feat: replace fake streaming with real SSE StreamGenerate

Use handler-base StreamGenerate() to publish real token-by-token
ChatStreamChunk messages to NATS as they arrive from Ray Serve,
instead of calling Generate() and splitting into 4-word chunks.

Add 8 streaming tests: happy path, system prompt, RAG context,
nil callback, timeout, HTTP error, context canceled, fallback.

Dockerfile

@@ -3,10 +3,13 @@ FROM golang:1.25-alpine AS builder
 
 WORKDIR /app
 
-RUN apk add --no-cache ca-certificates
+RUN apk add --no-cache ca-certificates git
+
+ENV GOPRIVATE=git.daviestechlabs.io
+ENV GONOSUMCHECK=git.daviestechlabs.io
 
 COPY go.mod go.sum ./
-RUN go mod download
+RUN --mount=type=secret,id=netrc,target=/root/.netrc go mod download
 
 COPY . .
 

e2e_test.go

@@ -3,8 +3,11 @@ package main
 import (
 	"context"
 	"encoding/json"
+	"fmt"
 	"net/http"
 	"net/http/httptest"
+	"strings"
+	"sync"
 	"testing"
 	"time"
 
@@ -198,6 +201,220 @@ func TestChatPipeline_TypedDecoding(t *testing.T) {
 	}
 }
 
+// ────────────────────────────────────────────────────────────────────────────
+// Streaming tests: exercise StreamGenerate path (the real SSE pipeline)
+// ────────────────────────────────────────────────────────────────────────────
+
+// sseChunk builds an OpenAI-compatible SSE data line.
+func sseChunk(content string) string {
+	return fmt.Sprintf("data: {\"choices\":[{\"delta\":{\"content\":%q}}]}\n\n", content)
+}
+
+// newStreamingLLM creates a mock LLM server that responds with SSE-streamed tokens.
+func newStreamingLLM(t *testing.T, tokens []string) *httptest.Server {
+	t.Helper()
+	srv := httptest.NewServer(http.HandlerFunc(func(w http.ResponseWriter, r *http.Request) {
+		var req map[string]any
+		_ = json.NewDecoder(r.Body).Decode(&req)
+		// Verify stream=true was requested.
+		if stream, ok := req["stream"].(bool); !ok || !stream {
+			t.Error("expected stream=true in request body")
+		}
+
+		w.Header().Set("Content-Type", "text/event-stream")
+		w.Header().Set("Cache-Control", "no-cache")
+		flusher, _ := w.(http.Flusher)
+
+		// Role-only chunk (should be skipped by StreamGenerate)
+		_, _ = fmt.Fprintf(w, "data: {\"choices\":[{\"delta\":{\"role\":\"assistant\"}}]}\n\n")
+		if flusher != nil {
+			flusher.Flush()
+		}
+
+		for _, tok := range tokens {
+			_, _ = fmt.Fprint(w, sseChunk(tok))
+			if flusher != nil {
+				flusher.Flush()
+			}
+		}
+		_, _ = fmt.Fprintf(w, "data: [DONE]\n\n")
+		if flusher != nil {
+			flusher.Flush()
+		}
+	}))
+	t.Cleanup(srv.Close)
+	return srv
+}
+
+func TestChatPipeline_StreamGenerate(t *testing.T) {
+	tokens := []string{"Paris", " is", " the", " capital", " of", " France", "."}
+	srv := newStreamingLLM(t, tokens)
+	llm := clients.NewLLMClient(srv.URL, 5*time.Second)
+
+	var mu sync.Mutex
+	var received []string
+	full, err := llm.StreamGenerate(context.Background(), "capital of France?", "", "", func(token string) {
