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docs: add warning and troubleshooting for self-hosted LLM provider config bug (#1577)
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@ -39,6 +39,17 @@ With multiple providers configured, the first one in the order above is used.
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Image, video, and high-fidelity PDF understanding require a Gemini or Vertex AI key. Text ingestion, memory extraction, and search work with any provider.
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</Note>
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> [!WARNING]
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> **Known Issue: LLM Provider Configuration Bug (No model provider configured)**
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>
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> In version `v0.0.8` (and some previous releases), there is a known issue where document processing succeeds at first but the background memory generation fails with `[llm] No model provider configured. Set OPENAI_API_KEY ...`. This occurs even if `supermemory doctor` detects the provider (e.g. `llm provider openai` checks pass) and `OPENAI_API_KEY` is present in the parent process environment.
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>
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> **Root Cause:**
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> The LLM provider registry is instantiated inside a memoized initializer that runs exactly once when the server modules are loaded. Because the background `IngestContentWorkflow` runs in a sandboxed V8 isolate (Miniflare/workerd context), host environment variables on `process.env` are not automatically propagated to the sandbox. Additionally, if the credentials database was decrypted post-startup, the in-memory registry remains unpopulated for the worker.
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>
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> **Workaround:**
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> Ensure that `OPENAI_API_KEY` (or the relevant key for your provider) is exported in the shell environment **before** starting the `supermemory-server` process, and that the server is launched via the generated wrapper script (`~/.local/bin/supermemory-server`) which properly exports keys from `~/.supermemory/env` using `set -a`. If using a process manager (like systemd or PM2) or Docker, explicitly pass the environment variables to the service container/process.
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### Fully offline with local models
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`OPENAI_API_KEY` + `OPENAI_BASE_URL` covers any OpenAI-compatible endpoint: Ollama, LM Studio, vLLM, llama.cpp server, Together, Fireworks, and more.
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