A local-first private AI assistant for everyday use. Runs on-device models with encrypted P2P sync, and supports sharing chats publicly on ATProto.
Merge pull request #97 from tilesprivacy/build/pkg-build-enhancements
portable installer + pkg enhancements
authored by
Anandu Pavanan
and committed by
GitHub
09005518
2d836329
+461
-138
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CHANGELOG.md
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CHANGELOG.md
···
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## [Unreleased]
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## [0.4.4] - 2026-03-16
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### Added
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- Added a core daemon process which will be useful for handling background processes in https://github.com/tilesprivacy/tiles/pull/102
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- Use `tiles daemon stop` and `tiles daemon start` for starting and stopping the daemon explicitly. NOTE: daemon will auto-start when you run `tiles`.
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- Added support for fully offline/portable installer in https://github.com/tilesprivacy/tiles/pull/97
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## [0.4.3] - 2026-03-08
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### Added
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Cargo.lock
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Cargo.lock
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justfile
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justfile
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mem-agent
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mem-agent
···
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FROM driaforall/mem-agent-mlx-4bit
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modelfiles/qwen
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modelfiles/qwen
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pkg/build.sh
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pkg/build.sh
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MODELFILE_DIR="modelfiles"
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SERVER_DIR="server"
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BINARY_NAME="tiles"
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-
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MODELS_DIR="models"
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VERSION=$(grep '^version' tiles/Cargo.toml | head -1 | awk -F'"' '{print $2}')
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OS=$(uname -s | tr '[:upper:]' '[:lower:]')
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ARCH=$(uname -m)
···
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cp "target/${TARGET}/${BINARY_NAME}" "${CLI_BIN_PATH}"
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chmod +x "${CLI_BIN_PATH}/tiles"
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# Signing the tiles binary
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codesign --force \
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--sign "$DEVELOPER_ID_APPLICATION"\
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--options runtime \
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--timestamp \
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--strict \
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"${CLI_BIN_PATH}/tiles"
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# Build venvstack and move to /usr/local/share/tiles
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#
···
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# Creating .pkg
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pkgbuild --root pkgroot --scripts pkg/scripts --identifier com.tilesprivacy.tiles --version "$VERSION" "tiles-${VERSION}".pkg
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pkgbuild --root pkgroot --scripts pkg/scripts --identifier com.tilesprivacy.tiles --version "$VERSION" pkg/tiles-unsigned.pkg
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# signing
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# notarizing
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pkg/build_full.sh
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pkg/build_full.sh
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#!/usr/bin/env bash
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set -euo pipefail
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VERSION=$(grep '^version' tiles/Cargo.toml | head -1 | awk -F'"' '{print $2}')
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productbuild \
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--distribution pkg/distribution.xml \
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--resources pkg/resources \
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--package-path pkg/ \
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pkg/tiles-full-unsigned.pkg
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# signing
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#
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productsign \
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--sign "$DEVELOPER_ID_INSTALLER" \
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pkg/tiles-full-unsigned.pkg \
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pkg/tiles-full.pkg
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# notarizing
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#
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# xcrun notarytool submit pkg/tiles-full.pkg \
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# --keychain-profile "tiles-notary-profile" \
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# --wait
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# # staple the approval ticket to pkg
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# xcrun stapler staple pkg/tiles-full.pkg
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rm pkg/tiles-full-unsigned.pkg
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pkg/build_model.sh
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pkg/build_model.sh
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pkg/bundle_network_installer.sh
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pkg/bundle_network_installer.sh
···
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#!/usr/bin/env bash
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set -euo pipefail
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VERSION=$(grep '^version' tiles/Cargo.toml | head -1 | awk -F'"' '{print $2}')
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productbuild \
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--distribution pkg/distribution_network.xml \
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--resources pkg/resources \
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--package-path pkg/ \
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pkg/tiles-dist-unsigned.pkg
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# signing
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productsign \
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--sign "$DEVELOPER_ID_INSTALLER" \
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pkg/tiles-dist-unsigned.pkg \
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pkg/tiles.pkg
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# notarizing
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xcrun notarytool submit pkg/tiles.pkg \
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--keychain-profile "tiles-notary-profile" \
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--wait
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# staple the approval ticket to pkg
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xcrun stapler staple pkg/tiles.pkg
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rm pkg/tiles-unsigned.pkg
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rm pkg/tiles-dist-unsigned.pkg
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pkg/distribution.xml
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pkg/distribution.xml
···
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<?xml version="1.0" encoding="utf-8"?>
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<installer-gui-script minSpecVersion="1">
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<title>Tiles</title>
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<!-- <background file="sidebar.png" mime-type="image/png" scaling="proportionally" alignment="left"/> -->
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<!-- <background-darkAqua file="sidebar.png" mime-type="image/png" scaling="proportionally" alignment="left"/> -->
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<options customize="never"/>
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<welcome file="welcome.html"/>
