### What problem does this PR solve?
1. Add license announcement
2. Add sanity check on API config
3. Add base class: BaseModel
4. Add GetBaseURL
### Type of change
- [x] Refactoring
---------
Signed-off-by: Jin Hai <haijin.chn@gmail.com>
### What problem does this PR solve?
Closes#15379
Around 29 Go model providers in `internal/entity/models/` share an
`http.Client` configured with `Timeout: 120 * time.Second`, and reuse
that same client for `ChatStreamlyWithSender`. Go's
`http.Client.Timeout` is a hard ceiling on the whole request that also
covers reading the response body, so it behaves as a wall clock on
streaming. Any streamed chat response that lasts longer than 120 seconds
gets cut off in the middle with a timeout error. Long generations,
reasoning model outputs, and slow or overloaded upstreams are the common
victims.
The providers that already behave correctly (`groq`, `mistral`,
`voyage`, `anthropic`) set no client `Timeout` and instead wrap each
request in a `context.WithTimeout`. This change converges the affected
providers onto that same pattern.
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
---------
Co-authored-by: Jin Hai <haijin.chn@gmail.com>
### Summary
Closes#15381
Every provider in `internal/entity/models/` reads its streaming response
with `bufio.NewScanner(resp.Body)` and iterates over `scanner.Scan()`.
The default `bufio.Scanner` maximum token size is 64KB, so when an
upstream sends a single SSE `data:` line larger than 64KB (long content
deltas, large tool or function call argument blobs, bundled
`reasoning_content`, or providers that emit a whole message in one
event) `scanner.Scan()` returns `false` and `scanner.Err()` returns
`bufio.ErrTooLong`. Streaming chat then ends with an error partway
through the response.
This change adds `scanner.Buffer(make([]byte, 64*1024), 1024*1024)`
immediately after every SSE scanner that was still bare, raising the cap
to 1MB. 1MB is the value already used for streaming chat in `openai.go`,
`modelscope.go`, `groq.go`, `mistral.go`, `xai.go` and the other already
patched providers (the 8MB cap in the repo is reserved for TTS and
embedding paths), so this simply converges the remaining providers onto
the established pattern. Nothing else changes: line parsing, `data:`
prefix handling, `[DONE]` detection, JSON unmarshalling, error handling,
and the existing `scanner.Err()` checks all stay the same.
Providers covered (23 scanners across 22 files): 302ai, aliyun,
baichuan, baidu, cohere, deepinfra, deepseek, gitee, huggingface,
lmstudio, minimax (the chat scanner, whose TTS scanner was already
bumped), moonshot, nvidia, ollama, openrouter, orcarouter, paddleocr,
siliconflow, tokenhub, vllm, volcengine, xunfei, zhipu-ai. `jiekouai.go`
is excluded because it is covered by the in flight #15337.
A table driven regression test (`sse_scanner_buffer_test.go`) streams a
single 128KB `data:` content delta followed by `data: [DONE]` through an
`httptest` server and asserts that `ChatStreamlyWithSender` delivers the
full content with no error across a representative subset of providers.
Without the buffer fix the test fails with `bufio.Scanner: token too
long`.
This PR also removes three duplicate declarations of the package level
`roundTripperFunc` test helper that several recently merged provider PRs
each added independently, which had left the `internal/entity/models`
test package unable to compile. The helper now lives in a single place
and is shared.
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
### What problem does this PR solve?
Closes#15089.
Adds PPIO support to the Go model-provider layer so PPIO instances can
be routed through the Go API server with the same OpenAI-compatible
chat, streaming, model listing, and connection-check flow used by other
SaaS providers.
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
## Summary
- Added a PPIO Go model driver.
- Added the PPIO provider catalog and default OpenAI-compatible API URL.
- Registered PPIO in the model factory.
- Added focused provider and provider-manager tests.
## What changed
- Implemented chat completions, SSE streaming, ListModels, and
CheckConnection for PPIO.
