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2 Commits

Author SHA1 Message Date
Parth Sareen
6b2abfb433 server: add tests and fix isHuggingFaceURL edge case
- Add comprehensive tests for isHuggingFaceURL and getNumDownloadParts
- Fix bug where domains ending in huggingface.co (like nothuggingface.co)
  would incorrectly match as HuggingFace URLs
- Improve code comments with more detailed documentation
2026-01-18 16:45:17 -08:00
Parth Sareen
805ed4644c server: reduce download concurrency for HuggingFace URLs
Reduces concurrent download parts from 16 to 4 for HuggingFace URLs
to avoid triggering rate limits (HTTP 429 errors).

Adds OLLAMA_HF_CONCURRENCY environment variable for users who want
to customize the concurrency level.

Fixes #13297
2026-01-18 16:38:49 -08:00
32 changed files with 460 additions and 610 deletions

View File

@@ -190,7 +190,7 @@ if(MLX_ENGINE)
install(TARGETS mlx mlxc
RUNTIME_DEPENDENCIES
DIRECTORIES ${CUDAToolkit_BIN_DIR} ${CUDAToolkit_BIN_DIR}/x64 ${CUDAToolkit_LIBRARY_DIR}
PRE_INCLUDE_REGEXES cublas cublasLt cudart nvrtc nvrtc-builtins cudnn nccl openblas gfortran
PRE_INCLUDE_REGEXES cublas cublasLt cudart nvrtc cudnn nccl
PRE_EXCLUDE_REGEXES ".*"
RUNTIME DESTINATION ${OLLAMA_INSTALL_DIR} COMPONENT MLX
LIBRARY DESTINATION ${OLLAMA_INSTALL_DIR} COMPONENT MLX

