mirror of
https://github.com/dogkeeper886/ollama37.git
synced 2025-12-10 15:57:04 +00:00
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with comprehensive build instructions - Documented toolchain constraints and CPU architecture trade-offs - Removed outdated CI/CD workflows (tesla-k80-*.yml) - Cleaned up temporary development artifacts ## Rationale This fork maintains Tesla K80 GPU support (compute 3.7) which was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>
384 lines
10 KiB
Go
384 lines
10 KiB
Go
//go:build integration
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package integration
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import (
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"bytes"
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"context"
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"fmt"
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"math/rand"
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"strings"
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"testing"
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"time"
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"github.com/ollama/ollama/api"
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)
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func TestAPIGenerate(t *testing.T) {
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initialTimeout := 60 * time.Second
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streamTimeout := 30 * time.Second
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ctx, cancel := context.WithTimeout(context.Background(), 1*time.Minute)
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defer cancel()
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// Set up the test data
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req := api.GenerateRequest{
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Model: smol,
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Prompt: blueSkyPrompt,
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Options: map[string]interface{}{
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"temperature": 0,
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"seed": 123,
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},
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}
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client, _, cleanup := InitServerConnection(ctx, t)
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defer cleanup()
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if err := PullIfMissing(ctx, client, req.Model); err != nil {
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t.Fatalf("pull failed %s", err)
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}
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tests := []struct {
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name string
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stream bool
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}{
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{
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name: "stream",
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stream: true,
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},
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{
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name: "no_stream",
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stream: false,
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},
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}
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for _, test := range tests {
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t.Run(test.name, func(t *testing.T) {
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stallTimer := time.NewTimer(initialTimeout)
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var buf bytes.Buffer
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fn := func(response api.GenerateResponse) error {
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// Fields that must always be present
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if response.Model == "" {
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t.Errorf("response missing model: %#v", response)
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}
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if response.Done {
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// Required fields for final updates:
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if response.DoneReason == "" && *req.Stream {
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// TODO - is the lack of done reason on non-stream a bug?
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t.Errorf("final response missing done_reason: %#v", response)
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}
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if response.Metrics.TotalDuration == 0 {
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t.Errorf("final response missing total_duration: %#v", response)
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}
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if response.Metrics.LoadDuration == 0 {
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t.Errorf("final response missing load_duration: %#v", response)
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}
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if response.Metrics.PromptEvalDuration == 0 {
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t.Errorf("final response missing prompt_eval_duration: %#v", response)
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}
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if response.Metrics.EvalCount == 0 {
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t.Errorf("final response missing eval_count: %#v", response)
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}
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if response.Metrics.EvalDuration == 0 {
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t.Errorf("final response missing eval_duration: %#v", response)
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}
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if len(response.Context) == 0 {
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t.Errorf("final response missing context: %#v", response)
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}
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// Note: caching can result in no prompt eval count, so this can't be verified reliably
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// if response.Metrics.PromptEvalCount == 0 {
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// t.Errorf("final response missing prompt_eval_count: %#v", response)
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// }
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} // else incremental response, nothing to check right now...
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buf.Write([]byte(response.Response))
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if !stallTimer.Reset(streamTimeout) {
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return fmt.Errorf("stall was detected while streaming response, aborting")
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}
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return nil
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}
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done := make(chan int)
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var genErr error
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go func() {
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req.Stream = &test.stream
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req.Options["seed"] = rand.Int() // bust cache for prompt eval results
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genErr = client.Generate(ctx, &req, fn)
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done <- 0
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}()
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select {
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case <-stallTimer.C:
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if buf.Len() == 0 {
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t.Errorf("generate never started. Timed out after :%s", initialTimeout.String())
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} else {
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t.Errorf("generate stalled. Response so far:%s", buf.String())
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}
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case <-done:
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if genErr != nil {
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t.Fatalf("failed with %s request prompt %s ", req.Model, req.Prompt)
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}
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// Verify the response contains the expected data
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response := buf.String()
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atLeastOne := false
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for _, resp := range blueSkyExpected {
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if strings.Contains(strings.ToLower(response), resp) {
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atLeastOne = true
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break
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}
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}
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if !atLeastOne {
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t.Errorf("none of %v found in %s", blueSkyExpected, response)
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}
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case <-ctx.Done():
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t.Error("outer test context done while waiting for generate")
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}
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})
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}
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// Validate PS while we're at it...
