feat: add Atlas Cloud as LLM/AI provider (#2279)

* feat: add Atlas Cloud as OpenAI-compatible LLM provider

- Add Atlas Cloud env vars to .env.example (ATLAS_API_KEY, ATLAS_BASE_URL)
- Add docs/ATLAS-CLOUD-GUIDE.md with configuration, model list, and usage example
- Atlas Cloud provides 59+ LLM models via OpenAI-compatible API at https://api.atlascloud.ai/v1

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

* feat(atlascloud): add Atlas Cloud provider implementation

Wire Atlas Cloud in as a first-class OpenAI-compatible LLM provider,
complementing the existing .env.example/docs entries.

- src/llm/providers/atlas.py: AtlasProvider adapter (base_url
  https://api.atlascloud.ai/v1, default model deepseek-ai/deepseek-v4-pro);
  floors max_tokens to 512 for reasoning models; reads ATLAS_API_KEY
  (falls back to ATLASCLOUD_API_KEY), ATLAS_BASE_URL, ATLAS_MODEL
- src/llm/core/types.py: add ProviderType.ATLAS
- providers __init__/resolver: export + register AtlasProvider
- tests: test_atlas_provider.py + resolver coverage for "atlas"

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>

---------

Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com>

src/llm/core/types.py

@@ -20,6 +20,7 @@ class ProviderType(str, Enum):
     OLLAMA = "ollama"
     ASTRAFLOW = "astraflow"
     ASTRAFLOW_CN = "astraflow_cn"
+    ATLAS = "atlas"
 
 
 @dataclass(frozen=True)

src/llm/providers/__init__.py

@@ -1,6 +1,7 @@
 """Provider adapters for multiple LLM backends."""
 
 from llm.providers.astraflow import AstraflowCNProvider, AstraflowProvider
+from llm.providers.atlas import AtlasProvider
 from llm.providers.claude import ClaudeProvider
 from llm.providers.openai import OpenAIProvider
 from llm.providers.ollama import OllamaProvider
@@ -9,6 +10,7 @@ from llm.providers.resolver import get_provider, register_provider
 __all__ = (
     "AstraflowCNProvider",
     "AstraflowProvider",
+    "AtlasProvider",
     "ClaudeProvider",
     "OpenAIProvider",
     "OllamaProvider",

