mirror of
https://github.com/httprunner/httprunner.git
synced 2026-05-11 18:11:21 +08:00
refactor: ai asserter
This commit is contained in:
@@ -49,6 +49,8 @@ type LLMServiceType string
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const (
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LLMServiceTypeUITARS LLMServiceType = "ui-tars"
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LLMServiceTypeGPT4o LLMServiceType = "gpt-4o"
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LLMServiceTypeGPT4Vision LLMServiceType = "gpt-4-vision"
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LLMServiceTypeQwenVL LLMServiceType = "qwen-vl"
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LLMServiceTypeDeepSeekV3 LLMServiceType = "deepseek-v3"
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)
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@@ -58,45 +60,33 @@ type ILLMService interface {
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Assert(opts *AssertOptions) (*AssertionResponse, error)
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}
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func WithLLMService(service LLMServiceType) AIServiceOption {
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func WithLLMService(modelType LLMServiceType) AIServiceOption {
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return func(opts *AIServices) {
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switch service {
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// init planner
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var planner IPlanner
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var err error
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switch modelType {
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case LLMServiceTypeGPT4o:
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// TODO: implement gpt-4o planner and asserter
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planner, err := NewPlanner(context.Background())
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if err != nil {
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log.Error().Err(err).Msg("init gpt-4o planner failed")
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os.Exit(code.GetErrorCode(err))
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}
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asserter, err := NewUITarsAsserter(context.Background())
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if err != nil {
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log.Error().Err(err).Msg("init ui-tars asserter failed")
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os.Exit(code.GetErrorCode(err))
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}
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opts.ILLMService = &combinedLLMService{
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planner: planner,
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asserter: asserter,
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}
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planner, err = NewPlanner(context.Background())
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case LLMServiceTypeUITARS:
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planner, err := NewUITarsPlanner(context.Background())
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if err != nil {
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log.Error().Err(err).Msg("init ui-tars planner failed")
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os.Exit(code.GetErrorCode(err))
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}
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planner, err = NewUITarsPlanner(context.Background())
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}
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if err != nil {
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log.Error().Err(err).Msgf("init %s planner failed", modelType)
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os.Exit(code.GetErrorCode(err))
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}
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asserter, err := NewUITarsAsserter(context.Background())
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if err != nil {
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log.Error().Err(err).Msg("init ui-tars asserter failed")
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os.Exit(code.GetErrorCode(err))
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}
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// init asserter
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asserter, err := NewAsserter(context.Background(), modelType)
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if err != nil {
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log.Error().Err(err).Msgf("init %s asserter failed", modelType)
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os.Exit(code.GetErrorCode(err))
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}
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opts.ILLMService = &combinedLLMService{
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planner: planner,
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asserter: asserter,
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}
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opts.ILLMService = &combinedLLMService{
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planner: planner,
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asserter: asserter,
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}
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}
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}
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62
uixt/ai/ai_ark.go
Normal file
62
uixt/ai/ai_ark.go
Normal file
@@ -0,0 +1,62 @@
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package ai
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import (
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"os"
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"github.com/cloudwego/eino-ext/components/model/ark"
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"github.com/httprunner/httprunner/v5/code"
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"github.com/httprunner/httprunner/v5/internal/config"
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"github.com/pkg/errors"
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"github.com/rs/zerolog/log"
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)
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const (
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EnvArkBaseURL = "ARK_BASE_URL"
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EnvArkAPIKey = "ARK_API_KEY"
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EnvArkModelID = "ARK_MODEL_ID"
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)
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func GetArkModelConfig() (*ark.ChatModelConfig, error) {
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if err := config.LoadEnv(); err != nil {
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return nil, errors.Wrap(code.LoadEnvError, err.Error())
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}
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arkBaseURL := os.Getenv(EnvArkBaseURL)
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arkAPIKey := os.Getenv(EnvArkAPIKey)
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if arkAPIKey == "" {
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return nil, errors.Wrapf(code.LLMEnvMissedError,
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"env %s missed", EnvArkAPIKey)
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}
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modelName := os.Getenv(EnvArkModelID)
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if modelName == "" {
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return nil, errors.Wrapf(code.LLMEnvMissedError,
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"env %s missed", EnvArkModelID)
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}
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timeout := defaultTimeout
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// https://www.volcengine.com/docs/82379/1494384?redirect=1
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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。
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// 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。
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// 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。
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// 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。
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modelConfig := &ark.ChatModelConfig{
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BaseURL: arkBaseURL,
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APIKey: arkAPIKey,
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Model: modelName,
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Timeout: &timeout,
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Temperature: &temperature,
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// TopP: &topP,
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// MaxTokens: &maxTokens,
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// FrequencyPenalty: &frequencyPenalty,
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}
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// log config info
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log.Info().Str("model", modelConfig.Model).