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<conclusion file="conclusion.html"/>
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<choices-outline>
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<line choice="app" />
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<line choice="model" />
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</choices-outline>
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<choice id="app" visible="true" start_selected="true" title="app">
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<pkg-ref id="com.tilesprivacy.tiles" onConclusion="none">tiles-unsigned.pkg</pkg-ref>
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</choice>
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<choice id="model" visible="true" start_selected="true" title="model">
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<pkg-ref id="com.tilesprivacy.tiles_models" onConclusion="none">tiles-model.pkg</pkg-ref>
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</choice>
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</installer-gui-script>
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pkg/distribution_network.xml
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pkg/distribution_network.xml
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<?xml version="1.0" encoding="utf-8"?>
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<installer-gui-script minSpecVersion="1">
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<title>Tiles</title>
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<!-- <background file="sidebar.png" mime-type="image/png" scaling="proportionally" alignment="left"/> -->
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<!-- <background-darkAqua file="sidebar.png" mime-type="image/png" scaling="proportionally" alignment="left"/> -->
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<options customize="never"/>
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<welcome file="welcome_network.html"/>
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<conclusion file="conclusion.html"/>
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<choices-outline>
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<line choice="app" />
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</choices-outline>
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<choice id="app" visible="true" start_selected="true" title="app">
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<pkg-ref id="com.tilesprivacy.tiles" onConclusion="none">tiles-unsigned.pkg</pkg-ref>
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</choice>
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</installer-gui-script>
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+43
pkg/pkg_building.md
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pkg/pkg_building.md
···
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## How the Tiles pkgs are build
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### Network Installer
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Network installer is basically Tiles without any ML models included in it.
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So when model is needed, Tiles will download it. (Maybe in a later version
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a user should be able to download from its peers locally too).
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```
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just bundle_pkg
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```
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Creates tiles.pkg, signs and notarize it
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### Offline Installer
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Offline Installer includes the default model too in it, so once
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downloaded provides a portable installer, and can work w/o
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internet forever and ever...
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```
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just bundle_model_pkg
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```
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This will bundle only the model in a .pkg.
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> We run this command only when a model is updated/added etc..
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Since this is a time taking process and is not needed to run
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in every release build
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The basic approach we will take for offline installer building is that
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we build 2 pkgs essentially, the network installer and a pkg with
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only models. Then we create a final package that has these 2 pkgs with
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the command below.
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```
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just bundle_pkg_full
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```
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Creates tiles-full.pkg, signs and notarize it
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pkg/resources/conclusion.html
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pkg/resources/conclusion.html
···
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<html>
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<head>
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<meta charset="utf-8">
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<style>
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body {
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font-family: -apple-system, BlinkMacSystemFont, "Helvetica Neue", Helvetica, Arial, sans-serif;
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font-size: 13px;
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}
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</style>
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</head>
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<body>
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<h2>Tiles Installed 🚀</h2>
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<p>The <b>tiles</b> CLI is now installed.</p>
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<p>Open Terminal and run:</p>
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<pre>tiles</pre><br>
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<p>Then complete CLI onboarding to set up your account and start using the chat interface.</p>
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<p>For more options run:</p>
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<pre>tiles --help</pre><br><br>
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<p style="font-size: 0.8em;"><i>keep on tiling...</i></p>
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</body>
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</html>
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pkg/resources/welcome.html
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pkg/resources/welcome.html
···
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<html>
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<head>
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<style>
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body {
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font-family: -apple-system, BlinkMacSystemFont, "Helvetica Neue", Helvetica, Arial, sans-serif;
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font-size: 13px;
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}
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</style>
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</head>
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<body>
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<h2>Welcome to the Offline Tiles installer.</h2>
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<p>
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Tiles is your private and secure AI assistant for everyday use. Developed as an independent open source project, made possible by wonderful sponsors.<br><br>
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This setup installs the Tiles runtime, dependencies, and the default <i>gpt-oss-20b</i> model so the system works fully offline with no additional downloads.<br><br>
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Tiles installs its CLI and runtime in <i><b>/usr/local</b></i> so that it is available system-wide. MacOS will request administrator authorization (password or Touch ID) to allow this installation.
