fd3e2992b1
Introduce per-model `custom_headers` config (similar to OpenAI Python SDK's `extra_headers`) so users can inject gateway auth tokens, trace IDs, etc. into every outbound API request for chat / embedding / rerank / VLLM / ASR models. Reserved headers like Authorization / Content-Type are always preserved to avoid breaking auth or signing flows. Along the way, unify production and "test connection" paths onto a single `ConfigFromModel(*types.Model, appID, appSecret)` constructor in each model package. Both `service.modelService.GetXxxModel` and the four `handler.initialization.Check*Model` / `TestEmbeddingModel` endpoints now go through the same field mapping, so new parameters only need to be added in one place. Backend: - Add `CustomHeaders map[string]string` to `types.ModelParameters` with JSON/YAML `omitempty` tags for forward compatibility. - New `internal/utils/extraheaders.go` providing `ApplyCustomHeaders` (for hand-rolled HTTP paths) and `WrapHTTPClientWithHeaders` / `CustomHeadersRoundTripper` (for SDK paths like go-openai). Reserved headers (Authorization, api-key, Content-Type, Accept, Host, Content-Length, User-Agent) are filtered out. - Inject headers in every remote model path: chat (SDK + raw HTTP), embedding (openai/aliyun/jina/volcengine/nvidia/azure_openai), rerank (remote_api/aliyun/jina/nvidia/zhipu — via shared `customHeaderSetter` interface), VLM and ASR (via http.Client wrapping). - Add `ConfigFromModel` to each of chat/embedding/rerank/vlm/asr, consolidating field mapping (ExtraConfig, CustomHeaders, InterfaceType defaulting, WeKnoraCloud credentials, etc.) and cover it with dedicated unit tests per package. - Refactor `service/model.go`: replace ~100 lines of hand-written Config literals with one-line `ConfigFromModel` calls; drop the now-unused `stringMapToAnyMap` helper. - Refactor `handler/initialization.go` test-connection endpoints: merge four ad-hoc request structs into one `ModelTestRequest`, extract `buildTestModel` and `resolveTenantWeKnoraCloudCreds` helpers, and route all four endpoints through `ConfigFromModel` + `NewXxx` so the test path is now behaviorally identical to production. Frontend: - Add `custom_headers` to the `ModelConfig` API type. - `ModelEditorDialog.vue`: new Key-Value header editor (add/remove rows), auto-converts map <-> array when loading/saving, and passes the current header set to the `Test Connection` button so the preview reflects exactly what production will send. - `ModelSettings.vue`: serialize the header array back into a map for the backend (drops empty rows). - i18n: add custom-header labels / descriptions / placeholders to zh-CN, en-US, ru-RU, ko-KR. Tests: - `internal/utils/extraheaders_test.go` covers reserved-header filtering and round-tripper wrapping (including nil-client fallback). - New `config_from_model_test.go` in chat / embedding / rerank / vlm / asr verifies all fields (CustomHeaders, ExtraConfig, InterfaceType defaulting, AppID/AppSecret) are propagated end-to-end.
