Merge branch 'master' into compilade/imatrix-batched-chunks
This commit is contained in:
commit
1be357d990
149 changed files with 14407 additions and 5105 deletions
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@ -65,6 +65,7 @@ add_library(${TARGET} STATIC
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console.h
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json-schema-to-grammar.cpp
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json.hpp
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llguidance.cpp
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log.cpp
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log.h
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minja.hpp
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|
@ -91,6 +92,33 @@ if (LLAMA_CURL)
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set(LLAMA_COMMON_EXTRA_LIBS ${LLAMA_COMMON_EXTRA_LIBS} ${CURL_LIBRARY})
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endif ()
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if (LLAMA_LLGUIDANCE)
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include(ExternalProject)
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set(LLGUIDANCE_SRC ${CMAKE_BINARY_DIR}/llguidance/source)
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set(LLGUIDANCE_PATH ${LLGUIDANCE_SRC}/target/release)
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ExternalProject_Add(llguidance_ext
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GIT_REPOSITORY https://github.com/guidance-ai/llguidance
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# v0.6.12:
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GIT_TAG ced1c9023d47ec194fa977932d35ce65c2ebfc09
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PREFIX ${CMAKE_BINARY_DIR}/llguidance
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SOURCE_DIR ${LLGUIDANCE_SRC}
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BUILD_IN_SOURCE TRUE
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CONFIGURE_COMMAND ""
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BUILD_COMMAND cargo build --release
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INSTALL_COMMAND ""
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BUILD_BYPRODUCTS ${LLGUIDANCE_PATH}/libllguidance.a ${LLGUIDANCE_PATH}/llguidance.h
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UPDATE_COMMAND ""
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)
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target_compile_definitions(${TARGET} PUBLIC LLAMA_USE_LLGUIDANCE)
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add_library(llguidance STATIC IMPORTED)
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set_target_properties(llguidance PROPERTIES IMPORTED_LOCATION ${LLGUIDANCE_PATH}/libllguidance.a)
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add_dependencies(llguidance llguidance_ext)
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target_include_directories(${TARGET} PRIVATE ${LLGUIDANCE_PATH})
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set(LLAMA_COMMON_EXTRA_LIBS ${LLAMA_COMMON_EXTRA_LIBS} llguidance)
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endif ()
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target_include_directories(${TARGET} PUBLIC .)
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target_compile_features (${TARGET} PUBLIC cxx_std_17)
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target_link_libraries (${TARGET} PRIVATE ${LLAMA_COMMON_EXTRA_LIBS} PUBLIC llama Threads::Threads)
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|
|
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@ -1465,15 +1465,28 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
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{"--list-devices"},
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"print list of available devices and exit",
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[](common_params &) {
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printf("Available devices:\n");
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std::vector<ggml_backend_dev_t> rpc_devices;
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std::vector<ggml_backend_dev_t> all_devices;
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for (size_t i = 0; i < ggml_backend_dev_count(); ++i) {
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auto * dev = ggml_backend_dev_get(i);
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if (ggml_backend_dev_type(dev) == GGML_BACKEND_DEVICE_TYPE_GPU) {
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size_t free, total;
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ggml_backend_dev_memory(dev, &free, &total);
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printf(" %s: %s (%zu MiB, %zu MiB free)\n", ggml_backend_dev_name(dev), ggml_backend_dev_description(dev), total / 1024 / 1024, free / 1024 / 1024);
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ggml_backend_reg_t reg = ggml_backend_dev_backend_reg(dev);
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if (ggml_backend_reg_name(reg) == std::string("RPC")) {
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rpc_devices.push_back(dev);
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} else {
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all_devices.push_back(dev);
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}
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}
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}
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// insert RPC devices in front
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all_devices.insert(all_devices.begin(), rpc_devices.begin(), rpc_devices.end());
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printf("Available devices:\n");
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for (size_t i = 0; i < all_devices.size(); ++i) {
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auto * dev = all_devices[i];
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size_t free, total;
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ggml_backend_dev_memory(dev, &free, &total);
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printf(" %s: %s (%zu MiB, %zu MiB free)\n", ggml_backend_dev_name(dev), ggml_backend_dev_description(dev), total / 1024 / 1024, free / 1024 / 1024);
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}
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exit(0);
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}
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));
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@ -2311,5 +2324,47 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
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}
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).set_examples({LLAMA_EXAMPLE_TTS}));
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add_opt(common_arg(
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{"--embd-bge-small-en-default"},
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string_format("use default bge-small-en-v1.5 model (note: can download weights from the internet)"),
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[](common_params & params) {
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params.hf_repo = "ggml-org/bge-small-en-v1.5-Q8_0-GGUF";
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params.hf_file = "bge-small-en-v1.5-q8_0.gguf";
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params.pooling_type = LLAMA_POOLING_TYPE_NONE;
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params.embd_normalize = 2;
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params.n_ctx = 512;
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params.verbose_prompt = true;
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params.embedding = true;
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}
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).set_examples({LLAMA_EXAMPLE_EMBEDDING, LLAMA_EXAMPLE_SERVER}));
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add_opt(common_arg(
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{"--embd-e5-small-en-default"},
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string_format("use default e5-small-v2 model (note: can download weights from the internet)"),
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[](common_params & params) {
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params.hf_repo = "ggml-org/e5-small-v2-Q8_0-GGUF";
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params.hf_file = "e5-small-v2-q8_0.gguf";
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params.pooling_type = LLAMA_POOLING_TYPE_NONE;
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params.embd_normalize = 2;
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params.n_ctx = 512;
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params.verbose_prompt = true;
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params.embedding = true;
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}
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).set_examples({LLAMA_EXAMPLE_EMBEDDING, LLAMA_EXAMPLE_SERVER}));
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add_opt(common_arg(
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{"--embd-gte-small-default"},
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string_format("use default gte-small model (note: can download weights from the internet)"),
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[](common_params & params) {
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params.hf_repo = "ggml-org/gte-small-Q8_0-GGUF";
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params.hf_file = "gte-small-q8_0.gguf";
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params.pooling_type = LLAMA_POOLING_TYPE_NONE;
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params.embd_normalize = 2;
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params.n_ctx = 512;
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params.verbose_prompt = true;
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params.embedding = true;
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}
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).set_examples({LLAMA_EXAMPLE_EMBEDDING, LLAMA_EXAMPLE_SERVER}));
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return ctx_arg;
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}
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|
|
|
@ -33,6 +33,29 @@ struct chat_template_caps {
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bool requires_typed_content = false;
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};
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struct chat_template_inputs {
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nlohmann::ordered_json messages;
