fix typo "RLIMIT_MLOCK" (#5175)

ggml-ci

convert.py

@@ -334,7 +334,10 @@ class Params:
 class BpeVocab:
     def __init__(self, fname_tokenizer: Path, fname_added_tokens: Path | None) -> None:
         self.bpe_tokenizer = json.loads(open(str(fname_tokenizer), encoding="utf-8").read())
-        self.vocab = self.bpe_tokenizer["model"]["vocab"]
+        try:
+            self.vocab = self.bpe_tokenizer["model"]["vocab"]
+        except KeyError:
+            self.vocab = self.bpe_tokenizer
         added_tokens: dict[str, int]
         if fname_added_tokens is not None:
             # FIXME: Verify that added tokens here _cannot_ overlap with the main vocab.

examples/server/oai.hpp

@@ -206,3 +206,18 @@ inline static std::vector<json> format_partial_response_oaicompat(const task_res
 
     return std::vector<json>({ret});
 }
+
+inline static json format_embeddings_response_oaicompat(const json &request, const json &embeddings)
+{
+    json res =
+        json{
+            {"model", json_value(request, "model", std::string(DEFAULT_OAICOMPAT_MODEL))},
+            {"object", "list"},
+            {"usage",
+                json{{"prompt_tokens", 0},
+                     {"total_tokens", 0}}},
+            {"data", embeddings}
+        };
+    return res;
+}
+

examples/server/server.cpp

@@ -2929,6 +2929,66 @@ int main(int argc, char **argv)
                 return res.set_content(result.result_json.dump(), "application/json; charset=utf-8");
             });
 
+    svr.Post("/v1/embeddings", [&llama](const httplib::Request &req, httplib::Response &res)
+            {
+                res.set_header("Access-Control-Allow-Origin", req.get_header_value("Origin"));
+                const json body = json::parse(req.body);
+
+                json prompt;
+                if (body.count("input") != 0)
+                {
+                    prompt = body["input"];
+                    // batch
+                    if(prompt.is_array()) {
+                        json data = json::array();
+                        int i = 0;
+                        for (const json &elem : prompt) {
+                            const int task_id = llama.queue_tasks.get_new_id();
+                            llama.queue_results.add_waiting_task_id(task_id);
+                            llama.request_completion(task_id, { {"prompt", elem}, { "n_predict", 0} }, false, true, -1);
+
+                            // get the result
+                            task_result result = llama.queue_results.recv(task_id);
+                            llama.queue_results.remove_waiting_task_id(task_id);
+
+                            json embedding = json{
+                                {"embedding", json_value(result.result_json, "embedding", json::array())},
+                                {"index", i++},
+                                {"object", "embedding"}
+                            };
+                            data.push_back(embedding);
+                        }
+                        json result = format_embeddings_response_oaicompat(body, data);
+                        return res.set_content(result.dump(), "application/json; charset=utf-8");
+                    }
+                }
+                else
+                {
+                    prompt = "";
+                }
+
+                // create and queue the task
+                const int task_id = llama.queue_tasks.get_new_id();
+                llama.queue_results.add_waiting_task_id(task_id);
+                llama.request_completion(task_id, { {"prompt", prompt}, { "n_predict", 0}}, false, true, -1);
+
+                // get the result
+                task_result result = llama.queue_results.recv(task_id);
+                llama.queue_results.remove_waiting_task_id(task_id);
+
+                json data = json::array({json{
+                        {"embedding", json_value(result.result_json, "embedding", json::array())},
+                        {"index", 0},
+                        {"object", "embedding"}
+                    }}
+                );
+
+                json root = format_embeddings_response_oaicompat(body, data);
+
+                // send the result
+                return res.set_content(root.dump(), "application/json; charset=utf-8");
+            });
+
     // GG: if I put the main loop inside a thread, it crashes on the first request when build in Debug!?
     //     "Bus error: 10" - this is on macOS, it does not crash on Linux
     //std::thread t2([&]()

ggml-metal.m

@@ -2375,6 +2375,16 @@ GGML_CALL static size_t ggml_backend_metal_buffer_type_get_alignment(ggml_backen
     UNUSED(buft);
 }
 
