refactor: ai asserter

This commit is contained in:
lilong.129
2025-04-29 14:59:14 +08:00
parent 14e353a572
commit 4d7c7e8aaf
12 changed files with 405 additions and 414 deletions

View File

@@ -49,6 +49,8 @@ type LLMServiceType string
const (
LLMServiceTypeUITARS LLMServiceType = "ui-tars"
LLMServiceTypeGPT4o LLMServiceType = "gpt-4o"
LLMServiceTypeGPT4Vision LLMServiceType = "gpt-4-vision"
LLMServiceTypeQwenVL LLMServiceType = "qwen-vl"
LLMServiceTypeDeepSeekV3 LLMServiceType = "deepseek-v3"
)
@@ -58,45 +60,33 @@ type ILLMService interface {
Assert(opts *AssertOptions) (*AssertionResponse, error)
}
func WithLLMService(service LLMServiceType) AIServiceOption {
func WithLLMService(modelType LLMServiceType) AIServiceOption {
return func(opts *AIServices) {
switch service {
// init planner
var planner IPlanner
var err error
switch modelType {
case LLMServiceTypeGPT4o:
// TODO: implement gpt-4o planner and asserter
planner, err := NewPlanner(context.Background())
if err != nil {
log.Error().Err(err).Msg("init gpt-4o planner failed")
os.Exit(code.GetErrorCode(err))
}
asserter, err := NewUITarsAsserter(context.Background())
if err != nil {
log.Error().Err(err).Msg("init ui-tars asserter failed")
os.Exit(code.GetErrorCode(err))
}
opts.ILLMService = &combinedLLMService{
planner: planner,
asserter: asserter,
}
planner, err = NewPlanner(context.Background())
case LLMServiceTypeUITARS:
planner, err := NewUITarsPlanner(context.Background())
if err != nil {
log.Error().Err(err).Msg("init ui-tars planner failed")
os.Exit(code.GetErrorCode(err))
}
planner, err = NewUITarsPlanner(context.Background())
}
if err != nil {
log.Error().Err(err).Msgf("init %s planner failed", modelType)
os.Exit(code.GetErrorCode(err))
}
asserter, err := NewUITarsAsserter(context.Background())
if err != nil {
log.Error().Err(err).Msg("init ui-tars asserter failed")
os.Exit(code.GetErrorCode(err))
}
// init asserter
asserter, err := NewAsserter(context.Background(), modelType)
if err != nil {
log.Error().Err(err).Msgf("init %s asserter failed", modelType)
os.Exit(code.GetErrorCode(err))
}
opts.ILLMService = &combinedLLMService{
planner: planner,
asserter: asserter,
}
opts.ILLMService = &combinedLLMService{
planner: planner,
asserter: asserter,
}
}
}

62
uixt/ai/ai_ark.go Normal file
View File

@@ -0,0 +1,62 @@
package ai
import (
"os"
"github.com/cloudwego/eino-ext/components/model/ark"
"github.com/httprunner/httprunner/v5/code"
"github.com/httprunner/httprunner/v5/internal/config"
"github.com/pkg/errors"
"github.com/rs/zerolog/log"
)
const (
EnvArkBaseURL = "ARK_BASE_URL"
EnvArkAPIKey = "ARK_API_KEY"
EnvArkModelID = "ARK_MODEL_ID"
)
func GetArkModelConfig() (*ark.ChatModelConfig, error) {
if err := config.LoadEnv(); err != nil {
return nil, errors.Wrap(code.LoadEnvError, err.Error())
}
arkBaseURL := os.Getenv(EnvArkBaseURL)
arkAPIKey := os.Getenv(EnvArkAPIKey)
if arkAPIKey == "" {
return nil, errors.Wrapf(code.LLMEnvMissedError,
"env %s missed", EnvArkAPIKey)
}
modelName := os.Getenv(EnvArkModelID)
if modelName == "" {
return nil, errors.Wrapf(code.LLMEnvMissedError,
"env %s missed", EnvArkModelID)
}
timeout := defaultTimeout
// https://www.volcengine.com/docs/82379/1494384?redirect=1
temperature := float32(0.01) // [0, 2] 采样温度。控制了生成文本时对每个候选词的概率分布进行平滑的程度。
// topP := float32(0.7) // [0, 1] 核采样概率阈值。模型会考虑概率质量在 top_p 内的 token 结果。
// maxTokens := int(4096) // 模型可以生成的最大 token 数量。输入 token 和输出 token 的总长度还受模型的上下文长度限制。
// frequencyPenalty := float32(0) // [-2, 2] 频率惩罚系数。如果值为正,会根据新 token 在文本中的出现频率对其进行惩罚,从而降低模型逐字重复的可能性。
modelConfig := &ark.ChatModelConfig{
BaseURL: arkBaseURL,
APIKey: arkAPIKey,
Model: modelName,
Timeout: &timeout,
Temperature: &temperature,
// TopP: &topP,
// MaxTokens: &maxTokens,
// FrequencyPenalty: &frequencyPenalty,
}
// log config info
log.Info().Str("model", modelConfig.Model).
Str("baseURL", modelConfig.BaseURL).
Str("apiKey", maskAPIKey(modelConfig.APIKey)).
Str("timeout", defaultTimeout.String()).
Msg("get model config")
return modelConfig, nil
}