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</p>
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</body>
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</html>
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pkg/resources/welcome_network.html
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pkg/resources/welcome_network.html
···
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<html>
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<head>
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<style>
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body {
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font-family: -apple-system, BlinkMacSystemFont, "Helvetica Neue", Helvetica, Arial, sans-serif;
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font-size: 13px;
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}
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</style>
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</head>
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<body>
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<h2>Welcome to the Network Tiles installer.</h2>
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<p>
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Tiles is your private and secure AI assistant for everyday use. Developed as an independent open source project, made possible by wonderful sponsors.<br><br>
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This setup installs the Tiles runtime and required dependencies.
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During onboarding you will be prompted to download a model.<br><br>
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Tiles installs its CLI and runtime in <i><b>/usr/local</b></i> so that it is available system-wide. MacOS will request administrator authorization (password or Touch ID) to allow this installation.
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</p>
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</body>
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</html>
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scripts/install.sh
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scripts/install.sh
···
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ENV="prod" # prod is another env, try taking it from github env
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REPO="tilesprivacy/tiles"
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# VERSION="${TILES_VERSION:-latest}"
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VERSION=$(grep '^version' tiles/Cargo.toml | head -1 | awk -F'"' '{print $2}')
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VERSION="0.4.3"
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# INSTALL_DIR="$HOME/.local/bin" # CLI install location
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INSTALL_DIR="/usr/local/bin" # CLI install location
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# SERVER_DIR="$HOME/.local/lib/tiles/server" # Python server folder
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# MODELFILE_DIR="$HOME/.local/lib/tiles/modelfiles" # Python server folder
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SERVER_DIR="/usr/local/share/tiles/server" # Python server folder
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MODELFILE_DIR="/usr/local/share/tiles/modelfiles" # Python server folder
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MODELFILE_DIR="/usr/local/share/tiles/modelfiles" # Modelfile server folder
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TMPDIR="$(mktemp -d)"
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OS=$(uname -s | tr '[:upper:]' '[:lower:]')
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server/api.py
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server/api.py
···
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async def start_model(request: StartRequest):
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"""Load the model and start the agent"""
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global _messages, _runner, _memory_path
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print(f"CACHE PATH{request.model_cache_path}")
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_messages = [ChatMessage(role="system", content=request.system_prompt)]
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_memory_path = request.memory_path
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logger.info(f"{runtime.backend}")
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runtime.backend.get_or_load_model(request.model)
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runtime.backend.get_or_load_model(request.model, request.model_cache_path)
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return {"message": "Model loaded"}
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server/backend/mlx.py
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server/backend/mlx.py
···
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import time
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import uuid
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from collections.abc import AsyncGenerator
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from pathlib import Path
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from fastapi import HTTPException
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from openai_harmony import (
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Conversation,
···
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raise HTTPException(status_code=400, detail="Downloading model failed")
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def get_or_load_model(model_spec: str, verbose: bool = True) -> MLXRunner:
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def get_or_load_model(
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model_spec: str, model_cache_path: str | None = None, verbose: bool = True
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) -> MLXRunner:
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"""Get model from cache or load it if not cached."""
