.github/workflows/stale-prs.yml

@@ -1,55 +0,0 @@
-name: Close inactive PRs
-
-on:
-  schedule:
-    # Run daily. GitHub cron schedules use UTC.
-    - cron: "30 1 * * *"
-  workflow_dispatch:
-    inputs:
-      debug_only:
-        description: "Dry run: log intended actions without changing PRs"
-        required: false
-        default: false
-        type: boolean
-
-permissions:
-  issues: write
-  pull-requests: write
-
-concurrency:
-  group: ${{ github.workflow }}
-  cancel-in-progress: false
-
-jobs:
-  stale-prs:
-    runs-on: ubuntu-latest
-    steps:
-      - name: Mark and close inactive PRs
-        uses: actions/stale@v10
-        with:
-          days-before-issue-stale: -1
-          days-before-issue-close: -1
-
-          days-before-pr-stale: 365
-          days-before-pr-close: 7
-
-          stale-pr-label: pr:inactive
-          close-pr-label: pr:auto-closed
-          exempt-pr-labels: pr:keep-open
-
-          stale-pr-message: >
-            This PR has been inactive for 365 days. If there is no new activity
-            within 7 days, it will be closed automatically. Comment, push new
-            commits, or remove the pr:inactive label to keep it open. Add
-            pr:keep-open to exempt it from future inactive PR cleanup.
-
-          close-pr-message: >
-            Closing this PR because it has had no activity for 7 days after
-            being marked inactive. If this is still useful or ready to move
-            forward, feel free to reopen it with fresh context or updated
-            details. Sorry for any inconvenience.
-
-          remove-pr-stale-when-updated: true
-          delete-branch: false
-          operations-per-run: 100
-          debug-only: ${{ github.event_name == 'workflow_dispatch' && inputs.debug_only || false }}

README.md

@@ -15,15 +15,29 @@ API and command-line option may change frequently.***
 
 ## 🔥Important News
 
-* **2026/05/17** 🚀 stable-diffusion.cpp now supports **LTX-2.3**
 * **2026/04/11** 🚀 stable-diffusion.cpp now uses a brand-new embedded web UI.  
+  👉 Details: [PR #1408](https://github.com/leejet/stable-diffusion.cpp/pull/1408)
+
 * **2026/01/18** 🚀 stable-diffusion.cpp now supports **FLUX.2-klein**  
+  👉 Details: [PR #1193](https://github.com/leejet/stable-diffusion.cpp/pull/1193)
+
 * **2025/12/01** 🚀 stable-diffusion.cpp now supports **Z-Image**  
+  👉 Details: [PR #1020](https://github.com/leejet/stable-diffusion.cpp/pull/1020)
+
 * **2025/11/30** 🚀 stable-diffusion.cpp now supports **FLUX.2-dev**  
+  👉 Details: [PR #1016](https://github.com/leejet/stable-diffusion.cpp/pull/1016)
+
 * **2025/10/13** 🚀 stable-diffusion.cpp now supports **Qwen-Image-Edit / Qwen-Image-Edit 2509**  
+  👉 Details: [PR #877](https://github.com/leejet/stable-diffusion.cpp/pull/877)
+
 * **2025/10/12** 🚀 stable-diffusion.cpp now supports **Qwen-Image**  
+  👉 Details: [PR #851](https://github.com/leejet/stable-diffusion.cpp/pull/851)
+
 * **2025/09/14** 🚀 stable-diffusion.cpp now supports **Wan2.1 Vace**  
+  👉 Details: [PR #819](https://github.com/leejet/stable-diffusion.cpp/pull/819)
+
 * **2025/09/06** 🚀 stable-diffusion.cpp now supports **Wan2.1 / Wan2.2**  
+  👉 Details: [PR #778](https://github.com/leejet/stable-diffusion.cpp/pull/778)
 
 ## Features
 

examples/cli/README.md

@@ -105,7 +105,7 @@ Generation Options:
                                            antialiased), or a model name under --hires-upscalers-dir (default: Latent)
   --extra-sample-args <string>             extra sampler/scheduler args, key=value list. lcm supports noise_clip_std,
                                            noise_scale_start, noise_scale_end; ltx2 supports max_shift, base_shift,
-                                           stretch, terminal; euler_ge supports gamma
+                                           stretch, terminal
   -H, --height <int>                       image height, in pixel space (default: 512)
   -W, --width <int>                        image width, in pixel space (default: 512)
   --steps <int>                            number of sample steps (default: 20)

