macapp: add error handling for symlink operations

Refactor the installer to do a better job handling errors when creating symlinks.
It checks if paths are valid before trying to use them, safely creates
directories if they don't exist, and clearly tells you what went wrong if
something fails. It also uses TypeScript to catch mistakes early and makes
sure paths work correctly in all cases.

README.md

@@ -346,6 +346,9 @@ See the [API documentation](./docs/api.md) for all endpoints.
 - [Web management](https://github.com/lemonit-eric-mao/ollama-web-management) (Web management page)
 - [Promptery](https://github.com/promptery/promptery) (desktop client for Ollama.)
 - [Ollama App](https://github.com/JHubi1/ollama-app) (Modern and easy-to-use multi-platform client for Ollama)
+- [SpaceLlama](https://github.com/tcsenpai/spacellama) (Firefox and Chrome extension to quickly summarize web pages with ollama in a sidebar)
+- [YouLama](https://github.com/tcsenpai/youlama) (Webapp to quickly summarize any YouTube video, supporting Invidious as well)
+- [DualMind](https://github.com/tcsenpai/dualmind) (Experimental app allowing two models to talk to each other in the terminal or in a web interface)
 - [ollamarama-matrix](https://github.com/h1ddenpr0cess20/ollamarama-matrix) (Ollama chatbot for the Matrix chat protocol)
 - [ollama-chat-app](https://github.com/anan1213095357/ollama-chat-app) (Flutter-based chat app)
 - [Perfect Memory AI](https://www.perfectmemory.ai/) (Productivity AI assists personalized by what you have seen on your screen, heard and said in the meetings)
@@ -356,6 +359,7 @@ See the [API documentation](./docs/api.md) for all endpoints.
 - [Nosia](https://github.com/nosia-ai/nosia) (Easy to install and use RAG platform based on Ollama)
 - [Witsy](https://github.com/nbonamy/witsy) (An AI Desktop application avaiable for Mac/Windows/Linux)
 - [Abbey](https://github.com/US-Artificial-Intelligence/abbey) (A configurable AI interface server with notebooks, document storage, and YouTube support)
+- [Minima](https://github.com/dmayboroda/minima) (RAG with on-premises or fully local workflow)
 
 ### Cloud
 

api/types.go

@@ -146,6 +146,7 @@ type ToolCall struct {
 }
 
 type ToolCallFunction struct {
+	Index     int                       `json:"index,omitempty"`
 	Name      string                    `json:"name"`
 	Arguments ToolCallFunctionArguments `json:"arguments"`
 }

cmd/cmd_test.go

@@ -8,7 +8,6 @@ import (
 	"net/http"
 	"net/http/httptest"
 	"os"
-	"path/filepath"
 	"strings"
 	"testing"
 
@@ -180,18 +179,14 @@ Weigh anchor!
 
 	t.Run("license", func(t *testing.T) {
 		var b bytes.Buffer
-		license, err := os.ReadFile(filepath.Join("..", "LICENSE"))
-		if err != nil {
-			t.Fatal(err)
-		}
-
+		license := "MIT License\nCopyright (c) Ollama\n"
 		if err := showInfo(&api.ShowResponse{
 			Details: api.ModelDetails{
 				Family:            "test",
 				ParameterSize:     "7B",
 				QuantizationLevel: "FP16",
 			},
-			License: string(license),
+			License: license,
 		}, &b); err != nil {
 			t.Fatal(err)
 		}

docs/api.md

@@ -49,10 +49,10 @@ Advanced parameters (optional):
 - `options`: additional model parameters listed in the documentation for the [Modelfile](./modelfile.md#valid-parameters-and-values) such as `temperature`
 - `system`: system message to (overrides what is defined in the `Modelfile`)
 - `template`: the prompt template to use (overrides what is defined in the `Modelfile`)
-- `context`: the context parameter returned from a previous request to `/generate`, this can be used to keep a short conversational memory
 - `stream`: if `false` the response will be returned as a single response object, rather than a stream of objects
 - `raw`: if `true` no formatting will be applied to the prompt. You may choose to use the `raw` parameter if you are specifying a full templated prompt in your request to the API
 - `keep_alive`: controls how long the model will stay loaded into memory following the request (default: `5m`)
+- `context` (deprecated): the context parameter returned from a previous request to `/generate`, this can be used to keep a short conversational memory
 
