Files
ragflow/internal/entity/models/longcat.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

478 lines
16 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"
)
// LongCatModel implements ModelDriver for LongCat (Meituan).
//
// LongCat exposes an OpenAI-compatible chat completions endpoint at
// https://api.longcat.chat/openai/v1/chat/completions. The official
// docs (https://longcat.chat/platform/docs/APIDocs.html) only describe
// the chat-completions surface — no /models, /embeddings, /rerank,
// /audio, or /ocr endpoints are advertised. The wire shape matches the
// OpenAI convention: response/delta carry reasoning_content alongside
// content for thinking models.
//
// Documented request fields are limited to: model, messages, stream,
// max_tokens, temperature, top_p. Sending other OpenAI-style fields
// (stop, reasoning_effort, etc.) is not documented and is therefore
// omitted to avoid relying on undocumented upstream behavior.
type LongCatModel struct {
BaseURL map[string]string
URLSuffix URLSuffix
httpClient *http.Client
}
// NewLongCatModel creates a new LongCat 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 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 NewLongCatModel(baseURL map[string]string, urlSuffix URLSuffix) *LongCatModel {
transport := http.DefaultTransport.(*http.Transport).Clone()
transport.MaxIdleConns = 100
transport.MaxIdleConnsPerHost = 10
transport.IdleConnTimeout = 90 * time.Second
transport.DisableCompression = false
transport.ResponseHeaderTimeout = 60 * time.Second
return &LongCatModel{
BaseURL: baseURL,
URLSuffix: urlSuffix,
httpClient: &http.Client{
Transport: transport,
},
}
}
func (l *LongCatModel) NewInstance(baseURL map[string]string) ModelDriver {
return NewLongCatModel(baseURL, l.URLSuffix)
}
func (l *LongCatModel) Name() string {
return "longcat"
}
// 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 (l *LongCatModel) baseURLForRegion(region string) (string, error) {
base, ok := l.BaseURL[region]
if !ok || base == "" {
return "", fmt.Errorf("longcat: no base URL configured for region %q", region)
}
return base, nil
}
// ChatWithMessages sends multiple messages with roles and returns the response.
func (l *LongCatModel) 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")
}
region := "default"
if apiConfig.Region != nil && *apiConfig.Region != "" {
region = *apiConfig.Region
}
baseURL, err := l.baseURLForRegion(region)
if err != nil {
return nil, err
}
url := fmt.Sprintf("%s/%s", baseURL, l.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,
}
// Note: do NOT propagate chatModelConfig.Stream into the request body
// here. ChatWithMessages parses a single JSON response, so stream must
// always be off for this code path.
//
// Only the fields documented at
// https://longcat.chat/platform/docs/APIDocs.html are forwarded.
// Other ChatConfig fields (Stop, Effort, ...) are dropped on the
// floor because the upstream behavior is undefined.
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
}
}
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 := 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", 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")
}
// LongCat-Flash-Thinking returns the chain-of-thought in a
// `reasoning_content` field on the message (OpenAI o-series shape,
// also used by kimi-k2.6 and DeepSeek-R1). Pass it through when
// present so callers can surface reasoning to the UI. Absent or
// non-string means no reasoning was emitted — leave it empty.
reasonContent := ""
if r, ok := messageMap["reasoning_content"].(string); ok {
reasonContent = r
}
return &ChatResponse{
Answer: &content,
ReasonContent: &reasonContent,
}, nil
}
// ChatStreamlyWithSender sends messages and streams the response via the
// sender function. The LongCat SSE stream uses the same shape as the
// OpenAI o-series: "data:" lines carrying JSON events with
// delta.content for the visible answer and delta.reasoning_content for
// the chain-of-thought (LongCat-Flash-Thinking only), terminated by
// a [DONE] line.
func (l *LongCatModel) ChatStreamlyWithSender(modelName string, messages []Message, apiConfig *APIConfig, chatModelConfig *ChatConfig, sender func(*string, *string) error) error {
if sender == nil {
return fmt.Errorf("sender is required")
}
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")
}
region := "default"
if apiConfig.Region != nil && *apiConfig.Region != "" {
region = *apiConfig.Region
}
baseURL, err := l.baseURLForRegion(region)
if err != nil {
return err
}
url := fmt.Sprintf("%s/%s", baseURL, l.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 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.
if chatModelConfig.Stream != nil && !*chatModelConfig.Stream {
return fmt.Errorf("stream must be true in ChatStreamlyWithSender")
}
// Only documented fields are forwarded; see ChatWithMessages.
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
}
}
jsonData, err := json.Marshal(reqBody)
if err != nil {
return fmt.Errorf("failed to marshal request: %w", err)
}
// SSE streams are long-lived. Rely on the transport's
// ResponseHeaderTimeout to cap the connection-establishment phase
// instead of attaching a hard deadline here.
