Merge commit '4df6e859e92dac52536f735785bb9e0a3bc63e2b' into concedo_experimental

# Conflicts:
#	.github/workflows/build.yml
#	README.md
#	ci/run.sh
#	examples/gen-docs/gen-docs.cpp
#	scripts/snapdragon/adb/run-cli.sh
#	tests/test-lora-conversion-inference.sh
#	tools/CMakeLists.txt
#	tools/completion/CMakeLists.txt
#	tools/completion/README.md
#	tools/server/CMakeLists.txt
This commit is contained in:
Concedo
2025-12-12 17:23:25 +08:00
18 changed files with 690 additions and 101 deletions
+2 -2
View File
@@ -766,9 +766,9 @@ clean:
rm -vrf llguidance
# useful tools
main: tools/main/main.cpp common/arg.cpp common/download.cpp build-info.h ggml.o ggml-cpu.o ggml-ops.o ggml-vec.o ggml-binops.o ggml-unops.o llama.o console.o llavaclip_default.o llava.o ggml-backend_default.o ggml-backend-reg_default.o ggml-repack.o $(OBJS_FULL) $(OBJS)
main: tools/completion/completion.cpp common/arg.cpp common/download.cpp build-info.h ggml.o ggml-cpu.o ggml-ops.o ggml-vec.o ggml-binops.o ggml-unops.o llama.o console.o llavaclip_default.o llava.o ggml-backend_default.o ggml-backend-reg_default.o ggml-repack.o $(OBJS_FULL) $(OBJS)
$(CXX) $(CXXFLAGS) $(filter-out %.h,$^) -o $@ $(LDFLAGS)
mainvk: tools/main/main.cpp common/arg.cpp common/download.cpp build-info.h ggml_v4_vulkan.o ggml-cpu.o ggml-ops.o ggml-vec.o ggml-binops.o ggml-unops.o llama.o console.o llavaclip_vulkan.o llava.o ggml-backend_vulkan.o ggml-backend-reg_vulkan.o ggml-vulkan.o ggml-vulkan-shaders.o ggml-repack.o $(OBJS_FULL) $(OBJS) lib/vulkan-1.lib
mainvk: tools/completion/completion.cpp common/arg.cpp common/download.cpp build-info.h ggml_v4_vulkan.o ggml-cpu.o ggml-ops.o ggml-vec.o ggml-binops.o ggml-unops.o llama.o console.o llavaclip_vulkan.o llava.o ggml-backend_vulkan.o ggml-backend-reg_vulkan.o ggml-vulkan.o ggml-vulkan-shaders.o ggml-repack.o $(OBJS_FULL) $(OBJS) lib/vulkan-1.lib
$(CXX) $(CXXFLAGS) -DGGML_USE_VULKAN -DSD_USE_VULKAN $(filter-out %.h,$^) -o $@ $(LDFLAGS)
sdmain: otherarch/sdcpp/util.cpp otherarch/sdcpp/main.cpp otherarch/sdcpp/stable-diffusion.cpp otherarch/sdcpp/upscaler.cpp otherarch/sdcpp/model.cpp otherarch/sdcpp/name_conversion.cpp otherarch/sdcpp/tokenize_util.cpp otherarch/sdcpp/thirdparty/zip.c build-info.h ggml.o ggml-cpu.o ggml-ops.o ggml-vec.o ggml-binops.o ggml-unops.o llama.o console.o ggml-backend_default.o ggml-backend-reg_default.o ggml-repack.o $(OBJS_FULL) $(OBJS)
$(CXX) $(CXXFLAGS) $(filter-out %.h,$^) -o $@ $(LDFLAGS)
+61 -53
View File
@@ -53,6 +53,7 @@ using json = nlohmann::ordered_json;
static std::initializer_list<enum llama_example> mmproj_examples = {
LLAMA_EXAMPLE_MTMD,
LLAMA_EXAMPLE_SERVER,
LLAMA_EXAMPLE_CLI,
};
static std::string read_file(const std::string & fname) {
@@ -470,6 +471,8 @@ static bool common_params_parse_ex(int argc, char ** argv, common_params_context
));
}
common_log_set_verbosity_thold(params.verbosity);
return true;
}
@@ -792,7 +795,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
[](common_params & params) {
params.display_prompt = false;
}
).set_examples({LLAMA_EXAMPLE_MAIN}));
).set_examples({LLAMA_EXAMPLE_COMPLETION, LLAMA_EXAMPLE_CLI}));
add_opt(common_arg(
{"-co", "--color"}, "[on|off|auto]",
"Colorize output to distinguish prompt and user input from generations ('on', 'off', or 'auto', default: 'auto')\n"
@@ -809,7 +812,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
string_format("error: unknown value for --color: '%s'\n", value.c_str()));
}
}
).set_examples({LLAMA_EXAMPLE_MAIN, LLAMA_EXAMPLE_SPECULATIVE, LLAMA_EXAMPLE_LOOKUP}));
).set_examples({LLAMA_EXAMPLE_COMPLETION, LLAMA_EXAMPLE_CLI, LLAMA_EXAMPLE_SPECULATIVE, LLAMA_EXAMPLE_LOOKUP}));
add_opt(common_arg(
{"-t", "--threads"}, "N",
string_format("number of CPU threads to use during generation (default: %d)", params.cpuparams.n_threads),
@@ -942,7 +945,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
add_opt(common_arg(
{"-n", "--predict", "--n-predict"}, "N",
string_format(
ex == LLAMA_EXAMPLE_MAIN
ex == LLAMA_EXAMPLE_COMPLETION
? "number of tokens to predict (default: %d, -1 = infinity, -2 = until context filled)"
: "number of tokens to predict (default: %d, -1 = infinity)",
params.n_predict),
@@ -986,7 +989,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
[](common_params & params, int value) {
params.n_ctx_checkpoints = value;
}
).set_env("LLAMA_ARG_CTX_CHECKPOINTS").set_examples({LLAMA_EXAMPLE_SERVER}));
).set_env("LLAMA_ARG_CTX_CHECKPOINTS").set_examples({LLAMA_EXAMPLE_SERVER, LLAMA_EXAMPLE_CLI}));
add_opt(common_arg(
{"--cache-ram", "-cram"}, "N",
string_format("set the maximum cache size in MiB (default: %d, -1 - no limit, 0 - disable)\n"
@@ -994,7 +997,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
[](common_params & params, int value) {
params.cache_ram_mib = value;
}
).set_env("LLAMA_ARG_CACHE_RAM").set_examples({LLAMA_EXAMPLE_SERVER}));
).set_env("LLAMA_ARG_CACHE_RAM").set_examples({LLAMA_EXAMPLE_SERVER, LLAMA_EXAMPLE_CLI}));
add_opt(common_arg(
{"--kv-unified", "-kvu"},
string_format("use single unified KV buffer for the KV cache of all sequences (default: %s)\n"
@@ -1009,14 +1012,14 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
[](common_params & params) {
params.ctx_shift = false;
}
).set_examples({LLAMA_EXAMPLE_MAIN, LLAMA_EXAMPLE_SERVER, LLAMA_EXAMPLE_IMATRIX, LLAMA_EXAMPLE_PERPLEXITY}).set_env("LLAMA_ARG_NO_CONTEXT_SHIFT"));
).set_examples({LLAMA_EXAMPLE_COMPLETION, LLAMA_EXAMPLE_CLI, LLAMA_EXAMPLE_SERVER, LLAMA_EXAMPLE_IMATRIX, LLAMA_EXAMPLE_PERPLEXITY}).set_env("LLAMA_ARG_NO_CONTEXT_SHIFT"));
add_opt(common_arg(
{"--context-shift"},
string_format("enables context shift on infinite text generation (default: %s)", params.ctx_shift ? "enabled" : "disabled"),
[](common_params & params) {
params.ctx_shift = true;
}
).set_examples({LLAMA_EXAMPLE_MAIN, LLAMA_EXAMPLE_SERVER, LLAMA_EXAMPLE_IMATRIX, LLAMA_EXAMPLE_PERPLEXITY}).set_env("LLAMA_ARG_CONTEXT_SHIFT"));
).set_examples({LLAMA_EXAMPLE_COMPLETION, LLAMA_EXAMPLE_CLI, LLAMA_EXAMPLE_SERVER, LLAMA_EXAMPLE_IMATRIX, LLAMA_EXAMPLE_PERPLEXITY}).set_env("LLAMA_ARG_CONTEXT_SHIFT"));
add_opt(common_arg(
{"--chunks"}, "N",
string_format("max number of chunks to process (default: %d, -1 = all)", params.n_chunks),
