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feat: improve parameter generation by forcing reasoning (#193)

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* feat: improve parameter generation by forcing reasoning

Signed-off-by: mudler <mudler@localai.io>

* Update core/agent/actions.go

Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>

* Update core/agent/actions.go

Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>

* Try to change default models

Signed-off-by: mudler <mudler@localai.io>

---------

Signed-off-by: mudler <mudler@localai.io>
Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
This commit is contained in:
Ettore Di Giacinto
2025-06-01 10:11:04 +02:00
committed by GitHub
parent f0dac5ca22
commit 56b6f7240c
4 changed files with 68 additions and 23 deletions
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63
core/agent/actions.go
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@@ -5,6 +5,7 @@ import (
"encoding/json"
"fmt"
"os"
"strings"
"github.com/mudler/LocalAGI/core/action"
"github.com/mudler/LocalAGI/core/types"
@@ -12,12 +13,24 @@ import (
"github.com/mudler/LocalAGI/pkg/xlog"
"github.com/sashabaranov/go-openai"
"github.com/sashabaranov/go-openai/jsonschema"
)
const parameterReasoningPrompt = `You are tasked with generating the optimal parameters for the action "%s". The action requires the following parameters:
%s
Your task is to:
1. Generate the best possible values for each required parameter
2. If the parameter requires code, provide complete, working code
3. If the parameter requires text or documentation, provide comprehensive, well-structured content
4. Ensure all parameters are complete and ready to be used
Focus on quality and completeness. Do not explain your reasoning or analyze the action's purpose - just provide the best possible parameter values.`
type decisionResult struct {
actionParams types.ActionParams
message string
actioName string
actionName string
}
// decision forces the agent to take one of the available actions
@@ -131,7 +144,7 @@ func (a *Agent) decision(
a.observer.Update(*obs)
}
return &decisionResult{actionParams: params, actioName: msg.ToolCalls[0].Function.Name, message: msg.Content}, nil
return &decisionResult{actionParams: params, actionName: msg.ToolCalls[0].Function.Name, message: msg.Content}, nil
}
return nil, fmt.Errorf("failed to make a decision after %d attempts: %w", maxRetries, lastErr)
@@ -248,9 +261,32 @@ func (a *Agent) generateParameters(job *types.Job, pickTemplate string, act type
cc := conversation
if a.options.forceReasoning {
// First, get the LLM to reason about optimal parameter usage
parameterReasoningPrompt := fmt.Sprintf(parameterReasoningPrompt,
act.Definition().Name,
formatProperties(act.Definition().Properties))
// Get initial reasoning about parameters using askLLM
paramReasoningMsg, err := a.askLLM(job.GetContext(),
append(conversation, openai.ChatCompletionMessage{
Role: "system",
Content: parameterReasoningPrompt,
}),
maxAttempts,
)
if err != nil {
xlog.Warn("Failed to get parameter reasoning", "error", err)
}
// Combine original reasoning with parameter-specific reasoning
enhancedReasoning := reasoning
if paramReasoningMsg.Content != "" {
enhancedReasoning = fmt.Sprintf("%s\n\nParameter Analysis:\n%s", reasoning, paramReasoningMsg.Content)
}
cc = append(conversation, openai.ChatCompletionMessage{
Role: "system",
Content: fmt.Sprintf("The agent decided to use the tool %s with the following reasoning: %s", act.Definition().Name, reasoning),
Content: fmt.Sprintf("The agent decided to use the tool %s with the following reasoning: %s", act.Definition().Name, enhancedReasoning),
})
}
@@ -273,6 +309,15 @@ func (a *Agent) generateParameters(job *types.Job, pickTemplate string, act type
return nil, fmt.Errorf("failed to generate parameters after %d attempts: %w", maxAttempts, attemptErr)
}
// Helper function to format properties for the prompt
func formatProperties(props map[string]jsonschema.Definition) string {
var result strings.Builder
for name, prop := range props {
result.WriteString(fmt.Sprintf("- %s: %s\n", name, prop.Description))
}
return result.String()
}
func (a *Agent) handlePlanning(ctx context.Context, job *types.Job, chosenAction types.Action, actionParams types.ActionParams, reasoning string, pickTemplate string, conv Messages) (Messages, error) {
// Planning: run all the actions in sequence
if !chosenAction.Definition().Name.Is(action.PlanActionName) {
@@ -455,12 +500,12 @@ func (a *Agent) pickAction(job *types.Job, templ string, messages []openai.ChatC
return nil, nil, "", err
}
xlog.Debug(fmt.Sprintf("thought action Name: %v", thought.actioName))
xlog.Debug(fmt.Sprintf("thought message: %v", thought.message))
xlog.Debug("thought action Name", "actionName", thought.actionName)
xlog.Debug("thought message", "message", thought.message)
// Find the action
chosenAction := a.availableActions().Find(thought.actioName)
if chosenAction == nil || thought.actioName == "" {
chosenAction := a.availableActions().Find(thought.actionName)
if chosenAction == nil || thought.actionName == "" {
xlog.Debug("no answer")
// LLM replied with an answer?
@@ -496,8 +541,8 @@ func (a *Agent) pickAction(job *types.Job, templ string, messages []openai.ChatC
if err != nil {
return nil, nil, "", err
}
if thought.actioName != "" && thought.actioName != reasoningAction.Definition().Name.String() {
return nil, nil, "", fmt.Errorf("Expected reasoning action not: %s", thought.actioName)
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)
}
originalReasoning := ""