2026-05-07 14:17:57 +08:00
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|
{
|
|
|
|
|
"name": "Nvidia",
|
|
|
|
|
"url": {
|
|
|
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|
"default": "https://integrate.api.nvidia.com/v1"
|
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|
},
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"url_suffix": {
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"chat": "chat/completions",
|
Go: implement Encode (embeddings) in NVIDIA driver (#14700)
### What problem does this PR solve?
The NVIDIA Go driver in `internal/entity/models/nvidia.go` shipped with
a stub `Encode`
method that returned `no such method`. `conf/models/nvidia.json` already
lists
`nvidia/llama-3.2-nemoretriever-1b-vlm-embed-v1` as an embedding model,
but the conf had
no `embedding` URL suffix, so the picker had nothing wired even if
`Encode` worked.
A tenant who wanted to use NVIDIA NIM for chat (already working) and
embeddings from a
single provider could not, even though the upstream endpoint is public
at
`https://integrate.api.nvidia.com/v1/embeddings` and uses an
OpenAI-compatible request
body extended with the NVIDIA-specific `input_type` and `truncate`
fields. Several other
Go drivers already implement `Encode` (siliconflow, zhipu-ai, aliyun),
so the interface
and the pattern are well-established.
This PR fills the gap.
### What this PR includes
* `conf/models/nvidia.json`: declare the `embedding` URL suffix
alongside the existing
`chat` and `models` entries. The embedding model entry was already
present, so no
model addition is needed.
* `internal/entity/models/nvidia.go`: replace the `Encode` stub with a
real
implementation. Adds a small local response type that matches the
OpenAI-compatible
shape NVIDIA NIM returns.
No factory change. No interface change.
### How the driver works
* Validates `apiConfig` and the API key, validates the model name,
resolves the region
with a default fallback (matching the pattern the merged `ListModels`
and
`CheckConnection` paths in this driver already use), and builds the URL
from
`BaseURL[region] + URLSuffix.Embedding`.
* Sends all input texts in one request as the `input` array, with the
NVIDIA-specific `input_type: "query"`, `encoding_format: "float"`, and
`truncate: "END"`
fields, mirroring the Python `NvidiaEmbed` reference.
* Parses `data[*].embedding` and copies each slice into `[][]float64`
indexed by
`data[*].index` so the output order matches the input order even if the
API returns
items in a different order.
* Handles 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.
* Per-call 30s context deadline so a slow call cannot block forever.
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
### How was this tested?
* `go build ./internal/entity/models/...` returns exit 0.
* `go vet ./internal/entity/models/...` is clean.
* `gofmt -l internal/entity/models/nvidia.go` is clean.
* The full method set on `NvidiaModel` still matches the `ModelDriver`
interface.
* Pattern parity with the just-merged Aliyun `Encode` (#14647).
Closes #14699
2026-05-10 18:50:50 -10:00
|
|
|
"models": "models",
|
2026-05-11 11:21:16 +02:00
|
|
|
"embedding": "embeddings",
|
|
|
|
|
"rerank": "ranking"
|
2026-05-07 14:17:57 +08:00
|
|
|
},
|
|
|
|
|
"class": "nvidia",
|
|
|
|
|
"models": [
|
|
|
|
|
{
|
|
|
|
|
"name": "abacusai/dracarys-llama-3.1-70b-instruct",
|
|
|
|
|
"max_tokens": 131072,
|
|
|
|
|
"model_types": [
|
|
|
|
|
"chat"
|
|
|
|
|
]
|
|
|
|
|
},
|
Go: implement Encode (embeddings) in NVIDIA driver (#14700)
### What problem does this PR solve?
The NVIDIA Go driver in `internal/entity/models/nvidia.go` shipped with
a stub `Encode`
method that returned `no such method`. `conf/models/nvidia.json` already
lists
`nvidia/llama-3.2-nemoretriever-1b-vlm-embed-v1` as an embedding model,
but the conf had
no `embedding` URL suffix, so the picker had nothing wired even if
`Encode` worked.
A tenant who wanted to use NVIDIA NIM for chat (already working) and
embeddings from a
single provider could not, even though the upstream endpoint is public
at
`https://integrate.api.nvidia.com/v1/embeddings` and uses an
OpenAI-compatible request
body extended with the NVIDIA-specific `input_type` and `truncate`
fields. Several other
Go drivers already implement `Encode` (siliconflow, zhipu-ai, aliyun),
so the interface
and the pattern are well-established.
