Organize Agentbox runtime code
Co-authored-by: codegirl007 <codegirl-007@users.noreply.github.com>
This commit is contained in:
Cursor Agent
co-authored by
codegirl007
codegirl007
parent
f2fee5d26b
commit
4d2fb4a733
@@ -3,16 +3,12 @@ package agent
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import (
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"bytes"
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"context"
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"encoding/base64"
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"encoding/json"
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"errors"
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"fmt"
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"io"
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"net/http"
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"strings"
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"time"
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"agentbox/internal/environment"
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)
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type OpenAIConfig struct {
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@@ -22,6 +18,8 @@ type OpenAIConfig struct {
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Client *http.Client
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}
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// OpenAI adapts the Responses API to Agentbox's provider-neutral Agent
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// contract. HTTP and wire-format details do not leak into the runtime.
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type OpenAI struct {
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config OpenAIConfig
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}
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@@ -42,203 +40,59 @@ func NewOpenAI(config OpenAIConfig) (*OpenAI, error) {
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return &OpenAI{config: config}, nil
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}
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func (a *OpenAI) Name() string {
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return "openai:" + a.config.Model
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func (openAI *OpenAI) Name() string {
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return "openai:" + openAI.config.Model
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}
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func (a *OpenAI) NextAction(
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func (openAI *OpenAI) NextAction(
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ctx context.Context,
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task string,
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history []Step,
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observation Observation,
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) (Decision, error) {
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prompt, err := modelPrompt(task, history, observation)
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requestBody, err := buildResponsesRequest(
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openAI.config.Model,
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task,
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history,
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observation,
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)
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if err != nil {
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return Decision{}, err
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}
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requestBody := map[string]any{
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"model": a.config.Model,
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"input": []any{
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map[string]any{
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"role": "user",
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"content": []any{
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map[string]any{"type": "input_text", "text": prompt},
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map[string]any{
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"type": "input_image",
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"image_url": "data:image/png;base64," +
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base64.StdEncoding.EncodeToString(observation.Screenshot),
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},
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},
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},
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},
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"text": map[string]any{
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"format": map[string]any{
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"type": "json_schema",
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"name": "agentbox_action",
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"strict": true,
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"schema": decisionSchema(),
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},
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},
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}
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body, err := json.Marshal(requestBody)
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request, err := http.NewRequestWithContext(
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ctx,
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http.MethodPost,
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strings.TrimRight(openAI.config.BaseURL, "/")+"/responses",
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bytes.NewReader(requestBody),
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)
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if err != nil {
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return Decision{}, err
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}
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request, err := http.NewRequestWithContext(ctx, http.MethodPost,
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strings.TrimRight(a.config.BaseURL, "/")+"/responses", bytes.NewReader(body))
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if err != nil {
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return Decision{}, err
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}
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request.Header.Set("Authorization", "Bearer "+a.config.APIKey)
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request.Header.Set("Authorization", "Bearer "+openAI.config.APIKey)
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request.Header.Set("Content-Type", "application/json")
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response, err := a.config.Client.Do(request)
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httpResponse, err := openAI.config.Client.Do(request)
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if err != nil {
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return Decision{}, err
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}
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defer response.Body.Close()
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responseBody, err := io.ReadAll(io.LimitReader(response.Body, 4<<20))
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defer httpResponse.Body.Close()
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responseBody, err := io.ReadAll(io.LimitReader(httpResponse.Body, 4<<20))
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if err != nil {
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return Decision{}, err
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}
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if response.StatusCode < 200 || response.StatusCode >= 300 {
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return Decision{}, fmt.Errorf("OpenAI response %s: %s",
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response.Status, strings.TrimSpace(string(responseBody)))
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if httpResponse.StatusCode < 200 || httpResponse.StatusCode >= 300 {
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return Decision{}, fmt.Errorf(
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"OpenAI response %s: %s",
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httpResponse.Status,
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strings.TrimSpace(string(responseBody)),
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)
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}
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text, err := responseText(responseBody)
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outputText, err := extractResponseText(responseBody)
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if err != nil {
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return Decision{}, err
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}
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return parseModelDecision(text)
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}
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func modelPrompt(task string, history []Step, observation Observation) (string, error) {
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contextData := struct {
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Task string `json:"task"`
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History []Step `json:"history"`
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RecentLogs []environment.LogEntry `json:"recent_logs"`