View File

@@ -48,7 +48,7 @@ ollama run gemma3
## Model library
Ollama supports a list of models available on [ollama.com/library](https://ollama.com/library "ollama model library")
Ollama supports a list of models available on [ollama.com/library](https://ollama.com/library 'ollama model library')
Here are some example models that can be downloaded:
@@ -79,7 +79,7 @@ Here are some example models that can be downloaded:
| Code Llama | 7B | 3.8GB | `ollama run codellama` |
| Llama 2 Uncensored | 7B | 3.8GB | `ollama run llama2-uncensored` |
| LLaVA | 7B | 4.5GB | `ollama run llava` |
| Granite-3.3 | 8B | 4.9GB | `ollama run granite3.3` |
| Granite-3.3 | 8B | 4.9GB | `ollama run granite3.3` |
> [!NOTE]
> You should have at least 8 GB of RAM available to run the 7B models, 16 GB to run the 13B models, and 32 GB to run the 33B models.
@@ -260,38 +260,6 @@ Finally, in a separate shell, run a model:
./ollama run llama3.2
```
## Building with MLX (experimental)
First build the MLX libraries:
```shell
cmake --preset MLX
cmake --build --preset MLX --parallel
cmake --install build --component MLX
```
Next, build the `ollama-mlx` binary, which is a separate build of the Ollama runtime with MLX support enabled (needs to be in the same directory as `ollama`):
```shell
go build -tags mlx -o ollama-mlx .
```
Finally, start the server:
```
./ollama serve
```
### Building MLX with CUDA
When building with CUDA, use the preset "MLX CUDA 13" or "MLX CUDA 12" to enable CUDA with default architectures:
```shell
cmake --preset 'MLX CUDA 13'
cmake --build --preset 'MLX CUDA 13' --parallel
cmake --install build --component MLX
```
## REST API
Ollama has a REST API for running and managing models.
@@ -322,7 +290,6 @@ See the [API documentation](./docs/api.md) for all endpoints.
### Web & Desktop
- [Onyx](https://github.com/onyx-dot-app/onyx)
- [Open WebUI](https://github.com/open-webui/open-webui)
- [SwiftChat (macOS with ReactNative)](https://github.com/aws-samples/swift-chat)
- [Enchanted (macOS native)](https://github.com/AugustDev/enchanted)
@@ -454,7 +421,7 @@ See the [API documentation](./docs/api.md) for all endpoints.
- [AppFlowy](https://github.com/AppFlowy-IO/AppFlowy) (AI collaborative workspace with Ollama, cross-platform and self-hostable)
- [Lumina](https://github.com/cushydigit/lumina.git) (A lightweight, minimal React.js frontend for interacting with Ollama servers)
- [Tiny Notepad](https://pypi.org/project/tiny-notepad) (A lightweight, notepad-like interface to chat with ollama available on PyPI)
- [macLlama (macOS native)](https://github.com/hellotunamayo/macLlama) (A native macOS GUI application for interacting with Ollama models, featuring a chat interface.)
- [macLlama (macOS native)](https://github.com/hellotunamayo/macLlama) (A native macOS GUI application for interacting with Ollama models, featuring a chat interface.)
- [GPTranslate](https://github.com/philberndt/GPTranslate) (A fast and lightweight, AI powered desktop translation application written with Rust and Tauri. Features real-time translation with OpenAI/Azure/Ollama.)
- [ollama launcher](https://github.com/NGC13009/ollama-launcher) (A launcher for Ollama, aiming to provide users with convenient functions such as ollama server launching, management, or configuration.)
- [ai-hub](https://github.com/Aj-Seven/ai-hub) (AI Hub supports multiple models via API keys and Chat support via Ollama API.)
@@ -526,7 +493,7 @@ See the [API documentation](./docs/api.md) for all endpoints.
### Database
- [pgai](https://github.com/timescale/pgai) - PostgreSQL as a vector database (Create and search embeddings from Ollama models using pgvector)
- [Get started guide](https://github.com/timescale/pgai/blob/main/docs/vectorizer-quick-start.md)
- [Get started guide](https://github.com/timescale/pgai/blob/main/docs/vectorizer-quick-start.md)
- [MindsDB](https://github.com/mindsdb/mindsdb/blob/staging/mindsdb/integrations/handlers/ollama_handler/README.md) (Connects Ollama models with nearly 200 data platforms and apps)
- [chromem-go](https://github.com/philippgille/chromem-go/blob/v0.5.0/embed_ollama.go) with [example](https://github.com/philippgille/chromem-go/tree/v0.5.0/examples/rag-wikipedia-ollama)
- [Kangaroo](https://github.com/dbkangaroo/kangaroo) (AI-powered SQL client and admin tool for popular databases)
@@ -669,7 +636,6 @@ See the [API documentation](./docs/api.md) for all endpoints.
- [llama.cpp](https://github.com/ggml-org/llama.cpp) project founded by Georgi Gerganov.
### Observability
- [Opik](https://www.comet.com/docs/opik/cookbook/ollama) is an open-source platform to debug, evaluate, and monitor your LLM applications, RAG systems, and agentic workflows with comprehensive tracing, automated evaluations, and production-ready dashboards. Opik supports native integration to Ollama.
- [Lunary](https://lunary.ai/docs/integrations/ollama) is the leading open-source LLM observability platform. It provides a variety of enterprise-grade features such as real-time analytics, prompt templates management, PII masking, and comprehensive agent tracing.
- [OpenLIT](https://github.com/openlit/openlit) is an OpenTelemetry-native tool for monitoring Ollama Applications & GPUs using traces and metrics.
@@ -678,5 +644,4 @@ See the [API documentation](./docs/api.md) for all endpoints.
- [MLflow Tracing](https://mlflow.org/docs/latest/llms/tracing/index.html#automatic-tracing) is an open source LLM observability tool with a convenient API to log and visualize traces, making it easy to debug and evaluate GenAI applications.
### Security
- [Ollama Fortress](https://github.com/ParisNeo/ollama_proxy_server)

View File

@@ -14,7 +14,6 @@ extern NSString *SystemWidePath;
@interface AppDelegate () <NSWindowDelegate, WKNavigationDelegate, WKUIDelegate>
@property(strong, nonatomic) NSStatusItem *statusItem;
@property(assign, nonatomic) BOOL updateAvailable;
@property(assign, nonatomic) BOOL systemShutdownInProgress;
@end
@implementation AppDelegate
@@ -41,13 +40,6 @@ bool firstTimeRun,startHidden; // Set in run before initialization
}
- (void)applicationDidFinishLaunching:(NSNotification *)aNotification {
// Register for system shutdown/restart notification so we can allow termination
[[[NSWorkspace sharedWorkspace] notificationCenter]
addObserver:self
selector:@selector(systemWillPowerOff:)
name:NSWorkspaceWillPowerOffNotification
object:nil];
// if we're in development mode, set the app icon
NSString *bundlePath = [[NSBundle mainBundle] bundlePath];
if (![bundlePath hasSuffix:@".app"]) {
@@ -286,18 +278,7 @@ bool firstTimeRun,startHidden; // Set in run before initialization
[NSApp activateIgnoringOtherApps:YES];
}
- (void)systemWillPowerOff:(NSNotification *)notification {
// Set flag so applicationShouldTerminate: knows to allow termination.
// The system will call applicationShouldTerminate: after posting this notification.
self.systemShutdownInProgress = YES;
}
- (NSApplicationTerminateReply)applicationShouldTerminate:(NSApplication *)sender {
// Allow termination if the system is shutting down or restarting
if (self.systemShutdownInProgress) {
return NSTerminateNow;
}
// Otherwise just hide the app (for Cmd+Q, close button, etc.)
[NSApp hide:nil];
[NSApp setActivationPolicy:NSApplicationActivationPolicyAccessory];
return NSTerminateCancel;

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@@ -116,7 +116,7 @@ func generateInteractive(cmd *cobra.Command, opts runOptions) error {
Prompt: ">>> ",
AltPrompt: "... ",
Placeholder: "Send a message (/? for help)",
AltPlaceholder: "Press Enter to send",
AltPlaceholder: `Use """ to end multi-line input`,
})
if err != nil {
return err

View File

@@ -21,7 +21,6 @@ ollama pull glm-4.7:cloud
To use Ollama with tools that expect the Anthropic API (like Claude Code), set these environment variables:
```shell
export ANTHROPIC_AUTH_TOKEN=ollama # required but ignored
export ANTHROPIC_BASE_URL=http://localhost:11434
export ANTHROPIC_API_KEY=ollama # required but ignored
```
@@ -248,13 +247,12 @@ curl -X POST http://localhost:11434/v1/messages \
[Claude Code](https://code.claude.com/docs/en/overview) can be configured to use Ollama as its backend:
```shell
ANTHROPIC_AUTH_TOKEN=ollama ANTHROPIC_BASE_URL=http://localhost:11434 ANTHROPIC_API_KEY=ollama claude --model qwen3-coder
