Feat: add gpustack model provider (#4469)

### What problem does this PR solve?

Add GPUStack as a new model provider.
[GPUStack](https://github.com/gpustack/gpustack) is an open-source GPU
cluster manager for running LLMs. Currently, locally deployed models in
GPUStack cannot integrate well with RAGFlow. GPUStack provides both
OpenAI compatible APIs (Models / Chat Completions / Embeddings /
Speech2Text / TTS) and other APIs like Rerank. We would like to use
GPUStack as a model provider in ragflow.

[GPUStack Docs](https://docs.gpustack.ai/latest/quickstart/)

Related issue: #4064.

### Type of change

- [x] New Feature (non-breaking change which adds functionality)



### Testing Instructions
1. Install GPUStack and deploy the `llama-3.2-1b-instruct` llm, `bge-m3`
text embedding model, `bge-reranker-v2-m3` rerank model,
`faster-whisper-medium` Speech-to-Text model, `cosyvoice-300m-sft` in
GPUStack.
2. Add provider in ragflow settings.
3. Testing in ragflow.

api/apps/llm_app.py

@@ -329,7 +329,7 @@ def my_llms():
 @manager.route('/list', methods=['GET'])  # noqa: F821
 @login_required
 def list_app():
-    self_deploied = ["Youdao", "FastEmbed", "BAAI", "Ollama", "Xinference", "LocalAI", "LM-Studio"]
+    self_deployed = ["Youdao", "FastEmbed", "BAAI", "Ollama", "Xinference", "LocalAI", "LM-Studio", "GPUStack"]
     weighted = ["Youdao", "FastEmbed", "BAAI"] if settings.LIGHTEN != 0 else []
     model_type = request.args.get("model_type")
     try:
@@ -339,7 +339,7 @@ def list_app():
         llms = [m.to_dict()
                 for m in llms if m.status == StatusEnum.VALID.value and m.fid not in weighted]
         for m in llms:
-            m["available"] = m["fid"] in facts or m["llm_name"].lower() == "flag-embedding" or m["fid"] in self_deploied
+            m["available"] = m["fid"] in facts or m["llm_name"].lower() == "flag-embedding" or m["fid"] in self_deployed
 
         llm_set = set([m["llm_name"] + "@" + m["fid"] for m in llms])
         for o in objs:

conf/llm_factories.json

@@ -2543,6 +2543,13 @@
             "tags": "TEXT EMBEDDING",
             "status": "1",
             "llm": []
+        },
+        {
+            "name": "GPUStack",
+            "logo": "",
+            "tags": "LLM,TEXT EMBEDDING,TTS,SPEECH2TEXT,TEXT RE-RANK",
+            "status": "1",
+            "llm": []
         }
     ]
 }

rag/llm/__init__.py

@@ -42,6 +42,7 @@
     VoyageEmbed,
     HuggingFaceEmbed,
     VolcEngineEmbed,
+    GPUStackEmbed,
 )
 from .chat_model import (
     GptTurbo,
@@ -80,6 +81,7 @@
     AnthropicChat,
     GoogleChat,
     HuggingFaceChat,
+    GPUStackChat,
 )
 
 from .cv_model import (
@@ -116,20 +118,23 @@
     BaiduYiyanRerank,
     VoyageRerank,
     QWenRerank,
+    GPUStackRerank,
 )
 from .sequence2txt_model import (
     GPTSeq2txt,
     QWenSeq2txt,
     AzureSeq2txt,
     XinferenceSeq2txt,
     TencentCloudSeq2txt,
+    GPUStackSeq2txt,
 )
 from .tts_model import (
     FishAudioTTS,
     QwenTTS,
     OpenAITTS,
     SparkTTS,
     XinferenceTTS,
+    GPUStackTTS,
 )
 
 EmbeddingModel = {
@@ -161,6 +166,7 @@
     "Voyage AI": VoyageEmbed,
     "HuggingFace": HuggingFaceEmbed,
     "VolcEngine": VolcEngineEmbed,
+    "GPUStack": GPUStackEmbed,
 }
 
