Files
ragflow/internal/entity/models/lmstudio.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

564 lines
15 KiB
Go

package models
import (
"bufio"
"bytes"
"context"
"encoding/json"
"fmt"
"io"
"net/http"
"ragflow/internal/common"
"strings"
"time"
)
// LmStudioModel implements ModelDriver for lm-studio
type LmStudioModel struct {
BaseURL map[string]string
URLSuffix URLSuffix
httpClient *http.Client
}
// NewLmStudioModel
func NewLmStudioModel(baseURL map[string]string, urlSuffix URLSuffix) *LmStudioModel {
return &LmStudioModel{
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 (l *LmStudioModel) NewInstance(baseURL map[string]string) ModelDriver {
return &LmStudioModel{
BaseURL: baseURL,
URLSuffix: l.URLSuffix,
httpClient: &http.Client{
Timeout: 120 * time.Second,
Transport: &http.Transport{
MaxIdleConns: 100,
MaxIdleConnsPerHost: 10,
IdleConnTimeout: 90 * time.Second,
DisableCompression: false,
},
},
}
}
func (l *LmStudioModel) Name() string {
return "lmstudio"
}
// ChatWithMessages sends multiple messages with roles and returns response
func (l *LmStudioModel) 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.Region != nil {
region = *apiConfig.Region
}
url := fmt.Sprintf("%s/%s", l.BaseURL[region], l.URLSuffix.Chat)
// For qwen/glm models, use async chat endpoint
modelType := strings.Split(modelName, "-")[0]
if modelType == "qwen" || modelType == "glm" {
url = fmt.Sprintf("%s/%s", l.BaseURL[region], l.URLSuffix.AsyncChat)
}
// 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
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 {
reqBody["thinking"] = map[string]interface{}{
"type": "enabled",
}
} 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")
req.Header.Set("Authorization", fmt.Sprintf("Bearer %s", *apiConfig.ApiKey))
resp, err := l.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 :%s", resp.StatusCode, string(body), messages[0].Content)
}
// 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 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 (l *LmStudioModel) ChatStreamlyWithSender(modelName string, messages []Message, apiConfig *APIConfig, modelConfig *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/%s", l.BaseURL[region], l.URLSuffix.Chat)
modelType := strings.Split(modelName, "-")[0]
if modelType == "qwen" || modelType == "glm" {
url = fmt.Sprintf("%s/%s", l.BaseURL[region], l.URLSuffix.AsyncChat)
}
// Convert messages to API format (supporting multimodal content)
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,
}
if modelConfig.Stream != nil {
reqBody["stream"] = *modelConfig.Stream
}
if modelConfig.MaxTokens != nil {
reqBody["max_tokens"] = *modelConfig.MaxTokens
}
if modelConfig.Temperature != nil {
reqBody["temperature"] = *modelConfig.Temperature
}
if modelConfig.DoSample != nil {
reqBody["do_sample"] = *modelConfig.DoSample
}
if modelConfig.TopP != nil {
reqBody["top_p"] = *modelConfig.TopP
}
if modelConfig.Stop != nil {
reqBody["stop"] = *modelConfig.Stop
}
if modelConfig.Thinking != nil {
if *modelConfig.Thinking {
reqBody["thinking"] = map[string]interface{}{
"type": "enabled",
}
} 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 := l.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
}
reasoningContent, ok := delta["reasoning_content"].(string)
if ok && reasoningContent != "" {
if err := sender(nil, &reasoningContent); err != nil {
return err
}
}
content, ok := delta["content"].(string)
if ok && content != "" {
if err := sender(&content, nil); 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()
}
func (l *LmStudioModel) Embed(modelName *string, texts []string, apiConfig *APIConfig, embeddingConfig *EmbeddingConfig) ([]EmbeddingData, error) {
if len(texts) == 0 {
return []EmbeddingData{}, nil
}
if modelName == nil || *modelName == "" {
return nil, fmt.Errorf("model name is required")
}
region := "default"
if apiConfig != nil && apiConfig.Region != nil && *apiConfig.Region != "" {
region = *apiConfig.Region
}
baseURL := l.BaseURL[region]
if baseURL == "" {
baseURL = l.BaseURL["default"]
}
if baseURL == "" {
return nil, fmt.Errorf("missing base URL: please configure the local access address for LM Studio (e.g., http://127.0.0.1:1234/v1)")
}
url := fmt.Sprintf("%s/%s", strings.TrimSuffix(baseURL, "/"), l.URLSuffix.Embedding)
reqBody := map[string]interface{}{
"model": *modelName,
