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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>
34 lines
1004 B
Go
34 lines
1004 B
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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"net/http"
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"ragflow/internal/model"
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)
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func init() {
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RegisterEmbeddingModelFactory("OpenAI-API-Compatible", func(apiKey, apiBase, modelName string, httpClient *http.Client) model.EmbeddingModel {
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return &openAIEmbeddingModel{
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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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