src/llm/providers/atlas.py

@@ -0,0 +1,147 @@
+"""Atlas Cloud OpenAI-compatible provider adapter."""
+
+from __future__ import annotations
+
+import json
+import os
+from typing import Any
+
+from openai import OpenAI
+
+from llm.core.interface import (
+    AuthenticationError,
+    ContextLengthError,
+    LLMProvider,
+    RateLimitError,
+)
+from llm.core.types import LLMInput, LLMOutput, ModelInfo, ProviderType, ToolCall
+from llm.providers.constants import EMPTY_FILTERED_RESPONSE_ERROR
+
+ATLAS_BASE_URL = "https://api.atlascloud.ai/v1"
+DEFAULT_ATLAS_MODEL = "deepseek-ai/deepseek-v4-pro"
+# Reasoning models need enough headroom for their thinking budget plus the answer.
+DEFAULT_ATLAS_MAX_TOKENS = 512
+
+
+def _parse_tool_arguments(raw_arguments: str | None) -> dict[str, Any]:
+    if not raw_arguments:
+        return {}
+
+    try:
+        arguments = json.loads(raw_arguments)
+    except json.JSONDecodeError:
+        return {"raw": raw_arguments}
+
+    if isinstance(arguments, dict):
+        return arguments
+    return {"value": arguments}
+
+
+class AtlasProvider(LLMProvider):
+    """Atlas Cloud endpoint using OpenAI-compatible chat completions.
+
+    Atlas Cloud (https://atlascloud.ai) exposes 300+ hosted models behind a
+    single OpenAI-compatible API, so it reuses the same chat-completions flow as
+    the other OpenAI-compatible adapters in this package.
+    """
+
+    provider_type = ProviderType.ATLAS
+    # ``.env.example`` documents ATLAS_API_KEY; ATLASCLOUD_API_KEY is the name used
+    # by the Atlas Cloud SDK/skill, so accept either for convenience.
+    api_key_env = "ATLAS_API_KEY"
+    fallback_api_key_env = "ATLASCLOUD_API_KEY"
+    base_url_env = "ATLAS_BASE_URL"
+    model_env = "ATLAS_MODEL"
+    default_base_url = ATLAS_BASE_URL
+
+    def __init__(
+        self,
+        api_key: str | None = None,
+        base_url: str | None = None,
+        default_model: str | None = None,
+    ) -> None:
+        self.api_key = (
+            api_key
+            or os.environ.get(self.api_key_env)
+            or os.environ.get(self.fallback_api_key_env)
+            or ""
+        )
+        self.base_url = base_url or os.environ.get(self.base_url_env, self.default_base_url)
+        env_model = os.environ.get(self.model_env)
+        self.default_model = default_model or env_model or DEFAULT_ATLAS_MODEL
+        self.client = OpenAI(api_key=self.api_key, base_url=self.base_url, _enforce_credentials=False)
+        self._models = [
+            ModelInfo(
+                name=self.default_model,
+                provider=self.provider_type,
+                supports_tools=True,
+                supports_vision=False,
+            )
+        ]
+
+    def generate(self, llm_input: LLMInput) -> LLMOutput:
+        try:
+            params: dict[str, Any] = {
+                "model": llm_input.model or self.default_model,
+                "messages": [msg.to_dict() for msg in llm_input.messages],
+            }
+            if llm_input.temperature != 1.0:
+                params["temperature"] = llm_input.temperature
+            # Atlas reasoning models spend tokens on a thinking budget before the
+            # answer, so floor max_tokens to avoid truncated/empty completions.
+            max_tokens = llm_input.max_tokens
+            if max_tokens is None or max_tokens < DEFAULT_ATLAS_MAX_TOKENS:
+                max_tokens = DEFAULT_ATLAS_MAX_TOKENS
+            params["max_tokens"] = max_tokens
+            if llm_input.tools:
+                params["tools"] = [tool.to_openai_tool() for tool in llm_input.tools]
+
+            response = self.client.chat.completions.create(**params)
+            if not response.choices or response.choices[0].message is None:
+                raise ValueError(EMPTY_FILTERED_RESPONSE_ERROR)
+            choice = response.choices[0]
+
+            tool_calls = None
+            if choice.message.tool_calls:
+                tool_calls = [
+                    ToolCall(
+                        id=tc.id or "",
+                        name=tc.function.name,
+                        arguments=_parse_tool_arguments(tc.function.arguments),
+                    )
+                    for tc in choice.message.tool_calls
+                ]
+
+            usage = None
+            if response.usage:
+                usage = {
+                    "prompt_tokens": response.usage.prompt_tokens,
+                    "completion_tokens": response.usage.completion_tokens,
+                    "total_tokens": response.usage.total_tokens,
+                }
+
+            return LLMOutput(
+                content=choice.message.content or "",
+                tool_calls=tool_calls,
+                model=response.model,
+                usage=usage,
+                stop_reason=choice.finish_reason,
+            )
+        except Exception as e:
+            msg = str(e)
+            if "401" in msg or "authentication" in msg.lower():
+                raise AuthenticationError(msg, provider=self.provider_type) from e
+            if "429" in msg or "rate_limit" in msg.lower():
+                raise RateLimitError(msg, provider=self.provider_type) from e
+            if "context" in msg.lower() and "length" in msg.lower():
+                raise ContextLengthError(msg, provider=self.provider_type) from e
+            raise
+
+    def list_models(self) -> list[ModelInfo]:
+        return self._models.copy()
+
+    def validate_config(self) -> bool:
+        return bool(self.api_key)
+
+    def get_default_model(self) -> str:
+        return self.default_model

src/llm/providers/resolver.py

@@ -8,6 +8,7 @@ from pathlib import Path
 from llm.core.interface import LLMProvider
 from llm.core.types import ProviderType
 from llm.providers.astraflow import AstraflowCNProvider, AstraflowProvider
+from llm.providers.atlas import AtlasProvider
 from llm.providers.claude import ClaudeProvider
 from llm.providers.openai import OpenAIProvider
 from llm.providers.ollama import OllamaProvider
@@ -16,6 +17,7 @@ from llm.providers.ollama import OllamaProvider
 _PROVIDER_MAP: dict[ProviderType, type[LLMProvider]] = {
     ProviderType.ASTRAFLOW: AstraflowProvider,
     ProviderType.ASTRAFLOW_CN: AstraflowCNProvider,
+    ProviderType.ATLAS: AtlasProvider,
     ProviderType.CLAUDE: ClaudeProvider,
     ProviderType.OPENAI: OpenAIProvider,
     ProviderType.OLLAMA: OllamaProvider,