Files
ragflow/internal/entity/models/deepseek.go
Haruko386 bf41d35729 Go: implement PaddleOCR provider and implement ASR for CoHere (#14954)
### What problem does this PR solve?

This PR implement implement OCR for Baidu and Mistral, implement
PaddleOCR provider and implement ASR for CoHere

**Verified examples from the CLI:**

```
RAGFlow(user)> ocr with 'mistral-ocr-2512@test@mistral' file './internal/text.jpg'
+------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| text                                                                                                                                                                                                                                                             |
+------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| Parallel to these organizational innovations there were significant complementary technical innovations (e.g., improved methods of manufacturing cast-iron pipe and of coating interiors for pressure maintenance, and newer paving and construction material... |
+------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+


RAGFlow(user)> ocr with 'paddleocr-vl-0.9b@test@baidu' file './internal/text.jpg'
+------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| text                                                                                                                                                                                                                                                             |
+------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| Parallel to these organizational innovations there were significant complementary technical innovations (e.g., improved methods of manufacturing cast-iron pipe and of coating interiors for pressure maintenance, and newer paving and construction material... |
+------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+

# PaddleOCR
RAGFlow(user)> ocr with 'PaddleOCR-VL-1.5@test@paddleocr' file './internal/test.pdf'
+------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| text                                                                                                                                                                                                                                                             |
+------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| # Repurposing Diffusion-Based Image Generators for Monocular Depth Estimation

Bingxin Ke

Nando Metzger

Photogra

Anton Obukhov

Rodrigo Caye Daudt

netry and Remote Sensing,

Shengyu Huang

Konrad Schindler

ETH Zürich





<div style="text-align: c...  |
+------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+

# Cohere

RAGFlow(user)> asr with 'cohere-transcribe-03-2026@test@cohere' audio './internal/test.wav' param '{"language": "en"}'
+-----------------------------------------------------------------------------------------------------------------------+
| text                                                                                                                  |
+-----------------------------------------------------------------------------------------------------------------------+
|  The examination and testimony of the experts enabled the Commission to conclude that five shots may have been fired. |
+-----------------------------------------------------------------------------------------------------------------------+
```

### Type of change

- [x] New Feature (non-breaking change which adds functionality)
- [x] Refactoring
2026-05-15 18:41:43 +08:00

623 lines
17 KiB
Go

//
// Copyright 2026 The InfiniFlow Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
//
package models
import (
"bufio"
"bytes"
"encoding/json"
"fmt"
"io"
"net/http"
"ragflow/internal/common"
"strconv"
"strings"
"time"
)
// DeepSeekModel implements ModelDriver for DeepSeek
type DeepSeekModel struct {
BaseURL map[string]string
URLSuffix URLSuffix
