## 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 Aliyun Go driver has a stub `Rerank` method that always returns
`"Aliyun, Rerank not implemented"`. DashScope exposes an
OpenAI-compatible rerank endpoint (`compatible-mode/v1/rerank`) and
hosts dedicated bilingual rerankers (`gte-rerank-v2`, `gte-rerank`) that
are a natural pairing with the embedding models already in
`aliyun.json`. Without this, Aliyun users cannot use reranking within
RAGFlow.
Closes#14675
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
### What problem does this PR solve?
The Aliyun Go driver shipped with a stub \`Encode\` method that returned
\`no such method\`, even though \`conf/models/aliyun.json\` already
wires the OpenAI-compatible embeddings URL suffix at
\`compatible-mode/v1/embeddings\`. The same config also did not list any
embedding models, so the picker had nothing to select.
So an Aliyun tenant who wanted to use Tongyi text-embedding-v3 or v4 in
the Go layer could not, even though the upstream endpoint is public and
uses the standard \`POST /v1/embeddings\` shape that the SiliconFlow and
ZhipuAI
drivers already support.
This PR fills the gap.
### What this PR includes
- \`conf/models/aliyun.json\`: add \`text-embedding-v4\` and
\`text-embedding-v3\` to the \`models\` array.
- \`internal/entity/models/aliyun.go\`: replace the \`Encode\` stub with
a real implementation. Adds a small local response type that matches the
OpenAI-compatible shape.
No factory change. No interface change.
### How the driver works
- Validate \`apiConfig\` and the API key, validate the model name,
resolve the region with a default fallback, build the
URL from \`BaseURL[region] + URLSuffix.Embedding\`.
- Send all input texts in one request as the \`input\` array, the same
OpenAI-compatible shape the SiliconFlow \`Encode\`
uses.
- Parse \`data[*].embedding\` and copy each slice into a \`[][]float64\`
indexed by \`data[*].index\` so the output order matches the input order
even if the API returns items in a different order.
- Handle both \`float64\` and \`float32\` element types.
- Empty input returns \`[][]float64{}\` with no HTTP call.
- Non-200 responses propagate the upstream status line and body.
- A final pass checks every input slot got a vector and returns a clear
error if any slot is still nil.
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
### How was this tested?
- \`go build ./internal/entity/models/...\` in a clean go 1.25 image
returns exit 0.
- The full method set on \`AliyunModel\` still matches the
\`ModelDriver\` interface.
- Pattern parity with the existing SiliconFlow Encode implementation.
Closes#14646
---------
Co-authored-by: Jin Hai <haijin.chn@gmail.com>
### What problem does this PR solve?
As title.
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
---------
Signed-off-by: Jin Hai <haijin.chn@gmail.com>