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PreviousActions []environment.InputAction `json:"previous_actions"`
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}{
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Task: task,
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History: history,
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RecentLogs: observation.Logs,
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PreviousActions: observation.PreviousActions,
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}
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data, err := json.Marshal(contextData)
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if err != nil {
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return "", err
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}
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return "You control an interactive Linux application from screenshots. " +
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"Choose exactly one safe input action, or mark done when the task is complete. " +
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"Use X11 key names such as RIGHT, Return, or Escape. Keep waits under 5000 ms.\n" +
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string(data), nil
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}
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func decisionSchema() map[string]any {
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actionProperties := map[string]any{
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"type": map[string]any{
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"type": "string",
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"enum": []string{
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string(environment.KeyDown), string(environment.KeyUp),
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string(environment.MouseMove), string(environment.MouseDown),
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string(environment.MouseUp), string(environment.Wait),
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},
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},
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"key": map[string]any{"type": "string"},
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"x": map[string]any{"type": "integer"},
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"y": map[string]any{"type": "integer"},
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"button": map[string]any{"type": "integer"},
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"duration_ms": map[string]any{"type": "integer"},
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}
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return map[string]any{
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"type": "object",
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"additionalProperties": false,
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"properties": map[string]any{
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"reason": map[string]any{"type": "string"},
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"done": map[string]any{"type": "boolean"},
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"action": map[string]any{
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"anyOf": []any{
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map[string]any{
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"type": "object",
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"additionalProperties": false,
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"properties": actionProperties,
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"required": []string{
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"type", "key", "x", "y", "button", "duration_ms",
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},
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},
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map[string]any{"type": "null"},
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},
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},
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},
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"required": []string{"reason", "done", "action"},
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}
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}
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func responseText(data []byte) (string, error) {
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var response struct {
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Output []struct {
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Content []struct {
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Type string `json:"type"`
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Text string `json:"text"`
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} `json:"content"`
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} `json:"output"`
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}
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if err := json.Unmarshal(data, &response); err != nil {
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return "", fmt.Errorf("decode OpenAI response: %w", err)
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}
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for _, output := range response.Output {
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for _, content := range output.Content {
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if content.Type == "output_text" && content.Text != "" {
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return content.Text, nil
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}
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}
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}
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return "", errors.New("OpenAI response contained no output_text")
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}
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func parseModelDecision(text string) (Decision, error) {
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var result struct {
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Reason string `json:"reason"`
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Done bool `json:"done"`
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Action *struct {
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Type environment.InputType `json:"type"`
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Key string `json:"key"`
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X int `json:"x"`
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Y int `json:"y"`
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Button int `json:"button"`
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DurationMS int `json:"duration_ms"`
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} `json:"action"`
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}
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if err := json.Unmarshal([]byte(text), &result); err != nil {
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return Decision{}, fmt.Errorf("decode model decision: %w", err)
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}
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if result.Reason == "" {
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return Decision{}, errors.New("model decision requires reason")
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}
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if result.Done {
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return Decision{Reason: result.Reason, Done: true}, nil
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}
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if result.Action == nil {
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return Decision{}, errors.New("model decision requires action when not done")
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}
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if result.Action.DurationMS < 0 || result.Action.DurationMS > 5000 {
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return Decision{}, errors.New("model wait must be between 0 and 5000 ms")
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}
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action := environment.InputAction{
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Type: result.Action.Type,
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Key: result.Action.Key,
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X: result.Action.X,
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Y: result.Action.Y,
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Button: result.Action.Button,
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DurationMS: result.Action.DurationMS,
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}
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switch action.Type {
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case environment.KeyDown, environment.KeyUp, environment.MouseMove,
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environment.MouseDown, environment.MouseUp, environment.Wait:
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default:
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return Decision{}, fmt.Errorf("model returned unsupported action %q", action.Type)
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}
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return Decision{Reason: result.Reason, Action: &action}, nil
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return parseModelDecision(outputText)
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}
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var _ Agent = (*OpenAI)(nil)
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