Add Atlas Cloud LLM provider preset

README.md

@@ -102,6 +102,7 @@ for fast retrieval and self-evolving reuse.
 | Capability | Provider | Used for | Fill these `.env` slots |
 | --- | --- | --- | --- |
 | Chat + multimodal | [OpenRouter](https://openrouter.ai/) | `LLM` / `MULTIMODAL` | `EVEROS_LLM__API_KEY`, `EVEROS_MULTIMODAL__API_KEY` |
+| Chat | Atlas Cloud OpenAI-compatible endpoint | `LLM` | `EVEROS_LLM__PROVIDER=atlascloud`, `EVEROS_LLM__API_KEY` |
 | Embedding + rerank | [DeepInfra](https://deepinfra.com/) | `EMBEDDING` / `RERANK` | `EVEROS_EMBEDDING__API_KEY`, `EVEROS_RERANK__API_KEY` |
 
 You can use other OpenAI-compatible providers by changing the matching

config.example.toml

@@ -21,10 +21,17 @@
 # ── LLM ───────────────────────────────────────────────
 # OpenAI-protocol chat-completions endpoint used by the algo extractors.
 [llm]
+provider = "openai"
 model    = "gpt-4.1-mini"
 api_key  = "sk-..."
 base_url = "https://api.openai.com/v1"
 
+# Atlas Cloud is also supported through its OpenAI-compatible endpoint:
+# provider = "atlascloud"
+# model    = "qwen/qwen3.5-flash"
+# api_key  = "..."
+# base_url = "https://api.atlascloud.ai/v1"
+
 # ── Embedding ─────────────────────────────────────────
 [embedding]
 model    = "Qwen/Qwen3-Embedding-4B"

