WeKnora deployment source with the reviewed wiki identity, summary and recovery fixes

internal/models/embedding/gemini.go

@@ -0,0 +1,248 @@
+package embedding
+
+import (
+	"bytes"
+	"context"
+	"encoding/json"
+	"fmt"
+	"io"
+	"net/http"
+	"strings"
+	"time"
+
+	"github.com/Tencent/WeKnora/internal/logger"
+	"github.com/Tencent/WeKnora/internal/models/requestbudget"
+	secutils "github.com/Tencent/WeKnora/internal/utils"
+)
+
+const geminiEmbeddingBaseURL = "https://generativelanguage.googleapis.com/v1beta"
+
+// GeminiEmbedder implements text vectorization using the native Gemini
+// embedContent / batchEmbedContents REST API.
+type GeminiEmbedder struct {
+	apiKey                    string
+	baseURL                   string
+	modelName                 string
+	truncatePromptTokens      int
+	dimensions                int
+	modelID                   string
+	httpClient                *http.Client
+	timeout                   time.Duration
+	maxRetries                int
+	customHeaders             map[string]string
+	supportsDimensionOverride bool
+	EmbedderPooler
+}
+
+type geminiBatchEmbedRequest struct {
+	Requests []geminiEmbedRequest `json:"requests"`
+}
+
+type geminiEmbedRequest struct {
+	Model                string        `json:"model"`
+	Content              geminiContent `json:"content"`
+	TaskType             string        `json:"taskType,omitempty"`
+	OutputDimensionality int           `json:"output_dimensionality,omitempty"`
+}
+
+type geminiContent struct {
+	Parts []geminiPart `json:"parts"`
+}
+
+type geminiPart struct {
+	Text string `json:"text"`
+}
+
+type geminiBatchEmbedResponse struct {
+	Embeddings []geminiEmbedding `json:"embeddings"`
+}
+
+type geminiEmbedding struct {
+	Values []float32 `json:"values"`
+}
+
+func NewGeminiEmbedder(apiKey, baseURL, modelName string,
+	truncatePromptTokens int, dimensions int, modelID string, pooler EmbedderPooler,
+) (*GeminiEmbedder, error) {
+	if modelName == "" {
+		return nil, fmt.Errorf("model name is required")
+	}
+	if truncatePromptTokens == 0 {
+		truncatePromptTokens = 511
+	}
+	if baseURL == "" {
+		baseURL = geminiEmbeddingBaseURL
+	}
+
+	baseURL = strings.TrimRight(baseURL, "/")
+	if strings.HasSuffix(baseURL, "/openai") {
+		baseURL = strings.TrimSuffix(baseURL, "/openai")
+	}
+
+	timeout := 60 * time.Second
+
+	if err := validateEmbeddingBaseURL(baseURL); err != nil {
+		return nil, err
+	}
+
+	return &GeminiEmbedder{
+		apiKey:               apiKey,
+		baseURL:              baseURL,
+		modelName:            strings.TrimPrefix(modelName, "models/"),
+		truncatePromptTokens: truncatePromptTokens,
+		dimensions:           dimensions,
+		modelID:              modelID,
+		httpClient:           newEmbeddingHTTPClient(timeout),
+		timeout:              timeout,
+		maxRetries:           3,
+		EmbedderPooler:       pooler,
+	}, nil
+}
+
+func (e *GeminiEmbedder) SetCustomHeaders(headers map[string]string) {
+	e.customHeaders = headers
+}
+
+func (e *GeminiEmbedder) SetSupportsDimensionOverride(supported bool) {
+	e.supportsDimensionOverride = supported
+}
+
+func (e *GeminiEmbedder) Embed(ctx context.Context, text string) ([]float32, error) {
+	embeddings, err := e.BatchEmbed(ctx, []string{text})
+	if err != nil {
+		return nil, err
+	}
+	if len(embeddings) == 0 {
+		return nil, fmt.Errorf("no embedding returned")
+	}
+	return embeddings[0], nil
+}
+
+func (e *GeminiEmbedder) BatchEmbed(ctx context.Context, texts []string) ([][]float32, error) {
+	if len(texts) == 0 {
+		return nil, nil
+	}
+
+	requests := make([]geminiEmbedRequest, 0, len(texts))
+	for _, text := range texts {
+		req := geminiEmbedRequest{
+			Model: "models/" + e.modelName,
+			Content: geminiContent{Parts: []geminiPart{
+				{Text: text},
+			}},
+		}
+		if e.supportsDimensionOverride && e.dimensions > 0 {
+			req.OutputDimensionality = e.dimensions
+		}
+		requests = append(requests, req)
+	}
+
+	jsonData, err := json.Marshal(geminiBatchEmbedRequest{Requests: requests})
+	if err != nil {
+		logger.GetLogger(ctx).Errorf("GeminiEmbedder BatchEmbed marshal request error: %v", err)
+		return nil, fmt.Errorf("marshal request: %w", err)
+	}
+
+	logger.GetLogger(ctx).Debugf("GeminiEmbedder BatchEmbed: model=%s, input_count=%d",
+		e.modelName, len(texts))
+
+	resp, err := e.doRequestWithRetry(ctx, jsonData)
+	if err != nil {
+		logger.GetLogger(ctx).Errorf("GeminiEmbedder BatchEmbed send request error: %v", err)
+		return nil, fmt.Errorf("send request: %w", err)
+	}
+	if resp.Body != nil {
+		defer resp.Body.Close()
+	}
+
+	body, err := io.ReadAll(resp.Body)
+	if err != nil {
+		logger.GetLogger(ctx).Errorf("GeminiEmbedder BatchEmbed read response error: %v", err)
+		return nil, fmt.Errorf("read response: %w", err)
+	}
+
+	if resp.StatusCode != http.StatusOK {
+		bodyStr := string(body)
+		if len(bodyStr) > 1000 {
+			bodyStr = bodyStr[:1000] + "... (truncated)"
+		}
+		logger.GetLogger(ctx).Errorf("GeminiEmbedder BatchEmbed API error: Http Status %s, Response Body: %s", resp.Status, bodyStr)
+		return nil, fmt.Errorf("Gemini BatchEmbed API error: Http Status %s, Response: %s", resp.Status, bodyStr)
+	}
+
+	var response geminiBatchEmbedResponse
+	if err := json.Unmarshal(body, &response); err != nil {
+		logger.GetLogger(ctx).Errorf("GeminiEmbedder BatchEmbed unmarshal response error: %v", err)
+		return nil, fmt.Errorf("unmarshal response: %w", err)
+	}
+	if len(response.Embeddings) != len(texts) {
+		return nil, fmt.Errorf("Gemini BatchEmbed returned %d embeddings for %d inputs", len(response.Embeddings), len(texts))
+	}
+
+	embeddings := make([][]float32, 0, len(response.Embeddings))
+	for _, embedding := range response.Embeddings {
+		embeddings = append(embeddings, embedding.Values)
+	}
+	return embeddings, nil
+}
+
+func (e *GeminiEmbedder) doRequestWithRetry(ctx context.Context, jsonData []byte) (*http.Response, error) {
+	ctx = requestbudget.WithModel(ctx, e.modelID)
+	var resp *http.Response
+	var err error
+	url := fmt.Sprintf("%s/models/%s:batchEmbedContents", e.baseURL, e.modelName)
+
+	for i := 0; i <= e.maxRetries; i++ {
+		if err := requestbudget.Check(ctx); err != nil {
+			return nil, err
+		}
+		if i > 0 {
+			backoffTime := time.Duration(1<<uint(i-1)) * time.Second
+			if backoffTime > 10*time.Second {
+				backoffTime = 10 * time.Second
+			}
+			logger.GetLogger(ctx).
+				Infof("GeminiEmbedder retrying request (%d/%d), waiting %v", i, e.maxRetries, backoffTime)
+
+			select {
+			case <-time.After(backoffTime):
+			case <-ctx.Done():
+				return nil, ctx.Err()
+			}
+		}
+
+		var req *http.Request
+		req, err = http.NewRequestWithContext(ctx, "POST", url, bytes.NewReader(jsonData))
+		if err != nil {
+			logger.GetLogger(ctx).Errorf("GeminiEmbedder failed to create request: %v", err)
+			continue
+		}
+		req.Header.Set("Content-Type", "application/json")
+		req.Header.Set("x-goog-api-key", e.apiKey)
+		secutils.ApplyCustomHeaders(req, e.customHeaders)
+
+		resp, err = e.httpClient.Do(req)
+		if stopProviderRetry(ctx, err) {
+			return nil, err
+		}
+		if err == nil {
+			return resp, nil
+		}
+
+		logger.GetLogger(ctx).Errorf("GeminiEmbedder request failed (attempt %d/%d): %v", i+1, e.maxRetries+1, err)
+	}
+
+	return nil, err
+}
+
+func (e *GeminiEmbedder) GetModelName() string {
+	return e.modelName
+}
+
+func (e *GeminiEmbedder) GetDimensions() int {
+	return e.dimensions
+}
+
+func (e *GeminiEmbedder) GetModelID() string {
+	return e.modelID
+}