// 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" "strings" "sync" "sync/atomic" "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" "github.com/sipeed/picoclaw/pkg/utils" ) type AgentLoop struct { bus *bus.MessageBus provider providers.LLMProvider workspace string model string contextWindow int // Maximum context window size in tokens maxIterations int sessions *session.SessionManager contextBuilder *ContextBuilder tools *tools.ToolRegistry running atomic.Bool summarizing sync.Map // Tracks which sessions are currently being summarized } // processOptions configures how a message is processed type processOptions struct { SessionKey string // Session identifier for history/context Channel string // Target channel for tool execution ChatID string // Target chat ID for tool execution UserMessage string // User message content (may include prefix) DefaultResponse string // Response when LLM returns empty EnableSummary bool // Whether to trigger summarization SendResponse bool // Whether to send response via bus } func NewAgentLoop(cfg *config.Config, msgBus *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)) // Register message tool messageTool := tools.NewMessageTool() messageTool.SetSendCallback(func(channel, chatID, content string) error { msgBus.PublishOutbound(bus.OutboundMessage{ Channel: channel, ChatID: chatID, Content: content, }) return nil }) toolsRegistry.Register(messageTool) // Register spawn tool subagentManager := tools.NewSubagentManager(provider, workspace, msgBus) spawnTool := tools.NewSpawnTool(subagentManager) toolsRegistry.Register(spawnTool) // Register edit file tool editFileTool := tools.NewEditFileTool(workspace) toolsRegistry.Register(editFileTool) sessionsManager := session.NewSessionManager(filepath.Join(workspace, "sessions")) // Create context builder and set tools registry contextBuilder := NewContextBuilder(workspace) contextBuilder.SetToolsRegistry(toolsRegistry) return &AgentLoop{ bus: msgBus, provider: provider, workspace: workspace, model: cfg.Agents.Defaults.Model, contextWindow: cfg.Agents.Defaults.MaxTokens, // Restore context window for summarization maxIterations: cfg.Agents.Defaults.MaxToolIterations, sessions: sessionsManager, contextBuilder: contextBuilder, tools: toolsRegistry, summarizing: sync.Map{}, } } func (al *AgentLoop) Run(ctx context.Context) error { al.running.Store(true) for al.running.Load() { 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.Store(false) } func (al *AgentLoop) RegisterTool(tool tools.Tool) { al.tools.Register(tool) } func (al *AgentLoop) ProcessDirect(ctx context.Context, content, sessionKey string) (string, error) { return al.ProcessDirectWithChannel(ctx, content, sessionKey, "cli", "direct") } func (al *AgentLoop) ProcessDirectWithChannel(ctx context.Context, content, sessionKey, channel, chatID string) (string, error) { msg := bus.InboundMessage{ Channel: channel, SenderID: "cron", ChatID: chatID, Content: content, SessionKey: sessionKey, } return al.processMessage(ctx, msg) } func (al *AgentLoop) processMessage(ctx context.Context, msg bus.InboundMessage) (string, error) { // Add message preview to log preview := utils.Truncate(msg.Content, 80) logger.InfoCF("agent", fmt.Sprintf("Processing message from %s:%s: %s", msg.Channel, msg.SenderID, preview), map[string]interface{}{ "channel": msg.Channel, "chat_id": msg.ChatID, "sender_id": msg.SenderID, "session_key": msg.SessionKey, }) // Route system messages to processSystemMessage if msg.Channel == "system" { return al.processSystemMessage(ctx, msg) } // Process as user message return al.runAgentLoop(ctx, processOptions{ SessionKey: msg.SessionKey, Channel: msg.Channel, ChatID: msg.ChatID, UserMessage: msg.Content, DefaultResponse: "I've completed processing but have no response to give.", EnableSummary: true, SendResponse: false, }) } func (al *AgentLoop) processSystemMessage(ctx context.Context, msg bus.InboundMessage) (string, error) { // Verify this is a system message if msg.Channel != "system" { return "", fmt.Errorf("processSystemMessage called with non-system message channel: %s", msg.Channel) } logger.InfoCF("agent", "Processing system message", map[string]interface{}{ "sender_id": msg.SenderID, "chat_id": msg.ChatID, }) // Parse origin from chat_id (format: "channel:chat_id") var originChannel, originChatID string if idx := strings.Index(msg.ChatID, ":"); idx > 0 { originChannel = msg.ChatID[:idx] originChatID = msg.ChatID[idx+1:] } else { // Fallback originChannel = "cli" originChatID = msg.ChatID } // Use the origin session for context sessionKey := fmt.Sprintf("%s:%s", originChannel, originChatID) // Process as system message with routing back to origin return al.runAgentLoop(ctx, processOptions{ SessionKey: sessionKey, Channel: originChannel, ChatID: originChatID, UserMessage: fmt.Sprintf("[System: %s] %s", msg.SenderID, msg.Content), DefaultResponse: "Background task completed.", EnableSummary: false, SendResponse: true, // Send response back to original channel }) } // runAgentLoop is the core message processing logic. // It handles context building, LLM calls, tool execution, and response handling. func (al *AgentLoop) runAgentLoop(ctx context.Context, opts processOptions) (string, error) { // 1. Update tool contexts al.updateToolContexts(opts.Channel, opts.ChatID) // 2. Build messages history := al.sessions.GetHistory(opts.SessionKey) summary := al.sessions.GetSummary(opts.SessionKey) messages := al.contextBuilder.BuildMessages( history, summary, opts.UserMessage, nil, opts.Channel, opts.ChatID, ) // 3. Save user message to session al.sessions.AddMessage(opts.SessionKey, "user", opts.UserMessage) // 4. Run LLM iteration loop finalContent, iteration, lastToolResult, err := al.runLLMIteration(ctx, messages, opts) if err != nil { return "", err } // If last tool had ForUser content and we already sent it, we might not need to send final response // This is controlled by the tool's Silent flag and ForUser content _ = lastToolResult // Use lastToolResult for future decisions (e.g., US-008 callback injection) // 5. Handle empty response if finalContent == "" { finalContent = opts.DefaultResponse } // 6. Save final assistant message to session al.sessions.AddMessage(opts.SessionKey, "assistant", finalContent) al.sessions.Save(al.sessions.GetOrCreate(opts.SessionKey)) // 7. Optional: summarization if opts.EnableSummary { al.maybeSummarize(opts.SessionKey) } // 8. Optional: send response via bus if opts.SendResponse { al.bus.PublishOutbound(bus.OutboundMessage{ Channel: opts.Channel, ChatID: opts.ChatID, Content: finalContent, }) } // 9. Log response responsePreview := utils.Truncate(finalContent, 120) logger.InfoCF("agent", fmt.Sprintf("Response: %s", responsePreview), map[string]interface{}{ "session_key": opts.SessionKey, "iterations": iteration, "final_length": len(finalContent), }) return finalContent, nil } // runLLMIteration executes the LLM call loop with tool handling. // Returns the final content, iteration count, last tool result, and any error. func (al *AgentLoop) runLLMIteration(ctx context.Context, messages []providers.Message, opts processOptions) (string, int, *tools.ToolResult, error) { iteration := 0 var finalContent string var lastToolResult *tools.ToolResult for iteration < al.maxIterations { iteration++ logger.DebugCF("agent", "LLM iteration", map[string]interface{}{ "iteration": iteration, "max": al.maxIterations, }) // Build tool definitions 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{}), }, }) } // Log LLM request details logger.DebugCF("agent", "LLM request", map[string]interface{}{ "iteration": iteration, "model": al.model, "messages_count": len(messages), "tools_count": len(providerToolDefs), "max_tokens": 8192, "temperature": 0.7, "system_prompt_len": len(messages[0].Content), }) // Log full messages (detailed) logger.DebugCF("agent", "Full LLM request", map[string]interface{}{ "iteration": iteration, "messages_json": formatMessagesForLog(messages), "tools_json": formatToolsForLog(providerToolDefs), }) // Call LLM 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 "", iteration, nil, fmt.Errorf("LLM call failed: %w", err) } // Check if no tool calls - we're done 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 } // Log tool calls 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(response.ToolCalls), "iteration": iteration, }) // Build assistant message with tool calls 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) // Save assistant message with tool calls to session al.sessions.AddFullMessage(opts.SessionKey, assistantMsg) // Execute tool calls for _, tc := range response.ToolCalls { // Log tool call with arguments preview argsJSON, _ := json.Marshal(tc.Arguments) argsPreview := utils.Truncate(string(argsJSON), 200) logger.InfoCF("agent", fmt.Sprintf("Tool call: %s(%s)", tc.Name, argsPreview), map[string]interface{}{ "tool": tc.Name, "iteration": iteration, }) // Create async callback for tools that implement AsyncTool // This callback sends async completion results to the user asyncCallback := func(callbackCtx context.Context, result *tools.ToolResult) { // Send ForUser content to user if not silent if !result.Silent && result.ForUser != "" { al.bus.PublishOutbound(bus.OutboundMessage{ Channel: opts.Channel, ChatID: opts.ChatID, Content: result.ForUser, }) logger.InfoCF("agent", "Async tool result sent to user", map[string]interface{}{ "tool": tc.Name, "content_len": len(result.ForUser), }) } } toolResult := al.tools.ExecuteWithContext(ctx, tc.Name, tc.Arguments, opts.Channel, opts.ChatID, asyncCallback) lastToolResult = toolResult // Send ForUser content to user immediately if not Silent if !toolResult.Silent && toolResult.ForUser != "" && opts.SendResponse { al.bus.PublishOutbound(bus.OutboundMessage{ Channel: opts.Channel, ChatID: opts.ChatID, Content: toolResult.ForUser, }) logger.DebugCF("agent", "Sent tool result to user", map[string]interface{}{ "tool": tc.Name, "content_len": len(toolResult.ForUser), }) } // Determine content for LLM based on tool result contentForLLM := toolResult.ForLLM if contentForLLM == "" && toolResult.Err != nil { contentForLLM = toolResult.Err.Error() } toolResultMsg := providers.Message{ Role: "tool", Content: contentForLLM, ToolCallID: tc.ID, } messages = append(messages, toolResultMsg) // Save tool result message to session al.sessions.AddFullMessage(opts.SessionKey, toolResultMsg) } } return finalContent, iteration, lastToolResult, nil } // updateToolContexts updates the context for tools that need channel/chatID info. func (al *AgentLoop) updateToolContexts(channel, chatID string) { // Use ContextualTool interface instead of type assertions if tool, ok := al.tools.Get("message"); ok { if mt, ok := tool.(tools.ContextualTool); ok { mt.SetContext(channel, chatID) } } if tool, ok := al.tools.Get("spawn"); ok { if st, ok := tool.(tools.ContextualTool); ok { st.SetContext(channel, chatID) } } } // maybeSummarize triggers summarization if the session history exceeds thresholds. func (al *AgentLoop) maybeSummarize(sessionKey string) { newHistory := al.sessions.GetHistory(sessionKey) tokenEstimate := al.estimateTokens(newHistory) threshold := al.contextWindow * 75 / 100 if len(newHistory) > 20 || tokenEstimate > threshold { if _, loading := al.summarizing.LoadOrStore(sessionKey, true); !loading { go func() { defer al.summarizing.Delete(sessionKey) al.summarizeSession(sessionKey) }() } } } // GetStartupInfo returns information about loaded tools and skills for logging. func (al *AgentLoop) GetStartupInfo() map[string]interface{} { info := make(map[string]interface{}) // Tools info tools := al.tools.List() info["tools"] = map[string]interface{}{ "count": len(tools), "names": tools, } // Skills info info["skills"] = al.contextBuilder.GetSkillsInfo() return info } // formatMessagesForLog formats messages for logging func formatMessagesForLog(messages []providers.Message) string { if len(messages) == 0 { return "[]" } var result string result += "[\n" for i, msg := range messages { result += fmt.Sprintf(" [%d] Role: %s\n", i, msg.Role) if msg.ToolCalls != nil && len(msg.ToolCalls) > 0 { result += " ToolCalls:\n" for _, tc := range msg.ToolCalls { result += fmt.Sprintf(" - ID: %s, Type: %s, Name: %s\n", tc.ID, tc.Type, tc.Name) if tc.Function != nil { result += fmt.Sprintf(" Arguments: %s\n", utils.Truncate(tc.Function.Arguments, 200)) } } } if msg.Content != "" { content := utils.Truncate(msg.Content, 200) result += fmt.Sprintf(" Content: %s\n", content) } if msg.ToolCallID != "" { result += fmt.Sprintf(" ToolCallID: %s\n", msg.ToolCallID) } result += "\n" } result += "]" return result } // formatToolsForLog formats tool definitions for logging func formatToolsForLog(tools []providers.ToolDefinition) string { if len(tools) == 0 { return "[]" } var result string result += "[\n" for i, tool := range tools { result += fmt.Sprintf(" [%d] Type: %s, Name: %s\n", i, tool.Type, tool.Function.Name) result += fmt.Sprintf(" Description: %s\n", tool.Function.Description) if len(tool.Function.Parameters) > 0 { result += fmt.Sprintf(" Parameters: %s\n", utils.Truncate(fmt.Sprintf("%v", tool.Function.Parameters), 200)) } } result += "]" return result } // summarizeSession summarizes the conversation history for a session. 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 // 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)) } } // summarizeBatch summarizes a batch of messages. 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 } // estimateTokens estimates the number of tokens in a message list. 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 }