rogee
6d8eda28b5
- token_estimator.go (new): TokenEstimator with ~4 chars/token heuristic, EstimateText/EstimateMessages methods, TruncateMessages sliding window that drops oldest messages to fit token budget, BuildContextWindow entry point that converts conversation messages to LLM format with token-budgeted truncation (default 4096 tokens) - copilot_context_service.go: fetch up to 100 messages (was 20), then apply BuildContextWindow truncation to fit within 4096 token budget; log how many messages were dropped Verified: go build + go vet + go test all pass Semantic search route reaches handler (times out on LLM call without API key, confirming route + service wiring is correct)
322 lines
11 KiB
Go
322 lines
11 KiB
Go
package service
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import (
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"context"
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"fmt"
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"strings"
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"github.com/gochat/gochat/internal/llm"
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"github.com/gochat/gochat/internal/model"
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"github.com/gochat/gochat/internal/repository"
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applogger "github.com/gochat/gochat/pkg/logger"
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)
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// CopilotContextService provides conversation context injection for Copilot LLM calls.
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// Reference: Chatwoot Captain::Copilot::ChatService — current_viewing_history + account context
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//
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// This service retrieves the conversation the agent is currently viewing,
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// formats it as LLM context, and enriches Copilot prompts with real data.
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type CopilotContextService struct {
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messageRepo *repository.MessageRepo
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conversationRepo *repository.ConversationRepo
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contactRepo *repository.ContactRepo
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llmProvider llm.Provider
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}
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// NewCopilotContextService creates a new CopilotContextService.
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func NewCopilotContextService(
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messageRepo *repository.MessageRepo,
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conversationRepo *repository.ConversationRepo,
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contactRepo *repository.ContactRepo,
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llmProvider llm.Provider,
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) *CopilotContextService {
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return &CopilotContextService{
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messageRepo: messageRepo,
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conversationRepo: conversationRepo,
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contactRepo: contactRepo,
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llmProvider: llmProvider,
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}
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}
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// --- Conversation Context Building ---
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// Reference: Chatwoot Captain::Copilot::ChatService#current_viewing_history
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// ConversationContext holds formatted context from the currently viewed conversation.
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type ConversationContext struct {
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ConversationID uint `json:"conversation_id"`
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ContactName string `json:"contact_name,omitempty"`
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ContactEmail string `json:"contact_email,omitempty"`
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Messages []ContextMessage `json:"messages"`
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Summary string `json:"summary,omitempty"`
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}
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// ContextMessage is a simplified message format for LLM context injection.
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type ContextMessage struct {
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Role string `json:"role"` // "customer" or "agent"
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Content string `json:"content"`
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Timestamp string `json:"timestamp,omitempty"`
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}
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// GetCurrentViewingContext retrieves and formats the conversation context
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// that the agent is currently viewing, to inject into Copilot LLM calls.
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func (s *CopilotContextService) GetCurrentViewingContext(ctx context.Context, accountID, conversationID uint) (*ConversationContext, error) {
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// Get conversation messages (fetch up to 100, then truncate by token budget)
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messages, _, err := s.messageRepo.FindByConversation(ctx, conversationID, 0, 100)
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if err != nil {
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applogger.L().Errorf("GetCurrentViewingContext FindByConversation: %v", err)
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return nil, fmt.Errorf("retrieve conversation messages: %w", err)
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}
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// Get conversation for contact info
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conversation, err := s.conversationRepo.FindByID(ctx, conversationID)
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if err != nil {
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applogger.L().Errorf("GetCurrentViewingContext GetByID: %v", err)
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return nil, fmt.Errorf("retrieve conversation: %w", err)
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}
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// Build context
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context := &ConversationContext{
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ConversationID: conversationID,
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}
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// Add contact details if available
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if conversation.ContactID != 0 {
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contact, err := s.contactRepo.FindByID(ctx, conversation.ContactID)
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if err == nil && contact != nil {
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context.ContactName = contact.Name
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context.ContactEmail = contact.Email
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}
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}
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// Format messages for LLM context with token-budgeted truncation
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// (keeps most recent messages, drops older ones to fit token budget)
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convMsgs := make([]ConversationMessage, 0, len(messages))
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for _, m := range messages {
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// Skip activity/template messages
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if m.MessageType == "activity" || m.ContentType != "text" {
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continue
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}
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convMsgs = append(convMsgs, ConversationMessage{
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Content: m.Content,
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MessageType: m.MessageType,
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})
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}
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truncated, dropped := BuildContextWindow(convMsgs, 4096)
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if dropped > 0 {
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applogger.L().Infof("GetCurrentViewingContext: truncated %d older messages to fit token budget", dropped)
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}
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for _, msg := range truncated {
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role := "customer"
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if msg.Role == "assistant" {
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role = "agent"
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}
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context.Messages = append(context.Messages, ContextMessage{
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Role: role,
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Content: msg.Content,
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})
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}
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return context, nil
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}
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// BuildCopilotSystemPrompt constructs the system prompt for Copilot chat.
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// Incorporates assistant configuration, product context, and available tools.
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// Reference: Chatwoot Captain::Copilot::ChatService system_message building
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func BuildCopilotSystemPrompt(assistant *model.CaptainAssistant, assistantConfig *model.AssistantConfig, context *ConversationContext) string {
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var parts []string
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// Base identity
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parts = append(parts, "You are an AI copilot assistant helping a customer support agent.")
