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feat: do not use JSON extraction for reasoning (#194)

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Signed-off-by: mudler <mudler@localai.io>
This commit is contained in:
Ettore Di Giacinto
2025-06-02 10:29:19 +02:00
committed by GitHub
parent 56b6f7240c
commit 50cad776aa
1 changed files with 25 additions and 22 deletions
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47
core/agent/actions.go
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@@ -516,6 +516,7 @@ func (a *Agent) pickAction(job *types.Job, templ string, messages []openai.ChatC
return chosenAction, thought.actionParams, thought.message, nil
}
// Force the LLM to think and we extract a "reasoning" to pick a specific action and with which parameters
xlog.Debug("[pickAction] forcing reasoning")
prompt, err := renderTemplate(templ, a.prepareHUD(), a.availableActions(), "")
@@ -533,33 +534,35 @@ func (a *Agent) pickAction(job *types.Job, templ string, messages []openai.ChatC
}, c...)
}
reasoningAction := action.NewReasoning()
thought, err := a.decision(job,
c,
types.Actions{reasoningAction}.ToTools(),
reasoningAction.Definition().Name.String(), maxRetries)
if err != nil {
return nil, nil, "", err
// Create a detailed prompt for reasoning that includes available actions and their properties
reasoningPrompt := "Analyze the current situation and determine the best course of action. Consider the following:\n\n"
reasoningPrompt += "Available Actions:\n"
for _, act := range a.availableActions() {
reasoningPrompt += fmt.Sprintf("- %s: %s\n", act.Definition().Name, act.Definition().Description)
if len(act.Definition().Properties) > 0 {
reasoningPrompt += " Properties:\n"
for name, prop := range act.Definition().Properties {
reasoningPrompt += fmt.Sprintf(" - %s: %s\n", name, prop.Description)
}
if thought.actionName != "" && thought.actionName != reasoningAction.Definition().Name.String() {
return nil, nil, "", fmt.Errorf("expected reasoning action %s, got %s", reasoningAction.Definition().Name.String(), thought.actionName)
}
reasoningPrompt += "\n"
}
reasoningPrompt += "\nProvide a detailed reasoning about what action would be most appropriate in this situation and why. You can also just reply with a simple message by choosing the 'reply' or 'answer' action."
// Get reasoning using askLLM
reasoningMsg, err := a.askLLM(job.GetContext(),
append(c, openai.ChatCompletionMessage{
Role: "system",
Content: reasoningPrompt,
}),
maxRetries)
if err != nil {
return nil, nil, "", fmt.Errorf("failed to get reasoning: %w", err)
}
originalReasoning := ""
response := &action.ReasoningResponse{}
if thought.actionParams != nil {
if err := thought.actionParams.Unmarshal(response); err != nil {
return nil, nil, "", err
}
originalReasoning = response.Reasoning
}
if thought.message != "" {
originalReasoning = thought.message
}
originalReasoning := reasoningMsg.Content
xlog.Debug("[pickAction] picking action", "messages", c)
// thought, err := a.askLLM(ctx,
// c,
actionsID := []string{"reply"}
for _, m := range a.availableActions() {