naive whitespace detection

README.md

@@ -62,8 +62,6 @@ Here are some example models that can be downloaded:
 | Orca Mini          | 3B         | 1.9GB | `ollama run orca-mini`         |
 | Vicuna             | 7B         | 3.8GB | `ollama run vicuna`            |
 | LLaVA              | 7B         | 4.5GB | `ollama run llava`             |
-| Gemma              | 2B         | 1.4GB | `ollama run gemma:2b`          |
-| Gemma              | 7B         | 4.8GB | `ollama run gemma:7b`          |
 
 > Note: You should have at least 8 GB of RAM available to run the 7B models, 16 GB to run the 13B models, and 32 GB to run the 33B models.
 
@@ -260,21 +258,19 @@ See the [API documentation](./docs/api.md) for all endpoints.
 ### Web & Desktop
 
 - [Bionic GPT](https://github.com/bionic-gpt/bionic-gpt)
-- [Enchanted (macOS native)](https://github.com/AugustDev/enchanted)
 - [HTML UI](https://github.com/rtcfirefly/ollama-ui)
 - [Chatbot UI](https://github.com/ivanfioravanti/chatbot-ollama)
 - [Typescript UI](https://github.com/ollama-interface/Ollama-Gui?tab=readme-ov-file)
 - [Minimalistic React UI for Ollama Models](https://github.com/richawo/minimal-llm-ui)
 - [Open WebUI](https://github.com/open-webui/open-webui)
 - [Ollamac](https://github.com/kevinhermawan/Ollamac)
-- [big-AGI](https://github.com/enricoros/big-AGI/blob/main/docs/config-local-ollama.md)
+- [big-AGI](https://github.com/enricoros/big-agi/blob/main/docs/config-ollama.md)
 - [Cheshire Cat assistant framework](https://github.com/cheshire-cat-ai/core)
 - [Amica](https://github.com/semperai/amica)
 - [chatd](https://github.com/BruceMacD/chatd)
 - [Ollama-SwiftUI](https://github.com/kghandour/Ollama-SwiftUI)
 - [MindMac](https://mindmac.app)
 - [NextJS Web Interface for Ollama](https://github.com/jakobhoeg/nextjs-ollama-llm-ui)
-- [Msty](https://msty.app)
 
 ### Terminal
 
@@ -305,7 +301,6 @@ See the [API documentation](./docs/api.md) for all endpoints.
 
 - [LangChain](https://python.langchain.com/docs/integrations/llms/ollama) and [LangChain.js](https://js.langchain.com/docs/modules/model_io/models/llms/integrations/ollama) with [example](https://js.langchain.com/docs/use_cases/question_answering/local_retrieval_qa)
 - [LangChainGo](https://github.com/tmc/langchaingo/) with [example](https://github.com/tmc/langchaingo/tree/main/examples/ollama-completion-example)
-- [LangChain4j](https://github.com/langchain4j/langchain4j) with [example](https://github.com/langchain4j/langchain4j-examples/tree/main/ollama-examples/src/main/java)
 - [LlamaIndex](https://gpt-index.readthedocs.io/en/stable/examples/llm/ollama.html)
 - [LangChain4j](https://github.com/langchain4j/langchain4j/tree/main/langchain4j-ollama)
 - [LiteLLM](https://github.com/BerriAI/litellm)
@@ -320,10 +315,8 @@ See the [API documentation](./docs/api.md) for all endpoints.
 - [LangChainDart](https://github.com/davidmigloz/langchain_dart)
 - [Semantic Kernel - Python](https://github.com/microsoft/semantic-kernel/tree/main/python/semantic_kernel/connectors/ai/ollama)
 - [Haystack](https://github.com/deepset-ai/haystack-integrations/blob/main/integrations/ollama.md)
-- [Elixir LangChain](https://github.com/brainlid/langchain)
 - [Ollama for R - rollama](https://github.com/JBGruber/rollama)
 - [Ollama-ex for Elixir](https://github.com/lebrunel/ollama-ex)
-- [Ollama Connector for SAP ABAP](https://github.com/b-tocs/abap_btocs_ollama)
 
