### What problem does this PR solve?
This PR implement implement OCR for Baidu and Mistral, implement
PaddleOCR provider and implement ASR for CoHere
**Verified examples from the CLI:**
```
RAGFlow(user)> ocr with 'mistral-ocr-2512@test@mistral' file './internal/text.jpg'
+------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| text |
+------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| Parallel to these organizational innovations there were significant complementary technical innovations (e.g., improved methods of manufacturing cast-iron pipe and of coating interiors for pressure maintenance, and newer paving and construction material... |
+------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
RAGFlow(user)> ocr with 'paddleocr-vl-0.9b@test@baidu' file './internal/text.jpg'
+------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| text |
+------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| Parallel to these organizational innovations there were significant complementary technical innovations (e.g., improved methods of manufacturing cast-iron pipe and of coating interiors for pressure maintenance, and newer paving and construction material... |
+------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
# PaddleOCR
RAGFlow(user)> ocr with 'PaddleOCR-VL-1.5@test@paddleocr' file './internal/test.pdf'
+------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| text |
+------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| # Repurposing Diffusion-Based Image Generators for Monocular Depth Estimation
Bingxin Ke
Nando Metzger
Photogra
Anton Obukhov
Rodrigo Caye Daudt
netry and Remote Sensing,
Shengyu Huang
Konrad Schindler
ETH Zürich
<div style="text-align: c... |
+------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
# Cohere
RAGFlow(user)> asr with 'cohere-transcribe-03-2026@test@cohere' audio './internal/test.wav' param '{"language": "en"}'
+-----------------------------------------------------------------------------------------------------------------------+
| text |
+-----------------------------------------------------------------------------------------------------------------------+
| The examination and testimony of the experts enabled the Commission to conclude that five shots may have been fired. |
+-----------------------------------------------------------------------------------------------------------------------+
```
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
- [x] Refactoring
### What problem does this PR solve?
```
RAGFlow(user)> ocr with 'hunyuanocr@test@gitee' file './picture.png'
+----------------------------------------------------------+
| text |
+----------------------------------------------------------+
| 生活不是等待风暴过去，而是学会在雨中翩翩起舞。
——佚名 |
+----------------------------------------------------------+
RAGFlow(user)> list 'test@gitee' tasks;
+---------+----------------------------------+
| status | task_id |
+---------+----------------------------------+
| success | C3FX4MQNKY5MGC6ZFMIXIAMJKHCEBQB5 |
+---------+----------------------------------+
RAGFlow(user)> show 'test@gitee' task 'C3FX4MQNKY5MGC6ZFMIXIAMJKHCEBQB5';
+------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+-------+
| content | index |
+------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+-------+
| # PDF 1: Purpose of RAGFlow
RAGFlow is an open source Retrieval-Augmented Generation (RAG) engine designed to turn raw documents into reliable context for large language models.Its purpose is to make it practical to build an Al assistant that can ans... | 1 |
+------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+-------+
```
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
---------
Signed-off-by: Jin Hai <haijin.chn@gmail.com>
### What problem does this PR solve?
RAGFlow(user)> ocr with 'hunyuanocr@test@gitee' file './picture.png'
+----------------------------------------------------------+
| text |
+----------------------------------------------------------+
| 生活不是等待风暴过去，而是学会在雨中翩翩起舞。
——佚名 |
+----------------------------------------------------------+
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
---------
Signed-off-by: Jin Hai <haijin.chn@gmail.com>
### What problem does this PR solve?
```
RAGFlow(user)> asr with 'glm-asr-2512@test@zhipu-ai' audio './speech.wav';
CLI error: zhipu, no such method
RAGFlow(user)> stream asr with 'glm-asr-2512@test@zhipu-ai' audio './speech.wav';
CLI error: zhipu, no such method
RAGFlow(user)> tts with 'glm-tts@test@zhipu-ai' text 'how are you';
CLI error: zhipu, no such method
RAGFlow(user)> stream tts with 'glm-tts@test@zhipu-ai' text 'how are you';
CLI error: zhipu, no such method
RAGFlow(user)> ocr with 'glm-ocr@test@zhipu-ai' file './test.log';
CLI error: zhipu, no such method
```
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
Signed-off-by: Jin Hai <haijin.chn@gmail.com>
## Summary
- Replaces the `"no such method"` stub on `NvidiaModel.Rerank`
(`internal/entity/models/nvidia.go`) with a real implementation against
NVIDIA NIM's `/ranking` endpoint.
- Mirrors the existing Python `NvidiaRerank` class at
`rag/llm/rerank_model.py:149-190` for behavior parity: same
`passages`/`query.text`/`logit` payload shape; `top_n` set to
`len(documents)` so every input gets a score returned in original order
(the issue body's spec omitted `top_n`, which would cause silent data
loss).
- Adds the `"rerank": "ranking"` URL suffix and two NIM rerank model
entries (`nvidia/nv-rerankqa-mistral-4b-v3`,
`nvidia/llama-3.2-nv-rerankqa-1b-v2`) to `conf/models/nvidia.json` so
the picker exposes them.
- Follows the same shape as the recently merged Aliyun (#14676), Gitee
(#14656), and ZhipuAI (#14608) Rerank implementations: lowercase
per-driver request/response types, conversion to the project-wide
`RerankResponse{Data: []RerankResult}`, per-call `context.WithTimeout`
of 30s.
