mlogclub
5d7c10aeab
- Updated runtime configuration to use __CS_AI_AGENT_WIDGET_CONFIG__ instead of __CS_AGENT_WIDGET_CONFIG__. - Changed message types in support host bridge from "cs-agent" to "cs-ai-agent". - Minified SDK script updated to reflect new AI agent naming conventions. - Adjusted scrollbar styles in main.scss to use .cs-ai-agent-scrollbar instead of .cs-agent-scrollbar.
102 lines
2.5 KiB
Go
102 lines
2.5 KiB
Go
package ai
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import (
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"context"
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"fmt"
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openai "github.com/openai/openai-go/v3"
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"cs-ai-agent/internal/models"
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"cs-ai-agent/internal/pkg/enums"
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"cs-ai-agent/internal/pkg/errorsx"
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)
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type EmbeddingResult struct {
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Vector []float32
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TokensUsed int
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ModelName string
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Dimension int
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}
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type embedding struct{}
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var Embedding = &embedding{}
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func (s *embedding) GetModel(ctx context.Context) (*models.AIConfig, error) {
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config, err := GetEnabledAIConfig(enums.AIModelTypeEmbedding)
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if err != nil {
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return nil, errorsx.BusinessError(2001, "未配置可用的 Embedding 模型")
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}
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return config, nil
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}
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func (s *embedding) GenerateEmbedding(ctx context.Context, text string) (*EmbeddingResult, error) {
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if text == "" {
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return nil, errorsx.InvalidParam("文本内容不能为空")
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}
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result, err := s.callEmbeddingAPI(ctx, text)
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if err != nil {
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return nil, err
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}
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return result, nil
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}
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func (s *embedding) GenerateBatchEmbeddings(ctx context.Context, texts []string) ([]EmbeddingResult, error) {
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if len(texts) == 0 {
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return nil, errorsx.InvalidParam("文本列表不能为空")
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}
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results := make([]EmbeddingResult, 0, len(texts))
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for _, text := range texts {
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result, err := s.callEmbeddingAPI(ctx, text)
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if err != nil {
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return nil, fmt.Errorf("failed to generate embedding for text: %w", err)
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}
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results = append(results, *result)
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}
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return results, nil
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}
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func (s *embedding) callEmbeddingAPI(ctx context.Context, text string) (*EmbeddingResult, error) {
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config, err := GetEnabledAIConfig(enums.AIModelTypeEmbedding)
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if err != nil {
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return nil, err
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}
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client := newOpenAIClient(*config)
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embeddingResp, err := client.Embeddings.New(ctx, openai.EmbeddingNewParams{
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Input: openai.EmbeddingNewParamsInputUnion{
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OfString: openai.String(text),
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},
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Model: openai.EmbeddingModel(config.ModelName),
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})
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if err != nil {
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return nil, fmt.Errorf("failed to call embedding api: %w", err)
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}
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if len(embeddingResp.Data) == 0 {
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return nil, fmt.Errorf("no embedding data in response")
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}
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vector := make([]float32, 0, len(embeddingResp.Data[0].Embedding))
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for _, item := range embeddingResp.Data[0].Embedding {
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vector = append(vector, float32(item))
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}
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return &EmbeddingResult{
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Vector: vector,
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TokensUsed: int(embeddingResp.Usage.TotalTokens),
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ModelName: embeddingResp.Model,
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Dimension: len(vector),
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}, nil
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}
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func (s *embedding) GetDimension(ctx context.Context) (int, error) {
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model, err := s.GetModel(ctx)
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if err != nil {
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return 0, err
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}
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return model.Dimension, nil
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}
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