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Add semantic memory with chromem-go vector store

Browse source 
Introduce remember/recall tools backed by chromem-go and Ollama
embeddings for persistent semantic memory. Fix ContextWindow to use
config value (128k) instead of MaxTokens (8k) to prevent premature
summarization. Add auto-extraction of key facts during summarization
and integrate streaming into the agent loop.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
This commit is contained in:
pmorgan 2026-02-22 11:58:10 -07:00
parent c656fc8a10
commit 3d5fe5bc4d
15 changed files with 1416 additions and 26 deletions
Show stats Download patch file Download diff file Expand all files Collapse all files

1
go.mod
View file

@ -22,6 +22,7 @@ require (
require (
github.com/davecgh/go-spew v1.1.1 // indirect
github.com/philippgille/chromem-go v0.7.0 // indirect
github.com/pmezard/go-difflib v1.0.0 // indirect
gopkg.in/yaml.v3 v3.0.1 // indirect
)

2
go.sum
View file

@ -102,6 +102,8 @@ github.com/open-dingtalk/dingtalk-stream-sdk-go v0.9.1 h1:Lb/Uzkiw2Ugt2Xf03J5wmv
github.com/open-dingtalk/dingtalk-stream-sdk-go v0.9.1/go.mod h1:ln3IqPYYocZbYvl9TAOrG/cxGR9xcn4pnZRLdCTEGEU=
github.com/openai/openai-go/v3 v3.22.0 h1:6MEoNoV8sbjOVmXdvhmuX3BjVbVdcExbVyGixiyJ8ys=
github.com/openai/openai-go/v3 v3.22.0/go.mod h1:cdufnVK14cWcT9qA1rRtrXx4FTRsgbDPW7Ia7SS5cZo=
github.com/philippgille/chromem-go v0.7.0 h1:4jfvfyKymjKNfGxBUhHUcj1kp7B17NL/I1P+vGh1RvY=
github.com/philippgille/chromem-go v0.7.0/go.mod h1:hTd+wGEm/fFPQl7ilfCwQXkgEUxceYh86iIdoKMolPo=
github.com/pkg/diff v0.0.0-20210226163009-20ebb0f2a09e/go.mod h1:pJLUxLENpZxwdsKMEsNbx1VGcRFpLqf3715MtcvvzbA=
github.com/pmezard/go-difflib v1.0.0 h1:4DBwDE0NGyQoBHbLQYPwSUPoCMWR5BEzIk/f1lZbAQM=
github.com/pmezard/go-difflib v1.0.0/go.mod h1:iKH77koFhYxTK1pcRnkKkqfTogsbg7gZNVY4sRDYZ/4=

7
pkg/agent/instance.go
View file

@ -95,6 +95,11 @@ func NewAgentInstance(
}
candidates := providers.ResolveCandidates(modelCfg, defaults.Provider)
contextWindow := defaults.ContextWindow
if contextWindow == 0 {
contextWindow = 128000
}
return &AgentInstance{
ID: agentID,
Name: agentName,
@ -104,7 +109,7 @@ func NewAgentInstance(
MaxIterations: maxIter,
MaxTokens: maxTokens,
Temperature: temperature,
ContextWindow: maxTokens,
ContextWindow: contextWindow,
Provider: provider,
Sessions: sessionsManager,
ContextBuilder: contextBuilder,

