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# RAGFlow Go Implementation Plan 🚀 This repository tracks the progress of porting RAGFlow to Go. We'll implement core features and provide performance comparisons between Python and Go versions. ## Implementation Checklist - [x] User Management APIs - [x] Dataset Management Operations - [x] Retrieval Test - [x] Chat Management Operations - [x] Infinity Go SDK --------- Signed-off-by: Jin Hai <haijin.chn@gmail.com> Co-authored-by: Yingfeng Zhang <yingfeng.zhang@gmail.com>
124 lines
3.4 KiB
Go
124 lines
3.4 KiB
Go
//
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// Copyright 2026 The InfiniFlow Authors. All Rights Reserved.
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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//
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package models
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import (
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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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"ragflow/internal/model"
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"strings"
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)
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// siliconflowEmbeddingModel implements EmbeddingModel for SILICONFLOW API (OpenAI-compatible)
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type siliconflowEmbeddingModel struct {
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apiKey string
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apiBase string
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model string
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httpClient *http.Client
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}
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// SiliconflowEmbeddingRequest represents SILICONFLOW embedding request
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type SiliconflowEmbeddingRequest struct {
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Model string `json:"model"`
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Input []string `json:"input"`
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}
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// SiliconflowEmbeddingResponse represents SILICONFLOW embedding response
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type SiliconflowEmbeddingResponse struct {
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Data []struct {
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Embedding []float64 `json:"embedding"`
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Index int `json:"index"`
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} `json:"data"`
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}
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// Encode encodes a list of texts into embeddings using SILICONFLOW API
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func (m *siliconflowEmbeddingModel) Encode(texts []string) ([][]float64, error) {
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if len(texts) == 0 {
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return [][]float64{}, nil
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}
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reqBody := SiliconflowEmbeddingRequest{
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Model: m.model,
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Input: texts,
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}
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jsonData, err := json.Marshal(reqBody)
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if err != nil {
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return nil, fmt.Errorf("failed to marshal request: %w", err)
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}
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req, err := http.NewRequest("POST", m.apiBase+"/embeddings", strings.NewReader(string(jsonData)))
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if err != nil {
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return nil, fmt.Errorf("failed to 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", "Bearer "+m.apiKey)
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resp, err := m.httpClient.Do(req)
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if err != nil {
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return nil, fmt.Errorf("failed to send request: %w", err)
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}
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defer resp.Body.Close()
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if resp.StatusCode != http.StatusOK {
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body, _ := io.ReadAll(resp.Body)
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return nil, fmt.Errorf("SILICONFLOW API error: %s, body: %s", resp.Status, string(body))
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}
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var embeddingResp SiliconflowEmbeddingResponse
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if err := json.NewDecoder(resp.Body).Decode(&embeddingResp); err != nil {
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return nil, fmt.Errorf("failed to decode response: %w", err)
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}
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// Sort embeddings by index to ensure correct order
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embeddings := make([][]float64, len(texts))
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for _, data := range embeddingResp.Data {
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if data.Index < len(embeddings) {
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embeddings[data.Index] = data.Embedding
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}
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}
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return embeddings, nil
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}
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// EncodeQuery encodes a single query string into embedding
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func (m *siliconflowEmbeddingModel) EncodeQuery(query string) ([]float64, error) {
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embeddings, err := m.Encode([]string{query})
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if err != nil {
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return nil, err
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}
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if len(embeddings) == 0 {
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return nil, fmt.Errorf("no embedding returned")
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}
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return embeddings[0], nil
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}
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// init registers the SILICONFLOW embedding model factory
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func init() {
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RegisterEmbeddingModelFactory("SILICONFLOW", func(apiKey, apiBase, modelName string, httpClient *http.Client) model.EmbeddingModel {
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return &siliconflowEmbeddingModel{
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apiKey: apiKey,
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apiBase: apiBase,
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model: modelName,
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httpClient: httpClient,
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}
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})
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}
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