+GGML_CALL static size_t ggml_backend_metal_buffer_type_get_max_size(ggml_backend_buffer_type_t buft) {
+    id<MTLDevice> device = ggml_backend_metal_get_device();
+    size_t max_size = device.maxBufferLength;
+    ggml_backend_metal_free_device();
+
+    return max_size;
+
+    UNUSED(buft);
+}
+
 GGML_CALL static bool ggml_backend_metal_buffer_type_supports_backend(ggml_backend_buffer_type_t buft, ggml_backend_t backend) {
     return ggml_backend_is_metal(backend) || ggml_backend_is_cpu(backend);
 
@@ -2393,7 +2403,7 @@ GGML_CALL ggml_backend_buffer_type_t ggml_backend_metal_buffer_type(void) {
             /* .get_name         = */ ggml_backend_metal_buffer_type_get_name,
             /* .alloc_buffer     = */ ggml_backend_metal_buffer_type_alloc_buffer,
             /* .get_alignment    = */ ggml_backend_metal_buffer_type_get_alignment,
-            /* .get_max_size     = */ NULL, // TODO: return device.maxBufferLength
+            /* .get_max_size     = */ ggml_backend_metal_buffer_type_get_max_size,
             /* .get_alloc_size   = */ NULL, // defaults to ggml_nbytes
             /* .supports_backend = */ ggml_backend_metal_buffer_type_supports_backend,
             /* .is_host          = */ ggml_backend_metal_buffer_type_is_host,

ggml-opencl.cpp

@@ -2125,6 +2125,15 @@ static size_t ggml_backend_opencl_buffer_type_get_alignment(ggml_backend_buffer_
     GGML_UNUSED(buffer_type);
 }
 
+static size_t ggml_backend_opencl_buffer_type_get_max_size(ggml_backend_buffer_type_t buffer_type) {
+    static size_t max_size = -1;
+    if (max_size == (size_t)-1) {
+        ggml_cl_init();
+        clGetDeviceInfo(device, CL_DEVICE_MAX_MEM_ALLOC_SIZE, sizeof(size_t), &max_size, NULL);
+    }
+    return max_size;
+}
+
 static bool ggml_backend_opencl_buffer_type_supports_backend(ggml_backend_buffer_type_t buffer_type, ggml_backend_t backend) {
     //return ggml_backend_is_opencl(backend); // opencl must be used through the cpu backend
     return ggml_backend_is_cpu(backend);
@@ -2136,7 +2145,7 @@ static ggml_backend_buffer_type_i ggml_backend_opencl_buffer_type_interface = {
     /* .get_name         = */ ggml_backend_opencl_buffer_type_name,
     /* .alloc_buffer     = */ ggml_backend_opencl_buffer_type_alloc_buffer,
     /* .get_alignment    = */ ggml_backend_opencl_buffer_type_get_alignment,
-    /* .get_max_size     = */ NULL, // TODO: return from device info
+    /* .get_max_size     = */ ggml_backend_opencl_buffer_type_get_max_size,
     /* .get_alloc_size   = */ NULL,
     /* .supports_backend = */ ggml_backend_opencl_buffer_type_supports_backend,
     /* .is_host          = */ NULL,

llama.cpp

@@ -1158,10 +1158,10 @@ struct llama_mlock {
     #ifdef __APPLE__
         #define MLOCK_SUGGESTION \
             "Try increasing the sysctl values 'vm.user_wire_limit' and 'vm.global_user_wire_limit' and/or " \
-            "decreasing 'vm.global_no_user_wire_amount'.  Also try increasing RLIMIT_MLOCK (ulimit -l).\n"
+            "decreasing 'vm.global_no_user_wire_amount'.  Also try increasing RLIMIT_MEMLOCK (ulimit -l).\n"
     #else
         #define MLOCK_SUGGESTION \
-            "Try increasing RLIMIT_MLOCK ('ulimit -l' as root).\n"
+            "Try increasing RLIMIT_MEMLOCK ('ulimit -l' as root).\n"
     #endif
 
     bool raw_lock(const void * addr, size_t size) const {