## Summary
- Verify and populate `content_length` (context window) and `max_output`
(max generation tokens) for all **478 chat/vision models** across **47
provider configs**
- Data sourced from **official API documentation** via 12 parallel
agents + targeted web verification
- Update Go test assertions to match verified values
Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
### What problem does this PR solve?
The Upstage Go driver landed in #14817 with chat, list models, and check
connection. `Embed` was left as a stub that returns `"not implemented"`.
This PR fills the gap.
Upstage exposes an OpenAI-compatible embeddings endpoint at
`https://api.upstage.ai/v1/solar/embeddings` via the
`solar-embedding-1-large` family (`solar-embedding-1-large-query` for
queries, `solar-embedding-1-large-passage` for passages), and the Python
side has had `UpstageEmbed(OpenAIEmbed)` in `rag/llm/embedding_model.py`
for a long time targeting this same path. The existing
`conf/models/upstage.json` did not list any embedding model out of the
box, so a tenant who wanted to use Upstage end to end could not run an
embedding call. This PR fills the gap.
### What this PR includes
- `conf/models/upstage.json`: add `"embedding": "embeddings"` under
`url_suffix` so the driver can build the URL from config (matches the
`URLSuffix.Embedding` field already used by openai, mistral,
siliconflow, zhipu-ai), and add `solar-embedding-1-large-query` and
`solar-embedding-1-large-passage` entries under `models`.
- `internal/entity/models/upstage.go`: replace the `Embed` stub with a
real implementation that POSTs to `/v1/solar/embeddings`. Adds local
response types `upstageEmbeddingData` and `upstageEmbeddingResponse`.
No factory change. No interface change.
### How the implementation works
- Validate `apiConfig`, the API key, and the model name. Use the
existing `baseURLForRegion` helper so an unknown region fails fast with
a clear error.
- Wrap the request with `context.WithTimeout(nonStreamCallTimeout)` so
the call has a clear deadline. Same pattern as `ChatWithMessages` and
`ListModels` already use in this file.
- Send all input texts in one request. The Upstage API accepts the
`input` field as an array.
- Parse `data[*].embedding` and copy each slice into a `[]EmbeddingData`
indexed by `data[*].index` so the output order matches the input order
even if the API returns items in a different order.
- An empty input slice returns `[]EmbeddingData{}` with no HTTP call.
- Non-200 responses propagate the upstream status line and body.
- A final pass checks that every input slot got a vector. If any slot is
still empty, return a clear error so the caller does not silently use a
zero vector.
### Note on stacking
This PR builds on #14817 (the Upstage driver). Until #14817 merges, this
PR's diff on GitHub will include both that PR's commits and this one.
After #14817 lands on `main`, GitHub will auto-reduce this PR to only
the `Embed` changes (one commit, ~119 line diff in `upstage.go` plus ~15
lines in `upstage.json`).
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
### How was this tested?
- `go build ./internal/entity/models/...` returns exit 0 on go 1.25 (the
`go.mod` minimum).
- The full method set on `UpstageModel` still matches the `ModelDriver`
interface.
- Pattern parity with the existing Mistral Embed
(`internal/entity/models/mistral.go`) and OpenAI Embed
(`internal/entity/models/openai.go`) implementations.
Closes#14818
Depends on #14817
Tracking: #14736
---------
Co-authored-by: Jin Hai <haijin.chn@gmail.com>
