OpenAI Delete Endpoint

.github/workflows/release.yaml

@@ -31,7 +31,7 @@ jobs:
           security set-keychain-settings -lut 3600 build.keychain
       - uses: actions/setup-go@v5
         with:
-          go-version: "stable"
+          go-version-file: go.mod
           cache: true
       - name: Build Darwin
         env:
@@ -87,7 +87,7 @@ jobs:
           write-host "plugin installed"
       - uses: actions/setup-go@v5
         with:
-          go-version: "stable"
+          go-version-file: go.mod
           cache: true
       - run: go get ./...
       - run: |
@@ -141,13 +141,13 @@ jobs:
           write-host "plugin installed"
       - uses: actions/setup-go@v5
         with:
-          go-version: "stable"
+          go-version-file: go.mod
           cache: true
       - name: 'Install ROCm'
         run: |
           $ErrorActionPreference = "Stop"
           write-host "downloading AMD HIP Installer"
-          Invoke-WebRequest -Uri "https://download.amd.com/developer/eula/rocm-hub/AMD-Software-PRO-Edition-24.Q3-WinSvr2022-For-HIP.exe" -OutFile "${env:RUNNER_TEMP}\rocm-install.exe"
+          Invoke-WebRequest -Uri "https://download.amd.com/developer/eula/rocm-hub/AMD-Software-PRO-Edition-23.Q4-WinSvr2022-For-HIP.exe" -OutFile "${env:RUNNER_TEMP}\rocm-install.exe"
           write-host "Installing AMD HIP"
           Start-Process "${env:RUNNER_TEMP}\rocm-install.exe" -ArgumentList '-install' -NoNewWindow -Wait
           write-host "Completed AMD HIP"
@@ -218,7 +218,7 @@ jobs:
           write-host "plugin installed"
       - uses: actions/setup-go@v5
         with:
-          go-version: "stable"
+          go-version-file: go.mod
           cache: true
       - name: 'Install CUDA'
         run: |
@@ -306,7 +306,7 @@ jobs:
           write-host "plugin installed"
       - uses: actions/setup-go@v5
         with:
-          go-version: "stable"
+          go-version-file: go.mod
           cache: true
       - run: go get
       - uses: actions/download-artifact@v4
@@ -437,7 +437,6 @@ jobs:
     env:
       OLLAMA_SKIP_IMAGE_BUILD: '1'
       PUSH: '1'
-      GH_TOKEN: ${{ github.token }}
     steps:
       - uses: actions/checkout@v4
       - name: Set Version
@@ -461,20 +460,15 @@ jobs:
           ls -lh dist/
           (cd dist; sha256sum * > sha256sum.txt)
           cat dist/sha256sum.txt
-      - name: Create or update Release
-        run: |
-          echo "Looking for existing release for ${{ env.RELEASE_VERSION }}"
-          OLD_TAG=$(gh release ls --json name,tagName | jq -r ".[] | select(.name == \"${{ env.RELEASE_VERSION }}\") | .tagName")
-          if [ -n "$OLD_TAG" ]; then
-            echo "Updating release ${{ env.RELEASE_VERSION }} to point to new tag ${GITHUB_REF_NAME}"
-            gh release edit ${OLD_TAG} --tag ${GITHUB_REF_NAME}
-          else
-            echo "Creating new release ${{ env.RELEASE_VERSION }} pointing to tag ${GITHUB_REF_NAME}"
-            gh release create ${GITHUB_REF_NAME} \
-              --title ${{ env.RELEASE_VERSION }} \
-              --draft \
-              --generate-notes \
-              --prerelease
-          fi
-          echo "Uploading artifacts for tag ${GITHUB_REF_NAME}"
-          gh release upload ${GITHUB_REF_NAME} dist/* --clobber
+      - uses: ncipollo/release-action@v1
+        with:
+          name: ${{ env.RELEASE_VERSION }}
+          allowUpdates: true
+          artifacts: 'dist/*'
+          draft: true
+          prerelease: true
+          omitBodyDuringUpdate: true
+          generateReleaseNotes: true
+          omitDraftDuringUpdate: true
+          omitPrereleaseDuringUpdate: true
+          replacesArtifacts: true

.github/workflows/test.yaml

@@ -58,12 +58,11 @@ jobs:
     runs-on: ${{ matrix.os }}
     env:
       GOARCH: ${{ matrix.arch }}
-      CGO_ENABLED: '1'
     steps:
       - uses: actions/checkout@v4
       - uses: actions/setup-go@v5
         with:
-          go-version: "stable"
+          go-version-file: go.mod
           cache: true
       - run: go get ./...
       - run: |
@@ -80,7 +79,6 @@ jobs:
       - run: go generate -x ./...
         if: ${{ ! startsWith(matrix.os, 'windows-') }}
         name: 'Unix Go Generate'
-      - run: go build .
       - uses: actions/upload-artifact@v4
         with:
           name: ${{ matrix.os }}-${{ matrix.arch }}-libraries
@@ -126,7 +124,7 @@ jobs:
     strategy:
       matrix:
         rocm-version:
-          - '6.1.2'
+          - '6.0.2'
     runs-on: linux
     container: rocm/dev-ubuntu-20.04:${{ matrix.rocm-version }}
     steps:
@@ -163,13 +161,13 @@ jobs:
       - uses: actions/checkout@v4
       - uses: actions/setup-go@v5
         with:
-          go-version: "stable"
+          go-version-file: go.mod
           cache: true
       - name: 'Install ROCm'
         run: |
           $ErrorActionPreference = "Stop"
           write-host "downloading AMD HIP Installer"
-          Invoke-WebRequest -Uri "https://download.amd.com/developer/eula/rocm-hub/AMD-Software-PRO-Edition-24.Q3-WinSvr2022-For-HIP.exe" -OutFile "${env:RUNNER_TEMP}\rocm-install.exe"
+          Invoke-WebRequest -Uri "https://download.amd.com/developer/eula/rocm-hub/AMD-Software-PRO-Edition-23.Q4-WinSvr2022-For-HIP.exe" -OutFile "${env:RUNNER_TEMP}\rocm-install.exe"
           write-host "Installing AMD HIP"
           Start-Process "${env:RUNNER_TEMP}\rocm-install.exe" -ArgumentList '-install' -NoNewWindow -Wait
           write-host "Completed AMD HIP"
@@ -200,7 +198,7 @@ jobs:
       - uses: actions/checkout@v4
       - uses: actions/setup-go@v5
         with:
-          go-version: "stable"
+          go-version-file: go.mod
           cache: true
       - name: 'Install CUDA'
         run: |
@@ -255,7 +253,7 @@ jobs:
           submodules: recursive
       - uses: actions/setup-go@v5
         with:
-          go-version: "stable"
+          go-version-file: go.mod
           cache: false
       - run: |
           case ${{ matrix.arch }} in
@@ -297,7 +295,7 @@ jobs:
           submodules: recursive
       - uses: actions/setup-go@v5
         with:
-          go-version: "stable"
+          go-version-file: go.mod
           cache: true
       - run: |
           case ${{ matrix.arch }} in

Dockerfile

@@ -1,8 +1,8 @@
-ARG GOLANG_VERSION=1.22.5
+ARG GOLANG_VERSION=1.22.1
 ARG CMAKE_VERSION=3.22.1
 # this CUDA_VERSION corresponds with the one specified in docs/gpu.md
 ARG CUDA_VERSION=11.3.1
-ARG ROCM_VERSION=6.1.2
+ARG ROCM_VERSION=6.0.2
 
 # Copy the minimal context we need to run the generate scripts
 FROM scratch AS llm-code
@@ -70,12 +70,12 @@ RUN OLLAMA_SKIP_STATIC_GENERATE=1 OLLAMA_CPU_TARGET="cpu_avx" sh gen_linux.sh
 FROM --platform=linux/amd64 cpu-builder-amd64 AS cpu_avx2-build-amd64
 RUN OLLAMA_SKIP_STATIC_GENERATE=1 OLLAMA_CPU_TARGET="cpu_avx2" sh gen_linux.sh
 
-FROM --platform=linux/arm64 rockylinux:8 AS cpu-builder-arm64
+FROM --platform=linux/arm64 centos:7 AS cpu-builder-arm64
 ARG CMAKE_VERSION
 ARG GOLANG_VERSION
 COPY ./scripts/rh_linux_deps.sh /
 RUN CMAKE_VERSION=${CMAKE_VERSION} GOLANG_VERSION=${GOLANG_VERSION} sh /rh_linux_deps.sh
-ENV PATH /opt/rh/gcc-toolset-10/root/usr/bin:$PATH
+ENV PATH /opt/rh/devtoolset-10/root/usr/bin:$PATH
 COPY --from=llm-code / /go/src/github.com/ollama/ollama/
 ARG OLLAMA_CUSTOM_CPU_DEFS
 ARG CGO_CFLAGS

README.md

@@ -35,10 +35,10 @@ The official [Ollama Docker image](https://hub.docker.com/r/ollama/ollama) `olla
 
 ## Quickstart
 
-To run and chat with [Llama 3.1](https://ollama.com/library/llama3.1):
+To run and chat with [Llama 3](https://ollama.com/library/llama3):
 
 ```
-ollama run llama3.1
+ollama run llama3
 ```
 
 ## Model library
@@ -49,13 +49,12 @@ Here are some example models that can be downloaded:
 
 | Model              | Parameters | Size  | Download                       |
 | ------------------ | ---------- | ----- | ------------------------------ |
-| Llama 3.1          | 8B         | 4.7GB | `ollama run llama3.1`          |
-| Llama 3.1          | 70B        | 40GB  | `ollama run llama3.1:70b`      |
-| Llama 3.1          | 405B       | 231GB | `ollama run llama3.1:405b`     |
+| Llama 3            | 8B         | 4.7GB | `ollama run llama3`            |
+| Llama 3            | 70B        | 40GB  | `ollama run llama3:70b`        |
 | Phi 3 Mini         | 3.8B       | 2.3GB | `ollama run phi3`              |
 | Phi 3 Medium       | 14B        | 7.9GB | `ollama run phi3:medium`       |
-| Gemma 2            | 9B         | 5.5GB | `ollama run gemma2`            |
-| Gemma 2            | 27B        | 16GB  | `ollama run gemma2:27b`        |
+| Gemma              | 2B         | 1.4GB | `ollama run gemma:2b`          |
+| Gemma              | 7B         | 4.8GB | `ollama run gemma:7b`          |
 | Mistral            | 7B         | 4.1GB | `ollama run mistral`           |
 | Moondream 2        | 1.4B       | 829MB | `ollama run moondream`         |
 | Neural Chat        | 7B         | 4.1GB | `ollama run neural-chat`       |
@@ -65,8 +64,7 @@ Here are some example models that can be downloaded:
 | LLaVA              | 7B         | 4.5GB | `ollama run llava`             |
 | Solar              | 10.7B      | 6.1GB | `ollama run solar`             |
 
-> [!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.
+> 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.
 
 ## Customize a model
 
@@ -98,16 +96,16 @@ See the [guide](docs/import.md) on importing models for more information.
 
 ### Customize a prompt
 
-Models from the Ollama library can be customized with a prompt. For example, to customize the `llama3.1` model:
+Models from the Ollama library can be customized with a prompt. For example, to customize the `llama3` model:
 
 ```
-ollama pull llama3.1
+ollama pull llama3
 ```
 
 Create a `Modelfile`:
 
 ```
-FROM llama3.1
+FROM llama3
 
 # set the temperature to 1 [higher is more creative, lower is more coherent]
 PARAMETER temperature 1
@@ -142,7 +140,7 @@ ollama create mymodel -f ./Modelfile
 ### Pull a model
 
 ```
-ollama pull llama3.1
+ollama pull llama3
 ```
 
 > This command can also be used to update a local model. Only the diff will be pulled.
@@ -150,13 +148,13 @@ ollama pull llama3.1
 ### Remove a model
 
 ```
-ollama rm llama3.1
+ollama rm llama3
 ```
 
 ### Copy a model
 
 ```
-ollama cp llama3.1 my-model
+ollama cp llama3 my-model
 ```
 
 ### Multiline input
@@ -173,23 +171,17 @@ I'm a basic program that prints the famous "Hello, world!" message to the consol
 ### Multimodal models
 
 ```
-ollama run llava "What's in this image? /Users/jmorgan/Desktop/smile.png"
+>>> What's in this image? /Users/jmorgan/Desktop/smile.png
 The image features a yellow smiley face, which is likely the central focus of the picture.
 ```
 
 ### Pass the prompt as an argument
 
 ```
-$ ollama run llama3.1 "Summarize this file: $(cat README.md)"
+$ ollama run llama3 "Summarize this file: $(cat README.md)"
  Ollama is a lightweight, extensible framework for building and running language models on the local machine. It provides a simple API for creating, running, and managing models, as well as a library of pre-built models that can be easily used in a variety of applications.
 ```
 
-### Show model information
-
-```
-ollama show llama3.1
-```
-
 ### List models on your computer
 
 ```
@@ -215,7 +207,7 @@ Next, start the server:
 Finally, in a separate shell, run a model:
 
 ```
-./ollama run llama3.1
+./ollama run llama3
 ```
 
 ## REST API
@@ -226,7 +218,7 @@ Ollama has a REST API for running and managing models.
 
 ```
 curl http://localhost:11434/api/generate -d '{
-  "model": "llama3.1",
+  "model": "llama3",
   "prompt":"Why is the sky blue?"
 }'
 ```
@@ -235,7 +227,7 @@ curl http://localhost:11434/api/generate -d '{
 
 ```
 curl http://localhost:11434/api/chat -d '{
-  "model": "llama3.1",
+  "model": "llama3",
   "messages": [
     { "role": "user", "content": "why is the sky blue?" }
   ]
@@ -294,11 +286,6 @@ See the [API documentation](./docs/api.md) for all endpoints.
 - [Olpaka](https://github.com/Otacon/olpaka) (User-friendly Flutter Web App for Ollama)
 - [OllamaSpring](https://github.com/CrazyNeil/OllamaSpring) (Ollama Client for macOS)
 - [LLocal.in](https://github.com/kartikm7/llocal) (Easy to use Electron Desktop Client for Ollama)
-- [Ollama with Google Mesop](https://github.com/rapidarchitect/ollama_mesop/) (Mesop Chat Client implementation with Ollama)
-- [Kerlig AI](https://www.kerlig.com/) (AI writing assistant for macOS)
-- [AI Studio](https://github.com/MindWorkAI/AI-Studio)
-- [Sidellama](https://github.com/gyopak/sidellama) (browser-based LLM client)
-- [LLMStack](https://github.com/trypromptly/LLMStack) (No-code multi-agent framework to build LLM agents and workflows)
 
 ### Terminal
 
@@ -390,7 +377,7 @@ See the [API documentation](./docs/api.md) for all endpoints.
 - [Llama Coder](https://github.com/ex3ndr/llama-coder) (Copilot alternative using Ollama)
 - [Ollama Copilot](https://github.com/bernardo-bruning/ollama-copilot) (Proxy that allows you to use ollama as a copilot like Github copilot)
 - [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 Hugging Face)
+- [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)
 - [AI Telegram Bot](https://github.com/tusharhero/aitelegrambot) (Telegram bot using Ollama in backend)
 - [AI ST Completion](https://github.com/yaroslavyaroslav/OpenAI-sublime-text) (Sublime Text 4 AI assistant plugin with Ollama support)

api/client.go

@@ -347,16 +347,7 @@ func (c *Client) Heartbeat(ctx context.Context) error {
 	return nil
 }
 
-// Embed generates embeddings from a model.
-func (c *Client) Embed(ctx context.Context, req *EmbedRequest) (*EmbedResponse, error) {
-	var resp EmbedResponse
-	if err := c.do(ctx, http.MethodPost, "/api/embed", req, &resp); err != nil {
-		return nil, err
-	}
-	return &resp, nil
-}
-
-// Embeddings generates an embedding from a model.
+// Embeddings generates embeddings from a model.
 func (c *Client) Embeddings(ctx context.Context, req *EmbeddingRequest) (*EmbeddingResponse, error) {
 	var resp EmbeddingResponse
 	if err := c.do(ctx, http.MethodPost, "/api/embeddings", req, &resp); err != nil {

api/types.go

@@ -47,9 +47,6 @@ type GenerateRequest struct {
 	// Prompt is the textual prompt to send to the model.
 	Prompt string `json:"prompt"`
 
-	// Suffix is the text that comes after the inserted text.
-	Suffix string `json:"suffix"`
-
 	// System overrides the model's default system message/prompt.
 	System string `json:"system"`
 
@@ -100,85 +97,17 @@ type ChatRequest struct {
 	// followin the request.
 	KeepAlive *Duration `json:"keep_alive,omitempty"`
 
-	// Tools is an optional list of tools the model has access to.
-	Tools `json:"tools,omitempty"`
-
 	// Options lists model-specific options.
 	Options map[string]interface{} `json:"options"`
 }
 
-type Tools []Tool
-
-func (t Tools) String() string {
-	bts, _ := json.Marshal(t)
-	return string(bts)
-}
-
-func (t Tool) String() string {
-	bts, _ := json.Marshal(t)
-	return string(bts)
-}
-
 // Message is a single message in a chat sequence. The message contains the
 // role ("system", "user", or "assistant"), the content and an optional list
 // of images.
 type Message struct {
-	Role      string      `json:"role"`
-	Content   string      `json:"content"`
-	Images    []ImageData `json:"images,omitempty"`
-	ToolCalls []ToolCall  `json:"tool_calls,omitempty"`
-}
-
-func (m *Message) UnmarshalJSON(b []byte) error {
-	type Alias Message
-	var a Alias
-	if err := json.Unmarshal(b, &a); err != nil {
-		return err
-	}
-
-	*m = Message(a)
-	m.Role = strings.ToLower(m.Role)
-	return nil
-}
-
-type ToolCall struct {
-	Function ToolCallFunction `json:"function"`
-}
-
-type ToolCallFunction struct {
-	Name      string                    `json:"name"`
-	Arguments ToolCallFunctionArguments `json:"arguments"`
-}
-
-type ToolCallFunctionArguments map[string]any
-
-func (t *ToolCallFunctionArguments) String() string {
-	bts, _ := json.Marshal(t)
-	return string(bts)
-}
-
-type Tool struct {
-	Type     string       `json:"type"`
-	Function ToolFunction `json:"function"`
-}
-
-type ToolFunction struct {
-	Name        string `json:"name"`
-	Description string `json:"description"`
-	Parameters  struct {
-		Type       string   `json:"type"`
-		Required   []string `json:"required"`
-		Properties map[string]struct {
-			Type        string   `json:"type"`
-			Description string   `json:"description"`
-			Enum        []string `json:"enum,omitempty"`
-		} `json:"properties"`
-	} `json:"parameters"`
-}
-
-func (t *ToolFunction) String() string {
-	bts, _ := json.Marshal(t)
-	return string(bts)
+	Role    string      `json:"role"`
+	Content string      `json:"content"`
+	Images  []ImageData `json:"images,omitempty"`
 }
 
 // ChatResponse is the response returned by [Client.Chat]. Its fields are
@@ -214,7 +143,6 @@ type Options struct {
 	NumPredict       int      `json:"num_predict,omitempty"`
 	TopK             int      `json:"top_k,omitempty"`
 	TopP             float32  `json:"top_p,omitempty"`
-	MinP             float32  `json:"min_p,omitempty"`
 	TFSZ             float32  `json:"tfs_z,omitempty"`
 	TypicalP         float32  `json:"typical_p,omitempty"`
 	RepeatLastN      int      `json:"repeat_last_n,omitempty"`
@@ -231,46 +159,18 @@ type Options struct {
 
 // Runner options which must be set when the model is loaded into memory
 type Runner struct {
-	UseNUMA   bool  `json:"numa,omitempty"`
-	NumCtx    int   `json:"num_ctx,omitempty"`
-	NumBatch  int   `json:"num_batch,omitempty"`
-	NumGPU    int   `json:"num_gpu,omitempty"`
-	MainGPU   int   `json:"main_gpu,omitempty"`
-	LowVRAM   bool  `json:"low_vram,omitempty"`
-	F16KV     bool  `json:"f16_kv,omitempty"`
-	LogitsAll bool  `json:"logits_all,omitempty"`
-	VocabOnly bool  `json:"vocab_only,omitempty"`
-	UseMMap   *bool `json:"use_mmap,omitempty"`
-	UseMLock  bool  `json:"use_mlock,omitempty"`
-	NumThread int   `json:"num_thread,omitempty"`
-}
-
-// EmbedRequest is the request passed to [Client.Embed].
-type EmbedRequest struct {
-	// Model is the model name.
-	Model string `json:"model"`
-
-	// Input is the input to embed.
-	Input any `json:"input"`
-
-	// KeepAlive controls how long the model will stay loaded in memory following
-	// this request.
-	KeepAlive *Duration `json:"keep_alive,omitempty"`
-
-	Truncate *bool `json:"truncate,omitempty"`
-
-	// Options lists model-specific options.
-	Options map[string]interface{} `json:"options"`
-}
-
-// EmbedResponse is the response from [Client.Embed].
-type EmbedResponse struct {
-	Model      string      `json:"model"`
-	Embeddings [][]float32 `json:"embeddings"`
-
-	TotalDuration   time.Duration `json:"total_duration,omitempty"`
-	LoadDuration    time.Duration `json:"load_duration,omitempty"`
-	PromptEvalCount int           `json:"prompt_eval_count,omitempty"`
+	UseNUMA   bool `json:"numa,omitempty"`
+	NumCtx    int  `json:"num_ctx,omitempty"`
+	NumBatch  int  `json:"num_batch,omitempty"`
+	NumGPU    int  `json:"num_gpu,omitempty"`
+	MainGPU   int  `json:"main_gpu,omitempty"`
+	LowVRAM   bool `json:"low_vram,omitempty"`
+	F16KV     bool `json:"f16_kv,omitempty"`
+	LogitsAll bool `json:"logits_all,omitempty"`
+	VocabOnly bool `json:"vocab_only,omitempty"`
+	UseMMap   bool `json:"use_mmap,omitempty"`
+	UseMLock  bool `json:"use_mlock,omitempty"`
+	NumThread int  `json:"num_thread,omitempty"`
 }
 
 // EmbeddingRequest is the request passed to [Client.Embeddings].
@@ -319,12 +219,9 @@ type DeleteRequest struct {
 
 // ShowRequest is the request passed to [Client.Show].
 type ShowRequest struct {
-	Model  string `json:"model"`
-	System string `json:"system"`
-
-	// Template is deprecated
+	Model    string `json:"model"`
+	System   string `json:"system"`
 	Template string `json:"template"`
-	Verbose  bool   `json:"verbose"`
 
 	Options map[string]interface{} `json:"options"`
 
@@ -334,16 +231,13 @@ type ShowRequest struct {
 
 // ShowResponse is the response returned from [Client.Show].
 type ShowResponse struct {
-	License       string         `json:"license,omitempty"`
-	Modelfile     string         `json:"modelfile,omitempty"`
-	Parameters    string         `json:"parameters,omitempty"`
-	Template      string         `json:"template,omitempty"`
-	System        string         `json:"system,omitempty"`
-	Details       ModelDetails   `json:"details,omitempty"`
-	Messages      []Message      `json:"messages,omitempty"`
-	ModelInfo     map[string]any `json:"model_info,omitempty"`
-	ProjectorInfo map[string]any `json:"projector_info,omitempty"`
-	ModifiedAt    time.Time      `json:"modified_at,omitempty"`
+	License    string       `json:"license,omitempty"`
+	Modelfile  string       `json:"modelfile,omitempty"`
+	Parameters string       `json:"parameters,omitempty"`
+	Template   string       `json:"template,omitempty"`
+	System     string       `json:"system,omitempty"`
+	Details    ModelDetails `json:"details,omitempty"`
+	Messages   []Message    `json:"messages,omitempty"`
 }
 
 // CopyRequest is the request passed to [Client.Copy].
@@ -416,13 +310,6 @@ type ProcessModelResponse struct {
 	SizeVRAM  int64        `json:"size_vram"`
 }
 
-type RetrieveModelResponse struct {
-	Id      string `json:"id"`
-	Object  string `json:"object"`
-	Created int64  `json:"created"`
-	OwnedBy string `json:"owned_by"`
-}
-
 type TokenResponse struct {
 	Token string `json:"token"`
 }
@@ -561,17 +448,6 @@ func (opts *Options) FromMap(m map[string]interface{}) error {
 					slice[i] = str
 				}
 				field.Set(reflect.ValueOf(slice))
-			case reflect.Pointer:
-				var b bool
-				if field.Type() == reflect.TypeOf(&b) {
-					val, ok := val.(bool)
-					if !ok {
-						return fmt.Errorf("option %q must be of type boolean", key)
-					}
-					field.Set(reflect.ValueOf(&val))
-				} else {
-					return fmt.Errorf("unknown type loading config params: %v %v", field.Kind(), field.Type())
-				}
 			default:
 				return fmt.Errorf("unknown type loading config params: %v", field.Kind())
 			}
@@ -614,7 +490,7 @@ func DefaultOptions() Options {
 			LowVRAM:   false,
 			F16KV:     true,
 			UseMLock:  false,
-			UseMMap:   nil,
+			UseMMap:   true,
 			UseNUMA:   false,
 		},
 	}
@@ -711,17 +587,6 @@ func FormatParams(params map[string][]string) (map[string]interface{}, error) {
 				case reflect.Slice:
 					// TODO: only string slices are supported right now
 					out[key] = vals
-				case reflect.Pointer:
-					var b bool
-					if field.Type() == reflect.TypeOf(&b) {
-						boolVal, err := strconv.ParseBool(vals[0])
-						if err != nil {
-							return nil, fmt.Errorf("invalid bool value %s", vals)
-						}
-						out[key] = &boolVal
-					} else {
-						return nil, fmt.Errorf("unknown type %s for %s", field.Kind(), key)
-					}
 				default:
 					return nil, fmt.Errorf("unknown type %s for %s", field.Kind(), key)
 				}

api/types_test.go

@@ -2,7 +2,6 @@ package api
 
 import (
 	"encoding/json"
-	"fmt"
 	"math"
 	"testing"
 	"time"
@@ -106,128 +105,3 @@ func TestDurationMarshalUnmarshal(t *testing.T) {
 		})
 	}
 }
-
-func TestUseMmapParsingFromJSON(t *testing.T) {
-	tr := true
-	fa := false
-	tests := []struct {
-		name string
-		req  string
-		exp  *bool
-	}{
-		{
-			name: "Undefined",
-			req:  `{ }`,
-			exp:  nil,
-		},
-		{
-			name: "True",
-			req:  `{ "use_mmap": true }`,
-			exp:  &tr,
-		},
-		{
-			name: "False",
-			req:  `{ "use_mmap": false }`,
-			exp:  &fa,
-		},
-	}
-
-	for _, test := range tests {
-		t.Run(test.name, func(t *testing.T) {
-			var oMap map[string]interface{}
-			err := json.Unmarshal([]byte(test.req), &oMap)
-			require.NoError(t, err)
-			opts := DefaultOptions()
-			err = opts.FromMap(oMap)
-			require.NoError(t, err)
-			assert.Equal(t, test.exp, opts.UseMMap)
-		})
-	}
-}
-
-func TestUseMmapFormatParams(t *testing.T) {
-	tr := true
-	fa := false
-	tests := []struct {
-		name string
-		req  map[string][]string
-		exp  *bool
-		err  error
-	}{
-		{
-			name: "True",
-			req: map[string][]string{
-				"use_mmap": {"true"},
-			},
-			exp: &tr,
-			err: nil,
-		},
-		{
-			name: "False",
-			req: map[string][]string{
-				"use_mmap": {"false"},
-			},
-			exp: &fa,
-			err: nil,
-		},
-		{
-			name: "Numeric True",
-			req: map[string][]string{
-				"use_mmap": {"1"},
-			},
-			exp: &tr,
-			err: nil,
-		},
-		{
-			name: "Numeric False",
-			req: map[string][]string{
-				"use_mmap": {"0"},
-			},
-			exp: &fa,
-			err: nil,
-		},
-		{
-			name: "invalid string",
-			req: map[string][]string{
-				"use_mmap": {"foo"},
-			},
-			exp: nil,
-			err: fmt.Errorf("invalid bool value [foo]"),
-		},
-	}
-
-	for _, test := range tests {
-		t.Run(test.name, func(t *testing.T) {
-			resp, err := FormatParams(test.req)
-			require.Equal(t, test.err, err)
-			respVal, ok := resp["use_mmap"]
-			if test.exp != nil {
-				assert.True(t, ok, "resp: %v", resp)
-				assert.Equal(t, *test.exp, *respVal.(*bool))
-			}
-		})
-	}
-}
-
-func TestMessage_UnmarshalJSON(t *testing.T) {
-	tests := []struct {
-		input    string
-		expected string
-	}{
-		{`{"role": "USER", "content": "Hello!"}`, "user"},
-		{`{"role": "System", "content": "Initialization complete."}`, "system"},
-		{`{"role": "assistant", "content": "How can I help you?"}`, "assistant"},
-		{`{"role": "TOOl", "content": "Access granted."}`, "tool"},
-	}
-
-	for _, test := range tests {
-		var msg Message
-		if err := json.Unmarshal([]byte(test.input), &msg); err != nil {
-			t.Errorf("Unexpected error: %v", err)
-		}
-
-		if msg.Role != test.expected {
-			t.Errorf("role not lowercased: got %v, expected %v", msg.Role, test.expected)
-		}
-	}
-}

app/lifecycle/logging.go

@@ -5,8 +5,6 @@ import (
 	"log/slog"
 	"os"
 	"path/filepath"
-	"strconv"
-	"strings"
 
 	"github.com/ollama/ollama/envconfig"
 )
@@ -26,7 +24,6 @@ func InitLogging() {
 		logFile = os.Stderr
 		// TODO - write one-line to the app.log file saying we're running in console mode to help avoid confusion
 	} else {
-		rotateLogs(AppLogFile)
 		logFile, err = os.OpenFile(AppLogFile, os.O_APPEND|os.O_WRONLY|os.O_CREATE, 0755)
 		if err != nil {
 			slog.Error(fmt.Sprintf("failed to create server log %v", err))
@@ -49,32 +46,3 @@ func InitLogging() {
 
 	slog.Info("ollama app started")
 }
-
-func rotateLogs(logFile string) {
-	if _, err := os.Stat(logFile); os.IsNotExist(err) {
-		return
-	}
-	index := strings.LastIndex(logFile, ".")
-	pre := logFile[:index]
-	post := "." + logFile[index+1:]
-	for i := LogRotationCount; i > 0; i-- {
-		older := pre + "-" + strconv.Itoa(i) + post
-		newer := pre + "-" + strconv.Itoa(i-1) + post
-		if i == 1 {
-			newer = pre + post
-		}
-		if _, err := os.Stat(newer); err == nil {
-			if _, err := os.Stat(older); err == nil {
-				err := os.Remove(older)
-				if err != nil {
-					slog.Warn("Failed to remove older log", "older", older, "error", err)
-					continue
-				}
-			}
-			err := os.Rename(newer, older)
-			if err != nil {
-				slog.Warn("Failed to rotate log", "older", older, "newer", newer, "error", err)
-			}
-		}
-	}
-}

app/lifecycle/logging_test.go

@@ -1,44 +0,0 @@
-package lifecycle
-
-import (
-	"os"
-	"path/filepath"
-	"strconv"
-	"testing"
-
-	"github.com/stretchr/testify/assert"
-	"github.com/stretchr/testify/require"
-)
-
-func TestRotateLogs(t *testing.T) {
-	logDir := t.TempDir()
-	logFile := filepath.Join(logDir, "testlog.log")
-
-	// No log exists
-	rotateLogs(logFile)
-
-	require.NoError(t, os.WriteFile(logFile, []byte("1"), 0644))
-	assert.FileExists(t, logFile)
-	// First rotation
-	rotateLogs(logFile)
-	assert.FileExists(t, filepath.Join(logDir, "testlog-1.log"))
-	assert.NoFileExists(t, filepath.Join(logDir, "testlog-2.log"))
-	assert.NoFileExists(t, logFile)
-
-	// Should be a no-op without a new log
-	rotateLogs(logFile)
-	assert.FileExists(t, filepath.Join(logDir, "testlog-1.log"))
-	assert.NoFileExists(t, filepath.Join(logDir, "testlog-2.log"))
-	assert.NoFileExists(t, logFile)
-
-	for i := 2; i <= LogRotationCount+1; i++ {
-		require.NoError(t, os.WriteFile(logFile, []byte(strconv.Itoa(i)), 0644))
-		assert.FileExists(t, logFile)
-		rotateLogs(logFile)
-		assert.NoFileExists(t, logFile)
-		for j := 1; j < i; j++ {
-			assert.FileExists(t, filepath.Join(logDir, "testlog-"+strconv.Itoa(j)+".log"))
-		}
-		assert.NoFileExists(t, filepath.Join(logDir, "testlog-"+strconv.Itoa(i+1)+".log"))
-	}
-}

app/lifecycle/paths.go

@@ -16,12 +16,11 @@ var (
 	AppDir     = "/opt/Ollama"
 	AppDataDir = "/opt/Ollama"
 	// TODO - should there be a distinct log dir?
-	UpdateStageDir   = "/tmp"
-	AppLogFile       = "/tmp/ollama_app.log"
-	ServerLogFile    = "/tmp/ollama.log"
-	UpgradeLogFile   = "/tmp/ollama_update.log"
-	Installer        = "OllamaSetup.exe"
-	LogRotationCount = 5
+	UpdateStageDir = "/tmp"
+	AppLogFile     = "/tmp/ollama_app.log"
+	ServerLogFile  = "/tmp/ollama.log"
+	UpgradeLogFile = "/tmp/ollama_update.log"
+	Installer      = "OllamaSetup.exe"
 )
 
 func init() {

app/lifecycle/server.go

@@ -54,7 +54,7 @@ func start(ctx context.Context, command string) (*exec.Cmd, error) {
 		return nil, fmt.Errorf("failed to spawn server stderr pipe: %w", err)
 	}
 
-	rotateLogs(ServerLogFile)
+	// TODO - rotation
 	logFile, err := os.OpenFile(ServerLogFile, os.O_APPEND|os.O_WRONLY|os.O_CREATE, 0755)
 	if err != nil {
 		return nil, fmt.Errorf("failed to create server log: %w", err)

app/ollama.iss

@@ -88,15 +88,10 @@ DialogFontSize=12
 [Files]
 Source: ".\app.exe"; DestDir: "{app}"; DestName: "{#MyAppExeName}" ; Flags: ignoreversion 64bit
 Source: "..\ollama.exe"; DestDir: "{app}"; Flags: ignoreversion 64bit
+Source: "..\dist\windows-{#ARCH}\*.dll"; DestDir: "{app}"; Flags: ignoreversion 64bit
 Source: "..\dist\windows-{#ARCH}\ollama_runners\*"; DestDir: "{app}\ollama_runners"; Flags: ignoreversion 64bit recursesubdirs
 Source: "..\dist\ollama_welcome.ps1"; DestDir: "{app}"; Flags: ignoreversion
 Source: ".\assets\app.ico"; DestDir: "{app}"; Flags: ignoreversion
-#if DirExists("..\dist\windows-amd64\cuda")
-  Source: "..\dist\windows-amd64\cuda\*"; DestDir: "{app}\cuda\"; Flags: ignoreversion recursesubdirs
-#endif
-#if DirExists("..\dist\windows-amd64\oneapi")
-  Source: "..\dist\windows-amd64\oneapi\*"; DestDir: "{app}\oneapi\"; Flags: ignoreversion recursesubdirs
-#endif
 #if DirExists("..\dist\windows-amd64\rocm")
   Source: "..\dist\windows-amd64\rocm\*"; DestDir: "{app}\rocm\"; Flags: ignoreversion recursesubdirs
 #endif
@@ -127,10 +122,6 @@ Type: filesandordirs; Name: "{%USERPROFILE}\.ollama\models"
 Type: filesandordirs; Name: "{%USERPROFILE}\.ollama\history"
 ; NOTE: if the user has a custom OLLAMA_MODELS it will be preserved
 
-[InstallDelete]
-Type: filesandordirs; Name: "{%TEMP}\ollama*"
-Type: filesandordirs; Name: "{%LOCALAPPDATA}\Programs\Ollama"
-
 [Messages]
 WizardReady=Ollama Windows Preview
 ReadyLabel1=%nLet's get you up and running with your own large language models.
@@ -138,7 +129,7 @@ SetupAppRunningError=Another Ollama installer is running.%n%nPlease cancel or fi
 
 
 ;FinishedHeadingLabel=Run your first model
-;FinishedLabel=%nRun this command in a PowerShell or cmd terminal.%n%n%n    ollama run llama3.1
+;FinishedLabel=%nRun this command in a PowerShell or cmd terminal.%n%n%n    ollama run llama3
 ;ClickFinish=%n
 
 [Registry]

app/ollama_welcome.ps1

@@ -4,5 +4,5 @@ write-host "Welcome to Ollama!"
 write-host ""
 write-host "Run your first model:"
 write-host ""
-write-host "`tollama run llama3.1"
+write-host "`tollama run llama3"
 write-host ""

cmd/cmd.go

@@ -162,6 +162,9 @@ func tempZipFiles(path string) (string, error) {
 	}
 	defer tempfile.Close()
 
+	zipfile := zip.NewWriter(tempfile)
+	defer zipfile.Close()
+
 	detectContentType := func(path string) (string, error) {
 		f, err := os.Open(path)
 		if err != nil {
@@ -230,9 +233,6 @@ func tempZipFiles(path string) (string, error) {
 		files = append(files, tks...)
 	}
 
-	zipfile := zip.NewWriter(tempfile)
-	defer zipfile.Close()
-
 	for _, file := range files {
 		f, err := os.Open(file)
 		if err != nil {
@@ -287,12 +287,38 @@ func createBlob(cmd *cobra.Command, client *api.Client, path string) (string, er
 }
 
 func RunHandler(cmd *cobra.Command, args []string) error {
+	client, err := api.ClientFromEnvironment()
+	if err != nil {
+		return err
+	}
+
+	name := args[0]
+
+	// check if the model exists on the server
+	show, err := client.Show(cmd.Context(), &api.ShowRequest{Name: name})
+	var statusError api.StatusError
+	switch {
+	case errors.As(err, &statusError) && statusError.StatusCode == http.StatusNotFound:
+		if err := PullHandler(cmd, []string{name}); err != nil {
+			return err
+		}
+
+		show, err = client.Show(cmd.Context(), &api.ShowRequest{Name: name})
+		if err != nil {
+			return err
+		}
+	case err != nil:
+		return err
+	}
+
 	interactive := true
 
 	opts := runOptions{
-		Model:    args[0],
-		WordWrap: os.Getenv("TERM") == "xterm-256color",
-		Options:  map[string]interface{}{},
+		Model:       args[0],
+		WordWrap:    os.Getenv("TERM") == "xterm-256color",
+		Options:     map[string]interface{}{},
+		MultiModal:  slices.Contains(show.Details.Families, "clip"),
+		ParentModel: show.Details.ParentModel,
 	}
 
 	format, err := cmd.Flags().GetString("format")
@@ -336,38 +362,11 @@ func RunHandler(cmd *cobra.Command, args []string) error {
 	}
 	opts.WordWrap = !nowrap
 
-	// Fill out the rest of the options based on information about the
-	// model.
-	client, err := api.ClientFromEnvironment()
-	if err != nil {
-		return err
+	if !interactive {
+		return generate(cmd, opts)
 	}
 
-	name := args[0]
-	info, err := func() (*api.ShowResponse, error) {
-		showReq := &api.ShowRequest{Name: name}
-		info, err := client.Show(cmd.Context(), showReq)
-		var se api.StatusError
-		if errors.As(err, &se) && se.StatusCode == http.StatusNotFound {
-			if err := PullHandler(cmd, []string{name}); err != nil {
-				return nil, err
-			}
-			return client.Show(cmd.Context(), &api.ShowRequest{Name: name})
-		}
-		return info, err
-	}()
-	if err != nil {
-		return err
-	}
-
-	opts.MultiModal = slices.Contains(info.Details.Families, "clip")
-	opts.ParentModel = info.Details.ParentModel
-	opts.Messages = append(opts.Messages, info.Messages...)
-
-	if interactive {
-		return generateInteractive(cmd, opts)
-	}
-	return generate(cmd, opts)
+	return generateInteractive(cmd, opts)
 }
 
 func errFromUnknownKey(unknownKeyErr error) error {
@@ -580,6 +579,10 @@ func ShowHandler(cmd *cobra.Command, args []string) error {
 		return err
 	}
 
+	if len(args) != 1 {
+		return errors.New("missing model name")
+	}
+
 	license, errLicense := cmd.Flags().GetBool("license")
 	modelfile, errModelfile := cmd.Flags().GetBool("modelfile")
 	parameters, errParams := cmd.Flags().GetBool("parameters")
@@ -622,6 +625,8 @@ func ShowHandler(cmd *cobra.Command, args []string) error {
 
 	if flagsSet > 1 {
 		return errors.New("only one of '--license', '--modelfile', '--parameters', '--system', or '--template' can be specified")
+	} else if flagsSet == 0 {
+		return errors.New("one of '--license', '--modelfile', '--parameters', '--system', or '--template' must be specified")
 	}
 
 	req := api.ShowRequest{Name: args[0]}
@@ -630,141 +635,22 @@ func ShowHandler(cmd *cobra.Command, args []string) error {
 		return err
 	}
 
-	if flagsSet == 1 {
-		switch showType {
-		case "license":
-			fmt.Println(resp.License)
-		case "modelfile":
-			fmt.Println(resp.Modelfile)
-		case "parameters":
-			fmt.Println(resp.Parameters)
-		case "system":
-			fmt.Println(resp.System)
-		case "template":
-			fmt.Println(resp.Template)
-		}
-
-		return nil
+	switch showType {
+	case "license":
+		fmt.Println(resp.License)
+	case "modelfile":
+		fmt.Println(resp.Modelfile)
+	case "parameters":
+		fmt.Println(resp.Parameters)
+	case "system":
+		fmt.Println(resp.System)
+	case "template":
+		fmt.Println(resp.Template)
 	}
 
-	showInfo(resp)
-
 	return nil
 }
 
-func showInfo(resp *api.ShowResponse) {
-	arch := resp.ModelInfo["general.architecture"].(string)
-
-	modelData := [][]string{
-		{"arch", arch},
-		{"parameters", resp.Details.ParameterSize},
-		{"quantization", resp.Details.QuantizationLevel},
-		{"context length", fmt.Sprintf("%v", resp.ModelInfo[fmt.Sprintf("%s.context_length", arch)].(float64))},
-		{"embedding length", fmt.Sprintf("%v", resp.ModelInfo[fmt.Sprintf("%s.embedding_length", arch)].(float64))},
-	}
-
-	mainTableData := [][]string{
-		{"Model"},
-		{renderSubTable(modelData, false)},
-	}
-
-	if resp.ProjectorInfo != nil {
-		projectorData := [][]string{
-			{"arch", "clip"},
-			{"parameters", format.HumanNumber(uint64(resp.ProjectorInfo["general.parameter_count"].(float64)))},
-		}
-
-		if projectorType, ok := resp.ProjectorInfo["clip.projector_type"]; ok {
-			projectorData = append(projectorData, []string{"projector type", projectorType.(string)})
-		}
-
-		projectorData = append(projectorData,
-			[]string{"embedding length", fmt.Sprintf("%v", resp.ProjectorInfo["clip.vision.embedding_length"].(float64))},
-			[]string{"projection dimensionality", fmt.Sprintf("%v", resp.ProjectorInfo["clip.vision.projection_dim"].(float64))},
-		)
-
-		mainTableData = append(mainTableData,
-			[]string{"Projector"},
-			[]string{renderSubTable(projectorData, false)},
-		)
-	}
-
-	if resp.Parameters != "" {
-		mainTableData = append(mainTableData, []string{"Parameters"}, []string{formatParams(resp.Parameters)})
-	}
-
-	if resp.System != "" {
-		mainTableData = append(mainTableData, []string{"System"}, []string{renderSubTable(twoLines(resp.System), true)})
-	}
-
-	if resp.License != "" {
-		mainTableData = append(mainTableData, []string{"License"}, []string{renderSubTable(twoLines(resp.License), true)})
-	}
-
-	table := tablewriter.NewWriter(os.Stdout)
-	table.SetAutoWrapText(false)
-	table.SetBorder(false)
-	table.SetAlignment(tablewriter.ALIGN_LEFT)
-
-	for _, v := range mainTableData {
-		table.Append(v)
-	}
-
-	table.Render()
-}
-
-func renderSubTable(data [][]string, file bool) string {
-	var buf bytes.Buffer
-	table := tablewriter.NewWriter(&buf)
-	table.SetAutoWrapText(!file)
-	table.SetBorder(false)
-	table.SetNoWhiteSpace(true)
-	table.SetTablePadding("\t")
-	table.SetAlignment(tablewriter.ALIGN_LEFT)
-
-	for _, v := range data {
-		table.Append(v)
-	}
-
-	table.Render()
-
-	renderedTable := buf.String()
-	lines := strings.Split(renderedTable, "\n")
-	for i, line := range lines {
-		lines[i] = "\t" + line
-	}
-
-	return strings.Join(lines, "\n")
-}
-
-func twoLines(s string) [][]string {
-	lines := strings.Split(s, "\n")
-	res := [][]string{}
-
-	count := 0
-	for _, line := range lines {
-		line = strings.TrimSpace(line)
-		if line != "" {
-			count++
-			res = append(res, []string{line})
-			if count == 2 {
-				return res
-			}
-		}
-	}
-	return res
-}
-
-func formatParams(s string) string {
-	lines := strings.Split(s, "\n")
-	table := [][]string{}
-
-	for _, line := range lines {
-		table = append(table, strings.Fields(line))
-	}
-	return renderSubTable(table, false)
-}
-
 func CopyHandler(cmd *cobra.Command, args []string) error {
 	client, err := api.ClientFromEnvironment()
 	if err != nil {
@@ -843,6 +729,7 @@ type runOptions struct {
 	WordWrap    bool
 	Format      string
 	System      string
+	Template    string
 	Images      []api.ImageData
 	Options     map[string]interface{}
 	MultiModal  bool
@@ -1036,6 +923,7 @@ func generate(cmd *cobra.Command, opts runOptions) error {
 		Images:    opts.Images,
 		Format:    opts.Format,
 		System:    opts.System,
+		Template:  opts.Template,
 		Options:   opts.Options,
 		KeepAlive: opts.KeepAlive,
 	}
@@ -1341,10 +1229,10 @@ func NewCLI() *cobra.Command {
 				envVars["OLLAMA_NUM_PARALLEL"],
 				envVars["OLLAMA_NOPRUNE"],
 				envVars["OLLAMA_ORIGINS"],
-				envVars["OLLAMA_SCHED_SPREAD"],
 				envVars["OLLAMA_TMPDIR"],
 				envVars["OLLAMA_FLASH_ATTENTION"],
 				envVars["OLLAMA_LLM_LIBRARY"],
+				envVars["OLLAMA_MAX_VRAM"],
 			})
 		default:
 			appendEnvDocs(cmd, envs)

cmd/interactive.go

@@ -1,7 +1,6 @@
 package cmd
 
 import (
-	"cmp"
 	"errors"
 	"fmt"
 	"io"
@@ -10,14 +9,13 @@ import (
 	"path/filepath"
 	"regexp"
 	"slices"
+	"sort"
 	"strings"
 
 	"github.com/spf13/cobra"
-	"golang.org/x/exp/maps"
 
 	"github.com/ollama/ollama/api"
 	"github.com/ollama/ollama/envconfig"
-	"github.com/ollama/ollama/parser"
 	"github.com/ollama/ollama/progress"
 	"github.com/ollama/ollama/readline"
 	"github.com/ollama/ollama/types/errtypes"
@@ -29,43 +27,69 @@ const (
 	MultilineNone MultilineState = iota
 	MultilinePrompt
 	MultilineSystem
+	MultilineTemplate
 )
 
 func loadModel(cmd *cobra.Command, opts *runOptions) error {
+	client, err := api.ClientFromEnvironment()
+	if err != nil {
+		return err
+	}
+
 	p := progress.NewProgress(os.Stderr)
 	defer p.StopAndClear()
 
 	spinner := progress.NewSpinner("")
 	p.Add("", spinner)
 
-	client, err := api.ClientFromEnvironment()
+	showReq := api.ShowRequest{Name: opts.Model}
+	showResp, err := client.Show(cmd.Context(), &showReq)
 	if err != nil {
 		return err
 	}
+	opts.MultiModal = slices.Contains(showResp.Details.Families, "clip")
+	opts.ParentModel = showResp.Details.ParentModel
 
-	chatReq := &api.ChatRequest{
-		Model:     opts.Model,
-		KeepAlive: opts.KeepAlive,
+	if len(showResp.Messages) > 0 {
+		opts.Messages = append(opts.Messages, showResp.Messages...)
 	}
 
-	return client.Chat(cmd.Context(), chatReq, func(resp api.ChatResponse) error {
+	chatReq := &api.ChatRequest{
+		Model:    opts.Model,
+		Messages: []api.Message{},
+	}
+
+	if opts.KeepAlive != nil {
+		chatReq.KeepAlive = opts.KeepAlive
+	}
+
+	err = client.Chat(cmd.Context(), chatReq, func(resp api.ChatResponse) error {
 		p.StopAndClear()
-		for _, msg := range opts.Messages {
-			switch msg.Role {
-			case "user":
-				fmt.Printf(">>> %s\n", msg.Content)
-			case "assistant":
-				state := &displayResponseState{}
-				displayResponse(msg.Content, opts.WordWrap, state)
-				fmt.Println()
-				fmt.Println()
+		if len(opts.Messages) > 0 {
+			for _, msg := range opts.Messages {
+				switch msg.Role {
+				case "user":
+					fmt.Printf(">>> %s\n", msg.Content)
+				case "assistant":
+					state := &displayResponseState{}
+					displayResponse(msg.Content, opts.WordWrap, state)
+					fmt.Println()
+					fmt.Println()
+				}
 			}
 		}
 		return nil
 	})
+	if err != nil {
+		return err
+	}
+
+	return nil
 }
 
 func generateInteractive(cmd *cobra.Command, opts runOptions) error {
+	opts.Messages = make([]api.Message, 0)
+
 	err := loadModel(cmd, &opts)
 	if err != nil {
 		return err
@@ -95,6 +119,7 @@ func generateInteractive(cmd *cobra.Command, opts runOptions) error {
 		fmt.Fprintln(os.Stderr, "Available Commands:")
 		fmt.Fprintln(os.Stderr, "  /set parameter ...     Set a parameter")
 		fmt.Fprintln(os.Stderr, "  /set system <string>   Set system message")
+		fmt.Fprintln(os.Stderr, "  /set template <string> Set prompt template")
 		fmt.Fprintln(os.Stderr, "  /set history           Enable history")
 		fmt.Fprintln(os.Stderr, "  /set nohistory         Disable history")
 		fmt.Fprintln(os.Stderr, "  /set wordwrap          Enable wordwrap")
@@ -140,7 +165,6 @@ func generateInteractive(cmd *cobra.Command, opts runOptions) error {
 		fmt.Fprintln(os.Stderr, "  /set parameter num_predict <int>      Max number of tokens to predict")
 		fmt.Fprintln(os.Stderr, "  /set parameter top_k <int>            Pick from top k num of tokens")
 		fmt.Fprintln(os.Stderr, "  /set parameter top_p <float>          Pick token based on sum of probabilities")
-		fmt.Fprintln(os.Stderr, "  /set parameter min_p <float>          Pick token based on top token probability * min_p")
 		fmt.Fprintln(os.Stderr, "  /set parameter num_ctx <int>          Set the context size")
 		fmt.Fprintln(os.Stderr, "  /set parameter temperature <float>    Set creativity level")
 		fmt.Fprintln(os.Stderr, "  /set parameter repeat_penalty <float> How strongly to penalize repetitions")
@@ -205,6 +229,10 @@ func generateInteractive(cmd *cobra.Command, opts runOptions) error {
 				opts.Messages = append(opts.Messages, api.Message{Role: "system", Content: opts.System})
 				fmt.Println("Set system message.")
 				sb.Reset()
+			case MultilineTemplate:
+				opts.Template = sb.String()
+				fmt.Println("Set prompt template.")
+				sb.Reset()
 			}
 
 			multiline = MultilineNone
@@ -323,13 +351,17 @@ func generateInteractive(cmd *cobra.Command, opts runOptions) error {
 					}
 					fmt.Printf("Set parameter '%s' to '%s'\n", args[2], strings.Join(params, ", "))
 					opts.Options[args[2]] = fp[args[2]]
-				case "system":
+				case "system", "template":
 					if len(args) < 3 {
 						usageSet()
 						continue
 					}
 
-					multiline = MultilineSystem
+					if args[1] == "system" {
+						multiline = MultilineSystem
+					} else if args[1] == "template" {
+						multiline = MultilineTemplate
+					}
 
 					line := strings.Join(args[2:], " ")
 					line, ok := strings.CutPrefix(line, `"""`)
@@ -349,17 +381,23 @@ func generateInteractive(cmd *cobra.Command, opts runOptions) error {
 						continue
 					}
 
-					opts.System = sb.String() // for display in modelfile
-					newMessage := api.Message{Role: "system", Content: sb.String()}
-					// Check if the slice is not empty and the last message is from 'system'
-					if len(opts.Messages) > 0 && opts.Messages[len(opts.Messages)-1].Role == "system" {
-						// Replace the last message
-						opts.Messages[len(opts.Messages)-1] = newMessage
-					} else {
-						opts.Messages = append(opts.Messages, newMessage)
+					if args[1] == "system" {
+						opts.System = sb.String() // for display in modelfile
+						newMessage := api.Message{Role: "system", Content: sb.String()}
+						// Check if the slice is not empty and the last message is from 'system'
+						if len(opts.Messages) > 0 && opts.Messages[len(opts.Messages)-1].Role == "system" {
+							// Replace the last message
+							opts.Messages[len(opts.Messages)-1] = newMessage
+						} else {
+							opts.Messages = append(opts.Messages, newMessage)
+						}
+						fmt.Println("Set system message.")
+						sb.Reset()
+					} else if args[1] == "template" {
+						opts.Template = sb.String()
+						fmt.Println("Set prompt template.")
+						sb.Reset()
 					}
-					fmt.Println("Set system message.")
-					sb.Reset()
 
 					sb.Reset()
 					continue
@@ -378,9 +416,10 @@ func generateInteractive(cmd *cobra.Command, opts runOptions) error {
 					return err
 				}
 				req := &api.ShowRequest{
-					Name:    opts.Model,
-					System:  opts.System,
-					Options: opts.Options,
+					Name:     opts.Model,
+					System:   opts.System,
+					Template: opts.Template,
+					Options:  opts.Options,
 				}
 				resp, err := client.Show(cmd.Context(), req)
 				if err != nil {
@@ -390,7 +429,15 @@ func generateInteractive(cmd *cobra.Command, opts runOptions) error {
 
 				switch args[1] {
 				case "info":
-					showInfo(resp)
+					fmt.Println("Model details:")
+					if len(resp.Details.Families) > 0 {
+						fmt.Printf("Family              %s\n", strings.Join(resp.Details.Families, ", "))
+					} else if resp.Details.Family != "" {
+						fmt.Printf("Family              %s\n", resp.Details.Family)
+					}
+					fmt.Printf("Parameter Size      %s\n", resp.Details.ParameterSize)
+					fmt.Printf("Quantization Level  %s\n", resp.Details.QuantizationLevel)
+					fmt.Println("")
 				case "license":
 					if resp.License == "" {
 						fmt.Println("No license was specified for this model.")
@@ -423,9 +470,12 @@ func generateInteractive(cmd *cobra.Command, opts runOptions) error {
 						fmt.Println("No system message was specified for this model.")
 					}
 				case "template":
-					if resp.Template != "" {
+					switch {
+					case opts.Template != "":
+						fmt.Println(opts.Template + "\n")
+					case resp.Template != "":
 						fmt.Println(resp.Template)
-					} else {
+					default:
 						fmt.Println("No prompt template was specified for this model.")
 					}
 				default:
@@ -509,35 +559,35 @@ func generateInteractive(cmd *cobra.Command, opts runOptions) error {
 }
 
 func buildModelfile(opts runOptions) string {
-	var f parser.File
-	f.Commands = append(f.Commands, parser.Command{Name: "model", Args: cmp.Or(opts.ParentModel, opts.Model)})
-
+	var mf strings.Builder
+	model := opts.ParentModel
+	if model == "" {
+		model = opts.Model
+	}
+	fmt.Fprintf(&mf, "FROM %s\n", model)
 	if opts.System != "" {
-		f.Commands = append(f.Commands, parser.Command{Name: "system", Args: opts.System})
+		fmt.Fprintf(&mf, "SYSTEM \"\"\"%s\"\"\"\n", opts.System)
 	}
 
-	keys := maps.Keys(opts.Options)
-	slices.Sort(keys)
+	if opts.Template != "" {
+		fmt.Fprintf(&mf, "TEMPLATE \"\"\"%s\"\"\"\n", opts.Template)
+	}
+
+	keys := make([]string, 0)
+	for k := range opts.Options {
+		keys = append(keys, k)
+	}
+	sort.Strings(keys)
 	for _, k := range keys {
-		v := opts.Options[k]
-		var cmds []parser.Command
-		switch t := v.(type) {
-		case []string:
-			for _, s := range t {
-				cmds = append(cmds, parser.Command{Name: k, Args: s})
-			}
-		default:
-			cmds = append(cmds, parser.Command{Name: k, Args: fmt.Sprintf("%v", t)})
-		}
-
-		f.Commands = append(f.Commands, cmds...)
+		fmt.Fprintf(&mf, "PARAMETER %s %v\n", k, opts.Options[k])
 	}
+	fmt.Fprintln(&mf)
 
 	for _, msg := range opts.Messages {
-		f.Commands = append(f.Commands, parser.Command{Name: "message", Args: fmt.Sprintf("%s: %s", msg.Role, msg.Content)})
+		fmt.Fprintf(&mf, "MESSAGE %s \"\"\"%s\"\"\"\n", msg.Role, msg.Content)
 	}
 
-	return f.String()
+	return mf.String()
 }
 
 func normalizeFilePath(fp string) string {

cmd/interactive_test.go

@@ -1,10 +1,12 @@
 package cmd
 
 import (
+	"bytes"
 	"testing"
+	"text/template"
 
-	"github.com/google/go-cmp/cmp"
 	"github.com/stretchr/testify/assert"
+	"github.com/stretchr/testify/require"
 
 	"github.com/ollama/ollama/api"
 )
@@ -55,53 +57,61 @@ d:\path with\spaces\seven.svg inbetween7 c:\users\jdoe\eight.png inbetween8
 
 func TestModelfileBuilder(t *testing.T) {
 	opts := runOptions{
-		Model:  "hork",
-		System: "You are part horse and part shark, but all hork. Do horklike things",
+		Model:    "hork",
+		System:   "You are part horse and part shark, but all hork. Do horklike things",
+		Template: "This is a template.",
 		Messages: []api.Message{
 			{Role: "user", Content: "Hey there hork!"},
 			{Role: "assistant", Content: "Yes it is true, I am half horse, half shark."},
 		},
-		Options: map[string]any{
-			"temperature":      0.9,
-			"seed":             42,
-			"penalize_newline": false,
-			"stop":             []string{"hi", "there"},
-		},
+		Options: map[string]interface{}{},
 	}
 
-	t.Run("model", func(t *testing.T) {
-		expect := `FROM hork
-SYSTEM You are part horse and part shark, but all hork. Do horklike things
+	opts.Options["temperature"] = 0.9
+	opts.Options["seed"] = 42
+	opts.Options["penalize_newline"] = false
+	opts.Options["stop"] = []string{"hi", "there"}
+
+	mf := buildModelfile(opts)
+	expectedModelfile := `FROM {{.Model}}
+SYSTEM """{{.System}}"""
+TEMPLATE """{{.Template}}"""
 PARAMETER penalize_newline false
 PARAMETER seed 42
-PARAMETER stop hi
-PARAMETER stop there
+PARAMETER stop [hi there]
 PARAMETER temperature 0.9
-MESSAGE user Hey there hork!
-MESSAGE assistant Yes it is true, I am half horse, half shark.
+
+MESSAGE user """Hey there hork!"""
+MESSAGE assistant """Yes it is true, I am half horse, half shark."""
 `
 
-		actual := buildModelfile(opts)
-		if diff := cmp.Diff(expect, actual); diff != "" {
-			t.Errorf("mismatch (-want +got):\n%s", diff)
-		}
-	})
+	tmpl, err := template.New("").Parse(expectedModelfile)
+	require.NoError(t, err)
 
-	t.Run("parent model", func(t *testing.T) {
-		opts.ParentModel = "horseshark"
-		expect := `FROM horseshark
-SYSTEM You are part horse and part shark, but all hork. Do horklike things
+	var buf bytes.Buffer
+	err = tmpl.Execute(&buf, opts)
+	require.NoError(t, err)
+	assert.Equal(t, buf.String(), mf)
+
+	opts.ParentModel = "horseshark"
+	mf = buildModelfile(opts)
+	expectedModelfile = `FROM {{.ParentModel}}
+SYSTEM """{{.System}}"""
+TEMPLATE """{{.Template}}"""
 PARAMETER penalize_newline false
 PARAMETER seed 42
-PARAMETER stop hi
-PARAMETER stop there
+PARAMETER stop [hi there]
 PARAMETER temperature 0.9
-MESSAGE user Hey there hork!
-MESSAGE assistant Yes it is true, I am half horse, half shark.
+
+MESSAGE user """Hey there hork!"""
+MESSAGE assistant """Yes it is true, I am half horse, half shark."""
 `
-		actual := buildModelfile(opts)
-		if diff := cmp.Diff(expect, actual); diff != "" {
-			t.Errorf("mismatch (-want +got):\n%s", diff)
-		}
-	})
+
+	tmpl, err = template.New("").Parse(expectedModelfile)
+	require.NoError(t, err)
+
+	var parentBuf bytes.Buffer
+	err = tmpl.Execute(&parentBuf, opts)
+	require.NoError(t, err)
+	assert.Equal(t, parentBuf.String(), mf)
 }

convert/mistral.go

@@ -71,11 +71,6 @@ func (m *MistralModel) WriteGGUF(ws io.WriteSeeker) error {
 		"tokenizer.ggml.unknown_token_id": uint32(0),
 	}
 
-	if m.Params.HeadDimension > 0 {
-		kv["llama.attention.key_length"] = uint32(m.Params.HeadDimension)
-		kv["llama.attention.value_length"] = uint32(m.Params.HeadDimension)
-	}
-
 	return llm.NewGGUFV3(m.Params.ByteOrder).Encode(ws, kv, m.Tensors)
 }
 

docs/api.md

@@ -26,7 +26,7 @@ All durations are returned in nanoseconds.
 
 ### Streaming responses
 
-Certain endpoints stream responses as JSON objects. Streaming can be disabled by providing `{"stream": false}` for these endpoints.
+Certain endpoints stream responses as JSON objects and can optional return non-streamed responses.
 
 ## Generate a completion
 
@@ -40,7 +40,6 @@ Generate a response for a given prompt with a provided model. This is a streamin
 
 - `model`: (required) the [model name](#model-names)
 - `prompt`: the prompt to generate a response for
-- `suffix`: the text after the model response
 - `images`: (optional) a list of base64-encoded images (for multimodal models such as `llava`)
 
 Advanced parameters (optional):
@@ -58,8 +57,7 @@ Advanced parameters (optional):
 
 Enable JSON mode by setting the `format` parameter to `json`. This will structure the response as a valid JSON object. See the JSON mode [example](#request-json-mode) below.
 
-> [!IMPORTANT]
-> It's important to instruct the model to use JSON in the `prompt`. Otherwise, the model may generate large amounts whitespace.
+> Note: it's important to instruct the model to use JSON in the `prompt`. Otherwise, the model may generate large amounts whitespace.
 
 ### Examples
 
@@ -150,44 +148,8 @@ If `stream` is set to `false`, the response will be a single JSON object:
 }
 ```
 