httpClient *http.Client // Reusable HTTP client with connection pool
}
// NewDeepSeekModel creates a new DeepSeek model instance
func NewDeepSeekModel(baseURL map[string]string, urlSuffix URLSuffix) *DeepSeekModel {
return &DeepSeekModel{
BaseURL: baseURL,
URLSuffix: urlSuffix,
httpClient: &http.Client{
Timeout: 120 * time.Second,
Transport: &http.Transport{
MaxIdleConns: 100,
MaxIdleConnsPerHost: 10,
IdleConnTimeout: 90 * time.Second,
DisableCompression: false,
},
},
}
}
func (z *DeepSeekModel) NewInstance(baseURL map[string]string) ModelDriver {
return nil
}
func (z *DeepSeekModel) Name() string {
return "deepseek"
}
func (z *DeepSeekModel) ChatWithMessages(modelName string, messages []Message, apiConfig *APIConfig, chatModelConfig *ChatConfig) (*ChatResponse, error) {
if len(messages) == 0 {
return nil, fmt.Errorf("messages is empty")
}
var region = "default"
if apiConfig != nil && apiConfig.Region != nil && *apiConfig.Region != "" {
region = *apiConfig.Region
}
url := fmt.Sprintf("%s/%s", z.BaseURL[region], z.URLSuffix.Chat)
// Convert messages to the format expected by API
apiMessages := make([]map[string]interface{}, len(messages))
for i, msg := range messages {
apiMessages[i] = map[string]interface{}{
"role": msg.Role,
"content": msg.Content,
}
}
// Build request body
reqBody := map[string]interface{}{
"model": modelName,
"messages": apiMessages,
"stream": false,
"temperature": 1,
}
if chatModelConfig != nil {
if chatModelConfig.Stream != nil {
reqBody["stream"] = *chatModelConfig.Stream
}
if chatModelConfig.MaxTokens != nil {
reqBody["max_tokens"] = *chatModelConfig.MaxTokens
}
if chatModelConfig.Temperature != nil {
reqBody["temperature"] = *chatModelConfig.Temperature
}
if chatModelConfig.TopP != nil {
reqBody["top_p"] = *chatModelConfig.TopP
}
if chatModelConfig.Stop != nil {
reqBody["stop"] = *chatModelConfig.Stop
}
if chatModelConfig.Thinking != nil {
if *chatModelConfig.Thinking {
var thinkingFlag string
effort := "high"
if chatModelConfig.Effort != nil {
effort = *chatModelConfig.Effort
}
switch effort {
case "none":
thinkingFlag = "disabled"
chatModelConfig.Thinking = nil
case "low":
thinkingFlag = "disabled"
chatModelConfig.Thinking = nil
case "medium":
thinkingFlag = "disabled"
chatModelConfig.Thinking = nil
case "high":
thinkingFlag = "enabled"
reqBody["reasoning_effort"] = "high"
case "default":
thinkingFlag = "enabled"
reqBody["reasoning_effort"] = "high"
case "max":
thinkingFlag = "enabled"
reqBody["reasoning_effort"] = "max"
default:
thinkingFlag = "enabled"
reqBody["reasoning_effort"] = effort
}
reqBody["thinking"] = map[string]interface{}{
"type": thinkingFlag,
}
} else {
reqBody["thinking"] = map[string]interface{}{
"type": "disabled",
}
}
}
}
jsonData, err := json.Marshal(reqBody)
if err != nil {
return nil, fmt.Errorf("failed to marshal request: %w", err)
}
req, err := http.NewRequest("POST", url, bytes.NewBuffer(jsonData))
if err != nil {
return nil, fmt.Errorf("failed to create request: %w", err)
}
req.Header.Set("Content-Type", "application/json")
if apiConfig != nil && apiConfig.ApiKey != nil {
req.Header.Set("Authorization", fmt.Sprintf("Bearer %s", *apiConfig.ApiKey))
}
resp, err := z.httpClient.Do(req)
if err != nil {
return nil, fmt.Errorf("failed to send request: %w", err)
}
defer resp.Body.Close()
body, err := io.ReadAll(resp.Body)
if err != nil {
return nil, fmt.Errorf("failed to read response: %w", err)
}
if resp.StatusCode != http.StatusOK {
return nil, fmt.Errorf("API request failed with status %d: %s", resp.StatusCode, string(body))
}
// Parse response
var result map[string]interface{}
if err = json.Unmarshal(body, &result); err != nil {
return nil, fmt.Errorf("failed to parse response: %w", err)
}
choices, ok := result["choices"].([]interface{})
if !ok || len(choices) == 0 {
return nil, fmt.Errorf("no choices in response")
}
firstChoice, ok := choices[0].(map[string]interface{})
if !ok {
return nil, fmt.Errorf("invalid choice format")
