feat: add Atlas Cloud model provider

apps/models_provider/constants/model_provider_constants.py

@@ -1,6 +1,7 @@
 # coding=utf-8
 from enum import Enum
 
+from models_provider.impl.atlas_cloud_model_provider.atlas_cloud_model_provider import AtlasCloudModelProvider
 from models_provider.impl.aliyun_bai_lian_model_provider.aliyun_bai_lian_model_provider import \
     AliyunBaiLianModelProvider
 from models_provider.impl.anthropic_model_provider.anthropic_model_provider import AnthropicModelProvider
@@ -28,6 +29,7 @@
 
 
 class ModelProvideConstants(Enum):
+    model_atlas_cloud_provider = AtlasCloudModelProvider()
     model_azure_provider = AzureModelProvider()
     model_wenxin_provider = WenxinModelProvider()
     model_ollama_provider = OllamaModelProvider()

apps/models_provider/impl/atlas_cloud_model_provider/atlas_cloud_model_provider.py

@@ -0,0 +1,42 @@
+from models_provider.base_model_provider import (
+    IModelProvider,
+    ModelInfo,
+    ModelInfoManage,
+    ModelProvideInfo,
+    ModelTypeConst,
+)
+from models_provider.impl.atlas_cloud_model_provider.credential.llm import AtlasCloudLLMModelCredential
+from models_provider.impl.atlas_cloud_model_provider.model.llm import AtlasCloudChatModel
+
+
+atlas_cloud_llm_model_credential = AtlasCloudLLMModelCredential()
+atlas_cloud_llm_list = [
+    ModelInfo("google/gemini-2.5-flash", "", ModelTypeConst.LLM, atlas_cloud_llm_model_credential, AtlasCloudChatModel),
+    ModelInfo("google/gemini-2.5-pro", "", ModelTypeConst.LLM, atlas_cloud_llm_model_credential, AtlasCloudChatModel),
+    ModelInfo(
+        "anthropic/claude-sonnet-4.6", "", ModelTypeConst.LLM, atlas_cloud_llm_model_credential, AtlasCloudChatModel
+    ),
+    ModelInfo("openai/gpt-4o", "", ModelTypeConst.LLM, atlas_cloud_llm_model_credential, AtlasCloudChatModel),
+    ModelInfo(
+        "deepseek-ai/deepseek-v3.2", "", ModelTypeConst.LLM, atlas_cloud_llm_model_credential, AtlasCloudChatModel
+    ),
+    ModelInfo("moonshotai/kimi-k2.5", "", ModelTypeConst.LLM, atlas_cloud_llm_model_credential, AtlasCloudChatModel),
+    ModelInfo("zai-org/glm-5", "", ModelTypeConst.LLM, atlas_cloud_llm_model_credential, AtlasCloudChatModel),
+    ModelInfo("openai/gpt-5.4", "", ModelTypeConst.LLM, atlas_cloud_llm_model_credential, AtlasCloudChatModel),
+    ModelInfo("qwen/qwen3.7-max", "", ModelTypeConst.LLM, atlas_cloud_llm_model_credential, AtlasCloudChatModel),
+]
+
+model_info_manage = (
+    ModelInfoManage.builder()
+    .append_model_info_list(atlas_cloud_llm_list)
+    .append_default_model_info(atlas_cloud_llm_list[0])
+    .build()
+)
+
+
+class AtlasCloudModelProvider(IModelProvider):
+    def get_model_info_manage(self):
+        return model_info_manage
+
+    def get_model_provide_info(self):
+        return ModelProvideInfo(provider="model_atlas_cloud_provider", name="Atlas Cloud", icon="")

apps/models_provider/impl/atlas_cloud_model_provider/constants.py

@@ -0,0 +1 @@
+ATLAS_CLOUD_API_BASE = "https://api.atlascloud.ai/v1"

apps/models_provider/impl/atlas_cloud_model_provider/credential/llm.py

@@ -0,0 +1,92 @@
+from typing import Dict
+
+from django.utils.translation import gettext, gettext_lazy as _
+from langchain_core.messages import HumanMessage
+
+from common import forms
+from common.exception.app_exception import AppApiException
+from common.forms import BaseForm, TooltipLabel
+from common.utils.logger import maxkb_logger
+from models_provider.base_model_provider import BaseModelCredential, ValidCode
+from models_provider.impl.atlas_cloud_model_provider.constants import ATLAS_CLOUD_API_BASE
+
+
+class AtlasCloudLLMModelParams(BaseForm):
+    temperature = forms.SliderField(
+        TooltipLabel(
+            _("Temperature"),
+            _("Higher values make the output more random, while lower values make it more focused and deterministic"),
+        ),
+        required=True,
+        default_value=0.7,
+        _min=0.1,
+        _max=1.0,
+        _step=0.01,
+        precision=2,
+    )
+
+    max_tokens = forms.SliderField(
+        TooltipLabel(
+            _("Output the maximum Tokens"),
+            _("Specify the maximum number of tokens that the model can generate"),
+        ),
+        required=True,
+        default_value=8192,
+        _min=1,
+        _max=100000,
+        _step=1,
+        precision=0,
+    )
+
+
+class AtlasCloudLLMModelCredential(BaseForm, BaseModelCredential):
+    def is_valid(
+        self,
+        model_type: str,
+        model_name,
+        model_credential: Dict[str, object],
+        model_params,
+        provider,
+        raise_exception=False,
+    ):
+        model_type_list = provider.get_model_type_list()
+        if not any(item.get("value") == model_type for item in model_type_list):
+            raise AppApiException(
+                ValidCode.valid_error.value,
+                gettext("{model_type} Model type is not supported").format(model_type=model_type),
+            )
+
+        for key in ["api_base", "api_key"]:
+            if key not in model_credential:
+                if raise_exception:
+                    raise AppApiException(
+                        ValidCode.valid_error.value,
+                        gettext("{key}  is required").format(key=key),
+                    )
+                return False
+
+        try:
+            model = provider.get_model(model_type, model_name, model_credential, **model_params)
+            model.invoke([HumanMessage(content=gettext("Hello"))])
+        except Exception as exc:
+            maxkb_logger.error("Exception: %s", exc, exc_info=True)
+            if isinstance(exc, AppApiException):
+                raise exc
+            if raise_exception:
+                raise AppApiException(
+                    ValidCode.valid_error.value,
+                    gettext("Verification failed, please check whether the parameters are correct: {error}").format(
+                        error=str(exc)
+                    ),
+                )
+            return False
+        return True
+
+    def encryption_dict(self, model: Dict[str, object]):
+        return {**model, "api_key": super().encryption(model.get("api_key", ""))}
+
+    api_base = forms.TextInputField(_("API URL"), required=True, default_value=ATLAS_CLOUD_API_BASE)
+    api_key = forms.PasswordInputField("API Key", required=True)
+
+    def get_model_params_setting_form(self, model_name):
+        return AtlasCloudLLMModelParams()

apps/models_provider/impl/atlas_cloud_model_provider/model/llm.py

@@ -0,0 +1,21 @@
+from typing import Dict
+
+from models_provider.base_model_provider import MaxKBBaseModel
+from models_provider.impl.atlas_cloud_model_provider.constants import ATLAS_CLOUD_API_BASE
+from models_provider.impl.base_chat_open_ai import BaseChatOpenAI
+
+
+class AtlasCloudChatModel(MaxKBBaseModel, BaseChatOpenAI):
+    @staticmethod
+    def is_cache_model():
+        return False
+
+    @staticmethod
+    def new_instance(model_type, model_name, model_credential: Dict[str, object], **model_kwargs):
+        optional_params = MaxKBBaseModel.filter_optional_params(model_kwargs)
+        return AtlasCloudChatModel(
+            model=model_name,
+            openai_api_base=model_credential.get("api_base") or ATLAS_CLOUD_API_BASE,
+            openai_api_key=model_credential.get("api_key"),
+            **optional_params,
+        )

apps/models_provider/tests.py

@@ -1,3 +1,62 @@
-from django.test import TestCase
+from unittest import TestCase
+from unittest.mock import patch
 
-# Create your tests here.
+from models_provider.impl.atlas_cloud_model_provider.atlas_cloud_model_provider import AtlasCloudModelProvider
+from models_provider.impl.atlas_cloud_model_provider.constants import ATLAS_CLOUD_API_BASE
+from models_provider.impl.atlas_cloud_model_provider.credential.llm import AtlasCloudLLMModelCredential
+from models_provider.impl.atlas_cloud_model_provider.model.llm import AtlasCloudChatModel
+
+
+class AtlasCloudModelProviderTest(TestCase):
+    def test_provider_metadata(self):
+        provider = AtlasCloudModelProvider()
+
+        self.assertIsInstance(provider, AtlasCloudModelProvider)
+        self.assertEqual(
+            provider.get_model_provide_info().to_dict(),
+            {"provider": "model_atlas_cloud_provider", "name": "Atlas Cloud", "icon": ""},
+        )
+
+    def test_provider_exposes_current_model_ids(self):
+        provider = AtlasCloudModelProvider()
+
+        model_names = {model["name"] for model in provider.get_model_list("LLM")}
+
+        self.assertIn("google/gemini-2.5-flash", model_names)
+        self.assertIn("anthropic/claude-sonnet-4.6", model_names)
+        self.assertIn("openai/gpt-5.4", model_names)
+
+    def test_credential_defaults_to_atlas_cloud_api(self):
+        credential = AtlasCloudLLMModelCredential()
+
+        self.assertEqual(credential.api_base.default_value, ATLAS_CLOUD_API_BASE)
+
+    def test_model_uses_openai_compatible_configuration(self):
+        factory = AtlasCloudChatModel.new_instance
+        with patch(
+            "models_provider.impl.atlas_cloud_model_provider.model.llm.AtlasCloudChatModel"
+        ) as model_constructor:
+            model = factory(
+                "LLM",
+                "google/gemini-2.5-flash",
+                {"api_key": "test-key", "api_base": ""},
+                temperature=0.2,
+                streaming=True,
+                model_id="internal-id",
+            )
+
+        self.assertIs(model, model_constructor.return_value)
+        model_constructor.assert_called_once_with(
+            model="google/gemini-2.5-flash",
+            openai_api_base=ATLAS_CLOUD_API_BASE,
+            openai_api_key="test-key",
+            temperature=0.2,
+        )
+
+    def test_api_key_is_masked(self):
+        credential = AtlasCloudLLMModelCredential()
+
+        encrypted = credential.encryption_dict({"api_key": "test-secret-api-key", "api_base": ATLAS_CLOUD_API_BASE})
+
+        self.assertNotEqual(encrypted["api_key"], "test-secret-api-key")
+        self.assertEqual(encrypted["api_base"], ATLAS_CLOUD_API_BASE)

ui/src/components/dynamics-form/items/model/provider-data.ts

@@ -108,5 +108,10 @@ export const providerList = [
     "provider": "model_minimax_provider",
     "name": "MiniMax",
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+  },
+  {
+    "provider": "model_atlas_cloud_provider",
+    "name": "Atlas Cloud",
+    "icon": ""
   }
 ]