79
uixt/ai/ai_openai.go Normal file
View File

@@ -0,0 +1,79 @@
package ai
import (
"os"
"github.com/cloudwego/eino-ext/components/model/openai"
openai2 "github.com/cloudwego/eino-ext/libs/acl/openai"
"github.com/getkin/kin-openapi/openapi3gen"
"github.com/httprunner/httprunner/v5/code"
"github.com/httprunner/httprunner/v5/internal/config"
"github.com/pkg/errors"
"github.com/rs/zerolog/log"
)
const (
EnvOpenAIBaseURL = "OPENAI_BASE_URL"
EnvOpenAIAPIKey = "OPENAI_API_KEY"
EnvModelName = "LLM_MODEL_NAME"
)
// GetOpenAIModelConfig get OpenAI config
func GetOpenAIModelConfig() (*openai.ChatModelConfig, error) {
if err := config.LoadEnv(); err != nil {
return nil, errors.Wrap(code.LoadEnvError, err.Error())
}
openaiBaseURL := os.Getenv(EnvOpenAIBaseURL)
if openaiBaseURL == "" {
return nil, errors.Wrapf(code.LLMEnvMissedError,
"env %s missed", EnvOpenAIBaseURL)
}
openaiAPIKey := os.Getenv(EnvOpenAIAPIKey)
if openaiAPIKey == "" {
return nil, errors.Wrapf(code.LLMEnvMissedError,
"env %s missed", EnvOpenAIAPIKey)
}
modelName := os.Getenv(EnvModelName)
if modelName == "" {
return nil, errors.Wrapf(code.LLMEnvMissedError,
"env %s missed", EnvModelName)
}
type OutputFormat struct {
Thought string `json:"thought"`
Action string `json:"action"`
Error string `json:"error,omitempty"`
}
outputFormatSchema, err := openapi3gen.NewSchemaRefForValue(&OutputFormat{}, nil)
if err != nil {
return nil, err
}
modelConfig := &openai.ChatModelConfig{
BaseURL: openaiBaseURL,
APIKey: openaiAPIKey,
Model: modelName,
Timeout: defaultTimeout,
// set structured response format
// https://github.com/cloudwego/eino-ext/blob/main/components/model/openai/examples/structured/structured.go
ResponseFormat: &openai2.ChatCompletionResponseFormat{
Type: openai2.ChatCompletionResponseFormatTypeJSONSchema,
JSONSchema: &openai2.ChatCompletionResponseFormatJSONSchema{
Name: "thought_and_action",
Description: "data that describes planning thought and action",
Schema: outputFormatSchema.Value,
Strict: false,
},
},
}
// log config info
log.Info().Str("model", modelConfig.Model).
Str("baseURL", modelConfig.BaseURL).
Str("apiKey", maskAPIKey(modelConfig.APIKey)).
Str("timeout", defaultTimeout.String()).
Msg("get model config")
return modelConfig, nil
}

