- Introduced a comprehensive JSON configuration for a new workflow that includes user guidance, input handling, and AI chat integration.
- The workflow features nodes for system configuration, workflow start, and accident information collection, enhancing user interaction and data collection capabilities.
- Implemented various input types and configurations to support dynamic user interactions and improve overall workflow efficiency.
- Introduced a comprehensive prompt file detailing the role and operational guidelines for a traffic accident reporting AI.
- Established strict output formatting rules to ensure clarity in user interactions, including state management and response protocols.
- Emphasized safety prioritization and robust handling of user inputs, particularly regarding the assessment of potential injuries and the transition to human assistance.
- Changed the module name for form extraction to "更新表单" for clarity.
- Enhanced the extraction process to accommodate various output formats from nodes, ensuring compatibility with different structures.
- Improved handling of empty or invalid form updates, returning an empty object when necessary to maintain robustness.
- Updated prompts to enhance clarity and consistency in user interactions, particularly focusing on safety prioritization and accurate information collection.
- Introduced new YAML evaluation cases to test various user input scenarios, ensuring robust handling of short, ambiguous, or irrelevant responses.
- Enhanced guidelines for transitioning to human assistance, emphasizing strict conditions for triggering state changes based on user responses.
- Introduced new section for user inputs that confirm system availability, detailing specific phrases that indicate active engagement.
- Clarified response protocol for such inputs, ensuring the system maintains its current state and provides brief confirmations.
- Enhanced overall user experience by addressing common interaction scenarios in the accident reporting process.
- Updated the evaluation runner to support live dialogue printing and transcript saving in both Markdown and JSON formats.
- Introduced new data classes for managing transcripts and their components, improving structure and readability.
- Modified existing YAML case files to align with the new direct client mode and updated stage codes.
- Added new test cases for the direct client mode, ensuring comprehensive coverage of user interactions.
- Introduced a normalization function for client mode to default to "direct" when input is empty or None.
- Updated the clientMode field to use a new type with BeforeValidator for improved validation.
- Added a test to ensure empty client mode inputs correctly default to "direct".
- Introduced two new prompt files for traffic accident reporting, detailing the interaction protocol and state management for both single and dual vehicle scenarios.
- Established strict output formatting rules to ensure clarity and consistency in user interactions, including handling of user responses.
- Enhanced guidelines for safety prioritization and accurate information collection during the accident reporting process.
- Revised state codes to enhance clarity in user interactions, replacing previous codes with new ones indicating successful verification and transition to human assistance.
- Adjusted output messages to reflect the updated state management, ensuring a smoother user experience during the information confirmation phase.
- Improved guidelines for handling user responses, emphasizing accurate information collection and efficient transition to human support.
- Introduced a detailed prompt file for dual vehicle accident photo capture and verification, outlining the interaction protocol and state management.
- Established strict output formatting rules to ensure clarity and consistency in user interactions.
- Included comprehensive guidelines for handling various user responses, prioritizing accurate information collection during dual vehicle accident reporting.
- Introduced a detailed prompt file for a traffic accident reporting AI, outlining the interaction protocol and state management.
- Established strict output formatting rules to ensure clarity and consistency in user interactions.
- Included comprehensive guidelines for handling various user responses, prioritizing safety and accurate information collection during accident reporting.
- Introduced a comprehensive prompt file for a traffic accident reporting AI, detailing the interaction protocol and state management.
- Established strict output formatting rules to ensure clarity and consistency in user interactions.
- Included guidelines for handling various user responses, emphasizing safety and accurate information collection during accident reporting.
- Introduced a comprehensive document detailing the interaction interface design for the intelligent information collection robot.
- Updated version history with new features, including the addition of the clientMode parameter and its impact on output formatting.
- Enhanced clarity in the API request and response structures, including examples for better understanding of the interaction flow.
- Introduced new files for single and dual vehicle accident photo guidance, detailing step-by-step instructions and state management protocols.
- Implemented strict output formatting and error handling for user interactions during the photo capture process.
- Enhanced the overall structure to ensure clarity and consistency in guiding users through the accident documentation process.
- Updated documentation and API endpoint to include a new state code '0005' for handling cases where photo recognition fails consecutively, directing to human assistance.
- Ensured consistency between documentation and code for improved clarity in state management.
- Revised the formUpdate section to clarify the conditions under which structured updates are pushed.
- Added specific examples for accident vehicle count and cause of the incident to enhance understanding.
- Adjusted text_delta examples for improved clarity in response handling.
- Replaced hardcoded URLs with a base URL variable for better configurability.
- Updated request payloads to use sessionId and timeStamp variables.
- Enhanced the chat request with new parameters: needFormUpdate and useTextChunk.
- Adjusted response content types and lengths for consistency.
- Updated timestamps in response headers for accuracy.
- Added support for UserStartedSpeakingFrame to enhance user interaction tracking.
- Updated the pipeline to reset idle prompt count when a user starts speaking, improving responsiveness during conversations.
- Integrated new event handlers for better management of user turn events and upstream frame processing.
- Added idle prompt timeout, maximum count, and text to multiple voice configuration files to improve user interaction during idle periods.
- Updated greeting mode to 'fastgpt_opener' in relevant configurations for a more dynamic greeting experience.
- Introduced a new voice configuration file for xfyun TTS, including detailed service settings and parameters.
- Refactored the pipeline to handle idle prompts and user turn events, ensuring smoother interaction flow.
- Adjusted the VAD and turn configurations to accommodate new idle prompt features.
- Introduced a camera drawer for capturing images during the conversation flow.
- Added prompts for various camera states to guide users through the photo capture process.
- Updated HTML structure to include camera-related elements and integrated them with existing chat functionality.
- Enhanced JavaScript logic to manage camera state and button enabling/disabling based on connection status.
- Updated CSS for styling the camera drawer and its components, ensuring responsive design across devices.
- Adjusted README to reflect the new demo URL for voice functionality.
Parse leading <state> tags from LLM replies and emit response.state over the product websocket while stripping tags from TTS/text streams. Add FastGPT+Xfyun voice configs (including state-enabled preset), SuperTTS support, and context sync for interrupted turns. Refresh the voice demo with a state indicator and collapsible audio delta websocket log groups.
Co-authored-by: Cursor <cursoragent@cursor.com>
Eric Wang