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global _model_cache, _current_model_path
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# Use the existing model path resolution from cache_utils
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try:
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model_path, model_name, commit_hash = get_model_path(model_spec)
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if not model_path.exists():
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logger.info(f"Model {model_spec} not found in cache")
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raise HTTPException(
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status_code=404, detail=f"Model {model_spec} not found in cache"
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)
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except Exception as e:
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logger.info(f"Model {model_spec} not found in: {str(e)}")
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raise HTTPException(
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status_code=404, detail=f"Model {model_spec} not found: {str(e)}"
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)
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# Check if it's an MLX model
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model_path_str = str(model_path)
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# Check if we need to load a different model
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if _current_model_path != model_path_str:
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# Proactively clean up any previously loaded runner to release memory
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if _model_cache:
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try:
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for _old_runner in list(_model_cache.values()):
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try:
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_old_runner.cleanup()
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except Exception:
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pass
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finally:
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_model_cache.clear()
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model_name = model_spec
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if isinstance(model_cache_path, str):
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model_path_str = model_cache_path
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# Check if we need to load a different model
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if _current_model_path != model_path_str:
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# Proactively clean up any previously loaded runner to release memory
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if _model_cache:
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try:
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for _old_runner in list(_model_cache.values()):
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try:
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_old_runner.cleanup()
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except Exception:
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pass
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finally:
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_model_cache.clear()
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# Load new model
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if verbose:
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print(f"Loading model: {model_name}")
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# Load new model
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if verbose:
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print(f"Loading model: {model_name}")
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logger.info(f"Loading model: {model_name}")
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runner = MLXRunner(model_path_str, verbose=verbose)
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runner.load_model()
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logger.info(f"Loading model: {model_name}")
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runner = MLXRunner(model_path_str, verbose=verbose)
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runner.load_model()
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_model_cache[model_path_str] = runner
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_current_model_path = model_path_str
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_model_cache[model_path_str] = runner
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_current_model_path = model_path_str
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return runner
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else:
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logger.info(f"Model {model_name} already in memory")
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return _model_cache[_current_model_path] # pyright: ignore
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else:
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logger.info(f"Model {model_name} already in memory")