 ### Mobile
 
@@ -344,9 +337,6 @@ See the [API documentation](./docs/api.md) for all endpoints.
 - [Rivet plugin](https://github.com/abrenneke/rivet-plugin-ollama)
 - [Llama Coder](https://github.com/ex3ndr/llama-coder) (Copilot alternative using Ollama)
 - [Obsidian BMO Chatbot plugin](https://github.com/longy2k/obsidian-bmo-chatbot)
-- [Copilot for Obsidian plugin](https://github.com/logancyang/obsidian-copilot)
-- [Obsidian Local GPT plugin](https://github.com/pfrankov/obsidian-local-gpt)
 - [Open Interpreter](https://docs.openinterpreter.com/language-model-setup/local-models/ollama)
 - [twinny](https://github.com/rjmacarthy/twinny) (Copilot and Copilot chat alternative using Ollama)
 - [Wingman-AI](https://github.com/RussellCanfield/wingman-ai) (Copilot code and chat alternative using Ollama and HuggingFace)
-- [Page Assist](https://github.com/n4ze3m/page-assist) (Chrome Extension)

api/client.go

@@ -21,7 +21,7 @@ import (
 
 type Client struct {
 	base *url.URL
-	http *http.Client
+	http http.Client
 }
 
 func checkError(resp *http.Response, body []byte) error {
@@ -66,13 +66,30 @@ func ClientFromEnvironment() (*Client, error) {
 		}
 	}
 
-	return &Client{
+	client := Client{
 		base: &url.URL{
 			Scheme: scheme,
 			Host:   net.JoinHostPort(host, port),
 		},
-		http: http.DefaultClient,
-	}, nil
+	}
+
+	mockRequest, err := http.NewRequest(http.MethodHead, client.base.String(), nil)
+	if err != nil {
+		return nil, err
+	}
+
+	proxyURL, err := http.ProxyFromEnvironment(mockRequest)
+	if err != nil {
+		return nil, err
+	}
+
+	client.http = http.Client{
+		Transport: &http.Transport{
+			Proxy: http.ProxyURL(proxyURL),
+		},
+	}
+
+	return &client, nil
 }
 
 func (c *Client) do(ctx context.Context, method, path string, reqData, respData any) error {

app/lifecycle/updater.go

@@ -34,6 +34,20 @@ type UpdateResponse struct {
 	UpdateVersion string `json:"version"`
 }
 
+func getClient(req *http.Request) http.Client {
+	proxyURL, err := http.ProxyFromEnvironment(req)
+	if err != nil {
+		slog.Warn(fmt.Sprintf("failed to handle proxy: %s", err))
+		return http.Client{}
+	}
+
+	return http.Client{
+		Transport: &http.Transport{
+			Proxy: http.ProxyURL(proxyURL),
+		},
+	}
+}
+
 func IsNewReleaseAvailable(ctx context.Context) (bool, UpdateResponse) {
 	var updateResp UpdateResponse
 
@@ -69,9 +83,10 @@ func IsNewReleaseAvailable(ctx context.Context) (bool, UpdateResponse) {
 	}
 	req.Header.Set("Authorization", signature)
 	req.Header.Set("User-Agent", fmt.Sprintf("ollama/%s (%s %s) Go/%s", version.Version, runtime.GOARCH, runtime.GOOS, runtime.Version()))
+	client := getClient(req)
 
 	slog.Debug("checking for available update", "requestURL", requestURL)
-	resp, err := http.DefaultClient.Do(req)
+	resp, err := client.Do(req)
 	if err != nil {
 		slog.Warn(fmt.Sprintf("failed to check for update: %s", err))
 		return false, updateResp
@@ -104,8 +119,8 @@ func DownloadNewRelease(ctx context.Context, updateResp UpdateResponse) error {
 	if err != nil {
 		return err
 	}
-
-	resp, err := http.DefaultClient.Do(req)
+	client := getClient(req)
+	resp, err := client.Do(req)
 	if err != nil {
 		return fmt.Errorf("error checking update: %w", err)
 	}
@@ -136,7 +151,7 @@ func DownloadNewRelease(ctx context.Context, updateResp UpdateResponse) error {
 	cleanupOldDownloads()
 
 	req.Method = http.MethodGet
-	resp, err = http.DefaultClient.Do(req)
+	resp, err = client.Do(req)
 	if err != nil {
 		return fmt.Errorf("error checking update: %w", err)
 	}

app/ollama.iss

@@ -37,7 +37,7 @@ PrivilegesRequired=lowest
 OutputBaseFilename="OllamaSetup"
 SetupIconFile={#MyIcon}
 UninstallDisplayIcon={uninstallexe}
-Compression=zip
+Compression=lzma2
 SolidCompression=no
 WizardStyle=modern
 ChangesEnvironment=yes

docs/faq.md

@@ -113,9 +113,9 @@ If a different directory needs to be used, set the environment variable `OLLAMA_
 
