in [shared.user_data_dir / 'characters' / f"{character}.{extension}" for extension in ['png', 'jpg', 'jpeg']]:
|
||||
if path.exists():
|
||||
original_img = Image.open(path)
|
||||
pfp_path = cache_folder / 'pfp_character.png'
|
||||
thumb_path = cache_folder / 'pfp_character_thumb.png'
|
||||
# Define file paths
|
||||
pfp_path = Path(f'{cache_folder}/pfp_character.png')
|
||||
thumb_path = Path(f'{cache_folder}/pfp_character_thumb.png')
|
||||
|
||||
# Save main picture and thumbnail
|
||||
original_img.save(pfp_path, format='PNG')
|
||||
thumb = make_thumbnail(original_img)
|
||||
thumb.save(thumb_path, format='PNG')
|
||||
|
||||
# Return the path to the thumbnail, not the in-memory PIL Image object.
|
||||
return str(thumb_path)
|
||||
|
||||
return None
|
||||
|
|
@ -1935,13 +1916,13 @@ def load_character(character, name1, name2):
|
|||
logger.error(f"Could not find the character \"{character}\" inside {shared.user_data_dir}/characters. No character has been loaded.")
|
||||
raise ValueError
|
||||
|
||||
with open(filepath, 'r', encoding='utf-8') as fh:
|
||||
file_contents = fh.read()
|
||||
file_contents = open(filepath, 'r', encoding='utf-8').read()
|
||||
data = json.loads(file_contents) if extension == "json" else yaml.safe_load(file_contents)
|
||||
cache_folder = Path(shared.args.disk_cache_dir)
|
||||
|
||||
for path in [cache_folder / "pfp_character.png", cache_folder / "pfp_character_thumb.png"]:
|
||||
path.unlink(missing_ok=True)
|
||||
for path in [Path(f"{cache_folder}/pfp_character.png"), Path(f"{cache_folder}/pfp_character_thumb.png")]:
|
||||
if path.exists():
|
||||
path.unlink()
|
||||
|
||||
picture = generate_pfp_cache(character)
|
||||
|
||||
|
|
@ -1997,7 +1978,9 @@ def clear_character_for_ui(state):
|
|||
# Clear the cache files
|
||||
cache_folder = Path(shared.args.disk_cache_dir)
|
||||
for cache_file in ['pfp_character.png', 'pfp_character_thumb.png']:
|
||||
(cache_folder / cache_file).unlink(missing_ok=True)
|
||||
cache_path = Path(f'{cache_folder}/{cache_file}')
|
||||
if cache_path.exists():
|
||||
cache_path.unlink()
|
||||
|
||||
return state, state['name2'], state['context'], state['greeting'], None
|
||||
|
||||
|
|
@ -2092,10 +2075,11 @@ def upload_your_profile_picture(img_path):
|
|||
cache_folder.mkdir()
|
||||
|
||||
if img is None:
|
||||
(cache_folder / "pfp_me.png").unlink(missing_ok=True)
|
||||
if Path(f"{cache_folder}/pfp_me.png").exists():
|
||||
Path(f"{cache_folder}/pfp_me.png").unlink()
|
||||
else:
|
||||
img = make_thumbnail(img)
|
||||
img.save(cache_folder / 'pfp_me.png')
|
||||
img.save(Path(f'{cache_folder}/pfp_me.png'))
|
||||
logger.info(f'Profile picture saved to "{cache_folder}/pfp_me.png"')
|
||||
|
||||
|
||||
|
|
@ -2151,12 +2135,13 @@ def generate_user_pfp_cache(user):
|
|||
if not cache_folder.exists():
|
||||
cache_folder.mkdir()
|
||||
|
||||
for extension in ['png', 'jpg', 'jpeg']:
|
||||
path = shared.user_data_dir / 'users' / f"{user}.{extension}"
|
||||
for path in [shared.user_data_dir / 'users' / f"{user}.{extension}" for extension in ['png', 'jpg', 'jpeg']]:
|
||||
if path.exists():
|
||||
original_img = Image.open(path)
|
||||
pfp_path = cache_folder / 'pfp_me.png'
|
||||
# Define file paths
|
||||
pfp_path = Path(f'{cache_folder}/pfp_me.png')
|
||||
|
||||
# Save thumbnail
|
||||
thumb = make_thumbnail(original_img)
|
||||
thumb.save(pfp_path, format='PNG')
|
||||
logger.info(f'User profile picture cached to "{pfp_path}"')
|
||||
|
|
@ -2188,7 +2173,9 @@ def load_user(user_name, name1, user_bio):
|
|||
|
||||
# Clear existing user picture cache
|
||||
cache_folder = Path(shared.args.disk_cache_dir)
|
||||
(cache_folder / "pfp_me.png").unlink(missing_ok=True)
|
||||
pfp_path = Path(f"{cache_folder}/pfp_me.png")
|
||||
if pfp_path.exists():
|
||||
pfp_path.unlink()
|
||||
|
||||
# Generate new picture cache
|
||||
picture = generate_user_pfp_cache(user_name)
|
||||
|
|
@ -2612,13 +2599,15 @@ def handle_character_picture_change(picture_path):
|
|||
|
||||
if picture is not None:
|
||||
# Save to cache
|
||||
picture.save(cache_folder / 'pfp_character.png', format='PNG')
|
||||
picture.save(Path(f'{cache_folder}/pfp_character.png'), format='PNG')
|
||||
thumb = make_thumbnail(picture)
|
||||
thumb.save(cache_folder / 'pfp_character_thumb.png', format='PNG')
|
||||
thumb.save(Path(f'{cache_folder}/pfp_character_thumb.png'), format='PNG')
|
||||
else:
|
||||
# Remove cache files when picture is cleared
|
||||
for cache_file in ['pfp_character.png', 'pfp_character_thumb.png']:
|
||||
(cache_folder / cache_file).unlink(missing_ok=True)
|
||||
cache_path = Path(f'{cache_folder}/{cache_file}')
|
||||
if cache_path.exists():
|
||||
cache_path.unlink()
|
||||
|
||||
|
||||
def handle_mode_change(state):
|
||||
|
|
|
|||
|
|
@ -14,13 +14,6 @@ from modules.reasoning import extract_reasoning
|
|||
from modules.sane_markdown_lists import SaneListExtension
|
||||
from modules.utils import get_available_chat_styles
|
||||
|
||||
# Pre-compiled regex for protecting markdown-sensitive characters inside LaTeX.
|
||||
# Covers $$...$$, \[...\], \(...\), and inline $...$ (when content contains \\).
|
||||
_LATEX_PATTERN = re.compile(
|
||||
r'((?:^|[\r\n\s])\$\$[^`]*?\$\$)|\\\[(.*?)\\\]|\\\((.*?)\\\)|(?<!\$)\$(?!\$)([^\$\n]*\\\\[^\$\n]*?)\$(?!\$)',
|
||||
re.DOTALL
|
||||
)
|
||||
|
||||
# This is to store the paths to the thumbnails of the profile pictures
|
||||
image_cache = {}
|
||||
|
||||
|
|
@ -192,29 +185,28 @@ def process_markdown_content(string):
|
|||
if not string:
|
||||
return ""
|
||||
|
||||
# Define unique placeholders for LaTeX characters that conflict with markdown
|
||||
# Define unique placeholders for LaTeX asterisks and underscores
|
||||
LATEX_ASTERISK_PLACEHOLDER = "LATEXASTERISKPLACEHOLDER"
|
||||
LATEX_UNDERSCORE_PLACEHOLDER = "LATEXUNDERSCOREPLACEHOLDER"
|
||||
LATEX_PIPE_PLACEHOLDER = "LATEXPIPEPLACEHOLDER"
|
||||
|
||||
def protect_latex_content(content):
|
||||
"""Protect markdown-sensitive characters inside LaTeX."""
|
||||
content = content.replace('*', LATEX_ASTERISK_PLACEHOLDER)
|
||||
content = content.replace('_', LATEX_UNDERSCORE_PLACEHOLDER)
|
||||
content = content.replace('|', LATEX_PIPE_PLACEHOLDER)
|
||||
return content
|
||||
|
||||
def protect_asterisks_underscores_in_latex(match):
|
||||
"""A replacer function for re.sub to protect markdown-sensitive characters in multiple LaTeX formats."""
|
||||
"""A replacer function for re.sub to protect asterisks and underscores in multiple LaTeX formats."""
