providers.template.yaml was a Raycast AI template. It named Raycast in its comments
and used api_keys/abilities/context — none of which provider_registry.py reads, while
omitting user_api_key and server_api_key_env, which it requires. Anyone copying it
got a file the application ignored. Replaced with one matching the code, covering
vLLM, Ollama, OpenRouter, Berget, OpenAI and Gemini.
docs/SETUP.md is written to be executed rather than skimmed: what the four external
dependencies are and which are optional, how to choose between providers, and a
verification command after every step that calls the real thing. Chat and tool calling
are checked separately, because a model can hold a conversation perfectly and still
never call a tool — which in this project means confident answers with no sources, the
one failure mode that matters most here.
Embeddings get their own section because they are a separate endpoint from chat and
conflating the two is the most common setup mistake, and because the dimension is
load-bearing: changing the model means re-embedding the whole corpus.
Ends with a symptom/cause/fix table covering the traps found during the production
cutover — the EnvironmentFile parsing difference, app.fts_config not surviving a
restore, and .env being unsourceable in bash.
Verified: every verification block in the guide was run against the live deployment.