+		mu.Lock()
+		defer mu.Unlock()
+		received = append(received, token)
+	})
+	if err != nil {
+		t.Fatal(err)
+	}
+	if full != "Paris is the capital of France." {
+		t.Errorf("full = %q", full)
+	}
+	if len(received) != len(tokens) {
+		t.Errorf("callback count = %d, want %d", len(received), len(tokens))
+	}
+	for i, tok := range tokens {
+		if received[i] != tok {
+			t.Errorf("token[%d] = %q, want %q", i, received[i], tok)
+		}
+	}
+}
+
+func TestChatPipeline_StreamWithSystemPrompt(t *testing.T) {
+	srv := newStreamingLLM(t, []string{"Hello", "!"})
+	llm := clients.NewLLMClient(srv.URL, 5*time.Second)
+
+	full, err := llm.StreamGenerate(context.Background(), "greet me", "", "You are a friendly assistant.", func(token string) {})
+	if err != nil {
+		t.Fatal(err)
+	}
+	if full != "Hello!" {
+		t.Errorf("full = %q", full)
+	}
+}
+
+func TestChatPipeline_StreamWithRAGContext(t *testing.T) {
+	m := newMockBackends(t)
+	srv := newStreamingLLM(t, []string{"The", " answer", " is", " 42"})
+	embeddings := clients.NewEmbeddingsClient(m.Embeddings.URL, 5*time.Second, "bge")
+	llm := clients.NewLLMClient(srv.URL, 5*time.Second)
+
+	ctx := context.Background()
+
+	// 1. Embed
+	embedding, err := embeddings.EmbedSingle(ctx, "deep thought")
+	if err != nil {
+		t.Fatal(err)
+	}
+	if len(embedding) == 0 {
+		t.Fatal("empty embedding")
+	}
+
+	// 2. Stream with context
+	var tokens []string
+	full, err := llm.StreamGenerate(ctx, "deep thought", "The answer to everything is 42.", "", func(tok string) {
+		tokens = append(tokens, tok)
+	})
+	if err != nil {
+		t.Fatal(err)
+	}
+	if full != "The answer is 42" {
+		t.Errorf("full = %q", full)
+	}
+	if len(tokens) != 4 {
+		t.Errorf("token count = %d, want 4", len(tokens))
+	}
+}
+
+func TestChatPipeline_StreamNilCallback(t *testing.T) {
+	srv := newStreamingLLM(t, []string{"ok"})
+	llm := clients.NewLLMClient(srv.URL, 5*time.Second)
+
+	full, err := llm.StreamGenerate(context.Background(), "test", "", "", nil)
+	if err != nil {
+		t.Fatal(err)
+	}
+	if full != "ok" {
+		t.Errorf("full = %q", full)
+	}
+}
+
+func TestChatPipeline_StreamTimeout(t *testing.T) {
+	slow := httptest.NewServer(http.HandlerFunc(func(w http.ResponseWriter, r *http.Request) {
+		time.Sleep(200 * time.Millisecond)
+		w.Header().Set("Content-Type", "text/event-stream")
+		_, _ = fmt.Fprint(w, sseChunk("late"))
+		_, _ = fmt.Fprint(w, "data: [DONE]\n\n")
+	}))
+	defer slow.Close()
+
+	llm := clients.NewLLMClient(slow.URL, 100*time.Millisecond)
+	_, err := llm.StreamGenerate(context.Background(), "hello", "", "", nil)
+	if err == nil {
+		t.Error("expected timeout error")
+	}
+}
+
+func TestChatPipeline_StreamHTTPError(t *testing.T) {
+	errSrv := httptest.NewServer(http.HandlerFunc(func(w http.ResponseWriter, r *http.Request) {
+		w.WriteHeader(http.StatusInternalServerError)