View File

@@ -8,6 +8,8 @@ import (
"time"
"github.com/cloudwego/eino-ext/components/model/ark"
"github.com/cloudwego/eino-ext/components/model/openai"
"github.com/cloudwego/eino/components/model"
"github.com/cloudwego/eino/schema"
"github.com/httprunner/httprunner/v5/code"
"github.com/httprunner/httprunner/v5/internal/json"
@@ -16,60 +18,11 @@ import (
"github.com/rs/zerolog/log"
)
// IAsserter interface defines the contract for assertion operations
type IAsserter interface {
Assert(opts *AssertOptions) (*AssertionResponse, error)
}
// UI-TARS assertion system prompt
const uiTarsAssertionPrompt = `You are a senior testing engineer. User will give an assertion and a screenshot of a page. By carefully viewing the screenshot, please tell whether the assertion is truthy.
## Output Json String Format
` + "```" + `
"{
"pass": <<is a boolean value from the enum [true, false], true means the assertion is truthy>>,
"thought": "<<is a string, give the reason why the assertion is falsy or truthy. Otherwise.>>"
}"
` + "```" + `
## Rules **MUST** follow
- Make sure to return **only** the JSON, with **no additional** text or explanations.
- Use Chinese in 'thought' part.
- You **MUST** strictly follow up the **Output Json String Format**.`
// AssertionResponse represents the response from an AI assertion
type AssertionResponse struct {
Pass bool `json:"pass"`
Thought string `json:"thought"`
}
// UITarsAsserter handles assertion using UI-TARS VLM
type UITarsAsserter struct {
ctx context.Context
model *ark.ChatModel
config *ark.ChatModelConfig
systemPrompt string
history ConversationHistory
}
// NewUITarsAsserter creates a new UITarsAsserter instance
func NewUITarsAsserter(ctx context.Context) (*UITarsAsserter, error) {
config, err := GetArkModelConfig()
if err != nil {
return nil, err
}
chatModel, err := ark.NewChatModel(ctx, config)
if err != nil {
return nil, err
}
return &UITarsAsserter{
ctx: ctx,
config: config,
model: chatModel,
systemPrompt: uiTarsAssertionPrompt,
}, nil
}
// AssertOptions represents the input options for assertion
type AssertOptions struct {
Assertion string `json:"assertion"` // The assertion text to verify
@@ -77,18 +30,65 @@ type AssertOptions struct {
Size types.Size `json:"size"` // Screen dimensions
}
func validateAssertionInput(opts *AssertOptions) error {
if opts.Assertion == "" {
return errors.Wrap(code.LLMPrepareRequestError, "assertion text is required")
// AssertionResponse represents the response from an AI assertion
type AssertionResponse struct {
Pass bool `json:"pass"`
Thought string `json:"thought"`
}
// Asserter handles assertion using different AI models
type Asserter struct {
ctx context.Context
model model.ToolCallingChatModel
systemPrompt string
history ConversationHistory
modelType LLMServiceType
}
// NewAsserter creates a new Asserter instance
func NewAsserter(ctx context.Context, modelType LLMServiceType) (*Asserter, error) {
asserter := &Asserter{
ctx: ctx,
modelType: modelType,
systemPrompt: getAssertionSystemPrompt(modelType),
}
if opts.Screenshot == "" {
return errors.Wrap(code.LLMPrepareRequestError, "screenshot is required")
switch modelType {
case LLMServiceTypeUITARS:
config, err := GetArkModelConfig()
if err != nil {
return nil, err
}
asserter.model, err = ark.NewChatModel(ctx, config)
if err != nil {
return nil, err
}
case LLMServiceTypeGPT4Vision, LLMServiceTypeGPT4o:
config, err := GetOpenAIModelConfig()
if err != nil {
return nil, err
}
asserter.model, err = openai.NewChatModel(ctx, config)
if err != nil {
return nil, err
}
default:
return nil, errors.New("not supported model type for asserter")
}
return nil
return asserter, nil
}
// getAssertionSystemPrompt returns the appropriate system prompt for the given model type
func getAssertionSystemPrompt(modelType LLMServiceType) string {
if modelType == LLMServiceTypeUITARS {
return defaultAssertionPrompt + "\n\n" + uiTarsAssertionResponseFormat
}
return defaultAssertionPrompt + "\n\n" + defaultAssertionResponseJsonFormat
}
// Assert performs the assertion check on the screenshot
func (a *UITarsAsserter) Assert(opts *AssertOptions) (*AssertionResponse, error) {
func (a *Asserter) Assert(opts *AssertOptions) (*AssertionResponse, error) {
// Validate input parameters
if err := validateAssertionInput(opts); err != nil {
return nil, errors.Wrap(err, "validate assertion parameters failed")
@@ -133,7 +133,7 @@ Here is the assertion. Please tell whether it is truthy according to the screens