examples/common/common.cpp

@@ -833,7 +833,7 @@ ArgOptions SDGenerationParams::get_options() {
          &hires_upscaler},
         {"",
          "--extra-sample-args",
-         "extra sampler/scheduler args, key=value list. lcm supports noise_clip_std, noise_scale_start, noise_scale_end; ltx2 supports max_shift, base_shift, stretch, terminal; euler_ge supports gamma",
+         "extra sampler/scheduler args, key=value list. lcm supports noise_clip_std, noise_scale_start, noise_scale_end; ltx2 supports max_shift, base_shift, stretch, terminal",
          &extra_sample_args},
     };
 

examples/server/README.md

@@ -207,7 +207,7 @@ Default Generation Options:
                                            antialiased), or a model name under --hires-upscalers-dir (default: Latent)
   --extra-sample-args <string>             extra sampler/scheduler args, key=value list. lcm supports noise_clip_std,
                                            noise_scale_start, noise_scale_end; ltx2 supports max_shift, base_shift,
-                                           stretch, terminal; euler_ge supports gamma
+                                           stretch, terminal
   -H, --height <int>                       image height, in pixel space (default: 512)
   -W, --width <int>                        image width, in pixel space (default: 512)
   --steps <int>                            number of sample steps (default: 20)

include/stable-diffusion.h

@@ -53,7 +53,6 @@ enum sample_method_t {
     ER_SDE_SAMPLE_METHOD,
     EULER_CFG_PP_SAMPLE_METHOD,
     EULER_A_CFG_PP_SAMPLE_METHOD,
-    EULER_GE_SAMPLE_METHOD,
     SAMPLE_METHOD_COUNT
 };
 

src/denoiser.hpp

@@ -1276,52 +1276,82 @@ static sd::Tensor<float> sample_dpmpp_2m_v2(denoise_cb_t model,
     return x;
 }
 
-using SamplerExtraArgs = std::vector<std::pair<std::string, std::string>>;
-
 static sd::Tensor<float> sample_lcm(denoise_cb_t model,
                                     sd::Tensor<float> x,
                                     const std::vector<float>& sigmas,
                                     std::shared_ptr<RNG> rng,
                                     bool is_flow_denoiser,
-                                    const SamplerExtraArgs& extra_sample_args) {
+                                    const char* extra_sample_args = nullptr) {
     struct LCMSampleArgs {
         float noise_clip_std    = 0.0f;
         float noise_scale_start = 1.0f;
         float noise_scale_end   = 1.0f;
     };
 
+    auto trim = [](std::string value) -> std::string {
+        const char* whitespace = " \t\r\n";
+        size_t begin           = value.find_first_not_of(whitespace);
+        if (begin == std::string::npos) {
+            return "";
+        }
+        size_t end = value.find_last_not_of(whitespace);
+        return value.substr(begin, end - begin + 1);
+    };
+
     LCMSampleArgs args;
-    bool noise_scale_end_was_set   = false;
-    bool noise_scale_start_was_set = false;
-
-    for (const auto& [key, value] : extra_sample_args) {
-        float parsed = 0.0f;
-        try {
-            size_t consumed = 0;
-            parsed          = std::stof(value, &consumed);
-            if (trim(value.substr(consumed)).size() != 0) {
-                LOG_WARN("ignoring invalid lcm extra sample arg '%s'", key.c_str());
-                continue;
+    if (extra_sample_args != nullptr && extra_sample_args[0] != '\0') {
+        std::string raw(extra_sample_args);
+        size_t start                   = 0;
+        bool noise_scale_end_was_set   = false;
+        bool noise_scale_start_was_set = false;
+        auto parse_arg                 = [&](const std::string& item) {
+            std::string token = trim(item);
+            if (token.empty()) {
+                return;
+            }
+            size_t eq = token.find('=');
+            if (eq == std::string::npos) {
+                LOG_WARN("ignoring invalid lcm extra sample arg '%s'", token.c_str());
+                return;
             }
-        } catch (const std::exception&) {
-            LOG_WARN("ignoring invalid lcm extra sample arg '%s=%s'", key.c_str());
-            continue;
-        }
-        if (key == "noise_clip_std") {
-            args.noise_clip_std = parsed;
-        } else if (key == "noise_scale_start") {
-            args.noise_scale_start    = parsed;
-            noise_scale_start_was_set = true;
-        } else if (key == "noise_scale_end") {
-            args.noise_scale_end    = parsed;
-            noise_scale_end_was_set = true;
-        } else {
-            LOG_WARN("ignoring unknown lcm extra sample arg '%s'", key.c_str());
-        }
-    }
 