}
messageMap, ok := firstChoice["message"].(map[string]interface{})
if !ok {
return nil, fmt.Errorf("invalid message format")
}
content, ok := messageMap["content"].(string)
if !ok {
return nil, fmt.Errorf("invalid content format")
}
var reasonContent string
if chatModelConfig != nil && chatModelConfig.Thinking != nil && *chatModelConfig.Thinking {
reasonContent, ok = messageMap["reasoning_content"].(string)
if !ok {
return nil, fmt.Errorf("invalid content format")
}
// if first char of reasonContent is \n remove the '\n'
if reasonContent != "" && reasonContent[0] == '\n' {
reasonContent = reasonContent[1:]
}
}
chatResponse := &ChatResponse{
Answer: &content,
ReasonContent: &reasonContent,
}
return chatResponse, nil
}
// ChatStreamlyWithSender sends messages and streams response via sender function (best performance, no channel)
func (z *DeepSeekModel) ChatStreamlyWithSender(modelName string, messages []Message, apiConfig *APIConfig, chatModelConfig *ChatConfig, sender func(*string, *string) error) error {
if len(messages) == 0 {
return fmt.Errorf("messages is empty")
}
var region = "default"
if apiConfig != nil && apiConfig.Region != nil && *apiConfig.Region != "" {
region = *apiConfig.Region
}
url := fmt.Sprintf("%s/chat/completions", z.BaseURL[region])
// Convert messages to API format
apiMessages := make([]map[string]interface{}, len(messages))
for i, msg := range messages {
apiMessages[i] = map[string]interface{}{
"role": msg.Role,
"content": msg.Content,
}
}
// Build request body with streaming enabled
reqBody := map[string]interface{}{
"model": modelName,
"messages": apiMessages,
"stream": true,
"temperature": 1,
}
if chatModelConfig != nil {
if chatModelConfig.Stream != nil {
reqBody["stream"] = *chatModelConfig.Stream
}
if chatModelConfig.MaxTokens != nil {
reqBody["max_tokens"] = *chatModelConfig.MaxTokens
}
if chatModelConfig.Temperature != nil {
reqBody["temperature"] = *chatModelConfig.Temperature
}
if chatModelConfig.DoSample != nil {
reqBody["do_sample"] = *chatModelConfig.DoSample
}
if chatModelConfig.TopP != nil {
reqBody["top_p"] = *chatModelConfig.TopP
}
if chatModelConfig.Stop != nil {
reqBody["stop"] = *chatModelConfig.Stop
}
if chatModelConfig.Thinking != nil {
if *chatModelConfig.Thinking {
var thinkingFlag string
switch *chatModelConfig.Effort {
case "none":
thinkingFlag = "disabled"
break
case "low":
thinkingFlag = "disabled"
break
case "medium":
thinkingFlag = "disabled"
break
case "high":
thinkingFlag = "enabled"
reqBody["reasoning_effort"] = "high"
break
case "default":
thinkingFlag = "enabled"
reqBody["reasoning_effort"] = "high"
break
case "max":
thinkingFlag = "enabled"
reqBody["reasoning_effort"] = "max"
break
default:
return fmt.Errorf("invalid effort level")
}
reqBody["thinking"] = map[string]interface{}{
"type": thinkingFlag,
}
} else {
reqBody["thinking"] = map[string]interface{}{
"type": "disabled",
}
}
}
}
jsonData, err := json.Marshal(reqBody)
if err != nil {
return fmt.Errorf("failed to marshal request: %w", err)
}
req, err := http.NewRequest("POST", url, bytes.NewBuffer(jsonData))
if err != nil {
return fmt.Errorf("failed to create request: %w", err)
}
req.Header.Set("Content-Type", "application/json")
req.Header.Set("Authorization", fmt.Sprintf("Bearer %s", *apiConfig.ApiKey))
resp, err := z.httpClient.Do(req)
if err != nil {
return fmt.Errorf("failed to send request: %w", err)
}
defer resp.Body.Close()
if resp.StatusCode != http.StatusOK {
body, _ := io.ReadAll(resp.Body)
return fmt.Errorf("API request failed with status %d: %s", resp.StatusCode, string(body))
}
// SSE parsing: read line by line
scanner := bufio.NewScanner(resp.Body)
for scanner.Scan() {
line := scanner.Text()
common.Info(line)
// SSE data line starts with "data:"
if !strings.HasPrefix(line, "data:") {
continue
}
// Extract JSON after "data:"
data := strings.TrimSpace(line[5:])
// [DONE] marks the end of stream
if data == "[DONE]" {
break
}
// Parse the JSON event