- Covered request shape, stream termination, reasoning fallback, model
listing, custom base URLs, safe transport setup, unsupported methods,
and provider config loading.
- Kept the provider catalog aligned with the existing RAGFlow PPIO
factory model set.
- Cleaned up pre-existing Go model package validation blockers so the
scoped provider tests can run normally with vet enabled.
## Why
The existing Python/provider catalog path includes PPIO, but the Go
model-provider layer did not have a PPIO driver, so the Go API server
could not instantiate or use PPIO as requested in #15089.
### 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>
### What problem does this PR solve?
This PR completes the Baichuan provider
**The following functionalities are now supported:**
**Baichuan:**
- [x] Chat / Stream Chat
- [x] Embedding
- [ ] ~~Rerank~~
- [ ] ~~Model listing~~
- [ ] ~~Provider connection checking~~
- [ ] ~~Balance~~
**Verified examples from the CLI:**
```plaintext
# Baichuan
RAGFlow(user)> embed text 'walkerwhat' 'jumperwho' with 'Baichuan-Text-Embedding@test@baichuan' dimension 16;
+-----------+-------+
| dimension | index |
+-----------+-------+
| 1024 | 0 |
| 1024 | 1 |
+-----------+-------+
AGFlow(user)> chat with 'Baichuan-M2@test@baichuan' message 'who r u'
Answer: I'm BaiChuan, a helpful AI assistant created by Baichuan-AI. I'm designed to be a knowledgeable, friendly, and reliable assistant for various tasks like answering questions, explaining concepts, writing content, and more. Feel free to ask me anything! 😊
Time: 1.637975
RAGFlow(user)> stream chat with 'Baichuan-M2@test@baichuan' message 'who r u'
Answer: I'm BaiChuan-m2, an AI assistant developed by Baichuan-AI. My purpose is to help you with a wide range of tasks by providing information, answering questions, solving problems, and assisting with creative projects. Think of me as a helpful digital companion! If you have any questions or need assistance, just let me know.😊
Time: 1.692321
```
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
- [x] Refactoring
### What problem does this PR solve?
This PR completes the Cohere provider integration (upgrading to the new
Cohere V2 API) and enhances the Fish Audio provider in RAGFlow.
**The following functionalities are now supported:**
**Cohere:**
- [x] Chat / Think Chat / Stream Chat / Stream Think Chat
- [x] Embedding
- [x] Rerank
- [x] Model listing
- [x] Provider connection checking
- [ ] Balance
**Fish Audio:**
- [x] Model listing (`ListModels`)
- [x] Balance (`Balance`)
-----
**Verified examples from the CLI:**
```plaintext
# Cohere
RAGFlow(user)> think chat with 'command-a-reasoning-08-2025@test3@cohere' message 'jumperwho'
Thinking: Okay, the user wrote "jumperwho". Let me try to figure out what they might be asking. First, I'll check if it's a misspelling. "Jumper" ...... Hmm. Since the query is unclear, the best approach is to ask the user to provide more context or correct any possible typos.
Answer: It seems there might be a typo or missing context in your query "jumperwho." Could you clarify what you're referring to? For example:
- Are you asking about a **jumper** (a type of sweater, a person who jumps, or a component in electronics)?
- Is this related to a specific context, like a movie (e.g., the 2008 film *Jumper*) or a game?
- Did you mean to ask about a person ("who") associated with jumping (e.g., a parachutist)?
Let me know so I can provide a helpful response! 😊
Time: 6.710331
RAGFlow(user)> stream think chat with 'command-a-reasoning-08-2025@test3@cohere' message 'jumperwho'
Thinking: , the user mentioned "jumperwho". Let me try to figure out what they're referring to. First, I'll check if it's a misspelling. "Jumper" could be a typo for "jumper" or maybe a username. Alternatively, it might be a combination of words like "jumper who",....... the best approach is to inform the user that I don't recognize the term and ask if they can provide more context or clarify what they mean by "jumperwho". That way, I can assist them better once I have more information.