193
pkg/agent/loop.go
View file

@ -16,11 +16,14 @@ import (
"time"
"unicode/utf8"
"path/filepath"
"github.com/sipeed/picoclaw/pkg/bus"
"github.com/sipeed/picoclaw/pkg/channels"
"github.com/sipeed/picoclaw/pkg/config"
"github.com/sipeed/picoclaw/pkg/constants"
"github.com/sipeed/picoclaw/pkg/logger"
"github.com/sipeed/picoclaw/pkg/memory"
"github.com/sipeed/picoclaw/pkg/providers"
"github.com/sipeed/picoclaw/pkg/routing"
"github.com/sipeed/picoclaw/pkg/skills"
@ -38,6 +41,7 @@ type AgentLoop struct {
summarizing sync.Map
fallback *providers.FallbackChain
channelManager *channels.Manager
semanticStores map[string]memory.Store
}
// processOptions configures how a message is processed
@ -55,8 +59,8 @@ type processOptions struct {
func NewAgentLoop(cfg *config.Config, msgBus *bus.MessageBus, provider providers.LLMProvider) *AgentLoop {
registry := NewAgentRegistry(cfg, provider)
// Register shared tools to all agents
registerSharedTools(cfg, msgBus, registry, provider)
// Register shared tools to all agents (including memory tools)
stores := registerSharedTools(cfg, msgBus, registry, provider)
// Set up shared fallback chain
cooldown := providers.NewCooldownTracker()
@ -76,16 +80,20 @@ func NewAgentLoop(cfg *config.Config, msgBus *bus.MessageBus, provider providers
state: stateManager,
summarizing: sync.Map{},
fallback: fallbackChain,
semanticStores: stores,
}
}
// registerSharedTools registers tools that are shared across all agents (web, message, spawn).
// registerSharedTools registers tools that are shared across all agents (web, message, spawn, memory).
// Returns a map of agent ID to semantic memory store for auto-extraction.
func registerSharedTools(
cfg *config.Config,
msgBus *bus.MessageBus,
registry *AgentRegistry,
provider providers.LLMProvider,
) {
) map[string]memory.Store {
stores := make(map[string]memory.Store)
for _, agentID := range registry.ListAgentIDs() {
agent, ok := registry.GetAgent(agentID)
if !ok {
@ -145,9 +153,30 @@ func registerSharedTools(
})
agent.Tools.Register(spawnTool)
// Semantic memory tools (graceful degradation if Ollama unavailable)
vectorDir := filepath.Join(agent.Workspace, "memory", "vectors")
store, err := memory.NewSemanticStore(
vectorDir,
cfg.Tools.Memory.OllamaURL,
cfg.Tools.Memory.EmbeddingModel,
)
if err != nil {
logger.WarnCF("agent", "Semantic memory unavailable",
map[string]any{
"agent_id": agentID,
"error": err.Error(),
})
} else if store.IsAvailable() {
agent.Tools.Register(tools.NewRememberTool(store))
agent.Tools.Register(tools.NewRecallTool(store))
stores[agentID] = store
}
// Update context builder with the complete tools registry
agent.ContextBuilder.SetToolsRegistry(agent.Tools)
}
return stores
}
func (al *AgentLoop) Run(ctx context.Context) error {
@ -514,14 +543,16 @@ func (al *AgentLoop) runLLMIteration(
var response *providers.LLMResponse
var err error
llmOpts := map[string]any{
"max_tokens": agent.MaxTokens,
"temperature": agent.Temperature,
}
callLLM := func() (*providers.LLMResponse, error) {
if len(agent.Candidates) > 1 && al.fallback != nil {
fbResult, fbErr := al.fallback.Execute(ctx, agent.Candidates,
func(ctx context.Context, provider, model string) (*providers.LLMResponse, error) {
return agent.Provider.Chat(ctx, messages, providerToolDefs, model, map[string]any{
"max_tokens": agent.MaxTokens,
"temperature": agent.Temperature,
})
return agent.Provider.Chat(ctx, messages, providerToolDefs, model, llmOpts)
},
)
if fbErr != nil {
@ -534,11 +565,18 @@ func (al *AgentLoop) runLLMIteration(
}
return fbResult.Response, nil
}
return agent.Provider.Chat(ctx, messages, providerToolDefs, agent.Model, map[string]any{
"max_tokens": agent.MaxTokens,
"temperature": agent.Temperature,
// Use streaming if the provider supports it
if sp, ok := agent.Provider.(providers.StreamingProvider); ok {
return sp.ChatStream(ctx, messages, providerToolDefs, agent.Model, llmOpts,
func(delta string) {
// Streaming delta received — currently logged only.
// Future: push partial content to user via message bus.
logger.DebugCF("agent", "Stream delta",
map[string]any{"len": len(delta)})
})
}
return agent.Provider.Chat(ctx, messages, providerToolDefs, agent.Model, llmOpts)
}
// Retry loop for context/token errors
maxRetries := 2
@ -783,8 +821,9 @@ func (al *AgentLoop) forceCompression(agent *AgentInstance, sessionKey string) {
return
}
// Helper to find the mid-point of the conversation
mid := len(conversation) / 2
// Find the mid-point of the conversation, adjusted to avoid splitting
// tool_use/tool_result pairs.
mid := safeSplitIndex(conversation, len(conversation)/2)
// New history structure:
// 1. System Prompt (with compression note appended)
@ -820,6 +859,33 @@ func (al *AgentLoop) forceCompression(agent *AgentInstance, sessionKey string) {
})
}
// safeSplitIndex finds a split point in messages at or after targetIdx that
// does not break a tool_use/tool_result pair. An assistant message with
// ToolCalls must be kept together with the tool-result messages that
// immediately follow it. The returned index is the first message to KEEP
// (i.e. messages[:idx] are dropped, messages[idx:] are kept).
func safeSplitIndex(messages []providers.Message, targetIdx int) int {
if targetIdx >= len(messages) {
return len(messages)
}
idx := targetIdx
// If we landed on a "tool" message, walk forward past all consecutive
// tool results so we don't orphan them from their assistant message.
for idx < len(messages) && messages[idx].Role == "tool" {
idx++
}
// If we ended up past the end, back up to just before the tool group.
if idx >= len(messages) {
// Walk backwards from targetIdx to find a safe point.
idx = targetIdx
for idx > 0 && messages[idx].Role == "tool" {
idx--
}
// idx now points to the assistant message; keep it and its tool results.
}
return idx
}
// GetStartupInfo returns information about loaded tools and skills for logging.
func (al *AgentLoop) GetStartupInfo() map[string]any {
info := make(map[string]any)
@ -907,12 +973,17 @@ func (al *AgentLoop) summarizeSession(agent *AgentInstance, sessionKey string) {
history := agent.Sessions.GetHistory(sessionKey)
summary := agent.Sessions.GetSummary(sessionKey)
// Keep last 4 messages for continuity
if len(history) <= 4 {
// Keep last few messages for continuity, adjusting the split point so we
// never orphan a tool_use from its tool_result(s).
if len(history) <= 6 {
return
}
toSummarize := history[:len(history)-4]
keepIdx := safeSplitIndex(history, len(history)-6)
if keepIdx <= 0 {
return
}
toSummarize := history[:keepIdx]
// Oversized Message Guard
maxMessageTokens := agent.ContextWindow / 2
@ -920,7 +991,7 @@ func (al *AgentLoop) summarizeSession(agent *AgentInstance, sessionKey string) {
omitted := false
for _, m := range toSummarize {
if m.Role != "user" && m.Role != "assistant" {
if m.Role != "user" && m.Role != "assistant" && m.Role != "tool" {
continue
}
msgTokens := len(m.Content) / 2
@ -975,8 +1046,94 @@ func (al *AgentLoop) summarizeSession(agent *AgentInstance, sessionKey string) {
if finalSummary != "" {
agent.Sessions.SetSummary(sessionKey, finalSummary)
agent.Sessions.TruncateHistory(sessionKey, 4)
agent.Sessions.TruncateHistory(sessionKey, len(history)-keepIdx)
agent.Sessions.Save(sessionKey)
// Auto-extract key facts from the summarized messages into semantic memory
if al.cfg.Tools.Memory.AutoExtract {
if store, ok := al.semanticStores[agent.ID]; ok {
go al.extractMemories(ctx, agent, store, toSummarize)
}
}
}
}
// extractMemories uses the LLM to extract key facts from conversation messages
// and stores them in the semantic memory store for later recall.
func (al *AgentLoop) extractMemories(
ctx context.Context,
agent *AgentInstance,
store memory.Store,
messages []providers.Message,
) {
if !store.IsAvailable() {
return
}
// Build a prompt asking the LLM to extract memorable facts
var sb strings.Builder
sb.WriteString("Extract key facts, user preferences, decisions, and important context from this conversation.\n")
sb.WriteString("Output one fact per line in the format: [category] fact\n")
sb.WriteString("Categories: preference, fact, decision, context\n")
sb.WriteString("Only extract genuinely important or reusable information. Skip trivial details.\n\n")
for _, m := range messages {
if m.Role == "user" || m.Role == "assistant" {
fmt.Fprintf(&sb, "%s: %s\n", m.Role, utils.Truncate(m.Content, 500))
}
}
extractCtx, cancel := context.WithTimeout(ctx, 30*time.Second)
defer cancel()
resp, err := agent.Provider.Chat(
extractCtx,
[]providers.Message{{Role: "user", Content: sb.String()}},
nil,
agent.Model,
map[string]any{
"max_tokens": 512,
"temperature": 0.2,
},
)
if err != nil {
logger.WarnCF("agent", "Memory extraction failed",
map[string]any{"error": err.Error()})
return
}
// Parse "[category] fact" lines
stored := 0
for _, line := range strings.Split(resp.Content, "\n") {
line = strings.TrimSpace(line)
if line == "" || !strings.HasPrefix(line, "[") {
continue
}
closeBracket := strings.Index(line, "]")
if closeBracket < 2 {
continue
}
category := strings.TrimSpace(line[1:closeBracket])
content := strings.TrimSpace(line[closeBracket+1:])
if content == "" {
continue
}
entry := memory.MemoryEntry{
Content: content,
Category: category,
Source: "auto-extract",
}
if err := store.Remember(extractCtx, entry); err != nil {
logger.WarnCF("agent", "Failed to store extracted memory",
map[string]any{"error": err.Error()})
continue
}
stored++
}
if stored > 0 {
logger.InfoCF("agent", "Auto-extracted memories",
map[string]any{"count": stored, "agent_id": agent.ID})
}
}

