Files
picoclaw/pkg/agent/loop.go
2026-02-11 00:11:39 +08:00

367 lines
9.7 KiB
Go

// PicoClaw - Ultra-lightweight personal AI agent
// Inspired by and based on nanobot: https://github.com/HKUDS/nanobot
// License: MIT
//
// Copyright (c) 2026 PicoClaw contributors
package agent
import (
"context"
"encoding/json"
"fmt"
"os"
"path/filepath"
"sync"
"time"
"github.com/sipeed/picoclaw/pkg/bus"
"github.com/sipeed/picoclaw/pkg/config"
"github.com/sipeed/picoclaw/pkg/logger"
"github.com/sipeed/picoclaw/pkg/providers"
"github.com/sipeed/picoclaw/pkg/session"
"github.com/sipeed/picoclaw/pkg/tools"
)
type AgentLoop struct {
bus *bus.MessageBus
provider providers.LLMProvider
workspace string
model string
contextWindow int
maxIterations int
sessions *session.SessionManager
contextBuilder *ContextBuilder
tools *tools.ToolRegistry
running bool
summarizing sync.Map
}
func NewAgentLoop(cfg *config.Config, bus *bus.MessageBus, provider providers.LLMProvider) *AgentLoop {
workspace := cfg.WorkspacePath()
os.MkdirAll(workspace, 0755)
toolsRegistry := tools.NewToolRegistry()
toolsRegistry.Register(&tools.ReadFileTool{})
toolsRegistry.Register(&tools.WriteFileTool{})
toolsRegistry.Register(&tools.ListDirTool{})
toolsRegistry.Register(tools.NewExecTool(workspace))
braveAPIKey := cfg.Tools.Web.Search.APIKey
toolsRegistry.Register(tools.NewWebSearchTool(braveAPIKey, cfg.Tools.Web.Search.MaxResults))
toolsRegistry.Register(tools.NewWebFetchTool(50000))
sessionsManager := session.NewSessionManager(filepath.Join(filepath.Dir(cfg.WorkspacePath()), "sessions"))
return &AgentLoop{
bus: bus,
provider: provider,
workspace: workspace,
model: cfg.Agents.Defaults.Model,
contextWindow: cfg.Agents.Defaults.MaxTokens,
maxIterations: cfg.Agents.Defaults.MaxToolIterations,
sessions: sessionsManager,
contextBuilder: NewContextBuilder(workspace),
tools: toolsRegistry,
running: false,
summarizing: sync.Map{},
}
}
func (al *AgentLoop) Run(ctx context.Context) error {
al.running = true
for al.running {
select {
case <-ctx.Done():
return nil
default:
msg, ok := al.bus.ConsumeInbound(ctx)
if !ok {
continue
}
response, err := al.processMessage(ctx, msg)
if err != nil {
response = fmt.Sprintf("Error processing message: %v", err)
}
if response != "" {
al.bus.PublishOutbound(bus.OutboundMessage{
Channel: msg.Channel,
ChatID: msg.ChatID,
Content: response,
})
}
}
}
return nil
}
func (al *AgentLoop) Stop() {
al.running = false
}
func (al *AgentLoop) ProcessDirect(ctx context.Context, content, sessionKey string) (string, error) {
msg := bus.InboundMessage{
Channel: "cli",
SenderID: "user",
ChatID: "direct",
Content: content,
SessionKey: sessionKey,
}
return al.processMessage(ctx, msg)
}
func (al *AgentLoop) processMessage(ctx context.Context, msg bus.InboundMessage) (string, error) {
logger.InfoCF("agent", "Processing message",
map[string]interface{}{
"channel": msg.Channel,
"chat_id": msg.ChatID,
"sender_id": msg.SenderID,
"session_key": msg.SessionKey,
})
history := al.sessions.GetHistory(msg.SessionKey)
summary := al.sessions.GetSummary(msg.SessionKey)
messages := al.contextBuilder.BuildMessages(
history,
summary,
msg.Content,
nil,
)
iteration := 0
var finalContent string
for iteration < al.maxIterations {
iteration++
logger.DebugCF("agent", "LLM iteration",
map[string]interface{}{
"iteration": iteration,
"max": al.maxIterations,
})
toolDefs := al.tools.GetDefinitions()
providerToolDefs := make([]providers.ToolDefinition, 0, len(toolDefs))
for _, td := range toolDefs {
providerToolDefs = append(providerToolDefs, providers.ToolDefinition{
Type: td["type"].(string),
Function: providers.ToolFunctionDefinition{
Name: td["function"].(map[string]interface{})["name"].(string),
Description: td["function"].(map[string]interface{})["description"].(string),
Parameters: td["function"].(map[string]interface{})["parameters"].(map[string]interface{}),
},
})
}
response, err := al.provider.Chat(ctx, messages, providerToolDefs, al.model, map[string]interface{}{
"max_tokens": 8192,
"temperature": 0.7,
})
if err != nil {
logger.ErrorCF("agent", "LLM call failed",
map[string]interface{}{
"iteration": iteration,
"error": err.Error(),
})
return "", fmt.Errorf("LLM call failed: %w", err)
}
if len(response.ToolCalls) == 0 {
finalContent = response.Content
logger.InfoCF("agent", "LLM response without tool calls (direct answer)",
map[string]interface{}{
"iteration": iteration,
"content_chars": len(finalContent),
})
break
}
toolNames := make([]string, 0, len(response.ToolCalls))
for _, tc := range response.ToolCalls {
toolNames = append(toolNames, tc.Name)
}
logger.InfoCF("agent", "LLM requested tool calls",
map[string]interface{}{
"tools": toolNames,
"count": len(toolNames),
"iteration": iteration,
})
assistantMsg := providers.Message{
Role: "assistant",
Content: response.Content,
}
for _, tc := range response.ToolCalls {
argumentsJSON, _ := json.Marshal(tc.Arguments)
assistantMsg.ToolCalls = append(assistantMsg.ToolCalls, providers.ToolCall{
ID: tc.ID,
Type: "function",
Function: &providers.FunctionCall{
Name: tc.Name,
Arguments: string(argumentsJSON),
},
})
}
messages = append(messages, assistantMsg)
for _, tc := range response.ToolCalls {
result, err := al.tools.Execute(ctx, tc.Name, tc.Arguments)
if err != nil {
result = fmt.Sprintf("Error: %v", err)
}
toolResultMsg := providers.Message{
Role: "tool",
Content: result,
ToolCallID: tc.ID,
}
messages = append(messages, toolResultMsg)
}
}
if finalContent == "" {
finalContent = "I've completed processing but have no response to give."
}
al.sessions.AddMessage(msg.SessionKey, "user", msg.Content)
al.sessions.AddMessage(msg.SessionKey, "assistant", finalContent)
// Context compression logic
newHistory := al.sessions.GetHistory(msg.SessionKey)
// Token Awareness (Dynamic)
// Trigger if history > 20 messages OR estimated tokens > 75% of context window
tokenEstimate := al.estimateTokens(newHistory)
threshold := al.contextWindow * 75 / 100
if len(newHistory) > 20 || tokenEstimate > threshold {
if _, loading := al.summarizing.LoadOrStore(msg.SessionKey, true); !loading {
go func() {
defer al.summarizing.Delete(msg.SessionKey)
al.summarizeSession(msg.SessionKey)
}()
}
}
al.sessions.Save(al.sessions.GetOrCreate(msg.SessionKey))
logger.InfoCF("agent", "Message processing completed",
map[string]interface{}{
"iterations": iteration,
"final_length": len(finalContent),
})
return finalContent, nil
}
func (al *AgentLoop) summarizeSession(sessionKey string) {
ctx, cancel := context.WithTimeout(context.Background(), 120*time.Second)
defer cancel()
history := al.sessions.GetHistory(sessionKey)
summary := al.sessions.GetSummary(sessionKey)
// Keep last 4 messages for continuity
if len(history) <= 4 {
return
}
toSummarize := history[:len(history)-4]
// Oversized Message Guard (Dynamic)
// Skip messages larger than 50% of context window to prevent summarizer overflow.
maxMessageTokens := al.contextWindow / 2
validMessages := make([]providers.Message, 0)
omitted := false
for _, m := range toSummarize {
if m.Role != "user" && m.Role != "assistant" {
continue
}
// Estimate tokens for this message
msgTokens := len(m.Content) / 4
if msgTokens > maxMessageTokens {
omitted = true
continue
}
validMessages = append(validMessages, m)
}
if len(validMessages) == 0 {
return
}
// Multi-Part Summarization
// Split into two parts if history is significant
var finalSummary string
if len(validMessages) > 10 {
mid := len(validMessages) / 2
part1 := validMessages[:mid]
part2 := validMessages[mid:]
s1, _ := al.summarizeBatch(ctx, part1, "")
s2, _ := al.summarizeBatch(ctx, part2, "")
// Merge them
mergePrompt := fmt.Sprintf("Merge these two conversation summaries into one cohesive summary:\n\n1: %s\n\n2: %s", s1, s2)
resp, err := al.provider.Chat(ctx, []providers.Message{{Role: "user", Content: mergePrompt}}, nil, al.model, map[string]interface{}{
"max_tokens": 1024,
"temperature": 0.3,
})
if err == nil {
finalSummary = resp.Content
} else {
finalSummary = s1 + " " + s2
}
} else {
finalSummary, _ = al.summarizeBatch(ctx, validMessages, summary)
}
if omitted && finalSummary != "" {
finalSummary += "\n[Note: Some oversized messages were omitted from this summary for efficiency.]"
}
if finalSummary != "" {
al.sessions.SetSummary(sessionKey, finalSummary)
al.sessions.TruncateHistory(sessionKey, 4)
al.sessions.Save(al.sessions.GetOrCreate(sessionKey))
}
}
func (al *AgentLoop) summarizeBatch(ctx context.Context, batch []providers.Message, existingSummary string) (string, error) {
prompt := "Provide a concise summary of this conversation segment, preserving core context and key points.\n"
if existingSummary != "" {
prompt += "Existing context: " + existingSummary + "\n"
}
prompt += "\nCONVERSATION:\n"
for _, m := range batch {
prompt += fmt.Sprintf("%s: %s\n", m.Role, m.Content)
}
response, err := al.provider.Chat(ctx, []providers.Message{{Role: "user", Content: prompt}}, nil, al.model, map[string]interface{}{
"max_tokens": 1024,
"temperature": 0.3,
})
if err != nil {
return "", err
}
return response.Content, nil
}
func (al *AgentLoop) estimateTokens(messages []providers.Message) int {
total := 0
for _, m := range messages {
total += len(m.Content) / 4 // Simple heuristic: 4 chars per token
}
return total
}