-#### Request (with suffix)
-
-##### Request
-
-```shell
-curl http://localhost:11434/api/generate -d '{
-  "model": "codellama:code",
-  "prompt": "def compute_gcd(a, b):",
-  "suffix": "    return result",
-  "options": {
-    "temperature": 0
-  },
-  "stream": false
-}'
-```
-
-##### Response
-
-```json
-{
-  "model": "codellama:code",
-  "created_at": "2024-07-22T20:47:51.147561Z",
-  "response": "\n  if a == 0:\n    return b\n  else:\n    return compute_gcd(b % a, a)\n\ndef compute_lcm(a, b):\n  result = (a * b) / compute_gcd(a, b)\n",
-  "done": true,
-  "done_reason": "stop",
-  "context": [...],
-  "total_duration": 1162761250,
-  "load_duration": 6683708,
-  "prompt_eval_count": 17,
-  "prompt_eval_duration": 201222000,
-  "eval_count": 63,
-  "eval_duration": 953997000
-}
-```
-
 #### Request (JSON mode)
 
-> [!IMPORTANT]
 > When `format` is set to `json`, the output will always be a well-formed JSON object. It's important to also instruct the model to respond in JSON.
 
 ##### Request
@@ -336,7 +298,6 @@ curl http://localhost:11434/api/generate -d '{
     "num_predict": 100,
     "top_k": 20,
     "top_p": 0.9,
-    "min_p": 0.0,
     "tfs_z": 0.5,
     "typical_p": 0.7,
     "repeat_last_n": 33,
@@ -419,14 +380,12 @@ Generate the next message in a chat with a provided model. This is a streaming e
 
 - `model`: (required) the [model name](#model-names)
 - `messages`: the messages of the chat, this can be used to keep a chat memory
-- `tools`: tools for the model to use if supported. Requires `stream` to be set to `false`
 
 The `message` object has the following fields:
 
-- `role`: the role of the message, either `system`, `user`, `assistant`, or `tool`
+- `role`: the role of the message, either `system`, `user` or `assistant`
 - `content`: the content of the message
 - `images` (optional): a list of images to include in the message (for multimodal models such as `llava`)
-- `tool_calls` (optional): a list of tools the model wants to use
 
 Advanced parameters (optional):
 
@@ -587,7 +546,7 @@ Final response:
 
 ##### Request
 
-Send a chat message with images. The images should be provided as an array, with the individual images encoded in Base64.
+Send a chat message with a conversation history.
 
 ```shell
 curl http://localhost:11434/api/chat -d '{
@@ -663,79 +622,6 @@ curl http://localhost:11434/api/chat -d '{
 }
 ```
 
-#### Chat request (with tools)
-
-##### Request
-
-```
-curl http://localhost:11434/api/chat -d '{
-  "model": "mistral",
-  "messages": [
-    {
-      "role": "user",
-      "content": "What is the weather today in Paris?"
-    }
-  ],
-  "stream": false,
-  "tools": [
-    {
-      "type": "function",
-      "function": {
-        "name": "get_current_weather",
-        "description": "Get the current weather for a location",
-        "parameters": {
-          "type": "object",
-          "properties": {
-            "location": {
-              "type": "string",
-              "description": "The location to get the weather for, e.g. San Francisco, CA"
-            },
-            "format": {
-              "type": "string",
-              "description": "The format to return the weather in, e.g. 'celsius' or 'fahrenheit'",
-              "enum": ["celsius", "fahrenheit"]
-            }
-          },
-          "required": ["location", "format"]
-        }
-      }
-    }
-  ]
-}'
-```
-
-##### Response
-
-```json
-{
-  "model": "mistral:7b-instruct-v0.3-q4_K_M",
-  "created_at": "2024-07-22T20:33:28.123648Z",
-  "message": {
-    "role": "assistant",
-    "content": "",
-    "tool_calls": [
-      {
-        "function": {
-          "name": "get_current_weather",
-          "arguments": {
-            "format": "celsius",
-            "location": "Paris, FR"
-          }
-        }
-      }
-    ]
-  },
-  "done_reason": "stop",
-  "done": true,
-  "total_duration": 885095291,
-  "load_duration": 3753500,
-  "prompt_eval_count": 122,
-  "prompt_eval_duration": 328493000,
-  "eval_count": 33,
-  "eval_duration": 552222000
-}
-```
-
 ## Create a Model
 
 ```shell
@@ -891,12 +777,11 @@ A single JSON object will be returned.
 POST /api/show
 ```
 
-Show information about a model including details, modelfile, template, parameters, license, system prompt.
+Show information about a model including details, modelfile, template, parameters, license, and system prompt.
 
 ### Parameters
 
 - `name`: name of the model to show
-- `verbose`: (optional) if set to `true`, returns full data for verbose response fields
 
 ### Examples
 
@@ -913,40 +798,14 @@ curl http://localhost:11434/api/show -d '{
 ```json
 {
   "modelfile": "# Modelfile generated by \"ollama show\"\n# To build a new Modelfile based on this one, replace the FROM line with:\n# FROM llava:latest\n\nFROM /Users/matt/.ollama/models/blobs/sha256:200765e1283640ffbd013184bf496e261032fa75b99498a9613be4e94d63ad52\nTEMPLATE \"\"\"{{ .System }}\nUSER: {{ .Prompt }}\nASSISTANT: \"\"\"\nPARAMETER num_ctx 4096\nPARAMETER stop \"\u003c/s\u003e\"\nPARAMETER stop \"USER:\"\nPARAMETER stop \"ASSISTANT:\"",
-  "parameters": "num_keep                       24\nstop                           \"<|start_header_id|>\"\nstop                           \"<|end_header_id|>\"\nstop                           \"<|eot_id|>\"",
-  "template": "{{ if .System }}<|start_header_id|>system<|end_header_id|>\n\n{{ .System }}<|eot_id|>{{ end }}{{ if .Prompt }}<|start_header_id|>user<|end_header_id|>\n\n{{ .Prompt }}<|eot_id|>{{ end }}<|start_header_id|>assistant<|end_header_id|>\n\n{{ .Response }}<|eot_id|>",
+  "parameters": "num_ctx                        4096\nstop                           \u003c/s\u003e\nstop                           USER:\nstop                           ASSISTANT:",
+  "template": "{{ .System }}\nUSER: {{ .Prompt }}\nASSISTANT: ",
   "details": {
-    "parent_model": "",
     "format": "gguf",
     "family": "llama",
-    "families": [
-      "llama"
-    ],
-    "parameter_size": "8.0B",
+    "families": ["llama", "clip"],
+    "parameter_size": "7B",
     "quantization_level": "Q4_0"
-  },
-  "model_info": {
-    "general.architecture": "llama",
-    "general.file_type": 2,
-    "general.parameter_count": 8030261248,
-    "general.quantization_version": 2,
-    "llama.attention.head_count": 32,
-    "llama.attention.head_count_kv": 8,
-    "llama.attention.layer_norm_rms_epsilon": 0.00001,
-    "llama.block_count": 32,
-    "llama.context_length": 8192,
-    "llama.embedding_length": 4096,
-    "llama.feed_forward_length": 14336,
-    "llama.rope.dimension_count": 128,
-    "llama.rope.freq_base": 500000,
-    "llama.vocab_size": 128256,
-    "tokenizer.ggml.bos_token_id": 128000,
-    "tokenizer.ggml.eos_token_id": 128009,
-    "tokenizer.ggml.merges": [],            // populates if `verbose=true`
-    "tokenizer.ggml.model": "gpt2",
-    "tokenizer.ggml.pre": "llama-bpe",
-    "tokenizer.ggml.token_type": [],        // populates if `verbose=true`
-    "tokenizer.ggml.tokens": []             // populates if `verbose=true`
   }
 }
 ```
@@ -1140,7 +999,7 @@ If `stream` is set to `false`, then the response is a single JSON object:
 ## Generate Embeddings
 
 ```shell
-POST /api/embed
+POST /api/embeddings
 ```
 
 Generate embeddings from a model
@@ -1148,11 +1007,10 @@ Generate embeddings from a model
 ### Parameters
 
 - `model`: name of model to generate embeddings from
-- `input`: text or list of text to generate embeddings for
+- `prompt`: text to generate embeddings for
 
 Advanced parameters:
 
-- `truncate`: truncates the end of each input to fit within context length. Returns error if `false` and context length is exceeded. Defaults to `true`
 - `options`: additional model parameters listed in the documentation for the [Modelfile](./modelfile.md#valid-parameters-and-values) such as `temperature`
 - `keep_alive`: controls how long the model will stay loaded into memory following the request (default: `5m`)
 
@@ -1161,9 +1019,9 @@ Advanced parameters:
 #### Request
 
 ```shell
-curl http://localhost:11434/api/embed -d '{
+curl http://localhost:11434/api/embeddings -d '{
   "model": "all-minilm",
-  "input": "Why is the sky blue?"
+  "prompt": "Here is an article about llamas..."
 }'
 ```
 
@@ -1171,35 +1029,10 @@ curl http://localhost:11434/api/embed -d '{
 
 ```json
 {
-  "model": "all-minilm",
-  "embeddings": [[
-    0.010071029, -0.0017594862, 0.05007221, 0.04692972, 0.054916814,
-    0.008599704, 0.105441414, -0.025878139, 0.12958129, 0.031952348
-  ]]
-}
-```
-
-#### Request (Multiple input)
-
-```shell
-curl http://localhost:11434/api/embed -d '{
-  "model": "all-minilm",
-  "input": ["Why is the sky blue?", "Why is the grass green?"]
-}'
-```
-
-#### Response
-
-```json
-{
-  "model": "all-minilm",
-  "embeddings": [[
-    0.010071029, -0.0017594862, 0.05007221, 0.04692972, 0.054916814,
-    0.008599704, 0.105441414, -0.025878139, 0.12958129, 0.031952348
-  ],[
-    -0.0098027075, 0.06042469, 0.025257962, -0.006364387, 0.07272725,
-    0.017194884, 0.09032035, -0.051705178, 0.09951512, 0.09072481
-  ]]
+  "embedding": [
+    0.5670403838157654, 0.009260174818336964, 0.23178744316101074, -0.2916173040866852, -0.8924556970596313,
+    0.8785552978515625, -0.34576427936553955, 0.5742510557174683, -0.04222835972905159, -0.137906014919281
+  ]
 }
 ```
 
@@ -1246,45 +1079,3 @@ A single JSON object will be returned.
   ]
 }
 ```
-
-## Generate Embedding
-
-> Note: this endpoint has been superseded by `/api/embed`
-
-```shell
-POST /api/embeddings
-```
-
-Generate embeddings from a model
-
-### Parameters
-
-- `model`: name of model to generate embeddings from
-- `prompt`: text to generate embeddings for
-
-Advanced parameters:
-
-- `options`: additional model parameters listed in the documentation for the [Modelfile](./modelfile.md#valid-parameters-and-values) such as `temperature`
-- `keep_alive`: controls how long the model will stay loaded into memory following the request (default: `5m`)
-
-### Examples
-
-#### Request
-
-```shell
-curl http://localhost:11434/api/embeddings -d '{
-  "model": "all-minilm",
-  "prompt": "Here is an article about llamas..."
-}'
-```
-
-#### Response
-
-```json
-{
-  "embedding": [
-    0.5670403838157654, 0.009260174818336964, 0.23178744316101074, -0.2916173040866852, -0.8924556970596313,
-    0.8785552978515625, -0.34576427936553955, 0.5742510557174683, -0.04222835972905159, -0.137906014919281
-  ]
-}
-```

docs/development.md

@@ -104,7 +104,7 @@ like to use. For example, to compile an optimized binary for an Intel i9-9880H,
 you might use:
 
 ```
-OLLAMA_CUSTOM_CPU_DEFS="-DGGML_AVX=on -DGGML_AVX2=on -DGGML_F16C=on -DGGML_FMA=on" go generate ./...
+OLLAMA_CUSTOM_CPU_DEFS="-DLLAMA_AVX=on -DLLAMA_AVX2=on -DLLAMA_F16C=on -DLLAMA_FMA=on" go generate ./...
 go build .
 ```
 
@@ -114,18 +114,15 @@ If you have Docker available, you can build linux binaries with `./scripts/build
 
 ### Windows
 
-Note: The Windows build for Ollama is still under development.
+Note: The windows build for Ollama is still under development.
 
-First, install required tools:
+Install required tools:
 
 - MSVC toolchain - C/C++ and cmake as minimal requirements
 - Go version 1.22 or higher
 - MinGW (pick one variant) with GCC.
   - [MinGW-w64](https://www.mingw-w64.org/)
   - [MSYS2](https://www.msys2.org/)
-- The `ThreadJob` Powershell module: `Install-Module -Name ThreadJob -Scope CurrentUser`
-
-Then, build the `ollama` binary:
 
 ```powershell
 $env:CGO_ENABLED="1"

docs/docker.md

@@ -63,7 +63,7 @@ docker run -d --device /dev/kfd --device /dev/dri -v ollama:/root/.ollama -p 114
 Now you can run a model:
 
 ```
-docker exec -it ollama ollama run llama3.1
+docker exec -it ollama ollama run llama3
 ```
 
 ### Try different models

docs/faq.md

@@ -227,7 +227,7 @@ curl http://localhost:11434/api/chat -d '{"model": "mistral"}'
 
 To preload a model using the CLI, use the command:
 ```shell
-ollama run llama3.1 ""
+ollama run llama3 ""
 ```
 
 ## How do I keep a model loaded in memory or make it unload immediately?
@@ -257,23 +257,3 @@ If you wish to override the `OLLAMA_KEEP_ALIVE` setting, use the `keep_alive` AP
 ## How do I manage the maximum number of requests the Ollama server can queue?
 
 If too many requests are sent to the server, it will respond with a 503 error indicating the server is overloaded.  You can adjust how many requests may be queue by setting `OLLAMA_MAX_QUEUE`.
-
-## How does Ollama handle concurrent requests?
-
-Ollama supports two levels of concurrent processing.  If your system has sufficient available memory (system memory when using CPU inference, or VRAM for GPU inference) then multiple models can be loaded at the same time.  For a given model, if there is sufficient available memory when the model is loaded, it is configured to allow parallel request processing.
-
-If there is insufficient available memory to load a new model request while one or more models are already loaded, all new requests will be queued until the new model can be loaded.  As prior models become idle, one or more will be unloaded to make room for the new model.  Queued requests will be processed in order.  When using GPU inference new models must be able to completely fit in VRAM to allow concurrent model loads.
-
-Parallel request processing for a given model results in increasing the context size by the number of parallel requests.  For example, a 2K context with 4 parallel requests will result in an 8K context and additional memory allocation.
-
-The following server settings may be used to adjust how Ollama handles concurrent requests on most platforms:
-
-- `OLLAMA_MAX_LOADED_MODELS` - The maximum number of models that can be loaded concurrently provided they fit in available memory.  The default is 3 * the number of GPUs or 3 for CPU inference.
-- `OLLAMA_NUM_PARALLEL` - The maximum number of parallel requests each model will process at the same time.  The default will auto-select either 4 or 1 based on available memory.
-- `OLLAMA_MAX_QUEUE` - The maximum number of requests Ollama will queue when busy before rejecting additional requests. The default is 512
-
-Note: Windows with Radeon GPUs currently default to 1 model maximum due to limitations in ROCm v5.7 for available VRAM reporting.  Once ROCm v6.2 is available, Windows Radeon will follow the defaults above.  You may enable concurrent model loads on Radeon on Windows, but ensure you don't load more models than will fit into your GPUs VRAM.
-
-## How does Ollama load models on multiple GPUs?
-
-Installing multiple GPUs of the same brand can be a great way to increase your available VRAM to load larger models.  When you load a new model, Ollama evaluates the required VRAM for the model against what is currently available.  If the model will entirely fit on any single GPU, Ollama will load the model on that GPU.  This typically provides the best performance as it reduces the amount of data transfering across the PCI bus during inference.  If the model does not fit entirely on one GPU, then it will be spread across all the available GPUs.

docs/gpu.md

@@ -8,7 +8,7 @@ Check your compute compatibility to see if your card is supported:
 | Compute Capability | Family              | Cards                                                                                                       |
 | ------------------ | ------------------- | ----------------------------------------------------------------------------------------------------------- |
 | 9.0                | NVIDIA              | `H100`                                                                                                      |
-| 8.9                | GeForce RTX 40xx    | `RTX 4090` `RTX 4080 SUPER` `RTX 4080` `RTX 4070 Ti SUPER` `RTX 4070 Ti` `RTX 4070 SUPER` `RTX 4070` `RTX 4060 Ti` `RTX 4060`  |
+| 8.9                | GeForce RTX 40xx    | `RTX 4090` `RTX 4080` `RTX 4070 Ti` `RTX 4060 Ti`                                                           |
 |                    | NVIDIA Professional | `L4` `L40` `RTX 6000`                                                                                       |
 | 8.6                | GeForce RTX 30xx    | `RTX 3090 Ti` `RTX 3090` `RTX 3080 Ti` `RTX 3080` `RTX 3070 Ti` `RTX 3070` `RTX 3060 Ti` `RTX 3060`         |
 |                    | NVIDIA Professional | `A40` `RTX A6000` `RTX A5000` `RTX A4000` `RTX A3000` `RTX A2000` `A10` `A16` `A2`                          |
@@ -18,7 +18,7 @@ Check your compute compatibility to see if your card is supported:
 |                    | Quadro              | `RTX 8000` `RTX 6000` `RTX 5000` `RTX 4000`                                                                 |
 | 7.0                | NVIDIA              | `TITAN V` `V100` `Quadro GV100`                                                                             |
 | 6.1                | NVIDIA TITAN        | `TITAN Xp` `TITAN X`                                                                                        |
-|                    | GeForce GTX         | `GTX 1080 Ti` `GTX 1080` `GTX 1070 Ti` `GTX 1070` `GTX 1060` `GTX 1050 Ti` `GTX 1050`                       |
+|                    | GeForce GTX         | `GTX 1080 Ti` `GTX 1080` `GTX 1070 Ti` `GTX 1070` `GTX 1060` `GTX 1050`                                     |
 |                    | Quadro              | `P6000` `P5200` `P4200` `P3200` `P5000` `P4000` `P3000` `P2200` `P2000` `P1000` `P620` `P600` `P500` `P520` |
 |                    | Tesla               | `P40` `P4`                                                                                                  |
 | 6.0                | NVIDIA              | `Tesla P100` `Quadro GP100`                                                                                 |
@@ -46,24 +46,13 @@ sudo modprobe nvidia_uvm`
 
 ## AMD Radeon
 Ollama supports the following AMD GPUs:
-
-### Linux Support
 | Family         | Cards and accelerators                                                                                                               |
 | -------------- | ---------------------------------------------------------------------------------------------------------------------------------------------- |
 | AMD Radeon RX  | `7900 XTX` `7900 XT` `7900 GRE` `7800 XT` `7700 XT` `7600 XT` `7600` `6950 XT` `6900 XTX` `6900XT` `6800 XT` `6800` `Vega 64` `Vega 56`    |
 | AMD Radeon PRO | `W7900` `W7800` `W7700` `W7600` `W7500` `W6900X` `W6800X Duo` `W6800X` `W6800` `V620` `V420` `V340` `V320` `Vega II Duo` `Vega II` `VII` `SSG` |
 | AMD Instinct   | `MI300X` `MI300A` `MI300` `MI250X` `MI250` `MI210` `MI200` `MI100` `MI60` `MI50`                                                               |
 
-### Windows Support
-With ROCm v6.1, the following GPUs are supported on Windows.
-
-| Family         | Cards and accelerators                                                                                                               |
-| -------------- | ---------------------------------------------------------------------------------------------------------------------------------------------- |
-| AMD Radeon RX  | `7900 XTX` `7900 XT` `7900 GRE` `7800 XT` `7700 XT` `7600 XT` `7600` `6950 XT` `6900 XTX` `6900XT` `6800 XT` `6800`    |
-| AMD Radeon PRO | `W7900` `W7800` `W7700` `W7600` `W7500` `W6900X` `W6800X Duo` `W6800X` `W6800` `V620` |
-
-
-### Overrides on Linux
+### Overrides
 Ollama leverages the AMD ROCm library, which does not support all AMD GPUs. In
 some cases you can force the system to try to use a similar LLVM target that is
 close.  For example The Radeon RX 5400 is `gfx1034` (also known as 10.3.4)
@@ -74,7 +63,7 @@ would set `HSA_OVERRIDE_GFX_VERSION="10.3.0"` as an environment variable for the
 server.  If you have an unsupported AMD GPU you can experiment using the list of
 supported types below.
 
-At this time, the known supported GPU types on linux are the following LLVM Targets.
+At this time, the known supported GPU types are the following LLVM Targets.
 This table shows some example GPUs that map to these LLVM targets:
 | **LLVM Target** | **An Example GPU** |
 |-----------------|---------------------|

docs/import.md

@@ -47,13 +47,19 @@ success
 
 ### Supported Quantizations
 
+<details>
+<summary>Legacy Quantization</summary>
+
 - `Q4_0`
 - `Q4_1`
 - `Q5_0`
 - `Q5_1`
 - `Q8_0`
 
-#### K-means Quantizations
+</details>
+
+<details>
+<summary>K-means Quantization</summary>`
 
 - `Q3_K_S`
 - `Q3_K_M`
@@ -64,6 +70,11 @@ success
 - `Q5_K_M`
 - `Q6_K`
 
+</details>
+
+> [!NOTE]
+> Activation-aware Weight Quantization (i.e. IQ) are not currently supported for automatic quantization however you can still import the quantized model into Ollama, see [Import GGUF](#import-gguf).
+
 ## Template Detection
 
 > [!NOTE]

docs/modelfile.md

@@ -1,7 +1,6 @@
 # Ollama Model File
 
-> [!NOTE]
-> `Modelfile` syntax is in development
+> Note: `Modelfile` syntax is in development
 
 A model file is the blueprint to create and share models with Ollama.
 
@@ -141,7 +140,6 @@ PARAMETER <parameter> <parametervalue>
 | num_predict    | Maximum number of tokens to predict when generating text. (Default: 128, -1 = infinite generation, -2 = fill context)                                                                                                                                   | int        | num_predict 42       |
 | top_k          | Reduces the probability of generating nonsense. A higher value (e.g. 100) will give more diverse answers, while a lower value (e.g. 10) will be more conservative. (Default: 40)                                                                        | int        | top_k 40             |
 | top_p          | Works together with top-k. A higher value (e.g., 0.95) will lead to more diverse text, while a lower value (e.g., 0.5) will generate more focused and conservative text. (Default: 0.9)                                                                 | float      | top_p 0.9            |
-| min_p          | Alternative to the top_p, and aims to ensure a balance of quality and variety. The parameter *p* represents the minimum probability for a token to be considered, relative to the probability of the most likely token. For example, with *p*=0.05 and the most likely token having a probability of 0.9, logits with a value less than 0.045 are filtered out. (Default: 0.0) | float      | min_p 0.05            |
 
 ### TEMPLATE
 

docs/openai.md

@@ -65,7 +65,6 @@ curl http://localhost:11434/v1/chat/completions \
             }
         ]
     }'
-
 ```
 
 ## Endpoints
@@ -78,8 +77,8 @@ curl http://localhost:11434/v1/chat/completions \
 - [x] Streaming
 - [x] JSON mode
 - [x] Reproducible outputs
-- [x] Tools (streaming support coming soon)
 - [ ] Vision
+- [ ] Function calling
 - [ ] Logprobs
 
 #### Supported request fields
@@ -97,12 +96,18 @@ curl http://localhost:11434/v1/chat/completions \
 - [x] `temperature`
 - [x] `top_p`
 - [x] `max_tokens`
-- [x] `tools`
-- [ ] `tool_choice`
 - [ ] `logit_bias`
+- [ ] `tools`
+- [ ] `tool_choice`
 - [ ] `user`
 - [ ] `n`
 
+#### Notes
+
+- Setting `seed` will always set `temperature` to `0`
+- `finish_reason` will always be `stop`
+- `usage.prompt_tokens` will be 0 for completions where prompt evaluation is cached
+
 ## Models
 
 Before using a model, pull it locally `ollama pull`:

docs/template.md

@@ -1,173 +0,0 @@
-# Template
-
-Ollama provides a powerful templating engine backed by Go's built-in templating engine to construct prompts for your large language model. This feature is a valuable tool to get the most out of your models.
-
-## Basic Template Structure
-
-A basic Go template consists of three main parts:
-
-* **Layout**: The overall structure of the template.
-* **Variables**: Placeholders for dynamic data that will be replaced with actual values when the template is rendered.
-* **Functions**: Custom functions or logic that can be used to manipulate the template's content.
-
-Here's an example of a simple chat template:
-
-```gotmpl
-{{- range .Messages }}
-{{ .Role }}: {{ .Content }}
-{{- end }}
-```
-
-In this example, we have:
-
-* A basic messages structure (layout)
-* Three variables: `Messages`, `Role`, and `Content` (variables)
-* A custom function (action) that iterates over an array of items (`range .Messages`) and displays each item
-
-## Adding templates to your model
-
-By default, models imported into Ollama have a default template of `{{ .Prompt }}`, i.e. user inputs are sent verbatim to the LLM. This is appropriate for text or code completion models but lacks essential markers for chat or instruction models.
-
-Omitting a template in these models puts the responsibility of correctly templating input onto the user. Adding a template allows users to easily get the best results from the model.
-
-To add templates in your model, you'll need to add a `TEMPLATE` command to the Modelfile. Here's an example using Meta's Llama 3.
-
-```dockerfile
-FROM llama3
-
-TEMPLATE """{{- if .System }}<|start_header_id|>system<|end_header_id|>
-
-{{ .System }}<|eot_id|>
-{{- end }}
-{{- range .Messages }}<|start_header_id|>{{ .Role }}<|end_header_id|>
-
-{{ .Content }}<|eot_id|>
-{{- end }}<|start_header_id|>assistant<|end_header_id|>
-
-"""
-```
-
-## Variables
-
-`System` (string): system prompt
-
-`Prompt` (string): user prompt
-
-`Response` (string): assistant response
-
-`Suffix` (string): text inserted after the assistant's response
-
-`Messages` (list): list of messages
-
-`Messages[].Role` (string): role which can be one of `system`, `user`, `assistant`, or `tool`
-
-`Messages[].Content` (string):  message content
-
-`Messages[].ToolCalls` (list): list of tools the model wants to call
-
-`Messages[].ToolCalls[].Function` (object): function to call
-
-`Messages[].ToolCalls[].Function.Name` (string): function name
-
-`Messages[].ToolCalls[].Function.Arguments` (map): mapping of argument name to argument value
-
-`Tools` (list): list of tools the model can access
-
-`Tools[].Type` (string): schema type. `type` is always `function`
-
-`Tools[].Function` (object): function definition
-
-`Tools[].Function.Name` (string): function name
-
-`Tools[].Function.Description` (string): function description
-
-`Tools[].Function.Parameters` (object): function parameters
-
-`Tools[].Function.Parameters.Type` (string): schema type. `type` is always `object`
-
-`Tools[].Function.Parameters.Required` (list): list of required properties
-
-`Tools[].Function.Parameters.Properties` (map): mapping of property name to property definition
-
-`Tools[].Function.Parameters.Properties[].Type` (string): property type
-
-`Tools[].Function.Parameters.Properties[].Description` (string): property description
-
-`Tools[].Function.Parameters.Properties[].Enum` (list): list of valid values
-
-## Tips and Best Practices
-
-Keep the following tips and best practices in mind when working with Go templates:
-
-* **Be mindful of dot**: Control flow structures like `range` and `with` changes the value `.`
-* **Out-of-scope variables**: Use `$.` to reference variables not currently in scope, starting from the root
-* **Whitespace control**: Use `-` to trim leading (`{{-`) and trailing (`-}}`) whitespace
-
-## Examples
-
-### Example Messages
-
-#### ChatML
-
-ChatML is a popular template format. It can be used for models such as Databrick's DBRX, Intel's Neural Chat, and Microsoft's Orca 2.
-
-```gotmpl
-{{- if .System }}<|im_start|>system
-{{ .System }}<|im_end|>
-{{ end }}
-{{- range .Messages }}<|im_start|>{{ .Role }}
-{{ .Content }}<|im_end|>
-{{ end }}<|im_start|>assistant
-{{ else }}
-{{ if .System }}<|im_start|>system
-{{ .System }}<|im_end|>
-```
-
-### Example Tools
-
-Tools support can be added to a model by adding a `{{ .Tools }}` node to the template. This feature is useful for models trained to call external tools and can a powerful tool for retrieving real-time data or performing complex tasks.
-
-#### Mistral
-
-Mistral v0.3 and Mixtral 8x22B supports tool calling.
-
-```gotmpl
-{{- range $index, $_ := .Messages }}
-{{- if eq .Role "user" }}
-{{- if and (le (len (slice $.Messages $index)) 2) $.Tools }}[AVAILABLE_TOOLS] {{ json $.Tools }}[/AVAILABLE_TOOLS]
-{{- end }}[INST] {{ if and (eq (len (slice $.Messages $index)) 1) $.System }}{{ $.System }}
-
-{{ end }}{{ .Content }}[/INST]
-{{- else if eq .Role "assistant" }}
-{{- if .Content }} {{ .Content }}</s>
-{{- else if .ToolCalls }}[TOOL_CALLS] [
-{{- range .ToolCalls }}{"name": "{{ .Function.Name }}", "arguments": {{ json .Function.Arguments }}}
-{{- end }}]</s>
-{{- end }}
-{{- else if eq .Role "tool" }}[TOOL_RESULTS] {"content": {{ .Content }}}[/TOOL_RESULTS]
-{{- end }}
-{{- end }}
-```
-
-### Example Fill-in-Middle
-
-Fill-in-middle support can be added to a model by adding a `{{ .Suffix }}` node to the template. This feature is useful for models that are trained to generate text in the middle of user input, such as code completion models.
-
-#### CodeLlama
-
-CodeLlama [7B](https://ollama.com/library/codellama:7b-code) and [13B](https://ollama.com/library/codellama:13b-code) code completion models support fill-in-middle.
-
-```gotmpl
-<PRE> {{ .Prompt }} <SUF>{{ .Suffix }} <MID>
-```
-
-> [!NOTE]
-> CodeLlama 34B and 70B code completion and all instruct and Python fine-tuned models do not support fill-in-middle.
-
-#### Codestral
-
-Codestral [22B](https://ollama.com/library/codestral:22b) supports fill-in-middle.
-
-```gotmpl
-[SUFFIX]{{ .Suffix }}[PREFIX] {{ .Prompt }}
-```

docs/troubleshooting.md

@@ -22,7 +22,7 @@ docker logs <container-name>
 If manually running `ollama serve` in a terminal, the logs will be on that terminal.
 
 When you run Ollama on **Windows**, there are a few different locations. You can view them in the explorer window by hitting `<cmd>+R` and type in:
-- `explorer %LOCALAPPDATA%\Ollama` to view logs.  The most recent server logs will be in `server.log` and older logs will be in `server-#.log` 
+- `explorer %LOCALAPPDATA%\Ollama` to view logs
 - `explorer %LOCALAPPDATA%\Programs\Ollama` to browse the binaries (The installer adds this to your user PATH)
 - `explorer %HOMEPATH%\.ollama` to browse where models and configuration is stored
 - `explorer %TEMP%` where temporary executable files are stored in one or more `ollama*` directories
@@ -70,18 +70,14 @@ curl -fsSL https://ollama.com/install.sh | OLLAMA_VERSION="0.1.29" sh
 
 If your system is configured with the "noexec" flag where Ollama stores its temporary executable files, you can specify an alternate location by setting OLLAMA_TMPDIR to a location writable by the user ollama runs as. For example OLLAMA_TMPDIR=/usr/share/ollama/
 
-## NVIDIA GPU Discovery
+## Container fails to run on NVIDIA GPU
 
-When Ollama starts up, it takes inventory of the GPUs present in the system to determine compatibility and how much VRAM is available.  Sometimes this discovery can fail to find your GPUs.  In general, running the latest driver will yield the best results.
+Make sure you've set up the container runtime first as described in [docker.md](./docker.md)
 
-### Linux NVIDIA Troubleshooting
+Sometimes the container runtime can have difficulties initializing the GPU. When you check the server logs, this can show up as various error codes, such as "3" (not initialized), "46" (device unavailable), "100" (no device), "999" (unknown), or others. The following troubleshooting techniques may help resolve the problem
 
-If you are using a container to run Ollama, make sure you've set up the container runtime first as described in [docker.md](./docker.md)
-
-Sometimes the Ollama can have difficulties initializing the GPU. When you check the server logs, this can show up as various error codes, such as "3" (not initialized), "46" (device unavailable), "100" (no device), "999" (unknown), or others. The following troubleshooting techniques may help resolve the problem
-
-- If you are using a container, is the container runtime working?  Try `docker run --gpus all ubuntu nvidia-smi` - if this doesn't work, Ollama wont be able to see your NVIDIA GPU.
-- Is the uvm driver loaded? `sudo nvidia-modprobe -u`
+- Is the container runtime working?  Try `docker run --gpus all ubuntu nvidia-smi` - if this doesn't work, Ollama wont be able to see your NVIDIA GPU.
+- Is the uvm driver not loaded? `sudo nvidia-modprobe -u`
 - Try reloading the nvidia_uvm driver - `sudo rmmod nvidia_uvm` then `sudo modprobe nvidia_uvm`
 - Try rebooting
 - Make sure you're running the latest nvidia drivers
@@ -89,8 +85,3 @@ Sometimes the Ollama can have difficulties initializing the GPU. When you check
 If none of those resolve the problem, gather additional information and file an issue:
 - Set `CUDA_ERROR_LEVEL=50` and try again to get more diagnostic logs
 - Check dmesg for any errors `sudo dmesg | grep -i nvrm` and `sudo dmesg | grep -i nvidia`
-
-
-## Windows Terminal Errors
-
-Older versions of Windows 10 (e.g., 21H1) are known to have a bug where the standard terminal program does not display control characters correctly.  This can result in a long string of strings like `←[?25h←[?25l` being displayed, sometimes erroring with `The parameter is incorrect`  To resolve this problem, please update to Win 10 22H1 or newer.

docs/tutorials/langchainjs.md

@@ -15,7 +15,7 @@ import { Ollama } from "@langchain/community/llms/ollama";
 
 const ollama = new Ollama({
   baseUrl: "http://localhost:11434",
-  model: "llama3.1",
+  model: "llama3",
 });
 
 const answer = await ollama.invoke(`why is the sky blue?`);
@@ -23,7 +23,7 @@ const answer = await ollama.invoke(`why is the sky blue?`);
 console.log(answer);
 ```
 
-That will get us the same thing as if we ran `ollama run llama3.1 "why is the sky blue"` in the terminal. But we want to load a document from the web to ask a question against. **Cheerio** is a great library for ingesting a webpage, and **LangChain** uses it in their **CheerioWebBaseLoader**. So let's install **Cheerio** and build that part of the app.
+That will get us the same thing as if we ran `ollama run llama3 "why is the sky blue"` in the terminal. But we want to load a document from the web to ask a question against. **Cheerio** is a great library for ingesting a webpage, and **LangChain** uses it in their **CheerioWebBaseLoader**. So let's install **Cheerio** and build that part of the app.
 
 ```bash
 npm install cheerio

docs/windows.md

@@ -19,12 +19,10 @@ Logs will often be helpful in diagnosing the problem (see
 
 ## System Requirements
 
-* Windows 10 22H2 or newer, Home or Pro
+* Windows 10 or newer, Home or Pro
 * NVIDIA 452.39 or newer Drivers if you have an NVIDIA card
 * AMD Radeon Driver https://www.amd.com/en/support if you have a Radeon card
 
-Ollama uses unicode characters for progress indication, which may render as unknown squares in some older terminal fonts in Windows 10. If you see this, try changing your terminal font settings.
-
 ## API Access
 
 Here's a quick example showing API access from `powershell`
@@ -41,8 +39,8 @@ server.
 Ollama on Windows stores files in a few different locations.  You can view them in
 the explorer window by hitting `<cmd>+R` and type in:
 - `explorer %LOCALAPPDATA%\Ollama` contains logs, and downloaded updates
-    - *app.log* contains most resent logs from the GUI application
-    - *server.log* contains the most recent server logs
+    - *app.log* contains logs from the GUI application
+    - *server.log* contains the server logs
     - *upgrade.log* contains log output for upgrades
 - `explorer %LOCALAPPDATA%\Programs\Ollama` contains the binaries (The installer adds this to your user PATH)
 - `explorer %HOMEPATH%\.ollama` contains models and configuration

envconfig/config.go

@@ -4,14 +4,12 @@ import (
 	"errors"
 	"fmt"
 	"log/slog"
-	"math"
 	"net"
 	"os"
 	"path/filepath"
 	"runtime"
 	"strconv"
 	"strings"
-	"time"
 )
 
 type OllamaHost struct {
@@ -36,7 +34,7 @@ var (
 	// Set via OLLAMA_HOST in the environment
 	Host *OllamaHost
 	// Set via OLLAMA_KEEP_ALIVE in the environment
-	KeepAlive time.Duration
+	KeepAlive string
 	// Set via OLLAMA_LLM_LIBRARY in the environment
 	LLMLibrary string
 	// Set via OLLAMA_MAX_LOADED_MODELS in the environment
@@ -45,6 +43,8 @@ var (
 	MaxQueuedRequests int
 	// Set via OLLAMA_MODELS in the environment
 	ModelsDir string
+	// Set via OLLAMA_MAX_VRAM in the environment
+	MaxVRAM uint64
 	// Set via OLLAMA_NOHISTORY in the environment
 	NoHistory bool
 	// Set via OLLAMA_NOPRUNE in the environment
@@ -53,23 +53,8 @@ var (
 	NumParallel int
 	// Set via OLLAMA_RUNNERS_DIR in the environment
 	RunnersDir string
-	// Set via OLLAMA_SCHED_SPREAD in the environment
-	SchedSpread bool
 	// Set via OLLAMA_TMPDIR in the environment
 	TmpDir string
-	// Set via OLLAMA_INTEL_GPU in the environment
-	IntelGpu bool
-
-	// Set via CUDA_VISIBLE_DEVICES in the environment
-	CudaVisibleDevices string
-	// Set via HIP_VISIBLE_DEVICES in the environment
-	HipVisibleDevices string
-	// Set via ROCR_VISIBLE_DEVICES in the environment
-	RocrVisibleDevices string
-	// Set via GPU_DEVICE_ORDINAL in the environment
-	GpuDeviceOrdinal string
-	// Set via HSA_OVERRIDE_GFX_VERSION in the environment
-	HsaOverrideGfxVersion string
 )
 
 type EnvVar struct {
@@ -79,32 +64,23 @@ type EnvVar struct {
 }
 
 func AsMap() map[string]EnvVar {
-	ret := map[string]EnvVar{
+	return map[string]EnvVar{
 		"OLLAMA_DEBUG":             {"OLLAMA_DEBUG", Debug, "Show additional debug information (e.g. OLLAMA_DEBUG=1)"},
 		"OLLAMA_FLASH_ATTENTION":   {"OLLAMA_FLASH_ATTENTION", FlashAttention, "Enabled flash attention"},
 		"OLLAMA_HOST":              {"OLLAMA_HOST", Host, "IP Address for the ollama server (default 127.0.0.1:11434)"},
 		"OLLAMA_KEEP_ALIVE":        {"OLLAMA_KEEP_ALIVE", KeepAlive, "The duration that models stay loaded in memory (default \"5m\")"},
 		"OLLAMA_LLM_LIBRARY":       {"OLLAMA_LLM_LIBRARY", LLMLibrary, "Set LLM library to bypass autodetection"},
-		"OLLAMA_MAX_LOADED_MODELS": {"OLLAMA_MAX_LOADED_MODELS", MaxRunners, "Maximum number of loaded models per GPU"},
+		"OLLAMA_MAX_LOADED_MODELS": {"OLLAMA_MAX_LOADED_MODELS", MaxRunners, "Maximum number of loaded models (default 1)"},
 		"OLLAMA_MAX_QUEUE":         {"OLLAMA_MAX_QUEUE", MaxQueuedRequests, "Maximum number of queued requests"},
+		"OLLAMA_MAX_VRAM":          {"OLLAMA_MAX_VRAM", MaxVRAM, "Maximum VRAM"},
 		"OLLAMA_MODELS":            {"OLLAMA_MODELS", ModelsDir, "The path to the models directory"},
 		"OLLAMA_NOHISTORY":         {"OLLAMA_NOHISTORY", NoHistory, "Do not preserve readline history"},
 		"OLLAMA_NOPRUNE":           {"OLLAMA_NOPRUNE", NoPrune, "Do not prune model blobs on startup"},
-		"OLLAMA_NUM_PARALLEL":      {"OLLAMA_NUM_PARALLEL", NumParallel, "Maximum number of parallel requests"},
+		"OLLAMA_NUM_PARALLEL":      {"OLLAMA_NUM_PARALLEL", NumParallel, "Maximum number of parallel requests (default 1)"},
 		"OLLAMA_ORIGINS":           {"OLLAMA_ORIGINS", AllowOrigins, "A comma separated list of allowed origins"},
 		"OLLAMA_RUNNERS_DIR":       {"OLLAMA_RUNNERS_DIR", RunnersDir, "Location for runners"},
-		"OLLAMA_SCHED_SPREAD":      {"OLLAMA_SCHED_SPREAD", SchedSpread, "Always schedule model across all GPUs"},
 		"OLLAMA_TMPDIR":            {"OLLAMA_TMPDIR", TmpDir, "Location for temporary files"},
 	}
-	if runtime.GOOS != "darwin" {
-		ret["CUDA_VISIBLE_DEVICES"] = EnvVar{"CUDA_VISIBLE_DEVICES", CudaVisibleDevices, "Set which NVIDIA devices are visible"}
-		ret["HIP_VISIBLE_DEVICES"] = EnvVar{"HIP_VISIBLE_DEVICES", HipVisibleDevices, "Set which AMD devices are visible"}
-		ret["ROCR_VISIBLE_DEVICES"] = EnvVar{"ROCR_VISIBLE_DEVICES", RocrVisibleDevices, "Set which AMD devices are visible"}
-		ret["GPU_DEVICE_ORDINAL"] = EnvVar{"GPU_DEVICE_ORDINAL", GpuDeviceOrdinal, "Set which AMD devices are visible"}
-		ret["HSA_OVERRIDE_GFX_VERSION"] = EnvVar{"HSA_OVERRIDE_GFX_VERSION", HsaOverrideGfxVersion, "Override the gfx used for all detected AMD GPUs"}
-		ret["OLLAMA_INTEL_GPU"] = EnvVar{"OLLAMA_INTEL_GPU", IntelGpu, "Enable experimental Intel GPU detection"}
-	}
-	return ret
 }
 
 func Values() map[string]string {
@@ -128,10 +104,9 @@ func clean(key string) string {
 
 func init() {
 	// default values
-	NumParallel = 0 // Autoselect
-	MaxRunners = 0  // Autoselect
+	NumParallel = 1
+	MaxRunners = 1
 	MaxQueuedRequests = 512
-	KeepAlive = 5 * time.Minute
 
 	LoadConfig()
 }
@@ -191,12 +166,22 @@ func LoadConfig() {
 
 	TmpDir = clean("OLLAMA_TMPDIR")
 
+	userLimit := clean("OLLAMA_MAX_VRAM")
+	if userLimit != "" {
+		avail, err := strconv.ParseUint(userLimit, 10, 64)
+		if err != nil {
+			slog.Error("invalid setting, ignoring", "OLLAMA_MAX_VRAM", userLimit, "error", err)
+		} else {
+			MaxVRAM = avail
+		}
+	}
+
 	LLMLibrary = clean("OLLAMA_LLM_LIBRARY")
 
 	if onp := clean("OLLAMA_NUM_PARALLEL"); onp != "" {
 		val, err := strconv.Atoi(onp)
-		if err != nil {
-			slog.Error("invalid setting, ignoring", "OLLAMA_NUM_PARALLEL", onp, "error", err)
+		if err != nil || val <= 0 {
+			slog.Error("invalid setting must be greater than zero", "OLLAMA_NUM_PARALLEL", onp, "error", err)
 		} else {
 			NumParallel = val
 		}
@@ -206,15 +191,6 @@ func LoadConfig() {
 		NoHistory = true
 	}
 
-	if spread := clean("OLLAMA_SCHED_SPREAD"); spread != "" {
-		s, err := strconv.ParseBool(spread)
-		if err == nil {
-			SchedSpread = s
-		} else {
-			SchedSpread = true
-		}
-	}
-
 	if noprune := clean("OLLAMA_NOPRUNE"); noprune != "" {
 		NoPrune = true
 	}
@@ -241,7 +217,7 @@ func LoadConfig() {
 	if maxRunners != "" {
 		m, err := strconv.Atoi(maxRunners)
 		if err != nil {
-			slog.Error("invalid setting, ignoring", "OLLAMA_MAX_LOADED_MODELS", maxRunners, "error", err)
+			slog.Error("invalid setting", "OLLAMA_MAX_LOADED_MODELS", maxRunners, "error", err)
 		} else {
 			MaxRunners = m
 		}
@@ -250,16 +226,13 @@ func LoadConfig() {
 	if onp := os.Getenv("OLLAMA_MAX_QUEUE"); onp != "" {
 		p, err := strconv.Atoi(onp)
 		if err != nil || p <= 0 {
-			slog.Error("invalid setting, ignoring", "OLLAMA_MAX_QUEUE", onp, "error", err)
+			slog.Error("invalid setting", "OLLAMA_MAX_QUEUE", onp, "error", err)
 		} else {
 			MaxQueuedRequests = p
 		}
 	}
 
-	ka := clean("OLLAMA_KEEP_ALIVE")
-	if ka != "" {
-		loadKeepAlive(ka)
-	}
+	KeepAlive = clean("OLLAMA_KEEP_ALIVE")
 
 	var err error
 	ModelsDir, err = getModelsDir()
@@ -271,16 +244,6 @@ func LoadConfig() {
 	if err != nil {
 		slog.Error("invalid setting", "OLLAMA_HOST", Host, "error", err, "using default port", Host.Port)
 	}
-
-	if set, err := strconv.ParseBool(clean("OLLAMA_INTEL_GPU")); err == nil {
-		IntelGpu = set
-	}
-
-	CudaVisibleDevices = clean("CUDA_VISIBLE_DEVICES")
-	HipVisibleDevices = clean("HIP_VISIBLE_DEVICES")
-	RocrVisibleDevices = clean("ROCR_VISIBLE_DEVICES")
-	GpuDeviceOrdinal = clean("GPU_DEVICE_ORDINAL")
-	HsaOverrideGfxVersion = clean("HSA_OVERRIDE_GFX_VERSION")
 }
 
 func getModelsDir() (string, error) {
@@ -337,24 +300,3 @@ func getOllamaHost() (*OllamaHost, error) {
 		Port:   port,
 	}, nil
 }
-
-func loadKeepAlive(ka string) {
-	v, err := strconv.Atoi(ka)
-	if err != nil {
-		d, err := time.ParseDuration(ka)
-		if err == nil {
-			if d < 0 {
-				KeepAlive = time.Duration(math.MaxInt64)
-			} else {
-				KeepAlive = d
-			}
-		}
-	} else {
-		d := time.Duration(v) * time.Second
-		if d < 0 {
-			KeepAlive = time.Duration(math.MaxInt64)
-		} else {
-			KeepAlive = d
-		}
-	}
-}

envconfig/config_test.go

@@ -2,10 +2,8 @@ package envconfig
 
 import (
 	"fmt"
-	"math"
 	"net"
 	"testing"
-	"time"
 
 	"github.com/stretchr/testify/assert"
 	"github.com/stretchr/testify/require"
@@ -25,21 +23,6 @@ func TestConfig(t *testing.T) {
 	t.Setenv("OLLAMA_FLASH_ATTENTION", "1")
 	LoadConfig()
 	require.True(t, FlashAttention)
-	t.Setenv("OLLAMA_KEEP_ALIVE", "")
-	LoadConfig()
-	require.Equal(t, 5*time.Minute, KeepAlive)
-	t.Setenv("OLLAMA_KEEP_ALIVE", "3")
-	LoadConfig()
-	require.Equal(t, 3*time.Second, KeepAlive)
-	t.Setenv("OLLAMA_KEEP_ALIVE", "1h")
-	LoadConfig()
-	require.Equal(t, 1*time.Hour, KeepAlive)
-	t.Setenv("OLLAMA_KEEP_ALIVE", "-1s")
-	LoadConfig()
-	require.Equal(t, time.Duration(math.MaxInt64), KeepAlive)
-	t.Setenv("OLLAMA_KEEP_ALIVE", "-1")
-	LoadConfig()
-	require.Equal(t, time.Duration(math.MaxInt64), KeepAlive)
 }
 
 func TestClientFromEnvironment(t *testing.T) {

examples/go-chat/main.go

@@ -35,7 +35,7 @@ func main() {
 
 	ctx := context.Background()
 	req := &api.ChatRequest{
-		Model:    "llama3.1",
+		Model:    "llama3",
 		Messages: messages,
 	}
 

examples/go-generate-streaming/main.go

@@ -16,7 +16,7 @@ func main() {
 
 	// By default, GenerateRequest is streaming.
 	req := &api.GenerateRequest{
-		Model:  "gemma2",
+		Model:  "gemma",
 		Prompt: "how many planets are there?",
 	}
 

examples/go-generate/main.go

@@ -15,7 +15,7 @@ func main() {
 	}
 
 	req := &api.GenerateRequest{
-		Model:  "gemma2",
+		Model:  "gemma",
 		Prompt: "how many planets are there?",
 
 		// set streaming to false

examples/langchain-python-rag-document/README.md

@@ -4,14 +4,6 @@ This example provides an interface for asking questions to a PDF document.
 
 ## Setup
 
-1. Ensure you have the `llama3.1` model installed:
-
-```
-ollama pull llama3.1
-```
-
-2. Install the Python Requirements.
-
 ```
 pip install -r requirements.txt
 ```

examples/langchain-python-rag-document/main.py

@@ -51,7 +51,7 @@ while True:
         template=template,
     )
 
-    llm = Ollama(model="llama3.1", callback_manager=CallbackManager([StreamingStdOutCallbackHandler()]))
+    llm = Ollama(model="llama3:8b", callback_manager=CallbackManager([StreamingStdOutCallbackHandler()]))
     qa_chain = RetrievalQA.from_chain_type(
         llm,
         retriever=vectorstore.as_retriever(),

examples/langchain-python-rag-websummary/README.md

@@ -4,10 +4,10 @@ This example summarizes the website, [https://ollama.com/blog/run-llama2-uncenso
 
 ## Running the Example
 
-1. Ensure you have the `llama3.1` model installed:
+1. Ensure you have the `llama2` model installed:
 
    ```bash
-   ollama pull llama3.1
+   ollama pull llama2
    ```
 
 2. Install the Python Requirements.

examples/langchain-python-rag-websummary/main.py

@@ -5,8 +5,8 @@ from langchain.chains.summarize import load_summarize_chain
 loader = WebBaseLoader("https://ollama.com/blog/run-llama2-uncensored-locally")
 docs = loader.load()
 
-llm = Ollama(model="llama3.1")
+llm = Ollama(model="llama3")
 chain = load_summarize_chain(llm, chain_type="stuff")
 
-result = chain.invoke(docs)
+result = chain.invoke(docs) 
 print(result)

examples/langchain-python-simple/README.md

@@ -4,10 +4,10 @@ This example is a basic "hello world" of using LangChain with Ollama.
 
 ## Running the Example
 
-1. Ensure you have the `llama3.1` model installed:
+1. Ensure you have the `llama3` model installed:
 
    ```bash
-   ollama pull llama3.1
+   ollama pull llama3
    ```
 
 2. Install the Python Requirements.

examples/langchain-python-simple/main.py

@@ -1,6 +1,6 @@
 from langchain.llms import Ollama
 
 input = input("What is your question?")
-llm = Ollama(model="llama3.1")
+llm = Ollama(model="llama3")
 res = llm.predict(input)
 print (res)

examples/modelfile-mario/Modelfile

@@ -1,4 +1,4 @@
-FROM llama3.1
+FROM llama3
 PARAMETER temperature 1
 SYSTEM """
 You are Mario from super mario bros, acting as an assistant.

examples/modelfile-mario/readme.md

@@ -2,12 +2,12 @@
 
 # Example character: Mario
 
-This example shows how to create a basic character using Llama3.1 as the base model.
+This example shows how to create a basic character using Llama3 as the base model.
 
 To run this example:
 
 1. Download the Modelfile
-2. `ollama pull llama3.1` to get the base model used in the model file.
+2. `ollama pull llama3` to get the base model used in the model file.
 3. `ollama create NAME -f ./Modelfile`
 4. `ollama run NAME`
 
@@ -18,7 +18,7 @@ Ask it some questions like "Who are you?" or "Is Peach in trouble again?"
 What the model file looks like:
 
 ```
-FROM llama3.1
+FROM llama3
 PARAMETER temperature 1
 SYSTEM """
 You are Mario from Super Mario Bros, acting as an assistant.

examples/python-dockerit/dockerit.py

@@ -4,7 +4,7 @@ imageName = input("Enter the name of the image: ")
 client = docker.from_env()
 s = requests.Session()
 output=""
-with s.post('http://localhost:11434/api/generate', json={'model': 'mattw/dockerit', 'prompt': inputDescription}, stream=True) as r:
+with s.post('http://localhost:11434/api/generate', json={'model': 'dockerit', 'prompt': inputDescription}, stream=True) as r:
   for line in r.iter_lines():
     if line:
       j = json.loads(line)

examples/python-json-datagenerator/predefinedschema.py

@@ -2,7 +2,7 @@ import requests
 import json
 import random
 
-model = "llama3.1"
+model = "llama3"
 template = {
   "firstName": "",
   "lastName": "",

examples/python-json-datagenerator/randomaddresses.py

@@ -12,7 +12,7 @@ countries = [
     "France",
 ]
 country = random.choice(countries)
-model = "llama3.1"
+model = "llama3"
 
 prompt = f"generate one realistically believable sample data set of a persons first name, last name, address in {country}, and phone number. Do not use common names. Respond using JSON. Key names should have no backslashes, values should use plain ascii with no special characters."
 

examples/python-json-datagenerator/readme.md

@@ -6,10 +6,10 @@ There are two python scripts in this example. `randomaddresses.py` generates ran
 
 ## Running the Example
 
-1. Ensure you have the `llama3.1` model installed:
+1. Ensure you have the `llama3` model installed:
 
    ```bash
-   ollama pull llama3.1
+   ollama pull llama3
    ```
 
 2. Install the Python Requirements.

examples/python-simplechat/client.py

@@ -2,7 +2,7 @@ import json
 import requests
 
 # NOTE: ollama must be running for this to work, start the ollama app or run `ollama serve`
-model = "llama3.1"  # TODO: update this for whatever model you wish to use
+model = "llama3"  # TODO: update this for whatever model you wish to use
 
 
 def chat(messages):

examples/python-simplechat/readme.md

@@ -4,10 +4,10 @@ The **chat** endpoint is one of two ways to generate text from an LLM with Ollam
 
 ## Running the Example
 
-1. Ensure you have the `llama3.1` model installed:
+1. Ensure you have the `llama3` model installed:
 
    ```bash
-   ollama pull llama3.1
+   ollama pull llama3
    ```
 
 2. Install the Python Requirements.

examples/typescript-simplechat/client.ts

@@ -1,6 +1,6 @@
 import * as readline from "readline";
 
-const model = "llama3.1";
+const model = "llama3";
 type Message = {
   role: "assistant" | "user" | "system";
   content: string;

go.mod

@@ -18,7 +18,6 @@ require (
 require (
 	github.com/agnivade/levenshtein v1.1.1
 	github.com/d4l3k/go-bfloat16 v0.0.0-20211005043715-690c3bdd05f1
-	github.com/google/go-cmp v0.6.0
 	github.com/mattn/go-runewidth v0.0.14
 	github.com/nlpodyssey/gopickle v0.3.0
 	github.com/pdevine/tensor v0.0.0-20240510204454-f88f4562727c
@@ -72,7 +71,7 @@ require (
 	golang.org/x/net v0.25.0 // indirect
 	golang.org/x/sys v0.20.0
 	golang.org/x/term v0.20.0
-	golang.org/x/text v0.15.0
+	golang.org/x/text v0.15.0 // indirect
 	google.golang.org/protobuf v1.34.1
 	gopkg.in/yaml.v3 v3.0.1 // indirect
 )

gpu/amd_common.go

@@ -49,17 +49,9 @@ func rocmGetVisibleDevicesEnv(gpuInfo []GpuInfo) (string, string) {
 }
 
 func commonAMDValidateLibDir() (string, error) {
-	// Favor our bundled version
-
-	// Installer payload location if we're running the installed binary
-	exe, err := os.Executable()
-	if err == nil {
-		rocmTargetDir := filepath.Join(filepath.Dir(exe), "rocm")
-		if rocmLibUsable(rocmTargetDir) {
-			slog.Debug("detected ROCM next to ollama executable " + rocmTargetDir)
-			return rocmTargetDir, nil
-		}
-	}
+	// We try to favor system paths first, so that we can wire up the subprocess to use
+	// the system version.  Only use our bundled version if the system version doesn't work
+	// This gives users a more recovery options if versions have subtle problems at runtime
 
 	// Prefer explicit HIP env var
 	hipPath := os.Getenv("HIP_PATH")
@@ -95,5 +87,14 @@ func commonAMDValidateLibDir() (string, error) {
 		}
 	}
 
+	// Installer payload location if we're running the installed binary
+	exe, err := os.Executable()
+	if err == nil {
+		rocmTargetDir := filepath.Join(filepath.Dir(exe), "rocm")
+		if rocmLibUsable(rocmTargetDir) {
+			slog.Debug("detected ROCM next to ollama executable " + rocmTargetDir)
+			return rocmTargetDir, nil
+		}
+	}
 	return "", fmt.Errorf("no suitable rocm found, falling back to CPU")
 }

gpu/amd_hip_windows.go

@@ -33,10 +33,9 @@ type HipLib struct {
 }
 
 func NewHipLib() (*HipLib, error) {
-	// At runtime we depend on v6, so discover GPUs with the same library for a consistent set of GPUs
-	h, err := windows.LoadLibrary("amdhip64_6.dll")
+	h, err := windows.LoadLibrary("amdhip64.dll")
 	if err != nil {
-		return nil, fmt.Errorf("unable to load amdhip64_6.dll, please make sure to upgrade to the latest amd driver: %w", err)
+		return nil, fmt.Errorf("unable to load amdhip64.dll: %w", err)
 	}
 	hl := &HipLib{}
 	hl.dll = h
@@ -85,8 +84,9 @@ func (hl *HipLib) AMDDriverVersion() (driverMajor, driverMinor int, err error) {
 	}
 
 	slog.Debug("hipDriverGetVersion", "version", version)
-	driverMajor = version / 10000000
-	driverMinor = (version - (driverMajor * 10000000)) / 100000
+	// TODO - this isn't actually right, but the docs claim hipDriverGetVersion isn't accurate anyway...
+	driverMajor = version / 1000
+	driverMinor = (version - (driverMajor * 1000)) / 10
 
 	return driverMajor, driverMinor, nil
 }

gpu/amd_linux.go

@@ -10,11 +10,9 @@ import (
 	"path/filepath"
 	"regexp"
 	"slices"
-	"sort"
 	"strconv"
 	"strings"
 
-	"github.com/ollama/ollama/envconfig"
 	"github.com/ollama/ollama/format"
 )
 
@@ -27,16 +25,7 @@ const (
 
 	// Prefix with the node dir
 	GPUTotalMemoryFileGlob = "mem_banks/*/properties" // size_in_bytes line
-
-	// Direct Rendering Manager sysfs location
-	DRMDeviceDirGlob   = "/sys/class/drm/card*/device"
-	DRMTotalMemoryFile = "mem_info_vram_total"
-	DRMUsedMemoryFile  = "mem_info_vram_used"
-
-	// In hex; properties file is in decimal
-	DRMUniqueIDFile = "unique_id"
-	DRMVendorFile   = "vendor"
-	DRMDeviceFile   = "device"
+	GPUUsedMemoryFileGlob  = "mem_banks/*/used_memory"
 )
 
 var (
@@ -46,8 +35,8 @@ var (
 )
 
 // Gather GPU information from the amdgpu driver if any supported GPUs are detected
-func AMDGetGPUInfo() []RocmGPUInfo {
-	resp := []RocmGPUInfo{}
+func AMDGetGPUInfo() []GpuInfo {
+	resp := []GpuInfo{}
 	if !AMDDetected() {
 		return resp
 	}
@@ -61,9 +50,9 @@ func AMDGetGPUInfo() []RocmGPUInfo {
 
 	// Determine if the user has already pre-selected which GPUs to look at, then ignore the others
 	var visibleDevices []string
-	hipVD := envconfig.HipVisibleDevices   // zero based index only
-	rocrVD := envconfig.RocrVisibleDevices // zero based index or UUID, but consumer cards seem to not support UUID
-	gpuDO := envconfig.GpuDeviceOrdinal    // zero based index
+	hipVD := os.Getenv("HIP_VISIBLE_DEVICES")   // zero based index only
+	rocrVD := os.Getenv("ROCR_VISIBLE_DEVICES") // zero based index or UUID, but consumer cards seem to not support UUID
+	gpuDO := os.Getenv("GPU_DEVICE_ORDINAL")    // zero based index
 	switch {
 	// TODO is this priorty order right?
 	case hipVD != "":
@@ -76,27 +65,13 @@ func AMDGetGPUInfo() []RocmGPUInfo {
 		visibleDevices = strings.Split(gpuDO, ",")
 	}
 
-	gfxOverride := envconfig.HsaOverrideGfxVersion
+	gfxOverride := os.Getenv("HSA_OVERRIDE_GFX_VERSION")
 	var supported []string
 	libDir := ""
 
 	// The amdgpu driver always exposes the host CPU(s) first, but we have to skip them and subtract
 	// from the other IDs to get alignment with the HIP libraries expectations (zero is the first GPU, not the CPU)
 	matches, _ := filepath.Glob(GPUPropertiesFileGlob)
-	sort.Slice(matches, func(i, j int) bool {
-		// /sys/class/kfd/kfd/topology/nodes/<number>/properties
-		a, err := strconv.ParseInt(filepath.Base(filepath.Dir(matches[i])), 10, 64)
-		if err != nil {
-			slog.Debug("parse err", "error", err, "match", matches[i])
-			return false
-		}
-		b, err := strconv.ParseInt(filepath.Base(filepath.Dir(matches[j])), 10, 64)
-		if err != nil {
-			slog.Debug("parse err", "error", err, "match", matches[i])
-			return false
-		}
-		return a < b
-	})
 	cpuCount := 0
 	for _, match := range matches {
 		slog.Debug("evaluating amdgpu node " + match)
@@ -115,7 +90,7 @@ func AMDGetGPUInfo() []RocmGPUInfo {
 		scanner := bufio.NewScanner(fp)
 		isCPU := false
 		var major, minor, patch uint64
-		var vendor, device, uniqueID uint64
+		var vendor, device uint64
 		for scanner.Scan() {
 			line := strings.TrimSpace(scanner.Text())
 			// Note: we could also use "cpu_cores_count X" where X is greater than zero to detect CPUs
@@ -146,43 +121,30 @@ func AMDGetGPUInfo() []RocmGPUInfo {
 			} else if strings.HasPrefix(line, "vendor_id") {
 				ver := strings.Fields(line)
 				if len(ver) != 2 {
-					slog.Debug("malformed", "vendor_id", line)
+					slog.Debug("malformed vendor_id", "vendor_id", line)
 					continue
 				}
-				vendor, err = strconv.ParseUint(ver[1], 10, 64)
+				vendor, err = strconv.ParseUint(ver[1], 10, 32)
 				if err != nil {
-					slog.Debug("malformed", "vendor_id", line, "error", err)
+					slog.Debug("malformed vendor_id" + line)
 				}
 			} else if strings.HasPrefix(line, "device_id") {
 				ver := strings.Fields(line)
 				if len(ver) != 2 {
-					slog.Debug("malformed", "device_id", line)
+					slog.Debug("malformed device_id", "device_id", line)
 					continue
 				}
-				device, err = strconv.ParseUint(ver[1], 10, 64)
+				device, err = strconv.ParseUint(ver[1], 10, 32)
 				if err != nil {
-					slog.Debug("malformed", "device_id", line, "error", err)
-				}
-			} else if strings.HasPrefix(line, "unique_id") {
-				ver := strings.Fields(line)
-				if len(ver) != 2 {
-					slog.Debug("malformed", "unique_id", line)
-					continue
-				}
-				uniqueID, err = strconv.ParseUint(ver[1], 10, 64)
-				if err != nil {
-					slog.Debug("malformed", "unique_id", line, "error", err)
+					slog.Debug("malformed device_id" + line)
 				}
 			}
+
 			// TODO - any other properties we want to extract and record?
 			// vendor_id + device_id -> pci lookup for "Name"
 			// Other metrics that may help us understand relative performance between multiple GPUs
 		}
 
-		// Note: while ./mem_banks/*/used_memory exists, it doesn't appear to take other VRAM consumers
-		// into consideration, so we instead map the device over to the DRM driver sysfs nodes which
-		// do reliably report VRAM usage.
-
 		if isCPU {
 			cpuCount++
 			continue
@@ -194,7 +156,7 @@ func AMDGetGPUInfo() []RocmGPUInfo {
 		// Shouldn't happen, but just in case...
 		if gpuID < 0 {
 			slog.Error("unexpected amdgpu sysfs data resulted in negative GPU ID, please set OLLAMA_DEBUG=1 and report an issue")
-			return nil
+			return []GpuInfo{}
 		}
 
 		if int(major) < RocmComputeMin {
@@ -205,68 +167,65 @@ func AMDGetGPUInfo() []RocmGPUInfo {
 		// Look up the memory for the current node
 		totalMemory := uint64(0)
 		usedMemory := uint64(0)
-		var usedFile string
-		mapping := []struct {
-			id       uint64
-			filename string
-		}{
-			{vendor, DRMVendorFile},
-			{device, DRMDeviceFile},
-			{uniqueID, DRMUniqueIDFile}, // Not all devices will report this
+		propGlob := filepath.Join(AMDNodesSysfsDir, strconv.Itoa(nodeID), GPUTotalMemoryFileGlob)
+		propFiles, err := filepath.Glob(propGlob)
+		if err != nil {
+			slog.Warn("error looking up total GPU memory", "glob", propGlob, "error", err)
 		}
-		slog.Debug("mapping amdgpu to drm sysfs nodes", "amdgpu", match, "vendor", vendor, "device", device, "unique_id", uniqueID)
-		// Map over to DRM location to find the total/free memory
-		drmMatches, _ := filepath.Glob(DRMDeviceDirGlob)
-		for _, devDir := range drmMatches {
-			matched := true
-			for _, m := range mapping {
-				if m.id == 0 {
-					// Null ID means it didn't populate, so we can't use it to match
-					continue
-				}
-				filename := filepath.Join(devDir, m.filename)
-				buf, err := os.ReadFile(filename)
-				if err != nil {
-					slog.Debug("failed to read sysfs node", "file", filename, "error", err)
-					matched = false
-					break
-				}
-				// values here are in hex, strip off the lead 0x and parse so we can compare the numeric (decimal) values in amdgpu
-				cmp, err := strconv.ParseUint(strings.TrimPrefix(strings.TrimSpace(string(buf)), "0x"), 16, 64)
-				if err != nil {
-					slog.Debug("failed to parse sysfs node", "file", filename, "error", err)
-					matched = false
-					break
-				}
-				if cmp != m.id {
-					matched = false
-					break
-				}
-			}
-			if !matched {
+		// 1 or more memory banks - sum the values of all of them
+		for _, propFile := range propFiles {
+			fp, err := os.Open(propFile)
+			if err != nil {
+				slog.Warn("failed to open sysfs node", "file", propFile, "erroir", err)
 				continue
 			}
-
-			// Found the matching DRM directory
-			slog.Debug("matched", "amdgpu", match, "drm", devDir)
-			totalFile := filepath.Join(devDir, DRMTotalMemoryFile)
-			buf, err := os.ReadFile(totalFile)
-			if err != nil {
-				slog.Debug("failed to read sysfs node", "file", totalFile, "error", err)
-				break
+			defer fp.Close()
+			scanner := bufio.NewScanner(fp)
+			for scanner.Scan() {
+				line := strings.TrimSpace(scanner.Text())
+				if strings.HasPrefix(line, "size_in_bytes") {
+					ver := strings.Fields(line)
+					if len(ver) != 2 {
+						slog.Warn("malformed " + line)
+						continue
+					}
+					bankSizeInBytes, err := strconv.ParseUint(ver[1], 10, 64)
+					if err != nil {
+						slog.Warn("malformed int " + line)
+						continue
+					}
+					totalMemory += bankSizeInBytes
+				}
 			}
-			totalMemory, err = strconv.ParseUint(strings.TrimSpace(string(buf)), 10, 64)
+		}
+		if totalMemory == 0 {
+			slog.Warn("amdgpu reports zero total memory", "gpu", gpuID)
+			continue
+		}
+		usedGlob := filepath.Join(AMDNodesSysfsDir, strconv.Itoa(nodeID), GPUUsedMemoryFileGlob)
+		usedFiles, err := filepath.Glob(usedGlob)
+		if err != nil {
+			slog.Warn("error looking up used GPU memory", "glob", usedGlob, "error", err)
+			continue
+		}
+		for _, usedFile := range usedFiles {
+			fp, err := os.Open(usedFile)
 			if err != nil {
-				slog.Debug("failed to parse sysfs node", "file", totalFile, "error", err)
-				break
+				slog.Warn("failed to open sysfs node", "file", usedFile, "error", err)
+				continue
 			}
-
-			usedFile = filepath.Join(devDir, DRMUsedMemoryFile)
-			usedMemory, err = getFreeMemory(usedFile)
+			defer fp.Close()
+			data, err := io.ReadAll(fp)
 			if err != nil {
-				slog.Debug("failed to update used memory", "error", err)
+				slog.Warn("failed to read sysfs node", "file", usedFile, "error", err)
+				continue
 			}
-			break
+			used, err := strconv.ParseUint(strings.TrimSpace(string(data)), 10, 64)
+			if err != nil {
+				slog.Warn("malformed used memory", "data", string(data), "error", err)
+				continue
+			}
+			usedMemory += used
 		}
 
 		// iGPU detection, remove this check once we can support an iGPU variant of the rocm library
@@ -282,21 +241,18 @@ func AMDGetGPUInfo() []RocmGPUInfo {
 
 		slog.Debug("amdgpu memory", "gpu", gpuID, "total", format.HumanBytes2(totalMemory))
 		slog.Debug("amdgpu memory", "gpu", gpuID, "available", format.HumanBytes2(totalMemory-usedMemory))
-		gpuInfo := RocmGPUInfo{
-			GpuInfo: GpuInfo{
-				Library: "rocm",
-				memInfo: memInfo{
-					TotalMemory: totalMemory,
-					FreeMemory:  (totalMemory - usedMemory),
-				},
-				ID:            strconv.Itoa(gpuID),
-				Name:          name,
-				Compute:       fmt.Sprintf("gfx%d%x%x", major, minor, patch),
-				MinimumMemory: rocmMinimumMemory,
-				DriverMajor:   driverMajor,
-				DriverMinor:   driverMinor,
+		gpuInfo := GpuInfo{
+			Library: "rocm",
+			memInfo: memInfo{
+				TotalMemory: totalMemory,
+				FreeMemory:  (totalMemory - usedMemory),
 			},
-			usedFilepath: usedFile,
+			ID:            fmt.Sprintf("%d", gpuID),
+			Name:          name,
+			Compute:       fmt.Sprintf("gfx%d%x%x", major, minor, patch),
+			MinimumMemory: rocmMinimumMemory,
+			DriverMajor:   driverMajor,
+			DriverMinor:   driverMinor,
 		}
 
 		// If the user wants to filter to a subset of devices, filter out if we aren't a match
@@ -320,7 +276,7 @@ func AMDGetGPUInfo() []RocmGPUInfo {
 			libDir, err = AMDValidateLibDir()
 			if err != nil {
 				slog.Warn("unable to verify rocm library, will use cpu", "error", err)
-				return nil
+				return []GpuInfo{}
 			}
 		}
 		gpuInfo.DependencyPath = libDir
@@ -331,7 +287,7 @@ func AMDGetGPUInfo() []RocmGPUInfo {
 				supported, err = GetSupportedGFX(libDir)
 				if err != nil {
 					slog.Warn("failed to lookup supported GFX types, falling back to CPU mode", "error", err)
-					return nil
+					return []GpuInfo{}
 				}
 				slog.Debug("rocm supported GPUs", "types", supported)
 			}
@@ -348,11 +304,6 @@ func AMDGetGPUInfo() []RocmGPUInfo {
 			slog.Info("skipping rocm gfx compatibility check", "HSA_OVERRIDE_GFX_VERSION", gfxOverride)
 		}
 
-		// Check for env var workarounds
-		if name == "1002:687f" { // Vega RX 56
-			gpuInfo.EnvWorkarounds = append(gpuInfo.EnvWorkarounds, [2]string{"HSA_ENABLE_SDMA", "0"})
-		}
-
 		// The GPU has passed all the verification steps and is supported
 		resp = append(resp, gpuInfo)
 	}
@@ -427,31 +378,3 @@ func AMDDriverVersion() (driverMajor, driverMinor int, err error) {
 	}
 	return driverMajor, driverMinor, nil
 }
-
-func (gpus RocmGPUInfoList) RefreshFreeMemory() error {
-	if len(gpus) == 0 {
-		return nil
-	}
-	for i := range gpus {
-		usedMemory, err := getFreeMemory(gpus[i].usedFilepath)
-		if err != nil {
-			return err
-		}
-		slog.Debug("updating rocm free memory", "gpu", gpus[i].ID, "name", gpus[i].Name, "before", format.HumanBytes2(gpus[i].FreeMemory), "now", format.HumanBytes2(gpus[i].TotalMemory-usedMemory))
-		gpus[i].FreeMemory = gpus[i].TotalMemory - usedMemory
-	}
-	return nil
-}
-
-func getFreeMemory(usedFile string) (uint64, error) {
-	buf, err := os.ReadFile(usedFile)
-	if err != nil {
-		return 0, fmt.Errorf("failed to read sysfs node %s %w", usedFile, err)
-	}
-	usedMemory, err := strconv.ParseUint(strings.TrimSpace(string(buf)), 10, 64)
-	if err != nil {
-		slog.Debug("failed to parse sysfs node", "file", usedFile, "error", err)
-		return 0, fmt.Errorf("failed to parse sysfs node %s %w", usedFile, err)
-	}
-	return usedMemory, nil
-}

gpu/amd_windows.go

@@ -7,10 +7,8 @@ import (
 	"os"
 	"path/filepath"
 	"slices"
-	"strconv"
 	"strings"
 
-	"github.com/ollama/ollama/envconfig"
 	"github.com/ollama/ollama/format"
 )
 
@@ -22,12 +20,12 @@ const (
 
 var (
 	// Used to validate if the given ROCm lib is usable
-	ROCmLibGlobs          = []string{"hipblas.dll", "rocblas"}                 // This is not sufficient to discern v5 vs v6
-	RocmStandardLocations = []string{"C:\\Program Files\\AMD\\ROCm\\6.1\\bin"} // TODO glob?
+	ROCmLibGlobs          = []string{"hipblas.dll", "rocblas"}                 // TODO - probably include more coverage of files here...
+	RocmStandardLocations = []string{"C:\\Program Files\\AMD\\ROCm\\5.7\\bin"} // TODO glob?
 )
 
-func AMDGetGPUInfo() []RocmGPUInfo {
-	resp := []RocmGPUInfo{}
+func AMDGetGPUInfo() []GpuInfo {
+	resp := []GpuInfo{}
 	hl, err := NewHipLib()
 	if err != nil {
 		slog.Debug(err.Error())
@@ -35,11 +33,12 @@ func AMDGetGPUInfo() []RocmGPUInfo {
 	}
 	defer hl.Release()
 
-	driverMajor, driverMinor, err := hl.AMDDriverVersion()
-	if err != nil {
-		// For now this is benign, but we may eventually need to fail compatibility checks
-		slog.Debug("error looking up amd driver version", "error", err)
-	}
+	// TODO - this reports incorrect version information, so omitting for now
+	// driverMajor, driverMinor, err := hl.AMDDriverVersion()
+	// if err != nil {
+	// 	// For now this is benign, but we may eventually need to fail compatibility checks
+	// 	slog.Debug("error looking up amd driver version", "error", err)
+	// }
 
 	// Note: the HIP library automatically handles subsetting to any HIP_VISIBLE_DEVICES the user specified
 	count := hl.HipGetDeviceCount()
@@ -53,7 +52,7 @@ func AMDGetGPUInfo() []RocmGPUInfo {
 	}
 
 	var supported []string
-	gfxOverride := envconfig.HsaOverrideGfxVersion
+	gfxOverride := os.Getenv("HSA_OVERRIDE_GFX_VERSION")
 	if gfxOverride == "" {
 		supported, err = GetSupportedGFX(libDir)
 		if err != nil {
@@ -92,8 +91,7 @@ func AMDGetGPUInfo() []RocmGPUInfo {
 			continue
 		}
 		if gfxOverride == "" {
-			// Strip off Target Features when comparing
-			if !slices.Contains[[]string, string](supported, strings.Split(gfx, ":")[0]) {
+			if !slices.Contains[[]string, string](supported, gfx) {
 				slog.Warn("amdgpu is not supported", "gpu", i, "gpu_type", gfx, "library", libDir, "supported_types", supported)
 				// TODO - consider discrete markdown just for ROCM troubleshooting?
 				slog.Warn("See https://github.com/ollama/ollama/blob/main/docs/troubleshooting.md for HSA_OVERRIDE_GFX_VERSION usage")
@@ -115,27 +113,25 @@ func AMDGetGPUInfo() []RocmGPUInfo {
 			continue
 		}
 
+		// TODO revisit this once ROCm v6 is available on windows.
+		// v5.7 only reports VRAM used by this process, so it's completely wrong and unusable
 		slog.Debug("amdgpu memory", "gpu", i, "total", format.HumanBytes2(totalMemory))
 		slog.Debug("amdgpu memory", "gpu", i, "available", format.HumanBytes2(freeMemory))
-		gpuInfo := RocmGPUInfo{
-			GpuInfo: GpuInfo{
-				Library: "rocm",
-				memInfo: memInfo{
-					TotalMemory: totalMemory,
-					FreeMemory:  freeMemory,
-				},
-				// Free memory reporting on Windows is not reliable until we bump to ROCm v6.2
-				UnreliableFreeMemory: true,
-
-				ID:             strconv.Itoa(i), // TODO this is probably wrong if we specify visible devices
-				DependencyPath: libDir,
-				MinimumMemory:  rocmMinimumMemory,
-				Name:           name,
-				Compute:        gfx,
-				DriverMajor:    driverMajor,
-				DriverMinor:    driverMinor,
+		gpuInfo := GpuInfo{
+			Library: "rocm",
+			memInfo: memInfo{
+				TotalMemory: totalMemory,
+				FreeMemory:  freeMemory,
 			},
-			index: i,
+			ID:             fmt.Sprintf("%d", i), // TODO this is probably wrong if we specify visible devices
+			DependencyPath: libDir,
+			MinimumMemory:  rocmMinimumMemory,
+			Name:           name,
+			Compute:        gfx,
+
+			// TODO - this information isn't accurate on windows, so don't report it until we find the right way to retrieve
+			// DriverMajor:    driverMajor,
+			// DriverMinor:    driverMinor,
 		}
 
 		resp = append(resp, gpuInfo)
@@ -163,30 +159,3 @@ func AMDValidateLibDir() (string, error) {
 	slog.Warn("amdgpu detected, but no compatible rocm library found.  Please install ROCm")
 	return "", fmt.Errorf("no suitable rocm found, falling back to CPU")
 }
-
-func (gpus RocmGPUInfoList) RefreshFreeMemory() error {
-	if len(gpus) == 0 {
-		return nil
-	}
-	hl, err := NewHipLib()
-	if err != nil {
-		slog.Debug(err.Error())
-		return nil
-	}
-	defer hl.Release()
-
-	for i := range gpus {
-		err := hl.HipSetDevice(gpus[i].index)
-		if err != nil {
-			return err
-		}
-		freeMemory, _, err := hl.HipMemGetInfo()
-		if err != nil {
-			slog.Warn("get mem info", "id", i, "error", err)
-			continue
-		}
-		slog.Debug("updating rocm free memory", "gpu", gpus[i].ID, "name", gpus[i].Name, "before", format.HumanBytes2(gpus[i].FreeMemory), "now", format.HumanBytes2(freeMemory))
-		gpus[i].FreeMemory = freeMemory
-	}
-	return nil
-}

gpu/assets.go

@@ -77,27 +77,20 @@ func cleanupTmpDirs() {
 			continue
 		}
 		raw, err := os.ReadFile(filepath.Join(d, "ollama.pid"))
+		if err == nil {
+			pid, err := strconv.Atoi(string(raw))
+			if err == nil {
+				if proc, err := os.FindProcess(pid); err == nil && !errors.Is(proc.Signal(syscall.Signal(0)), os.ErrProcessDone) {
+					// Another running ollama, ignore this tmpdir
+					continue
+				}
+			}
+		} else {
+			slog.Debug("failed to open ollama.pid", "path", d, "error", err)
+		}
+		err = os.RemoveAll(d)
 		if err != nil {
-			slog.Warn("failed to read ollama.pid", "path", d, "error", err)
-			// No pid, ignore this tmpdir
-			continue
-		}
-
-		pid, err := strconv.Atoi(string(raw))
-		if err != nil {
-			slog.Warn("failed to parse pid", "path", d, "error", err)
-			continue
-		}
-
-		proc, err := os.FindProcess(pid)
-		if err == nil && !errors.Is(proc.Signal(syscall.Signal(0)), os.ErrProcessDone) {
-			slog.Warn("found running ollama", "pid", pid, "path", d)
-			// Another running ollama, ignore this tmpdir
-			continue
-		}
-
-		if err := os.Remove(d); err != nil {
-			slog.Warn("unable to cleanup stale tmpdir", "path", d, "error", err)
+			slog.Debug("unable to cleanup stale tmpdir", "path", d, "error", err)
 		}
 	}
 }

gpu/cpu_common.go

@@ -1,16 +1,21 @@
 package gpu
 
 import (
+	"log/slog"
+
 	"golang.org/x/sys/cpu"
 )
 
-func GetCPUCapability() CPUCapability {
+func GetCPUVariant() string {
 	if cpu.X86.HasAVX2 {
-		return CPUCapabilityAVX2
+		slog.Debug("CPU has AVX2")
+		return "avx2"
 	}
 	if cpu.X86.HasAVX {
-		return CPUCapabilityAVX
+		slog.Debug("CPU has AVX")
+		return "avx"
 	}
+	slog.Debug("CPU does not have vector extensions")
 	// else LCD
-	return CPUCapabilityNone
+	return ""
 }

gpu/gpu.go

@@ -24,37 +24,19 @@ import (
 	"github.com/ollama/ollama/format"
 )
 
-type cudaHandles struct {
+type handles struct {
 	deviceCount int
 	cudart      *C.cudart_handle_t
 	nvcuda      *C.nvcuda_handle_t
-	nvml        *C.nvml_handle_t
-}
-
-type oneapiHandles struct {
 	oneapi      *C.oneapi_handle_t
-	deviceCount int
 }
 
 const (
 	cudaMinimumMemory = 457 * format.MebiByte
 	rocmMinimumMemory = 457 * format.MebiByte
-	// TODO OneAPI minimum memory
 )
 
-var (
-	gpuMutex      sync.Mutex
-	bootstrapped  bool
-	cpuCapability CPUCapability
-	cpus          []CPUInfo
-	cudaGPUs      []CudaGPUInfo
-	nvcudaLibPath string
-	cudartLibPath string
-	oneapiLibPath string
-	nvmlLibPath   string
-	rocmGPUs      []RocmGPUInfo
-	oneapiGPUs    []OneapiGPUInfo
-)
+var gpuMutex sync.Mutex
 
 // With our current CUDA compile flags, older than 5.0 will not work properly
 var CudaComputeMin = [2]C.int{5, 0}
@@ -64,113 +46,113 @@ var RocmComputeMin = 9
 // TODO find a better way to detect iGPU instead of minimum memory
 const IGPUMemLimit = 1 * format.GibiByte // 512G is what they typically report, so anything less than 1G must be iGPU
 
+var CudartLinuxGlobs = []string{
+	"/usr/local/cuda/lib64/libcudart.so*",
+	"/usr/lib/x86_64-linux-gnu/nvidia/current/libcudart.so*",
+	"/usr/lib/x86_64-linux-gnu/libcudart.so*",
+	"/usr/lib/wsl/lib/libcudart.so*",
+	"/usr/lib/wsl/drivers/*/libcudart.so*",
+	"/opt/cuda/lib64/libcudart.so*",
+	"/usr/local/cuda*/targets/aarch64-linux/lib/libcudart.so*",
+	"/usr/lib/aarch64-linux-gnu/nvidia/current/libcudart.so*",
+	"/usr/lib/aarch64-linux-gnu/libcudart.so*",
+	"/usr/local/cuda/lib*/libcudart.so*",
+	"/usr/lib*/libcudart.so*",
+	"/usr/local/lib*/libcudart.so*",
+}
+
+var CudartWindowsGlobs = []string{
+	"c:\\Program Files\\NVIDIA GPU Computing Toolkit\\CUDA\\v*\\bin\\cudart64_*.dll",
+}
+
+var NvcudaLinuxGlobs = []string{
+	"/usr/local/cuda*/targets/*/lib/libcuda.so*",
+	"/usr/lib/*-linux-gnu/nvidia/current/libcuda.so*",
+	"/usr/lib/*-linux-gnu/libcuda.so*",
+	"/usr/lib/wsl/lib/libcuda.so*",
+	"/usr/lib/wsl/drivers/*/libcuda.so*",
+	"/opt/cuda/lib*/libcuda.so*",
+	"/usr/local/cuda/lib*/libcuda.so*",
+	"/usr/lib*/libcuda.so*",
+	"/usr/local/lib*/libcuda.so*",
+}
+
+var NvcudaWindowsGlobs = []string{
+	"c:\\windows\\system*\\nvcuda.dll",
+}
+
+var OneapiWindowsGlobs = []string{
+	"c:\\Windows\\System32\\DriverStore\\FileRepository\\*\\ze_intel_gpu64.dll",
+}
+
+var OneapiLinuxGlobs = []string{
+	"/usr/lib/x86_64-linux-gnu/libze_intel_gpu.so*",
+	"/usr/lib*/libze_intel_gpu.so*",
+}
+
 // Jetson devices have JETSON_JETPACK="x.y.z" factory set to the Jetpack version installed.
 // Included to drive logic for reducing Ollama-allocated overhead on L4T/Jetson devices.
 var CudaTegra string = os.Getenv("JETSON_JETPACK")
 
 // Note: gpuMutex must already be held
-func initCudaHandles() *cudaHandles {
+func initGPUHandles() *handles {
 
 	// TODO - if the ollama build is CPU only, don't do these checks as they're irrelevant and confusing
 
-	cHandles := &cudaHandles{}
-	// Short Circuit if we already know which library to use
-	if nvmlLibPath != "" {
-		cHandles.nvml, _ = LoadNVMLMgmt([]string{nvmlLibPath})
-		return cHandles
-	}
-	if nvcudaLibPath != "" {
-		cHandles.deviceCount, cHandles.nvcuda, _ = LoadNVCUDAMgmt([]string{nvcudaLibPath})
-		return cHandles
-	}
-	if cudartLibPath != "" {
-		cHandles.deviceCount, cHandles.cudart, _ = LoadCUDARTMgmt([]string{cudartLibPath})
-		return cHandles
-	}
-
-	slog.Debug("searching for GPU discovery libraries for NVIDIA")
+	gpuHandles := &handles{}
+	var cudartMgmtName string
 	var cudartMgmtPatterns []string
+	var nvcudaMgmtName string
+	var nvcudaMgmtPatterns []string
 
-	// Aligned with driver, we can't carry as payloads
-	nvcudaMgmtPatterns := NvcudaGlobs
-
-	if runtime.GOOS == "windows" {
-		localAppData := os.Getenv("LOCALAPPDATA")
-		cudartMgmtPatterns = []string{filepath.Join(localAppData, "Programs", "Ollama", CudartMgmtName)}
-	}
 	tmpDir, _ := PayloadsDir()
-	if tmpDir != "" {
-		// TODO - add "payloads" for subprocess
-		cudartMgmtPatterns = []string{filepath.Join(tmpDir, "cuda*", CudartMgmtName)}
-	}
-	cudartMgmtPatterns = append(cudartMgmtPatterns, CudartGlobs...)
-
-	if len(NvmlGlobs) > 0 {
-		nvmlLibPaths := FindGPULibs(NvmlMgmtName, NvmlGlobs)
-		if len(nvmlLibPaths) > 0 {
-			nvml, libPath := LoadNVMLMgmt(nvmlLibPaths)
-			if nvml != nil {
-				slog.Debug("nvidia-ml loaded", "library", libPath)
-				cHandles.nvml = nvml
-				nvmlLibPath = libPath
-			}
+	switch runtime.GOOS {
+	case "windows":
+		cudartMgmtName = "cudart64_*.dll"
+		localAppData := os.Getenv("LOCALAPPDATA")
+		cudartMgmtPatterns = []string{filepath.Join(localAppData, "Programs", "Ollama", cudartMgmtName)}
+		cudartMgmtPatterns = append(cudartMgmtPatterns, CudartWindowsGlobs...)
+		// Aligned with driver, we can't carry as payloads
+		nvcudaMgmtName = "nvcuda.dll"
+		nvcudaMgmtPatterns = NvcudaWindowsGlobs
+	case "linux":
+		cudartMgmtName = "libcudart.so*"
+		if tmpDir != "" {
+			// TODO - add "payloads" for subprocess
+			cudartMgmtPatterns = []string{filepath.Join(tmpDir, "cuda*", cudartMgmtName)}
 		}
+		cudartMgmtPatterns = append(cudartMgmtPatterns, CudartLinuxGlobs...)
+		// Aligned with driver, we can't carry as payloads
+		nvcudaMgmtName = "libcuda.so*"
+		nvcudaMgmtPatterns = NvcudaLinuxGlobs
+	default:
+		return gpuHandles
 	}
 
-	nvcudaLibPaths := FindGPULibs(NvcudaMgmtName, nvcudaMgmtPatterns)
+	slog.Debug("Detecting GPUs")
+	nvcudaLibPaths := FindGPULibs(nvcudaMgmtName, nvcudaMgmtPatterns)
 	if len(nvcudaLibPaths) > 0 {
 		deviceCount, nvcuda, libPath := LoadNVCUDAMgmt(nvcudaLibPaths)
 		if nvcuda != nil {
 			slog.Debug("detected GPUs", "count", deviceCount, "library", libPath)
-			cHandles.nvcuda = nvcuda
-			cHandles.deviceCount = deviceCount
-			nvcudaLibPath = libPath
-			return cHandles
+			gpuHandles.nvcuda = nvcuda
+			gpuHandles.deviceCount = deviceCount
+			return gpuHandles
 		}
 	}
 
-	cudartLibPaths := FindGPULibs(CudartMgmtName, cudartMgmtPatterns)
+	cudartLibPaths := FindGPULibs(cudartMgmtName, cudartMgmtPatterns)
 	if len(cudartLibPaths) > 0 {
 		deviceCount, cudart, libPath := LoadCUDARTMgmt(cudartLibPaths)
 		if cudart != nil {
 			slog.Debug("detected GPUs", "library", libPath, "count", deviceCount)
-			cHandles.cudart = cudart
-			cHandles.deviceCount = deviceCount
-			cudartLibPath = libPath
-			return cHandles
+			gpuHandles.cudart = cudart
+			gpuHandles.deviceCount = deviceCount
+			return gpuHandles
 		}
 	}
 
-	return cHandles
-}
-
-// Note: gpuMutex must already be held
-func initOneAPIHandles() *oneapiHandles {
-	oHandles := &oneapiHandles{}
-
-	// Short Circuit if we already know which library to use
-	if oneapiLibPath != "" {
-		oHandles.deviceCount, oHandles.oneapi, _ = LoadOneapiMgmt([]string{oneapiLibPath})
-		return oHandles
-	}
-
-	oneapiLibPaths := FindGPULibs(OneapiMgmtName, OneapiGlobs)
-	if len(oneapiLibPaths) > 0 {
-		oHandles.deviceCount, oHandles.oneapi, oneapiLibPath = LoadOneapiMgmt(oneapiLibPaths)
-	}
-
-	return oHandles
-}
-
-func GetCPUInfo() GpuInfoList {
-	gpuMutex.Lock()
-	if !bootstrapped {
-		gpuMutex.Unlock()
-		GetGPUInfo()
-	} else {
-		gpuMutex.Unlock()
-	}
-	return GpuInfoList{cpus[0].GpuInfo}
+	return gpuHandles
 }
 
 func GetGPUInfo() GpuInfoList {
@@ -178,288 +160,112 @@ func GetGPUInfo() GpuInfoList {
 	// GPUs so we can report warnings if we see Nvidia/AMD but fail to load the libraries
 	gpuMutex.Lock()
 	defer gpuMutex.Unlock()
-	needRefresh := true
-	var cHandles *cudaHandles
-	var oHandles *oneapiHandles
+
+	gpuHandles := initGPUHandles()
 	defer func() {
-		if cHandles != nil {
-			if cHandles.cudart != nil {
-				C.cudart_release(*cHandles.cudart)
-			}
-			if cHandles.nvcuda != nil {
-				C.nvcuda_release(*cHandles.nvcuda)
-			}
-			if cHandles.nvml != nil {
-				C.nvml_release(*cHandles.nvml)
-			}
+		if gpuHandles.cudart != nil {
+			C.cudart_release(*gpuHandles.cudart)
 		}
-		if oHandles != nil {
-			if oHandles.oneapi != nil {
-				// TODO - is this needed?
-				C.oneapi_release(*oHandles.oneapi)
-			}
+		if gpuHandles.nvcuda != nil {
+			C.nvcuda_release(*gpuHandles.nvcuda)
 		}
 	}()
 
-	if !bootstrapped {
-		slog.Info("looking for compatible GPUs")
-		needRefresh = false
-		cpuCapability = GetCPUCapability()
-		var memInfo C.mem_info_t
-
-		mem, err := GetCPUMem()
-		if err != nil {
-			slog.Warn("error looking up system memory", "error", err)
-		}
-		cpus = []CPUInfo{CPUInfo{
-			GpuInfo: GpuInfo{
-				memInfo: mem,
-				Library: "cpu",
-				Variant: cpuCapability,
-				ID:      "0",
-			},
-		}}
-
-		// Fallback to CPU mode if we're lacking required vector extensions on x86
-		if cpuCapability < GPURunnerCPUCapability && runtime.GOARCH == "amd64" {
-			slog.Warn("CPU does not have minimum vector extensions, GPU inference disabled", "required", GPURunnerCPUCapability, "detected", cpuCapability)
-			bootstrapped = true
-			// No need to do any GPU discovery, since we can't run on them
-			return GpuInfoList{cpus[0].GpuInfo}
-		}
-
-		// On windows we bundle the nvidia library one level above the runner dir
-		depPath := ""
-		if runtime.GOOS == "windows" && envconfig.RunnersDir != "" {
-			depPath = filepath.Join(filepath.Dir(envconfig.RunnersDir), "cuda")
-		}
-
-		// Load ALL libraries
-		cHandles = initCudaHandles()
-
-		// NVIDIA
-		for i := range cHandles.deviceCount {
-			if cHandles.cudart != nil || cHandles.nvcuda != nil {
-				gpuInfo := CudaGPUInfo{
-					GpuInfo: GpuInfo{
-						Library: "cuda",
-					},
-					index: i,
-				}
-				var driverMajor int
-				var driverMinor int
-				if cHandles.cudart != nil {
-					C.cudart_bootstrap(*cHandles.cudart, C.int(i), &memInfo)
-				} else {
-					C.nvcuda_bootstrap(*cHandles.nvcuda, C.int(i), &memInfo)
-					driverMajor = int(cHandles.nvcuda.driver_major)
-					driverMinor = int(cHandles.nvcuda.driver_minor)
-				}
-				if memInfo.err != nil {
-					slog.Info("error looking up nvidia GPU memory", "error", C.GoString(memInfo.err))
-					C.free(unsafe.Pointer(memInfo.err))
-					continue
-				}
-				if memInfo.major < CudaComputeMin[0] || (memInfo.major == CudaComputeMin[0] && memInfo.minor < CudaComputeMin[1]) {
-					slog.Info(fmt.Sprintf("[%d] CUDA GPU is too old. Compute Capability detected: %d.%d", i, memInfo.major, memInfo.minor))
-					continue
-				}
-				gpuInfo.TotalMemory = uint64(memInfo.total)
-				gpuInfo.FreeMemory = uint64(memInfo.free)
-				gpuInfo.ID = C.GoString(&memInfo.gpu_id[0])
-				gpuInfo.Compute = fmt.Sprintf("%d.%d", memInfo.major, memInfo.minor)
-				gpuInfo.MinimumMemory = cudaMinimumMemory
-				gpuInfo.DependencyPath = depPath
-				gpuInfo.Name = C.GoString(&memInfo.gpu_name[0])
-				gpuInfo.DriverMajor = driverMajor
-				gpuInfo.DriverMinor = driverMinor
-
-				// query the management library as well so we can record any skew between the two
-				// which represents overhead on the GPU we must set aside on subsequent updates
-				if cHandles.nvml != nil {
-					C.nvml_get_free(*cHandles.nvml, C.int(gpuInfo.index), &memInfo.free, &memInfo.total, &memInfo.used)
-					if memInfo.err != nil {
-						slog.Warn("error looking up nvidia GPU memory", "error", C.GoString(memInfo.err))
-						C.free(unsafe.Pointer(memInfo.err))
-					} else {
-						if memInfo.free != 0 && uint64(memInfo.free) > gpuInfo.FreeMemory {
-							gpuInfo.OSOverhead = uint64(memInfo.free) - gpuInfo.FreeMemory
-							slog.Info("detected OS VRAM overhead",
-								"id", gpuInfo.ID,
-								"library", gpuInfo.Library,
-								"compute", gpuInfo.Compute,
-								"driver", fmt.Sprintf("%d.%d", gpuInfo.DriverMajor, gpuInfo.DriverMinor),
-								"name", gpuInfo.Name,
-								"overhead", format.HumanBytes2(gpuInfo.OSOverhead),
-							)
-						}
-					}
-				}
-
-				// TODO potentially sort on our own algorithm instead of what the underlying GPU library does...
-				cudaGPUs = append(cudaGPUs, gpuInfo)
-			}
-		}
-
-		// Intel
-		if envconfig.IntelGpu {
-			oHandles = initOneAPIHandles()
-			// On windows we bundle the oneapi library one level above the runner dir
-			depPath = ""
-			if runtime.GOOS == "windows" && envconfig.RunnersDir != "" {
-				depPath = filepath.Join(filepath.Dir(envconfig.RunnersDir), "oneapi")
-			}
-
-			for d := range oHandles.oneapi.num_drivers {
-				if oHandles.oneapi == nil {
-					// shouldn't happen
-					slog.Warn("nil oneapi handle with driver count", "count", int(oHandles.oneapi.num_drivers))
-					continue
-				}
-				devCount := C.oneapi_get_device_count(*oHandles.oneapi, C.int(d))
-				for i := range devCount {
-					gpuInfo := OneapiGPUInfo{
-						GpuInfo: GpuInfo{
-							Library: "oneapi",
-						},
-						driverIndex: int(d),
-						gpuIndex:    int(i),
-					}
-					// TODO - split bootstrapping from updating free memory
-					C.oneapi_check_vram(*oHandles.oneapi, C.int(d), i, &memInfo)
-					// TODO - convert this to MinimumMemory based on testing...
-					var totalFreeMem float64 = float64(memInfo.free) * 0.95 // work-around: leave some reserve vram for mkl lib used in ggml-sycl backend.
-					memInfo.free = C.uint64_t(totalFreeMem)
-					gpuInfo.TotalMemory = uint64(memInfo.total)
-					gpuInfo.FreeMemory = uint64(memInfo.free)
-					gpuInfo.ID = C.GoString(&memInfo.gpu_id[0])
-					gpuInfo.Name = C.GoString(&memInfo.gpu_name[0])
-					gpuInfo.DependencyPath = depPath
-					oneapiGPUs = append(oneapiGPUs, gpuInfo)
-				}
-			}
-		}
-
-		rocmGPUs = AMDGetGPUInfo()
-		bootstrapped = true
-		if len(cudaGPUs) == 0 && len(rocmGPUs) == 0 && len(oneapiGPUs) == 0 {
-			slog.Info("no compatible GPUs were discovered")
-		}
+	// All our GPU builds on x86 have AVX enabled, so fallback to CPU if we don't detect at least AVX
+	cpuVariant := GetCPUVariant()
+	if cpuVariant == "" && runtime.GOARCH == "amd64" {
+		slog.Warn("CPU does not have AVX or AVX2, disabling GPU support.")
 	}
 
-	// For detected GPUs, load library if not loaded
+	// On windows we bundle the nvidia library one level above the runner dir
+	depPath := ""
+	if runtime.GOOS == "windows" && envconfig.RunnersDir != "" {
+		depPath = filepath.Dir(envconfig.RunnersDir)
+	}
 
-	// Refresh free memory usage
-	if needRefresh {
-		mem, err := GetCPUMem()
-		if err != nil {
-			slog.Warn("error looking up system memory", "error", err)
-		} else {
-			slog.Debug("updating system memory data",
-				slog.Group(
-					"before",
-					"total", format.HumanBytes2(cpus[0].TotalMemory),
-					"free", format.HumanBytes2(cpus[0].FreeMemory),
-					"free_swap", format.HumanBytes2(cpus[0].FreeSwap),
-				),
-				slog.Group(
-					"now",
-					"total", format.HumanBytes2(mem.TotalMemory),
-					"free", format.HumanBytes2(mem.FreeMemory),
-					"free_swap", format.HumanBytes2(mem.FreeSwap),
-				),
-			)
-			cpus[0].FreeMemory = mem.FreeMemory
-			cpus[0].FreeSwap = mem.FreeSwap
-		}
+	var memInfo C.mem_info_t
+	resp := []GpuInfo{}
 
-		var memInfo C.mem_info_t
-		if cHandles == nil && len(cudaGPUs) > 0 {
-			cHandles = initCudaHandles()
+	// NVIDIA first
+	for i := range gpuHandles.deviceCount {
+		// TODO once we support CPU compilation variants of GPU libraries refine this...
+		if cpuVariant == "" && runtime.GOARCH == "amd64" {
+			continue
 		}
-		for i, gpu := range cudaGPUs {
-			if cHandles.nvml != nil {
-				C.nvml_get_free(*cHandles.nvml, C.int(gpu.index), &memInfo.free, &memInfo.total, &memInfo.used)
-			} else if cHandles.cudart != nil {
-				C.cudart_bootstrap(*cHandles.cudart, C.int(gpu.index), &memInfo)
-			} else if cHandles.nvcuda != nil {
-				C.nvcuda_get_free(*cHandles.nvcuda, C.int(gpu.index), &memInfo.free, &memInfo.total)
-				memInfo.used = memInfo.total - memInfo.free
+		if gpuHandles.cudart != nil || gpuHandles.nvcuda != nil {
+			gpuInfo := GpuInfo{
+				Library: "cuda",
+			}
+			var driverMajor int
+			var driverMinor int
+			if gpuHandles.cudart != nil {
+				C.cudart_check_vram(*gpuHandles.cudart, C.int(i), &memInfo)
 			} else {
-				// shouldn't happen
-				slog.Warn("no valid cuda library loaded to refresh vram usage")
-				break
+				C.nvcuda_check_vram(*gpuHandles.nvcuda, C.int(i), &memInfo)
+				driverMajor = int(gpuHandles.nvcuda.driver_major)
+				driverMinor = int(gpuHandles.nvcuda.driver_minor)
 			}
 			if memInfo.err != nil {
-				slog.Warn("error looking up nvidia GPU memory", "error", C.GoString(memInfo.err))
+				slog.Info("error looking up nvidia GPU memory", "error", C.GoString(memInfo.err))
 				C.free(unsafe.Pointer(memInfo.err))
 				continue
 			}
-			if memInfo.free == 0 {
-				slog.Warn("error looking up nvidia GPU memory")
+			if memInfo.major < CudaComputeMin[0] || (memInfo.major == CudaComputeMin[0] && memInfo.minor < CudaComputeMin[1]) {
+				slog.Info(fmt.Sprintf("[%d] CUDA GPU is too old. Compute Capability detected: %d.%d", i, memInfo.major, memInfo.minor))
 				continue
 			}
-			if cHandles.nvml != nil && gpu.OSOverhead > 0 {
-				// When using the management library update based on recorded overhead
-				memInfo.free -= C.uint64_t(gpu.OSOverhead)
-			}
-			slog.Debug("updating cuda memory data",
-				"gpu", gpu.ID,
-				"name", gpu.Name,
-				"overhead", format.HumanBytes2(gpu.OSOverhead),
-				slog.Group(
-					"before",
-					"total", format.HumanBytes2(gpu.TotalMemory),
-					"free", format.HumanBytes2(gpu.FreeMemory),
-				),
-				slog.Group(
-					"now",
-					"total", format.HumanBytes2(uint64(memInfo.total)),
-					"free", format.HumanBytes2(uint64(memInfo.free)),
-					"used", format.HumanBytes2(uint64(memInfo.used)),
-				),
-			)
-			cudaGPUs[i].FreeMemory = uint64(memInfo.free)
-		}
+			gpuInfo.TotalMemory = uint64(memInfo.total)
+			gpuInfo.FreeMemory = uint64(memInfo.free)
+			gpuInfo.ID = C.GoString(&memInfo.gpu_id[0])
+			gpuInfo.Compute = fmt.Sprintf("%d.%d", memInfo.major, memInfo.minor)
+			gpuInfo.MinimumMemory = cudaMinimumMemory
+			gpuInfo.DependencyPath = depPath
+			gpuInfo.Name = C.GoString(&memInfo.gpu_name[0])
+			gpuInfo.DriverMajor = driverMajor
+			gpuInfo.DriverMinor = driverMinor
 
-		if oHandles == nil && len(oneapiGPUs) > 0 {
-			oHandles = initOneAPIHandles()
-		}
-		for i, gpu := range oneapiGPUs {
-			if oHandles.oneapi == nil {
-				// shouldn't happen
-				slog.Warn("nil oneapi handle with device count", "count", oHandles.deviceCount)
-				continue
-			}
-			C.oneapi_check_vram(*oHandles.oneapi, C.int(gpu.driverIndex), C.int(gpu.gpuIndex), &memInfo)
-			// TODO - convert this to MinimumMemory based on testing...
-			var totalFreeMem float64 = float64(memInfo.free) * 0.95 // work-around: leave some reserve vram for mkl lib used in ggml-sycl backend.
-			memInfo.free = C.uint64_t(totalFreeMem)
-			oneapiGPUs[i].FreeMemory = uint64(memInfo.free)
-		}
-
-		err = RocmGPUInfoList(rocmGPUs).RefreshFreeMemory()
-		if err != nil {
-			slog.Debug("problem refreshing ROCm free memory", "error", err)
+			// TODO potentially sort on our own algorithm instead of what the underlying GPU library does...
+			resp = append(resp, gpuInfo)
 		}
 	}
 
-	resp := []GpuInfo{}
-	for _, gpu := range cudaGPUs {
-		resp = append(resp, gpu.GpuInfo)
-	}
-	for _, gpu := range rocmGPUs {
-		resp = append(resp, gpu.GpuInfo)
-	}
-	for _, gpu := range oneapiGPUs {
-		resp = append(resp, gpu.GpuInfo)
-	}
+	// Then AMD
+	resp = append(resp, AMDGetGPUInfo()...)
+
 	if len(resp) == 0 {
-		resp = append(resp, cpus[0].GpuInfo)
+		C.cpu_check_ram(&memInfo)
+		if memInfo.err != nil {
+			slog.Info("error looking up CPU memory", "error", C.GoString(memInfo.err))
+			C.free(unsafe.Pointer(memInfo.err))
+			return resp
+		}
+		gpuInfo := GpuInfo{
+			Library: "cpu",
+			Variant: cpuVariant,
+		}
+		gpuInfo.TotalMemory = uint64(memInfo.total)
+		gpuInfo.FreeMemory = uint64(memInfo.free)
+		gpuInfo.ID = C.GoString(&memInfo.gpu_id[0])
+
+		resp = append(resp, gpuInfo)
 	}
+
 	return resp
 }
 
+func GetCPUMem() (memInfo, error) {
+	var ret memInfo
+	var info C.mem_info_t
+	C.cpu_check_ram(&info)
+	if info.err != nil {
+		defer C.free(unsafe.Pointer(info.err))
+		return ret, fmt.Errorf(C.GoString(info.err))
+	}
+	ret.FreeMemory = uint64(info.free)
+	ret.TotalMemory = uint64(info.total)
+	return ret, nil
+}
+
 func FindGPULibs(baseLibName string, defaultPatterns []string) []string {
 	// Multiple GPU libraries may exist, and some may not work, so keep trying until we exhaust them
 	var ldPaths []string
@@ -547,23 +353,7 @@ func LoadNVCUDAMgmt(nvcudaLibPaths []string) (int, *C.nvcuda_handle_t, string) {
 		defer C.free(unsafe.Pointer(lib))
 		C.nvcuda_init(lib, &resp)
 		if resp.err != nil {
-			// Decide what log level based on the type of error message to help users understand why
-			msg := C.GoString(resp.err)
-			switch resp.cudaErr {
-			case C.CUDA_ERROR_INSUFFICIENT_DRIVER, C.CUDA_ERROR_SYSTEM_DRIVER_MISMATCH:
-				slog.Warn("version mismatch between driver and cuda driver library - reboot or upgrade may be required", "library", libPath, "error", msg)
-			case C.CUDA_ERROR_NO_DEVICE:
-				slog.Info("no nvidia devices detected", "library", libPath)
-			case C.CUDA_ERROR_UNKNOWN:
-				slog.Warn("unknown error initializing cuda driver library", "library", libPath, "error", msg)
-				slog.Warn("see https://github.com/ollama/ollama/blob/main/docs/troubleshooting.md for more information")
-			default:
-				if strings.Contains(msg, "wrong ELF class") {
-					slog.Debug("skipping 32bit library", "library", libPath)
-				} else {
-					slog.Info("unable to load cuda driver library", "library", libPath, "error", msg)
-				}
-			}
+			slog.Debug("Unable to load nvcuda", "library", libPath, "error", C.GoString(resp.err))
 			C.free(unsafe.Pointer(resp.err))
 		} else {
 			return int(resp.num_devices), &resp.ch, libPath
@@ -572,26 +362,8 @@ func LoadNVCUDAMgmt(nvcudaLibPaths []string) (int, *C.nvcuda_handle_t, string) {
 	return 0, nil, ""
 }
 
-func LoadNVMLMgmt(nvmlLibPaths []string) (*C.nvml_handle_t, string) {
-	var resp C.nvml_init_resp_t
-	resp.ch.verbose = getVerboseState()
-	for _, libPath := range nvmlLibPaths {
-		lib := C.CString(libPath)
-		defer C.free(unsafe.Pointer(lib))
-		C.nvml_init(lib, &resp)
-		if resp.err != nil {
-			slog.Info(fmt.Sprintf("Unable to load NVML management library %s: %s", libPath, C.GoString(resp.err)))
-			C.free(unsafe.Pointer(resp.err))
-		} else {
-			return &resp.ch, libPath
-		}
-	}
-	return nil, ""
-}
-
 func LoadOneapiMgmt(oneapiLibPaths []string) (int, *C.oneapi_handle_t, string) {
 	var resp C.oneapi_init_resp_t
-	num_devices := 0
 	resp.oh.verbose = getVerboseState()
 	for _, libPath := range oneapiLibPaths {
 		lib := C.CString(libPath)
@@ -601,10 +373,7 @@ func LoadOneapiMgmt(oneapiLibPaths []string) (int, *C.oneapi_handle_t, string) {
 			slog.Debug("Unable to load oneAPI management library", "library", libPath, "error", C.GoString(resp.err))
 			C.free(unsafe.Pointer(resp.err))
 		} else {
-			for i := range resp.oh.num_drivers {
-				num_devices += int(C.oneapi_get_device_count(resp.oh, C.int(i)))
-			}
-			return num_devices, &resp.oh, libPath
+			return int(resp.num_devices), &resp.oh, libPath
 		}
 	}
 	return 0, nil, ""

gpu/gpu_darwin.go

@@ -24,7 +24,7 @@ func GetGPUInfo() GpuInfoList {
 		return []GpuInfo{
 			{
 				Library: "cpu",
-				Variant: GetCPUCapability(),
+				Variant: GetCPUVariant(),
 				memInfo: mem,
 			},
 		}
@@ -42,22 +42,10 @@ func GetGPUInfo() GpuInfoList {
 	return []GpuInfo{info}
 }
 
-func GetCPUInfo() GpuInfoList {
-	mem, _ := GetCPUMem()
-	return []GpuInfo{
-		{
-			Library: "cpu",
-			Variant: GetCPUCapability(),
-			memInfo: mem,
-		},
-	}
-}
-
 func GetCPUMem() (memInfo, error) {
 	return memInfo{
 		TotalMemory: uint64(C.getPhysicalMemory()),
-		FreeMemory:  uint64(C.getFreeMemory()),
-		// FreeSwap omitted as Darwin uses dynamic paging
+		FreeMemory:  0,
 	}, nil
 }
 

gpu/gpu_info.h

@@ -47,7 +47,6 @@ typedef struct mem_info {
   char gpu_name[GPU_NAME_LEN];
   uint64_t total;
   uint64_t free;
-  uint64_t used;
 
   // Compute Capability
   int major; 
@@ -63,7 +62,6 @@ void cpu_check_ram(mem_info_t *resp);
 
 #include "gpu_info_cudart.h"
 #include "gpu_info_nvcuda.h"
-#include "gpu_info_nvml.h"
 #include "gpu_info_oneapi.h"
 
 #endif  // __GPU_INFO_H__

gpu/gpu_info_cpu.c

@@ -0,0 +1,45 @@
+#include "gpu_info.h"
+// Fallbacks for CPU mode
+
+#ifdef _WIN32
+#include <sysinfoapi.h>
+void cpu_check_ram(mem_info_t *resp) {
+  resp->err = NULL;
+  MEMORYSTATUSEX info;
+  info.dwLength = sizeof(info);
+  if (GlobalMemoryStatusEx(&info) != 0) {
+    resp->total = info.ullTotalPhys;
+    resp->free = info.ullAvailPhys;
+    snprintf(&resp->gpu_id[0], GPU_ID_LEN, "0");
+  } else {
+    resp->err = LOAD_ERR();
+  }
+  return;
+}
+
+#elif __linux__
+#include <errno.h>
+#include <string.h>
+#include <sys/sysinfo.h>
+void cpu_check_ram(mem_info_t *resp) {
+  struct sysinfo info;
+  resp->err = NULL;
+  if (sysinfo(&info) != 0) {
+    resp->err = strdup(strerror(errno));
+  } else {
+    resp->total = info.totalram * info.mem_unit;
+    resp->free = info.freeram * info.mem_unit;
+    snprintf(&resp->gpu_id[0], GPU_ID_LEN, "0");
+  }
+  return;
+}
+
+#elif __APPLE__
+// TODO consider an Apple implementation that does something useful
+// mem_info_t cpu_check_ram() {
+//   mem_info_t resp = {0, 0, NULL};
+//   return resp;
+// }
+#else
+#error "Unsupported platform"
+#endif

gpu/gpu_info_cudart.c

@@ -40,7 +40,7 @@ void cudart_init(char *cudart_lib_path, cudart_init_resp_t *resp) {
 
   for (i = 0; l[i].s != NULL; i++) {
     *l[i].p = LOAD_SYMBOL(resp->ch.handle, l[i].s);
-    if (!*(l[i].p)) {
+    if (!l[i].p) {
       char *msg = LOAD_ERR();
       LOG(resp->ch.verbose, "dlerr: %s\n", msg);
       UNLOAD_LIBRARY(resp->ch.handle);
@@ -94,7 +94,7 @@ void cudart_init(char *cudart_lib_path, cudart_init_resp_t *resp) {
 }
 
 
-void cudart_bootstrap(cudart_handle_t h, int i, mem_info_t *resp) {
+void cudart_check_vram(cudart_handle_t h, int i, mem_info_t *resp) {
   resp->err = NULL;
   cudartMemory_t memInfo = {0,0,0};
   cudartReturn_t ret;
@@ -166,11 +166,9 @@ void cudart_bootstrap(cudart_handle_t h, int i, mem_info_t *resp) {
 
   resp->total = memInfo.total;
   resp->free = memInfo.free;
-  resp->used = memInfo.used;
 
   LOG(h.verbose, "[%s] CUDA totalMem %lu\n", resp->gpu_id, resp->total);
   LOG(h.verbose, "[%s] CUDA freeMem %lu\n", resp->gpu_id, resp->free);
-  LOG(h.verbose, "[%s] CUDA usedMem %lu\n", resp->gpu_id, resp->used);
   LOG(h.verbose, "[%s] Compute Capability %d.%d\n", resp->gpu_id, resp->major, resp->minor);
 }
 

gpu/gpu_info_cudart.h

@@ -140,8 +140,7 @@ typedef struct cudart_init_resp {
 } cudart_init_resp_t;
 
 void cudart_init(char *cudart_lib_path, cudart_init_resp_t *resp);
-void cudart_bootstrap(cudart_handle_t ch, int device_id, mem_info_t *resp);
-// TODO - if we keep this library longer term, add cudart_get_free
+void cudart_check_vram(cudart_handle_t ch, int device_id, mem_info_t *resp);
 void cudart_release(cudart_handle_t ch);
 
 #endif  // __GPU_INFO_CUDART_H__

gpu/gpu_info_darwin.h

@@ -2,4 +2,3 @@
 #include <stdint.h>
 uint64_t getRecommendedMaxVRAM();
 uint64_t getPhysicalMemory();
-uint64_t getFreeMemory();

gpu/gpu_info_darwin.m

@@ -1,5 +1,4 @@
-#import <Foundation/Foundation.h>
-#import <mach/mach.h>
+// go:build darwin
 #include "gpu_info_darwin.h"
 
 uint64_t getRecommendedMaxVRAM() {
@@ -9,27 +8,6 @@ uint64_t getRecommendedMaxVRAM() {
   return result;
 }
 
-// getPhysicalMemory returns the total physical memory in bytes
 uint64_t getPhysicalMemory() {
-  return [NSProcessInfo processInfo].physicalMemory;
-}
-
-// getFreeMemory returns the total free memory in bytes, including inactive
-// memory that can be reclaimed by the system.
-uint64_t getFreeMemory() {
-  mach_port_t host_port = mach_host_self();
-  mach_msg_type_number_t host_size = sizeof(vm_statistics64_data_t) / sizeof(integer_t);
-  vm_size_t pagesize;
-  vm_statistics64_data_t vm_stat;
-
-  host_page_size(host_port, &pagesize);
-  if (host_statistics64(host_port, HOST_VM_INFO64, (host_info64_t)&vm_stat, &host_size) != KERN_SUCCESS) {
-    return 0;
-  }
-
-  uint64_t free_memory = (uint64_t)vm_stat.free_count * pagesize;
-  free_memory += (uint64_t)vm_stat.speculative_count * pagesize;
-  free_memory += (uint64_t)vm_stat.inactive_count * pagesize;
-
-  return free_memory;
+  return [[NSProcessInfo processInfo] physicalMemory];
 }

gpu/gpu_info_nvcuda.c

@@ -7,7 +7,6 @@ void nvcuda_init(char *nvcuda_lib_path, nvcuda_init_resp_t *resp) {
   CUresult ret;
   resp->err = NULL;
   resp->num_devices = 0;
-  resp->cudaErr = CUDA_SUCCESS;
   const int buflen = 256;
   char buf[buflen + 1];
   int i;
@@ -39,13 +38,12 @@ void nvcuda_init(char *nvcuda_lib_path, nvcuda_init_resp_t *resp) {
             nvcuda_lib_path, msg);
     free(msg);
     resp->err = strdup(buf);
-    resp->cudaErr = -1;
     return;
   }
 
   for (i = 0; l[i].s != NULL; i++) {
     *l[i].p = LOAD_SYMBOL(resp->ch.handle, l[i].s);
-    if (!*(l[i].p)) {
+    if (!*l[i].p) {
       char *msg = LOAD_ERR();
       LOG(resp->ch.verbose, "dlerr: %s\n", msg);
       UNLOAD_LIBRARY(resp->ch.handle);
@@ -54,7 +52,6 @@ void nvcuda_init(char *nvcuda_lib_path, nvcuda_init_resp_t *resp) {
               msg);
       free(msg);
       resp->err = strdup(buf);
-      resp->cudaErr = -1;
       return;
     }
   }
@@ -64,9 +61,12 @@ void nvcuda_init(char *nvcuda_lib_path, nvcuda_init_resp_t *resp) {
     LOG(resp->ch.verbose, "cuInit err: %d\n", ret);
     UNLOAD_LIBRARY(resp->ch.handle);
     resp->ch.handle = NULL;
-    snprintf(buf, buflen, "cuda driver library init failure: %d", ret);
+    if (ret == CUDA_ERROR_INSUFFICIENT_DRIVER) {
+      resp->err = strdup("your nvidia driver is too old or missing.  If you have a CUDA GPU please upgrade to run ollama");
+      return;
+    }
+    snprintf(buf, buflen, "nvcuda init failure: %d", ret);
     resp->err = strdup(buf);
-    resp->cudaErr = ret;
     return;
   }
 
@@ -91,13 +91,12 @@ void nvcuda_init(char *nvcuda_lib_path, nvcuda_init_resp_t *resp) {
     resp->ch.handle = NULL;
     snprintf(buf, buflen, "unable to get device count: %d", ret);
     resp->err = strdup(buf);
-    resp->cudaErr = ret;
     return;
   }
 }
 
 const int buflen = 256;
-void nvcuda_bootstrap(nvcuda_handle_t h, int i, mem_info_t *resp) {
+void nvcuda_check_vram(nvcuda_handle_t h, int i, mem_info_t *resp) {
   resp->err = NULL;
   nvcudaMemory_t memInfo = {0,0};
   CUresult ret;
@@ -107,13 +106,13 @@ void nvcuda_bootstrap(nvcuda_handle_t h, int i, mem_info_t *resp) {
   CUuuid uuid = {0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0};
 
   if (h.handle == NULL) {
-    resp->err = strdup("cuda driver library handle isn't initialized");
+    resp->err = strdup("nvcuda handle isn't initialized");
     return;
   }
 
   ret = (*h.cuDeviceGet)(&device, i);
   if (ret != CUDA_SUCCESS) {
-    snprintf(buf, buflen, "cuda driver library device failed to initialize");
+    snprintf(buf, buflen, "nvcuda device failed to initialize");
     resp->err = strdup(buf);
     return;
   }
@@ -169,14 +168,14 @@ void nvcuda_bootstrap(nvcuda_handle_t h, int i, mem_info_t *resp) {
   // To get memory we have to set (and release) a context
   ret = (*h.cuCtxCreate_v3)(&ctx, NULL, 0, 0, device);
   if (ret != CUDA_SUCCESS) {
-    snprintf(buf, buflen, "cuda driver library failed to get device context %d", ret);
+    snprintf(buf, buflen, "nvcuda failed to get primary device context %d", ret);
     resp->err = strdup(buf);
     return;
   }
 
   ret = (*h.cuMemGetInfo_v2)(&memInfo.free, &memInfo.total);
   if (ret != CUDA_SUCCESS) {
-    snprintf(buf, buflen, "cuda driver library device memory info lookup failure %d", ret);
+    snprintf(buf, buflen, "nvcuda device memory info lookup failure %d", ret);
     resp->err = strdup(buf);
     // Best effort on failure...
     (*h.cuCtxDestroy)(ctx);
@@ -194,47 +193,12 @@ void nvcuda_bootstrap(nvcuda_handle_t h, int i, mem_info_t *resp) {
 
   ret = (*h.cuCtxDestroy)(ctx);
   if (ret != CUDA_SUCCESS) {
-    LOG(1, "cuda driver library failed to release device context %d", ret);
-  }
-}
-
-void nvcuda_get_free(nvcuda_handle_t h, int i, uint64_t *free, uint64_t *total) {
-  CUresult ret;
-  CUcontext ctx = NULL;
-  CUdevice device = -1;
-  *free = 0;
-  *total = 0;
-
-  ret = (*h.cuDeviceGet)(&device, i);
-  if (ret != CUDA_SUCCESS) {
-    LOG(1, "cuda driver library device failed to initialize");
-    return;
-  }
-
-
-  // To get memory we have to set (and release) a context
-  ret = (*h.cuCtxCreate_v3)(&ctx, NULL, 0, 0, device);
-  if (ret != CUDA_SUCCESS) {
-    LOG(1, "cuda driver library failed to get device context %d", ret);
-    return;
-  }
-
-  ret = (*h.cuMemGetInfo_v2)(free, total);
-  if (ret != CUDA_SUCCESS) {
-    LOG(1, "cuda driver library device memory info lookup failure %d", ret);
-    // Best effort on failure...
-    (*h.cuCtxDestroy)(ctx);
-    return;
-  }
-
-  ret = (*h.cuCtxDestroy)(ctx);
-  if (ret != CUDA_SUCCESS) {
-    LOG(1, "cuda driver library failed to release device context %d", ret);
+    LOG(1, "nvcuda failed to release primary device context %d", ret);
   }
 }
 
 void nvcuda_release(nvcuda_handle_t h) {
-  LOG(h.verbose, "releasing cuda driver library\n");
+  LOG(h.verbose, "releasing nvcuda library\n");
   UNLOAD_LIBRARY(h.handle);
   // TODO and other context release logic?
   h.handle = NULL;

gpu/gpu_info_nvcuda.h

@@ -7,12 +7,9 @@
 typedef enum cudaError_enum {
   CUDA_SUCCESS = 0,
   CUDA_ERROR_INVALID_VALUE = 1,
-  CUDA_ERROR_OUT_OF_MEMORY = 2,
+  CUDA_ERROR_MEMORY_ALLOCATION = 2,
   CUDA_ERROR_NOT_INITIALIZED = 3,
   CUDA_ERROR_INSUFFICIENT_DRIVER = 35,
-  CUDA_ERROR_NO_DEVICE = 100,
-  CUDA_ERROR_SYSTEM_DRIVER_MISMATCH = 803,
-  CUDA_ERROR_UNKNOWN = 999,
   // Other values omitted for now...
 } CUresult;
 
@@ -67,12 +64,10 @@ typedef struct nvcuda_init_resp {
   char *err;  // If err is non-null handle is invalid
   nvcuda_handle_t ch;
   int num_devices;
-  CUresult cudaErr;
 } nvcuda_init_resp_t;
 
 void nvcuda_init(char *nvcuda_lib_path, nvcuda_init_resp_t *resp);
-void nvcuda_bootstrap(nvcuda_handle_t ch, int device_id, mem_info_t *resp);
-void nvcuda_get_free(nvcuda_handle_t ch,  int device_id, uint64_t *free, uint64_t *total);
+void nvcuda_check_vram(nvcuda_handle_t ch, int device_id, mem_info_t *resp);
 void nvcuda_release(nvcuda_handle_t ch);
 
 #endif  // __GPU_INFO_NVCUDA_H__

gpu/gpu_info_nvml.c

@@ -1,104 +0,0 @@
-#ifndef __APPLE__  // TODO - maybe consider nvidia support on intel macs?
-
-#include <string.h>
-
-#include "gpu_info_nvml.h"
-
-void nvml_init(char *nvml_lib_path, nvml_init_resp_t *resp) {
-  nvmlReturn_t ret;
-  resp->err = NULL;
-  const int buflen = 256;
-  char buf[buflen + 1];
-  int i;
-
-  struct lookup {
-    char *s;
-    void **p;
-  } l[] = {
-      {"nvmlInit_v2", (void *)&resp->ch.nvmlInit_v2},
-      {"nvmlShutdown", (void *)&resp->ch.nvmlShutdown},
-      {"nvmlDeviceGetHandleByIndex", (void *)&resp->ch.nvmlDeviceGetHandleByIndex},
-      {"nvmlDeviceGetMemoryInfo", (void *)&resp->ch.nvmlDeviceGetMemoryInfo},
-      {NULL, NULL},
-  };
-
-  resp->ch.handle = LOAD_LIBRARY(nvml_lib_path, RTLD_LAZY);
-  if (!resp->ch.handle) {
-    char *msg = LOAD_ERR();
-    LOG(resp->ch.verbose, "library %s load err: %s\n", nvml_lib_path, msg);
-    snprintf(buf, buflen,
-             "Unable to load %s library to query for Nvidia GPUs: %s",
-             nvml_lib_path, msg);
-    free(msg);
-    resp->err = strdup(buf);
-    return;
-  }
-
-  // TODO once we've squashed the remaining corner cases remove this log
-  // LOG(resp->ch.verbose, "wiring nvidia management library functions in %s\n", nvml_lib_path);
-  
-  for (i = 0; l[i].s != NULL; i++) {
-    // TODO once we've squashed the remaining corner cases remove this log
-    // LOG(resp->ch.verbose, "dlsym: %s\n", l[i].s);
-
-    *l[i].p = LOAD_SYMBOL(resp->ch.handle, l[i].s);
-    if (!*(l[i].p)) {
-      resp->ch.handle = NULL;
-      char *msg = LOAD_ERR();
-      LOG(resp->ch.verbose, "dlerr: %s\n", msg);
-      UNLOAD_LIBRARY(resp->ch.handle);
-      snprintf(buf, buflen, "symbol lookup for %s failed: %s", l[i].s,
-               msg);
-      free(msg);
-      resp->err = strdup(buf);
-      return;
-    }
-  }
-
-  ret = (*resp->ch.nvmlInit_v2)();
-  if (ret != NVML_SUCCESS) {
-    LOG(resp->ch.verbose, "nvmlInit_v2 err: %d\n", ret);
-    UNLOAD_LIBRARY(resp->ch.handle);
-    resp->ch.handle = NULL;
-    snprintf(buf, buflen, "nvml vram init failure: %d", ret);
-    resp->err = strdup(buf);
-    return;
-  }
-}
-
-
-void nvml_get_free(nvml_handle_t h, int device_id, uint64_t *free, uint64_t *total, uint64_t *used) {
-    nvmlDevice_t device;
-    nvmlMemory_t memInfo = {0};
-    nvmlReturn_t ret;
-    ret = (*h.nvmlDeviceGetHandleByIndex)(device_id, &device);
-    if (ret != NVML_SUCCESS) {
-        LOG(1, "unable to get device handle %d: %d", device_id, ret);
-        *free = 0;
-        return;
-    }
-
-    ret = (*h.nvmlDeviceGetMemoryInfo)(device, &memInfo);
-    if (ret != NVML_SUCCESS) {
-        LOG(1, "device memory info lookup failure %d: %d", device_id, ret);
-        *free = 0;
-        return;
-    }
-    *free = memInfo.free;
-    *total = memInfo.total;
-    *used = memInfo.used;
-}
-
-
-void nvml_release(nvml_handle_t h) {
-  LOG(h.verbose, "releasing nvml library\n");
-  nvmlReturn_t ret;
-  ret = (*h.nvmlShutdown)();
-  if (ret != NVML_SUCCESS) {
-    LOG(1, "error during nvmlShutdown %d", ret);
-  }
-  UNLOAD_LIBRARY(h.handle);
-  h.handle = NULL;
-}
-
-#endif  // __APPLE__

gpu/gpu_info_nvml.h

@@ -1,48 +0,0 @@
-#ifndef __APPLE__
-#ifndef __GPU_INFO_NVML_H__
-#define __GPU_INFO_NVML_H__
-#include "gpu_info.h"
-
-// Just enough typedef's to dlopen/dlsym for memory information
-typedef enum nvmlReturn_enum {
-  NVML_SUCCESS = 0,
-  // Other values omitted for now...
-} nvmlReturn_t;
-typedef void *nvmlDevice_t;  // Opaque is sufficient
-typedef struct nvmlMemory_st {
-  unsigned long long total;
-  unsigned long long free;
-  unsigned long long used;
-} nvmlMemory_t;
-
-typedef enum nvmlBrandType_enum
-{
-    NVML_BRAND_UNKNOWN          = 0,
-} nvmlBrandType_t;
-
-typedef struct nvml_handle {
-  void *handle;
-  uint16_t verbose;
-  nvmlReturn_t (*nvmlInit_v2)(void);
-  nvmlReturn_t (*nvmlShutdown)(void);
-  nvmlReturn_t (*nvmlDeviceGetHandleByIndex)(unsigned int, nvmlDevice_t *);
-  nvmlReturn_t (*nvmlDeviceGetMemoryInfo)(nvmlDevice_t, nvmlMemory_t *);
-} nvml_handle_t;
-
-typedef struct nvml_init_resp {
-  char *err;  // If err is non-null handle is invalid
-  nvml_handle_t ch;
-} nvml_init_resp_t;
-
-typedef struct nvml_compute_capability {
-  char *err;
-  int major;
-  int minor;
-} nvml_compute_capability_t;
-
-void nvml_init(char *nvml_lib_path, nvml_init_resp_t *resp);
-void nvml_get_free(nvml_handle_t ch,  int device_id, uint64_t *free, uint64_t *total, uint64_t *used);
-void nvml_release(nvml_handle_t ch);
-
-#endif  // __GPU_INFO_NVML_H__
-#endif  // __APPLE__

gpu/gpu_info_oneapi.c

@@ -4,17 +4,15 @@
 
 #include <string.h>
 
-void oneapi_init(char *oneapi_lib_path, oneapi_init_resp_t *resp) {
+void oneapi_init(char *oneapi_lib_path, oneapi_init_resp_t *resp)
+{
   ze_result_t ret;
   resp->err = NULL;
-  resp->oh.devices = NULL;
-  resp->oh.num_devices = NULL;
-  resp->oh.drivers = NULL;
-  resp->oh.num_drivers = 0;
   const int buflen = 256;
   char buf[buflen + 1];
-  int i, d;
-  struct lookup {
+  int i;
+  struct lookup
+  {
     char *s;
     void **p;
   } l[] = {
@@ -30,7 +28,8 @@ void oneapi_init(char *oneapi_lib_path, oneapi_init_resp_t *resp) {
   };
 
   resp->oh.handle = LOAD_LIBRARY(oneapi_lib_path, RTLD_LAZY);
-  if (!resp->oh.handle) {
+  if (!resp->oh.handle)
+  {
     char *msg = LOAD_ERR();
     snprintf(buf, buflen,
              "Unable to load %s library to query for Intel GPUs: %s\n",
@@ -45,12 +44,14 @@ void oneapi_init(char *oneapi_lib_path, oneapi_init_resp_t *resp) {
       "wiring Level-Zero management library functions in %s\n",
       oneapi_lib_path);
 
-  for (i = 0; l[i].s != NULL; i++) {
+  for (i = 0; l[i].s != NULL; i++)
+  {
     // TODO once we've squashed the remaining corner cases remove this log
     LOG(resp->oh.verbose, "dlsym: %s\n", l[i].s);
 
     *l[i].p = LOAD_SYMBOL(resp->oh.handle, l[i].s);
-    if (!*(l[i].p)) {
+    if (!l[i].p)
+    {
       resp->oh.handle = NULL;
       char *msg = LOAD_ERR();
       LOG(resp->oh.verbose, "dlerr: %s\n", msg);
@@ -62,70 +63,23 @@ void oneapi_init(char *oneapi_lib_path, oneapi_init_resp_t *resp) {
     }
   }
 
-  LOG(resp->oh.verbose, "calling zesInit\n");
-
   ret = (*resp->oh.zesInit)(0);
-  if (ret != ZE_RESULT_SUCCESS) {
-    LOG(resp->oh.verbose, "zesInit err: %x\n", ret);
-    snprintf(buf, buflen, "oneapi vram init failure: %x", ret);
+  if (ret != ZE_RESULT_SUCCESS)
+  {
+    LOG(resp->oh.verbose, "zesInit err: %d\n", ret);
+    UNLOAD_LIBRARY(resp->oh.handle);
+    resp->oh.handle = NULL;
+    snprintf(buf, buflen, "oneapi vram init failure: %d", ret);
     resp->err = strdup(buf);
-    oneapi_release(resp->oh);
-    return;
   }
 
-  LOG(resp->oh.verbose, "calling zesDriverGet\n");
-  ret = (*resp->oh.zesDriverGet)(&resp->oh.num_drivers, NULL);
-  if (ret != ZE_RESULT_SUCCESS) {
-    LOG(resp->oh.verbose, "zesDriverGet err: %x\n", ret);
-    snprintf(buf, buflen, "unable to get driver count: %x", ret);
-    resp->err = strdup(buf);
-    oneapi_release(resp->oh);
-    return;
-  }
-  LOG(resp->oh.verbose, "oneapi driver count: %d\n", resp->oh.num_drivers);
-  resp->oh.drivers = malloc(resp->oh.num_drivers * sizeof(zes_driver_handle_t));
-  resp->oh.num_devices = malloc(resp->oh.num_drivers * sizeof(uint32_t));
-  memset(&resp->oh.num_devices[0], 0, resp->oh.num_drivers * sizeof(uint32_t));
-  resp->oh.devices =
-      malloc(resp->oh.num_drivers * sizeof(zes_device_handle_t *));
-  ret = (*resp->oh.zesDriverGet)(&resp->oh.num_drivers, &resp->oh.drivers[0]);
-  if (ret != ZE_RESULT_SUCCESS) {
-    LOG(resp->oh.verbose, "zesDriverGet err: %x\n", ret);
-    snprintf(buf, buflen, "unable to get driver count: %x", ret);
-    resp->err = strdup(buf);
-    oneapi_release(resp->oh);
-    return;
-  }
-
-  for (d = 0; d < resp->oh.num_drivers; d++) {
-    LOG(resp->oh.verbose, "calling zesDeviceGet count %d: %p\n", d, resp->oh.drivers[d]);
-    ret = (*resp->oh.zesDeviceGet)(resp->oh.drivers[d],
-                                   &resp->oh.num_devices[d], NULL);
-    if (ret != ZE_RESULT_SUCCESS) {
-      LOG(resp->oh.verbose, "zesDeviceGet err: %x\n", ret);
-      snprintf(buf, buflen, "unable to get device count: %x", ret);
-      resp->err = strdup(buf);
-      oneapi_release(resp->oh);
-      return;
-    }
-    resp->oh.devices[d] =
-        malloc(resp->oh.num_devices[d] * sizeof(zes_device_handle_t));
-    ret = (*resp->oh.zesDeviceGet)(
-        resp->oh.drivers[d], &resp->oh.num_devices[d], resp->oh.devices[d]);
-    if (ret != ZE_RESULT_SUCCESS) {
-      LOG(resp->oh.verbose, "zesDeviceGet err: %x\n", ret);
-      snprintf(buf, buflen, "unable to get device count: %x", ret);
-      resp->err = strdup(buf);
-      oneapi_release(resp->oh);
-      return;
-    }
-  }
+  (*resp->oh.zesDriverGet)(&resp->num_devices, NULL);
 
   return;
 }
 
-void oneapi_check_vram(oneapi_handle_t h, int driver, int device,
-                       mem_info_t *resp) {
+void oneapi_check_vram(oneapi_handle_t h, mem_info_t *resp)
+{
   ze_result_t ret;
   resp->err = NULL;
   uint64_t totalMem = 0;
@@ -134,126 +88,127 @@ void oneapi_check_vram(oneapi_handle_t h, int driver, int device,
   char buf[buflen + 1];
   int i, d, m;
 
-  if (h.handle == NULL) {
+  if (h.handle == NULL)
+  {
     resp->err = strdup("Level-Zero handle not initialized");
     return;
   }
 
-  if (driver > h.num_drivers || device > h.num_devices[driver]) {
-    resp->err = strdup("driver of device index out of bounds");
+  uint32_t driversCount = 0;
+  ret = (*h.zesDriverGet)(&driversCount, NULL);
+  if (ret != ZE_RESULT_SUCCESS)
+  {
+    snprintf(buf, buflen, "unable to get driver count: %d", ret);
+    resp->err = strdup(buf);
     return;
   }
+  LOG(h.verbose, "discovered %d Level-Zero drivers\n", driversCount);
+
+  zes_driver_handle_t *allDrivers =
+      malloc(driversCount * sizeof(zes_driver_handle_t));
+  (*h.zesDriverGet)(&driversCount, allDrivers);
 
   resp->total = 0;
   resp->free = 0;
 
-  zes_device_ext_properties_t ext_props;
-  ext_props.stype = ZES_STRUCTURE_TYPE_DEVICE_EXT_PROPERTIES;
-  ext_props.pNext = NULL;
-
-  zes_device_properties_t props;
-  props.stype = ZES_STRUCTURE_TYPE_DEVICE_PROPERTIES;
-  props.pNext = &ext_props;
-
-  ret = (*h.zesDeviceGetProperties)(h.devices[driver][device], &props);
-  if (ret != ZE_RESULT_SUCCESS) {
-    snprintf(buf, buflen, "unable to get device properties: %d", ret);
-    resp->err = strdup(buf);
-    return;
-  }
-
-  snprintf(&resp->gpu_name[0], GPU_NAME_LEN, "%s", props.modelName);
-
-  // TODO this needs to map to ONEAPI_DEVICE_SELECTOR syntax
-  // (this is probably wrong...)
-  // TODO - the driver isn't included - what if there are multiple drivers?
-  snprintf(&resp->gpu_id[0], GPU_ID_LEN, "%d", device);
-
-  if (h.verbose) {
-    // When in verbose mode, report more information about
-    // the card we discover.
-    LOG(h.verbose, "[%d:%d] oneAPI device name: %s\n", driver, device,
-        props.modelName);
-    LOG(h.verbose, "[%d:%d] oneAPI brand: %s\n", driver, device,
-        props.brandName);
-    LOG(h.verbose, "[%d:%d] oneAPI vendor: %s\n", driver, device,
-        props.vendorName);
-    LOG(h.verbose, "[%d:%d] oneAPI S/N: %s\n", driver, device,
-        props.serialNumber);
-    LOG(h.verbose, "[%d:%d] oneAPI board number: %s\n", driver, device,
-        props.boardNumber);
-  }
-
-  // TODO
-  // Compute Capability equivalent in resp->major, resp->minor, resp->patch
-
-  uint32_t memCount = 0;
-  ret = (*h.zesDeviceEnumMemoryModules)(h.devices[driver][device], &memCount,
-                                        NULL);
-  if (ret != ZE_RESULT_SUCCESS) {
-    snprintf(buf, buflen, "unable to enumerate Level-Zero memory modules: %x",
-             ret);
-    resp->err = strdup(buf);
-    return;
-  }
-
-  LOG(h.verbose, "discovered %d Level-Zero memory modules\n", memCount);
-
-  zes_mem_handle_t *mems = malloc(memCount * sizeof(zes_mem_handle_t));
-  (*h.zesDeviceEnumMemoryModules)(h.devices[driver][device], &memCount, mems);
-
-  for (m = 0; m < memCount; m++) {
-    zes_mem_state_t state;
-    state.stype = ZES_STRUCTURE_TYPE_MEM_STATE;
-    state.pNext = NULL;
-    ret = (*h.zesMemoryGetState)(mems[m], &state);
-    if (ret != ZE_RESULT_SUCCESS) {
-      snprintf(buf, buflen, "unable to get memory state: %x", ret);
+  for (d = 0; d < driversCount; d++)
+  {
+    uint32_t deviceCount = 0;
+    ret = (*h.zesDeviceGet)(allDrivers[d], &deviceCount, NULL);
+    if (ret != ZE_RESULT_SUCCESS)
+    {
+      snprintf(buf, buflen, "unable to get device count: %d", ret);
       resp->err = strdup(buf);
-      free(mems);
+      free(allDrivers);
       return;
     }
 
-    resp->total += state.size;
-    resp->free += state.free;
-  }
+    LOG(h.verbose, "discovered %d Level-Zero devices\n", deviceCount);
 
-  free(mems);
-}
+    zes_device_handle_t *devices =
+        malloc(deviceCount * sizeof(zes_device_handle_t));
+    (*h.zesDeviceGet)(allDrivers[d], &deviceCount, devices);
 
-void oneapi_release(oneapi_handle_t h) {
-  int d;
-  LOG(h.verbose, "releasing oneapi library\n");
-  for (d = 0; d < h.num_drivers; d++) {
-    if (h.devices != NULL && h.devices[d] != NULL) {
-      free(h.devices[d]);
+    for (i = 0; i < deviceCount; i++)
+    {
+      zes_device_ext_properties_t ext_props;
+      ext_props.stype = ZES_STRUCTURE_TYPE_DEVICE_EXT_PROPERTIES;
+      ext_props.pNext = NULL;
+
+      zes_device_properties_t props;
+      props.stype = ZES_STRUCTURE_TYPE_DEVICE_PROPERTIES;
+      props.pNext = &ext_props;
+
+      ret = (*h.zesDeviceGetProperties)(devices[i], &props);
+      if (ret != ZE_RESULT_SUCCESS)
+      {
+        snprintf(buf, buflen, "unable to get device properties: %d", ret);
+        resp->err = strdup(buf);
+        free(allDrivers);
+        free(devices);
+        return;
+      }
+
+      if (h.verbose)
+      {
+        // When in verbose mode, report more information about
+        // the card we discover.
+        LOG(h.verbose, "[%d] oneAPI device name: %s\n", i,
+            props.modelName);
+        LOG(h.verbose, "[%d] oneAPI brand: %s\n", i,
+            props.brandName);
+        LOG(h.verbose, "[%d] oneAPI vendor: %s\n", i,
+            props.vendorName);
+        LOG(h.verbose, "[%d] oneAPI S/N: %s\n", i,
+            props.serialNumber);
+        LOG(h.verbose, "[%d] oneAPI board number: %s\n", i,
+            props.boardNumber);
+      }
+
+      uint32_t memCount = 0;
+      ret = (*h.zesDeviceEnumMemoryModules)(devices[i], &memCount, NULL);
+      if (ret != ZE_RESULT_SUCCESS)
+      {
+        snprintf(buf, buflen,
+                 "unable to enumerate Level-Zero memory modules: %d", ret);
+        resp->err = strdup(buf);
+        free(allDrivers);
+        free(devices);
+        return;
+      }
+
+      LOG(h.verbose, "discovered %d Level-Zero memory modules\n", memCount);
+
+      zes_mem_handle_t *mems = malloc(memCount * sizeof(zes_mem_handle_t));
+      (*h.zesDeviceEnumMemoryModules)(devices[i], &memCount, mems);
+
+      for (m = 0; m < memCount; m++)
+      {
+        zes_mem_state_t state;
+        state.stype = ZES_STRUCTURE_TYPE_MEM_STATE;
+        state.pNext = NULL;
+        ret = (*h.zesMemoryGetState)(mems[m], &state);
+        if (ret != ZE_RESULT_SUCCESS)
+        {
+          snprintf(buf, buflen, "unable to get memory state: %d", ret);
+          resp->err = strdup(buf);
+          free(allDrivers);
+          free(devices);
+          free(mems);
+          return;
+        }
+
+        resp->total += state.size;
+        resp->free += state.free;
+      }
+
+      free(mems);
     }
-  }
-  if (h.devices != NULL) {
-    free(h.devices);
-    h.devices = NULL;
-  }
-  if (h.num_devices != NULL) {
-    free(h.num_devices);
-    h.num_devices = NULL;
-  }
-  if (h.drivers != NULL) {
-    free(h.drivers);
-    h.drivers = NULL;
-  }
-  h.num_drivers = 0;
-  UNLOAD_LIBRARY(h.handle);
-  h.handle = NULL;
-}
 
-int oneapi_get_device_count(oneapi_handle_t h, int driver) {
-  if (h.handle == NULL || h.num_devices == NULL) {
-    return 0;
+    free(devices);
   }
-  if (driver > h.num_drivers) {
-    return 0;
-  }
-  return (int)h.num_devices[driver];
+
+  free(allDrivers);
 }
 
 #endif // __APPLE__

gpu/gpu_info_oneapi.h

@@ -9,7 +9,8 @@
 #define ZE_BIT(_i) (1 << _i)
 
 // Just enough typedef's to dlopen/dlsym for memory information
-typedef enum ze_result_t {
+typedef enum ze_result_t
+{
   ZE_RESULT_SUCCESS = 0,
   // Other values omitted for now...
 } ze_result_t;
@@ -19,11 +20,13 @@ typedef struct _zes_driver_handle_t *zes_driver_handle_t;
 typedef struct _zes_device_handle_t *zes_device_handle_t;
 typedef struct _zes_mem_handle_t *zes_mem_handle_t;
 
-typedef enum _ze_structure_type_t {
+typedef enum _ze_structure_type_t
+{
   ZE_STRUCTURE_TYPE_FORCE_UINT32 = 0x7fffffff
 } ze_structure_type_t;
 
-typedef enum _zes_structure_type_t {
+typedef enum _zes_structure_type_t
+{
   ZES_STRUCTURE_TYPE_DEVICE_PROPERTIES = 0x1,
   ZES_STRUCTURE_TYPE_MEM_PROPERTIES = 0xb,
   ZES_STRUCTURE_TYPE_MEM_STATE = 0x1e,
@@ -31,29 +34,35 @@ typedef enum _zes_structure_type_t {
   ZES_STRUCTURE_TYPE_FORCE_UINT32 = 0x7fffffff
 } zes_structure_type_t;
 
-typedef enum _zes_mem_type_t {
+typedef enum _zes_mem_type_t
+{
   ZES_MEM_TYPE_FORCE_UINT32 = 0x7fffffff
 } zes_mem_type_t;
 
-typedef enum _zes_mem_loc_t {
+typedef enum _zes_mem_loc_t
+{
   ZES_MEM_LOC_SYSTEM = 0,
   ZES_MEM_LOC_DEVICE = 1,
   ZES_MEM_LOC_FORCE_UINT32 = 0x7fffffff
 } zes_mem_loc_t;
 
-typedef enum _zes_mem_health_t {
+typedef enum _zes_mem_health_t
+{
   ZES_MEM_HEALTH_FORCE_UINT32 = 0x7fffffff
 } zes_mem_health_t;
 
-typedef struct _ze_device_uuid_t {
+typedef struct _ze_device_uuid_t
+{
   uint8_t id[ZE_MAX_DEVICE_UUID_SIZE];
 } ze_device_uuid_t;
 
-typedef struct _zes_uuid_t {
+typedef struct _zes_uuid_t
+{
   uint8_t id[ZE_MAX_DEVICE_UUID_SIZE];
 } zes_uuid_t;
 
-typedef enum _ze_device_type_t {
+typedef enum _ze_device_type_t
+{
   ZE_DEVICE_TYPE_GPU = 1,
   ZE_DEVICE_TYPE_CPU = 2,
   ZE_DEVICE_TYPE_FPGA = 3,
@@ -62,7 +71,8 @@ typedef enum _ze_device_type_t {
   ZE_DEVICE_TYPE_FORCE_UINT32 = 0x7fffffff
 } ze_device_type_t;
 
-typedef enum _zes_device_type_t {
+typedef enum _zes_device_type_t
+{
   ZES_DEVICE_TYPE_GPU = 1,
   ZES_DEVICE_TYPE_CPU = 2,
   ZES_DEVICE_TYPE_FPGA = 3,
@@ -72,7 +82,8 @@ typedef enum _zes_device_type_t {
 } zes_device_type_t;
 
 typedef uint32_t ze_device_property_flags_t;
-typedef enum _ze_device_property_flag_t {
+typedef enum _ze_device_property_flag_t
+{
   ZE_DEVICE_PROPERTY_FLAG_INTEGRATED = ZE_BIT(0),
   ZE_DEVICE_PROPERTY_FLAG_SUBDEVICE = ZE_BIT(1),
   ZE_DEVICE_PROPERTY_FLAG_ECC = ZE_BIT(2),
@@ -81,7 +92,8 @@ typedef enum _ze_device_property_flag_t {
 } ze_device_property_flag_t;
 
 typedef uint32_t zes_device_property_flags_t;
-typedef enum _zes_device_property_flag_t {
+typedef enum _zes_device_property_flag_t
+{
   ZES_DEVICE_PROPERTY_FLAG_INTEGRATED = ZE_BIT(0),
   ZES_DEVICE_PROPERTY_FLAG_SUBDEVICE = ZE_BIT(1),
   ZES_DEVICE_PROPERTY_FLAG_ECC = ZE_BIT(2),
@@ -89,7 +101,8 @@ typedef enum _zes_device_property_flag_t {
   ZES_DEVICE_PROPERTY_FLAG_FORCE_UINT32 = 0x7fffffff
 } zes_device_property_flag_t;
 
-typedef struct _ze_device_properties_t {
+typedef struct _ze_device_properties_t
+{
   ze_structure_type_t stype;
   void *pNext;
   ze_device_type_t type;
@@ -113,7 +126,8 @@ typedef struct _ze_device_properties_t {
   char name[ZE_MAX_DEVICE_NAME];
 } ze_device_properties_t;
 
-typedef struct _zes_device_properties_t {
+typedef struct _zes_device_properties_t
+{
   zes_structure_type_t stype;
   void *pNext;
   ze_device_properties_t core;
@@ -126,7 +140,8 @@ typedef struct _zes_device_properties_t {
   char driverVersion[ZES_STRING_PROPERTY_SIZE];
 } zes_device_properties_t;
 
-typedef struct _zes_device_ext_properties_t {
+typedef struct _zes_device_ext_properties_t
+{
   zes_structure_type_t stype;
   void *pNext;
   zes_uuid_t uuid;
@@ -134,7 +149,8 @@ typedef struct _zes_device_ext_properties_t {
   zes_device_property_flags_t flags;
 } zes_device_ext_properties_t;
 
-typedef struct _zes_mem_properties_t {
+typedef struct _zes_mem_properties_t
+{
   zes_structure_type_t stype;
   void *pNext;
   zes_mem_type_t type;
@@ -146,7 +162,8 @@ typedef struct _zes_mem_properties_t {
   int32_t numChannels;
 } zes_mem_properties_t;
 
-typedef struct _zes_mem_state_t {
+typedef struct _zes_mem_state_t
+{
   zes_structure_type_t stype;
   const void *pNext;
   zes_mem_health_t health;
@@ -154,19 +171,10 @@ typedef struct _zes_mem_state_t {
   uint64_t size;
 } zes_mem_state_t;
 
-typedef struct oneapi_handle {
+typedef struct oneapi_handle
+{
   void *handle;
   uint16_t verbose;
-
-  uint32_t num_drivers;
-  zes_driver_handle_t *drivers;
-  uint32_t *num_devices;
-  zes_device_handle_t **devices;
-
-  // TODO Driver major, minor information
-  // int driver_major;
-  // int driver_minor;
-
   ze_result_t (*zesInit)(int);
   ze_result_t (*zesDriverGet)(uint32_t *pCount, zes_driver_handle_t *phDrivers);
   ze_result_t (*zesDeviceGet)(zes_driver_handle_t hDriver, uint32_t *pCount,
@@ -183,21 +191,21 @@ typedef struct oneapi_handle {
 
 } oneapi_handle_t;
 
-typedef struct oneapi_init_resp {
+typedef struct oneapi_init_resp
+{
   char *err; // If err is non-null handle is invalid
+  int num_devices;
   oneapi_handle_t oh;
 } oneapi_init_resp_t;
 
-typedef struct oneapi_version_resp {
+typedef struct oneapi_version_resp
+{
   ze_result_t status;
   char *str; // Contains version or error string if status != 0
 } oneapi_version_resp_t;
 
 void oneapi_init(char *oneapi_lib_path, oneapi_init_resp_t *resp);
-void oneapi_check_vram(oneapi_handle_t h, int driver, int device,
-                       mem_info_t *resp);
-void oneapi_release(oneapi_handle_t h);
-int oneapi_get_device_count(oneapi_handle_t h, int driver);
+void oneapi_check_vram(oneapi_handle_t rh, mem_info_t *resp);
 
 #endif // __GPU_INFO_INTEL_H__
 #endif // __APPLE__

gpu/gpu_linux.go

@@ -1,90 +0,0 @@
-package gpu
-
-import (
-	"bufio"
-	"fmt"
-	"os"
-	"strings"
-
-	"github.com/ollama/ollama/format"
-)
-
-var CudartGlobs = []string{
-	"/usr/local/cuda/lib64/libcudart.so*",
-	"/usr/lib/x86_64-linux-gnu/nvidia/current/libcudart.so*",
-	"/usr/lib/x86_64-linux-gnu/libcudart.so*",
-	"/usr/lib/wsl/lib/libcudart.so*",
-	"/usr/lib/wsl/drivers/*/libcudart.so*",
-	"/opt/cuda/lib64/libcudart.so*",
-	"/usr/local/cuda*/targets/aarch64-linux/lib/libcudart.so*",
-	"/usr/lib/aarch64-linux-gnu/nvidia/current/libcudart.so*",
-	"/usr/lib/aarch64-linux-gnu/libcudart.so*",
-	"/usr/local/cuda/lib*/libcudart.so*",
-	"/usr/lib*/libcudart.so*",
-	"/usr/local/lib*/libcudart.so*",
-}
-
-var NvmlGlobs = []string{}
-
-var NvcudaGlobs = []string{
-	"/usr/local/cuda*/targets/*/lib/libcuda.so*",
-	"/usr/lib/*-linux-gnu/nvidia/current/libcuda.so*",
-	"/usr/lib/*-linux-gnu/libcuda.so*",
-	"/usr/lib/wsl/lib/libcuda.so*",
-	"/usr/lib/wsl/drivers/*/libcuda.so*",
-	"/opt/cuda/lib*/libcuda.so*",
-	"/usr/local/cuda/lib*/libcuda.so*",
-	"/usr/lib*/libcuda.so*",
-	"/usr/local/lib*/libcuda.so*",
-}
-
-var OneapiGlobs = []string{
-	"/usr/lib/x86_64-linux-gnu/libze_intel_gpu.so*",
-	"/usr/lib*/libze_intel_gpu.so*",
-}
-
-var CudartMgmtName = "libcudart.so*"
-var NvcudaMgmtName = "libcuda.so*"
-var NvmlMgmtName = "" // not currently wired on linux
-var OneapiMgmtName = "libze_intel_gpu.so"
-
-func GetCPUMem() (memInfo, error) {
-	var mem memInfo
-	var total, available, free, buffers, cached, freeSwap uint64
-	f, err := os.Open("/proc/meminfo")
-	if err != nil {
-		return mem, err
-	}
-	defer f.Close()
-	s := bufio.NewScanner(f)
-	for s.Scan() {
-		line := s.Text()
-		switch {
-		case strings.HasPrefix(line, "MemTotal:"):
-			_, err = fmt.Sscanf(line, "MemTotal:%d", &total)
-		case strings.HasPrefix(line, "MemAvailable:"):
-			_, err = fmt.Sscanf(line, "MemAvailable:%d", &available)
-		case strings.HasPrefix(line, "MemFree:"):
-			_, err = fmt.Sscanf(line, "MemFree:%d", &free)
-		case strings.HasPrefix(line, "Buffers:"):
-			_, err = fmt.Sscanf(line, "Buffers:%d", &buffers)
-		case strings.HasPrefix(line, "Cached:"):
-			_, err = fmt.Sscanf(line, "Cached:%d", &cached)
-		case strings.HasPrefix(line, "SwapFree:"):
-			_, err = fmt.Sscanf(line, "SwapFree:%d", &freeSwap)
-		default:
-			continue
-		}
-		if err != nil {
-			return mem, err
-		}
-	}
-	mem.TotalMemory = total * format.KibiByte
-	mem.FreeSwap = freeSwap * format.KibiByte
-	if available > 0 {
-		mem.FreeMemory = available * format.KibiByte
-	} else {
-		mem.FreeMemory = (free + buffers + cached) * format.KibiByte
-	}
-	return mem, nil
-}

gpu/gpu_windows.go

@@ -1,55 +0,0 @@
-package gpu
-
-import (
-	"fmt"
-	"syscall"
-	"unsafe"
-)
-
-type MEMORYSTATUSEX struct {
-	length               uint32
-	MemoryLoad           uint32
-	TotalPhys            uint64
-	AvailPhys            uint64
-	TotalPageFile        uint64
-	AvailPageFile        uint64
-	TotalVirtual         uint64
-	AvailVirtual         uint64
-	AvailExtendedVirtual uint64
-}
-
-var (
-	k32                      = syscall.NewLazyDLL("kernel32.dll")
-	globalMemoryStatusExProc = k32.NewProc("GlobalMemoryStatusEx")
-	sizeofMemoryStatusEx     = uint32(unsafe.Sizeof(MEMORYSTATUSEX{}))
-)
-
-var CudartGlobs = []string{
-	"c:\\Program Files\\NVIDIA GPU Computing Toolkit\\CUDA\\v*\\bin\\cudart64_*.dll",
-}
-
-var NvmlGlobs = []string{
-	"c:\\Windows\\System32\\nvml.dll",
-}
-
-var NvcudaGlobs = []string{
-	"c:\\windows\\system*\\nvcuda.dll",
-}
-
-var OneapiGlobs = []string{
-	"c:\\Windows\\System32\\DriverStore\\FileRepository\\*\\ze_intel_gpu64.dll",
-}
-
-var CudartMgmtName = "cudart64_*.dll"
-var NvcudaMgmtName = "nvcuda.dll"
-var NvmlMgmtName = "nvml.dll"
-var OneapiMgmtName = "ze_intel_gpu64.dll"
-
-func GetCPUMem() (memInfo, error) {
-	memStatus := MEMORYSTATUSEX{length: sizeofMemoryStatusEx}
-	r1, _, err := globalMemoryStatusExProc.Call(uintptr(unsafe.Pointer(&memStatus)))
-	if r1 == 0 {
-		return memInfo{}, fmt.Errorf("GlobalMemoryStatusEx failed: %w", err)
-	}
-	return memInfo{TotalMemory: memStatus.TotalPhys, FreeMemory: memStatus.AvailPhys, FreeSwap: memStatus.AvailPageFile}, nil
-}

gpu/types.go

@@ -10,7 +10,6 @@ import (
 type memInfo struct {
 	TotalMemory uint64 `json:"total_memory,omitempty"`
 	FreeMemory  uint64 `json:"free_memory,omitempty"`
-	FreeSwap    uint64 `json:"free_swap,omitempty"`
 }
 
 // Beginning of an `ollama info` command
@@ -19,7 +18,7 @@ type GpuInfo struct {
 	Library string `json:"library,omitempty"`
 
 	// Optional variant to select (e.g. versions, cpu feature flags)
-	Variant CPUCapability `json:"variant"`
+	Variant string `json:"variant,omitempty"`
 
 	// MinimumMemory represents the minimum memory required to use the GPU
 	MinimumMemory uint64 `json:"-"`
@@ -27,14 +26,6 @@ type GpuInfo struct {
 	// Any extra PATH/LD_LIBRARY_PATH dependencies required for the Library to operate properly
 	DependencyPath string `json:"lib_path,omitempty"`
 
-	// Extra environment variables specific to the GPU as list of [key,value]
-	EnvWorkarounds [][2]string `json:"envs,omitempty"`
-
-	// Set to true if we can NOT reliably discover FreeMemory.  A value of true indicates
-	// the FreeMemory is best effort, and may over or under report actual memory usage
-	// False indicates FreeMemory can generally be trusted on this GPU
-	UnreliableFreeMemory bool
-
 	// GPU information
 	ID      string `json:"gpu_id"`  // string to use for selection of this specific GPU
 	Name    string `json:"name"`    // user friendly name if available
@@ -47,31 +38,6 @@ type GpuInfo struct {
 	// TODO other performance capability info to help in scheduling decisions
 }
 
-type CPUInfo struct {
-	GpuInfo
-}
-
-type CudaGPUInfo struct {
-	GpuInfo
-	OSOverhead uint64 // Memory overhead between the driver library and management library
-	index      int    //nolint:unused,nolintlint
-}
-type CudaGPUInfoList []CudaGPUInfo
-
-type RocmGPUInfo struct {
-	GpuInfo
-	usedFilepath string //nolint:unused,nolintlint
-	index        int    //nolint:unused,nolintlint
-}
-type RocmGPUInfoList []RocmGPUInfo
-
-type OneapiGPUInfo struct {
-	GpuInfo
-	driverIndex int //nolint:unused,nolintlint
-	gpuIndex    int //nolint:unused,nolintlint
-}
-type OneapiGPUInfoList []OneapiGPUInfo
-
 type GpuInfoList []GpuInfo
 
 // Split up the set of gpu info's by Library and variant
@@ -81,8 +47,8 @@ func (l GpuInfoList) ByLibrary() []GpuInfoList {
 	for _, info := range l {
 		found := false
 		requested := info.Library
-		if info.Variant != CPUCapabilityNone {
-			requested += "_" + info.Variant.String()
+		if info.Variant != "" {
+			requested += "_" + info.Variant
 		}
 		for i, lib := range libs {
 			if lib == requested {
@@ -120,26 +86,3 @@ type ByFreeMemory []GpuInfo
 func (a ByFreeMemory) Len() int           { return len(a) }
 func (a ByFreeMemory) Swap(i, j int)      { a[i], a[j] = a[j], a[i] }
 func (a ByFreeMemory) Less(i, j int) bool { return a[i].FreeMemory < a[j].FreeMemory }
-
-type CPUCapability uint32
-
-// Override at build time when building base GPU runners
-var GPURunnerCPUCapability = CPUCapabilityAVX
-
-const (
-	CPUCapabilityNone CPUCapability = iota
-	CPUCapabilityAVX
-	CPUCapabilityAVX2
-	// TODO AVX512
-)
-
-func (c CPUCapability) String() string {
-	switch c {
-	case CPUCapabilityAVX:
-		return "avx"
-	case CPUCapabilityAVX2:
-		return "avx2"
-	default:
-		return "no vector extensions"
-	}
-}

integration/concurrency_test.go

@@ -19,19 +19,17 @@ func TestMultiModelConcurrency(t *testing.T) {
 	var (
 		req = [2]api.GenerateRequest{
 			{
-				Model:     "orca-mini",
-				Prompt:    "why is the ocean blue?",
-				Stream:    &stream,
-				KeepAlive: &api.Duration{Duration: 10 * time.Second},
+				Model:  "orca-mini",
+				Prompt: "why is the ocean blue?",
+				Stream: &stream,
 				Options: map[string]interface{}{
 					"seed":        42,
 					"temperature": 0.0,
 				},
 			}, {
-				Model:     "tinydolphin",
-				Prompt:    "what is the origin of the us thanksgiving holiday?",
-				Stream:    &stream,
-				KeepAlive: &api.Duration{Duration: 10 * time.Second},
+				Model:  "tinydolphin",
+				Prompt: "what is the origin of the us thanksgiving holiday?",
+				Stream: &stream,
 				Options: map[string]interface{}{
 					"seed":        42,
 					"temperature": 0.0,
@@ -40,64 +38,42 @@ func TestMultiModelConcurrency(t *testing.T) {
 		}
 		resp = [2][]string{
 			[]string{"sunlight"},
-			[]string{"england", "english", "massachusetts", "pilgrims", "british"},
+			[]string{"england", "english", "massachusetts", "pilgrims"},
 		}
 	)
 	var wg sync.WaitGroup
 	wg.Add(len(req))
-	ctx, cancel := context.WithTimeout(context.Background(), time.Second*240)
+	ctx, cancel := context.WithTimeout(context.Background(), time.Second*120)
 	defer cancel()
-
-	client, _, cleanup := InitServerConnection(ctx, t)
-	defer cleanup()
-
-	for i := 0; i < len(req); i++ {
-		require.NoError(t, PullIfMissing(ctx, client, req[i].Model))
-	}
-
 	for i := 0; i < len(req); i++ {
 		go func(i int) {
 			defer wg.Done()
-			DoGenerate(ctx, t, client, req[i], resp[i], 60*time.Second, 10*time.Second)
+			GenerateTestHelper(ctx, t, req[i], resp[i])
 		}(i)
 	}
 	wg.Wait()
 }
 
 func TestIntegrationConcurrentPredictOrcaMini(t *testing.T) {
-	req, resp := GenerateRequests()
-	reqLimit := len(req)
-	iterLimit := 5
-
-	vram := os.Getenv("OLLAMA_MAX_VRAM") // TODO - discover actual VRAM
-	if vram != "" {
-		max, err := strconv.ParseUint(vram, 10, 64)
-		require.NoError(t, err)
-		// Don't hammer on small VRAM cards...
-		if max < 4*1024*1024*1024 {
-			reqLimit = min(reqLimit, 2)
-			iterLimit = 2
-		}
-	}
-
-	ctx, cancel := context.WithTimeout(context.Background(), 9*time.Minute)
+	ctx, cancel := context.WithTimeout(context.Background(), 10*time.Minute) // GTX 750 2G card takes ~9 minutes
 	defer cancel()
 	client, _, cleanup := InitServerConnection(ctx, t)
 	defer cleanup()
 
+	req, resp := GenerateRequests()
 	// Get the server running (if applicable) warm the model up with a single initial request
-	DoGenerate(ctx, t, client, req[0], resp[0], 60*time.Second, 10*time.Second)
+	DoGenerate(ctx, t, client, req[0], resp[0], 60*time.Second, 5*time.Second)
 
 	var wg sync.WaitGroup
-	wg.Add(reqLimit)
-	for i := 0; i < reqLimit; i++ {
+	wg.Add(len(req))
+	for i := 0; i < len(req); i++ {
 		go func(i int) {
 			defer wg.Done()
-			for j := 0; j < iterLimit; j++ {
+			for j := 0; j < 5; j++ {
 				slog.Info("Starting", "req", i, "iter", j)
-				// On slower GPUs it can take a while to process the concurrent requests
+				// On slower GPUs it can take a while to process the 4 concurrent requests
 				// so we allow a much longer initial timeout
-				DoGenerate(ctx, t, client, req[i], resp[i], 120*time.Second, 20*time.Second)
+				DoGenerate(ctx, t, client, req[i], resp[i], 90*time.Second, 5*time.Second)
 			}
 		}(i)
 	}
@@ -106,7 +82,7 @@ func TestIntegrationConcurrentPredictOrcaMini(t *testing.T) {
 
 // Stress the system if we know how much VRAM it has, and attempt to load more models than will fit
 func TestMultiModelStress(t *testing.T) {
-	vram := os.Getenv("OLLAMA_MAX_VRAM") // TODO - discover actual VRAM
+	vram := os.Getenv("OLLAMA_MAX_VRAM")
 	if vram == "" {
 		t.Skip("OLLAMA_MAX_VRAM not specified, can't pick the right models for the stress test")
 	}
@@ -245,23 +221,5 @@ func TestMultiModelStress(t *testing.T) {
 			}
 		}(i)
 	}
-	go func() {
-		for {
-			time.Sleep(2 * time.Second)
-			select {
-			case <-ctx.Done():
-				return
-			default:
-				models, err := client.ListRunning(ctx)
-				if err != nil {
-					slog.Warn("failed to list running models", "error", err)
-					continue
-				}
-				for _, m := range models.Models {
-					slog.Info("loaded model snapshot", "model", m)
-				}
-			}
-		}
-	}()
 	wg.Wait()
 }

integration/context_test.go

@@ -11,8 +11,7 @@ import (
 )
 
 func TestContextExhaustion(t *testing.T) {
-	// Longer needed for small footprint GPUs
-	ctx, cancel := context.WithTimeout(context.Background(), 5*time.Minute)
+	ctx, cancel := context.WithTimeout(context.Background(), 2*time.Minute) // TODO maybe shorter?
 	defer cancel()
 	// Set up the test data
 	req := api.GenerateRequest{
@@ -25,10 +24,5 @@ func TestContextExhaustion(t *testing.T) {
 			"num_ctx":     128,
 		},
 	}
-	client, _, cleanup := InitServerConnection(ctx, t)
-	defer cleanup()
-	if err := PullIfMissing(ctx, client, req.Model); err != nil {
-		t.Fatalf("PullIfMissing failed: %v", err)
-	}
-	DoGenerate(ctx, t, client, req, []string{"once", "upon", "lived"}, 120*time.Second, 10*time.Second)
+	GenerateTestHelper(ctx, t, req, []string{"once", "upon", "lived"})
 }

integration/embed_test.go

@@ -1,209 +0,0 @@
-//go:build integration
-
-package integration
-
-import (
-	"context"
-	"math"
-	"testing"
-	"time"
-
-	"github.com/ollama/ollama/api"
-)
-
-func floatsEqual32(a, b float32) bool {
-	return math.Abs(float64(a-b)) <= 1e-4
-}
-
-func floatsEqual64(a, b float64) bool {
-	return math.Abs(a-b) <= 1e-4
-}
-
-func TestAllMiniLMEmbeddings(t *testing.T) {
-	ctx, cancel := context.WithTimeout(context.Background(), 2*time.Minute)
-	defer cancel()
-
-	req := api.EmbeddingRequest{
-		Model:  "all-minilm",
-		Prompt: "why is the sky blue?",
-	}
-
-	res, err := embeddingTestHelper(ctx, t, req)
-
-	if err != nil {
-		t.Fatalf("error: %v", err)
-	}
-
-	if len(res.Embedding) != 384 {
-		t.Fatalf("expected 384 floats, got %d", len(res.Embedding))
-	}
-
-	if !floatsEqual64(res.Embedding[0], 0.06642947345972061) {
-		t.Fatalf("expected 0.06642947345972061, got %.16f", res.Embedding[0])
-	}
-}
-
-func TestAllMiniLMEmbed(t *testing.T) {
-	ctx, cancel := context.WithTimeout(context.Background(), 2*time.Minute)
-	defer cancel()
-
-	req := api.EmbedRequest{
-		Model: "all-minilm",
-		Input: "why is the sky blue?",
-	}
-
-	res, err := embedTestHelper(ctx, t, req)
-
-	if err != nil {
-		t.Fatalf("error: %v", err)
-	}
-
-	if len(res.Embeddings) != 1 {
-		t.Fatalf("expected 1 embedding, got %d", len(res.Embeddings))
-	}
-
-	if len(res.Embeddings[0]) != 384 {
-		t.Fatalf("expected 384 floats, got %d", len(res.Embeddings[0]))
-	}
-
-	if !floatsEqual32(res.Embeddings[0][0], 0.010071031) {
-		t.Fatalf("expected 0.010071031, got %.8f", res.Embeddings[0][0])
-	}
-
-	if res.PromptEvalCount != 8 {
-		t.Fatalf("expected 8 prompt tokens, got %d", res.PromptEvalCount)
-	}
-}
-
-func TestAllMiniLMBatchEmbed(t *testing.T) {
-	ctx, cancel := context.WithTimeout(context.Background(), 2*time.Minute)
-	defer cancel()
-
-	req := api.EmbedRequest{
-		Model: "all-minilm",
-		Input: []string{"why is the sky blue?", "why is the grass green?"},
-	}
-
-	res, err := embedTestHelper(ctx, t, req)
-
-	if err != nil {
-		t.Fatalf("error: %v", err)
-	}
-
-	if len(res.Embeddings) != 2 {
-		t.Fatalf("expected 2 embeddings, got %d", len(res.Embeddings))
-	}
-
-	if len(res.Embeddings[0]) != 384 {
-		t.Fatalf("expected 384 floats, got %d", len(res.Embeddings[0]))
-	}
-
-	if !floatsEqual32(res.Embeddings[0][0], 0.010071031) || !floatsEqual32(res.Embeddings[1][0], -0.009802706) {
-		t.Fatalf("expected 0.010071031 and -0.009802706, got %.8f and %.8f", res.Embeddings[0][0], res.Embeddings[1][0])
-	}
-
-	if res.PromptEvalCount != 16 {
-		t.Fatalf("expected 16 prompt tokens, got %d", res.PromptEvalCount)
-	}
-}
-
-func TestAllMiniLMEmbedTruncate(t *testing.T) {
-	ctx, cancel := context.WithTimeout(context.Background(), 2*time.Minute)
-	defer cancel()
-
-	truncTrue, truncFalse := true, false
-
-	type testReq struct {
-		Name    string
-		Request api.EmbedRequest
-	}
-
-	reqs := []testReq{
-		{
-			Name: "Target Truncation",
-			Request: api.EmbedRequest{
-				Model: "all-minilm",
-				Input: "why",
-			},
-		},
-		{
-			Name: "Default Truncate",
-			Request: api.EmbedRequest{
-				Model:   "all-minilm",
-				Input:   "why is the sky blue?",
-				Options: map[string]any{"num_ctx": 1},
-			},
-		},
-		{
-			Name: "Explicit Truncate",
-			Request: api.EmbedRequest{
-				Model:    "all-minilm",
-				Input:    "why is the sky blue?",
-				Truncate: &truncTrue,
-				Options:  map[string]any{"num_ctx": 1},
-			},
-		},
-	}
-
-	res := make(map[string]*api.EmbedResponse)
-
-	for _, req := range reqs {
-		response, err := embedTestHelper(ctx, t, req.Request)
-		if err != nil {
-			t.Fatalf("error: %v", err)
-		}
-		res[req.Name] = response
-	}
-
-	if res["Target Truncation"].Embeddings[0][0] != res["Default Truncate"].Embeddings[0][0] {
-		t.Fatal("expected default request to truncate correctly")
-	}
-
-	if res["Default Truncate"].Embeddings[0][0] != res["Explicit Truncate"].Embeddings[0][0] {
-		t.Fatal("expected default request and truncate true request to be the same")
-	}
-
-	// check that truncate set to false returns an error if context length is exceeded
-	_, err := embedTestHelper(ctx, t, api.EmbedRequest{
-		Model:    "all-minilm",
-		Input:    "why is the sky blue?",
-		Truncate: &truncFalse,
-		Options:  map[string]any{"num_ctx": 1},
-	})
-
-	if err == nil {
-		t.Fatal("expected error, got nil")
-	}
-}
-
-func embeddingTestHelper(ctx context.Context, t *testing.T, req api.EmbeddingRequest) (*api.EmbeddingResponse, error) {
-	client, _, cleanup := InitServerConnection(ctx, t)
-	defer cleanup()
-	if err := PullIfMissing(ctx, client, req.Model); err != nil {
-		t.Fatalf("failed to pull model %s: %v", req.Model, err)
-	}
-
-	response, err := client.Embeddings(ctx, &req)
-
-	if err != nil {
-		return nil, err
-	}
-
-	return response, nil
-}
-
-func embedTestHelper(ctx context.Context, t *testing.T, req api.EmbedRequest) (*api.EmbedResponse, error) {
-	client, _, cleanup := InitServerConnection(ctx, t)
-	defer cleanup()
-	if err := PullIfMissing(ctx, client, req.Model); err != nil {
-		t.Fatalf("failed to pull model %s: %v", req.Model, err)
-	}
-
-	response, err := client.Embed(ctx, &req)
-
-	if err != nil {
-		return nil, err
-	}
-
-	return response, nil
-}

integration/llm_image_test.go

@@ -32,11 +32,7 @@ func TestIntegrationMultimodal(t *testing.T) {
 	resp := "the ollam"
 	ctx, cancel := context.WithTimeout(context.Background(), 3*time.Minute)
 	defer cancel()
-	client, _, cleanup := InitServerConnection(ctx, t)
-	defer cleanup()
-	require.NoError(t, PullIfMissing(ctx, client, req.Model))
-	// llava models on CPU can be quite slow to start,
-	DoGenerate(ctx, t, client, req, []string{resp}, 120*time.Second, 30*time.Second)
+	GenerateTestHelper(ctx, t, req, []string{resp})
 }
 
 const imageEncoding = `iVBORw0KGgoAAAANSUhEUgAAANIAAAB4CAYAAACHHqzKAAAAAXNSR0IArs4c6QAAAIRlWElmTU0AKgAAAAgABQESAAMAAAABAAEAAAEaAAUAAAABAAAASgEb

integration/utils_test.go

@@ -140,7 +140,7 @@ func PullIfMissing(ctx context.Context, client *api.Client, modelName string) er
 
 	showCtx, cancel := context.WithDeadlineCause(
 		ctx,
-		time.Now().Add(10*time.Second),
+		time.Now().Add(5*time.Second),
 		fmt.Errorf("show for existing model %s took too long", modelName),
 	)
 	defer cancel()
@@ -287,46 +287,41 @@ func DoGenerate(ctx context.Context, t *testing.T, client *api.Client, genReq ap
 func GenerateRequests() ([]api.GenerateRequest, [][]string) {
 	return []api.GenerateRequest{
 			{
-				Model:     "orca-mini",
-				Prompt:    "why is the ocean blue?",
-				Stream:    &stream,
-				KeepAlive: &api.Duration{Duration: 10 * time.Second},
+				Model:  "orca-mini",
+				Prompt: "why is the ocean blue?",
+				Stream: &stream,
 				Options: map[string]interface{}{
 					"seed":        42,
 					"temperature": 0.0,
 				},
 			}, {
-				Model:     "orca-mini",
-				Prompt:    "why is the color of dirt brown?",
-				Stream:    &stream,
-				KeepAlive: &api.Duration{Duration: 10 * time.Second},
+				Model:  "orca-mini",
+				Prompt: "why is the color of dirt brown?",
+				Stream: &stream,
 				Options: map[string]interface{}{
 					"seed":        42,
 					"temperature": 0.0,
 				},
 			}, {
-				Model:     "orca-mini",
-				Prompt:    "what is the origin of the us thanksgiving holiday?",
-				Stream:    &stream,
-				KeepAlive: &api.Duration{Duration: 10 * time.Second},
+				Model:  "orca-mini",
+				Prompt: "what is the origin of the us thanksgiving holiday?",
+				Stream: &stream,
 				Options: map[string]interface{}{
 					"seed":        42,
 					"temperature": 0.0,
 				},
 			}, {
-				Model:     "orca-mini",
-				Prompt:    "what is the origin of independence day?",
-				Stream:    &stream,
-				KeepAlive: &api.Duration{Duration: 10 * time.Second},
+				Model:  "orca-mini",
+				Prompt: "what is the origin of independence day?",
+				Stream: &stream,
 				Options: map[string]interface{}{
 					"seed":        42,
 					"temperature": 0.0,
 				},
 			}, {
-				Model:     "orca-mini",
-				Prompt:    "what is the composition of air?",
-				Stream:    &stream,
-				KeepAlive: &api.Duration{Duration: 10 * time.Second},
+				Model:  "orca-mini",
+				Prompt: "what is the composition of air?",
+				Stream: &stream,
 				Options: map[string]interface{}{
 					"seed":        42,
 					"temperature": 0.0,
@@ -336,7 +331,7 @@ func GenerateRequests() ([]api.GenerateRequest, [][]string) {
 		[][]string{
 			[]string{"sunlight"},
 			[]string{"soil", "organic", "earth", "black", "tan"},
-			[]string{"england", "english", "massachusetts", "pilgrims", "british"},
+			[]string{"england", "english", "massachusetts", "pilgrims"},
 			[]string{"fourth", "july", "declaration", "independence"},
 			[]string{"nitrogen", "oxygen", "carbon", "dioxide"},
 		}

llm/ext_server/CMakeLists.txt

@@ -1,13 +1,14 @@
-set(TARGET ollama_llama_server)
-option(LLAMA_SERVER_VERBOSE "Build verbose logging option for Server" ON)
-include_directories(${CMAKE_CURRENT_SOURCE_DIR})
-add_executable(${TARGET} server.cpp utils.hpp json.hpp httplib.h)
-install(TARGETS ${TARGET} RUNTIME)
-target_compile_definitions(${TARGET} PRIVATE
-    SERVER_VERBOSE=$<BOOL:${LLAMA_SERVER_VERBOSE}>
-)
-target_link_libraries(${TARGET} PRIVATE ggml llama common llava ${CMAKE_THREAD_LIBS_INIT})
-if (WIN32)
-    TARGET_LINK_LIBRARIES(${TARGET} PRIVATE ws2_32)
-endif()
+
+set(TARGET ollama_llama_server)
+option(LLAMA_SERVER_VERBOSE "Build verbose logging option for Server" ON)
+include_directories(${CMAKE_CURRENT_SOURCE_DIR})
+add_executable(${TARGET} server.cpp utils.hpp json.hpp httplib.h)
+install(TARGETS ${TARGET} RUNTIME)
+target_compile_definitions(${TARGET} PRIVATE
+    SERVER_VERBOSE=$<BOOL:${LLAMA_SERVER_VERBOSE}>
+)
+target_link_libraries(${TARGET} PRIVATE common llava ${CMAKE_THREAD_LIBS_INIT})
+if (WIN32)
+    TARGET_LINK_LIBRARIES(${TARGET} PRIVATE ws2_32)
+endif()
 target_compile_features(${TARGET} PRIVATE cxx_std_11)

llm/ext_server/server.cpp

@@ -41,7 +41,6 @@
 
 #if defined(_WIN32)
 #include <windows.h>
-#include <errhandlingapi.h>
 #endif
 
 #include <cstddef>
@@ -57,6 +56,7 @@ struct server_params {
     std::string hostname = "127.0.0.1";
     std::vector<std::string> api_keys;
     std::string public_path = "examples/server/public";
+    std::string chat_template = "";
     int32_t port = 8080;
     int32_t read_timeout = 600;
     int32_t write_timeout = 600;
@@ -427,6 +427,16 @@ struct llama_server_context
         return true;
     }
 
+    void validate_model_chat_template(server_params & sparams) {
+        llama_chat_message chat[] = {{"user", "test"}};
+        std::vector<char> buf(1);
+        int res = llama_chat_apply_template(model, nullptr, chat, 1, true, buf.data(), buf.size());
+        if (res < 0) {
+            LOG_ERROR("The chat template comes with this model is not yet supported, falling back to chatml. This may cause the model to output suboptimal responses", {});
+            sparams.chat_template = "chatml";
+        }
+    }
+
     void initialize() {
         // create slots
         all_slots_are_idle = true;
@@ -1221,7 +1231,6 @@ struct llama_server_context
                 res.result_json = json
                 {
                     {"embedding", std::vector<float>(embd, embd + n_embd)},
-                    {"timings",             slot.get_formated_timings()},
                 };
             }
         }
@@ -1384,50 +1393,12 @@ struct llama_server_context
         }
     }
 
-    std::string common_prefix(const std::string& str1, const std::string& str2) {
-        auto mismatch_pair = std::mismatch(str1.begin(), str1.end(), str2.begin());
-        return std::string(str1.begin(), mismatch_pair.first);
-    }
-
-    // Find the slot that has the greatest common prefix
-    server_slot *prefix_slot(const json &prompt) {
-        if (!prompt.is_string()) {
-            return nullptr;
-        }
-
-        std::string prompt_str = prompt.get<std::string>();
-        server_slot *slot = nullptr;
-        size_t longest = 0;
-
-        for (server_slot &s : slots) {
-            if (s.available() && s.prompt.is_string()) {
-                std::string s_prompt = s.prompt.get<std::string>();
-                std::string prefix = common_prefix(s_prompt, prompt_str);
-
-                if (prefix.size() > longest) {
-                    slot = &s;
-                    longest = prefix.size();
-                }
-            }
-        }
-
-        if (!slot) {
-            return get_slot(-1);
-        }
-
-        LOG_DEBUG("slot with common prefix found", {{
-            "slot_id", slot->id,
-            "characters", longest
-        }});
-        return slot;
-    }
-
     void process_single_task(task_server& task)
     {
         switch (task.type)
         {
             case TASK_TYPE_COMPLETION: {
-                server_slot *slot = prefix_slot(task.data["prompt"]);
+                server_slot *slot = get_slot(json_value(task.data, "slot_id", -1));
                 if (slot == nullptr)
                 {
                     // if no slot is available, we defer this task for processing later
@@ -1694,23 +1665,22 @@ struct llama_server_context
                     if (slot.ga_n == 1 && slot.n_prompt_tokens >= slot.n_ctx)
                     {
                         const int n_left = slot.n_ctx - slot.params.n_keep;
-                        const int n_shift = n_left / 2;
-                        const int n_erase = slot.n_prompt_tokens - slot.params.n_keep - n_shift;
+                        const int n_block_size = n_left / 2;
+                        const int erased_blocks = (slot.n_prompt_tokens - slot.params.n_keep - n_block_size) / n_block_size;
 
                         std::vector<llama_token> new_tokens(
                             prompt_tokens.begin(),
                             prompt_tokens.begin() + slot.params.n_keep);
                         new_tokens.insert(
                             new_tokens.end(),
-                            prompt_tokens.begin() + slot.params.n_keep + n_erase,
+                            prompt_tokens.begin() + slot.params.n_keep + erased_blocks * n_block_size,
                             prompt_tokens.end());
 
-                        LOG_INFO("input truncated", {
-                            {"n_ctx",        slot.n_ctx},
-                            {"n_keep",       slot.params.n_keep},
-                            {"n_left",       n_left},
-                            {"n_shift",      n_shift},
-                            {"n_erase",      n_erase},
+                        LOG_VERBOSE("input truncated", {
+                            {"n_ctx",      slot.n_ctx},
+                            {"n_keep",     slot.params.n_keep},
+                            {"n_left",     n_left},
+                            {"new_tokens", tokens_to_str(ctx, new_tokens.cbegin(), new_tokens.cend())},
                         });
                         slot.truncated = true;
                         prompt_tokens = new_tokens;
@@ -1745,7 +1715,7 @@ struct llama_server_context
                             slot.n_past -= 1;
                         }
 
-                        slot.n_prompt_tokens_processed = slot.n_prompt_tokens;
+                        slot.n_prompt_tokens_processed = slot.n_prompt_tokens - slot.n_past;
 
                         if (slot.ga_n != 1)
                         {
@@ -2365,9 +2335,9 @@ static void server_params_parse(int argc, char **argv, server_params &sparams, g
                 invalid_param = true;
                 break;
             }
-#ifndef GGML_USE_CUDA
-            fprintf(stderr, "warning: llama.cpp was compiled without CUDA. Setting the split mode has no effect.\n");
-#endif // GGML_USE_CUDA
+#ifndef GGML_USE_CUBLAS
+            fprintf(stderr, "warning: llama.cpp was compiled without cuBLAS. Setting the split mode has no effect.\n");
+#endif // GGML_USE_CUBLAS
         }
         else if (arg == "--tensor-split" || arg == "-ts")
         {
@@ -2376,7 +2346,7 @@ static void server_params_parse(int argc, char **argv, server_params &sparams, g
                 invalid_param = true;
                 break;
             }
-#if defined(GGML_USE_CUDA) || defined(GGML_USE_SYCL)
+#if defined(GGML_USE_CUBLAS) || defined(GGML_USE_SYCL)
             std::string arg_next = argv[i];
 
             // split string by , and /
@@ -2397,8 +2367,8 @@ static void server_params_parse(int argc, char **argv, server_params &sparams, g
                 }
             }
 #else
-            LOG_WARNING("llama.cpp was compiled without CUDA. It is not possible to set a tensor split.\n", {});
-#endif // GGML_USE_CUDA
+            LOG_WARNING("llama.cpp was compiled without cuBLAS. It is not possible to set a tensor split.\n", {});
+#endif // GGML_USE_CUBLAS
         }
         else if (arg == "--main-gpu" || arg == "-mg")
         {
@@ -2407,7 +2377,7 @@ static void server_params_parse(int argc, char **argv, server_params &sparams, g
                 invalid_param = true;
                 break;
             }
-#if defined(GGML_USE_CUDA) || defined(GGML_USE_SYCL)
+#if defined(GGML_USE_CUBLAS) || defined(GGML_USE_SYCL)
             params.main_gpu = std::stoi(argv[i]);
 #else
             LOG_WARNING("llama.cpp was compiled without cuBLAS. It is not possible to set a main GPU.", {});
@@ -2439,6 +2409,15 @@ static void server_params_parse(int argc, char **argv, server_params &sparams, g
             params.lora_adapter.emplace_back(lora_adapter, std::stof(argv[i]));
             params.use_mmap = false;
         }
+        else if (arg == "--lora-base")
+        {
+            if (++i >= argc)
+            {
+                invalid_param = true;
+                break;
+            }
+            params.lora_base = argv[i];
+        }
         else if (arg == "-v" || arg == "--verbose")
         {
             server_verbose = true;
@@ -2556,6 +2535,7 @@ static void server_params_parse(int argc, char **argv, server_params &sparams, g
                 invalid_param = true;
                 break;
             }
+            sparams.chat_template = argv[i];
         }
         else if (arg == "--override-kv")
         {
@@ -2730,9 +2710,6 @@ int wmain(int argc, wchar_t **wargv) {
     for (int i = 0; i < argc; ++i) {
         argv[i] = wchar_to_char(wargv[i]);
     }
-
-    // Adjust error mode to avoid error dialog after we start.
-    SetErrorMode(SEM_FAILCRITICALERRORS);
 #else
 int main(int argc, char **argv) {
 #endif
@@ -3031,6 +3008,11 @@ int main(int argc, char **argv) {
     }
     const auto model_meta = llama.model_meta();
 
+    if (sparams.chat_template.empty()) { // custom chat template is not supplied
+        // check if the template comes with the model is supported by us
+        llama.validate_model_chat_template(sparams);
+    }
+
     // Middleware for API key validation
     auto validate_api_key = [&sparams](const httplib::Request &req, httplib::Response &res) -> bool {
         // If API key is not set, skip validation
@@ -3184,37 +3166,26 @@ int main(int argc, char **argv) {
                     prompt = "";
                 }
 
-                if (prompt.size() == 1) {
-                    prompt = prompt[0];
+                json image_data;
+                if (body.count("image_data") != 0) {
+                    image_data = body["image_data"];
+                }
+                else
+                {
+                    image_data = "";
                 }
 
                 // create and queue the task
-                json responses;
-                {
-                    const int id_task = llama.queue_tasks.get_new_id();
-                    llama.queue_results.add_waiting_task_id(id_task);
-                    llama.request_completion(id_task, {{"prompt", prompt}}, true, -1);
+                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}, {"image_data", image_data} }, true, -1);
 
-                    // get the result
-                    task_result result = llama.queue_results.recv(id_task);
-                    llama.queue_results.remove_waiting_task_id(id_task);
-                    if (result.error) {
-                        return res.set_content(result.result_json.dump(), "application/json; charset=utf-8");
-                    }
+                // get the result
+                task_result result = llama.queue_results.recv(task_id);
+                llama.queue_results.remove_waiting_task_id(task_id);
 
-                    responses = result.result_json.value("results", std::vector<json>{result.result_json});
-                    json embeddings = json::array();
-
-                    int prompt_n = 0;
-                    for (auto & elem : responses) {
-                        embeddings.push_back(elem.at("embedding"));
-                        prompt_n += elem.at("timings").at("prompt_n").get<int>();
-                    }
-
-                    // send the result
-                    json embedding_res = json{{"embedding", embeddings}, {"prompt_n", prompt_n}};
-                    return res.set_content(embedding_res.dump(), "application/json; charset=utf-8");
-                }
+                // send the result
+                return res.set_content(result.result_json.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!?

llm/generate/gen_darwin.sh

@@ -18,16 +18,16 @@ sign() {
     fi
 }
 
-COMMON_DARWIN_DEFS="-DBUILD_SHARED_LIBS=off -DCMAKE_OSX_DEPLOYMENT_TARGET=11.3 -DLLAMA_METAL_MACOSX_VERSION_MIN=11.3 -DCMAKE_SYSTEM_NAME=Darwin -DGGML_METAL_EMBED_LIBRARY=on -DGGML_OPENMP=off"
+COMMON_DARWIN_DEFS="-DCMAKE_OSX_DEPLOYMENT_TARGET=11.3 -DLLAMA_METAL_MACOSX_VERSION_MIN=11.3 -DCMAKE_SYSTEM_NAME=Darwin -DLLAMA_METAL_EMBED_LIBRARY=on"
 
 case "${GOARCH}" in
 "amd64")
-    COMMON_CPU_DEFS="${COMMON_DARWIN_DEFS} -DCMAKE_SYSTEM_PROCESSOR=${ARCH} -DCMAKE_OSX_ARCHITECTURES=${ARCH} -DGGML_METAL=off -DGGML_NATIVE=off"
+    COMMON_CPU_DEFS="${COMMON_DARWIN_DEFS} -DCMAKE_SYSTEM_PROCESSOR=${ARCH} -DCMAKE_OSX_ARCHITECTURES=${ARCH} -DLLAMA_METAL=off -DLLAMA_NATIVE=off"
 
     # Static build for linking into the Go binary
     init_vars
     CMAKE_TARGETS="--target llama --target ggml"
-    CMAKE_DEFS="${COMMON_CPU_DEFS} -DGGML_BLAS=off -DGGML_ACCELERATE=off -DGGML_AVX=off -DGGML_AVX2=off -DGGML_AVX512=off -DGGML_FMA=off -DGGML_F16C=off ${CMAKE_DEFS}"
+    CMAKE_DEFS="${COMMON_CPU_DEFS} -DBUILD_SHARED_LIBS=off -DLLAMA_ACCELERATE=off -DLLAMA_AVX=off -DLLAMA_AVX2=off -DLLAMA_AVX512=off -DLLAMA_FMA=off -DLLAMA_F16C=off ${CMAKE_DEFS}"
     BUILD_DIR="../build/darwin/${ARCH}_static"
     echo "Building static library"
     build
@@ -37,7 +37,7 @@ case "${GOARCH}" in
         # CPU first for the default library, set up as lowest common denominator for maximum compatibility (including Rosetta)
         #
         init_vars
-        CMAKE_DEFS="${COMMON_CPU_DEFS} -DGGML_ACCELERATE=off -DGGML_BLAS=off -DGGML_AVX=off -DGGML_AVX2=off -DGGML_AVX512=off -DGGML_FMA=off -DGGML_F16C=off ${CMAKE_DEFS}"
+        CMAKE_DEFS="${COMMON_CPU_DEFS} -DLLAMA_ACCELERATE=off -DLLAMA_AVX=off -DLLAMA_AVX2=off -DLLAMA_AVX512=off -DLLAMA_FMA=off -DLLAMA_F16C=off ${CMAKE_DEFS}"
         BUILD_DIR="../build/darwin/${ARCH}/cpu"
         echo "Building LCD CPU"
         build
@@ -49,7 +49,7 @@ case "${GOARCH}" in
         # Approximately 400% faster than LCD on same CPU
         #
         init_vars
-        CMAKE_DEFS="${COMMON_CPU_DEFS} -DGGML_ACCELERATE=off -DGGML_BLAS=off -DGGML_AVX=on -DGGML_AVX2=off -DGGML_AVX512=off -DGGML_FMA=off -DGGML_F16C=off ${CMAKE_DEFS}"
+        CMAKE_DEFS="${COMMON_CPU_DEFS} -DLLAMA_ACCELERATE=off -DLLAMA_AVX=on -DLLAMA_AVX2=off -DLLAMA_AVX512=off -DLLAMA_FMA=off -DLLAMA_F16C=off ${CMAKE_DEFS}"
         BUILD_DIR="../build/darwin/${ARCH}/cpu_avx"
         echo "Building AVX CPU"
         build
@@ -61,7 +61,7 @@ case "${GOARCH}" in
         # Approximately 10% faster than AVX on same CPU
         #
         init_vars
-        CMAKE_DEFS="${COMMON_CPU_DEFS} -DGGML_ACCELERATE=on -DGGML_BLAS=off -DGGML_AVX=on -DGGML_AVX2=on -DGGML_AVX512=off -DGGML_FMA=on -DGGML_F16C=on ${CMAKE_DEFS}"
+        CMAKE_DEFS="${COMMON_CPU_DEFS} -DLLAMA_ACCELERATE=on -DLLAMA_AVX=on -DLLAMA_AVX2=on -DLLAMA_AVX512=off -DLLAMA_FMA=on -DLLAMA_F16C=on ${CMAKE_DEFS}"
         BUILD_DIR="../build/darwin/${ARCH}/cpu_avx2"
         echo "Building AVX2 CPU"
         EXTRA_LIBS="${EXTRA_LIBS} -framework Accelerate -framework Foundation"
@@ -75,14 +75,14 @@ case "${GOARCH}" in
     # Static build for linking into the Go binary
     init_vars
     CMAKE_TARGETS="--target llama --target ggml"
-    CMAKE_DEFS="${COMMON_DARWIN_DEFS} -DCMAKE_OSX_DEPLOYMENT_TARGET=11.3 -DCMAKE_SYSTEM_NAME=Darwin -DCMAKE_SYSTEM_PROCESSOR=${ARCH} -DCMAKE_OSX_ARCHITECTURES=${ARCH} ${CMAKE_DEFS}"
+    CMAKE_DEFS="-DCMAKE_OSX_DEPLOYMENT_TARGET=11.3 -DCMAKE_SYSTEM_NAME=Darwin -DBUILD_SHARED_LIBS=off -DCMAKE_SYSTEM_PROCESSOR=${ARCH} -DCMAKE_OSX_ARCHITECTURES=${ARCH} -DLLAMA_METAL=off -DLLAMA_ACCELERATE=off -DLLAMA_AVX=off -DLLAMA_AVX2=off -DLLAMA_AVX512=off -DLLAMA_FMA=off -DLLAMA_F16C=off ${CMAKE_DEFS}"
     BUILD_DIR="../build/darwin/${ARCH}_static"
     echo "Building static library"
     build
 
     if [ -z "$OLLAMA_SKIP_METAL_GENERATE" ]; then
         init_vars
-        CMAKE_DEFS="${COMMON_DARWIN_DEFS} -DCMAKE_SYSTEM_PROCESSOR=${ARCH} -DCMAKE_OSX_ARCHITECTURES=${ARCH} ${CMAKE_DEFS}"
+        CMAKE_DEFS="${COMMON_DARWIN_DEFS} -DLLAMA_ACCELERATE=on -DCMAKE_SYSTEM_PROCESSOR=${ARCH} -DCMAKE_OSX_ARCHITECTURES=${ARCH} -DLLAMA_METAL=on ${CMAKE_DEFS}"
         BUILD_DIR="../build/darwin/${ARCH}/metal"
         EXTRA_LIBS="${EXTRA_LIBS} -framework Accelerate -framework Foundation -framework Metal -framework MetalKit -framework MetalPerformanceShaders"
         build

llm/generate/gen_linux.sh

@@ -51,7 +51,7 @@ if [ -z "${CUDACXX}" ]; then
         export CUDACXX=$(command -v nvcc)
     fi
 fi
-COMMON_CMAKE_DEFS="-DBUILD_SHARED_LIBS=off -DCMAKE_POSITION_INDEPENDENT_CODE=on -DGGML_NATIVE=off -DGGML_AVX=on -DGGML_AVX2=off -DGGML_AVX512=off -DGGML_FMA=off -DGGML_F16C=off -DGGML_OPENMP=off"
+COMMON_CMAKE_DEFS="-DCMAKE_POSITION_INDEPENDENT_CODE=on -DLLAMA_NATIVE=off -DLLAMA_AVX=on -DLLAMA_AVX2=off -DLLAMA_AVX512=off -DLLAMA_FMA=off -DLLAMA_F16C=off"
 source $(dirname $0)/gen_common.sh
 init_vars
 git_module_setup
@@ -64,7 +64,7 @@ if [ -z "${OLLAMA_SKIP_STATIC_GENERATE}" -o "${OLLAMA_CPU_TARGET}" = "static" ];
     # Static build for linking into the Go binary
     init_vars
     CMAKE_TARGETS="--target llama --target ggml"
-    CMAKE_DEFS="-DBUILD_SHARED_LIBS=off -DGGML_NATIVE=off -DGGML_AVX=off -DGGML_AVX2=off -DGGML_AVX512=off -DGGML_FMA=off -DGGML_F16C=off -DGGML_OPENMP=off ${CMAKE_DEFS}"
+    CMAKE_DEFS="-DBUILD_SHARED_LIBS=off -DLLAMA_NATIVE=off -DLLAMA_AVX=off -DLLAMA_AVX2=off -DLLAMA_AVX512=off -DLLAMA_FMA=off -DLLAMA_F16C=off ${CMAKE_DEFS}"
     BUILD_DIR="../build/linux/${ARCH}_static"
     echo "Building static library"
     build
@@ -77,29 +77,29 @@ if [ -z "${OLLAMA_SKIP_CPU_GENERATE}" ]; then
     if [ -n "${OLLAMA_CUSTOM_CPU_DEFS}" ]; then
         init_vars
         echo "OLLAMA_CUSTOM_CPU_DEFS=\"${OLLAMA_CUSTOM_CPU_DEFS}\""
-        CMAKE_DEFS="${OLLAMA_CUSTOM_CPU_DEFS} -DBUILD_SHARED_LIBS=off -DCMAKE_POSITION_INDEPENDENT_CODE=on ${CMAKE_DEFS}"
+        CMAKE_DEFS="${OLLAMA_CUSTOM_CPU_DEFS} -DCMAKE_POSITION_INDEPENDENT_CODE=on ${CMAKE_DEFS}"
         BUILD_DIR="../build/linux/${ARCH}/cpu"
         echo "Building custom CPU"
         build
         compress
     else
         # Darwin Rosetta x86 emulation does NOT support AVX, AVX2, AVX512
-        # -DGGML_AVX -- 2011 Intel Sandy Bridge & AMD Bulldozer
-        # -DGGML_F16C -- 2012 Intel Ivy Bridge & AMD 2011 Bulldozer (No significant improvement over just AVX)
-        # -DGGML_AVX2 -- 2013 Intel Haswell & 2015 AMD Excavator / 2017 AMD Zen
-        # -DGGML_FMA (FMA3) -- 2013 Intel Haswell & 2012 AMD Piledriver
+        # -DLLAMA_AVX -- 2011 Intel Sandy Bridge & AMD Bulldozer
+        # -DLLAMA_F16C -- 2012 Intel Ivy Bridge & AMD 2011 Bulldozer (No significant improvement over just AVX)
+        # -DLLAMA_AVX2 -- 2013 Intel Haswell & 2015 AMD Excavator / 2017 AMD Zen
+        # -DLLAMA_FMA (FMA3) -- 2013 Intel Haswell & 2012 AMD Piledriver
         # Note: the following seem to yield slower results than AVX2 - ymmv
-        # -DGGML_AVX512 -- 2017 Intel Skylake and High End DeskTop (HEDT)
-        # -DGGML_AVX512_VBMI -- 2018 Intel Cannon Lake
-        # -DGGML_AVX512_VNNI -- 2021 Intel Alder Lake
+        # -DLLAMA_AVX512 -- 2017 Intel Skylake and High End DeskTop (HEDT)
+        # -DLLAMA_AVX512_VBMI -- 2018 Intel Cannon Lake
+        # -DLLAMA_AVX512_VNNI -- 2021 Intel Alder Lake
 
-        COMMON_CPU_DEFS="-DBUILD_SHARED_LIBS=off -DCMAKE_POSITION_INDEPENDENT_CODE=on -DGGML_NATIVE=off -DGGML_OPENMP=off"
+        COMMON_CPU_DEFS="-DCMAKE_POSITION_INDEPENDENT_CODE=on -DLLAMA_NATIVE=off"
         if [ -z "${OLLAMA_CPU_TARGET}" -o "${OLLAMA_CPU_TARGET}" = "cpu" ]; then
             #
             # CPU first for the default library, set up as lowest common denominator for maximum compatibility (including Rosetta)
             #
             init_vars
-            CMAKE_DEFS="${COMMON_CPU_DEFS} -DGGML_AVX=off -DGGML_AVX2=off -DGGML_AVX512=off -DGGML_FMA=off -DGGML_F16C=off ${CMAKE_DEFS}"
+            CMAKE_DEFS="${COMMON_CPU_DEFS} -DLLAMA_AVX=off -DLLAMA_AVX2=off -DLLAMA_AVX512=off -DLLAMA_FMA=off -DLLAMA_F16C=off ${CMAKE_DEFS}"
             BUILD_DIR="../build/linux/${ARCH}/cpu"
             echo "Building LCD CPU"
             build
@@ -116,7 +116,7 @@ if [ -z "${OLLAMA_SKIP_CPU_GENERATE}" ]; then
                 # Approximately 400% faster than LCD on same CPU
                 #
                 init_vars
-                CMAKE_DEFS="${COMMON_CPU_DEFS} -DGGML_AVX=on -DGGML_AVX2=off -DGGML_AVX512=off -DGGML_FMA=off -DGGML_F16C=off ${CMAKE_DEFS}"
+                CMAKE_DEFS="${COMMON_CPU_DEFS} -DLLAMA_AVX=on -DLLAMA_AVX2=off -DLLAMA_AVX512=off -DLLAMA_FMA=off -DLLAMA_F16C=off ${CMAKE_DEFS}"
                 BUILD_DIR="../build/linux/${ARCH}/cpu_avx"
                 echo "Building AVX CPU"
                 build
@@ -129,7 +129,7 @@ if [ -z "${OLLAMA_SKIP_CPU_GENERATE}" ]; then
                 # Approximately 10% faster than AVX on same CPU
                 #
                 init_vars
-                CMAKE_DEFS="${COMMON_CPU_DEFS} -DGGML_AVX=on -DGGML_AVX2=on -DGGML_AVX512=off -DGGML_FMA=on -DGGML_F16C=on ${CMAKE_DEFS}"
+                CMAKE_DEFS="${COMMON_CPU_DEFS} -DLLAMA_AVX=on -DLLAMA_AVX2=on -DLLAMA_AVX512=off -DLLAMA_FMA=on -DLLAMA_F16C=on ${CMAKE_DEFS}"
                 BUILD_DIR="../build/linux/${ARCH}/cpu_avx2"
                 echo "Building AVX2 CPU"
                 build
@@ -170,15 +170,15 @@ if [ -z "${OLLAMA_SKIP_CUDA_GENERATE}" -a -d "${CUDA_LIB_DIR}" ]; then
         #
         # CUDA compute < 6.0 lacks proper FP16 support on ARM.
         # Disabling has minimal performance effect while maintaining compatibility.
-        ARM64_DEFS="-DGGML_AVX=off -DGGML_AVX2=off -DGGML_AVX512=off -DGGML_CUDA_F16=off"
+        ARM64_DEFS="-DLLAMA_AVX=off -DLLAMA_AVX2=off -DLLAMA_AVX512=off -DLLAMA_CUDA_F16=off"
     fi
     # Users building from source can tune the exact flags we pass to cmake for configuring llama.cpp
     if [ -n "${OLLAMA_CUSTOM_CUDA_DEFS}" ]; then
         echo "OLLAMA_CUSTOM_CUDA_DEFS=\"${OLLAMA_CUSTOM_CUDA_DEFS}\""
-        CMAKE_CUDA_DEFS="-DGGML_CUDA=on -DCMAKE_CUDA_ARCHITECTURES=${CMAKE_CUDA_ARCHITECTURES} ${OLLAMA_CUSTOM_CUDA_DEFS}"
+        CMAKE_CUDA_DEFS="-DLLAMA_CUDA=on -DCMAKE_CUDA_ARCHITECTURES=${CMAKE_CUDA_ARCHITECTURES} ${OLLAMA_CUSTOM_CUDA_DEFS}"
         echo "Building custom CUDA GPU"
     else
-        CMAKE_CUDA_DEFS="-DGGML_CUDA=on -DCMAKE_CUDA_FLAGS=-t8 -DCMAKE_CUDA_ARCHITECTURES=${CMAKE_CUDA_ARCHITECTURES}"
+        CMAKE_CUDA_DEFS="-DLLAMA_CUDA=on -DLLAMA_CUDA_FORCE_MMQ=on -DCMAKE_CUDA_ARCHITECTURES=${CMAKE_CUDA_ARCHITECTURES}"
     fi
     CMAKE_DEFS="${COMMON_CMAKE_DEFS} ${CMAKE_DEFS} ${ARM64_DEFS} ${CMAKE_CUDA_DEFS}"
     BUILD_DIR="../build/linux/${ARCH}/cuda${CUDA_VARIANT}"
@@ -216,7 +216,7 @@ if [ -z "${OLLAMA_SKIP_ONEAPI_GENERATE}" -a -d "${ONEAPI_ROOT}" ]; then
     init_vars
     source ${ONEAPI_ROOT}/setvars.sh --force # set up environment variables for oneAPI
     CC=icx
-    CMAKE_DEFS="${COMMON_CMAKE_DEFS} ${CMAKE_DEFS} -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx -DGGML_SYCL=ON -DGGML_SYCL_F16=OFF"
+    CMAKE_DEFS="${COMMON_CMAKE_DEFS} ${CMAKE_DEFS} -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx -DLLAMA_SYCL=ON -DLLAMA_SYCL_F16=OFF"
     BUILD_DIR="../build/linux/${ARCH}/oneapi"
     EXTRA_LIBS="-fsycl -Wl,-rpath,${ONEAPI_ROOT}/compiler/latest/lib,-rpath,${ONEAPI_ROOT}/mkl/latest/lib,-rpath,${ONEAPI_ROOT}/tbb/latest/lib,-rpath,${ONEAPI_ROOT}/compiler/latest/opt/oclfpga/linux64/lib -lOpenCL -lmkl_core -lmkl_sycl_blas -lmkl_intel_ilp64 -lmkl_tbb_thread -ltbb"
     DEBUG_FLAGS="" # icx compiles with -O0 if we pass -g, so we must remove it
@@ -254,7 +254,7 @@ if [ -z "${OLLAMA_SKIP_ROCM_GENERATE}" -a -d "${ROCM_PATH}" ]; then
         ROCM_VARIANT=_v$(ls ${ROCM_PATH}/lib/librocblas.so.*.*.????? | cut -f5 -d. || true)
     fi
     init_vars
-    CMAKE_DEFS="${COMMON_CMAKE_DEFS} ${CMAKE_DEFS} -DGGML_HIPBLAS=on -DLLAMA_CUDA_NO_PEER_COPY=on -DCMAKE_C_COMPILER=$ROCM_PATH/llvm/bin/clang -DCMAKE_CXX_COMPILER=$ROCM_PATH/llvm/bin/clang++ -DAMDGPU_TARGETS=$(amdGPUs) -DGPU_TARGETS=$(amdGPUs)"
+    CMAKE_DEFS="${COMMON_CMAKE_DEFS} ${CMAKE_DEFS} -DLLAMA_HIPBLAS=on -DCMAKE_C_COMPILER=$ROCM_PATH/llvm/bin/clang -DCMAKE_CXX_COMPILER=$ROCM_PATH/llvm/bin/clang++ -DAMDGPU_TARGETS=$(amdGPUs) -DGPU_TARGETS=$(amdGPUs)"
     # Users building from source can tune the exact flags we pass to cmake for configuring llama.cpp
     if [ -n "${OLLAMA_CUSTOM_ROCM_DEFS}" ]; then
         echo "OLLAMA_CUSTOM_ROCM_DEFS=\"${OLLAMA_CUSTOM_ROCM_DEFS}\""

llm/generate/gen_windows.ps1

@@ -6,9 +6,18 @@ function amdGPUs {
     if ($env:AMDGPU_TARGETS) {
         return $env:AMDGPU_TARGETS
     }
-    # Current supported rocblas list from ROCm v6.1.2 on windows
-    # https://rocm.docs.amd.com/projects/install-on-windows/en/latest/reference/system-requirements.html#windows-supported-gpus
+    # TODO - load from some common data file for linux + windows build consistency
     $GPU_LIST = @(
+        "gfx900"
+        "gfx906:xnack-"
+        "gfx908:xnack-"
+        "gfx90a:xnack+"
+        "gfx90a:xnack-"
+        "gfx940"
+        "gfx941"
+        "gfx942"
+        "gfx1010"
+        "gfx1012"
         "gfx1030"
         "gfx1100"
         "gfx1101"
@@ -30,8 +39,7 @@ function init_vars {
     }
     $script:cmakeDefs = @(
         "-DBUILD_SHARED_LIBS=on",
-        "-DGGML_NATIVE=off",
-        "-DGGML_OPENMP=off"
+        "-DLLAMA_NATIVE=off"
         )
     $script:commonCpuDefs = @("-DCMAKE_POSITION_INDEPENDENT_CODE=on")
     $script:ARCH = $Env:PROCESSOR_ARCHITECTURE.ToLower()
@@ -114,13 +122,8 @@ function build {
     & cmake --version
     & cmake -S "${script:llamacppDir}" -B $script:buildDir $script:cmakeDefs
     if ($LASTEXITCODE -ne 0) { exit($LASTEXITCODE)}
-    if ($cmakeDefs -contains "-G") {
-        $extra=@("-j8")
-    } else {
-        $extra= @("--", "/p:CL_MPcount=8")
-    }
-    write-host "building with: cmake --build $script:buildDir --config $script:config $($script:cmakeTargets | ForEach-Object { `"--target`", $_ }) $extra"
-    & cmake --build $script:buildDir --config $script:config ($script:cmakeTargets | ForEach-Object { "--target", $_ }) $extra
+    write-host "building with: cmake --build $script:buildDir --config $script:config $($script:cmakeTargets | ForEach-Object { `"--target`", $_ })"
+    & cmake --build $script:buildDir --config $script:config ($script:cmakeTargets | ForEach-Object { "--target", $_ })
     if ($LASTEXITCODE -ne 0) { exit($LASTEXITCODE)}
     # Rearrange output to be consistent between different generators
     if ($null -ne ${script:config} -And (test-path -path "${script:buildDir}/bin/${script:config}" ) ) {
@@ -173,9 +176,9 @@ function cleanup {
 }
 
 
-# -DGGML_AVX -- 2011 Intel Sandy Bridge & AMD Bulldozer
-# -DGGML_AVX2 -- 2013 Intel Haswell & 2015 AMD Excavator / 2017 AMD Zen
-# -DGGML_FMA (FMA3) -- 2013 Intel Haswell & 2012 AMD Piledriver
+# -DLLAMA_AVX -- 2011 Intel Sandy Bridge & AMD Bulldozer
+# -DLLAMA_AVX2 -- 2013 Intel Haswell & 2015 AMD Excavator / 2017 AMD Zen
+# -DLLAMA_FMA (FMA3) -- 2013 Intel Haswell & 2012 AMD Piledriver
 
 
 function build_static() {
@@ -195,13 +198,12 @@ function build_static() {
             "-DCMAKE_C_COMPILER=gcc.exe",
             "-DCMAKE_CXX_COMPILER=g++.exe",
             "-DBUILD_SHARED_LIBS=off",
-            "-DGGML_NATIVE=off",
-            "-DGGML_AVX=off",
-            "-DGGML_AVX2=off",
-            "-DGGML_AVX512=off",
-            "-DGGML_F16C=off",
-            "-DGGML_FMA=off",
-            "-DGGML_OPENMP=off")
+            "-DLLAMA_NATIVE=off",
+            "-DLLAMA_AVX=off",
+            "-DLLAMA_AVX2=off",
+            "-DLLAMA_AVX512=off",
+            "-DLLAMA_F16C=off",
+            "-DLLAMA_FMA=off")
         $script:buildDir="../build/windows/${script:ARCH}_static"
         write-host "Building static library"
         build
@@ -215,7 +217,7 @@ function build_cpu($gen_arch) {
     if ((-not "${env:OLLAMA_SKIP_CPU_GENERATE}" ) -and ((-not "${env:OLLAMA_CPU_TARGET}") -or ("${env:OLLAMA_CPU_TARGET}" -eq "cpu"))) {
         # remaining llama.cpp builds use MSVC 
         init_vars
-        $script:cmakeDefs = $script:commonCpuDefs + @("-A", $gen_arch, "-DGGML_AVX=off", "-DGGML_AVX2=off", "-DGGML_AVX512=off", "-DGGML_FMA=off", "-DGGML_F16C=off") + $script:cmakeDefs
+        $script:cmakeDefs = $script:commonCpuDefs + @("-A", $gen_arch, "-DLLAMA_AVX=off", "-DLLAMA_AVX2=off", "-DLLAMA_AVX512=off", "-DLLAMA_FMA=off", "-DLLAMA_F16C=off") + $script:cmakeDefs
         $script:buildDir="../build/windows/${script:ARCH}/cpu"
         $script:distDir="$script:DIST_BASE\cpu"
         write-host "Building LCD CPU"
@@ -230,7 +232,7 @@ function build_cpu($gen_arch) {
 function build_cpu_avx() {
     if ((-not "${env:OLLAMA_SKIP_CPU_GENERATE}" ) -and ((-not "${env:OLLAMA_CPU_TARGET}") -or ("${env:OLLAMA_CPU_TARGET}" -eq "cpu_avx"))) {
         init_vars
-        $script:cmakeDefs = $script:commonCpuDefs + @("-A", "x64", "-DGGML_AVX=on", "-DGGML_AVX2=off", "-DGGML_AVX512=off", "-DGGML_FMA=off", "-DGGML_F16C=off") + $script:cmakeDefs
+        $script:cmakeDefs = $script:commonCpuDefs + @("-A", "x64", "-DLLAMA_AVX=on", "-DLLAMA_AVX2=off", "-DLLAMA_AVX512=off", "-DLLAMA_FMA=off", "-DLLAMA_F16C=off") + $script:cmakeDefs
         $script:buildDir="../build/windows/${script:ARCH}/cpu_avx"
         $script:distDir="$script:DIST_BASE\cpu_avx"
         write-host "Building AVX CPU"
@@ -245,7 +247,7 @@ function build_cpu_avx() {
 function build_cpu_avx2() {
     if ((-not "${env:OLLAMA_SKIP_CPU_GENERATE}" ) -and ((-not "${env:OLLAMA_CPU_TARGET}") -or ("${env:OLLAMA_CPU_TARGET}" -eq "cpu_avx2"))) {
         init_vars
-        $script:cmakeDefs = $script:commonCpuDefs + @("-A", "x64", "-DGGML_AVX=on", "-DGGML_AVX2=on", "-DGGML_AVX512=off", "-DGGML_FMA=on", "-DGGML_F16C=on") + $script:cmakeDefs
+        $script:cmakeDefs = $script:commonCpuDefs + @("-A", "x64", "-DLLAMA_AVX=on", "-DLLAMA_AVX2=on", "-DLLAMA_AVX512=off", "-DLLAMA_FMA=on", "-DLLAMA_F16C=on") + $script:cmakeDefs
         $script:buildDir="../build/windows/${script:ARCH}/cpu_avx2"
         $script:distDir="$script:DIST_BASE\cpu_avx2"
         write-host "Building AVX2 CPU"
@@ -268,15 +270,7 @@ function build_cuda() {
         init_vars
         $script:buildDir="../build/windows/${script:ARCH}/cuda$script:CUDA_VARIANT"
         $script:distDir="$script:DIST_BASE\cuda$script:CUDA_VARIANT"
-        $script:cmakeDefs += @(
-            "-A", "x64",
-            "-DGGML_CUDA=ON",
-            "-DGGML_AVX=on",
-            "-DGGML_AVX2=off",
-            "-DCUDAToolkit_INCLUDE_DIR=$script:CUDA_INCLUDE_DIR",
-            "-DCMAKE_CUDA_FLAGS=-t8",
-            "-DCMAKE_CUDA_ARCHITECTURES=${script:CMAKE_CUDA_ARCHITECTURES}"
-            )
+        $script:cmakeDefs += @("-A", "x64", "-DLLAMA_CUDA=ON", "-DLLAMA_AVX=on", "-DLLAMA_AVX2=off", "-DCUDAToolkit_INCLUDE_DIR=$script:CUDA_INCLUDE_DIR", "-DCMAKE_CUDA_ARCHITECTURES=${script:CMAKE_CUDA_ARCHITECTURES}")
         if ($null -ne $env:OLLAMA_CUSTOM_CUDA_DEFS) {
             write-host "OLLAMA_CUSTOM_CUDA_DEFS=`"${env:OLLAMA_CUSTOM_CUDA_DEFS}`""
             $script:cmakeDefs +=@("${env:OLLAMA_CUSTOM_CUDA_DEFS}")
@@ -286,12 +280,10 @@ function build_cuda() {
         sign
         install
 
-        rm -ea 0 -recurse -force -path "${script:SRC_DIR}\dist\windows-${script:ARCH}\cuda\"
-        md "${script:SRC_DIR}\dist\windows-${script:ARCH}\cuda\" -ea 0 > $null
-        write-host "copying CUDA dependencies to ${script:SRC_DIR}\dist\windows-${script:ARCH}\cuda\"
-        cp "${script:CUDA_LIB_DIR}\cudart64_*.dll" "${script:SRC_DIR}\dist\windows-${script:ARCH}\cuda\"
-        cp "${script:CUDA_LIB_DIR}\cublas64_*.dll" "${script:SRC_DIR}\dist\windows-${script:ARCH}\cuda\"
-        cp "${script:CUDA_LIB_DIR}\cublasLt64_*.dll" "${script:SRC_DIR}\dist\windows-${script:ARCH}\cuda\"
+        write-host "copying CUDA dependencies to ${script:SRC_DIR}\dist\windows-${script:ARCH}\"
+        cp "${script:CUDA_LIB_DIR}\cudart64_*.dll" "${script:SRC_DIR}\dist\windows-${script:ARCH}\"
+        cp "${script:CUDA_LIB_DIR}\cublas64_*.dll" "${script:SRC_DIR}\dist\windows-${script:ARCH}\"
+        cp "${script:CUDA_LIB_DIR}\cublasLt64_*.dll" "${script:SRC_DIR}\dist\windows-${script:ARCH}\"
     } else {
         write-host "Skipping CUDA generation step"
     }
@@ -310,7 +302,7 @@ function build_oneapi() {
     $script:distDir ="$script:DIST_BASE\oneapi$script:ONEAPI_VARIANT"
     $script:cmakeDefs += @(
       "-G", "MinGW Makefiles",
-      "-DGGML_SYCL=ON",
+      "-DLLAMA_SYCL=ON",
       "-DCMAKE_C_COMPILER=icx",
       "-DCMAKE_CXX_COMPILER=icx",
       "-DCMAKE_BUILD_TYPE=Release"
@@ -325,18 +317,16 @@ function build_oneapi() {
     sign
     install
 
-    rm -ea 0 -recurse -force -path "${script:SRC_DIR}\dist\windows-${script:ARCH}\oneapi\"
-    md "${script:SRC_DIR}\dist\windows-${script:ARCH}\oneapi\" -ea 0 > $null
-    cp "${env:ONEAPI_ROOT}\compiler\latest\bin\libirngmd.dll" "${script:SRC_DIR}\dist\windows-${script:ARCH}\oneapi\"
-    cp "${env:ONEAPI_ROOT}\compiler\latest\bin\libmmd.dll" "${script:SRC_DIR}\dist\windows-${script:ARCH}\oneapi\"
-    cp "${env:ONEAPI_ROOT}\compiler\latest\bin\pi_level_zero.dll" "${script:SRC_DIR}\dist\windows-${script:ARCH}\oneapi\"
-    cp "${env:ONEAPI_ROOT}\compiler\latest\bin\pi_unified_runtime.dll" "${script:SRC_DIR}\dist\windows-${script:ARCH}\oneapi\"
-    cp "${env:ONEAPI_ROOT}\compiler\latest\bin\pi_win_proxy_loader.dll" "${script:SRC_DIR}\dist\windows-${script:ARCH}\oneapi\"
-    cp "${env:ONEAPI_ROOT}\compiler\latest\bin\svml_dispmd.dll" "${script:SRC_DIR}\dist\windows-${script:ARCH}\oneapi\"
-    cp "${env:ONEAPI_ROOT}\compiler\latest\bin\sycl7.dll" "${script:SRC_DIR}\dist\windows-${script:ARCH}\oneapi\"
-    cp "${env:ONEAPI_ROOT}\mkl\latest\bin\mkl_core.2.dll" "${script:SRC_DIR}\dist\windows-${script:ARCH}\oneapi\"
-    cp "${env:ONEAPI_ROOT}\mkl\latest\bin\mkl_sycl_blas.4.dll" "${script:SRC_DIR}\dist\windows-${script:ARCH}\oneapi\"
-    cp "${env:ONEAPI_ROOT}\mkl\latest\bin\mkl_tbb_thread.2.dll" "${script:SRC_DIR}\dist\windows-${script:ARCH}\oneapi\"
+    cp "${env:ONEAPI_ROOT}\compiler\latest\bin\libirngmd.dll" "${script:distDir}"
+    cp "${env:ONEAPI_ROOT}\compiler\latest\bin\libmmd.dll" "${script:distDir}"
+    cp "${env:ONEAPI_ROOT}\compiler\latest\bin\pi_level_zero.dll" "${script:distDir}"
+    cp "${env:ONEAPI_ROOT}\compiler\latest\bin\pi_unified_runtime.dll" "${script:distDir}"
+    cp "${env:ONEAPI_ROOT}\compiler\latest\bin\pi_win_proxy_loader.dll" "${script:distDir}"
+    cp "${env:ONEAPI_ROOT}\compiler\latest\bin\svml_dispmd.dll" "${script:distDir}"
+    cp "${env:ONEAPI_ROOT}\compiler\latest\bin\sycl7.dll" "${script:distDir}"
+    cp "${env:ONEAPI_ROOT}\mkl\latest\bin\mkl_core.2.dll" "${script:distDir}"
+    cp "${env:ONEAPI_ROOT}\mkl\latest\bin\mkl_sycl_blas.4.dll" "${script:distDir}"
+    cp "${env:ONEAPI_ROOT}\mkl\latest\bin\mkl_tbb_thread.2.dll" "${script:distDir}"
   } else {
     Write-Host "Skipping oneAPI generation step"
   }
@@ -356,11 +346,10 @@ function build_rocm() {
             "-G", "Ninja", 
             "-DCMAKE_C_COMPILER=clang.exe",
             "-DCMAKE_CXX_COMPILER=clang++.exe",
-            "-DGGML_HIPBLAS=on",
-            "-DLLAMA_CUDA_NO_PEER_COPY=on",
+            "-DLLAMA_HIPBLAS=on",
             "-DHIP_PLATFORM=amd",
-            "-DGGML_AVX=on",
-            "-DGGML_AVX2=off",
+            "-DLLAMA_AVX=on",
+            "-DLLAMA_AVX2=off",
             "-DCMAKE_POSITION_INDEPENDENT_CODE=on",
             "-DAMDGPU_TARGETS=$(amdGPUs)",
             "-DGPU_TARGETS=$(amdGPUs)"
@@ -386,6 +375,7 @@ function build_rocm() {
         sign
         install
 
+        # Assumes v5.7, may need adjustments for v6
         rm -ea 0 -recurse -force -path "${script:SRC_DIR}\dist\windows-${script:ARCH}\rocm\"
         md "${script:SRC_DIR}\dist\windows-${script:ARCH}\rocm\rocblas\library\" -ea 0 > $null
         cp "${env:HIP_PATH}\bin\hipblas.dll" "${script:SRC_DIR}\dist\windows-${script:ARCH}\rocm\"

llm/ggla.go

@@ -53,7 +53,7 @@ func (llm *ggla) Tensors() Tensors {
 	return llm.tensors
 }
 
-func (llm *ggla) decode(rs io.ReadSeeker) (retErr error) {
+func (llm *ggla) decode(rs io.ReadSeeker) error {
 	var r uint32
 	if err := binary.Read(rs, binary.LittleEndian, &r); err != nil {
 		return err
@@ -69,18 +69,9 @@ func (llm *ggla) decode(rs io.ReadSeeker) (retErr error) {
 	for {
 		var dims uint32
 		if err := binary.Read(rs, binary.LittleEndian, &dims); err != nil {
-			if errors.Is(err, io.EOF) {
-				return nil
-			}
 			return err
 		}
 
-		defer func() {
-			if errors.Is(retErr, io.EOF) {
-				retErr = io.ErrUnexpectedEOF
-			}
-		}()
-
 		var namesize uint32
 		if err := binary.Read(rs, binary.LittleEndian, &namesize); err != nil {
 			return err
@@ -117,7 +108,7 @@ func (llm *ggla) decode(rs io.ReadSeeker) (retErr error) {
 			return err
 		}
 
-		if _, err := rs.Seek((offset+31)&-32-offset, io.SeekCurrent); err != nil {
+		if _, err := rs.Seek((offset+31)&-32, io.SeekStart); err != nil {
 			return err
 		}
 

llm/ggml.go

@@ -6,8 +6,6 @@ import (
 	"fmt"
 	"io"
 	"strings"
-
-	"github.com/ollama/ollama/util/bufioutil"
 )
 
 type GGML struct {
@@ -71,30 +69,6 @@ func (kv KV) HeadCountKV() uint64 {
 	return 1
 }
 
-func (kv KV) EmbeddingHeadCount() uint64 {
-	if heads := kv.HeadCount(); heads > 0 {
-		return kv.EmbeddingLength() / kv.HeadCount()
-	}
-
-	return 0
-}
-
-func (kv KV) EmbeddingHeadCountK() uint64 {
-	if k := kv.u64(fmt.Sprintf("%s.attention.key_length", kv.Architecture())); k > 0 {
-		return k
-	}
-
-	return kv.EmbeddingHeadCount()
-}
-
-func (kv KV) EmbeddingHeadCountV() uint64 {
-	if v := kv.u64(fmt.Sprintf("%s.attention.value_length", kv.Architecture())); v > 0 {
-		return v
-	}
-
-	return kv.EmbeddingHeadCount()
-}
-
 func (kv KV) GQA() uint64 {
 	return kv.HeadCount() / kv.HeadCountKV()
 }
@@ -280,18 +254,7 @@ func DetectGGMLType(b []byte) string {
 	}
 }
 
-// DecodeGGML decodes a GGML model from the given reader.
-//
-// It collects array values for arrays with a size less than or equal to
-// maxArraySize. If maxArraySize is 0, the default value of 1024 is used. If
-// the maxArraySize is negative, all arrays are collected.
-func DecodeGGML(rs io.ReadSeeker, maxArraySize int) (*GGML, int64, error) {
-	if maxArraySize == 0 {
-		maxArraySize = 1024
-	}
-
-	rs = bufioutil.NewBufferedSeeker(rs, 32<<10)
-
+func DecodeGGML(rs io.ReadSeeker) (*GGML, int64, error) {
 	var magic uint32
 	if err := binary.Read(rs, binary.LittleEndian, &magic); err != nil {
 		return nil, 0, err
@@ -304,15 +267,17 @@ func DecodeGGML(rs io.ReadSeeker, maxArraySize int) (*GGML, int64, error) {
 	case FILE_MAGIC_GGLA:
 		c = &containerGGLA{}
 	case FILE_MAGIC_GGUF_LE:
-		c = &containerGGUF{ByteOrder: binary.LittleEndian, maxArraySize: maxArraySize}
+		c = &containerGGUF{ByteOrder: binary.LittleEndian}
 	case FILE_MAGIC_GGUF_BE:
-		c = &containerGGUF{ByteOrder: binary.BigEndian, maxArraySize: maxArraySize}
+		c = &containerGGUF{ByteOrder: binary.BigEndian}
 	default:
 		return nil, 0, errors.New("invalid file magic")
 	}
 
 	model, err := c.Decode(rs)
-	if err != nil {
+	if errors.Is(err, io.EOF) {
+		// noop
+	} else if err != nil {
 		return nil, 0, err
 	}
 
@@ -332,10 +297,7 @@ func (llm GGML) GraphSize(context, batch uint64) (partialOffload, fullOffload ui
 	embedding := llm.KV().EmbeddingLength()
 	heads := llm.KV().HeadCount()
 	headsKV := llm.KV().HeadCountKV()
-	vocab := uint64(llm.KV()["tokenizer.ggml.tokens"].(*array).size)
-
-	embeddingHeads := llm.KV().EmbeddingHeadCount()
-	embeddingHeadsK := llm.KV().EmbeddingHeadCountK()
+	vocab := uint64(len(llm.KV()["tokenizer.ggml.tokens"].([]any)))
 
 	layers := llm.Tensors().Layers()
 
@@ -345,8 +307,7 @@ func (llm GGML) GraphSize(context, batch uint64) (partialOffload, fullOffload ui
 
 		partialOffload = 4 * batch * embedding
 		partialOffload += max(
-			// 4*batch*(4+6*embedding+context*(2*heads)+llm.KV().GQA()),
-			4*batch*(1+embedding+max(context, embedding))+embedding*embedding*9/16+4*context*(batch*heads+embeddingHeads*headsKV),
+			4*batch*(1+embedding+max(context, embedding))+embedding*embedding*9/16+4*context*(batch*heads+embedding/heads*headsKV),
 			4*batch*(embedding+vocab)+embedding*vocab*105/128,
 		)
 
@@ -354,30 +315,21 @@ func (llm GGML) GraphSize(context, batch uint64) (partialOffload, fullOffload ui
 			// mixtral 8x22b
 			ff := uint64(llm.KV()["llama.feed_forward_length"].(uint32))
 			partialOffload = max(
-				3*ffnGateExpsWeight.Size()+4*batch*(2*ff+headsKV+embedding+context+embeddingHeads*headsKV),
-				4*(context*batch*heads+context*embeddingHeads*headsKV+batch*1024+embeddingHeads*headsKV*batch),
+				3*ffnGateExpsWeight.Size()+4*batch*(2*ff+headsKV+embedding+context+embedding/heads*headsKV),
+				4*(context*batch*heads+context*embedding/heads*headsKV+batch*1024+embedding/heads*headsKV*batch),
 			)
 		} else if ffnGateWeight, ok := layers["blk.0"]["ffn_gate.0.weight"]; ok {
 			// mixtral 8x7b
 			ffnGateWeight1 := ffnGateWeight.Shape[1]
 			fullOffload = 4 * batch * (2 + 3*embedding + context*(1+heads) + 2*headsKV + ffnGateWeight1)
 			partialOffload = max(
-				4*batch*(3+embeddingHeads*headsKV+embedding+context*(1+heads)+ffnGateWeight1)+(embedding*embedding+3*embedding*headsKV*ffnGateWeight1)*9/16,
+				4*batch*(3+embedding/heads*headsKV+embedding+context*(1+heads)+ffnGateWeight1)+(embedding*embedding+3*embedding*headsKV*ffnGateWeight1)*9/16,
 				4*batch*(1+2*embedding+context*(1+heads))+embedding*(6*context*headsKV/heads+embedding*9/16),
 			)
 		}
-	case "gemma", "gemma2":
-		fullOffload = max(
-			4*batch*(embedding+vocab),
-			4*batch*(2+context+context*heads+2*embedding+2*embeddingHeadsK*heads),
-		)
-
-		partialOffload = max(
-			4*embedding*batch+embedding*vocab*105/128+4*vocab*batch,
-			4*batch*(2*embedding+1+2*embeddingHeadsK*heads+context+context*heads)+
-				4*embeddingHeadsK*context*8+
-				embedding*embeddingHeadsK*heads*9/16,
-		)
+	case "gemma":
+		fullOffload = 4 * batch * (embedding + vocab)
+		partialOffload = 4*batch*(2*embedding+vocab+1) + embedding*vocab*105/128
 	case "command-r":
 		fullOffload = max(
 			4*batch*(embedding+vocab),
@@ -414,42 +366,6 @@ func (llm GGML) GraphSize(context, batch uint64) (partialOffload, fullOffload ui
 			4*batch*(vocab+2*embedding),
 			fullOffload,
 		)
-	case "deepseek2":
-		fullOffload = max(
-			4*batch*(3*embedding+vocab),
-			4*batch*(3*embedding+2+context*(1+headsKV)+2*embeddingHeadsK*headsKV),
-		)
-
-		partialOffload = max(
-			4*batch*(3*embedding+vocab)+embedding*vocab*105/128,
-			4*batch*(2*embedding+1+2*embeddingHeadsK*headsKV+context+context*headsKV)+4*embeddingHeadsK*context*headsKV+embedding*embeddingHeadsK*headsKV*9/16,
-		)
-	case "chatglm":
-		fullOffload = 4 * batch * (embedding + vocab)
-		partialOffload = 4*batch*(embedding+vocab) + embedding*vocab*105/128
-		if qkvBias, ok := layers["blk.0"]["attn_qkv.bias"]; ok {
-			fullOffload = max(
-				fullOffload,
-				4*batch*(2+
-					2*embedding+
-					context+
-					context*heads+
-					embeddingHeadsK*heads+
-					qkvBias.Shape[0]),
-			)
-
-			partialOffload = max(
-				partialOffload,
-				4*batch*(1+
-					2*embedding+
-					embeddingHeadsK*heads+
-					context+
-					context*heads)+
-					4*embeddingHeadsK*context+
-					4*context*embeddingHeadsK+
-					4*qkvBias.Shape[0],
-			)
-		}
 	}
 
 	return

llm/ggml_test.go

@@ -1 +0,0 @@
-package llm

llm/gguf.go

@@ -3,10 +3,11 @@ package llm
 import (
 	"bytes"
 	"encoding/binary"
-	"encoding/json"
 	"fmt"
 	"io"
 	"strings"
+
+	"log/slog"
 )
 
 type containerGGUF struct {
@@ -28,12 +29,6 @@ type containerGGUF struct {
 		NumTensor uint64
 		NumKV     uint64
 	}
-
-	maxArraySize int
-}
-
-func (c *containerGGUF) canCollectArray(size int) bool {
-	return c.maxArraySize < 0 || size <= c.maxArraySize
 }
 
 func (c *containerGGUF) Name() string {
@@ -59,6 +54,7 @@ func (c *containerGGUF) Decode(rs io.ReadSeeker) (model, error) {
 	}
 
 	model := newGGUF(c)
+	slog.Debug(fmt.Sprintf("model = %#v", model))
 	if err := model.Decode(rs); err != nil {
 		return nil, err
 	}
@@ -89,8 +85,6 @@ type gguf struct {
 	tensors []*Tensor
 
 	parameters uint64
-
-	scratch [16 << 10]byte
 }
 
 func newGGUF(container *containerGGUF) *gguf {
@@ -187,34 +181,34 @@ func (llm *gguf) Decode(rs io.ReadSeeker) error {
 	}
 
 	// decode tensors
-	for range llm.numTensor() {
+	for i := 0; uint64(i) < llm.numTensor(); i++ {
 		name, err := readGGUFString(llm, rs)
 		if err != nil {
-			return fmt.Errorf("failed to read tensor name: %w", err)
+			return err
 		}
 
 		// dims is the number of dimensions in the tensor
 		dims, err := readGGUF[uint32](llm, rs)
 		if err != nil {
-			return fmt.Errorf("failed to read tensor dimensions: %w", err)
+			return err
 		}
 
 		shape := [4]uint64{1, 1, 1, 1}
 		for i := 0; uint32(i) < dims; i++ {
 			shape[i], err = readGGUF[uint64](llm, rs)
 			if err != nil {
-				return fmt.Errorf("failed to read tensor shape: %w", err)
+				return err
 			}
 		}
 
 		kind, err := readGGUF[uint32](llm, rs)
 		if err != nil {
-			return fmt.Errorf("failed to read tensor kind: %w", err)
+			return err
 		}
 
 		offset, err := readGGUF[uint64](llm, rs)
 		if err != nil {
-			return fmt.Errorf("failed to read tensor offset: %w", err)
+			return err
 		}
 
 		tensor := Tensor{
@@ -236,19 +230,24 @@ func (llm *gguf) Decode(rs io.ReadSeeker) error {
 		alignment = 32
 	}
 
+	offset, err := rs.Seek(0, io.SeekCurrent)
+	if err != nil {
+		return err
+	}
+
+	padding := llm.padding(offset, int64(alignment))
+	if _, err := rs.Seek(padding, io.SeekCurrent); err != nil {
+		return err
+	}
+
 	for _, tensor := range llm.tensors {
-		offset, err := rs.Seek(0, io.SeekCurrent)
-		if err != nil {
-			return fmt.Errorf("failed to get current offset: %w", err)
-		}
-
-		padding := llm.padding(offset, int64(alignment))
-		if _, err := rs.Seek(padding, io.SeekCurrent); err != nil {
-			return fmt.Errorf("failed to seek to init padding: %w", err)
-		}
-
 		if _, err := rs.Seek(int64(tensor.Size()), io.SeekCurrent); err != nil {
-			return fmt.Errorf("failed to seek to tensor: %w", err)
+			return err
+		}
+
+		padding := llm.padding(int64(tensor.Size()), int64(alignment))
+		if _, err := rs.Seek(padding, io.SeekCurrent); err != nil {
+			return err
 		}
 	}
 
@@ -286,48 +285,22 @@ func readGGUFV1String(llm *gguf, r io.Reader) (string, error) {
 	return b.String(), nil
 }
 
-func discardGGUFString(llm *gguf, r io.Reader) error {
-	buf := llm.scratch[:8]
-	_, err := io.ReadFull(r, buf)
-	if err != nil {
-		return err
-	}
-
-	size := int(llm.ByteOrder.Uint64(buf))
-	for size > 0 {
-		n, err := r.Read(llm.scratch[:min(size, cap(llm.scratch))])
-		if err != nil {
-			return err
-		}
-		size -= n
-	}
-	return nil
-}
-
 func readGGUFString(llm *gguf, r io.Reader) (string, error) {
 	if llm.Version == 1 {
 		return readGGUFV1String(llm, r)
 	}
 
-	buf := llm.scratch[:8]
-	_, err := io.ReadFull(r, buf)
-	if err != nil {
+	var length uint64
+	if err := binary.Read(r, llm.ByteOrder, &length); err != nil {
 		return "", err
 	}
 
-	length := int(llm.ByteOrder.Uint64(buf))
-	if length > len(llm.scratch) {
-		buf = make([]byte, length)
-	} else {
-		buf = llm.scratch[:length]
-	}
-	clear(buf)
-
-	_, err = io.ReadFull(r, buf)
-	if err != nil {
+	var b bytes.Buffer
+	if _, err := io.CopyN(&b, r, int64(length)); err != nil {
 		return "", err
 	}
-	return string(buf), nil
+
+	return b.String(), nil
 }
 
 func writeGGUFString(llm *gguf, w io.Writer, s string) error {
@@ -343,16 +316,7 @@ func writeGGUFString(llm *gguf, w io.Writer, s string) error {
 	return err
 }
 
-type array struct {
-	size   int
-	values []any
-}
-
-func (a *array) MarshalJSON() ([]byte, error) {
-	return json.Marshal(a.values)
-}
-
-func readGGUFV1Array(llm *gguf, r io.Reader) (*array, error) {
+func readGGUFV1Array(llm *gguf, r io.Reader) (a []any, err error) {
 	t, err := readGGUF[uint32](llm, r)
 	if err != nil {
 		return nil, err
@@ -363,12 +327,7 @@ func readGGUFV1Array(llm *gguf, r io.Reader) (*array, error) {
 		return nil, err
 	}
 
-	a := &array{size: int(n)}
-	if llm.canCollectArray(int(n)) {
-		a.values = make([]any, 0, int(n))
-	}
-
-	for i := range n {
+	for i := 0; uint32(i) < n; i++ {
 		var e any
 		switch t {
 		case ggufTypeUint8:
@@ -402,15 +361,13 @@ func readGGUFV1Array(llm *gguf, r io.Reader) (*array, error) {
 			return nil, err
 		}
 
-		if a.values != nil {
-			a.values[i] = e
-		}
+		a = append(a, e)
 	}
 
-	return a, nil
+	return
 }
 
-func readGGUFArray(llm *gguf, r io.Reader) (*array, error) {
+func readGGUFArray(llm *gguf, r io.Reader) (a []any, err error) {
 	if llm.Version == 1 {
 		return readGGUFV1Array(llm, r)
 	}
@@ -425,12 +382,7 @@ func readGGUFArray(llm *gguf, r io.Reader) (*array, error) {
 		return nil, err
 	}
 
-	a := &array{size: int(n)}
-	if llm.canCollectArray(int(n)) {
-		a.values = make([]any, int(n))
-	}
-
-	for i := range n {
+	for i := 0; uint64(i) < n; i++ {
 		var e any
 		switch t {
 		case ggufTypeUint8:
@@ -456,11 +408,7 @@ func readGGUFArray(llm *gguf, r io.Reader) (*array, error) {
 		case ggufTypeBool:
 			e, err = readGGUF[bool](llm, r)
 		case ggufTypeString:
-			if a.values != nil {
-				e, err = readGGUFString(llm, r)
-			} else {
-				err = discardGGUFString(llm, r)
-			}
+			e, err = readGGUFString(llm, r)
 		default:
 			return nil, fmt.Errorf("invalid array type: %d", t)
 		}
@@ -468,12 +416,10 @@ func readGGUFArray(llm *gguf, r io.Reader) (*array, error) {
 			return nil, err
 		}
 
-		if a.values != nil {
-			a.values[i] = e
-		}
+		a = append(a, e)
 	}
 
-	return a, nil
+	return
 }
 
 func writeGGUFArray[S ~[]E, E any](llm *gguf, w io.Writer, t uint32, s S) error {
@@ -537,7 +483,6 @@ var ggufKVOrder = map[string][]string{
 		"tokenizer.ggml.add_bos_token",
 		"tokenizer.ggml.add_eos_token",
 		"tokenizer.chat_template",
-		"bert.pooling_type",
 	},
 }
 

llm/llm.go

@@ -1,13 +1,12 @@
 package llm
 
-// #cgo CFLAGS: -Illama.cpp -Illama.cpp/include -Illama.cpp/ggml/include
-// #cgo LDFLAGS: -lllama -lggml -lstdc++ -lpthread
-// #cgo darwin,arm64 LDFLAGS: -L${SRCDIR}/build/darwin/arm64_static -L${SRCDIR}/build/darwin/arm64_static/src -L${SRCDIR}/build/darwin/arm64_static/ggml/src -framework Accelerate -framework Metal
-// #cgo darwin,amd64 LDFLAGS: -L${SRCDIR}/build/darwin/x86_64_static -L${SRCDIR}/build/darwin/x86_64_static/src -L${SRCDIR}/build/darwin/x86_64_static/ggml/src
-// #cgo windows,amd64 LDFLAGS: -static-libstdc++ -static-libgcc -static -L${SRCDIR}/build/windows/amd64_static -L${SRCDIR}/build/windows/amd64_static/src -L${SRCDIR}/build/windows/amd64_static/ggml/src
-// #cgo windows,arm64 LDFLAGS: -static-libstdc++ -static-libgcc -static -L${SRCDIR}/build/windows/arm64_static -L${SRCDIR}/build/windows/arm64_static/src -L${SRCDIR}/build/windows/arm64_static/ggml/src
-// #cgo linux,amd64 LDFLAGS: -L${SRCDIR}/build/linux/x86_64_static -L${SRCDIR}/build/linux/x86_64_static/src -L${SRCDIR}/build/linux/x86_64_static/ggml/src
-// #cgo linux,arm64 LDFLAGS: -L${SRCDIR}/build/linux/arm64_static -L${SRCDIR}/build/linux/arm64_static/src -L${SRCDIR}/build/linux/arm64_static/ggml/src
+// #cgo CFLAGS: -Illama.cpp
+// #cgo darwin,arm64 LDFLAGS: ${SRCDIR}/build/darwin/arm64_static/libllama.a -lstdc++
+// #cgo darwin,amd64 LDFLAGS: ${SRCDIR}/build/darwin/x86_64_static/libllama.a -lstdc++
+// #cgo windows,amd64 LDFLAGS: ${SRCDIR}/build/windows/amd64_static/libllama.a -static -lstdc++
+// #cgo windows,arm64 LDFLAGS: ${SRCDIR}/build/windows/arm64_static/libllama.a -static -lstdc++
+// #cgo linux,amd64 LDFLAGS: ${SRCDIR}/build/linux/x86_64_static/libllama.a -lstdc++
+// #cgo linux,arm64 LDFLAGS: ${SRCDIR}/build/linux/arm64_static/libllama.a -lstdc++
 // #include <stdlib.h>
 // #include "llama.h"
 import "C"
@@ -33,7 +32,7 @@ func Quantize(infile, outfile string, ftype fileType) error {
 	params.ftype = ftype.Value()
 
 	if rc := C.llama_model_quantize(cinfile, coutfile, &params); rc != 0 {
-		return fmt.Errorf("failed to quantize model. This model architecture may not be supported, or you may need to upgrade Ollama to the latest version")
+		return fmt.Errorf("llama_model_quantize: %d", rc)
 	}
 
 	return nil

llm/llm_darwin_amd64.go

@@ -2,10 +2,7 @@ package llm
 
 import (
 	"embed"
-	"syscall"
 )
 
 //go:embed build/darwin/x86_64/*/bin/*
 var libEmbed embed.FS
-
-var LlamaServerSysProcAttr = &syscall.SysProcAttr{}

llm/llm_darwin_arm64.go

@@ -2,10 +2,7 @@ package llm
 
 import (
 	"embed"
-	"syscall"
 )
 
 //go:embed build/darwin/arm64/*/bin/*
 var libEmbed embed.FS
-
-var LlamaServerSysProcAttr = &syscall.SysProcAttr{}

llm/llm_linux.go

@@ -1,11 +1,6 @@
 package llm
 
-import (
-	"embed"
-	"syscall"
-)
+import "embed"
 
 //go:embed build/linux/*/*/bin/*
 var libEmbed embed.FS
-
-var LlamaServerSysProcAttr = &syscall.SysProcAttr{}

llm/llm_windows.go

@@ -1,20 +1,6 @@
 package llm
 
-import (
-	"embed"
-	"syscall"
-)
+import "embed"
 
 // unused on windows
 var libEmbed embed.FS
-
-const CREATE_DEFAULT_ERROR_MODE = 0x04000000
-
-var LlamaServerSysProcAttr = &syscall.SysProcAttr{
-	// Wire up the default error handling logic If for some reason a DLL is
-	// missing in the path this will pop up a GUI Dialog explaining the fault so
-	// the user can either fix their PATH, or report a bug. Without this
-	// setting, the process exits immediately with a generic exit status but no
-	// way to (easily) figure out what the actual missing DLL was.
-	CreationFlags: CREATE_DEFAULT_ERROR_MODE,
-}

llm/memory.go

@@ -3,10 +3,9 @@ package llm
 import (
 	"fmt"
 	"log/slog"
-	"strconv"
-	"strings"
 
 	"github.com/ollama/ollama/api"
+	"github.com/ollama/ollama/envconfig"
 	"github.com/ollama/ollama/format"
 	"github.com/ollama/ollama/gpu"
 )
@@ -17,8 +16,7 @@ func PredictServerFit(allGpus gpu.GpuInfoList, ggml *GGML, adapters, projectors
 	var estimatedVRAM uint64
 	for _, gpus := range allGpus.ByLibrary() {
 		var layerCount int
-		estimate := EstimateGPULayers(gpus, ggml, projectors, opts)
-		layerCount, estimatedVRAM = estimate.Layers, estimate.VRAMSize
+		layerCount, estimatedVRAM, _ = EstimateGPULayers(gpus, ggml, projectors, opts)
 		if opts.NumGPU < 0 {
 			if layerCount > 0 && layerCount >= int(ggml.KV().BlockCount()+1) {
 				return true, estimatedVRAM
@@ -32,76 +30,24 @@ func PredictServerFit(allGpus gpu.GpuInfoList, ggml *GGML, adapters, projectors
 	return false, estimatedVRAM
 }
 
-type MemoryEstimate struct {
-	// How many layers we predict we can load
-	Layers int
-
-	// The size of the graph which occupies the main GPU
-	Graph uint64
-
-	// How much VRAM will be allocated given the number of layers we predict
-	VRAMSize uint64
-
-	// The total size of the model if loaded into VRAM.  If all layers are loaded, VRAMSize == TotalSize
-	TotalSize uint64
-
-	// For multi-GPU scenarios, this provides the tensor split parameter
-	TensorSplit string
-
-	// For multi-GPU scenarios, this is the size in bytes per GPU
-	GPUSizes []uint64
-
-	// internal fields for logging purposes
-	inferenceLibrary    string
-	layersRequested     int
-	layersModel         int
-	availableList       []string
-	kv                  uint64
-	allocationsList     []string
-	memoryWeights       uint64
-	memoryLayerOutput   uint64
-	graphFullOffload    uint64
-	graphPartialOffload uint64
-}
-
 // Given a model and one or more GPU targets, predict how many layers and bytes we can load, and the total size
 // The GPUs provided must all be the same Library
-func EstimateGPULayers(gpus []gpu.GpuInfo, ggml *GGML, projectors []string, opts api.Options) MemoryEstimate {
-	// Graph size for a partial offload, applies to all GPUs
-	var graphPartialOffload uint64
-
-	// Graph size when all layers are offloaded, applies to all GPUs
-	var graphFullOffload uint64
-
-	// Final graph offload once we know full or partial
-	var graphOffload uint64
-
-	// Projectors loaded into GPU0 only
-	var projectorSize uint64
-
-	// Conditional output size on GPU 0
-	var memoryLayerOutput uint64
-
-	// The sizes of a layer
-	var layerSize uint64
-
-	// The sum of all the layer sizes (just for logging)
-	var memoryWeights uint64
-
-	// True if all the layers are loaded
-	var fullyLoaded bool
-
-	// Overflow that didn't fit into the GPU
-	var overflow uint64
-
-	availableList := make([]string, len(gpus))
-	for i, gpu := range gpus {
-		availableList[i] = format.HumanBytes2(gpu.FreeMemory)
+func EstimateGPULayers(gpus []gpu.GpuInfo, ggml *GGML, projectors []string, opts api.Options) (int, uint64, uint64) {
+	var memoryAvailable uint64
+	for _, info := range gpus {
+		memoryAvailable += info.FreeMemory
 	}
-	slog.Debug("evaluating", "library", gpus[0].Library, "gpu_count", len(gpus), "available", availableList)
+	if envconfig.MaxVRAM > 0 {
+		memoryAvailable = envconfig.MaxVRAM
+	}
+
+	slog.Debug("evaluating", "library", gpus[0].Library, "gpu_count", len(gpus), "available", format.HumanBytes2(memoryAvailable))
+
+	// TODO - this is probably wrong, first GPU vs secondaries will have different overheads
+	memoryMinimum := gpus[0].MinimumMemory
 
 	for _, projector := range projectors {
-		projectorSize += projectorMemoryRequirements(projector)
+		memoryMinimum += projectorMemoryRequirements(projector)
 
 		// multimodal models require at least 2048 context
 		opts.NumCtx = max(opts.NumCtx, 2048)
@@ -110,246 +56,127 @@ func EstimateGPULayers(gpus []gpu.GpuInfo, ggml *GGML, projectors []string, opts
 	layers := ggml.Tensors().Layers()
 	// add one layer worth of memory as a buffer
 	if blk0, ok := layers["blk.0"]; ok {
-		layerSize = blk0.size()
-	} else {
-		slog.Warn("model missing blk.0 layer size")
+		memoryMinimum += blk0.size()
 	}
 
-	// fp16 k,v = sizeof(float16) * n_ctx * n_layer * (n_embd_head_k + n_embd_head_v) * n_head_kv
-	var kv uint64 = 2 * uint64(opts.NumCtx) * ggml.KV().BlockCount() * (ggml.KV().EmbeddingHeadCountK() + ggml.KV().EmbeddingHeadCountV()) * ggml.KV().HeadCountKV()
+	// fp16 k,v = (1 (k) + 1 (v)) * sizeof(float16) * n_ctx * n_layer * n_embd / n_head * n_head_kv
+	var kv uint64 = 2 * 2 * uint64(opts.NumCtx) * ggml.KV().BlockCount() * ggml.KV().EmbeddingLength() / ggml.KV().HeadCount() * ggml.KV().HeadCountKV()
 
-	// KV is proportional to the number of layers
-	layerSize += kv / ggml.KV().BlockCount()
-
-	graphPartialOffload, graphFullOffload = ggml.GraphSize(uint64(opts.NumCtx), uint64(min(opts.NumCtx, opts.NumBatch)))
+	graphPartialOffload, graphFullOffload := ggml.GraphSize(uint64(opts.NumCtx), uint64(min(opts.NumCtx, opts.NumBatch)))
 	if graphPartialOffload == 0 {
 		graphPartialOffload = ggml.KV().GQA() * kv / 6
 	}
+
 	if graphFullOffload == 0 {
 		graphFullOffload = graphPartialOffload
 	}
 
+	graphFullOffload *= uint64(len(gpus))
+	graphPartialOffload *= uint64(len(gpus))
+
 	// on metal there's no partial offload overhead
 	if gpus[0].Library == "metal" {
 		graphPartialOffload = graphFullOffload
-	} else if len(gpus) > 1 {
-		// multigpu should always use the partial graph size
-		graphFullOffload = graphPartialOffload
 	}
 
+	// memoryRequiredTotal represents the memory required for full GPU offloading (all layers)
+	memoryRequiredTotal := memoryMinimum + graphFullOffload
+
+	// memoryRequiredPartial represents the memory required for partial GPU offloading (n > 0, n < layers)
+	memoryRequiredPartial := memoryMinimum + graphPartialOffload
+
+	var memoryLayerOutput uint64
 	if layer, ok := layers["output_norm"]; ok {
 		memoryLayerOutput += layer.size()
 	}
+
 	if layer, ok := layers["output"]; ok {
 		memoryLayerOutput += layer.size()
 	} else if layer, ok := layers["token_embd"]; ok {
 		memoryLayerOutput += layer.size()
 	}
 
-	// Output layer handled at the end if we have space
-	gpuZeroOverhead := projectorSize
+	if gpus[0].Library == "metal" && opts.UseMMap {
+		// memory is preallocated for output tensors
+		memoryRequiredTotal += memoryLayerOutput
+		memoryRequiredPartial += memoryLayerOutput
+	}
 
-	// Reduce set of GPUs to only those that have sufficient space to fit overhead and at least one layer
 	var layerCount int
-	layerCounts := make([]int, len(gpus))
-	gpuAllocations := make([]uint64, len(gpus))
-	type gs struct {
-		i int
-		g *gpu.GpuInfo
-	}
-	gpusWithSpace := []gs{}
-	for i := range gpus {
-		var gzo uint64
-		if len(gpusWithSpace) == 0 {
-			gzo = gpuZeroOverhead
-		}
-		// Only include GPUs that can fit the graph, gpu minimum, the layer buffer and at least more layer
-		if gpus[i].FreeMemory < gzo+max(graphPartialOffload, graphFullOffload)+gpus[i].MinimumMemory+2*layerSize {
-			slog.Debug("gpu has too little memory to allocate any layers", "gpu", gpus[i])
-			continue
-		}
-		gpusWithSpace = append(gpusWithSpace, gs{i, &gpus[i]})
-		gpuAllocations[i] += gpus[i].MinimumMemory + layerSize // We hold off on graph until we know partial vs. full
-	}
-
-	var gpuZeroID int
-	if len(gpusWithSpace) > 0 {
-		gpuZeroID = gpusWithSpace[0].i
-		gpuAllocations[gpuZeroID] += gpuZeroOverhead
-	}
-
-	// For all the layers, find where they can fit on the GPU(s)
 	for i := range int(ggml.KV().BlockCount()) {
-		// Some models have inconsistent layer sizes
 		if blk, ok := layers[fmt.Sprintf("blk.%d", i)]; ok {
-			layerSize = blk.size()
-			layerSize += kv / ggml.KV().BlockCount()
-		}
-		memoryWeights += layerSize
+			memoryLayer := blk.size()
 
-		if opts.NumGPU >= 0 && layerCount >= opts.NumGPU {
-			// Stop allocating on GPU(s) once we hit the users target NumGPU
-			continue
-		}
+			// KV is proportional to the number of layers
+			memoryLayer += kv / ggml.KV().BlockCount()
 
-		// distribute the layers across the GPU(s) that have space
-		for j := len(gpusWithSpace); j > 0; j-- {
-			g := gpusWithSpace[i%j]
-			used := gpuAllocations[g.i] + max(graphPartialOffload, graphFullOffload)
-			if g.g.FreeMemory > used+layerSize {
-				gpuAllocations[g.i] += layerSize
-				layerCounts[g.i]++
+			memoryRequiredTotal += memoryLayer
+			if (opts.NumGPU >= 0 && layerCount+1 <= opts.NumGPU) || (opts.NumGPU < 0 && memoryAvailable > memoryRequiredPartial+memoryLayer) {
+				memoryRequiredPartial += memoryLayer
 				layerCount++
-				break
-			} else {
-				gpusWithSpace = append(gpusWithSpace[:i%j], gpusWithSpace[i%j+1:]...)
 			}
 		}
 	}
-	if layerCount >= int(ggml.KV().BlockCount()) {
-		fullyLoaded = true
-	} else {
-		for i := layerCount; i < int(ggml.KV().BlockCount()); i++ {
-			overflow += layerSize
-		}
+
+	if gpus[0].Library != "metal" || !opts.UseMMap {
+		// memory was not preallocated for output tensors
+		memoryRequiredTotal += memoryLayerOutput
 	}
 
-	// Determine if we need to consider output then find where it fits
-	if memoryLayerOutput > 0 && (opts.NumGPU < 0 || layerCount < opts.NumGPU) {
-		for j := len(gpusWithSpace); j > 0; j-- {
-			g := gpusWithSpace[layerCount%j]
-			used := gpuAllocations[g.i] + max(graphPartialOffload, graphFullOffload)
-			if g.g.FreeMemory > used+memoryLayerOutput {
-				gpuAllocations[g.i] += memoryLayerOutput
-				layerCounts[g.i]++
-				layerCount++
-				break
-			}
-		}
-
-		if layerCount < int(ggml.KV().BlockCount())+1 {
-			fullyLoaded = false
-			overflow += memoryLayerOutput
-		}
+	if (opts.NumGPU >= 0 && layerCount+1 <= opts.NumGPU) || (opts.NumGPU < 0 && memoryAvailable > memoryRequiredTotal) {
+		layerCount = int(ggml.KV().BlockCount()) + 1
+		memoryRequiredPartial = memoryRequiredTotal
 	}
 
-	// Add the applicable (full or partial) graph allocations
-	for i := range gpus {
-		if layerCounts[i] <= 0 {
-			continue
-		}
-		if fullyLoaded {
-			gpuAllocations[i] += graphFullOffload
-		} else {
-			gpuAllocations[i] += graphPartialOffload
-		}
-	}
-	if fullyLoaded {
-		graphOffload = graphFullOffload
-	} else {
-		graphOffload = graphPartialOffload
-	}
+	memoryWeights := memoryRequiredTotal - memoryMinimum - graphFullOffload - kv
 
-	// Summaries for the log
-	var memoryRequiredPartial, memoryRequiredTotal uint64
-	for i := range gpuAllocations {
-		memoryRequiredPartial += gpuAllocations[i]
-	}
-	memoryRequiredTotal = memoryRequiredPartial + overflow
-
-	tensorSplit := ""
-	if len(gpus) > 1 {
-		splits := make([]string, len(gpus))
-		for i, count := range layerCounts {
-			splits[i] = strconv.Itoa(count)
-		}
-		tensorSplit = strings.Join(splits, ",")
-	}
-	allocationsList := []string{}
-	for _, a := range gpuAllocations {
-		allocationsList = append(allocationsList, format.HumanBytes2(a))
-	}
-
-	estimate := MemoryEstimate{
-		TotalSize: memoryRequiredTotal,
-		Layers:    0,
-		Graph:     0,
-		VRAMSize:  0,
-		GPUSizes:  []uint64{},
-
-		inferenceLibrary:    gpus[0].Library,
-		layersRequested:     opts.NumGPU,
-		layersModel:         int(ggml.KV().BlockCount()) + 1,
-		availableList:       availableList,
-		kv:                  kv,
-		allocationsList:     allocationsList,
-		memoryWeights:       memoryWeights,
-		memoryLayerOutput:   memoryLayerOutput,
-		graphFullOffload:    graphFullOffload,
-		graphPartialOffload: graphPartialOffload,
-	}
-
-	if gpus[0].Library == "cpu" {
-		return estimate
-	}
-	if layerCount == 0 {
-		slog.Debug("insufficient VRAM to load any model layers")
-		return estimate
-	}
-	estimate.Layers = layerCount
-	estimate.Graph = graphOffload
-	estimate.VRAMSize = memoryRequiredPartial
-	estimate.TotalSize = memoryRequiredTotal
-	estimate.TensorSplit = tensorSplit
-	estimate.GPUSizes = gpuAllocations
-	return estimate
-}
-
-func (m MemoryEstimate) log() {
 	slog.Info(
-		"offload to "+m.inferenceLibrary,
+		"offload to gpu",
 		slog.Group(
 			"layers",
 			// requested number of layers to offload
-			"requested", m.layersRequested,
-			// The number of layers the model has (including output)
-			"model", m.layersModel,
+			"requested", opts.NumGPU,
 			// estimated number of layers that can be offloaded
-			"offload", m.Layers,
-			// multi-gpu split for tensors
-			"split", m.TensorSplit,
+			"real", layerCount,
 		),
 		slog.Group(
 			"memory",
-			// memory available by GPU for offloading
-			"available", m.availableList,
+			// memory available for offloading
+			"available", format.HumanBytes2(memoryAvailable),
 			slog.Group(
 				"required",
 				// memory required for full offloading
-				"full", format.HumanBytes2(m.TotalSize),
+				"full", format.HumanBytes2(memoryRequiredTotal),
 				// memory required to offload layers.estimate layers
-				"partial", format.HumanBytes2(m.VRAMSize),
+				"partial", format.HumanBytes2(memoryRequiredPartial),
 				// memory of KV cache
-				"kv", format.HumanBytes2(m.kv),
-				// Allocations across the GPUs
-				"allocations", m.allocationsList,
+				"kv", format.HumanBytes2(kv),
 			),
 			slog.Group(
 				"weights",
 				// memory of the weights
-				"total", format.HumanBytes2(m.memoryWeights),
+				"total", format.HumanBytes2(memoryWeights),
 				// memory of repeating layers
-				"repeating", format.HumanBytes2(m.memoryWeights-m.memoryLayerOutput),
+				"repeating", format.HumanBytes2(memoryWeights-memoryLayerOutput),
 				// memory of non-repeating layers
-				"nonrepeating", format.HumanBytes2(m.memoryLayerOutput),
+				"nonrepeating", format.HumanBytes2(memoryLayerOutput),
 			),
 			slog.Group(
 				"graph",
 				// memory of graph when fully offloaded
-				"full", format.HumanBytes2(m.graphFullOffload),
+				"full", format.HumanBytes2(graphFullOffload),
 				// memory of graph when not fully offloaded
-				"partial", format.HumanBytes2(m.graphPartialOffload),
+				"partial", format.HumanBytes2(graphPartialOffload),
 			),
 		),
 	)
+	if gpus[0].Library == "cpu" {
+		return 0, 0, memoryRequiredTotal
+	}
+	if memoryRequiredPartial > memoryAvailable {
+		slog.Debug("insufficient VRAM to load any model layers")
+		return 0, 0, memoryRequiredTotal
+	}
+
+	return layerCount, memoryRequiredPartial, memoryRequiredTotal
 }

llm/memory_test.go

@@ -1,130 +0,0 @@
-package llm
-
-import (
-	"bytes"
-	"encoding/binary"
-	"fmt"
-	"os"
-	"testing"
-
-	"github.com/ollama/ollama/api"
-	"github.com/ollama/ollama/envconfig"
-	"github.com/ollama/ollama/gpu"
-	"github.com/stretchr/testify/assert"
-	"github.com/stretchr/testify/require"
-)
-
-func TestEstimateGPULayers(t *testing.T) {
-	envconfig.Debug = true
-	modelName := "dummy"
-	f, err := os.CreateTemp(t.TempDir(), modelName)
-	require.NoError(t, err)
-	defer f.Close()
-	gguf := NewGGUFV3(binary.LittleEndian)
-	inputLayerCount := 5
-
-	tensors := []Tensor{
-		{Name: "blk.0.attn.weight", Kind: uint32(0), Offset: uint64(0), Shape: []uint64{1, 1, 1, 1}, WriterTo: bytes.NewReader(make([]byte, 32))},
-		{Name: "blk.1.attn.weight", Kind: uint32(0), Offset: uint64(0), Shape: []uint64{1, 1, 1, 1}, WriterTo: bytes.NewReader(make([]byte, 32))},
-		{Name: "blk.2.attn.weight", Kind: uint32(0), Offset: uint64(0), Shape: []uint64{1, 1, 1, 1}, WriterTo: bytes.NewReader(make([]byte, 32))},
-		{Name: "blk.3.attn.weight", Kind: uint32(0), Offset: uint64(0), Shape: []uint64{1, 1, 1, 1}, WriterTo: bytes.NewReader(make([]byte, 32))},
-		{Name: "blk.4.attn.weight", Kind: uint32(0), Offset: uint64(0), Shape: []uint64{1, 1, 1, 1}, WriterTo: bytes.NewReader(make([]byte, 32))},
-		{Name: "output.weight", Kind: uint32(0), Offset: uint64(0), Shape: []uint64{1, 1, 1, 1}, WriterTo: bytes.NewReader(make([]byte, 32))},
-	}
-	assert.Len(t, tensors, inputLayerCount+1)
-	err = gguf.Encode(f, KV{
-		"general.architecture":          "llama",
-		"general.name":                  "name",
-		"llama.context_length":          uint32(32),
-		"llama.embedding_length":        uint32(4096),
-		"llama.block_count":             uint32(inputLayerCount),
-		"llama.attention.head_count":    uint32(32),
-		"llama.attention.head_count_kv": uint32(32),
-		"tokenizer.ggml.tokens":         []string{" "},
-		"tokenizer.ggml.scores":         []float32{0},
-		"tokenizer.ggml.token_type":     []int32{0},
-	}, tensors)
-	require.NoError(t, err)
-
-	ggml, err := LoadModel(f.Name(), 0)
-	if err != nil {
-		t.Fatal(err)
-	}
-
-	// Simple CPU scenario
-	gpus := []gpu.GpuInfo{
-		{
-			Library: "cpu",
-		},
-	}
-	projectors := []string{}
-	opts := api.DefaultOptions()
-	t.Run("cpu", func(t *testing.T) {
-		estimate := EstimateGPULayers(gpus, ggml, projectors, opts)
-		assert.Equal(t, 0, estimate.Layers)
-		assert.Equal(t, uint64(0), estimate.Graph)
-	})
-
-	// derived from the dummy ggml file above
-	graphPartialOffload := uint64(202377216)
-	graphFullOffload := uint64(171968512)
-	layerSize := uint64(33554436)
-	projectorSize := uint64(0)
-	memoryLayerOutput := uint64(4)
-
-	// Dual CUDA scenario with assymetry
-	gpuMinimumMemory := uint64(2048)
-	gpus = []gpu.GpuInfo{
-		{
-			Library:       "cuda",
-			MinimumMemory: gpuMinimumMemory,
-		},
-		{
-			Library:       "cuda",
-			MinimumMemory: gpuMinimumMemory,
-		},
-	}
-	// Nested array: GPU0 layer space, GPU1 layer space, expected gpu0, expected gpu1
-	for i, s := range []struct {
-		layer0, layer1   uint64
-		expect0, expect1 uint64
-	}{
-		{1, 1, 1, 1},
-		{2, 1, 2, 1},
-		{2, 2, 2, 2},
-		{1, 2, 1, 2},
-		{3, 3, 3, 3},
-		{4, 4, 3, 3},
-		{6, 6, 3, 3},
-		{0, 3, 0, 3},
-	} {
-		t.Run(fmt.Sprintf("%v", s), func(t *testing.T) {
-			gpus[0].FreeMemory = 0
-			gpus[1].FreeMemory = 0
-			gpus[0].FreeMemory += projectorSize
-			if s.layer0 > 0 {
-				gpus[0].FreeMemory += memoryLayerOutput
-			} else {
-				gpus[1].FreeMemory += memoryLayerOutput
-			}
-			gpus[0].FreeMemory += gpuMinimumMemory + layerSize + s.layer0*layerSize + 1
-			gpus[1].FreeMemory += gpuMinimumMemory + layerSize + s.layer1*layerSize + 1
-			gpus[0].FreeMemory += max(graphFullOffload, graphPartialOffload)
-			gpus[1].FreeMemory += max(graphFullOffload, graphPartialOffload)
-			estimate := EstimateGPULayers(gpus, ggml, projectors, opts)
-			assert.Equal(t, int(s.expect0+s.expect1), estimate.Layers, "scenario %d: %v", i, s)
-			assert.Equal(t, fmt.Sprintf("%d,%d", s.expect0, s.expect1), estimate.TensorSplit, "scenario %d: %v", i, s)
-			var layerSums uint64
-			for _, b := range estimate.GPUSizes {
-				layerSums += b
-			}
-			if estimate.Layers < inputLayerCount+1 {
-				assert.Less(t, estimate.VRAMSize, estimate.TotalSize, "scenario %d: %v %+v", i, s, estimate)
-				assert.Equal(t, estimate.VRAMSize, layerSums, "scenario %d: %v %+v", i, s, estimate)
-			} else {
-				assert.Equal(t, estimate.VRAMSize, estimate.TotalSize, "scenario %d: %v %+v", i, s, estimate)
-				assert.Equal(t, estimate.TotalSize, layerSums, "scenario %d: %v %+v", i, s, estimate)
-			}
-		})
-	}
-}

llm/patches/01-load-progress.diff

@@ -1,8 +1,8 @@
 diff --git a/common/common.cpp b/common/common.cpp
-index 2c05a4d4..927f0e3d 100644
+index ba1ecf0e..cead57cc 100644
 --- a/common/common.cpp
 +++ b/common/common.cpp
-@@ -2093,6 +2093,8 @@ struct llama_model_params llama_model_params_from_gpt_params(const gpt_params &
+@@ -1836,6 +1836,8 @@ struct llama_model_params llama_model_params_from_gpt_params(const gpt_params &
      mparams.use_mmap        = params.use_mmap;
      mparams.use_mlock       = params.use_mlock;
      mparams.check_tensors   = params.check_tensors;
@@ -12,20 +12,20 @@ index 2c05a4d4..927f0e3d 100644
          mparams.kv_overrides = NULL;
      } else {
 diff --git a/common/common.h b/common/common.h
-index 65c0ef81..ebca2c77 100644
+index d80344f2..71e84834 100644
 --- a/common/common.h
 +++ b/common/common.h
-@@ -184,6 +184,13 @@ struct gpt_params {
+@@ -174,6 +174,13 @@ struct gpt_params {
+     // multimodal models (see examples/llava)
      std::string mmproj = "";        // path to multimodal projector
      std::vector<std::string> image; // path to image file(s)
- 
++
 +    // Called with a progress value between 0.0 and 1.0. Pass NULL to disable.
 +    // If the provided progress_callback returns true, model loading continues.
 +    // If it returns false, model loading is immediately aborted.
 +    llama_progress_callback progress_callback = NULL;
 +    // context pointer passed to the progress callback
 +    void * progress_callback_user_data;
-+
-     // embedding
-     bool embedding         = false; // get only sentence embedding
-     int32_t embd_normalize = 2;     // normalisation for embendings (-1=none, 0=max absolute int16, 1=taxicab, 2=euclidean, >2=p-norm)
+ };
+ 
+ void gpt_params_handle_model_default(gpt_params & params);

llm/patches/03-load_exception.diff

@@ -1,8 +1,17 @@
-diff --git a/src/llama.cpp b/src/llama.cpp
-index 73f52435..58a00fb1 100644
---- a/src/llama.cpp
-+++ b/src/llama.cpp
-@@ -7241,7 +7241,7 @@ static int llama_model_load(const std::string & fname, llama_model & model, llam
+From 544a2d2e646d39e878d87dfbb3398a356bc560ab Mon Sep 17 00:00:00 2001
+From: Michael Yang <mxyng@pm.me>
+Date: Thu, 23 May 2024 11:18:45 -0700
+Subject: [PATCH] throw exception on load errors
+
+---
+ llama.cpp | 25 ++++++++++++++++---------
+ 1 file changed, 16 insertions(+), 9 deletions(-)
+
+diff --git a/llama.cpp b/llama.cpp
+index 15c66077..8ba90b6a 100644
+--- a/llama.cpp
++++ b/llama.cpp
+@@ -6346,7 +6346,7 @@ static int llama_model_load(const std::string & fname, llama_model & model, llam
          }
      } catch (const std::exception & err) {
          LLAMA_LOG_ERROR("%s: error loading model: %s\n", __func__, err.what());
@@ -11,7 +20,7 @@ index 73f52435..58a00fb1 100644
      }
  
      return 0;
-@@ -17564,16 +17564,23 @@ struct llama_model * llama_load_model_from_file(
+@@ -15600,16 +15600,23 @@ struct llama_model * llama_load_model_from_file(
          }
          model->rpc_servers.push_back(servers);
      }
@@ -43,3 +52,6 @@ index 73f52435..58a00fb1 100644
      }
  
      return model;
+-- 
+2.45.1
+

llm/patches/04-metal.diff

@@ -1,7 +1,7 @@
-diff --git a/ggml/src/ggml-metal.m b/ggml/src/ggml-metal.m
+diff --git a/ggml-metal.m b/ggml-metal.m
 index 0207b787..b5e9884b 100644
---- a/ggml/src/ggml-metal.m
-+++ b/ggml/src/ggml-metal.m
+--- a/ggml-metal.m
++++ b/ggml-metal.m
 @@ -1396,27 +1396,23 @@ static enum ggml_status ggml_metal_graph_compute(
                          // to the matrix-vector kernel
                          int ne11_mm_min = 1;

llm/patches/05-default-pretokenizer.diff

@@ -1,11 +1,11 @@
-diff --git a/src/llama.cpp b/src/llama.cpp
-index a207451f..2ddf431d 100644
---- a/src/llama.cpp
-+++ b/src/llama.cpp
-@@ -5347,16 +5347,7 @@ static void llm_load_vocab(
+diff --git a/llama.cpp b/llama.cpp
+index 40d2ec2c..74f3ee9c 100644
+--- a/llama.cpp
++++ b/llama.cpp
+@@ -4642,16 +4642,7 @@ static void llm_load_vocab(
+ 
+         // for now, only BPE models have pre-tokenizers
          if (vocab.type == LLAMA_VOCAB_TYPE_BPE) {
-             vocab.tokenizer_add_space_prefix = false;
-             vocab.tokenizer_clean_spaces = true;
 -            if (tokenizer_pre.empty()) {
 -                LLAMA_LOG_WARN("%s: missing pre-tokenizer type, using: 'default'\n", __func__);
 -                LLAMA_LOG_WARN("%s:                                             \n", __func__);
@@ -15,18 +15,18 @@ index a207451f..2ddf431d 100644
 -                LLAMA_LOG_WARN("%s: ************************************        \n", __func__);
 -                LLAMA_LOG_WARN("%s:                                             \n", __func__);
 -                vocab.type_pre = LLAMA_VOCAB_PRE_TYPE_DEFAULT;
--            } else if (tokenizer_pre == "default") {
-+            if (tokenizer_pre == "default") {
+-            } else if (
++            if (
+                     tokenizer_pre == "default") {
                  vocab.type_pre = LLAMA_VOCAB_PRE_TYPE_DEFAULT;
              } else if (
-                     tokenizer_pre == "llama3"   ||
-@@ -5443,7 +5434,8 @@ static void llm_load_vocab(
-                 tokenizer_pre == "codeshell") {
-                 vocab.type_pre = LLAMA_VOCAB_PRE_TYPE_CODESHELL;
+@@ -4703,7 +4694,8 @@ static void llm_load_vocab(
+                 tokenizer_pre == "smaug-bpe") {
+                 vocab.type_pre = LLAMA_VOCAB_PRE_TYPE_SMAUG;
              } else {
 -                throw std::runtime_error(format("unknown pre-tokenizer type: '%s'", tokenizer_pre.c_str()));
 +                LLAMA_LOG_WARN("%s: missing or unrecognized pre-tokenizer type, using: 'default'\n", __func__);
 +                vocab.type_pre = LLAMA_VOCAB_PRE_TYPE_DEFAULT;
              }
-         } else if (vocab.type == LLAMA_VOCAB_TYPE_SPM) {
+         } else {
              vocab.type_pre = LLAMA_VOCAB_PRE_TYPE_DEFAULT;