157
pkg/agent/loop_test.go
View file

@ -521,6 +521,163 @@ func TestToolResult_UserFacingToolDoesSendMessage(t *testing.T) {
}
}
// TestSafeSplitIndex verifies that safeSplitIndex never breaks tool_use/tool_result pairs.
func TestSafeSplitIndex(t *testing.T) {
tests := []struct {
name string
messages []providers.Message
targetIdx int
wantIdx int
}{
{
name: "no tool messages, split at target",
messages: []providers.Message{
{Role: "user", Content: "hi"},
{Role: "assistant", Content: "hello"},
{Role: "user", Content: "bye"},
},
targetIdx: 1,
wantIdx: 1,
},
{
name: "target lands on tool result, skip forward",
messages: []providers.Message{
{Role: "user", Content: "hi"},
{Role: "assistant", Content: "", ToolCalls: []providers.ToolCall{{ID: "1", Name: "exec"}}},
{Role: "tool", Content: "result1"},
{Role: "user", Content: "thanks"},
},
targetIdx: 2, // lands on tool result
wantIdx: 3, // skip past it
},
{
name: "target lands on first of two tool results, skip both",
messages: []providers.Message{
{Role: "user", Content: "hi"},
{Role: "assistant", Content: "", ToolCalls: []providers.ToolCall{{ID: "1"}, {ID: "2"}}},
{Role: "tool", Content: "result1"},
{Role: "tool", Content: "result2"},
{Role: "user", Content: "thanks"},
},
targetIdx: 2,
wantIdx: 4,
},
{
name: "target on non-tool message, no adjustment",
messages: []providers.Message{
{Role: "user", Content: "hi"},
{Role: "assistant", Content: "hello"},
{Role: "user", Content: "bye"},
{Role: "assistant", Content: "goodbye"},
},
targetIdx: 2,
wantIdx: 2,
},
{
name: "target on tool at end, back up to assistant",
messages: []providers.Message{
{Role: "user", Content: "hi"},
{Role: "assistant", Content: "", ToolCalls: []providers.ToolCall{{ID: "1"}}},
{Role: "tool", Content: "result"},
},
targetIdx: 2, // tool at end
wantIdx: 1, // back up to include assistant+tool pair
},
{
name: "target beyond messages length",
messages: []providers.Message{
{Role: "user", Content: "hi"},
},
targetIdx: 5,
wantIdx: 1,
},
}
for _, tt := range tests {
t.Run(tt.name, func(t *testing.T) {
got := safeSplitIndex(tt.messages, tt.targetIdx)
if got != tt.wantIdx {
t.Errorf("safeSplitIndex(target=%d) = %d, want %d", tt.targetIdx, got, tt.wantIdx)
}
})
}
}
// TestSanitizeHistoryForProvider_MultipleToolResults verifies that consecutive
// tool results from parallel tool calls are not dropped.
func TestSanitizeHistoryForProvider_MultipleToolResults(t *testing.T) {
tests := []struct {
name string
history []providers.Message
wantLen int
wantDesc string
}{
{
name: "single tool result kept",
history: []providers.Message{
{Role: "user", Content: "hi"},
{Role: "assistant", Content: "", ToolCalls: []providers.ToolCall{{ID: "call_1", Name: "exec"}}},
{Role: "tool", Content: "result1", ToolCallID: "call_1"},
{Role: "assistant", Content: "done"},
},
wantLen: 4,
wantDesc: "all messages kept",
},
{
name: "three consecutive tool results all kept",
history: []providers.Message{
{Role: "user", Content: "check endpoints"},
{Role: "assistant", Content: "", ToolCalls: []providers.ToolCall{
{ID: "call_1", Name: "web_fetch"},
{ID: "call_2", Name: "web_fetch"},
{ID: "call_3", Name: "web_fetch"},
}},
{Role: "tool", Content: `{"status":"ok"}`, ToolCallID: "call_1"},
{Role: "tool", Content: `{"status":"ok"}`, ToolCallID: "call_2"},
{Role: "tool", Content: `{"status":"ok"}`, ToolCallID: "call_3"},
{Role: "assistant", Content: "All endpoints healthy"},
},
wantLen: 6,
wantDesc: "all 3 tool results kept",
},
{
name: "orphaned leading tool message dropped",
history: []providers.Message{
{Role: "tool", Content: "orphan", ToolCallID: "call_0"},
{Role: "user", Content: "hi"},
{Role: "assistant", Content: "hello"},
},
wantLen: 2,
wantDesc: "orphaned tool message dropped, user+assistant kept",
},
{
name: "tool result after non-toolcall assistant dropped",
history: []providers.Message{
{Role: "user", Content: "hi"},
{Role: "assistant", Content: "hello"},
{Role: "tool", Content: "orphan", ToolCallID: "call_0"},
{Role: "user", Content: "bye"},
},
wantLen: 3,
wantDesc: "orphaned tool result dropped",
},
}
for _, tt := range tests {
t.Run(tt.name, func(t *testing.T) {
got := sanitizeHistoryForProvider(tt.history)
if len(got) != tt.wantLen {
roles := make([]string, len(got))
for i, m := range got {
roles[i] = m.Role
}
t.Errorf("sanitizeHistoryForProvider() len = %d, want %d (%s); roles = %v",
len(got), tt.wantLen, tt.wantDesc, roles)
}
})
}
}
// failFirstMockProvider fails on the first N calls with a specific error
type failFirstMockProvider struct {
failures int