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return _model_cache[model_path_str]
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logger.info(f"Model Path {_current_model_path} already in memory")
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return _model_cache[_current_model_path] # pyright: ignore
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async def generate_chat_stream(
···
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_messages = messages
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completion_id = f"chatcmpl-{uuid.uuid4()}"
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created = int(time.time())
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runner = get_or_load_model(request.model)
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runner = get_or_load_model(request.model, None)
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if request.chat_start:
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_messages.extend(request.messages)
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# Convert messages to dict format for runner
···
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"""Generate streaming chat responses for OpenResponses API."""
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model = request.model
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created = int(time.time())
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runner = get_or_load_model(model)
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runner = get_or_load_model(model, None)
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metrics = None
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user_input_content = ""
···
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response_id = f"resp-{uuid.uuid4()}"
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msg_id = f"msg_{uuid.uuid4()}"
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created = int(time.time())
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runner = get_or_load_model(model)
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runner = get_or_load_model(model, None)
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user_input_content = ""
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+1
server/schemas.py
+1
server/schemas.py
+1
-1
server/stack/requirements/app-server/packages-app-server.txt
+1
-1
server/stack/requirements/app-server/packages-app-server.txt
+2
-2
server/stack/requirements/app-server/pylock.app-server.meta.json
+2
-2
server/stack/requirements/app-server/pylock.app-server.meta.json
···
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{
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"lock_input_hash": "sha256:c836d5cfb697330a57241b2b8f275a804178488ec906b19866809ef33c95ba81",
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"lock_version": 1,
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"locked_at": "2026-03-13T17:42:07.680623+00:00",
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"locked_at": "2026-03-15T22:15:15.536434+00:00",
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"other_inputs_hash": "sha256:63b3c2cfe2ec414938e81dace7aac779c7b902bae681618cd8827e9f16880985",
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"requirements_hash": "sha256:641adc25f61b50b1a2c832d6e2bca50ff879f623e3956bb04a5792ee8679ed57",
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"requirements_hash": "sha256:71fb833c54864760da900c69c2a0829e19fef2c6b6e8c174162fdb7f021a4eb3",
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"version_inputs_hash": "sha256:58db986b7cd72eeded675f7c9afd8138fe024fb51451131b5562922bbde3cf43"
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}
+17
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server/stack/requirements/app-server/pylock.app-server.toml
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-17
server/stack/requirements/app-server/pylock.app-server.toml
···
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[[packages]]
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name = "charset-normalizer"
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version = "3.4.5"
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version = "3.4.6"
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index = "https://pypi.org/simple"
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[[packages.wheels]]
82
-
url = "https://files.pythonhosted.org/packages/f5/48/9f34ec4bb24aa3fdba1890c1bddb97c8a4be1bd84ef5c42ac2352563ad05/charset_normalizer-3.4.5-cp313-cp313-macosx_10_13_universal2.whl"
83
-
upload-time = 2026-03-06T06:01:37Z
84
-
size = 280788
82
+
url = "https://files.pythonhosted.org/packages/1e/1d/4fdabeef4e231153b6ed7567602f3b68265ec4e5b76d6024cf647d43d981/charset_normalizer-3.4.6-cp313-cp313-macosx_10_13_universal2.whl"
83
+
upload-time = 2026-03-15T18:51:15Z
84
+
size = 294823
85
85
86
86
[packages.wheels.hashes]
87
-
sha256 = "ac59c15e3f1465f722607800c68713f9fbc2f672b9eb649fe831da4019ae9b23"
87
+
sha256 = "11afb56037cbc4b1555a34dd69151e8e069bee82e613a73bef6e714ce733585f"
88
88
89
89
[[packages.wheels]]
90
-
url = "https://files.pythonhosted.org/packages/94/0a/af49691938dfe175d71b8a929bd7e4ace2809c0c5134e28bc535660d5262/charset_normalizer-3.4.5-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl"
91
-
upload-time = 2026-03-06T06:01:43Z
92
-
size = 195572
90
+
