Add Jinja template support (#11016)
* Copy minja from58f0ca6dd7* Add --jinja and --chat-template-file flags * Add missing <optional> include * Avoid print in get_hf_chat_template.py * No designated initializers yet * Try and work around msvc++ non-macro max resolution quirk * Update test_chat_completion.py * Wire LLM_KV_TOKENIZER_CHAT_TEMPLATE_N in llama_model_chat_template * Refactor test-chat-template * Test templates w/ minja * Fix deprecation * Add --jinja to llama-run * Update common_chat_format_example to use minja template wrapper * Test chat_template in e2e test * Update utils.py * Update test_chat_completion.py * Update run.cpp * Update arg.cpp * Refactor common_chat_* functions to accept minja template + use_jinja option * Attempt to fix linkage of LLAMA_CHATML_TEMPLATE * Revert LLAMA_CHATML_TEMPLATE refactor * Normalize newlines in test-chat-templates for windows tests * Forward decl minja::chat_template to avoid eager json dep * Flush stdout in chat template before potential crash * Fix copy elision warning * Rm unused optional include * Add missing optional include to server.cpp * Disable jinja test that has a cryptic windows failure * minja: fix vigogne (https://github.com/google/minja/pull/22) * Apply suggestions from code review Co-authored-by: Xuan Son Nguyen <thichthat@gmail.com> Co-authored-by: Georgi Gerganov <ggerganov@gmail.com> * Finish suggested renamings * Move chat_templates inside server_context + remove mutex * Update --chat-template-file w/ recent change to --chat-template * Refactor chat template validation * Guard against missing eos/bos tokens (null token otherwise throws in llama_vocab::impl::token_get_attr) * Warn against missing eos / bos tokens when jinja template references them * rename: common_chat_template[s] * reinstate assert on chat_templates.template_default * Update minja tob8437df626* Update minja to https://github.com/google/minja/pull/25 * Update minja from https://github.com/google/minja/pull/27 * rm unused optional header --------- Co-authored-by: Xuan Son Nguyen <thichthat@gmail.com> Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
This commit is contained in:
Olivier Chafik
GitHub
parent
e28245f35f
commit
6171c9d258
22 changed files with 3563 additions and 133 deletions
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@ -4,6 +4,7 @@
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#include "log.h"
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#include "sampling.h"
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#include "llama.h"
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#include "chat-template.hpp"
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#include <cstdio>
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#include <cstring>
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@ -84,14 +85,6 @@ static void sigint_handler(int signo) {
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}
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#endif
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static std::string chat_add_and_format(struct llama_model * model, std::vector<common_chat_msg> & chat_msgs, const std::string & role, const std::string & content) {
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common_chat_msg new_msg{role, content};
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auto formatted = common_chat_format_single(model, g_params->chat_template, chat_msgs, new_msg, role == "user");
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chat_msgs.push_back({role, content});
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LOG_DBG("formatted: '%s'\n", formatted.c_str());
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return formatted;
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}
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int main(int argc, char ** argv) {
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common_params params;
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g_params = ¶ms;
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@ -165,6 +158,7 @@ int main(int argc, char ** argv) {
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}
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const llama_vocab * vocab = llama_model_get_vocab(model);
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auto chat_templates = common_chat_templates_from_model(model, params.chat_template);
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LOG_INF("%s: llama threadpool init, n_threads = %d\n", __func__, (int) params.cpuparams.n_threads);
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@ -207,7 +201,7 @@ int main(int argc, char ** argv) {
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}
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// auto enable conversation mode if chat template is available
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const bool has_chat_template = !common_get_builtin_chat_template(model).empty() || !params.chat_template.empty();
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const bool has_chat_template = chat_templates.has_explicit_template && chat_templates.template_default;
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if (params.conversation_mode == COMMON_CONVERSATION_MODE_AUTO) {
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if (has_chat_template) {
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LOG_INF("%s: chat template is available, enabling conversation mode (disable it with -no-cnv)\n", __func__);
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@ -225,7 +219,7 @@ int main(int argc, char ** argv) {
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// print chat template example in conversation mode
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if (params.conversation_mode) {
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if (params.enable_chat_template) {
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LOG_INF("%s: chat template example:\n%s\n", __func__, common_chat_format_example(model, params.chat_template).c_str());