9
pkg/config/config.go
View file

@ -175,6 +175,7 @@ type AgentDefaults struct {
ImageModel string `json:"image_model,omitempty" env:"PICOCLAW_AGENTS_DEFAULTS_IMAGE_MODEL"`
ImageModelFallbacks []string `json:"image_model_fallbacks,omitempty"`
MaxTokens int `json:"max_tokens" env:"PICOCLAW_AGENTS_DEFAULTS_MAX_TOKENS"`
ContextWindow int `json:"context_window,omitempty" env:"PICOCLAW_AGENTS_DEFAULTS_CONTEXT_WINDOW"`
Temperature *float64 `json:"temperature,omitempty" env:"PICOCLAW_AGENTS_DEFAULTS_TEMPERATURE"`
MaxToolIterations int `json:"max_tool_iterations" env:"PICOCLAW_AGENTS_DEFAULTS_MAX_TOOL_ITERATIONS"`
}
@ -449,6 +450,14 @@ type ToolsConfig struct {
Cron CronToolsConfig `json:"cron"`
Exec ExecConfig `json:"exec"`
Skills SkillsToolsConfig `json:"skills"`
Memory MemoryConfig `json:"memory"`
}
// MemoryConfig controls the semantic memory system backed by vector embeddings.
type MemoryConfig struct {
OllamaURL string `json:"ollama_url" env:"PICOCLAW_TOOLS_MEMORY_OLLAMA_URL"`
EmbeddingModel string `json:"embedding_model" env:"PICOCLAW_TOOLS_MEMORY_EMBEDDING_MODEL"`
AutoExtract bool `json:"auto_extract" env:"PICOCLAW_TOOLS_MEMORY_AUTO_EXTRACT"`
}
type SkillsToolsConfig struct {

6
pkg/config/defaults.go
View file

@ -15,6 +15,7 @@ func DefaultConfig() *Config {
Provider: "",
Model: "glm-4.7",
MaxTokens: 8192,
ContextWindow: 128000,
Temperature: nil, // nil means use provider default
MaxToolIterations: 20,
},
@ -303,6 +304,11 @@ func DefaultConfig() *Config {
TTLSeconds: 300,
},
},
Memory: MemoryConfig{
OllamaURL: "http://localhost:11434",
EmbeddingModel: "nomic-embed-text",
AutoExtract: true,
},
},
Heartbeat: HeartbeatConfig{
Enabled: true,

67
pkg/memory/ollama.go Normal file
View file

@ -0,0 +1,67 @@
// ABOUTME: Ollama connectivity for embedding generation.
// ABOUTME: Provides health checks and constants for the Ollama embedding service.
package memory
import (
"context"
"encoding/json"
"fmt"
"net/http"
"time"
)
const (
DefaultOllamaURL = "http://localhost:11434"
DefaultEmbeddingModel = "nomic-embed-text"
)
// ollamaTagsResponse is the response from GET /api/tags.
type ollamaTagsResponse struct {
Models []ollamaModel `json:"models"`
}
type ollamaModel struct {
Name string `json:"name"`
}
// CheckOllamaAvailable checks whether Ollama is reachable and has the
// requested embedding model installed. Returns nil on success.
func CheckOllamaAvailable(ctx context.Context, ollamaURL, model string) error {
if ollamaURL == "" {
ollamaURL = DefaultOllamaURL
}
if model == "" {
model = DefaultEmbeddingModel
}
client := &http.Client{Timeout: 5 * time.Second}
req, err := http.NewRequestWithContext(ctx, http.MethodGet, ollamaURL+"/api/tags", nil)
if err != nil {
return fmt.Errorf("creating request: %w", err)
}
resp, err := client.Do(req)
if err != nil {
return fmt.Errorf("ollama unreachable at %s: %w", ollamaURL, err)
}
defer resp.Body.Close()
if resp.StatusCode != http.StatusOK {
return fmt.Errorf("ollama returned status %d", resp.StatusCode)
}
var tags ollamaTagsResponse
if err := json.NewDecoder(resp.Body).Decode(&tags); err != nil {
return fmt.Errorf("decoding tags response: %w", err)
}
for _, m := range tags.Models {
// Ollama model names can include ":latest" suffix
if m.Name == model || m.Name == model+":latest" {
return nil
}
}
return fmt.Errorf("model %q not found in ollama (have %d models); run: ollama pull %s",
model, len(tags.Models), model)
}

113
pkg/memory/ollama_test.go Normal file
View file

@ -0,0 +1,113 @@
// ABOUTME: Tests for Ollama health check and connectivity.
// ABOUTME: Uses httptest mock server to verify model detection behavior.
package memory
import (
"encoding/json"
"net/http"
"net/http/httptest"
"testing"
)
func TestCheckOllamaAvailable_ModelFound(t *testing.T) {
server := httptest.NewServer(http.HandlerFunc(func(w http.ResponseWriter, r *http.Request) {
if r.URL.Path != "/api/tags" {
http.Error(w, "not found", http.StatusNotFound)
return
}
resp := ollamaTagsResponse{
Models: []ollamaModel{
{Name: "llama3.2:latest"},
{Name: "nomic-embed-text:latest"},
},
}
json.NewEncoder(w).Encode(resp)
}))
defer server.Close()
err := CheckOllamaAvailable(t.Context(), server.URL, "nomic-embed-text")
if err != nil {
t.Fatalf("expected no error, got: %v", err)
}
}
func TestCheckOllamaAvailable_ModelFoundExactMatch(t *testing.T) {
server := httptest.NewServer(http.HandlerFunc(func(w http.ResponseWriter, r *http.Request) {
resp := ollamaTagsResponse{
Models: []ollamaModel{
{Name: "nomic-embed-text"},
},
}
json.NewEncoder(w).Encode(resp)
}))
defer server.Close()
err := CheckOllamaAvailable(t.Context(), server.URL, "nomic-embed-text")
if err != nil {
t.Fatalf("expected no error for exact match, got: %v", err)
}
}
func TestCheckOllamaAvailable_ModelNotFound(t *testing.T) {
server := httptest.NewServer(http.HandlerFunc(func(w http.ResponseWriter, r *http.Request) {
resp := ollamaTagsResponse{
Models: []ollamaModel{
{Name: "llama3.2:latest"},
},
}
json.NewEncoder(w).Encode(resp)
}))
defer server.Close()
err := CheckOllamaAvailable(t.Context(), server.URL, "nomic-embed-text")
if err == nil {
t.Fatal("expected error when model not found")
}
if got := err.Error(); !contains(got, "not found") {
t.Errorf("error = %q, want it to contain 'not found'", got)
}
}
func TestCheckOllamaAvailable_ServerUnreachable(t *testing.T) {
err := CheckOllamaAvailable(t.Context(), "http://127.0.0.1:1", "nomic-embed-text")
if err == nil {
t.Fatal("expected error when server unreachable")
}
if got := err.Error(); !contains(got, "unreachable") {
t.Errorf("error = %q, want it to contain 'unreachable'", got)
}
}
func TestCheckOllamaAvailable_ServerError(t *testing.T) {
server := httptest.NewServer(http.HandlerFunc(func(w http.ResponseWriter, r *http.Request) {
http.Error(w, "internal error", http.StatusInternalServerError)
}))
defer server.Close()
err := CheckOllamaAvailable(t.Context(), server.URL, "nomic-embed-text")
if err == nil {
t.Fatal("expected error on server 500")
}
if got := err.Error(); !contains(got, "status 500") {
t.Errorf("error = %q, want it to contain 'status 500'", got)
}
}
func TestCheckOllamaAvailable_DefaultValues(t *testing.T) {
// When called with empty strings, it should use defaults and likely fail
// (no local Ollama in test environment). Just verify it doesn't panic.
_ = CheckOllamaAvailable(t.Context(), "", "")
}
func contains(s, substr string) bool {
return len(s) >= len(substr) && searchSubstring(s, substr)
}
func searchSubstring(s, substr string) bool {
for i := 0; i <= len(s)-len(substr); i++ {
if s[i:i+len(substr)] == substr {
return true
}
}
return false
}

