Files
ragflow/internal/entity/models/openai.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

632 lines
19 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"
"context"
"encoding/json"
"fmt"
"io"
"net/http"
"strings"
"time"
)
// OpenAIModel implements ModelDriver for OpenAI (GPT models).
// The non-streaming call timeout is the shared nonStreamCallTimeout
// constant defined alongside the xAI driver in this package.
type OpenAIModel struct {
BaseURL map[string]string
URLSuffix URLSuffix
httpClient *http.Client // Reusable HTTP client with connection pool
}
// NewOpenAIModel creates a new OpenAI model instance.
//
// We clone http.DefaultTransport so we keep Go's defaults for
// ProxyFromEnvironment, DialContext (with KeepAlive), HTTP/2,
// TLSHandshakeTimeout, and ExpectContinueTimeout, and only override
// the few connection-pool fields we care about.
//
// The Client itself has no Timeout. http.Client.Timeout would also
// cap the time spent reading the response body, which would cut off
// long-lived SSE streams in ChatStreamlyWithSender. Non-streaming
// callers wrap each request with context.WithTimeout instead.
func NewOpenAIModel(baseURL map[string]string, urlSuffix URLSuffix) *OpenAIModel {
transport := http.DefaultTransport.(*http.Transport).Clone()
transport.MaxIdleConns = 100
transport.MaxIdleConnsPerHost = 10
transport.IdleConnTimeout = 90 * time.Second
transport.DisableCompression = false
// Cap how long the client waits for the first response header.
// This protects ChatStreamlyWithSender, which has no client-wide
// timeout, against a server that opens the TCP connection and
// then never sends a response.
transport.ResponseHeaderTimeout = 60 * time.Second
return &OpenAIModel{
BaseURL: baseURL,
URLSuffix: urlSuffix,
httpClient: &http.Client{
Transport: transport,
},
}
}
func (z *OpenAIModel) NewInstance(baseURL map[string]string) ModelDriver {
return NewOpenAIModel(baseURL, z.URLSuffix)
}
func (z *OpenAIModel) Name() string {
return "openai"
}
// baseURLForRegion returns the base URL for the given region, or an
// error if no entry exists. This makes a misconfigured region fail
// fast with a clear message, instead of silently producing a relative
// URL that the HTTP transport then rejects.
func (z *OpenAIModel) baseURLForRegion(region string) (string, error) {
base, ok := z.BaseURL[region]
if !ok || base == "" {
return "", fmt.Errorf("openai: no base URL configured for region %q", region)
}
return base, nil
}
// ChatWithMessages sends multiple messages with roles and returns the response
func (z *OpenAIModel) ChatWithMessages(modelName string, messages []Message, apiConfig *APIConfig, chatModelConfig *ChatConfig) (*ChatResponse, error) {
if apiConfig == nil || apiConfig.ApiKey == nil || *apiConfig.ApiKey == "" {
return nil, fmt.Errorf("api key is required")
}
if len(messages) == 0 {
return nil, fmt.Errorf("messages is empty")
}
var region = "default"
if apiConfig.Region != nil {
region = *apiConfig.Region
}
baseURL, err := z.baseURLForRegion(region)
if err != nil {
return nil, err
}
url := fmt.Sprintf("%s/%s", baseURL, z.URLSuffix.Chat)
// Convert messages to the format expected by the 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,
}
// Note: do NOT propagate chatModelConfig.Stream into the request body
// here. ChatWithMessages parses a single JSON response, so SSE/stream
// must always be off for this code path.
if chatModelConfig != nil {
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
}
}
jsonData, err := json.Marshal(reqBody)
if err != nil {
return nil, fmt.Errorf("failed to marshal request: %w", err)
}
ctx, cancel := context.WithTimeout(context.Background(), nonStreamCallTimeout)
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 := 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")
}
// OpenAI reasoning models (o-series and similar) return reasoning text in
// the reasoning_content field. Pass it through when present.
var reasonContent string
if rc, ok := messageMap["reasoning_content"].(string); ok {
reasonContent = rc
if reasonContent != "" && reasonContent[0] == '\n' {
reasonContent = reasonContent[1:]
}
}
chatResponse := &ChatResponse{
Answer: &content,
ReasonContent: &reasonContent,
}
return chatResponse, nil
}
// ChatStreamlyWithSender sends messages and streams the response via the
// sender function. Used for streaming chat responses with no extra channel.
func (z *OpenAIModel) 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")
}
if apiConfig == nil || apiConfig.ApiKey == nil || *apiConfig.ApiKey == "" {
return fmt.Errorf("api key is required")
}
var region = "default"
if apiConfig.Region != nil && *apiConfig.Region != "" {
region = *apiConfig.Region
}
baseURL, err := z.baseURLForRegion(region)
if err != nil {
return err
}
url := fmt.Sprintf("%s/%s", baseURL, z.URLSuffix.Chat)
// Convert messages to API format (supports 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 on by default
reqBody := map[string]interface{}{
"model": modelName,
"messages": apiMessages,
"stream": true,
}
if chatModelConfig != nil {
// Refuse to run if the caller explicitly asked for stream=false.
