Files
ragflow/internal/entity/models/nvidia.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

673 lines
19 KiB
Go

package models
import (
"bufio"
"bytes"
"context"
"encoding/json"
"fmt"
"io"
"net/http"
"strings"
"time"
)
// NvidiaModel implements ModelDriver for Nvidia
type NvidiaModel struct {
BaseURL map[string]string
URLSuffix URLSuffix
httpClient *http.Client
}
// NewNvidiaModel creates a new Nvidia model instance
func NewNvidiaModel(baseURL map[string]string, urlSuffix URLSuffix) *NvidiaModel {
return &NvidiaModel{
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 (n NvidiaModel) NewInstance(baseURL map[string]string) ModelDriver {
return &NvidiaModel{
BaseURL: baseURL,
URLSuffix: n.URLSuffix,
httpClient: &http.Client{
Timeout: 120 * time.Second,
Transport: &http.Transport{
MaxIdleConns: 100,
MaxIdleConnsPerHost: 10,
IdleConnTimeout: 90 * time.Second,
DisableCompression: false,
},
},
}
}
func (n NvidiaModel) Name() string {
return "nvidia"
}
func (n *NvidiaModel) 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 {
region = *apiConfig.Region
}
baseURL := n.BaseURL[region]
if baseURL == "" {
baseURL = n.BaseURL["default"]
}
url := fmt.Sprintf("%s/%s", baseURL, n.URLSuffix.Chat)
apiMessages := make([]map[string]interface{}, len(messages))
for i, msg := range messages {
apiMessages[i] = map[string]interface{}{
"role": msg.Role,
"content": msg.Content,
}
}
reqBody := map[string]interface{}{
"model": modelName,
"messages": apiMessages,
"stream": false,
}
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")
if apiConfig != nil && apiConfig.ApiKey != nil {
req.Header.Set("Authorization", fmt.Sprintf("Bearer %s", *apiConfig.ApiKey))
}
resp, err := n.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))
}
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
}
func (n *NvidiaModel) 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
}
baseURL := n.BaseURL[region]
if baseURL == "" {
baseURL = n.BaseURL["default"]
}
url := fmt.Sprintf("%s/%s", baseURL, n.URLSuffix.Chat)
apiMessages := make([]map[string]interface{}, len(messages))
for i, msg := range messages {
apiMessages[i] = map[string]interface{}{
"role": msg.Role,
"content": msg.Content,
}
}
reqBody := map[string]interface{}{
"model": modelName,
"messages": apiMessages,
"stream": true,
}
if modelConfig != nil {
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")
if apiConfig != nil && apiConfig.ApiKey != nil {
req.Header.Set("Authorization", fmt.Sprintf("Bearer %s", *apiConfig.ApiKey))
}
resp, err := n.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))
}
scanner := bufio.NewScanner(resp.Body)
for scanner.Scan() {
line := scanner.Text()
if !strings.HasPrefix(line, "data:") {
continue
}
data := strings.TrimSpace(line[5:])
if data == "[DONE]" {
break
}
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
}
}
endOfStream := "[DONE]"
if err = sender(&endOfStream, nil); err != nil {
return err
}
return scanner.Err()
}
type nvidiaEmbeddingResponse struct {
Data []struct {
Index int `json:"index"`
Embedding []float64 `json:"embedding"`
} `json:"data"`
}
func (n NvidiaModel) Embed(modelName *string, texts []string, apiConfig *APIConfig, embeddingConfig *EmbeddingConfig) ([]EmbeddingData, error) {
if len(texts) == 0 {
return []EmbeddingData{}, nil
}
if apiConfig == nil || apiConfig.ApiKey == nil || *apiConfig.ApiKey == "" {
return nil, fmt.Errorf("api key is required")
}
if modelName == nil || *modelName == "" {
return nil, fmt.Errorf("model name is required")
}
region := "default"
if apiConfig.Region != nil && *apiConfig.Region != "" {
region = *apiConfig.Region
}
baseURL := n.BaseURL[region]
if baseURL == "" {
baseURL = n.BaseURL["default"]
}
if baseURL == "" {
return nil, fmt.Errorf("nvidia: no base URL configured for region %q", region)
}
url := fmt.Sprintf("%s/%s", strings.TrimSuffix(baseURL, "/"), n.URLSuffix.Embedding)
reqBody := map[string]interface{}{
"model": *modelName,
"input": texts,
"input_type": "query",
"encoding_format": "float",
"truncate": "END",
}
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")
req.Header.Set("Authorization", fmt.Sprintf("Bearer %s", *apiConfig.ApiKey))
resp, err := n.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("Nvidia embeddings API error: %s, body: %s", resp.Status, string(body))
}
var parsed nvidiaEmbeddingResponse
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
}
// nvidiaRerankRequest mirrors the NIM /ranking request shape:
// query is an object with a "text" field, passages is an array of
// objects each with a "text" field. truncate=END matches the Python
// NvidiaRerank reference at rag/llm/rerank_model.py.
