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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>
70 lines
3.2 KiB
Markdown
70 lines
3.2 KiB
Markdown
# Atlas Cloud — LLM Provider Guide
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[Atlas Cloud](https://www.atlascloud.ai/?utm_source=github&utm_medium=link&utm_campaign=everything-claude-code) is a full-modal AI inference platform providing an OpenAI-compatible API for 59+ LLM models, image generation, and video generation.
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## Configuration
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Set the following environment variables to use Atlas Cloud as your LLM backend:
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```bash
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ATLAS_API_KEY=<your-atlascloud-api-key>
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ATLAS_BASE_URL=https://api.atlascloud.ai/v1
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```
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Or copy from `.env.example`:
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```bash
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cp .env.example .env
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# Then fill in ATLAS_API_KEY
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```
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## Install
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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:
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```bash
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export ATLAS_API_KEY=your-key-here
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export ATLAS_BASE_URL=https://api.atlascloud.ai/v1
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```
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## Available Models
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<details>
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<summary>All Atlas Cloud LLM models (59+)</summary>
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- **Anthropic**: `anthropic/claude-haiku-4.5-20251001`, `anthropic/claude-opus-4.8`, `anthropic/claude-sonnet-4.6`
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- **OpenAI**: `openai/gpt-5.4`, `openai/gpt-5.5`
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- **Google Gemini**: `google/gemini-3.1-flash-lite`, `google/gemini-3.1-pro-preview`, `google/gemini-3.5-flash`
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- **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`
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- **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`
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- **Kimi**: `moonshotai/Kimi-K2-Instruct`, `moonshotai/Kimi-K2-Instruct-0905`, `moonshotai/Kimi-K2-Thinking`, `moonshotai/kimi-k2.5`, `moonshotai/kimi-k2.6`
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- **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`
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- **MiniMax**: `MiniMaxAI/MiniMax-M2`, `minimaxai/minimax-m2.1`, `minimaxai/minimax-m2.5`, `minimaxai/minimax-m2.7`
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- **xAI**: `xai/grok-4.3`
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- **KAT**: `kwaipilot/kat-coder-pro-v2`
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- **Other**: `owl`
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</details>
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## Usage Example
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```python
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from openai import OpenAI
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import os
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client = OpenAI(
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api_key=os.environ["ATLAS_API_KEY"],
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base_url=os.environ.get("ATLAS_BASE_URL", "https://api.atlascloud.ai/v1"),
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)
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response = client.chat.completions.create(
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model="anthropic/claude-sonnet-4.6",
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messages=[{"role": "user", "content": "Hello from ECC + Atlas Cloud!"}],
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)
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print(response.choices[0].message.content)
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```
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## Get API Credits
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Visit [Atlas Cloud Coding Plan](https://www.atlascloud.ai/console/coding-plan) for API credits.
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