The "Import from /models" button was using the wrong Z.AI API surface
(Anthropic-compatible /api/anthropic/v1/models with x-api-key auth).
Switched to the correct Coding API endpoints with Authorization: Bearer
auth, matching the pattern used by the quota/usage tracking code.
- International: https://api.z.ai/api/coding/paas/v4/models
- China: https://open.bigmodel.cn/api/coding/paas/v4/models
- Auth: Authorization: Bearer <token> (not x-api-key)
- Region sourced from providerSpecificData.apiRegion
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* fix(stream): normalize delta.reasoning to reasoning_content in SSE streaming
NVIDIA kimi-k2.5 (and potentially other providers) send reasoning
tokens as `delta.reasoning` in SSE streaming chunks instead of the
standard OpenAI `delta.reasoning_content` field. This caused reasoning
content to be silently dropped during stream passthrough — clients
received only the final answer with no reasoning separation.
The non-streaming sanitizer (responseSanitizer.ts) already handled this
alias, but the streaming pipeline did not.
Fix applied in 4 locations:
- stream.ts passthrough: normalize + force re-serialize sanitized chunk
- stream.ts translate: accumulate reasoning from delta.reasoning
- sseParser.ts: collect delta.reasoning in parseSSEToOpenAIResponse
- streamPayloadCollector.ts: collect delta.reasoning in buildOpenAISummary
* fix: eliminate injectedUsage reuse bug and add reasoning alias tests
- Detect delta.reasoning alias before sanitizeStreamingChunk() which
already normalizes it, removing dead post-sanitization normalization
- Replace injectedUsage reuse with separate needsReserialization flag
so reasoning re-serialization cannot block finish_reason/usage
mutations on the same SSE chunk (fixes CRITICAL review finding)
- Add unit test for parseSSEToOpenAIResponse reasoning alias
- Add unit test for buildStreamSummaryFromEvents reasoning alias
* fix(stream): separate reasoning from content in passthrough response body
The passthroughAccumulatedContent variable was mixing delta.content and
delta.reasoning_content into one string, causing the client_response
log and responseBody to lose reasoning separation.
- Add passthroughAccumulatedReasoning accumulator for reasoning deltas
- Set message.reasoning_content in responseBody when reasoning exists
- Only accumulate delta.content into passthroughAccumulatedContent
* fix: trim leading whitespace from assembled content in log summaries
NVIDIA and other providers emit token deltas with leading spaces
(e.g. ' The', ' user'). When joined, these produce a leading space in
the provider_response and parsed non-streaming response logs. Trim
the joined content and reasoning_content in both buildOpenAISummary
and parseSSEToOpenAIResponse for consistent log output.
* fix(stream): split combined reasoning+content deltas into separate SSE events
Some providers (e.g. NVIDIA NIM) send transition chunks with both
`delta.reasoning` and `delta.content` in the same SSE event.
After sanitization this becomes `reasoning_content` + `content`,
which violates the standard OpenAI streaming contract where these
fields are never mixed. Clients using if/else logic (LobeChat, etc.)
skip content when reasoning_content is present, losing the first
content token.
Split such combined chunks into two separate SSE events:
1. Reasoning-only event (finish_reason=null, no usage)
2. Content-only event (carries finish_reason and usage)
* chore(release): v3.2.8 — Docker auto-update UI and cache analytics fixes
* fix(sse): remove race condition in cache metrics tracking (#758)
- Remove in-memory metrics tracking (currentMetrics, trackCacheMetrics, updateCacheMetrics)
- Cache metrics now computed on-the-fly from usage_history table (single source of truth)
- Fixes CRITICAL issue from code review: concurrent requests overwriting metrics
- Fixes WARNING: duplicate metric tracking logic in streaming/non-streaming paths
Ref: PR #752 (merged before this fix was included)
* fix: handle allRateLimited credentials & forward extra body keys in embeddings/images routes (#757)
* fix: handle allRateLimited credentials in embeddings and images routes
When getProviderCredentials() returns an allRateLimited object (truthy,
but without apiKey/accessToken), the embeddings and images routes
incorrectly passed it to handlers as valid credentials. The handlers
then sent upstream requests without Authorization headers, causing
401 errors from providers (e.g. NVIDIA NIM).
This only manifested under concurrent requests: a chat/completions
call could trigger rate limiting on a provider account, and a
simultaneous embeddings request would receive the allRateLimited
sentinel — but treat it as valid credentials.
