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https://github.com/ggerganov/llama.cpp.git
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server : clean up built-in template detection (#11026)
* server : clean up built-in template detection * fix compilation * add chat template test * fix condition
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@ -1614,6 +1614,18 @@ std::string common_detokenize(llama_context * ctx, const std::vector<llama_token
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// Chat template utils
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//
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std::string common_get_builtin_chat_template(const struct llama_model * model) {
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static const char * template_key = "tokenizer.chat_template";
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// call with NULL buffer to get the total size of the string
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int32_t res = llama_model_meta_val_str(model, template_key, NULL, 0);
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if (res > 0) {
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std::vector<char> model_template(res + 1, 0);
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llama_model_meta_val_str(model, template_key, model_template.data(), model_template.size());
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return std::string(model_template.data(), model_template.size() - 1);
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}
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return "";
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}
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bool common_chat_verify_template(const std::string & tmpl) {
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llama_chat_message chat[] = {{"user", "test"}};
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int res = llama_chat_apply_template(nullptr, tmpl.c_str(), chat, 1, true, nullptr, 0);
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@ -571,6 +571,9 @@ struct common_chat_msg {
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std::string content;
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};
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// Get the built-in chat template for the model. Return empty string if not present.
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std::string common_get_builtin_chat_template(const struct llama_model * model);
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// Check if the template supplied via "--chat-template" is supported or not. Returns true if it's valid
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bool common_chat_verify_template(const std::string & tmpl);
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@ -1724,17 +1724,10 @@ struct server_context {
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return true;
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}
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bool validate_model_chat_template() const {
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std::vector<char> model_template(2048, 0); // longest known template is about 1200 bytes
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std::string template_key = "tokenizer.chat_template";
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int32_t res = llama_model_meta_val_str(model, template_key.c_str(), model_template.data(), model_template.size());
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if (res >= 0) {
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llama_chat_message chat[] = {{"user", "test"}};
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std::string tmpl = std::string(model_template.data(), model_template.size());
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int32_t chat_res = llama_chat_apply_template(model, tmpl.c_str(), chat, 1, true, nullptr, 0);
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return chat_res > 0;
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}
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return false;
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bool validate_builtin_chat_template() const {
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llama_chat_message chat[] = {{"user", "test"}};
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int32_t chat_res = llama_chat_apply_template(model, nullptr, chat, 1, true, nullptr, 0);
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return chat_res > 0;
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}
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void init() {
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@ -3583,7 +3576,7 @@ 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", llama_get_chat_template(ctx_server.model) },
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{ "chat_template", common_get_builtin_chat_template(ctx_server.model) },
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{ "build_info", build_info },
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};
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@ -4223,14 +4216,16 @@ 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_model_chat_template()) {
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if (!ctx_server.validate_builtin_chat_template()) {
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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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}
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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, built_in: %d, chat_example: '%s'\n", __func__, params.chat_template.empty(), common_chat_format_example(ctx_server.model, params.chat_template).c_str());
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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.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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@ -100,6 +100,23 @@ def test_chat_completion_with_openai_library():
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assert match_regex("(Suddenly)+", res.choices[0].message.content)
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def test_chat_template():
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global server
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server.chat_template = "llama3"
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server.debug = True # to get the "__verbose" object in the response
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server.start()
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res = server.make_request("POST", "/chat/completions", data={
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"max_tokens": 8,
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"messages": [
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{"role": "system", "content": "Book"},
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{"role": "user", "content": "What is the best book"},
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]
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})
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assert res.status_code == 200
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assert "__verbose" in res.body
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assert res.body["__verbose"]["prompt"] == "<s> <|start_header_id|>system<|end_header_id|>\n\nBook<|eot_id|><|start_header_id|>user<|end_header_id|>\n\nWhat is the best book<|eot_id|><|start_header_id|>assistant<|end_header_id|>\n\n"
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@pytest.mark.parametrize("response_format,n_predicted,re_content", [
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({"type": "json_object", "schema": {"const": "42"}}, 6, "\"42\""),
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({"type": "json_object", "schema": {"items": [{"type": "integer"}]}}, 10, "[ -3000 ]"),
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@ -74,6 +74,7 @@ class ServerProcess:
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draft_min: int | None = None
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draft_max: int | None = None
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no_webui: bool | None = None
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chat_template: str | None = None
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# session variables
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process: subprocess.Popen | None = None
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@ -164,6 +165,8 @@ class ServerProcess:
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server_args.extend(["--draft-min", self.draft_min])
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if self.no_webui:
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server_args.append("--no-webui")
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if self.chat_template:
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server_args.extend(["--chat-template", self.chat_template])
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args = [str(arg) for arg in [server_path, *server_args]]
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print(f"bench: starting server with: {' '.join(args)}")
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@ -382,19 +382,6 @@ inline std::string format_chat(const struct llama_model * model, const std::stri
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return formatted_chat;
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}
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static std::string llama_get_chat_template(const struct llama_model * model) {
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std::string template_key = "tokenizer.chat_template";
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// call with NULL buffer to get the total size of the string
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int32_t res = llama_model_meta_val_str(model, template_key.c_str(), NULL, 0);
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if (res < 2) {
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return "";
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} else {
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std::vector<char> model_template(res + 1, 0);
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llama_model_meta_val_str(model, template_key.c_str(), model_template.data(), model_template.size());
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return std::string(model_template.data(), model_template.size() - 1);
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}
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}
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//
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// base64 utils (TODO: move to common in the future)
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//
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