feat(memory): add embedding hint routes and upgrade guidance
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8 changed files with 449 additions and 15 deletions
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@ -143,3 +143,56 @@ Then call with a hint model name (for example from tool or integration paths):
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```text
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hint:reasoning
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```
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## Embedding Routing (`hint:<name>`)
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You can route embedding calls with the same hint pattern using `[[embedding_routes]]`.
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Set `[memory].embedding_model` to a `hint:<name>` value to activate routing.
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```toml
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[memory]
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embedding_model = "hint:semantic"
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[[embedding_routes]]
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hint = "semantic"
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provider = "openai"
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model = "text-embedding-3-small"
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dimensions = 1536
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[[embedding_routes]]
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hint = "archive"
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provider = "custom:https://embed.example.com/v1"
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model = "your-embedding-model-id"
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dimensions = 1024
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```
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Supported embedding providers:
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- `none`
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- `openai`
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- `custom:<url>` (OpenAI-compatible embeddings endpoint)
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Optional per-route key override:
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```toml
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[[embedding_routes]]
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hint = "semantic"
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provider = "openai"
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model = "text-embedding-3-small"
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api_key = "sk-route-specific"
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```
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## Upgrading Models Safely
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Use stable hints and update only route targets when providers deprecate model IDs.
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Recommended workflow:
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1. Keep call sites stable (`hint:reasoning`, `hint:semantic`).
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2. Change only the target model under `[[model_routes]]` or `[[embedding_routes]]`.
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3. Run:
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- `zeroclaw doctor`
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- `zeroclaw status`
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4. Smoke test one representative flow (chat + memory retrieval) before rollout.
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This minimizes breakage because integrations and prompts do not need to change when model IDs are upgraded.
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