server: Enable transcriptions API for LFM2-Audio (#22000)
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+21
-5
@@ -544,6 +544,26 @@ bool common_chat_templates_was_explicit(const struct common_chat_templates * tmp
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return tmpls->has_explicit_template;
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}
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// LFM2 format detection: template uses <|tool_list_start|>[...]<|tool_list_end|> around the tool list
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// and <|tool_call_start|>[...]<|tool_call_end|> around each tool call
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static bool is_lfm2_template(const std::string & src) {
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return src.find("<|tool_list_start|>") != std::string::npos &&
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src.find("<|tool_list_end|>") != std::string::npos;
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}
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common_chat_prompt_preset common_chat_get_asr_prompt(const common_chat_templates * chat_templates) {
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common_chat_prompt_preset asr_preset;
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asr_preset.system = "";
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asr_preset.user = "Transcribe audio to text";
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if (chat_templates && chat_templates->template_default && is_lfm2_template(chat_templates->template_default->source())) {
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asr_preset.system = "Perform ASR.";
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asr_preset.user = "";
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}
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return asr_preset;
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}
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std::string common_chat_templates_source(const struct common_chat_templates * tmpls, const std::string & variant) {
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if (!variant.empty()) {
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if (variant == "tool_use") {
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@@ -2053,10 +2073,7 @@ std::optional<common_chat_params> common_chat_try_specialized_template(
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return common_chat_params_init_kimi_k2(tmpl, params);
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}
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// LFM2 format detection: template uses <|tool_list_start|>[...]<|tool_list_end|> around the tool list
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// and <|tool_call_start|>[...]<|tool_call_end|> around each tool call
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if (src.find("<|tool_list_start|>") != std::string::npos &&
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src.find("<|tool_list_end|>") != std::string::npos) {
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if (is_lfm2_template(src)) {
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LOG_DBG("Using specialized template: LFM2\n");
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return common_chat_params_init_lfm2(tmpl, params);
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}
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@@ -2365,4 +2382,3 @@ std::map<std::string, bool> common_chat_templates_get_caps(const common_chat_tem
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GGML_ASSERT(chat_templates->template_default != nullptr);
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return chat_templates->template_default->caps.to_map();
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}
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@@ -274,3 +274,11 @@ std::optional<common_chat_params> common_chat_try_specialized_template(
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const common_chat_template & tmpl,
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const std::string & src,
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autoparser::generation_params & params);
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// specialized per-task preset
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struct common_chat_prompt_preset {
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std::string system;
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std::string user;
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};
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common_chat_prompt_preset common_chat_get_asr_prompt(const common_chat_templates * chat_templates);
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@@ -535,6 +535,7 @@ json server_chat_msg_diff_to_json_oaicompat(const common_chat_msg_diff & diff) {
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json convert_transcriptions_to_chatcmpl(
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const json & inp_body,
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const common_chat_templates * tmpls,
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const std::map<std::string, raw_buffer> & in_files,
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std::vector<raw_buffer> & out_files) {
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// TODO @ngxson : this function may need to be improved in the future
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@@ -554,21 +555,23 @@ json convert_transcriptions_to_chatcmpl(
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if (response_format != "json") {
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throw std::invalid_argument("Only 'json' response_format is supported for transcription");
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}
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const common_chat_prompt_preset preset = common_chat_get_asr_prompt(tmpls);
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if (prompt.empty()) {
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prompt = "Transcribe audio to text";
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prompt = preset.user;
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}
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if (!language.empty()) {
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prompt += string_format(" (language: %s)", language.c_str());
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}
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prompt += get_media_marker();
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json messages = json::array();
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if (!preset.system.empty()) {
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messages.push_back({{"role", "system"}, {"content", preset.system}});
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}
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messages.push_back({{"role", "user"}, {"content", prompt}});
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json chatcmpl_body = inp_body; // copy all fields
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chatcmpl_body["messages"] = json::array({
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{
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{"role", "user"},
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{"content", prompt},
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},
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});
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chatcmpl_body["messages"] = messages;
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// because input from form-data, everything is string, we need to correct the types here
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std::string stream = json_value(inp_body, "stream", std::string("false"));
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@@ -18,6 +18,7 @@ json server_chat_convert_anthropic_to_oai(const json & body);
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// convert OpenAI transcriptions API format to OpenAI Chat Completions API format
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json convert_transcriptions_to_chatcmpl(
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const json & body,
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const common_chat_templates * tmpls,
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const std::map<std::string, raw_buffer> & in_files,
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std::vector<raw_buffer> & out_files);
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@@ -3807,6 +3807,7 @@ void server_routes::init_routes() {
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std::vector<raw_buffer> files;
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json body = convert_transcriptions_to_chatcmpl(
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json::parse(req.body),
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meta->chat_params.tmpls.get(),
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req.files,
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files);
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SRV_DBG("%s\n", "Request converted: OpenAI Transcriptions -> OpenAI Chat Completions");
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