+		_, _ = w.Write([]byte("internal error"))
+	}))
+	defer errSrv.Close()
+
+	llm := clients.NewLLMClient(errSrv.URL, 5*time.Second)
+	_, err := llm.StreamGenerate(context.Background(), "hello", "", "", nil)
+	if err == nil {
+		t.Error("expected error for HTTP 500")
+	}
+	if !strings.Contains(err.Error(), "500") {
+		t.Errorf("error = %q, should mention status 500", err)
+	}
+}
+
+func TestChatPipeline_StreamContextCanceled(t *testing.T) {
+	ctx, cancel := context.WithCancel(context.Background())
+	cancel() // cancel immediately
+
+	srv := newStreamingLLM(t, []string{"should", "not", "arrive"})
+	llm := clients.NewLLMClient(srv.URL, 5*time.Second)
+
+	_, err := llm.StreamGenerate(ctx, "hello", "", "", nil)
+	if err == nil {
+		t.Error("expected context canceled error")
+	}
+}
+
+func TestChatPipeline_StreamFallbackToNonStreaming(t *testing.T) {
+	// Simulate the branching in main.go: non-streaming uses Generate(),
+	// streaming uses StreamGenerate(). Verify both paths work from same mock.
+	m := newMockBackends(t)
+	streamSrv := newStreamingLLM(t, []string{"streamed", " answer"})
+
+	nonStreamLLM := clients.NewLLMClient(m.LLM.URL, 5*time.Second)
+	streamLLM := clients.NewLLMClient(streamSrv.URL, 5*time.Second)
+
+	ctx := context.Background()
+
+	// Non-streaming path
+	resp1, err := nonStreamLLM.Generate(ctx, "hello", "", "")
+	if err != nil {
+		t.Fatal(err)
+	}
+	if resp1 != "Paris is the capital of France." {
+		t.Errorf("non-stream = %q", resp1)
+	}
+
+	// Streaming path
+	var tokens []string
+	resp2, err := streamLLM.StreamGenerate(ctx, "hello", "", "", func(tok string) {
+		tokens = append(tokens, tok)
+	})
+	if err != nil {
+		t.Fatal(err)
+	}
+	if resp2 != "streamed answer" {
+		t.Errorf("stream = %q", resp2)
+	}
+	if len(tokens) != 2 {
+		t.Errorf("token count = %d", len(tokens))
+	}
+}
+
 // ────────────────────────────────────────────────────────────────────────────
 // Benchmark: full chat pipeline overhead (mock backends)
 // ────────────────────────────────────────────────────────────────────────────
@@ -245,3 +462,23 @@ func BenchmarkChatPipeline_RAGFlow(b *testing.B) {
 		_, _ = llm.Generate(ctx, "question", "context", "")
 	}
 }
+
+func BenchmarkChatPipeline_StreamGenerate(b *testing.B) {
+	tokens := []string{"one", " two", " three", " four", " five"}
+	srv := httptest.NewServer(http.HandlerFunc(func(w http.ResponseWriter, r *http.Request) {
+		w.Header().Set("Content-Type", "text/event-stream")
+		for _, tok := range tokens {
+			_, _ = fmt.Fprintf(w, "data: {\"choices\":[{\"delta\":{\"content\":%q}}]}\n\n", tok)
+		}
+		_, _ = fmt.Fprint(w, "data: [DONE]\n\n")
+	}))
+	defer srv.Close()
+
+	llm := clients.NewLLMClient(srv.URL, 10*time.Second)
+	ctx := context.Background()
+
+	b.ResetTimer()
+	for b.Loop() {
+		_, _ = llm.StreamGenerate(ctx, "question", "", "", func(string) {})
+	}
+}