-    if (noise_scale_start_was_set && !noise_scale_end_was_set) {
-        args.noise_scale_end = args.noise_scale_start;
+            std::string key   = trim(token.substr(0, eq));
+            std::string value = trim(token.substr(eq + 1));
+            float parsed      = 0.0f;
+            try {
+                size_t consumed = 0;
+                parsed          = std::stof(value, &consumed);
+                if (trim(value.substr(consumed)).size() != 0) {
+                    LOG_WARN("ignoring invalid lcm extra sample arg '%s'", token.c_str());
+                    return;
+                }
+            } catch (const std::exception&) {
+                LOG_WARN("ignoring invalid lcm extra sample arg '%s'", token.c_str());
+                return;
+            }
+
+            if (key == "noise_clip_std") {
+                args.noise_clip_std = parsed;
+            } else if (key == "noise_scale_start") {
+                args.noise_scale_start    = parsed;
+                noise_scale_start_was_set = true;
+            } else if (key == "noise_scale_end") {
+                args.noise_scale_end    = parsed;
+                noise_scale_end_was_set = true;
+            } else {
+                LOG_WARN("ignoring unknown lcm extra sample arg '%s'", key.c_str());
+            }
+        };
+
+        for (size_t pos = 0; pos <= raw.size(); ++pos) {
+            if (pos == raw.size() || raw[pos] == ',' || raw[pos] == ';') {
+                parse_arg(raw.substr(start, pos - start));
+                start = pos + 1;
+            }
+        }
+        if (noise_scale_start_was_set && !noise_scale_end_was_set) {
+            args.noise_scale_end = args.noise_scale_start;
+        }
     }
 
     int steps = static_cast<int>(sigmas.size()) - 1;
@@ -1849,113 +1879,6 @@ static sd::Tensor<float> sample_euler_ancestral_cfg_pp(denoise_cb_t model,
     return x;
 }
 
