- Added context enrichment for actions in `fetch_new_actions_from_db`, providing complete information for posts, comments, and user interactions.
- Introduced a new `_enrich_action_context` function to supplement action arguments with relevant details such as post content, author names, and comment information.
- Updated the `ZepGraphMemoryUpdater` to batch send activities by platform, improving efficiency in processing and logging.
- Enhanced logging to include detailed statistics on sent activities and skipped actions, ensuring better traceability and monitoring of the activity flow.
- Introduced a prefix to optimize interview prompts, ensuring agents respond directly with text without invoking tools.
- Updated the simulation API to utilize the optimized prompts for individual and batch interviews.
- Modified the `get_interview_history` function to allow for flexible platform querying, returning results from both Reddit and Twitter when no platform is specified.
- Enhanced README.md to include new prompt optimization details and updated API usage examples for clarity.
- Added a new Interview module to facilitate interactions with agents post-simulation, allowing for single and batch interviews.
- Introduced IPC communication mechanism for command and response handling between the Flask backend and simulation scripts.
- Updated README.md to include detailed instructions on the new Interview functionality, including API endpoints and usage examples.
- Enhanced simulation scripts to support waiting for commands after completion, improving user control over the simulation environment.
- Implemented error handling and logging for interview processes, ensuring robust operation and traceability.
- Removed content truncation logic from the AgentActivity class, allowing full content to be logged for posts, comments, and quotes.
- Updated the `fetch_new_actions_from_db` function to retain complete content in action arguments, enhancing data accuracy.
- Adjusted simulation scripts to ensure that full content is sent during action creation, improving the representation of agent activities.
- Changed the activity logging format to remove simulation prefixes, ensuring clearer natural language descriptions.
- Updated the `ZepGraphMemoryUpdater` to send activities individually, enhancing the accuracy of entity and relationship extraction.
- Adjusted the README.md to reflect these changes in activity processing and Zep integration, providing clearer instructions for users.
- Added a new optional parameter `enable_graph_memory_update` to the simulation API, allowing real-time updates of agent activities to the Zep knowledge graph.
- Introduced `ZepGraphMemoryUpdater` and `ZepGraphMemoryManager` classes to handle the background processing of activity updates, ensuring efficient API calls and data management.
- Updated the README.md to include detailed instructions on the new graph memory update functionality and its configuration.
- Enhanced the simulation runner to manage the lifecycle of the graph memory updater, including starting and stopping the updater based on user configuration.
- Improved logging to track the status of graph memory updates, providing better insights into the simulation process.
- Added logging for the start and end of round 0 in both Twitter and Reddit simulations, improving traceability of initial events.
- Updated the logging mechanism to record round end even when no active agents are present, ensuring comprehensive action tracking.
- Introduced initial action count tracking to provide insights into the number of actions taken during the initial phase of simulations.
- Added support for a `max_rounds` parameter in simulation API, allowing users to limit the number of simulation rounds, improving control over simulation duration.
- Updated README.md to reflect the new `max_rounds` parameter and its usage in simulation requests.
- Enhanced error handling for `max_rounds` input validation to ensure it is a positive integer.
- Modified simulation runner and related scripts to incorporate `max_rounds` functionality, ensuring consistent application across Twitter and Reddit simulations.
- Improved logging to indicate when the number of rounds is truncated due to the `max_rounds` setting, enhancing traceability during simulation execution.
- Introduced `get_agent_names_from_config` function to map agent IDs to their entity names from the simulation configuration, enhancing clarity in action representation.
- Updated simulation scripts to utilize this new function for fetching agent names, ensuring that real entity names are displayed instead of default identifiers.
- Improved handling of agent names by falling back to default names only if not specified in the configuration, maintaining consistency across simulations.
- Added a new endpoint to retrieve real-time agent profiles during simulation, allowing users to monitor progress without going through the SimulationManager.
- Enhanced the profile generation process to support real-time saving of generated profiles to specified file formats (JSON for Reddit, CSV for Twitter).
- Updated the simulation configuration generator to assign appropriate agents to initial posts based on their types, improving the relevance of generated content.
- Improved error handling and logging for better traceability during profile generation and retrieval processes.
- Updated .env.example to include new keys for dual LLM configuration, allowing for both general and boost settings.
- Modified create_model function to support an optional use_boost parameter, enabling the selection of either general or boost LLM configurations based on availability.
- Improved logging to indicate which LLM configuration is being used during model creation, enhancing clarity for users.
- Introduced MaxTokensWarningFilter to suppress specific warnings related to max_tokens in the logging output across simulation scripts.
- Added a semaphore parameter to limit the maximum concurrent LLM requests in Twitter and Reddit simulation functions, preventing API overload.
- Ensured the filter is applied immediately upon module loading for effective logging management.
- Introduced a new Python script to check and display the balance of credits using the OpenRouter API.
- Implemented error handling for API requests and included informative print statements for total credits, total usage, and remaining balance.
- Added a placeholder for the API key to facilitate user customization.
- Translated and reorganized the README.md to provide a comprehensive overview of the MiroFish Backend, including project introduction, technical architecture, and core functionalities.
- Added a structured table of contents for easier navigation.
- Enhanced descriptions of core features such as knowledge graph construction, ontology generation, and dual-platform simulation capabilities.
- Updated project structure section to reflect the current file organization and added detailed explanations for key components.
- Included API documentation for graph management and simulation processes, improving clarity for developers and users.
- Registered a cleanup function for simulation processes to ensure proper termination on server shutdown.
- Improved logging during application startup to confirm the registration of the cleanup function.
- Updated simulation preparation checks to clarify the conditions for considering a simulation ready, enhancing error handling and user feedback.
- Added detailed logging for simulation status changes, improving traceability during the simulation lifecycle.
- Introduced new files for simulation configuration and profile data, supporting enhanced testing and visualization capabilities.
- Updated simulation preparation checks to exclude script files from the required files list, improving clarity on file management.
- Implemented a robust retry mechanism for Zep API calls in the ZepEntityReader service, enhancing reliability.
- Enhanced logging in simulation scripts to provide clearer insights into the simulation process and errors.
- Updated simulation runner to manage stdout and stderr logs more effectively, ensuring better error tracking.
- Improved profile generation to standardize gender fields and ensure all required fields are populated correctly.
- Updated README.md to include detailed descriptions of new features, including Zep mixed search functionality and detailed persona generation for individual and group entities.
- Implemented a robust mechanism for checking simulation preparation status to avoid redundant profile generation.
- Added support for parallel profile generation, improving efficiency in creating OASIS Agent Profiles.
- Enhanced the simulation configuration generator to adopt a stepwise approach, ensuring better handling of complex configurations.
- Introduced error handling and retry mechanisms for LLM calls, improving the reliability of profile generation.
- Updated simulation management to support new API parameters for controlling profile generation behavior.
- Updated README.md to include new simulation scripts and configuration details for OASIS, including API retry mechanisms and environment variable settings.
- Added simulation management and configuration generation services to streamline the simulation process across Twitter and Reddit platforms.
- Introduced new API routes for simulation-related operations, including entity retrieval and simulation status management.
- Implemented a robust retry mechanism for external API calls to improve system stability.
- Enhanced task management model to include detailed progress tracking.
- Added logging capabilities for action tracking during simulations.
- Included new scripts for running parallel simulations and testing profile formats.
- Updated README.md to reflect the removal of the project creation endpoint, adjusting the workflow steps accordingly.
- Removed the `create_project` function from graph.py, streamlining the project management API by eliminating deprecated functionality.
- Updated `run.py` to conditionally print startup information only in the reloader process to avoid duplicate logs in debug mode.
- Modified `__init__.py` to log startup and completion messages based on the reloader process condition.
- Added warnings suppression in `graph_builder.py` for Pydantic v2 regarding Field usage.
- Revised `ontology_generator.py` to enforce strict design guidelines for entity types and relationships, ensuring compliance with new requirements.
- Improved logging behavior in `logger.py` to prevent log propagation to the root logger, avoiding duplicate outputs.
- Created a new Streamlit application for visualizing knowledge graphs.
- Implemented text extraction from PDF, Markdown, and TXT files.
- Developed graph building logic using Zep Cloud API.
- Added support for custom entity types and relationships.
- Included interactive HTML visualization for generated graphs.
- Updated .gitignore to include new directories and files.
- Added example environment configuration file (.env.example) for API key setup.
- Created README.md with installation and usage instructions.
- Introduced various utility scripts and styles for enhanced functionality.