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Str("baseURL", modelConfig.BaseURL).
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Str("apiKey", maskAPIKey(modelConfig.APIKey)).
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Str("timeout", defaultTimeout.String()).
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Msg("get model config")
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return modelConfig, nil
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}
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79
uixt/ai/ai_openai.go
Normal file
79
uixt/ai/ai_openai.go
Normal file
@@ -0,0 +1,79 @@
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package ai
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import (
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"os"
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"github.com/cloudwego/eino-ext/components/model/openai"
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openai2 "github.com/cloudwego/eino-ext/libs/acl/openai"
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"github.com/getkin/kin-openapi/openapi3gen"
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"github.com/httprunner/httprunner/v5/code"
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"github.com/httprunner/httprunner/v5/internal/config"
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"github.com/pkg/errors"
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"github.com/rs/zerolog/log"
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)
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const (
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EnvOpenAIBaseURL = "OPENAI_BASE_URL"
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EnvOpenAIAPIKey = "OPENAI_API_KEY"
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EnvModelName = "LLM_MODEL_NAME"
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)
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// GetOpenAIModelConfig get OpenAI config
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func GetOpenAIModelConfig() (*openai.ChatModelConfig, error) {
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if err := config.LoadEnv(); err != nil {
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return nil, errors.Wrap(code.LoadEnvError, err.Error())
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}
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openaiBaseURL := os.Getenv(EnvOpenAIBaseURL)
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if openaiBaseURL == "" {
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return nil, errors.Wrapf(code.LLMEnvMissedError,
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"env %s missed", EnvOpenAIBaseURL)
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}
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openaiAPIKey := os.Getenv(EnvOpenAIAPIKey)
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if openaiAPIKey == "" {
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return nil, errors.Wrapf(code.LLMEnvMissedError,
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"env %s missed", EnvOpenAIAPIKey)
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}
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modelName := os.Getenv(EnvModelName)
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if modelName == "" {
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return nil, errors.Wrapf(code.LLMEnvMissedError,
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"env %s missed", EnvModelName)
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}
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type OutputFormat struct {
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Thought string `json:"thought"`
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Action string `json:"action"`
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Error string `json:"error,omitempty"`
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}
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outputFormatSchema, err := openapi3gen.NewSchemaRefForValue(&OutputFormat{}, nil)
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if err != nil {
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return nil, err
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}
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modelConfig := &openai.ChatModelConfig{
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BaseURL: openaiBaseURL,
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APIKey: openaiAPIKey,
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Model: modelName,
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Timeout: defaultTimeout,
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// set structured response format
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// https://github.com/cloudwego/eino-ext/blob/main/components/model/openai/examples/structured/structured.go
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ResponseFormat: &openai2.ChatCompletionResponseFormat{
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Type: openai2.ChatCompletionResponseFormatTypeJSONSchema,
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JSONSchema: &openai2.ChatCompletionResponseFormatJSONSchema{
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Name: "thought_and_action",
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Description: "data that describes planning thought and action",
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Schema: outputFormatSchema.Value,
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Strict: false,
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},
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},
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}
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// log config info
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log.Info().Str("model", modelConfig.Model).
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Str("baseURL", modelConfig.BaseURL).
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Str("apiKey", maskAPIKey(modelConfig.APIKey)).
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Str("timeout", defaultTimeout.String()).
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Msg("get model config")
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return modelConfig, nil
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}
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@@ -8,6 +8,8 @@ import (
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"time"
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"github.com/cloudwego/eino-ext/components/model/ark"
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"github.com/cloudwego/eino-ext/components/model/openai"
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"github.com/cloudwego/eino/components/model"
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"github.com/cloudwego/eino/schema"
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"github.com/httprunner/httprunner/v5/code"
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"github.com/httprunner/httprunner/v5/internal/json"
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@@ -16,60 +18,11 @@ import (
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"github.com/rs/zerolog/log"
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)
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// IAsserter interface defines the contract for assertion operations
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type IAsserter interface {
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Assert(opts *AssertOptions) (*AssertionResponse, error)
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}
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// UI-TARS assertion system prompt
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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.