@@ -1052,7 +1055,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
[](common_params & params, const std::string & value) {
params.system_prompt = value;
}
).set_examples({LLAMA_EXAMPLE_MAIN, LLAMA_EXAMPLE_DIFFUSION}));
).set_examples({LLAMA_EXAMPLE_COMPLETION, LLAMA_EXAMPLE_CLI, LLAMA_EXAMPLE_DIFFUSION}));
add_opt(common_arg(
{"--no-perf"},
string_format("disable internal libllama performance timings (default: %s)", params.no_perf ? "true" : "false"),
@@ -1061,6 +1064,13 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
params.sampling.no_perf = true;
}
).set_env("LLAMA_ARG_NO_PERF"));
add_opt(common_arg(
{"--no-show-timings"},
string_format("disable timing information after each response (default: %s)", params.show_timings ? "true" : "false"),
[](common_params & params) {
params.show_timings = false;
}
).set_examples({LLAMA_EXAMPLE_CLI}).set_env("LLAMA_ARG_NO_SHOW_TIMINGS"));
add_opt(common_arg(
{"-f", "--file"}, "FNAME",
"a file containing the prompt (default: none)",
@@ -1082,7 +1092,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
params.system_prompt.pop_back();
}
}
).set_examples({LLAMA_EXAMPLE_MAIN, LLAMA_EXAMPLE_DIFFUSION}));
).set_examples({LLAMA_EXAMPLE_COMPLETION, LLAMA_EXAMPLE_CLI, LLAMA_EXAMPLE_DIFFUSION}));
add_opt(common_arg(
{"--in-file"}, "FNAME",
"an input file (repeat to specify multiple files)",
@@ -1130,42 +1140,42 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
[](common_params & params, int value) {
params.n_print = value;
}
).set_examples({LLAMA_EXAMPLE_MAIN}));
).set_examples({LLAMA_EXAMPLE_COMPLETION}));
add_opt(common_arg(
{"--prompt-cache"}, "FNAME",
"file to cache prompt state for faster startup (default: none)",
[](common_params & params, const std::string & value) {
params.path_prompt_cache = value;
}
).set_examples({LLAMA_EXAMPLE_MAIN}));
).set_examples({LLAMA_EXAMPLE_COMPLETION}));
add_opt(common_arg(
{"--prompt-cache-all"},
"if specified, saves user input and generations to cache as well\n",
[](common_params & params) {
params.prompt_cache_all = true;
}
).set_examples({LLAMA_EXAMPLE_MAIN}));
).set_examples({LLAMA_EXAMPLE_COMPLETION}));
add_opt(common_arg(
{"--prompt-cache-ro"},
"if specified, uses the prompt cache but does not update it",
[](common_params & params) {
params.prompt_cache_ro = true;
}
).set_examples({LLAMA_EXAMPLE_MAIN}));
).set_examples({LLAMA_EXAMPLE_COMPLETION}));
add_opt(common_arg(
{"-r", "--reverse-prompt"}, "PROMPT",
"halt generation at PROMPT, return control in interactive mode\n",
[](common_params & params, const std::string & value) {
params.antiprompt.emplace_back(value);
}
).set_examples({LLAMA_EXAMPLE_MAIN, LLAMA_EXAMPLE_SERVER}));
).set_examples({LLAMA_EXAMPLE_COMPLETION, LLAMA_EXAMPLE_CLI, LLAMA_EXAMPLE_SERVER}));
add_opt(common_arg(
{"-sp", "--special"},
string_format("special tokens output enabled (default: %s)", params.special ? "true" : "false"),
[](common_params & params) {
params.special = true;
}
).set_examples({LLAMA_EXAMPLE_MAIN, LLAMA_EXAMPLE_SERVER}));
).set_examples({LLAMA_EXAMPLE_COMPLETION, LLAMA_EXAMPLE_CLI, LLAMA_EXAMPLE_SERVER}));
add_opt(common_arg(
{"-cnv", "--conversation"},
"run in conversation mode:\n"
@@ -1175,14 +1185,14 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
[](common_params & params) {
params.conversation_mode = COMMON_CONVERSATION_MODE_ENABLED;
}
).set_examples({LLAMA_EXAMPLE_MAIN}));
).set_examples({LLAMA_EXAMPLE_COMPLETION}));
add_opt(common_arg(
{"-no-cnv", "--no-conversation"},
"force disable conversation mode (default: false)",
[](common_params & params) {
params.conversation_mode = COMMON_CONVERSATION_MODE_DISABLED;
}
).set_examples({LLAMA_EXAMPLE_MAIN}));
).set_examples({LLAMA_EXAMPLE_COMPLETION, LLAMA_EXAMPLE_CLI}));
add_opt(common_arg(
{"-st", "--single-turn"},
"run conversation for a single turn only, then exit when done\n"
@@ -1191,28 +1201,28 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
[](common_params & params) {
params.single_turn = true;
}
).set_examples({LLAMA_EXAMPLE_MAIN}));
).set_examples({LLAMA_EXAMPLE_COMPLETION, LLAMA_EXAMPLE_CLI}));
add_opt(common_arg(
{"-i", "--interactive"},
string_format("run in interactive mode (default: %s)", params.interactive ? "true" : "false"),
[](common_params & params) {
params.interactive = true;
}
).set_examples({LLAMA_EXAMPLE_MAIN}));
).set_examples({LLAMA_EXAMPLE_COMPLETION}));
add_opt(common_arg(
{"-if", "--interactive-first"},
string_format("run in interactive mode and wait for input right away (default: %s)", params.interactive_first ? "true" : "false"),
[](common_params & params) {
params.interactive_first = true;
}
).set_examples({LLAMA_EXAMPLE_MAIN}));
).set_examples({LLAMA_EXAMPLE_COMPLETION}));
add_opt(common_arg(
{"-mli", "--multiline-input"},
"allows you to write or paste multiple lines without ending each in '\\'",
[](common_params & params) {
params.multiline_input = true;
}
).set_examples({LLAMA_EXAMPLE_MAIN}));
).set_examples({LLAMA_EXAMPLE_COMPLETION, LLAMA_EXAMPLE_CLI}));
add_opt(common_arg(
{"--in-prefix-bos"},
"prefix BOS to user inputs, preceding the `--in-prefix` string",
@@ -1220,7 +1230,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
params.input_prefix_bos = true;
params.enable_chat_template = false;
}
).set_examples({LLAMA_EXAMPLE_MAIN}));
).set_examples({LLAMA_EXAMPLE_COMPLETION}));
add_opt(common_arg(
{"--in-prefix"}, "STRING",
"string to prefix user inputs with (default: empty)",
@@ -1228,7 +1238,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
params.input_prefix = value;
params.enable_chat_template = false;
}
).set_examples({LLAMA_EXAMPLE_MAIN}));
).set_examples({LLAMA_EXAMPLE_COMPLETION}));
add_opt(common_arg(
{"--in-suffix"}, "STRING",
"string to suffix after user inputs with (default: empty)",
@@ -1236,14 +1246,14 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
params.input_suffix = value;
params.enable_chat_template = false;
}
).set_examples({LLAMA_EXAMPLE_MAIN}));
).set_examples({LLAMA_EXAMPLE_COMPLETION}));
add_opt(common_arg(
{"--no-warmup"},
"skip warming up the model with an empty run",
[](common_params & params) {
params.warmup = false;
}
