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Add long term memory

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This commit is contained in:
mudler
2024-12-17 19:53:07 +01:00
parent d053dc249c
commit 2561f2f175
6 changed files with 104 additions and 47 deletions
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9
agent/actions.go
View File

@@ -68,6 +68,7 @@ func (a *Agent) decision(
Tools: tools,
ToolChoice: toolchoice,
}
resp, err := a.client.CreateChatCompletion(ctx, decision)
if err != nil {
return nil, err
@@ -96,6 +97,14 @@ func (m Messages) ToOpenAI() []openai.ChatCompletionMessage {
return []openai.ChatCompletionMessage(m)
}
func (m Messages) String() string {
s := ""
for _, cc := range m {
s += cc.Role + ": " + cc.Content + "\n"
}
return s
}
func (m Messages) Exist(content string) bool {
for _, cc := range m {
if cc.Content == content {

92
agent/agent.go
View File

@@ -151,14 +151,50 @@ func (a *Agent) SetConversation(conv []openai.ChatCompletionMessage) {
a.currentConversation = conv
}
func (a *Agent) askLLM(ctx context.Context, conversation []openai.ChatCompletionMessage) (openai.ChatCompletionMessage, error) {
resp, err := a.client.CreateChatCompletion(ctx,
openai.ChatCompletionRequest{
Model: a.options.LLMAPI.Model,
Messages: conversation,
},
)
if err != nil {
return openai.ChatCompletionMessage{}, err
}
if len(resp.Choices) != 1 {
return openai.ChatCompletionMessage{}, fmt.Errorf("no enough choices: %w", err)
}
return resp.Choices[0].Message, nil
}
func (a *Agent) ResetConversation() {
a.Lock()
defer a.Unlock()
xlog.Info("Resetting conversation", "agent", a.Character.Name)
// store into memory the conversation before pruning it
// TODO: Shall we summarize the conversation into a bullet list of highlights
// using the LLM instead?
if a.options.enableKB {
if a.options.enableLongTermMemory {
xlog.Info("Saving conversation", "agent", a.Character.Name, "conversation size", len(a.currentConversation))
if a.options.enableSummaryMemory {
msg, err := a.askLLM(a.context.Context, []openai.ChatCompletionMessage{{
Role: "user",
Content: "Summarize the conversation below, keep the highlights as a bullet list:\n" + Messages(a.currentConversation).String(),
}})
if err != nil {
xlog.Error("Error summarizing conversation", "error", err)
}
if err := a.options.ragdb.Store(msg.Content); err != nil {
xlog.Error("Error storing into memory", "error", err)
}
} else {
for _, message := range a.currentConversation {
if message.Role == "user" {
if err := a.options.ragdb.Store(message.Content); err != nil {
@@ -168,6 +204,8 @@ func (a *Agent) ResetConversation() {
}
}
}
a.currentConversation = []openai.ChatCompletionMessage{}
}
@@ -612,34 +650,15 @@ func (a *Agent) consumeJob(job *Job, role string) {
return
}
resp, err := a.client.CreateChatCompletion(ctx,
openai.ChatCompletionRequest{
Model: a.options.LLMAPI.Model,
// Force the AI to response without using any tool
// Why: some models might be silly enough to attempt to call tools even if evaluated
// that a reply was not necessary anymore
Messages: append(a.currentConversation, openai.ChatCompletionMessage{
msg, err := a.askLLM(ctx, append(a.currentConversation, openai.ChatCompletionMessage{
Role: "system",
Content: "The assistant needs to reply without using any tool.",
// + replyResponse.Message,
},
),
//Messages: a.currentConversation,
},
)
}))
if err != nil {
job.Result.Finish(err)
return
}
if len(resp.Choices) != 1 {
job.Result.Finish(fmt.Errorf("no enough choices: %w", err))
return
}
// display OpenAI's response to the original question utilizing our function
msg := resp.Choices[0].Message
// If we didn't got any message, we can use the response from the action
if chosenAction.Definition().Name.Is(action.ReplyActionName) && msg.Content == "" ||
strings.Contains(msg.Content, "<tool_call>") {
@@ -661,9 +680,6 @@ func (a *Agent) periodicallyRun(timer *time.Timer) {
// Remember always to reset the timer - if we don't the agent will stop..
defer timer.Reset(a.options.periodicRuns)
if !a.options.standaloneJob {
return
}
a.StopAction()
xlog.Debug("Agent is running periodically", "agent", a.Character.Name)
@@ -675,18 +691,24 @@ func (a *Agent) periodicallyRun(timer *time.Timer) {
xlog.Info("START -- Periodically run is starting")
if len(a.CurrentConversation()) != 0 {
// Here the LLM could decide to store some part of the conversation too in the memory
evaluateMemory := NewJob(
WithText(
`Evaluate the current conversation and decide if we need to store some relevant informations from it`,
),
WithReasoningCallback(a.options.reasoningCallback),
WithResultCallback(a.options.resultCallback),
)
a.consumeJob(evaluateMemory, SystemRole)
// if len(a.CurrentConversation()) != 0 {
// // Here the LLM could decide to store some part of the conversation too in the memory
// evaluateMemory := NewJob(
// WithText(
// `Evaluate the current conversation and decide if we need to store some relevant informations from it`,
// ),
// WithReasoningCallback(a.options.reasoningCallback),
// WithResultCallback(a.options.resultCallback),
// )
// a.consumeJob(evaluateMemory, SystemRole)
// a.ResetConversation()
// }
if !a.options.standaloneJob {
a.ResetConversation()
return
}
// Here we go in a loop of

