Add memory system, dynamic tool loading, and fix logging issues
- Add MemoryStore for persistent long-term and daily notes - Add dynamic tool summary generation in system prompt - Fix YAML frontmatter parsing for nanobot skill format - Add GetSummaries() method to ToolRegistry - Fix DebugCF logging to use structured metadata - Improve web_search and shell tool descriptions
This commit is contained in:
yinwm
@@ -78,7 +78,7 @@ func NewAgentLoop(cfg *config.Config, msgBus *bus.MessageBus, provider providers
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model: cfg.Agents.Defaults.Model,
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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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contextBuilder: NewContextBuilder(workspace, func() []string { return toolsRegistry.GetSummaries() }),
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tools: toolsRegistry,
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running: false,
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}
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@@ -159,12 +159,8 @@ func (al *AgentLoop) processMessage(ctx context.Context, msg bus.InboundMessage)
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}
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}
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history := al.sessions.GetHistory(msg.SessionKey)
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summary := al.sessions.GetSummary(msg.SessionKey)
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messages := al.contextBuilder.BuildMessages(
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history,
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summary,
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al.sessions.GetHistory(msg.SessionKey),
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msg.Content,
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nil,
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msg.Channel,
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@@ -196,6 +192,26 @@ func (al *AgentLoop) processMessage(ctx context.Context, msg bus.InboundMessage)
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})
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}
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// Log LLM request details
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logger.DebugCF("agent", "LLM request",
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map[string]interface{}{
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"iteration": iteration,
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"model": al.model,
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"messages_count": len(messages),
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"tools_count": len(providerToolDefs),
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"max_tokens": 8192,
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"temperature": 0.7,
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"system_prompt_len": len(messages[0].Content),
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})
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// Log full messages (detailed)
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logger.DebugCF("agent", "Full LLM request",
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map[string]interface{}{
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"iteration": iteration,
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"messages_json": formatMessagesForLog(messages),
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"tools_json": formatToolsForLog(providerToolDefs),
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})
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response, err := al.provider.Chat(ctx, messages, providerToolDefs, al.model, map[string]interface{}{
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"max_tokens": 8192,
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"temperature": 0.7,
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@@ -331,11 +347,8 @@ func (al *AgentLoop) processSystemMessage(ctx context.Context, msg bus.InboundMe
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}
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// Build messages with the announce content
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history := al.sessions.GetHistory(sessionKey)
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summary := al.sessions.GetSummary(sessionKey)
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messages := al.contextBuilder.BuildMessages(
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history,
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summary,
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al.sessions.GetHistory(sessionKey),
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msg.Content,
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nil,
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originChannel,
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@@ -361,6 +374,26 @@ func (al *AgentLoop) processSystemMessage(ctx context.Context, msg bus.InboundMe
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})
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}
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// Log LLM request details
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logger.DebugCF("agent", "LLM request",
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map[string]interface{}{
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"iteration": iteration,
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"model": al.model,
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"messages_count": len(messages),
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"tools_count": len(providerToolDefs),
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"max_tokens": 8192,
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"temperature": 0.7,
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"system_prompt_len": len(messages[0].Content),
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})
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// Log full messages (detailed)
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logger.DebugCF("agent", "Full LLM request",
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map[string]interface{}{
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"iteration": iteration,
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"messages_json": formatMessagesForLog(messages),
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"tools_json": formatToolsForLog(providerToolDefs),
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})
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response, err := al.provider.Chat(ctx, messages, providerToolDefs, al.model, map[string]interface{}{
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"max_tokens": 8192,
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"temperature": 0.7,
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@@ -462,104 +495,64 @@ func (al *AgentLoop) GetStartupInfo() map[string]interface{} {
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return info
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}
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func (al *AgentLoop) summarizeSession(sessionKey string) {
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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 for continuity
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if len(history) <= 4 {
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return
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// formatMessagesForLog formats messages for logging
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func formatMessagesForLog(messages []providers.Message) string {
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if len(messages) == 0 {
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return "[]"
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}
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toSummarize := history[:len(history)-4]
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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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for _, m := range toSummarize {
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if m.Role != "user" && m.Role != "assistant" {
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continue
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var result string
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result += "[\n"
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for i, msg := range messages {
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result += fmt.Sprintf(" [%d] Role: %s\n", i, msg.Role)
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if msg.ToolCalls != nil && len(msg.ToolCalls) > 0 {
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result += " ToolCalls:\n"
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for _, tc := range msg.ToolCalls {
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result += fmt.Sprintf(" - ID: %s, Type: %s, Name: %s\n", tc.ID, tc.Type, tc.Name)
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if tc.Function != nil {
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result += fmt.Sprintf(" Arguments: %s\n", truncateString(tc.Function.Arguments, 200))
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}
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}
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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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if msg.Content != "" {
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content := truncateString(msg.Content, 200)
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result += fmt.Sprintf(" Content: %s\n", content)
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}
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validMessages = append(validMessages, m)
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}
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if len(validMessages) == 0 {
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return
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}
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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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if msg.ToolCallID != "" {
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result += fmt.Sprintf(" ToolCallID: %s\n", msg.ToolCallID)
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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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result += "\n"
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}
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result += "]"
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return result
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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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// formatToolsForLog formats tool definitions for logging
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func formatToolsForLog(tools []providers.ToolDefinition) string {
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if len(tools) == 0 {
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return "[]"
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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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var result string
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result += "[\n"
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for i, tool := range tools {
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result += fmt.Sprintf(" [%d] Type: %s, Name: %s\n", i, tool.Type, tool.Function.Name)
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result += fmt.Sprintf(" Description: %s\n", tool.Function.Description)
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if len(tool.Function.Parameters) > 0 {
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result += fmt.Sprintf(" Parameters: %s\n", truncateString(fmt.Sprintf("%v", tool.Function.Parameters), 200))
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}
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}
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return response.Content, nil
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result += "]"
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return result
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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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// truncateString truncates a string to max length
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func truncateString(s string, maxLen int) string {
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if len(s) <= maxLen {
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return s
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}
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return total
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if maxLen <= 3 {
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return s[:maxLen]
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}
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return s[:maxLen-3] + "..."
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}
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