 #### JSON mode
 

docs/modelfile.md

@@ -63,7 +63,7 @@ SYSTEM You are Mario from super mario bros, acting as an assistant.
 To use this:
 
 1. Save it as a file (e.g. `Modelfile`)
-2. `ollama create choose-a-model-name -f <location of the file e.g. ./Modelfile>'`
+2. `ollama create choose-a-model-name -f <location of the file e.g. ./Modelfile>`
 3. `ollama run choose-a-model-name`
 4. Start using the model!
 
@@ -156,7 +156,7 @@ PARAMETER <parameter> <parametervalue>
 | seed           | Sets the random number seed to use for generation. Setting this to a specific number will make the model generate the same text for the same prompt. (Default: 0)                                                                                       | int        | seed 42              |
 | stop           | Sets the stop sequences to use. When this pattern is encountered the LLM will stop generating text and return. Multiple stop patterns may be set by specifying multiple separate `stop` parameters in a modelfile.                                      | string     | stop "AI assistant:" |
 | tfs_z          | Tail free sampling is used to reduce the impact of less probable tokens from the output. A higher value (e.g., 2.0) will reduce the impact more, while a value of 1.0 disables this setting. (default: 1)                                               | float      | tfs_z 1              |
-| num_predict    | Maximum number of tokens to predict when generating text. (Default: 128, -1 = infinite generation, -2 = fill context)                                                                                                                                   | int        | num_predict 42       |
+| num_predict    | Maximum number of tokens to predict when generating text. (Default: -1, infinite generation)                                                                                                                                   | 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            |

llama/README.md

@@ -105,7 +105,7 @@ make apply-patches
 
 **Pin to new base commit**
 
-To update to a newer base commit, select the upstream git tag or commit and update `llama/vendoring.env`
+To update to a newer base commit, select the upstream git tag or commit and update `llama/vendoring`
 
 #### Applying patches
 

llama/runner/runner.go

@@ -833,10 +833,21 @@ func (s *Server) health(w http.ResponseWriter, r *http.Request) {
 	}
 }
 
+type multiLPath []string
+
+func (m *multiLPath) Set(value string) error {
+	*m = append(*m, value)
+	return nil
+}
+
+func (m *multiLPath) String() string {
+	return strings.Join(*m, ", ")
+}
+
 func (s *Server) loadModel(
 	params llama.ModelParams,
 	mpath string,
-	lpath string,
+	lpath multiLPath,
 	ppath string,
 	kvSize int,
 	flashAttention bool,
@@ -857,12 +868,14 @@ func (s *Server) loadModel(
 		panic(err)
 	}
 
-	if lpath != "" {
-		err := s.model.ApplyLoraFromFile(s.lc, lpath, 1.0, threads)
+	if lpath.String() != "" {
+		for _, path := range lpath {
+			err := s.model.ApplyLoraFromFile(s.lc, path, 1.0, threads)
 			if err != nil {
 				panic(err)
 			}
 		}
+	}
 
 	if ppath != "" {
 		var err error
@@ -890,7 +903,6 @@ func main() {
 	mainGpu := flag.Int("main-gpu", 0, "Main GPU")
 	flashAttention := flag.Bool("flash-attn", false, "Enable flash attention")
 	kvSize := flag.Int("ctx-size", 2048, "Context (or KV cache) size")
-	lpath := flag.String("lora", "", "Path to lora layer file")
 	port := flag.Int("port", 8080, "Port to expose the server on")
 	threads := flag.Int("threads", runtime.NumCPU(), "Number of threads to use during generation")
 	verbose := flag.Bool("verbose", false, "verbose output (default: disabled)")
@@ -900,6 +912,9 @@ func main() {
 	multiUserCache := flag.Bool("multiuser-cache", false, "optimize input cache algorithm for multiple users")
 	requirements := flag.Bool("requirements", false, "print json requirement information")
 