).set_examples({LLAMA_EXAMPLE_MAIN, LLAMA_EXAMPLE_SERVER, LLAMA_EXAMPLE_MTMD, LLAMA_EXAMPLE_EMBEDDING, LLAMA_EXAMPLE_RETRIEVAL, LLAMA_EXAMPLE_PERPLEXITY}));
).set_examples({LLAMA_EXAMPLE_COMPLETION, LLAMA_EXAMPLE_CLI, LLAMA_EXAMPLE_SERVER, LLAMA_EXAMPLE_MTMD, LLAMA_EXAMPLE_EMBEDDING, LLAMA_EXAMPLE_RETRIEVAL, LLAMA_EXAMPLE_PERPLEXITY}));
add_opt(common_arg(
{"--spm-infill"},
string_format(
@@ -1634,14 +1644,14 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
[](common_params & params, int value) {
params.grp_attn_n = value;
}
).set_env("LLAMA_ARG_GRP_ATTN_N").set_examples({LLAMA_EXAMPLE_MAIN, LLAMA_EXAMPLE_PASSKEY}));
).set_env("LLAMA_ARG_GRP_ATTN_N").set_examples({LLAMA_EXAMPLE_COMPLETION, LLAMA_EXAMPLE_PASSKEY}));
add_opt(common_arg(
{"-gaw", "--grp-attn-w"}, "N",
string_format("group-attention width (default: %d)", params.grp_attn_w),
[](common_params & params, int value) {
params.grp_attn_w = value;
}
).set_env("LLAMA_ARG_GRP_ATTN_W").set_examples({LLAMA_EXAMPLE_MAIN}));
).set_env("LLAMA_ARG_GRP_ATTN_W").set_examples({LLAMA_EXAMPLE_COMPLETION}));
add_opt(common_arg(
{"-nkvo", "--no-kv-offload"},
"disable KV offload",
@@ -1831,7 +1841,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
[](common_params & params, const std::string & value) {
params.image.emplace_back(value);
}
).set_examples({LLAMA_EXAMPLE_MTMD}));
).set_examples({LLAMA_EXAMPLE_MTMD, LLAMA_EXAMPLE_CLI}));
add_opt(common_arg(
{"--image-min-tokens"}, "N",
"minimum number of tokens each image can take, only used by vision models with dynamic resolution (default: read from model)",
@@ -1924,7 +1934,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
"override tensor buffer type for draft model", [](common_params & params, const std::string & value) {
parse_tensor_buffer_overrides(value, params.speculative.tensor_buft_overrides);
}
).set_examples({LLAMA_EXAMPLE_SPECULATIVE, LLAMA_EXAMPLE_SERVER}));
).set_examples({LLAMA_EXAMPLE_SPECULATIVE, LLAMA_EXAMPLE_SERVER, LLAMA_EXAMPLE_CLI}));
add_opt(common_arg(
{"--cpu-moe", "-cmoe"},
"keep all Mixture of Experts (MoE) weights in the CPU",
@@ -1953,7 +1963,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
[](common_params & params) {
params.speculative.tensor_buft_overrides.push_back(llm_ffn_exps_cpu_override());
}
).set_examples({LLAMA_EXAMPLE_SPECULATIVE, LLAMA_EXAMPLE_SERVER}).set_env("LLAMA_ARG_CPU_MOE_DRAFT"));
).set_examples({LLAMA_EXAMPLE_SPECULATIVE, LLAMA_EXAMPLE_SERVER, LLAMA_EXAMPLE_CLI}).set_env("LLAMA_ARG_CPU_MOE_DRAFT"));
add_opt(common_arg(
{"--n-cpu-moe-draft", "-ncmoed"}, "N",
"keep the Mixture of Experts (MoE) weights of the first N layers in the CPU for the draft model",
@@ -1967,7 +1977,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
params.speculative.tensor_buft_overrides.push_back({buft_overrides_draft.back().c_str(), ggml_backend_cpu_buffer_type()});
}
}
).set_examples({LLAMA_EXAMPLE_SPECULATIVE, LLAMA_EXAMPLE_SERVER}).set_env("LLAMA_ARG_N_CPU_MOE_DRAFT"));
).set_examples({LLAMA_EXAMPLE_SPECULATIVE, LLAMA_EXAMPLE_SERVER, LLAMA_EXAMPLE_CLI}).set_env("LLAMA_ARG_N_CPU_MOE_DRAFT"));
add_opt(common_arg(
{"-ngl", "--gpu-layers", "--n-gpu-layers"}, "N",
string_format("max. number of layers to store in VRAM (default: %d)", params.n_gpu_layers),
@@ -2446,7 +2456,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
params.default_template_kwargs[item.key()] = item.value().dump();
}
}
).set_examples({LLAMA_EXAMPLE_SERVER}).set_env("LLAMA_CHAT_TEMPLATE_KWARGS"));
).set_examples({LLAMA_EXAMPLE_SERVER, LLAMA_EXAMPLE_CLI}).set_env("LLAMA_CHAT_TEMPLATE_KWARGS"));
add_opt(common_arg(
{"-to", "--timeout"}, "N",
string_format("server read/write timeout in seconds (default: %d)", params.timeout_read),
@@ -2555,14 +2565,14 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
[](common_params & params) {
params.use_jinja = true;
}
).set_examples({LLAMA_EXAMPLE_SERVER, LLAMA_EXAMPLE_MAIN, LLAMA_EXAMPLE_MTMD}).set_env("LLAMA_ARG_JINJA"));
).set_examples({LLAMA_EXAMPLE_SERVER, LLAMA_EXAMPLE_COMPLETION, LLAMA_EXAMPLE_CLI, LLAMA_EXAMPLE_MTMD}).set_env("LLAMA_ARG_JINJA"));
add_opt(common_arg(
{"--no-jinja"},
string_format("disable jinja template for chat (default: %s)\n", params.use_jinja ? "enabled" : "disabled"),
[](common_params & params) {
params.use_jinja = false;
}
).set_examples({LLAMA_EXAMPLE_SERVER, LLAMA_EXAMPLE_MAIN, LLAMA_EXAMPLE_MTMD}).set_env("LLAMA_ARG_NO_JINJA"));
).set_examples({LLAMA_EXAMPLE_SERVER, LLAMA_EXAMPLE_COMPLETION, LLAMA_EXAMPLE_CLI, LLAMA_EXAMPLE_MTMD}).set_env("LLAMA_ARG_NO_JINJA"));
add_opt(common_arg(
{"--reasoning-format"}, "FORMAT",
"controls whether thought tags are allowed and/or extracted from the response, and in which format they're returned; one of:\n"
@@ -2573,7 +2583,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
[](common_params & params, const std::string & value) {
params.reasoning_format = common_reasoning_format_from_name(value);
}
).set_examples({LLAMA_EXAMPLE_SERVER, LLAMA_EXAMPLE_MAIN}).set_env("LLAMA_ARG_THINK"));
).set_examples({LLAMA_EXAMPLE_SERVER, LLAMA_EXAMPLE_COMPLETION, LLAMA_EXAMPLE_CLI}).set_env("LLAMA_ARG_THINK"));
add_opt(common_arg(
{"--reasoning-budget"}, "N",
"controls the amount of thinking allowed; currently only one of: -1 for unrestricted thinking budget, or 0 to disable thinking (default: -1)",
@@ -2581,7 +2591,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
if (value != 0 && value != -1) { throw std::invalid_argument("invalid value"); }
params.reasoning_budget = value;
}
).set_examples({LLAMA_EXAMPLE_SERVER, LLAMA_EXAMPLE_MAIN}).set_env("LLAMA_ARG_THINK_BUDGET"));
).set_examples({LLAMA_EXAMPLE_SERVER, LLAMA_EXAMPLE_COMPLETION, LLAMA_EXAMPLE_CLI}).set_env("LLAMA_ARG_THINK_BUDGET"));
add_opt(common_arg(
{"--chat-template"}, "JINJA_TEMPLATE",
string_format(
@@ -2593,7 +2603,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
[](common_params & params, const std::string & value) {
params.chat_template = value;
}
).set_examples({LLAMA_EXAMPLE_MAIN, LLAMA_EXAMPLE_SERVER, LLAMA_EXAMPLE_MTMD}).set_env("LLAMA_ARG_CHAT_TEMPLATE"));
).set_examples({LLAMA_EXAMPLE_COMPLETION, LLAMA_EXAMPLE_CLI, LLAMA_EXAMPLE_SERVER, LLAMA_EXAMPLE_MTMD}).set_env("LLAMA_ARG_CHAT_TEMPLATE"));
add_opt(common_arg(