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LOG_INF("%s: chat template example:\n%s\n", __func__, common_chat_format_example(*chat_templates.template_default, params.use_jinja).c_str());
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} else {
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LOG_INF("%s: in-suffix/prefix is specified, chat template will be disabled\n", __func__);
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}
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@ -269,10 +263,18 @@ int main(int argc, char ** argv) {
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std::vector<llama_token> embd_inp;
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auto chat_add_and_format = [&chat_msgs, &chat_templates](const std::string & role, const std::string & content) {
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common_chat_msg new_msg{role, content};
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auto formatted = common_chat_format_single(*chat_templates.template_default, chat_msgs, new_msg, role == "user", g_params->use_jinja);
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chat_msgs.push_back({role, content});
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LOG_DBG("formatted: '%s'\n", formatted.c_str());
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return formatted;
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};
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{
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auto prompt = (params.conversation_mode && params.enable_chat_template)
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// format the system prompt in conversation mode (fallback to default if empty)
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? chat_add_and_format(model, chat_msgs, "system", params.prompt.empty() ? DEFAULT_SYSTEM_MESSAGE : params.prompt)
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? chat_add_and_format("system", params.prompt.empty() ? DEFAULT_SYSTEM_MESSAGE : params.prompt)
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// otherwise use the prompt as is
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: params.prompt;
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if (params.interactive_first || !params.prompt.empty() || session_tokens.empty()) {
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@ -779,7 +781,7 @@ int main(int argc, char ** argv) {
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}
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if (params.enable_chat_template) {
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chat_add_and_format(model, chat_msgs, "assistant", assistant_ss.str());
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chat_add_and_format("assistant", assistant_ss.str());
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}
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is_interacting = true;
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LOG("\n");
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@ -844,7 +846,7 @@ int main(int argc, char ** argv) {
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bool format_chat = params.conversation_mode && params.enable_chat_template;
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std::string user_inp = format_chat
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? chat_add_and_format(model, chat_msgs, "user", std::move(buffer))
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? chat_add_and_format("user", std::move(buffer))
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: std::move(buffer);
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// TODO: one inconvenient of current chat template implementation is that we can't distinguish between user input and special tokens (prefix/postfix)
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const auto line_pfx = common_tokenize(ctx, params.input_prefix, false, true);
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@ -28,6 +28,7 @@
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#include "json.hpp"
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#include "linenoise.cpp/linenoise.h"
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#include "llama-cpp.h"
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#include "chat-template.hpp"
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#if defined(__unix__) || (defined(__APPLE__) && defined(__MACH__)) || defined(_WIN32)
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[[noreturn]] static void sigint_handler(int) {
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@ -105,6 +106,7 @@ class Opt {
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llama_model_params model_params;
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std::string model_;
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std::string user;
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bool use_jinja = false;
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int context_size = -1, ngl = -1;
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float temperature = -1;
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bool verbose = false;
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@ -156,6 +158,8 @@ class Opt {
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} else if (options_parsing &&
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(parse_flag(argv, i, "-v", "--verbose") || parse_flag(argv, i, "-v", "--log-verbose"))) {
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verbose = true;
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} else if (options_parsing && strcmp(argv[i], "--jinja") == 0) {
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use_jinja = true;
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} else if (options_parsing && parse_flag(argv, i, "-h", "--help")) {
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help = true;
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return 0;
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@ -713,13 +717,31 @@ static void add_message(const char * role, const std::string & text, LlamaData &
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}