docs/configuration.md

@@ -103,6 +103,7 @@ everos init --root /data/everos
 
 | Field | Type | Default | Required | Description |
 |---|---|---|---|---|
+| `provider` | string | `"openrouter"` | No | Provider preset. Use `"atlascloud"` to apply Atlas Cloud's OpenAI-compatible defaults. |
 | `model` | string | `"gpt-4.1-mini"` | No | LLM model identifier. |
 | `api_key` | string | — | **Yes** | API key for the LLM provider. |
 | `base_url` | string | — | No | Custom endpoint URL (OpenAI-compatible). |
@@ -202,8 +203,9 @@ variables directly:
 
 ```dockerfile
 ENV EVEROS_ROOT=/data/everos
+ENV EVEROS_LLM__PROVIDER=atlascloud
 ENV EVEROS_LLM__API_KEY=sk-...
-ENV EVEROS_LLM__MODEL=gpt-4o
+ENV EVEROS_LLM__MODEL=qwen/qwen3.5-flash
 ENV EVEROS_EMBEDDING__MODEL=text-embedding-3-large
 ENV EVEROS_EMBEDDING__API_KEY=sk-...
 ENV EVEROS_EMBEDDING__BASE_URL=https://api.openai.com/v1
@@ -225,6 +227,7 @@ Examples:
 
 | TOML | Environment Variable |
 |---|---|
+| `[llm] provider = "atlascloud"` | `EVEROS_LLM__PROVIDER=atlascloud` |
 | `[llm] api_key = "sk-..."` | `EVEROS_LLM__API_KEY=sk-...` |
 | `[sqlite] busy_timeout_ms = 10000` | `EVEROS_SQLITE__BUSY_TIMEOUT_MS=10000` |
 | `[memory] timezone = "Asia/Tokyo"` | `EVEROS_MEMORY__TIMEZONE=Asia/Tokyo` |

src/everos/config/default.toml

@@ -52,8 +52,10 @@ cache_size_kb = 2048
 
 [llm]
 # Provider-agnostic OpenAI-protocol client config. Override via env:
-#   EVEROS_LLM__MODEL, EVEROS_LLM__API_KEY, EVEROS_LLM__BASE_URL
+#   EVEROS_LLM__PROVIDER, EVEROS_LLM__MODEL, EVEROS_LLM__API_KEY,
+#   EVEROS_LLM__BASE_URL
 # Or set the field directly in this file (<root>/everos.toml).
+provider = "openrouter"
 model = "openai/gpt-4.1-mini"
 api_key = ""
 base_url = "https://openrouter.ai/api/v1"

src/everos/config/settings.py

@@ -28,7 +28,14 @@
 from typing import Literal
 from zoneinfo import ZoneInfo, ZoneInfoNotFoundError
 
-from pydantic import BaseModel, ConfigDict, Field, SecretStr, field_validator
+from pydantic import (
+    BaseModel,
+    ConfigDict,
+    Field,
+    SecretStr,
+    field_validator,
+    model_validator,
+)
 from pydantic_settings import (
     BaseSettings,
     PydanticBaseSettingsSource,
@@ -38,6 +45,9 @@
 
 _DEFAULT_TOML_PATH = Path(__file__).parent / "default.toml"
 _DEFAULT_ROOT = Path("~/.everos")
+_ATLASCLOUD_BASE_URL = "https://api.atlascloud.ai/v1"
+_ATLASCLOUD_DEFAULT_MODEL = "qwen/qwen3.5-flash"
+_OPENROUTER_BASE_URL = "https://openrouter.ai/api/v1"
 
 
 def resolve_root(explicit: str | None = None) -> Path:
@@ -124,15 +134,38 @@ class LLMSettings(BaseModel):
     endpoint plugs in via ``base_url``.
 
     Env binding (via parent ``Settings``):
+        EVEROS_LLM__PROVIDER
         EVEROS_LLM__MODEL
         EVEROS_LLM__API_KEY
         EVEROS_LLM__BASE_URL
     """
 
+    provider: Literal["openrouter", "openai", "atlascloud", "custom"] = "openrouter"
     model: str = "gpt-4.1-mini"
     api_key: SecretStr | None = None
     base_url: str | None = None
 
+    @model_validator(mode="after")
+    def _apply_provider_defaults(self) -> LLMSettings:
+        """Apply provider-specific OpenAI-compatible defaults."""
+        if self.provider != "atlascloud":
+            return self
+
+        if not self.base_url or self.base_url == _OPENROUTER_BASE_URL:
+            self.base_url = _ATLASCLOUD_BASE_URL
+
+        if self.model in {"openai/gpt-4.1-mini", "gpt-4.1-mini"}:
+            self.model = _ATLASCLOUD_DEFAULT_MODEL
+
+        if not self.api_key or not self.api_key.get_secret_value():
+            atlas_key = os.environ.get("ATLASCLOUD_API_KEY") or os.environ.get(
+                "ATLAS_CLOUD_API_KEY"
+            )
+            if atlas_key:
+                self.api_key = SecretStr(atlas_key)
+
+        return self
+
 
 class MultimodalSettings(BaseModel):
     """Multimodal parsing LLM config (everalgo-parser).

src/everos/templates/env.template

@@ -22,10 +22,11 @@
 
 # ─── LLM (OpenAI-protocol compatible) ────────────────
 # Any OpenAI-API-compatible endpoint plugs in via base_url. Defaults
-# below target OpenRouter (one key, broad model catalogue); switch to
-# OpenAI, vLLM, Ollama (OpenAI bridge), or any other compatible endpoint
-# by changing model + base_url + api_key.
+# below target OpenRouter (one key, broad model catalogue). Set
+# EVEROS_LLM__PROVIDER=atlascloud to use Atlas Cloud's preset endpoint
+# and model defaults.
 
+EVEROS_LLM__PROVIDER=openrouter
 EVEROS_LLM__MODEL=openai/gpt-4.1-mini
 EVEROS_LLM__API_KEY=
 EVEROS_LLM__BASE_URL=https://openrouter.ai/api/v1

tests/unit/test_config/test_settings.py

@@ -118,6 +118,34 @@ def test_embedding_rerank_defaults() -> None:
     assert s.rerank.api_key.get_secret_value() == ""
     assert s.rerank.timeout_seconds == 30.0
     assert s.llm.api_key.get_secret_value() == ""
+    assert s.llm.provider == "openrouter"
+
+
+def test_atlascloud_llm_provider_defaults(monkeypatch: pytest.MonkeyPatch) -> None:
+    monkeypatch.setenv("ATLASCLOUD_API_KEY", "atlas-key")
+    s = Settings(llm={"provider": "atlascloud"})
+
+    assert s.llm.provider == "atlascloud"
+    assert s.llm.model == "qwen/qwen3.5-flash"
+    assert s.llm.base_url == "https://api.atlascloud.ai/v1"
+    assert s.llm.api_key is not None
+    assert s.llm.api_key.get_secret_value() == "atlas-key"
+
+
+def test_atlascloud_llm_provider_preserves_explicit_values() -> None:
+    s = Settings(
+        llm={
+            "provider": "atlascloud",
+            "model": "deepseek-ai/deepseek-v4-pro",
+            "api_key": "custom-key",
+            "base_url": "https://proxy.example.test/v1",
+        }
+    )
+
+    assert s.llm.model == "deepseek-ai/deepseek-v4-pro"
+    assert s.llm.base_url == "https://proxy.example.test/v1"
+    assert s.llm.api_key is not None
+    assert s.llm.api_key.get_secret_value() == "custom-key"
 
 
 def test_resolve_root_default(monkeypatch: pytest.MonkeyPatch) -> None: