Replace empty reasoning_content with explicit </think> closing tag when exiting thinking block to properly signal end of reasoning section in streaming responses.
- Encode thoughtSignature into tool_call.id using _TSIG_ delimiter and base64url
- Decode _TSIG_ on request to restore thoughtSignature for Gemini multi-turn thinking
- Track pendingThoughtSignature across parts for deferred signature attachment
- Add LocalMutex (2-layer locking) to prevent ELOCKED on concurrent DB access
- Increase lockfile retries from 5 to 15 for multi-process robustness
- Restore db.json seed on first run to prevent ENOENT on lockfile.lock
- Use process.env.BASE_URL fallback in models test route
- Remove gemini-3-flash-lite-preview from provider models
Co-authored-by: kwanLeeFrmVi <quanle96@outlook.com>
Closes#450
Made-with: Cursor
- Add claudeHeaderCache.js to intercept and cache live Claude Code client headers
- Forward cached headers dynamically to api.anthropic.com via default.js
- Strip first-party identity headers (x-app, claude-code-* beta) for non-Anthropic upstreams
- Validate and sanitize tool call IDs to match Anthropic pattern (^[a-zA-Z0-9_-]+$)
- Skip thinking blocks when applying cache_control; fix max_tokens buffer (+1024)
- Strip cache_control from thinking blocks in openai-to-claude translator
- Comment out thoughtSignature in Gemini translator (kept for reference)
- Expand .gitignore to match all deploy*.sh variants
Co-authored-by: kwanLeeFrmVi <quanle96@outlook.com>
Closes#433
Made-with: Cursor
Apply fix from PR #354 by @tannk4w to properly signal tool_calls finish_reason
when model emits tool calls, allowing OpenAI-compatible clients to continue with
tool result processing instead of stopping prematurely.
Refactored finish_reason logic into computeFinishReason() helper to eliminate
duplication and improve maintainability across flush and completion paths.
Co-authored-by: tannk4w <tannk@tmi-soft.vn>
Thanks to @tannk4w, @trungtq2799, @quanhavn, and @East-rayyy for the thorough
review and improvement suggestions on the original PR.
Made-with: Cursor
Previously only base64 data: URLs were handled in the OpenAI-to-Claude
and OpenAI-to-Gemini request translators. HTTP/HTTPS image URLs were
silently dropped, causing vision-capable models to respond with
"I don't see any image."
Some upstream providers (e.g. Antigravity) return non-standard finish_reason
values like 'other' instead of the OpenAI-standard 'tool_calls' when the
model invokes tools. This causes downstream consumers (e.g. OpenClaw) to
fail to execute tool calls, breaking agentic sub-agent workflows.
Changes:
- nonStreamingHandler: post-translation guard that normalizes finish_reason
to 'tool_calls' when message.tool_calls is present
- sseToJsonHandler: accumulate tool_calls from streaming deltas in
parseSSEToOpenAIResponse; extract function_call items from Responses API
output in handleForcedSSEToJson
- openai-responses translator: use toolCallIndex to choose between
'tool_calls' and 'stop' in flush and response.completed events
Tested: 7 scenarios (non-stream text, single/multiple tool calls, stream
text/tool calls, multi-turn tool conversation, tools present but unused)
Gemini API requires enum properties to have an explicit type:"string"
declaration. Without it, tool calls with enum parameters return 400
Bad Request. Fixes#359.
Translates OpenAI response_format parameter into Claude-compatible system
prompt instructions, enabling structured JSON output for json_schema and
json_object types.
Co-authored-by: Nick Roth <nlr06886@gmail.com>
Made-with: Cursor
Cursor sends images as Chat Completions format:
{ type: "image_url", image_url: { url: "data:...", detail: "auto" } }
But Codex Responses API requires:
{ type: "input_image", image_url: "data:..." }
- openai-responses.js: bidirectional conversion image_url <-> input_image
- responsesApiHelper.js: input_image -> image_url in Responses->Chat path
- codex.js: safety net conversion in executor before sending to Codex API
Note: Cursor has a known bug where images bypass the Override OpenAI Base URL
and are sent directly to api.openai.com. This fix is effective for other clients
(curl, Codex CLI, Claude Code) that route through the proxy correctly.