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## Output Json String Format
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` + "```" + `
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"{
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"pass": <<is a boolean value from the enum [true, false], true means the assertion is truthy>>,
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"thought": "<<is a string, give the reason why the assertion is falsy or truthy. Otherwise.>>"
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}"
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` + "```" + `
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## Rules **MUST** follow
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- Make sure to return **only** the JSON, with **no additional** text or explanations.
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- Use Chinese in 'thought' part.
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- You **MUST** strictly follow up the **Output Json String Format**.`
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// AssertionResponse represents the response from an AI assertion
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type AssertionResponse struct {
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Pass bool `json:"pass"`
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Thought string `json:"thought"`
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}
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// UITarsAsserter handles assertion using UI-TARS VLM
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type UITarsAsserter struct {
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ctx context.Context
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model *ark.ChatModel
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config *ark.ChatModelConfig
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systemPrompt string
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history ConversationHistory
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}
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// NewUITarsAsserter creates a new UITarsAsserter instance
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func NewUITarsAsserter(ctx context.Context) (*UITarsAsserter, error) {
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config, err := GetArkModelConfig()
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if err != nil {
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return nil, err
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}
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chatModel, err := ark.NewChatModel(ctx, config)
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if err != nil {
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return nil, err
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}
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return &UITarsAsserter{
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ctx: ctx,
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config: config,
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model: chatModel,
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systemPrompt: uiTarsAssertionPrompt,
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}, nil
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}
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// AssertOptions represents the input options for assertion
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type AssertOptions struct {
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Assertion string `json:"assertion"` // The assertion text to verify
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@@ -77,18 +30,65 @@ type AssertOptions struct {
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Size types.Size `json:"size"` // Screen dimensions
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}
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func validateAssertionInput(opts *AssertOptions) error {
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if opts.Assertion == "" {
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return errors.Wrap(code.LLMPrepareRequestError, "assertion text is required")
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// AssertionResponse represents the response from an AI assertion
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type AssertionResponse struct {
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Pass bool `json:"pass"`
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Thought string `json:"thought"`
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}
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// Asserter handles assertion using different AI models
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type Asserter struct {
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ctx context.Context
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model model.ToolCallingChatModel
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systemPrompt string
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history ConversationHistory
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modelType LLMServiceType
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}
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// NewAsserter creates a new Asserter instance
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func NewAsserter(ctx context.Context, modelType LLMServiceType) (*Asserter, error) {
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asserter := &Asserter{
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ctx: ctx,
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modelType: modelType,
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systemPrompt: getAssertionSystemPrompt(modelType),
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}
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if opts.Screenshot == "" {
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return errors.Wrap(code.LLMPrepareRequestError, "screenshot is required")
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switch modelType {
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case LLMServiceTypeUITARS:
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config, err := GetArkModelConfig()
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if err != nil {
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return nil, err
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}
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asserter.model, err = ark.NewChatModel(ctx, config)
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if err != nil {
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return nil, err
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}
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case LLMServiceTypeGPT4Vision, LLMServiceTypeGPT4o:
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config, err := GetOpenAIModelConfig()
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if err != nil {
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return nil, err
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}
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asserter.model, err = openai.NewChatModel(ctx, config)
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if err != nil {
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return nil, err
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}
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default:
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return nil, errors.New("not supported model type for asserter")
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}
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return nil
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return asserter, nil
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}
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// getAssertionSystemPrompt returns the appropriate system prompt for the given model type
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func getAssertionSystemPrompt(modelType LLMServiceType) string {
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if modelType == LLMServiceTypeUITARS {
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return defaultAssertionPrompt + "\n\n" + uiTarsAssertionResponseFormat
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}
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return defaultAssertionPrompt + "\n\n" + defaultAssertionResponseJsonFormat
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}
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// Assert performs the assertion check on the screenshot
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func (a *UITarsAsserter) Assert(opts *AssertOptions) (*AssertionResponse, error) {
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func (a *Asserter) Assert(opts *AssertOptions) (*AssertionResponse, error) {
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// Validate input parameters
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if err := validateAssertionInput(opts); err != nil {
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return nil, errors.Wrap(err, "validate assertion parameters failed")
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@@ -133,7 +133,7 @@ Here is the assertion. Please tell whether it is truthy according to the screens
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startTime := time.Now()
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resp, err := a.model.Generate(a.ctx, a.history)
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log.Info().Float64("elapsed(s)", time.Since(startTime).Seconds()).