var event map[string]interface{}
if err = json.Unmarshal([]byte(data), &event); err != nil {
continue
}
choices, ok := event["choices"].([]interface{})
if !ok || len(choices) == 0 {
continue
}
firstChoice, ok := choices[0].(map[string]interface{})
if !ok {
continue
}
delta, ok := firstChoice["delta"].(map[string]interface{})
if !ok {
continue
}
content, ok := delta["content"].(string)
if ok && content != "" {
if err := sender(&content, nil); err != nil {
return err
}
}
reasoningContent, ok := delta["reasoning_content"].(string)
if ok && reasoningContent != "" {
if err := sender(nil, &reasoningContent); err != nil {
return err
}
}
finishReason, ok := firstChoice["finish_reason"].(string)
if ok && finishReason != "" {
break
}
}
// Send [DONE] marker for OpenAI compatibility
endOfStream := "[DONE]"
if err = sender(&endOfStream, nil); err != nil {
return err
}
return scanner.Err()
}
// Embed embeds a list of texts into embeddings
func (z *DeepSeekModel) Embed(modelName *string, texts []string, apiConfig *APIConfig, embeddingConfig *EmbeddingConfig) ([]EmbeddingData, error) {
return nil, fmt.Errorf("%s, no such method", z.Name())
}
type DSModel struct {
ID string `json:"id"`
Object string `json:"object"`
OwnedBy string `json:"owned_by"`
}
type DSModelList struct {
Object string `json:"object"`
Models []DSModel `json:"data"`
}
func (z *DeepSeekModel) ListModels(apiConfig *APIConfig) ([]string, error) {
var region = "default"
if apiConfig.Region != nil {
region = *apiConfig.Region
}
url := fmt.Sprintf("%s/%s", z.BaseURL[region], z.URLSuffix.Models)
// Build request body
reqBody := map[string]interface{}{}
jsonData, err := json.Marshal(reqBody)
if err != nil {
return nil, fmt.Errorf("failed to marshal request: %w", err)
}
req, err := http.NewRequest("GET", url, bytes.NewBuffer(jsonData))
if err != nil {
return nil, fmt.Errorf("failed to create request: %w", err)
}
req.Header.Set("Content-Type", "application/json")
req.Header.Set("Authorization", fmt.Sprintf("Bearer %s", *apiConfig.ApiKey))
resp, err := z.httpClient.Do(req)
if err != nil {
return nil, fmt.Errorf("failed to send request: %w", err)
}
defer resp.Body.Close()
body, err := io.ReadAll(resp.Body)
if err != nil {
return nil, fmt.Errorf("failed to read response: %w", err)
}
if resp.StatusCode != http.StatusOK {
return nil, fmt.Errorf("API request failed with status %d: %s", resp.StatusCode, string(body))
}
// Parse response
var modelList DSModelList
if err = json.Unmarshal(body, &modelList); err != nil {
return nil, fmt.Errorf("failed to parse response: %w", err)
}
var models []string
for _, model := range modelList.Models {
models = append(models, model.ID)
}
return models, nil
}
// deepseekBalanceResponse is the shape returned by
// GET /user/balance. The balance fields are strings in the
// upstream API, so we parse them on our side.
type deepseekBalanceResponse struct {
IsAvailable bool `json:"is_available"`
BalanceInfos []struct {
Currency string `json:"currency"`
TotalBalance string `json:"total_balance"`
GrantedBalance string `json:"granted_balance"`
ToppedUpBalance string `json:"topped_up_balance"`
} `json:"balance_infos"`
}
// Balance returns the user's available balance on DeepSeek by
// calling GET /user/balance with the configured Bearer token.
// The result map matches the shape used by the Moonshot driver,
// so the UI can render it without provider-specific code.
func (z *DeepSeekModel) Balance(apiConfig *APIConfig) (map[string]interface{}, error) {
if apiConfig == nil || apiConfig.ApiKey == nil || *apiConfig.ApiKey == "" {
return nil, fmt.Errorf("api key is required")
}
region := "default"
if apiConfig.Region != nil && *apiConfig.Region != "" {
region = *apiConfig.Region
}
// Look up the base URL for the requested region. If the region was
// supplied but is not configured (or is empty), fall back to the
// "default" region instead of erroring out, so a stray region value
// does not break an otherwise valid request.