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nlohmann::ordered_json tools;
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bool add_generation_prompt = true;
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nlohmann::ordered_json extra_context;
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std::chrono::system_clock::time_point now = std::chrono::system_clock::now();
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};
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struct chat_template_options {
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bool apply_polyfills = true;
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bool use_bos_token = true;
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bool use_eos_token = true;
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bool define_strftime_now = true;
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bool polyfill_tools = true;
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bool polyfill_tool_call_examples = true;
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bool polyfill_tool_calls = true;
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bool polyfill_tool_responses = true;
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bool polyfill_system_role = true;
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bool polyfill_object_arguments = true;
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bool polyfill_typed_content = true;
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};
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class chat_template {
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private:
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|
@ -41,6 +64,7 @@ class chat_template {
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std::string bos_token_;
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std::string eos_token_;
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std::shared_ptr<minja::TemplateNode> template_root_;
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std::string tool_call_example_;
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std::string try_raw_render(
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const nlohmann::ordered_json & messages,
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|
@ -49,7 +73,18 @@ class chat_template {
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const nlohmann::ordered_json & extra_context = nlohmann::ordered_json()) const
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{
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try {
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auto prompt = apply(messages, tools, add_generation_prompt, extra_context, /* adjust_inputs= */ false);
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chat_template_inputs inputs;
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inputs.messages = messages;
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inputs.tools = tools;
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inputs.add_generation_prompt = add_generation_prompt;
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inputs.extra_context = extra_context;
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// Use fixed date for tests
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inputs.now = std::chrono::system_clock::from_time_t(0);
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chat_template_options opts;
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opts.apply_polyfills = false;
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auto prompt = apply(inputs, opts);
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// fprintf(stderr, "try_raw_render: %s\n", prompt.c_str());
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return prompt;
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} catch (const std::exception & e) {
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|
@ -176,6 +211,58 @@ class chat_template {
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caps_.supports_tool_responses = contains(out, "Some response!");
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caps_.supports_tool_call_id = contains(out, "call_911_");
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}
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try {
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if (!caps_.supports_tools) {
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const json user_msg {
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{"role", "user"},
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{"content", "Hey"},
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};
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const json args {
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{"arg1", "some_value"},
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};
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const json tool_call_msg {
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{"role", "assistant"},
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{"content", nullptr},
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{"tool_calls", json::array({
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{
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||||
// TODO: detect if requires numerical id or fixed length == 6 like Nemo
|
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{"id", "call_1___"},
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{"type", "function"},
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{"function", {
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{"name", "tool_name"},
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{"arguments", (caps_.requires_object_arguments ? args : json(minja::Value(args).dump(-1, /* to_json= */ true)))},
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}},
|
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},
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})},
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};
|
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std::string prefix, full;
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{
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chat_template_inputs inputs;
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inputs.messages = json::array({user_msg});
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inputs.add_generation_prompt = true;
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prefix = apply(inputs);
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}
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{
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chat_template_inputs inputs;
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inputs.messages = json::array({user_msg, tool_call_msg});
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inputs.add_generation_prompt = false;
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full = apply(inputs);
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}
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if (full.find(prefix) != 0) {
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if (prefix.rfind(eos_token_) == prefix.size() - eos_token_.size()) {
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prefix = prefix.substr(0, prefix.size() - eos_token_.size());
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}
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}
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if (full.find(prefix) != 0) {
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fprintf(stderr, "Failed to infer a tool call example (possible template bug)\n");
|
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}
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tool_call_example_ = full.substr(prefix.size());
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}
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} catch (const std::exception & e) {
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fprintf(stderr, "Failed to generate tool call example: %s\n", e.what());
|
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}
|
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}
|
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|
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const std::string & source() const { return source_; }
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|
@ -183,28 +270,72 @@ class chat_template {
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const std::string & eos_token() const { return eos_token_; }
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const chat_template_caps & original_caps() const { return caps_; }
|
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|
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// Deprecated, please use the form with chat_template_inputs and chat_template_options
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std::string apply(
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const nlohmann::ordered_json & messages,
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const nlohmann::ordered_json & tools,
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bool add_generation_prompt,
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const nlohmann::ordered_json & extra_context = nlohmann::ordered_json(),
|
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bool adjust_inputs = true) const
|
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bool apply_polyfills = true)
|
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{
|
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fprintf(stderr, "[%s] Deprecated!\n", __func__);
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chat_template_inputs inputs;
|
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inputs.messages = messages;
|
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inputs.tools = tools;
|
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inputs.add_generation_prompt = add_generation_prompt;
|
||||
inputs.extra_context = extra_context;
|
||||
inputs.now = std::chrono::system_clock::now();
|
||||
|
||||
chat_template_options opts;
|
||||
opts.apply_polyfills = apply_polyfills;
|
||||
|
||||
return apply(inputs, opts);
|
||||
}
|
||||
|
||||
std::string apply(
|
||||
const chat_template_inputs & inputs,
|
||||
const chat_template_options & opts = chat_template_options()) const
|
||||
{
|
||||
json actual_messages;
|
||||
|
||||
auto needs_adjustments = adjust_inputs && (false
|
||||
|| !caps_.supports_system_role
|
||||
|| !caps_.supports_tools
|
||||
|| !caps_.supports_tool_responses
|
||||
|| !caps_.supports_tool_calls
|
||||
|| caps_.requires_object_arguments
|
||||
|| caps_.requires_typed_content
|
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auto has_tools = inputs.tools.is_array() && !inputs.tools.empty();
|
||||