{"--chat-template-file"}, "JINJA_TEMPLATE_FILE",
string_format(
@@ -2605,7 +2615,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
[](common_params & params, const std::string & value) {
params.chat_template = read_file(value);
}
).set_examples({LLAMA_EXAMPLE_MAIN, LLAMA_EXAMPLE_SERVER}).set_env("LLAMA_ARG_CHAT_TEMPLATE_FILE"));
).set_examples({LLAMA_EXAMPLE_COMPLETION, LLAMA_EXAMPLE_CLI, LLAMA_EXAMPLE_SERVER}).set_env("LLAMA_ARG_CHAT_TEMPLATE_FILE"));
add_opt(common_arg(
{"--no-prefill-assistant"},
string_format(
@@ -2636,7 +2646,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
[](common_params & params) {
params.simple_io = true;
}
).set_examples({LLAMA_EXAMPLE_MAIN}));
).set_examples({LLAMA_EXAMPLE_COMPLETION, LLAMA_EXAMPLE_CLI}));
add_opt(common_arg(
{"--positive-file"}, "FNAME",
string_format("positive prompts file, one prompt per line (default: '%s')", params.cvector_positive_file.c_str()),
@@ -2719,7 +2729,6 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
"Set verbosity level to infinity (i.e. log all messages, useful for debugging)",
[](common_params & params) {
params.verbosity = INT_MAX;
common_log_set_verbosity_thold(INT_MAX);
}
));
add_opt(common_arg(
@@ -2740,7 +2749,6 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
"(default: %d)\n", params.verbosity),
[](common_params & params, int value) {
params.verbosity = value;
common_log_set_verbosity_thold(value);
}
).set_env("LLAMA_LOG_VERBOSITY"));
add_opt(common_arg(
@@ -2873,14 +2881,14 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
[](common_params & params, int value) {
params.speculative.n_max = value;
}
).set_examples({LLAMA_EXAMPLE_SPECULATIVE, LLAMA_EXAMPLE_LOOKUP, LLAMA_EXAMPLE_SERVER}).set_env("LLAMA_ARG_DRAFT_MAX"));
).set_examples({LLAMA_EXAMPLE_SPECULATIVE, LLAMA_EXAMPLE_LOOKUP, LLAMA_EXAMPLE_SERVER, LLAMA_EXAMPLE_CLI}).set_env("LLAMA_ARG_DRAFT_MAX"));
add_opt(common_arg(
{"--draft-min", "--draft-n-min"}, "N",
string_format("minimum number of draft tokens to use for speculative decoding (default: %d)", params.speculative.n_min),
[](common_params & params, int value) {
params.speculative.n_min = value;
}
).set_examples({LLAMA_EXAMPLE_SPECULATIVE, LLAMA_EXAMPLE_LOOKUP, LLAMA_EXAMPLE_SERVER}).set_env("LLAMA_ARG_DRAFT_MIN"));
).set_examples({LLAMA_EXAMPLE_SPECULATIVE, LLAMA_EXAMPLE_LOOKUP, LLAMA_EXAMPLE_SERVER, LLAMA_EXAMPLE_CLI}).set_env("LLAMA_ARG_DRAFT_MIN"));
add_opt(common_arg(
{"--draft-p-split"}, "P",
string_format("speculative decoding split probability (default: %.1f)", (double)params.speculative.p_split),
@@ -2894,14 +2902,14 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
[](common_params & params, const std::string & value) {
params.speculative.p_min = std::stof(value);
}
).set_examples({LLAMA_EXAMPLE_SPECULATIVE, LLAMA_EXAMPLE_SERVER}).set_env("LLAMA_ARG_DRAFT_P_MIN"));
).set_examples({LLAMA_EXAMPLE_SPECULATIVE, LLAMA_EXAMPLE_SERVER, LLAMA_EXAMPLE_CLI}).set_env("LLAMA_ARG_DRAFT_P_MIN"));
add_opt(common_arg(
{"-cd", "--ctx-size-draft"}, "N",
string_format("size of the prompt context for the draft model (default: %d, 0 = loaded from model)", params.speculative.n_ctx),
[](common_params & params, int value) {
params.speculative.n_ctx = value;
}
).set_examples({LLAMA_EXAMPLE_SPECULATIVE, LLAMA_EXAMPLE_SERVER}).set_env("LLAMA_ARG_CTX_SIZE_DRAFT"));
).set_examples({LLAMA_EXAMPLE_SPECULATIVE, LLAMA_EXAMPLE_SERVER, LLAMA_EXAMPLE_CLI}).set_env("LLAMA_ARG_CTX_SIZE_DRAFT"));
add_opt(common_arg(
{"-devd", "--device-draft"}, "<dev1,dev2,..>",
"comma-separated list of devices to use for offloading the draft model (none = don't offload)\n"
@@ -2909,7 +2917,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
[](common_params & params, const std::string & value) {
params.speculative.devices = parse_device_list(value);
}
).set_examples({LLAMA_EXAMPLE_SPECULATIVE, LLAMA_EXAMPLE_SERVER}));
).set_examples({LLAMA_EXAMPLE_SPECULATIVE, LLAMA_EXAMPLE_SERVER, LLAMA_EXAMPLE_CLI}));
add_opt(common_arg(
{"-ngld", "--gpu-layers-draft", "--n-gpu-layers-draft"}, "N",
"number of layers to store in VRAM for the draft model",
@@ -2921,21 +2929,21 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
fprintf(stderr, "warning: consult docs/build.md for compilation instructions\n");
}
}
).set_examples({LLAMA_EXAMPLE_SPECULATIVE, LLAMA_EXAMPLE_SERVER}).set_env("LLAMA_ARG_N_GPU_LAYERS_DRAFT"));
).set_examples({LLAMA_EXAMPLE_SPECULATIVE, LLAMA_EXAMPLE_SERVER, LLAMA_EXAMPLE_CLI}).set_env("LLAMA_ARG_N_GPU_LAYERS_DRAFT"));
add_opt(common_arg(
{"-md", "--model-draft"}, "FNAME",
"draft model for speculative decoding (default: unused)",
[](common_params & params, const std::string & value) {
params.speculative.model.path = value;
}
).set_examples({LLAMA_EXAMPLE_SPECULATIVE, LLAMA_EXAMPLE_SERVER}).set_env("LLAMA_ARG_MODEL_DRAFT"));
).set_examples({LLAMA_EXAMPLE_SPECULATIVE, LLAMA_EXAMPLE_SERVER, LLAMA_EXAMPLE_CLI}).set_env("LLAMA_ARG_MODEL_DRAFT"));
add_opt(common_arg(
{"--spec-replace"}, "TARGET", "DRAFT",
"translate the string in TARGET into DRAFT if the draft model and main model are not compatible",
[](common_params & params, const std::string & tgt, const std::string & dft) {
params.speculative.replacements.push_back({ tgt, dft });
}
).set_examples({LLAMA_EXAMPLE_SPECULATIVE, LLAMA_EXAMPLE_SERVER}));
).set_examples({LLAMA_EXAMPLE_SPECULATIVE, LLAMA_EXAMPLE_SERVER, LLAMA_EXAMPLE_CLI}));
add_opt(common_arg(
{"-ctkd", "--cache-type-k-draft"}, "TYPE",
string_format(
@@ -3199,7 +3207,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
params.use_jinja = true;
//params.default_template_kwargs["reasoning_effort"] = "\"high\"";
}
).set_examples({LLAMA_EXAMPLE_SERVER}));
).set_examples({LLAMA_EXAMPLE_SERVER, LLAMA_EXAMPLE_CLI}));
add_opt(common_arg(
{"--gpt-oss-120b-default"},
@@ -3218,7 +3226,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
params.use_jinja = true;
//params.default_template_kwargs["reasoning_effort"] = "\"high\"";
}
).set_examples({LLAMA_EXAMPLE_SERVER}));
).set_examples({LLAMA_EXAMPLE_SERVER, LLAMA_EXAMPLE_CLI}));
add_opt(common_arg(
{"--vision-gemma-4b-default"},
@@ -3229,7 +3237,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
params.n_ctx = 0;
params.use_jinja = true;
