- Eliminated all instances of the final_answer tool from the agent's configuration and logic, transitioning to a model where the agent concludes responses with plain text instead.
- Updated event handling and response analysis to reflect this change, ensuring that the agent's output is now directly delivered as text without relying on a dedicated final answer tool.
- Adjusted localization strings across multiple languages to remove references to final_answer, enhancing clarity and consistency in user-facing messages.
- Improved the overall structure of the agent's response handling to streamline the process and reduce potential confusion regarding tool usage.
refactor(agent): streamline answer handling and preamble logic
- Updated the agent's response handling to treat any text streamed before a tool call as a preamble, ensuring it is not included in the final answer.
- Removed the superseded marker logic from the event emission process, simplifying the flow of answer content and enhancing clarity in the UI.
- Adjusted the event handling to ensure that preamble segments are correctly retracted and relocated into the steps tree, improving the overall user experience.
- Enhanced the agent's internal logic to better manage answer segments and their states during streaming, leading to a more coherent response structure.
To diagnose where latency lives between "user hits send" and "first
token appears" we need a single number that can be matched across
the browser console and the server log. Add correlated TTFB markers
keyed by X-Request-ID:
Frontend (streame.ts)
* Generate the X-Request-ID once and reuse it for logging.
* Log request:start when fetchEventSource is invoked, response:headers
when onopen fires, and response:first_answer the first time an SSE
payload with response_type === 'answer' arrives. Filtering by event
type avoids treating session_title / references / tool_call as the
"first token".
Backend (session handler)
* parseQARequest records the wall-clock entry time and logs TTFB:start
with the same X-Request-ID.
* qaRequestContext carries receivedAt through to the stream handler.
* AgentStreamHandler emits a one-shot TTFB:first_answer_chunk log the
first time it observes an AgentFinalAnswerData chunk, so the delta
against TTFB:start is the server's request-in → first-token-out
budget.
The frontend delta minus the backend delta is then attributable to
network + gin middleware, which were previously invisible.
Add an opt-in human approval gate so Agent runs pause before executing
MCP tools that operators flag as dangerous, surface an approval card in
the chat UI, and only resume after the user approves (optionally with
edited args) or rejects.
Backend
- New mcp_tool_approvals table + repo/service to mark per-tool approval
required (PG migration 000042 + sqlite init).
- approval.Gate coordinates RequestAndWait / Resolve with sync.Once
delivery, configurable timeout, and Redis Pub/Sub fan-out so multi-
replica deployments work without sticky sessions.
- MCPTool.Execute integrates the gate; uses a round-level ApprovalCtx
(without the per-tool 60s timeout) for the wait, and re-derives a
fresh 60s exec ctx after approval so CallTool keeps a full window.
- New SSE response types (tool_approval_required / _resolved) and
EventBus events plumb approval state to AgentStreamDisplay.
- REST: list/set per-tool approval flag, resolve pending approval.
- Configurable via agent.tool_approval_timeout_seconds (yaml) or
WEKNORA_AGENT_TOOL_APPROVAL_TIMEOUT env (accepts seconds or Go
duration).
Frontend
- MCP settings: per-tool "require approval" switch on the test panel.
- Chat: ToolApprovalCard renders the pause point with editable JSON
args, validation feedback, mm:ss countdown that turns warning/danger
near deadline, and a resolved state that retains context.
- i18n strings added for zh-CN / en-US / ko-KR / ru-RU.
Docs
- docs/zh/mcp-approval.md covering behavior, config, API, deployment
considerations (Redis cross-instance, restart limitations).
- Updated context template to include runtime metadata such as current time and week, improving contextual awareness in user queries.
- Enhanced rewrite template with critical instructions for intent classification, ensuring that rewritten questions preserve essential entities and keywords.
- Refined intent classification logic to prioritize user intents more effectively, improving the accuracy of responses based on user queries.
- Added examples to clarify expected input and output formats for intent classification, enhancing usability for developers.
- Added diagnostics for streaming events in the AgentEngine, including chunk counts and response type distributions.
- Implemented logging for emitted event types during the thinking process to aid in debugging and performance analysis.
- Updated the session handler to provide more informative warnings when fallback answers are emitted due to non-streaming behavior.
- Introduced a dedicated HTTP client for Ollama to improve connection handling and timeout management during streaming calls.
- Updated the AgentEngine to emit final answer events even when the LLM stops without calling the final_answer tool, ensuring the frontend can render responses correctly.
- Added fallback logic in the AgentStreamHandler to emit final answers as fallback events when no answer events are streamed, improving robustness in edge cases.
- Introduced the final_answer tool to ensure agents submit their complete responses as the last action, improving response accuracy and consistency.
- Updated the agent engine to log detailed information about tool calls and responses, including the total duration of agent execution.
- Enhanced the chat message model to include agent_duration_ms, tracking the total execution time from query start to answer delivery.
- Implemented JSON field extraction for streaming responses, allowing for more efficient handling of tool call outputs.
These changes significantly improve the agent's response handling and ensure that final answers are consistently delivered, enhancing overall user experience.
- Introduced a new `is_fallback` property to track when responses are generated without knowledge base matches.
- Updated the chat components to display fallback hints and indicators in the UI, enhancing user awareness of fallback responses.
- Added translations for fallback hints in multiple languages, improving accessibility for diverse users.
- Modified backend logic to emit fallback status in response events, ensuring consistent handling across the application.
These changes improve the user experience by providing clear feedback on fallback responses, enhancing the overall interaction with the chat system.
- Added a new `.env.lite.example` file for the Lite version, providing a minimal configuration template.
- Updated `.env.example` to remove deprecated variables and include new Docreader settings.
- Enhanced Docker configurations to support the Lite version, including a new Dockerfile for the Docreader service.
- Introduced a Makefile target for building and running the Lite version, along with packaging capabilities.
- Created GitHub workflows for building and releasing Lite binaries, including Homebrew formula support.
- Implemented a new service file for managing the Lite version as a system service.
This update enables a streamlined, single-binary deployment of WeKnora, reducing external dependencies and simplifying setup.
- Removed outdated DEVELOPMENT.md, consolidating development instructions into relevant documentation.
- Updated conversation configuration to include new parameters such as max rounds, embedding thresholds, and rewrite prompts.
- Enhanced UI components to support new conversation settings, including AgentSettings.vue and related views.
- Improved localization in English, Russian, and Chinese for new conversation configuration fields and UI elements.
- Implemented logic to apply tenant-specific conversation settings, ensuring defaults are respected.
- Added duration tracking for agent steps and tool calls, improving event data accuracy.
- Updated AgentStreamDisplay and ToolResultRenderer components to include fallback headers and improved output styling.
- Refactored duration handling in the agent engine and session management to ensure consistent duration reporting.
- Enhanced UI elements for better user experience, including scrollable output areas and improved tooltip visibility.
- Added logic to load and manage web search configuration in the InputField component, ensuring proper handling of web search states.
- Implemented user notifications for unconfigured web search settings, guiding users to the appropriate settings page.
- Enhanced the AgentStreamDisplay component to improve tooltip content rendering for knowledge base citations.
- Updated event data structures to include total duration in milliseconds for better precision in agent completion events.
- Refactored citation handling to ensure inline citations are displayed correctly, improving user experience in content rendering.
- Added Swiper library to package dependencies for improved UI components.
- Updated chat API to include summary model ID in message handling, allowing for more flexible model selection.
- Enhanced InputField component to manage model selection and state more effectively.
- Improved event handling in chat components to support new model features and ensure accurate message processing.
- Refactored SVG assets for better visual consistency and updated styles for improved user experience.
wizardchen