This PR fills the gap.
### What this PR includes
* `conf/models/nvidia.json`: declare the `embedding` URL suffix
alongside the existing
`chat` and `models` entries. The embedding model entry was already
present, so no
model addition is needed.
* `internal/entity/models/nvidia.go`: replace the `Encode` stub with a
real
implementation. Adds a small local response type that matches the
OpenAI-compatible
shape NVIDIA NIM returns.
No factory change. No interface change.
### How the driver works
* Validates `apiConfig` and the API key, validates the model name,
resolves the region
with a default fallback (matching the pattern the merged `ListModels`
and
`CheckConnection` paths in this driver already use), and builds the URL
from
`BaseURL[region] + URLSuffix.Embedding`.
* Sends all input texts in one request as the `input` array, with the
NVIDIA-specific `input_type: "query"`, `encoding_format: "float"`, and
`truncate: "END"`
fields, mirroring the Python `NvidiaEmbed` reference.
* Parses `data[*].embedding` and copies each slice into `[][]float64`
indexed by
`data[*].index` so the output order matches the input order even if the
API returns
items in a different order.
* Handles 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.
* Per-call 30s context deadline so a slow call cannot block forever.
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
### How was this tested?
* `go build ./internal/entity/models/...` returns exit 0.
* `go vet ./internal/entity/models/...` is clean.
* `gofmt -l internal/entity/models/nvidia.go` is clean.
* The full method set on `NvidiaModel` still matches the `ModelDriver`
interface.
* Pattern parity with the just-merged Aliyun `Encode` (#14647).
Closes #14699
2026-05-10 18:50:50 -10:00
|
|
|
{
|
|
|
|
|
"name": "baai/bge-m3",
|
|
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"max_tokens": 8192,
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"model_types": [
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"embedding"
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]
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},
|
2026-05-07 14:17:57 +08:00
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{
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"name": "bytedance/seed-oss-36b-instruct",
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"max_tokens": 32768,
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"model_types": [
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"chat"
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]
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},
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"name": "deepseek-ai/deepseek-v4-flash",
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"max_tokens": 1048576,
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"model_types": [
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"chat"
|
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]
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},
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{
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"name": "deepseek-ai/deepseek-v4-pro",
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"name": "deepseek-ai/deepseek-v3.2",
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"max_tokens": 131072,
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"thinking": {
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"default_value": true,
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"clear_thinking": true
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}
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},
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"name": "deepseek-ai/deepseek-v3.1",
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"thinking": {
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"default_value": true,
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"clear_thinking": true
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}
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"name": "google/codegemma-7b",
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"name": "google/gemma-2-2b-it",
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"name": "google/gemma-4-31b-it",
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"max_tokens": 131072,
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{
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"name": "google/gemma-7b",
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"name": "ibm/granite-3.3-8b-instruct",
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"name": "meta/llama-3.1-405b-instruct",
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"name": "meta/llama-3.2-90b-vision-instruct",
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"name": "meta/llama-4-maverick-17b-128e-instruct",
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"name": "moonshotai/kimi-k2-thinking",
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"thinking": {
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"default_value": true,
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"clear_thinking": true
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"name": "nvidia/gliner-pii",
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"max_tokens": 4096,
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"model_types": [
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"max_tokens": 131072,
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"max_tokens": 131072,
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{
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"name": "nvidia/llama-3.1-nemotron-nano-8b-v1",
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"max_tokens": 8192,
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"model_types": [
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|
|
|
|
},
|
|
|
|
|
{
|
|
|
|
|
"name": "nvidia/llama-3.1-nemotron-safety-guard-8b-v3",
|
|
|
|
|
"max_tokens": 131072,
|
|
|
|
|
"model_types": [
|
|
|
|
|
"chat"
|
|
|
|
|
]
|
|
|
|
|
},
|
|
|
|
|
{
|
|
|
|
|
"name": "nvidia/llama-3.1-nemotron-ultra-253b-v1",
|
|
|
|
|
"max_tokens": 131072,
|
|
|
|
|
"model_types": [
|
|
|
|
|
"chat"
|
|
|
|
|
],
|
|
|
|
|
"thinking": {
|
|
|
|
|
"default_value": true,
|
|
|
|
|
"clear_thinking": true
|
|
|
|
|
}
|
|
|
|
|
},
|
|
|
|
|
{
|
|
|
|
|
"name": "nvidia/llama-3.2-nemoretriever-1b-vlm-embed-v1",
|
|
|
|
|
"max_tokens": 8192,
|
|
|
|
|
"model_types": [
|
|
|
|
|
"embedding"
|
|
|
|
|
]
|
|
|
|
|
},
|
Go: implement Encode (embeddings) in NVIDIA driver (#14700)