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// ABOUTME: Semantic memory store backed by chromem-go vector database.
// ABOUTME: Provides Remember/Recall operations with Ollama embeddings for persistent memory.
package memory
import (
"context"
"fmt"
"strings"
"time"
chromem "github.com/philippgille/chromem-go"
)
// MemoryEntry represents a single memory to be stored.
type MemoryEntry struct {
ID string
Content string
Category string // "preference", "fact", "decision", etc.
Tags []string
Source string // "agent", "auto-extract"
Timestamp time.Time
}
// RecallResult is a memory entry returned from a search, with similarity score.
type RecallResult struct {
MemoryEntry
Similarity float32
}
// Store is the interface for semantic memory operations.
// Using an interface allows easy testing with mock implementations.
type Store interface {
IsAvailable() bool
Count() int
Remember(ctx context.Context, entry MemoryEntry) error
Recall(ctx context.Context, query string, topK int) ([]RecallResult, error)
}
// SemanticStore implements Store using chromem-go for vector storage
// and Ollama for embedding generation.
type SemanticStore struct {
db *chromem.DB
collection *chromem.Collection
available bool
}
// NewSemanticStore creates a persistent vector store at persistDir.
// It connects to Ollama at ollamaURL for embeddings using the given model.
// If Ollama is unreachable, the store is created in a degraded state
// where IsAvailable() returns false and all operations return clean errors.
func NewSemanticStore(persistDir, ollamaURL, embeddingModel string) (*SemanticStore, error) {
if ollamaURL == "" {
ollamaURL = DefaultOllamaURL
}
if embeddingModel == "" {
embeddingModel = DefaultEmbeddingModel
}
// chromem-go expects the Ollama API base URL (ending in /api), not
// the server root. Normalize so users can provide either form.
ollamaAPIBase := normalizeOllamaURL(ollamaURL)
embedFn := chromem.NewEmbeddingFuncOllama(embeddingModel, ollamaAPIBase)
db, err := chromem.NewPersistentDB(persistDir, false)
if err != nil {
return &SemanticStore{available: false}, fmt.Errorf("creating vector db: %w", err)
}
collection, err := db.GetOrCreateCollection("memories", nil, embedFn)
if err != nil {
return &SemanticStore{available: false}, fmt.Errorf("creating collection: %w", err)
}
return &SemanticStore{
db: db,
collection: collection,
available: true,
}, nil
}
// NewSemanticStoreWithEmbedding creates a store with a custom embedding function.
// This is primarily for testing without requiring Ollama.
func NewSemanticStoreWithEmbedding(persistDir string, embedFn chromem.EmbeddingFunc) (*SemanticStore, error) {
db, err := chromem.NewPersistentDB(persistDir, false)
if err != nil {
return nil, fmt.Errorf("creating vector db: %w", err)
}
collection, err := db.GetOrCreateCollection("memories", nil, embedFn)
if err != nil {
return nil, fmt.Errorf("creating collection: %w", err)
}
return &SemanticStore{
db: db,
collection: collection,
available: true,
}, nil
}
func (s *SemanticStore) IsAvailable() bool {
return s.available
}
func (s *SemanticStore) Count() int {
if !s.available {
return 0
}
return s.collection.Count()
}
func (s *SemanticStore) Remember(ctx context.Context, entry MemoryEntry) error {
if !s.available {
return fmt.Errorf("semantic memory is not available")
}
if entry.ID == "" {
entry.ID = fmt.Sprintf("mem_%d", time.Now().UnixNano())
}
if entry.Timestamp.IsZero() {
entry.Timestamp = time.Now()
}
metadata := map[string]string{
"category": entry.Category,
"source": entry.Source,
"timestamp": entry.Timestamp.Format(time.RFC3339),
}
if len(entry.Tags) > 0 {
metadata["tags"] = strings.Join(entry.Tags, ",")
}
doc := chromem.Document{
ID: entry.ID,
Content: entry.Content,
Metadata: metadata,
}
return s.collection.AddDocument(ctx, doc)
}
func (s *SemanticStore) Recall(ctx context.Context, query string, topK int) ([]RecallResult, error) {
if !s.available {
return nil, fmt.Errorf("semantic memory is not available")
}
if topK <= 0 {
topK = 5
}
if topK > 20 {
topK = 20
}
// chromem-go returns an error if topK > collection count, so we
// cap it to the collection size.
count := s.collection.Count()
if count == 0 {
return nil, nil
}
if topK > count {
topK = count
}
results, err := s.collection.Query(ctx, query, topK, nil, nil)
if err != nil {
return nil, fmt.Errorf("querying memories: %w", err)
}
var recalls []RecallResult
for _, r := range results {
entry := MemoryEntry{
ID: r.ID,
Content: r.Content,
Category: r.Metadata["category"],
Source: r.Metadata["source"],
}
if ts, ok := r.Metadata["timestamp"]; ok {
if t, err := time.Parse(time.RFC3339, ts); err == nil {
entry.Timestamp = t
}
}
if tagStr, ok := r.Metadata["tags"]; ok && tagStr != "" {
entry.Tags = strings.Split(tagStr, ",")
}
recalls = append(recalls, RecallResult{
MemoryEntry: entry,
Similarity: r.Similarity,
})
}
return recalls, nil
}
// normalizeOllamaURL ensures the URL ends with /api as required by
// chromem-go's NewEmbeddingFuncOllama. Users typically configure the
// Ollama server root (http://localhost:11434) without the /api suffix.
func normalizeOllamaURL(url string) string {
url = strings.TrimRight(url, "/")
if url == "" {
return "" // let chromem-go use its default
}
if !strings.HasSuffix(url, "/api") {
url += "/api"
}
return url
}