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// Function to apply the chat template and resize `formatted` if needed
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static int apply_chat_template(LlamaData & llama_data, const bool append) {
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static int apply_chat_template(const common_chat_template & tmpl, LlamaData & llama_data, const bool append, bool use_jinja) {
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if (use_jinja) {
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json messages = json::array();
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for (const auto & msg : llama_data.messages) {
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messages.push_back({
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{"role", msg.role},
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{"content", msg.content},
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});
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}
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try {
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auto result = tmpl.apply(messages, /* tools= */ json(), append);
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llama_data.fmtted.resize(result.size() + 1);
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memcpy(llama_data.fmtted.data(), result.c_str(), result.size() + 1);
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return result.size();
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} catch (const std::exception & e) {
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printe("failed to render the chat template: %s\n", e.what());
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return -1;
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}
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}
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int result = llama_chat_apply_template(
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llama_model_chat_template(llama_data.model.get()), llama_data.messages.data(), llama_data.messages.size(), append,
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tmpl.source().c_str(), llama_data.messages.data(), llama_data.messages.size(), append,
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append ? llama_data.fmtted.data() : nullptr, append ? llama_data.fmtted.size() : 0);
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if (append && result > static_cast<int>(llama_data.fmtted.size())) {
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llama_data.fmtted.resize(result);
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result = llama_chat_apply_template(llama_model_chat_template(llama_data.model.get()), llama_data.messages.data(),
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result = llama_chat_apply_template(tmpl.source().c_str(), llama_data.messages.data(),
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llama_data.messages.size(), append, llama_data.fmtted.data(),
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llama_data.fmtted.size());
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}
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@ -871,8 +893,8 @@ static int generate_response(LlamaData & llama_data, const std::string & prompt,
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}
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// Helper function to apply the chat template and handle errors
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static int apply_chat_template_with_error_handling(LlamaData & llama_data, const bool append, int & output_length) {
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const int new_len = apply_chat_template(llama_data, append);
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static int apply_chat_template_with_error_handling(const common_chat_template & tmpl, LlamaData & llama_data, const bool append, int & output_length, bool use_jinja) {
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const int new_len = apply_chat_template(tmpl, llama_data, append, use_jinja);
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if (new_len < 0) {
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printe("failed to apply the chat template\n");
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return -1;
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@ -931,9 +953,11 @@ static int get_user_input(std::string & user_input, const std::string & user) {
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}
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// Main chat loop function
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static int chat_loop(LlamaData & llama_data, const std::string & user) {
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static int chat_loop(LlamaData & llama_data, const std::string & user, bool use_jinja) {
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int prev_len = 0;
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llama_data.fmtted.resize(llama_n_ctx(llama_data.context.get()));
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auto chat_templates = common_chat_templates_from_model(llama_data.model.get(), "");
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GGML_ASSERT(chat_templates.template_default);
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static const bool stdout_a_terminal = is_stdout_a_terminal();
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while (true) {
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// Get user input
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@ -944,7 +968,7 @@ static int chat_loop(LlamaData & llama_data, const std::string & user) {
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add_message("user", user.empty() ? user_input : user, llama_data);
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int new_len;
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if (apply_chat_template_with_error_handling(llama_data, true, new_len) < 0) {
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if (apply_chat_template_with_error_handling(*chat_templates.template_default, llama_data, true, new_len, use_jinja) < 0) {
