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* create: add server-side MLX imports and drop GGUF conversion Support safetensors imports through the MLX create pipeline both locally and on the server, including remote upload/staging, draft layer handling, cancellation propagation, transfer limits, and shared manifest/blob writing. Limit GGUF create to wrapping existing GGUF inputs into Ollama manifests. Remove the in-tree safetensors-to-GGUF converter, server quantization path, and converter-only dependencies so GGUF conversion and quantization stay in llama.cpp tooling. Keep the MLX path focused on supported safetensors model creation with validation before MLX work, and expose that flow without the --experimental CLI gate. * address comments * add client side gguf create fast path * address comments * rebase adjustments
141 lines
3.9 KiB
Go
141 lines
3.9 KiB
Go
package server
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import (
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"bytes"
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"context"
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"net/http"
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"testing"
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"time"
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"github.com/gin-gonic/gin"
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"github.com/ollama/ollama/api"
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gguftest "github.com/ollama/ollama/internal/testutil/gguf"
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"github.com/ollama/ollama/llm"
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)
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// malformedToolCall closes <parameter> with </function>, which the qwen3.5
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// parser rejects.
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const malformedToolCall = "<think>\nthinking\n</think>\n\n<tool_call>\n<function=write_file>\n<parameter=path>\nprobe.txt\n</function>\n</tool_call>"
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func TestChatParseErrorMidStreamDoesNotWedge(t *testing.T) {
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gin.SetMode(gin.TestMode)
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secondChunkReturned := make(chan struct{})
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mock := mockRunner{
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CompletionFn: func(ctx context.Context, r llm.CompletionRequest, fn func(llm.CompletionResponse)) error {
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fn(llm.CompletionResponse{Content: malformedToolCall})
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// The chunk after the failed parse is the one that wedges.
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fn(llm.CompletionResponse{Content: "trailing"})
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close(secondChunkReturned)
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fn(llm.CompletionResponse{Done: true, DoneReason: llm.DoneReasonStop})
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return nil
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},
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}
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s := newServerWithMockRunner(t, &mock)
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createParserModel(t, s, "parse-wedge", "qwen3.5")
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stream := false
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done := make(chan struct{})
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go func() {
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defer close(done)
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w := createRequest(t, s.ChatHandler, api.ChatRequest{
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Model: "parse-wedge",
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Messages: []api.Message{{Role: "user", Content: "hello"}},
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Stream: &stream,
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})
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if w.Code != http.StatusInternalServerError {
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t.Errorf("expected 500 from parse failure, got %d: %s", w.Code, w.Body.String())
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}
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}()
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select {
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case <-secondChunkReturned:
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case <-time.After(5 * time.Second):
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t.Fatal("completion callback blocked after a parse error")
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}
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select {
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case <-done:
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case <-time.After(5 * time.Second):
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t.Fatal("chat handler did not return after a parse error")
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}
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}
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func TestGenerateParseErrorMidStreamDoesNotWedge(t *testing.T) {
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gin.SetMode(gin.TestMode)
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secondChunkReturned := make(chan struct{})
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mock := mockRunner{
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CompletionFn: func(ctx context.Context, r llm.CompletionRequest, fn func(llm.CompletionResponse)) error {
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fn(llm.CompletionResponse{Content: malformedToolCall})
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fn(llm.CompletionResponse{Content: "trailing"})
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close(secondChunkReturned)
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fn(llm.CompletionResponse{Done: true, DoneReason: llm.DoneReasonStop})
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return nil
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},
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}
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s := newServerWithMockRunner(t, &mock)
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createParserModel(t, s, "parse-wedge-gen", "qwen3.5")
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stream := false
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done := make(chan struct{})
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go func() {
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defer close(done)
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w := createRequest(t, s.GenerateHandler, api.GenerateRequest{
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Model: "parse-wedge-gen",
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Prompt: "hello",
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Stream: &stream,
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})
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if w.Code != http.StatusInternalServerError {
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t.Errorf("expected 500 from parse failure, got %d: %s", w.Code, w.Body.String())
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}
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}()
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select {
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case <-secondChunkReturned:
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case <-time.After(5 * time.Second):
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t.Fatal("completion callback blocked after a parse error")
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}
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select {
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case <-done:
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case <-time.After(5 * time.Second):
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t.Fatal("generate handler did not return after a parse error")
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}
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}
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func createParserModel(t *testing.T, s *Server, name, parser string) {
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t.Helper()
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kv := gguftest.KV{
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"general.architecture": "llama",
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"llama.block_count": uint32(1),
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"llama.context_length": uint32(8192),
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"llama.embedding_length": uint32(4096),
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"llama.attention.head_count": uint32(32),
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"llama.attention.head_count_kv": uint32(8),
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"tokenizer.ggml.tokens": []string{""},
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"tokenizer.ggml.scores": []float32{0},
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"tokenizer.ggml.token_type": []int32{0},
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}
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_, digest := createBinFile(t, kv, []*gguftest.Tensor{
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{Name: "token_embd.weight", Shape: []uint64{1}, WriterTo: bytes.NewReader(make([]byte, 4))},
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})
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stream := false
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w := createRequest(t, s.CreateHandler, api.CreateRequest{
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Model: name,
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Files: map[string]string{"file.gguf": digest},
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Parser: parser,
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Stream: &stream,
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})
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if w.Code != http.StatusOK {
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t.Fatalf("creating model: %d: %s", w.Code, w.Body.String())
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}
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}
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