merge upstream

.devops/musa.Dockerfile

@@ -1,6 +1,6 @@
 ARG UBUNTU_VERSION=22.04
 # This needs to generally match the container host's environment.
-ARG MUSA_VERSION=rc3.1.0
+ARG MUSA_VERSION=rc3.1.1
 # Target the MUSA build image
 ARG BASE_MUSA_DEV_CONTAINER=mthreads/musa:${MUSA_VERSION}-devel-ubuntu${UBUNTU_VERSION}
 

.github/workflows/build.yml

@@ -403,6 +403,34 @@ jobs:
           # This is using llvmpipe and runs slower than other backends
           ctest -L main --verbose --timeout 1800
 
+      - name: Determine tag name
+        id: tag
+        shell: bash
+        run: |
+          BUILD_NUMBER="$(git rev-list --count HEAD)"
+          SHORT_HASH="$(git rev-parse --short=7 HEAD)"
+          if [[ "${{ env.BRANCH_NAME }}" == "master" ]]; then
+            echo "name=b${BUILD_NUMBER}" >> $GITHUB_OUTPUT
+          else
+            SAFE_NAME=$(echo "${{ env.BRANCH_NAME }}" | tr '/' '-')
+            echo "name=${SAFE_NAME}-b${BUILD_NUMBER}-${SHORT_HASH}" >> $GITHUB_OUTPUT
+          fi
+
+      - name: Pack artifacts
+        id: pack_artifacts
+        if: ${{ ( github.event_name == 'push' && github.ref == 'refs/heads/master' ) || github.event.inputs.create_release == 'true' }}
+        run: |
+          cp LICENSE ./build/bin/
+          cp examples/run/linenoise.cpp/LICENSE ./build/bin/LICENSE.linenoise.cpp
+          zip -r llama-${{ steps.tag.outputs.name }}-bin-ubuntu-vulkan-x64.zip ./build/bin/*
+
+      - name: Upload artifacts
+        if: ${{ ( github.event_name == 'push' && github.ref == 'refs/heads/master' ) || github.event.inputs.create_release == 'true' }}
+        uses: actions/upload-artifact@v4
+        with:
+          path: llama-${{ steps.tag.outputs.name }}-bin-ubuntu-vulkan-x64.zip
+          name: llama-bin-ubuntu-vulkan-x64.zip
+
   ubuntu-22-cmake-hip:
     runs-on: ubuntu-22.04
     container: rocm/dev-ubuntu-22.04:6.0.2
@@ -443,7 +471,7 @@ jobs:
 
   ubuntu-22-cmake-musa:
     runs-on: ubuntu-22.04
-    container: mthreads/musa:rc3.1.0-devel-ubuntu22.04
+    container: mthreads/musa:rc3.1.1-devel-ubuntu22.04
 
     steps:
       - name: Clone

README.md

@@ -235,6 +235,7 @@ Instructions for adding support for new models: [HOWTO-add-model.md](docs/develo
 | [HIP](docs/build.md#hip) | AMD GPU |
 | [Vulkan](docs/build.md#vulkan) | GPU |
 | [CANN](docs/build.md#cann) | Ascend NPU |
+| [OpenCL](docs/backend/OPENCL.md) | Adreno GPU |
 
 ## Building the project
 
@@ -518,5 +519,18 @@ If your issue is with model generation quality, then please at least scan the fo
     - [Aligning language models to follow instructions](https://openai.com/research/instruction-following)
     - [Training language models to follow instructions with human feedback](https://arxiv.org/abs/2203.02155)
 
-#### References
-
+## Completions
+Command-line completion is available for some environments.
+
+#### Bash Completion
+```bash
+$ build/bin/llama-cli --completion-bash > ~/.llama-completion.bash
+$ source ~/.llama-completion.bash
+```
+Optionally this can be added to your `.bashrc` or `.bash_profile` to load it
+automatically. For example:
+```console
+$ echo "source ~/.llama-completion.bash" >> ~/.bashrc
+```
+
+## References

common/arg.cpp

@@ -365,6 +365,108 @@ static void common_params_print_usage(common_params_context & ctx_arg) {
     print_options(specific_options);
 }
 
+static void common_params_print_completion(common_params_context & ctx_arg) {
+    std::vector<common_arg *> common_options;
+    std::vector<common_arg *> sparam_options;
+    std::vector<common_arg *> specific_options;
+
+    for (auto & opt : ctx_arg.options) {
+        if (opt.is_sparam) {
+            sparam_options.push_back(&opt);
+        } else if (opt.in_example(ctx_arg.ex)) {
+            specific_options.push_back(&opt);
+        } else {
+            common_options.push_back(&opt);
+        }
+    }
+
+    printf("_llama_completions() {\n");
+    printf("    local cur prev opts\n");
+    printf("    COMPREPLY=()\n");
+    printf("    cur=\"${COMP_WORDS[COMP_CWORD]}\"\n");
+    printf("    prev=\"${COMP_WORDS[COMP_CWORD-1]}\"\n\n");
+
+    printf("    opts=\"");
+    auto print_options = [](const std::vector<common_arg *> & options) {
+        for (const common_arg * opt : options) {
+            for (const char * arg : opt->args) {
+                printf("%s ", arg);
+            }
+        }
+    };
+
+    print_options(common_options);
+    print_options(sparam_options);
+    print_options(specific_options);
+    printf("\"\n\n");
+
+    printf("    case \"$prev\" in\n");
+    printf("        --model)\n");
+    printf("            COMPREPLY=( $(compgen -f -X '!*.gguf' -- \"$cur\") $(compgen -d -- \"$cur\") )\n");
+    printf("            return 0\n");
+    printf("            ;;\n");
+    printf("        --grammar-file)\n");
+    printf("            COMPREPLY=( $(compgen -f -X '!*.gbnf' -- \"$cur\") $(compgen -d -- \"$cur\") )\n");
+    printf("            return 0\n");
+    printf("            ;;\n");
+    printf("        *)\n");
+    printf("            COMPREPLY=( $(compgen -W \"${opts}\" -- \"$cur\") )\n");
+    printf("            return 0\n");
+    printf("            ;;\n");
+    printf("    esac\n");
+    printf("}\n\n");
+
+    std::set<std::string> executables = {
+        "llama-batched",
+        "llama-batched-bench",
+        "llama-bench",
+        "llama-cli",
+        "llama-convert-llama2c-to-ggml",
+        "llama-cvector-generator",
+        "llama-embedding",
+        "llama-eval-callback",
+        "llama-export-lora",
+        "llama-gbnf-validator",
+        "llama-gen-docs",
+        "llama-gguf",
+        "llama-gguf-hash",
+        "llama-gguf-split",
+        "llama-gritlm",
+        "llama-imatrix",
+        "llama-infill",
+        "llama-llava-cli",
+        "llama-llava-clip-quantize-cli",
+        "llama-lookahead",
+        "llama-lookup",
+        "llama-lookup-create",
+        "llama-lookup-merge",
+        "llama-lookup-stats",
+        "llama-minicpmv-cli",
+        "llama-parallel",
+        "llama-passkey",
+        "llama-perplexity",
+        "llama-q8dot",
+        "llama-quantize",
+        "llama-quantize-stats",
+        "llama-qwen2vl-cli",
+        "llama-retrieval",
+        "llama-run",
+        "llama-save-load-state",
+        "llama-server",
+        "llama-simple",
+        "llama-simple-chat",
+        "llama-speculative",
+        "llama-speculative-simple",
+        "llama-tokenize",
+        "llama-tts",
+        "llama-vdot"
+    };
+
+    for (const auto& exe : executables) {
+        printf("complete -F _llama_completions %s\n", exe.c_str());
+    }
+}
+
 static std::vector<ggml_backend_dev_t> parse_device_list(const std::string & value) {
     std::vector<ggml_backend_dev_t> devices;
     auto dev_names = string_split<std::string>(value, ',');
@@ -426,6 +528,10 @@ bool common_params_parse(int argc, char ** argv, common_params & params, llama_e
             }
             exit(0);
         }
+        if (ctx_arg.params.completion) {
+            common_params_print_completion(ctx_arg);
+            exit(0);
+        }
     } catch (const std::invalid_argument & ex) {
         fprintf(stderr, "%s\n", ex.what());
         ctx_arg.params = params_org;
@@ -494,6 +600,13 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
             exit(0);
         }
     ));
+    add_opt(common_arg(
+        {"--completion-bash"},
+        "print source-able bash completion script for llama.cpp",
+        [](common_params & params) {
+            params.completion = true;
+        }
+    ));
     add_opt(common_arg(
         {"--verbose-prompt"},
         string_format("print a verbose prompt before generation (default: %s)", params.verbose_prompt ? "true" : "false"),
@@ -946,6 +1059,13 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
             params.sampling.min_p = std::stof(value);
         }
     ).set_sparam());
+    add_opt(common_arg(
+        {"--top-nsigma"}, "N",
+        string_format("top-n-sigma sampling (default: %.1f, -1.0 = disabled)", params.sampling.top_n_sigma),
+        [](common_params & params, const std::string & value) {
+            params.sampling.top_n_sigma = std::stof(value);
+        }
+    ).set_examples({LLAMA_EXAMPLE_MAIN}).set_sparam());
     add_opt(common_arg(
         {"--xtc-probability"}, "N",
         string_format("xtc probability (default: %.1f, 0.0 = disabled)", (double)params.sampling.xtc_probability),
@@ -1975,6 +2095,17 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
             params.use_jinja = true;
         }
     ).set_examples({LLAMA_EXAMPLE_SERVER, LLAMA_EXAMPLE_MAIN}).set_env("LLAMA_ARG_JINJA"));
+    add_opt(common_arg(
+        {"--reasoning-format"}, "FORMAT",
+        "reasoning format (default: deepseek; allowed values: deepseek, none)\n"
+        "controls whether thought tags are extracted from the response, and in which format they're returned. 'none' leaves thoughts unparsed in `message.content`, 'deepseek' puts them in `message.reasoning_content` (for DeepSeek R1 & Command R7B only).\n"
+        "only supported for non-streamed responses",
+        [](common_params & params, const std::string & value) {
+            /**/ if (value == "deepseek") { params.reasoning_format = COMMON_REASONING_FORMAT_DEEPSEEK; }
+            else if (value == "none") {     params.reasoning_format = COMMON_REASONING_FORMAT_NONE; }
+            else { std::invalid_argument("invalid value"); }
+        }
+    ).set_examples({LLAMA_EXAMPLE_SERVER, LLAMA_EXAMPLE_MAIN}).set_env("LLAMA_ARG_THINK"));
     add_opt(common_arg(
         {"--chat-template"}, "JINJA_TEMPLATE",
         string_format(