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https://github.com/mudler/LocalAI.git
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* feat: add distributed mode (experimental) Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix data races, mutexes, transactions Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * refactorings Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fixups Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix events and tool stream in agent chat Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * use ginkgo Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * refactoring and consolidation Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * refactoring and consolidation Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * refactoring and consolidation Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * refactoring and consolidation Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * refactoring and consolidation Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * refactoring and consolidation Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * refactoring and consolidation Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * refactoring and consolidation Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(cron): compute correctly time boundaries avoiding re-triggering Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * enhancements, refactorings Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * do not flood of healthy checks Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * do not list obvious backends as text backends Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * tests fixups Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * refactoring and consolidation Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * Drop redundant healthcheck Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * enhancements, refactorings Signed-off-by: Ettore Di Giacinto <mudler@localai.io> --------- Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
263 lines
8.3 KiB
Go
263 lines
8.3 KiB
Go
package agents
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import (
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"bytes"
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"context"
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"encoding/json"
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"fmt"
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"io"
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"mime/multipart"
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"net/http"
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"strings"
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"time"
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"github.com/mudler/cogito"
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"github.com/mudler/xlog"
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)
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// KBSearchResult represents a search result from the knowledge base.
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type KBSearchResult struct {
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Content string `json:"content"`
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Score float64 `json:"score"`
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Similarity float64 `json:"similarity"`
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Metadata map[string]string `json:"metadata"`
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}
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// kbSearchResponse is the wrapper returned by the collection search endpoint.
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type kbSearchResponse struct {
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Results []KBSearchResult `json:"results"`
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Count int `json:"count"`
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}
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// KBAutoSearchPrompt queries the knowledge base with the user's message
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// and returns a system prompt block with relevant results.
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// Uses LocalAI's collection search endpoint via the API.
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func KBAutoSearchPrompt(ctx context.Context, apiURL, apiKey, collection, query string, maxResults int, userID string) string {
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if collection == "" || query == "" {
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return ""
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}
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if maxResults <= 0 {
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maxResults = 5
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}
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// Call LocalAI's collection search API
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searchURL := strings.TrimRight(apiURL, "/") + "/api/agents/collections/" + collection + "/search"
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if userID != "" {
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searchURL += "?user_id=" + userID
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}
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reqBody, _ := json.Marshal(map[string]any{
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"query": query,
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"max_results": maxResults,
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})
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req, err := http.NewRequestWithContext(ctx, http.MethodPost, searchURL, strings.NewReader(string(reqBody)))
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if err != nil {
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xlog.Warn("KB auto-search: failed to create request", "error", err)
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return ""
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}
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req.Header.Set("Content-Type", "application/json")
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if apiKey != "" {
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req.Header.Set("Authorization", "Bearer "+apiKey)
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}
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resp, err := http.DefaultClient.Do(req)
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if err != nil {
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xlog.Warn("KB auto-search: request failed", "error", err)
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return ""
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}
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defer resp.Body.Close()
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if resp.StatusCode != http.StatusOK {
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body, _ := io.ReadAll(resp.Body)
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xlog.Warn("KB auto-search: non-200 response", "status", resp.StatusCode, "body", string(body))
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return ""
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}
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var searchResp kbSearchResponse
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if err := json.NewDecoder(resp.Body).Decode(&searchResp); err != nil {
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xlog.Warn("KB auto-search: failed to decode response", "error", err)
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return ""
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}
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if len(searchResp.Results) == 0 {
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return ""
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}
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// Format results as a system prompt block (same format as LocalAGI)
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var sb strings.Builder
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sb.WriteString("Given the user input you have the following in memory:\n")
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for i, r := range searchResp.Results {
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sb.WriteString(fmt.Sprintf("- %s", r.Content))
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if len(r.Metadata) > 0 {
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meta, _ := json.Marshal(r.Metadata)
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sb.WriteString(fmt.Sprintf(" (%s)", string(meta)))
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}
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if i < len(searchResp.Results)-1 {
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sb.WriteString("\n")
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}
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}
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return sb.String()
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}
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// KBSearchMemoryArgs defines the arguments for the search_memory tool.
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type KBSearchMemoryArgs struct {
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Query string `json:"query" jsonschema:"description=The search query to find relevant information in memory"`
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}
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// KBSearchMemoryTool implements the search_memory MCP tool.
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type KBSearchMemoryTool struct {
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APIURL string
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APIKey string
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Collection string
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MaxResults int
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UserID string
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}
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func (t KBSearchMemoryTool) Run(args KBSearchMemoryArgs) (string, any, error) {
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ctx, cancel := context.WithTimeout(context.Background(), 30*time.Second)
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defer cancel()
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result := KBAutoSearchPrompt(ctx, t.APIURL, t.APIKey, t.Collection, args.Query, t.MaxResults, t.UserID)
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if result == "" {
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return "No results found.", nil, nil
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}
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return result, nil, nil
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}
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// KBAddMemoryArgs defines the arguments for the add_memory tool.
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type KBAddMemoryArgs struct {
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Content string `json:"content" jsonschema:"description=The content to store in memory for later retrieval"`
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}
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// KBAddMemoryTool implements the add_memory MCP tool.