ANTHROPIC_BASE_URL=http://localhost:11434 ANTHROPIC_API_KEY=ollama claude --model qwen3-coder
```
Or set the environment variables in your shell profile:
```shell
export ANTHROPIC_AUTH_TOKEN=ollama
export ANTHROPIC_BASE_URL=http://localhost:11434
export ANTHROPIC_API_KEY=ollama
```

View File

@@ -110,7 +110,7 @@ More Ollama [Python example](https://github.com/ollama/ollama-python/blob/main/e
import { Ollama } from "ollama";
const client = new Ollama();
const results = await client.webSearch("what is ollama?");
const results = await client.webSearch({ query: "what is ollama?" });
console.log(JSON.stringify(results, null, 2));
```
@@ -213,7 +213,7 @@ models](https://ollama.com/models)\n\nAvailable for macOS, Windows, and Linux',
import { Ollama } from "ollama";
const client = new Ollama();
const fetchResult = await client.webFetch("https://ollama.com");
const fetchResult = await client.webFetch({ url: "https://ollama.com" });
console.log(JSON.stringify(fetchResult, null, 2));
```

View File

@@ -111,9 +111,7 @@
"/integrations/zed",
"/integrations/roo-code",
"/integrations/n8n",
"/integrations/xcode",
"/integrations/onyx",
"/integrations/marimo"
"/integrations/xcode"
]
},
{

View File

@@ -22,7 +22,7 @@ Please refer to the [GPU docs](./gpu).
## How can I specify the context window size?
By default, Ollama uses a context window size of 4096 tokens.
By default, Ollama uses a context window size of 2048 tokens.
This can be overridden with the `OLLAMA_CONTEXT_LENGTH` environment variable. For example, to set the default context window to 8K, use:

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@@ -25,7 +25,6 @@ Claude Code connects to Ollama using the Anthropic-compatible API.
1. Set the environment variables:
```shell
export ANTHROPIC_AUTH_TOKEN=ollama
export ANTHROPIC_BASE_URL=http://localhost:11434
export ANTHROPIC_API_KEY=ollama
```
@@ -39,7 +38,7 @@ claude --model qwen3-coder
Or run with environment variables inline:
```shell
ANTHROPIC_AUTH_TOKEN=ollama ANTHROPIC_BASE_URL=http://localhost:11434 ANTHROPIC_API_KEY=ollama claude --model qwen3-coder
ANTHROPIC_BASE_URL=http://localhost:11434 ANTHROPIC_API_KEY=ollama claude --model qwen3-coder
```
## Connecting to ollama.com

View File

@@ -1,73 +0,0 @@
---
title: marimo
---
## Install
Install [marimo](https://marimo.io). You can use `pip` or `uv` for this. You
can also use `uv` to create a sandboxed environment for marimo by running:
```
uvx marimo edit --sandbox notebook.py
```
## Usage with Ollama
1. In marimo, go to the user settings and go to the AI tab. From here
you can find and configure Ollama as an AI provider. For local use you
would typically point the base url to `http://localhost:11434/v1`.
<div style={{ display: 'flex', justifyContent: 'center' }}>
<img
src="/images/marimo-settings.png"
alt="Ollama settings in marimo"
width="50%"
/>
</div>
2. Once the AI provider is set up, you can turn on/off specific AI models you'd like to access.
<div style={{ display: 'flex', justifyContent: 'center' }}>
<img
src="/images/marimo-models.png"
alt="Selecting an Ollama model"
width="50%"
/>
</div>
3. You can also add a model to the list of available models by scrolling to the bottom and using the UI there.
<div style={{ display: 'flex', justifyContent: 'center' }}>
<img
src="/images/marimo-add-model.png"
alt="Adding a new Ollama model"
width="50%"
/>
</div>
4. Once configured, you can now use Ollama for AI chats in marimo.
<div style={{ display: 'flex', justifyContent: 'center' }}>
<img
src="/images/marimo-chat.png"
alt="Configure code completion"
width="50%"
/>
</div>
4. Alternatively, you can now use Ollama for **inline code completion** in marimo. This can be configured in the "AI Features" tab.
<div style={{ display: 'flex', justifyContent: 'center' }}>
<img
src="/images/marimo-code-completion.png"
alt="Configure code completion"
width="50%"
/>
</div>
## Connecting to ollama.com
1. Sign in to ollama cloud via `ollama signin`
2. In the ollama model settings add a model that ollama hosts, like `gpt-oss:120b`.
3. You can now refer to this model in marimo!

View File

@@ -1,63 +0,0 @@
---
title: Onyx
---
## Overview
[Onyx](http://onyx.app/) is a self-hostable Chat UI that integrates with all Ollama models. Features include:
- Creating custom Agents
- Web search
- Deep Research
- RAG over uploaded documents and connected apps
- Connectors to applications like Google Drive, Email, Slack, etc.
- MCP and OpenAPI Actions support
- Image generation
- User/Groups management, RBAC, SSO, etc.
Onyx can be deployed for single users or large organizations.
## Install Onyx
Deploy Onyx with the [quickstart guide](https://docs.onyx.app/deployment/getting_started/quickstart).
<Info>
Resourcing/scaling docs [here](https://docs.onyx.app/deployment/getting_started/resourcing).
</Info>
## Usage with Ollama
1. Login to your Onyx deployment (create an account first).
<div style={{ display: 'flex', justifyContent: 'center' }}>
<img
src="/images/onyx-login.png"
alt="Onyx Login Page"
width="75%"
/>
</div>
2. In the set-up process select `Ollama` as the LLM provider.
<div style={{ display: 'flex', justifyContent: 'center' }}>
<img
src="/images/onyx-ollama-llm.png"
alt="Onyx Set Up Form"
width="75%"
/>
</div>
3. Provide your **Ollama API URL** and select your models.
<Note>If you're running Onyx in Docker, to access your computer's local network use `http://host.docker.internal` instead of `http://127.0.0.1`.</Note>
<div style={{ display: 'flex', justifyContent: 'center' }}>
<img
src="/images/onyx-ollama-form.png"
alt="Selecting Ollama Models"
width="75%"
/>
</div>
You can also easily connect up Onyx Cloud with the `Ollama Cloud` tab of the setup.
## Send your first query
<div style={{ display: 'flex', justifyContent: 'center' }}>
<img
src="/images/onyx-query.png"
alt="Onyx Query Example"
width="75%"
/>
</div>

View File

@@ -1,5 +1,5 @@
---
title: Linux
title: "Linux"
---
## Install
@@ -13,15 +13,14 @@ curl -fsSL https://ollama.com/install.sh | sh
## Manual install
<Note>
If you are upgrading from a prior version, you should remove the old libraries
with `sudo rm -rf /usr/lib/ollama` first.
If you are upgrading from a prior version, you should remove the old libraries with `sudo rm -rf /usr/lib/ollama` first.
</Note>
Download and extract the package:
```shell
curl -fsSL https://ollama.com/download/ollama-linux-amd64.tar.zst \
| sudo tar x -C /usr
curl -fsSL https://ollama.com/download/ollama-linux-amd64.tgz \
| sudo tar zx -C /usr
```
Start Ollama:
@@ -41,8 +40,8 @@ ollama -v
If you have an AMD GPU, also download and extract the additional ROCm package:
```shell
curl -fsSL https://ollama.com/download/ollama-linux-amd64-rocm.tar.zst \
| sudo tar x -C /usr
curl -fsSL https://ollama.com/download/ollama-linux-amd64-rocm.tgz \
| sudo tar zx -C /usr
```
### ARM64 install
@@ -50,8 +49,8 @@ curl -fsSL https://ollama.com/download/ollama-linux-amd64-rocm.tar.zst \
Download and extract the ARM64-specific package:
```shell
curl -fsSL https://ollama.com/download/ollama-linux-arm64.tar.zst \
| sudo tar x -C /usr
curl -fsSL https://ollama.com/download/ollama-linux-arm64.tgz \
| sudo tar zx -C /usr
```
### Adding Ollama as a startup service (recommended)
@@ -113,11 +112,7 @@ sudo systemctl status ollama
```
<Note>
While AMD has contributed the `amdgpu` driver upstream to the official linux
kernel source, the version is older and may not support all ROCm features. We
recommend you install the latest driver from
https://www.amd.com/en/support/linux-drivers for best support of your Radeon
GPU.
While AMD has contributed the `amdgpu` driver upstream to the official linux kernel source, the version is older and may not support all ROCm features. We recommend you install the latest driver from https://www.amd.com/en/support/linux-drivers for best support of your Radeon GPU.
</Note>
## Customizing
@@ -146,8 +141,8 @@ curl -fsSL https://ollama.com/install.sh | sh
Or by re-downloading Ollama:
```shell
curl -fsSL https://ollama.com/download/ollama-linux-amd64.tar.zst \
| sudo tar x -C /usr
curl -fsSL https://ollama.com/download/ollama-linux-amd64.tgz \
| sudo tar zx -C /usr
```
## Installing specific versions
@@ -196,4 +191,4 @@ Remove the downloaded models and Ollama service user and group:
sudo userdel ollama
sudo groupdel ollama
sudo rm -r /usr/share/ollama
```
```