+	var lpaths multiLPath
+	flag.Var(&lpaths, "lora", "Path to lora layer file (can be specified multiple times)")
+
 	flag.Parse()
 	if *requirements {
 		printRequirements(os.Stdout)
@@ -946,7 +961,7 @@ func main() {
 	params := llama.ModelParams{
 		NumGpuLayers: *nGpuLayers,
 		MainGpu:      *mainGpu,
-		UseMmap:      !*noMmap && *lpath == "",
+		UseMmap:      !*noMmap && lpaths.String() == "",
 		UseMlock:     *mlock,
 		TensorSplit:  tensorSplitFloats,
 		Progress: func(progress float32) {
@@ -955,7 +970,7 @@ func main() {
 	}
 
 	server.ready.Add(1)
-	go server.loadModel(params, *mpath, *lpath, *ppath, *kvSize, *flashAttention, *threads, *multiUserCache)
+	go server.loadModel(params, *mpath, lpaths, *ppath, *kvSize, *flashAttention, *threads, *multiUserCache)
 
 	server.cond = sync.NewCond(&server.mu)
 

llm/server.go

@@ -144,10 +144,6 @@ func NewLlamaServer(gpus discover.GpuInfoList, model string, ggml *GGML, adapter
 	// Loop through potential servers
 	finalErr := errors.New("no suitable llama servers found")
 
-	if len(adapters) > 1 {
-		return nil, errors.New("ollama supports only one lora adapter, but multiple were provided")
-	}
-
 	rDir, err := runners.Refresh(build.EmbedFS)
 	if err != nil {
 		return nil, err
@@ -201,8 +197,9 @@ func NewLlamaServer(gpus discover.GpuInfoList, model string, ggml *GGML, adapter
 	}
 
 	if len(adapters) > 0 {
-		// TODO: applying multiple adapters is not supported by the llama.cpp server yet
-		params = append(params, "--lora", adapters[0])
+		for _, adapter := range adapters {
+			params = append(params, "--lora", adapter)
+		}
 	}
 
 	if len(projectors) > 0 {

macapp/src/install.ts

@@ -1,21 +1,35 @@
 import * as fs from 'fs'
-import { exec as cbExec } from 'child_process'
+import { spawn } from 'child_process'
 import * as path from 'path'
-import { promisify } from 'util'
 
 const app = process && process.type === 'renderer' ? require('@electron/remote').app : require('electron').app
 const ollama = app.isPackaged ? path.join(process.resourcesPath, 'ollama') : path.resolve(process.cwd(), '..', 'ollama')
-const exec = promisify(cbExec)
 const symlinkPath = '/usr/local/bin/ollama'
 
-export function installed() {
+export function installed(): boolean {
   return fs.existsSync(symlinkPath) && fs.readlinkSync(symlinkPath) === ollama
 }
 
-export async function install() {
-  const command = `do shell script "mkdir -p ${path.dirname(
-    symlinkPath
-  )} && ln -F -s \\"${ollama}\\" \\"${symlinkPath}\\"" with administrator privileges`
-
-  await exec(`osascript -e '${command}'`)
+function validPath(targetPath: string): boolean {
+  const normalized = path.normalize(targetPath)
+  return !(/[;&|`$(){}[\]<>]/.test(normalized) || normalized.includes('..'))
+}
+
+export async function install(): Promise<void> {
+  if (!validPath(ollama) || !validPath(symlinkPath)) {
+    throw new Error('Invalid path format')
+  }
+
+  await fs.promises.mkdir(path.dirname(symlinkPath), { recursive: true })
+    .catch(err => err.code === 'EEXIST' ? null : Promise.reject(err))
+
+  const process = spawn('osascript', [
+    '-e',
+    `do shell script "ln -F -s '${path.normalize(ollama)}' '${path.normalize(symlinkPath)}'" with administrator privileges`
+  ])
+
+  await new Promise<void>((resolve, reject) => {
+    process.on('error', reject)
+    process.on('close', code => code === 0 ? resolve() : reject(new Error(`Failed with code ${code}`)))
+  })
 }

