Victor Vargas
1c0c86de10
Fragments now carry a memory type in metadata (legacy fragments count as procedural) with SearchByType filtering, and EpisodeCapture summarizes a finished turn with the local LLM and stores it as episodic memory, so the agent can answer "what did we do yesterday?". Includes an E2E test against a live llama.cpp server (gated) and taxonomy unit tests. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
99 lines
3.5 KiB
Go
99 lines
3.5 KiB
Go
package rag_test
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import (
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"context"
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"net/http"
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"path/filepath"
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"testing"
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"time"
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llm_llamacpp "github.com/VictorVargas/rony-llm-agent/pkg/llm/providers/llamacpp"
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"github.com/VictorVargas/rony-llm-agent/pkg/rag"
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"github.com/VictorVargas/rony-llm-agent/pkg/rag/backends/sqlitevec"
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"github.com/VictorVargas/rony-llm-agent/pkg/rag/embeddings"
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)
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// TestEpisodeCapture_EndToEndLocalServer exercises the full auto-capture
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// path — real LLM summarization, sqlitevec storage, taxonomy-filtered
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// recall — against the llama.cpp server Rony actually uses. Skipped when no
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// server is listening on localhost:8080, so it never breaks CI or offline
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// runs; with the server up it's the proof the feature works for real, not
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// just against stubs.
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func TestEpisodeCapture_EndToEndLocalServer(t *testing.T) {
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probe, err := (&http.Client{Timeout: 2 * time.Second}).Get("http://localhost:8080/v1/models")
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if err != nil {
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t.Skipf("no local llama.cpp server on :8080: %v", err)
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}
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probe.Body.Close()
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client, err := llm_llamacpp.New(llm_llamacpp.Config{})
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if err != nil {
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t.Fatalf("llamacpp client: %v", err)
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}
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backend, err := sqlitevec.New(filepath.Join(t.TempDir(), "e2e_memory.db"))
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if err != nil {
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t.Fatalf("sqlitevec: %v", err)
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}
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defer backend.Close()
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// Same embedder wiring the harness uses: llama.cpp embeddings when the
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// server exposes them, transparent FTS5 fallback otherwise.
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embedder, err := embeddings.NewLlamaCpp(embeddings.LlamaCppConfig{})
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if err != nil {
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t.Fatalf("embedder: %v", err)
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}
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mem, err := rag.New(rag.Config{Backend: backend, Embedder: embedder})
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if err != nil {
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t.Fatalf("memory: %v", err)
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}
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capture := &rag.EpisodeCapture{
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Memory: mem,
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LLM: client,
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ProjectID: "e2e-test",
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Prompt: "Resume el siguiente intercambio entre un usuario y un asistente de IA en 1-2 frases, en pasado, " +
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"enfocándote en qué se pidió y qué se hizo. Responde ÚNICAMENTE con el resumen. /no_think",
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}
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ctx, cancel := context.WithTimeout(context.Background(), 120*time.Second)
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defer cancel()
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userInput := "¿Puedes optimizar el cliente OpenAI del proyecto? El streaming no funciona."
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reply := "Encontré que Stream() enviaba stream:false y descartaba el modelo configurado. " +
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"Reescribí el cliente: ahora hace streaming real, acumula tool calls y reporta el usage. Los tests pasan."
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if err := capture.Capture(ctx, userInput, reply, "read", "edit", "bash"); err != nil {
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t.Fatalf("capture failed against the real server: %v", err)
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}
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// Recall it back, restricted to episodic memory.
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episodes, err := mem.SearchByType(ctx, "optimización del cliente OpenAI streaming", 5, rag.MemoryEpisodic)
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if err != nil {
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t.Fatalf("search failed: %v", err)
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}
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if len(episodes) == 0 {
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t.Fatal("expected the captured episode to be recallable via SearchByType(episodic)")
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}
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ep := episodes[0]
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if ep.Type != rag.MemoryEpisodic {
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t.Fatalf("expected episodic type, got %q", ep.Type)
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}
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if ep.Metadata["tools"] != "read,edit,bash" {
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t.Fatalf("expected tools metadata, got %q", ep.Metadata["tools"])
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}
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if ep.Metadata["date"] == "" {
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t.Fatal("expected a date on the episode")
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}
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t.Logf("captured episode: %s", ep.Content)
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// A procedural-only search must NOT return the episode.
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procs, err := mem.SearchByType(ctx, "optimización del cliente OpenAI streaming", 5, rag.MemoryProcedural)
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if err != nil {
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t.Fatalf("procedural search failed: %v", err)
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}
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for _, p := range procs {
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if p.ID == ep.ID {
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t.Fatal("episode leaked into a procedural-only search")
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}
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}
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}
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