## What
This pull request adds **MWS GPT Model Hub** as a built-in model
provider in RAGFlow.
The integration allows users to configure an MWS project endpoint and
token, discover the models available to that project, and use supported
MWS models for chat completion, embeddings, and reranking.
Co-authored-by: ilarionov_n <ilarionov_n@promis.ru>
Re-materialize wiki page graph from merged wiki_page rows after each
batch merge. Adds ProjectWikiGraph/DropWikiGraph, full page_type/slug
identity, delete-then-insert, tests.
## Summary
- Add embedding batch-size metadata to model responses and tenant
overrides.
- Validate embedding dimensions and batch limits across provider
verification and embedding requests.
- Expand validation tests for defaults, limits, and missing metadata.
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Signed-off-by: Jin Hai <haijin.chn@gmail.com>
Co-authored-by: Jin Hai <haijin.chn@gmail.com>
Ports dataset knowledge compilation (wiki/graph/tree/mindmap) to the Go
scheduler with a status contract, aligns wiki storage/retrieval with
Python, sizes prompts by content_length, and resolves embedding batch
size from provider capability.
Ports the dataset knowledge compilation (wiki/graph/tree/mindmap) to the
Go scheduler with a status contract, aligns wiki storage/retrieval with
Python, and sizes prompts by content_length.
## Summary
The generic `buildRequestBody` in `internal/entity/models/base_model.go`
unconditionally forwarded `ChatConfig.MaxTokens` as `"max_tokens"` for
every OpenAI-compatible provider.
Providers that need a different token field already delete or override
it after the call (e.g. Xiaomi uses `max_completion_tokens`, Replicate
uses `max_new_tokens`). This change stops setting `max_tokens` in the
shared builder so it only forwards the parameters common across
providers, and each provider remains free to set its own token limit
field.
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Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
## Summary
Update `conf/all_models.json`: replace legacy `max_tokens` with
`content_length` + `max_output` for all 2,178 chat/vision models, with
values verified against official vendor documentation.
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Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
## 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>
Relate to #17284.
## Summary
Batch 5/6 migrated the rest of the Go model drivers onto the shared HTTP
helpers (`doRequest`, `doStreamRequest`, `applyAuth`). This PR completes
the batch for the remaining OpenAI-compatible chat-streaming drivers
that were still hand-writing HTTP requests:
- **7 drop-in migrations**: deepseek, gpustack, groq, longcat, moonshot,
openai, siliconflow
- **1 adapter migration**: minimax (relocated its `io.Pipe`
error-interception into the `doStreamRequest` handler)
- **1 full migration**: azure_openai (all four paths: chat, streaming,
embeddings, list-models) plus the auth header hook
- **1 receiver fix**: nvidia `NewInstance` value → pointer
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Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Relate to #17284.
## Problem
`novitaHandleStream` guarded usage recording with `if found &&
chatConfig != nil`. When a caller passes a nil `*ChatConfig` — common in
the service layer (`model_chat.go`, `chat_pipeline.go`) — the streamed
token usage is dropped entirely.
The shared `HandleStreamingResponse` only uses `chatConfig` to expose
`UsageResult` and records usage whenever the stream carries it. Novita's
bespoke handler diverged from every other OpenAI-compatible streaming
driver.
## Fix
Record usage whenever the stream carries a usage event, mirroring
`HandleStreamingResponse`. `applyStreamUsage` already handles a nil
`chatConfig` internally (it only writes `chatConfig.UsageResult` when
non-nil), so the extra guard was doing nothing but dropping usage.
## Test
`TestNovitaStreamRecordsUsageWithoutChatConfig`:
- nil `chatConfig` + usage event → stream completes without error (guard
removed safely)
- non-nil `chatConfig` + usage event → `UsageResult` populated with the
streamed tokens
Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
## Summary
Relate to #17284.
Completes the migration of the four non-OpenAI-compatible model drivers
(`anthropic`, `cohere`, `google`, `bedrock`) onto the shared
usage-recording path. Earlier batches (#17634, #17643, #17696–#17700)
covered only the OpenAI-compatible cluster; these four providers ship
wire formats that do not fit the OpenAI `choices[0].delta` / `usage`
block template and so were left for a separate pass.