url = "https://files.pythonhosted.org/packages/2b/58/a199d245894b12db0b957d627516c78e055adc3a0d978bc7f65ddaf7c399/charset_normalizer-3.4.6-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl"
91
+
upload-time = 2026-03-15T18:51:21Z
92
+
size = 206587
93
93
94
94
[packages.wheels.hashes]
95
-
sha256 = "0625665e4ebdddb553ab185de5db7054393af8879fb0c87bd5690d14379d6819"
95
+
sha256 = "530e8cebeea0d76bdcf93357aa5e41336f48c3dc709ac52da2bb167c5b8271d9"
96
96
97
97
[[packages.wheels]]
98
-
url = "https://files.pythonhosted.org/packages/84/31/faa6c5b9d3688715e1ed1bb9d124c384fe2fc1633a409e503ffe1c6398c1/charset_normalizer-3.4.5-cp313-cp313-musllinux_1_2_x86_64.whl"
99
-
upload-time = 2026-03-06T06:01:56Z
100
-
size = 197509
98
+
url = "https://files.pythonhosted.org/packages/53/e9/5f85f6c5e20669dbe56b165c67b0260547dea97dba7e187938833d791687/charset_normalizer-3.4.6-cp313-cp313-musllinux_1_2_x86_64.whl"
99
+
upload-time = 2026-03-15T18:51:34Z
100
+
size = 208652
101
101
102
102
[packages.wheels.hashes]
103
-
sha256 = "c7a80a9242963416bd81f99349d5f3fce1843c303bd404f204918b6d75a75fd6"
103
+
sha256 = "6cceb5473417d28edd20c6c984ab6fee6c6267d38d906823ebfe20b03d607dc2"
104
104
105
105
[[packages.wheels]]
106
-
url = "https://files.pythonhosted.org/packages/c5/60/3a621758945513adfd4db86827a5bafcc615f913dbd0b4c2ed64a65731be/charset_normalizer-3.4.5-py3-none-any.whl"
107
-
upload-time = 2026-03-06T06:03:17Z
108
-
size = 55455
106
+
url = "https://files.pythonhosted.org/packages/2a/68/687187c7e26cb24ccbd88e5069f5ef00eba804d36dde11d99aad0838ab45/charset_normalizer-3.4.6-py3-none-any.whl"
107
+
upload-time = 2026-03-15T18:53:23Z
108
+
size = 61455
109
109
110
110
[packages.wheels.hashes]
111
-
sha256 = "9db5e3fcdcee89a78c04dffb3fe33c79f77bd741a624946db2591c81b2fc85b0"
111
+
sha256 = "947cf925bc916d90adba35a64c82aace04fa39b46b52d4630ece166655905a69"
112
112
113
113
[[packages]]
114
114
name = "click"
+1
-1
tiles/Cargo.toml
+1
-1
tiles/Cargo.toml
+46
-31
tiles/src/runtime/mlx.rs
+46
-31
tiles/src/runtime/mlx.rs
···
2
2
use crate::core::chats::{Message, save_chat};
3
3
use crate::core::storage::db::get_db_conn;
4
4
use crate::runtime::RunArgs;
5
-
use crate::utils::config::{ConfigProvider, DefaultProvider, get_memory_path};
5
+
use crate::utils::config::{ConfigProvider, DefaultProvider, get_memory_path, get_model_cache};
6
6
use crate::utils::hf_model_downloader::*;
7
7
use anyhow::{Context, Result, anyhow};
8
8
use futures_util::StreamExt;
···
90
90
}
91
91
};
92
92
93
-
run_model_with_server(self, modelfile, default_modelfile, &run_args)
94
-
.await
95
-
.inspect_err(|e| eprintln!("Failed to run the model due to {e}"))
93
+
run_model_with_server(self, modelfile, default_modelfile, &run_args).await
96
94
}
97
95
98
96
#[allow(clippy::zombie_processes)]
···
404
402
default_modelfile: &Modelfile,
405
403
memory_path: &str,
406
404
) -> Result<()> {
407
-
let client = Client::new();
408
405
let model_name = modelfile.from.clone().unwrap();
409
-
let body = json!({
410
-
"model": model_name,
411
-
"memory_path": memory_path,
412
-
"system_prompt": modelfile.system.clone().unwrap_or(default_modelfile.system.clone().unwrap_or("".to_owned()))
413
-
});
414
406
415
-
let res = client
416
-
.post("http://127.0.0.1:6969/start")
417
-
.json(&body)
418
-
.send()
419
-
.await?;
420
-
match res.status() {
421
-
StatusCode::OK => Ok(()),
422
-
StatusCode::NOT_FOUND => {
423
-
println!("Downloading {}\n", model_name);
424
-
match pull_model(&model_name).await {
425
-
Ok(_) => {
426
-
println!("\nDownloading completed \n");
427
-
Ok(())
428
-
}
429
-
Err(err) => Err(anyhow::anyhow!(format!("Download failed due to {:?}", err))),
430
-
}
431
-
}
432
-
_ => Err(anyhow::anyhow!(format!(
433
-
"Failed to load model {} due to {:?}",
434
-
model_name, res
435
-
))),
407
+
if let Ok(model_cache_path) = get_model_cache(&model_name) {
408
+
load_model_in_py(modelfile, default_modelfile, memory_path, &model_cache_path).await
409
+
} else {
410
+
download_model(&model_name).await?;
411
+
let model_cache_path = get_model_cache(&model_name)?;
412
+
load_model_in_py(modelfile, default_modelfile, memory_path, &model_cache_path).await
436
413
}
437
414
}
438
415
···
649
626
vec![dev_msg, input]
650
627
}
651
628
}
629
+
630
+
async fn load_model_in_py(
631
+
modelfile: &Modelfile,
632
+
default_modelfile: &Modelfile,
633
+
memory_path: &str,
634
+
model_cache_path: &PathBuf,
635
+
) -> Result<()> {
636
+
let client = Client::new();
637
+
let model_name = modelfile.from.clone().unwrap();
638
+
let body = json!({
639
+
"model": model_name,
640
+
"memory_path": memory_path,
641
+
"model_cache_path": model_cache_path,
642
+
"system_prompt": modelfile.system.clone().unwrap_or(default_modelfile.system.clone().unwrap_or("".to_owned()))
643
+
});
644
+
let res = client
645
+
.post("http://127.0.0.1:6969/start")
646
+
.json(&body)
647
+
.send()
648
+
.await?;
649
+
match res.status() {
650
+
StatusCode::OK => Ok(()),
651
+
_ => Err(anyhow::anyhow!(format!(
652
+
"Failed to load model {} due to {:?}",
653
+
model_name, res
654
+
))),
655
+
}
656
+
}
657
+
658
+
async fn download_model(model_name: &str) -> Result<()> {
659
+
match pull_model(model_name).await {
660
+
Ok(_) => {
661
+
println!("\nDownloading completed \n");
662
+
Ok(())
663
+
}
664
+
Err(err) => Err(anyhow::anyhow!(format!("Download failed due to {:?}", err))),
665
+
}
666
+
}
+69
-1
tiles/src/utils/config.rs
+69
-1
tiles/src/utils/config.rs
···
12
12
/// - /usr/local/share/tiles (lib dir) - Some internal App files, libraries etc go here..