auto has_tool_calls = false;
|
||||
auto has_tool_responses = false;
|
||||
auto has_string_content = false;
|
||||
for (const auto & message : inputs.messages) {
|
||||
if (message.contains("tool_calls") && !message["tool_calls"].is_null()) {
|
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has_tool_calls = true;
|
||||
}
|
||||
if (message.contains("role") && message["role"] == "tool") {
|
||||
has_tool_responses = true;
|
||||
}
|
||||
if (message.contains("content") && message["content"].is_string()) {
|
||||
has_string_content = true;
|
||||
}
|
||||
}
|
||||
|
||||
auto polyfill_system_role = opts.polyfill_system_role && !caps_.supports_system_role;
|
||||
auto polyfill_tools = opts.polyfill_tools && has_tools && !caps_.supports_tools;
|
||||
auto polyfill_tool_call_example = polyfill_tools && opts.polyfill_tool_call_examples;
|
||||
auto polyfill_tool_calls = opts.polyfill_tool_calls && has_tool_calls && !caps_.supports_tool_calls;
|
||||
auto polyfill_tool_responses = opts.polyfill_tool_responses && has_tool_responses && !caps_.supports_tool_responses;
|
||||
auto polyfill_object_arguments = opts.polyfill_object_arguments && has_tool_calls && caps_.requires_object_arguments;
|
||||
auto polyfill_typed_content = opts.polyfill_typed_content && has_string_content && caps_.requires_typed_content;
|
||||
|
||||
auto needs_polyfills = opts.apply_polyfills && (false
|
||||
|| polyfill_system_role
|
||||
|| polyfill_tools
|
||||
|| polyfill_tool_calls
|
||||
|| polyfill_tool_responses
|
||||
|| polyfill_object_arguments
|
||||
|| polyfill_typed_content
|
||||
);
|
||||
if (needs_adjustments) {
|
||||
|
||||
if (needs_polyfills) {
|
||||
actual_messages = json::array();
|
||||
|
||||
auto add_message = [&](const json & msg) {
|
||||
if (caps_.requires_typed_content && msg.contains("content") && !msg.at("content").is_null() && msg.at("content").is_string()) {
|
||||
if (polyfill_typed_content && msg.contains("content") && !msg.at("content").is_null() && msg.at("content").is_string()) {
|
||||
actual_messages.push_back({
|
||||
{"role", msg.at("role")},
|
||||
{"content", {{
|
||||
|
@ -227,9 +358,17 @@ class chat_template {
|
|||
pending_system.clear();
|
||||
}
|
||||
};
|
||||
auto needs_tools_in_system = !tools.is_null() && tools.size() > 0 && !caps_.supports_tools;
|
||||
|
||||
for (const auto & message_ : needs_tools_in_system ? add_system(messages, "Available tools: " + tools.dump(2)) : messages) {
|
||||
json adjusted_messages;
|
||||
if (polyfill_tools) {
|
||||
adjusted_messages = add_system(inputs.messages,
|
||||
"You can call any of the following tools to satisfy the user's requests: " + minja::Value(inputs.tools).dump(2, /* to_json= */ true) +
|
||||
(!polyfill_tool_call_example || tool_call_example_.empty() ? "" : "\n\nExample tool call syntax:\n\n" + tool_call_example_));
|
||||
} else {
|
||||
adjusted_messages = inputs.messages;
|
||||
}
|
||||
|
||||
for (const auto & message_ : adjusted_messages) {
|
||||
auto message = message_;
|
||||
if (!message.contains("role") || !message.contains("content")) {
|
||||
throw std::runtime_error("message must have 'role' and 'content' fields: " + message.dump());
|
||||
|
@ -237,7 +376,7 @@ class chat_template {
|
|||
std::string role = message.at("role");
|
||||
|
||||
if (message.contains("tool_calls")) {
|
||||
if (caps_.requires_object_arguments || !caps_.supports_tool_calls) {
|
||||
if (polyfill_object_arguments || polyfill_tool_calls) {
|
||||
for (auto & tool_call : message.at("tool_calls")) {
|
||||
if (tool_call["type"] == "function") {
|
||||
auto & function = tool_call.at("function");
|
||||
|
@ -252,7 +391,7 @@ class chat_template {
|
|||
}
|
||||
}
|
||||
}
|
||||
if (!caps_.supports_tool_calls) {
|
||||
if (polyfill_tool_calls) {
|
||||
auto content = message.at("content");
|
||||
auto tool_calls = json::array();
|
||||
for (const auto & tool_call : message.at("tool_calls")) {
|
||||
|
@ -279,14 +418,16 @@ class chat_template {
|
|||
message.erase("tool_calls");
|
||||
}
|
||||
}
|
||||
if (!caps_.supports_tool_responses && role == "tool") {
|
||||
if (polyfill_tool_responses && role == "tool") {
|
||||
message["role"] = "user";
|
||||
auto obj = json {
|
||||
{"tool_response", {
|
||||
{"tool", message.at("name")},
|
||||
{"content", message.at("content")},
|
||||
}},
|
||||
};
|
||||
if (message.contains("name")) {
|
||||
obj["tool_response"]["name"] = message.at("name");
|
||||
}
|
||||
if (message.contains("tool_call_id")) {
|
||||
obj["tool_response"]["tool_call_id"] = message.at("tool_call_id");
|
||||
}
|
||||
|
@ -294,7 +435,7 @@ class chat_template {
|
|||
message.erase("name");
|
||||
}
|
||||
|
||||
if (!message["content"].is_null() && !caps_.supports_system_role) {
|
||||
if (!message["content"].is_null() && polyfill_system_role) {
|
||||
std::string content = message.at("content");
|
||||
if (role == "system") {
|
||||
if (!pending_system.empty()) pending_system += "\n";
|
||||
|
@ -313,28 +454,36 @@ class chat_template {
|
|||
}
|
||||
add_message(message);
|
||||
}
|
||||
if (!caps_.supports_system_role) {
|
||||
flush_sys();
|
||||
}
|
||||
flush_sys();
|
||||
} else {
|
||||
actual_messages = messages;
|
||||
actual_messages = inputs.messages;
|
||||
}
|
||||
|
||||
auto context = minja::Context::make(json({
|
||||
{"messages", actual_messages},
|
||||
{"add_generation_prompt", add_generation_prompt},
|
||||
{"bos_token", bos_token_},
|
||||
{"eos_token", eos_token_},
|
||||
{"add_generation_prompt", inputs.add_generation_prompt},
|
||||
}));
|
||||
context->set("bos_token", opts.use_bos_token ? bos_token_ : "");
|
||||
context->set("eos_token", opts.use_eos_token ? eos_token_ : "");
|
||||
if (opts.define_strftime_now) {
|
||||
auto now = inputs.now;
|
||||
context->set("strftime_now", Value::callable([now](const std::shared_ptr<minja::Context> &, minja::ArgumentsValue & args) {
|
||||
args.expectArgs("strftime_now", {1, 1}, {0, 0});
|
||||
auto format = args.args[0].get<std::string>();
|
||||
|
||||
if (!tools.is_null()) {
|
||||
auto tools_val = minja::Value(tools);
|
||||
context->set("tools", tools_val);
|
||||
auto time = std::chrono::system_clock::to_time_t(now);
|
||||
auto local_time = *std::localtime(&time);
|
||||
std::ostringstream ss;
|
||||
ss << std::put_time(&local_time, format.c_str());
|
||||
return ss.str();
|
||||
}));
|
||||
}
|
||||
if (!extra_context.is_null()) {
|
||||
for (auto & kv : extra_context.items()) {
|
||||
minja::Value val(kv.value());
|
||||
context->set(kv.key(), val);
|
||||
if (!inputs.tools.is_null()) {
|
||||
context->set("tools", minja::Value(inputs.tools));
|
||||
}
|
||||
if (!inputs.extra_context.is_null()) {
|
||||
for (auto & kv : inputs.extra_context.items()) {
|
||||
context->set(kv.key(), minja::Value(kv.value()));
|
||||
}
|
||||
}
|
||||
|
||||
|
@ -351,7 +500,7 @@ class chat_template {
|
|||
std::string existing_system = messages_with_system.at(0).at("content");
|
||||
messages_with_system[0] = json {
|
||||
{"role", "system"},
|
||||
{"content", existing_system + "\n" + system_prompt},
|
||||
{"content", existing_system + "\n\n" + system_prompt},
|
||||
};
|
||||
} else {
|
||||
messages_with_system.insert(messages_with_system.begin(), json {
|
||||
|
|
150
common/chat.cpp
150
common/chat.cpp
|
@ -16,6 +16,7 @@ std::string common_chat_format_name(common_chat_format format) {
|
|||
case COMMON_CHAT_FORMAT_FUNCTIONARY_V3_2: return "Functionary v3.2";
|
||||
case COMMON_CHAT_FORMAT_FUNCTIONARY_V3_1_LLAMA_3_1: return "Functionary v3.1 Llama 3.1";
|
||||
case COMMON_CHAT_FORMAT_HERMES_2_PRO: return "Hermes 2 Pro";
|
||||
case COMMON_CHAT_FORMAT_COMMAND_R7B: return "Command R7B";
|
||||
default:
|
||||
throw std::runtime_error("Unknown chat format");
|
||||
}
|
||||
|
@ -162,6 +163,28 @@ static void foreach_function(const json & tools, const std::function<void(const
|
|||
}
|
||||
}
|
||||
|
||||
static std::string apply(
|
||||
const common_chat_template & tmpl,
|
||||
const nlohmann::ordered_json & messages,
|
||||
const nlohmann::ordered_json & tools,
|
||||
bool add_generation_prompt,
|
||||
const nlohmann::ordered_json & extra_context = nlohmann::ordered_json())
|
||||
{
|
||||
minja::chat_template_inputs tmpl_inputs;
|
||||
tmpl_inputs.messages = messages;
|
||||
tmpl_inputs.tools = tools;
|
||||
tmpl_inputs.add_generation_prompt = add_generation_prompt;
|
||||
tmpl_inputs.extra_context = extra_context;
|
||||
// TODO: add flag to control date/time, if only for testing purposes.
|
||||
// tmpl_inputs.now = std::chrono::system_clock::now();
|
||||
|
||||
minja::chat_template_options tmpl_opts;
|
||||
tmpl_opts.use_bos_token = false;
|
||||
tmpl_opts.use_eos_token = false;
|
||||
|
||||
return tmpl.apply(tmpl_inputs, tmpl_opts);
|
||||
}
|
||||
|
||||
static common_chat_params common_chat_params_init_generic(const common_chat_template & tmpl, const struct common_chat_inputs & inputs) {
|
||||
common_chat_params data;
|
||||
|
||||
|
@ -243,7 +266,7 @@ static common_chat_params common_chat_params_init_generic(const common_chat_temp
|
|||
inputs.messages,
|
||||
"Respond in JSON format, either with `tool_call` (a request to call tools) or with `response` reply to the user's request");
|
||||
|
||||
data.prompt = tmpl.apply(tweaked_messages, inputs.tools.empty() ? json() : inputs.tools, inputs.add_generation_prompt);
|
||||
data.prompt = apply(tmpl, tweaked_messages, inputs.tools.empty() ? json() : inputs.tools, inputs.add_generation_prompt);
|
||||
data.format = COMMON_CHAT_FORMAT_GENERIC;
|
||||
return data;
|
||||
}
|
||||
|
@ -309,7 +332,7 @@ static common_chat_params common_chat_params_init_mistral_nemo(const common_chat
|
|||
builder.add_rule("root", "\"[TOOL_CALLS]\" " + builder.add_schema("tool_calls", schema));
|
||||
}, grammar_options);
|
||||
data.grammar_triggers.push_back({"[TOOL_CALLS]", /* .at_start = */ true});
|
||||
data.prompt = tmpl.apply(inputs.messages, inputs.tools.empty() ? json() : inputs.tools, inputs.add_generation_prompt);
|
||||
data.prompt = apply(tmpl, inputs.messages, inputs.tools.empty() ? json() : inputs.tools, inputs.add_generation_prompt);
|
||||
data.format = COMMON_CHAT_FORMAT_MISTRAL_NEMO;
|
||||
return data;
|
||||
}
|
||||
|
@ -317,6 +340,79 @@ static common_chat_msg common_chat_parse_mistral_nemo(const std::string & input)
|
|||
return parse_prefixed_json_tool_call_array(input, "[TOOL_CALLS]");
|
||||
}
|
||||
|
||||
static common_chat_params common_chat_params_init_command_r7b(const common_chat_template & tmpl, const struct common_chat_inputs & inputs) {
|
||||
common_chat_params data;
|
||||
data.grammar_lazy = inputs.tool_choice != "required";
|
||||
data.grammar = build_grammar([&](const common_grammar_builder & builder) {
|
||||
auto schemas = json::array();
|
||||
foreach_function(inputs.tools, [&](const json & tool) {
|
||||
const auto & function = tool["function"];
|
||||
schemas.push_back({
|
||||
{"type", "object"},
|
||||
{"properties", {
|
||||
{"tool_call_id", {
|
||||
{"type", "string"},
|
||||
// Command-R's template expects an integer string.