"input": texts,
}
if embeddingConfig != nil && embeddingConfig.Dimension > 0 {
reqBody["dimensions"] = embeddingConfig.Dimension
}
jsonData, err := json.Marshal(reqBody)
if err != nil {
return nil, fmt.Errorf("failed to marshal request: %w", err)
}
ctx, cancel := context.WithTimeout(context.Background(), 30*time.Second)
defer cancel()
req, err := http.NewRequestWithContext(ctx, "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 && *apiConfig.ApiKey != "" {
req.Header.Set("Authorization", fmt.Sprintf("Bearer %s", *apiConfig.ApiKey))
}
resp, err := l.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("LM Studio embeddings API error: %s, body: %s", resp.Status, string(body))
}
var parsed openaiEmbeddingResponse
if err = json.Unmarshal(body, &parsed); err != nil {
return nil, fmt.Errorf("failed to parse response: %w", err)
}
var embeddings []EmbeddingData
for _, dataElem := range parsed.Data {
var embeddingData EmbeddingData
embeddingData.Embedding = dataElem.Embedding
embeddingData.Index = dataElem.Index
embeddings = append(embeddings, embeddingData)
}
return embeddings, nil
}
func (l *LmStudioModel) Rerank(modelName *string, query string, documents []string, apiConfig *APIConfig, rerankConfig *RerankConfig) (*RerankResponse, error) {
return nil, fmt.Errorf("no such method")
}
// TranscribeAudio transcribe audio
func (z *LmStudioModel) TranscribeAudio(modelName *string, file *string, apiConfig *APIConfig, asrConfig *ASRConfig) (*ASRResponse, error) {
return nil, fmt.Errorf("%s, no such method", z.Name())
}
func (z *LmStudioModel) 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 (z *LmStudioModel) AudioSpeech(modelName *string, audioContent *string, apiConfig *APIConfig, ttsConfig *TTSConfig) (*TTSResponse, error) {
return nil, fmt.Errorf("%s, no such method", z.Name())
}
func (z *LmStudioModel) 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 (l *LmStudioModel) OCRFile(modelName *string, content []byte, url *string, apiConfig *APIConfig, ocrConfig *OCRConfig) (*OCRFileResponse, error) {
return nil, fmt.Errorf("%s, no such method", l.Name())
}
// ParseFile parse file
func (z *LmStudioModel) ParseFile(modelName *string, content []byte, url *string, apiConfig *APIConfig, parseFileConfig *ParseFileConfig) (*ParseFileResponse, error) {
return nil, fmt.Errorf("%s, no such method", z.Name())
}
// ListModels list supported models
func (l *LmStudioModel) ListModels(apiConfig *APIConfig) ([]string, error) {
var region = "default"
if apiConfig != nil && apiConfig.Region != nil && *apiConfig.Region != "" {
region = *apiConfig.Region
}
baseURL := l.BaseURL[region]
if baseURL == "" {
baseURL = l.BaseURL["default"]
}
if baseURL == "" {
return nil, fmt.Errorf("missing base URL: please configure the local access address for LM Studio (e.g., http://127.0.0.1:1234/v1)")
}
url := fmt.Sprintf("%s/%s", baseURL, l.URLSuffix.Models)
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")
// LM Studio is a local provider and the API key is optional. Only
// set the Authorization header when a non-empty key was supplied.
// This also avoids a nil-pointer dereference on apiConfig or ApiKey.
if apiConfig != nil && apiConfig.ApiKey != nil && *apiConfig.ApiKey != "" {
req.Header.Set("Authorization", fmt.Sprintf("Bearer %s", *apiConfig.ApiKey))
}
resp, err := l.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 body: %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)
}
// convert result["data"] 2 []map[string]interface{}
models := make([]string, 0)
for _, model := range result["data"].([]interface{}) {
modelMap := model.(map[string]interface{})
modelName := modelMap["id"].(string)
models = append(models, modelName)
}
return models, nil
}
func (l *LmStudioModel) Balance(apiConfig *APIConfig) (map[string]interface{}, error) {
return nil, fmt.Errorf("no such method")
}
// CheckConnection verifies that the configured LM Studio base URL is reachable
func (l *LmStudioModel) CheckConnection(apiConfig *APIConfig) error {
_, err := l.ListModels(apiConfig)
return err
}
func (z *LmStudioModel) ListTasks(apiConfig *APIConfig) ([]ListTaskStatus, error) {
return nil, fmt.Errorf("%s, no such method", z.Name())
}
func (z *LmStudioModel) ShowTask(taskID string, apiConfig *APIConfig) (*TaskResponse, error) {
return nil, fmt.Errorf("%s, no such method", z.Name())
}