Made-with: Cursor
Codex CLI sends "hosted" tools (e.g. `request_user_input`) via the OpenAI
Responses API. These tools have no explicit `name` field. The previous
`body.tools.map()` pass propagated `name: undefined` into the resulting
Chat Completions function declarations, which then became anonymous
`functionDeclarations` after the OpenAI→Gemini translation step.
Gemini strictly requires every function declaration to have a valid name
and rejects the entire request with:
GenerateContentRequest.tools[0].function_declarations[4].name:
Invalid function name. Must start with a letter or an underscore.
Fix: filter out any Responses API tool that lacks a non-empty `name`
string before converting to `{ type: "function", function: { name, ... } }`.
Named function tools are unaffected; only unnamed hosted tools are skipped.
Fixes: Gemini 400 error when Codex CLI is routed through 9router.
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-authored-by: Claude <noreply@anthropic.com>
- Added handling for HTTP_STATUS.NOT_ACCEPTABLE in error types and messages.
- Enhanced the `prepareClaudeRequest` function to filter built-in tools for non-Anthropic providers and clean up empty tool arrays.
- Updated the `openaiToClaudeRequest` function to handle built-in tools more effectively and ensure proper tool conversion.
- Improved the `claudeToOpenAIResponse` function to skip processing for built-in server tool blocks.
- Refined error message handling in the `parseUpstreamError` function to ensure meaningful output.
- Adjusted command checks for tool installations across various settings routes to use `command -v` for better compatibility.
* feat: add AI request details feature with latency tracking
Add comprehensive request history and debugging capability to the Usage dashboard:
**Storage Layer** (usageDb.js):
- Add saveRequestDetail() for storing full request/response details
- Implement FIFO queue with 1000-record limit in request-details.json
- Auto-sanitize sensitive headers (authorization, api-key, cookie, token)
- Add getRequestDetails() with pagination and filtering support
- Add getRequestDetailById() for single record lookup
**Pipeline Integration** (chatCore.js):
- Track request start time and calculate total latency
- Record TTFT (Time To First Token) and total latency for all requests
- Capture full request details (messages, model, parameters)
- Save response content for non-streaming, mark streaming responses
- Handle error cases with detailed error information
- Async non-blocking saves to avoid impacting request performance
**API Layer** (/api/usage/request-details):
- GET endpoint with pagination (page, pageSize: 1-100)
- Filter by provider, model, connectionId, status, date range
- Returns { details: [...], pagination: {...} } format
**UI Components**:
- Drawer.js: Right slide-out panel with backdrop blur and ESC close
- Pagination.js: Full pagination with page size selector (10/20/50)
- RequestDetailsTab.js: Complete table view with filters and detail drawer
**Dashboard Integration**:
- Add "Details" tab to Usage page (4th tab after Overview/Logger/Limits)
- Table columns: Timestamp, Model, Provider, Input Tokens, Output Tokens, Latency (TTFT/Total), Action
- Provider filter dropdown (9 providers supported)
- Date range filters (start/end datetime)
- Click "Detail" button to view full request/response JSON in slide-out drawer
**Features**:
- Real-time latency monitoring (TTFT & Total)
- Complete request/response inspection for debugging
- Filterable and searchable request history
- Responsive design with mobile-friendly filters
- Data security with automatic header sanitization
- Performance: async saves don't block request pipeline
**Files Created/Modified**:
- src/lib/usageDb.js (modified)
- open-sse/handlers/chatCore.js (modified)
- src/app/api/usage/request-details/route.js (new)
- src/shared/components/Drawer.js (new)
- src/shared/components/Pagination.js (new)
- src/app/(dashboard)/dashboard/usage/components/RequestDetailsTab.js (new)
- src/app/(dashboard)/dashboard/usage/page.js (modified)
Closes: AI Observability Dashboard feature
* feat: enhance request details with full config and streaming content capture
Improve Request Details feature to capture comprehensive request parameters
and actual streaming response content:
**Request Configuration Enhancement** (chatCore.js):
- Add extractRequestConfig() helper function to capture all request parameters
- Include temperature controls: temperature, top_p, top_k
- Include token limits: max_tokens, max_completion_tokens
- Include thinking/reasoning modes: thinking, reasoning, enable_thinking
- Include OpenAI parameters: presence_penalty, frequency_penalty, seed, stop,
tools, tool_choice, response_format, n, logprobs, top_logprobs, logit_bias,
user, parallel_tool_calls, prediction, store, metadata
- Apply to all request types: non-streaming, streaming, and error cases
**Streaming Content Capture** (chatCore.js & stream.js):
- Add onStreamComplete callback mechanism to stream processors
- Accumulate content from all formats: OpenAI, Claude, Gemini
- Track content from delta.content, delta.reasoning_content, delta.text,
delta.thinking, and Gemini content.parts
- Save initial record with "[Streaming in progress...]" marker
- Update record with actual content when stream completes
- Include usage tokens when available from stream
**Files Modified**:
- open-sse/handlers/chatCore.js - extractRequestConfig() + streaming capture
- open-sse/utils/stream.js - onStreamComplete callback + content accumulation
**Benefits**:
- View complete request configuration in Request Details (thinking mode, etc.)
- See actual streaming response content instead of placeholder
- Better debugging and observability for AI requests
Refs: #request-details-enhancement
* feat: separate thinking/reasoning content from response content
Improve Request Details to display thinking process separately from final response:
**Backend Changes**:
- stream.js: Capture content and thinking separately in streaming mode
- Add accumulatedThinking variable alongside accumulatedContent
- Route delta.content to content, delta.reasoning_content to thinking
- Support OpenAI (reasoning_content), Claude (thinking), Gemini (part.thought)
- Update onStreamComplete callback to return { content, thinking } object
- chatCore.js: Update response structure to include thinking field
- Non-streaming: Extract thinking from reasoning_content field
- Streaming: Receive { content, thinking } from stream callback
- Error responses: Include thinking: null
- Initial streaming save: Include thinking: null
**Frontend Changes**:
- RequestDetailsTab.js: Display thinking and content in separate sections
- Add amber/yellow themed "Thinking Process" section with psychology icon
- Show "Final Response" label when thinking is present
- Use distinct visual styling for thinking (amber bg) vs content (gray bg)
- Only show thinking section when thinking content exists
**Benefits**:
- Users can clearly see model's reasoning process vs final answer
- Better debugging for models with thinking capabilities (Claude, o1, etc.)
- Visual distinction makes it easy to identify thinking vs response
Refs: #thinking-content-separation
* fix: map Claude thinking to reasoning_content field
Fix Claude thinking content to be properly captured as reasoning_content
instead of regular content, enabling separate display in Request Details:
**Changes**:
- claude-to-openai.js: Use reasoning_content field for thinking blocks
- thinking start: send { reasoning_content: "" } instead of { content: "```\n```" }
- thinking delta: map to reasoning_content instead of content
- thinking stop: send { reasoning_content: "" } instead of { content: "```\n```" }
**Why This Matters**:
- Previously Claude thinking was sent as `content` field, mixed with actual response
- Now thinking uses `reasoning_content` field, matching OpenAI's o1 format
- stream.js can now properly route thinking to accumulatedThinking variable
- Request Details UI will show Claude thinking in separate "Thinking Process" section
**Supported Thinking Formats**:
- OpenAI: delta.reasoning_content → thinking
- Claude: delta.thinking → reasoning_content (now fixed)
- Gemini: part.thought === true → thinking
Refs: #claude-thinking-fix
* feat(observability): capture and display full 4-layer request chain
Capture complete request/response chain in AI Request Details:
- Add providerRequest field (translated request sent to provider)
- Add providerResponse field (raw provider response, streaming indicator)
- Update chatCore.js at all 5 saveRequestDetail() call sites
- Reorganize UI into 4 collapsible sections with Material icons
- Preserve backward compatibility for old records
- Add distinct styling for streaming indicator
* fix(observability): resolve React duplicate key warning in request details table
- Use composite key (detail.id + index) to ensure unique keys
- Prevents React warnings when database contains duplicate IDs from old ID generation
* fix(observability): display actual content in streaming request details
Change providerResponse field for streaming requests from placeholder
"[Streaming - raw response not captured]" to actual final content.
