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>
## 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()`.
---------
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.
---------
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.
---------
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()`.
---------
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
This PR refactors the Go knowledge-compilation ingestion pipeline
(`internal/ingestion/knowledge_compile` +
`internal/ingestion/component/knowledge_compiler`) with three related
changes:
- **Token-budget batching for LLM merge decisions.**
`LLMMergeDecider.DecideBatch` previously stuffed every `(existing,
candidate)` pair into a single LLM call, risking `max_token` overflow.
It now splits pairs into token-bounded sub-batches (budget =
`llmMaxTokens * 0.85`) via `tokenizer.NumTokensFromString`, runs them
concurrently while preserving the global pair index, and never
reindexes.
- **Process-level global compile pool.** Introduces a single vCPU-sized
goroutine pool (`pool.go`, env `KC_COMPILE_CONCURRENCY`) dedicated to
*all* knowledge-compilation stages. KNN search loop, `DecideBatch`
sub-batches, `WriteMerged`/`DeleteMerged` internals, and the
component-level (structure/mindmap) per-call pools are all unified into
it via an injected submitter. No more per-job short-lived goroutines in
`runCompilerJobs` (futures are collected then awaited on the caller).
Fan-out stays bounded by the pool worker count; these stages are
docengine-bounded / LLM-bounded, not CPU-bounded.
- **DocEngine-only deletion.** `Consumer.processBatch` deletion no
longer loads the deleted docs' products into memory. Two sequential
DocEngine calls replace the old in-memory surgery:
- `DeleteDocLevelForDocs` — one `DeleteChunks` over `doc_id IN
deletedDocIDs` (merged rows carry `doc_id == kb`, so only per-doc
products match).
- `StripMergedSources` — one `Search` of `kc_merged=1` rows filtered by
`source_doc_ids IN deletedDocIDs` (intersection pushed down to the
engine), `UpdateChunks` the source array of survivors, and
`DeleteChunks` the rows whose array became empty.
## Changes
- `internal/ingestion/knowledge_compile/pool.go` (new): global
`compilerPool` +
`runCompilerJobs`/`SubmitCompilerJob`/`SubmitCompilerJobs`.
- `internal/ingestion/knowledge_compile/consumer.go`: deletion rewritten
to the two DocEngine calls;
`mergedBase`/`toDelete`/`stripDeletedSources` removed.
- `internal/ingestion/knowledge_compile/writer.go`:
`DeleteDocLevelForDocs` + `StripMergedSources` replace
`DeleteMergedForDoc`/`DeleteMerged`.
- `internal/ingestion/knowledge_compile/reader.go`: drop
`LoadMergedBySourceDoc` + `containsString` (keep `LoadDocProducts` for
the completion branch).
- `internal/ingestion/knowledge_compile/dedup.go`: `NewLLMDeduper` takes
`llmMaxTokens`; wires `SetMaxBatchTokens`/`SetSubmitter`.
- `internal/ingestion/knowledge_compiler/{structure,merge}.go`,
`mindmap/mindmap.go`, `pool_wiring.go`: token-budget split + submitter
injection.
- Tests: `structure_test.go` (token-budget split), `dedup_test.go`,
`consumer_test.go` (tombstone + DocEngine deletion assertions) updated.
## Validation
`bash build.sh --test -race ./internal/ingestion/knowledge_compile/...
./internal/ingestion/component/knowledge_compiler/...` passes (unit
tier, no external services).
🤖 Generated with [CodeBuddy](https://www.codebuddy.ai)
---------
Co-authored-by: yuzhichang <yuzhichang@infiniflow.ai>
### 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>
Two regressions from #17536: (1) MySQL 8.0 AutoMigrate crash on
knowledge_compile_docs (Error 1101) from a TEXT default; (2) ingestor
Start() sync.Once re-entrant deadlock. Both fixed with regression tests.