type nvidiaRerankRequest struct {
Model string `json:"model"`
Query nvidiaRerankText `json:"query"`
Passages []nvidiaRerankText `json:"passages"`
Truncate string `json:"truncate,omitempty"`
TopN int `json:"top_n"`
}
type nvidiaRerankText struct {
Text string `json:"text"`
}
// nvidiaRerankResponse maps the NIM rankings array. Each entry pairs
// the original passage index with a logit score; the caller uses the
// index to restore original input order.
type nvidiaRerankResponse struct {
Rankings []struct {
Index int `json:"index"`
Logit float64 `json:"logit"`
} `json:"rankings"`
}
// Rerank scores documents against the query using an NVIDIA NIM
// reranking model. Mirrors the Python NvidiaRerank class in
// rag/llm/rerank_model.py for payload shape (passages/query/logit).
// Defaults top_n to len(documents) so the API returns a score per
// input; callers may shrink it via RerankConfig.TopN, in which case
// only the top RerankConfig.TopN entries come back. Returned
// RerankResult entries are in the API's ranking order; callers that
// need original-input order should sort by Index. Same return-shape
// contract as the Aliyun and ZhipuAI Rerank drivers.
func (n NvidiaModel) Rerank(modelName *string, query string, documents []string, apiConfig *APIConfig, rerankConfig *RerankConfig) (*RerankResponse, error) {
if len(documents) == 0 {
return &RerankResponse{}, nil
}
if apiConfig == nil || apiConfig.ApiKey == nil || *apiConfig.ApiKey == "" {
return nil, fmt.Errorf("api key is required")
}
if modelName == nil || *modelName == "" {
return nil, fmt.Errorf("model name is required")
}
region := "default"
if apiConfig.Region != nil && *apiConfig.Region != "" {
region = *apiConfig.Region
}
baseURL := n.BaseURL[region]
if baseURL == "" {
baseURL = n.BaseURL["default"]
}
if baseURL == "" {
return nil, fmt.Errorf("nvidia: no base URL configured for region %q", region)
}
url := fmt.Sprintf("%s/%s", strings.TrimSuffix(baseURL, "/"), n.URLSuffix.Rerank)
topN := len(documents)
if rerankConfig != nil && rerankConfig.TopN > 0 && rerankConfig.TopN < topN {
topN = rerankConfig.TopN
}
passages := make([]nvidiaRerankText, len(documents))
for i, doc := range documents {
passages[i] = nvidiaRerankText{Text: doc}
}
reqBody := nvidiaRerankRequest{
Model: *modelName,
Query: nvidiaRerankText{Text: query},
Passages: passages,
Truncate: "END",
TopN: topN,
}
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")
req.Header.Set("Authorization", fmt.Sprintf("Bearer %s", *apiConfig.ApiKey))
resp, err := n.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("Nvidia rerank API error: %s, body: %s", resp.Status, string(body))
}
var parsed nvidiaRerankResponse
if err = json.Unmarshal(body, &parsed); err != nil {
return nil, fmt.Errorf("failed to parse response: %w", err)
}
rerankResponse := RerankResponse{Data: make([]RerankResult, 0, len(parsed.Rankings))}
for _, r := range parsed.Rankings {
if r.Index < 0 || r.Index >= len(documents) {
return nil, fmt.Errorf("unexpected rerank index %d for %d inputs", r.Index, len(documents))
}
rerankResponse.Data = append(rerankResponse.Data, RerankResult{
Index: r.Index,
RelevanceScore: r.Logit,
})
}
return &rerankResponse, nil
}
// TranscribeAudio transcribe audio