### What problem does this PR solve?
The NVIDIA Go driver in `internal/entity/models/nvidia.go` shipped with
a stub `Encode`
method that returned `no such method`. `conf/models/nvidia.json` already
lists
`nvidia/llama-3.2-nemoretriever-1b-vlm-embed-v1` as an embedding model,
but the conf had
no `embedding` URL suffix, so the picker had nothing wired even if
`Encode` worked.
A tenant who wanted to use NVIDIA NIM for chat (already working) and
embeddings from a
single provider could not, even though the upstream endpoint is public
at
`https://integrate.api.nvidia.com/v1/embeddings` and uses an
OpenAI-compatible request
body extended with the NVIDIA-specific `input_type` and `truncate`
fields. Several other
Go drivers already implement `Encode` (siliconflow, zhipu-ai, aliyun),
so the interface
and the pattern are well-established.
This PR fills the gap.
### What this PR includes
* `conf/models/nvidia.json`: declare the `embedding` URL suffix
alongside the existing
`chat` and `models` entries. The embedding model entry was already
present, so no
model addition is needed.
* `internal/entity/models/nvidia.go`: replace the `Encode` stub with a
real
implementation. Adds a small local response type that matches the
OpenAI-compatible
shape NVIDIA NIM returns.
No factory change. No interface change.
### How the driver works
* Validates `apiConfig` and the API key, validates the model name,
resolves the region
with a default fallback (matching the pattern the merged `ListModels`
and
`CheckConnection` paths in this driver already use), and builds the URL
from
`BaseURL[region] + URLSuffix.Embedding`.
* Sends all input texts in one request as the `input` array, with the
NVIDIA-specific `input_type: "query"`, `encoding_format: "float"`, and
`truncate: "END"`
fields, mirroring the Python `NvidiaEmbed` reference.
* Parses `data[*].embedding` and copies each slice into `[][]float64`
indexed by
`data[*].index` so the output order matches the input order even if the
API returns
items in a different order.
* Handles 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.
* Per-call 30s context deadline so a slow call cannot block forever.
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
### How was this tested?
* `go build ./internal/entity/models/...` returns exit 0.
* `go vet ./internal/entity/models/...` is clean.
* `gofmt -l internal/entity/models/nvidia.go` is clean.
* The full method set on `NvidiaModel` still matches the `ModelDriver`
interface.
* Pattern parity with the just-merged Aliyun `Encode` (#14647).
Closes #14699
2026-05-10 18:50:50 -10:00
|
|
|
{
|
|
|
|
|
"name": "nvidia/llama-3.2-nv-embedqa-1b-v2",
|
|
|
|
|
"max_tokens": 8192,
|
|
|
|
|
"model_types": [
|
|
|
|
|
"embedding"
|
|
|
|
|
]
|
|
|
|
|
},
|
2026-05-07 14:17:57 +08:00
|
|
|
{
|
|
|
|
|
"name": "nvidia/llama-3.3-nemotron-super-49b-v1",
|
|
|
|
|
"max_tokens": 131072,
|
|
|
|
|
"model_types": [
|
|
|
|
|
"chat"
|
|
|
|
|
]
|
|
|
|
|
},
|
|
|
|
|
{
|
|
|
|
|
"name": "nvidia/llama-3.3-nemotron-super-49b-v1.5",
|
|
|
|
|
"max_tokens": 131072,
|
|
|
|
|
"model_types": [
|
|
|
|
|
"chat"
|
|
|
|
|
],
|
|
|
|
|
"thinking": {
|
|
|
|
|
"default_value": true,
|
|
|
|
|
"clear_thinking": true
|
|
|
|
|
}
|
|
|
|
|
},
|
|
|
|
|
{
|
|
|
|
|
"name": "nvidia/nemoguard-jailbreak-detect",
|
|
|
|
|
"max_tokens": 4096,
|
|
|
|
|
"model_types": [
|
|
|
|
|
"chat"
|
|
|
|
|
]
|
|
|
|
|
},
|
|
|
|
|
{
|
|
|
|
|
"name": "nvidia/nemotron-3-nano-30b-a3b",
|
|
|
|
|
"max_tokens": 131072,