|
||||
{"pattern", "^[0-9]{1,10}$"},
|
||||
}},
|
||||
{"tool_name", {
|
||||
{"type", "string"},
|
||||
{"const", function["name"]},
|
||||
}},
|
||||
{"parameters", function["parameters"]},
|
||||
}},
|
||||
{"required", json::array({"tool_call_id", "tool_name", "parameters"})},
|
||||
});
|
||||
});
|
||||
auto schema = json {
|
||||
{"type", "array"},
|
||||
{"items", schemas.size() == 1 ? schemas[0] : json {{"anyOf", schemas}}},
|
||||
{"minItems", 1},
|
||||
};
|
||||
if (!inputs.parallel_tool_calls) {
|
||||
schema["maxItems"] = 1;
|
||||
}
|
||||
builder.add_rule("root", "\"<|START_ACTION|>\" " + builder.add_schema("tool_calls", schema) + " \"<|END_ACTION|>\"");
|
||||
}, grammar_options);
|
||||
data.grammar_triggers.push_back({"<|START_ACTION|>", /* .at_start = */ false});
|
||||
data.preserved_tokens = {
|
||||
"<|START_RESPONSE|>",
|
||||
"<|END_RESPONSE|>",
|
||||
"<|START_THINKING|>",
|
||||
"<|END_THINKING|>",
|
||||
"<|END_ACTION|>",
|
||||
};
|
||||
data.prompt = apply(tmpl, inputs.messages, inputs.tools.empty() ? json() : inputs.tools, inputs.add_generation_prompt);
|
||||
data.format = COMMON_CHAT_FORMAT_COMMAND_R7B;
|
||||
return data;
|
||||
}
|
||||
static common_chat_msg common_chat_parse_command_r7b(const std::string & input) {
|
||||
static std::regex response_regex("<\\|START_RESPONSE\\|>([\\s\\S\\n\\r]*?)<\\|END_RESPONSE\\|>");
|
||||
static std::regex thought_action_regex("<\\|START_THINKING\\|>([\\s\\S\\n\\r]*?)<\\|END_THINKING\\|><\\|START_ACTION\\|>([\\s\\S\\n\\r]*?)<\\|END_ACTION\\|>");
|
||||
std::smatch match;
|
||||
|
||||
common_chat_msg result;
|
||||
result.role = "assistant";
|
||||
if (std::regex_match(input, match, response_regex)) {
|
||||
result.content = match[1].str();
|
||||
} else if (std::regex_match(input, match, thought_action_regex)) {
|
||||
result.tool_plan = match[1].str();
|
||||
auto actions_str = match[2].str();
|
||||
auto actions = json::parse(actions_str);
|
||||
for (const auto & action : actions) {
|
||||
result.tool_calls.push_back({
|
||||
/* .name = */ action["tool_name"],
|
||||
/* .arguments = */ action["parameters"].dump(),
|
||||
/* .id = */ action["tool_call_id"],
|
||||
});
|
||||
}
|
||||
} else {
|
||||
LOG_ERR("Failed to parse command_r output");
|
||||
result.content = input;
|
||||
}
|
||||
return result;
|
||||
}
|
||||
|
||||
static void expect_tool_parameters(const std::string & name, const json & parameters, const std::vector<std::string> & expected_properties) {
|
||||
if (!parameters.is_object() || !parameters.contains("type") || parameters["type"] != "object" || !parameters.contains("properties") || !parameters.contains("required")) {
|
||||
throw std::runtime_error("Parameters of tool " + name + " must be an object w/ required properties");
|
||||
|
@ -384,21 +480,26 @@ static common_chat_params common_chat_params_init_llama_3_1_tool_calls(const com
|
|||
tool_rules.push_back(
|
||||
builder.add_rule(
|
||||
name + "-call",
|
||||
"\"{\" ( \"\\\"type\\\": \\\"function\\\", \" | space ) "
|
||||
"\"{\" space "
|
||||
"( \"\\\"type\\\":\" space \"\\\"function\\\",\" space )? "
|
||||
"\"\\\"name\\\": \\\"" + name + "\\\", \\\"parameters\\\": \" " +
|
||||
builder.add_schema(name + "-args", parameters) +
|
||||
" \"}\""));
|
||||
data.grammar_triggers.push_back({"{\"name\": \"" + name + "\"", /* .at_start = */ true});
|
||||
});
|
||||
data.grammar_triggers.push_back({"{\"name\":", /* .at_start = */ true});
|
||||
data.grammar_triggers.push_back({"{\n \"name\":", /* .at_start = */ true});
|
||||
data.grammar_triggers.push_back({"{\n \"name\":", /* .at_start = */ true});
|
||||
data.grammar_triggers.push_back({"{\"type\": \"function\"", /* .at_start = */ true});
|
||||
data.grammar_triggers.push_back({"{\n \"type\": \"function\"", /* .at_start = */ true});
|
||||
data.grammar_triggers.push_back({"{\n \"type\": \"function\"", /* .at_start = */ true});
|
||||
if (!builtin_tools.empty()) {
|
||||
data.grammar_triggers.push_back({"<|python_tag|>", /* .at_start = */ false});
|
||||
}
|
||||
builder.add_rule("root", string_join(tool_rules, " | "));
|
||||
}, grammar_options);
|
||||
data.additional_stops.push_back("<|eom_id|>");
|
||||
data.prompt = tmpl.apply(inputs.messages, inputs.tools.empty() ? json() : inputs.tools, inputs.add_generation_prompt, {
|
||||
data.prompt = apply(tmpl, inputs.messages, inputs.tools.empty() ? json() : inputs.tools, inputs.add_generation_prompt, {
|
||||
{"tools_in_user_message", false},
|
||||
{"builtin_tools", builtin_tools.empty() ? json() : builtin_tools},
|
||||
});
|
||||
|
@ -457,9 +558,14 @@ static common_chat_params common_chat_params_init_deepseek_r1(const common_chat_
|
|||
"\"<|tool▁call▁begin|>function<|tool▁sep|>" + name + "\\n```json\\n\" " + args_rule + " \"```<|tool▁call▁end|>\""));
|
||||
});
|
||||
data.grammar_triggers.push_back({"<|tool▁calls▁begin|>", /* .at_start = */ false});
|
||||
data.preserved_tokens = {
|
||||
"<|tool▁sep|>",
|
||||
"<|tool▁call▁end|>",
|
||||
};
|
||||
builder.add_rule("root", "\"<|tool▁calls▁begin|>\" (" + string_join(tool_rules, " | ") + ")" + (inputs.parallel_tool_calls ? "*" : "") + " space");
|
||||
}, grammar_options);
|
||||
data.prompt = tmpl.apply(inputs.messages, inputs.tools.empty() ? json() : inputs.tools, inputs.add_generation_prompt);
|
||||
auto prompt = apply(tmpl, inputs.messages, inputs.tools.empty() ? json() : inputs.tools, inputs.add_generation_prompt);
|
||||
data.prompt = prompt;
|
||||
data.format = COMMON_CHAT_FORMAT_DEEPSEEK_R1;
|
||||
return data;
|
||||
}
|
||||
|
@ -473,10 +579,10 @@ static common_chat_msg common_chat_parse_deepseek_r1(const std::string & input)
|
|||
static common_chat_params common_chat_params_init_firefunction_v2(const common_chat_template & tmpl, const struct common_chat_inputs & inputs) {
|
||||
fprintf(stderr, "%s\n", __func__);
|
||||
common_chat_params data;
|
||||
data.prompt = tmpl.apply(inputs.messages, /* tools= */ nullptr, inputs.add_generation_prompt, {
|
||||
data.prompt = apply(tmpl, inputs.messages, /* tools= */ nullptr, inputs.add_generation_prompt, {
|
||||
{"datetime", "Jan 29 2025 13:00:00 GMT"},
|
||||
{"functions", json(inputs.tools.empty() ? "" : inputs.tools.dump(2))},
|
||||
}, /* adjust_inputs= */ false);
|
||||
});
|
||||
if (!inputs.tools.is_null() && !inputs.tools.empty()) {
|
||||
data.grammar_lazy = inputs.tool_choice != "required";
|
||||
data.grammar = build_grammar([&](const common_grammar_builder & builder) {
|
||||
|
@ -520,7 +626,7 @@ static common_chat_params common_chat_params_init_functionary_v3_2(const common_
|
|||
// >>>all\nlet's call functions>>>fn1\n{"arg1": 1...}\n>>>fn2\n{"arg1": 1...}...
|
||||
// Using ">>>f1\n", ">>>f2\n"... as trigger words for the grammar
|
||||
common_chat_params data;
|
||||
data.prompt = tmpl.apply(inputs.messages, inputs.tools.empty() ? json() : inputs.tools, inputs.add_generation_prompt);
|
||||
data.prompt = apply(tmpl, inputs.messages, inputs.tools.empty() ? json() : inputs.tools, inputs.add_generation_prompt);
|
||||
data.format = COMMON_CHAT_FORMAT_FUNCTIONARY_V3_2;
|
||||
if (!inputs.tools.is_null() && !inputs.tools.empty()) {
|
||||
data.grammar_lazy = inputs.tool_choice != "required";
|
||||
|
@ -586,9 +692,17 @@ static common_chat_msg common_chat_parse_functionary_v3_2(const std::string & in
|
|||
}
|
||||
}
|
||||
// TODO: tighten & simplify.
|
||||
auto res = parse_json_tool_calls(std::string(it, end), std::nullopt, function_regex, close_regex);
|
||||
res.content = content;
|
||||
return res;
|
||||
try {
|
||||
auto res = parse_json_tool_calls(std::string(it, end), std::nullopt, function_regex, close_regex);
|
||||
res.content = content + res.content;
|
||||
return res;
|
||||
} catch (const std::exception & e) {
|
||||
LOG_ERR("Failed to parse functionary v3.2 input: %s\n", e.what());
|
||||
common_chat_msg res;
|
||||
res.role = "assistant";
|
||||
res.content = input;
|
||||
return res;
|
||||
}
|
||||
}
|
||||
|
||||
static common_chat_params common_chat_params_init_functionary_v3_1_llama_3_1(const common_chat_template & tmpl, const struct common_chat_inputs & inputs) {
|
||||
|
@ -639,7 +753,7 @@ static common_chat_params common_chat_params_init_functionary_v3_1_llama_3_1(con
|
|||
data.grammar_triggers.push_back({"<function=", /* .at_start = */ false});
|
||||
}, grammar_options);
|
||||
|
||||
data.prompt = tmpl.apply(inputs.messages, inputs.tools.empty() ? json() : inputs.tools, inputs.add_generation_prompt);
|
||||
data.prompt = apply(tmpl, inputs.messages, inputs.tools.empty() ? json() : inputs.tools, inputs.add_generation_prompt);
|
||||
// TODO: if (has_raw_python)
|
||||
data.format = COMMON_CHAT_FORMAT_FUNCTIONARY_V3_1_LLAMA_3_1;
|
||||
return data;
|
||||
|
@ -691,11 +805,10 @@ static common_chat_params common_chat_params_init_hermes_2_pro(const common_chat
|
|||
auto tool_call = "\"<tool_call>\" space " + builder.add_rule("tool_call", string_join(tool_rules, " | ")) + " \"</tool_call>\" space";
|
||||
builder.add_rule("root", inputs.parallel_tool_calls ? "(" + tool_call + ")+" : tool_call);
|
||||
data.grammar_triggers.push_back({"<tool_call>", /* .at_start = */ false});
|
||||
// Not really a trigger but need to print this special token to get a successful parse.