openai/openai.go

@@ -140,6 +140,7 @@ type CompletionChunk struct {
 
 type ToolCall struct {
 	ID       string `json:"id"`
+	Index    int    `json:"index"`
 	Type     string `json:"type"`
 	Function struct {
 		Name      string `json:"name"`
@@ -200,12 +201,13 @@ func toolCallId() string {
 	return "call_" + strings.ToLower(string(b))
 }
 
-func toChatCompletion(id string, r api.ChatResponse) ChatCompletion {
-	toolCalls := make([]ToolCall, len(r.Message.ToolCalls))
-	for i, tc := range r.Message.ToolCalls {
+func toToolCalls(tc []api.ToolCall) []ToolCall {
+	toolCalls := make([]ToolCall, len(tc))
+	for i, tc := range tc {
 		toolCalls[i].ID = toolCallId()
 		toolCalls[i].Type = "function"
 		toolCalls[i].Function.Name = tc.Function.Name
+		toolCalls[i].Index = tc.Function.Index
 
 		args, err := json.Marshal(tc.Function.Arguments)
 		if err != nil {
@@ -215,7 +217,11 @@ func toChatCompletion(id string, r api.ChatResponse) ChatCompletion {
 
 		toolCalls[i].Function.Arguments = string(args)
 	}
+	return toolCalls
+}
 
+func toChatCompletion(id string, r api.ChatResponse) ChatCompletion {
+	toolCalls := toToolCalls(r.Message.ToolCalls)
 	return ChatCompletion{
 		Id:                id,
 		Object:            "chat.completion",
@@ -244,6 +250,7 @@ func toChatCompletion(id string, r api.ChatResponse) ChatCompletion {
 }
 
 func toChunk(id string, r api.ChatResponse) ChatCompletionChunk {
+	toolCalls := toToolCalls(r.Message.ToolCalls)
 	return ChatCompletionChunk{
 		Id:                id,
 		Object:            "chat.completion.chunk",
@@ -252,7 +259,7 @@ func toChunk(id string, r api.ChatResponse) ChatCompletionChunk {
 		SystemFingerprint: "fp_ollama",
 		Choices: []ChunkChoice{{
 			Index: 0,
-			Delta: Message{Role: "assistant", Content: r.Message.Content},
+			Delta: Message{Role: "assistant", Content: r.Message.Content, ToolCalls: toolCalls},
 			FinishReason: func(reason string) *string {
 				if len(reason) > 0 {
 					return &reason

