Files
ollama37/integration/api_test.go
Shang Chieh Tseng ef14fb5b26 Sync with upstream ollama/ollama and restore Tesla K80 (compute 3.7) support
This commit represents a complete rework after pulling the latest changes from
official ollama/ollama repository and re-applying Tesla K80 compatibility patches.

## Key Changes

### CUDA Compute Capability 3.7 Support (Tesla K80)
- Added sm_37 (compute 3.7) to CMAKE_CUDA_ARCHITECTURES in CMakeLists.txt
- Updated CMakePresets.json to include compute 3.7 in "CUDA 11" preset
- Using 37-virtual (PTX with JIT compilation) for maximum compatibility

### Legacy Toolchain Compatibility
- **NVIDIA Driver**: 470.256.02 (last version supporting Kepler/K80)
- **CUDA Version**: 11.4.4 (last CUDA 11.x supporting compute 3.7)
- **GCC Version**: 10.5.0 (required by CUDA 11.4 host_config.h)

### CPU Architecture Trade-offs
Due to GCC 10.5 limitation, sacrificed newer CPU optimizations:
- Alderlake CPU variant enabled WITHOUT AVX_VNNI (requires GCC 11+)
- Still supports: SSE4.2, AVX, F16C, AVX2, BMI2, FMA
- Performance impact: ~3-7% on newer CPUs (acceptable for K80 compatibility)

### Build System Updates
- Modified ml/backend/ggml/ggml/src/ggml-cuda/CMakeLists.txt for compute 3.7
- Added -Wno-deprecated-gpu-targets flag to suppress warnings
- Updated ml/backend/ggml/ggml/src/CMakeLists.txt for Alderlake without AVX_VNNI

### Upstream Sync
Merged latest llama.cpp changes including:
- Enhanced KV cache management with ISWA and hybrid memory support
- Improved multi-modal support (mtmd framework)
- New model architectures (Gemma3, Llama4, Qwen3, etc.)
- GPU backend improvements for CUDA, Metal, and ROCm
- Updated quantization support and GGUF format handling

### Documentation
- Updated CLAUDE.md with comprehensive build instructions
- Documented toolchain constraints and CPU architecture trade-offs
- Removed outdated CI/CD workflows (tesla-k80-*.yml)
- Cleaned up temporary development artifacts

## Rationale

This fork maintains Tesla K80 GPU support (compute 3.7) which was dropped in
official Ollama due to legacy driver/CUDA requirements. The toolchain constraint
creates a deadlock:
- K80 → Driver 470 → CUDA 11.4 → GCC 10 → No AVX_VNNI

We accept the loss of cutting-edge CPU optimizations to enable running modern
LLMs on legacy but still capable Tesla K80 hardware (12GB VRAM per GPU).

