tests/test-autorelease: tests/test-autorelease.cpp ggml.o llama.o tests/get-model.cpp $(COMMON_DEPS) $(OBJS)
$(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<)
$(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS)
+
+tests/test-chat-template: tests/test-chat-template.cpp ggml.o llama.o $(COMMON_DEPS) $(OBJS)
+ $(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<)
+ $(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS)
return 0;
}
+// trim whitespace from the beginning and end of a string
+static std::string trim(const std::string & str) {
+ size_t start = 0;
+ size_t end = str.size();
+ while (start < end && isspace(str[start])) {
+ start += 1;
+ }
+ while (end > start && isspace(str[end - 1])) {
+ end -= 1;
+ }
+ return str.substr(start, end - start);
+}
+
+// Simple version of "llama_apply_chat_template" that only works with strings
+// This function uses heuristic checks to determine commonly used template. It is not a jinja parser.
+static int32_t llama_chat_apply_template_internal(
+ const std::string & tmpl,
+ const std::vector<const llama_chat_message *> & chat,
+ std::string & dest, bool add_ass) {
+ // Taken from the research: https://github.com/ggerganov/llama.cpp/issues/5527
+ std::stringstream ss;
+ if (tmpl.find("<|im_start|>") != std::string::npos) {
+ // chatml template
+ for (auto message : chat) {
+ ss << "<|im_start|>" << message->role << "\n" << message->content << "<|im_end|>\n";
+ }
+ if (add_ass) {
+ ss << "<|im_start|>assistant\n";
+ }
+ } else if (tmpl.find("[INST]") != std::string::npos) {
+ // llama2 template and its variants
+ // [variant] support system message
+ bool support_system_message = tmpl.find("<<SYS>>") != std::string::npos;
+ // [variant] space before + after response
+ bool space_around_response = tmpl.find("' ' + eos_token") != std::string::npos;
+ // [variant] add BOS inside history
+ bool add_bos_inside_history = tmpl.find("bos_token + '[INST]") != std::string::npos;
+ // [variant] trim spaces from the input message
+ bool strip_message = tmpl.find("content.strip()") != std::string::npos;
+ // construct the prompt
+ bool is_inside_turn = true; // skip BOS at the beginning
+ ss << "[INST] ";
+ for (auto message : chat) {
+ std::string content = strip_message ? trim(message->content) : message->content;
+ std::string role(message->role);
+ if (!is_inside_turn) {
+ is_inside_turn = true;
+ ss << (add_bos_inside_history ? "<s>[INST] " : "[INST] ");
+ }
+ if (role == "system") {
+ if (support_system_message) {
+ ss << "<<SYS>>\n" << content << "\n<</SYS>>\n\n";
+ } else {
+ // if the model does not support system message, we still include it in the first message, but without <<SYS>>
+ ss << content << "\n";
+ }
+ } else if (role == "user") {
+ ss << content << " [/INST]";
+ } else {
+ ss << (space_around_response ? " " : "") << content << (space_around_response ? " " : "") << "</s>";
+ is_inside_turn = false;
+ }
+ }
+ // llama2 templates seem to not care about "add_generation_prompt"
+ } else if (tmpl.find("<|user|>") != std::string::npos) {
+ // zephyr template
+ for (auto message : chat) {
+ ss << "<|" << message->role << "|>" << "\n" << message->content << "<|endoftext|>\n";
+ }
+ if (add_ass) {
+ ss << "<|assistant|>\n";
+ }
+ } else {
+ // template not supported
+ return -1;
+ }
+ dest = ss.str();
+ return dest.size();
+}
+
+LLAMA_API int32_t llama_chat_apply_template(
+ const struct llama_model * model,
+ const char * tmpl,
+ const struct llama_chat_message * chat,
+ size_t n_msg,
+ bool add_ass,
+ char * buf,
+ int32_t length) {
+ std::string curr_tmpl(tmpl == nullptr ? "" : tmpl);
+ if (tmpl == nullptr) {
+ GGML_ASSERT(model != nullptr);
+ // load template from model
+ std::vector<char> model_template(2048, 0); // longest known template is about 1200 bytes