openai/openai_test.go

@@ -195,7 +195,86 @@ func TestChatMiddleware(t *testing.T) {
 				Stream: &False,
 			},
 		},
-
+		{
+			name: "chat handler with streaming tools",
+			body: `{
+				"model": "test-model",
+				"messages": [
+					{"role": "user", "content": "What's the weather like in Paris?"}
+				],
+				"stream": true,
+				"tools": [{
+					"type": "function",
+					"function": {
+						"name": "get_weather",
+						"description": "Get the current weather",
+						"parameters": {
+							"type": "object",
+							"required": ["location"],
+							"properties": {
+								"location": {
+									"type": "string",
+									"description": "The city and state"
+								},
+								"unit": {
+									"type": "string",
+									"enum": ["celsius", "fahrenheit"]
+								}
+							}
+						}
+					}
+				}]
+			}`,
+			req: api.ChatRequest{
+				Model: "test-model",
+				Messages: []api.Message{
+					{
+						Role:    "user",
+						Content: "What's the weather like in Paris?",
+					},
+				},
+				Tools: []api.Tool{
+					{
+						Type: "function",
+						Function: api.ToolFunction{
+							Name:        "get_weather",
+							Description: "Get the current weather",
+							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"`
+							}{
+								Type:     "object",
+								Required: []string{"location"},
+								Properties: map[string]struct {
+									Type        string   `json:"type"`
+									Description string   `json:"description"`
+									Enum        []string `json:"enum,omitempty"`
+								}{
+									"location": {
+										Type:        "string",
+										Description: "The city and state",
+									},
+									"unit": {
+										Type: "string",
+										Enum: []string{"celsius", "fahrenheit"},
+									},
+								},
+							},
+						},
+					},
+				},
+				Options: map[string]any{
+					"temperature": 1.0,
+					"top_p":       1.0,
+				},
+				Stream: &True,
+			},
+		},
 		{
 			name: "chat handler error forwarding",
 			body: `{

server/model_test.go

@@ -39,6 +39,7 @@ func TestExecuteWithTools(t *testing.T) {
 		{"mistral", `[TOOL_CALLS]  [{"name": "get_current_weather", "arguments": {"format":"fahrenheit","location":"San Francisco, CA"}},{"name": "get_current_weather", "arguments": {"format":"celsius","location":"Toronto, Canada"}}]
 
 The temperature in San Francisco, CA is 70°F and in Toronto, Canada is 20°C.`, true},
+		{"mistral", `[TOOL_CALLS]  [{"name": "get_current_weather", "arguments": {"format":"fahrenheit","location":"San Francisco, CA"}},{"name": "get_current_weather", "arguments": {"format":"celsius","location":"Toronto, Canada"}},{"name": "get_current_weather", "arguments": {"format":"celsius","location":"To }]`, false},
 		{"mistral", `I'm not aware of that information. However, I can suggest searching for the weather using the "get_current_weather" function:
 
 		[{"name": "get_current_weather", "arguments": {"format":"fahrenheit","location":"San Francisco, CA"}},{"name": "get_current_weather", "arguments": {"format":"celsius","location":"Toronto, Canada"}}]`, true},

server/routes.go

@@ -251,6 +251,7 @@ func (s *Server) GenerateHandler(c *gin.Context) {
 
 		var b bytes.Buffer
 		if req.Context != nil {
+			slog.Warn("the context field is deprecated and will be removed in a future version of Ollama")
 			s, err := r.Detokenize(c.Request.Context(), req.Context)
 			if err != nil {
 				c.JSON(http.StatusInternalServerError, gin.H{"error": err.Error()})
@@ -1458,6 +1459,7 @@ func (s *Server) ChatHandler(c *gin.Context) {
 
 	prompt, images, err := chatPrompt(c.Request.Context(), m, r.Tokenize, opts, msgs, req.Tools)
 	if err != nil {
+		slog.Error("chat prompt error", "error", err)
 		c.JSON(http.StatusInternalServerError, gin.H{"error": err.Error()})
 		return
 	}
@@ -1467,6 +1469,8 @@ func (s *Server) ChatHandler(c *gin.Context) {
 	ch := make(chan any)
 	go func() {
 		defer close(ch)
+		var sb strings.Builder
+		var toolCallIndex int = 0
 		if err := r.Completion(c.Request.Context(), llm.CompletionRequest{
 			Prompt:  prompt,
 			Images:  images,
@@ -1492,7 +1496,37 @@ func (s *Server) ChatHandler(c *gin.Context) {
 				res.LoadDuration = checkpointLoaded.Sub(checkpointStart)
 			}
 