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-05 14:03:05 +08:00

384 lines
10 KiB
Go

//go:build integration
package integration
import (
"bytes"
"context"
"fmt"
"math/rand"
"strings"
"testing"
"time"
"github.com/ollama/ollama/api"
)
func TestAPIGenerate(t *testing.T) {
initialTimeout := 60 * time.Second
streamTimeout := 30 * time.Second
ctx, cancel := context.WithTimeout(context.Background(), 1*time.Minute)
defer cancel()
// Set up the test data
req := api.GenerateRequest{
Model: smol,
Prompt: blueSkyPrompt,
Options: map[string]interface{}{
"temperature": 0,
"seed": 123,
},
}
client, _, cleanup := InitServerConnection(ctx, t)
defer cleanup()
if err := PullIfMissing(ctx, client, req.Model); err != nil {
t.Fatalf("pull failed %s", err)
}
tests := []struct {
name string
stream bool
}{
{
name: "stream",
stream: true,
},
{
name: "no_stream",
stream: false,
},
}
for _, test := range tests {
t.Run(test.name, func(t *testing.T) {
stallTimer := time.NewTimer(initialTimeout)
var buf bytes.Buffer
fn := func(response api.GenerateResponse) error {
// Fields that must always be present
if response.Model == "" {
t.Errorf("response missing model: %#v", response)
}
if response.Done {
// Required fields for final updates:
if response.DoneReason == "" && *req.Stream {
// TODO - is the lack of done reason on non-stream a bug?
t.Errorf("final response missing done_reason: %#v", response)
}
if response.Metrics.TotalDuration == 0 {
t.Errorf("final response missing total_duration: %#v", response)
}
if response.Metrics.LoadDuration == 0 {
t.Errorf("final response missing load_duration: %#v", response)
}
if response.Metrics.PromptEvalDuration == 0 {
t.Errorf("final response missing prompt_eval_duration: %#v", response)
}
if response.Metrics.EvalCount == 0 {
t.Errorf("final response missing eval_count: %#v", response)
}
if response.Metrics.EvalDuration == 0 {
t.Errorf("final response missing eval_duration: %#v", response)
}
if len(response.Context) == 0 {
t.Errorf("final response missing context: %#v", response)
}
// Note: caching can result in no prompt eval count, so this can't be verified reliably
// if response.Metrics.PromptEvalCount == 0 {
// t.Errorf("final response missing prompt_eval_count: %#v", response)
// }
} // else incremental response, nothing to check right now...
buf.Write([]byte(response.Response))
if !stallTimer.Reset(streamTimeout) {
return fmt.Errorf("stall was detected while streaming response, aborting")
}
return nil
}
done := make(chan int)
var genErr error
go func() {
req.Stream = &test.stream
req.Options["seed"] = rand.Int() // bust cache for prompt eval results
genErr = client.Generate(ctx, &req, fn)
done <- 0
}()
select {
case <-stallTimer.C:
if buf.Len() == 0 {
t.Errorf("generate never started. Timed out after :%s", initialTimeout.String())
} else {
t.Errorf("generate stalled. Response so far:%s", buf.String())
}
case <-done:
if genErr != nil {
t.Fatalf("failed with %s request prompt %s ", req.Model, req.Prompt)
}
// Verify the response contains the expected data
response := buf.String()
atLeastOne := false
for _, resp := range blueSkyExpected {
if strings.Contains(strings.ToLower(response), resp) {
atLeastOne = true
break
}
}
if !atLeastOne {
t.Errorf("none of %v found in %s", blueSkyExpected, response)
}
case <-ctx.Done():
t.Error("outer test context done while waiting for generate")
}
})
}
// Validate PS while we're at it...
resp, err := client.ListRunning(ctx)
if err != nil {
t.Fatalf("list models API error: %s", err)
}
if resp == nil || len(resp.Models) == 0 {
t.Fatalf("list models API returned empty list while model should still be loaded")
}
// Find the model we just loaded and verify some attributes
found := false
for _, model := range resp.Models {
if strings.Contains(model.Name, req.Model) {
found = true
if model.Model == "" {
t.Errorf("model field omitted: %#v", model)
}
if model.Size == 0 {
t.Errorf("size omitted: %#v", model)
}
if model.Digest == "" {
t.Errorf("digest omitted: %#v", model)
}
verifyModelDetails(t, model.Details)
var nilTime time.Time
if model.ExpiresAt == nilTime {
t.Errorf("expires_at omitted: %#v", model)
}
// SizeVRAM could be zero.
}
}
if !found {
t.Errorf("unable to locate running model: %#v", resp)
}
}
func TestAPIChat(t *testing.T) {
initialTimeout := 60 * time.Second
streamTimeout := 30 * time.Second
ctx, cancel := context.WithTimeout(context.Background(), 1*time.Minute)
defer cancel()
// Set up the test data
req := api.ChatRequest{
Model: smol,
Messages: []api.Message{
{
Role: "user",
Content: blueSkyPrompt,
},
},
Options: map[string]interface{}{
"temperature": 0,
"seed": 123,
},
}
client, _, cleanup := InitServerConnection(ctx, t)
defer cleanup()
if err := PullIfMissing(ctx, client, req.Model); err != nil {
t.Fatalf("pull failed %s", err)
}
tests := []struct {
name string
stream bool
}{
{
name: "stream",