|
||||
data.grammar_triggers.push_back({"</tool_call>", /* .at_start = */ false});
|
||||
data.preserved_tokens = { "</tool_call>" };
|
||||
}, grammar_options);
|
||||
|
||||
data.prompt = tmpl.apply(inputs.messages, inputs.tools.empty() ? json() : inputs.tools, inputs.add_generation_prompt);
|
||||
data.prompt = apply(tmpl, inputs.messages, inputs.tools.empty() ? json() : inputs.tools, inputs.add_generation_prompt);
|
||||
data.format = COMMON_CHAT_FORMAT_HERMES_2_PRO;
|
||||
return data;
|
||||
}
|
||||
|
@ -756,7 +869,7 @@ static common_chat_msg common_chat_parse_hermes_2_pro(const std::string & input)
|
|||
|
||||
static common_chat_params common_chat_params_init_without_tools(const common_chat_template & tmpl, const struct common_chat_inputs & inputs) {
|
||||
common_chat_params data;
|
||||
data.prompt = tmpl.apply(inputs.messages, inputs.tools.empty() ? json() : inputs.tools, inputs.add_generation_prompt);
|
||||
data.prompt = apply(tmpl, inputs.messages, inputs.tools.empty() ? json() : inputs.tools, inputs.add_generation_prompt);
|
||||
data.format = COMMON_CHAT_FORMAT_CONTENT_ONLY;
|
||||
data.grammar_lazy = false;
|
||||
if (!inputs.json_schema.is_null()) {
|
||||
|
@ -809,6 +922,9 @@ common_chat_params common_chat_params_init(const common_chat_template & tmpl, co
|
|||
if (src.find("[TOOL_CALLS]") != std::string::npos) {
|
||||
return common_chat_params_init_mistral_nemo(tmpl, inputs);
|
||||
}
|
||||
if (src.find("<|END_THINKING|><|START_ACTION|>") != std::string::npos) {
|
||||
return common_chat_params_init_command_r7b(tmpl, inputs);
|
||||
}
|
||||
return common_chat_params_init_generic(tmpl, inputs);
|
||||
}
|
||||
|
||||
|
@ -842,6 +958,8 @@ common_chat_msg common_chat_parse(const std::string & input, common_chat_format
|
|||
return common_chat_parse_hermes_2_pro(input);
|
||||
case COMMON_CHAT_FORMAT_FIREFUNCTION_V2:
|
||||
return common_chat_parse_firefunction_v2(input);
|
||||
case COMMON_CHAT_FORMAT_COMMAND_R7B:
|
||||
return common_chat_parse_command_r7b(input);
|
||||
default:
|
||||
throw std::runtime_error("Unsupported format: " + common_chat_format_name(format));
|
||||
}
|
||||
|
|
|
@ -32,6 +32,7 @@ enum common_chat_format {
|
|||
COMMON_CHAT_FORMAT_FUNCTIONARY_V3_2,
|
||||
COMMON_CHAT_FORMAT_FUNCTIONARY_V3_1_LLAMA_3_1,
|
||||
COMMON_CHAT_FORMAT_HERMES_2_PRO,
|
||||
COMMON_CHAT_FORMAT_COMMAND_R7B,
|
||||
|
||||
COMMON_CHAT_FORMAT_COUNT, // Not a format, just the # formats
|
||||
};
|
||||
|
@ -42,6 +43,7 @@ struct common_chat_params {
|
|||
std::string grammar;
|
||||
bool grammar_lazy = false;
|
||||
std::vector<common_grammar_trigger> grammar_triggers;
|
||||
std::vector<std::string> preserved_tokens;
|
||||
std::vector<std::string> additional_stops;
|
||||
};
|
||||
|
||||
|
|
|
@ -1869,11 +1869,19 @@ std::string common_chat_format_example(const common_chat_template & tmpl, bool u
|
|||
return common_chat_apply_template(tmpl, msgs, true, use_jinja);
|
||||
}
|
||||
|
||||
#define CHATML_TEMPLATE_SRC \
|
||||
"{%- for message in messages -%}\n" \
|
||||
" {{- '<|im_start|>' + message.role + '\n' + message.content + '<|im_end|>\n' -}}\n" \
|
||||
"{%- endfor -%}\n" \
|
||||
"{%- if add_generation_prompt -%}\n" \
|
||||
" {{- '<|im_start|>assistant\n' -}}\n" \
|
||||
"{%- endif -%}"
|
||||
|
||||
common_chat_templates common_chat_templates_from_model(const struct llama_model * model, const std::string & chat_template_override)
|
||||
{
|
||||
auto vocab = llama_model_get_vocab(model);
|
||||
std::string default_template_src = chat_template_override;
|
||||
std::string template_tool_use_src = chat_template_override;
|
||||
std::string default_template_src;
|
||||
std::string template_tool_use_src;
|
||||
|
||||
bool has_explicit_template = !chat_template_override.empty();
|
||||
if (chat_template_override.empty()) {
|
||||
auto str = llama_model_chat_template(model, /* name */ nullptr);
|
||||
|
@ -1886,21 +1894,17 @@ common_chat_templates common_chat_templates_from_model(const struct llama_model
|
|||
template_tool_use_src = str;
|
||||
has_explicit_template = true;
|
||||
}
|
||||
} else {
|
||||
default_template_src = chat_template_override;
|
||||
}
|
||||
if (default_template_src.empty() || default_template_src == "chatml") {
|
||||
if (!template_tool_use_src.empty()) {
|
||||
default_template_src = template_tool_use_src;
|
||||
} else {
|
||||
default_template_src = R"(
|
||||
{%- for message in messages -%}
|
||||
{{- "<|im_start|>" + message.role + "\n" + message.content + "<|im_end|>\n" -}}
|
||||
{%- endfor -%}
|
||||
{%- if add_generation_prompt -%}
|
||||
{{- "<|im_start|>assistant\n" -}}
|
||||
{%- endif -%}
|
||||
)";
|
||||
default_template_src = CHATML_TEMPLATE_SRC;
|
||||
}
|
||||
}
|
||||
auto vocab = llama_model_get_vocab(model);
|
||||
const auto get_token = [&](llama_token token, const char * name, const char * jinja_variable_name) {
|
||||
if (token == LLAMA_TOKEN_NULL) {
|
||||
if (default_template_src.find(jinja_variable_name) != std::string::npos
|
||||
|
@ -1914,13 +1918,22 @@ common_chat_templates common_chat_templates_from_model(const struct llama_model
|
|||
};
|
||||
auto token_bos = get_token(llama_vocab_bos(vocab), "BOS", "bos_token");
|
||||
auto token_eos = get_token(llama_vocab_eos(vocab), "EOS", "eos_token");
|
||||
return {
|
||||
has_explicit_template,
|
||||
std::make_unique<minja::chat_template>(default_template_src, token_bos, token_eos),
|
||||
template_tool_use_src.empty()
|
||||
? nullptr
|
||||
: std::make_unique<minja::chat_template>(template_tool_use_src, token_bos, token_eos)
|
||||
};
|
||||
try {
|
||||
return {
|
||||
has_explicit_template,
|
||||
std::make_unique<minja::chat_template>(default_template_src, token_bos, token_eos),
|
||||
template_tool_use_src.empty()
|
||||
? nullptr
|
||||
: std::make_unique<minja::chat_template>(template_tool_use_src, token_bos, token_eos),
|
||||
};
|
||||
} catch (const std::exception & e) {
|
||||
LOG_ERR("%s: failed to parse chat template: %s\n", __func__, e.what());
|
||||
return {
|
||||
has_explicit_template,
|
||||
std::make_unique<minja::chat_template>(CHATML_TEMPLATE_SRC, token_bos, token_eos),
|
||||
nullptr,
|
||||
};
|
||||
}
|
||||
}
|
||||
|
||||
//
|
||||
|
|
|
@ -4,6 +4,7 @@
|
|||
|
||||
#include "llama-cpp.h"
|
||||
|
||||
#include <set>
|
||||
#include <string>
|
||||
#include <vector>
|
||||
#include <sstream>
|
||||
|
@ -163,6 +164,7 @@ struct common_params_sampling {
|
|||
bool grammar_lazy = false;
|
||||
std::vector<common_grammar_trigger> grammar_trigger_words; // optional trigger words to trigger lazy grammar
|
||||
std::vector<llama_token> grammar_trigger_tokens; // optional trigger tokens to trigger lazy grammar and print trigger special tokens.
