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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>
72 lines
2.5 KiB
Go
72 lines
2.5 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 model
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// ModelType represents the type of model
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type ModelType string
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const (
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// ModelTypeChat chat model
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ModelTypeChat ModelType = "chat"
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// ModelTypeEmbedding embedding model
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ModelTypeEmbedding ModelType = "embedding"
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// ModelTypeSpeech2Text speech to text model
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ModelTypeSpeech2Text ModelType = "speech2text"
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// ModelTypeImage2Text image to text model
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ModelTypeImage2Text ModelType = "image2text"
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// ModelTypeRerank rerank model
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ModelTypeRerank ModelType = "rerank"
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// ModelTypeTTS text to speech model
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ModelTypeTTS ModelType = "tts"
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// ModelTypeOCR optical character recognition model
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ModelTypeOCR ModelType = "ocr"
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)
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// EmbeddingModel interface for embedding models
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type EmbeddingModel interface {
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// Encode encodes a list of texts into embeddings
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Encode(texts []string) ([][]float64, error)
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// EncodeQuery encodes a single query string into embedding
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EncodeQuery(query string) ([]float64, error)
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}
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// ChatModel interface for chat models
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type ChatModel interface {
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// Chat sends a message and returns response
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Chat(system string, history []map[string]string, genConf map[string]interface{}) (string, error)
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// ChatStreamly sends a message and streams response
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ChatStreamly(system string, history []map[string]string, genConf map[string]interface{}) (<-chan string, error)
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}
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// RerankModel interface for rerank models
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type RerankModel interface {
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// Similarity calculates similarity between query and texts
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Similarity(query string, texts []string) ([]float64, error)
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}
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// ModelConfig represents configuration for a model
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type ModelConfig struct {
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TenantID string `json:"tenant_id"`
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LLMFactory string `json:"llm_factory"`
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ModelType ModelType `json:"model_type"`
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LLMName string `json:"llm_name"`
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APIKey string `json:"api_key"`
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APIBase string `json:"api_base"`
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MaxTokens int64 `json:"max_tokens"`
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IsTools bool `json:"is_tools"`
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}
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