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return 1;
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}
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@ -959,7 +983,7 @@ static int chat_loop(LlamaData & llama_data, const std::string & user) {
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}
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add_message("assistant", response, llama_data);
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if (apply_chat_template_with_error_handling(llama_data, false, prev_len) < 0) {
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if (apply_chat_template_with_error_handling(*chat_templates.template_default, llama_data, false, prev_len, use_jinja) < 0) {
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return 1;
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}
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}
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@ -1019,7 +1043,7 @@ int main(int argc, const char ** argv) {
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return 1;
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}
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if (chat_loop(llama_data, opt.user)) {
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if (chat_loop(llama_data, opt.user, opt.use_jinja)) {
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return 1;
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}
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@ -126,7 +126,7 @@ The project is under active development, and we are [looking for feedback and co
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| `--grammar GRAMMAR` | BNF-like grammar to constrain generations (see samples in grammars/ dir) (default: '') |
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| `--grammar-file FNAME` | file to read grammar from |
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| `-j, --json-schema SCHEMA` | JSON schema to constrain generations (https://json-schema.org/), e.g. `{}` for any JSON object<br/>For schemas w/ external $refs, use --grammar + example/json_schema_to_grammar.py instead |
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| `--jinja` | Enable experimental Jinja templating engine (needed for tool use) |
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**Example-specific params**
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@ -1688,6 +1688,8 @@ struct server_context {
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// Necessary similarity of prompt for slot selection
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float slot_prompt_similarity = 0.0f;
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common_chat_templates chat_templates;
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~server_context() {
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// Clear any sampling context
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for (server_slot & slot : slots) {
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@ -1767,14 +1769,39 @@ struct server_context {
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cparams_dft.type_v = GGML_TYPE_F16;
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}
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chat_templates = common_chat_templates_from_model(model, params_base.chat_template);
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GGML_ASSERT(chat_templates.template_default.get() != nullptr);
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return true;
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}
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bool validate_builtin_chat_template() const {
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bool validate_builtin_chat_template(bool use_jinja) const {
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llama_chat_message chat[] = {{"user", "test"}};
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const char * tmpl = llama_model_chat_template(model);
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const int32_t chat_res = llama_chat_apply_template(tmpl, chat, 1, true, nullptr, 0);
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return chat_res > 0;
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if (use_jinja) {
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auto templates = common_chat_templates_from_model(model, "");
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GGML_ASSERT(templates.template_default);
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try {
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templates.template_default->apply({{
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{"role", "user"},
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{"content", "test"},
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}}, json(), true);
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if (templates.template_tool_use) {
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templates.template_tool_use->apply({{
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{"role", "user"},
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{"content", "test"},
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}}, json(), true);
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}
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return true;
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} catch (const std::exception & e) {
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SRV_ERR("failed to apply template: %s\n", e.what());
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return false;
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}
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} else {
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const char * tmpl = llama_model_chat_template(model, /* name */ nullptr);
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const int32_t chat_res = llama_chat_apply_template(tmpl, chat, 1, true, nullptr, 0);
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return chat_res > 0;