+			// TODO: tool call checking and filtering should be moved outside of this callback once streaming
+			// however this was a simple change for now without reworking streaming logic of this (and other)
+			// handlers
+			if req.Stream != nil && !*req.Stream || len(req.Tools) == 0 {
 				ch <- res
+				return
+			}
+
+			// Streaming tool calls:
+			// If tools are recognized, use a flag to track the sending of a tool downstream
+			// This ensures that content is cleared from the message on the last chunk sent
+			sb.WriteString(r.Content)
+			if toolCalls, ok := m.parseToolCalls(sb.String()); ok {
+				res.Message.ToolCalls = toolCalls
+				for i := range toolCalls {
+					toolCalls[i].Function.Index = toolCallIndex
+					toolCallIndex++
+				}
+				res.Message.Content = ""
+				sb.Reset()
+				ch <- res
+				return
+			}
+
+			if r.Done {
+				// Send any remaining content if no tool calls were detected
+				if toolCallIndex == 0 {
+					res.Message.Content = sb.String()
+				}
+				ch <- res
+			}
 		}); err != nil {
 			ch <- gin.H{"error": err.Error()}
 		}

server/routes_generate_test.go

@@ -8,6 +8,7 @@ import (
 	"io"
 	"net/http"
 	"strings"
+	"sync"
 	"testing"
 	"time"
 
@@ -25,10 +26,14 @@ type mockRunner struct {
 	// CompletionRequest is only valid until the next call to Completion
 	llm.CompletionRequest
 	llm.CompletionResponse
+	CompletionFn func(context.Context, llm.CompletionRequest, func(llm.CompletionResponse)) error
 }
 
-func (m *mockRunner) Completion(_ context.Context, r llm.CompletionRequest, fn func(r llm.CompletionResponse)) error {
+func (m *mockRunner) Completion(ctx context.Context, r llm.CompletionRequest, fn func(r llm.CompletionResponse)) error {
 	m.CompletionRequest = r
+	if m.CompletionFn != nil {
+		return m.CompletionFn(ctx, r, fn)
+	}
 	fn(m.CompletionResponse)
 	return nil
 }
@@ -88,9 +93,14 @@ func TestGenerateChat(t *testing.T) {
 		Model: "test",
 		Modelfile: fmt.Sprintf(`FROM %s
 		TEMPLATE """
-{{- if .System }}System: {{ .System }} {{ end }}
-{{- if .Prompt }}User: {{ .Prompt }} {{ end }}
-{{- if .Response }}Assistant: {{ .Response }} {{ end }}"""
+{{- if .Tools }}
+{{ .Tools }}
+{{ end }}
+{{- range .Messages }}
+{{- .Role }}: {{ .Content }}
+{{- range .ToolCalls }}{"name": "{{ .Function.Name }}", "arguments": {{ .Function.Arguments }}}
+{{- end }}
+{{ end }}"""
 `, createBinFile(t, llm.KV{
 			"general.architecture":          "llama",
 			"llama.block_count":             uint32(1),
@@ -263,7 +273,7 @@ func TestGenerateChat(t *testing.T) {
 			t.Errorf("expected status 200, got %d", w.Code)
 		}
 
-		if diff := cmp.Diff(mock.CompletionRequest.Prompt, "User: Hello! "); diff != "" {
+		if diff := cmp.Diff(mock.CompletionRequest.Prompt, "user: Hello!\n"); diff != "" {
 			t.Errorf("mismatch (-got +want):\n%s", diff)
 		}
 
@@ -292,7 +302,7 @@ func TestGenerateChat(t *testing.T) {
 			t.Errorf("expected status 200, got %d", w.Code)
 		}
 
-		if diff := cmp.Diff(mock.CompletionRequest.Prompt, "System: You are a helpful assistant. User: Hello! "); diff != "" {
+		if diff := cmp.Diff(mock.CompletionRequest.Prompt, "system: You are a helpful assistant.\nuser: Hello!\n"); diff != "" {
 			t.Errorf("mismatch (-got +want):\n%s", diff)
 		}
 