// The body of this method only knows how to read SSE, so a non-SSE
// JSON response would be parsed as if it were a stream and produce
// no chunks. Better to fail clearly. Leave reqBody["stream"] as
// the default (true) when Stream is nil or true.
if chatModelConfig.Stream != nil && !*chatModelConfig.Stream {
return fmt.Errorf("stream must be true in ChatStreamlyWithSender")
}
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
}
}
jsonData, err := json.Marshal(reqBody)
if err != nil {
return fmt.Errorf("failed to marshal request: %w", err)
}
// Use an explicit background context here so the request is at least
// cancellable in principle. We do not attach a hard deadline because
// SSE streams are long-lived. The transport's ResponseHeaderTimeout
// caps the connection-establishment phase. Threading a real ctx
// through the ModelDriver interface is a wider change for a follow-up.
req, err := http.NewRequestWithContext(context.Background(), "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. The default bufio.Scanner buffer
// is 64KB, which can be too small for long SSE chunks. Bump it to
// 1MB so we never silently truncate a long data: line.
scanner := bufio.NewScanner(resp.Body)
scanner.Buffer(make([]byte, 64*1024), 1024*1024)
// sawTerminal flips to true when the upstream actually told us the
// stream is over (either a "[DONE]" marker or a non-empty
// finish_reason). If the body closes before either of those, we
// must not emit a synthetic "[DONE]" because that would hide a
// truncated response from the caller.
sawTerminal := false
for scanner.Scan() {
line := scanner.Text()
// 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 the stream
if data == "[DONE]" {
sawTerminal = true
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 != "" {
sawTerminal = true
break
}
}
if err := scanner.Err(); err != nil {
return fmt.Errorf("failed to scan response body: %w", err)
}
if !sawTerminal {
return fmt.Errorf("openai: stream ended before [DONE] or finish_reason")
}
// Send the [DONE] marker for OpenAI compatibility
endOfStream := "[DONE]"
if err := sender(&endOfStream, nil); err != nil {
return err
}
return nil
}
type openaiEmbeddingResponse struct {
Data []openrouterEmbeddingData `json:"data"`
Model string `json:"model"`
Object string `json:"object"`
Usage openrouterUsage `json:"usage"`
}
type openaiEmbeddingData struct {
Embedding []float64 `json:"embedding"`
Object string `json:"object"`
Index int `json:"index"`
}
type openaiUsage struct {
PromptTokens int `json:"prompt_tokens"`
TotalTokens int `json:"total_tokens"`
}
// Embed turns a list of texts into embedding vectors using the
// OpenAI /v1/embeddings endpoint (e.g. text-embedding-3-small,
// text-embedding-3-large, text-embedding-ada-002). The output has
// one vector per input, in the same order the inputs were given.
func (z *OpenAIModel) 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, err := z.baseURLForRegion(region)
if err != nil {
return nil, err
}
url := fmt.Sprintf("%s/%s", baseURL, z.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(), nonStreamCallTimeout)
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 := 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("OpenAI 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
}
// ListModels returns the list of model ids visible to the API key.
func (z *OpenAIModel) ListModels(apiConfig *APIConfig) ([]string, error) {
if apiConfig == nil || apiConfig.ApiKey == nil || *apiConfig.ApiKey == "" {
return nil, fmt.Errorf("api key is required")
}
var region = "default"
if apiConfig.Region != nil {
region = *apiConfig.Region
}
baseURL, err := z.baseURLForRegion(region)
if err != nil {
return nil, err
}
url := fmt.Sprintf("%s/%s", baseURL, z.URLSuffix.Models)
ctx, cancel := context.WithTimeout(context.Background(), nonStreamCallTimeout)
defer cancel()
req, err := http.NewRequestWithContext(ctx, "GET", url, nil)
if err != nil {
return nil, fmt.Errorf("failed to create request: %w", err)
}
// GET has no body, so Content-Type is not needed.
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)
}
data, ok := result["data"].([]interface{})
if !ok {
return nil, fmt.Errorf("invalid models list format")
}
models := make([]string, 0)
for _, model := range data {
modelMap, ok := model.(map[string]interface{})
if !ok {
continue
}
modelName, ok := modelMap["id"].(string)
if !ok {
continue
}
models = append(models, modelName)
}
return models, nil
}
// Balance is not exposed by the OpenAI API, so this returns "no such method".
func (z *OpenAIModel) Balance(apiConfig *APIConfig) (map[string]interface{}, error) {
return nil, fmt.Errorf("no such method")
}
// CheckConnection runs a lightweight ListModels call to verify the API key.
func (z *OpenAIModel) CheckConnection(apiConfig *APIConfig) error {
_, err := z.ListModels(apiConfig)
if err != nil {
return err
}
return nil
}
// Rerank calculates similarity scores between query and documents. OpenAI does
// not expose a rerank API, so this is left unimplemented.
func (z *OpenAIModel) 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 (o *OpenAIModel) TranscribeAudio(modelName *string, file *string, apiConfig *APIConfig, asrConfig *ASRConfig) (*ASRResponse, error) {
return nil, fmt.Errorf("%s, no such method", o.Name())
}
func (z *OpenAIModel) 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 (o *OpenAIModel) AudioSpeech(modelName *string, audioContent *string, apiConfig *APIConfig, ttsConfig *TTSConfig) (*TTSResponse, error) {
return nil, fmt.Errorf("%s, no such method", o.Name())
}
func (z *OpenAIModel) 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 *OpenAIModel) 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 *OpenAIModel) 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 *OpenAIModel) ListTasks(apiConfig *APIConfig) ([]ListTaskStatus, error) {
return nil, fmt.Errorf("%s, no such method", z.Name())
}
func (z *OpenAIModel) ShowTask(taskID string, apiConfig *APIConfig) (*TaskResponse, error) {
return nil, fmt.Errorf("%s, no such method", z.Name())
}