 CvModel = {
@@ -220,6 +226,7 @@
     "Anthropic": AnthropicChat,
     "Google Cloud": GoogleChat,
     "HuggingFace": HuggingFaceChat,
+    "GPUStack": GPUStackChat,
 }
 
 RerankModel = {
@@ -237,6 +244,7 @@
     "BaiduYiyan": BaiduYiyanRerank,
     "Voyage AI": VoyageRerank,
     "Tongyi-Qianwen": QWenRerank,
+    "GPUStack": GPUStackRerank,
 }
 
 Seq2txtModel = {
@@ -245,6 +253,7 @@
     "Azure-OpenAI": AzureSeq2txt,
     "Xinference": XinferenceSeq2txt,
     "Tencent Cloud": TencentCloudSeq2txt,
+    "GPUStack": GPUStackSeq2txt,
 }
 
 TTSModel = {
@@ -253,4 +262,5 @@
     "OpenAI": OpenAITTS,
     "XunFei Spark": SparkTTS,
     "Xinference": XinferenceTTS,
+    "GPUStack": GPUStackTTS,
 }

rag/llm/chat_model.py

@@ -1514,3 +1514,11 @@ def chat_streamly(self, system, history, gen_conf):
                 yield ans + "\n**ERROR**: " + str(e)
 
             yield response._chunks[-1].usage_metadata.total_token_count
+
+class GPUStackChat(Base):
+    def __init__(self, key=None, model_name="", base_url=""):
+        if not base_url:
+            raise ValueError("Local llm url cannot be None")
+        if base_url.split("/")[-1] != "v1-openai":
+            base_url = os.path.join(base_url, "v1-openai")
+        super().__init__(key, model_name, base_url)

rag/llm/embedding_model.py

@@ -30,7 +30,7 @@
 from api import settings
 from api.utils.file_utils import get_home_cache_dir
 from rag.utils import num_tokens_from_string, truncate
-import google.generativeai as genai 
+import google.generativeai as genai
 import json
 
 
@@ -799,3 +799,14 @@ def __init__(self, key, model_name, base_url="https://ark.cn-beijing.volces.com/
         ark_api_key = json.loads(key).get('ark_api_key', '')
         model_name = json.loads(key).get('ep_id', '') + json.loads(key).get('endpoint_id', '')
         super().__init__(ark_api_key,model_name,base_url)
+
+class GPUStackEmbed(OpenAIEmbed):
+    def __init__(self, key, model_name, base_url):
+        if not base_url:
+            raise ValueError("url cannot be None")
+        if base_url.split("/")[-1] != "v1-openai":
+            base_url = os.path.join(base_url, "v1-openai")
+
+        print(key,base_url)
+        self.client = OpenAI(api_key=key, base_url=base_url)
+        self.model_name = model_name

rag/llm/rerank_model.py

@@ -18,10 +18,12 @@
 from urllib.parse import urljoin
 
 import requests
+import httpx
 from huggingface_hub import snapshot_download
 import os
 from abc import ABC
 import numpy as np
+from yarl import URL
 
 from api import settings
 from api.utils.file_utils import get_home_cache_dir
@@ -457,3 +459,53 @@ def similarity(self, query: str, texts: list):
             return rank, resp.usage.total_tokens
         else:
             raise ValueError(f"Error calling QWenRerank model {self.model_name}: {resp.status_code} - {resp.text}")
+
+class GPUStackRerank(Base):
+    def __init__(
+            self, key, model_name, base_url
+    ):
+        if not base_url:
+            raise ValueError("url cannot be None")
+
+        self.model_name = model_name
+        self.base_url = str(URL(base_url)/ "v1" / "rerank")
+        self.headers = {
+            "accept": "application/json",
+            "content-type": "application/json",
+            "authorization": f"Bearer {key}",
+        }
+
+    def similarity(self, query: str, texts: list):
+        payload = {
+            "model": self.model_name,
+            "query": query,
+            "documents": texts,
+            "top_n": len(texts),
+        }
+
+        try:
+            response = requests.post(
+                self.base_url, json=payload, headers=self.headers
+            )
+            response.raise_for_status()
+            response_json = response.json()
+
+            rank = np.zeros(len(texts), dtype=float)
+            if "results" not in response_json:
+                return rank, 0
+
+            token_count = 0
+            for t in texts:
+                token_count += num_tokens_from_string(t)
+
+            for result in response_json["results"]:
+                rank[result["index"]] = result["relevance_score"]
+
+            return (
+                rank,
+                token_count,
+            )
+
+        except httpx.HTTPStatusError as e:
+            raise ValueError(f"Error calling GPUStackRerank model {self.model_name}: {e.response.status_code} - {e.response.text}")
+