baseURL := z.BaseURL["default"]
if region != "default" {
if regional, ok := z.BaseURL[region]; ok && regional != "" {
baseURL = regional
}
}
if baseURL == "" {
return nil, fmt.Errorf("deepseek: no base URL configured for default region")
}
url := fmt.Sprintf("%s/%s", strings.TrimSuffix(baseURL, "/"), z.URLSuffix.Balance)
req, err := http.NewRequest("GET", url, nil)
if err != nil {
return nil, fmt.Errorf("failed to create request: %w", err)
}
req.Header.Set("Authorization", fmt.Sprintf("Bearer %s", *apiConfig.ApiKey))
resp, err := z.httpClient.Do(req)
if err != nil {
return nil, fmt.Errorf("failed to send request: %w", err)
}
defer resp.Body.Close()
body, err := io.ReadAll(resp.Body)
if err != nil {
return nil, fmt.Errorf("failed to read response: %w", err)
}
if resp.StatusCode != http.StatusOK {
return nil, fmt.Errorf("DeepSeek balance API error: %s, body: %s", resp.Status, string(body))
}
var parsed deepseekBalanceResponse
if err = json.Unmarshal(body, &parsed); err != nil {
return nil, fmt.Errorf("failed to parse response: %w", err)
}
if len(parsed.BalanceInfos) == 0 {
return nil, fmt.Errorf("no balance info in response")
}
// Pick the first balance entry, the same way the Moonshot
// driver returns a single {balance, currency} pair to the UI.
first := parsed.BalanceInfos[0]
total, err := strconv.ParseFloat(first.TotalBalance, 64)
if err != nil {
return nil, fmt.Errorf("invalid total_balance %q: %w", first.TotalBalance, err)
}
return map[string]interface{}{
"balance": total,
"currency": first.Currency,
}, nil
}
func (z *DeepSeekModel) CheckConnection(apiConfig *APIConfig) error {
_, err := z.ListModels(apiConfig)
if err != nil {
return err
}
return nil
}
// Rerank calculates similarity scores between query and documents
func (z *DeepSeekModel) Rerank(modelName *string, query string, documents []string, apiConfig *APIConfig, rerankConfig *RerankConfig) (*RerankResponse, error) {
return nil, fmt.Errorf("%s, Rerank not implemented", z.Name())
}
// TranscribeAudio transcribe audio
func (d *DeepSeekModel) TranscribeAudio(modelName *string, file *string, apiConfig *APIConfig, asrConfig *ASRConfig) (*ASRResponse, error) {
return nil, fmt.Errorf("%s, no such method", d.Name())
}
func (z *DeepSeekModel) TranscribeAudioWithSender(modelName *string, file *string, apiConfig *APIConfig, asrConfig *ASRConfig, sender func(*string, *string) error) error {
return fmt.Errorf("%s, no such method", z.Name())
}
// AudioSpeech convert text to audio
func (d *DeepSeekModel) AudioSpeech(modelName *string, audioContent *string, apiConfig *APIConfig, ttsConfig *TTSConfig) (*TTSResponse, error) {
return nil, fmt.Errorf("%s, no such method", d.Name())
}
func (z *DeepSeekModel) AudioSpeechWithSender(modelName *string, audioContent *string, apiConfig *APIConfig, ttsConfig *TTSConfig, sender func(*string, *string) error) error {
return fmt.Errorf("%s, no such method", z.Name())
}
// OCRFile OCR file
func (d *DeepSeekModel) OCRFile(modelName *string, content []byte, url *string, apiConfig *APIConfig, ocrConfig *OCRConfig) (*OCRFileResponse, error) {
return nil, fmt.Errorf("%s, no such method", d.Name())
}
// ParseFile parse file
func (z *DeepSeekModel) ParseFile(modelName *string, content []byte, url *string, apiConfig *APIConfig, parseFileConfig *ParseFileConfig) (*ParseFileResponse, error) {
return nil, fmt.Errorf("%s, no such method", z.Name())
}
func (z *DeepSeekModel) ListTasks(apiConfig *APIConfig) ([]ListTaskStatus, error) {
return nil, fmt.Errorf("%s, no such method", z.Name())
}
func (z *DeepSeekModel) ShowTask(taskID string, apiConfig *APIConfig) (*TaskResponse, error) {
return nil, fmt.Errorf("%s, no such method", z.Name())
}