-// https://github.com/ToyotaResearchInstitute/gradient-estimation-sampler
-static sd::Tensor<float> sample_gradient_estimation(denoise_cb_t model,
-                                                    sd::Tensor<float> x,
-                                                    const std::vector<float>& sigmas,
-                                                    std::shared_ptr<RNG> rng,
-                                                    bool is_flow_denoiser,
-                                                    float eta,
-                                                    const SamplerExtraArgs& extra_sample_args) {
-    float ge_gamma = 2.0f;
-
-    for (const auto& [key, value] : extra_sample_args) {
-        float parsed = 0.0f;
-        try {
-            size_t consumed = 0;
-            parsed          = std::stof(value, &consumed);
-            if (trim(value.substr(consumed)).size() != 0) {
-                LOG_WARN("ignoring invalid euler_ge extra sample arg '%s'", key.c_str());
-                continue;
-            }
-        } catch (const std::exception&) {
-            LOG_WARN("ignoring invalid euler_ge extra sample arg '%s'", key.c_str());
-            continue;
-        }
-        if (key == "gamma") {
-            LOG_DEBUG("setting euler_ge gamma to %.2f", parsed);
-            ge_gamma = parsed;
-        } else {
-            LOG_WARN("ignoring unknown euler_ge extra sample arg '%s'", key.c_str());
-        }
-    }
-
-    int steps = static_cast<int>(sigmas.size()) - 1;
-    sd::Tensor<float> old_d;
-    bool has_old_d = false;
-    for (int i = 0; i < steps; i++) {
-        float sigma       = sigmas[i];
-        float sigma_to    = sigmas[i + 1];
-        auto denoised_opt = model(x, sigma, i + 1);
-        if (denoised_opt.pred.empty()) {
-            return {};
-        }
-        sd::Tensor<float> denoised = std::move(denoised_opt.pred);
-        if (sigma_to == 0.f) {
-            x = denoised;
-        } else {
-            auto [sigma_down, sigma_up, alpha_scale] = get_ancestral_step(sigma, sigma_to, eta, is_flow_denoiser);
-            sd::Tensor<float> d                      = (x - denoised) / sigma;
-            float dt                                 = sigma_down - sigma;
-            if (has_old_d) {
-                sd::Tensor<float> d_bar = d * ge_gamma + old_d * (1.0f - ge_gamma);
-                x += d_bar * dt;
-            } else {
-                x += d * dt;
-            }
-            old_d     = std::move(d);
-            has_old_d = true;
-            if (sigma_up > 0.f) {
-                if (is_flow_denoiser) {
-                    x *= alpha_scale;
-                }
-                x += sd::Tensor<float>::randn_like(x, rng) * sigma_up;
-            }
-        }
-    }
-    return x;
-}
-
-static SamplerExtraArgs parse_sampler_args(const char* extra_sample_args) {
-    SamplerExtraArgs pairs;
-
-    if (extra_sample_args == nullptr || extra_sample_args[0] == '\0') {
-        return pairs;
-    }
-
-    auto trim = [](std::string value) -> std::string {
-        const char* whitespace = " \t\r\n";
-        size_t begin           = value.find_first_not_of(whitespace);
-        if (begin == std::string::npos) {
-            return "";
-        }
-        size_t end = value.find_last_not_of(whitespace);
-        return value.substr(begin, end - begin + 1);
-    };
-
-    std::string raw(extra_sample_args);
-    size_t start = 0;
-
-    for (size_t pos = 0; pos <= raw.size(); ++pos) {
-        if (pos == raw.size() || raw[pos] == ',' || raw[pos] == ';') {
-            std::string item  = raw.substr(start, pos - start);
-            std::string token = trim(item);
-
-            if (!token.empty()) {
-                size_t eq = token.find('=');
-                if (eq != std::string::npos) {
-                    std::string key   = trim(token.substr(0, eq));
-                    std::string value = trim(token.substr(eq + 1));
-                    pairs.emplace_back(std::move(key), std::move(value));
-                }
-            }
-            start = pos + 1;
-        }
-    }
-
-    return pairs;
-}
-
 // k diffusion reverse ODE: dx = (x - D(x;\sigma)) / \sigma dt; \sigma(t) = t
 static sd::Tensor<float> sample_k_diffusion(sample_method_t method,
                                             denoise_cb_t model,
@@ -1965,7 +1888,6 @@ static sd::Tensor<float> sample_k_diffusion(sample_method_t method,
                                             float eta,
                                             bool is_flow_denoiser,
                                             const char* extra_sample_args) {
-    SamplerExtraArgs extra_args = parse_sampler_args(extra_sample_args);
     switch (method) {
         case EULER_A_SAMPLE_METHOD:
             return sample_euler_ancestral(model, std::move(x), sigmas, rng, is_flow_denoiser, eta);
@@ -1985,7 +1907,7 @@ static sd::Tensor<float> sample_k_diffusion(sample_method_t method,
         case DPMPP2Mv2_SAMPLE_METHOD:
             return sample_dpmpp_2m_v2(model, std::move(x), sigmas);
         case LCM_SAMPLE_METHOD:
-            return sample_lcm(model, std::move(x), sigmas, rng, is_flow_denoiser, extra_args);
+            return sample_lcm(model, std::move(x), sigmas, rng, is_flow_denoiser, extra_sample_args);
         case IPNDM_SAMPLE_METHOD:
             return sample_ipndm(model, std::move(x), sigmas);
         case IPNDM_V_SAMPLE_METHOD:
@@ -2005,8 +1927,6 @@ static sd::Tensor<float> sample_k_diffusion(sample_method_t method,
             return sample_euler_cfg_pp(model, std::move(x), sigmas);
         case EULER_A_CFG_PP_SAMPLE_METHOD:
             return sample_euler_ancestral_cfg_pp(model, std::move(x), sigmas, rng, eta);
-        case EULER_GE_SAMPLE_METHOD:
-            return sample_gradient_estimation(model, std::move(x), sigmas, rng, is_flow_denoiser, eta, extra_args);
         default:
             return {};
     }

src/stable-diffusion.cpp

@@ -81,7 +81,6 @@ const char* sampling_methods_str[] = {
     "ER-SDE",
     "Euler CFG++",
     "Euler A CFG++",
-    "Euler GE",
 };
 
 /*================================================== Helper Functions ================================================*/
@@ -2283,7 +2282,6 @@ const char* sample_method_to_str[] = {
     "er_sde",
     "euler_cfg_pp",
     "euler_a_cfg_pp",
-    "euler_ge",
 };
 
 const char* sd_sample_method_name(enum sample_method_t sample_method) {

src/tokenizers/vocab/vocab.cpp

@@ -1,11 +1,9 @@
 #include "vocab.h"
-#include "clip_merges.hpp"
+#include "clip_t5.hpp"
 #include "gemma_merges.hpp"
 #include "gemma_vocab.hpp"
-#include "mistral_merges.hpp"
-#include "mistral_vocab.hpp"
-#include "qwen_merges.hpp"
-#include "t5.hpp"
+#include "mistral.hpp"
+#include "qwen.hpp"
 #include "umt5.hpp"
 
 std::string load_clip_merges() {