}
).set_examples({LLAMA_EXAMPLE_SERVER}));
).set_examples({LLAMA_EXAMPLE_SERVER, LLAMA_EXAMPLE_CLI}));
add_opt(common_arg(
{"--vision-gemma-12b-default"},
@@ -3240,7 +3248,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
params.n_ctx = 0;
params.use_jinja = true;
}
).set_examples({LLAMA_EXAMPLE_SERVER}));
).set_examples({LLAMA_EXAMPLE_SERVER, LLAMA_EXAMPLE_CLI}));
return ctx_arg;
}
+3 -1
View File
@@ -78,7 +78,8 @@ int32_t cpu_get_num_math();
enum llama_example {
LLAMA_EXAMPLE_COMMON,
LLAMA_EXAMPLE_SPECULATIVE,
LLAMA_EXAMPLE_MAIN,
LLAMA_EXAMPLE_COMPLETION,
LLAMA_EXAMPLE_CLI,
LLAMA_EXAMPLE_EMBEDDING,
LLAMA_EXAMPLE_PERPLEXITY,
LLAMA_EXAMPLE_RETRIEVAL,
@@ -402,6 +403,7 @@ struct common_params {
bool simple_io = false; // improves compatibility with subprocesses and limited consoles
bool cont_batching = true; // insert new sequences for decoding on-the-fly
bool no_perf = false; // disable performance metrics
bool show_timings = true; // show timing information on CLI
bool ctx_shift = false; // context shift on infinite text generation
bool swa_full = false; // use full-size SWA cache (https://github.com/ggml-org/llama.cpp/pull/13194#issuecomment-2868343055)
bool kv_unified = false; // enable unified KV cache
+98 -18
View File
@@ -1,4 +1,5 @@
#include "console.h"
#include "log.h"
#include <vector>
#include <iostream>
#include <cassert>
@@ -6,6 +7,10 @@
#include <cctype>
#include <cwctype>
#include <cstdint>
#include <condition_variable>
#include <mutex>
#include <thread>
#include <stdarg.h>
#if defined(_WIN32)
#define WIN32_LEAN_AND_MEAN
@@ -35,6 +40,7 @@
#define ANSI_COLOR_BLUE "\x1b[34m"
#define ANSI_COLOR_MAGENTA "\x1b[35m"
#define ANSI_COLOR_CYAN "\x1b[36m"
#define ANSI_COLOR_GRAY "\x1b[90m"
#define ANSI_COLOR_RESET "\x1b[0m"
#define ANSI_BOLD "\x1b[1m"
@@ -61,17 +67,17 @@ namespace console {
//
#endif
static bool advanced_display = false;
static bool simple_io = true;
static display_t current_display = reset;
static bool advanced_display = false;
static bool simple_io = true;
static display_type current_display = DISPLAY_TYPE_RESET;
static FILE* out = stdout;
static FILE* out = stdout;
#if defined (_WIN32)
static void* hConsole;
static void* hConsole;
#else
static FILE* tty = nullptr;
static termios initial_state;
static FILE* tty = nullptr;
static termios initial_state;
#endif
//
@@ -142,7 +148,7 @@ namespace console {
void cleanup() {
// Reset console display
set_display(reset);
set_display(DISPLAY_TYPE_RESET);
#if !defined(_WIN32)
// Restore settings on POSIX systems
@@ -162,20 +168,26 @@ namespace console {
//
// Keep track of current display and only emit ANSI code if it changes
void set_display(display_t display) {
void set_display(display_type display) {
if (advanced_display && current_display != display) {
fflush(stdout);
common_log_flush(common_log_main());
switch(display) {
case reset:
case DISPLAY_TYPE_RESET:
fprintf(out, ANSI_COLOR_RESET);
break;
case prompt:
case DISPLAY_TYPE_INFO:
fprintf(out, ANSI_COLOR_MAGENTA);
break;
case DISPLAY_TYPE_PROMPT:
fprintf(out, ANSI_COLOR_YELLOW);
break;
case user_input:
case DISPLAY_TYPE_REASONING:
fprintf(out, ANSI_COLOR_GRAY);
break;
case DISPLAY_TYPE_USER_INPUT:
fprintf(out, ANSI_BOLD ANSI_COLOR_GREEN);
break;
case error:
case DISPLAY_TYPE_ERROR:
fprintf(out, ANSI_BOLD ANSI_COLOR_RED);
}
current_display = display;
@@ -778,7 +790,6 @@ namespace console {
}
if (is_special_char) {
set_display(user_input);
replace_last(line.back());
is_special_char = false;
}
@@ -961,7 +972,6 @@ namespace console {
}
if (!line.empty() && (line.back() == '\\' || line.back() == '/')) {
set_display(prompt);
replace_last(line.back());
is_special_char = true;
}
@@ -1046,12 +1056,82 @@ namespace console {
}
bool readline(std::string & line, bool multiline_input) {
set_display(user_input);
if (simple_io) {
return readline_simple(line, multiline_input);
}
return readline_advanced(line, multiline_input);
}
namespace spinner {
static const char LOADING_CHARS[] = {'|', '/', '-', '\\'};
static std::condition_variable cv_stop;
static std::thread th;
static size_t frame = 0; // only modified by one thread
static bool running = false;
static std::mutex mtx;
static auto wait_time = std::chrono::milliseconds(100);
static void draw_next_frame() {
// don't need lock because only one thread modifies running
frame = (frame + 1) % sizeof(LOADING_CHARS);
replace_last(LOADING_CHARS[frame]);
fflush(out);
}
void start() {
std::unique_lock<std::mutex> lock(mtx);
if (simple_io || running) {
return;
}
common_log_flush(common_log_main());
fprintf(out, "%c", LOADING_CHARS[0]);
fflush(out);
frame = 1;
running = true;
th = std::thread([]() {
std::unique_lock<std::mutex> lock(mtx);
while (true) {
if (cv_stop.wait_for(lock, wait_time, []{ return !running; })) {
break;
}
draw_next_frame();
}
});
}
void stop() {
{
std::unique_lock<std::mutex> lock(mtx);
if (simple_io || !running) {
return;
}
running = false;
cv_stop.notify_all();
}
if (th.joinable()) {
th.join();
}
replace_last(' ');
pop_cursor();
fflush(out);
}
}
void log(const char * fmt, ...) {
va_list args;
va_start(args, fmt);
vfprintf(out, fmt, args);
va_end(args);
}
void error(const char * fmt, ...) {
va_list args;
va_start(args, fmt);
display_type cur = current_display;
set_display(DISPLAY_TYPE_ERROR);
vfprintf(out, fmt, args);
set_display(cur); // restore previous color
va_end(args);
}
void flush() {
fflush(out);
}
}
+30 -8
View File
@@ -2,18 +2,40 @@
#pragma once
#include "common.h"
#include <string>
namespace console {
enum display_t {
reset = 0,
prompt,
user_input,
error
};
enum display_type {
DISPLAY_TYPE_RESET = 0,
DISPLAY_TYPE_INFO,
DISPLAY_TYPE_PROMPT,
DISPLAY_TYPE_REASONING,
DISPLAY_TYPE_USER_INPUT,
DISPLAY_TYPE_ERROR
};
namespace console {
void init(bool use_simple_io, bool use_advanced_display);
void cleanup();
void set_display(display_t display);
void set_display(display_type display);
bool readline(std::string & line, bool multiline_input);
namespace spinner {
void start();
void stop();
}
// note: the logging API below output directly to stdout
// it can negatively impact performance if used on inference thread
// only use in in a dedicated CLI thread
// for logging in inference thread, use log.h instead