Closes#14720
## Test plan
- [x] `gofmt -l internal/entity/models/nvidia.go` — clean
- [x] `go vet ./internal/entity/models/...` — no new errors introduced
(the two pre-existing vet errors in `baidu.go:642` and
`openrouter.go:566` are unrelated to this PR)
- [x] `go build ./internal/entity/models/...` — succeeds
- [x] `python3 -c "import json;
json.load(open('conf/models/nvidia.json'))"` — JSON valid
- [ ] Live smoke test against NVIDIA NIM with a real API key (requires
reviewer with NIM credentials)
## Notes for reviewers
- The issue body suggested omitting `top_n`. The Python reference
includes it (`top_n: len(texts)`), and without it NVIDIA returns only
the default top-K rankings rather than scores for every input. This PR
follows the Python.
- The URL host is `integrate.api.nvidia.com` (kept consistent with the
existing chat/embeddings BaseURL in `nvidia.go`), not the legacy
`ai.api.nvidia.com` host the Python uses. NIM's unified endpoint accepts
the model names as-is, so no per-model URL transform is needed.
### What problem does this PR solve?
Provide embedding index according to the input text
### Type of change
- [x] Refactoring
---------
Signed-off-by: Jin Hai <haijin.chn@gmail.com>
### 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
### What problem does this PR solve?
```
RAGFlow(user)> embed text 'what is rag' 'who are you' with 'embedding-3@test@zhipu-ai' dimension 16;
+-----------+-------+
| dimension | index |
+-----------+-------+
| 16 | 0 |
| 16 | 1 |
+-----------+-------+
RAGFlow(user)> rerank query 'what is rag' document 'rag is retrieval augment generation' 'rag need llm' 'famous rag project includes ragflow' with 'rerank@test@zhipu-ai' top 2;
+-------+-----------------+
| index | relevance_score |
+-------+-----------------+
| 0 | 1 |
| 2 | 0.99999976 |
+-------+-----------------+
```
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
Signed-off-by: Jin Hai <haijin.chn@gmail.com>
### What problem does this PR solve?
The NVIDIA Go driver added in #14623 has a real chat path, but
\`ListModels\` and \`CheckConnection\` are stubs that always return \`no
such method\`. So:
- The model picker cannot auto-populate available NVIDIA NIM model ids.
Users have to type the full id by hand (e.g.
\`abacusai/dracarys-llama-3.1-70b-instruct\`).
- The "Check connection" button always fails for NVIDIA, even when the
base URL is reachable and the API key is accepted.
NVIDIA NIM is OpenAI-compatible. \`/v1/models\` works with the same
Bearer token used for chat. The
\`conf/models/nvidia.json\` file already wires the \`models\`
url_suffix, so no config change is needed.
### What this PR includes
- \`internal/entity/models/nvidia.go\`:
- \`ListModels\` now calls
\`GET ${BaseURL}/${URLSuffix.Models}\`, parses
\`response.data[*].id\`, and returns the list. Same shape
as the moonshot, xai, and openai drivers.
- \`CheckConnection\` now calls \`ListModels\` and returns its
error. Same pattern xai, moonshot, deepseek, aliyun, and
gitee already use.
\`Balance\`, \`Encode\`, and \`Rerank\` are still stubs in this PR and
can be added in follow-ups.
No JSON change. No factory change. No interface change.
### How the implementation works
- Region resolution falls back to \`default\` when the supplied region
is unknown, so a stray region value does not break a valid request.
- The Authorization header is only set when \`apiConfig\` and \`ApiKey\`
are non-nil and non-empty. This avoids a nil-pointer dereference and
lets self-hosted NIM deployments without a key still work.
- Non-200 responses propagate the upstream status line and body so the
user sees a real error message.
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
### How was this tested?
- \`go build ./internal/entity/models/...\` in a clean go 1.25 image
(the go.mod minimum) returns exit 0.
- The full method set on \`NvidiaModel\` still matches the
\`ModelDriver\` interface.
- Pattern parity with the existing xai, moonshot, deepseek, aliyun,
gitee, and openai drivers.
Closes#14635
### What problem does this PR solve?
1. **Implement `OpenRouter` Provider:** Fully support OpenRouter AI
models (e.g., `gemma`, `minimax`). Includes robust handling of
Server-Sent Events (SSE) streams, error event interception, and proper
parsing of both `reasoning_content` and standard `content`.
2. **Fix BaseURL Resolution Bug:** Fixed a critical edge case in region
configuration parsing. Added a strict empty string check
(`*apiConfig.Region != ""`) alongside the `nil` check. This ensures that
if the UI passes an empty string, the system correctly falls back to the
`"default"` region, preventing `unsupported protocol scheme ""` errors
during HTTP requests.
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
- [x] New Feature (non-breaking change which adds functionality)
### What problem does this PR solve?
1. **Implement `Nvidia` Provider:** Fully support NVIDIA NIM APIs with
robust parameter handling (including the `thinking` parameter) and safe
URL merging in `NewInstance`.
2. **Fix Misleading CLI Errors:** Corrected a bug in `common_command.go`
where failed chat requests inaccurately reported `failed to list
instance models`.
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
- [x] New Feature (non-breaking change which adds functionality)