147 lines
4.7 KiB
Go
147 lines
4.7 KiB
Go
package rerank
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import (
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"bytes"
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"context"
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"encoding/json"
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"fmt"
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"io"
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"net/http"
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"github.com/Tencent/WeKnora/internal/logger"
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secutils "github.com/Tencent/WeKnora/internal/utils"
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)
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// NvidiaReranker implements a reranking system using Jina AI API
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// Jina API uses different parameters than standard OpenAI-compatible APIs
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type NvidiaReranker struct {
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modelName string // Name of the model used for reranking
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modelID string // Unique identifier of the model
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apiKey string // API key for authentication
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baseURL string // Base URL for API requests
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client *http.Client // HTTP client for making API requests
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customHeaders map[string]string
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}
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// SetCustomHeaders 设置用户自定义 HTTP 请求头(类似 OpenAI Python SDK 的 extra_headers)。
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func (r *NvidiaReranker) SetCustomHeaders(headers map[string]string) {
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r.customHeaders = headers
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}
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type NvidiaRerankDocument struct {
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Text string `json:"text"`
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}
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// NvidiaRerankRequest represents a Jina rerank request
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// Note: Jina does NOT support truncate_prompt_tokens parameter
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type NvidiaRerankRequest struct {
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Model string `json:"model"` // Model to use for reranking
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Query NvidiaRerankDocument `json:"query"` // Query text to compare documents against
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Documents []NvidiaRerankDocument `json:"passages"` // List of document texts to rerank
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}
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type NvidiaRankResult struct {
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Index int `json:"index"`
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RelevanceScore float64 `json:"logit"`
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}
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// NvidiaRerankResponse represents the response from a Jina reranking request
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type NvidiaRerankResponse struct {
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Model string `json:"model"` // Model used for reranking
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Results []NvidiaRankResult `json:"rankings"` // Ranked results with relevance scores
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}
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// NewNvidiaReranker creates a new instance of Jina reranker with the provided configuration
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func NewNvidiaReranker(config *RerankerConfig) (*NvidiaReranker, error) {
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apiKey := config.APIKey
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baseURL := "https://ai.api.nvidia.com/v1/retrieval/nvidia/reranking"
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if url := config.BaseURL; url != "" {
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baseURL = url
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}
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return &NvidiaReranker{
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modelName: config.ModelName,
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modelID: config.ModelID,
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apiKey: apiKey,
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baseURL: baseURL,
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client: &http.Client{
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Transport: &http.Transport{
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Proxy: http.ProxyFromEnvironment,
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},
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},
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}, nil
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}
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// Rerank performs document reranking based on relevance to the query
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func (r *NvidiaReranker) Rerank(ctx context.Context, query string, documents []string) ([]RankResult, error) {
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// Build the request body - Jina does NOT use truncate_prompt_tokens
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requestBody := &NvidiaRerankRequest{
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Model: r.modelName,
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Query: NvidiaRerankDocument{Text: query},
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Documents: make([]NvidiaRerankDocument, len(documents)),
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}
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for i := range requestBody.Documents {
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requestBody.Documents[i].Text = documents[i]
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}
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jsonData, err := json.Marshal(requestBody)
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if err != nil {
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return nil, fmt.Errorf("marshal request body: %w", err)
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}
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// Send the request
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req, err := http.NewRequestWithContext(ctx, "POST", r.baseURL, bytes.NewBuffer(jsonData))
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if err != nil {
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return nil, fmt.Errorf("create request: %w", err)
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}
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req.Header.Set("Content-Type", "application/json")
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req.Header.Set("Authorization", fmt.Sprintf("Bearer %s", r.apiKey))
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secutils.ApplyCustomHeaders(req, r.customHeaders)
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// Log the curl equivalent for debugging (API key masked for security)
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logger.GetLogger(ctx).Infof(
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"curl -X POST %s/rerank -H \"Content-Type: application/json\" -H \"Authorization: Bearer ***\" -d '%s'",
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r.baseURL, string(jsonData),
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)
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resp, err := r.client.Do(req)
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if err != nil {
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return nil, fmt.Errorf("do request: %w", err)
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}
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defer resp.Body.Close()
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// Read the response
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body, err := io.ReadAll(resp.Body)
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if err != nil {
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return nil, fmt.Errorf("read response body: %w", err)
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}
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if resp.StatusCode != http.StatusOK {
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logger.GetLogger(ctx).Errorf("JinaReranker API error: Http Status: %s, Body: %s", resp.Status, string(body))
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return nil, fmt.Errorf("Rerank API error: Http Status: %s", resp.Status)
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}
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var response NvidiaRerankResponse
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if err := json.Unmarshal(body, &response); err != nil {
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return nil, fmt.Errorf("unmarshal response: %w", err)
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}
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ret := make([]RankResult, len(response.Results))
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for i, result := range response.Results {
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ret[i] = RankResult{
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Index: result.Index,
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Document: DocumentInfo{Text: documents[result.Index]},
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RelevanceScore: result.RelevanceScore,
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}
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}
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return ret, nil
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}
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// GetModelName returns the name of the reranking model
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func (r *NvidiaReranker) GetModelName() string {
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return r.modelName
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}
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// GetModelID returns the unique identifier of the reranking model
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func (r *NvidiaReranker) GetModelID() string {
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return r.modelID
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}
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