View File

@@ -131,7 +131,7 @@ func TestAPIToolCalling(t *testing.T) {
t.Errorf("unexpected tool called: got %q want %q", lastToolCall.Function.Name, "get_weather")
}
if _, ok := lastToolCall.Function.Arguments.Get("location"); !ok {
if _, ok := lastToolCall.Function.Arguments["location"]; !ok {
t.Errorf("expected tool arguments to include 'location', got: %s", lastToolCall.Function.Arguments.String())
}
case <-ctx.Done():

View File

@@ -8,7 +8,6 @@ import (
"math/rand"
"net/http"
"strings"
"time"
"github.com/gin-gonic/gin"
@@ -442,7 +441,6 @@ type ResponsesWriter struct {
stream bool
responseID string
itemID string
request openai.ResponsesRequest
}
func (w *ResponsesWriter) writeEvent(eventType string, data any) error {
@@ -480,9 +478,7 @@ func (w *ResponsesWriter) writeResponse(data []byte) (int, error) {
// Non-streaming response
w.ResponseWriter.Header().Set("Content-Type", "application/json")
response := openai.ToResponse(w.model, w.responseID, w.itemID, chatResponse, w.request)
completedAt := time.Now().Unix()
response.CompletedAt = &completedAt
response := openai.ToResponse(w.model, w.responseID, w.itemID, chatResponse)
return len(data), json.NewEncoder(w.ResponseWriter).Encode(response)
}
@@ -527,12 +523,11 @@ func ResponsesMiddleware() gin.HandlerFunc {
w := &ResponsesWriter{
BaseWriter: BaseWriter{ResponseWriter: c.Writer},
converter: openai.NewResponsesStreamConverter(responseID, itemID, req.Model, req),
converter: openai.NewResponsesStreamConverter(responseID, itemID, req.Model),
model: req.Model,
stream: streamRequested,
responseID: responseID,
itemID: itemID,
request: req,
}
// Set headers based on streaming mode

View File

@@ -630,10 +630,6 @@ func nameFromToolCallID(messages []Message, toolCallID string) string {
// decodeImageURL decodes a base64 data URI into raw image bytes.
func decodeImageURL(url string) (api.ImageData, error) {
if strings.HasPrefix(url, "http://") || strings.HasPrefix(url, "https://") {
return nil, errors.New("image URLs are not currently supported, please use base64 encoded data instead")
}
types := []string{"jpeg", "jpg", "png", "webp"}
// Support blank mime type to match /api/chat's behavior of taking just unadorned base64