stream: true,
},
{
name: "no_stream",
stream: false,
},
}
for _, test := range tests {
t.Run(test.name, func(t *testing.T) {
stallTimer := time.NewTimer(initialTimeout)
var buf bytes.Buffer
fn := func(response api.ChatResponse) error {
// Fields that must always be present
if response.Model == "" {
t.Errorf("response missing model: %#v", response)
}
if response.Done {
// Required fields for final updates:
var nilTime time.Time
if response.CreatedAt == nilTime {
t.Errorf("final response missing total_duration: %#v", response)
}
if response.DoneReason == "" {
t.Errorf("final response missing done_reason: %#v", response)
}
if response.Metrics.TotalDuration == 0 {
t.Errorf("final response missing total_duration: %#v", response)
}
if response.Metrics.LoadDuration == 0 {
t.Errorf("final response missing load_duration: %#v", response)
}
if response.Metrics.PromptEvalDuration == 0 {
t.Errorf("final response missing prompt_eval_duration: %#v", response)
}
if response.Metrics.EvalCount == 0 {
t.Errorf("final response missing eval_count: %#v", response)
}
if response.Metrics.EvalDuration == 0 {
t.Errorf("final response missing eval_duration: %#v", response)
}
if response.Metrics.PromptEvalCount == 0 {
t.Errorf("final response missing prompt_eval_count: %#v", response)
}
} // else incremental response, nothing to check right now...
buf.Write([]byte(response.Message.Content))
if !stallTimer.Reset(streamTimeout) {
return fmt.Errorf("stall was detected while streaming response, aborting")
}
return nil
}
done := make(chan int)
var genErr error
go func() {
req.Stream = &test.stream
req.Options["seed"] = rand.Int() // bust cache for prompt eval results
genErr = client.Chat(ctx, &req, fn)
done <- 0
}()
select {
case <-stallTimer.C:
if buf.Len() == 0 {
t.Errorf("chat never started. Timed out after :%s", initialTimeout.String())
} else {
t.Errorf("chat stalled. Response so far:%s", buf.String())
}
case <-done:
if genErr != nil {
t.Fatalf("failed with %s request prompt %v", req.Model, req.Messages)
}
// Verify the response contains the expected data
response := buf.String()
atLeastOne := false
for _, resp := range blueSkyExpected {
if strings.Contains(strings.ToLower(response), resp) {
atLeastOne = true
break
}
}
if !atLeastOne {
t.Errorf("none of %v found in %s", blueSkyExpected, response)
}
case <-ctx.Done():
t.Error("outer test context done while waiting for chat")
}
})
}
}
func TestAPIListModels(t *testing.T) {
ctx, cancel := context.WithTimeout(context.Background(), 10*time.Second)
defer cancel()
client, _, cleanup := InitServerConnection(ctx, t)
defer cleanup()
// Make sure we have at least one model so an empty list can be considered a failure
if err := PullIfMissing(ctx, client, smol); err != nil {
t.Fatalf("pull failed %s", err)
}
resp, err := client.List(ctx)
if err != nil {
t.Fatalf("unable to list models: %s", err)
}
if len(resp.Models) == 0 {
t.Fatalf("list should not be empty")
}
model := resp.Models[0]
if model.Name == "" {
t.Errorf("first model name empty: %#v", model)
}
var nilTime time.Time
if model.ModifiedAt == nilTime {
t.Errorf("first model modified_at empty: %#v", model)
}
if model.Size == 0 {
t.Errorf("first model size empty: %#v", model)
}
if model.Digest == "" {
t.Errorf("first model digest empty: %#v", model)
}
verifyModelDetails(t, model.Details)
}
func verifyModelDetails(t *testing.T, details api.ModelDetails) {
if details.Format == "" {
t.Errorf("first model details.format empty: %#v", details)
}
if details.Family == "" {
t.Errorf("first model details.family empty: %#v", details)
}
if details.ParameterSize == "" {
t.Errorf("first model details.parameter_size empty: %#v", details)
}
if details.QuantizationLevel == "" {
t.Errorf("first model details.quantization_level empty: %#v", details)
}
}
func TestAPIShowModel(t *testing.T) {
modelName := "llama3.2"
ctx, cancel := context.WithTimeout(context.Background(), 1*time.Minute)
defer cancel()
client, _, cleanup := InitServerConnection(ctx, t)
defer cleanup()
if err := PullIfMissing(ctx, client, modelName); err != nil {
t.Fatalf("pull failed %s", err)
}
resp, err := client.Show(ctx, &api.ShowRequest{Name: modelName})
if err != nil {
t.Fatalf("unable to show model: %s", err)
}
if resp.License == "" {
t.Errorf("%s missing license: %#v", modelName, resp)
}
if resp.Modelfile == "" {
t.Errorf("%s missing modelfile: %#v", modelName, resp)
}
if resp.Parameters == "" {
t.Errorf("%s missing parameters: %#v", modelName, resp)
}
if resp.Template == "" {
t.Errorf("%s missing template: %#v", modelName, resp)
}
// llama3 omits system
verifyModelDetails(t, resp.Details)
// llama3 ommits messages
if len(resp.ModelInfo) == 0 {
t.Errorf("%s missing model_info: %#v", modelName, resp)
}
// llama3 omits projectors
var nilTime time.Time
if resp.ModifiedAt == nilTime {
t.Errorf("%s missing modified_at: %#v", modelName, resp)
}
}