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resp, err := client.ListRunning(ctx)
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if err != nil {
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t.Fatalf("list models API error: %s", err)
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}
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if resp == nil || len(resp.Models) == 0 {
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t.Fatalf("list models API returned empty list while model should still be loaded")
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}
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// Find the model we just loaded and verify some attributes
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found := false
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for _, model := range resp.Models {
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if strings.Contains(model.Name, req.Model) {
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found = true
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if model.Model == "" {
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t.Errorf("model field omitted: %#v", model)
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}
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if model.Size == 0 {
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t.Errorf("size omitted: %#v", model)
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}
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if model.Digest == "" {
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t.Errorf("digest omitted: %#v", model)
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}
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verifyModelDetails(t, model.Details)
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var nilTime time.Time
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if model.ExpiresAt == nilTime {
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t.Errorf("expires_at omitted: %#v", model)
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}
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// SizeVRAM could be zero.
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}
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}
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if !found {
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t.Errorf("unable to locate running model: %#v", resp)
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}
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}
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func TestAPIChat(t *testing.T) {
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initialTimeout := 60 * time.Second
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streamTimeout := 30 * time.Second
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ctx, cancel := context.WithTimeout(context.Background(), 1*time.Minute)
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defer cancel()
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// Set up the test data
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req := api.ChatRequest{
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Model: smol,
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Messages: []api.Message{
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{
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Role: "user",
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Content: blueSkyPrompt,
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},
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},
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Options: map[string]interface{}{
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"temperature": 0,
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"seed": 123,
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},
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}
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client, _, cleanup := InitServerConnection(ctx, t)
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defer cleanup()
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if err := PullIfMissing(ctx, client, req.Model); err != nil {
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t.Fatalf("pull failed %s", err)
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}
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tests := []struct {
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name string
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stream bool
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}{
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{
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name: "stream",
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stream: true,
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},
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{
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name: "no_stream",
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stream: false,
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},
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}
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for _, test := range tests {
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t.Run(test.name, func(t *testing.T) {
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stallTimer := time.NewTimer(initialTimeout)
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var buf bytes.Buffer
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fn := func(response api.ChatResponse) error {
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// Fields that must always be present
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if response.Model == "" {
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t.Errorf("response missing model: %#v", response)
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}
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if response.Done {
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// Required fields for final updates:
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var nilTime time.Time
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if response.CreatedAt == nilTime {
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t.Errorf("final response missing total_duration: %#v", response)
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}
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if response.DoneReason == "" {
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t.Errorf("final response missing done_reason: %#v", response)
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}
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if response.Metrics.TotalDuration == 0 {
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t.Errorf("final response missing total_duration: %#v", response)
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}
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if response.Metrics.LoadDuration == 0 {
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t.Errorf("final response missing load_duration: %#v", response)
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}
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if response.Metrics.PromptEvalDuration == 0 {
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t.Errorf("final response missing prompt_eval_duration: %#v", response)
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}
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if response.Metrics.EvalCount == 0 {
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t.Errorf("final response missing eval_count: %#v", response)
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}
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if response.Metrics.EvalDuration == 0 {
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t.Errorf("final response missing eval_duration: %#v", response)
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}
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if response.Metrics.PromptEvalCount == 0 {
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t.Errorf("final response missing prompt_eval_count: %#v", response)
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}
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} // else incremental response, nothing to check right now...