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// ABOUTME: Tests for the SemanticStore vector memory implementation.
// ABOUTME: Uses a deterministic mock embedding function to test without Ollama.
package memory
import (
"context"
"os"
"testing"
)
// mockEmbeddingFunc returns a deterministic embedding based on text length.
// This gives different texts different (but reproducible) embeddings,
// allowing cosine similarity to work for testing.
func mockEmbeddingFunc(text string) []float32 {
const dims = 64
embedding := make([]float32, dims)
for i, ch := range text {
embedding[i%dims] += float32(ch) / 1000.0
}
// Normalize to unit vector for cosine similarity
var norm float32
for _, v := range embedding {
norm += v * v
}
if norm > 0 {
norm = sqrt32(norm)
for i := range embedding {
embedding[i] /= norm
}
}
return embedding
}
func sqrt32(x float32) float32 {
// Newton's method for float32
z := x / 2
for i := 0; i < 10; i++ {
z = z - (z*z-x)/(2*z)
}
return z
}
func newTestStore(t *testing.T) *SemanticStore {
t.Helper()
dir := t.TempDir()
embedFn := func(_ context.Context, text string) ([]float32, error) {
return mockEmbeddingFunc(text), nil
}
store, err := NewSemanticStoreWithEmbedding(dir, embedFn)
if err != nil {
t.Fatalf("NewSemanticStoreWithEmbedding: %v", err)
}
return store
}
func TestSemanticStore_IsAvailable(t *testing.T) {
store := newTestStore(t)
if !store.IsAvailable() {
t.Error("expected store to be available")
}
}
func TestSemanticStore_RememberAndRecall(t *testing.T) {
store := newTestStore(t)
ctx := t.Context()
// Store some memories
entries := []MemoryEntry{
{Content: "User prefers dark mode in all applications", Category: "preference", Source: "agent"},
{Content: "The database password is rotated every 90 days", Category: "fact", Source: "agent"},
{Content: "We decided to use PostgreSQL instead of MySQL", Category: "decision", Source: "agent"},
}
for _, entry := range entries {
if err := store.Remember(ctx, entry); err != nil {
t.Fatalf("Remember(%q): %v", entry.Content, err)
}
}
// Recall with a query related to preferences
results, err := store.Recall(ctx, "What does the user prefer for themes?", 3)
if err != nil {
t.Fatalf("Recall: %v", err)
}
if len(results) != 3 {
t.Fatalf("expected 3 results, got %d", len(results))
}
// All results should have content
for _, r := range results {
if r.Content == "" {
t.Error("result has empty content")
}
if r.Similarity <= 0 {
t.Errorf("expected positive similarity, got %f", r.Similarity)
}
}
}
func TestSemanticStore_RecallEmpty(t *testing.T) {
store := newTestStore(t)
ctx := t.Context()
results, err := store.Recall(ctx, "anything", 5)
if err != nil {
t.Fatalf("Recall on empty store: %v", err)
}
if len(results) != 0 {
t.Errorf("expected 0 results from empty store, got %d", len(results))
}
}
func TestSemanticStore_RememberAutoID(t *testing.T) {
store := newTestStore(t)
ctx := t.Context()
entry := MemoryEntry{Content: "test content", Category: "fact"}
if err := store.Remember(ctx, entry); err != nil {
t.Fatalf("Remember: %v", err)
}
results, err := store.Recall(ctx, "test", 1)
if err != nil {
t.Fatalf("Recall: %v", err)
}
if len(results) != 1 {
t.Fatalf("expected 1 result, got %d", len(results))
}
if results[0].ID == "" {
t.Error("expected auto-generated ID, got empty")
}
}
func TestSemanticStore_MetadataPreserved(t *testing.T) {
store := newTestStore(t)
ctx := t.Context()
entry := MemoryEntry{
Content: "Important fact about the project",
Category: "fact",
Tags: []string{"project", "architecture"},
Source: "auto-extract",
}
if err := store.Remember(ctx, entry); err != nil {
t.Fatalf("Remember: %v", err)
}
results, err := store.Recall(ctx, "project fact", 1)
if err != nil {
t.Fatalf("Recall: %v", err)
}
if len(results) != 1 {
t.Fatalf("expected 1 result, got %d", len(results))
}
r := results[0]
if r.Category != "fact" {
t.Errorf("category = %q, want %q", r.Category, "fact")
}
if r.Source != "auto-extract" {
t.Errorf("source = %q, want %q", r.Source, "auto-extract")
}
if len(r.Tags) != 2 || r.Tags[0] != "project" || r.Tags[1] != "architecture" {
t.Errorf("tags = %v, want [project architecture]", r.Tags)
}
if r.Timestamp.IsZero() {
t.Error("expected non-zero timestamp")
}
}
func TestSemanticStore_RecallTopKCapped(t *testing.T) {
store := newTestStore(t)
ctx := t.Context()
// Store 2 entries, ask for 10
store.Remember(ctx, MemoryEntry{Content: "first memory"})
store.Remember(ctx, MemoryEntry{Content: "second memory"})
results, err := store.Recall(ctx, "memory", 10)
if err != nil {
t.Fatalf("Recall: %v", err)
}
if len(results) != 2 {
t.Errorf("expected 2 results (capped to collection size), got %d", len(results))
}
}
func TestSemanticStore_UnavailableStore(t *testing.T) {
store := &SemanticStore{available: false}
if store.IsAvailable() {
t.Error("expected unavailable store")
}
err := store.Remember(t.Context(), MemoryEntry{Content: "test"})
if err == nil {
t.Error("expected error from unavailable store Remember")
}
_, err = store.Recall(t.Context(), "test", 5)
if err == nil {
t.Error("expected error from unavailable store Recall")
}
}
func TestSemanticStore_Persistence(t *testing.T) {
dir := t.TempDir()
ctx := t.Context()
embedFn := func(_ context.Context, text string) ([]float32, error) {
return mockEmbeddingFunc(text), nil
}
// Create store and add memory
store1, err := NewSemanticStoreWithEmbedding(dir, embedFn)
if err != nil {
t.Fatalf("first store: %v", err)
}
store1.Remember(ctx, MemoryEntry{Content: "persistent memory test"})
// Create a second store from the same directory
store2, err := NewSemanticStoreWithEmbedding(dir, embedFn)
if err != nil {
t.Fatalf("second store: %v", err)
}
results, err := store2.Recall(ctx, "persistent", 1)
if err != nil {
t.Fatalf("Recall from second store: %v", err)
}
if len(results) != 1 {
t.Fatalf("expected 1 persisted result, got %d", len(results))
}
if results[0].Content != "persistent memory test" {
t.Errorf("content = %q, want %q", results[0].Content, "persistent memory test")
}
}
func TestNewSemanticStore_BadDir(t *testing.T) {
// Try to create a store in a path that can't exist
_, err := NewSemanticStoreWithEmbedding("/dev/null/impossible", nil)
if err == nil {
t.Error("expected error for impossible path")
}
}
func TestNewSemanticStore_WithOllamaDefaults(t *testing.T) {
// This tests the constructor with empty strings (uses defaults).
// It will fail to connect to Ollama in test env, but should return
// a store (possibly in degraded state) without panicking.
dir := t.TempDir()
defer os.RemoveAll(dir)
// We can't actually test with Ollama here, just verify no panic
store, _ := NewSemanticStore(dir, "http://127.0.0.1:1", "fake-model")
if store == nil {
t.Error("expected non-nil store even on connection failure")
}
}

