mirror of
https://github.com/infiniflow/ragflow.git
synced 2026-06-08 08:07:21 +08:00
### 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
701 lines
20 KiB
Go
701 lines
20 KiB
Go
//
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// Copyright 2026 The InfiniFlow Authors. All Rights Reserved.
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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//
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package models
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import (
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"bufio"
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"bytes"
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"context"
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"encoding/json"
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"fmt"
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"io"
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"net/http"
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"ragflow/internal/common"
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"strings"
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"time"
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)
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// VllmModel implements ModelDriver for Vllm AI
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type VllmModel struct {
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BaseURL map[string]string
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URLSuffix URLSuffix
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httpClient *http.Client // Reusable HTTP client with connection pool
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}
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// NewVllmModel creates a new Vllm AI model instance
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func NewVllmModel(baseURL map[string]string, urlSuffix URLSuffix) *VllmModel {
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return &VllmModel{
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BaseURL: baseURL,
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URLSuffix: urlSuffix,
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httpClient: &http.Client{
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Timeout: 120 * time.Second,
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Transport: &http.Transport{
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MaxIdleConns: 100,
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MaxIdleConnsPerHost: 10,
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IdleConnTimeout: 90 * time.Second,
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DisableCompression: false,
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},
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},
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}
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}
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func (z *VllmModel) NewInstance(baseURL map[string]string) ModelDriver {
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return &VllmModel{
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BaseURL: baseURL,
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URLSuffix: z.URLSuffix,
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httpClient: &http.Client{
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Timeout: 120 * time.Second,
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Transport: &http.Transport{
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MaxIdleConns: 100,
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MaxIdleConnsPerHost: 10,
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IdleConnTimeout: 90 * time.Second,
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DisableCompression: false,
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},
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},
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}
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}
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func (z *VllmModel) Name() string {
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return "vllm"
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}
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// ChatWithMessages sends multiple messages with roles and returns response
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func (z *VllmModel) ChatWithMessages(modelName string, messages []Message, apiConfig *APIConfig, chatModelConfig *ChatConfig) (*ChatResponse, error) {
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if len(messages) == 0 {
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return nil, fmt.Errorf("messages is empty")
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}
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var region = "default"
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if apiConfig != nil && apiConfig.Region != nil && *apiConfig.Region != "" {
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region = *apiConfig.Region
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}
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url := fmt.Sprintf("%s/%s", z.BaseURL[region], z.URLSuffix.Chat)
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// For qwen/glm models, use async chat endpoint
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modelType := strings.Split(modelName, "-")[0]
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if modelType == "qwen" || modelType == "glm" {
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url = fmt.Sprintf("%s/%s", z.BaseURL[region], z.URLSuffix.AsyncChat)
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}
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// Convert messages to API format
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apiMessages := make([]map[string]interface{}, len(messages))
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for i, msg := range messages {
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apiMessages[i] = map[string]interface{}{
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"role": msg.Role,
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"content": msg.Content,
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}
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}
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// Build request body
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reqBody := map[string]interface{}{
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"model": modelName,
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"messages": apiMessages,
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"stream": false,
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"temperature": 1,
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}
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if chatModelConfig != nil {
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if chatModelConfig.Stream != nil {
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reqBody["stream"] = *chatModelConfig.Stream
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}
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if chatModelConfig.MaxTokens != nil {
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reqBody["max_tokens"] = *chatModelConfig.MaxTokens
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}
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if chatModelConfig.Temperature != nil {
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reqBody["temperature"] = *chatModelConfig.Temperature
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}
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if chatModelConfig.TopP != nil {
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reqBody["top_p"] = *chatModelConfig.TopP
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}
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if chatModelConfig.Stop != nil {
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reqBody["stop"] = *chatModelConfig.Stop
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}
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if chatModelConfig.Thinking != nil {
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if *chatModelConfig.Thinking {
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reqBody["thinking"] = map[string]interface{}{
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"type": "enabled",
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}
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} else {