startTime := time.Now()
resp, err := a.model.Generate(a.ctx, a.history)
log.Info().Float64("elapsed(s)", time.Since(startTime).Seconds()).
Str("model", a.config.Model).Msg("call model service for assertion")
Str("model", string(a.modelType)).Msg("call model service for assertion")
if err != nil {
return nil, errors.Wrap(code.LLMRequestServiceError, err.Error())
}
@@ -154,78 +154,36 @@ Here is the assertion. Please tell whether it is truthy according to the screens
return result, nil
}
// parseAssertionResult 解析模型返回的JSON响应
// validateAssertionInput validates the input parameters for assertion
func validateAssertionInput(opts *AssertOptions) error {
if opts.Assertion == "" {
return errors.Wrap(code.LLMPrepareRequestError, "assertion text is required")
}
if opts.Screenshot == "" {
return errors.Wrap(code.LLMPrepareRequestError, "screenshot is required")
}
return nil
}
// parseAssertionResult parses the model response into AssertionResponse
func parseAssertionResult(content string) (*AssertionResponse, error) {
// 1. 从响应中提取JSON内容
// Extract JSON content from response
jsonContent := extractJSON(content)
if jsonContent == "" {
return nil, errors.New("could not extract JSON from response")
}
// 2. 预处理和标准解析尝试
jsonContent = prepareJSON(jsonContent)
// Parse JSON response
var result AssertionResponse
if err := json.Unmarshal([]byte(jsonContent), &result); err == nil {
return &result, nil
if err := json.Unmarshal([]byte(jsonContent), &result); err != nil {
return nil, errors.Wrap(code.LLMParseAssertionResponseError, err.Error())
}
// 3. 备用:正则表达式解析
if pass, thought := extractWithRegex(jsonContent); thought != "" {
return &AssertionResponse{Pass: pass, Thought: thought}, nil
}
return nil, errors.New("failed to parse assertion result")
}
// prepareJSON 预处理JSON字符串修复常见问题
func prepareJSON(jsonStr string) string {
// 1. 去除可能的外层引号
jsonStr = strings.TrimSpace(jsonStr)
if strings.HasPrefix(jsonStr, "\"") && strings.HasSuffix(jsonStr, "\"") {
jsonStr = jsonStr[1 : len(jsonStr)-1]
}
// 2. 转义thought内容中的引号
thoughtRegex := regexp.MustCompile(`"thought":\s*"([^"]*)"`)
matches := thoughtRegex.FindStringSubmatch(jsonStr)
if len(matches) > 1 {
thoughtValue := matches[1]
fixedThought := strings.ReplaceAll(thoughtValue, "\"", "\\\"")
jsonStr = strings.Replace(jsonStr, matches[0], fmt.Sprintf(`"thought": "%s"`, fixedThought), 1)
}
// 3. 处理换行和特殊字符
jsonStr = strings.ReplaceAll(jsonStr, "\n", "\\n")
jsonStr = strings.ReplaceAll(jsonStr, "\r", "\\r")
jsonStr = strings.ReplaceAll(jsonStr, "\t", "\\t")
return jsonStr
}
// extractWithRegex 使用正则表达式提取pass和thought值
func extractWithRegex(jsonStr string) (pass bool, thought string) {
// 提取pass值
passRegex := regexp.MustCompile(`"pass":\s*(true|false)`)
passMatches := passRegex.FindStringSubmatch(jsonStr)
// 提取thought值
thoughtRegex := regexp.MustCompile(`"thought":\s*"([^"]*(?:"[^"]*)*)"`)
thoughtMatches := thoughtRegex.FindStringSubmatch(jsonStr)
if len(passMatches) > 1 && len(thoughtMatches) > 1 {
// 处理提取的值
pass = passMatches[1] == "true"
thought = strings.ReplaceAll(thoughtMatches[1], "\\\"", "\"")
thought = strings.ReplaceAll(thought, "\\\\", "\\")
return pass, thought
}
return false, ""
return &result, nil
}
// extractJSON extracts JSON content from a string that might contain markdown or other formatting
func extractJSON(content string) string {
// Try to extract JSON directly
content = strings.TrimSpace(content)
// If the content is already a valid JSON, return it
@@ -233,7 +191,7 @@ func extractJSON(content string) string {
return content
}
// Check for markdown code blocks with more flexible pattern
// Try to extract JSON from markdown code blocks
jsonRegex := regexp.MustCompile(`(?:json)?\s*({[\s\S]*?})\s*`)
matches := jsonRegex.FindStringSubmatch(content)
if len(matches) > 1 {
@@ -241,7 +199,6 @@ func extractJSON(content string) string {
}
// Try a more robust approach for JSON with Chinese characters
// First look for the outermost pair of curly braces
startIdx := strings.Index(content, "{")
if startIdx >= 0 {
depth := 1
@@ -251,19 +208,11 @@ func extractJSON(content string) string {
} else if content[i] == '}' {
depth--
if depth == 0 {
// Found the closing brace
return content[startIdx : i+1]
}
}
}
}
// Fallback to regex approach
braceRegex := regexp.MustCompile(`{[\s\S]*?}`)
matches = braceRegex.FindStringSubmatch(content)
if len(matches) > 0 {
return strings.TrimSpace(matches[0])
}
return ""
return content
}