@@ -314,7 +324,7 @@ func TestGenerateChat(t *testing.T) {
 			t.Errorf("expected status 200, got %d", w.Code)
 		}
 
-		if diff := cmp.Diff(mock.CompletionRequest.Prompt, "System: You can perform magic tricks. User: Hello! "); diff != "" {
+		if diff := cmp.Diff(mock.CompletionRequest.Prompt, "system: You can perform magic tricks.\nuser: Hello!\n"); diff != "" {
 			t.Errorf("mismatch (-got +want):\n%s", diff)
 		}
 
@@ -337,12 +347,242 @@ func TestGenerateChat(t *testing.T) {
 			t.Errorf("expected status 200, got %d", w.Code)
 		}
 
-		if diff := cmp.Diff(mock.CompletionRequest.Prompt, "System: You are a helpful assistant. User: Hello! Assistant: I can help you with that. System: You can perform magic tricks. User: Help me write tests. "); diff != "" {
+		if diff := cmp.Diff(mock.CompletionRequest.Prompt, "system: You are a helpful assistant.\nuser: Hello!\nassistant: I can help you with that.\nsystem: You can perform magic tricks.\nuser: Help me write tests.\n"); diff != "" {
 			t.Errorf("mismatch (-got +want):\n%s", diff)
 		}
 