go.mod

@@ -3,7 +3,7 @@ module git.daviestechlabs.io/daviestechlabs/chat-handler
 go 1.25.1
 
 require (
-	git.daviestechlabs.io/daviestechlabs/handler-base v0.1.3
+	git.daviestechlabs.io/daviestechlabs/handler-base v0.1.5
 	github.com/nats-io/nats.go v1.48.0
 	github.com/vmihailenco/msgpack/v5 v5.4.1
 )

go.sum

@@ -1,5 +1,5 @@
-git.daviestechlabs.io/daviestechlabs/handler-base v0.1.3 h1:uYog8B839ulqrWoht3qqCvT7CnR3e2skpaLZc2Pg3GI=
+git.daviestechlabs.io/daviestechlabs/handler-base v0.1.5 h1:DqYZpeluTXh5QKqdVFgN8YIMh4Ycqzw5E9+5FTNDFCA=
-git.daviestechlabs.io/daviestechlabs/handler-base v0.1.3/go.mod h1:M3HgvUDWnRn7cX3BE8l+HvoCUYtmRr5OoumB+hnRHoE=
+git.daviestechlabs.io/daviestechlabs/handler-base v0.1.5/go.mod h1:M3HgvUDWnRn7cX3BE8l+HvoCUYtmRr5OoumB+hnRHoE=
 github.com/cenkalti/backoff/v5 v5.0.3 h1:ZN+IMa753KfX5hd8vVaMixjnqRZ3y8CuJKRKj1xcsSM=
 github.com/cenkalti/backoff/v5 v5.0.3/go.mod h1:rkhZdG3JZukswDf7f0cwqPNk4K0sa+F97BxZthm/crw=
 github.com/cespare/xxhash/v2 v2.3.0 h1:UL815xU9SqsFlibzuggzjXhog7bL6oX9BbNZnL2UFvs=

main.go

@@ -157,8 +157,27 @@ func main() {
 			}
 		}
 
-		// 5. Generate LLM response
+		// 5. Generate LLM response (streaming when requested)
-		responseText, err := llm.Generate(ctx, query, contextText, systemPrompt)
+		var responseText string
+		if req.EnableStreaming {
+			streamSubject := fmt.Sprintf("ai.chat.response.stream.%s", requestID)
+			responseText, err = llm.StreamGenerate(ctx, query, contextText, systemPrompt, func(token string) {
+				_ = h.NATS.Publish(streamSubject, &messages.ChatStreamChunk{
+					RequestID: requestID,
+					Type:      "chunk",
+					Content:   token,
+					Timestamp: messages.Timestamp(),
+				})
+			})
+			_ = h.NATS.Publish(streamSubject, &messages.ChatStreamChunk{
+				RequestID: requestID,
+				Type:      "done",
+				Done:      true,
+				Timestamp: messages.Timestamp(),
+			})
+		} else {
+			responseText, err = llm.Generate(ctx, query, contextText, systemPrompt)
+		}
 		if err != nil {
 			slog.Error("LLM generation failed", "error", err)
 			return &messages.ChatResponse{
@@ -168,33 +187,7 @@ func main() {
 			}, nil
 		}
 
-		// 6. Stream chunks if requested
+		// 6. Optional TTS — audio as raw bytes (no base64)
-		if req.EnableStreaming {
-			streamSubject := fmt.Sprintf("ai.chat.response.stream.%s", requestID)
-			words := strings.Fields(responseText)
-			chunkSize := 4
-			for i := 0; i < len(words); i += chunkSize {
-				end := i + chunkSize
-				if end > len(words) {
-					end = len(words)
-				}
-				chunk := strings.Join(words[i:end], " ")
-				_ = h.NATS.Publish(streamSubject, &messages.ChatStreamChunk{
-					RequestID: requestID,
-					Type:      "chunk",
-					Content:   chunk,
-					Timestamp: messages.Timestamp(),
-				})
-			}
-			_ = h.NATS.Publish(streamSubject, &messages.ChatStreamChunk{
-				RequestID: requestID,
-				Type:      "done",
-				Done:      true,
-				Timestamp: messages.Timestamp(),
-			})
-		}
-
-		// 7. Optional TTS — audio as raw bytes (no base64)
 		var audio []byte
 		if reqEnableTTS && tts != nil {
 			audioBytes, err := tts.Synthesize(ctx, responseText, ttsLanguage, "")