 Refer to the section [above](#how-do-i-configure-ollama-server) for how to set environment variables on your platform.
 
-## Does Ollama send my prompts and answers back to ollama.com?
+## Does Ollama send my prompts and answers back to Ollama.ai to use in any way?
 
-No. Ollama runs locally, and conversation data does not leave your machine.
+No, Ollama runs entirely locally, and conversation data will never leave your machine.
 
 ## How can I use Ollama in Visual Studio Code?
 

docs/import.md

@@ -124,10 +124,7 @@ ollama run example "What is your favourite condiment?"
 Publishing models is in early alpha. If you'd like to publish your model to share with others, follow these steps:
 
 1. Create [an account](https://ollama.com/signup)
-2. Copy your Ollama public key:
-  - macOS: `cat ~/.ollama/id_ed25519.pub`
-  - Windows: `type %USERPROFILE%\.ollama\id_ed25519.pub`
-  - Linux: `cat /usr/share/ollama/.ollama/id_ed25519.pub`
+2. Run `cat ~/.ollama/id_ed25519.pub` (or `type %USERPROFILE%\.ollama\id_ed25519.pub` on Windows) to view your Ollama public key. Copy this to the clipboard.
 3. Add your public key to your [Ollama account](https://ollama.com/settings/keys)
 
 Next, copy your model to your username's namespace:

examples/python-chat-app/README.md

@@ -1,21 +0,0 @@
-# Ollama Chat App
-
-Build a Llama2 chat app using Streamlit and Ollama.
-
-## Running the Example
-
-1. Ensure you have the `llama2` model installed:
-
-   ```bash
-   ollama pull llama2
-   ```
-2. Install the Python Requirements.
-
-   ```bash
-   pip install -r requirements.txt
-   ```
-3. Run the example:
-
-   ```bash
-   python main.py
-   ```

llm/dyn_ext_server.go

@@ -106,12 +106,7 @@ func newDynExtServer(library, model string, adapters, projectors []string, opts
 	sparams.memory_f16 = C.bool(opts.F16KV)
 	sparams.use_mlock = C.bool(opts.UseMLock)
 	sparams.use_mmap = C.bool(opts.UseMMap)
-
-	if opts.UseNUMA {
-		sparams.numa = C.int(1)
-	} else {
-		sparams.numa = C.int(0)
-	}
+	sparams.numa = C.bool(opts.UseNUMA)
 
 	sparams.lora_adapters = nil
 	for i := 0; i < len(adapters); i++ {
@@ -199,6 +194,7 @@ func (llm *dynExtServer) Predict(ctx context.Context, predict PredictOpts, fn fu
 		request["grammar"] = jsonGrammar
 	}
 
+	var whitespace int
 	retryDelay := 100 * time.Microsecond
 	for retries := 0; retries < maxRetries; retries++ {
 		if retries > 0 {
@@ -257,6 +253,24 @@ func (llm *dynExtServer) Predict(ctx context.Context, predict PredictOpts, fn fu
 					break out
 				}
 
