### Summary
Closes#17848.
This replaces #17958 with a smaller implementation focused on the
original requirement. The previous PR gradually expanded beyond the
necessary scope; the optional custom endpoint extension is intentionally
excluded from this version.
- Add request-scoped Bedrock API key authentication to the Python
Bedrock adapters and Go chat runtime.
- Discover and persist models available to API key instances, so users
do not need to manually enter the model type, model name, or maximum
token count.
- Add API Key mode to the existing Bedrock settings UI and refresh the
model and default-model lists after instance changes.
- Preserve selected models during credential-only updates while keeping
the existing SigV4 authentication modes unchanged.
- Return a clear error for unsupported API-key reranking.
- Document instance-scoped authentication and short-term API key
guidance.
Ports the smart-reasoning (agentic RAG) conversation mode to the eino ADK, with Go retrieval tools (grep_chunks, search_chunks, list_chunks), deep-read XML output, and frontend agent-mode wiring.
Some NVIDIA hosted models (e.g. meta/llama-3.2-11b-vision-instruct )
expose a full
endpoint URL per model that does not follow the normal base_url +
url_suffix
assembly. Previously the Go driver always called {base}/chat/completions
, so chat
requests for these vision models hit the wrong endpoint and failed.
This PR adds an optional per-model url field in conf/models/nvidia.json
. When
present, every NVIDIA driver request (chat, streaming chat, embedding,
rerank, model
listing) uses it directly; otherwise the standard assembly is unchanged.
## 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.
---------
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.
---------
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.
---------
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
---------
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>