This improves debugging experience by showing the real AI response
in the "Provider Response (Raw)" section instead of a confusing
placeholder message.
Files changed:
- open-sse/handlers/chatCore.js: Save contentObj.content to providerResponse
- src/app/.../RequestDetailsTab.js: Remove special handling for placeholder
* refactor(observability): migrate request details to SQLite for improved concurrency
- Replace LowDB JSON storage with better-sqlite3
- Enable WAL mode for true concurrent read/write support
- Add 5 indexes to accelerate queries (timestamp, provider, model, connection_id, status)
- Perform pagination at the database level to reduce memory footprint
- Maintain 1000 record limit with automatic cleanup of old data
- Ensure API compatibility via re-exports, requiring no caller changes
Performance improvements:
- Concurrent Writes: Lock-free WAL mode prevents data contention
- Query Efficiency: Index-based searches replace full dataset loading
- Data Integrity: Atomic operations prevent file corruption
* fix(observability): resolve pagination statistics display issues
- Fix issue where totalItems=0 showed 'Showing 1 to 0 of 0 results'
- Hide pagination controls when totalItems=0 or totalPages<=1
- Standardize API response fields: pagination.total -> pagination.totalItems
Before: Incorrect stats shown for empty data, and pager visible even for single-page results
After: Stats hidden for empty data, pager hidden when navigation is unnecessary
* feat(observability): display friendly provider names in request details
- Add /api/usage/providers endpoint to dynamically fetch provider list with names
- Replace hardcoded provider options with dynamic loading from database
- Display friendly provider names instead of IDs in both table and detail drawer
- Support custom provider nodes (e.g., OpenAI-compatible) with user-defined names
- Add provider name caching to optimize performance
* fix(observability): use INSERT OR REPLACE for request details to handle streaming updates
* fix(observability): resolve zero-token display issue by ensuring streaming usage capture and fixing key mismatch
* fix(observability): separate TTFT and total latency calculation for streaming requests
* feat(observability): implement SQLite write queue and JSON size limits
- Added in-memory buffer and batch writing for SQLite to prevent lock contention
- Implemented with configurable 1MB limit to prevent DB bloat
- Added dashboard UI for observability performance and data management settings
- Integrated graceful shutdown handlers to prevent data loss
* fix(observability): resolve ReferenceError by declaring dbInstance
- Added new observability settings in the dashboard for max records, batch size, flush interval, and max JSON size.
- Introduced `extractRequestConfig` function to capture full request configurations.
- Enhanced error handling by saving detailed request information on failures.
- Updated usage tracking to include new token metrics.
- Modified streaming functions to support detailed content and reasoning tracking.
Preserve thinking configuration when converting OpenAI requests to Claude format.
- Handle thinking.type with 'enabled' as default
- Preserve thinking.budget_tokens when present
- Preserve thinking.max_tokens when present
This enables proper thinking mode support for o1-series models
when routed through 9Router to Claude endpoints.
Ultraworked with [Sisyphus](https://github.com/code-yeongyu/oh-my-opencode)
Co-authored-by: Sisyphus <clio-agent@sisyphuslabs.ai>
(cherry picked from commit 65d80e9269cc6789cb1522b276e8b8399fddbcab)
decolua