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type KBAddMemoryTool struct {
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APIURL string
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APIKey string
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Collection string
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UserID string
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}
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func (t KBAddMemoryTool) Run(args KBAddMemoryArgs) (string, any, error) {
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if args.Content == "" {
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return "No content provided.", nil, nil
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}
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ctx, cancel := context.WithTimeout(context.Background(), 30*time.Second)
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defer cancel()
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err := KBStoreContent(ctx, t.APIURL, t.APIKey, t.Collection, args.Content, t.UserID)
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if err != nil {
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xlog.Warn("add_memory: failed to store content", "error", err, "collection", t.Collection)
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return fmt.Sprintf("Failed to store content: %v", err), nil, nil
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}
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return "Content stored in memory.", nil, nil
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}
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// KBStoreContent uploads text content to a collection via the multipart upload API.
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func KBStoreContent(ctx context.Context, apiURL, apiKey, collection, content, userID string) error {
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uploadURL := strings.TrimRight(apiURL, "/") + "/api/agents/collections/" + collection + "/upload"
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if userID != "" {
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uploadURL += "?user_id=" + userID
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}
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// Build multipart form with the text content as a file
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var buf bytes.Buffer
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writer := multipart.NewWriter(&buf)
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filename := fmt.Sprintf("memory_%d.txt", time.Now().UnixNano())
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part, err := writer.CreateFormFile("file", filename)
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if err != nil {
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return fmt.Errorf("failed to create form file: %w", err)
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}
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if _, err := io.Copy(part, strings.NewReader(content)); err != nil {
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return fmt.Errorf("failed to write content: %w", err)
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}
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writer.Close()
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req, err := http.NewRequestWithContext(ctx, http.MethodPost, uploadURL, &buf)
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if err != nil {
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return fmt.Errorf("failed to create request: %w", err)
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}
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req.Header.Set("Content-Type", writer.FormDataContentType())
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if apiKey != "" {
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req.Header.Set("Authorization", "Bearer "+apiKey)
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}
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resp, err := http.DefaultClient.Do(req)
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if err != nil {
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return fmt.Errorf("upload request failed: %w", err)
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}
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defer resp.Body.Close()
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if resp.StatusCode != http.StatusOK {
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body, _ := io.ReadAll(resp.Body)
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return fmt.Errorf("upload failed (status %d): %s", resp.StatusCode, string(body))
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}
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return nil
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}
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// saveConversationToKB stores conversation content in the agent's KB collection
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// based on the configured storage mode and summary settings.
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func saveConversationToKB(ctx context.Context, llm cogito.LLM, apiURL, apiKey string, cfg *AgentConfig, userMessage, assistantResponse, userID string) {
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if apiURL == "" || cfg.Name == "" {
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return
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}
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mode := cfg.ConversationStorageMode
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if mode == "" {
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mode = ConvStorageUserOnly
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}
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// If summary mode is enabled, summarize the conversation first
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if cfg.SummaryLongTermMemory {
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summary := summarizeConversation(ctx, llm, userMessage, assistantResponse)
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if summary != "" {
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if err := KBStoreContent(ctx, apiURL, apiKey, cfg.Name, summary, userID); err != nil {
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xlog.Warn("Failed to store conversation summary in KB", "agent", cfg.Name, "error", err)
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}
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}
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return
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}
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switch mode {
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case ConvStorageUserOnly:
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if err := KBStoreContent(ctx, apiURL, apiKey, cfg.Name, userMessage, userID); err != nil {
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xlog.Warn("Failed to store user message in KB", "agent", cfg.Name, "error", err)
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}
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case ConvStorageUserAndAssistant:
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if err := KBStoreContent(ctx, apiURL, apiKey, cfg.Name, "User: "+userMessage, userID); err != nil {
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xlog.Warn("Failed to store user message in KB", "agent", cfg.Name, "error", err)
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}
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if err := KBStoreContent(ctx, apiURL, apiKey, cfg.Name, "Assistant: "+assistantResponse, userID); err != nil {
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xlog.Warn("Failed to store assistant response in KB", "agent", cfg.Name, "error", err)
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}
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case ConvStorageWholeConversation:
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block := "User: " + userMessage + "\nAssistant: " + assistantResponse
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if err := KBStoreContent(ctx, apiURL, apiKey, cfg.Name, block, userID); err != nil {
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xlog.Warn("Failed to store conversation in KB", "agent", cfg.Name, "error", err)
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}
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}
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}
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// summarizeConversation uses the LLM to summarize a conversation exchange.
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func summarizeConversation(ctx context.Context, llm cogito.LLM, userMessage, assistantResponse string) string {
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prompt := fmt.Sprintf(
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"Summarize the conversation below, keep the highlights as a bullet list:\n\nUser: %s\nAssistant: %s",
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userMessage, assistantResponse,
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)
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fragment := cogito.NewEmptyFragment().
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AddMessage(cogito.SystemMessageRole, "You are a helpful summarizer. Produce a concise bullet-point summary.").
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AddMessage(cogito.UserMessageRole, prompt)
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result, err := cogito.ExecuteTools(llm, fragment, cogito.WithContext(ctx))
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if err != nil {
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xlog.Warn("Failed to summarize conversation", "error", err)
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return ""
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}
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if len(result.Messages) > 0 {
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return result.Messages[len(result.Messages)-1].Content
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}
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return ""
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}
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