|
|
|
|
|
"model_types": [
|
|
|
|
|
"chat"
|
|
|
|
|
]
|
|
|
|
|
},
|
|
|
|
|
{
|
|
|
|
|
"name": "nvidia/nemotron-3-nano-omni-30b-a3b-reasoning",
|
|
|
|
|
"max_tokens": 131072,
|
|
|
|
|
"model_types": [
|
|
|
|
|
"chat",
|
|
|
|
|
"vision"
|
|
|
|
|
],
|
|
|
|
|
"thinking": {
|
|
|
|
|
"default_value": true,
|
|
|
|
|
"clear_thinking": true
|
|
|
|
|
}
|
|
|
|
|
},
|
|
|
|
|
{
|
|
|
|
|
"name": "nvidia/nemotron-3-super-120b-a12b",
|
|
|
|
|
"max_tokens": 131072,
|
|
|
|
|
"model_types": [
|
|
|
|
|
"chat"
|
|
|
|
|
]
|
|
|
|
|
},
|
|
|
|
|
{
|
|
|
|
|
"name": "nvidia/nemotron-content-safety-reasoning-4b",
|
|
|
|
|
"max_tokens": 8192,
|
|
|
|
|
"model_types": [
|
|
|
|
|
"chat"
|
|
|
|
|
]
|
|
|
|
|
},
|
|
|
|
|
{
|
|
|
|
|
"name": "nvidia/nemotron-mini-4b-instruct",
|
|
|
|
|
"max_tokens": 4096,
|
|
|
|
|
"model_types": [
|
|
|
|
|
"chat"
|
|
|
|
|
]
|
|
|
|
|
},
|
Go: implement Encode (embeddings) in NVIDIA driver (#14700)
### What problem does this PR solve?
The NVIDIA Go driver in `internal/entity/models/nvidia.go` shipped with
a stub `Encode`
method that returned `no such method`. `conf/models/nvidia.json` already
lists
`nvidia/llama-3.2-nemoretriever-1b-vlm-embed-v1` as an embedding model,
but the conf had
no `embedding` URL suffix, so the picker had nothing wired even if
`Encode` worked.
A tenant who wanted to use NVIDIA NIM for chat (already working) and
embeddings from a
single provider could not, even though the upstream endpoint is public
at
`https://integrate.api.nvidia.com/v1/embeddings` and uses an
OpenAI-compatible request
body extended with the NVIDIA-specific `input_type` and `truncate`
fields. Several other
Go drivers already implement `Encode` (siliconflow, zhipu-ai, aliyun),
so the interface
and the pattern are well-established.
This PR fills the gap.
### What this PR includes
* `conf/models/nvidia.json`: declare the `embedding` URL suffix
alongside the existing
`chat` and `models` entries. The embedding model entry was already
present, so no
model addition is needed.
* `internal/entity/models/nvidia.go`: replace the `Encode` stub with a
real
implementation. Adds a small local response type that matches the
OpenAI-compatible
shape NVIDIA NIM returns.
No factory change. No interface change.
### How the driver works
* Validates `apiConfig` and the API key, validates the model name,
resolves the region
with a default fallback (matching the pattern the merged `ListModels`
and
`CheckConnection` paths in this driver already use), and builds the URL
from
`BaseURL[region] + URLSuffix.Embedding`.
* Sends all input texts in one request as the `input` array, with the
NVIDIA-specific `input_type: "query"`, `encoding_format: "float"`, and
`truncate: "END"`
fields, mirroring the Python `NvidiaEmbed` reference.
* Parses `data[*].embedding` and copies each slice into `[][]float64`
indexed by
`data[*].index` so the output order matches the input order even if the
API returns
items in a different order.
* Handles 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.
* Per-call 30s context deadline so a slow call cannot block forever.
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
### How was this tested?
* `go build ./internal/entity/models/...` returns exit 0.
* `go vet ./internal/entity/models/...` is clean.
* `gofmt -l internal/entity/models/nvidia.go` is clean.
* The full method set on `NvidiaModel` still matches the `ModelDriver`
interface.
* Pattern parity with the just-merged Aliyun `Encode` (#14647).