The chat pipeline already handled this case correctly. This commit
adds the same allRateLimited guard to all affected routes:
- POST /v1/embeddings
- POST /v1/providers/{provider}/embeddings
- POST /v1/images/generations
- POST /v1/providers/{provider}/images/generations
Also adds a defense-in-depth guard in the embeddings handler itself:
if no auth token is available for a non-local provider, return 401
immediately instead of sending an unauthenticated request upstream.
Made-with: Cursor
* fix(embeddings): forward extra body keys to upstream providers
The embeddings handler only forwarded model, input, dimensions, and
encoding_format to upstream providers, silently dropping any additional
fields. This broke asymmetric embedding APIs (e.g. NVIDIA NIM
nv-embedqa-e5-v5) that require input_type, and other providers
expecting user or truncate parameters.
Add a KNOWN_FIELDS exclusion set and forward all unrecognized body
keys to the upstream request, matching the passthrough pattern used
by the chat pipeline's DefaultExecutor.transformRequest().
Made-with: Cursor
* fix(auth): redirect and unconditional 401 on disabled requireLogin + fix test cases
* fix(build): remove legacy proxy.ts causing Next.js build collision
* fix(build): revert middleware.ts rename to proxy.ts because of Next.js Edge constraints
---------
Co-authored-by: diegosouzapw <diegosouzapw@users.noreply.github.com>
Co-authored-by: tombii <tombii@users.noreply.github.com>
Co-authored-by: Gorchakov-Pressure <117600961+Gorchakov-Pressure@users.noreply.github.com>
- Add usage_history table creation in test setup
- Simplify byStrategy query to avoid non-existent combo_strategy column
- Update test assertions to work with existing test data
Adds intelligent cache control preservation for Claude Code clients:
- New cacheControlPolicy.ts module with detection logic:
- isClaudeCodeClient(): Detects Claude Code via User-Agent
- providerSupportsCaching(): Checks provider (claude, anthropic, zai, qwen)
- isDeterministicStrategy(): Identifies priority/cost-optimized strategies
- shouldPreserveCacheControl(): Main policy decision
- Cache control is preserved when:
1. Client is Claude Code (detected via User-Agent)
2. Provider supports prompt caching
3. Request routing is deterministic:
- Single model requests (always)
- Combo with priority or cost-optimized strategy only
- Updated translator to accept preserveCacheControl option
- Updated chatCore and chat handler to propagate combo strategy
- Added comprehensive unit tests (24 tests)
Non-deterministic combo strategies (weighted, round-robin, random, etc.)
continue to use OmniRoute's managed caching strategy.
Refs: #cache-control-preservation
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
OpenCode Go mixes request protocols by model family:
- `glm-5` and `kimi-k2.5` use OpenAI-style `/chat/completions`
- `minimax-m2.5` and `minimax-m2.7` use Anthropic-style `/messages`
OmniRoute already routed MiniMax Go models to `/messages`, but the
executor still sent `Authorization: Bearer ...`, which caused upstream
`401 Missing API key` errors.
This changes `OpencodeExecutor` to send:
- `x-api-key` + `anthropic-version` for Claude-targeted OpenCode Go requests
- `Authorization: Bearer ...` for the remaining OpenCode Go request formats
Also updates unit coverage to assert the correct header behavior for
MiniMax Go models.
Validated with:
- direct curl repro against OpenCode Go endpoints
- `node --import tsx/esm --test tests/unit/opencode-executor.test.mjs`
- `npm run typecheck:core`
- `npm run build`
HTTP 400 "invalid argument" was triggered when OmniRoute translated OpenAI
tool_calls to Gemini format, because thoughtSignature was injected onto every
functionCall part unconditionally.
thoughtSignature is only valid on thinking/reasoning parts (those with
thought: true). The Gemini API rejects any request where a functionCall
part carries a thoughtSignature field, returning HTTP 400.
Fix: remove the thoughtSignature field from functionCall parts. The thinking
parts that legitimately require thoughtSignature (emitted when a message has
reasoning_content) are unchanged.
Adds regression test (T43) with three cases:
- single tool call: no thoughtSignature on functionCall part
- multiple tool calls: none carry thoughtSignature
- thinking part regression guard: thoughtSignature still present on thought parts
Fixes#725
Non-streaming: Fixed json.messages check to use json.choices[0].message
(OpenAI format). Streaming: inject pin tag before finish_reason chunk for
tool-call-only streams. injectModelTag now appends synthetic assistant
message when content is null/array (tool_calls).
