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* 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>
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Atlas Cloud — LLM Provider Guide
Atlas Cloud is a full-modal AI inference platform providing an OpenAI-compatible API for 59+ LLM models, image generation, and video generation.
Configuration
Set the following environment variables to use Atlas Cloud as your LLM backend:
ATLAS_API_KEY=<your-atlascloud-api-key>
ATLAS_BASE_URL=https://api.atlascloud.ai/v1
Or copy from .env.example:
cp .env.example .env
# Then fill in ATLAS_API_KEY
Install
ECC can install its managed surfaces into any OpenAI-compatible backend. To use Atlas Cloud with Claude Code (or any ECC-managed harness), set the base URL and API key:
export ATLAS_API_KEY=your-key-here
export ATLAS_BASE_URL=https://api.atlascloud.ai/v1
Available Models
All Atlas Cloud LLM models (59+)
- Anthropic:
anthropic/claude-haiku-4.5-20251001,anthropic/claude-opus-4.8,anthropic/claude-sonnet-4.6 - OpenAI:
openai/gpt-5.4,openai/gpt-5.5 - Google Gemini:
google/gemini-3.1-flash-lite,google/gemini-3.1-pro-preview,google/gemini-3.5-flash - Qwen:
qwen/qwen2.5-7b-instruct,Qwen/Qwen3-235B-A22B-Instruct-2507,qwen/qwen3-235b-a22b-thinking-2507,qwen/qwen3-30b-a3b,Qwen/Qwen3-30B-A3B-Instruct-2507,qwen/qwen3-30b-a3b-thinking-2507,qwen/qwen3-32b,qwen/qwen3-8b,Qwen/Qwen3-Coder,qwen/qwen3-coder-next,qwen/qwen3-max-2026-01-23,Qwen/Qwen3-Next-80B-A3B-Instruct,Qwen/Qwen3-Next-80B-A3B-Thinking,Qwen/Qwen3-VL-235B-A22B-Instruct,qwen/qwen3-vl-235b-a22b-thinking,qwen/qwen3-vl-30b-a3b-instruct,qwen/qwen3-vl-30b-a3b-thinking,qwen/qwen3-vl-8b-instruct,qwen/qwen3.5-122b-a10b,qwen/qwen3.5-27b,qwen/qwen3.5-35b-a3b,qwen/qwen3.5-397b-a17b,qwen/qwen3.6-35b-a3b,qwen/qwen3.6-plus - DeepSeek:
deepseek-ai/deepseek-ocr,deepseek-ai/deepseek-r1-0528,deepseek-ai/DeepSeek-V3-0324,deepseek-ai/DeepSeek-V3.1,deepseek-ai/DeepSeek-V3.1-Terminus,deepseek-ai/deepseek-v3.2,deepseek-ai/DeepSeek-V3.2-Exp,deepseek-ai/deepseek-v4-flash,deepseek-ai/deepseek-v4-pro - Kimi:
moonshotai/Kimi-K2-Instruct,moonshotai/Kimi-K2-Instruct-0905,moonshotai/Kimi-K2-Thinking,moonshotai/kimi-k2.5,moonshotai/kimi-k2.6 - GLM:
zai-org/GLM-4.6,zai-org/glm-4.7,zai-org/glm-5,zai-org/glm-5-turbo,zai-org/glm-5.1,zai-org/glm-5v-turbo - MiniMax:
MiniMaxAI/MiniMax-M2,minimaxai/minimax-m2.1,minimaxai/minimax-m2.5,minimaxai/minimax-m2.7 - xAI:
xai/grok-4.3 - KAT:
kwaipilot/kat-coder-pro-v2 - Other:
owl
Usage Example
from openai import OpenAI
import os
client = OpenAI(
api_key=os.environ["ATLAS_API_KEY"],
base_url=os.environ.get("ATLAS_BASE_URL", "https://api.atlascloud.ai/v1"),
)
response = client.chat.completions.create(
model="anthropic/claude-sonnet-4.6",
messages=[{"role": "user", "content": "Hello from ECC + Atlas Cloud!"}],
)
print(response.choices[0].message.content)
Get API Credits
Visit Atlas Cloud Coding Plan for API credits.