|
||||
# Check which delimiter group was captured
|
||||
if match.group(1) is not None: # Content from $$...$$
|
||||
return protect_latex_content(match.group(1))
|
||||
content = match.group(1)
|
||||
modified_content = content.replace('*', LATEX_ASTERISK_PLACEHOLDER)
|
||||
modified_content = modified_content.replace('_', LATEX_UNDERSCORE_PLACEHOLDER)
|
||||
return f'{modified_content}'
|
||||
elif match.group(2) is not None: # Content from \[...\]
|
||||
return f'\\[{protect_latex_content(match.group(2))}\\]'
|
||||
content = match.group(2)
|
||||
modified_content = content.replace('*', LATEX_ASTERISK_PLACEHOLDER)
|
||||
modified_content = modified_content.replace('_', LATEX_UNDERSCORE_PLACEHOLDER)
|
||||
return f'\\[{modified_content}\\]'
|
||||
elif match.group(3) is not None: # Content from \(...\)
|
||||
return f'\\({protect_latex_content(match.group(3))}\\)'
|
||||
elif match.group(4) is not None: # Content from $...$
|
||||
return f'${protect_latex_content(match.group(4).strip())}$'
|
||||
content = match.group(3)
|
||||
modified_content = content.replace('*', LATEX_ASTERISK_PLACEHOLDER)
|
||||
modified_content = modified_content.replace('_', LATEX_UNDERSCORE_PLACEHOLDER)
|
||||
return f'\\({modified_content}\\)'
|
||||
|
||||
return match.group(0) # Fallback
|
||||
|
||||
|
|
@ -248,7 +240,9 @@ def process_markdown_content(string):
|
|||
string = re.sub(r"(.)```", r"\1\n```", string)
|
||||
|
||||
# Protect asterisks and underscores within all LaTeX blocks before markdown conversion
|
||||
string = _LATEX_PATTERN.sub(protect_asterisks_underscores_in_latex, string)
|
||||
latex_pattern = re.compile(r'((?:^|[\r\n\s])\$\$[^`]*?\$\$)|\\\[(.*?)\\\]|\\\((.*?)\\\)',
|
||||
re.DOTALL)
|
||||
string = latex_pattern.sub(protect_asterisks_underscores_in_latex, string)
|
||||
|
||||
result = ''
|
||||
is_code = False
|
||||
|
|
@ -312,7 +306,6 @@ def process_markdown_content(string):
|
|||
# Restore the LaTeX asterisks and underscores after markdown conversion
|
||||
html_output = html_output.replace(LATEX_ASTERISK_PLACEHOLDER, '*')
|
||||
html_output = html_output.replace(LATEX_UNDERSCORE_PLACEHOLDER, '_')
|
||||
html_output = html_output.replace(LATEX_PIPE_PLACEHOLDER, '|')
|
||||
|
||||
# Remove extra newlines before </code>
|
||||
html_output = re.sub(r'\s*</code>', '</code>', html_output)
|
||||
|
|
|
|||
|
|
@ -10,49 +10,72 @@ def get_quantization_config(quant_method):
|
|||
Get the appropriate quantization config based on the selected method.
|
||||
Applies quantization to both the transformer and the text_encoder.
|
||||
"""
|
||||
if quant_method == 'none' or not quant_method:
|
||||
return None
|
||||
|
||||
import torch
|
||||
# Import BitsAndBytesConfig from BOTH libraries to be safe
|
||||
from diffusers import BitsAndBytesConfig as DiffusersBnBConfig
|
||||
from diffusers import TorchAoConfig
|
||||
from diffusers.quantizers import PipelineQuantizationConfig
|
||||
from transformers import BitsAndBytesConfig as TransformersBnBConfig
|
||||
|
||||
torchao_methods = {
|
||||
'torchao-int8wo': 'int8wo',
|
||||
'torchao-fp4': 'fp4_e2m1',
|
||||
'torchao-float8wo': 'float8wo',
|
||||
}
|
||||
if quant_method == 'none' or not quant_method:
|
||||
return None
|
||||
|
||||
if quant_method == 'bnb-8bit':
|
||||
# Bitsandbytes 8-bit quantization
|
||||
elif quant_method == 'bnb-8bit':
|
||||
return PipelineQuantizationConfig(
|
||||
quant_mapping={
|
||||
"transformer": DiffusersBnBConfig(load_in_8bit=True),
|
||||
"text_encoder": TransformersBnBConfig(load_in_8bit=True)
|
||||
"transformer": DiffusersBnBConfig(
|
||||
load_in_8bit=True
|
||||
),
|
||||
"text_encoder": TransformersBnBConfig(
|
||||
load_in_8bit=True
|
||||
)
|
||||
}
|
||||
)
|
||||
|
||||
# Bitsandbytes 4-bit quantization
|
||||
elif quant_method == 'bnb-4bit':
|
||||
bnb_4bit_kwargs = dict(
|
||||
load_in_4bit=True,
|
||||
bnb_4bit_quant_type="nf4",
|
||||
bnb_4bit_compute_dtype=torch.bfloat16,
|
||||
bnb_4bit_use_double_quant=True
|
||||
)
|
||||
return PipelineQuantizationConfig(
|
||||
quant_mapping={
|
||||
"transformer": DiffusersBnBConfig(**bnb_4bit_kwargs),
|
||||
"text_encoder": TransformersBnBConfig(**bnb_4bit_kwargs)
|
||||
"transformer": DiffusersBnBConfig(
|
||||
load_in_4bit=True,
|
||||
bnb_4bit_quant_type="nf4",
|
||||
bnb_4bit_compute_dtype=torch.bfloat16,
|
||||
bnb_4bit_use_double_quant=True
|
||||
),
|
||||
"text_encoder": TransformersBnBConfig(
|
||||
load_in_4bit=True,
|
||||
bnb_4bit_quant_type="nf4",
|
||||
bnb_4bit_compute_dtype=torch.bfloat16,
|
||||
bnb_4bit_use_double_quant=True
|
||||
)
|
||||
}
|
||||
)
|
||||
|
||||
elif quant_method in torchao_methods:
|
||||
ao_type = torchao_methods[quant_method]
|
||||
# torchao int8 weight-only
|
||||
elif quant_method == 'torchao-int8wo':
|
||||
return PipelineQuantizationConfig(
|
||||
quant_mapping={
|
||||
"transformer": TorchAoConfig(ao_type),
|
||||
"text_encoder": TorchAoConfig(ao_type)
|
||||
"transformer": TorchAoConfig("int8wo"),
|
||||
"text_encoder": TorchAoConfig("int8wo")
|
||||
}
|
||||
)
|
||||
|
||||
# torchao fp4 (e2m1)
|
||||
elif quant_method == 'torchao-fp4':
|
||||
return PipelineQuantizationConfig(
|
||||
quant_mapping={
|
||||
"transformer": TorchAoConfig("fp4_e2m1"),
|
||||
"text_encoder": TorchAoConfig("fp4_e2m1")
|
||||
}
|
||||
)
|
||||
|
||||
# torchao float8 weight-only
|
||||
elif quant_method == 'torchao-float8wo':
|
||||
return PipelineQuantizationConfig(
|
||||
quant_mapping={
|
||||
"transformer": TorchAoConfig("float8wo"),
|
||||
"text_encoder": TorchAoConfig("float8wo")
|
||||
}
|
||||
)
|
||||
|
||||
|
|
@ -129,7 +152,7 @@ def load_image_model(model_name, dtype='bfloat16', attn_backend='sdpa', cpu_offl
|
|||
|
||||
modules = ["transformer", "unet"]
|
||||
|
||||
# Set attention backend (diffusers defaults to native/SDPA)
|
||||
# Set attention backend
|
||||
if attn_backend == 'flash_attention_2':
|
||||
for name in modules:
|
||||
mod = getattr(pipe, name, None)
|
||||
|
|
|
|||
|
|
@ -373,7 +373,6 @@ class LlamaServer:
|
|||
"""Check if a port is available for use."""
|
||||
with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as s:
|
||||
try:
|
||||
s.setsockopt(socket.SOL_SOCKET, socket.SO_REUSEADDR, 1)
|
||||
s.bind(('', port))
|
||||
return True
|
||||
except OSError:
|
||||
|
|
|
|||
|
|
@ -400,19 +400,14 @@ def load_instruction_template(template):
|
|||
if template == 'None':
|
||||
return ''
|
||||
|
||||
for name in (template, 'Alpaca'):
|
||||
path = shared.user_data_dir / 'instruction-templates' / f'{name}.yaml'
|
||||
try:
|
||||
with open(path, 'r', encoding='utf-8') as f:
|
||||
file_contents = f.read()
|
||||
except FileNotFoundError:
|
||||
if name == template:
|
||||
logger.warning(f"Instruction template '{template}' not found, falling back to Alpaca")
|
||||
continue
|
||||
|
||||
break
|
||||
for filepath in [shared.user_data_dir / 'instruction-templates' / f'{template}.yaml', shared.user_data_dir / 'instruction-templates' / 'Alpaca.yaml']:
|
||||
if filepath.exists():
|
||||
break
|
||||
else:
|
||||
return ''
|
||||
|
||||
with open(filepath, 'r', encoding='utf-8') as f:
|
||||
file_contents = f.read()
|
||||
data = yaml.safe_load(file_contents)
|
||||
if 'instruction_template' in data:
|
||||
return data['instruction_template']
|
||||
|
|
|
|||
|
|
@ -1,7 +1,6 @@
|
|||
from pathlib import Path
|
||||
|
||||
from modules import shared, utils
|
||||
from modules.utils import sanitize_filename
|
||||
from modules.text_generation import get_encoded_length
|
||||
|
||||
|
||||
|
|
@ -19,7 +18,6 @@ def load_prompt(fname):
|
|||
|
||||
return initial_content
|
||||
|
||||
fname = sanitize_filename(fname)
|
||||
file_path = shared.user_data_dir / 'logs' / 'notebook' / f'{fname}.txt'
|
||||
if file_path.exists():
|
||||
with open(file_path, 'r', encoding='utf-8') as f:
|
||||
|
|
|
|||
|
|
@ -73,16 +73,9 @@ def extract_reasoning(text, html_escaped=False):
|
|||
if content_pos != -1:
|
||||
content_start = content_pos + len(content_esc)
|
||||
else:
|
||||
# Content tag not present yet. In GPT-OSS the region
|
||||
# between <|end|> and the content tag contains internal
|
||||
# markup (<|start|>assistant…) that must not be shown.
|
||||
# Suppress it to prevent tag leaks during streaming.
|
||||
remainder = text[end_pos + len(end_esc):].lstrip()
|
||||
framing_token = esc('<|start|>')
|
||||
if not remainder or remainder.startswith(framing_token) or framing_token.startswith(remainder):
|
||||
content_start = len(text)
|
||||
else:
|
||||
content_start = end_pos + len(end_esc)
|
||||
# Content tag not present — fall back to content after
|
||||
# end_tag (e.g. GPT-OSS tool calls skip the final channel).
|
||||
content_start = end_pos + len(end_esc)
|
||||
else:
|
||||
content_start = end_pos + len(end_esc)
|
||||
|
||||
|
|
|
|||
|
|
@ -259,7 +259,6 @@ settings = {
|
|||
'enable_web_search': False,
|
||||
'web_search_pages': 3,
|
||||
'selected_tools': [],
|
||||
'mcp_servers': '',
|
||||
'prompt-notebook': '',
|
||||
'preset': 'Top-P' if (user_data_dir / 'presets/Top-P.yaml').exists() else None,
|
||||
'max_new_tokens': 512,
|
||||
|
|
@ -364,7 +363,7 @@ settings = {
|
|||
'image_llm_variations_prompt': 'Write a variation of the image generation prompt above. Consider the intent of the user with that prompt and write something that will likely please them, with added details. Output only the new prompt. Do not add any explanations, prefixes, or additional text.',
|
||||
'image_model_menu': 'None',
|
||||
'image_dtype': 'bfloat16',
|
||||
'image_attn_backend': 'sdpa',
|
||||
'image_attn_backend': 'flash_attention_2',
|
||||
'image_cpu_offload': False,
|
||||
'image_compile': False,
|
||||
'image_quant': 'none',
|
||||
|
|
|
|||
|
|
@ -31,7 +31,7 @@ TOOL_CALL_OPENING_MARKERS = [
|
|||
]
|
||||
|
||||
|
||||
def streaming_tool_buffer_check(text, markers=None, tool_names=None, check_bare_names=False, partial_match=True):
|
||||
def streaming_tool_buffer_check(text, markers=None, tool_names=None, check_bare_names=False):
|
||||
'''
|
||||
Check whether streaming output should be withheld because it may
|
||||
contain tool-call markup.
|
||||
|
|
@ -43,10 +43,6 @@ def streaming_tool_buffer_check(text, markers=None, tool_names=None, check_bare_
|
|||
tool_names: List of tool function names.
|
||||
check_bare_names: Whether to do partial-prefix matching on tool
|
||||
names (for models with unknown template format).
|
||||
partial_match: Whether to check partial prefixes of markers/names.
|
||||
Set to False for end-of-generation checks where a
|
||||
partial prefix is just normal text, not an incomplete
|
||||
tool call.
|
||||
'''
|
||||
# Strip thinking blocks so tool-call syntax inside <think> doesn't
|
||||
# trigger false positives.
|
||||
|
|
@ -64,9 +60,6 @@ def streaming_tool_buffer_check(text, markers=None, tool_names=None, check_bare_
|
|||
if name + '{' in text or name + ' {' in text:
|
||||
return True
|
||||
|
||||
if not partial_match:
|
||||
return False
|
||||
|
||||
# Partial-prefix matching: only for template-specific markers.
|
||||
for marker in (markers if markers is not None else TOOL_CALL_OPENING_MARKERS):
|
||||
for prefix_len in range(min(len(marker) - 1, len(text)), 0, -1):
|
||||
|
|
@ -638,15 +631,9 @@ def parse_tool_call(answer: str, tool_names: list[str], return_prefix: bool = Fa
|
|||
# Strip thinking blocks so tool-call syntax inside <think> is ignored.
|
||||
original_answer = answer
|
||||
_, answer = extract_reasoning(answer)
|
||||
# Reasoning extraction returns empty content when GPT-OSS internal
|
||||
# markup (<|start|>assistant…) follows the thinking block without a
|
||||
# content tag. Fall back to the full text so tool-call markers can
|
||||
# be found.
|
||||
if not answer.strip():
|
||||
answer = original_answer
|
||||
reasoning_offset = 0
|
||||
else:
|
||||
reasoning_offset = len(original_answer) - len(answer)
|
||||
# Offset between original and stripped text, used to map start_pos
|
||||
# back to the original string when returning a prefix.
|
||||
reasoning_offset = len(original_answer) - len(answer)
|
||||
|
||||
matches = []
|
||||
start_pos = None
|
||||
|
|
@ -712,8 +699,6 @@ def parse_tool_call(answer: str, tool_names: list[str], return_prefix: bool = Fa
|
|||
if not isinstance(candidates, list):
|
||||
candidates = [candidates]
|
||||
for candidate_dict in candidates:
|
||||
if not isinstance(candidate_dict, dict):
|
||||
continue
|
||||
checked_candidate = check_and_sanitize_tool_call_candidate(candidate_dict, tool_names)
|
||||
if checked_candidate is not None:
|
||||
matches.append(checked_candidate)
|
||||
|
|
|
|||
|
|
@ -1,4 +1,3 @@
|
|||
import asyncio
|
||||
import importlib.util
|
||||
import json
|
||||
|
||||
|
|
@ -56,119 +55,6 @@ def load_tools(selected_names):
|
|||
return tool_defs, executors
|
||||
|
||||
|
||||
def _parse_mcp_servers(servers_str):
|
||||
"""Parse MCP servers textbox: one server per line, format 'url' or 'url,Header: value,Header2: value2'."""
|
||||
servers = []
|
||||
for line in servers_str.strip().splitlines():
|
||||
line = line.strip()
|
||||
if not line:
|
||||
continue
|
||||
parts = line.split(',')
|
||||
url = parts[0].strip()
|
||||
headers = {}
|
||||
for part in parts[1:]:
|
||||
part = part.strip()
|
||||
if ':' in part:
|
||||
key, val = part.split(':', 1)
|
||||
headers[key.strip()] = val.strip()
|
||||
servers.append((url, headers))
|
||||
return servers
|
||||
|
||||
|
||||
def _mcp_tool_to_openai(tool):
|
||||
"""Convert an MCP Tool object to OpenAI-format tool dict."""
|
||||
return {
|
||||
"type": "function",
|
||||
"function": {
|
||||
"name": tool.name,
|
||||
"description": tool.description or "",
|
||||
"parameters": tool.inputSchema or {"type": "object", "properties": {}}
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
async def _mcp_session(url, headers, callback):
|
||||
"""Open an MCP session and pass it to the callback."""
|
||||
from mcp.client.streamable_http import streamablehttp_client
|
||||
from mcp import ClientSession
|
||||
|
||||
async with streamablehttp_client(url, headers=headers or None) as (read_stream, write_stream, _):
|
||||
async with ClientSession(read_stream, write_stream) as session:
|
||||
await session.initialize()
|
||||
return await callback(session)
|
||||
|
||||
|
||||
def _make_mcp_executor(name, url, headers):
|
||||
def executor(arguments):
|
||||
return asyncio.run(_call_mcp_tool(name, arguments, url, headers))
|
||||
return executor
|
||||
|
||||
|
||||
async def _connect_mcp_server(url, headers):
|
||||
"""Connect to one MCP server and return (tool_defs, executors)."""
|
||||
|
||||
async def _discover(session):
|
||||
result = await session.list_tools()
|
||||
tool_defs = []
|
||||
executors = {}
|
||||
for tool in result.tools:
|
||||
tool_defs.append(_mcp_tool_to_openai(tool))
|
||||
executors[tool.name] = _make_mcp_executor(tool.name, url, headers)
|
||||
return tool_defs, executors
|
||||
|
||||
return await _mcp_session(url, headers, _discover)
|
||||
|
||||
|
||||
async def _call_mcp_tool(name, arguments, url, headers):
|
||||
"""Connect to an MCP server and call a single tool."""
|
||||
|
||||
async def _invoke(session):
|
||||
result = await session.call_tool(name, arguments)
|
||||
parts = []
|
||||
for content in result.content:
|
||||
if hasattr(content, 'text'):
|
||||
parts.append(content.text)
|
||||
else:
|
||||
parts.append(str(content))
|
||||
return '\n'.join(parts) if parts else ''
|
||||
|
||||
return await _mcp_session(url, headers, _invoke)
|
||||
|
||||
|
||||
async def _connect_all_mcp_servers(servers):
|
||||
"""Connect to all MCP servers concurrently."""
|
||||
results = await asyncio.gather(
|
||||
*(_connect_mcp_server(url, headers) for url, headers in servers),
|
||||
return_exceptions=True
|
||||
)
|
||||
all_defs = []
|
||||
all_executors = {}
|
||||
for (url, _), result in zip(servers, results):
|
||||
if isinstance(result, Exception):
|
||||
logger.exception(f'Failed to connect to MCP server "{url}"', exc_info=result)
|
||||
continue
|
||||
defs, execs = result
|
||||
for td, (fn, ex) in zip(defs, execs.items()):
|
||||
if fn in all_executors:
|
||||
logger.warning(f'MCP tool "{fn}" from {url} conflicts with an already loaded tool. Skipping.')
|
||||
continue
|
||||
all_defs.append(td)
|
||||
all_executors[fn] = ex
|
||||
return all_defs, all_executors
|
||||
|
||||
|
||||
def load_mcp_tools(servers_str):
|
||||
"""
|
||||
Parse MCP servers string and discover tools from each server.
|
||||
Returns (tool_defs, executors) in the same format as load_tools.
|
||||
"""
|
||||
servers = _parse_mcp_servers(servers_str)
|
||||
if not servers:
|
||||
return [], {}
|
||||
|
||||
return asyncio.run(_connect_all_mcp_servers(servers))
|
||||
|
||||
|
||||
def execute_tool(func_name, arguments, executors):
|
||||
"""Execute a tool by function name. Returns result as a JSON string."""
|
||||
fn = executors.get(func_name)
|
||||
|
|
|
|||
|
|
@ -52,7 +52,7 @@ def create_ui():
|
|||
with gr.Column():
|
||||
always_override = gr.Checkbox(label='Override Existing Files', value=False, info='If the name is the same, checking will replace the existing file, and unchecking will load and continue from it (the rank must be the same).', elem_classes=['no-background'])
|
||||
|
||||
with gr.Accordion(label='Target Modules', open=False):
|
||||
with gr.Accordion(label='Target Modules', open=False, elem_classes='tgw-accordion'):
|
||||
gr.Markdown("Selects which modules to target in training. Targeting more modules is closer to a full fine-tune at the cost of increased VRAM and adapter size.")
|
||||
all_linear = gr.Checkbox(label='Target all linear layers', value=True, info='Targets every nn.Linear layer except lm_head. Works for any model architecture. When checked, the individual module checkboxes below are ignored.', elem_classes=['no-background'])
|
||||
with gr.Row():
|
||||
|
|
@ -87,7 +87,7 @@ def create_ui():
|
|||
with gr.Row():
|
||||
lr_scheduler_type = gr.Dropdown(label='LR Scheduler', value='cosine', choices=['linear', 'constant', 'constant_with_warmup', 'cosine', 'cosine_with_restarts', 'polynomial', 'inverse_sqrt'], info='Learning rate scheduler - defines how the learning rate changes over time. "Constant" means never change, "linear" means to go in a straight line from the learning rate down to 0, cosine follows a curve, etc.', elem_classes=['slim-dropdown'])
|
||||
|
||||
with gr.Accordion(label='Advanced Options', open=False):
|
||||
with gr.Accordion(label='Advanced Options', open=False, elem_classes='tgw-accordion'):
|
||||
with gr.Row():
|
||||
with gr.Column():
|
||||
optimizer = gr.Dropdown(label='Optimizer', value='adamw_torch', choices=['adamw_hf', 'adamw_torch', 'adamw_torch_fused', 'adamw_torch_xla', 'adamw_apex_fused', 'adafactor', 'adamw_bnb_8bit', 'adamw_anyprecision', 'sgd', 'adagrad'], info='Optimizer algorithm. adamw_torch is the standard choice. adamw_bnb_8bit uses less VRAM. adafactor is memory-efficient for large models.', elem_classes=['slim-dropdown'])
|
||||
|
|
|
|||
|
|
@ -75,7 +75,7 @@ if not shared.args.old_colors:
|
|||
background_fill_primary_dark='var(--darker-gray, #1C1C1D)',
|
||||
body_background_fill="white",
|
||||
block_background_fill="transparent",
|
||||
body_text_color='#1a1a1a',
|
||||
body_text_color='rgb(64, 64, 64)',
|
||||
button_secondary_background_fill="white",
|
||||
button_secondary_border_color="var(--border-color-primary)",
|
||||
block_title_text_color='*body_text_color',
|
||||
|
|
@ -209,7 +209,6 @@ def list_interface_input_elements():
|
|||
'textbox',
|
||||
'start_with',
|
||||
'selected_tools',
|
||||
'mcp_servers',
|
||||
'mode',
|
||||
'chat_style',
|
||||
'chat-instruct_command',
|
||||
|
|
@ -435,7 +434,6 @@ def setup_auto_save():
|
|||
'custom_system_message',
|
||||
'chat_template_str',
|
||||
'selected_tools',
|
||||
'mcp_servers',
|
||||
|
||||
# Parameters tab (ui_parameters.py) - Generation parameters
|
||||
'preset_menu',
|
||||
|
|
|
|||
|
|
@ -52,7 +52,7 @@ def create_ui():
|
|||
shared.gradio['html_display'] = gr.HTML(value=chat_html_wrapper({'internal': [], 'visible': [], 'metadata': {}}, '', '', '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='<div class="hover-element" onclick="void(0)"><span id="hover-element-button"><svg xmlns="http://www.w3.org/2000/svg" width="20" height="20" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round"><line x1="4" y1="6" x2="20" y2="6"></line><line x1="4" y1="12" x2="20" y2="12"></line><line x1="4" y1="18" x2="20" y2="18"></line></svg></span><div class="hover-menu" id="hover-menu"></div></div>', elem_id='gr-hover')
|
||||
gr.HTML(value='<div class="hover-element" onclick="void(0)"><span style="width: 100px; display: block" id="hover-element-button">☰</span><div class="hover-menu" id="hover-menu"></div>', elem_id='gr-hover')
|
||||
|
||||
with gr.Column(scale=10, elem_id='chat-input-container'):
|
||||
shared.gradio['textbox'] = gr.MultimodalTextbox(label='', placeholder='Send a message', file_types=['text', '.pdf', 'image'], file_count="multiple", elem_id='chat-input', elem_classes=['add_scrollbar'])
|
||||
|
|
@ -105,9 +105,6 @@ def create_ui():
|
|||
|
||||
shared.gradio['selected_tools'].change(fn=sync_web_tools, inputs=[shared.gradio['selected_tools']], outputs=[shared.gradio['selected_tools']], show_progress=False)
|
||||
|
||||
with gr.Accordion('MCP servers', open=False):
|
||||
shared.gradio['mcp_servers'] = gr.Textbox(value=shared.settings.get('mcp_servers', ''), lines=3, max_lines=3, label='', info='One url per line. For headers, write url,Header: value,Header2: value2', elem_classes=['add_scrollbar'])
|
||||
|
||||
gr.HTML("<div class='sidebar-vertical-separator'></div>")
|
||||
|
||||
with gr.Row():
|
||||
|
|
|
|||
|
|
@ -10,7 +10,7 @@ from modules.text_generation import (
|
|||
stop_everything_event
|
||||
)
|
||||
from modules.ui_notebook import store_notebook_state_and_debounce
|
||||
from modules.utils import gradio, sanitize_filename
|
||||
from modules.utils import gradio
|
||||
|
||||
inputs = ('textbox-default', 'interface_state')
|
||||
outputs = ('output_textbox', 'html-default')
|
||||
|
|
@ -167,7 +167,6 @@ def handle_new_prompt():
|
|||
|
||||
|
||||
def handle_delete_prompt_confirm_default(prompt_name):
|
||||
prompt_name = sanitize_filename(prompt_name)
|
||||
available_prompts = utils.get_available_prompts()
|
||||
current_index = available_prompts.index(prompt_name) if prompt_name in available_prompts else 0
|
||||
|
||||
|
|
@ -200,8 +199,6 @@ def handle_rename_prompt_click_default(current_name):
|
|||
|
||||
|
||||
def handle_rename_prompt_confirm_default(new_name, current_name):
|
||||
new_name = sanitize_filename(new_name)
|
||||
current_name = sanitize_filename(current_name)
|
||||
old_path = shared.user_data_dir / "logs" / "notebook" / f"{current_name}.txt"
|
||||
new_path = shared.user_data_dir / "logs" / "notebook" / f"{new_name}.txt"
|
||||
|
||||
|
|
|
|||
|
|
@ -798,9 +798,6 @@ def generate(state, save_images=True):
|
|||
if seed == -1:
|
||||
seed = random.randint(0, 2**32 - 1)
|
||||
|
||||
# Store resolved seed back so callers (e.g. API) can access it
|
||||
state['image_seed_resolved'] = seed
|
||||
|
||||
device = get_device()
|
||||
if device is None:
|
||||
device = "cpu"
|
||||
|
|
|
|||
|
|
@ -54,6 +54,7 @@ def create_ui():
|
|||
if not shared.args.portable:
|
||||
shared.gradio['ik'] = gr.Checkbox(label="ik", value=shared.args.ik, info='Use ik_llama.cpp instead of upstream llama.cpp.')
|
||||
|
||||
shared.gradio['cpu_moe'] = gr.Checkbox(label="cpu-moe", value=shared.args.cpu_moe, info='Move the experts to the CPU. Saves VRAM on MoE models.')
|
||||
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)
|
||||
|
|
@ -66,13 +67,13 @@ def create_ui():
|
|||
)
|
||||
|
||||
# Multimodal
|
||||
with gr.Accordion("Multimodal (vision)", open=False) as shared.gradio['mmproj_accordion']:
|
||||
with gr.Accordion("Multimodal (vision)", open=False, elem_classes='tgw-accordion') as shared.gradio['mmproj_accordion']:
|
||||
with gr.Row():
|
||||
shared.gradio['mmproj'] = gr.Dropdown(label="mmproj file", choices=utils.get_available_mmproj(), value=lambda: shared.args.mmproj or 'None', elem_classes='slim-dropdown', info=f'Select a file that matches your model. Must be placed in {shared.user_data_dir}/mmproj/', interactive=not mu)
|
||||
ui.create_refresh_button(shared.gradio['mmproj'], lambda: None, lambda: {'choices': utils.get_available_mmproj()}, 'refresh-button', interactive=not mu)
|
||||
|
||||
# Speculative decoding
|
||||
with gr.Accordion("Speculative decoding", open=False) as shared.gradio['speculative_decoding_accordion']:
|
||||
with gr.Accordion("Speculative decoding", open=False, elem_classes='tgw-accordion') as shared.gradio['speculative_decoding_accordion']:
|
||||
shared.gradio['draft_max'] = gr.Number(label="draft-max", precision=0, step=1, value=shared.args.draft_max, info='Maximum number of tokens to draft for speculative decoding. Recommended: 4 for draft model, 64 for n-gram.')
|
||||
|
||||
gr.Markdown('#### Draft model')
|
||||
|
|
@ -91,7 +92,7 @@ def create_ui():
|
|||
shared.gradio['spec_ngram_min_hits'] = gr.Number(label="spec-ngram-min-hits", precision=0, step=1, value=shared.args.spec_ngram_min_hits, info='Minimum n-gram hits for ngram-map speculative decoding.', visible=shared.args.spec_type != 'none')
|
||||
|
||||
gr.Markdown("## Other options")
|
||||
with gr.Accordion("See more options", open=False):
|
||||
with gr.Accordion("See more options", open=False, elem_classes='tgw-accordion'):
|
||||
with gr.Row():
|
||||
with gr.Column():
|
||||
shared.gradio['parallel'] = gr.Slider(label="parallel", minimum=1, step=1, maximum=64, value=shared.args.parallel, info='Number of parallel request slots for the API. The context size is divided equally among slots. For example, to have 4 slots with 8192 context each, set ctx_size to 32768.')
|
||||
|
|
@ -108,7 +109,6 @@ def create_ui():
|
|||
with gr.Column():
|
||||
shared.gradio['cpu'] = gr.Checkbox(label="cpu", value=shared.args.cpu, info='Use PyTorch in CPU mode.')
|
||||
shared.gradio['disk'] = gr.Checkbox(label="disk", value=shared.args.disk)
|
||||
shared.gradio['cpu_moe'] = gr.Checkbox(label="cpu-moe", value=shared.args.cpu_moe, info='Move the experts to the CPU. Saves VRAM on MoE models.')
|
||||
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 performance.')
|
||||
shared.gradio['no_mmap'] = gr.Checkbox(label="no-mmap", value=shared.args.no_mmap)
|
||||
|
|
|
|||
|
|
@ -11,7 +11,7 @@ from modules.text_generation import (
|
|||
get_token_ids,
|
||||
stop_everything_event
|
||||
)
|
||||
from modules.utils import gradio, sanitize_filename
|
||||
from modules.utils import gradio
|
||||
|
||||
_notebook_file_lock = threading.Lock()
|
||||
_notebook_auto_save_timer = None
|
||||
|
|
@ -202,7 +202,6 @@ def handle_new_prompt():
|
|||
|
||||
|
||||
def handle_delete_prompt_confirm_notebook(prompt_name):
|
||||
prompt_name = sanitize_filename(prompt_name)
|
||||
available_prompts = utils.get_available_prompts()
|
||||
current_index = available_prompts.index(prompt_name) if prompt_name in available_prompts else 0
|
||||
|
||||
|
|
@ -234,8 +233,6 @@ def handle_rename_prompt_click_notebook(current_name):
|
|||
|
||||
|
||||
def handle_rename_prompt_confirm_notebook(new_name, current_name):
|
||||
new_name = sanitize_filename(new_name)
|
||||
current_name = sanitize_filename(current_name)
|
||||
old_path = shared.user_data_dir / "logs" / "notebook" / f"{current_name}.txt"
|
||||
new_path = shared.user_data_dir / "logs" / "notebook" / f"{new_name}.txt"
|
||||
|
||||
|
|
@ -252,7 +249,6 @@ def handle_rename_prompt_confirm_notebook(new_name, current_name):
|
|||
|
||||
def autosave_prompt(text, prompt_name):
|
||||
"""Automatically save the text to the selected prompt file"""
|
||||
prompt_name = sanitize_filename(prompt_name)
|
||||
if prompt_name and text.strip():
|
||||
prompt_path = shared.user_data_dir / "logs" / "notebook" / f"{prompt_name}.txt"
|
||||
prompt_path.parent.mkdir(parents=True, exist_ok=True)
|
||||
|
|
|
|||
|
|
@ -9,7 +9,6 @@ flash-linear-attention==0.4.*
|
|||
huggingface-hub==1.5.*
|
||||
jinja2==3.1.6
|
||||
markdown
|
||||
mcp==1.27.0
|
||||
numpy==2.2.*
|
||||
pandas
|
||||
peft==0.18.*
|
||||
|
|
@ -32,8 +31,8 @@ tqdm
|
|||
wandb
|
||||
|
||||
# Gradio
|
||||
https://github.com/oobabooga/gradio/releases/download/4.37.2-custom.19/gradio-4.37.2+custom.19-py3-none-any.whl
|
||||
https://github.com/oobabooga/gradio/releases/download/4.37.2-custom.19/gradio_client-1.0.2+custom.19-py3-none-any.whl
|
||||
https://github.com/oobabooga/gradio/releases/download/4.37.2-custom.17/gradio-4.37.2+custom.17-py3-none-any.whl
|
||||
https://github.com/oobabooga/gradio/releases/download/4.37.2-custom.17/gradio_client-1.0.2+custom.17-py3-none-any.whl
|
||||
|
||||
# API
|
||||
flask_cloudflared==0.0.15
|
||||
|
|
@ -41,10 +40,10 @@ sse-starlette==1.6.5
|
|||
tiktoken
|
||||
|
||||
# CUDA wheels
|
||||
https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.110.0/llama_cpp_binaries-0.110.0+cu124-py3-none-win_amd64.whl; platform_system == "Windows"
|
||||
https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.110.0/llama_cpp_binaries-0.110.0+cu124-py3-none-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64"
|
||||
https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.110.0/ik_llama_cpp_binaries-0.110.0+cu124-py3-none-win_amd64.whl; platform_system == "Windows"
|
||||
https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.110.0/ik_llama_cpp_binaries-0.110.0+cu124-py3-none-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64"
|
||||
https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.106.0/llama_cpp_binaries-0.106.0+cu124-py3-none-win_amd64.whl; platform_system == "Windows"
|
||||
https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.106.0/llama_cpp_binaries-0.106.0+cu124-py3-none-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64"
|
||||
https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.106.0/ik_llama_cpp_binaries-0.106.0+cu124-py3-none-win_amd64.whl; platform_system == "Windows"
|
||||
https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.106.0/ik_llama_cpp_binaries-0.106.0+cu124-py3-none-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64"
|
||||
https://github.com/turboderp-org/exllamav3/releases/download/v0.0.28/exllamav3-0.0.28+cu128.torch2.9.0-cp313-cp313-win_amd64.whl; platform_system == "Windows" and python_version == "3.13"
|
||||
https://github.com/turboderp-org/exllamav3/releases/download/v0.0.28/exllamav3-0.0.28+cu128.torch2.9.0-cp313-cp313-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.13"
|
||||
https://github.com/kingbri1/flash-attention/releases/download/v2.8.3/flash_attn-2.8.3+cu128torch2.9.0cxx11abiFALSE-cp313-cp313-win_amd64.whl; platform_system == "Windows" and python_version == "3.13"
|
||||
|
|
|
|||
|
|
@ -7,7 +7,6 @@ fastapi==0.112.4
|
|||
huggingface-hub==1.5.*
|
||||
jinja2==3.1.6
|
||||
markdown
|
||||
mcp==1.27.0
|
||||
numpy==2.2.*
|
||||
pandas
|
||||
peft==0.18.*
|
||||
|
|
@ -29,8 +28,8 @@ trafilatura==2.0.0
|
|||
wandb
|
||||
|
||||
# Gradio
|
||||
https://github.com/oobabooga/gradio/releases/download/4.37.2-custom.19/gradio-4.37.2+custom.19-py3-none-any.whl
|
||||
https://github.com/oobabooga/gradio/releases/download/4.37.2-custom.19/gradio_client-1.0.2+custom.19-py3-none-any.whl
|
||||
https://github.com/oobabooga/gradio/releases/download/4.37.2-custom.17/gradio-4.37.2+custom.17-py3-none-any.whl
|
||||
https://github.com/oobabooga/gradio/releases/download/4.37.2-custom.17/gradio_client-1.0.2+custom.17-py3-none-any.whl
|
||||
|
||||
# API
|
||||
flask_cloudflared==0.0.15
|
||||
|
|
@ -38,5 +37,5 @@ sse-starlette==1.6.5
|
|||
tiktoken
|
||||
|
||||
# AMD wheels
|
||||
https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.110.0/llama_cpp_binaries-0.110.0+rocm7.2-py3-none-win_amd64.whl; platform_system == "Windows"
|
||||
https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.110.0/llama_cpp_binaries-0.110.0+rocm7.2-py3-none-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64"
|
||||
https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.106.0/llama_cpp_binaries-0.106.0+rocm7.2-py3-none-win_amd64.whl; platform_system == "Windows"
|
||||
https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.106.0/llama_cpp_binaries-0.106.0+rocm7.2-py3-none-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64"
|
||||
|
|
|
|||
|
|
@ -7,7 +7,6 @@ fastapi==0.112.4
|
|||
huggingface-hub==1.5.*
|
||||
jinja2==3.1.6
|
||||
markdown
|
||||
mcp==1.27.0
|
||||
numpy==2.2.*
|
||||
pandas
|
||||
peft==0.18.*
|
||||
|
|
@ -29,8 +28,8 @@ trafilatura==2.0.0
|
|||
wandb
|
||||
|
||||
# Gradio
|
||||
https://github.com/oobabooga/gradio/releases/download/4.37.2-custom.19/gradio-4.37.2+custom.19-py3-none-any.whl
|
||||
https://github.com/oobabooga/gradio/releases/download/4.37.2-custom.19/gradio_client-1.0.2+custom.19-py3-none-any.whl
|
||||
https://github.com/oobabooga/gradio/releases/download/4.37.2-custom.17/gradio-4.37.2+custom.17-py3-none-any.whl
|
||||
https://github.com/oobabooga/gradio/releases/download/4.37.2-custom.17/gradio_client-1.0.2+custom.17-py3-none-any.whl
|
||||
|
||||
# API
|
||||
flask_cloudflared==0.0.15
|
||||
|
|
@ -38,4 +37,4 @@ sse-starlette==1.6.5
|
|||
tiktoken
|
||||
|
||||
# Mac wheels
|
||||
https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.110.0/llama_cpp_binaries-0.110.0-py3-none-macosx_13_0_x86_64.whl; platform_system == "Darwin"
|
||||
https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.106.0/llama_cpp_binaries-0.106.0-py3-none-macosx_13_0_x86_64.whl; platform_system == "Darwin"
|
||||
|
|
|
|||
|
|
@ -7,7 +7,6 @@ fastapi==0.112.4
|
|||
huggingface-hub==1.5.*
|
||||
jinja2==3.1.6
|
||||
markdown
|
||||
mcp==1.27.0
|
||||
numpy==2.2.*
|
||||
pandas
|
||||
peft==0.18.*
|
||||
|
|
@ -29,8 +28,8 @@ trafilatura==2.0.0
|
|||
wandb
|
||||
|
||||
# Gradio
|
||||
https://github.com/oobabooga/gradio/releases/download/4.37.2-custom.19/gradio-4.37.2+custom.19-py3-none-any.whl
|
||||
https://github.com/oobabooga/gradio/releases/download/4.37.2-custom.19/gradio_client-1.0.2+custom.19-py3-none-any.whl
|
||||
https://github.com/oobabooga/gradio/releases/download/4.37.2-custom.17/gradio-4.37.2+custom.17-py3-none-any.whl
|
||||
https://github.com/oobabooga/gradio/releases/download/4.37.2-custom.17/gradio_client-1.0.2+custom.17-py3-none-any.whl
|
||||
|
||||
# API
|
||||
flask_cloudflared==0.0.15
|
||||
|
|
@ -38,4 +37,4 @@ sse-starlette==1.6.5
|
|||
tiktoken
|
||||
|
||||
# Mac wheels
|
||||
https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.110.0/llama_cpp_binaries-0.110.0-py3-none-macosx_13_0_arm64.whl; platform_system == "Darwin"
|
||||
https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.106.0/llama_cpp_binaries-0.106.0-py3-none-macosx_13_0_arm64.whl; platform_system == "Darwin"
|
||||
|
|
|
|||
|
|
@ -7,7 +7,6 @@ fastapi==0.112.4
|
|||
huggingface-hub==1.5.*
|
||||
jinja2==3.1.6
|
||||
markdown
|
||||
mcp==1.27.0
|
||||
numpy==2.2.*
|
||||
pandas
|
||||
peft==0.18.*
|
||||
|
|
@ -29,8 +28,8 @@ trafilatura==2.0.0
|
|||
wandb
|
||||
|
||||
# Gradio
|
||||
https://github.com/oobabooga/gradio/releases/download/4.37.2-custom.19/gradio-4.37.2+custom.19-py3-none-any.whl
|
||||
https://github.com/oobabooga/gradio/releases/download/4.37.2-custom.19/gradio_client-1.0.2+custom.19-py3-none-any.whl
|
||||
https://github.com/oobabooga/gradio/releases/download/4.37.2-custom.17/gradio-4.37.2+custom.17-py3-none-any.whl
|
||||
https://github.com/oobabooga/gradio/releases/download/4.37.2-custom.17/gradio_client-1.0.2+custom.17-py3-none-any.whl
|
||||
|
||||
# API
|
||||
flask_cloudflared==0.0.15
|
||||
|
|
@ -38,7 +37,7 @@ sse-starlette==1.6.5
|
|||
tiktoken
|
||||
|
||||
# llama.cpp (CPU only)
|
||||
https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.110.0/llama_cpp_binaries-0.110.0+cpu-py3-none-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64"
|
||||
https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.110.0/llama_cpp_binaries-0.110.0+cpu-py3-none-win_amd64.whl; platform_system == "Windows"
|
||||
https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.110.0/ik_llama_cpp_binaries-0.110.0+cpu-py3-none-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64"
|
||||
https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.110.0/ik_llama_cpp_binaries-0.110.0+cpu-py3-none-win_amd64.whl; platform_system == "Windows"
|
||||
https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.106.0/llama_cpp_binaries-0.106.0+cpu-py3-none-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64"
|
||||
https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.106.0/llama_cpp_binaries-0.106.0+cpu-py3-none-win_amd64.whl; platform_system == "Windows"
|
||||
https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.106.0/ik_llama_cpp_binaries-0.106.0+cpu-py3-none-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64"
|
||||
https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.106.0/ik_llama_cpp_binaries-0.106.0+cpu-py3-none-win_amd64.whl; platform_system == "Windows"
|
||||
|
|
|
|||
|
|
@ -7,7 +7,6 @@ fastapi==0.112.4
|
|||
huggingface-hub==1.5.*
|
||||
jinja2==3.1.6
|
||||
markdown
|
||||
mcp==1.27.0
|
||||
numpy==2.2.*
|
||||
pandas
|
||||
peft==0.18.*
|
||||
|
|
@ -29,8 +28,8 @@ trafilatura==2.0.0
|
|||
wandb
|
||||
|
||||
# Gradio
|
||||
https://github.com/oobabooga/gradio/releases/download/4.37.2-custom.19/gradio-4.37.2+custom.19-py3-none-any.whl
|
||||
https://github.com/oobabooga/gradio/releases/download/4.37.2-custom.19/gradio_client-1.0.2+custom.19-py3-none-any.whl
|
||||
https://github.com/oobabooga/gradio/releases/download/4.37.2-custom.17/gradio-4.37.2+custom.17-py3-none-any.whl
|
||||
https://github.com/oobabooga/gradio/releases/download/4.37.2-custom.17/gradio_client-1.0.2+custom.17-py3-none-any.whl
|
||||
|
||||
# API
|
||||
flask_cloudflared==0.0.15
|
||||
|
|
|
|||
|
|
@ -3,7 +3,6 @@ fastapi==0.112.4
|
|||
huggingface-hub==1.5.*
|
||||
jinja2==3.1.6
|
||||
markdown
|
||||
mcp==1.27.0
|
||||
numpy==2.2.*
|
||||
pydantic==2.11.0
|
||||
pymupdf==1.27.*
|
||||
|
|
@ -15,8 +14,8 @@ trafilatura==2.0.0
|
|||
tqdm
|
||||
|
||||
# Gradio
|
||||
https://github.com/oobabooga/gradio/releases/download/4.37.2-custom.19/gradio-4.37.2+custom.19-py3-none-any.whl
|
||||
https://github.com/oobabooga/gradio/releases/download/4.37.2-custom.19/gradio_client-1.0.2+custom.19-py3-none-any.whl
|
||||
https://github.com/oobabooga/gradio/releases/download/4.37.2-custom.17/gradio-4.37.2+custom.17-py3-none-any.whl
|
||||
https://github.com/oobabooga/gradio/releases/download/4.37.2-custom.17/gradio_client-1.0.2+custom.17-py3-none-any.whl
|
||||
|
||||
# API
|
||||
flask_cloudflared==0.0.15
|
||||
|
|
@ -24,5 +23,5 @@ sse-starlette==1.6.5
|
|||
tiktoken
|
||||
|
||||
# CUDA wheels
|
||||
https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.110.0/llama_cpp_binaries-0.110.0+cu124-py3-none-win_amd64.whl; platform_system == "Windows"
|
||||
https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.110.0/llama_cpp_binaries-0.110.0+cu124-py3-none-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64"
|
||||
https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.106.0/llama_cpp_binaries-0.106.0+cu124-py3-none-win_amd64.whl; platform_system == "Windows"
|
||||
https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.106.0/llama_cpp_binaries-0.106.0+cu124-py3-none-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64"
|
||||
|
|
|
|||
|
|
@ -3,7 +3,6 @@ fastapi==0.112.4
|
|||
huggingface-hub==1.5.*
|
||||
jinja2==3.1.6
|
||||
markdown
|
||||
mcp==1.27.0
|
||||
numpy==2.2.*
|
||||
pydantic==2.11.0
|
||||
pymupdf==1.27.*
|
||||
|
|
@ -15,8 +14,8 @@ trafilatura==2.0.0
|
|||
tqdm
|
||||
|
||||
# Gradio
|
||||
https://github.com/oobabooga/gradio/releases/download/4.37.2-custom.19/gradio-4.37.2+custom.19-py3-none-any.whl
|
||||
https://github.com/oobabooga/gradio/releases/download/4.37.2-custom.19/gradio_client-1.0.2+custom.19-py3-none-any.whl
|
||||
https://github.com/oobabooga/gradio/releases/download/4.37.2-custom.17/gradio-4.37.2+custom.17-py3-none-any.whl
|
||||
https://github.com/oobabooga/gradio/releases/download/4.37.2-custom.17/gradio_client-1.0.2+custom.17-py3-none-any.whl
|
||||
|
||||
# API
|
||||
flask_cloudflared==0.0.15
|
||||
|
|
@ -24,5 +23,5 @@ sse-starlette==1.6.5
|
|||
tiktoken
|
||||
|
||||
# AMD wheels
|
||||
https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.110.0/llama_cpp_binaries-0.110.0+rocm7.2-py3-none-win_amd64.whl; platform_system == "Windows"
|
||||
https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.110.0/llama_cpp_binaries-0.110.0+rocm7.2-py3-none-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64"
|
||||
https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.106.0/llama_cpp_binaries-0.106.0+rocm7.2-py3-none-win_amd64.whl; platform_system == "Windows"
|
||||
https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.106.0/llama_cpp_binaries-0.106.0+rocm7.2-py3-none-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64"
|
||||
|
|
|
|||
|
|
@ -3,7 +3,6 @@ fastapi==0.112.4
|
|||
huggingface-hub==1.5.*
|
||||
jinja2==3.1.6
|
||||
markdown
|
||||
mcp==1.27.0
|
||||
numpy==2.2.*
|
||||
pydantic==2.11.0
|
||||
pymupdf==1.27.*
|
||||
|
|
@ -15,8 +14,8 @@ trafilatura==2.0.0
|
|||
tqdm
|
||||
|
||||
# Gradio
|
||||
https://github.com/oobabooga/gradio/releases/download/4.37.2-custom.19/gradio-4.37.2+custom.19-py3-none-any.whl
|
||||
https://github.com/oobabooga/gradio/releases/download/4.37.2-custom.19/gradio_client-1.0.2+custom.19-py3-none-any.whl
|
||||
https://github.com/oobabooga/gradio/releases/download/4.37.2-custom.17/gradio-4.37.2+custom.17-py3-none-any.whl
|
||||
https://github.com/oobabooga/gradio/releases/download/4.37.2-custom.17/gradio_client-1.0.2+custom.17-py3-none-any.whl
|
||||
|
||||
# API
|
||||
flask_cloudflared==0.0.15
|
||||
|
|
@ -24,4 +23,4 @@ sse-starlette==1.6.5
|
|||
tiktoken
|
||||
|
||||
# Mac wheels
|
||||
https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.110.0/llama_cpp_binaries-0.110.0-py3-none-macosx_13_0_x86_64.whl; platform_system == "Darwin"
|
||||
https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.106.0/llama_cpp_binaries-0.106.0-py3-none-macosx_13_0_x86_64.whl; platform_system == "Darwin"
|
||||
|
|
|
|||
|
|
@ -3,7 +3,6 @@ fastapi==0.112.4
|
|||
huggingface-hub==1.5.*
|
||||
jinja2==3.1.6
|
||||
markdown
|
||||
mcp==1.27.0
|
||||
numpy==2.2.*
|
||||
pydantic==2.11.0
|
||||
pymupdf==1.27.*
|
||||
|
|
@ -15,8 +14,8 @@ trafilatura==2.0.0
|
|||
tqdm
|
||||
|
||||
# Gradio
|
||||
https://github.com/oobabooga/gradio/releases/download/4.37.2-custom.19/gradio-4.37.2+custom.19-py3-none-any.whl
|
||||
https://github.com/oobabooga/gradio/releases/download/4.37.2-custom.19/gradio_client-1.0.2+custom.19-py3-none-any.whl
|
||||
https://github.com/oobabooga/gradio/releases/download/4.37.2-custom.17/gradio-4.37.2+custom.17-py3-none-any.whl
|
||||
https://github.com/oobabooga/gradio/releases/download/4.37.2-custom.17/gradio_client-1.0.2+custom.17-py3-none-any.whl
|
||||
|
||||
# API
|
||||
flask_cloudflared==0.0.15
|
||||
|
|
@ -24,4 +23,4 @@ sse-starlette==1.6.5
|
|||
tiktoken
|
||||
|
||||
# Mac wheels
|
||||
https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.110.0/llama_cpp_binaries-0.110.0-py3-none-macosx_13_0_arm64.whl; platform_system == "Darwin"
|
||||
https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.106.0/llama_cpp_binaries-0.106.0-py3-none-macosx_13_0_arm64.whl; platform_system == "Darwin"
|
||||
|
|
|
|||
|
|
@ -3,7 +3,6 @@ fastapi==0.112.4
|
|||
huggingface-hub==1.5.*
|
||||
jinja2==3.1.6
|
||||
markdown
|
||||
mcp==1.27.0
|
||||
numpy==2.2.*
|
||||
pydantic==2.11.0
|
||||
pymupdf==1.27.*
|
||||
|
|
@ -15,8 +14,8 @@ trafilatura==2.0.0
|
|||
tqdm
|
||||
|
||||
# Gradio
|
||||
https://github.com/oobabooga/gradio/releases/download/4.37.2-custom.19/gradio-4.37.2+custom.19-py3-none-any.whl
|
||||
https://github.com/oobabooga/gradio/releases/download/4.37.2-custom.19/gradio_client-1.0.2+custom.19-py3-none-any.whl
|
||||
https://github.com/oobabooga/gradio/releases/download/4.37.2-custom.17/gradio-4.37.2+custom.17-py3-none-any.whl
|
||||
https://github.com/oobabooga/gradio/releases/download/4.37.2-custom.17/gradio_client-1.0.2+custom.17-py3-none-any.whl
|
||||
|
||||
# API
|
||||
flask_cloudflared==0.0.15
|
||||
|
|
@ -24,5 +23,5 @@ sse-starlette==1.6.5
|
|||
tiktoken
|
||||
|
||||
# llama.cpp (CPU only)
|
||||
https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.110.0/llama_cpp_binaries-0.110.0+cpu-py3-none-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64"
|
||||
https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.110.0/llama_cpp_binaries-0.110.0+cpu-py3-none-win_amd64.whl; platform_system == "Windows"
|
||||
https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.106.0/llama_cpp_binaries-0.106.0+cpu-py3-none-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64"
|
||||
https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.106.0/llama_cpp_binaries-0.106.0+cpu-py3-none-win_amd64.whl; platform_system == "Windows"
|
||||
|
|
|
|||
|
|
@ -3,7 +3,6 @@ fastapi==0.112.4
|
|||
huggingface-hub==1.5.*
|
||||
jinja2==3.1.6
|
||||
markdown
|
||||
mcp==1.27.0
|
||||
numpy==2.2.*
|
||||
pydantic==2.11.0
|
||||
pymupdf==1.27.*
|
||||
|
|
@ -15,8 +14,8 @@ trafilatura==2.0.0
|
|||
tqdm
|
||||
|
||||
# Gradio
|
||||
https://github.com/oobabooga/gradio/releases/download/4.37.2-custom.19/gradio-4.37.2+custom.19-py3-none-any.whl
|
||||
https://github.com/oobabooga/gradio/releases/download/4.37.2-custom.19/gradio_client-1.0.2+custom.19-py3-none-any.whl
|
||||
https://github.com/oobabooga/gradio/releases/download/4.37.2-custom.17/gradio-4.37.2+custom.17-py3-none-any.whl
|
||||
https://github.com/oobabooga/gradio/releases/download/4.37.2-custom.17/gradio_client-1.0.2+custom.17-py3-none-any.whl
|
||||
|
||||
# API
|
||||
flask_cloudflared==0.0.15
|
||||
|
|
@ -24,5 +23,5 @@ sse-starlette==1.6.5
|
|||
tiktoken
|
||||
|
||||
# CUDA wheels
|
||||
https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.110.0/llama_cpp_binaries-0.110.0+cu131-py3-none-win_amd64.whl; platform_system == "Windows"
|
||||
https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.110.0/llama_cpp_binaries-0.110.0+cu131-py3-none-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64"
|