rag/llm/sequence2txt_model.py

@@ -13,6 +13,7 @@
 #  See the License for the specific language governing permissions and
 #  limitations under the License.
 #
+import os
 import requests
 from openai.lib.azure import AzureOpenAI
 import io
@@ -191,3 +192,14 @@ def transcription(self, audio, max_retries=60, retry_interval=5):
             return "**ERROR**: " + str(e), 0
         except Exception as e:
             return "**ERROR**: " + str(e), 0
+
+
+class GPUStackSeq2txt(Base):
+    def __init__(self, key, model_name, base_url):
+        if not base_url:
+            raise ValueError("url cannot be None")
+        if base_url.split("/")[-1] != "v1-openai":
+            base_url = os.path.join(base_url, "v1-openai")
+        self.base_url = base_url
+        self.model_name = model_name
+        self.key = key

rag/llm/tts_model.py

@@ -355,3 +355,35 @@ def tts(self, text, voice="standard-voice"):
         for chunk in response.iter_content():
             if chunk:
                 yield chunk
+
+class GPUStackTTS:
+    def __init__(self, key, model_name, **kwargs):
+        self.base_url = kwargs.get("base_url", None)
+        self.api_key = key
+        self.model_name = model_name
+        self.headers = {
+            "accept": "application/json",
+            "Content-Type": "application/json",
+            "Authorization": f"Bearer {self.api_key}"
+        }
+
+    def tts(self, text, voice="Chinese Female", stream=True):
+        payload = {
+            "model": self.model_name,
+            "input": text,
+            "voice": voice
+        }
+
+        response = requests.post(
+            f"{self.base_url}/v1-openai/audio/speech",
+            headers=self.headers,
+            json=payload,
+            stream=stream
+        )
+
+        if response.status_code != 200:
+            raise Exception(f"**Error**: {response.status_code}, {response.text}")
+
+        for chunk in response.iter_content(chunk_size=1024):
+            if chunk:
+                yield chunk

web/src/constants/setting.ts

@@ -72,6 +72,7 @@ export const IconMap = {
   'nomic-ai': 'nomic-ai',
   jinaai: 'jina',
   'sentence-transformers': 'sentence-transformers',
+  GPUStack: 'gpustack',
 };
 
 export const TimezoneList = [

web/src/pages/user-setting/constants.tsx

@@ -31,6 +31,7 @@ export const LocalLlmFactories = [
   'Replicate',
   'OpenRouter',
   'HuggingFace',
+  'GPUStack',
 ];
 
 export enum TenantRole {

web/src/pages/user-setting/setting-model/ollama-modal/index.tsx

@@ -29,6 +29,7 @@ const llmFactoryToUrlMap = {
   OpenRouter: 'https://openrouter.ai/docs',
   HuggingFace:
     'https://huggingface.co/docs/text-embeddings-inference/quick_tour',
+  GPUStack: 'https://docs.gpustack.ai/latest/quickstart',
 };
 type LlmFactory = keyof typeof llmFactoryToUrlMap;
 
@@ -76,6 +77,13 @@ const OllamaModal = ({
       { value: 'speech2text', label: 'sequence2text' },
       { value: 'tts', label: 'tts' },
     ],
+    GPUStack: [
+      { value: 'chat', label: 'chat' },
+      { value: 'embedding', label: 'embedding' },
+      { value: 'rerank', label: 'rerank' },
+      { value: 'speech2text', label: 'sequence2text' },
+      { value: 'tts', label: 'tts' },
+    ],
     Default: [
       { value: 'chat', label: 'chat' },
       { value: 'embedding', label: 'embedding' },