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ragflow/internal/entity/models/vllm.go

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//
// 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 (
"bytes"
Go: implement Encode (embeddings) in vLLM driver (#14688) ### What problem does this PR solve? The vLLM Go driver shipped with a stub \`Encode\` method that returned \`not implemented\`, even though vLLM is one of the most common production-grade self-hosted inference servers and exposes an OpenAI-compatible embeddings endpoint at \`/v1/embeddings\`. Users who self-host \`BAAI/bge-m3\`, \`Qwen3-Embedding-*\`, \`NV-Embed-v2\`, or similar models on vLLM could not run an embedding call through the Go layer. The existing \`ListModels\` already discovers the loaded models, but the embedding path failed because \`Encode\` was a stub. ### What this PR includes - \`conf/models/vllm.json\`: add \`\"embedding\": \"embeddings\"\` under \`url_suffix\` so the driver can build the URL from config. - \`internal/entity/models/vllm.go\`: replace the \`Encode\` stub with a real implementation. Adds a small local response type that matches the OpenAI-compatible shape. No factory change. No interface change. ### How the driver works - Validate the model name. The API key is optional for self-hosted vLLM, so the Authorization header is only set when both \`apiConfig\` and \`ApiKey\` are non-nil and non-empty, the same pattern the recently merged CheckConnection PR (#14614) uses. - Resolve the region with a default fallback. Return a clear "missing base URL" error when the user has not configured the local access address yet. - Use a per-call \`context.WithTimeout(30s)\` and \`http.NewRequestWithContext\`, the same pattern the merged Aliyun Encode (#14647) and in-flight Ollama Encode (#14664) use. - Send \`{model, input: [texts]}\` in one request. - Parse \`data[*].embedding\` and copy each slice into a \`[][]float64\` indexed by \`data[*].index\`, so the output order matches the input order. - Handle both \`float64\` and \`float32\` element types. - Empty input returns \`[][]float64{}\` with no HTTP call. - Length mismatch between input and result, out-of-range index, and any missing slot all return clear errors instead of silent zero vectors. ### Type of change - [x] New Feature (non-breaking change which adds functionality) ### How was this tested? - \`go build ./internal/entity/models/...\` in a clean go 1.25 image returns exit 0. - The full method set on \`VllmModel\` still matches the \`ModelDriver\` interface. - Pattern parity with the merged Aliyun Encode (#14647), the in-flight Ollama Encode (#14664), and the existing SiliconFlow Encode. Closes #14687
2026-05-11 06:09:17 +02:00
"context"
"encoding/json"
"fmt"
"io"
"net/http"
"ragflow/internal/common"
"strings"
)
// VllmModel implements ModelDriver for Vllm AI
type VllmModel struct {
baseModel BaseModel
}
// NewVllmModel creates a new Vllm AI model instance
func NewVllmModel(baseURL map[string]string, urlSuffix URLSuffix) *VllmModel {
return &VllmModel{
baseModel: BaseModel{
BaseURL: baseURL,
URLSuffix: urlSuffix,
AllowEmptyAPIKey: true,
httpClient: NewDriverHTTPClient(),
},
}
}
func (v *VllmModel) NewInstance(baseURL map[string]string) ModelDriver {
return NewVllmModel(baseURL, v.baseModel.URLSuffix)
}
func (v *VllmModel) Name() string {
return "vllm"
}
// ChatWithMessages sends multiple messages with roles and returns response
func (v *VllmModel) ChatWithMessages(modelName string, messages []Message, apiConfig *APIConfig, chatModelConfig *ChatConfig) (*ChatResponse, error) {
if err := v.baseModel.APIConfigCheck(apiConfig); err != nil {
return nil, err
}
if len(messages) == 0 {
return nil, fmt.Errorf("messages is empty")
}
resolvedBaseURL, err := v.baseModel.GetBaseURL(apiConfig)
if err != nil {
return nil, err
}
url := fmt.Sprintf("%s/%s", resolvedBaseURL, v.baseModel.URLSuffix.Chat)
// For qwen/glm models, use async chat endpoint
modelType := strings.Split(modelName, "-")[0]
if modelType == "qwen" || modelType == "glm" {
url = fmt.Sprintf("%s/%s", resolvedBaseURL, v.baseModel.URLSuffix.AsyncChat)
}
// Convert messages to API format
apiMessages := make([]map[string]interface{}, len(messages))
for i, msg := range messages {
apiMessages[i] = map[string]interface{}{
"role": msg.Role,
"content": msg.Content,
}
}
// Build request body
reqBody := map[string]interface{}{
"model": modelName,
Go: implement provider: Vllm (#14532) ### What problem does this PR solve? Implement the vLLM model provider for RAGFlow to fully support local and self-hosted open-source models (e.g., Qwen, GLM, Llama) via the vLLM framework, and fix several critical bugs related to model instance management and API requests. **Key changes and fixes:** 1. **Added Standard vLLM Provider (`vllm.go`, `vllm.json`):** - Implemented `VllmModel` driver strictly adhering to the OpenAI API specification. - Removed hardcoded and dangerous routing logic (e.g., forcing `AsyncChat` for Qwen/GLM prefixes), ensuring standard `/v1/chat/completions` compatibility. - Refactored `ListModels` to use safe JSON parsing (resolving nil pointer panics) and standard `GET` requests without bodies. - Added `APIConfig.Region` fallback logic to prevent empty `base_url` fetching when checking models. 2. **Fixed `ChatToModelStreamWithSender` Bug (`model_service.go`):** - Resolved the `model is disabled` error when streaming chat with local database-saved models. - Added the missing `if modelInfo.Status == "active"` block to correctly invoke `NewInstance` and inject the dynamic `base_url` into the provider driver before starting the SSE stream. 3. **Fixed `ListSupportedModels` Bug (`model_service.go`):** - Added dynamic `NewInstance` injection for `base_url`. Previously, the list models function used the static JSON config without injecting user-configured dynamic URLs from the database, resulting in an `unsupported protocol scheme ""` error. ### Type of change - [x] Bug Fix (non-breaking change which fixes an issue) - [x] New Feature (non-breaking change which adds functionality)
2026-04-30 16:30:14 +08:00
"messages": apiMessages,
"stream": false,
"temperature": 1,
}
if chatModelConfig != nil {
if chatModelConfig.Stream != nil {
reqBody["stream"] = *chatModelConfig.Stream
}
if chatModelConfig.MaxTokens != nil {
reqBody["max_tokens"] = *chatModelConfig.MaxTokens
}
if chatModelConfig.Temperature != nil {
reqBody["temperature"] = *chatModelConfig.Temperature
}
if chatModelConfig.TopP != nil {
reqBody["top_p"] = *chatModelConfig.TopP
}
if chatModelConfig.Stop != nil {
reqBody["stop"] = *chatModelConfig.Stop
}
if chatModelConfig.Thinking != nil {
if *chatModelConfig.Thinking {
reqBody["thinking"] = map[string]interface{}{
"type": "enabled",
}
} else {
reqBody["thinking"] = map[string]interface{}{
"type": "disabled",
}
}
}
}
jsonData, err := json.Marshal(reqBody)
if err != nil {
return nil, fmt.Errorf("failed to marshal request: %w", err)
}
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")
if auth := BearerAuth(apiConfig); auth != "" {
req.Header.Set("Authorization", auth)
}
resp, err := v.baseModel.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")
}
var reasonContent string
if chatModelConfig != nil && chatModelConfig.Thinking != nil && *chatModelConfig.Thinking {
reasonContent, ok = messageMap["reasoning_content"].(string)
if !ok {
return nil, fmt.Errorf("invalid content format")
}
if reasonContent != "" && reasonContent[0] == '\n' {
reasonContent = reasonContent[1:]
}
}
chatResponse := &ChatResponse{
Answer: &content,
ReasonContent: &reasonContent,
}
return chatResponse, nil
}
// ChatStreamlyWithSender sends messages and streams response via sender function (best performance, no channel)
func (v *VllmModel) ChatStreamlyWithSender(modelName string, messages []Message, apiConfig *APIConfig, modelConfig *ChatConfig, sender func(*string, *string) error) error {
if err := v.baseModel.APIConfigCheck(apiConfig); err != nil {
return err
}
if len(messages) == 0 {
return fmt.Errorf("messages is empty")
}
resolvedBaseURL, err := v.baseModel.GetBaseURL(apiConfig)
if err != nil {
return err
Go: implement provider: Vllm (#14532) ### What problem does this PR solve? Implement the vLLM model provider for RAGFlow to fully support local and self-hosted open-source models (e.g., Qwen, GLM, Llama) via the vLLM framework, and fix several critical bugs related to model instance management and API requests. **Key changes and fixes:** 1. **Added Standard vLLM Provider (`vllm.go`, `vllm.json`):** - Implemented `VllmModel` driver strictly adhering to the OpenAI API specification. - Removed hardcoded and dangerous routing logic (e.g., forcing `AsyncChat` for Qwen/GLM prefixes), ensuring standard `/v1/chat/completions` compatibility. - Refactored `ListModels` to use safe JSON parsing (resolving nil pointer panics) and standard `GET` requests without bodies. - Added `APIConfig.Region` fallback logic to prevent empty `base_url` fetching when checking models. 2. **Fixed `ChatToModelStreamWithSender` Bug (`model_service.go`):** - Resolved the `model is disabled` error when streaming chat with local database-saved models. - Added the missing `if modelInfo.Status == "active"` block to correctly invoke `NewInstance` and inject the dynamic `base_url` into the provider driver before starting the SSE stream. 3. **Fixed `ListSupportedModels` Bug (`model_service.go`):** - Added dynamic `NewInstance` injection for `base_url`. Previously, the list models function used the static JSON config without injecting user-configured dynamic URLs from the database, resulting in an `unsupported protocol scheme ""` error. ### Type of change - [x] Bug Fix (non-breaking change which fixes an issue) - [x] New Feature (non-breaking change which adds functionality)
2026-04-30 16:30:14 +08:00
}
url := fmt.Sprintf("%s/%s", resolvedBaseURL, v.baseModel.URLSuffix.Chat)
modelType := strings.Split(modelName, "-")[0]
Go: implement provider: Vllm (#14532) ### What problem does this PR solve? Implement the vLLM model provider for RAGFlow to fully support local and self-hosted open-source models (e.g., Qwen, GLM, Llama) via the vLLM framework, and fix several critical bugs related to model instance management and API requests. **Key changes and fixes:** 1. **Added Standard vLLM Provider (`vllm.go`, `vllm.json`):** - Implemented `VllmModel` driver strictly adhering to the OpenAI API specification. - Removed hardcoded and dangerous routing logic (e.g., forcing `AsyncChat` for Qwen/GLM prefixes), ensuring standard `/v1/chat/completions` compatibility. - Refactored `ListModels` to use safe JSON parsing (resolving nil pointer panics) and standard `GET` requests without bodies. - Added `APIConfig.Region` fallback logic to prevent empty `base_url` fetching when checking models. 2. **Fixed `ChatToModelStreamWithSender` Bug (`model_service.go`):** - Resolved the `model is disabled` error when streaming chat with local database-saved models. - Added the missing `if modelInfo.Status == "active"` block to correctly invoke `NewInstance` and inject the dynamic `base_url` into the provider driver before starting the SSE stream. 3. **Fixed `ListSupportedModels` Bug (`model_service.go`):** - Added dynamic `NewInstance` injection for `base_url`. Previously, the list models function used the static JSON config without injecting user-configured dynamic URLs from the database, resulting in an `unsupported protocol scheme ""` error. ### Type of change - [x] Bug Fix (non-breaking change which fixes an issue) - [x] New Feature (non-breaking change which adds functionality)
2026-04-30 16:30:14 +08:00
if modelType == "qwen" || modelType == "glm" {
url = fmt.Sprintf("%s/%s", resolvedBaseURL, v.baseModel.URLSuffix.AsyncChat)
Go: implement provider: Vllm (#14532) ### What problem does this PR solve? Implement the vLLM model provider for RAGFlow to fully support local and self-hosted open-source models (e.g., Qwen, GLM, Llama) via the vLLM framework, and fix several critical bugs related to model instance management and API requests. **Key changes and fixes:** 1. **Added Standard vLLM Provider (`vllm.go`, `vllm.json`):** - Implemented `VllmModel` driver strictly adhering to the OpenAI API specification. - Removed hardcoded and dangerous routing logic (e.g., forcing `AsyncChat` for Qwen/GLM prefixes), ensuring standard `/v1/chat/completions` compatibility. - Refactored `ListModels` to use safe JSON parsing (resolving nil pointer panics) and standard `GET` requests without bodies. - Added `APIConfig.Region` fallback logic to prevent empty `base_url` fetching when checking models. 2. **Fixed `ChatToModelStreamWithSender` Bug (`model_service.go`):** - Resolved the `model is disabled` error when streaming chat with local database-saved models. - Added the missing `if modelInfo.Status == "active"` block to correctly invoke `NewInstance` and inject the dynamic `base_url` into the provider driver before starting the SSE stream. 3. **Fixed `ListSupportedModels` Bug (`model_service.go`):** - Added dynamic `NewInstance` injection for `base_url`. Previously, the list models function used the static JSON config without injecting user-configured dynamic URLs from the database, resulting in an `unsupported protocol scheme ""` error. ### Type of change - [x] Bug Fix (non-breaking change which fixes an issue) - [x] New Feature (non-breaking change which adds functionality)
2026-04-30 16:30:14 +08:00
}
// Convert messages to API format (supporting multimodal content)
apiMessages := make([]map[string]interface{}, len(messages))
for i, msg := range messages {
apiMessages[i] = map[string]interface{}{
"role": msg.Role,
"content": msg.Content,
}
}
Go: implement provider: Vllm (#14532) ### What problem does this PR solve? Implement the vLLM model provider for RAGFlow to fully support local and self-hosted open-source models (e.g., Qwen, GLM, Llama) via the vLLM framework, and fix several critical bugs related to model instance management and API requests. **Key changes and fixes:** 1. **Added Standard vLLM Provider (`vllm.go`, `vllm.json`):** - Implemented `VllmModel` driver strictly adhering to the OpenAI API specification. - Removed hardcoded and dangerous routing logic (e.g., forcing `AsyncChat` for Qwen/GLM prefixes), ensuring standard `/v1/chat/completions` compatibility. - Refactored `ListModels` to use safe JSON parsing (resolving nil pointer panics) and standard `GET` requests without bodies. - Added `APIConfig.Region` fallback logic to prevent empty `base_url` fetching when checking models. 2. **Fixed `ChatToModelStreamWithSender` Bug (`model_service.go`):** - Resolved the `model is disabled` error when streaming chat with local database-saved models. - Added the missing `if modelInfo.Status == "active"` block to correctly invoke `NewInstance` and inject the dynamic `base_url` into the provider driver before starting the SSE stream. 3. **Fixed `ListSupportedModels` Bug (`model_service.go`):** - Added dynamic `NewInstance` injection for `base_url`. Previously, the list models function used the static JSON config without injecting user-configured dynamic URLs from the database, resulting in an `unsupported protocol scheme ""` error. ### Type of change - [x] Bug Fix (non-breaking change which fixes an issue) - [x] New Feature (non-breaking change which adds functionality)
2026-04-30 16:30:14 +08:00
// Build request body with streaming enabled
reqBody := map[string]interface{}{
"model": modelName,
"messages": apiMessages,
"stream": true,