|
||||
std::set<llama_token> preserved_tokens;
|
||||
|
||||
std::vector<llama_logit_bias> logit_bias; // logit biases to apply
|
||||
|
||||
|
@ -621,6 +623,7 @@ struct common_chat_msg {
|
|||
std::string role;
|
||||
std::string content;
|
||||
std::vector<common_tool_call> tool_calls;
|
||||
std::string tool_plan = "";
|
||||
};
|
||||
|
||||
// Check if the template supplied via "--chat-template" is supported or not. Returns true if it's valid
|
||||
|
|
|
@ -991,7 +991,14 @@ public:
|
|||
}
|
||||
};
|
||||
|
||||
std::string json_schema_to_grammar(const json & schema) {
|
||||
std::string json_schema_to_grammar(const json & schema, bool force_gbnf) {
|
||||
#ifdef LLAMA_USE_LLGUIDANCE
|
||||
if (!force_gbnf) {
|
||||
return "%llguidance {}\nstart: %json " + schema.dump();
|
||||
}
|
||||
#else
|
||||
(void)force_gbnf;
|
||||
#endif // LLAMA_USE_LLGUIDANCE
|
||||
return build_grammar([&](const common_grammar_builder & callbacks) {
|
||||
auto copy = schema;
|
||||
callbacks.resolve_refs(copy);
|
||||
|
|
|
@ -5,7 +5,8 @@
|
|||
#define JSON_ASSERT GGML_ASSERT
|
||||
#include "json.hpp"
|
||||
|
||||
std::string json_schema_to_grammar(const nlohmann::ordered_json & schema);
|
||||
std::string json_schema_to_grammar(const nlohmann::ordered_json & schema,
|
||||
bool force_gbnf = false);
|
||||
|
||||
struct common_grammar_builder {
|
||||
std::function<std::string(const std::string &, const std::string &)> add_rule;
|
||||
|
|
270
common/llguidance.cpp
Normal file
270
common/llguidance.cpp
Normal file
|
@ -0,0 +1,270 @@
|
|||
#include "sampling.h"
|
||||
#include "log.h"
|
||||
|
||||
#ifdef LLAMA_USE_LLGUIDANCE
|
||||
|
||||
# include "llguidance.h"
|
||||
# include <cmath>
|
||||
|
||||
struct llama_sampler_llg {
|
||||
const llama_vocab * vocab;
|
||||
std::string grammar_kind;
|
||||
std::string grammar_data;
|
||||
LlgTokenizer * tokenizer;
|
||||
LlgConstraint * grammar;
|
||||
LlgMaskResult llg_res;
|
||||
bool has_llg_res;
|
||||
};
|
||||
|
||||
static LlgConstraint * llama_sampler_llg_new(LlgTokenizer * tokenizer, const char * grammar_kind,
|
||||
const char * grammar_data) {
|
||||
LlgConstraintInit cinit;
|
||||
llg_constraint_init_set_defaults(&cinit, tokenizer);
|
||||
const char * log_level = getenv("LLGUIDANCE_LOG_LEVEL");
|
||||
if (log_level && *log_level) {
|
||||
cinit.log_stderr_level = atoi(log_level);
|
||||
}
|
||||
auto c = llg_new_constraint_any(&cinit, grammar_kind, grammar_data);
|
||||
if (llg_get_error(c)) {
|
||||
LOG_ERR("llg error: %s\n", llg_get_error(c));
|
||||
llg_free_constraint(c);
|
||||
return nullptr;
|
||||
}
|
||||
return c;
|
||||
}
|
||||
|
||||
static const char * llama_sampler_llg_name(const llama_sampler * /*smpl*/) {
|
||||
return "llguidance";
|
||||
}
|
||||
|
||||
static void llama_sampler_llg_accept_impl(llama_sampler * smpl, llama_token token) {
|
||||
auto * ctx = (llama_sampler_llg *) smpl->ctx;
|
||||
if (ctx->grammar) {
|
||||
LlgCommitResult res;
|
||||
llg_commit_token(ctx->grammar, token, &res);
|
||||
ctx->has_llg_res = false;
|
||||
}
|
||||
}
|
||||
|
||||
static void llama_sampler_llg_apply(llama_sampler * smpl, llama_token_data_array * cur_p) {
|
||||
auto * ctx = (llama_sampler_llg *) smpl->ctx;
|
||||
if (ctx->grammar) {
|
||||
if (!ctx->has_llg_res) {
|
||||
if (llg_compute_mask(ctx->grammar, &ctx->llg_res) == 0) {
|
||||
ctx->has_llg_res = true;
|
||||
} else {
|
||||
LOG_ERR("llg error: %s\n", llg_get_error(ctx->grammar));
|
||||
llg_free_constraint(ctx->grammar);
|
||||
ctx->grammar = nullptr;
|
||||
}
|
||||
}
|
||||
if (ctx->has_llg_res) {
|
||||
if (ctx->llg_res.is_stop) {
|
||||
for (size_t i = 0; i < cur_p->size; ++i) {
|
||||
if (!llama_vocab_is_eog(ctx->vocab, cur_p->data[i].id)) {
|
||||
cur_p->data[i].logit = -INFINITY;
|
||||
}
|
||||
}
|
||||
} else {
|
||||
const uint32_t * mask = ctx->llg_res.sample_mask;
|
||||
for (size_t i = 0; i < cur_p->size; ++i) {
|
||||
auto token = cur_p->data[i].id;
|
||||
if ((mask[token / 32] & (1 << (token % 32))) == 0) {
|
||||
cur_p->data[i].logit = -INFINITY;
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
static void llama_sampler_llg_reset(llama_sampler * smpl) {
|
||||
auto * ctx = (llama_sampler_llg *) smpl->ctx;
|
||||
if (!ctx->grammar) {
|
||||
return;
|
||||
}
|
||||
|
||||
auto * grammar_new = llama_sampler_llg_new(ctx->tokenizer, ctx->grammar_kind.c_str(), ctx->grammar_data.c_str());
|
||||
llg_free_constraint(ctx->grammar);
|
||||
ctx->grammar = grammar_new;
|
||||
ctx->has_llg_res = false;
|
||||
}
|
||||
|
||||
static llama_sampler * llama_sampler_llg_clone(const llama_sampler * smpl) {
|
||||
const auto * ctx = (const llama_sampler_llg *) smpl->ctx;
|
||||
|
||||
auto * result = llama_sampler_init_llg(ctx->vocab, nullptr, nullptr);
|
||||
|
||||
// copy the state
|
||||
{
|
||||
auto * result_ctx = (llama_sampler_llg *) result->ctx;
|
||||
|
||||
if (ctx->grammar) {
|
||||
result_ctx->grammar_kind = ctx->grammar_kind;
|
||||
result_ctx->grammar_data = ctx->grammar_data;
|
||||
result_ctx->grammar = llg_clone_constraint(ctx->grammar);
|
||||
result_ctx->tokenizer = llg_clone_tokenizer(ctx->tokenizer);
|
||||
}
|
||||
}
|
||||
|
||||
return result;
|
||||
}
|
||||
|
||||
static void llama_sampler_llg_free(llama_sampler * smpl) {
|
||||
const auto * ctx = (llama_sampler_llg *) smpl->ctx;
|
||||
|
||||
if (ctx->grammar) {
|
||||
llg_free_constraint(ctx->grammar);
|
||||
llg_free_tokenizer(ctx->tokenizer);
|
||||
}
|
||||
|
||||
delete ctx;
|
||||
}
|
||||
|
||||
static llama_sampler_i llama_sampler_llg_i = {
|
||||
/* .name = */ llama_sampler_llg_name,
|
||||
/* .accept = */ llama_sampler_llg_accept_impl,
|
||||
/* .apply = */ llama_sampler_llg_apply,
|
||||
/* .reset = */ llama_sampler_llg_reset,
|
||||
/* .clone = */ llama_sampler_llg_clone,
|
||||
/* .free = */ llama_sampler_llg_free,
|
||||
};
|
||||
|
||||
static size_t llama_sampler_llg_tokenize_fn(const void * user_data, const uint8_t * bytes, size_t bytes_len,
|
||||
uint32_t * output_tokens, size_t output_tokens_len) {
|
||||
const llama_vocab * vocab = (const llama_vocab *) user_data;
|
||||
int r = 0;
|
||||
try {
|
||||
r = llama_tokenize(vocab, (const char *) bytes, bytes_len, (int32_t *) output_tokens, output_tokens_len, false,
|
||||
true);
|
||||
} catch (const std::exception & e) {
|
||||
GGML_ABORT("llama_tokenize failed: %s\n", e.what());
|
||||
}
|
||||
if (r < 0) {
|
||||
return -r;
|
||||
}
|
||||
return r;
|
||||
}
|
||||
|
||||
static LlgTokenizer * llama_sampler_llg_new_tokenizer(const llama_vocab * vocab) {
|
||||
// TODO store the tokenizer in the vocab somehow
|
||||
static const llama_vocab * vocab_cache;
|
||||
static LlgTokenizer * tokenizer_cache;
|
||||
|
||||
if (vocab_cache == vocab) {
|
||||
return llg_clone_tokenizer(tokenizer_cache);
|
||||
}
|
||||
|
||||
auto tok_eos = llama_vocab_eot(vocab);
|
||||
if (tok_eos == LLAMA_TOKEN_NULL) {
|
||||
tok_eos = llama_vocab_eos(vocab);
|
||||
}
|
||||
|
||||
size_t vocab_size = llama_vocab_n_tokens(vocab);
|
||||
|
||||
auto token_lens = new uint32_t[vocab_size];
|
||||
// we typically have ~7 bytes per token; let's go on the safe side here
|
||||
auto token_bytes_size = vocab_size * 16 + 1024 * 1024;
|
||||