View File

@@ -0,0 +1,25 @@
package ai
// Default assertion system prompt
const defaultAssertionPrompt = `You are a senior testing engineer. User will give an assertion and a screenshot of a page. By carefully viewing the screenshot, please tell whether the assertion is truthy.`
// Default assertion response format
const defaultAssertionResponseJsonFormat = `Return in the following JSON format:
{
pass: boolean, // whether the assertion is truthy
thought: string | null, // string, if the result is falsy, give the reason why it is falsy. Otherwise, put null.
}`
// UI-TARS assertion response format
const uiTarsAssertionResponseFormat = `## Output Json String Format
` + "```" + `
"{
"pass": <<is a boolean value from the enum [true, false], true means the assertion is truthy>>,
"thought": "<<is a string, give the reason why the assertion is falsy or truthy. Otherwise.>>"
}"
` + "```" + `
## Rules **MUST** follow
- Make sure to return **only** the JSON, with **no additional** text or explanations.
- Use Chinese in ` + "`Thought`" + ` part.
- You **MUST** strictly follow up the **Output Json String Format**.`

View File

@@ -16,7 +16,6 @@ import (
"github.com/httprunner/httprunner/v5/code"
"github.com/httprunner/httprunner/v5/uixt/types"
"github.com/pkg/errors"
"github.com/rs/zerolog/log"
)
type IPlanner interface {
@@ -85,100 +84,6 @@ func validatePlanningInput(opts *PlanningOptions) error {
return nil
}
func logRequest(messages []*schema.Message) {
msgs := make([]*schema.Message, 0, len(messages))
for _, message := range messages {
msg := &schema.Message{
Role: message.Role,
}
if message.Content != "" {
msg.Content = message.Content
} else if len(message.MultiContent) > 0 {
for _, mc := range message.MultiContent {
switch mc.Type {
case schema.ChatMessagePartTypeImageURL:
// Create a copy of the ImageURL to avoid modifying the original message
imageURLCopy := *mc.ImageURL
if strings.HasPrefix(imageURLCopy.URL, "data:image/") {
imageURLCopy.URL = "<data:image/base64...>"
}
msg.MultiContent = append(msg.MultiContent, schema.ChatMessagePart{
Type: mc.Type,
ImageURL: &imageURLCopy,
})
}
}
}
msgs = append(msgs, msg)
}
log.Debug().Interface("messages", msgs).Msg("log request messages")
}
func logResponse(resp *schema.Message) {
logger := log.Info().Str("role", string(resp.Role)).
Str("content", resp.Content)
if resp.ResponseMeta != nil {
logger = logger.Interface("response_meta", resp.ResponseMeta)
}
if resp.Extra != nil {
logger = logger.Interface("extra", resp.Extra)
}
logger.Msg("log response message")
}
type ConversationHistory []*schema.Message
// Append adds a message to the conversation history
func (h *ConversationHistory) Append(msg *schema.Message) {
// for user image message:
// - keep at most 4 user image messages
// - delete the oldest user image message when the limit is reached
if msg.Role == schema.User {
// get all existing user messages
userImgCount := 0
firstUserImgIndex := -1
// calculate the number of user messages and find the index of the first user message
for i, item := range *h {
if item.Role == schema.User {
userImgCount++
if firstUserImgIndex == -1 {
firstUserImgIndex = i
}
}
}
// if there are already 4 user messages, delete the first one before adding the new message
if userImgCount >= 4 && firstUserImgIndex >= 0 {
// delete the first user message
*h = append(
(*h)[:firstUserImgIndex],
(*h)[firstUserImgIndex+1:]...,
)
}
// add the new user message to the history
*h = append(*h, msg)
}
// for assistant message:
// - keep at most the last 10 assistant messages
if msg.Role == schema.Assistant {
// add the new assistant message to the history
*h = append(*h, msg)
// if there are more than 10 assistant messages, remove the oldest ones
assistantMsgCount := 0
for i := len(*h) - 1; i >= 0; i-- {
if (*h)[i].Role == schema.Assistant {
assistantMsgCount++
if assistantMsgCount > 10 {
*h = append((*h)[:i], (*h)[i+1:]...)
}
}
}
}
}
// SavePositionImg saves an image with position markers
func SavePositionImg(params struct {
InputImgBase64 string