Go: implement provider: Vllm (#14532) ### What problem does this PR solve? Implement the vLLM model provider for RAGFlow to fully support local and self-hosted open-source models (e.g., Qwen, GLM, Llama) via the vLLM framework, and fix several critical bugs related to model instance management and API requests. **Key changes and fixes:** 1. **Added Standard vLLM Provider (`vllm.go`, `vllm.json`):** - Implemented `VllmModel` driver strictly adhering to the OpenAI API specification. - Removed hardcoded and dangerous routing logic (e.g., forcing `AsyncChat` for Qwen/GLM prefixes), ensuring standard `/v1/chat/completions` compatibility. - Refactored `ListModels` to use safe JSON parsing (resolving nil pointer panics) and standard `GET` requests without bodies. - Added `APIConfig.Region` fallback logic to prevent empty `base_url` fetching when checking models. 2. **Fixed `ChatToModelStreamWithSender` Bug (`model_service.go`):** - Resolved the `model is disabled` error when streaming chat with local database-saved models. - Added the missing `if modelInfo.Status == "active"` block to correctly invoke `NewInstance` and inject the dynamic `base_url` into the provider driver before starting the SSE stream. 3. **Fixed `ListSupportedModels` Bug (`model_service.go`):** - Added dynamic `NewInstance` injection for `base_url`. Previously, the list models function used the static JSON config without injecting user-configured dynamic URLs from the database, resulting in an `unsupported protocol scheme ""` error. ### Type of change - [x] Bug Fix (non-breaking change which fixes an issue) - [x] New Feature (non-breaking change which adds functionality)
2026-04-30 16:30:14 +08:00
}
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)
}
ctx, cancel := context.WithTimeout(context.Background(), streamCallTimeout)
defer cancel()
req, err := http.NewRequestWithContext(ctx, "POST", url, bytes.NewBuffer(jsonData))
Go: implement provider: Vllm (#14532) ### What problem does this PR solve? Implement the vLLM model provider for RAGFlow to fully support local and self-hosted open-source models (e.g., Qwen, GLM, Llama) via the vLLM framework, and fix several critical bugs related to model instance management and API requests. **Key changes and fixes:** 1. **Added Standard vLLM Provider (`vllm.go`, `vllm.json`):** - Implemented `VllmModel` driver strictly adhering to the OpenAI API specification. - Removed hardcoded and dangerous routing logic (e.g., forcing `AsyncChat` for Qwen/GLM prefixes), ensuring standard `/v1/chat/completions` compatibility. - Refactored `ListModels` to use safe JSON parsing (resolving nil pointer panics) and standard `GET` requests without bodies. - Added `APIConfig.Region` fallback logic to prevent empty `base_url` fetching when checking models. 2. **Fixed `ChatToModelStreamWithSender` Bug (`model_service.go`):** - Resolved the `model is disabled` error when streaming chat with local database-saved models. - Added the missing `if modelInfo.Status == "active"` block to correctly invoke `NewInstance` and inject the dynamic `base_url` into the provider driver before starting the SSE stream. 3. **Fixed `ListSupportedModels` Bug (`model_service.go`):** - Added dynamic `NewInstance` injection for `base_url`. Previously, the list models function used the static JSON config without injecting user-configured dynamic URLs from the database, resulting in an `unsupported protocol scheme ""` error. ### Type of change - [x] Bug Fix (non-breaking change which fixes an issue) - [x] New Feature (non-breaking change which adds functionality)
2026-04-30 16:30:14 +08:00
if err != nil {
return fmt.Errorf("failed to create request: %w", err)
}
req.Header.Set("Content-Type", "application/json")
if auth := BearerAuth(apiConfig); auth != "" {
req.Header.Set("Authorization", auth)
}
Go: implement provider: Vllm (#14532) ### What problem does this PR solve? Implement the vLLM model provider for RAGFlow to fully support local and self-hosted open-source models (e.g., Qwen, GLM, Llama) via the vLLM framework, and fix several critical bugs related to model instance management and API requests. **Key changes and fixes:** 1. **Added Standard vLLM Provider (`vllm.go`, `vllm.json`):** - Implemented `VllmModel` driver strictly adhering to the OpenAI API specification. - Removed hardcoded and dangerous routing logic (e.g., forcing `AsyncChat` for Qwen/GLM prefixes), ensuring standard `/v1/chat/completions` compatibility. - Refactored `ListModels` to use safe JSON parsing (resolving nil pointer panics) and standard `GET` requests without bodies. - Added `APIConfig.Region` fallback logic to prevent empty `base_url` fetching when checking models. 2. **Fixed `ChatToModelStreamWithSender` Bug (`model_service.go`):** - Resolved the `model is disabled` error when streaming chat with local database-saved models. - Added the missing `if modelInfo.Status == "active"` block to correctly invoke `NewInstance` and inject the dynamic `base_url` into the provider driver before starting the SSE stream. 3. **Fixed `ListSupportedModels` Bug (`model_service.go`):** - Added dynamic `NewInstance` injection for `base_url`. Previously, the list models function used the static JSON config without injecting user-configured dynamic URLs from the database, resulting in an `unsupported protocol scheme ""` error. ### Type of change - [x] Bug Fix (non-breaking change which fixes an issue) - [x] New Feature (non-breaking change which adds functionality)
2026-04-30 16:30:14 +08:00
resp, err := v.baseModel.httpClient.Do(req)
Go: implement provider: Vllm (#14532) ### What problem does this PR solve? Implement the vLLM model provider for RAGFlow to fully support local and self-hosted open-source models (e.g., Qwen, GLM, Llama) via the vLLM framework, and fix several critical bugs related to model instance management and API requests. **Key changes and fixes:** 1. **Added Standard vLLM Provider (`vllm.go`, `vllm.json`):** - Implemented `VllmModel` driver strictly adhering to the OpenAI API specification. - Removed hardcoded and dangerous routing logic (e.g., forcing `AsyncChat` for Qwen/GLM prefixes), ensuring standard `/v1/chat/completions` compatibility. - Refactored `ListModels` to use safe JSON parsing (resolving nil pointer panics) and standard `GET` requests without bodies. - Added `APIConfig.Region` fallback logic to prevent empty `base_url` fetching when checking models. 2. **Fixed `ChatToModelStreamWithSender` Bug (`model_service.go`):** - Resolved the `model is disabled` error when streaming chat with local database-saved models. - Added the missing `if modelInfo.Status == "active"` block to correctly invoke `NewInstance` and inject the dynamic `base_url` into the provider driver before starting the SSE stream. 3. **Fixed `ListSupportedModels` Bug (`model_service.go`):** - Added dynamic `NewInstance` injection for `base_url`. Previously, the list models function used the static JSON config without injecting user-configured dynamic URLs from the database, resulting in an `unsupported protocol scheme ""` error. ### Type of change - [x] Bug Fix (non-breaking change which fixes an issue) - [x] New Feature (non-breaking change which adds functionality)
2026-04-30 16:30:14 +08:00
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
if _, err := ParseSSEStream[map[string]interface{}](resp.Body, func(event map[string]interface{}) error {
common.Info(fmt.Sprintf("%v", event))
Go: implement provider: Vllm (#14532) ### What problem does this PR solve? Implement the vLLM model provider for RAGFlow to fully support local and self-hosted open-source models (e.g., Qwen, GLM, Llama) via the vLLM framework, and fix several critical bugs related to model instance management and API requests. **Key changes and fixes:** 1. **Added Standard vLLM Provider (`vllm.go`, `vllm.json`):** - Implemented `VllmModel` driver strictly adhering to the OpenAI API specification. - Removed hardcoded and dangerous routing logic (e.g., forcing `AsyncChat` for Qwen/GLM prefixes), ensuring standard `/v1/chat/completions` compatibility. - Refactored `ListModels` to use safe JSON parsing (resolving nil pointer panics) and standard `GET` requests without bodies. - Added `APIConfig.Region` fallback logic to prevent empty `base_url` fetching when checking models. 2. **Fixed `ChatToModelStreamWithSender` Bug (`model_service.go`):** - Resolved the `model is disabled` error when streaming chat with local database-saved models. - Added the missing `if modelInfo.Status == "active"` block to correctly invoke `NewInstance` and inject the dynamic `base_url` into the provider driver before starting the SSE stream. 3. **Fixed `ListSupportedModels` Bug (`model_service.go`):** - Added dynamic `NewInstance` injection for `base_url`. Previously, the list models function used the static JSON config without injecting user-configured dynamic URLs from the database, resulting in an `unsupported protocol scheme ""` error. ### Type of change - [x] Bug Fix (non-breaking change which fixes an issue) - [x] New Feature (non-breaking change which adds functionality)
2026-04-30 16:30:14 +08:00
choices, ok := event["choices"].([]interface{})
if !ok || len(choices) == 0 {
return nil
Go: implement provider: Vllm (#14532) ### What problem does this PR solve? Implement the vLLM model provider for RAGFlow to fully support local and self-hosted open-source models (e.g., Qwen, GLM, Llama) via the vLLM framework, and fix several critical bugs related to model instance management and API requests. **Key changes and fixes:** 1. **Added Standard vLLM Provider (`vllm.go`, `vllm.json`):** - Implemented `VllmModel` driver strictly adhering to the OpenAI API specification. - Removed hardcoded and dangerous routing logic (e.g., forcing `AsyncChat` for Qwen/GLM prefixes), ensuring standard `/v1/chat/completions` compatibility. - Refactored `ListModels` to use safe JSON parsing (resolving nil pointer panics) and standard `GET` requests without bodies. - Added `APIConfig.Region` fallback logic to prevent empty `base_url` fetching when checking models. 2. **Fixed `ChatToModelStreamWithSender` Bug (`model_service.go`):** - Resolved the `model is disabled` error when streaming chat with local database-saved models. - Added the missing `if modelInfo.Status == "active"` block to correctly invoke `NewInstance` and inject the dynamic `base_url` into the provider driver before starting the SSE stream. 3. **Fixed `ListSupportedModels` Bug (`model_service.go`):** - Added dynamic `NewInstance` injection for `base_url`. Previously, the list models function used the static JSON config without injecting user-configured dynamic URLs from the database, resulting in an `unsupported protocol scheme ""` error. ### Type of change - [x] Bug Fix (non-breaking change which fixes an issue) - [x] New Feature (non-breaking change which adds functionality)
2026-04-30 16:30:14 +08:00
}
firstChoice, ok := choices[0].(map[string]interface{})
if !ok {
return nil
Go: implement provider: Vllm (#14532) ### What problem does this PR solve? Implement the vLLM model provider for RAGFlow to fully support local and self-hosted open-source models (e.g., Qwen, GLM, Llama) via the vLLM framework, and fix several critical bugs related to model instance management and API requests. **Key changes and fixes:** 1. **Added Standard vLLM Provider (`vllm.go`, `vllm.json`):** - Implemented `VllmModel` driver strictly adhering to the OpenAI API specification. - Removed hardcoded and dangerous routing logic (e.g., forcing `AsyncChat` for Qwen/GLM prefixes), ensuring standard `/v1/chat/completions` compatibility. - Refactored `ListModels` to use safe JSON parsing (resolving nil pointer panics) and standard `GET` requests without bodies. - Added `APIConfig.Region` fallback logic to prevent empty `base_url` fetching when checking models. 2. **Fixed `ChatToModelStreamWithSender` Bug (`model_service.go`):** - Resolved the `model is disabled` error when streaming chat with local database-saved models. - Added the missing `if modelInfo.Status == "active"` block to correctly invoke `NewInstance` and inject the dynamic `base_url` into the provider driver before starting the SSE stream. 3. **Fixed `ListSupportedModels` Bug (`model_service.go`):** - Added dynamic `NewInstance` injection for `base_url`. Previously, the list models function used the static JSON config without injecting user-configured dynamic URLs from the database, resulting in an `unsupported protocol scheme ""` error. ### Type of change - [x] Bug Fix (non-breaking change which fixes an issue) - [x] New Feature (non-breaking change which adds functionality)
2026-04-30 16:30:14 +08:00
}
delta, ok := firstChoice["delta"].(map[string]interface{})
if !ok {
return nil
Go: implement provider: Vllm (#14532) ### What problem does this PR solve? Implement the vLLM model provider for RAGFlow to fully support local and self-hosted open-source models (e.g., Qwen, GLM, Llama) via the vLLM framework, and fix several critical bugs related to model instance management and API requests. **Key changes and fixes:** 1. **Added Standard vLLM Provider (`vllm.go`, `vllm.json`):** - Implemented `VllmModel` driver strictly adhering to the OpenAI API specification. - Removed hardcoded and dangerous routing logic (e.g., forcing `AsyncChat` for Qwen/GLM prefixes), ensuring standard `/v1/chat/completions` compatibility. - Refactored `ListModels` to use safe JSON parsing (resolving nil pointer panics) and standard `GET` requests without bodies. - Added `APIConfig.Region` fallback logic to prevent empty `base_url` fetching when checking models. 2. **Fixed `ChatToModelStreamWithSender` Bug (`model_service.go`):** - Resolved the `model is disabled` error when streaming chat with local database-saved models. - Added the missing `if modelInfo.Status == "active"` block to correctly invoke `NewInstance` and inject the dynamic `base_url` into the provider driver before starting the SSE stream. 3. **Fixed `ListSupportedModels` Bug (`model_service.go`):** - Added dynamic `NewInstance` injection for `base_url`. Previously, the list models function used the static JSON config without injecting user-configured dynamic URLs from the database, resulting in an `unsupported protocol scheme ""` error. ### Type of change - [x] Bug Fix (non-breaking change which fixes an issue) - [x] New Feature (non-breaking change which adds functionality)
2026-04-30 16:30:14 +08:00
}
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
}
}
return nil
}); err != nil {
return fmt.Errorf("failed to scan response body: %w", err)
Go: implement provider: Vllm (#14532) ### What problem does this PR solve? Implement the vLLM model provider for RAGFlow to fully support local and self-hosted open-source models (e.g., Qwen, GLM, Llama) via the vLLM framework, and fix several critical bugs related to model instance management and API requests. **Key changes and fixes:** 1. **Added Standard vLLM Provider (`vllm.go`, `vllm.json`):** - Implemented `VllmModel` driver strictly adhering to the OpenAI API specification. - Removed hardcoded and dangerous routing logic (e.g., forcing `AsyncChat` for Qwen/GLM prefixes), ensuring standard `/v1/chat/completions` compatibility. - Refactored `ListModels` to use safe JSON parsing (resolving nil pointer panics) and standard `GET` requests without bodies. - Added `APIConfig.Region` fallback logic to prevent empty `base_url` fetching when checking models. 2. **Fixed `ChatToModelStreamWithSender` Bug (`model_service.go`):** - Resolved the `model is disabled` error when streaming chat with local database-saved models. - Added the missing `if modelInfo.Status == "active"` block to correctly invoke `NewInstance` and inject the dynamic `base_url` into the provider driver before starting the SSE stream. 3. **Fixed `ListSupportedModels` Bug (`model_service.go`):** - Added dynamic `NewInstance` injection for `base_url`. Previously, the list models function used the static JSON config without injecting user-configured dynamic URLs from the database, resulting in an `unsupported protocol scheme ""` error. ### Type of change - [x] Bug Fix (non-breaking change which fixes an issue) - [x] New Feature (non-breaking change which adds functionality)
2026-04-30 16:30:14 +08:00
}
// Send [DONE] marker for OpenAI compatibility
endOfStream := "[DONE]"
if err = sender(&endOfStream, nil); err != nil {
return err
}
return nil
}
// Encode encodes a list of texts into embeddings
Go: implement Encode (embeddings) in vLLM driver (#14688) ### What problem does this PR solve? The vLLM Go driver shipped with a stub \`Encode\` method that returned \`not implemented\`, even though vLLM is one of the most common production-grade self-hosted inference servers and exposes an OpenAI-compatible embeddings endpoint at \`/v1/embeddings\`. Users who self-host \`BAAI/bge-m3\`, \`Qwen3-Embedding-*\`, \`NV-Embed-v2\`, or similar models on vLLM could not run an embedding call through the Go layer. The existing \`ListModels\` already discovers the loaded models, but the embedding path failed because \`Encode\` was a stub. ### What this PR includes - \`conf/models/vllm.json\`: add \`\"embedding\": \"embeddings\"\` under \`url_suffix\` so the driver can build the URL from config. - \`internal/entity/models/vllm.go\`: replace the \`Encode\` stub with a real implementation. Adds a small local response type that matches the OpenAI-compatible shape. No factory change. No interface change. ### How the driver works - Validate the model name. The API key is optional for self-hosted vLLM, so the Authorization header is only set when both \`apiConfig\` and \`ApiKey\` are non-nil and non-empty, the same pattern the recently merged CheckConnection PR (#14614) uses. - Resolve the region with a default fallback. Return a clear "missing base URL" error when the user has not configured the local access address yet. - Use a per-call \`context.WithTimeout(30s)\` and \`http.NewRequestWithContext\`, the same pattern the merged Aliyun Encode (#14647) and in-flight Ollama Encode (#14664) use. - Send \`{model, input: [texts]}\` in one request. - Parse \`data[*].embedding\` and copy each slice into a \`[][]float64\` indexed by \`data[*].index\`, so the output order matches the input order. - Handle both \`float64\` and \`float32\` element types. - Empty input returns \`[][]float64{}\` with no HTTP call. - Length mismatch between input and result, out-of-range index, and any missing slot all return clear errors instead of silent zero vectors. ### Type of change - [x] New Feature (non-breaking change which adds functionality) ### How was this tested? - \`go build ./internal/entity/models/...\` in a clean go 1.25 image returns exit 0. - The full method set on \`VllmModel\` still matches the \`ModelDriver\` interface. - Pattern parity with the merged Aliyun Encode (#14647), the in-flight Ollama Encode (#14664), and the existing SiliconFlow Encode. Closes #14687
2026-05-11 06:09:17 +02:00
type vllmEmbeddingResponse struct {
Data []struct {
Index int `json:"index"`
Embedding []float64 `json:"embedding"`
Go: implement Encode (embeddings) in vLLM driver (#14688) ### What problem does this PR solve? The vLLM Go driver shipped with a stub \`Encode\` method that returned \`not implemented\`, even though vLLM is one of the most common production-grade self-hosted inference servers and exposes an OpenAI-compatible embeddings endpoint at \`/v1/embeddings\`. Users who self-host \`BAAI/bge-m3\`, \`Qwen3-Embedding-*\`, \`NV-Embed-v2\`, or similar models on vLLM could not run an embedding call through the Go layer. The existing \`ListModels\` already discovers the loaded models, but the embedding path failed because \`Encode\` was a stub. ### What this PR includes - \`conf/models/vllm.json\`: add \`\"embedding\": \"embeddings\"\` under \`url_suffix\` so the driver can build the URL from config. - \`internal/entity/models/vllm.go\`: replace the \`Encode\` stub with a real implementation. Adds a small local response type that matches the OpenAI-compatible shape. No factory change. No interface change. ### How the driver works - Validate the model name. The API key is optional for self-hosted vLLM, so the Authorization header is only set when both \`apiConfig\` and \`ApiKey\` are non-nil and non-empty, the same pattern the recently merged CheckConnection PR (#14614) uses. - Resolve the region with a default fallback. Return a clear "missing base URL" error when the user has not configured the local access address yet. - Use a per-call \`context.WithTimeout(30s)\` and \`http.NewRequestWithContext\`, the same pattern the merged Aliyun Encode (#14647) and in-flight Ollama Encode (#14664) use. - Send \`{model, input: [texts]}\` in one request. - Parse \`data[*].embedding\` and copy each slice into a \`[][]float64\` indexed by \`data[*].index\`, so the output order matches the input order. - Handle both \`float64\` and \`float32\` element types. - Empty input returns \`[][]float64{}\` with no HTTP call. - Length mismatch between input and result, out-of-range index, and any missing slot all return clear errors instead of silent zero vectors. ### Type of change - [x] New Feature (non-breaking change which adds functionality) ### How was this tested? - \`go build ./internal/entity/models/...\` in a clean go 1.25 image returns exit 0. - The full method set on \`VllmModel\` still matches the \`ModelDriver\` interface. - Pattern parity with the merged Aliyun Encode (#14647), the in-flight Ollama Encode (#14664), and the existing SiliconFlow Encode. Closes #14687
2026-05-11 06:09:17 +02:00
} `json:"data"`
}
// Embed embeds a list of texts into embeddings
func (v *VllmModel) Embed(modelName *string, texts []string, apiConfig *APIConfig, embeddingConfig *EmbeddingConfig) ([]EmbeddingData, error) {
if err := v.baseModel.APIConfigCheck(apiConfig); err != nil {
return nil, err
}
Go: implement Encode (embeddings) in vLLM driver (#14688) ### What problem does this PR solve? The vLLM Go driver shipped with a stub \`Encode\` method that returned \`not implemented\`, even though vLLM is one of the most common production-grade self-hosted inference servers and exposes an OpenAI-compatible embeddings endpoint at \`/v1/embeddings\`. Users who self-host \`BAAI/bge-m3\`, \`Qwen3-Embedding-*\`, \`NV-Embed-v2\`, or similar models on vLLM could not run an embedding call through the Go layer. The existing \`ListModels\` already discovers the loaded models, but the embedding path failed because \`Encode\` was a stub. ### What this PR includes - \`conf/models/vllm.json\`: add \`\"embedding\": \"embeddings\"\` under \`url_suffix\` so the driver can build the URL from config. - \`internal/entity/models/vllm.go\`: replace the \`Encode\` stub with a real implementation. Adds a small local response type that matches the OpenAI-compatible shape. No factory change. No interface change. ### How the driver works - Validate the model name. The API key is optional for self-hosted vLLM, so the Authorization header is only set when both \`apiConfig\` and \`ApiKey\` are non-nil and non-empty, the same pattern the recently merged CheckConnection PR (#14614) uses. - Resolve the region with a default fallback. Return a clear "missing base URL" error when the user has not configured the local access address yet. - Use a per-call \`context.WithTimeout(30s)\` and \`http.NewRequestWithContext\`, the same pattern the merged Aliyun Encode (#14647) and in-flight Ollama Encode (#14664) use. - Send \`{model, input: [texts]}\` in one request. - Parse \`data[*].embedding\` and copy each slice into a \`[][]float64\` indexed by \`data[*].index\`, so the output order matches the input order. - Handle both \`float64\` and \`float32\` element types. - Empty input returns \`[][]float64{}\` with no HTTP call. - Length mismatch between input and result, out-of-range index, and any missing slot all return clear errors instead of silent zero vectors. ### Type of change - [x] New Feature (non-breaking change which adds functionality) ### How was this tested? - \`go build ./internal/entity/models/...\` in a clean go 1.25 image returns exit 0. - The full method set on \`VllmModel\` still matches the \`ModelDriver\` interface. - Pattern parity with the merged Aliyun Encode (#14647), the in-flight Ollama Encode (#14664), and the existing SiliconFlow Encode. Closes #14687
2026-05-11 06:09:17 +02:00
if len(texts) == 0 {
return []EmbeddingData{}, nil
Go: implement Encode (embeddings) in vLLM driver (#14688) ### What problem does this PR solve? The vLLM Go driver shipped with a stub \`Encode\` method that returned \`not implemented\`, even though vLLM is one of the most common production-grade self-hosted inference servers and exposes an OpenAI-compatible embeddings endpoint at \`/v1/embeddings\`. Users who self-host \`BAAI/bge-m3\`, \`Qwen3-Embedding-*\`, \`NV-Embed-v2\`, or similar models on vLLM could not run an embedding call through the Go layer. The existing \`ListModels\` already discovers the loaded models, but the embedding path failed because \`Encode\` was a stub. ### What this PR includes - \`conf/models/vllm.json\`: add \`\"embedding\": \"embeddings\"\` under \`url_suffix\` so the driver can build the URL from config. - \`internal/entity/models/vllm.go\`: replace the \`Encode\` stub with a real implementation. Adds a small local response type that matches the OpenAI-compatible shape. No factory change. No interface change. ### How the driver works - Validate the model name. The API key is optional for self-hosted vLLM, so the Authorization header is only set when both \`apiConfig\` and \`ApiKey\` are non-nil and non-empty, the same pattern the recently merged CheckConnection PR (#14614) uses. - Resolve the region with a default fallback. Return a clear "missing base URL" error when the user has not configured the local access address yet. - Use a per-call \`context.WithTimeout(30s)\` and \`http.NewRequestWithContext\`, the same pattern the merged Aliyun Encode (#14647) and in-flight Ollama Encode (#14664) use. - Send \`{model, input: [texts]}\` in one request. - Parse \`data[*].embedding\` and copy each slice into a \`[][]float64\` indexed by \`data[*].index\`, so the output order matches the input order. - Handle both \`float64\` and \`float32\` element types. - Empty input returns \`[][]float64{}\` with no HTTP call. - Length mismatch between input and result, out-of-range index, and any missing slot all return clear errors instead of silent zero vectors. ### Type of change - [x] New Feature (non-breaking change which adds functionality) ### How was this tested? - \`go build ./internal/entity/models/...\` in a clean go 1.25 image returns exit 0. - The full method set on \`VllmModel\` still matches the \`ModelDriver\` interface. - Pattern parity with the merged Aliyun Encode (#14647), the in-flight Ollama Encode (#14664), and the existing SiliconFlow Encode. Closes #14687
2026-05-11 06:09:17 +02:00
}
if modelName == nil || *modelName == "" {
return nil, fmt.Errorf("model name is required")
}
resolvedBaseURL, err := v.baseModel.GetBaseURL(apiConfig)
if err != nil {
return nil, err
Go: implement Encode (embeddings) in vLLM driver (#14688) ### What problem does this PR solve? The vLLM Go driver shipped with a stub \`Encode\` method that returned \`not implemented\`, even though vLLM is one of the most common production-grade self-hosted inference servers and exposes an OpenAI-compatible embeddings endpoint at \`/v1/embeddings\`. Users who self-host \`BAAI/bge-m3\`, \`Qwen3-Embedding-*\`, \`NV-Embed-v2\`, or similar models on vLLM could not run an embedding call through the Go layer. The existing \`ListModels\` already discovers the loaded models, but the embedding path failed because \`Encode\` was a stub. ### What this PR includes - \`conf/models/vllm.json\`: add \`\"embedding\": \"embeddings\"\` under \`url_suffix\` so the driver can build the URL from config. - \`internal/entity/models/vllm.go\`: replace the \`Encode\` stub with a real implementation. Adds a small local response type that matches the OpenAI-compatible shape. No factory change. No interface change. ### How the driver works - Validate the model name. The API key is optional for self-hosted vLLM, so the Authorization header is only set when both \`apiConfig\` and \`ApiKey\` are non-nil and non-empty, the same pattern the recently merged CheckConnection PR (#14614) uses. - Resolve the region with a default fallback. Return a clear "missing base URL" error when the user has not configured the local access address yet. - Use a per-call \`context.WithTimeout(30s)\` and \`http.NewRequestWithContext\`, the same pattern the merged Aliyun Encode (#14647) and in-flight Ollama Encode (#14664) use. - Send \`{model, input: [texts]}\` in one request. - Parse \`data[*].embedding\` and copy each slice into a \`[][]float64\` indexed by \`data[*].index\`, so the output order matches the input order. - Handle both \`float64\` and \`float32\` element types. - Empty input returns \`[][]float64{}\` with no HTTP call. - Length mismatch between input and result, out-of-range index, and any missing slot all return clear errors instead of silent zero vectors. ### Type of change - [x] New Feature (non-breaking change which adds functionality) ### How was this tested? - \`go build ./internal/entity/models/...\` in a clean go 1.25 image returns exit 0. - The full method set on \`VllmModel\` still matches the \`ModelDriver\` interface. - Pattern parity with the merged Aliyun Encode (#14647), the in-flight Ollama Encode (#14664), and the existing SiliconFlow Encode. Closes #14687
2026-05-11 06:09:17 +02:00
}
baseURL := resolvedBaseURL
Go: implement Encode (embeddings) in vLLM driver (#14688) ### What problem does this PR solve? The vLLM Go driver shipped with a stub \`Encode\` method that returned \`not implemented\`, even though vLLM is one of the most common production-grade self-hosted inference servers and exposes an OpenAI-compatible embeddings endpoint at \`/v1/embeddings\`. Users who self-host \`BAAI/bge-m3\`, \`Qwen3-Embedding-*\`, \`NV-Embed-v2\`, or similar models on vLLM could not run an embedding call through the Go layer. The existing \`ListModels\` already discovers the loaded models, but the embedding path failed because \`Encode\` was a stub. ### What this PR includes - \`conf/models/vllm.json\`: add \`\"embedding\": \"embeddings\"\` under \`url_suffix\` so the driver can build the URL from config. - \`internal/entity/models/vllm.go\`: replace the \`Encode\` stub with a real implementation. Adds a small local response type that matches the OpenAI-compatible shape. No factory change. No interface change. ### How the driver works - Validate the model name. The API key is optional for self-hosted vLLM, so the Authorization header is only set when both \`apiConfig\` and \`ApiKey\` are non-nil and non-empty, the same pattern the recently merged CheckConnection PR (#14614) uses. - Resolve the region with a default fallback. Return a clear "missing base URL" error when the user has not configured the local access address yet. - Use a per-call \`context.WithTimeout(30s)\` and \`http.NewRequestWithContext\`, the same pattern the merged Aliyun Encode (#14647) and in-flight Ollama Encode (#14664) use. - Send \`{model, input: [texts]}\` in one request. - Parse \`data[*].embedding\` and copy each slice into a \`[][]float64\` indexed by \`data[*].index\`, so the output order matches the input order. - Handle both \`float64\` and \`float32\` element types. - Empty input returns \`[][]float64{}\` with no HTTP call. - Length mismatch between input and result, out-of-range index, and any missing slot all return clear errors instead of silent zero vectors. ### Type of change - [x] New Feature (non-breaking change which adds functionality) ### How was this tested? - \`go build ./internal/entity/models/...\` in a clean go 1.25 image returns exit 0. - The full method set on \`VllmModel\` still matches the \`ModelDriver\` interface. - Pattern parity with the merged Aliyun Encode (#14647), the in-flight Ollama Encode (#14664), and the existing SiliconFlow Encode. Closes #14687
2026-05-11 06:09:17 +02:00
if baseURL == "" {
baseURL = resolvedBaseURL
Go: implement Encode (embeddings) in vLLM driver (#14688) ### What problem does this PR solve? The vLLM Go driver shipped with a stub \`Encode\` method that returned \`not implemented\`, even though vLLM is one of the most common production-grade self-hosted inference servers and exposes an OpenAI-compatible embeddings endpoint at \`/v1/embeddings\`. Users who self-host \`BAAI/bge-m3\`, \`Qwen3-Embedding-*\`, \`NV-Embed-v2\`, or similar models on vLLM could not run an embedding call through the Go layer. The existing \`ListModels\` already discovers the loaded models, but the embedding path failed because \`Encode\` was a stub. ### What this PR includes - \`conf/models/vllm.json\`: add \`\"embedding\": \"embeddings\"\` under \`url_suffix\` so the driver can build the URL from config. - \`internal/entity/models/vllm.go\`: replace the \`Encode\` stub with a real implementation. Adds a small local response type that matches the OpenAI-compatible shape. No factory change. No interface change. ### How the driver works - Validate the model name. The API key is optional for self-hosted vLLM, so the Authorization header is only set when both \`apiConfig\` and \`ApiKey\` are non-nil and non-empty, the same pattern the recently merged CheckConnection PR (#14614) uses. - Resolve the region with a default fallback. Return a clear "missing base URL" error when the user has not configured the local access address yet. - Use a per-call \`context.WithTimeout(30s)\` and \`http.NewRequestWithContext\`, the same pattern the merged Aliyun Encode (#14647) and in-flight Ollama Encode (#14664) use. - Send \`{model, input: [texts]}\` in one request. - Parse \`data[*].embedding\` and copy each slice into a \`[][]float64\` indexed by \`data[*].index\`, so the output order matches the input order. - Handle both \`float64\` and \`float32\` element types. - Empty input returns \`[][]float64{}\` with no HTTP call. - Length mismatch between input and result, out-of-range index, and any missing slot all return clear errors instead of silent zero vectors. ### Type of change - [x] New Feature (non-breaking change which adds functionality) ### How was this tested? - \`go build ./internal/entity/models/...\` in a clean go 1.25 image returns exit 0. - The full method set on \`VllmModel\` still matches the \`ModelDriver\` interface. - Pattern parity with the merged Aliyun Encode (#14647), the in-flight Ollama Encode (#14664), and the existing SiliconFlow Encode. Closes #14687
2026-05-11 06:09:17 +02:00
}
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, "/"), v.baseModel.URLSuffix.Embedding)
Go: implement Encode (embeddings) in vLLM driver (#14688) ### What problem does this PR solve? The vLLM Go driver shipped with a stub \`Encode\` method that returned \`not implemented\`, even though vLLM is one of the most common production-grade self-hosted inference servers and exposes an OpenAI-compatible embeddings endpoint at \`/v1/embeddings\`. Users who self-host \`BAAI/bge-m3\`, \`Qwen3-Embedding-*\`, \`NV-Embed-v2\`, or similar models on vLLM could not run an embedding call through the Go layer. The existing \`ListModels\` already discovers the loaded models, but the embedding path failed because \`Encode\` was a stub. ### What this PR includes - \`conf/models/vllm.json\`: add \`\"embedding\": \"embeddings\"\` under \`url_suffix\` so the driver can build the URL from config. - \`internal/entity/models/vllm.go\`: replace the \`Encode\` stub with a real implementation. Adds a small local response type that matches the OpenAI-compatible shape. No factory change. No interface change. ### How the driver works - Validate the model name. The API key is optional for self-hosted vLLM, so the Authorization header is only set when both \`apiConfig\` and \`ApiKey\` are non-nil and non-empty, the same pattern the recently merged CheckConnection PR (#14614) uses. - Resolve the region with a default fallback. Return a clear "missing base URL" error when the user has not configured the local access address yet. - Use a per-call \`context.WithTimeout(30s)\` and \`http.NewRequestWithContext\`, the same pattern the merged Aliyun Encode (#14647) and in-flight Ollama Encode (#14664) use. - Send \`{model, input: [texts]}\` in one request. - Parse \`data[*].embedding\` and copy each slice into a \`[][]float64\` indexed by \`data[*].index\`, so the output order matches the input order. - Handle both \`float64\` and \`float32\` element types. - Empty input returns \`[][]float64{}\` with no HTTP call. - Length mismatch between input and result, out-of-range index, and any missing slot all return clear errors instead of silent zero vectors. ### Type of change - [x] New Feature (non-breaking change which adds functionality) ### How was this tested? - \`go build ./internal/entity/models/...\` in a clean go 1.25 image returns exit 0. - The full method set on \`VllmModel\` still matches the \`ModelDriver\` interface. - Pattern parity with the merged Aliyun Encode (#14647), the in-flight Ollama Encode (#14664), and the existing SiliconFlow Encode. Closes #14687
2026-05-11 06:09:17 +02:00
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)
Go: implement Encode (embeddings) in vLLM driver (#14688) ### What problem does this PR solve? The vLLM Go driver shipped with a stub \`Encode\` method that returned \`not implemented\`, even though vLLM is one of the most common production-grade self-hosted inference servers and exposes an OpenAI-compatible embeddings endpoint at \`/v1/embeddings\`. Users who self-host \`BAAI/bge-m3\`, \`Qwen3-Embedding-*\`, \`NV-Embed-v2\`, or similar models on vLLM could not run an embedding call through the Go layer. The existing \`ListModels\` already discovers the loaded models, but the embedding path failed because \`Encode\` was a stub. ### What this PR includes - \`conf/models/vllm.json\`: add \`\"embedding\": \"embeddings\"\` under \`url_suffix\` so the driver can build the URL from config. - \`internal/entity/models/vllm.go\`: replace the \`Encode\` stub with a real implementation. Adds a small local response type that matches the OpenAI-compatible shape. No factory change. No interface change. ### How the driver works - Validate the model name. The API key is optional for self-hosted vLLM, so the Authorization header is only set when both \`apiConfig\` and \`ApiKey\` are non-nil and non-empty, the same pattern the recently merged CheckConnection PR (#14614) uses. - Resolve the region with a default fallback. Return a clear "missing base URL" error when the user has not configured the local access address yet. - Use a per-call \`context.WithTimeout(30s)\` and \`http.NewRequestWithContext\`, the same pattern the merged Aliyun Encode (#14647) and in-flight Ollama Encode (#14664) use. - Send \`{model, input: [texts]}\` in one request. - Parse \`data[*].embedding\` and copy each slice into a \`[][]float64\` indexed by \`data[*].index\`, so the output order matches the input order. - Handle both \`float64\` and \`float32\` element types. - Empty input returns \`[][]float64{}\` with no HTTP call. - Length mismatch between input and result, out-of-range index, and any missing slot all return clear errors instead of silent zero vectors. ### Type of change - [x] New Feature (non-breaking change which adds functionality) ### How was this tested? - \`go build ./internal/entity/models/...\` in a clean go 1.25 image returns exit 0. - The full method set on \`VllmModel\` still matches the \`ModelDriver\` interface. - Pattern parity with the merged Aliyun Encode (#14647), the in-flight Ollama Encode (#14664), and the existing SiliconFlow Encode. Closes #14687
2026-05-11 06:09:17 +02:00
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 auth := BearerAuth(apiConfig); auth != "" {
req.Header.Set("Authorization", auth)
}
Go: implement Encode (embeddings) in vLLM driver (#14688) ### What problem does this PR solve? The vLLM Go driver shipped with a stub \`Encode\` method that returned \`not implemented\`, even though vLLM is one of the most common production-grade self-hosted inference servers and exposes an OpenAI-compatible embeddings endpoint at \`/v1/embeddings\`. Users who self-host \`BAAI/bge-m3\`, \`Qwen3-Embedding-*\`, \`NV-Embed-v2\`, or similar models on vLLM could not run an embedding call through the Go layer. The existing \`ListModels\` already discovers the loaded models, but the embedding path failed because \`Encode\` was a stub. ### What this PR includes - \`conf/models/vllm.json\`: add \`\"embedding\": \"embeddings\"\` under \`url_suffix\` so the driver can build the URL from config. - \`internal/entity/models/vllm.go\`: replace the \`Encode\` stub with a real implementation. Adds a small local response type that matches the OpenAI-compatible shape. No factory change. No interface change. ### How the driver works - Validate the model name. The API key is optional for self-hosted vLLM, so the Authorization header is only set when both \`apiConfig\` and \`ApiKey\` are non-nil and non-empty, the same pattern the recently merged CheckConnection PR (#14614) uses. - Resolve the region with a default fallback. Return a clear "missing base URL" error when the user has not configured the local access address yet. - Use a per-call \`context.WithTimeout(30s)\` and \`http.NewRequestWithContext\`, the same pattern the merged Aliyun Encode (#14647) and in-flight Ollama Encode (#14664) use. - Send \`{model, input: [texts]}\` in one request. - Parse \`data[*].embedding\` and copy each slice into a \`[][]float64\` indexed by \`data[*].index\`, so the output order matches the input order. - Handle both \`float64\` and \`float32\` element types. - Empty input returns \`[][]float64{}\` with no HTTP call. - Length mismatch between input and result, out-of-range index, and any missing slot all return clear errors instead of silent zero vectors. ### Type of change - [x] New Feature (non-breaking change which adds functionality) ### How was this tested? - \`go build ./internal/entity/models/...\` in a clean go 1.25 image returns exit 0. - The full method set on \`VllmModel\` still matches the \`ModelDriver\` interface. - Pattern parity with the merged Aliyun Encode (#14647), the in-flight Ollama Encode (#14664), and the existing SiliconFlow Encode. Closes #14687
2026-05-11 06:09:17 +02:00
resp, err := v.baseModel.httpClient.Do(req)
Go: implement Encode (embeddings) in vLLM driver (#14688) ### What problem does this PR solve? The vLLM Go driver shipped with a stub \`Encode\` method that returned \`not implemented\`, even though vLLM is one of the most common production-grade self-hosted inference servers and exposes an OpenAI-compatible embeddings endpoint at \`/v1/embeddings\`. Users who self-host \`BAAI/bge-m3\`, \`Qwen3-Embedding-*\`, \`NV-Embed-v2\`, or similar models on vLLM could not run an embedding call through the Go layer. The existing \`ListModels\` already discovers the loaded models, but the embedding path failed because \`Encode\` was a stub. ### What this PR includes - \`conf/models/vllm.json\`: add \`\"embedding\": \"embeddings\"\` under \`url_suffix\` so the driver can build the URL from config. - \`internal/entity/models/vllm.go\`: replace the \`Encode\` stub with a real implementation. Adds a small local response type that matches the OpenAI-compatible shape. No factory change. No interface change. ### How the driver works - Validate the model name. The API key is optional for self-hosted vLLM, so the Authorization header is only set when both \`apiConfig\` and \`ApiKey\` are non-nil and non-empty, the same pattern the recently merged CheckConnection PR (#14614) uses. - Resolve the region with a default fallback. Return a clear "missing base URL" error when the user has not configured the local access address yet. - Use a per-call \`context.WithTimeout(30s)\` and \`http.NewRequestWithContext\`, the same pattern the merged Aliyun Encode (#14647) and in-flight Ollama Encode (#14664) use. - Send \`{model, input: [texts]}\` in one request. - Parse \`data[*].embedding\` and copy each slice into a \`[][]float64\` indexed by \`data[*].index\`, so the output order matches the input order. - Handle both \`float64\` and \`float32\` element types. - Empty input returns \`[][]float64{}\` with no HTTP call. - Length mismatch between input and result, out-of-range index, and any missing slot all return clear errors instead of silent zero vectors. ### Type of change - [x] New Feature (non-breaking change which adds functionality) ### How was this tested? - \`go build ./internal/entity/models/...\` in a clean go 1.25 image returns exit 0. - The full method set on \`VllmModel\` still matches the \`ModelDriver\` interface. - Pattern parity with the merged Aliyun Encode (#14647), the in-flight Ollama Encode (#14664), and the existing SiliconFlow Encode. Closes #14687
2026-05-11 06:09:17 +02:00
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 embeddings API error: %s, body: %s", resp.Status, string(body))
}
var parsed vllmEmbeddingResponse
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)
Go: implement Encode (embeddings) in vLLM driver (#14688) ### What problem does this PR solve? The vLLM Go driver shipped with a stub \`Encode\` method that returned \`not implemented\`, even though vLLM is one of the most common production-grade self-hosted inference servers and exposes an OpenAI-compatible embeddings endpoint at \`/v1/embeddings\`. Users who self-host \`BAAI/bge-m3\`, \`Qwen3-Embedding-*\`, \`NV-Embed-v2\`, or similar models on vLLM could not run an embedding call through the Go layer. The existing \`ListModels\` already discovers the loaded models, but the embedding path failed because \`Encode\` was a stub. ### What this PR includes - \`conf/models/vllm.json\`: add \`\"embedding\": \"embeddings\"\` under \`url_suffix\` so the driver can build the URL from config. - \`internal/entity/models/vllm.go\`: replace the \`Encode\` stub with a real implementation. Adds a small local response type that matches the OpenAI-compatible shape. No factory change. No interface change. ### How the driver works - Validate the model name. The API key is optional for self-hosted vLLM, so the Authorization header is only set when both \`apiConfig\` and \`ApiKey\` are non-nil and non-empty, the same pattern the recently merged CheckConnection PR (#14614) uses. - Resolve the region with a default fallback. Return a clear "missing base URL" error when the user has not configured the local access address yet. - Use a per-call \`context.WithTimeout(30s)\` and \`http.NewRequestWithContext\`, the same pattern the merged Aliyun Encode (#14647) and in-flight Ollama Encode (#14664) use. - Send \`{model, input: [texts]}\` in one request. - Parse \`data[*].embedding\` and copy each slice into a \`[][]float64\` indexed by \`data[*].index\`, so the output order matches the input order. - Handle both \`float64\` and \`float32\` element types. - Empty input returns \`[][]float64{}\` with no HTTP call. - Length mismatch between input and result, out-of-range index, and any missing slot all return clear errors instead of silent zero vectors. ### Type of change - [x] New Feature (non-breaking change which adds functionality) ### How was this tested? - \`go build ./internal/entity/models/...\` in a clean go 1.25 image returns exit 0. - The full method set on \`VllmModel\` still matches the \`ModelDriver\` interface. - Pattern parity with the merged Aliyun Encode (#14647), the in-flight Ollama Encode (#14664), and the existing SiliconFlow Encode. Closes #14687