auto token_bytes = new uint8_t[token_bytes_size];
|
||||
|
||||
size_t offset = 0;
|
||||
for (size_t i = 0; i < vocab_size; i++) {
|
||||
size_t max_token = 1024;
|
||||
if (token_bytes_size - offset < max_token) {
|
||||
GGML_ABORT("token_bytes buffer too small\n");
|
||||
}
|
||||
|
||||
llama_token token = i;
|
||||
auto dp = (char *) token_bytes + offset;
|
||||
auto size = llama_detokenize(vocab, &token, 1, dp, max_token, false, false);
|
||||
if (size < 0) {
|
||||
GGML_ABORT("llama_detokenize failed\n");
|
||||
}
|
||||
if (size == 0) {
|
||||
size = llama_detokenize(vocab, &token, 1, dp + 1, max_token - 1, false, true);
|
||||
if (size < 0) {
|
||||
GGML_ABORT("llama_detokenize failed\n");
|
||||
}
|
||||
if (size != 0) {
|
||||
*dp = '\xff'; // special token prefix marker
|
||||
size += 1;
|
||||
}
|
||||
}
|
||||
|
||||
token_lens[i] = size;
|
||||
offset += size;
|
||||
}
|
||||
|
||||
LlgTokenizerInit tinit = {
|
||||
/* .vocab_size = */ (uint32_t) vocab_size,
|
||||
/* .tok_eos = */ (uint32_t) tok_eos,
|
||||
/* .token_lens = */ token_lens,
|
||||
/* .token_bytes = */ token_bytes,
|
||||
/* .tokenizer_json = */ nullptr,
|
||||
/* .tokenize_assumes_string = */ true,
|
||||
/* .tokenize_fn = */ llama_sampler_llg_tokenize_fn,
|
||||
/* .use_approximate_greedy_tokenize_fn = */ false,
|
||||
/* .tokenize_user_data = */ vocab,
|
||||
};
|
||||
|
||||
char error_buffer[1024];
|
||||
LlgTokenizer * tokenizer = llg_new_tokenizer(&tinit, error_buffer, sizeof(error_buffer));
|
||||
|
||||
delete[] token_bytes;
|
||||
delete[] token_lens;
|
||||
|
||||
if (tokenizer == nullptr) {
|
||||
LOG_ERR("llg tokenizer error: %s\n", error_buffer);
|
||||
return tokenizer;
|
||||
}
|
||||
|
||||
if (tokenizer_cache) {
|
||||
llg_free_tokenizer(tokenizer_cache);
|
||||
}
|
||||
vocab_cache = vocab;
|
||||
tokenizer_cache = tokenizer;
|
||||
|
||||
return llg_clone_tokenizer(tokenizer_cache);
|
||||
}
|
||||
|
||||
llama_sampler * llama_sampler_init_llg(const llama_vocab * vocab, const char * grammar_kind,
|
||||
const char * grammar_data) {
|
||||
auto * ctx = new llama_sampler_llg;
|
||||
|
||||
if (grammar_kind != nullptr && grammar_kind[0] != '\0') {
|
||||
auto tokenizer = llama_sampler_llg_new_tokenizer(vocab);
|
||||
*ctx = {
|
||||
/* .vocab = */ vocab,
|
||||
/* .grammar_kind = */ grammar_kind,
|
||||
/* .grammar_data = */ grammar_data,
|
||||
/* .tokenizer = */ tokenizer,
|
||||
/* .grammar = */ llama_sampler_llg_new(tokenizer, grammar_kind, grammar_data),
|
||||
/* .llg_res = */ {},
|
||||
/* .has_llg_res = */ false,
|
||||
};
|
||||
} else {
|
||||
*ctx = {
|
||||
/* .vocab = */ vocab,
|
||||
/* .grammar_kind = */ {},
|
||||
/* .grammar_data = */ {},
|
||||
/* .tokenizer = */ nullptr,
|
||||
/* .grammar = */ nullptr,
|
||||
/* .llg_res = */ {},
|
||||
/* .has_llg_res = */ false,
|
||||
};
|
||||
}
|
||||
|
||||
return llama_sampler_init(
|
||||
/* .iface = */ &llama_sampler_llg_i,
|
||||
/* .ctx = */ ctx
|
||||
);
|
||||
}
|
||||
|
||||
#else
|
||||
|
||||
llama_sampler * llama_sampler_init_llg(const llama_vocab *, const char *, const char *) {
|
||||
LOG_WRN("llguidance (cmake -DLLAMA_LLGUIDANCE=ON) is not enabled");
|
||||
return nullptr;
|
||||
}
|
||||
|
||||
#endif // LLAMA_USE_LLGUIDANCE
|
|
@ -14,16 +14,6 @@ void common_log_set_verbosity_thold(int verbosity) {
|
|||
common_log_verbosity_thold = verbosity;
|
||||
}
|
||||
|
||||
#define LOG_COL_DEFAULT "\033[0m"
|
||||
#define LOG_COL_BOLD "\033[1m"
|
||||
#define LOG_COL_RED "\033[31m"
|
||||
#define LOG_COL_GREEN "\033[32m"
|
||||
#define LOG_COL_YELLOW "\033[33m"
|
||||
#define LOG_COL_BLUE "\033[34m"
|
||||
#define LOG_COL_MAGENTA "\033[35m"
|
||||
#define LOG_COL_CYAN "\033[36m"
|
||||
#define LOG_COL_WHITE "\033[37m"
|
||||
|
||||
static int64_t t_us() {
|
||||
return std::chrono::duration_cast<std::chrono::microseconds>(std::chrono::system_clock::now().time_since_epoch()).count();
|
||||
}
|
||||
|
@ -206,6 +196,7 @@ public:
|
|||
vsnprintf(entry.msg.data(), entry.msg.size(), ss.str().c_str(), args_copy);
|
||||
}
|
||||
#endif
|
||||
va_end(args_copy);
|
||||
}
|
||||
|
||||
entry.level = level;
|
||||
|
|
11
common/log.h
11
common/log.h
|
@ -2,6 +2,17 @@
|
|||
|
||||
#include "ggml.h" // for ggml_log_level
|
||||
|
||||
#define LOG_CLR_TO_EOL "\033[K\r"
|
||||
#define LOG_COL_DEFAULT "\033[0m"
|
||||
#define LOG_COL_BOLD "\033[1m"
|
||||
#define LOG_COL_RED "\033[31m"
|
||||
#define LOG_COL_GREEN "\033[32m"
|
||||
#define LOG_COL_YELLOW "\033[33m"
|
||||
#define LOG_COL_BLUE "\033[34m"
|
||||
#define LOG_COL_MAGENTA "\033[35m"
|
||||
#define LOG_COL_CYAN "\033[36m"
|
||||
#define LOG_COL_WHITE "\033[37m"
|
||||
|
||||
#ifndef __GNUC__
|
||||
# define LOG_ATTRIBUTE_FORMAT(...)
|
||||
#elif defined(__MINGW32__)
|
||||
|
|
|
@ -693,7 +693,7 @@ enum SpaceHandling { Keep, Strip, StripSpaces, StripNewline };
|
|||
|
||||
class TemplateToken {
|
||||
public:
|
||||
enum class Type { Text, Expression, If, Else, Elif, EndIf, For, EndFor, Generation, EndGeneration, Set, EndSet, Comment, Macro, EndMacro, Filter, EndFilter };
|
||||
enum class Type { Text, Expression, If, Else, Elif, EndIf, For, EndFor, Generation, EndGeneration, Set, EndSet, Comment, Macro, EndMacro, Filter, EndFilter, Break, Continue };
|
||||
|
||||
static std::string typeToString(Type t) {
|
||||
switch (t) {
|
||||
|
@ -714,6 +714,8 @@ public:
|
|||
case Type::EndFilter: return "endfilter";
|
||||
case Type::Generation: return "generation";
|
||||
case Type::EndGeneration: return "endgeneration";
|
||||
case Type::Break: return "break";
|
||||
case Type::Continue: return "continue";
|
||||
}
|
||||
return "Unknown";
|
||||
}
|
||||
|
@ -815,6 +817,22 @@ struct CommentTemplateToken : public TemplateToken {
|
|||
CommentTemplateToken(const Location & location, SpaceHandling pre, SpaceHandling post, const std::string& t) : TemplateToken(Type::Comment, location, pre, post), text(t) {}
|
||||
};
|
||||
|
||||
enum class LoopControlType { Break, Continue };
|
||||
|
||||
class LoopControlException : public std::runtime_error {
|
||||
public:
|
||||
LoopControlType control_type;
|
||||
LoopControlException(const std::string & message, LoopControlType control_type) : std::runtime_error(message), control_type(control_type) {}
|
||||
LoopControlException(LoopControlType control_type)
|
||||
: std::runtime_error((control_type == LoopControlType::Continue ? "continue" : "break") + std::string(" outside of a loop")),
|
||||
control_type(control_type) {}
|
||||
};
|
||||
|
||||
struct LoopControlTemplateToken : public TemplateToken {
|
||||
LoopControlType control_type;
|
||||
LoopControlTemplateToken(const Location & location, SpaceHandling pre, SpaceHandling post, LoopControlType control_type) : TemplateToken(Type::Break, location, pre, post), control_type(control_type) {}
|
||||
};
|
||||
|
||||
class TemplateNode {
|
||||
Location location_;
|
||||
protected:
|
||||
|
@ -825,6 +843,12 @@ public:
|
|||
void render(std::ostringstream & out, const std::shared_ptr<Context> & context) const {
|
||||
try {
|
||||
do_render(out, context);
|
||||
} catch (const LoopControlException & e) {
|
||||
// TODO: make stack creation lazy. Only needed if it was thrown outside of a loop.