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// Product context from assistant config
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if assistantConfig != nil && assistantConfig.ProductName != "" {
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parts = append(parts, fmt.Sprintf("The agent is supporting customers of the product: %s.", assistantConfig.ProductName))
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}
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// Assistant name and description
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if assistant != nil {
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parts = append(parts, fmt.Sprintf("Your name is %s.", assistant.Name))
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if assistant.Description != "" {
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parts = append(parts, fmt.Sprintf("Your role: %s.", assistant.Description))
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}
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}
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// Response guidelines
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if assistant != nil && assistant.ResponseGuidelines != nil {
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guidelines, _ := assistant.GetResponseGuidelines()
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if guidelines != "" {
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parts = append(parts, "Response guidelines:\n" + guidelines)
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}
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}
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// Feature flags context
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if assistantConfig != nil {
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if assistantConfig.FeatureFAQ {
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parts = append(parts, "You have access to FAQ knowledge base search. Use it to find relevant answers.")
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}
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if assistantConfig.FeatureMemory {
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parts = append(parts, "You can remember previous interactions with this customer.")
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}
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if assistantConfig.FeatureContactAttributes {
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parts = append(parts, "You can access customer contact attributes and history.")
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}
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}
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// Conversation context injection
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if context != nil && len(context.Messages) > 0 {
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parts = append(parts, "\nCurrently viewed conversation context:")
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if context.ContactName != "" {
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parts = append(parts, fmt.Sprintf("Customer: %s", context.ContactName))
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if context.ContactEmail != "" {
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parts = append(parts, fmt.Sprintf("Email: %s", context.ContactEmail))
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}
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}
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parts = append(parts, "Conversation messages:")
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for _, msg := range context.Messages {
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parts = append(parts, fmt.Sprintf("[%s] %s: %s", msg.Timestamp, msg.Role, msg.Content))
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}
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}
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// Behavioral guidelines
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parts = append(parts, "\nBehavior guidelines:")
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parts = append(parts, "- Be concise and actionable in your suggestions.")
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parts = append(parts, "- Prioritize accuracy over speed; cite sources when possible.")
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parts = append(parts, "- When suggesting replies, tailor them to the customer's tone and urgency.")
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parts = append(parts, "- If you're unsure, say so rather than guessing.")
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parts = append(parts, "- Always respond in the same language as the user's message.")
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return strings.Join(parts, "\n")
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}
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// BuildCopilotToolDefinitions creates tool definitions for Copilot LLM function calling.
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// Reference: Chatwoot Captain::Copilot tools — GetConversation, SearchConversations,
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// GetContact, SearchArticles, SearchContacts, SearchLinearIssues, SearchDocumentation
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func BuildCopilotToolDefinitions() []llm.ToolDefinition {
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return []llm.ToolDefinition{
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{
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Type: "function",
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Function: llm.ToolFunction{
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Name: "search_documentation",
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Description: "Search the knowledge base / FAQ documentation for relevant information to answer the customer's question.",
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Parameters: map[string]interface{}{
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"type": "object",
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"properties": map[string]interface{}{
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"query": map[string]interface{}{
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"type": "string",
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"description": "The search query to find relevant documentation.",
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},
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},
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"required": []string{"query"},
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},
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},
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},
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{
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Type: "function",
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Function: llm.ToolFunction{
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Name: "get_conversation",
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Description: "Get details about a specific conversation including messages and metadata.",
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Parameters: map[string]interface{}{
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"type": "object",
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"properties": map[string]interface{}{
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"conversation_id": map[string]interface{}{
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"type": "integer",
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"description": "The ID of the conversation to retrieve.",
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},
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},
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"required": []string{"conversation_id"},
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},
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},
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},
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{
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Type: "function",
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Function: llm.ToolFunction{
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Name: "search_conversations",
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Description: "Search conversations by status, assignee, or content to find related cases.",
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Parameters: map[string]interface{}{
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"type": "object",
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"properties": map[string]interface{}{
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"query": map[string]interface{}{
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"type": "string",
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"description": "Search query for conversation content.",
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},
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"status": map[string]interface{}{
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"type": "string",
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"description": "Filter by conversation status (open, closed, pending).",
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},
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},
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"required": []string{"query"},
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},
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},
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},
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{
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Type: "function",
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Function: llm.ToolFunction{
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Name: "get_contact",
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Description: "Get details about a specific contact including name, email, and custom attributes.",
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Parameters: map[string]interface{}{
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"type": "object",
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"properties": map[string]interface{}{
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"contact_id": map[string]interface{}{
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"type": "integer",
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"description": "The ID of the contact to retrieve.",
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},
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},
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"required": []string{"contact_id"},
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},
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},
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},
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{
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Type: "function",
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Function: llm.ToolFunction{
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Name: "search_contacts",
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Description: "Search contacts by name, email, or custom attributes.",
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Parameters: map[string]interface{}{
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"type": "object",
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"properties": map[string]interface{}{
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"query": map[string]interface{}{
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"type": "string",
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"description": "Search query for contact information.",
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},
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},
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"required": []string{"query"},
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},
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},
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},
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{
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Type: "function",
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Function: llm.ToolFunction{
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Name: "get_article",
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Description: "Get a specific help center article by ID.",
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Parameters: map[string]interface{}{
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"type": "object",
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"properties": map[string]interface{}{
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"article_id": map[string]interface{}{
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"type": "integer",
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"description": "The ID of the article to retrieve.",
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},
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},
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"required": []string{"article_id"},
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},
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},
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},
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{
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Type: "function",
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Function: llm.ToolFunction{
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Name: "search_articles",
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Description: "Search help center articles by title or content.",
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Parameters: map[string]interface{}{
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"type": "object",
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"properties": map[string]interface{}{
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"query": map[string]interface{}{
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"type": "string",
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"description": "Search query for article content.",
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},
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},
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"required": []string{"query"},
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},
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},
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},
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}
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} |