+ std::string template_key = "tokenizer.chat_template";
+ int32_t res = llama_model_meta_val_str(model, template_key.c_str(), model_template.data(), curr_tmpl.size());
+ if (res < 0) {
+ // worst case: there is no information about template, we will use chatml by default
+ curr_tmpl = "<|im_start|>"; // see llama_chat_apply_template_internal
+ } else {
+ curr_tmpl = std::string(model_template.data(), model_template.size());
+ }
+ }
+ // format the chat to string
+ std::vector<const llama_chat_message *> chat_vec;
+ chat_vec.resize(n_msg);
+ for (size_t i = 0; i < n_msg; i++) {
+ chat_vec[i] = &chat[i];
+ }
+ std::string formatted_chat;
+ int32_t res = llama_chat_apply_template_internal(curr_tmpl, chat_vec, formatted_chat, add_ass);
+ if (res < 0) {
+ return res;
+ }
+ strncpy(buf, formatted_chat.c_str(), length);
+ return res;
+}
+
struct llama_timings llama_get_timings(struct llama_context * ctx) {
struct llama_timings result = {
/*.t_start_ms =*/ 1e-3 * ctx->t_start_us,
int32_t n_eval;
};
+ // used in chat template
+ typedef struct llama_chat_message {
+ const char * role;
+ const char * content;
+ } llama_chat_message;
+
// Helpers for getting default parameters
LLAMA_API struct llama_model_params llama_model_default_params(void);
LLAMA_API struct llama_context_params llama_context_default_params(void);
char * buf,
int32_t length);
+ /// Apply chat template. Inspired by hf apply_chat_template() on python.
+ /// Both "model" and "custom_template" are optional, but at least one is required. "custom_template" has higher precedence than "model"
+ /// NOTE: This function only support some known jinja templates. It is not a jinja parser.
+ /// @param tmpl A Jinja template to use for this chat. If this is nullptr, the model’s default chat template will be used instead.
+ /// @param chat Pointer to a list of multiple llama_chat_message
+ /// @param n_msg Number of llama_chat_message in this chat
+ /// @param add_ass Whether to end the prompt with the token(s) that indicate the start of an assistant message.
+ /// @param buf A buffer to hold the output formatted prompt. The recommended alloc size is 2 * (total number of characters of all messages)
+ /// @param length The size of the allocated buffer
+ /// @return The total number of bytes of the formatted prompt. If is it larger than the size of buffer, you may need to re-alloc it and then re-apply the template.
+ LLAMA_API int32_t llama_chat_apply_template(
+ const struct llama_model * model,
+ const char * tmpl,
+ const struct llama_chat_message * chat,
+ size_t n_msg,
+ bool add_ass,
+ char * buf,
+ int32_t length);
+
//
// Grammar
//
llama_build_and_test_executable(test-quantize-fns.cpp)
llama_build_and_test_executable(test-quantize-perf.cpp)
llama_build_and_test_executable(test-sampling.cpp)
+llama_build_and_test_executable(test-chat-template.cpp)
llama_build_executable(test-tokenizer-0-llama.cpp)
llama_test_executable (test-tokenizer-0-llama test-tokenizer-0-llama.cpp ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-llama.gguf)
--- /dev/null
+#include <iostream>
+#include <string>
+#include <vector>
+#include <sstream>
+
+#undef NDEBUG
+#include <cassert>
+
+#include "llama.h"
+
+int main(void) {
+ llama_chat_message conversation[] = {
+ {"system", "You are a helpful assistant"},
+ {"user", "Hello"},
+ {"assistant", "Hi there"},
+ {"user", "Who are you"},
+ {"assistant", " I am an assistant "},
+ {"user", "Another question"},
+ };
+ size_t message_count = 6;
+ std::vector<std::string> templates = {
+ // teknium/OpenHermes-2.5-Mistral-7B
+ "{% for message in messages %}{{'<|im_start|>' + message['role'] + '\\n' + message['content'] + '<|im_end|>' + '\\n'}}{% endfor %}{% if add_generation_prompt %}{{ '<|im_start|>assistant\\n' }}{% endif %}",
+ // mistralai/Mistral-7B-Instruct-v0.2
+ "{{ bos_token }}{% for message in messages %}{% if (message['role'] == 'user') != (loop.index0 % 2 == 0) %}{{ raise_exception('Conversation roles must alternate user/assistant/user/assistant/...') }}{% endif %}{% if message['role'] == 'user' %}{{ '[INST] ' + message['content'] + ' [/INST]' }}{% elif message['role'] == 'assistant' %}{{ message['content'] + eos_token}}{% else %}{{ raise_exception('Only user and assistant roles are supported!') }}{% endif %}{% endfor %}",
+ // TheBloke/FusionNet_34Bx2_MoE-AWQ
+ "{%- for idx in range(0, messages|length) -%}\\n{%- if messages[idx]['role'] == 'user' -%}\\n{%- if idx > 1 -%}\\n{{- bos_token + '[INST] ' + messages[idx]['content'] + ' [/INST]' -}}\\n{%- else -%}\\n{{- messages[idx]['content'] + ' [/INST]' -}}\\n{%- endif -%}\\n{% elif messages[idx]['role'] == 'system' %}\\n{{- '[INST] <<SYS>>\\\\n' + messages[idx]['content'] + '\\\\n<</SYS>>\\\\n\\\\n' -}}\\n{%- elif messages[idx]['role'] == 'assistant' -%}\\n{{- ' ' + messages[idx]['content'] + ' ' + eos_token -}}\\n{% endif %}\\n{% endfor %}",
+ // bofenghuang/vigogne-2-70b-chat
+ "{{ bos_token }}{% if messages[0]['role'] == 'system' %}{% set loop_messages = messages[1:] %}{% set system_message = messages[0]['content'] %}{% elif true == true and not '<<SYS>>' in messages[0]['content'] %}{% set loop_messages = messages %}{% set system_message = 'Vous êtes Vigogne, un assistant IA créé par Zaion Lab. Vous suivez extrêmement bien les instructions. Aidez autant que vous le pouvez.' %}{% else %}{% set loop_messages = messages %}{% set system_message = false %}{% endif %}{% for message in loop_messages %}{% if (message['role'] == 'user') != (loop.index0 % 2 == 0) %}{{ raise_exception('Conversation roles must alternate user/assistant/user/assistant/...') }}{% endif %}{% if loop.index0 == 0 and system_message != false %}{% set content = '<<SYS>>\\\\n' + system_message + '\\\\n<</SYS>>\\\\n\\\\n' + message['content'] %}{% else %}{% set content = message['content'] %}{% endif %}{% if message['role'] == 'user' %}{{ '[INST] ' + content.strip() + ' [/INST]' }}{% elif message['role'] == 'system' %}{{ '<<SYS>>\\\\n' + content.strip() + '\\\\n<</SYS>>\\\\n\\\\n' }}{% elif message['role'] == 'assistant' %}{{ ' ' + content.strip() + ' ' + eos_token }}{% endif %}{% endfor %}",
+ };
+ std::vector<std::string> expected_substr = {
+ "<|im_start|>assistant\n I am an assistant <|im_end|>\n<|im_start|>user\nAnother question<|im_end|>\n<|im_start|>assistant",
+ "[/INST]Hi there</s>[INST] Who are you [/INST] I am an assistant </s>[INST] Another question [/INST]",
+ "</s><s>[INST] Who are you [/INST] I am an assistant </s><s>[INST] Another question [/INST]",
+ "[/INST] Hi there </s>[INST] Who are you [/INST] I am an assistant </s>[INST] Another question [/INST]",
+ };
+ std::vector<char> formatted_chat(1024);
+ int32_t res;
+
+ // test invalid chat template
+ res = llama_chat_apply_template(nullptr, "INVALID TEMPLATE", conversation, message_count, true, formatted_chat.data(), formatted_chat.size());
+ assert(res < 0);
+
+ for (size_t i = 0; i < templates.size(); i++) {
+ std::string custom_template = templates[i];
+ std::string substr = expected_substr[i];
+ formatted_chat.resize(1024);
+ res = llama_chat_apply_template(
+ nullptr,
+ custom_template.c_str(),
+ conversation,
+ message_count,
+ true,
+ formatted_chat.data(),
+ formatted_chat.size()
+ );
+ formatted_chat.resize(res);
+ std::string output(formatted_chat.data(), formatted_chat.size());
+ std::cout << output << "\n-------------------------\n";
+ // expect the "formatted_chat" to contain pre-defined strings
+ assert(output.find(substr) != std::string::npos);
+ }
+ return 0;
+}
overview / pkg / ggml / sources / llama.cpp / commitdiff