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feat: add Atlas Cloud as an OpenAI-compatible LLM provider#2362

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nicoloboschi merged 1 commit into
vectorize-io:mainfrom
lucaszhu-hue:feat/atlascloud-provider
Jun 23, 2026
Merged

feat: add Atlas Cloud as an OpenAI-compatible LLM provider#2362
nicoloboschi merged 1 commit into
vectorize-io:mainfrom
lucaszhu-hue:feat/atlascloud-provider

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Summary

Adds Atlas Cloud as a first-class OpenAI-compatible LLM provider for Hindsight.

Atlas Cloud is a full-modal, OpenAI-compatible AI inference platform that gives one API access to DeepSeek, Qwen, GLM, Kimi, MiniMax and more. Because its /v1/chat/completions endpoint is OpenAI-compatible, it drops straight into the existing OpenAICompatibleLLM path — exactly like the deepseek / zai / opencode-go providers already in the tree.

Enable it for fact extraction, reflection and consolidation with:

export HINDSIGHT_API_LLM_PROVIDER=atlas
export HINDSIGHT_API_LLM_API_KEY=your-atlascloud-api-key   # base_url defaults to https://api.atlascloud.ai/v1
export HINDSIGHT_API_LLM_MODEL=deepseek-ai/deepseek-v4-pro

deepseek-ai/deepseek-v4-pro is a reasoning model, so it needs enough max_tokens (>= 512) — otherwise tokens get spent on the chain of thought and content can come back empty.

Changes

  • engine/llm_wrapper.py — register "atlas" in create_llm_provider(), in LLMProvider's valid_providers, and add its default base URL (https://api.atlascloud.ai/v1).
  • engine/providers/openai_compatible_llm.py — register "atlas" in valid_providers, default base URL, and the API-key-required check.
  • config.pyPROVIDER_DEFAULT_MODELS["atlas"] = "deepseek-ai/deepseek-v4-pro".
  • hindsight-embed control center — add Atlas Cloud to the config-wizard provider catalog.
  • docs — add Atlas Cloud to llmProviders.json (drives the providers grid + table) and a config example in developer/models.mdx.
  • README + .env.example — document the new provider.

No new dependencies; reuses the existing OpenAI-compatible client path.

Testing

Verified end-to-end through Hindsight's own code path: instantiated the provider via create_llm_provider(provider="atlas", ...) (confirmed it returns OpenAICompatibleLLM, resolves base_url=https://api.atlascloud.ai/v1 and the default model) and made a live call() to deepseek-ai/deepseek-v4-pro — HTTP 200, correct content, valid token usage. py_compile and JSON validation pass on all touched files.

Note

I help maintain Atlas Cloud and we're happy to support Hindsight users on the platform — glad to adjust naming/defaults or add follow-ups (e.g. embeddings) to match your conventions. Thanks for building Hindsight!

Atlas Cloud (https://www.atlascloud.ai) exposes an OpenAI-compatible
chat/completions endpoint, so it slots into the existing
OpenAICompatibleLLM path exactly like deepseek / zai / opencode-go.

Set `HINDSIGHT_API_LLM_PROVIDER=atlas` to route fact extraction,
reflection and consolidation through Atlas Cloud. The base URL defaults
to https://api.atlascloud.ai/v1 and the default model is
deepseek-ai/deepseek-v4-pro (a reasoning model — give it enough
max_tokens, >= 512).

Changes:
- engine/llm_wrapper.py: register "atlas" in create_llm_provider(),
  LLMProvider.valid_providers, and the default base_url map
- engine/providers/openai_compatible_llm.py: register "atlas" in
  valid_providers, default base_url, and the API-key-required check
- config.py: PROVIDER_DEFAULT_MODELS["atlas"] = deepseek-ai/deepseek-v4-pro
- hindsight-embed control center: add Atlas Cloud to the provider wizard
- docs: add Atlas Cloud to llmProviders.json (drives the providers grid
  and table) and a config example in developer/models.mdx
- README + .env.example: document the new provider

Verified end-to-end: instantiated the atlas provider through Hindsight's
own create_llm_provider() and made a live call() to
deepseek-ai/deepseek-v4-pro (HTTP 200, valid content + token usage).

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

@nicoloboschi nicoloboschi left a comment

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Provider wiring is clean and mirrors the opencode-go pattern correctly across config.py, llm_wrapper.py, and openai_compatible_llm.py. Approving to merge.

@nicoloboschi nicoloboschi merged commit f8d2776 into vectorize-io:main Jun 23, 2026
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