feat: add gpustack model provider (langgenius#10158)

api/core/model_runtime/model_providers/gpustack/gpustack.py

@@ -0,0 +1,10 @@
+import logging
+
+from core.model_runtime.model_providers.__base.model_provider import ModelProvider
+
+logger = logging.getLogger(__name__)
+
+
+class GPUStackProvider(ModelProvider):
+    def validate_provider_credentials(self, credentials: dict) -> None:
+        pass

api/core/model_runtime/model_providers/gpustack/gpustack.yaml

@@ -0,0 +1,120 @@
+provider: gpustack
+label:
+  en_US: GPUStack
+icon_small:
+  en_US: icon_s_en.png
+icon_large:
+  en_US: icon_l_en.png
+supported_model_types:
+  - llm
+  - text-embedding
+  - rerank
+configurate_methods:
+  - customizable-model
+model_credential_schema:
+  model:
+    label:
+      en_US: Model Name
+      zh_Hans: 模型名称
+    placeholder:
+      en_US: Enter your model name
+      zh_Hans: 输入模型名称
+  credential_form_schemas:
+    - variable: endpoint_url
+      label:
+        zh_Hans: 服务器地址
+        en_US: Server URL
+      type: text-input
+      required: true
+      placeholder:
+        zh_Hans: 输入 GPUStack 的服务器地址，如 http://192.168.1.100
+        en_US: Enter the GPUStack server URL, e.g. http://192.168.1.100
+    - variable: api_key
+      label:
+        en_US: API Key
+      type: secret-input
+      required: true
+      placeholder:
+        zh_Hans: 输入您的 API Key
+        en_US: Enter your API Key
+    - variable: mode
+      show_on:
+        - variable: __model_type
+          value: llm
+      label:
+        en_US: Completion mode
+      type: select
+      required: false
+      default: chat
+      placeholder:
+        zh_Hans: 选择补全类型
+        en_US: Select completion type
+      options:
+        - value: completion
+          label:
+            en_US: Completion
+            zh_Hans: 补全
+        - value: chat
+          label:
+            en_US: Chat
+            zh_Hans: 对话
+    - variable: context_size
+      label:
+        zh_Hans: 模型上下文长度
+        en_US: Model context size
+      required: true
+      type: text-input
+      default: "8192"
+      placeholder:
+        zh_Hans: 输入您的模型上下文长度
+        en_US: Enter your Model context size
+    - variable: max_tokens_to_sample
+      label:
+        zh_Hans: 最大 token 上限
+        en_US: Upper bound for max tokens
+      show_on:
+        - variable: __model_type
+          value: llm
+      default: "8192"
+      type: text-input
+    - variable: function_calling_type
+      show_on:
+        - variable: __model_type
+          value: llm
+      label:
+        en_US: Function calling
+      type: select
+      required: false
+      default: no_call
+      options:
+        - value: function_call
+          label:
+            en_US: Function Call
+            zh_Hans: Function Call
+        - value: tool_call
+          label:
+            en_US: Tool Call
+            zh_Hans: Tool Call
+        - value: no_call
+          label:
+            en_US: Not Support
+            zh_Hans: 不支持
+    - variable: vision_support
+      show_on:
+        - variable: __model_type
+          value: llm
+      label:
+        zh_Hans: Vision 支持
+        en_US: Vision Support
+      type: select
+      required: false
+      default: no_support
+      options:
+        - value: support
+          label:
+            en_US: Support
+            zh_Hans: 支持
+        - value: no_support
+          label:
+            en_US: Not Support
+            zh_Hans: 不支持

api/core/model_runtime/model_providers/gpustack/llm/llm.py

@@ -0,0 +1,45 @@
+from collections.abc import Generator
+
+from yarl import URL
+
+from core.model_runtime.entities.llm_entities import LLMResult
+from core.model_runtime.entities.message_entities import (
+    PromptMessage,
+    PromptMessageTool,
+)
+from core.model_runtime.model_providers.openai_api_compatible.llm.llm import (
+    OAIAPICompatLargeLanguageModel,
+)
+
+
+class GPUStackLanguageModel(OAIAPICompatLargeLanguageModel):
+    def _invoke(
+        self,
+        model: str,
+        credentials: dict,
+        prompt_messages: list[PromptMessage],
+        model_parameters: dict,
+        tools: list[PromptMessageTool] | None = None,
+        stop: list[str] | None = None,
+        stream: bool = True,
+        user: str | None = None,
+    ) -> LLMResult | Generator:
+        return super()._invoke(
+            model,
+            credentials,
+            prompt_messages,
+            model_parameters,
+            tools,
+            stop,
+            stream,
+            user,
+        )
+
+    def validate_credentials(self, model: str, credentials: dict) -> None:
+        self._add_custom_parameters(credentials)
+        super().validate_credentials(model, credentials)
+
+    @staticmethod
+    def _add_custom_parameters(credentials: dict) -> None:
+        credentials["endpoint_url"] = str(URL(credentials["endpoint_url"]) / "v1-openai")
+        credentials["mode"] = "chat"

