Request and model concurrency

This change adds support for multiple concurrent requests, as well as
loading multiple models by spawning multiple runners. The default
settings are currently set at 1 concurrent request per model and only 1
loaded model at a time, but these can be adjusted by setting
OLLAMA_NUM_PARALLEL and OLLAMA_MAX_LOADED_MODELS.

integration/concurrency_test.go

@@ -0,0 +1,225 @@
+//go:build integration
+
+package integration
+
+import (
+	"context"
+	"log/slog"
+	"os"
+	"strconv"
+	"sync"
+	"testing"
+	"time"
+
+	"github.com/ollama/ollama/api"
+	"github.com/stretchr/testify/require"
+)
+
+func TestMultiModelConcurrency(t *testing.T) {
+	var (
+		req = [2]api.GenerateRequest{
+			{
+				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,
+				Options: map[string]interface{}{
+					"seed":        42,
+					"temperature": 0.0,
+				},
+			},
+		}
+		resp = [2][]string{
+			[]string{"sunlight"},
+			[]string{"england", "english", "massachusetts", "pilgrims"},
+		}
+	)
+	var wg sync.WaitGroup
+	wg.Add(len(req))
+	ctx, cancel := context.WithTimeout(context.Background(), time.Second*120)
+	defer cancel()
+	for i := 0; i < len(req); i++ {
+		go func(i int) {
+			defer wg.Done()
+			GenerateTestHelper(ctx, t, req[i], resp[i])
+		}(i)
+	}
+	wg.Wait()
+}
+
+func TestIntegrationConcurrentPredictOrcaMini(t *testing.T) {
+	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, 5*time.Second)
+
+	var wg sync.WaitGroup
+	wg.Add(len(req))
+	for i := 0; i < len(req); i++ {
+		go func(i int) {
+			defer wg.Done()
+			for j := 0; j < 5; j++ {
+				slog.Info("Starting", "req", i, "iter", j)
+				// 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], 90*time.Second, 5*time.Second)
+			}
+		}(i)
+	}
+	wg.Wait()
+}
+
+// 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")
+	if vram == "" {
+		t.Skip("OLLAMA_MAX_VRAM not specified, can't pick the right models for the stress test")
+	}
+	max, err := strconv.ParseUint(vram, 10, 64)
+	require.NoError(t, err)
+	const MB = uint64(1024 * 1024)
+	type model struct {
+		name string
+		size uint64 // Approximate amount of VRAM they typically use when fully loaded in VRAM
+	}
+
+	smallModels := []model{
+		{
+			name: "orca-mini",
+			size: 2992 * MB,
+		},
+		{
+			name: "phi",
+			size: 2616 * MB,
+		},
+		{
+			name: "gemma:2b",
+			size: 2364 * MB,
+		},
+		{
+			name: "stable-code:3b",
+			size: 2608 * MB,
+		},
+		{
+			name: "starcoder2:3b",
+			size: 2166 * MB,
+		},
+	}
+	mediumModels := []model{
+		{
+			name: "llama2",
+			size: 5118 * MB,
+		},
+		{
+			name: "mistral",
+			size: 4620 * MB,
+		},
+		{
+			name: "orca-mini:7b",
+			size: 5118 * MB,
+		},
+		{
+			name: "dolphin-mistral",
+			size: 4620 * MB,
+		},
+		{
+			name: "gemma:7b",
+			size: 5000 * MB,
+		},
+		// TODO - uncomment this once #3565 is merged and this is rebased on it
+		// {
+		// 	name: "codellama:7b",
+		// 	size: 5118 * MB,
+		// },
+	}
+
+	// These seem to be too slow to be useful...
+	// largeModels := []model{
+	// 	{
+	// 		name: "llama2:13b",
+	// 		size: 7400 * MB,
+	// 	},
+	// 	{
+	// 		name: "codellama:13b",
+	// 		size: 7400 * MB,
+	// 	},
+	// 	{
+	// 		name: "orca-mini:13b",
+	// 		size: 7400 * MB,
+	// 	},
+	// 	{
+	// 		name: "gemma:7b",
+	// 		size: 5000 * MB,
+	// 	},
+	// 	{
+	// 		name: "starcoder2:15b",
+	// 		size: 9100 * MB,
+	// 	},
+	// }
+
+	var chosenModels []model
+	switch {
+	case max < 10000*MB:
+		slog.Info("selecting small models")
+		chosenModels = smallModels
+	// case max < 30000*MB:
+	default:
+		slog.Info("selecting medium models")
+		chosenModels = mediumModels
+		// default:
+		// 	slog.Info("selecting large models")
+		// 	chosenModels = largModels
+	}
+
+	req, resp := GenerateRequests()
+
+	for i := range req {
+		if i > len(chosenModels) {
+			break
+		}
+		req[i].Model = chosenModels[i].name
+	}
+
+	ctx, cancel := context.WithTimeout(context.Background(), 15*time.Minute) // TODO baseline -- 10m too short
+	defer cancel()
+	client, _, cleanup := InitServerConnection(ctx, t)
+	defer cleanup()
+
+	// Make sure all the models are pulled before we get started
+	for _, r := range req {
+		require.NoError(t, PullIfMissing(ctx, client, r.Model))
+	}
+
+	var wg sync.WaitGroup
+	consumed := uint64(256 * MB) // Assume some baseline usage
+	for i := 0; i < len(req); i++ {
+		// Always get at least 2 models, but dont' overshoot VRAM too much or we'll take too long
+		if i > 1 && consumed > max {
+			slog.Info("achieved target vram exhaustion", "count", i, "vramMB", max/1024/1024, "modelsMB", consumed/1024/1024)
+			break
+		}
+		consumed += chosenModels[i].size
+		slog.Info("target vram", "count", i, "vramMB", max/1024/1024, "modelsMB", consumed/1024/1024)
+
+		wg.Add(1)
+		go func(i int) {
+			defer wg.Done()
+			for j := 0; j < 3; j++ {
+				slog.Info("Starting", "req", i, "iter", j, "model", req[i].Model)
+				DoGenerate(ctx, t, client, req[i], resp[i], 90*time.Second, 5*time.Second)
+			}
+		}(i)
+	}
+	wg.Wait()
+}