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buf.Write([]byte(response.Message.Content))
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if !stallTimer.Reset(streamTimeout) {
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return fmt.Errorf("stall was detected while streaming response, aborting")
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}
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return nil
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}
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done := make(chan int)
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var genErr error
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go func() {
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req.Stream = &test.stream
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req.Options["seed"] = rand.Int() // bust cache for prompt eval results
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genErr = client.Chat(ctx, &req, fn)
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done <- 0
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}()
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select {
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case <-stallTimer.C:
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if buf.Len() == 0 {
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t.Errorf("chat never started. Timed out after :%s", initialTimeout.String())
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} else {
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t.Errorf("chat stalled. Response so far:%s", buf.String())
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}
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case <-done:
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if genErr != nil {
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t.Fatalf("failed with %s request prompt %v", req.Model, req.Messages)
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}
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// Verify the response contains the expected data
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response := buf.String()
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atLeastOne := false
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for _, resp := range blueSkyExpected {
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if strings.Contains(strings.ToLower(response), resp) {
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atLeastOne = true
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break
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}
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}
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if !atLeastOne {
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t.Errorf("none of %v found in %s", blueSkyExpected, response)
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}
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case <-ctx.Done():
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t.Error("outer test context done while waiting for chat")
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}
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})
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}
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}
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func TestAPIListModels(t *testing.T) {
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ctx, cancel := context.WithTimeout(context.Background(), 10*time.Second)
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defer cancel()
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client, _, cleanup := InitServerConnection(ctx, t)
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defer cleanup()
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// Make sure we have at least one model so an empty list can be considered a failure
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if err := PullIfMissing(ctx, client, smol); err != nil {
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t.Fatalf("pull failed %s", err)
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}
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resp, err := client.List(ctx)
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if err != nil {
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t.Fatalf("unable to list models: %s", err)
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}
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if len(resp.Models) == 0 {
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t.Fatalf("list should not be empty")
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}
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model := resp.Models[0]
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if model.Name == "" {
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t.Errorf("first model name empty: %#v", model)
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}
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var nilTime time.Time
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if model.ModifiedAt == nilTime {
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t.Errorf("first model modified_at empty: %#v", model)
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}
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if model.Size == 0 {
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t.Errorf("first model size empty: %#v", model)
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}
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if model.Digest == "" {
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t.Errorf("first model digest empty: %#v", model)
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}
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verifyModelDetails(t, model.Details)
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}
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func verifyModelDetails(t *testing.T, details api.ModelDetails) {
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if details.Format == "" {
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t.Errorf("first model details.format empty: %#v", details)
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}
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if details.Family == "" {
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t.Errorf("first model details.family empty: %#v", details)
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}
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if details.ParameterSize == "" {
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t.Errorf("first model details.parameter_size empty: %#v", details)
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}
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if details.QuantizationLevel == "" {
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t.Errorf("first model details.quantization_level empty: %#v", details)
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}
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}
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func TestAPIShowModel(t *testing.T) {
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modelName := "llama3.2"
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ctx, cancel := context.WithTimeout(context.Background(), 1*time.Minute)
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defer cancel()
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client, _, cleanup := InitServerConnection(ctx, t)
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defer cleanup()
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if err := PullIfMissing(ctx, client, modelName); err != nil {
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t.Fatalf("pull failed %s", err)
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}
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resp, err := client.Show(ctx, &api.ShowRequest{Name: modelName})
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if err != nil {
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t.Fatalf("unable to show model: %s", err)
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}
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if resp.License == "" {
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t.Errorf("%s missing license: %#v", modelName, resp)
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}
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if resp.Modelfile == "" {
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t.Errorf("%s missing modelfile: %#v", modelName, resp)
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}
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if resp.Parameters == "" {
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t.Errorf("%s missing parameters: %#v", modelName, resp)
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}
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if resp.Template == "" {
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t.Errorf("%s missing template: %#v", modelName, resp)
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}
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// llama3 omits system
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verifyModelDetails(t, resp.Details)
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// llama3 ommits messages
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if len(resp.ModelInfo) == 0 {
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t.Errorf("%s missing model_info: %#v", modelName, resp)
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}
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// llama3 omits projectors
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var nilTime time.Time
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if resp.ModifiedAt == nilTime {
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t.Errorf("%s missing modified_at: %#v", modelName, resp)
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}
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}
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