api/core/model_runtime/model_providers/gpustack/rerank/rerank.py

@@ -0,0 +1,146 @@
+from json import dumps
+from typing import Optional
+
+import httpx
+from requests import post
+from yarl import URL
+
+from core.model_runtime.entities.common_entities import I18nObject
+from core.model_runtime.entities.model_entities import (
+    AIModelEntity,
+    FetchFrom,
+    ModelPropertyKey,
+    ModelType,
+)
+from core.model_runtime.entities.rerank_entities import RerankDocument, RerankResult
+from core.model_runtime.errors.invoke import (
+    InvokeAuthorizationError,
+    InvokeBadRequestError,
+    InvokeConnectionError,
+    InvokeError,
+    InvokeRateLimitError,
+    InvokeServerUnavailableError,
+)
+from core.model_runtime.errors.validate import CredentialsValidateFailedError
+from core.model_runtime.model_providers.__base.rerank_model import RerankModel
+
+
+class GPUStackRerankModel(RerankModel):
+    """
+    Model class for GPUStack rerank model.
+    """
+
+    def _invoke(
+        self,
+        model: str,
+        credentials: dict,
+        query: str,
+        docs: list[str],
+        score_threshold: Optional[float] = None,
+        top_n: Optional[int] = None,
+        user: Optional[str] = None,
+    ) -> RerankResult:
+        """
+        Invoke rerank model
+
+        :param model: model name
+        :param credentials: model credentials
+        :param query: search query
+        :param docs: docs for reranking
+        :param score_threshold: score threshold
+        :param top_n: top n documents to return
+        :param user: unique user id
+        :return: rerank result
+        """
+        if len(docs) == 0:
+            return RerankResult(model=model, docs=[])
+
+        endpoint_url = credentials["endpoint_url"]
+        headers = {
+            "Authorization": f"Bearer {credentials.get('api_key')}",
+            "Content-Type": "application/json",
+        }
+
+        data = {"model": model, "query": query, "documents": docs, "top_n": top_n}
+
+        try:
+            response = post(
+                str(URL(endpoint_url) / "v1" / "rerank"),
+                headers=headers,
+                data=dumps(data),
+                timeout=10,
+            )
+            response.raise_for_status()
+            results = response.json()
+
+            rerank_documents = []
+            for result in results["results"]:
+                index = result["index"]
+                if "document" in result:
+                    text = result["document"]["text"]
+                else:
+                    text = docs[index]
+
+                rerank_document = RerankDocument(
+                    index=index,
+                    text=text,
+                    score=result["relevance_score"],
+                )
+
+                if score_threshold is None or result["relevance_score"] >= score_threshold:
+                    rerank_documents.append(rerank_document)
+
+            return RerankResult(model=model, docs=rerank_documents)
+        except httpx.HTTPStatusError as e:
+            raise InvokeServerUnavailableError(str(e))
+
+    def validate_credentials(self, model: str, credentials: dict) -> None:
+        """
+        Validate model credentials
+
+        :param model: model name
+        :param credentials: model credentials
+        :return:
+        """
+        try:
+            self._invoke(
+                model=model,
+                credentials=credentials,
+                query="What is the capital of the United States?",
+                docs=[
+                    "Carson City is the capital city of the American state of Nevada. At the 2010 United States "
+                    "Census, Carson City had a population of 55,274.",
+                    "The Commonwealth of the Northern Mariana Islands is a group of islands in the Pacific Ocean that "
+                    "are a political division controlled by the United States. Its capital is Saipan.",
+                ],
+                score_threshold=0.8,
+            )
+        except Exception as ex:
+            raise CredentialsValidateFailedError(str(ex))
+
+    @property
+    def _invoke_error_mapping(self) -> dict[type[InvokeError], list[type[Exception]]]:
+        """
+        Map model invoke error to unified error
+        """
+        return {
+            InvokeConnectionError: [httpx.ConnectError],
+            InvokeServerUnavailableError: [httpx.RemoteProtocolError],
+            InvokeRateLimitError: [],
+            InvokeAuthorizationError: [httpx.HTTPStatusError],
+            InvokeBadRequestError: [httpx.RequestError],
+        }
+
+    def get_customizable_model_schema(self, model: str, credentials: dict) -> AIModelEntity:
+        """
+        generate custom model entities from credentials
+        """
+        entity = AIModelEntity(
+            model=model,
+            label=I18nObject(en_US=model),
+            model_type=ModelType.RERANK,
+            fetch_from=FetchFrom.CUSTOMIZABLE_MODEL,
+            model_properties={ModelPropertyKey.CONTEXT_SIZE: int(credentials.get("context_size"))},
+        )
+
+        return entity

api/core/model_runtime/model_providers/gpustack/text_embedding/text_embedding.py

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+from typing import Optional
+
+from yarl import URL
+
+from core.entities.embedding_type import EmbeddingInputType
+from core.model_runtime.entities.text_embedding_entities import (
+    TextEmbeddingResult,
+)
+from core.model_runtime.model_providers.openai_api_compatible.text_embedding.text_embedding import (
+    OAICompatEmbeddingModel,
+)
+
+
+class GPUStackTextEmbeddingModel(OAICompatEmbeddingModel):
+    """
+    Model class for GPUStack text embedding model.
+    """
+
+    def _invoke(
+        self,
+        model: str,
+        credentials: dict,
+        texts: list[str],
+        user: Optional[str] = None,
+        input_type: EmbeddingInputType = EmbeddingInputType.DOCUMENT,
+    ) -> TextEmbeddingResult:
+        return super()._invoke(model, credentials, texts, user, input_type)
+
+    def validate_credentials(self, model: str, credentials: dict) -> None:
+        self._add_custom_parameters(credentials)
+        super().validate_credentials(model, credentials)
+
+    @staticmethod
+    def _add_custom_parameters(credentials: dict) -> None:
+        credentials["endpoint_url"] = str(URL(credentials["endpoint_url"]) / "v1-openai")