View File

@@ -4,90 +4,20 @@ import (
"context"
"fmt"
_ "image/jpeg"
"os"
"strings"
"time"
"github.com/cloudwego/eino-ext/components/model/openai"
openai2 "github.com/cloudwego/eino-ext/libs/acl/openai"
"github.com/cloudwego/eino/components/model"
"github.com/cloudwego/eino/schema"
"github.com/getkin/kin-openapi/openapi3gen"
"github.com/pkg/errors"
"github.com/rs/zerolog/log"
"github.com/httprunner/httprunner/v5/code"
"github.com/httprunner/httprunner/v5/internal/config"
"github.com/httprunner/httprunner/v5/internal/json"
"github.com/httprunner/httprunner/v5/uixt/types"
)
const (
EnvOpenAIBaseURL = "OPENAI_BASE_URL"
EnvOpenAIAPIKey = "OPENAI_API_KEY"
EnvModelName = "LLM_MODEL_NAME"
)
// GetOpenAIModelConfig get OpenAI config
func GetOpenAIModelConfig() (*openai.ChatModelConfig, error) {
if err := config.LoadEnv(); err != nil {
return nil, errors.Wrap(code.LoadEnvError, err.Error())
}
openaiBaseURL := os.Getenv(EnvOpenAIBaseURL)
if openaiBaseURL == "" {
return nil, errors.Wrapf(code.LLMEnvMissedError,
"env %s missed", EnvOpenAIBaseURL)
}
openaiAPIKey := os.Getenv(EnvOpenAIAPIKey)
if openaiAPIKey == "" {
return nil, errors.Wrapf(code.LLMEnvMissedError,
"env %s missed", EnvOpenAIAPIKey)
}
modelName := os.Getenv(EnvModelName)
if modelName == "" {
return nil, errors.Wrapf(code.LLMEnvMissedError,
"env %s missed", EnvModelName)
}
type OutputFormat struct {
Thought string `json:"thought"`
Action string `json:"action"`
Error string `json:"error,omitempty"`
}
outputFormatSchema, err := openapi3gen.NewSchemaRefForValue(&OutputFormat{}, nil)
if err != nil {
return nil, err
}
modelConfig := &openai.ChatModelConfig{
BaseURL: openaiBaseURL,
APIKey: openaiAPIKey,
Model: modelName,
Timeout: defaultTimeout,
// set structured response format
// https://github.com/cloudwego/eino-ext/blob/main/components/model/openai/examples/structured/structured.go
ResponseFormat: &openai2.ChatCompletionResponseFormat{
Type: openai2.ChatCompletionResponseFormatTypeJSONSchema,
JSONSchema: &openai2.ChatCompletionResponseFormatJSONSchema{
Name: "thought_and_action",
Description: "data that describes planning thought and action",
Schema: outputFormatSchema.Value,
Strict: false,
},
},
}
// log config info
log.Info().Str("model", modelConfig.Model).
Str("baseURL", modelConfig.BaseURL).
Str("apiKey", maskAPIKey(modelConfig.APIKey)).
Str("timeout", defaultTimeout.String()).
Msg("get model config")
return modelConfig, nil
}
func NewPlanner(ctx context.Context) (*Planner, error) {
config, err := GetOpenAIModelConfig()
if err != nil {
@@ -99,8 +29,8 @@ func NewPlanner(ctx context.Context) (*Planner, error) {
}
return &Planner{
ctx: ctx,
config: config,
model: model,
modelType: LLMServiceTypeGPT4o,
systemPrompt: uiTarsPlanningPrompt, // TODO: change prompt with function calling
}, nil
}
@@ -108,8 +38,8 @@ func NewPlanner(ctx context.Context) (*Planner, error) {
type Planner struct {
ctx context.Context
model model.ToolCallingChatModel
config *openai.ChatModelConfig
systemPrompt string
modelType LLMServiceType
history ConversationHistory
}
@@ -139,7 +69,7 @@ func (p *Planner) Call(opts *PlanningOptions) (*PlanningResult, error) {
startTime := time.Now()
resp, err := p.model.Generate(p.ctx, p.history)
log.Info().Float64("elapsed(s)", time.Since(startTime).Seconds()).
Str("model", p.config.Model).Msg("call model service")
Str("model", string(p.modelType)).Msg("call model service")
if err != nil {
return nil, errors.Wrap(code.LLMRequestServiceError, err.Error())
}