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@@ -4,7 +4,6 @@ import (
"encoding/json"
"fmt"
"math/rand"
"time"
"github.com/ollama/ollama/api"
)
@@ -266,9 +265,9 @@ type ResponsesText struct {
type ResponsesTool struct {
Type string `json:"type"` // "function"
Name string `json:"name"`
Description *string `json:"description"` // nullable but required
Strict *bool `json:"strict"` // nullable but required
Parameters map[string]any `json:"parameters"` // nullable but required
Description string `json:"description,omitempty"`
Strict bool `json:"strict,omitempty"`
Parameters map[string]any `json:"parameters,omitempty"`
}
type ResponsesRequest struct {
@@ -476,16 +475,11 @@ func convertTool(t ResponsesTool) (api.Tool, error) {
}
}
var description string
if t.Description != nil {
description = *t.Description
}
return api.Tool{
Type: t.Type,
Function: api.ToolFunction{
Name: t.Name,
Description: description,
Description: t.Description,
Parameters: params,
},
}, nil
@@ -522,60 +516,17 @@ func convertInputMessage(m ResponsesInputMessage) (api.Message, error) {
// Response types for the Responses API
// ResponsesTextField represents the text output configuration in the response.
type ResponsesTextField struct {
Format ResponsesTextFormat `json:"format"`
}
// ResponsesReasoningOutput represents reasoning configuration in the response.
type ResponsesReasoningOutput struct {
Effort *string `json:"effort,omitempty"`
Summary *string `json:"summary,omitempty"`
}
// ResponsesError represents an error in the response.
type ResponsesError struct {
Code string `json:"code"`
Message string `json:"message"`
}
// ResponsesIncompleteDetails represents details about why a response was incomplete.
type ResponsesIncompleteDetails struct {
Reason string `json:"reason"`
}
type ResponsesResponse struct {
ID string `json:"id"`
Object string `json:"object"`
CreatedAt int64 `json:"created_at"`
CompletedAt *int64 `json:"completed_at"`
Status string `json:"status"`
IncompleteDetails *ResponsesIncompleteDetails `json:"incomplete_details"`
Model string `json:"model"`
PreviousResponseID *string `json:"previous_response_id"`
Instructions *string `json:"instructions"`
Output []ResponsesOutputItem `json:"output"`
Error *ResponsesError `json:"error"`
Tools []ResponsesTool `json:"tools"`
ToolChoice any `json:"tool_choice"`
Truncation string `json:"truncation"`
ParallelToolCalls bool `json:"parallel_tool_calls"`
Text ResponsesTextField `json:"text"`
TopP float64 `json:"top_p"`
PresencePenalty float64 `json:"presence_penalty"`
FrequencyPenalty float64 `json:"frequency_penalty"`
TopLogprobs int `json:"top_logprobs"`
Temperature float64 `json:"temperature"`
Reasoning *ResponsesReasoningOutput `json:"reasoning"`
Usage *ResponsesUsage `json:"usage"`
MaxOutputTokens *int `json:"max_output_tokens"`
MaxToolCalls *int `json:"max_tool_calls"`
Store bool `json:"store"`
Background bool `json:"background"`
ServiceTier string `json:"service_tier"`
Metadata map[string]any `json:"metadata"`
SafetyIdentifier *string `json:"safety_identifier"`
PromptCacheKey *string `json:"prompt_cache_key"`
ID string `json:"id"`
Object string `json:"object"`
CreatedAt int64 `json:"created_at"`
Status string `json:"status"`
Model string `json:"model"`
Output []ResponsesOutputItem `json:"output"`
Usage *ResponsesUsage `json:"usage,omitempty"`
// TODO(drifkin): add `temperature` and `top_p` to the response, but this
// requires additional plumbing to find the effective values since the
// defaults can come from the model or the request
}
type ResponsesOutputItem struct {
@@ -599,39 +550,18 @@ type ResponsesReasoningSummary struct {
}
type ResponsesOutputContent struct {
Type string `json:"type"` // "output_text"
Text string `json:"text"`
Annotations []any `json:"annotations"`
Logprobs []any `json:"logprobs"`
}
type ResponsesInputTokensDetails struct {
CachedTokens int `json:"cached_tokens"`
}
type ResponsesOutputTokensDetails struct {
ReasoningTokens int `json:"reasoning_tokens"`
Type string `json:"type"` // "output_text"
Text string `json:"text"`
}
type ResponsesUsage struct {
InputTokens int `json:"input_tokens"`
OutputTokens int `json:"output_tokens"`
TotalTokens int `json:"total_tokens"`
InputTokensDetails ResponsesInputTokensDetails `json:"input_tokens_details"`
OutputTokensDetails ResponsesOutputTokensDetails `json:"output_tokens_details"`
InputTokens int `json:"input_tokens"`
OutputTokens int `json:"output_tokens"`
TotalTokens int `json:"total_tokens"`
}
// derefFloat64 returns the value of a float64 pointer, or a default if nil.
func derefFloat64(p *float64, def float64) float64 {
if p != nil {
return *p
}
return def
}
// ToResponse converts an api.ChatResponse to a Responses API response.
// The request is used to echo back request parameters in the response.
func ToResponse(model, responseID, itemID string, chatResponse api.ChatResponse, request ResponsesRequest) ResponsesResponse {
// ToResponse converts an api.ChatResponse to a Responses API response
func ToResponse(model, responseID, itemID string, chatResponse api.ChatResponse) ResponsesResponse {
var output []ResponsesOutputItem
// Add reasoning item if thinking is present
@@ -655,7 +585,6 @@ func ToResponse(model, responseID, itemID string, chatResponse api.ChatResponse,
output = append(output, ResponsesOutputItem{
ID: fmt.Sprintf("fc_%s_%d", responseID, i),
Type: "function_call",
Status: "completed",
CallID: tc.ID,
Name: tc.Function.Name,
Arguments: tc.Function.Arguments,
@@ -669,90 +598,25 @@ func ToResponse(model, responseID, itemID string, chatResponse api.ChatResponse,
Role: "assistant",
Content: []ResponsesOutputContent{
{
Type: "output_text",
Text: chatResponse.Message.Content,
Annotations: []any{},
Logprobs: []any{},
Type: "output_text",
Text: chatResponse.Message.Content,
},
},
})
}
var instructions *string
if request.Instructions != "" {
instructions = &request.Instructions
}
// Build truncation with default
truncation := "disabled"
if request.Truncation != nil {
truncation = *request.Truncation
}
tools := request.Tools
if tools == nil {
tools = []ResponsesTool{}
}
text := ResponsesTextField{
Format: ResponsesTextFormat{Type: "text"},
}
if request.Text != nil && request.Text.Format != nil {
text.Format = *request.Text.Format
}
// Build reasoning output from request
var reasoning *ResponsesReasoningOutput
if request.Reasoning.Effort != "" || request.Reasoning.Summary != "" {
reasoning = &ResponsesReasoningOutput{}
if request.Reasoning.Effort != "" {
reasoning.Effort = &request.Reasoning.Effort
}
if request.Reasoning.Summary != "" {
reasoning.Summary = &request.Reasoning.Summary
}
}
return ResponsesResponse{
ID: responseID,
Object: "response",
CreatedAt: chatResponse.CreatedAt.Unix(),
CompletedAt: nil, // Set by middleware when writing final response
Status: "completed",
IncompleteDetails: nil, // Only populated if response incomplete
Model: model,
PreviousResponseID: nil, // Not supported
Instructions: instructions,
Output: output,
Error: nil, // Only populated on failure
Tools: tools,
ToolChoice: "auto", // Default value
Truncation: truncation,
ParallelToolCalls: true, // Default value
Text: text,
TopP: derefFloat64(request.TopP, 1.0),
PresencePenalty: 0, // Default value
FrequencyPenalty: 0, // Default value
TopLogprobs: 0, // Default value
Temperature: derefFloat64(request.Temperature, 1.0),
Reasoning: reasoning,
ID: responseID,
Object: "response",
CreatedAt: chatResponse.CreatedAt.Unix(),
Status: "completed",
Model: model,
Output: output,
Usage: &ResponsesUsage{
InputTokens: chatResponse.PromptEvalCount,
OutputTokens: chatResponse.EvalCount,
TotalTokens: chatResponse.PromptEvalCount + chatResponse.EvalCount,
// TODO(drifkin): wire through the actual values
InputTokensDetails: ResponsesInputTokensDetails{CachedTokens: 0},
// TODO(drifkin): wire through the actual values
OutputTokensDetails: ResponsesOutputTokensDetails{ReasoningTokens: 0},
},
MaxOutputTokens: request.MaxOutputTokens,
MaxToolCalls: nil, // Not supported
Store: false, // We don't store responses
Background: request.Background,
ServiceTier: "default", // Default value
Metadata: map[string]any{},
SafetyIdentifier: nil, // Not supported
PromptCacheKey: nil, // Not supported
}
}
@@ -772,7 +636,6 @@ type ResponsesStreamConverter struct {
responseID string
itemID string
model string
request ResponsesRequest
// State tracking (mutated across Process calls)
firstWrite bool
@@ -805,12 +668,11 @@ func (c *ResponsesStreamConverter) newEvent(eventType string, data map[string]an
}
// NewResponsesStreamConverter creates a new converter with the given configuration.
func NewResponsesStreamConverter(responseID, itemID, model string, request ResponsesRequest) *ResponsesStreamConverter {
func NewResponsesStreamConverter(responseID, itemID, model string) *ResponsesStreamConverter {
return &ResponsesStreamConverter{
responseID: responseID,
itemID: itemID,
model: model,
request: request,
firstWrite: true,
}
}
@@ -855,120 +717,25 @@ func (c *ResponsesStreamConverter) Process(r api.ChatResponse) []ResponsesStream
return events
}
// buildResponseObject creates a full response object with all required fields for streaming events.
func (c *ResponsesStreamConverter) buildResponseObject(status string, output []any, usage map[string]any) map[string]any {
var instructions any = nil
if c.request.Instructions != "" {
instructions = c.request.Instructions
}
truncation := "disabled"
if c.request.Truncation != nil {
truncation = *c.request.Truncation
}
var tools []any
if c.request.Tools != nil {
for _, t := range c.request.Tools {
tools = append(tools, map[string]any{
"type": t.Type,
"name": t.Name,
"description": t.Description,
"strict": t.Strict,
"parameters": t.Parameters,
})
}
}
if tools == nil {
tools = []any{}
}
textFormat := map[string]any{"type": "text"}
if c.request.Text != nil && c.request.Text.Format != nil {
textFormat = map[string]any{
"type": c.request.Text.Format.Type,
}
if c.request.Text.Format.Name != "" {
textFormat["name"] = c.request.Text.Format.Name
}
if c.request.Text.Format.Schema != nil {
textFormat["schema"] = c.request.Text.Format.Schema
}
if c.request.Text.Format.Strict != nil {
textFormat["strict"] = *c.request.Text.Format.Strict
}
}
var reasoning any = nil
if c.request.Reasoning.Effort != "" || c.request.Reasoning.Summary != "" {
r := map[string]any{}
if c.request.Reasoning.Effort != "" {
r["effort"] = c.request.Reasoning.Effort
} else {
r["effort"] = nil
}
if c.request.Reasoning.Summary != "" {
r["summary"] = c.request.Reasoning.Summary
} else {
r["summary"] = nil
}
reasoning = r
}
// Build top_p and temperature with defaults
topP := 1.0
if c.request.TopP != nil {
topP = *c.request.TopP
}
temperature := 1.0
if c.request.Temperature != nil {
temperature = *c.request.Temperature
}
return map[string]any{
"id": c.responseID,
"object": "response",
"created_at": time.Now().Unix(),
"completed_at": nil,
"status": status,
"incomplete_details": nil,
"model": c.model,
"previous_response_id": nil,
"instructions": instructions,
"output": output,
"error": nil,
"tools": tools,
"tool_choice": "auto",
"truncation": truncation,
"parallel_tool_calls": true,
"text": map[string]any{"format": textFormat},
"top_p": topP,
"presence_penalty": 0,
"frequency_penalty": 0,
"top_logprobs": 0,
"temperature": temperature,
"reasoning": reasoning,
"usage": usage,
"max_output_tokens": c.request.MaxOutputTokens,
"max_tool_calls": nil,
"store": false,
"background": c.request.Background,
"service_tier": "default",
"metadata": map[string]any{},
"safety_identifier": nil,
"prompt_cache_key": nil,
}
}
func (c *ResponsesStreamConverter) createResponseCreatedEvent() ResponsesStreamEvent {
return c.newEvent("response.created", map[string]any{
"response": c.buildResponseObject("in_progress", []any{}, nil),
"response": map[string]any{
"id": c.responseID,
"object": "response",
"status": "in_progress",
"output": []any{},
},
})
}
func (c *ResponsesStreamConverter) createResponseInProgressEvent() ResponsesStreamEvent {
return c.newEvent("response.in_progress", map[string]any{
"response": c.buildResponseObject("in_progress", []any{}, nil),
"response": map[string]any{
"id": c.responseID,
"object": "response",
"status": "in_progress",
"output": []any{},
},
})
}
@@ -995,10 +762,9 @@ func (c *ResponsesStreamConverter) processThinking(thinking string) []ResponsesS
// Emit delta
events = append(events, c.newEvent("response.reasoning_summary_text.delta", map[string]any{
"item_id": c.reasoningItemID,
"output_index": c.outputIndex,
"summary_index": 0,
"delta": thinking,
"item_id": c.reasoningItemID,
"output_index": c.outputIndex,
"delta": thinking,
}))
// TODO(drifkin): consider adding
@@ -1017,10 +783,9 @@ func (c *ResponsesStreamConverter) finishReasoning() []ResponsesStreamEvent {
events := []ResponsesStreamEvent{
c.newEvent("response.reasoning_summary_text.done", map[string]any{
"item_id": c.reasoningItemID,
"output_index": c.outputIndex,
"summary_index": 0,
"text": c.accumulatedThinking,
"item_id": c.reasoningItemID,
"output_index": c.outputIndex,
"text": c.accumulatedThinking,
}),
c.newEvent("response.output_item.done", map[string]any{
"output_index": c.outputIndex,
@@ -1133,10 +898,8 @@ func (c *ResponsesStreamConverter) processTextContent(content string) []Response
"output_index": c.outputIndex,
"content_index": c.contentIndex,
"part": map[string]any{
"type": "output_text",
"text": "",
"annotations": []any{},
"logprobs": []any{},
"type": "output_text",
"text": "",
},
}))
}
@@ -1150,7 +913,6 @@ func (c *ResponsesStreamConverter) processTextContent(content string) []Response
"output_index": c.outputIndex,
"content_index": 0,
"delta": content,
"logprobs": []any{},
}))
return events
@@ -1182,10 +944,8 @@ func (c *ResponsesStreamConverter) buildFinalOutput() []any {
"status": "completed",
"role": "assistant",
"content": []map[string]any{{
"type": "output_text",
"text": c.accumulatedText,
"annotations": []any{},
"logprobs": []any{},
"type": "output_text",
"text": c.accumulatedText,
}},
})
}
@@ -1207,7 +967,6 @@ func (c *ResponsesStreamConverter) processCompletion(r api.ChatResponse) []Respo
"output_index": c.outputIndex,
"content_index": 0,
"text": c.accumulatedText,
"logprobs": []any{},
}))
// response.content_part.done
@@ -1216,10 +975,8 @@ func (c *ResponsesStreamConverter) processCompletion(r api.ChatResponse) []Respo
"output_index": c.outputIndex,
"content_index": 0,
"part": map[string]any{
"type": "output_text",
"text": c.accumulatedText,
"annotations": []any{},
"logprobs": []any{},
"type": "output_text",
"text": c.accumulatedText,
},
}))
@@ -1232,31 +989,26 @@ func (c *ResponsesStreamConverter) processCompletion(r api.ChatResponse) []Respo
"status": "completed",
"role": "assistant",
"content": []map[string]any{{
"type": "output_text",
"text": c.accumulatedText,
"annotations": []any{},
"logprobs": []any{},
"type": "output_text",
"text": c.accumulatedText,
}},
},
}))
}
// response.completed
usage := map[string]any{
"input_tokens": r.PromptEvalCount,
"output_tokens": r.EvalCount,
"total_tokens": r.PromptEvalCount + r.EvalCount,
"input_tokens_details": map[string]any{
"cached_tokens": 0,
},
"output_tokens_details": map[string]any{
"reasoning_tokens": 0,
},
}
response := c.buildResponseObject("completed", c.buildFinalOutput(), usage)
response["completed_at"] = time.Now().Unix()
events = append(events, c.newEvent("response.completed", map[string]any{
"response": response,
"response": map[string]any{
"id": c.responseID,
"object": "response",
"status": "completed",
"output": c.buildFinalOutput(),
"usage": map[string]any{
"input_tokens": r.PromptEvalCount,
"output_tokens": r.EvalCount,
"total_tokens": r.PromptEvalCount + r.EvalCount,
},
},
}))
return events

