d0cfc4c317
* switch to observer pattern Signed-off-by: mudler <mudler@localai.io> * keep conversation history in telegram and slack * generalize with conversation tracker --------- Signed-off-by: mudler <mudler@localai.io>
108 lines
3.3 KiB
Go
108 lines
3.3 KiB
Go
package agent
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import (
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"fmt"
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"os"
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"path/filepath"
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"time"
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"github.com/mudler/LocalAgent/pkg/xlog"
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"github.com/sashabaranov/go-openai"
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)
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func (a *Agent) knowledgeBaseLookup(conv Messages) {
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if (!a.options.enableKB && !a.options.enableLongTermMemory && !a.options.enableSummaryMemory) ||
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len(conv) <= 0 {
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xlog.Debug("[Knowledge Base Lookup] Disabled, skipping", "agent", a.Character.Name)
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return
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}
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// Walk conversation from bottom to top, and find the first message of the user
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// to use it as a query to the KB
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userMessage := conv.GetLatestUserMessage().Content
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xlog.Info("[Knowledge Base Lookup] Last user message", "agent", a.Character.Name, "message", userMessage, "lastMessage", conv.GetLatestUserMessage())
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if userMessage == "" {
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xlog.Info("[Knowledge Base Lookup] No user message found in conversation", "agent", a.Character.Name)
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return
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}
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results, err := a.options.ragdb.Search(userMessage, a.options.kbResults)
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if err != nil {
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xlog.Info("Error finding similar strings inside KB:", "error", err)
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}
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if len(results) == 0 {
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xlog.Info("[Knowledge Base Lookup] No similar strings found in KB", "agent", a.Character.Name)
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return
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}
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formatResults := ""
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for _, r := range results {
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formatResults += fmt.Sprintf("- %s \n", r)
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}
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xlog.Info("[Knowledge Base Lookup] Found similar strings in KB", "agent", a.Character.Name, "results", formatResults)
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// conv = append(conv,
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// openai.ChatCompletionMessage{
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// Role: "system",
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// Content: fmt.Sprintf("Given the user input you have the following in memory:\n%s", formatResults),
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// },
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// )
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conv = append([]openai.ChatCompletionMessage{
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{
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Role: "system",
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Content: fmt.Sprintf("Given the user input you have the following in memory:\n%s", formatResults),
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}}, conv...)
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}
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func (a *Agent) saveConversation(m Messages, prefix string) error {
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if a.options.conversationsPath == "" {
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return nil
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}
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dateTime := time.Now().Format("2006-01-02-15-04-05")
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fileName := a.Character.Name + "-" + dateTime + ".json"
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if prefix != "" {
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fileName = prefix + "-" + fileName
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}
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os.MkdirAll(a.options.conversationsPath, os.ModePerm)
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return m.Save(filepath.Join(a.options.conversationsPath, fileName))
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}
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func (a *Agent) saveCurrentConversation(conv Messages) {
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if err := a.saveConversation(conv, ""); err != nil {
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xlog.Error("Error saving conversation", "error", err)
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}
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if !a.options.enableLongTermMemory && !a.options.enableSummaryMemory {
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xlog.Debug("Long term memory is disabled", "agent", a.Character.Name)
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return
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}
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xlog.Info("Saving conversation", "agent", a.Character.Name, "conversation size", len(conv))
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if a.options.enableSummaryMemory && len(conv) > 0 {
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msg, err := a.askLLM(a.context.Context, []openai.ChatCompletionMessage{{
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Role: "user",
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Content: "Summarize the conversation below, keep the highlights as a bullet list:\n" + Messages(conv).String(),
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}})
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if err != nil {
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xlog.Error("Error summarizing conversation", "error", err)
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}
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if err := a.options.ragdb.Store(msg.Content); err != nil {
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xlog.Error("Error storing into memory", "error", err)
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}
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} else {
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for _, message := range conv {
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if message.Role == "user" {
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if err := a.options.ragdb.Store(message.Content); err != nil {
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xlog.Error("Error storing into memory", "error", err)
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}
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}
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}
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}
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}
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