||||
https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.106.0/llama_cpp_binaries-0.106.0+cu131-py3-none-win_amd64.whl; platform_system == "Windows"
|
||||
https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.106.0/llama_cpp_binaries-0.106.0+cu131-py3-none-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64"
|
||||
|
|
|
|||
|
|
@ -3,7 +3,6 @@ fastapi==0.112.4
|
|||
huggingface-hub==1.5.*
|
||||
jinja2==3.1.6
|
||||
markdown
|
||||
mcp==1.27.0
|
||||
numpy==2.2.*
|
||||
pydantic==2.11.0
|
||||
pymupdf==1.27.*
|
||||
|
|
@ -15,8 +14,8 @@ trafilatura==2.0.0
|
|||
tqdm
|
||||
|
||||
# Gradio
|
||||
https://github.com/oobabooga/gradio/releases/download/4.37.2-custom.19/gradio-4.37.2+custom.19-py3-none-any.whl
|
||||
https://github.com/oobabooga/gradio/releases/download/4.37.2-custom.19/gradio_client-1.0.2+custom.19-py3-none-any.whl
|
||||
https://github.com/oobabooga/gradio/releases/download/4.37.2-custom.17/gradio-4.37.2+custom.17-py3-none-any.whl
|
||||
https://github.com/oobabooga/gradio/releases/download/4.37.2-custom.17/gradio_client-1.0.2+custom.17-py3-none-any.whl
|
||||
|
||||
# API
|
||||
flask_cloudflared==0.0.15
|
||||
|
|
@ -24,5 +23,5 @@ sse-starlette==1.6.5
|
|||
tiktoken
|
||||
|
||||
# CUDA wheels
|
||||
https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.110.0/ik_llama_cpp_binaries-0.110.0+cu124-py3-none-win_amd64.whl; platform_system == "Windows"
|
||||
https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.110.0/ik_llama_cpp_binaries-0.110.0+cu124-py3-none-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64"
|
||||
https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.106.0/ik_llama_cpp_binaries-0.106.0+cu124-py3-none-win_amd64.whl; platform_system == "Windows"
|
||||
https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.106.0/ik_llama_cpp_binaries-0.106.0+cu124-py3-none-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64"
|
||||
|
|
|
|||
|
|
@ -3,7 +3,6 @@ fastapi==0.112.4
|
|||
huggingface-hub==1.5.*
|
||||
jinja2==3.1.6
|
||||
markdown
|
||||
mcp==1.27.0
|
||||
numpy==2.2.*
|
||||
pydantic==2.11.0
|
||||
pymupdf==1.27.*
|
||||
|
|
@ -15,8 +14,8 @@ trafilatura==2.0.0
|
|||
tqdm
|
||||
|
||||
# Gradio
|
||||
https://github.com/oobabooga/gradio/releases/download/4.37.2-custom.19/gradio-4.37.2+custom.19-py3-none-any.whl
|
||||
https://github.com/oobabooga/gradio/releases/download/4.37.2-custom.19/gradio_client-1.0.2+custom.19-py3-none-any.whl
|
||||
https://github.com/oobabooga/gradio/releases/download/4.37.2-custom.17/gradio-4.37.2+custom.17-py3-none-any.whl
|
||||
https://github.com/oobabooga/gradio/releases/download/4.37.2-custom.17/gradio_client-1.0.2+custom.17-py3-none-any.whl
|
||||
|
||||
# API
|
||||
flask_cloudflared==0.0.15
|
||||
|
|
@ -24,5 +23,5 @@ sse-starlette==1.6.5
|
|||
tiktoken
|
||||
|
||||
# ik_llama.cpp (CPU only)
|
||||
https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.110.0/ik_llama_cpp_binaries-0.110.0+cpu-py3-none-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64"
|
||||
https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.110.0/ik_llama_cpp_binaries-0.110.0+cpu-py3-none-win_amd64.whl; platform_system == "Windows"
|
||||
https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.106.0/ik_llama_cpp_binaries-0.106.0+cpu-py3-none-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64"
|
||||
https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.106.0/ik_llama_cpp_binaries-0.106.0+cpu-py3-none-win_amd64.whl; platform_system == "Windows"
|
||||
|
|
|
|||
|
|
@ -3,7 +3,6 @@ fastapi==0.112.4
|
|||
huggingface-hub==1.5.*
|
||||
jinja2==3.1.6
|
||||
markdown
|
||||
mcp==1.27.0
|
||||
numpy==2.2.*
|
||||
pydantic==2.11.0
|
||||
pymupdf==1.27.*
|
||||
|
|
@ -15,8 +14,8 @@ trafilatura==2.0.0
|
|||
tqdm
|
||||
|
||||
# Gradio
|
||||
https://github.com/oobabooga/gradio/releases/download/4.37.2-custom.19/gradio-4.37.2+custom.19-py3-none-any.whl
|
||||
https://github.com/oobabooga/gradio/releases/download/4.37.2-custom.19/gradio_client-1.0.2+custom.19-py3-none-any.whl
|
||||
https://github.com/oobabooga/gradio/releases/download/4.37.2-custom.17/gradio-4.37.2+custom.17-py3-none-any.whl
|
||||
https://github.com/oobabooga/gradio/releases/download/4.37.2-custom.17/gradio_client-1.0.2+custom.17-py3-none-any.whl
|
||||
|
||||
# API
|
||||
flask_cloudflared==0.0.15
|
||||
|
|
@ -24,5 +23,5 @@ sse-starlette==1.6.5
|
|||
tiktoken
|
||||
|
||||
# CUDA wheels
|
||||
https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.110.0/ik_llama_cpp_binaries-0.110.0+cu131-py3-none-win_amd64.whl; platform_system == "Windows"
|
||||
https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.110.0/ik_llama_cpp_binaries-0.110.0+cu131-py3-none-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64"
|
||||
https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.106.0/ik_llama_cpp_binaries-0.106.0+cu131-py3-none-win_amd64.whl; platform_system == "Windows"
|
||||
https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.106.0/ik_llama_cpp_binaries-0.106.0+cu131-py3-none-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64"
|
||||
|
|
|
|||
|
|
@ -3,7 +3,6 @@ fastapi==0.112.4
|
|||
huggingface-hub==1.5.*
|
||||
jinja2==3.1.6
|
||||
markdown
|
||||
mcp==1.27.0
|
||||
numpy==2.2.*
|
||||
pydantic==2.11.0
|
||||
pymupdf==1.27.*
|
||||
|
|
@ -15,8 +14,8 @@ trafilatura==2.0.0
|
|||
tqdm
|
||||
|
||||
# Gradio
|
||||
https://github.com/oobabooga/gradio/releases/download/4.37.2-custom.19/gradio-4.37.2+custom.19-py3-none-any.whl
|
||||
https://github.com/oobabooga/gradio/releases/download/4.37.2-custom.19/gradio_client-1.0.2+custom.19-py3-none-any.whl
|
||||
https://github.com/oobabooga/gradio/releases/download/4.37.2-custom.17/gradio-4.37.2+custom.17-py3-none-any.whl
|
||||
https://github.com/oobabooga/gradio/releases/download/4.37.2-custom.17/gradio_client-1.0.2+custom.17-py3-none-any.whl
|
||||
|
||||
# API
|
||||
flask_cloudflared==0.0.15
|
||||
|
|
|
|||
|
|
@ -3,7 +3,6 @@ fastapi==0.112.4
|
|||
huggingface-hub==1.5.*
|
||||
jinja2==3.1.6
|
||||
markdown
|
||||
mcp==1.27.0
|
||||
numpy==2.2.*
|
||||
pydantic==2.11.0
|
||||
pymupdf==1.27.*
|
||||
|
|
@ -15,8 +14,8 @@ trafilatura==2.0.0
|
|||
tqdm
|
||||
|
||||
# Gradio
|
||||
https://github.com/oobabooga/gradio/releases/download/4.37.2-custom.19/gradio-4.37.2+custom.19-py3-none-any.whl
|
||||
https://github.com/oobabooga/gradio/releases/download/4.37.2-custom.19/gradio_client-1.0.2+custom.19-py3-none-any.whl
|
||||
https://github.com/oobabooga/gradio/releases/download/4.37.2-custom.17/gradio-4.37.2+custom.17-py3-none-any.whl
|
||||
https://github.com/oobabooga/gradio/releases/download/4.37.2-custom.17/gradio_client-1.0.2+custom.17-py3-none-any.whl
|
||||
|
||||
# API
|
||||
flask_cloudflared==0.0.15
|
||||
|
|
@ -24,5 +23,5 @@ sse-starlette==1.6.5
|
|||
tiktoken
|
||||
|
||||
# Vulkan wheels
|
||||
https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.110.0/llama_cpp_binaries-0.110.0+vulkan-py3-none-win_amd64.whl; platform_system == "Windows"
|
||||
https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.110.0/llama_cpp_binaries-0.110.0+vulkan-py3-none-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64"
|
||||
https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.106.0/llama_cpp_binaries-0.106.0+vulkan-py3-none-win_amd64.whl; platform_system == "Windows"
|
||||
https://github.com/oobabooga/llama-cpp-binaries/releases/download/v0.106.0/llama_cpp_binaries-0.106.0+vulkan-py3-none-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64"
|
||||
|
|
|
|||
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