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}
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}
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void init() {
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@ -3659,9 +3686,12 @@ int main(int argc, char ** argv) {
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{ "default_generation_settings", ctx_server.default_generation_settings_for_props },
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{ "total_slots", ctx_server.params_base.n_parallel },
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{ "model_path", ctx_server.params_base.model },
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{ "chat_template", common_get_builtin_chat_template(ctx_server.model) },
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{ "chat_template", ctx_server.chat_templates.template_default->source() },
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{ "build_info", build_info },
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};
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if (ctx_server.params_base.use_jinja && ctx_server.chat_templates.template_tool_use) {
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data["chat_template_tool_use"] = ctx_server.chat_templates.template_tool_use->source();
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}
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res_ok(res, data);
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};
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@ -3889,7 +3919,10 @@ int main(int argc, char ** argv) {
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return;
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}
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json data = oaicompat_chat_completion_params_parse(ctx_server.model, json::parse(req.body), params.chat_template);
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auto body = json::parse(req.body);
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const auto & chat_template = body.contains("tools") && ctx_server.chat_templates.template_tool_use ? *ctx_server.chat_templates.template_tool_use : *ctx_server.chat_templates.template_default;
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json data = oaicompat_completion_params_parse(body, chat_template, params.use_jinja);
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return handle_completions_impl(
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SERVER_TASK_TYPE_COMPLETION,
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data,
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@ -4299,7 +4332,7 @@ int main(int argc, char ** argv) {
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// if a custom chat template is not supplied, we will use the one that comes with the model (if any)
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if (params.chat_template.empty()) {
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if (!ctx_server.validate_builtin_chat_template()) {
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if (!ctx_server.validate_builtin_chat_template(params.use_jinja)) {
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LOG_WRN("%s: The chat template that comes with this model is not yet supported, falling back to chatml. This may cause the model to output suboptimal responses\n", __func__);
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params.chat_template = "chatml";
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}
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@ -4307,8 +4340,8 @@ int main(int argc, char ** argv) {
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// print sample chat example to make it clear which template is used
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LOG_INF("%s: chat template, chat_template: %s, example_format: '%s'\n", __func__,
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params.chat_template.empty() ? "(built-in)" : params.chat_template.c_str(),
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common_chat_format_example(ctx_server.model, params.chat_template).c_str());
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ctx_server.chat_templates.template_default->source().c_str(),
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common_chat_format_example(*ctx_server.chat_templates.template_default, ctx_server.params_base.use_jinja).c_str());
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ctx_server.queue_tasks.on_new_task(std::bind(
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&server_context::process_single_task, &ctx_server, std::placeholders::_1));
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@ -4,22 +4,26 @@ from utils import *
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server = ServerPreset.tinyllama2()
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@pytest.fixture(scope="module", autouse=True)
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@pytest.fixture(autouse=True)
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def create_server():
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global server
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server = ServerPreset.tinyllama2()
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@pytest.mark.parametrize(
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"model,system_prompt,user_prompt,max_tokens,re_content,n_prompt,n_predicted,finish_reason",
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"model,system_prompt,user_prompt,max_tokens,re_content,n_prompt,n_predicted,finish_reason,jinja,chat_template",
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[
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(None, "Book", "What is the best book", 8, "(Suddenly)+", 77, 8, "length"),
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("codellama70b", "You are a coding assistant.", "Write the fibonacci function in c++.", 128, "(Aside|she|felter|alonger)+", 104, 64, "length"),
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(None, "Book", "What is the best book", 8, "(Suddenly)+", 77, 8, "length", False, None),