 		checkChatResponse(t, w.Body, "test-system", "Abra kadabra!")
 	})
+
+	t.Run("messages with tools (non-streaming)", func(t *testing.T) {
+		if w.Code != http.StatusOK {
+			t.Fatalf("failed to create test-system model: %d", w.Code)
+		}
+
+		tools := []api.Tool{
+			{
+				Type: "function",
+				Function: api.ToolFunction{
+					Name:        "get_weather",
+					Description: "Get the current weather",
+					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"`
+					}{
+						Type:     "object",
+						Required: []string{"location"},
+						Properties: map[string]struct {
+							Type        string   `json:"type"`
+							Description string   `json:"description"`
+							Enum        []string `json:"enum,omitempty"`
+						}{
+							"location": {
+								Type:        "string",
+								Description: "The city and state",
+							},
+							"unit": {
+								Type: "string",
+								Enum: []string{"celsius", "fahrenheit"},
+							},
+						},
+					},
+				},
+			},
+		}
+
+		mock.CompletionResponse = llm.CompletionResponse{
+			Content:            `{"name":"get_weather","arguments":{"location":"Seattle, WA","unit":"celsius"}}`,
+			Done:               true,
+			DoneReason:         "done",
+			PromptEvalCount:    1,
+			PromptEvalDuration: 1,
+			EvalCount:          1,
+			EvalDuration:       1,
+		}
+
+		streamRequest := true
+
+		w := createRequest(t, s.ChatHandler, api.ChatRequest{
+			Model: "test-system",
+			Messages: []api.Message{
+				{Role: "user", Content: "What's the weather in Seattle?"},
+			},
+			Tools:  tools,
+			Stream: &streamRequest,
+		})
+
+		if w.Code != http.StatusOK {
+			var errResp struct {
+				Error string `json:"error"`
+			}
+			if err := json.NewDecoder(w.Body).Decode(&errResp); err != nil {
+				t.Logf("Failed to decode error response: %v", err)
+			} else {
+				t.Logf("Error response: %s", errResp.Error)
+			}
+		}
+
+		if w.Code != http.StatusOK {
+			t.Errorf("expected status 200, got %d", w.Code)
+		}
+
+		var resp api.ChatResponse
+		if err := json.NewDecoder(w.Body).Decode(&resp); err != nil {
+			t.Fatal(err)
+		}
+
+		if resp.Message.ToolCalls == nil {
+			t.Error("expected tool calls, got nil")
+		}
+
+		expectedToolCall := api.ToolCall{
+			Function: api.ToolCallFunction{
+				Name: "get_weather",
+				Arguments: api.ToolCallFunctionArguments{
+					"location": "Seattle, WA",
+					"unit":     "celsius",
+				},
+			},
+		}
+
+		if diff := cmp.Diff(resp.Message.ToolCalls[0], expectedToolCall); diff != "" {
+			t.Errorf("tool call mismatch (-got +want):\n%s", diff)
+		}
+	})
+
+	t.Run("messages with tools (streaming)", func(t *testing.T) {
+		tools := []api.Tool{
+			{
+				Type: "function",
+				Function: api.ToolFunction{
+					Name:        "get_weather",
+					Description: "Get the current weather",
+					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"`
+					}{
+						Type:     "object",
+						Required: []string{"location"},
+						Properties: map[string]struct {
+							Type        string   `json:"type"`
+							Description string   `json:"description"`
+							Enum        []string `json:"enum,omitempty"`
+						}{
+							"location": {
+								Type:        "string",
+								Description: "The city and state",
+							},
+							"unit": {
+								Type: "string",
+								Enum: []string{"celsius", "fahrenheit"},
+							},
+						},
+					},
+				},
+			},
+		}
+
+		// Simulate streaming response with multiple chunks
+		var wg sync.WaitGroup
+		wg.Add(1)
+
+		mock.CompletionFn = func(ctx context.Context, r llm.CompletionRequest, fn func(r llm.CompletionResponse)) error {
+			defer wg.Done()
+
+			// Send chunks with small delays to simulate streaming
+			responses := []llm.CompletionResponse{
+				{
+					Content:            `{"name":"get_`,
+					Done:               false,
+					PromptEvalCount:    1,
+					PromptEvalDuration: 1,
+				},
+				{
+					Content:            `weather","arguments":{"location":"Seattle`,
+					Done:               false,
+					PromptEvalCount:    2,
+					PromptEvalDuration: 1,
+				},
+				{
+					Content:            `, WA","unit":"celsius"}}`,
+					Done:               true,
+					DoneReason:         "tool_call",
+					PromptEvalCount:    3,
+					PromptEvalDuration: 1,
+				},
+			}
+
+			for _, resp := range responses {
+				select {
+				case <-ctx.Done():
+					return ctx.Err()
+				default:
+					fn(resp)
+					time.Sleep(10 * time.Millisecond) // Small delay between chunks
+				}
+			}
+			return nil
+		}
+
+		w := createRequest(t, s.ChatHandler, api.ChatRequest{
+			Model: "test-system",
+			Messages: []api.Message{
+				{Role: "user", Content: "What's the weather in Seattle?"},
+			},
+			Tools:  tools,
+			Stream: &stream,
+		})
+
+		wg.Wait()
+
+		if w.Code != http.StatusOK {
+			t.Errorf("expected status 200, got %d", w.Code)
+		}
+
+		// Read and validate the streamed responses
+		decoder := json.NewDecoder(w.Body)
+		var finalToolCall api.ToolCall
+
+		for {
+			var resp api.ChatResponse
+			if err := decoder.Decode(&resp); err == io.EOF {
+				break
+			} else if err != nil {
+				t.Fatal(err)
+			}
+
+			if resp.Done {
+				if len(resp.Message.ToolCalls) != 1 {
+					t.Errorf("expected 1 tool call in final response, got %d", len(resp.Message.ToolCalls))
+				}
+				finalToolCall = resp.Message.ToolCalls[0]
+			}
+		}
+
+		expectedToolCall := api.ToolCall{
+			Function: api.ToolCallFunction{
+				Name: "get_weather",
+				Arguments: api.ToolCallFunctionArguments{
+					"location": "Seattle, WA",
+					"unit":     "celsius",
+				},
+			},
+		}
+
+		if diff := cmp.Diff(finalToolCall, expectedToolCall); diff != "" {
+			t.Errorf("final tool call mismatch (-got +want):\n%s", diff)
+		}
+	})
 }
 
 func TestGenerate(t *testing.T) {