13
13
/// - /modelfiles
14
14
/// - /server
15
+
/// - /models - Where the pre-downloaded models.
15
16
use anyhow::{Context, Result, anyhow};
16
17
use std::fs::File;
17
18
use std::path::PathBuf;
18
19
use std::str::FromStr;
20
+
use std::time::SystemTime;
19
21
use std::{env, fs};
20
22
use toml::Table;
21
23
24
+
const MODEL_SUB_PATH: &str = "models/huggingface/hub";
22
25
pub trait ConfigProvider {
23
26
fn get_config_dir(&self) -> Result<PathBuf>;
24
27
fn get_or_create_config_dir(&self) -> Result<PathBuf>;
···
115
118
fn get_lib_dir(&self) -> Result<PathBuf> {
116
119
if cfg!(debug_assertions) {
117
120
let base_dir = env::current_dir().context("Failed to fetch CURRENT_DIR")?;
118
-
Ok(base_dir)
121
+
Ok(base_dir.join(".tiles_dev/tiles"))
119
122
} else {
120
123
let data_dir = PathBuf::from_str("/usr/local/share")?;
121
124
Ok(data_dir.join("tiles"))
···
229
232
fs::copy(&tmp_path, &config_path)?;
230
233
fs::remove_file(tmp_path)?;
231
234
Ok(())
235
+
}
236
+
237
+
// Get the apt path where the model lies
238
+
pub fn get_model_cache(model_name: &str) -> Result<PathBuf> {
239
+
let hf_model_dir = if model_name.starts_with("mlx-community/") {
240
+
let model_spec_parts = model_name.split("/").collect::<Vec<&str>>();
241
+
format!("models--{}--{}", model_spec_parts[0], model_spec_parts[1])
242
+
} else {
243
+
return Err(anyhow!("Not implemented for non-mlx models"));
244
+
};
245
+
246
+
let lib_dir = DefaultProvider.get_lib_dir()?;
247
+
let pre_downloaded_model_path = lib_dir.join(MODEL_SUB_PATH).join(&hf_model_dir);
248
+
let data_dir = DefaultProvider.get_user_data_dir()?;
249
+
let user_data_dir_model_path = data_dir.join(MODEL_SUB_PATH).join(&hf_model_dir);
250
+
251
+
let legacy_model_path = PathBuf::from(format!(
252
+
"{}/.cache/huggingface/hub",
253
+
env::home_dir().unwrap().to_str().unwrap()
254
+
))
255
+
.join(&hf_model_dir);
256
+
257
+
if pre_downloaded_model_path.exists() {
258
+
get_commit_path(pre_downloaded_model_path)
259
+
} else if user_data_dir_model_path.exists() {
260
+
get_commit_path(user_data_dir_model_path)
261
+
} else if legacy_model_path.exists() {
262
+
get_commit_path(legacy_model_path)
263
+
} else {
264
+
Err(anyhow!("Model doesnt exist"))
265
+
}
266
+
}
267
+
268
+
fn get_commit_path(base_path: PathBuf) -> Result<PathBuf> {
269
+
let mut snapshots: Vec<(PathBuf, SystemTime)> = vec![];
270
+
let snapshot_path = base_path.join("snapshots");
271
+
if snapshot_path.exists() {
272
+
for entry in snapshot_path.read_dir()? {
273
+
if let Ok(item) = entry
274
+
&& item.path().is_dir()
275
+
{
276
+
snapshots.push((item.path(), item.path().metadata()?.modified()?));
277
+
}
278
+
}
279
+
if snapshots.is_empty() {
280
+
Ok(base_path)
281
+
} else {
282
+