|
||||
std::ostringstream err;
|
||||
err << e.what();
|
||||
if (location_.source) err << error_location_suffix(*location_.source, location_.pos);
|
||||
throw LoopControlException(err.str(), e.control_type);
|
||||
} catch (const std::exception & e) {
|
||||
std::ostringstream err;
|
||||
err << e.what();
|
||||
|
@ -897,6 +921,15 @@ public:
|
|||
}
|
||||
};
|
||||
|
||||
class LoopControlNode : public TemplateNode {
|
||||
LoopControlType control_type_;
|
||||
public:
|
||||
LoopControlNode(const Location & location, LoopControlType control_type) : TemplateNode(location), control_type_(control_type) {}
|
||||
void do_render(std::ostringstream &, const std::shared_ptr<Context> &) const override {
|
||||
throw LoopControlException(control_type_);
|
||||
}
|
||||
};
|
||||
|
||||
class ForNode : public TemplateNode {
|
||||
std::vector<std::string> var_names;
|
||||
std::shared_ptr<Expression> iterable;
|
||||
|
@ -961,7 +994,12 @@ public:
|
|||
loop.set("last", i == (n - 1));
|
||||
loop.set("previtem", i > 0 ? filtered_items.at(i - 1) : Value());
|
||||
loop.set("nextitem", i < n - 1 ? filtered_items.at(i + 1) : Value());
|
||||
body->render(out, loop_context);
|
||||
try {
|
||||
body->render(out, loop_context);
|
||||
} catch (const LoopControlException & e) {
|
||||
if (e.control_type == LoopControlType::Break) break;
|
||||
if (e.control_type == LoopControlType::Continue) continue;
|
||||
}
|
||||
}
|
||||
}
|
||||
};
|
||||
|
@ -2156,10 +2194,10 @@ private:
|
|||
}
|
||||
|
||||
TemplateTokenVector tokenize() {
|
||||
static std::regex comment_tok(R"(\{#([-~]?)(.*?)([-~]?)#\})");
|
||||
static std::regex comment_tok(R"(\{#([-~]?)([\s\S\r\n]*?)([-~]?)#\})");
|
||||
static std::regex expr_open_regex(R"(\{\{([-~])?)");
|
||||
static std::regex block_open_regex(R"(^\{%([-~])?[\s\n\r]*)");
|
||||
static std::regex block_keyword_tok(R"((if|else|elif|endif|for|endfor|generation|endgeneration|set|endset|block|endblock|macro|endmacro|filter|endfilter)\b)");
|
||||
static std::regex block_keyword_tok(R"((if|else|elif|endif|for|endfor|generation|endgeneration|set|endset|block|endblock|macro|endmacro|filter|endfilter|break|continue)\b)");
|
||||
static std::regex non_text_open_regex(R"(\{\{|\{%|\{#)");
|
||||
static std::regex expr_close_regex(R"([\s\n\r]*([-~])?\}\})");
|
||||
static std::regex block_close_regex(R"([\s\n\r]*([-~])?%\})");
|
||||
|
@ -2291,6 +2329,9 @@ private:
|
|||
} else if (keyword == "endfilter") {
|
||||
auto post_space = parseBlockClose();
|
||||
tokens.push_back(std::make_unique<EndFilterTemplateToken>(location, pre_space, post_space));
|
||||
} else if (keyword == "break" || keyword == "continue") {
|
||||
auto post_space = parseBlockClose();
|
||||
tokens.push_back(std::make_unique<LoopControlTemplateToken>(location, pre_space, post_space, keyword == "break" ? LoopControlType::Break : LoopControlType::Continue));
|
||||
} else {
|
||||
throw std::runtime_error("Unexpected block: " + keyword);
|
||||
}
|
||||
|
@ -2414,6 +2455,8 @@ private:
|
|||
children.emplace_back(std::make_shared<FilterNode>(token->location, std::move(filter_token->filter), std::move(body)));
|
||||
} else if (dynamic_cast<CommentTemplateToken*>(token.get())) {
|
||||
// Ignore comments
|
||||
} else if (auto ctrl_token = dynamic_cast<LoopControlTemplateToken*>(token.get())) {
|
||||
children.emplace_back(std::make_shared<LoopControlNode>(token->location, ctrl_token->control_type));
|
||||
} else if (dynamic_cast<EndForTemplateToken*>(token.get())
|
||||
|| dynamic_cast<EndSetTemplateToken*>(token.get())
|
||||
|| dynamic_cast<EndMacroTemplateToken*>(token.get())
|
||||
|
@ -2572,6 +2615,7 @@ inline std::shared_ptr<Context> Context::builtins() {
|
|||
}));
|
||||
globals.set("join", simple_function("join", { "items", "d" }, [](const std::shared_ptr<Context> &, Value & args) {
|
||||
auto do_join = [](Value & items, const std::string & sep) {
|
||||
if (!items.is_array()) throw std::runtime_error("object is not iterable: " + items.dump());
|
||||
std::ostringstream oss;
|
||||
auto first = true;
|
||||
for (size_t i = 0, n = items.size(); i < n; ++i) {
|
||||
|
@ -2652,6 +2696,10 @@ inline std::shared_ptr<Context> Context::builtins() {
|
|||
return Value::callable([=](const std::shared_ptr<Context> & context, ArgumentsValue & args) {
|
||||
args.expectArgs(is_select ? "select" : "reject", {2, (std::numeric_limits<size_t>::max)()}, {0, 0});
|
||||
auto & items = args.args[0];
|
||||
if (items.is_null())
|
||||
return Value::array();
|
||||
if (!items.is_array()) throw std::runtime_error("object is not iterable: " + items.dump());
|
||||
|
||||
auto filter_fn = context->get(args.args[1]);
|
||||
if (filter_fn.is_null()) throw std::runtime_error("Undefined filter: " + args.args[1].dump());
|
||||
|
||||
|
@ -2729,6 +2777,7 @@ inline std::shared_ptr<Context> Context::builtins() {
|
|||
auto & items = args.args[0];
|
||||
if (items.is_null())
|
||||
return Value::array();
|
||||
if (!items.is_array()) throw std::runtime_error("object is not iterable: " + items.dump());
|
||||
auto attr_name = args.args[1].get<std::string>();
|
||||
|
||||
bool has_test = false;
|
||||
|
|
|
@ -156,13 +156,25 @@ struct common_sampler * common_sampler_init(const struct llama_model * model, co
|
|||
for (const auto & str : params.grammar_trigger_words) {
|
||||
trigger_words.push_back(str.word.c_str());
|
||||
}
|
||||
|
||||
struct llama_sampler * grmr;
|
||||
if (params.grammar.compare(0, 11, "%llguidance") == 0) {
|
||||
#ifdef LLAMA_USE_LLGUIDANCE
|
||||
grmr = llama_sampler_init_llg(vocab, "lark", params.grammar.c_str());
|
||||
#else
|
||||
GGML_ABORT("llguidance (cmake -DLLAMA_LLGUIDANCE=ON) is not enabled");
|
||||
#endif // LLAMA_USE_LLGUIDANCE
|
||||
} else {
|
||||
grmr = params.grammar_lazy
|
||||
? llama_sampler_init_grammar_lazy(vocab, params.grammar.c_str(), "root",
|
||||
trigger_words.data(), trigger_words.size(),
|
||||
params.grammar_trigger_tokens.data(), params.grammar_trigger_tokens.size())
|
||||
: llama_sampler_init_grammar(vocab, params.grammar.c_str(), "root");
|
||||
}
|
||||
|
||||
auto * result = new common_sampler {
|
||||
/* .params = */ params,
|
||||
/* .grmr = */ params.grammar_lazy
|
||||
? llama_sampler_init_grammar_lazy(vocab, params.grammar.c_str(), "root",
|
||||
trigger_words.data(), trigger_words.size(),
|
||||
params.grammar_trigger_tokens.data(), params.grammar_trigger_tokens.size())
|
||||
: llama_sampler_init_grammar(vocab, params.grammar.c_str(), "root"),
|
||||
/* .grmr = */ grmr,
|
||||
/* .chain = */ llama_sampler_chain_init(lparams),
|
||||
/* .prev = */ ring_buffer<llama_token>(std::max(32, params.n_prev)),
|
||||
/* .cur = */ {},
|
||||
|
|
|
@ -102,3 +102,6 @@ std::string common_sampler_type_to_str(enum common_sampler_type cnstr);
|
|||
|
||||
std::vector<enum common_sampler_type> common_sampler_types_from_names(const std::vector<std::string> & names, bool allow_alt_names);
|
||||
std::vector<enum common_sampler_type> common_sampler_types_from_chars(const std::string & chars);
|
||||
|
||||
llama_sampler * llama_sampler_init_llg(const llama_vocab * vocab,
|
||||
const char * grammar_kind, const char * grammar_data);
|
||||
|
|
Loading…
Add table
Add a link
Reference in a new issue