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 := 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: bump the scanner buffer from the 64KB default 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 := false
for scanner.Scan() {
line := scanner.Text()
if !strings.HasPrefix(line, "data:") {
continue
}
data := strings.TrimSpace(line[5:])
if data == "[DONE]" {
sawTerminal = true
break
}
var event map[string]interface{}
if err = json.Unmarshal([]byte(data), &event); err != nil {
// A malformed frame can mean a truncated SSE event or an
// upstream incident; either way, the caller is better
// served by a hard failure than by silent partial output.
return fmt.Errorf("longcat: invalid SSE event: %w", err)
}
// LongCat (like other OpenAI-compatible upstreams) can emit a
// terminal `{"error": ...}` frame instead of a normal choices
// chunk when something goes wrong mid-stream. Surface it
// instead of falling through to the choices-missing branch.
if apiErr, ok := event["error"]; ok {
return fmt.Errorf("longcat: upstream stream error: %v", apiErr)
}
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
}
// Reasoning chunks first, content second. When an SSE event
// carries both, callers that pipe them to a UI render the
// chain-of-thought before the answer for that token, matching
// the wire ordering LongCat-Flash-Thinking emits.
if r, ok := delta["reasoning_content"].(string); ok && r != "" {
if err := sender(nil, &r); 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("longcat: stream ended before [DONE] or finish_reason")
}
endOfStream := "[DONE]"
if err := sender(&endOfStream, nil); err != nil {
return err
}
return nil
}
// ListModels is not exposed by the LongCat platform. The official
// docs at https://longcat.chat/platform/docs/APIDocs.html only
// document /openai/v1/chat/completions and /anthropic/v1/messages;
// no /models endpoint exists. The shipped catalog lives in
// conf/models/longcat.json; this driver method does not invent a
// fake one.
func (l *LongCatModel) ListModels(apiConfig *APIConfig) ([]string, error) {
return nil, fmt.Errorf("%s, no such method", l.Name())
}
// CheckConnection is not exposed by the LongCat platform. With no
// documented /models or /health endpoint, there is no cheap way to
// verify the API key without burning a real chat completion against
// a tenant's quota. Return the documented sentinel rather than
// pretend.
func (l *LongCatModel) CheckConnection(apiConfig *APIConfig) error {
return fmt.Errorf("%s, no such method", l.Name())
}
// Embed is not exposed by the LongCat API. The /v1/embeddings endpoint
// does not exist on api.longcat.chat; this returns the documented
// sentinel.
func (l *LongCatModel) Embed(modelName *string, texts []string, apiConfig *APIConfig, embeddingConfig *EmbeddingConfig) ([]EmbeddingData, error) {
return nil, fmt.Errorf("%s, no such method", l.Name())
}
// Rerank is not exposed by the LongCat API.
func (l *LongCatModel) Rerank(modelName *string, query string, documents []string, apiConfig *APIConfig, rerankConfig *RerankConfig) (*RerankResponse, error) {
return nil, fmt.Errorf("%s, no such method", l.Name())
}
// Balance is not exposed by the LongCat API.
func (l *LongCatModel) Balance(apiConfig *APIConfig) (map[string]interface{}, error) {
return nil, fmt.Errorf("%s, no such method", l.Name())
}
// TranscribeAudio (ASR) is not exposed by the LongCat API.
func (l *LongCatModel) TranscribeAudio(modelName *string, file *string, apiConfig *APIConfig, asrConfig *ASRConfig) (*ASRResponse, error) {
return nil, fmt.Errorf("%s, no such method", l.Name())
}
func (l *LongCatModel) TranscribeAudioWithSender(modelName *string, file *string, apiConfig *APIConfig, asrConfig *ASRConfig, sender func(*string, *string) error) error {
return fmt.Errorf("%s, no such method", l.Name())
}
// AudioSpeech (TTS) is not exposed by the LongCat API.
func (l *LongCatModel) AudioSpeech(modelName *string, audioContent *string, apiConfig *APIConfig, ttsConfig *TTSConfig) (*TTSResponse, error) {
return nil, fmt.Errorf("%s, no such method", l.Name())
}
func (l *LongCatModel) AudioSpeechWithSender(modelName *string, audioContent *string, apiConfig *APIConfig, ttsConfig *TTSConfig, sender func(*string, *string) error) error {
return fmt.Errorf("%s, no such method", l.Name())
}
// OCRFile is not exposed by the LongCat API.
func (l *LongCatModel) 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 *LongCatModel) 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 *LongCatModel) ListTasks(apiConfig *APIConfig) ([]ListTaskStatus, error) {
return nil, fmt.Errorf("%s, no such method", z.Name())
}
func (z *LongCatModel) ShowTask(taskID string, apiConfig *APIConfig) (*TaskResponse, error) {
return nil, fmt.Errorf("%s, no such method", z.Name())
}