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// ABOUTME: Recall tool for semantic search over stored memories.
// ABOUTME: Queries the vector store with natural language and returns ranked results.
package tools
import (
"context"
"fmt"
"strings"
"github.com/sipeed/picoclaw/pkg/memory"
)
// RecallTool performs semantic search over stored memories.
type RecallTool struct {
store memory.Store
}
func NewRecallTool(store memory.Store) *RecallTool {
return &RecallTool{store: store}
}
func (t *RecallTool) Name() string { return "recall" }
func (t *RecallTool) Description() string {
return "Search stored memories using natural language. Returns the most relevant memories ranked by similarity. Use this to recall facts, preferences, decisions, or context from previous conversations."
}
func (t *RecallTool) Parameters() map[string]any {
return map[string]any{
"type": "object",
"properties": map[string]any{
"query": map[string]any{
"type": "string",
"description": "Natural language search query describing what you want to recall.",
},
"top_k": map[string]any{
"type": "integer",
"description": "Number of results to return (default 5, max 20).",
},
},
"required": []any{"query"},
}
}
func (t *RecallTool) Execute(ctx context.Context, args map[string]any) *ToolResult {
if !t.store.IsAvailable() {
return ErrorResult("Semantic memory is not available. Ollama may not be running.")
}
query, _ := args["query"].(string)
if strings.TrimSpace(query) == "" {
return ErrorResult("query is required")
}
topK := 5
if k, ok := args["top_k"].(float64); ok && k > 0 {
topK = int(k)
}
results, err := t.store.Recall(ctx, query, topK)
if err != nil {
return ErrorResult("Failed to search memories: " + err.Error())
}
if len(results) == 0 {
return SilentResult("No memories found matching: " + query)
}
var sb strings.Builder
fmt.Fprintf(&sb, "Found %d memories:\n\n", len(results))
for i, r := range results {
fmt.Fprintf(&sb, "%d. [%.0f%% match] [%s] %s\n",
i+1, r.Similarity*100, r.Category, r.Content)
if len(r.Tags) > 0 {
fmt.Fprintf(&sb, " Tags: %s\n", strings.Join(r.Tags, ", "))
}
if !r.Timestamp.IsZero() {
fmt.Fprintf(&sb, " Stored: %s\n", r.Timestamp.Format("2006-01-02 15:04"))
}
}
return SilentResult(sb.String())
}

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// ABOUTME: Tests for the recall tool.
// ABOUTME: Uses a mock memory store to verify search and formatting behavior.
package tools
import (
"strings"
"testing"
"time"
"github.com/sipeed/picoclaw/pkg/memory"
)
func TestRecallTool_Name(t *testing.T) {
tool := NewRecallTool(&mockStore{available: true})
if got := tool.Name(); got != "recall" {
t.Errorf("Name() = %q, want %q", got, "recall")
}
}
func TestRecallTool_Execute_Success(t *testing.T) {
store := &mockStore{
available: true,
entries: []memory.MemoryEntry{
{
Content: "User prefers dark mode",
Category: "preference",
Tags: []string{"ui"},
Timestamp: time.Date(2026, 2, 22, 10, 0, 0, 0, time.UTC),
},
{
Content: "Database is PostgreSQL",
Category: "fact",
},
},
}
tool := NewRecallTool(store)
result := tool.Execute(t.Context(), map[string]any{
"query": "user preferences",
"top_k": float64(5),
})
if result.IsError {
t.Fatalf("expected success, got error: %s", result.ForLLM)
}
if !result.Silent {
t.Error("expected silent result")
}
if !strings.Contains(result.ForLLM, "Found 2 memories") {
t.Errorf("expected 'Found 2 memories' in result, got: %s", result.ForLLM)
}
if !strings.Contains(result.ForLLM, "dark mode") {
t.Errorf("expected 'dark mode' in result, got: %s", result.ForLLM)
}
if !strings.Contains(result.ForLLM, "90% match") {
t.Errorf("expected '90%% match' in result, got: %s", result.ForLLM)
}
}
func TestRecallTool_Execute_NoResults(t *testing.T) {
store := &mockStore{available: true, entries: nil}
tool := NewRecallTool(store)
result := tool.Execute(t.Context(), map[string]any{
"query": "nonexistent",
})
if result.IsError {
t.Fatalf("expected success (no results), got error: %s", result.ForLLM)
}
if !strings.Contains(result.ForLLM, "No memories found") {
t.Errorf("expected 'No memories found' in result, got: %s", result.ForLLM)
}
}
func TestRecallTool_Execute_EmptyQuery(t *testing.T) {
tool := NewRecallTool(&mockStore{available: true})
result := tool.Execute(t.Context(), map[string]any{
"query": "",
})
if !result.IsError {
t.Error("expected error for empty query")
}
}
func TestRecallTool_Execute_Unavailable(t *testing.T) {
tool := NewRecallTool(&mockStore{available: false})
result := tool.Execute(t.Context(), map[string]any{
"query": "test",
})
if !result.IsError {
t.Error("expected error when store unavailable")
}
}
func TestRecallTool_Execute_DefaultTopK(t *testing.T) {
// Ensure default top_k of 5 is used when not specified
store := &mockStore{
available: true,
entries: []memory.MemoryEntry{
{Content: "a", Category: "fact"},
{Content: "b", Category: "fact"},
{Content: "c", Category: "fact"},
{Content: "d", Category: "fact"},
{Content: "e", Category: "fact"},
{Content: "f", Category: "fact"},
},
}
tool := NewRecallTool(store)
result := tool.Execute(t.Context(), map[string]any{
"query": "test",
})
if result.IsError {
t.Fatalf("expected success, got error: %s", result.ForLLM)
}
if !strings.Contains(result.ForLLM, "Found 5 memories") {
t.Errorf("expected default top_k of 5, got: %s", result.ForLLM)
}
}

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// ABOUTME: Remember tool for storing semantic memories via vector embeddings.
// ABOUTME: Accepts content, category, and tags, and persists them for later recall.
package tools
import (
"context"
"strings"
"github.com/sipeed/picoclaw/pkg/memory"
)
// RememberTool stores a memory entry in the semantic memory store.
type RememberTool struct {
store memory.Store
}
func NewRememberTool(store memory.Store) *RememberTool {
return &RememberTool{store: store}
}
func (t *RememberTool) Name() string { return "remember" }
func (t *RememberTool) Description() string {
return "Store a memory for later recall. Use this to remember important facts, user preferences, decisions, or any information worth persisting across conversations."
}
func (t *RememberTool) Parameters() map[string]any {
return map[string]any{
"type": "object",
"properties": map[string]any{
"content": map[string]any{
"type": "string",
"description": "The information to remember. Be specific and self-contained.",
},
"category": map[string]any{
"type": "string",
"description": "Category: preference, fact, decision, context, or other.",
"enum": []string{"preference", "fact", "decision", "context", "other"},
},
"tags": map[string]any{
"type": "string",
"description": "Comma-separated tags for organization (e.g. 'project,database,architecture').",
},
},
"required": []any{"content"},
}
}
func (t *RememberTool) Execute(ctx context.Context, args map[string]any) *ToolResult {
if !t.store.IsAvailable() {
return ErrorResult("Semantic memory is not available. Ollama may not be running.")
}
content, _ := args["content"].(string)
if strings.TrimSpace(content) == "" {
return ErrorResult("content is required")
}
category, _ := args["category"].(string)
if category == "" {
category = "other"
}
var tags []string
if tagsStr, ok := args["tags"].(string); ok && tagsStr != "" {
for _, tag := range strings.Split(tagsStr, ",") {
tag = strings.TrimSpace(tag)
if tag != "" {
tags = append(tags, tag)
}
}
}
entry := memory.MemoryEntry{
Content: content,
Category: category,
Tags: tags,
Source: "agent",
}
if err := t.store.Remember(ctx, entry); err != nil {
return ErrorResult("Failed to store memory: " + err.Error())
}
return SilentResult("Memory stored successfully: " + content)
}

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// ABOUTME: Tests for the remember tool.
// ABOUTME: Uses a mock memory store to verify tool behavior without Ollama.
package tools
import (
"context"
"testing"
"github.com/sipeed/picoclaw/pkg/memory"
)
// mockStore implements memory.Store for testing.
type mockStore struct {
available bool
entries []memory.MemoryEntry
}
func (m *mockStore) IsAvailable() bool { return m.available }
func (m *mockStore) Count() int { return len(m.entries) }
func (m *mockStore) Remember(_ context.Context, entry memory.MemoryEntry) error {
m.entries = append(m.entries, entry)
return nil
}
func (m *mockStore) Recall(_ context.Context, query string, topK int) ([]memory.RecallResult, error) {
var results []memory.RecallResult
for i, e := range m.entries {
if i >= topK {
break
}
results = append(results, memory.RecallResult{
MemoryEntry: e,
Similarity: 0.9 - float32(i)*0.1,
})
}
return results, nil
}
func TestRememberTool_Name(t *testing.T) {
tool := NewRememberTool(&mockStore{available: true})
if got := tool.Name(); got != "remember" {
t.Errorf("Name() = %q, want %q", got, "remember")
}
}
func TestRememberTool_Execute_Success(t *testing.T) {
store := &mockStore{available: true}
tool := NewRememberTool(store)
result := tool.Execute(t.Context(), map[string]any{
"content": "User prefers dark mode",
"category": "preference",
"tags": "ui,theme",
})
if result.IsError {
t.Fatalf("expected success, got error: %s", result.ForLLM)
}
if !result.Silent {
t.Error("expected silent result")
}
if len(store.entries) != 1 {
t.Fatalf("expected 1 entry, got %d", len(store.entries))
}
entry := store.entries[0]
if entry.Content != "User prefers dark mode" {
t.Errorf("content = %q, want %q", entry.Content, "User prefers dark mode")
}
if entry.Category != "preference" {
t.Errorf("category = %q, want %q", entry.Category, "preference")
}
if len(entry.Tags) != 2 || entry.Tags[0] != "ui" || entry.Tags[1] != "theme" {
t.Errorf("tags = %v, want [ui theme]", entry.Tags)
}
if entry.Source != "agent" {
t.Errorf("source = %q, want %q", entry.Source, "agent")
}
}
func TestRememberTool_Execute_DefaultCategory(t *testing.T) {
store := &mockStore{available: true}
tool := NewRememberTool(store)
result := tool.Execute(t.Context(), map[string]any{
"content": "some fact",
})
if result.IsError {
t.Fatalf("expected success, got error: %s", result.ForLLM)
}
if store.entries[0].Category != "other" {
t.Errorf("category = %q, want default %q", store.entries[0].Category, "other")
}
}
func TestRememberTool_Execute_EmptyContent(t *testing.T) {
tool := NewRememberTool(&mockStore{available: true})
result := tool.Execute(t.Context(), map[string]any{
"content": "",
})
if !result.IsError {
t.Error("expected error for empty content")
}
}
func TestRememberTool_Execute_Unavailable(t *testing.T) {
tool := NewRememberTool(&mockStore{available: false})
result := tool.Execute(t.Context(), map[string]any{
"content": "test",
})
if !result.IsError {
t.Error("expected error when store unavailable")
}
}