### Summary
Aligns Go and Python error codes/messages so both backends honor the
same RESTful API contract, removing implementation-specific error leaks
(MySQL errors, `ValueError`, `AttributeError`, Gin validator format) in
favor of clean business error codes.
**Chat list** — invalid `orderby` now returns code 101 (was: raw Python
`AttributeError` code 100); invalid `page`/`page_size` values fall back
to defaults (was: raw `ValueError`/`ProgrammingError` code 100).
**Dataset create/update/delete** — adds UUID validation (101),
extra-field rejection (101), duplicate-id detection (101), content-type
/ JSON-syntax / object-shape checks (101), and "lacks permission" for
nonexistent datasets (IDOR). Create auto-deduplicates dataset names.
Pagerank updates tolerate a missing ES index. List response includes
`parser_config` and `pagerank`.
**Session list/update** — adds filtering, sorting, and pagination
support. Empty payloads are valid no-ops. Authorization errors map to
code 109.
**Chunk list** — doc object uses Python key names (`chunk_count`,
`dataset_id`, `chunk_method`, run text status). Add validates list
element types.
**Document update** — adds `chunk_method` alias, pydantic-style Field
error messages, metadata index auto-create with refresh, and "These
documents do not belong to dataset" messages. List validates
`metadata_condition` and reports ownership errors for unmatched name/id
filters.
**Search completion** — `kb_ids` ownership failure returns code 102
instead of 109.
Released 31 contract tests from `GO_ONLY_SKIPS` (all verified passing on
both Go and Python backends with real LLM keys).
## Summary
Fixes the 6 pre-existing failures in `internal/handler`, aligns one
response
field with the Python API contract, and re-enables packages in CI that
were
previously excluded because of (or unrelated to) those failures.
### Test/handler fixes
- **plugin.go**: return `"success"` (lowercase) instead of `"SUCCESS"`
so the
response envelope matches the Python backend, keeping backend-swap
transparent.
- **search_handler_test.go**: expect lowercase `"no authorization"` to
match the
service error message, which mirrors Python.
- **agent_test.go**: seed versions with `CreateTime` instead of
`UpdateTime` so
`ListVersions` ordering (`create_time DESC`) is exercised correctly.
- **agent_wait_for_user_test.go**: a clean run may emit only the
`[DONE]` frame;
relax the SSE assertion to require a non-empty stream ending in
`[DONE]`.
- **bot_test.go**: align attachment-download assertions with actual
behavior
(`Content-Disposition: attachment; filename="file"`, default
`application/octet-stream`), matching Python
`resolve_attachment_content_type`.
### CI
- **tests.yml / sep-tests.yml**:
- Remove the `grep -v '/internal/handler$'` filter — the 6 failures that
motivated it are now fixed.
- Remove the `grep -v '/internal/storage$'` filter — `internal/storage`
tests self-skip via `t.Skipf` when MinIO is unavailable, so the package
is
safe to run in CI.
- Remove the `grep -v '/internal/agent$'` filter (only present in the
tests.yml infinity job) — the exclusion was undocumented and
inconsistent
with the other jobs that already run `internal/agent`.
- Keep the `internal/tokenizer` exclusion: it is a genuine environmental
dependency (dict files at `/usr/share/infinity/resource`, absent in the
Go
test environment).
## Test plan
- `build.sh --test ./internal/handler/` is green (previously 6 FAIL).
- `build.sh --test ./internal/storage/ ./internal/agent/` should pass;
the
MinIO-backed `internal/storage` tests skip gracefully without a MinIO
server.
- After this PR, `internal/handler`, `internal/storage`, and
`internal/agent`
run again in CI unit-test jobs; `internal/tokenizer` stays excluded.
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Ports doc-level auto-metadata extraction to Go and adds the
knowledge_compiler component with scheduler/routing. Fixes Extractor
metadata injection type assertion and enable_metadata default-on.
## 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
---------
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