Closes #14699
2026-05-10 18:50:50 -10:00
|
|
|
{
|
|
|
|
|
"name": "nvidia/nv-embed-v1",
|
|
|
|
|
"max_tokens": 32768,
|
|
|
|
|
"model_types": [
|
|
|
|
|
"embedding"
|
|
|
|
|
]
|
|
|
|
|
},
|
|
|
|
|
{
|
|
|
|
|
"name": "nvidia/nv-embedqa-e5-v5",
|
|
|
|
|
"max_tokens": 512,
|
|
|
|
|
"model_types": [
|
|
|
|
|
"embedding"
|
|
|
|
|
]
|
|
|
|
|
},
|
|
|
|
|
{
|
|
|
|
|
"name": "nvidia/nv-embedqa-mistral-7b-v2",
|
|
|
|
|
"max_tokens": 512,
|
|
|
|
|
"model_types": [
|
|
|
|
|
"embedding"
|
|
|
|
|
]
|
|
|
|
|
},
|
2026-05-11 11:21:16 +02:00
|
|
|
{
|
|
|
|
|
"name": "nvidia/nv-rerankqa-mistral-4b-v3",
|
|
|
|
|
"max_tokens": 4096,
|
|
|
|
|
"model_types": [
|
|
|
|
|
"rerank"
|
|
|
|
|
]
|
|
|
|
|
},
|
|
|
|
|
{
|
|
|
|
|
"name": "nvidia/llama-3.2-nv-rerankqa-1b-v2",
|
|
|
|
|
"max_tokens": 4096,
|
|
|
|
|
"model_types": [
|
|
|
|
|
"rerank"
|
|
|
|
|
]
|
|
|
|
|
},
|
2026-05-07 14:17:57 +08:00
|
|
|
{
|
|
|
|
|
"name": "nvidia/nvidia-nemotron-nano-9b-v2",
|
|
|
|
|
"max_tokens": 131072,
|
|
|
|
|
"model_types": [
|
|
|
|
|
"chat"
|
|
|
|
|
]
|
|
|
|
|
},
|
|
|
|
|
{
|
|
|
|
|
"name": "nvidia/riva-translate-4b-instruct-v1_1",
|
|
|
|
|
"max_tokens": 4096,
|
|
|
|
|
"model_types": [
|
|
|
|
|
"chat"
|
|
|
|
|
]
|
|
|
|
|
},
|
|
|
|
|
{
|
|
|
|
|
"name": "nvidia/usdcode",
|
|
|
|
|
"max_tokens": 8192,
|
|
|
|
|
"model_types": [
|
|
|
|
|
"chat"
|
|
|
|
|
]
|
|
|
|
|
},
|
|
|
|
|
{
|
|
|
|
|
"name": "openai/gpt-oss-120b",
|
|
|
|
|
"max_tokens": 131072,
|
|
|
|
|
"model_types": [
|
|
|
|
|
"chat"
|
|
|
|
|
]
|
|
|
|
|
},
|
|
|
|
|
{
|
|
|
|
|
"name": "qwen/qwen2.5-coder-7b-instruct",
|
|
|
|
|
"max_tokens": 32768,
|
|
|
|
|
"model_types": [
|
|
|
|
|
"chat"
|
|
|
|
|
]
|
|
|
|
|
},
|
|
|
|
|
{
|
|
|
|
|
"name": "qwen/qwen3-5-122b-a10b",
|
|
|
|
|
"max_tokens": 131072,
|
|
|
|
|
"model_types": [
|
|
|
|
|
"chat"
|
|
|
|
|
]
|
|
|
|
|
},
|
|
|
|
|
{
|
|
|
|
|
"name": "qwen/qwen3-235b-a22b",
|
|
|
|
|
"max_tokens": 131072,
|
|
|
|
|
"model_types": [
|
|
|
|
|
"chat"
|
|
|
|
|
],
|
|
|
|
|
"thinking": {
|
|
|
|
|
"default_value": true,
|
|
|
|
|
"clear_thinking": true
|
|
|
|
|
}
|
|
|
|
|
},
|
|
|
|
|
{
|
|
|
|
|
"name": "qwen/qwen3-coder-480b-a35b-instruct",
|
|
|
|
|
"max_tokens": 262144,
|
|
|
|
|
"model_types": [
|
|
|
|
|
"chat"
|
|
|
|
|
],
|
|
|
|
|
"thinking": {
|
|
|
|
|
"default_value": true,
|
|
|
|
|
"clear_thinking": true
|
|
|
|
|
}
|
|
|
|
|
},
|
Go: implement Encode (embeddings) in NVIDIA driver (#14700)
### What problem does this PR solve?
The NVIDIA Go driver in `internal/entity/models/nvidia.go` shipped with
a stub `Encode`
method that returned `no such method`. `conf/models/nvidia.json` already
lists
`nvidia/llama-3.2-nemoretriever-1b-vlm-embed-v1` as an embedding model,
but the conf had
no `embedding` URL suffix, so the picker had nothing wired even if
`Encode` worked.