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(None, "Book", "What is the best book", 8, "(Suddenly)+", 77, 8, "length", True, None),
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(None, "Book", "What is the best book", 8, "^ blue", 23, 8, "length", True, "This is not a chat template, it is"),
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("codellama70b", "You are a coding assistant.", "Write the fibonacci function in c++.", 128, "(Aside|she|felter|alonger)+", 104, 64, "length", False, None),
|
||||
("codellama70b", "You are a coding assistant.", "Write the fibonacci function in c++.", 128, "(Aside|she|felter|alonger)+", 104, 64, "length", True, None),
|
||||
]
|
||||
)
|
||||
def test_chat_completion(model, system_prompt, user_prompt, max_tokens, re_content, n_prompt, n_predicted, finish_reason):
|
||||
def test_chat_completion(model, system_prompt, user_prompt, max_tokens, re_content, n_prompt, n_predicted, finish_reason, jinja, chat_template):
|
||||
global server
|
||||
server.jinja = jinja
|
||||
server.chat_template = chat_template
|
||||
server.start()
|
||||
res = server.make_request("POST", "/chat/completions", data={
|
||||
"model": model,
|
||||
|
|
|
|||
|
|
@ -72,13 +72,14 @@ class ServerProcess:
|
|||
pooling: str | None = None
|
||||
draft: int | None = None
|
||||
api_key: str | None = None
|
||||
response_format: str | None = None
|
||||
lora_files: List[str] | None = None
|
||||
disable_ctx_shift: int | None = False
|
||||
draft_min: int | None = None
|
||||
draft_max: int | None = None
|
||||
no_webui: bool | None = None
|
||||
jinja: bool | None = None
|
||||
chat_template: str | None = None
|
||||
chat_template_file: str | None = None
|
||||
|
||||
# session variables
|
||||
process: subprocess.Popen | None = None
|
||||
|
|
@ -169,8 +170,12 @@ class ServerProcess:
|
|||
server_args.extend(["--draft-min", self.draft_min])
|
||||
if self.no_webui:
|
||||
server_args.append("--no-webui")
|
||||
if self.jinja:
|
||||
server_args.append("--jinja")
|
||||
if self.chat_template:
|
||||
server_args.extend(["--chat-template", self.chat_template])
|
||||
if self.chat_template_file:
|
||||
server_args.extend(["--chat-template-file", self.chat_template_file])
|
||||
|
||||
args = [str(arg) for arg in [server_path, *server_args]]
|
||||
print(f"bench: starting server with: {' '.join(args)}")
|
||||
|
|
|
|||
|
|
@ -16,6 +16,8 @@
|
|||
// Change JSON_ASSERT from assert() to GGML_ASSERT:
|
||||
#define JSON_ASSERT GGML_ASSERT
|
||||
#include "json.hpp"
|
||||
#include "minja.hpp"
|
||||
#include "chat-template.hpp"
|
||||
|
||||
#include <random>
|
||||
#include <sstream>
|
||||
|
|
@ -349,7 +351,7 @@ static llama_tokens format_infill(
|
|||
}
|
||||
|
||||
// Format given chat. If tmpl is empty, we take the template from model metadata
|
||||
inline std::string format_chat(const struct llama_model * model, const std::string & tmpl, const std::vector<json> & messages) {
|
||||
inline std::string format_chat(const common_chat_template & tmpl, const std::vector<json> & messages) {
|
||||
std::vector<common_chat_msg> chat;
|
||||
|
||||
for (size_t i = 0; i < messages.size(); ++i) {
|
||||
|
|
@ -377,7 +379,7 @@ inline std::string format_chat(const struct llama_model * model, const std::stri
|
|||
chat.push_back({role, content});
|
||||
}
|
||||
|
||||
const auto formatted_chat = common_chat_apply_template(model, tmpl, chat, true);
|
||||
const auto formatted_chat = common_chat_apply_template(tmpl, chat, true, /* use_jinja= */ false);
|
||||
LOG_DBG("formatted_chat: '%s'\n", formatted_chat.c_str());
|
||||
|
||||
return formatted_chat;
|
||||
|
|
@ -576,14 +578,23 @@ static json oaicompat_completion_params_parse(const json & body) {
|
|||
return llama_params;
|
||||
}
|
||||
|
||||
static json oaicompat_chat_completion_params_parse(
|
||||
const struct llama_model * model,
|
||||
const json & body, /* openai api json semantics */
|
||||
const std::string & chat_template) {
|
||||
static json oaicompat_completion_params_parse(
|
||||
const json & body, /* openai api json semantics */
|
||||
const common_chat_template & tmpl,
|
||||
bool use_jinja)
|
||||
{
|
||||
json llama_params;
|
||||
|
||||
// Apply chat template to the list of messages
|
||||
llama_params["prompt"] = format_chat(model, chat_template, body.at("messages"));
|
||||
auto tools = json_value(body, "tools", json());
|
||||
auto has_tools = tools.is_array() && !tools.empty();
|
||||
|
||||
if (has_tools) {
|
||||
if (use_jinja) {
|
||||
LOG_WRN("tools param is not fully supported yet\n");
|
||||
} else {
|
||||
throw std::runtime_error("tools param requires --jinja flag");
|
||||
}
|
||||
}
|
||||
|
||||
// Handle "stop" field
|
||||
if (body.contains("stop") && body.at("stop").is_string()) {
|
||||
|
|
@ -606,6 +617,13 @@ static json oaicompat_chat_completion_params_parse(
|
|||
}
|
||||
}
|
||||
|
||||
// Apply chat template to the list of messages
|
||||
if (use_jinja) {
|
||||
llama_params["prompt"] = tmpl.apply(body.at("messages"), tools, /* add_generation_prompt= */ true);
|
||||
} else {
|
||||
llama_params["prompt"] = format_chat(tmpl, body.at("messages"));
|
||||
}
|
||||
|
||||
// Handle "n" field
|
||||
int n_choices = json_value(body, "n", 1);
|
||||
if (n_choices != 1) {
|
||||
|
|
@ -621,7 +639,7 @@ static json oaicompat_chat_completion_params_parse(
|
|||
}
|
||||
|
||||
// Params supported by OAI but unsupported by llama.cpp
|
||||
static const std::vector<std::string> unsupported_params { "tools", "tool_choice" };
|
||||
static const std::vector<std::string> unsupported_params { "tool_choice" };
|
||||
for (const auto & param : unsupported_params) {
|
||||
if (body.contains(param)) {
|
||||
throw std::runtime_error("Unsupported param: " + param);
|
||||
|
|
|
|||
|
|
@ -163,7 +163,7 @@ int main(int argc, char ** argv) {
|
|||
break;
|
||||
}
|
||||
|
||||
const char * tmpl = llama_model_chat_template(model);
|
||||
const char * tmpl = llama_model_chat_template(model, /* name */ nullptr);
|
||||
|
||||
// add the user input to the message list and format it
|
||||
messages.push_back({"user", strdup(user.c_str())});
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue