feat(reminders): add reminder system to perform long-term goals in the background (#176)
* feat(reminders): add self-ability to set reminders Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(reminders): surface reminders result to the user as new conversations Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * Fixups * Subscribe all connectors to agents new messages Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * Set reminders in the list * fix(telegram): do not always auth Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * Small fixups * Improve UX Signed-off-by: Ettore Di Giacinto <mudler@localai.io> --------- Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
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Ettore Di Giacinto
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@@ -15,6 +15,7 @@ import (
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"github.com/mudler/LocalAGI/core/action"
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"github.com/mudler/LocalAGI/core/types"
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"github.com/mudler/LocalAGI/pkg/llm"
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"github.com/robfig/cron/v3"
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"github.com/sashabaranov/go-openai"
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)
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@@ -1026,25 +1027,83 @@ func (a *Agent) periodicallyRun(timer *time.Timer) {
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xlog.Debug("Agent is running periodically", "agent", a.Character.Name)
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// TODO: Would be nice if we have a special action to
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// contact the user. This would actually make sure that
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// if the agent wants to initiate a conversation, it can do so.
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// This would be a special action that would be picked up by the agent
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// and would be used to contact the user.
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// Check for reminders that need to be triggered
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now := time.Now()
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var triggeredReminders []types.ReminderActionResponse
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var remainingReminders []types.ReminderActionResponse
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// if len(conv()) != 0 {
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// // Here the LLM could decide to store some part of the conversation too in the memory
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// evaluateMemory := NewJob(
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// WithText(
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// `Evaluate the current conversation and decide if we need to store some relevant informations from it`,
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// ),
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// WithReasoningCallback(a.options.reasoningCallback),
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// WithResultCallback(a.options.resultCallback),
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// )
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// a.consumeJob(evaluateMemory, SystemRole)
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for _, reminder := range a.sharedState.Reminders {
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xlog.Debug("Checking reminder", "reminder", reminder)
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if now.After(reminder.NextRun) {
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triggeredReminders = append(triggeredReminders, reminder)
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xlog.Debug("Reminder triggered", "reminder", reminder)
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// Calculate next run time for recurring reminders
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if reminder.IsRecurring {
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xlog.Debug("Reminder is recurring", "reminder", reminder)
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parser := cron.NewParser(cron.Second | cron.Minute | cron.Hour | cron.Dom | cron.Month | cron.Dow)
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schedule, err := parser.Parse(reminder.CronExpr)
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if err == nil {
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nextRun := schedule.Next(now)
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xlog.Debug("Next run time", "reminder", reminder, "nextRun", nextRun)
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reminder.LastRun = now
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reminder.NextRun = nextRun
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remainingReminders = append(remainingReminders, reminder)
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}
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}
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} else {
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xlog.Debug("Reminder not triggered", "reminder", reminder)
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remainingReminders = append(remainingReminders, reminder)
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}
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}
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// a.ResetConversation()
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// }
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// Update the reminders list
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a.sharedState.Reminders = remainingReminders
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// Handle triggered reminders
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for _, reminder := range triggeredReminders {
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xlog.Info("Processing triggered reminder", "agent", a.Character.Name, "message", reminder.Message)
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// Create a more natural conversation flow for the reminder
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reminderJob := types.NewJob(
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types.WithText(fmt.Sprintf("I have a reminder for you: %s", reminder.Message)),
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types.WithReasoningCallback(a.options.reasoningCallback),
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types.WithResultCallback(a.options.resultCallback),
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)
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// Add the reminder message to the job's metadata
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reminderJob.Metadata = map[string]interface{}{
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"message": reminder.Message,
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"is_reminder": true,
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}
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// Process the reminder as a normal conversation
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a.consumeJob(reminderJob, UserRole, a.options.loopDetectionSteps)
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// After the reminder job is complete, ensure the user is notified
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if reminderJob.Result != nil && reminderJob.Result.Conversation != nil {
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// Get the last assistant message from the conversation
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var lastAssistantMsg *openai.ChatCompletionMessage
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for i := len(reminderJob.Result.Conversation) - 1; i >= 0; i-- {
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if reminderJob.Result.Conversation[i].Role == AssistantRole {
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lastAssistantMsg = &reminderJob.Result.Conversation[i]
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break
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}
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}
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if lastAssistantMsg != nil && lastAssistantMsg.Content != "" {
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// Send the reminder response to the user
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msg := openai.ChatCompletionMessage{
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Role: "assistant",
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Content: fmt.Sprintf("Reminder Update: %s\n\n%s", reminder.Message, lastAssistantMsg.Content),
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}
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go func(agent *Agent) {
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xlog.Info("Sending reminder response to user", "agent", agent.Character.Name, "message", msg.Content)
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agent.newConversations <- msg
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}(a)
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}
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}
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}
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if !a.options.standaloneJob {
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return
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@@ -1056,7 +1115,6 @@ func (a *Agent) periodicallyRun(timer *time.Timer) {
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// - evaluating the result
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// - asking the agent to do something else based on the result
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// whatNext := NewJob(WithText("Decide what to do based on the state"))
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whatNext := types.NewJob(
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types.WithText(innerMonologueTemplate),
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types.WithReasoningCallback(a.options.reasoningCallback),
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@@ -1065,31 +1123,6 @@ func (a *Agent) periodicallyRun(timer *time.Timer) {
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a.consumeJob(whatNext, SystemRole, a.options.loopDetectionSteps)
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xlog.Info("STOP -- Periodically run is done", "agent", a.Character.Name)
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// Save results from state
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// a.ResetConversation()
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// doWork := NewJob(WithText("Select the tool to use based on your goal and the current state."))
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// a.consumeJob(doWork, SystemRole)
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// results := []string{}
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// for _, v := range doWork.Result.State {
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// results = append(results, v.Result)
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// }
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// a.ResetConversation()
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// // Here the LLM could decide to do something based on the result of our automatic action
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// evaluateAction := NewJob(
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// WithText(
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// `Evaluate the current situation and decide if we need to execute other tools (for instance to store results into permanent, or short memory).
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// We have done the following actions:
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// ` + strings.Join(results, "\n"),
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// ))
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// a.consumeJob(evaluateAction, SystemRole)
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// a.ResetConversation()
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}
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func (a *Agent) Run() error {
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