View File

@@ -0,0 +1,29 @@
package ai
// https://www.volcengine.com/docs/82379/1536429
const uiTarsPlanningPrompt = `
You are a GUI agent. You are given a task and your action history, with screenshots. You need to perform the next action to complete the task.
## Output Format
` + "```" + `
Thought: ...
Action: ...
` + "```" + `
## Action Space
click(start_box='[x1, y1, x2, y2]')
left_double(start_box='[x1, y1, x2, y2]')
right_single(start_box='[x1, y1, x2, y2]')
drag(start_box='[x1, y1, x2, y2]', end_box='[x3, y3, x4, y4]')
hotkey(key='')
type(content='') #If you want to submit your input, use "\n" at the end of ` + "`content`" + `.
scroll(start_box='[x1, y1, x2, y2]', direction='down or up or right or left')
wait() #Sleep for 5s and take a screenshot to check for any changes.
finished(content='xxx') # Use escape characters \\', \\", and \\n in content part to ensure we can parse the content in normal python string format.
## Note
- Use Chinese in ` + "`Thought`" + ` part.
- Write a small plan and finally summarize your next action (with its target element) in one sentence in ` + "`Thought`" + ` part.
## User Instruction
`

View File

@@ -4,7 +4,6 @@ import (
"context"
"fmt"
"math"
"os"
"regexp"
"strconv"
"strings"
@@ -14,64 +13,12 @@ import (
"github.com/cloudwego/eino/components/model"
"github.com/cloudwego/eino/schema"
"github.com/httprunner/httprunner/v5/code"
"github.com/httprunner/httprunner/v5/internal/config"
"github.com/httprunner/httprunner/v5/internal/json"
"github.com/httprunner/httprunner/v5/uixt/types"
"github.com/pkg/errors"
"github.com/rs/zerolog/log"
)
const (
EnvArkBaseURL = "ARK_BASE_URL"
EnvArkAPIKey = "ARK_API_KEY"
EnvArkModelID = "ARK_MODEL_ID"
)
func GetArkModelConfig() (*ark.ChatModelConfig, error) {
if err := config.LoadEnv(); err != nil {
return nil, errors.Wrap(code.LoadEnvError, err.Error())
}
arkBaseURL := os.Getenv(EnvArkBaseURL)
arkAPIKey := os.Getenv(EnvArkAPIKey)
if arkAPIKey == "" {
return nil, errors.Wrapf(code.LLMEnvMissedError,
"env %s missed", EnvArkAPIKey)
}
modelName := os.Getenv(EnvArkModelID)
if modelName == "" {
return nil, errors.Wrapf(code.LLMEnvMissedError,
"env %s missed", EnvArkModelID)
}
timeout := defaultTimeout
// https://www.volcengine.com/docs/82379/1494384?redirect=1
temperature := float32(0.01) // [0, 2] 采样温度。控制了生成文本时对每个候选词的概率分布进行平滑的程度。
// topP := float32(0.7) // [0, 1] 核采样概率阈值。模型会考虑概率质量在 top_p 内的 token 结果。
// maxTokens := int(4096) // 模型可以生成的最大 token 数量。输入 token 和输出 token 的总长度还受模型的上下文长度限制。
// frequencyPenalty := float32(0) // [-2, 2] 频率惩罚系数。如果值为正,会根据新 token 在文本中的出现频率对其进行惩罚,从而降低模型逐字重复的可能性。
modelConfig := &ark.ChatModelConfig{
BaseURL: arkBaseURL,
APIKey: arkAPIKey,
Model: modelName,
Timeout: &timeout,
Temperature: &temperature,
// TopP: &topP,
// MaxTokens: &maxTokens,
// FrequencyPenalty: &frequencyPenalty,
}
// log config info
log.Info().Str("model", modelConfig.Model).
Str("baseURL", modelConfig.BaseURL).
Str("apiKey", maskAPIKey(modelConfig.APIKey)).
Str("timeout", defaultTimeout.String()).
Msg("get model config")
return modelConfig, nil
}
func NewUITarsPlanner(ctx context.Context) (*UITarsPlanner, error) {
config, err := GetArkModelConfig()
if err != nil {
@@ -84,45 +31,17 @@ func NewUITarsPlanner(ctx context.Context) (*UITarsPlanner, error) {
return &UITarsPlanner{
ctx: ctx,
config: config,
model: chatModel,
modelType: LLMServiceTypeUITARS,
systemPrompt: uiTarsPlanningPrompt,
}, nil
}
// https://www.volcengine.com/docs/82379/1536429
const uiTarsPlanningPrompt = `
You are a GUI agent. You are given a task and your action history, with screenshots. You need to perform the next action to complete the task.
## Output Format
` + "```" + `
Thought: ...
Action: ...
` + "```" + `
## Action Space
click(start_box='[x1, y1, x2, y2]')
left_double(start_box='[x1, y1, x2, y2]')
right_single(start_box='[x1, y1, x2, y2]')
drag(start_box='[x1, y1, x2, y2]', end_box='[x3, y3, x4, y4]')
hotkey(key='')
type(content='') #If you want to submit your input, use "\n" at the end of ` + "`content`" + `.
scroll(start_box='[x1, y1, x2, y2]', direction='down or up or right or left')
wait() #Sleep for 5s and take a screenshot to check for any changes.
finished(content='xxx') # Use escape characters \\', \\", and \\n in content part to ensure we can parse the content in normal python string format.
## Note
- Use Chinese in ` + "`Thought`" + ` part.
- Write a small plan and finally summarize your next action (with its target element) in one sentence in ` + "`Thought`" + ` part.
## User Instruction
`
type UITarsPlanner struct {
ctx context.Context
model model.ToolCallingChatModel
config *ark.ChatModelConfig
systemPrompt string
modelType LLMServiceType
history ConversationHistory
}
@@ -152,7 +71,7 @@ func (p *UITarsPlanner) Call(opts *PlanningOptions) (*PlanningResult, error) {
startTime := time.Now()
resp, err := p.model.Generate(p.ctx, p.history)
log.Info().Float64("elapsed(s)", time.Since(startTime).Seconds()).
Str("model", p.config.Model).Msg("call model service")
Str("model", string(p.modelType)).Msg("call model service")
if err != nil {
return nil, errors.Wrap(code.LLMRequestServiceError, err.Error())
}