LLAMA_COMMON_ATTRIBUTE_FORMAT(1, 2)
void log(const char * fmt, ...);
LLAMA_COMMON_ATTRIBUTE_FORMAT(1, 2)
void error(const char * fmt, ...);
void flush();
}
+5
View File
@@ -420,6 +420,11 @@ void common_log_set_timestamps(struct common_log * log, bool timestamps) {
log->set_timestamps(timestamps);
}
void common_log_flush(struct common_log * log) {
log->pause();
log->resume();
}
static int common_get_verbosity(enum ggml_log_level level) {
switch (level) {
case GGML_LOG_LEVEL_DEBUG: return LOG_LEVEL_DEBUG;
+1
View File
@@ -84,6 +84,7 @@ void common_log_set_file (struct common_log * log, const char * file); // n
void common_log_set_colors (struct common_log * log, log_colors colors); // not thread-safe
void common_log_set_prefix (struct common_log * log, bool prefix); // whether to output prefix to each log
void common_log_set_timestamps(struct common_log * log, bool timestamps); // whether to output timestamps in the prefix
void common_log_flush (struct common_log * log); // flush all pending log messages
// helper macros for logging
// use these to avoid computing log arguments if the verbosity of the log is higher than the threshold
+1
View File
@@ -4326,6 +4326,7 @@ static bool ggml_backend_cuda_device_supports_op(ggml_backend_dev_t dev, const g
case GGML_UNARY_OP_EXPM1:
case GGML_UNARY_OP_SOFTPLUS:
case GGML_UNARY_OP_ELU:
case GGML_UNARY_OP_XIELU:
case GGML_UNARY_OP_FLOOR:
case GGML_UNARY_OP_CEIL:
case GGML_UNARY_OP_ROUND:
+10
View File
@@ -0,0 +1,10 @@
set(TARGET llama-cli)
add_executable(${TARGET} cli.cpp)
target_link_libraries(${TARGET} PRIVATE server-context PUBLIC common ${CMAKE_THREAD_LIBS_INIT})
target_compile_features(${TARGET} PRIVATE cxx_std_17)
include_directories(../server)
if(LLAMA_TOOLS_INSTALL)
install(TARGETS ${TARGET} RUNTIME)
endif()
+395
View File
@@ -0,0 +1,395 @@
#include "common.h"
#include "arg.h"
#include "console.h"
// #include "log.h"
#include "server-context.h"
#include "server-task.h"
#include <atomic>
#include <fstream>
#include <thread>
#include <signal.h>
#if defined(_WIN32)
#define WIN32_LEAN_AND_MEAN
#ifndef NOMINMAX
# define NOMINMAX
#endif
#include <windows.h>
#endif
const char * LLAMA_ASCII_LOGO = R"(
)";
static std::atomic<bool> g_is_interrupted = false;
static bool should_stop() {
return g_is_interrupted.load();
}
#if defined (__unix__) || (defined (__APPLE__) && defined (__MACH__)) || defined (_WIN32)
static void signal_handler(int) {
if (g_is_interrupted.load()) {
// second Ctrl+C - exit immediately
// make sure to clear colors before exiting (not using LOG or console.cpp here to avoid deadlock)
fprintf(stdout, "\033[0m\n");
fflush(stdout);
std::exit(130);
}
g_is_interrupted.store(true);
}
#endif
struct cli_context {
server_context ctx_server;
json messages = json::array();
std::vector<raw_buffer> input_files;
task_params defaults;
// thread for showing "loading" animation
std::atomic<bool> loading_show;
cli_context(const common_params & params) {
defaults.sampling = params.sampling;
defaults.speculative = params.speculative;
defaults.n_keep = params.n_keep;
defaults.n_predict = params.n_predict;
defaults.antiprompt = params.antiprompt;
defaults.stream = true; // make sure we always use streaming mode
defaults.timings_per_token = true; // in order to get timings even when we cancel mid-way
// defaults.return_progress = true; // TODO: show progress
defaults.oaicompat_chat_syntax.reasoning_format = COMMON_REASONING_FORMAT_DEEPSEEK;
}
std::string generate_completion(result_timings & out_timings) {
server_response_reader rd = ctx_server.get_response_reader();
{
// TODO: reduce some copies here in the future
server_task task = server_task(SERVER_TASK_TYPE_COMPLETION);
task.id = rd.get_new_id();
task.index = 0;
task.params = defaults; // copy
task.cli_input = messages; // copy
task.cli_files = input_files; // copy
rd.post_task({std::move(task)});
}
// wait for first result
console::spinner::start();
server_task_result_ptr result = rd.next(should_stop);
console::spinner::stop();
std::string curr_content;
bool is_thinking = false;
while (result) {
if (should_stop()) {
break;
}
if (result->is_error()) {
json err_data = result->to_json();
if (err_data.contains("message")) {
console::error("Error: %s\n", err_data["message"].get<std::string>().c_str());
} else {
console::error("Error: %s\n", err_data.dump().c_str());
}
return curr_content;
}
auto res_partial = dynamic_cast<server_task_result_cmpl_partial *>(result.get());
if (res_partial) {
out_timings = std::move(res_partial->timings);
for (const auto & diff : res_partial->oaicompat_msg_diffs) {
if (!diff.content_delta.empty()) {
if (is_thinking) {
console::log("\n[End thinking]\n\n");
console::set_display(DISPLAY_TYPE_RESET);
is_thinking = false;
}
curr_content += diff.content_delta;
console::log("%s", diff.content_delta.c_str());
console::flush();
}
if (!diff.reasoning_content_delta.empty()) {
console::set_display(DISPLAY_TYPE_REASONING);
if (!is_thinking) {
console::log("[Start thinking]\n");
}
is_thinking = true;
console::log("%s", diff.reasoning_content_delta.c_str());
console::flush();
}
}
}
auto res_final = dynamic_cast<server_task_result_cmpl_final *>(result.get());
if (res_final) {
out_timings = std::move(res_final->timings);
break;
}
result = rd.next(should_stop);
}
g_is_interrupted.store(false);
// server_response_reader automatically cancels pending tasks upon destruction
return curr_content;
}
// TODO: support remote files in the future (http, https, etc)
std::string load_input_file(const std::string & fname, bool is_media) {
std::ifstream file(fname, std::ios::binary);
if (!file) {
return "";
}
if (is_media) {
raw_buffer buf;
buf.assign((std::istreambuf_iterator<char>(file)), std::istreambuf_iterator<char>());
input_files.push_back(std::move(buf));
return mtmd_default_marker();
} else {
std::string content((std::istreambuf_iterator<char>(file)), std::istreambuf_iterator<char>());
return content;
}
}
};
int main(int argc, char ** argv) {
common_params params;
params.verbosity = LOG_LEVEL_ERROR; // by default, less verbose logs
if (!common_params_parse(argc, argv, params, LLAMA_EXAMPLE_CLI)) {
return 1;
}
// TODO: maybe support it later?
if (params.conversation_mode == COMMON_CONVERSATION_MODE_DISABLED) {
console::error("--no-conversation is not supported by llama-cli\n");
console::error("please use llama-completion instead\n");
}
common_init();
// struct that contains llama context and inference
cli_context ctx_cli(params);
llama_backend_init();
llama_numa_init(params.numa);
// TODO: avoid using atexit() here by making `console` a singleton
console::init(params.simple_io, params.use_color);
atexit([]() { console::cleanup(); });
console::set_display(DISPLAY_TYPE_RESET);
#if defined (__unix__) || (defined (__APPLE__) && defined (__MACH__))
struct sigaction sigint_action;
sigint_action.sa_handler = signal_handler;
sigemptyset (&sigint_action.sa_mask);
sigint_action.sa_flags = 0;
sigaction(SIGINT, &sigint_action, NULL);
sigaction(SIGTERM, &sigint_action, NULL);
#elif defined (_WIN32)
auto console_ctrl_handler = +[](DWORD ctrl_type) -> BOOL {
return (ctrl_type == CTRL_C_EVENT) ? (signal_handler(SIGINT), true) : false;
};
SetConsoleCtrlHandler(reinterpret_cast<PHANDLER_ROUTINE>(console_ctrl_handler), true);
#endif
console::log("\nLoading model... "); // followed by loading animation
console::spinner::start();
if (!ctx_cli.ctx_server.load_model(params)) {
console::spinner::stop();
console::error("\nFailed to load the model\n");
return 1;
}
ctx_cli.ctx_server.init();
console::spinner::stop();
console::log("\n");
std::thread inference_thread([&ctx_cli]() {
ctx_cli.ctx_server.start_loop();
});
auto inf = ctx_cli.ctx_server.get_info();
std::string modalities = "text";
if (inf.has_inp_image) {
modalities += ", vision";
}
if (inf.has_inp_audio) {
modalities += ", audio";
}
if (!params.system_prompt.empty()) {
ctx_cli.messages.push_back({
{"role", "system"},
{"content", params.system_prompt}
});
}
console::log("\n");
console::log("%s\n", LLAMA_ASCII_LOGO);
console::log("build : %s\n", inf.build_info.c_str());
console::log("model : %s\n", inf.model_name.c_str());
console::log("modalities : %s\n", modalities.c_str());
if (!params.system_prompt.empty()) {
console::log("using custom system prompt\n");
}
console::log("\n");
console::log("available commands:\n");
console::log(" /exit or Ctrl+C stop or exit\n");
console::log(" /regen regenerate the last response\n");
console::log(" /clear clear the chat history\n");
console::log(" /read add a text file\n");
if (inf.has_inp_image) {
console::log(" /image <file> add an image file\n");
}
if (inf.has_inp_audio) {
console::log(" /audio <file> add an audio file\n");
}
console::log("\n");
// interactive loop
std::string cur_msg;
while (true) {
std::string buffer;
console::set_display(DISPLAY_TYPE_USER_INPUT);
if (params.prompt.empty()) {
console::log("\n> ");
std::string line;
bool another_line = true;
do {
another_line = console::readline(line, params.multiline_input);
buffer += line;
} while (another_line);
} else {
// process input prompt from args
for (auto & fname : params.image) {
std::string marker = ctx_cli.load_input_file(fname, true);
if (marker.empty()) {
console::error("file does not exist or cannot be opened: '%s'\n", fname.c_str());
break;
}
console::log("Loaded media from '%s'\n", fname.c_str());
cur_msg += marker;
}
buffer = params.prompt;
if (buffer.size() > 500) {
console::log("\n> %s ... (truncated)\n", buffer.substr(0, 500).c_str());
} else {
console::log("\n> %s\n", buffer.c_str());
}
params.prompt.clear(); // only use it once
}
console::set_display(DISPLAY_TYPE_RESET);
console::log("\n");
if (should_stop()) {
g_is_interrupted.store(false);
break;
}
// remove trailing newline
if (!buffer.empty() &&buffer.back() == '\n') {
buffer.pop_back();
}
// skip empty messages
if (buffer.empty()) {
continue;
}
bool add_user_msg = true;
// process commands
if (string_starts_with(buffer, "/exit")) {
break;
} else if (string_starts_with(buffer, "/regen")) {
if (ctx_cli.messages.size() >= 2) {
size_t last_idx = ctx_cli.messages.size() - 1;
ctx_cli.messages.erase(last_idx);
add_user_msg = false;
} else {
console::error("No message to regenerate.\n");
continue;
}
} else if (string_starts_with(buffer, "/clear")) {
ctx_cli.messages.clear();
ctx_cli.input_files.clear();
console::log("Chat history cleared.\n");
continue;
} else if (
(string_starts_with(buffer, "/image ") && inf.has_inp_image) ||
(string_starts_with(buffer, "/audio ") && inf.has_inp_audio)) {
// just in case (bad copy-paste for example), we strip all trailing/leading spaces
std::string fname = string_strip(buffer.substr(7));
std::string marker = ctx_cli.load_input_file(fname, true);
if (marker.empty()) {
console::error("file does not exist or cannot be opened: '%s'\n", fname.c_str());
continue;
}
cur_msg += marker;
console::log("Loaded media from '%s'\n", fname.c_str());
continue;
} else if (string_starts_with(buffer, "/read ")) {
std::string fname = string_strip(buffer.substr(6));
std::string marker = ctx_cli.load_input_file(fname, false);
if (marker.empty()) {
console::error("file does not exist or cannot be opened: '%s'\n", fname.c_str());
continue;
}
cur_msg += marker;
console::log("Loaded text from '%s'\n", fname.c_str());
continue;
} else {
// not a command
cur_msg += buffer;
}
// generate response
if (add_user_msg) {
ctx_cli.messages.push_back({
{"role", "user"},
{"content", cur_msg}
});
cur_msg.clear();
}
result_timings timings;
std::string assistant_content = ctx_cli.generate_completion(timings);
ctx_cli.messages.push_back({
{"role", "assistant"},
{"content", assistant_content}
});
console::log("\n");
if (params.show_timings) {
console::set_display(DISPLAY_TYPE_INFO);
console::log("\n");
console::log("[ Prompt: %.1f t/s | Generation: %.1f t/s ]\n", timings.prompt_per_second, timings.predicted_per_second);
console::set_display(DISPLAY_TYPE_RESET);
}
if (params.single_turn) {
break;
}
}
console::set_display(DISPLAY_TYPE_RESET);
console::log("\nExiting...\n");
ctx_cli.ctx_server.terminate();
inference_thread.join();
// bump the log level to display timings
common_log_set_verbosity_thold(LOG_LEVEL_INFO);
llama_memory_breakdown_print(ctx_cli.ctx_server.get_llama_context());
return 0;
}
@@ -87,7 +87,7 @@ static void sigint_handler(int signo) {
int main(int argc, char ** argv) {
common_params params;
g_params = &params;
if (!common_params_parse(argc, argv, params, LLAMA_EXAMPLE_MAIN, print_usage)) {
if (!common_params_parse(argc, argv, params, LLAMA_EXAMPLE_COMPLETION, print_usage)) {
return 1;
}
@@ -522,12 +522,6 @@ int main(int argc, char ** argv) {
is_interacting = params.interactive_first;
}
LOG_WRN("*****************************\n");