2026-05-11 06:09:17 +02:00
}
return embeddings, nil
}
func (v *VllmModel) ListModels(apiConfig *APIConfig) ([]ListModelResponse, error) {
if err := v.baseModel.APIConfigCheck(apiConfig); err != nil {
return nil, err
Go: implement provider: Vllm (#14532) ### What problem does this PR solve? Implement the vLLM model provider for RAGFlow to fully support local and self-hosted open-source models (e.g., Qwen, GLM, Llama) via the vLLM framework, and fix several critical bugs related to model instance management and API requests. **Key changes and fixes:** 1. **Added Standard vLLM Provider (`vllm.go`, `vllm.json`):** - Implemented `VllmModel` driver strictly adhering to the OpenAI API specification. - Removed hardcoded and dangerous routing logic (e.g., forcing `AsyncChat` for Qwen/GLM prefixes), ensuring standard `/v1/chat/completions` compatibility. - Refactored `ListModels` to use safe JSON parsing (resolving nil pointer panics) and standard `GET` requests without bodies. - Added `APIConfig.Region` fallback logic to prevent empty `base_url` fetching when checking models. 2. **Fixed `ChatToModelStreamWithSender` Bug (`model_service.go`):** - Resolved the `model is disabled` error when streaming chat with local database-saved models. - Added the missing `if modelInfo.Status == "active"` block to correctly invoke `NewInstance` and inject the dynamic `base_url` into the provider driver before starting the SSE stream. 3. **Fixed `ListSupportedModels` Bug (`model_service.go`):** - Added dynamic `NewInstance` injection for `base_url`. Previously, the list models function used the static JSON config without injecting user-configured dynamic URLs from the database, resulting in an `unsupported protocol scheme ""` error. ### Type of change - [x] Bug Fix (non-breaking change which fixes an issue) - [x] New Feature (non-breaking change which adds functionality)
2026-04-30 16:30:14 +08:00
}
resolvedBaseURL, err := v.baseModel.GetBaseURL(apiConfig)
if err != nil {
return nil, err
}
baseURL := resolvedBaseURL
fix(go): wire CheckConnection to ListModels in ollama, lm-studio, and vllm (#14614) ### What problem does this PR solve? Three Go drivers had `CheckConnection` returning a hardcoded `no such method` error, even though each one already has a working `ListModels` that hits the configured base URL with the configured API key. So the "Check connection" button in the model provider UI always failed for these three providers, even when the underlying setup was fine. Affected drivers: - `internal/entity/models/ollama.go` - `internal/entity/models/lmstudio.go` - `internal/entity/models/vllm.go` This is a real user-facing gap because Ollama and LM Studio are two of the most popular local LLM runners, and vLLM is widely used for self-hosted deployments. ### What this PR includes For each of the three drivers, replace the stub with a small implementation that calls `ListModels` and returns its error: ```go func (o *OllamaModel) CheckConnection(apiConfig *APIConfig) error { _, err := o.ListModels(apiConfig) return err } ``` This is the exact pattern that xai, moonshot, deepseek, aliyun, and gitee already use for the same method. No JSON change. No factory change. No interface change. ### Type of change - [x] Bug Fix (non-breaking change which fixes an issue) ### How was this tested? - `go build ./internal/entity/models/...` in a clean go 1.25 image (the go.mod minimum) returns exit 0. - The full ModelDriver interface still resolves on each driver (NewInstance, Name, ChatWithMessages, ChatStreamlyWithSender, Encode, Rerank, ListModels, Balance, CheckConnection). - Pattern parity with the existing xai, moonshot, deepseek, aliyun, and gitee CheckConnection methods. Closes #14609
2026-05-08 06:00:10 +02:00
if baseURL == "" {
baseURL = resolvedBaseURL
fix(go): wire CheckConnection to ListModels in ollama, lm-studio, and vllm (#14614) ### What problem does this PR solve? Three Go drivers had `CheckConnection` returning a hardcoded `no such method` error, even though each one already has a working `ListModels` that hits the configured base URL with the configured API key. So the "Check connection" button in the model provider UI always failed for these three providers, even when the underlying setup was fine. Affected drivers: - `internal/entity/models/ollama.go` - `internal/entity/models/lmstudio.go` - `internal/entity/models/vllm.go` This is a real user-facing gap because Ollama and LM Studio are two of the most popular local LLM runners, and vLLM is widely used for self-hosted deployments. ### What this PR includes For each of the three drivers, replace the stub with a small implementation that calls `ListModels` and returns its error: ```go func (o *OllamaModel) CheckConnection(apiConfig *APIConfig) error { _, err := o.ListModels(apiConfig) return err } ``` This is the exact pattern that xai, moonshot, deepseek, aliyun, and gitee already use for the same method. No JSON change. No factory change. No interface change. ### Type of change - [x] Bug Fix (non-breaking change which fixes an issue) ### How was this tested? - `go build ./internal/entity/models/...` in a clean go 1.25 image (the go.mod minimum) returns exit 0. - The full ModelDriver interface still resolves on each driver (NewInstance, Name, ChatWithMessages, ChatStreamlyWithSender, Encode, Rerank, ListModels, Balance, CheckConnection). - Pattern parity with the existing xai, moonshot, deepseek, aliyun, and gitee CheckConnection methods. Closes #14609
2026-05-08 06:00:10 +02:00
}
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", baseURL, v.baseModel.URLSuffix.Models)
Go: implement provider: Vllm (#14532) ### What problem does this PR solve? Implement the vLLM model provider for RAGFlow to fully support local and self-hosted open-source models (e.g., Qwen, GLM, Llama) via the vLLM framework, and fix several critical bugs related to model instance management and API requests. **Key changes and fixes:** 1. **Added Standard vLLM Provider (`vllm.go`, `vllm.json`):** - Implemented `VllmModel` driver strictly adhering to the OpenAI API specification. - Removed hardcoded and dangerous routing logic (e.g., forcing `AsyncChat` for Qwen/GLM prefixes), ensuring standard `/v1/chat/completions` compatibility. - Refactored `ListModels` to use safe JSON parsing (resolving nil pointer panics) and standard `GET` requests without bodies. - Added `APIConfig.Region` fallback logic to prevent empty `base_url` fetching when checking models. 2. **Fixed `ChatToModelStreamWithSender` Bug (`model_service.go`):** - Resolved the `model is disabled` error when streaming chat with local database-saved models. - Added the missing `if modelInfo.Status == "active"` block to correctly invoke `NewInstance` and inject the dynamic `base_url` into the provider driver before starting the SSE stream. 3. **Fixed `ListSupportedModels` Bug (`model_service.go`):** - Added dynamic `NewInstance` injection for `base_url`. Previously, the list models function used the static JSON config without injecting user-configured dynamic URLs from the database, resulting in an `unsupported protocol scheme ""` error. ### Type of change - [x] Bug Fix (non-breaking change which fixes an issue) - [x] New Feature (non-breaking change which adds functionality)
2026-04-30 16:30:14 +08:00
reqBody := map[string]interface{}{}
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, "GET", url, bytes.NewBuffer(jsonData))
Go: implement provider: Vllm (#14532) ### What problem does this PR solve? Implement the vLLM model provider for RAGFlow to fully support local and self-hosted open-source models (e.g., Qwen, GLM, Llama) via the vLLM framework, and fix several critical bugs related to model instance management and API requests. **Key changes and fixes:** 1. **Added Standard vLLM Provider (`vllm.go`, `vllm.json`):** - Implemented `VllmModel` driver strictly adhering to the OpenAI API specification. - Removed hardcoded and dangerous routing logic (e.g., forcing `AsyncChat` for Qwen/GLM prefixes), ensuring standard `/v1/chat/completions` compatibility. - Refactored `ListModels` to use safe JSON parsing (resolving nil pointer panics) and standard `GET` requests without bodies. - Added `APIConfig.Region` fallback logic to prevent empty `base_url` fetching when checking models. 2. **Fixed `ChatToModelStreamWithSender` Bug (`model_service.go`):** - Resolved the `model is disabled` error when streaming chat with local database-saved models. - Added the missing `if modelInfo.Status == "active"` block to correctly invoke `NewInstance` and inject the dynamic `base_url` into the provider driver before starting the SSE stream. 3. **Fixed `ListSupportedModels` Bug (`model_service.go`):** - Added dynamic `NewInstance` injection for `base_url`. Previously, the list models function used the static JSON config without injecting user-configured dynamic URLs from the database, resulting in an `unsupported protocol scheme ""` error. ### Type of change - [x] Bug Fix (non-breaking change which fixes an issue) - [x] New Feature (non-breaking change which adds functionality)
2026-04-30 16:30:14 +08:00
if err != nil {
return nil, fmt.Errorf("failed to create request: %w", err)
}
req.Header.Set("Content-Type", "application/json")
if auth := BearerAuth(apiConfig); auth != "" {
req.Header.Set("Authorization", auth)
}
Go: implement provider: Vllm (#14532) ### What problem does this PR solve? Implement the vLLM model provider for RAGFlow to fully support local and self-hosted open-source models (e.g., Qwen, GLM, Llama) via the vLLM framework, and fix several critical bugs related to model instance management and API requests. **Key changes and fixes:** 1. **Added Standard vLLM Provider (`vllm.go`, `vllm.json`):** - Implemented `VllmModel` driver strictly adhering to the OpenAI API specification. - Removed hardcoded and dangerous routing logic (e.g., forcing `AsyncChat` for Qwen/GLM prefixes), ensuring standard `/v1/chat/completions` compatibility. - Refactored `ListModels` to use safe JSON parsing (resolving nil pointer panics) and standard `GET` requests without bodies. - Added `APIConfig.Region` fallback logic to prevent empty `base_url` fetching when checking models. 2. **Fixed `ChatToModelStreamWithSender` Bug (`model_service.go`):** - Resolved the `model is disabled` error when streaming chat with local database-saved models. - Added the missing `if modelInfo.Status == "active"` block to correctly invoke `NewInstance` and inject the dynamic `base_url` into the provider driver before starting the SSE stream. 3. **Fixed `ListSupportedModels` Bug (`model_service.go`):** - Added dynamic `NewInstance` injection for `base_url`. Previously, the list models function used the static JSON config without injecting user-configured dynamic URLs from the database, resulting in an `unsupported protocol scheme ""` error. ### Type of change - [x] Bug Fix (non-breaking change which fixes an issue) - [x] New Feature (non-breaking change which adds functionality)
2026-04-30 16:30:14 +08:00
resp, err := v.baseModel.httpClient.Do(req)
Go: implement provider: Vllm (#14532) ### What problem does this PR solve? Implement the vLLM model provider for RAGFlow to fully support local and self-hosted open-source models (e.g., Qwen, GLM, Llama) via the vLLM framework, and fix several critical bugs related to model instance management and API requests. **Key changes and fixes:** 1. **Added Standard vLLM Provider (`vllm.go`, `vllm.json`):** - Implemented `VllmModel` driver strictly adhering to the OpenAI API specification. - Removed hardcoded and dangerous routing logic (e.g., forcing `AsyncChat` for Qwen/GLM prefixes), ensuring standard `/v1/chat/completions` compatibility. - Refactored `ListModels` to use safe JSON parsing (resolving nil pointer panics) and standard `GET` requests without bodies. - Added `APIConfig.Region` fallback logic to prevent empty `base_url` fetching when checking models. 2. **Fixed `ChatToModelStreamWithSender` Bug (`model_service.go`):** - Resolved the `model is disabled` error when streaming chat with local database-saved models. - Added the missing `if modelInfo.Status == "active"` block to correctly invoke `NewInstance` and inject the dynamic `base_url` into the provider driver before starting the SSE stream. 3. **Fixed `ListSupportedModels` Bug (`model_service.go`):** - Added dynamic `NewInstance` injection for `base_url`. Previously, the list models function used the static JSON config without injecting user-configured dynamic URLs from the database, resulting in an `unsupported protocol scheme ""` error. ### Type of change - [x] Bug Fix (non-breaking change which fixes an issue) - [x] New Feature (non-breaking change which adds functionality)
2026-04-30 16:30:14 +08:00
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
// Parse response
var modelList ModelList
if err = json.Unmarshal(body, &modelList); err != nil {
Go: implement provider: Vllm (#14532) ### What problem does this PR solve? Implement the vLLM model provider for RAGFlow to fully support local and self-hosted open-source models (e.g., Qwen, GLM, Llama) via the vLLM framework, and fix several critical bugs related to model instance management and API requests. **Key changes and fixes:** 1. **Added Standard vLLM Provider (`vllm.go`, `vllm.json`):** - Implemented `VllmModel` driver strictly adhering to the OpenAI API specification. - Removed hardcoded and dangerous routing logic (e.g., forcing `AsyncChat` for Qwen/GLM prefixes), ensuring standard `/v1/chat/completions` compatibility. - Refactored `ListModels` to use safe JSON parsing (resolving nil pointer panics) and standard `GET` requests without bodies. - Added `APIConfig.Region` fallback logic to prevent empty `base_url` fetching when checking models. 2. **Fixed `ChatToModelStreamWithSender` Bug (`model_service.go`):** - Resolved the `model is disabled` error when streaming chat with local database-saved models. - Added the missing `if modelInfo.Status == "active"` block to correctly invoke `NewInstance` and inject the dynamic `base_url` into the provider driver before starting the SSE stream. 3. **Fixed `ListSupportedModels` Bug (`model_service.go`):** - Added dynamic `NewInstance` injection for `base_url`. Previously, the list models function used the static JSON config without injecting user-configured dynamic URLs from the database, resulting in an `unsupported protocol scheme ""` error. ### Type of change - [x] Bug Fix (non-breaking change which fixes an issue) - [x] New Feature (non-breaking change which adds functionality)
2026-04-30 16:30:14 +08:00
return nil, fmt.Errorf("failed to parse response: %w", err)
}
if modelList.Models == nil {
return nil, fmt.Errorf("invalid models list format")
Go: implement provider: Vllm (#14532) ### What problem does this PR solve? Implement the vLLM model provider for RAGFlow to fully support local and self-hosted open-source models (e.g., Qwen, GLM, Llama) via the vLLM framework, and fix several critical bugs related to model instance management and API requests. **Key changes and fixes:** 1. **Added Standard vLLM Provider (`vllm.go`, `vllm.json`):** - Implemented `VllmModel` driver strictly adhering to the OpenAI API specification. - Removed hardcoded and dangerous routing logic (e.g., forcing `AsyncChat` for Qwen/GLM prefixes), ensuring standard `/v1/chat/completions` compatibility. - Refactored `ListModels` to use safe JSON parsing (resolving nil pointer panics) and standard `GET` requests without bodies. - Added `APIConfig.Region` fallback logic to prevent empty `base_url` fetching when checking models. 2. **Fixed `ChatToModelStreamWithSender` Bug (`model_service.go`):** - Resolved the `model is disabled` error when streaming chat with local database-saved models. - Added the missing `if modelInfo.Status == "active"` block to correctly invoke `NewInstance` and inject the dynamic `base_url` into the provider driver before starting the SSE stream. 3. **Fixed `ListSupportedModels` Bug (`model_service.go`):** - Added dynamic `NewInstance` injection for `base_url`. Previously, the list models function used the static JSON config without injecting user-configured dynamic URLs from the database, resulting in an `unsupported protocol scheme ""` error. ### Type of change - [x] Bug Fix (non-breaking change which fixes an issue) - [x] New Feature (non-breaking change which adds functionality)
2026-04-30 16:30:14 +08:00
}
return ParseListModel(modelList), nil
}
func (v *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 (v *VllmModel) CheckConnection(apiConfig *APIConfig) error {
_, err := v.ListModels(apiConfig)
return err
}
Go: implement Rerank in vLLM driver (#14878) (#14880) ### What problem does this PR solve? Closes #14878. `VllmModel.Rerank()` in [internal/entity/models/vllm.go:551](internal/entity/models/vllm.go#L551) is currently a stub returning `nil, fmt.Errorf("%s, Rerank not implemented", z.Name())`, and [conf/models/vllm.json](conf/models/vllm.json) is missing a `rerank` entry in `url_suffix`. Chat (long-standing) and embeddings (#14688) already work, so rerank is the last missing leg of the retrieval pipeline for operators running everything on a single self-hosted vLLM server — today they have to point rerank at a different provider, which defeats the point of a fully local deployment. Upstream vLLM has supported a Jina/Cohere-compatible `POST /v1/rerank` endpoint since v0.7 ([vllm-project/vllm#12376](https://github.com/vllm-project/vllm/pull/12376)). The request/response shape is essentially identical to the NVIDIA driver landed in #14778, so this PR mirrors that structure with two vLLM-specific adjustments. This PR replaces the stub with a real implementation against vLLM's `/v1/rerank`: - `POST {baseURL}/rerank` - Request body: `{"model": "<modelName>", "query": "<query>", "documents": [...], "top_n": <int>}` — documents are a flat `[]string`, **not** wrapped as `{text: "..."}` like NVIDIA's `/ranking`. - Response body: `{"results": [{"index": int, "relevance_score": float}, ...]}` (Jina-compatible; the optional `document` field is ignored since callers reconstruct text via `Index`). - `Authorization: Bearer <ApiKey>` is set **only when `APIConfig.ApiKey` is non-empty**, matching the existing `Embed`/`ListModels` behaviour in this file. vLLM is a local driver and can be deployed without an API key. The return shape matches the existing `*RerankResponse` contract used by the NVIDIA ([nvidia.go:461](internal/entity/models/nvidia.go#L461)), Aliyun ([aliyun.go:507](internal/entity/models/aliyun.go#L507)), and ZhipuAI ([zhipu-ai.go:554](internal/entity/models/zhipu-ai.go#L554)) drivers, i.e. `Data []RerankResult` carrying `{Index, RelevanceScore}` in the API's ranking order. Callers that need original-input order sort by `Index`. Behaviour requirements from the issue, all covered: 1. Empty `documents` → returns `&RerankResponse{}` without an HTTP call. 2. Missing `modelName` → `"model name is required"` validation error. 3. `rerankConfig.TopN` honored when `0 < TopN < len(documents)`; otherwise `top_n` defaults to `len(documents)` so callers get a score per input. 4. Non-200 responses return an error including upstream status and body (`"vLLM rerank API error: <status>, body: <body>"`). 5. Response `index` values are bounds-checked against `len(documents)`. **Scope:** - [internal/entity/models/vllm.go](internal/entity/models/vllm.go) — replaces the `Rerank` stub at line 551 with a real implementation; adds `vllmRerankRequest`/`vllmRerankResponse` types for the slim subset of the payload we need. Region/baseURL resolution, 30s context timeout, conditional bearer header, and error wrapping all follow the existing patterns in this file. - [conf/models/vllm.json](conf/models/vllm.json) — adds `"rerank": "rerank"` to `url_suffix`, joined to the operator-configured vLLM base URL the same way the NVIDIA driver joins at [nvidia.go:485](internal/entity/models/nvidia.go#L485). - [internal/entity/models/vllm_rerank_test.go](internal/entity/models/vllm_rerank_test.go) — adds 7 `httptest`-backed tests mirroring `nvidia_rerank_test.go`: happy path (out-of-order ranking → Index preservation), `top_n` clamp to `RerankConfig.TopN`, empty-documents short-circuit, missing-model-name validation, HTTP error propagation, out-of-range index rejection, and a vLLM-specific `TestVllmRerankWithoutAPIKey` locking in the optional-auth behaviour that distinguishes this driver from NVIDIA. **Out of scope:** no interface change, no DDL, no frontend change. Chat, embeddings, and balance paths are untouched. No new user-facing docs required beyond the existing rerank model setup page — vLLM joins the list of providers whose rerank model can be selected once `/v1/rerank` is exposed by the server. ### Type of change - [x] New Feature (non-breaking change which adds functionality)
2026-05-14 22:27:22 -07:00
// 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 (v *VllmModel) Rerank(modelName *string, query string, documents []string, apiConfig *APIConfig, rerankConfig *RerankConfig) (*RerankResponse, error) {
if err := v.baseModel.APIConfigCheck(apiConfig); err != nil {
return nil, err
}
Go: implement Rerank in vLLM driver (#14878) (#14880) ### What problem does this PR solve? Closes #14878. `VllmModel.Rerank()` in [internal/entity/models/vllm.go:551](internal/entity/models/vllm.go#L551) is currently a stub returning `nil, fmt.Errorf("%s, Rerank not implemented", z.Name())`, and [conf/models/vllm.json](conf/models/vllm.json) is missing a `rerank` entry in `url_suffix`. Chat (long-standing) and embeddings (#14688) already work, so rerank is the last missing leg of the retrieval pipeline for operators running everything on a single self-hosted vLLM server — today they have to point rerank at a different provider, which defeats the point of a fully local deployment. Upstream vLLM has supported a Jina/Cohere-compatible `POST /v1/rerank` endpoint since v0.7 ([vllm-project/vllm#12376](https://github.com/vllm-project/vllm/pull/12376)). The request/response shape is essentially identical to the NVIDIA driver landed in #14778, so this PR mirrors that structure with two vLLM-specific adjustments. This PR replaces the stub with a real implementation against vLLM's `/v1/rerank`: - `POST {baseURL}/rerank` - Request body: `{"model": "<modelName>", "query": "<query>", "documents": [...], "top_n": <int>}` — documents are a flat `[]string`, **not** wrapped as `{text: "..."}` like NVIDIA's `/ranking`. - Response body: `{"results": [{"index": int, "relevance_score": float}, ...]}` (Jina-compatible; the optional `document` field is ignored since callers reconstruct text via `Index`). - `Authorization: Bearer <ApiKey>` is set **only when `APIConfig.ApiKey` is non-empty**, matching the existing `Embed`/`ListModels` behaviour in this file. vLLM is a local driver and can be deployed without an API key. The return shape matches the existing `*RerankResponse` contract used by the NVIDIA ([nvidia.go:461](internal/entity/models/nvidia.go#L461)), Aliyun ([aliyun.go:507](internal/entity/models/aliyun.go#L507)), and ZhipuAI ([zhipu-ai.go:554](internal/entity/models/zhipu-ai.go#L554)) drivers, i.e. `Data []RerankResult` carrying `{Index, RelevanceScore}` in the API's ranking order. Callers that need original-input order sort by `Index`. Behaviour requirements from the issue, all covered: 1. Empty `documents` → returns `&RerankResponse{}` without an HTTP call. 2. Missing `modelName` → `"model name is required"` validation error. 3. `rerankConfig.TopN` honored when `0 < TopN < len(documents)`; otherwise `top_n` defaults to `len(documents)` so callers get a score per input. 4. Non-200 responses return an error including upstream status and body (`"vLLM rerank API error: <status>, body: <body>"`). 5. Response `index` values are bounds-checked against `len(documents)`. **Scope:** - [internal/entity/models/vllm.go](internal/entity/models/vllm.go) — replaces the `Rerank` stub at line 551 with a real implementation; adds `vllmRerankRequest`/`vllmRerankResponse` types for the slim subset of the payload we need. Region/baseURL resolution, 30s context timeout, conditional bearer header, and error wrapping all follow the existing patterns in this file. - [conf/models/vllm.json](conf/models/vllm.json) — adds `"rerank": "rerank"` to `url_suffix`, joined to the operator-configured vLLM base URL the same way the NVIDIA driver joins at [nvidia.go:485](internal/entity/models/nvidia.go#L485). - [internal/entity/models/vllm_rerank_test.go](internal/entity/models/vllm_rerank_test.go) — adds 7 `httptest`-backed tests mirroring `nvidia_rerank_test.go`: happy path (out-of-order ranking → Index preservation), `top_n` clamp to `RerankConfig.TopN`, empty-documents short-circuit, missing-model-name validation, HTTP error propagation, out-of-range index rejection, and a vLLM-specific `TestVllmRerankWithoutAPIKey` locking in the optional-auth behaviour that distinguishes this driver from NVIDIA. **Out of scope:** no interface change, no DDL, no frontend change. Chat, embeddings, and balance paths are untouched. No new user-facing docs required beyond the existing rerank model setup page — vLLM joins the list of providers whose rerank model can be selected once `/v1/rerank` is exposed by the server. ### Type of change - [x] New Feature (non-breaking change which adds functionality)
2026-05-14 22:27:22 -07:00
if len(documents) == 0 {
return &RerankResponse{}, nil
}
if modelName == nil || *modelName == "" {
return nil, fmt.Errorf("model name is required")
}
resolvedBaseURL, err := v.baseModel.GetBaseURL(apiConfig)
if err != nil {
return nil, err
Go: implement Rerank in vLLM driver (#14878) (#14880) ### What problem does this PR solve? Closes #14878. `VllmModel.Rerank()` in [internal/entity/models/vllm.go:551](internal/entity/models/vllm.go#L551) is currently a stub returning `nil, fmt.Errorf("%s, Rerank not implemented", z.Name())`, and [conf/models/vllm.json](conf/models/vllm.json) is missing a `rerank` entry in `url_suffix`. Chat (long-standing) and embeddings (#14688) already work, so rerank is the last missing leg of the retrieval pipeline for operators running everything on a single self-hosted vLLM server — today they have to point rerank at a different provider, which defeats the point of a fully local deployment. Upstream vLLM has supported a Jina/Cohere-compatible `POST /v1/rerank` endpoint since v0.7 ([vllm-project/vllm#12376](https://github.com/vllm-project/vllm/pull/12376)). The request/response shape is essentially identical to the NVIDIA driver landed in #14778, so this PR mirrors that structure with two vLLM-specific adjustments. This PR replaces the stub with a real implementation against vLLM's `/v1/rerank`: - `POST {baseURL}/rerank` - Request body: `{"model": "<modelName>", "query": "<query>", "documents": [...], "top_n": <int>}` — documents are a flat `[]string`, **not** wrapped as `{text: "..."}` like NVIDIA's `/ranking`. - Response body: `{"results": [{"index": int, "relevance_score": float}, ...]}` (Jina-compatible; the optional `document` field is ignored since callers reconstruct text via `Index`). - `Authorization: Bearer <ApiKey>` is set **only when `APIConfig.ApiKey` is non-empty**, matching the existing `Embed`/`ListModels` behaviour in this file. vLLM is a local driver and can be deployed without an API key. The return shape matches the existing `*RerankResponse` contract used by the NVIDIA ([nvidia.go:461](internal/entity/models/nvidia.go#L461)), Aliyun ([aliyun.go:507](internal/entity/models/aliyun.go#L507)), and ZhipuAI ([zhipu-ai.go:554](internal/entity/models/zhipu-ai.go#L554)) drivers, i.e. `Data []RerankResult` carrying `{Index, RelevanceScore}` in the API's ranking order. Callers that need original-input order sort by `Index`. Behaviour requirements from the issue, all covered: 1. Empty `documents` → returns `&RerankResponse{}` without an HTTP call. 2. Missing `modelName` → `"model name is required"` validation error. 3. `rerankConfig.TopN` honored when `0 < TopN < len(documents)`; otherwise `top_n` defaults to `len(documents)` so callers get a score per input. 4. Non-200 responses return an error including upstream status and body (`"vLLM rerank API error: <status>, body: <body>"`). 5. Response `index` values are bounds-checked against `len(documents)`. **Scope:** - [internal/entity/models/vllm.go](internal/entity/models/vllm.go) — replaces the `Rerank` stub at line 551 with a real implementation; adds `vllmRerankRequest`/`vllmRerankResponse` types for the slim subset of the payload we need. Region/baseURL resolution, 30s context timeout, conditional bearer header, and error wrapping all follow the existing patterns in this file. - [conf/models/vllm.json](conf/models/vllm.json) — adds `"rerank": "rerank"` to `url_suffix`, joined to the operator-configured vLLM base URL the same way the NVIDIA driver joins at [nvidia.go:485](internal/entity/models/nvidia.go#L485). - [internal/entity/models/vllm_rerank_test.go](internal/entity/models/vllm_rerank_test.go) — adds 7 `httptest`-backed tests mirroring `nvidia_rerank_test.go`: happy path (out-of-order ranking → Index preservation), `top_n` clamp to `RerankConfig.TopN`, empty-documents short-circuit, missing-model-name validation, HTTP error propagation, out-of-range index rejection, and a vLLM-specific `TestVllmRerankWithoutAPIKey` locking in the optional-auth behaviour that distinguishes this driver from NVIDIA. **Out of scope:** no interface change, no DDL, no frontend change. Chat, embeddings, and balance paths are untouched. No new user-facing docs required beyond the existing rerank model setup page — vLLM joins the list of providers whose rerank model can be selected once `/v1/rerank` is exposed by the server. ### Type of change - [x] New Feature (non-breaking change which adds functionality)
2026-05-14 22:27:22 -07:00
}
baseURL := resolvedBaseURL
Go: implement Rerank in vLLM driver (#14878) (#14880) ### What problem does this PR solve? Closes #14878. `VllmModel.Rerank()` in [internal/entity/models/vllm.go:551](internal/entity/models/vllm.go#L551) is currently a stub returning `nil, fmt.Errorf("%s, Rerank not implemented", z.Name())`, and [conf/models/vllm.json](conf/models/vllm.json) is missing a `rerank` entry in `url_suffix`. Chat (long-standing) and embeddings (#14688) already work, so rerank is the last missing leg of the retrieval pipeline for operators running everything on a single self-hosted vLLM server — today they have to point rerank at a different provider, which defeats the point of a fully local deployment. Upstream vLLM has supported a Jina/Cohere-compatible `POST /v1/rerank` endpoint since v0.7 ([vllm-project/vllm#12376](https://github.com/vllm-project/vllm/pull/12376)). The request/response shape is essentially identical to the NVIDIA driver landed in #14778, so this PR mirrors that structure with two vLLM-specific adjustments. This PR replaces the stub with a real implementation against vLLM's `/v1/rerank`: - `POST {baseURL}/rerank` - Request body: `{"model": "<modelName>", "query": "<query>", "documents": [...], "top_n": <int>}` — documents are a flat `[]string`, **not** wrapped as `{text: "..."}` like NVIDIA's `/ranking`. - Response body: `{"results": [{"index": int, "relevance_score": float}, ...]}` (Jina-compatible; the optional `document` field is ignored since callers reconstruct text via `Index`). - `Authorization: Bearer <ApiKey>` is set **only when `APIConfig.ApiKey` is non-empty**, matching the existing `Embed`/`ListModels` behaviour in this file. vLLM is a local driver and can be deployed without an API key. The return shape matches the existing `*RerankResponse` contract used by the NVIDIA ([nvidia.go:461](internal/entity/models/nvidia.go#L461)), Aliyun ([aliyun.go:507](internal/entity/models/aliyun.go#L507)), and ZhipuAI ([zhipu-ai.go:554](internal/entity/models/zhipu-ai.go#L554)) drivers, i.e. `Data []RerankResult` carrying `{Index, RelevanceScore}` in the API's ranking order. Callers that need original-input order sort by `Index`. Behaviour requirements from the issue, all covered: 1. Empty `documents` → returns `&RerankResponse{}` without an HTTP call. 2. Missing `modelName` → `"model name is required"` validation error. 3. `rerankConfig.TopN` honored when `0 < TopN < len(documents)`; otherwise `top_n` defaults to `len(documents)` so callers get a score per input. 4. Non-200 responses return an error including upstream status and body (`"vLLM rerank API error: <status>, body: <body>"`). 5. Response `index` values are bounds-checked against `len(documents)`. **Scope:** - [internal/entity/models/vllm.go](internal/entity/models/vllm.go) — replaces the `Rerank` stub at line 551 with a real implementation; adds `vllmRerankRequest`/`vllmRerankResponse` types for the slim subset of the payload we need. Region/baseURL resolution, 30s context timeout, conditional bearer header, and error wrapping all follow the existing patterns in this file. - [conf/models/vllm.json](conf/models/vllm.json) — adds `"rerank": "rerank"` to `url_suffix`, joined to the operator-configured vLLM base URL the same way the NVIDIA driver joins at [nvidia.go:485](internal/entity/models/nvidia.go#L485). - [internal/entity/models/vllm_rerank_test.go](internal/entity/models/vllm_rerank_test.go) — adds 7 `httptest`-backed tests mirroring `nvidia_rerank_test.go`: happy path (out-of-order ranking → Index preservation), `top_n` clamp to `RerankConfig.TopN`, empty-documents short-circuit, missing-model-name validation, HTTP error propagation, out-of-range index rejection, and a vLLM-specific `TestVllmRerankWithoutAPIKey` locking in the optional-auth behaviour that distinguishes this driver from NVIDIA. **Out of scope:** no interface change, no DDL, no frontend change. Chat, embeddings, and balance paths are untouched. No new user-facing docs required beyond the existing rerank model setup page — vLLM joins the list of providers whose rerank model can be selected once `/v1/rerank` is exposed by the server. ### Type of change - [x] New Feature (non-breaking change which adds functionality)
2026-05-14 22:27:22 -07:00
if baseURL == "" {
baseURL = resolvedBaseURL
Go: implement Rerank in vLLM driver (#14878) (#14880) ### What problem does this PR solve? Closes #14878. `VllmModel.Rerank()` in [internal/entity/models/vllm.go:551](internal/entity/models/vllm.go#L551) is currently a stub returning `nil, fmt.Errorf("%s, Rerank not implemented", z.Name())`, and [conf/models/vllm.json](conf/models/vllm.json) is missing a `rerank` entry in `url_suffix`. Chat (long-standing) and embeddings (#14688) already work, so rerank is the last missing leg of the retrieval pipeline for operators running everything on a single self-hosted vLLM server — today they have to point rerank at a different provider, which defeats the point of a fully local deployment. Upstream vLLM has supported a Jina/Cohere-compatible `POST /v1/rerank` endpoint since v0.7 ([vllm-project/vllm#12376](https://github.com/vllm-project/vllm/pull/12376)). The request/response shape is essentially identical to the NVIDIA driver landed in #14778, so this PR mirrors that structure with two vLLM-specific adjustments. This PR replaces the stub with a real implementation against vLLM's `/v1/rerank`: - `POST {baseURL}/rerank` - Request body: `{"model": "<modelName>", "query": "<query>", "documents": [...], "top_n": <int>}` — documents are a flat `[]string`, **not** wrapped as `{text: "..."}` like NVIDIA's `/ranking`. - Response body: `{"results": [{"index": int, "relevance_score": float}, ...]}` (Jina-compatible; the optional `document` field is ignored since callers reconstruct text via `Index`). - `Authorization: Bearer <ApiKey>` is set **only when `APIConfig.ApiKey` is non-empty**, matching the existing `Embed`/`ListModels` behaviour in this file. vLLM is a local driver and can be deployed without an API key. The return shape matches the existing `*RerankResponse` contract used by the NVIDIA ([nvidia.go:461](internal/entity/models/nvidia.go#L461)), Aliyun ([aliyun.go:507](internal/entity/models/aliyun.go#L507)), and ZhipuAI ([zhipu-ai.go:554](internal/entity/models/zhipu-ai.go#L554)) drivers, i.e. `Data []RerankResult` carrying `{Index, RelevanceScore}` in the API's ranking order. Callers that need original-input order sort by `Index`. Behaviour requirements from the issue, all covered: 1. Empty `documents` → returns `&RerankResponse{}` without an HTTP call. 2. Missing `modelName` → `"model name is required"` validation error. 3. `rerankConfig.TopN` honored when `0 < TopN < len(documents)`; otherwise `top_n` defaults to `len(documents)` so callers get a score per input. 4. Non-200 responses return an error including upstream status and body (`"vLLM rerank API error: <status>, body: <body>"`). 5. Response `index` values are bounds-checked against `len(documents)`. **Scope:** - [internal/entity/models/vllm.go](internal/entity/models/vllm.go) — replaces the `Rerank` stub at line 551 with a real implementation; adds `vllmRerankRequest`/`vllmRerankResponse` types for the slim subset of the payload we need. Region/baseURL resolution, 30s context timeout, conditional bearer header, and error wrapping all follow the existing patterns in this file. - [conf/models/vllm.json](conf/models/vllm.json) — adds `"rerank": "rerank"` to `url_suffix`, joined to the operator-configured vLLM base URL the same way the NVIDIA driver joins at [nvidia.go:485](internal/entity/models/nvidia.go#L485). - [internal/entity/models/vllm_rerank_test.go](internal/entity/models/vllm_rerank_test.go) — adds 7 `httptest`-backed tests mirroring `nvidia_rerank_test.go`: happy path (out-of-order ranking → Index preservation), `top_n` clamp to `RerankConfig.TopN`, empty-documents short-circuit, missing-model-name validation, HTTP error propagation, out-of-range index rejection, and a vLLM-specific `TestVllmRerankWithoutAPIKey` locking in the optional-auth behaviour that distinguishes this driver from NVIDIA. **Out of scope:** no interface change, no DDL, no frontend change. Chat, embeddings, and balance paths are untouched. No new user-facing docs required beyond the existing rerank model setup page — vLLM joins the list of providers whose rerank model can be selected once `/v1/rerank` is exposed by the server. ### Type of change - [x] New Feature (non-breaking change which adds functionality)
2026-05-14 22:27:22 -07:00
}
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, "/"), v.baseModel.URLSuffix.Rerank)
Go: implement Rerank in vLLM driver (#14878) (#14880) ### What problem does this PR solve? Closes #14878. `VllmModel.Rerank()` in [internal/entity/models/vllm.go:551](internal/entity/models/vllm.go#L551) is currently a stub returning `nil, fmt.Errorf("%s, Rerank not implemented", z.Name())`, and [conf/models/vllm.json](conf/models/vllm.json) is missing a `rerank` entry in `url_suffix`. Chat (long-standing) and embeddings (#14688) already work, so rerank is the last missing leg of the retrieval pipeline for operators running everything on a single self-hosted vLLM server — today they have to point rerank at a different provider, which defeats the point of a fully local deployment. Upstream vLLM has supported a Jina/Cohere-compatible `POST /v1/rerank` endpoint since v0.7 ([vllm-project/vllm#12376](https://github.com/vllm-project/vllm/pull/12376)). The request/response shape is essentially identical to the NVIDIA driver landed in #14778, so this PR mirrors that structure with two vLLM-specific adjustments. This PR replaces the stub with a real implementation against vLLM's `/v1/rerank`: - `POST {baseURL}/rerank` - Request body: `{"model": "<modelName>", "query": "<query>", "documents": [...], "top_n": <int>}` — documents are a flat `[]string`, **not** wrapped as `{text: "..."}` like NVIDIA's `/ranking`. - Response body: `{"results": [{"index": int, "relevance_score": float}, ...]}` (Jina-compatible; the optional `document` field is ignored since callers reconstruct text via `Index`). - `Authorization: Bearer <ApiKey>` is set **only when `APIConfig.ApiKey` is non-empty**, matching the existing `Embed`/`ListModels` behaviour in this file. vLLM is a local driver and can be deployed without an API key. The return shape matches the existing `*RerankResponse` contract used by the NVIDIA ([nvidia.go:461](internal/entity/models/nvidia.go#L461)), Aliyun ([aliyun.go:507](internal/entity/models/aliyun.go#L507)), and ZhipuAI ([zhipu-ai.go:554](internal/entity/models/zhipu-ai.go#L554)) drivers, i.e. `Data []RerankResult` carrying `{Index, RelevanceScore}` in the API's ranking order. Callers that need original-input order sort by `Index`. Behaviour requirements from the issue, all covered: 1. Empty `documents` → returns `&RerankResponse{}` without an HTTP call. 2. Missing `modelName` → `"model name is required"` validation error. 3. `rerankConfig.TopN` honored when `0 < TopN < len(documents)`; otherwise `top_n` defaults to `len(documents)` so callers get a score per input. 4. Non-200 responses return an error including upstream status and body (`"vLLM rerank API error: <status>, body: <body>"`). 5. Response `index` values are bounds-checked against `len(documents)`. **Scope:** - [internal/entity/models/vllm.go](internal/entity/models/vllm.go) — replaces the `Rerank` stub at line 551 with a real implementation; adds `vllmRerankRequest`/`vllmRerankResponse` types for the slim subset of the payload we need. Region/baseURL resolution, 30s context timeout, conditional bearer header, and error wrapping all follow the existing patterns in this file. - [conf/models/vllm.json](conf/models/vllm.json) — adds `"rerank": "rerank"` to `url_suffix`, joined to the operator-configured vLLM base URL the same way the NVIDIA driver joins at [nvidia.go:485](internal/entity/models/nvidia.go#L485). - [internal/entity/models/vllm_rerank_test.go](internal/entity/models/vllm_rerank_test.go) — adds 7 `httptest`-backed tests mirroring `nvidia_rerank_test.go`: happy path (out-of-order ranking → Index preservation), `top_n` clamp to `RerankConfig.TopN`, empty-documents short-circuit, missing-model-name validation, HTTP error propagation, out-of-range index rejection, and a vLLM-specific `TestVllmRerankWithoutAPIKey` locking in the optional-auth behaviour that distinguishes this driver from NVIDIA. **Out of scope:** no interface change, no DDL, no frontend change. Chat, embeddings, and balance paths are untouched. No new user-facing docs required beyond the existing rerank model setup page — vLLM joins the list of providers whose rerank model can be selected once `/v1/rerank` is exposed by the server. ### Type of change - [x] New Feature (non-breaking change which adds functionality)
2026-05-14 22:27:22 -07:00
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(), nonStreamCallTimeout)
Go: implement Rerank in vLLM driver (#14878) (#14880) ### What problem does this PR solve? Closes #14878. `VllmModel.Rerank()` in [internal/entity/models/vllm.go:551](internal/entity/models/vllm.go#L551) is currently a stub returning `nil, fmt.Errorf("%s, Rerank not implemented", z.Name())`, and [conf/models/vllm.json](conf/models/vllm.json) is missing a `rerank` entry in `url_suffix`. Chat (long-standing) and embeddings (#14688) already work, so rerank is the last missing leg of the retrieval pipeline for operators running everything on a single self-hosted vLLM server — today they have to point rerank at a different provider, which defeats the point of a fully local deployment. Upstream vLLM has supported a Jina/Cohere-compatible `POST /v1/rerank` endpoint since v0.7 ([vllm-project/vllm#12376](https://github.com/vllm-project/vllm/pull/12376)). The request/response shape is essentially identical to the NVIDIA driver landed in #14778, so this PR mirrors that structure with two vLLM-specific adjustments. This PR replaces the stub with a real implementation against vLLM's `/v1/rerank`: - `POST {baseURL}/rerank` - Request body: `{"model": "<modelName>", "query": "<query>", "documents": [...], "top_n": <int>}` — documents are a flat `[]string`, **not** wrapped as `{text: "..."}` like NVIDIA's `/ranking`. - Response body: `{"results": [{"index": int, "relevance_score": float}, ...]}` (Jina-compatible; the optional `document` field is ignored since callers reconstruct text via `Index`). - `Authorization: Bearer <ApiKey>` is set **only when `APIConfig.ApiKey` is non-empty**, matching the existing `Embed`/`ListModels` behaviour in this file. vLLM is a local driver and can be deployed without an API key. The return shape matches the existing `*RerankResponse` contract used by the NVIDIA ([nvidia.go:461](internal/entity/models/nvidia.go#L461)), Aliyun ([aliyun.go:507](internal/entity/models/aliyun.go#L507)), and ZhipuAI ([zhipu-ai.go:554](internal/entity/models/zhipu-ai.go#L554)) drivers, i.e. `Data []RerankResult` carrying `{Index, RelevanceScore}` in the API's ranking order. Callers that need original-input order sort by `Index`. Behaviour requirements from the issue, all covered: 1. Empty `documents` → returns `&RerankResponse{}` without an HTTP call. 2. Missing `modelName` → `"model name is required"` validation error. 3. `rerankConfig.TopN` honored when `0 < TopN < len(documents)`; otherwise `top_n` defaults to `len(documents)` so callers get a score per input. 4. Non-200 responses return an error including upstream status and body (`"vLLM rerank API error: <status>, body: <body>"`). 5. Response `index` values are bounds-checked against `len(documents)`. **Scope:** - [internal/entity/models/vllm.go](internal/entity/models/vllm.go) — replaces the `Rerank` stub at line 551 with a real implementation; adds `vllmRerankRequest`/`vllmRerankResponse` types for the slim subset of the payload we need. Region/baseURL resolution, 30s context timeout, conditional bearer header, and error wrapping all follow the existing patterns in this file. - [conf/models/vllm.json](conf/models/vllm.json) — adds `"rerank": "rerank"` to `url_suffix`, joined to the operator-configured vLLM base URL the same way the NVIDIA driver joins at [nvidia.go:485](internal/entity/models/nvidia.go#L485). - [internal/entity/models/vllm_rerank_test.go](internal/entity/models/vllm_rerank_test.go) — adds 7 `httptest`-backed tests mirroring `nvidia_rerank_test.go`: happy path (out-of-order ranking → Index preservation), `top_n` clamp to `RerankConfig.TopN`, empty-documents short-circuit, missing-model-name validation, HTTP error propagation, out-of-range index rejection, and a vLLM-specific `TestVllmRerankWithoutAPIKey` locking in the optional-auth behaviour that distinguishes this driver from NVIDIA. **Out of scope:** no interface change, no DDL, no frontend change. Chat, embeddings, and balance paths are untouched. No new user-facing docs required beyond the existing rerank model setup page — vLLM joins the list of providers whose rerank model can be selected once `/v1/rerank` is exposed by the server. ### Type of change - [x] New Feature (non-breaking change which adds functionality)
2026-05-14 22:27:22 -07:00
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 auth := BearerAuth(apiConfig); auth != "" {
req.Header.Set("Authorization", auth)
}
Go: implement Rerank in vLLM driver (#14878) (#14880) ### What problem does this PR solve? Closes #14878. `VllmModel.Rerank()` in [internal/entity/models/vllm.go:551](internal/entity/models/vllm.go#L551) is currently a stub returning `nil, fmt.Errorf("%s, Rerank not implemented", z.Name())`, and [conf/models/vllm.json](conf/models/vllm.json) is missing a `rerank` entry in `url_suffix`. Chat (long-standing) and embeddings (#14688) already work, so rerank is the last missing leg of the retrieval pipeline for operators running everything on a single self-hosted vLLM server — today they have to point rerank at a different provider, which defeats the point of a fully local deployment. Upstream vLLM has supported a Jina/Cohere-compatible `POST /v1/rerank` endpoint since v0.7 ([vllm-project/vllm#12376](https://github.com/vllm-project/vllm/pull/12376)). The request/response shape is essentially identical to the NVIDIA driver landed in #14778, so this PR mirrors that structure with two vLLM-specific adjustments. This PR replaces the stub with a real implementation against vLLM's `/v1/rerank`: - `POST {baseURL}/rerank` - Request body: `{"model": "<modelName>", "query": "<query>", "documents": [...], "top_n": <int>}` — documents are a flat `[]string`, **not** wrapped as `{text: "..."}` like NVIDIA's `/ranking`. - Response body: `{"results": [{"index": int, "relevance_score": float}, ...]}` (Jina-compatible; the optional `document` field is ignored since callers reconstruct text via `Index`). - `Authorization: Bearer <ApiKey>` is set **only when `APIConfig.ApiKey` is non-empty**, matching the existing `Embed`/`ListModels` behaviour in this file. vLLM is a local driver and can be deployed without an API key. The return shape matches the existing `*RerankResponse` contract used by the NVIDIA ([nvidia.go:461](internal/entity/models/nvidia.go#L461)), Aliyun ([aliyun.go:507](internal/entity/models/aliyun.go#L507)), and ZhipuAI ([zhipu-ai.go:554](internal/entity/models/zhipu-ai.go#L554)) drivers, i.e. `Data []RerankResult` carrying `{Index, RelevanceScore}` in the API's ranking order. Callers that need original-input order sort by `Index`. Behaviour requirements from the issue, all covered: 1. Empty `documents` → returns `&RerankResponse{}` without an HTTP call. 2. Missing `modelName` → `"model name is required"` validation error. 3. `rerankConfig.TopN` honored when `0 < TopN < len(documents)`; otherwise `top_n` defaults to `len(documents)` so callers get a score per input. 4. Non-200 responses return an error including upstream status and body (`"vLLM rerank API error: <status>, body: <body>"`). 5. Response `index` values are bounds-checked against `len(documents)`. **Scope:** - [internal/entity/models/vllm.go](internal/entity/models/vllm.go) — replaces the `Rerank` stub at line 551 with a real implementation; adds `vllmRerankRequest`/`vllmRerankResponse` types for the slim subset of the payload we need. Region/baseURL resolution, 30s context timeout, conditional bearer header, and error wrapping all follow the existing patterns in this file. - [conf/models/vllm.json](conf/models/vllm.json) — adds `"rerank": "rerank"` to `url_suffix`, joined to the operator-configured vLLM base URL the same way the NVIDIA driver joins at [nvidia.go:485](internal/entity/models/nvidia.go#L485). - [internal/entity/models/vllm_rerank_test.go](internal/entity/models/vllm_rerank_test.go) — adds 7 `httptest`-backed tests mirroring `nvidia_rerank_test.go`: happy path (out-of-order ranking → Index preservation), `top_n` clamp to `RerankConfig.TopN`, empty-documents short-circuit, missing-model-name validation, HTTP error propagation, out-of-range index rejection, and a vLLM-specific `TestVllmRerankWithoutAPIKey` locking in the optional-auth behaviour that distinguishes this driver from NVIDIA. **Out of scope:** no interface change, no DDL, no frontend change. Chat, embeddings, and balance paths are untouched. No new user-facing docs required beyond the existing rerank model setup page — vLLM joins the list of providers whose rerank model can be selected once `/v1/rerank` is exposed by the server. ### Type of change - [x] New Feature (non-breaking change which adds functionality)
2026-05-14 22:27:22 -07:00
resp, err := v.baseModel.httpClient.Do(req)
Go: implement Rerank in vLLM driver (#14878) (#14880) ### What problem does this PR solve? Closes #14878. `VllmModel.Rerank()` in [internal/entity/models/vllm.go:551](internal/entity/models/vllm.go#L551) is currently a stub returning `nil, fmt.Errorf("%s, Rerank not implemented", z.Name())`, and [conf/models/vllm.json](conf/models/vllm.json) is missing a `rerank` entry in `url_suffix`. Chat (long-standing) and embeddings (#14688) already work, so rerank is the last missing leg of the retrieval pipeline for operators running everything on a single self-hosted vLLM server — today they have to point rerank at a different provider, which defeats the point of a fully local deployment. Upstream vLLM has supported a Jina/Cohere-compatible `POST /v1/rerank` endpoint since v0.7 ([vllm-project/vllm#12376](https://github.com/vllm-project/vllm/pull/12376)). The request/response shape is essentially identical to the NVIDIA driver landed in #14778, so this PR mirrors that structure with two vLLM-specific adjustments. This PR replaces the stub with a real implementation against vLLM's `/v1/rerank`: - `POST {baseURL}/rerank` - Request body: `{"model": "<modelName>", "query": "<query>", "documents": [...], "top_n": <int>}` — documents are a flat `[]string`, **not** wrapped as `{text: "..."}` like NVIDIA's `/ranking`. - Response body: `{"results": [{"index": int, "relevance_score": float}, ...]}` (Jina-compatible; the optional `document` field is ignored since callers reconstruct text via `Index`). - `Authorization: Bearer <ApiKey>` is set **only when `APIConfig.ApiKey` is non-empty**, matching the existing `Embed`/`ListModels` behaviour in this file. vLLM is a local driver and can be deployed without an API key. The return shape matches the existing `*RerankResponse` contract used by the NVIDIA ([nvidia.go:461](internal/entity/models/nvidia.go#L461)), Aliyun ([aliyun.go:507](internal/entity/models/aliyun.go#L507)), and ZhipuAI ([zhipu-ai.go:554](internal/entity/models/zhipu-ai.go#L554)) drivers, i.e. `Data []RerankResult` carrying `{Index, RelevanceScore}` in the API's ranking order. Callers that need original-input order sort by `Index`. Behaviour requirements from the issue, all covered: 1. Empty `documents` → returns `&RerankResponse{}` without an HTTP call. 2. Missing `modelName` → `"model name is required"` validation error. 3. `rerankConfig.TopN` honored when `0 < TopN < len(documents)`; otherwise `top_n` defaults to `len(documents)` so callers get a score per input. 4. Non-200 responses return an error including upstream status and body (`"vLLM rerank API error: <status>, body: <body>"`). 5. Response `index` values are bounds-checked against `len(documents)`. **Scope:** - [internal/entity/models/vllm.go](internal/entity/models/vllm.go) — replaces the `Rerank` stub at line 551 with a real implementation; adds `vllmRerankRequest`/`vllmRerankResponse` types for the slim subset of the payload we need. Region/baseURL resolution, 30s context timeout, conditional bearer header, and error wrapping all follow the existing patterns in this file. - [conf/models/vllm.json](conf/models/vllm.json) — adds `"rerank": "rerank"` to `url_suffix`, joined to the operator-configured vLLM base URL the same way the NVIDIA driver joins at [nvidia.go:485](internal/entity/models/nvidia.go#L485). - [internal/entity/models/vllm_rerank_test.go](internal/entity/models/vllm_rerank_test.go) — adds 7 `httptest`-backed tests mirroring `nvidia_rerank_test.go`: happy path (out-of-order ranking → Index preservation), `top_n` clamp to `RerankConfig.TopN`, empty-documents short-circuit, missing-model-name validation, HTTP error propagation, out-of-range index rejection, and a vLLM-specific `TestVllmRerankWithoutAPIKey` locking in the optional-auth behaviour that distinguishes this driver from NVIDIA. **Out of scope:** no interface change, no DDL, no frontend change. Chat, embeddings, and balance paths are untouched. No new user-facing docs required beyond the existing rerank model setup page — vLLM joins the list of providers whose rerank model can be selected once `/v1/rerank` is exposed by the server. ### Type of change - [x] New Feature (non-breaking change which adds functionality)
2026-05-14 22:27:22 -07:00
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 (v *VllmModel) TranscribeAudio(modelName *string, file *string, apiConfig *APIConfig, asrConfig *ASRConfig) (*ASRResponse, error) {
return nil, fmt.Errorf("%s, no such method", v.Name())
}
func (v *VllmModel) TranscribeAudioWithSender(modelName *string, file *string, apiConfig *APIConfig, asrConfig *ASRConfig, sender func(*string, *string) error) error {
return fmt.Errorf("%s, no such method", v.Name())
}
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
// AudioSpeech convert text to audio
func (v *VllmModel) AudioSpeech(modelName *string, audioContent *string, apiConfig *APIConfig, ttsConfig *TTSConfig) (*TTSResponse, error) {
return nil, fmt.Errorf("%s, no such method", v.Name())
}
func (v *VllmModel) AudioSpeechWithSender(modelName *string, audioContent *string, apiConfig *APIConfig, ttsConfig *TTSConfig, sender func(*string, *string) error) error {
return fmt.Errorf("%s, no such method", v.Name())
}
// OCRFile OCR file
func (v *VllmModel) OCRFile(modelName *string, content []byte, url *string, apiConfig *APIConfig, ocrConfig *OCRConfig) (*OCRFileResponse, error) {
return nil, fmt.Errorf("%s, no such method", v.Name())
}
Go: add file parse command (#14892) ### What problem does this PR solve? ``` RAGFlow(user)> ocr with 'hunyuanocr@test@gitee' file './picture.png' +----------------------------------------------------------+ | text | +----------------------------------------------------------+ | 生活不是等待风暴过去,而是学会在雨中翩翩起舞。 ——佚名 | +----------------------------------------------------------+ RAGFlow(user)> list 'test@gitee' tasks; +---------+----------------------------------+ | status | task_id | +---------+----------------------------------+ | success | C3FX4MQNKY5MGC6ZFMIXIAMJKHCEBQB5 | +---------+----------------------------------+ RAGFlow(user)> show 'test@gitee' task 'C3FX4MQNKY5MGC6ZFMIXIAMJKHCEBQB5'; +------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+-------+ | content | index | +------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+-------+ | # PDF 1: Purpose of RAGFlow RAGFlow is an open source Retrieval-Augmented Generation (RAG) engine designed to turn raw documents into reliable context for large language models.Its purpose is to make it practical to build an Al assistant that can ans... | 1 | +------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+-------+ ``` ### Type of change - [x] New Feature (non-breaking change which adds functionality) --------- Signed-off-by: Jin Hai <haijin.chn@gmail.com>
2026-05-15 12:29:52 +08:00
// ParseFile parse file
func (v *VllmModel) ParseFile(modelName *string, content []byte, url *string, apiConfig *APIConfig, parseFileConfig *ParseFileConfig) (*ParseFileResponse, error) {
return nil, fmt.Errorf("%s, no such method", v.Name())
Go: add file parse command (#14892) ### What problem does this PR solve? ``` RAGFlow(user)> ocr with 'hunyuanocr@test@gitee' file './picture.png' +----------------------------------------------------------+ | text | +----------------------------------------------------------+ | 生活不是等待风暴过去,而是学会在雨中翩翩起舞。 ——佚名 | +----------------------------------------------------------+ RAGFlow(user)> list 'test@gitee' tasks; +---------+----------------------------------+ | status | task_id | +---------+----------------------------------+ | success | C3FX4MQNKY5MGC6ZFMIXIAMJKHCEBQB5 | +---------+----------------------------------+ RAGFlow(user)> show 'test@gitee' task 'C3FX4MQNKY5MGC6ZFMIXIAMJKHCEBQB5'; +------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+-------+ | content | index | +------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+-------+ | # PDF 1: Purpose of RAGFlow RAGFlow is an open source Retrieval-Augmented Generation (RAG) engine designed to turn raw documents into reliable context for large language models.Its purpose is to make it practical to build an Al assistant that can ans... | 1 | +------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+-------+ ``` ### Type of change - [x] New Feature (non-breaking change which adds functionality) --------- Signed-off-by: Jin Hai <haijin.chn@gmail.com>
2026-05-15 12:29:52 +08:00
}
func (v *VllmModel) ListTasks(apiConfig *APIConfig) ([]ListTaskStatus, error) {
return nil, fmt.Errorf("%s, no such method", v.Name())
Go: add file parse command (#14892) ### What problem does this PR solve? ``` RAGFlow(user)> ocr with 'hunyuanocr@test@gitee' file './picture.png' +----------------------------------------------------------+ | text | +----------------------------------------------------------+ | 生活不是等待风暴过去,而是学会在雨中翩翩起舞。 ——佚名 | +----------------------------------------------------------+ RAGFlow(user)> list 'test@gitee' tasks; +---------+----------------------------------+ | status | task_id | +---------+----------------------------------+ | success | C3FX4MQNKY5MGC6ZFMIXIAMJKHCEBQB5 | +---------+----------------------------------+ RAGFlow(user)> show 'test@gitee' task 'C3FX4MQNKY5MGC6ZFMIXIAMJKHCEBQB5'; +------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+-------+ | content | index | +------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+-------+ | # PDF 1: Purpose of RAGFlow RAGFlow is an open source Retrieval-Augmented Generation (RAG) engine designed to turn raw documents into reliable context for large language models.Its purpose is to make it practical to build an Al assistant that can ans... | 1 | +------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+-------+ ``` ### Type of change - [x] New Feature (non-breaking change which adds functionality) --------- Signed-off-by: Jin Hai <haijin.chn@gmail.com>
2026-05-15 12:29:52 +08:00
}
func (v *VllmModel) ShowTask(taskID string, apiConfig *APIConfig) (*TaskResponse, error) {
return nil, fmt.Errorf("%s, no such method", v.Name())
Go: add file parse command (#14892) ### What problem does this PR solve? ``` RAGFlow(user)> ocr with 'hunyuanocr@test@gitee' file './picture.png' +----------------------------------------------------------+ | text | +----------------------------------------------------------+ | 生活不是等待风暴过去,而是学会在雨中翩翩起舞。 ——佚名 | +----------------------------------------------------------+ RAGFlow(user)> list 'test@gitee' tasks; +---------+----------------------------------+ | status | task_id | +---------+----------------------------------+ | success | C3FX4MQNKY5MGC6ZFMIXIAMJKHCEBQB5 | +---------+----------------------------------+ RAGFlow(user)> show 'test@gitee' task 'C3FX4MQNKY5MGC6ZFMIXIAMJKHCEBQB5'; +------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+-------+ | content | index | +------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+-------+ | # PDF 1: Purpose of RAGFlow RAGFlow is an open source Retrieval-Augmented Generation (RAG) engine designed to turn raw documents into reliable context for large language models.Its purpose is to make it practical to build an Al assistant that can ans... | 1 | +------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+-------+ ``` ### Type of change - [x] New Feature (non-breaking change which adds functionality) --------- Signed-off-by: Jin Hai <haijin.chn@gmail.com>
2026-05-15 12:29:52 +08:00
}