12
agent/options.go
View File

@@ -19,7 +19,7 @@ type options struct {
randomIdentityGuidance string
randomIdentity bool
userActions Actions
enableHUD, standaloneJob, showCharacter, enableKB bool
enableHUD, standaloneJob, showCharacter, enableKB, enableSummaryMemory, enableLongTermMemory bool
canStopItself bool
initiateConversations bool
@@ -127,6 +127,16 @@ var EnablePersonality = func(o *options) error {
return nil
}
var EnableSummaryMemory = func(o *options) error {
o.enableSummaryMemory = true
return nil
}
var EnableLongTermMemory = func(o *options) error {
o.enableLongTermMemory = true
return nil
}
func WithRAGDB(db RAGDB) Option {
return func(o *options) error {
o.ragdb = db

2
example/webui/agentconfig.go
View File

@@ -28,4 +28,6 @@ type AgentConfig struct {
KnowledgeBaseResults int `json:"kb_results" form:"kb_results"`
CanStopItself bool `json:"can_stop_itself" form:"can_stop_itself"`
SystemPrompt string `json:"system_prompt" form:"system_prompt"`
LongTermMemory bool `json:"long_term_memory" form:"long_term_memory"`
SummaryLongTermMemory bool `json:"summary_long_term_memory" form:"summary_long_term_memory"`
}

9
example/webui/agentpool.go
View File

@@ -248,6 +248,15 @@ func (a *AgentPool) startAgentWithConfig(name string, config *AgentConfig) error
if config.StandaloneJob {
opts = append(opts, EnableStandaloneJob)
}
if config.LongTermMemory {
opts = append(opts, EnableLongTermMemory)
}
if config.SummaryLongTermMemory {
opts = append(opts, EnableSummaryMemory)
}
if config.CanStopItself {
opts = append(opts, CanStopItself)
}

5
example/webui/views/create.html
View File

@@ -104,6 +104,11 @@
<label for="random_identity" class="block text-lg font-medium text-gray-400">Random Identity</label>
<input type="checkbox" name="random_identity" id="random_identity" class="mt-1 focus:ring-indigo-500 focus:border-indigo-500 block w-full shadow-sm sm:text-lg border-gray-300 rounded-md bg-gray-700 text-white">
<label for="long_term_memory" class="block text-lg font-medium text-gray-400">Long term memory</label>
<input type="checkbox" name="long_term_memory" id="long_term_memory" class="mt-1 focus:ring-indigo-500 focus:border-indigo-500 block w-full shadow-sm sm:text-lg border-gray-300 rounded-md bg-gray-700 text-white">
<label for="summary_long_term_memory" class="block text-lg font-medium text-gray-400">Long term memory (summarize!)</label>
<input type="checkbox" name="summary_long_term_memory" id="summary_long_term_memory" class="mt-1 focus:ring-indigo-500 focus:border-indigo-500 block w-full shadow-sm sm:text-lg border-gray-300 rounded-md bg-gray-700 text-white">
</div>
<div class="mb-4">
<label for="identity_guidance" class="block text-lg font-medium text-gray-400">Identity Guidance</label>