feat: make context compression dynamic and add thinking animation
- Implement dynamic context window awareness for compression thresholds - Add 'Thinking' animation for Telegram channel with auto-edit response - Refactor summarization to handle multi-part batches and oversized messages
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@@ -27,6 +27,7 @@ type AgentLoop struct {
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provider providers.LLMProvider
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workspace string
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model string
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contextWindow int
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maxIterations int
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sessions *session.SessionManager
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contextBuilder *ContextBuilder
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@@ -56,6 +57,7 @@ func NewAgentLoop(cfg *config.Config, bus *bus.MessageBus, provider providers.LL
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provider: provider,
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workspace: workspace,
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model: cfg.Agents.Defaults.Model,
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contextWindow: cfg.Agents.Defaults.MaxTokens,
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maxIterations: cfg.Agents.Defaults.MaxToolIterations,
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sessions: sessionsManager,
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contextBuilder: NewContextBuilder(workspace),
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@@ -198,7 +200,13 @@ func (al *AgentLoop) processMessage(ctx context.Context, msg bus.InboundMessage)
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// Context compression logic
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newHistory := al.sessions.GetHistory(msg.SessionKey)
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if len(newHistory) > 20 {
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// Token Awareness (Dynamic)
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// Trigger if history > 20 messages OR estimated tokens > 75% of context window
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tokenEstimate := al.estimateTokens(newHistory)
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threshold := al.contextWindow * 75 / 100
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if len(newHistory) > 20 || tokenEstimate > threshold {
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if _, loading := al.summarizing.LoadOrStore(msg.SessionKey, true); !loading {
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go func() {
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defer al.summarizing.Delete(msg.SessionKey)
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@@ -213,55 +221,104 @@ func (al *AgentLoop) processMessage(ctx context.Context, msg bus.InboundMessage)
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}
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func (al *AgentLoop) summarizeSession(sessionKey string) {
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ctx, cancel := context.WithTimeout(context.Background(), 60*time.Second)
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ctx, cancel := context.WithTimeout(context.Background(), 120*time.Second)
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defer cancel()
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history := al.sessions.GetHistory(sessionKey)
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summary := al.sessions.GetSummary(sessionKey)
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// Keep last 4 messages, summarize the rest
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// Keep last 4 messages for continuity
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if len(history) <= 4 {
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return
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}
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toSummarize := history[:len(history)-4]
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prompt := "Below is a conversation history and an optional existing summary. " +
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"Please provide a concise summary of the conversation so far, " +
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"preserving the core context and key points discussed. " +
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"If there's an existing summary, incorporate it into the new one.\n\n"
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// Oversized Message Guard (Dynamic)
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// Skip messages larger than 50% of context window to prevent summarizer overflow.
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maxMessageTokens := al.contextWindow / 2
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validMessages := make([]providers.Message, 0)
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omitted := false
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if summary != "" {
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prompt += "EXISTING SUMMARY: " + summary + "\n\n"
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}
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prompt += "CONVERSATION TO SUMMARIZE:\n"
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for _, m := range toSummarize {
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if m.Role == "user" || m.Role == "assistant" {
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prompt += fmt.Sprintf("%s: %s\n", m.Role, m.Content)
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if m.Role != "user" && m.Role != "assistant" {
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continue
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}
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// Estimate tokens for this message
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msgTokens := len(m.Content) / 4
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if msgTokens > maxMessageTokens {
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omitted = true
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continue
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}
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validMessages = append(validMessages, m)
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}
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messages := []providers.Message{
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{
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Role: "user",
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Content: prompt,
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},
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}
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response, err := al.provider.Chat(ctx, messages, nil, al.model, map[string]interface{}{
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"max_tokens": 1024,
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"temperature": 0.3,
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})
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if err != nil {
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fmt.Printf("Error summarizing session %s: %v\n", sessionKey, err)
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if len(validMessages) == 0 {
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return
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}
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if response.Content != "" {
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al.sessions.SetSummary(sessionKey, response.Content)
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// Multi-Part Summarization
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// Split into two parts if history is significant
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var finalSummary string
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if len(validMessages) > 10 {
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mid := len(validMessages) / 2
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part1 := validMessages[:mid]
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part2 := validMessages[mid:]
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s1, _ := al.summarizeBatch(ctx, part1, "")
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s2, _ := al.summarizeBatch(ctx, part2, "")
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// Merge them
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mergePrompt := fmt.Sprintf("Merge these two conversation summaries into one cohesive summary:\n\n1: %s\n\n2: %s", s1, s2)
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resp, err := al.provider.Chat(ctx, []providers.Message{{Role: "user", Content: mergePrompt}}, nil, al.model, map[string]interface{}{
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"max_tokens": 1024,
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"temperature": 0.3,
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})
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if err == nil {
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finalSummary = resp.Content
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} else {
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finalSummary = s1 + " " + s2
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}
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} else {
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finalSummary, _ = al.summarizeBatch(ctx, validMessages, summary)
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}
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if omitted && finalSummary != "" {
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finalSummary += "\n[Note: Some oversized messages were omitted from this summary for efficiency.]"
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}
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if finalSummary != "" {
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al.sessions.SetSummary(sessionKey, finalSummary)
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al.sessions.TruncateHistory(sessionKey, 4)
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al.sessions.Save(al.sessions.GetOrCreate(sessionKey))
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}
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}
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func (al *AgentLoop) summarizeBatch(ctx context.Context, batch []providers.Message, existingSummary string) (string, error) {
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prompt := "Provide a concise summary of this conversation segment, preserving core context and key points.\n"
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if existingSummary != "" {
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prompt += "Existing context: " + existingSummary + "\n"
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}
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prompt += "\nCONVERSATION:\n"
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for _, m := range batch {
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prompt += fmt.Sprintf("%s: %s\n", m.Role, m.Content)
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}
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response, err := al.provider.Chat(ctx, []providers.Message{{Role: "user", Content: prompt}}, nil, al.model, map[string]interface{}{
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"max_tokens": 1024,
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"temperature": 0.3,
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})
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if err != nil {
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return "", err
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}
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return response.Content, nil
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}
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func (al *AgentLoop) estimateTokens(messages []providers.Message) int {
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total := 0
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for _, m := range messages {
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total += len(m.Content) / 4 // Simple heuristic: 4 chars per token
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}
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return total
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}
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