let latest_snapshot = snapshots
283
+
.iter()
284
+
.max_by_key(|a| a.1)
285
+
.expect("Failed fetching latest snapshot");
286
+
Ok(latest_snapshot.0.clone())
287
+
}
288
+
} else {
289
+
Ok(base_path)
290
+
}
291
+
}
292
+
293
+
pub fn get_or_create_model_download_path() -> Result<PathBuf> {
294
+
let data_dir = DefaultProvider.get_user_data_dir()?;
295
+
let model_dir = data_dir.join(MODEL_SUB_PATH);
296
+
if !model_dir.exists() {
297
+
fs::create_dir_all(&model_dir)?;
298
+
}
299
+
Ok(model_dir)
232
300
}
233
301
234
302
//TODO: Add more tests for config.toml
+9
-22
tiles/src/utils/hf_model_downloader.rs
+9
-22
tiles/src/utils/hf_model_downloader.rs
···
1
1
/// Manages model snapshot downloading from HuggingFace
2
-
use std::{env, path::PathBuf};
3
-
2
+
use anyhow::{Result, anyhow};
4
3
use hf_hub::api::{
5
4
Siblings,
6
5
tokio::{ApiBuilder, ApiError},
7
6
};
8
7
8
+
use crate::utils::config::get_or_create_model_download_path;
9
+
9
10
/// Download the entire model (including snapshot) for the given model name
10
-
pub async fn pull_model(model_name: &str) -> Result<(), String> {
11
+
pub async fn pull_model(model_name: &str) -> Result<()> {
11
12
snapshot_download(model_name).await
12
13
}
13
14
14
-
pub async fn snapshot_download(modelname: &str) -> Result<(), String> {
15
+
pub async fn snapshot_download(modelname: &str) -> Result<()> {
15
16
let allow_patterns = [
16
17
".json",
17
18
".txt",
···
22
23
];
23
24
let api_build_result = ApiBuilder::new()
24
25
.with_progress(true)
25
-
.with_cache_dir(PathBuf::from(get_model_cache()))
26
+
.with_cache_dir(get_or_create_model_download_path()?)
26
27
.build();
27
28
28
29
match api_build_result {
···
42
43
43
44
for sibling in filtered_siblings {
44
45
if repo.get(&sibling.rfilename).await.is_err() {
45
-
return Err(format!(
46
+
return Err(anyhow!(
46
47
"{:?} failed to download, retry again",
47
48
&sibling.rfilename,
48
49
));
49
50
}
50
51
}
51
52
}
52
-
Err(err) => return Err(format_hf_api_error(err)),
53
+
Err(err) => return Err(anyhow!(format_hf_api_error(err))),
53
54
};
54
55
}
55
-
Err(err) => return Err(format_hf_api_error(err)),
56
+
Err(err) => return Err(anyhow!(format_hf_api_error(err))),
56
57
}
57
58
58
59
Ok(())
···
64
65
ApiError::TooManyRetries(err) => err.to_string(),
65
66
_err => "Something unexpected happened, check your internet connection".to_owned(),
66
67
}
67
-
}
68
-
69
-
fn get_model_cache() -> String {
70
-
let default_cache = format!(
71
-
"{}/.cache/huggingface",
72
-
env::home_dir().unwrap().to_str().unwrap()
73
-
);
74
-
let cache_root = if let Ok(home) = env::var("HF_HOME") {
75
-
home.to_owned()
76
-
} else {
77
-
default_cache
78
-
};
79
-
80
-
format!("{}/hub", cache_root)
81
68
}
82
69
83
70
#[cfg(test)]