fix: check model status before inferencing

engine/services/inference_service.cc

@@ -14,6 +14,21 @@ cpp::result<void, InferResult> InferenceService::HandleChatCompletion(
   }
   function_calling_utils::PreprocessRequest(json_body);
   auto tool_choice = json_body->get("tool_choice", Json::Value::null);
+  auto model_id = json_body->get("model", "").asString();
+  if (saved_models_.find(model_id) != saved_models_.end()) {
+    // check if model is started, if not start it first
+    Json::Value root;
+    root["model"] = model_id;
+    root["engine"] = engine_type;
+    auto ir = GetModelStatus(std::make_shared<Json::Value>(root));
+    auto status = std::get<0>(ir)["status_code"].asInt();
+    if (status != drogon::k200OK) {
+      CTL_INF("Model is not loaded, start loading it: " << model_id);
+      auto res = LoadModel(saved_models_.at(model_id));
+      // ignore return result
+    }
+  }
+
   auto engine_result = engine_service_->GetLoadedEngine(engine_type);
   if (engine_result.has_error()) {
     Json::Value res;
@@ -23,45 +38,42 @@ cpp::result<void, InferResult> InferenceService::HandleChatCompletion(
     LOG_WARN << "Engine is not loaded yet";
     return cpp::fail(std::make_pair(stt, res));
   }
+
+  if (!model_id.empty()) {
+    if (auto model_service = model_service_.lock()) {
+      auto metadata_ptr = model_service->GetCachedModelMetadata(model_id);
+      if (metadata_ptr != nullptr &&
+          !metadata_ptr->tokenizer->chat_template.empty()) {
+        auto tokenizer = metadata_ptr->tokenizer;
+        auto messages = (*json_body)["messages"];
+        Json::Value messages_jsoncpp(Json::arrayValue);
+        for (auto message : messages) {
+          messages_jsoncpp.append(message);
+        }
 
-  {
-    auto model_id = json_body->get("model", "").asString();
-    if (!model_id.empty()) {
-      if (auto model_service = model_service_.lock()) {
-        auto metadata_ptr = model_service->GetCachedModelMetadata(model_id);
-        if (metadata_ptr != nullptr &&
-            !metadata_ptr->tokenizer->chat_template.empty()) {
-          auto tokenizer = metadata_ptr->tokenizer;
-          auto messages = (*json_body)["messages"];
-          Json::Value messages_jsoncpp(Json::arrayValue);
-          for (auto message : messages) {
-            messages_jsoncpp.append(message);
-          }
-
-          Json::Value tools(Json::arrayValue);
-          Json::Value template_data_json;
-          template_data_json["messages"] = messages_jsoncpp;
-          // template_data_json["tools"] = tools;
-
-          auto prompt_result = jinja::RenderTemplate(
-              tokenizer->chat_template, template_data_json,
-              tokenizer->bos_token, tokenizer->eos_token,
-              tokenizer->add_bos_token, tokenizer->add_eos_token,
-              tokenizer->add_generation_prompt);
-          if (prompt_result.has_value()) {
-            (*json_body)["prompt"] = prompt_result.value();
-            Json::Value stops(Json::arrayValue);
-            stops.append(tokenizer->eos_token);
-            (*json_body)["stop"] = stops;
-          } else {
-            CTL_ERR("Failed to render prompt: " + prompt_result.error());
-          }
+        Json::Value tools(Json::arrayValue);
+        Json::Value template_data_json;
+        template_data_json["messages"] = messages_jsoncpp;
+        // template_data_json["tools"] = tools;
+
+        auto prompt_result = jinja::RenderTemplate(
+            tokenizer->chat_template, template_data_json, tokenizer->bos_token,
+            tokenizer->eos_token, tokenizer->add_bos_token,
+            tokenizer->add_eos_token, tokenizer->add_generation_prompt);
+        if (prompt_result.has_value()) {
+          (*json_body)["prompt"] = prompt_result.value();
+          Json::Value stops(Json::arrayValue);
+          stops.append(tokenizer->eos_token);
+          (*json_body)["stop"] = stops;
+        } else {
+          CTL_ERR("Failed to render prompt: " + prompt_result.error());
         }
       }
     }
   }
 
-  CTL_INF("Json body inference: " + json_body->toStyledString());
+
+  CTL_DBG("Json body inference: " + json_body->toStyledString());
 
   auto cb = [q, tool_choice](Json::Value status, Json::Value res) {
     if (!tool_choice.isNull()) {
@@ -205,6 +217,10 @@ InferResult InferenceService::LoadModel(
     std::get<RemoteEngineI*>(engine_result.value())
         ->LoadModel(json_body, std::move(cb));
   }
+  if (!engine_service_->IsRemoteEngine(engine_type)) {
+    auto model_id = json_body->get("model", "").asString();
+    saved_models_[model_id] = json_body;
+  }
   return std::make_pair(stt, r);
 }
 

engine/services/inference_service.h

@@ -47,7 +47,7 @@ class InferenceService {
 
   cpp::result<void, InferResult> HandleRouteRequest(
       std::shared_ptr<SyncQueue> q, std::shared_ptr<Json::Value> json_body);
-      
+
   InferResult LoadModel(std::shared_ptr<Json::Value> json_body);
 
   InferResult UnloadModel(const std::string& engine,
@@ -74,4 +74,6 @@ class InferenceService {
  private:
   std::shared_ptr<EngineService> engine_service_;
   std::weak_ptr<ModelService> model_service_;
+  using SavedModel = std::shared_ptr<Json::Value>;
+  std::unordered_map<std::string, SavedModel> saved_models_;
 };