View File

@@ -850,7 +850,7 @@ func TestFromResponsesRequest_Images(t *testing.T) {
}
func TestResponsesStreamConverter_TextOnly(t *testing.T) {
converter := NewResponsesStreamConverter("resp_123", "msg_456", "gpt-oss:20b", ResponsesRequest{})
converter := NewResponsesStreamConverter("resp_123", "msg_456", "gpt-oss:20b")
// First chunk with content
events := converter.Process(api.ChatResponse{
@@ -916,7 +916,7 @@ func TestResponsesStreamConverter_TextOnly(t *testing.T) {
}
func TestResponsesStreamConverter_ToolCalls(t *testing.T) {
converter := NewResponsesStreamConverter("resp_123", "msg_456", "gpt-oss:20b", ResponsesRequest{})
converter := NewResponsesStreamConverter("resp_123", "msg_456", "gpt-oss:20b")
events := converter.Process(api.ChatResponse{
Message: api.Message{
@@ -952,7 +952,7 @@ func TestResponsesStreamConverter_ToolCalls(t *testing.T) {
}
func TestResponsesStreamConverter_Reasoning(t *testing.T) {
converter := NewResponsesStreamConverter("resp_123", "msg_456", "gpt-oss:20b", ResponsesRequest{})
converter := NewResponsesStreamConverter("resp_123", "msg_456", "gpt-oss:20b")
// First chunk with thinking
events := converter.Process(api.ChatResponse{
@@ -1267,7 +1267,7 @@ func TestToResponse_WithReasoning(t *testing.T) {
Content: "The answer is 42",
},
Done: true,
}, ResponsesRequest{})
})
// Should have 2 output items: reasoning + message
if len(response.Output) != 2 {
@@ -1638,7 +1638,7 @@ func TestFromResponsesRequest_ShorthandFormats(t *testing.T) {
func TestResponsesStreamConverter_OutputIncludesContent(t *testing.T) {
// Verify that response.output_item.done includes content field for messages
converter := NewResponsesStreamConverter("resp_123", "msg_456", "gpt-oss:20b", ResponsesRequest{})
converter := NewResponsesStreamConverter("resp_123", "msg_456", "gpt-oss:20b")
// First chunk
converter.Process(api.ChatResponse{
@@ -1686,7 +1686,7 @@ func TestResponsesStreamConverter_OutputIncludesContent(t *testing.T) {
func TestResponsesStreamConverter_ResponseCompletedIncludesOutput(t *testing.T) {
// Verify that response.completed includes the output array
converter := NewResponsesStreamConverter("resp_123", "msg_456", "gpt-oss:20b", ResponsesRequest{})
converter := NewResponsesStreamConverter("resp_123", "msg_456", "gpt-oss:20b")
// Process some content
converter.Process(api.ChatResponse{
@@ -1730,7 +1730,7 @@ func TestResponsesStreamConverter_ResponseCompletedIncludesOutput(t *testing.T)
func TestResponsesStreamConverter_ResponseCreatedIncludesOutput(t *testing.T) {
// Verify that response.created includes an empty output array
converter := NewResponsesStreamConverter("resp_123", "msg_456", "gpt-oss:20b", ResponsesRequest{})
converter := NewResponsesStreamConverter("resp_123", "msg_456", "gpt-oss:20b")
events := converter.Process(api.ChatResponse{
Message: api.Message{Content: "Hi"},
@@ -1757,7 +1757,7 @@ func TestResponsesStreamConverter_ResponseCreatedIncludesOutput(t *testing.T) {
func TestResponsesStreamConverter_SequenceNumbers(t *testing.T) {
// Verify that events include incrementing sequence numbers
converter := NewResponsesStreamConverter("resp_123", "msg_456", "gpt-oss:20b", ResponsesRequest{})
converter := NewResponsesStreamConverter("resp_123", "msg_456", "gpt-oss:20b")
events := converter.Process(api.ChatResponse{
Message: api.Message{Content: "Hello"},
@@ -1791,7 +1791,7 @@ func TestResponsesStreamConverter_SequenceNumbers(t *testing.T) {
func TestResponsesStreamConverter_FunctionCallStatus(t *testing.T) {
// Verify that function call items include status field
converter := NewResponsesStreamConverter("resp_123", "msg_456", "gpt-oss:20b", ResponsesRequest{})
converter := NewResponsesStreamConverter("resp_123", "msg_456", "gpt-oss:20b")
events := converter.Process(api.ChatResponse{
Message: api.Message{

View File

@@ -5,7 +5,6 @@ import (
"fmt"
"io"
"os"
"strings"
)
type Prompt struct {
@@ -37,11 +36,10 @@ type Terminal struct {
}
type Instance struct {
Prompt *Prompt
Terminal *Terminal
History *History
Pasting bool
pastedLines []string
Prompt *Prompt
Terminal *Terminal
History *History
Pasting bool
}
func New(prompt Prompt) (*Instance, error) {
@@ -176,8 +174,6 @@ func (i *Instance) Readline() (string, error) {
case CharEsc:
esc = true
case CharInterrupt:
i.pastedLines = nil
i.Prompt.UseAlt = false
return "", ErrInterrupt
case CharPrev:
i.historyPrev(buf, &currentLineBuf)
@@ -192,23 +188,7 @@ func (i *Instance) Readline() (string, error) {
case CharForward:
buf.MoveRight()
case CharBackspace, CharCtrlH:
if buf.IsEmpty() && len(i.pastedLines) > 0 {
lastIdx := len(i.pastedLines) - 1
prevLine := i.pastedLines[lastIdx]
i.pastedLines = i.pastedLines[:lastIdx]
fmt.Print(CursorBOL + ClearToEOL + CursorUp + CursorBOL + ClearToEOL)
if len(i.pastedLines) == 0 {
fmt.Print(i.Prompt.Prompt)
i.Prompt.UseAlt = false
} else {
fmt.Print(i.Prompt.AltPrompt)
}
for _, r := range prevLine {
buf.Add(r)
}
} else {
buf.Remove()
}
buf.Remove()
case CharTab:
// todo: convert back to real tabs
for range 8 {
@@ -231,28 +211,13 @@ func (i *Instance) Readline() (string, error) {
case CharCtrlZ:
fd := os.Stdin.Fd()
return handleCharCtrlZ(fd, i.Terminal.termios)
case CharCtrlJ:
i.pastedLines = append(i.pastedLines, buf.String())
buf.Buf.Clear()
buf.Pos = 0
buf.DisplayPos = 0
buf.LineHasSpace.Clear()
fmt.Println()
fmt.Print(i.Prompt.AltPrompt)
i.Prompt.UseAlt = true
continue
case CharEnter:
case CharEnter, CharCtrlJ:
output := buf.String()
if len(i.pastedLines) > 0 {
output = strings.Join(i.pastedLines, "\n") + "\n" + output
i.pastedLines = nil
}
if output != "" {
i.History.Add(output)
}
buf.MoveToEnd()
fmt.Println()
i.Prompt.UseAlt = false
return output, nil
default:

View File

@@ -179,7 +179,7 @@ _build_macapp() {
fi
rm -f dist/Ollama-darwin.zip
ditto -c -k --norsrc --keepParent dist/Ollama.app dist/Ollama-darwin.zip
ditto -c -k --keepParent dist/Ollama.app dist/Ollama-darwin.zip
(cd dist/Ollama.app/Contents/Resources/; tar -cf - ollama ollama-mlx *.so *.dylib *.metallib 2>/dev/null) | gzip -9vc > dist/ollama-darwin.tgz
# Notarize and Staple
@@ -187,7 +187,7 @@ _build_macapp() {
$(xcrun -f notarytool) submit dist/Ollama-darwin.zip --wait --timeout 20m --apple-id "$APPLE_ID" --password "$APPLE_PASSWORD" --team-id "$APPLE_TEAM_ID"
rm -f dist/Ollama-darwin.zip
$(xcrun -f stapler) staple dist/Ollama.app
ditto -c -k --norsrc --keepParent dist/Ollama.app dist/Ollama-darwin.zip
ditto -c -k --keepParent dist/Ollama.app dist/Ollama-darwin.zip
rm -f dist/Ollama.dmg

View File

@@ -95,11 +95,48 @@ func (p *blobDownloadPart) UnmarshalJSON(b []byte) error {
}
const (
numDownloadParts = 16
// numDownloadParts is the default number of concurrent download parts for standard downloads
numDownloadParts = 16
// numHFDownloadParts is the reduced number of concurrent download parts for HuggingFace
// downloads to avoid triggering rate limits (HTTP 429 errors). See GitHub issue #13297.
numHFDownloadParts = 4
minDownloadPartSize int64 = 100 * format.MegaByte
maxDownloadPartSize int64 = 1000 * format.MegaByte
)
// isHuggingFaceURL returns true if the URL is from a HuggingFace domain.
// This includes:
// - huggingface.co (main domain)
// - *.huggingface.co (subdomains like cdn-lfs.huggingface.co)
// - hf.co (shortlink domain)
// - *.hf.co (CDN domains like cdn-lfs.hf.co, cdn-lfs3.hf.co)
func isHuggingFaceURL(u *url.URL) bool {
if u == nil {
return false
}
host := strings.ToLower(u.Hostname())
return host == "huggingface.co" ||
strings.HasSuffix(host, ".huggingface.co") ||
host == "hf.co" ||
strings.HasSuffix(host, ".hf.co")
}
// getNumDownloadParts returns the number of concurrent download parts to use
// for the given URL. HuggingFace URLs use reduced concurrency (default 4) to
// avoid triggering rate limits. This can be overridden via the OLLAMA_HF_CONCURRENCY
// environment variable. For non-HuggingFace URLs, returns the standard concurrency (16).
func getNumDownloadParts(u *url.URL) int {
if isHuggingFaceURL(u) {
if v := os.Getenv("OLLAMA_HF_CONCURRENCY"); v != "" {
if n, err := strconv.Atoi(v); err == nil && n > 0 {
return n
}
}
return numHFDownloadParts
}
return numDownloadParts
}
func (p *blobDownloadPart) Name() string {
return strings.Join([]string{
p.blobDownload.Name, "partial", strconv.Itoa(p.N),
@@ -271,7 +308,11 @@ func (b *blobDownload) run(ctx context.Context, requestURL *url.URL, opts *regis
}
g, inner := errgroup.WithContext(ctx)
g.SetLimit(numDownloadParts)
concurrency := getNumDownloadParts(directURL)
if concurrency != numDownloadParts {
slog.Info(fmt.Sprintf("using reduced concurrency (%d) for HuggingFace download", concurrency))
}
g.SetLimit(concurrency)
for i := range b.Parts {
part := b.Parts[i]
if part.Completed.Load() == part.Size {

194
server/download_test.go Normal file
View File

@@ -0,0 +1,194 @@
package server
import (
"net/url"
"testing"
"github.com/stretchr/testify/assert"
)
func TestIsHuggingFaceURL(t *testing.T) {
tests := []struct {
name string
url string
expected bool
}{
{
name: "nil url",
url: "",
expected: false,
},
{
name: "huggingface.co main domain",
url: "https://huggingface.co/some/model",
expected: true,
},
{
name: "cdn-lfs.huggingface.co subdomain",
url: "https://cdn-lfs.huggingface.co/repos/abc/123",
expected: true,
},
{
name: "cdn-lfs3.hf.co CDN domain",
url: "https://cdn-lfs3.hf.co/repos/abc/123",
expected: true,
},
{
name: "hf.co shortlink domain",
url: "https://hf.co/model",
expected: true,
},
{
name: "uppercase HuggingFace domain",
url: "https://HUGGINGFACE.CO/model",
expected: true,
},
{
name: "mixed case HF domain",
url: "https://Cdn-Lfs.HF.Co/repos",
expected: true,
},
{
name: "ollama registry",
url: "https://registry.ollama.ai/v2/library/llama3",
expected: false,
},
{
name: "github.com",
url: "https://github.com/ollama/ollama",
expected: false,
},
{
name: "fake huggingface domain",
url: "https://nothuggingface.co/model",
expected: false,
},
{
name: "fake hf domain",
url: "https://nothf.co/model",
expected: false,
},
{
name: "huggingface in path not host",
url: "https://example.com/huggingface.co/model",
expected: false,
},
}
for _, tc := range tests {
t.Run(tc.name, func(t *testing.T) {
var u *url.URL
if tc.url != "" {
var err error
u, err = url.Parse(tc.url)
if err != nil {
t.Fatalf("failed to parse URL: %v", err)
}
}
got := isHuggingFaceURL(u)
assert.Equal(t, tc.expected, got)
})
}
}
func TestGetNumDownloadParts(t *testing.T) {
tests := []struct {
name string
url string
envValue string
expected int
description string
}{
{
name: "nil url returns default",
url: "",
envValue: "",
expected: numDownloadParts,
description: "nil URL should return standard concurrency",
},
{
name: "ollama registry returns default",
url: "https://registry.ollama.ai/v2/library/llama3",
envValue: "",
expected: numDownloadParts,
description: "Ollama registry should use standard concurrency",
},
{
name: "huggingface returns reduced default",
url: "https://huggingface.co/model/repo",
envValue: "",
expected: numHFDownloadParts,
description: "HuggingFace should use reduced concurrency",
},
{
name: "hf.co CDN returns reduced default",
url: "https://cdn-lfs3.hf.co/repos/abc/123",
envValue: "",
expected: numHFDownloadParts,
description: "HuggingFace CDN should use reduced concurrency",
},
{
name: "huggingface with env override",
url: "https://huggingface.co/model/repo",
envValue: "2",
expected: 2,
description: "OLLAMA_HF_CONCURRENCY should override default",
},
{
name: "huggingface with higher env override",
url: "https://huggingface.co/model/repo",
envValue: "8",
expected: 8,
description: "OLLAMA_HF_CONCURRENCY can be set higher than default",
},
{
name: "huggingface with invalid env (non-numeric)",
url: "https://huggingface.co/model/repo",
envValue: "invalid",
expected: numHFDownloadParts,
description: "Invalid OLLAMA_HF_CONCURRENCY should fall back to default",
},
{
name: "huggingface with invalid env (zero)",
url: "https://huggingface.co/model/repo",
envValue: "0",
expected: numHFDownloadParts,
description: "Zero OLLAMA_HF_CONCURRENCY should fall back to default",
},
{
name: "huggingface with invalid env (negative)",
url: "https://huggingface.co/model/repo",
envValue: "-1",
expected: numHFDownloadParts,
description: "Negative OLLAMA_HF_CONCURRENCY should fall back to default",
},
{
name: "non-huggingface ignores env",
url: "https://registry.ollama.ai/v2/library/llama3",
envValue: "2",
expected: numDownloadParts,
description: "OLLAMA_HF_CONCURRENCY should not affect non-HF URLs",
},
}
for _, tc := range tests {
t.Run(tc.name, func(t *testing.T) {
// Set or clear the environment variable
if tc.envValue != "" {
t.Setenv("OLLAMA_HF_CONCURRENCY", tc.envValue)
}
var u *url.URL
if tc.url != "" {
var err error
u, err = url.Parse(tc.url)
if err != nil {
t.Fatalf("failed to parse URL: %v", err)
}
}
got := getNumDownloadParts(u)
assert.Equal(t, tc.expected, got, tc.description)
})
}
}