Per the maintainer's guidance for this batch, each driver is migrated on
its own terms rather than forced through a single template. The shared
machinery used is intentionally small: `recordResponseUsage`,
`parseChatCompletionResponse`, `BaseModel.newJSONPostRequest`, and the
existing `authHeader` hook for non-Bearer auth.
Co-authored-by: Haruko386 <tryeverypossible@163.com>
Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
## Summary
DeepSeek and Azure OpenAI require `stream_options.include_usage=true` to
return token usage in streaming responses. Without it, all streaming
calls report zero usage to ClickHouse and the UI shows no token stats.
- [x] Verify DeepSeek streaming calls now report usage
- [x] Verify Azure OpenAI streaming calls now report usage
## Summary
Relate to #17284. Completes the batch 5 migration of 7 OpenAI-compatible
drivers (`vllm`, `volcengine`, `xai`, `xiaomi`, `xinference`, `xunfei`,
`zhipu-ai`) onto the unified request/response helpers
(`doRequest`/`doStreamRequest` +
`HandleNonStreamingResponse`/`HandleStreamingResponse` +
`ParserConfig`), established by `deepseek` in #17634.
This branch is rebased on the current `pr/migrate-models-batch5` and
fixes the issues in the previous state of the PR.
Co-authored-by: Haruko386 <tryeverypossible@163.com>
Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
## Summary
Relate to #17284
Migrate 10 OpenAI-compatible drivers (`orcarouter`, `perplexity`,
`ppio`, `qiniu`, `ragcon`, `stepfun`, `togetherai`, `tokenhub`,
`tokenpony`, `upstage`) to use the unified response handlers
(`HandleNonStreamingResponse` / `HandleStreamingResponse`), following
the same pattern established by `deepseek` in #17634.
- Cut ~150 lines per driver (1436 lines removed, 62 added across 10
files).
- No functional changes — pure deduplication of HTTP plumbing.
- Each driver now routes through `baseModel.doRequest()` and
`HandleNonStreamingResponse()`.
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Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
## Summary
Relate to #17284
Migrate 10 OpenAI-compatible drivers (`minimax`, `mistral`,
`modelscope`, `moonshot`, `n1n`, `novita`, `ollama`, `openai`,
`openai_api_compatible`, `openrouter`) to use the unified response
handlers (`HandleNonStreamingResponse` / `HandleStreamingResponse`),
following the same pattern established by `deepseek` in #17634.
- Cut ~150 lines per driver (1692 lines removed, 172 added across 10
files).
- `openai_api_compatible` gains `ChatWithMessages` +
`ChatStreamlyWithSender` required by the unified handler infrastructure.
- `openai` driver preserves `reasoning_content` extraction for o-series
models.
- All drivers: pure deduplication of HTTP plumbing.
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Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
## Summary
Relate to #17284
Migrate 10 OpenAI-compatible drivers (`gitee`, `gpustack`, `greenpt`,
`huaweicloud`, `huggingface`, `hunyuan`, `jiekouai`, `jina`, `lmstudio`,
`localai`) to use the unified response handlers
(`HandleNonStreamingResponse` / `HandleStreamingResponse`), following
the same pattern established by `deepseek` in #17634.
- Cut ~150 lines per driver (1398 lines removed, 155 added across 10
files).
- `greenpt` gains `ChatWithMessages` + `ChatStreamlyWithSender` required
by the unified handler infrastructure.
- All other drivers: pure deduplication of HTTP plumbing.
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Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthoric.com>
## Summary
Relate to #17284
Migrate 10 OpenAI-compatible drivers (`302ai`, `aliyun`, `astraflow`,
`avian`, `azure_openai`, `baichuan`, `baidu`, `cometapi`, `deepinfra`,
`futurmix`) to use the unified response handlers
(`HandleNonStreamingResponse` / `HandleStreamingResponse`), following
the same pattern established by `deepseek` in #17634.
- Cut ~150 lines per driver (1507 lines removed, 144 added across 10
files).
- No functional changes — pure deduplication of HTTP plumbing.
- Each driver now routes through `baseModel.doRequest()` and
`HandleNonStreamingResponse()`.