103
uixt/ai/session.go Normal file
View File

@@ -0,0 +1,103 @@
package ai
import (
"strings"
"github.com/cloudwego/eino/schema"
"github.com/rs/zerolog/log"
)
// ConversationHistory represents a sequence of chat messages
type ConversationHistory []*schema.Message
// Append adds a new message to the conversation history
func (h *ConversationHistory) Append(msg *schema.Message) {
// for user image message:
// - keep at most 4 user image messages
// - delete the oldest user image message when the limit is reached
if msg.Role == schema.User {
// get all existing user messages
userImgCount := 0
firstUserImgIndex := -1
// calculate the number of user messages and find the index of the first user message
for i, item := range *h {
if item.Role == schema.User {
userImgCount++
if firstUserImgIndex == -1 {
firstUserImgIndex = i
}
}
}
// if there are already 4 user messages, delete the first one before adding the new message
if userImgCount >= 4 && firstUserImgIndex >= 0 {
// delete the first user message
*h = append(
(*h)[:firstUserImgIndex],
(*h)[firstUserImgIndex+1:]...,
)
}
// add the new user message to the history
*h = append(*h, msg)
}
// for assistant message:
// - keep at most the last 10 assistant messages
if msg.Role == schema.Assistant {
// add the new assistant message to the history
*h = append(*h, msg)
// if there are more than 10 assistant messages, remove the oldest ones
assistantMsgCount := 0
for i := len(*h) - 1; i >= 0; i-- {
if (*h)[i].Role == schema.Assistant {
assistantMsgCount++
if assistantMsgCount > 10 {
*h = append((*h)[:i], (*h)[i+1:]...)
}
}
}
}
}
func logRequest(messages ConversationHistory) {
msgs := make(ConversationHistory, 0, len(messages))
for _, message := range messages {
msg := &schema.Message{
Role: message.Role,
}
if message.Content != "" {
msg.Content = message.Content
} else if len(message.MultiContent) > 0 {
for _, mc := range message.MultiContent {
switch mc.Type {
case schema.ChatMessagePartTypeImageURL:
// Create a copy of the ImageURL to avoid modifying the original message
imageURLCopy := *mc.ImageURL
if strings.HasPrefix(imageURLCopy.URL, "data:image/") {
imageURLCopy.URL = "<data:image/base64...>"
}
msg.MultiContent = append(msg.MultiContent, schema.ChatMessagePart{
Type: mc.Type,
ImageURL: &imageURLCopy,
})
}
}
}
msgs = append(msgs, msg)
}
log.Debug().Interface("messages", msgs).Msg("log request messages")
}
func logResponse(resp *schema.Message) {
logger := log.Info().Str("role", string(resp.Role)).
Str("content", resp.Content)
if resp.ResponseMeta != nil {
logger = logger.Interface("response_meta", resp.ResponseMeta)
}
if resp.Extra != nil {
logger = logger.Interface("extra", resp.Extra)
}
logger.Msg("log response message")
}

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