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reqBody["thinking"] = map[string]interface{}{
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"type": "disabled",
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}
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}
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}
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}
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jsonData, err := json.Marshal(reqBody)
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if err != nil {
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return nil, fmt.Errorf("failed to marshal request: %w", err)
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}
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req, err := http.NewRequest("POST", url, bytes.NewBuffer(jsonData))
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if err != nil {
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return nil, fmt.Errorf("failed to create request: %w", err)
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}
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req.Header.Set("Content-Type", "application/json")
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req.Header.Set("Authorization", fmt.Sprintf("Bearer %s", *apiConfig.ApiKey))
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resp, err := z.httpClient.Do(req)
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if err != nil {
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return nil, fmt.Errorf("failed to send request: %w", err)
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}
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defer resp.Body.Close()
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body, err := io.ReadAll(resp.Body)
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if err != nil {
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return nil, fmt.Errorf("failed to read response: %w", err)
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}
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if resp.StatusCode != http.StatusOK {
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return nil, fmt.Errorf("API request failed with status %d: %s", resp.StatusCode, string(body))
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}
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// Parse response
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var result map[string]interface{}
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if err = json.Unmarshal(body, &result); err != nil {
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return nil, fmt.Errorf("failed to parse response: %w", err)
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}
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choices, ok := result["choices"].([]interface{})
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if !ok || len(choices) == 0 {
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return nil, fmt.Errorf("no choices in response")
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}
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firstChoice, ok := choices[0].(map[string]interface{})
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if !ok {
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return nil, fmt.Errorf("invalid choice format")
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}
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messageMap, ok := firstChoice["message"].(map[string]interface{})
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if !ok {
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return nil, fmt.Errorf("invalid message format")
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}
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content, ok := messageMap["content"].(string)
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if !ok {
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return nil, fmt.Errorf("invalid content format")
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}
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var reasonContent string
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if chatModelConfig != nil && chatModelConfig.Thinking != nil && *chatModelConfig.Thinking {
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reasonContent, ok = messageMap["reasoning_content"].(string)
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if !ok {
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return nil, fmt.Errorf("invalid content format")
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}
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if reasonContent != "" && reasonContent[0] == '\n' {
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reasonContent = reasonContent[1:]
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}
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}
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chatResponse := &ChatResponse{
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Answer: &content,
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ReasonContent: &reasonContent,
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}
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return chatResponse, nil
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}
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// ChatStreamlyWithSender sends messages and streams response via sender function (best performance, no channel)
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func (z *VllmModel) ChatStreamlyWithSender(modelName string, messages []Message, apiConfig *APIConfig, modelConfig *ChatConfig, sender func(*string, *string) error) error {
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if len(messages) == 0 {
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return fmt.Errorf("messages is empty")
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}
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var region = "default"
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if apiConfig != nil && apiConfig.Region != nil && *apiConfig.Region != "" {
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region = *apiConfig.Region
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}
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url := fmt.Sprintf("%s/%s", z.BaseURL[region], z.URLSuffix.Chat)
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modelType := strings.Split(modelName, "-")[0]
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if modelType == "qwen" || modelType == "glm" {
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url = fmt.Sprintf("%s/%s", z.BaseURL[region], z.URLSuffix.AsyncChat)
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}
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// Convert messages to API format (supporting multimodal content)
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apiMessages := make([]map[string]interface{}, len(messages))
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for i, msg := range messages {
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apiMessages[i] = map[string]interface{}{
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"role": msg.Role,
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"content": msg.Content,
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}
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}
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// Build request body with streaming enabled
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reqBody := map[string]interface{}{
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"model": modelName,
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"messages": apiMessages,
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"stream": true,
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}
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if modelConfig.Stream != nil {
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reqBody["stream"] = *modelConfig.Stream
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}
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if modelConfig.MaxTokens != nil {
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reqBody["max_tokens"] = *modelConfig.MaxTokens
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}
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if modelConfig.Temperature != nil {
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reqBody["temperature"] = *modelConfig.Temperature
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}
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if modelConfig.DoSample != nil {
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reqBody["do_sample"] = *modelConfig.DoSample
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}
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if modelConfig.TopP != nil {
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reqBody["top_p"] = *modelConfig.TopP
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}
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if modelConfig.Stop != nil {
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reqBody["stop"] = *modelConfig.Stop
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}
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if modelConfig.Thinking != nil {
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if *modelConfig.Thinking {
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reqBody["thinking"] = map[string]interface{}{
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"type": "enabled",
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}
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} else {
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reqBody["thinking"] = map[string]interface{}{
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"type": "disabled",
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}
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}
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}
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jsonData, err := json.Marshal(reqBody)
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if err != nil {
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return fmt.Errorf("failed to marshal request: %w", err)
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}
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req, err := http.NewRequest("POST", url, bytes.NewBuffer(jsonData))
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if err != nil {
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return fmt.Errorf("failed to create request: %w", err)
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}
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req.Header.Set("Content-Type", "application/json")
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req.Header.Set("Authorization", fmt.Sprintf("Bearer %s", *apiConfig.ApiKey))
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resp, err := z.httpClient.Do(req)
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if err != nil {
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return fmt.Errorf("failed to send request: %w", err)
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}
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defer resp.Body.Close()
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if resp.StatusCode != http.StatusOK {
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body, _ := io.ReadAll(resp.Body)
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return fmt.Errorf("API request failed with status %d: %s", resp.StatusCode, string(body))
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}
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// SSE parsing: read line by line
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scanner := bufio.NewScanner(resp.Body)
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for scanner.Scan() {
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line := scanner.Text()
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common.Info(line)
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// SSE data line starts with "data:"
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if !strings.HasPrefix(line, "data:") {
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continue
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}
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// Extract JSON after "data:"
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data := strings.TrimSpace(line[5:])
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// [DONE] marks the end of stream
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if data == "[DONE]" {
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break
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}
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// Parse the JSON event
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var event map[string]interface{}
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if err = json.Unmarshal([]byte(data), &event); err != nil {
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continue
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}
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choices, ok := event["choices"].([]interface{})
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if !ok || len(choices) == 0 {
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continue
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}
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firstChoice, ok := choices[0].(map[string]interface{})
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if !ok {
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continue
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}
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delta, ok := firstChoice["delta"].(map[string]interface{})
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if !ok {
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continue
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}
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reasoningContent, ok := delta["reasoning_content"].(string)
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if ok && reasoningContent != "" {
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if err := sender(nil, &reasoningContent); err != nil {
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return err
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}
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}
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content, ok := delta["content"].(string)
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if ok && content != "" {
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if err := sender(&content, nil); err != nil {
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return err
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}
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}
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finishReason, ok := firstChoice["finish_reason"].(string)
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if ok && finishReason != "" {
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break
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}
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}
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// Send [DONE] marker for OpenAI compatibility
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endOfStream := "[DONE]"
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if err = sender(&endOfStream, nil); err != nil {
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return err
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}
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return scanner.Err()
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}
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// Encode encodes a list of texts into embeddings
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type vllmEmbeddingResponse struct {
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Data []struct {
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Index int `json:"index"`
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Embedding []float64 `json:"embedding"`
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} `json:"data"`
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}
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// Embed embeds a list of texts into embeddings
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func (z *VllmModel) Embed(modelName *string, texts []string, apiConfig *APIConfig, embeddingConfig *EmbeddingConfig) ([]EmbeddingData, error) {
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if len(texts) == 0 {
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return []EmbeddingData{}, nil
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}
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if modelName == nil || *modelName == "" {
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return nil, fmt.Errorf("model name is required")
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}
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region := "default"
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if apiConfig != nil && apiConfig.Region != nil && *apiConfig.Region != "" {
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region = *apiConfig.Region
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}
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baseURL := z.BaseURL[region]
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if baseURL == "" {
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baseURL = z.BaseURL["default"]
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}
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if baseURL == "" {
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return nil, fmt.Errorf("missing base URL: please configure the local access address for vLLM (e.g., http://127.0.0.1:8000/v1)")
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}
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url := fmt.Sprintf("%s/%s", strings.TrimSuffix(baseURL, "/"), z.URLSuffix.Embedding)
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reqBody := map[string]interface{}{
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"model": *modelName,
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"input": texts,
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}
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if embeddingConfig != nil && embeddingConfig.Dimension > 0 {
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reqBody["dimensions"] = embeddingConfig.Dimension
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}
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jsonData, err := json.Marshal(reqBody)
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if err != nil {
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return nil, fmt.Errorf("failed to marshal request: %w", err)
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}
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ctx, cancel := context.WithTimeout(context.Background(), 30*time.Second)
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defer cancel()
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req, err := http.NewRequestWithContext(ctx, "POST", url, bytes.NewBuffer(jsonData))
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if err != nil {
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return nil, fmt.Errorf("failed to create request: %w", err)
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}
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req.Header.Set("Content-Type", "application/json")
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if apiConfig != nil && apiConfig.ApiKey != nil && *apiConfig.ApiKey != "" {
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req.Header.Set("Authorization", fmt.Sprintf("Bearer %s", *apiConfig.ApiKey))
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}
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resp, err := z.httpClient.Do(req)
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if err != nil {
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return nil, fmt.Errorf("failed to send request: %w", err)
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}
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defer resp.Body.Close()
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body, err := io.ReadAll(resp.Body)
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if err != nil {
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return nil, fmt.Errorf("failed to read response: %w", err)
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}
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if resp.StatusCode != http.StatusOK {
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return nil, fmt.Errorf("vLLM embeddings API error: %s, body: %s", resp.Status, string(body))
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}
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var parsed vllmEmbeddingResponse
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if err = json.Unmarshal(body, &parsed); err != nil {
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return nil, fmt.Errorf("failed to parse response: %w", err)
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}
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var embeddings []EmbeddingData
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for _, dataElem := range parsed.Data {
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var embeddingData EmbeddingData
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embeddingData.Embedding = dataElem.Embedding
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embeddingData.Index = dataElem.Index
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embeddings = append(embeddings, embeddingData)
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}
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return embeddings, nil
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}
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func (z *VllmModel) ListModels(apiConfig *APIConfig) ([]string, error) {
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var region = "default"
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if apiConfig != nil && apiConfig.Region != nil && *apiConfig.Region != "" {
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region = *apiConfig.Region
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}
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baseURL := z.BaseURL[region]
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if baseURL == "" {
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baseURL = z.BaseURL["default"]
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}
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if baseURL == "" {
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return nil, fmt.Errorf("missing base URL: please configure the local access address for vLLM (e.g., http://127.0.0.1:8000/v1)")
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}
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url := fmt.Sprintf("%s/%s", baseURL, z.URLSuffix.Models)
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reqBody := map[string]interface{}{}
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jsonData, err := json.Marshal(reqBody)
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if err != nil {
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return nil, fmt.Errorf("failed to marshal request: %w", err)
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}
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req, err := http.NewRequest("GET", url, bytes.NewBuffer(jsonData))
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if err != nil {
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return nil, fmt.Errorf("failed to create request: %w", err)
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}
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req.Header.Set("Content-Type", "application/json")
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// vLLM is a local provider and the API key is optional. Only set
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// the Authorization header when a non-empty key was supplied. This
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// also avoids a nil-pointer dereference on apiConfig or ApiKey.
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if apiConfig != nil && apiConfig.ApiKey != nil && *apiConfig.ApiKey != "" {
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req.Header.Set("Authorization", fmt.Sprintf("Bearer %s", *apiConfig.ApiKey))
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}
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|
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resp, err := z.httpClient.Do(req)
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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)
|
|
}
|
|
|
|
// convert result["data"] to []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 (z *VllmModel) Balance(apiConfig *APIConfig) (map[string]interface{}, error) {
|
|
return nil, fmt.Errorf("no such method")
|
|
}
|
|
|
|
// CheckConnection verifies that the configured vLLM base URL is reachable
|
|
func (z *VllmModel) CheckConnection(apiConfig *APIConfig) error {
|
|
_, err := z.ListModels(apiConfig)
|
|
return err
|
|
}
|
|
|
|
// vllmRerankRequest mirrors vLLM's Jina/Cohere-compatible /v1/rerank
|
|
// payload. Unlike NVIDIA NIM (which wraps each passage as {text: "..."}),
|
|
// vLLM accepts documents as a flat []string.
|
|
type vllmRerankRequest struct {
|
|
Model string `json:"model"`
|
|
Query string `json:"query"`
|
|
Documents []string `json:"documents"`
|
|
TopN int `json:"top_n"`
|
|
}
|
|
|
|
// vllmRerankResponse maps the Jina-style results array. The `document`
|
|
// field is intentionally ignored — callers reconstruct text from the
|
|
// original input via Index.
|
|
type vllmRerankResponse struct {
|
|
Results []struct {
|
|
Index int `json:"index"`
|
|
RelevanceScore float64 `json:"relevance_score"`
|
|
} `json:"results"`
|
|
}
|
|
|
|
// Rerank scores documents against the query using a vLLM rerank model
|
|
// served at /v1/rerank (stable since vLLM v0.7). Mirrors the contract
|
|
// of NvidiaModel.Rerank: defaults top_n to len(documents) so callers
|
|
// get a score per input, shrinks to RerankConfig.TopN only when set
|
|
// and smaller. Returned RerankResult entries are in the API's ranking
|
|
// order; callers that need original-input order sort by Index. The
|
|
// Authorization header is sent only when APIConfig.ApiKey is non-empty,
|
|
// matching the existing Embed/ListModels behaviour for this local
|
|
// driver.
|
|
func (z *VllmModel) Rerank(modelName *string, query string, documents []string, apiConfig *APIConfig, rerankConfig *RerankConfig) (*RerankResponse, error) {
|
|
if len(documents) == 0 {
|
|
return &RerankResponse{}, 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 := z.BaseURL[region]
|
|
if baseURL == "" {
|
|
baseURL = z.BaseURL["default"]
|
|
}
|
|
if baseURL == "" {
|
|
return nil, fmt.Errorf("missing base URL: please configure the local access address for vLLM (e.g., http://127.0.0.1:8000/v1)")
|
|
}
|
|
|
|
url := fmt.Sprintf("%s/%s", strings.TrimSuffix(baseURL, "/"), z.URLSuffix.Rerank)
|
|
|
|
topN := len(documents)
|
|
if rerankConfig != nil && rerankConfig.TopN > 0 && rerankConfig.TopN < topN {
|
|
topN = rerankConfig.TopN
|
|
}
|
|
|
|
reqBody := vllmRerankRequest{
|
|
Model: *modelName,
|
|
Query: query,
|
|
Documents: documents,
|
|
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")
|
|
if apiConfig != nil && apiConfig.ApiKey != nil && *apiConfig.ApiKey != "" {
|
|
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("vLLM rerank API error: %s, body: %s", resp.Status, string(body))
|
|
}
|
|
|
|
var parsed vllmRerankResponse
|
|
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.Results))}
|
|
for _, r := range parsed.Results {
|
|
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.RelevanceScore,
|
|
})
|
|
}
|
|
|
|
return &rerankResponse, nil
|
|
}
|
|
|
|
// TranscribeAudio transcribe audio
|
|
func (o *VllmModel) TranscribeAudio(modelName *string, file *string, apiConfig *APIConfig, asrConfig *ASRConfig) (*ASRResponse, error) {
|
|
return nil, fmt.Errorf("%s, no such method", o.Name())
|
|
}
|
|
|
|
func (z *VllmModel) 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 *VllmModel) AudioSpeech(modelName *string, audioContent *string, apiConfig *APIConfig, ttsConfig *TTSConfig) (*TTSResponse, error) {
|
|
return nil, fmt.Errorf("%s, no such method", o.Name())
|
|
}
|
|
|
|
func (z *VllmModel) 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 *VllmModel) 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 *VllmModel) 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 *VllmModel) ListTasks(apiConfig *APIConfig) ([]ListTaskStatus, error) {
|
|
return nil, fmt.Errorf("%s, no such method", z.Name())
|
|
}
|
|
|
|
func (z *VllmModel) ShowTask(taskID string, apiConfig *APIConfig) (*TaskResponse, error) {
|
|
return nil, fmt.Errorf("%s, no such method", z.Name())
|
|
}
|