func (n *NvidiaModel) TranscribeAudio(modelName *string, file *string, apiConfig *APIConfig, asrConfig *ASRConfig) (*ASRResponse, error) {
return nil, fmt.Errorf("%s, no such method", n.Name())
}
func (z *NvidiaModel) 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 (n *NvidiaModel) AudioSpeech(modelName *string, audioContent *string, apiConfig *APIConfig, ttsConfig *TTSConfig) (*TTSResponse, error) {
return nil, fmt.Errorf("%s, no such method", n.Name())
}
func (z *NvidiaModel) 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 (m *NvidiaModel) OCRFile(modelName *string, content []byte, url *string, apiConfig *APIConfig, ocrConfig *OCRConfig) (*OCRFileResponse, error) {
return nil, fmt.Errorf("%s, no such method", m.Name())
}
// ParseFile parse file
func (z *NvidiaModel) ParseFile(modelName *string, content []byte, url *string, apiConfig *APIConfig, parseFileConfig *ParseFileConfig) (*ParseFileResponse, error) {
return nil, fmt.Errorf("%s, no such method", z.Name())
}
// ListModels calls /v1/models on the configured NVIDIA NIM base URL
// and returns the list of available model ids. The endpoint is
// OpenAI-compatible, so the parsing follows the same shape used by
// the moonshot, xai, and openai drivers.
func (n NvidiaModel) ListModels(apiConfig *APIConfig) ([]string, error) {
var region = "default"
if apiConfig != nil && apiConfig.Region != nil && *apiConfig.Region != "" {
region = *apiConfig.Region
}
baseURL := n.BaseURL[region]
if baseURL == "" {
baseURL = n.BaseURL["default"]
}
if baseURL == "" {
return nil, fmt.Errorf("nvidia: no base URL configured for region %q", region)
}
url := fmt.Sprintf("%s/%s", baseURL, n.URLSuffix.Models)
req, err := http.NewRequest("GET", url, nil)
if err != nil {
return nil, fmt.Errorf("failed to create request: %w", err)
}
if apiConfig != nil && apiConfig.ApiKey != nil && *apiConfig.ApiKey != "" {
req.Header.Set("Authorization", fmt.Sprintf("Bearer %s", *apiConfig.ApiKey))
}
resp, err := n.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("Nvidia models API error: %s, body: %s", resp.Status, string(body))
}
var result map[string]interface{}
if err = json.Unmarshal(body, &result); err != nil {
return nil, fmt.Errorf("failed to parse response: %w", err)
}
data, ok := result["data"].([]interface{})
if !ok {
return nil, fmt.Errorf("invalid models list format")
}
models := make([]string, 0, len(data))
for _, item := range data {
m, ok := item.(map[string]interface{})
if !ok {
continue
}
id, ok := m["id"].(string)
if !ok {
continue
}
models = append(models, id)
}
return models, nil
}
func (n NvidiaModel) Balance(apiConfig *APIConfig) (map[string]interface{}, error) {
return nil, fmt.Errorf("no such method")
}
// CheckConnection verifies that the configured NVIDIA NIM base URL
// is reachable and that the API key is accepted, by issuing a
// lightweight ListModels call. Mirrors the pattern used by the xai,
// moonshot, deepseek, aliyun, and gitee drivers.
func (n NvidiaModel) CheckConnection(apiConfig *APIConfig) error {
_, err := n.ListModels(apiConfig)
return err
}
func (z *NvidiaModel) ListTasks(apiConfig *APIConfig) ([]ListTaskStatus, error) {
return nil, fmt.Errorf("%s, no such method", z.Name())
}
func (z *NvidiaModel) ShowTask(taskID string, apiConfig *APIConfig) (*TaskResponse, error) {
return nil, fmt.Errorf("%s, no such method", z.Name())
}