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Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
## Summary
Relate to #17284
Migrate four OpenAI-compatible drivers (`nvidia`, `siliconflow`, `groq`,
`longcat`) to use the unified response handlers
(`HandleNonStreamingResponse` / `HandleStreamingResponse`), following
the same pattern established by `deepseek` in #17634.
- Cut ~100 lines per driver (541 lines removed, 19 added across 4
files).
- `nvidia` now extracts token usage (previously had none).
- All four drivers produce the unified `StreamUsage` log.
### Summary
Add token usage reporting for the StepFun model provider. Related
to #17284.
Co-authored-by: Haruko386 <tryeverypossible@163.com>
Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
## Summary
- LongCat's token usage did not appear in the server terminal, while
DeepSeek's did — even though both drivers parse and record usage through
the same shared helpers. The gap was a missing debug log in LongCat's
SSE loop, so aggregate usage events were silently processed instead of
printed.
- The official LongCat API docs and live responses from
`api.longcat.chat` return a nested
`usage.completion_tokens_details.reasoning_tokens` breakdown for
thinking mode. The previous flat `LongCatChatResponse.Usage` struct
dropped this field on unmarshal.
- Add test coverage for the nested `reasoning_tokens` field on both the
non-streaming and streaming paths.
Closes#17284
### Summary
Add token usage reporting for the Groq model provider. Related to
#17284.
Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
## Summary
- Add provider-local Chat, Embedding, and Rerank response structures
with usage mapping.
- Align streaming usage and tool-call state handling across Gitee,
OpenRouter, Jiekou.AI, and Hunyuan.
- Preserve Jina's non-streaming behavior and explicit unsupported
streaming response, while fixing Jiekou.AI thinking=false handling.
### Summary
The Go Anthropic driver's `ChatStreamlyWithSender`
(internal/entity/models/anthropic.go) was a stub that always returned
`"no such method"`, so any caller requesting a streamed response from a
Claude model via the Go path failed outright — diverging from the Python
`AnthropicCV` driver, which already supports streaming.
This implements the method by opening the Messages API with
`stream=true` and parsing the SSE response via the shared
`ParseSSEStream` helper, forwarding `text_delta`/`thinking_delta`
content through the `sender` callback and treating `message_stop` as the
terminal event — consistent with the other Go drivers in this package
(e.g. Cohere).
Fixes#17333
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Co-authored-by: Abhay Yadav <abhayyadav@Abhays-MacBook-Air.local>
### Summary
Add token usage reporting for the LongCat (Meituan) model provider.
Related
to #17284.
Co-authored-by: Claude Fable 5 <noreply@anthropic.com>
## Summary
GreenPT is a European AI provider with an OpenAI-compatible API,
optimized infrastructure, and datacenters powered by 100% renewable
energy.
This adds native GreenPT support across RAGFlow’s Go-first provider
system and its Python compatibility layer:
- discovers the current catalog from `GET /v1/models`
- features `glm-5.2` and `kimi-k2.7-code` for chat and coding
- supports `green-embedding` through `/v1/embeddings`
- supports `green-rerank` through `/v1/rerank`
- supports `green-s` and `green-s-pro` speech-to-text through
`/v1/listen`
- adds provider configuration, UI icon, and supported-provider
documentation
## Summary
- Parse chat, embedding, and rerank usage from provider responses
- Record usage with the correct model type even when no usage sink is
provided
- Cover SiliconFlow, Aliyun, Huawei Cloud, Qiniu, and VolcEngine
response formats
### Summary
The FunASR provider added in #17171 defaults to a local
`http://localhost:8000/v1` server, but it still inherited the global
API-key requirement and unconditionally built an Authorization header.
This prevented the default unauthenticated self-hosted deployment from
working. The transcription path also dereferenced a missing model name
while building its multipart request.
This change:
- allows an empty API key for FunASR, matching other local providers
- omits the Authorization header when no key is configured while
preserving trimmed Bearer authentication when one is provided
- validates and trims the ASR model name before building the multipart
request, returning an error instead of panicking
- adds HTTP-level regression coverage for unauthenticated
transcription/model listing and optional authentication