LOG_WRN("IMPORTANT: The current llama-cli will be moved to llama-completion in the near future\n");
LOG_WRN(" New llama-cli will have enhanced features and improved user experience\n");
LOG_WRN(" More info: https://github.com/ggml-org/llama.cpp/discussions/17618\n");
LOG_WRN("*****************************\n");
bool is_antiprompt = false;
bool input_echo = true;
bool display = true;
@@ -544,7 +538,7 @@ int main(int argc, char ** argv) {
std::ostringstream assistant_ss; // for storing current assistant message, used in conversation mode
// the first thing we will do is to output the prompt, so set color accordingly
console::set_display(console::prompt);
console::set_display(DISPLAY_TYPE_PROMPT);
display = params.display_prompt;
std::vector<llama_token> embd;
@@ -589,9 +583,9 @@ int main(int argc, char ** argv) {
const int skipped_tokens = (int) embd.size() - max_embd_size;
embd.resize(max_embd_size);
console::set_display(console::error);
console::set_display(DISPLAY_TYPE_ERROR);
LOG_WRN("<<input too long: skipped %d token%s>>", skipped_tokens, skipped_tokens != 1 ? "s" : "");
console::set_display(console::reset);
console::set_display(DISPLAY_TYPE_RESET);
}
if (ga_n == 1) {
@@ -773,7 +767,7 @@ int main(int argc, char ** argv) {
// reset color to default if there is no pending user input
if (input_echo && (int) embd_inp.size() == n_consumed) {
console::set_display(console::reset);
console::set_display(DISPLAY_TYPE_RESET);
display = true;
}
@@ -869,7 +863,7 @@ int main(int argc, char ** argv) {
}
// color user input only
console::set_display(console::user_input);
console::set_display(DISPLAY_TYPE_USER_INPUT);
display = params.display_prompt;
std::string line;
@@ -880,7 +874,7 @@ int main(int argc, char ** argv) {
} while (another_line);
// done taking input, reset color
console::set_display(console::reset);
console::set_display(DISPLAY_TYPE_RESET);
display = true;
if (buffer.empty()) { // Ctrl+D on empty line exits
+1 -1
View File
@@ -19,7 +19,7 @@ fi
set -x
SPLIT=$1/llama-gguf-split
MAIN=$1/llama-cli
MAIN=$1/llama-completion
WORK_PATH=$TMP_DIR/gguf-split
ROOT_DIR=$(realpath $(dirname $0)/../../)
+5 -2
View File
@@ -310,6 +310,9 @@ int main(int argc, char ** argv) {
if (g_is_interrupted) return 130;
LOG_WRN("WARN: This is an experimental CLI for testing multimodal capability.\n");
LOG_WRN(" For normal use cases, please use the standard llama-cli\n");
if (is_single_turn) {
g_is_generating = true;
if (params.prompt.find(mtmd_default_marker()) == std::string::npos) {
@@ -349,11 +352,11 @@ int main(int argc, char ** argv) {
while (!g_is_interrupted) {
g_is_generating = false;
LOG("\n> ");
console::set_display(console::user_input);
console::set_display(DISPLAY_TYPE_USER_INPUT);
std::string line;
console::readline(line, false);
if (g_is_interrupted) break;
console::set_display(console::reset);
console::set_display(DISPLAY_TYPE_RESET);
line = string_strip(line);
if (line.empty()) {
continue;
+1 -1
View File
@@ -20,7 +20,7 @@ set -x
SPLIT=$1/llama-gguf-split
QUANTIZE=$1/llama-quantize
MAIN=$1/llama-cli
MAIN=$1/llama-completion
WORK_PATH=$TMP_DIR/quantize
ROOT_DIR=$(realpath $(dirname $0)/../../)
+51 -1
View File
@@ -1474,6 +1474,44 @@ struct server_context_impl {
// Functions to process the task
//
// tokenize the input if it's set by CLI, return false on error
bool tokenize_cli_input(server_task & task) {
if (task.cli_input == nullptr) {
return true; // nothing to do
}
try {
auto & opt = oai_parser_opt;
common_chat_templates_inputs inputs;
inputs.messages = common_chat_msgs_parse_oaicompat(task.cli_input);
inputs.tools = {}; // TODO
inputs.tool_choice = COMMON_CHAT_TOOL_CHOICE_NONE;
inputs.json_schema = ""; // TODO
inputs.grammar = ""; // TODO
inputs.use_jinja = opt.use_jinja;
inputs.parallel_tool_calls = false;
inputs.add_generation_prompt = true;
inputs.reasoning_format = opt.reasoning_format;
inputs.enable_thinking = opt.enable_thinking;
// Apply chat template to the list of messages
auto chat_params = common_chat_templates_apply(opt.tmpls, inputs);
// tokenize the resulting prompt
auto & prompt = chat_params.prompt;
if (mctx != nullptr) {
task.tokens = process_mtmd_prompt(mctx, prompt, task.cli_files);
} else {
task.tokens = std::move(tokenize_input_prompts(vocab, mctx, prompt, true, true)[0]);
}
task.cli_input.clear();
task.cli_files.clear();
} catch (const std::exception & e) {
send_error(task, std::string("Failed to format input: ") + e.what(), ERROR_TYPE_INVALID_REQUEST);
return false;
}
return true;
}
void process_single_task(server_task && task) {
switch (task.type) {
case SERVER_TASK_TYPE_COMPLETION:
@@ -1481,6 +1519,10 @@ struct server_context_impl {
case SERVER_TASK_TYPE_EMBEDDING:
case SERVER_TASK_TYPE_RERANK:
{
if (!tokenize_cli_input(task)) {
break;
}
const int id_slot = task.id_slot;
server_slot * slot = id_slot != -1 ? get_slot_by_id(id_slot) : get_available_slot(task);
@@ -1690,7 +1732,6 @@ struct server_context_impl {
res->id = task.id;
queue_results.send(std::move(res));
} break;
}
}
@@ -2626,6 +2667,15 @@ server_response_reader server_context::get_response_reader() {
return impl->get_response_reader();
}
server_context_info server_context::get_info() const {
return server_context_info {
/* build_info */ build_info,
/* model_name */ impl->model_name,
/* has_inp_image */ impl->oai_parser_opt.allow_image,
/* has_inp_audio */ impl->oai_parser_opt.allow_audio,
};
}
// generator-like API for HTTP response generation
+11
View File
@@ -9,6 +9,13 @@
struct server_context_impl; // private implementation
struct server_context_info {
std::string build_info;
std::string model_name;
bool has_inp_image;
bool has_inp_audio;
};
struct server_context {
std::unique_ptr<server_context_impl> impl;
@@ -33,6 +40,10 @@ struct server_context {
// get a new response reader, used by CLI application
server_response_reader get_response_reader();
// get server info
// used by CLI application
server_context_info get_info() const;
};
+4 -1
View File
@@ -135,7 +135,10 @@ struct server_response_reader {
stop();
}
void post_task(server_task && tasks);
int get_new_id() {
return queue_tasks.get_new_id();
}
void post_task(server_task && task);
void post_tasks(std::vector<server_task> && tasks);
bool has_next() const;
+4
View File
@@ -120,6 +120,10 @@ struct server_task {
task_params params;
server_tokens tokens;
// only used by CLI, this delegates the tokenization to the server
json cli_input = nullptr;
std::vector<raw_buffer> cli_files;
server_task_type type;
// used by SERVER_TASK_TYPE_SLOT_SAVE, SERVER_TASK_TYPE_SLOT_RESTORE, SERVER_TASK_TYPE_SLOT_ERASE