+				// detect if p.Content is entirely whitespace
+				if predict.Format == "json" && strings.TrimSpace(p.Content) == "" {
+					whitespace++
+
+					// if we get 100 consecutive whitespace responses, cancel
+					if whitespace > 100 {
+						slog.Debug("cancelling due to excessive whitespace")
+						C.dyn_llama_server_completion_cancel(llm.s, resp.id, &resp)
+						if resp.id < 0 {
+							return extServerResponseToErr(resp)
+						}
+
+						return nil
+					}
+				} else {
+					whitespace = 0
+				}
+
 				if p.Content != "" {
 					fn(PredictResult{
 						Content: p.Content,

llm/ext_server/ext_server.cpp

@@ -80,7 +80,7 @@ void llama_server_init(ext_server_params *sparams, ext_server_resp_t *err) {
     params.main_gpu = sparams->main_gpu;
     params.use_mlock = sparams->use_mlock;
     params.use_mmap = sparams->use_mmap;
-    params.numa = (ggml_numa_strategy)sparams->numa;
+    params.numa = sparams->numa;
     params.embedding = sparams->embedding;
     if (sparams->model != NULL) {
       params.model = sparams->model;
@@ -111,8 +111,7 @@ void llama_server_init(ext_server_params *sparams, ext_server_resp_t *err) {
     }
 #endif
 
-    llama_backend_init();
-    llama_numa_init(params.numa);
+    llama_backend_init(params.numa);
 
     // load the model
     if (!llama->load_model(params)) {
@@ -209,6 +208,7 @@ void llama_server_completion(const char *json_req, ext_server_resp_t *resp) {
 void llama_server_completion_next_result(const int task_id,
                                          ext_server_task_result_t *resp) {
   assert(llama != NULL && resp != NULL);
+  std::string msg;
   resp->id = -1;
   resp->stop = false;
   resp->error = false;

llm/ext_server/ext_server.h

@@ -41,7 +41,7 @@ typedef struct ext_server_params {
   int32_t main_gpu;      // the GPU that is used for scratch and small tensors
   bool use_mlock;        // force system to keep model in RAM
   bool use_mmap;         // use mmap if possible
-  int numa;              // attempt optimizations that help on some NUMA systems
+  bool numa;             // attempt optimizations that help on some NUMA systems
   bool embedding;        // get only sentence embedding
   ext_server_lora_adapter_t *lora_adapters;
   char *mmproj;

llm/generate/gen_windows.ps1

@@ -154,9 +154,8 @@ apply_patches
 # -DLLAMA_AVX2 -- 2013 Intel Haswell & 2015 AMD Excavator / 2017 AMD Zen
 # -DLLAMA_FMA (FMA3) -- 2013 Intel Haswell & 2012 AMD Piledriver
 
-$script:commonCpuDefs = @("-DCMAKE_POSITION_INDEPENDENT_CODE=on")
+$script:commonCpuDefs = @("-DCMAKE_POSITION_INDEPENDENT_CODE=on", "-DLLAMA_NATIVE=off")
 
-init_vars
 $script:cmakeDefs = $script:commonCpuDefs + @("-DLLAMA_AVX=off", "-DLLAMA_AVX2=off", "-DLLAMA_AVX512=off", "-DLLAMA_FMA=off", "-DLLAMA_F16C=off") + $script:cmakeDefs
 $script:buildDir="${script:llamacppDir}/build/windows/${script:ARCH}/cpu"
 write-host "Building LCD CPU"
@@ -165,7 +164,6 @@ install
 sign
 compress_libs
 
-init_vars
 $script:cmakeDefs = $script:commonCpuDefs + @("-DLLAMA_AVX=on", "-DLLAMA_AVX2=off", "-DLLAMA_AVX512=off", "-DLLAMA_FMA=off", "-DLLAMA_F16C=off") + $script:cmakeDefs
 $script:buildDir="${script:llamacppDir}/build/windows/${script:ARCH}/cpu_avx"
 write-host "Building AVX CPU"
@@ -174,7 +172,6 @@ install
 sign
 compress_libs
 
-init_vars
 $script:cmakeDefs = $script:commonCpuDefs + @("-DLLAMA_AVX=on", "-DLLAMA_AVX2=on", "-DLLAMA_AVX512=off", "-DLLAMA_FMA=on", "-DLLAMA_F16C=on") + $script:cmakeDefs
 $script:buildDir="${script:llamacppDir}/build/windows/${script:ARCH}/cpu_avx2"
 write-host "Building AVX2 CPU"

llm/ggml.go

@@ -31,11 +31,6 @@ const (
 	fileTypeQ5_K_S
 	fileTypeQ5_K_M
 	fileTypeQ6_K
-	fileTypeIQ2_XXS
-	fileTypeIQ2_XS
-	fileTypeQ2_K_S
-	fileTypeQ3_K_XS
-	fileTypeIQ3_XXS
 )
 
 func fileType(fileType uint32) string {
@@ -74,16 +69,6 @@ func fileType(fileType uint32) string {
 		return "Q5_K_M"
 	case fileTypeQ6_K:
 		return "Q6_K"
-	case fileTypeIQ2_XXS:
-		return "IQ2_XXS"
-	case fileTypeIQ2_XS:
-		return "IQ2_XS"
-	case fileTypeQ2_K_S:
-		return "Q2_K_S"
-	case fileTypeQ3_K_XS:
-		return "Q3_K_XS"
-	case fileTypeIQ3_XXS:
-		return "IQ3_XXS"
 	default:
 		return "unknown"
 	}

llm/gguf.go

@@ -115,14 +115,6 @@ func (t tensor) typeSize() uint64 {
 		return 2 + 2 + 12 + blockSize/8 + blockSize/2
 	case 14: // Q6_K
 		return blockSize/2 + blockSize/4 + blockSize/16 + 2
-	case 15: // Q8_K
-		return 2 + blockSize + 2*blockSize/16
-	case 16: // IQ2_XXS
-		return 2 + 2*blockSize/8
-	case 17: // IQ2_XS
-		return 2 + 2*blockSize/8 + blockSize/32
-	case 18: // IQ3_XXS
-		return 2 + 3*blockSize/8
 	default:
 		return 0
 	}

llm/patches/02-shutdown.diff

@@ -0,0 +1,96 @@
+diff --git a/examples/server/server.cpp b/examples/server/server.cpp
+index a0b46970..7800c6e7 100644
+--- a/examples/server/server.cpp
++++ b/examples/server/server.cpp
+@@ -28,6 +28,7 @@
+ #include <chrono>
+ #include <condition_variable>
+ #include <atomic>
++#include <signal.h>
+ 
+ using json = nlohmann::json;
+ 
+@@ -2511,6 +2512,9 @@ static void append_to_generated_text_from_generated_token_probs(llama_server_con
+     }
+ }
+ 
++std::function<void(int)> shutdown_handler;
++inline void signal_handler(int signal) { shutdown_handler(signal); }
++
+ int main(int argc, char **argv)
+ {
+ #if SERVER_VERBOSE != 1
+@@ -3128,8 +3132,25 @@ int main(int argc, char **argv)
+         std::placeholders::_2,
+         std::placeholders::_3
+     ));
+-    llama.queue_tasks.start_loop();
+ 
++    shutdown_handler = [&](int) {
++        llama.queue_tasks.terminate();
++    };
++
++#if defined (__unix__) || (defined (__APPLE__) && defined (__MACH__))
++    struct sigaction sigint_action;
++    sigint_action.sa_handler = signal_handler;
++    sigemptyset (&sigint_action.sa_mask);
++    sigint_action.sa_flags = 0;
++    sigaction(SIGINT, &sigint_action, NULL);
++#elif defined (_WIN32)
++    auto console_ctrl_handler = +[](DWORD ctrl_type) -> BOOL {
++        return (ctrl_type == CTRL_C_EVENT) ? (signal_handler(SIGINT), true) : false;
++    };
++    SetConsoleCtrlHandler(reinterpret_cast<PHANDLER_ROUTINE>(console_ctrl_handler), true);
++#endif
++    llama.queue_tasks.start_loop();
++    svr.stop();
+     t.join();
+ 
+     llama_backend_free();
+diff --git a/examples/server/utils.hpp b/examples/server/utils.hpp
+index 54854896..0ee670db 100644
+--- a/examples/server/utils.hpp
++++ b/examples/server/utils.hpp
+@@ -220,6 +220,7 @@ inline std::string format_chatml(std::vector<json> messages)
+ struct llama_server_queue {
+     int id = 0;
+     std::mutex mutex_tasks;
++    bool running;
+     // queues
+     std::vector<task_server> queue_tasks;
+     std::vector<task_server> queue_tasks_deferred;
+@@ -278,9 +279,18 @@ struct llama_server_queue {
+         queue_tasks_deferred.clear();
+     }
+ 
+-    // Start the main loop. This call is blocking
+-    [[noreturn]]
++    // end the start_loop routine
++    void terminate() {
++        {
++            std::unique_lock<std::mutex> lock(mutex_tasks);
++            running = false;
++        }
++        condition_tasks.notify_all();
++    }
++
++    // Start the main loop.
+     void start_loop() {
++        running = true;
+         while (true) {
+             // new task arrived
+             LOG_VERBOSE("have new task", {});
+@@ -324,8 +334,12 @@ struct llama_server_queue {
+             {
+                 std::unique_lock<std::mutex> lock(mutex_tasks);
+                 if (queue_tasks.empty()) {
++                    if (!running) {
++                        LOG_VERBOSE("ending start_loop", {});
++                        return;
++                    }
+                     condition_tasks.wait(lock, [&]{
+-                        return !queue_tasks.empty();
++                        return (!queue_tasks.empty() || !running);
+                     });
+                 }
+             }

llm/patches/03-cudaleaks.diff

@@ -1,29 +1,30 @@
 diff --git a/examples/server/server.cpp b/examples/server/server.cpp
-index 7800c6e7..be30db23 100644
+index 3102762c..568ac1d0 100644
 --- a/examples/server/server.cpp
 +++ b/examples/server/server.cpp
-@@ -30,6 +30,10 @@
- #include <atomic>
- #include <signal.h>
+@@ -307,6 +307,10 @@ struct llama_client_slot
+     }
+ };
  
 +#ifdef GGML_USE_CUBLAS
 +extern "C" GGML_CALL void ggml_free_cublas(void);
 +#endif
 +
- using json = nlohmann::json;
- 
- struct server_params
-@@ -353,6 +357,9 @@ struct llama_server_context
+ struct llama_server_context
+ {
+     llama_model *model = nullptr;
+@@ -353,6 +357,10 @@ struct llama_server_context
              llama_free_model(model);
              model = nullptr;
          }
 +#ifdef GGML_USE_CUBLAS
 +        ggml_free_cublas();
 +#endif
++
      }
  
      bool load_model(const gpt_params &params_)
-@@ -3143,6 +3150,7 @@ int main(int argc, char **argv)
+@@ -3093,6 +3101,7 @@ int main(int argc, char **argv)
      sigemptyset (&sigint_action.sa_mask);
      sigint_action.sa_flags = 0;
      sigaction(SIGINT, &sigint_action, NULL);
@@ -31,8 +32,13 @@ index 7800c6e7..be30db23 100644
  #elif defined (_WIN32)
      auto console_ctrl_handler = +[](DWORD ctrl_type) -> BOOL {
          return (ctrl_type == CTRL_C_EVENT) ? (signal_handler(SIGINT), true) : false;
+@@ -3106,3 +3115,4 @@ int main(int argc, char **argv)
+     llama_backend_free();
+     return 0;
+ }
++
 diff --git a/ggml-cuda.cu b/ggml-cuda.cu
-index 933ebbc4..88a4f664 100644
+index 96976f24..3543920e 100644
 --- a/ggml-cuda.cu
 +++ b/ggml-cuda.cu
 @@ -39,6 +39,7 @@
@@ -43,30 +49,30 @@ index 933ebbc4..88a4f664 100644
  #define cublasGemmEx hipblasGemmEx
  #define cublasGemmBatchedEx hipblasGemmBatchedEx
  #define cublasGemmStridedBatchedEx hipblasGemmStridedBatchedEx
-@@ -7991,10 +7992,10 @@ GGML_CALL bool ggml_cublas_loaded(void) {
+@@ -7928,10 +7929,11 @@ GGML_CALL bool ggml_cublas_loaded(void) {
      return g_cublas_loaded;
  }
  
--GGML_CALL void ggml_init_cublas() {
--    static bool initialized = false;
 +static bool g_cublas_initialized = false;
++
+ GGML_CALL void ggml_init_cublas() {
+-    static bool initialized = false;
  
 -    if (!initialized) {
-+GGML_CALL void ggml_init_cublas() {
 +    if (!g_cublas_initialized) {
  
  #ifdef __HIP_PLATFORM_AMD__
          // Workaround for a rocBLAS bug when using multiple graphics cards:
-@@ -8004,7 +8005,7 @@ GGML_CALL void ggml_init_cublas() {
+@@ -7941,7 +7943,7 @@ GGML_CALL void ggml_init_cublas() {
  #endif
  
          if (cudaGetDeviceCount(&g_device_count) != cudaSuccess) {
 -            initialized = true;
 +            g_cublas_initialized = true;
              g_cublas_loaded = false;
-             fprintf(stderr, "%s: no " GGML_CUDA_NAME " devices found, " GGML_CUDA_NAME " will be disabled\n", __func__);
              return;
-@@ -8075,7 +8076,7 @@ GGML_CALL void ggml_init_cublas() {
+         }
+@@ -8011,7 +8013,7 @@ GGML_CALL void ggml_init_cublas() {
          // configure logging to stdout
          // CUBLAS_CHECK(cublasLoggerConfigure(1, 1, 0, nullptr));
  
@@ -75,30 +81,25 @@ index 933ebbc4..88a4f664 100644
          g_cublas_loaded = true;
      }
  }
-@@ -11604,3 +11605,23 @@ GGML_CALL int ggml_backend_cuda_reg_devices() {
+@@ -11528,3 +11530,17 @@ GGML_CALL int ggml_backend_cuda_reg_devices() {
      }
      return device_count;
  }
 +
-+
 +extern "C" GGML_CALL void ggml_free_cublas(void);
 +GGML_CALL void ggml_free_cublas(void) {
 +    for (int id = 0; id < g_device_count; ++id) {
-+#if !(defined(GGML_USE_HIPBLAS) && defined(__HIP_PLATFORM_AMD__))
-+        if (g_device_caps[id].vmm) {
-+            CU_CHECK(cuMemUnmap(g_cuda_pool_addr[id], g_cuda_pool_size[id]));
-+            g_cuda_pool_size[id] = 0;
-+            g_cuda_pool_addr[id] = 0;
-+        }
++#if !defined(GGML_USE_HIPBLAS)
++        CU_CHECK(cuMemUnmap(g_cuda_pool_addr[id], g_cuda_pool_size[id]));
++        g_cuda_pool_size[id] = 0;
++        g_cuda_pool_addr[id] = 0;
 +#endif
-+        // TODO: free legacy non-vmm memory
-+        // destroy cublas handle
 +        CUBLAS_CHECK(cublasDestroy(g_cublas_handles[id]));
 +        g_cublas_handles[id] = nullptr;
 +    }
-+
 +    g_cublas_initialized = false;
 +}
+\ No newline at end of file
 diff --git a/ggml-cuda.h b/ggml-cuda.h
 index b1ebd61d..b4c80c2c 100644
 --- a/ggml-cuda.h

scripts/build_windows.ps1

@@ -53,14 +53,13 @@ function buildOllama() {
     write-host "Building ollama CLI"
     & go generate ./...
     if ($LASTEXITCODE -ne 0) { exit($LASTEXITCODE)}
-    & go build -ldflags "-X=github.com/jmorganca/ollama/version.Version=$script:VERSION -X=github.com/jmorganca/ollama/server.mode=release" .
+    & go build "-ldflags=-w -s ""-X=github.com/jmorganca/ollama/version.Version=$script:VERSION"" ""-X=github.com/jmorganca/ollama/server.mode=release""" .
     if ($LASTEXITCODE -ne 0) { exit($LASTEXITCODE)}
     if ("${env:KEY_CONTAINER}") {
         & "${script:SignTool}" sign /v /fd sha256 /t http://timestamp.digicert.com /f "${script:OLLAMA_CERT}" `
             /csp "Google Cloud KMS Provider" /kc ${env:KEY_CONTAINER} ollama.exe
         if ($LASTEXITCODE -ne 0) { exit($LASTEXITCODE)}
     }
-    New-Item -ItemType Directory -Path .\dist -Force
     cp .\ollama.exe .\dist\ollama-windows-amd64.exe
 }
 
@@ -68,7 +67,7 @@ function buildApp() {
     write-host "Building Ollama App"
     cd "${script:SRC_DIR}\app"
     & windres -l 0 -o ollama.syso ollama.rc
-    & go build -ldflags "-H windowsgui -X=github.com/jmorganca/ollama/version.Version=$script:VERSION -X=github.com/jmorganca/ollama/server.mode=release" .
+    & go build "-ldflags=-H windowsgui -w -s ""-X=github.com/jmorganca/ollama/version.Version=$script:VERSION"" ""-X=github.com/jmorganca/ollama/server.mode=release""" .
     if ($LASTEXITCODE -ne 0) { exit($LASTEXITCODE)}
     if ("${env:KEY_CONTAINER}") {
         & "${script:SignTool}" sign /v /fd sha256 /t http://timestamp.digicert.com /f "${script:OLLAMA_CERT}" `
@@ -130,4 +129,4 @@ try {
 } finally {
     set-location $script:SRC_DIR
     $env:PKG_VERSION=""
-}
+}

scripts/install.sh

@@ -72,7 +72,7 @@ $SUDO install -o0 -g0 -m755 -d $BINDIR
 $SUDO install -o0 -g0 -m755 $TEMP_DIR/ollama $BINDIR/ollama
 
 install_success() { 
-    status 'The Ollama API is now available at 127.0.0.1:11434.'
+    status 'The Ollama API is now available at 0.0.0.0:11434.'
     status 'Install complete. Run "ollama" from the command line.'
 }
 trap install_success EXIT

server/images.go

@@ -52,10 +52,6 @@ type Model struct {
 	Messages       []Message
 }
 
-func (m *Model) IsEmbedding() bool {
-	return slices.Contains(m.Config.ModelFamilies, "bert") || slices.Contains(m.Config.ModelFamilies, "nomic-bert")
-}
-
 type Message struct {
 	Role    string `json:"role"`
 	Content string `json:"content"`
@@ -1107,7 +1103,18 @@ func makeRequest(ctx context.Context, method string, requestURL *url.URL, header
 		req.ContentLength = contentLength
 	}
 
-	resp, err := http.DefaultClient.Do(req)
+	proxyURL, err := http.ProxyFromEnvironment(req)
+	if err != nil {
+		return nil, err
+	}
+
+	client := http.Client{
+		Transport: &http.Transport{
+			Proxy: http.ProxyURL(proxyURL),
+		},
+	}
+
+	resp, err := client.Do(req)
 	if err != nil {
 		return nil, err
 	}

server/routes.go

@@ -191,11 +191,6 @@ func GenerateHandler(c *gin.Context) {
 		return
 	}
 
-	if model.IsEmbedding() {
-		c.AbortWithStatusJSON(http.StatusBadRequest, gin.H{"error": "embedding models do not support generate"})
-		return
-	}
-
 	opts, err := modelOptions(model, req.Options)
 	if err != nil {
 		if errors.Is(err, api.ErrInvalidOpts) {
@@ -1148,11 +1143,6 @@ func ChatHandler(c *gin.Context) {
 		return
 	}
 
-	if model.IsEmbedding() {
-		c.AbortWithStatusJSON(http.StatusBadRequest, gin.H{"error": "embedding models do not support chat"})
-		return
-	}
-
 	opts, err := modelOptions(model, req.Options)
 	if err != nil {
 		if errors.Is(err, api.ErrInvalidOpts) {

server/upload.go

@@ -12,6 +12,7 @@ import (
 	"net/http"
 	"net/url"
 	"os"
+	"strings"
 	"sync"
 	"sync/atomic"
 	"time"
@@ -176,14 +177,16 @@ func (b *blobUpload) Run(ctx context.Context, opts *registryOptions) {
 	requestURL := <-b.nextURL
 
 	// calculate md5 checksum and add it to the commit request
-	md5sum := md5.New()
+	var sb strings.Builder
 	for _, part := range b.Parts {
-		md5sum.Write(part.Sum(nil))
+		sb.Write(part.Sum(nil))
 	}
 
+	md5sum := md5.Sum([]byte(sb.String()))
+
 	values := requestURL.Query()
 	values.Add("digest", b.Digest)
-	values.Add("etag", fmt.Sprintf("%x-%d", md5sum.Sum(nil), len(b.Parts)))
+	values.Add("etag", fmt.Sprintf("%x-%d", md5sum, len(b.Parts)))
 	requestURL.RawQuery = values.Encode()
 
 	headers := make(http.Header)