A tenant who wanted to use NVIDIA NIM for chat (already working) and
embeddings from a
single provider could not, even though the upstream endpoint is public
at
`https://integrate.api.nvidia.com/v1/embeddings` and uses an
OpenAI-compatible request
body extended with the NVIDIA-specific `input_type` and `truncate`
fields. Several other
Go drivers already implement `Encode` (siliconflow, zhipu-ai, aliyun),
so the interface
and the pattern are well-established.
This PR fills the gap.
### What this PR includes
* `conf/models/nvidia.json`: declare the `embedding` URL suffix
alongside the existing
`chat` and `models` entries. The embedding model entry was already
present, so no
model addition is needed.
* `internal/entity/models/nvidia.go`: replace the `Encode` stub with a
real
implementation. Adds a small local response type that matches the
OpenAI-compatible
shape NVIDIA NIM returns.
No factory change. No interface change.
### How the driver works
* Validates `apiConfig` and the API key, validates the model name,
resolves the region
with a default fallback (matching the pattern the merged `ListModels`
and
`CheckConnection` paths in this driver already use), and builds the URL
from
`BaseURL[region] + URLSuffix.Embedding`.
* Sends all input texts in one request as the `input` array, with the
NVIDIA-specific `input_type: "query"`, `encoding_format: "float"`, and
`truncate: "END"`
fields, mirroring the Python `NvidiaEmbed` reference.
* Parses `data[*].embedding` and copies each slice into `[][]float64`
indexed by
`data[*].index` so the output order matches the input order even if the
API returns
items in a different order.
* Handles 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.
* Per-call 30s context deadline so a slow call cannot block forever.
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
### How was this tested?
* `go build ./internal/entity/models/...` returns exit 0.
* `go vet ./internal/entity/models/...` is clean.
* `gofmt -l internal/entity/models/nvidia.go` is clean.
* The full method set on `NvidiaModel` still matches the `ModelDriver`
interface.
* Pattern parity with the just-merged Aliyun `Encode` (#14647).
Closes #14699
2026-05-10 18:50:50 -10:00
|
|
|
{
|
|
|
|
|
"name": "snowflake/arctic-embed-l",
|
|
|
|
|
"max_tokens": 512,
|
|
|
|
|
"model_types": [
|
|
|
|
|
"embedding"
|
|
|
|
|
]
|
|
|
|
|
},
|
2026-05-07 14:17:57 +08:00
|
|
|
{
|
|
|
|
|
"name": "z-ai/glm-5",
|
|
|
|
|
"max_tokens": 131072,
|
|
|
|
|
"model_types": [
|
|
|
|
|
"chat"
|
|
|
|
|
],
|
|
|
|
|
"thinking": {
|
|
|
|
|
"default_value": true,
|
|
|
|
|
"clear_thinking": true
|
|
|
|
|
}
|
|
|
|
|
},
|
|
|
|
|
{
|
|
|
|
|
"name": "z-ai/glm-5.1",
|
|
|
|
|
"max_tokens": 131072,
|
|
|
|
|
"model_types": [
|
|
|
|
|
"chat"
|
|
|
|
|
],
|
|
|
|
|
"thinking": {
|
|
|
|
|
"default_value": true,
|
|
|
|
|
"clear_thinking": true
|
|
|
|
|
}
|
|
|
|
|
},
|
|
|
|
|
{
|
|
|
|
|
"name": "z-ai/glm-4.7",
|
|
|
|
|
"max_tokens": 131072,
|
|
|
|
|
"model_types": [
|
|
|
|
|
"chat"
|
|
|
|
|
],
|
|
|
|
|
"thinking": {
|
|
|
|
|
"default_value": true,
|
|
|
|
|
"clear_thinking": true
|
|
|
|
|
}
|
|
|
|
|
}
|
|
|
|
|
]
|
|
|
|
|
}
|