- 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.
- Introduced a new function to extract the first state code and clean content by removing state tags.
- Updated the chat endpoint to utilize the new extraction function, improving state handling and content processing.
- Enhanced logging to provide clearer insights into extracted state codes and cleaned content.
- 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.
- Moved SentenceTextChunker and SentenceTextChunkerConfig to the utils module for better organization.
- Updated pytest.ini to include the current directory in the Python path.
- Added a new utils module with shared utility helpers.
- Adjusted import paths in the test files to reflect the new location of text chunking classes.
- Introduced SentenceTextChunker and SentenceTextChunkerConfig for improved text processing in chat responses.
- Updated chat endpoint to conditionally use text chunking based on the new 'useTextChunk' parameter from the request.
- Enhanced logging to include 'useTextChunk' status and adjusted text delta handling to support chunked responses.
- Modified ProcessRequest_chat model to include 'useTextChunk' field for request handling.
- Added unit tests for SentenceTextChunker to ensure correct chunking behavior and edge case handling.
- Added detailed logging for chat request processing, including session ID, input text length, and latency measurements.
- Implemented performance tracking for streaming events, capturing first event and text delta timings.
- Improved error handling logging to include session context and duration on failures.
- Updated non-stream response logging to include latency and output details for better debugging.
- Introduced a new function to parse JSON values in endpoints.py for improved data handling.
- Updated extract_form_update_from_flow_nodes to return structured data instead of strings.
- Changed formUpdate field in ProcessResponse_chat model to use Any type with a default empty dictionary for better flexibility in handling updates.
- Changed ANALYSIS_SERVICE_URL to localhost for local development.
- Updated ANALYSIS_AUTH_TOKEN and APP_ID for improved security.
- Added new functions in endpoints.py for form extraction and stage code normalization.
- Enhanced chat handling to support form updates and improved event streaming.
- Updated models to include new fields for form update handling.
- 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.
Eric Wang