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Str("model", a.config.Model).Msg("call model service for assertion")
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Str("model", string(a.modelType)).Msg("call model service for assertion")
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if err != nil {
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return nil, errors.Wrap(code.LLMRequestServiceError, err.Error())
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}
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@@ -154,78 +154,36 @@ Here is the assertion. Please tell whether it is truthy according to the screens
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return result, nil
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}
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// parseAssertionResult 解析模型返回的JSON响应
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// validateAssertionInput validates the input parameters for assertion
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func validateAssertionInput(opts *AssertOptions) error {
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if opts.Assertion == "" {
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return errors.Wrap(code.LLMPrepareRequestError, "assertion text is required")
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}
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if opts.Screenshot == "" {
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return errors.Wrap(code.LLMPrepareRequestError, "screenshot is required")
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}
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return nil
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}
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// parseAssertionResult parses the model response into AssertionResponse
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func parseAssertionResult(content string) (*AssertionResponse, error) {
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// 1. 从响应中提取JSON内容
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// Extract JSON content from response
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jsonContent := extractJSON(content)
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if jsonContent == "" {
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return nil, errors.New("could not extract JSON from response")
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}
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// 2. 预处理和标准解析尝试
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jsonContent = prepareJSON(jsonContent)
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// Parse JSON response
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var result AssertionResponse
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if err := json.Unmarshal([]byte(jsonContent), &result); err == nil {
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return &result, nil
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if err := json.Unmarshal([]byte(jsonContent), &result); err != nil {
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return nil, errors.Wrap(code.LLMParseAssertionResponseError, err.Error())
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}
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// 3. 备用:正则表达式解析
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if pass, thought := extractWithRegex(jsonContent); thought != "" {
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return &AssertionResponse{Pass: pass, Thought: thought}, nil
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}
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return nil, errors.New("failed to parse assertion result")
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}
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// prepareJSON 预处理JSON字符串,修复常见问题
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func prepareJSON(jsonStr string) string {
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// 1. 去除可能的外层引号
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jsonStr = strings.TrimSpace(jsonStr)
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if strings.HasPrefix(jsonStr, "\"") && strings.HasSuffix(jsonStr, "\"") {
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jsonStr = jsonStr[1 : len(jsonStr)-1]
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}
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// 2. 转义thought内容中的引号
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thoughtRegex := regexp.MustCompile(`"thought":\s*"([^"]*)"`)
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matches := thoughtRegex.FindStringSubmatch(jsonStr)
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if len(matches) > 1 {
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thoughtValue := matches[1]
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fixedThought := strings.ReplaceAll(thoughtValue, "\"", "\\\"")
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jsonStr = strings.Replace(jsonStr, matches[0], fmt.Sprintf(`"thought": "%s"`, fixedThought), 1)
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}
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// 3. 处理换行和特殊字符
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jsonStr = strings.ReplaceAll(jsonStr, "\n", "\\n")
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jsonStr = strings.ReplaceAll(jsonStr, "\r", "\\r")
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jsonStr = strings.ReplaceAll(jsonStr, "\t", "\\t")
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return jsonStr
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}
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// extractWithRegex 使用正则表达式提取pass和thought值
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func extractWithRegex(jsonStr string) (pass bool, thought string) {
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// 提取pass值
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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
|
||||
}
|
||||
25
uixt/ai/asserter_prompts.go
Normal file
25
uixt/ai/asserter_prompts.go
Normal 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**.`
|
||||
@@ -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
|
||||
|
||||
@@ -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())
|
||||
}
|
||||
|
||||
29
uixt/ai/planner_prompts.go
Normal file
29
uixt/ai/planner_prompts.go
Normal 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
|
||||
`
|
||||
@@ -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
103
uixt/ai/session.go
Normal 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")
|
||||
}
|
||||
BIN
uixt/ai/testdata/llk_4.png
vendored
Normal file
BIN
uixt/ai/testdata/llk_4.png
vendored
Normal file
Binary file not shown.
|
After Width: | Height: | Size: 585 KiB |
Reference in New Issue
Block a user