Task Memory Summary Ops¶
TrajectoryPreprocessOp¶
Purpose¶
Preprocesses trajectories by validating and classifying them based on their score.
Functionality¶
Validates and classifies trajectories as success or failure based on a threshold
Modifies tool calls in messages to ensure consistent format
Sets context for downstream operators with classified trajectories
Parameters¶
op.trajectory_preprocess_op.params.success_threshold(float, default:1.0):The threshold score that determines if a trajectory is considered successful
Trajectories with scores greater than or equal to this value are classified as successful
TrajectorySegmentationOp¶
Purpose¶
Segments trajectories into meaningful step sequences to enable more granular memory extraction.
Functionality¶
Uses LLM to identify logical break points in trajectories
Adds segmentation information to trajectory metadata
Enables more focused memory extraction from specific parts of conversations
Parameters¶
op.trajectory_segmentation_op.params.segment_target(string, default:"all"):Determines which trajectories to segment
Options:
"all","success","failure"
SuccessExtractionOp¶
Purpose¶
Extracts task memories from successful trajectories.
Functionality¶
Processes successful trajectories to identify valuable memories
Can work with both entire trajectories and segmented step sequences
Uses LLM to extract structured task memories with when-to-use conditions
Parameters¶
No specific parameters beyond the LLM configuration.
FailureExtractionOp¶
Purpose¶
Extracts task memories from failed trajectories to capture lessons learned from unsuccessful attempts.
Functionality¶
Processes failed trajectories to identify pitfalls and mistakes
Can work with both entire trajectories and segmented step sequences
Uses LLM to extract structured task memories with when-to-use conditions
Parameters¶
No specific parameters beyond the LLM configuration.
ComparativeExtractionOp¶
Purpose¶
Extracts comparative task memories by comparing different scoring trajectories.
Functionality¶
Performs “soft comparison” between highest and lowest scoring trajectories
Can perform “hard comparison” between success and failure trajectories using similarity search
Identifies key differences that contributed to success or failure
Parameters¶
op.comparative_extraction_op.params.enable_soft_comparison(boolean, default:true):When
true, enables comparison between highest and lowest scoring trajectories
op.comparative_extraction_op.params.enable_similarity_comparison(boolean, default:false):When
true, enables similarity-based comparison between success and failure trajectories
op.comparative_extraction_op.params.similarity_threshold(float, default:0.3):The threshold for considering two trajectories similar
op.comparative_extraction_op.params.max_similarity_sequences(integer, default:5):Maximum number of sequences to compare to avoid computational overload
op.comparative_extraction_op.params.max_similarity_pairs(integer, default:3):Maximum number of similar pairs to process
MemoryValidationOp¶
Purpose¶
Validates the quality of extracted task memories to ensure they are useful and relevant.
Functionality¶
Uses LLM to validate each extracted memory
Scores memories based on quality and relevance
Filters out low-quality memories based on validation threshold
Parameters¶
op.memory_validation_op.params.validation_threshold(float, default:0.5):The minimum score for a memory to be considered valid
MemoryDeduplicationOp¶
Purpose¶
Removes duplicate task memories to avoid redundancy in the vector store.
Functionality¶
Compares new memories with existing memories in the vector store
Uses embedding similarity to identify duplicates
Ensures only unique memories are stored
Parameters¶
op.memory_deduplication_op.params.similarity_threshold(float, default:0.5):The threshold for considering two memories similar
op.memory_deduplication_op.params.max_existing_task_memories(integer, default:1000):Maximum number of existing memories to check against
SimpleSummaryOp¶
Purpose¶
A simplified version of memory extraction that processes entire trajectories in one step.
Functionality¶
Classifies trajectories as success or failure based on score threshold
Extracts memories directly from complete trajectories
Useful for simpler use cases where detailed segmentation is not required
Parameters¶
op.simple_summary_op.params.success_score_threshold(float, default:0.9):The threshold score that determines if a trajectory is considered successful
SimpleComparativeSummaryOp¶
Purpose¶
A simplified version of comparative memory extraction.
Functionality¶
Groups trajectories by task ID
Compares the highest and lowest scoring trajectories for each task
Extracts comparative insights without complex segmentation
Parameters¶
No specific parameters beyond the LLM configuration.