Releases: IBM/Agentics
Release 0.3.4: Pydantic v2 Compatibility Fixes
What's Changed
This release includes critical Pydantic v2 compatibility fixes for Langflow 1.9 integration.
Bug Fixes
- Fixed Pydantic v2 mutable default values in AG class (
states,areduce_batches,crew_prompt_params) - Fixed
merge_statesmethod data alignment bug that caused sentiment analysis results to misalign - Improved error handling for empty LLM responses with detailed logging
Dependencies
- Added
apscheduler>=3.10.0to suppress litellm warnings - Added
fastapi-sso>=0.10.0for complete litellm proxy support
Installation
pip install git+https://github.com/IBM/Agentics.git@v0.3.4
Full Changelog: https://github.com/IBM/Agentics/compare/v0.3.3...v0.3.4v0.3.3
v0.3.3a1
Full Changelog: v0.3.1...v0.3.3a1
v0.3.2 langflow fix
Full Changelog: v0.3.1...v0.3.2
v0.3.1
0.3.0 - Semantic Operators & Documentation
🎯 Key Features
Semantic Operators
sem_map: Apply semantic transformations across datasetssem_filter: Semantically filter data based on LLM-powered predicatessem_agg: Aggregate semantic information across collections
Documentation & Architecture
- Comprehensive documentation improvements for semantic operators
- Refactored LLM connections module for better architecture
- Enhanced
server_urlparameter support for flexible LLM configuration - Updated README with semantic operators integration guide
Bug Fixes & Improvements
- Fixed undefined variable in PydanticTransducerVLLM executor
- Corrected dependency references in pyproject.toml
- Fixed package imports in async_executor.py
- Improved code formatting and pre-commit compliance
- Enhanced module organization and separation of concerns
📦 Installation
Install the latest version:
pip install agentics-py==0.3.0📖 Documentation
- Getting Started: https://github.com/IBM/Agentics/blob/main/docs/getting_started.md
- API Reference: https://github.com/IBM/Agentics/blob/main/docs
Release Date: February 12, 2026
Status: Latest Stable Release
v0.2.4
v0.2.3
v0.2.2
Changes
Core Dependencies
• Added duckdb>=1.4.3 for efficient data querying
• Added pandas>=2.3.3 for enhanced data manipulation
• Added async-lru>=2.0.5 for async caching capabilities
Type System Enhancements ( src/agentics/core/atype.py )
• Added comprehensive docstring to pydantic_model_from_dict() function explaining:
• Dynamic Pydantic model creation from sample dictionaries
• Type inference and field name normalization
• Usage examples and edge cases
• Renamed composition fields from left/right to target/source for semantic clarity:
• target : The destination type in a composition
• source : The source type in a composition
• Removed debug print statement from create_pydantic_model()
Default Types ( src/agentics/core/default_types.py )
• Added Abool type: A new semantic type for boolean values with type validation
• Ensures only boolean values are accepted during construction
• Follows the same pattern as existing Astr type
Transduction Improvements ( src/agentics/core/transducible_functions.py )
• Enhanced Transduce class with string representation methods:
• Added str() : Human-readable string output
• Added repr() : Developer-friendly representation
• Added _one_to_str() : Handles Pydantic models, dicts, lists, and generic types
• Added new parameters to transducible() decorator:
• transduce_fields : List of specific fields to transduce
• prompt_template : Custom prompt template for transduction
• Fixed transduction return type: Now returns TransductionResult consistently
• Fixed generate_prototypical_instances() : Updated field definition to use optional list
Core AG Enhancements ( src/agentics/core/agentics.py )
• Improved batch processing:
• Transduction now chunks inputs using amap_batch_size for better memory management
• Processes chunks sequentially to handle large datasets
• Fixed state merging logic:
• Now filters output fields against allowed model fields (Pydantic v2 compatibility)
• Prevents errors from extra fields in merged states
• Validates AG lengths before merging
• Enhanced explanation generation:
• Improved prompt instructions for better semantic understanding
• Renamed explanation variables for clarity ( left/right → target/source )
• Added confidence scoring guidance to LLM
• Improved compose_states() method:
• Changed from nested loops to paired zip() iteration (matching AG lengths)
• Fixed semantic naming: left/right → target/source
• More efficient and semantically correct composition
• Better error handling:
• Added validation in merge_states() to check length compatibility
• Meaningful error messages for debugging
• Truncated display names: Limited AG names to 30 characters in progress descriptions
v0.2.2a2 Preview - Semantic operators improvements
Changes
This alpha release includes significant improvements to the Agentics framework's type composition system and transduction capabilities.
Key Features
- Enhanced Type Composition: Renamed composition fields from
left/righttotarget/sourcefor better semantic clarity - New Abool Type: Added semantic type for boolean values with validation
- Improved Batch Processing: Transduction now chunks inputs for better memory management
- Better State Merging: Fixed Pydantic v2 compatibility with proper field filtering
- Enhanced Explanations: Improved LLM instructions for more meaningful semantic transductions
- New Dependencies: Added duckdb, pandas, and async-lru for improved data handling
Technical Improvements
- Chunked transduction prevents memory overload with large datasets
- Better error handling with meaningful validation messages
- Improved string representations for Transduce objects
- Pre-commit fixes applied
For detailed information, see PR #115