Answer: seems "jumperwho" isn't a widely recognized term, proper noun, or acronym in common usage. Could you provide more context or clarify what you mean by "jumperwho"? This will help me understand your question or request better!
Time: 4.513596
RAGFlow(user)> embed text 'walkerwhat' 'jumperwho' with 'embed-v4.0@test3@cohere' dimension 16;
+------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+-------+
| embedding | index |
+------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+-------+
| [-0.016643638 -0.001957038 0.0055713872 0.009027058 0.05275187 -0.024542313 -0.044006906 0.024119169 0.0014192933 0.006558722 0.0019129605 -0.021016119 -0.026516981 -0.017489925 0.021298215 0.017772019 0.04569948 0.008886009 0.012059584 -0.0014721862 0.... | 0 |
| [0.018778935 -0.0063459855 -0.0006839742 0.0046623563 0.0067668925 -0.018001877 -0.03963003 0.035744734 -0.014246088 -0.0020721585 -0.006313608 0.025124922 -0.010749322 0.01217393 -0.010231283 -0.025254432 0.021498645 -0.028880708 0.019167464 -0.0058279... | 1 |
+------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+-------+
RAGFlow(user)> rerank query 'what is rag' document 'rag is retrieval augment generation' 'rag need llm' 'famous rag project includes ragflow' with 'rerank-v4.0-pro@test@cohere' top 3;
+-------+-----------------+
| index | relevance_score |
+-------+-----------------+
| 0 | 0.91744334 |
| 1 | 0.7458429 |
| 2 | 0.68729424 |
+-------+-----------------+
RAGFlow(user)> list supported models from 'cohere' 'test'
+-------------------------------------+
| model_name |
+-------------------------------------+
| c4ai-aya-expanse-32b |
| c4ai-aya-vision-32b |
| cohere-transcribe-03-2026 |
| command-a-03-2025 |
| command-a-reasoning-08-2025 |
| command-a-translate-08-2025 |
| command-a-vision-07-2025 |
| command-r-08-2024 |
| command-r-plus-08-2024 |
| command-r7b-12-2024 |
| command-r7b-arabic-02-2025 |
| embed-english-light-v3.0 |
| embed-english-light-v3.0-image |
| embed-english-v3.0 |
| embed-english-v3.0-image |
| embed-multilingual-light-v3.0 |
| embed-multilingual-light-v3.0-image |
| embed-multilingual-v3.0 |
| embed-multilingual-v3.0-image |
| embed-v4.0 |
+-------------------------------------+
RAGFlow(user)> check instance 'test' from 'cohere'
SUCCESS
# FishAudio
RAGFlow(user)> list supported models from 'fishaudio' 'test'
+----------------------------------------+
| model_name |
+----------------------------------------+
| Valentino Narración Biblica Fer |
| Super Smash Bros. 4/Ultimate Announcer |
| Farid Dieck |
| عصام الشوالي |
| ALEX_CHIKNA |
| Energetic Male |
| voz de locutor k |
| يي |
| ELITE |
| Mortal Kombat |
+----------------------------------------+
RAGFlow(user)> show balance from 'fishaudio' 'test'
+----------------------------------+-----------------------------+--------+-----------------+------------------+-----------------------------+----------------------------------+
| _id | created_at | credit | has_free_credit | has_phone_sha256 | updated_at | user_id |
+----------------------------------+-----------------------------+--------+-----------------+------------------+-----------------------------+----------------------------------+
| 82ffec12cf984d88a30ec504d7909812 | 2026-05-09T07:52:16.119000Z | 0 | | false | 2026-05-09T07:52:16.119000Z | 2578ab1126804d6eaa630552400d7ff3 |
+----------------------------------+-----------------------------+--------+-----------------+------------------+-----------------------------+----------------------------------+
```
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
- [x] Refactoring