50
x/README.md Normal file
View File

@@ -0,0 +1,50 @@
# Experimental Features
## MLX Backend
We're working on a new experimental backend based on the [MLX project](https://github.com/ml-explore/mlx)
Support is currently limited to MacOS and Linux with CUDA GPUs. We're looking to add support for Windows CUDA soon, and other GPU vendors.
### Building ollama-mlx
The `ollama-mlx` binary is a separate build of Ollama with MLX support enabled. This enables experimental features like image generation.
#### macOS (Apple Silicon and Intel)
```bash
# Build MLX backend libraries
cmake --preset MLX
cmake --build --preset MLX --parallel
cmake --install build --component MLX
# Build ollama-mlx binary
go build -tags mlx -o ollama-mlx .
```
#### Linux (CUDA)
On Linux, use the preset "MLX CUDA 13" or "MLX CUDA 12" to enable CUDA with the default Ollama NVIDIA GPU architectures enabled:
```bash
# Build MLX backend libraries with CUDA support
cmake --preset 'MLX CUDA 13'
cmake --build --preset 'MLX CUDA 13' --parallel
cmake --install build --component MLX
# Build ollama-mlx binary
CGO_CFLAGS="-O3 -I$(pwd)/build/_deps/mlx-c-src" \
CGO_LDFLAGS="-L$(pwd)/build/lib/ollama -lmlxc -lmlx" \
go build -tags mlx -o ollama-mlx .
```
#### Using build scripts
The build scripts automatically create the `ollama-mlx` binary:
- **macOS**: `./scripts/build_darwin.sh` produces `dist/darwin/ollama-mlx`
- **Linux**: `./scripts/build_linux.sh` produces `ollama-mlx` in the output archives
## Image Generation
Image generation is built into the `ollama-mlx` binary. Run `ollama-mlx serve` to start the server with image generation support enabled.

View File

@@ -25,6 +25,14 @@ import (
"github.com/ollama/ollama/x/tools"
)
// MultilineState tracks the state of multiline input
type MultilineState int
const (
MultilineNone MultilineState = iota
MultilineSystem
)
// Tool output capping constants
const (
// localModelTokenLimit is the token limit for local models (smaller context).
@@ -648,7 +656,7 @@ func GenerateInteractive(cmd *cobra.Command, modelName string, wordWrap bool, op
Prompt: ">>> ",
AltPrompt: "... ",
Placeholder: "Send a message (/? for help)",
AltPlaceholder: "Press Enter to send",
AltPlaceholder: `Use """ to end multi-line input`,
})
if err != nil {
return err
@@ -699,6 +707,7 @@ func GenerateInteractive(cmd *cobra.Command, modelName string, wordWrap bool, op
var sb strings.Builder
var format string
var system string
var multiline MultilineState = MultilineNone
for {
line, err := scanner.Readline()
@@ -712,12 +721,37 @@ func GenerateInteractive(cmd *cobra.Command, modelName string, wordWrap bool, op
}
scanner.Prompt.UseAlt = false
sb.Reset()
multiline = MultilineNone
continue
case err != nil:
return err
}
switch {
case multiline != MultilineNone:
// check if there's a multiline terminating string
before, ok := strings.CutSuffix(line, `"""`)
sb.WriteString(before)
if !ok {
fmt.Fprintln(&sb)
continue
}
switch multiline {
case MultilineSystem:
system = sb.String()
newMessage := api.Message{Role: "system", Content: system}
if len(messages) > 0 && messages[len(messages)-1].Role == "system" {
messages[len(messages)-1] = newMessage
} else {
messages = append(messages, newMessage)
}
fmt.Println("Set system message.")
sb.Reset()
}
multiline = MultilineNone
scanner.Prompt.UseAlt = false
case strings.HasPrefix(line, "/exit"), strings.HasPrefix(line, "/bye"):
return nil
case strings.HasPrefix(line, "/clear"):
@@ -826,18 +860,41 @@ func GenerateInteractive(cmd *cobra.Command, modelName string, wordWrap bool, op
options[args[2]] = fp[args[2]]
case "system":
if len(args) < 3 {
fmt.Println("Usage: /set system <message>")
fmt.Println("Usage: /set system <message> or /set system \"\"\"<multi-line message>\"\"\"")
continue
}
system = strings.Join(args[2:], " ")
newMessage := api.Message{Role: "system", Content: system}
multiline = MultilineSystem
line := strings.Join(args[2:], " ")
line, ok := strings.CutPrefix(line, `"""`)
if !ok {
multiline = MultilineNone
} else {
// only cut suffix if the line is multiline
line, ok = strings.CutSuffix(line, `"""`)
if ok {
multiline = MultilineNone
}
}
sb.WriteString(line)
if multiline != MultilineNone {
scanner.Prompt.UseAlt = true
continue
}
system = sb.String()
newMessage := api.Message{Role: "system", Content: sb.String()}
// Check if the slice is not empty and the last message is from 'system'
if len(messages) > 0 && messages[len(messages)-1].Role == "system" {
// Replace the last message
messages[len(messages)-1] = newMessage
} else {
messages = append(messages, newMessage)
}
fmt.Println("Set system message.")
sb.Reset()
continue
default:
fmt.Printf("Unknown command '/set %s'. Type /? for help\n", args[1])
@@ -1024,7 +1081,7 @@ func GenerateInteractive(cmd *cobra.Command, modelName string, wordWrap bool, op
sb.WriteString(line)
}
if sb.Len() > 0 {
if sb.Len() > 0 && multiline == MultilineNone {
newMessage := api.Message{Role: "user", Content: sb.String()}
messages = append(messages, newMessage)