Changelog
Version history for Zorora.
Version 3.0.0 - Data Analysis Engine
Release Date: February 2026
Major Features
Data Analysis Engine:
/load <path>command — CSV ingest with automatic profiling (time series detection, ODS-E format recognition, null/gap analysis, descriptive statistics)/analyze <code>command — Sandboxed pandas/numpy/matplotlib code execution with blocked dangerous imports and smart result type detection- Session store — Persistent DataFrame state across analysis commands
- Plot capture — Automatic detection of matplotlib saves with file path return
Nehanda Local:
- Offline FAISS-based vector search over local policy document corpus
- Sentence-transformers embeddings with numpy cosine-similarity fallback
Load Dataset Workflow:
- Three-stage pipeline: ingest/detect → profile → session assembly
- Automatic timestamp parsing and ODS-E format detection
- File replacement (loading a new file replaces the previous session)
Architecture Changes
- New
tools/data_analysis/module (profiler, execute, session, nehanda_local) - New
workflows/load_dataset.pyworkflow - Router integration for automatic data analysis intent detection
- Tool registry integration (execute_analysis, nehanda_query)
Testing
- 179 new tests across 5 test suites
- End-to-end integration tests: load CSV → analyze with pandas/numpy/matplotlib
- Demo data validation: tested against real 17,569-row Solarman inverter dataset
Cleanup
- Removed legacy
tool_registry.pybackward-compat shim - Removed
tool_registry_legacy.py(3,300-line backup) - Removed
config.example.py
Dependencies Added
pandas>=2.0.0,numpy>=1.24.0,matplotlib>=3.7.0,scipy>=1.10.0
Version 2.5.0 - ONA Platform Integration & Enhanced Editing
Release Date: January 2025
Major Features
ONA Platform Integration:
- Remote ML model observation commands (
/ml-*) - Model lifecycle management - list challengers, compare models, promote/rollback
- Audit logging for all model changes
- Dual authentication support (Bearer token and AWS IAM)
Enhanced /code File Editing:
- Auto-detection of existing files in prompts
- Direct edit workflow (read → OLD_CODE/NEW_CODE → apply)
- Retry loop with error context (up to 3 attempts)
- No planning phase for simple edits
Beautiful Progress Display:
- Hierarchical tool visualization with tree-style display
- Real-time progress during multi-step operations
- Per-tool execution timing
- Visual status indicators (checkmarks and spinners)
Boxed Input UI:
- prompt_toolkit integration for modern terminal input
- Visual input box with borders
- Improved cursor handling and feedback
New Capabilities
/deep Command:
- Terminal deep research with full feature parity to Web UI
- Academic + web + newsroom multi-source synthesis
Modular Tool Registry (Complete):
- 19 tools migrated to modular
tools/structure - 5 categories: research, file_ops, shell, specialist, image
- Backward compatibility via legacy shim
Model-Agnostic Coding:
use_codestralrenamed touse_coding_agent- Works with any configured coding model
- Unified specialist client factory
Improvements
- Line numbers by default in
read_fileoutput replace_allparameter foredit_file- Better error messages with similar text suggestions
- SQLite threading fixes
- Read-before-edit enforcement
Breaking Changes
use_codestralrenamed touse_coding_agent(alias provided)- Import from
tools.registryinstead oftool_registry(deprecation warning)
Version 2.1.0 - Settings Modal & Multi-Provider Support
Release Date: Previous
Major Features:
- ✅ Web UI Settings Modal - Visual configuration interface
- ✅ Multi-provider endpoint support (HuggingFace, OpenAI, Anthropic)
- ✅ API key management for all providers (masked display, secure storage)
- ✅ Endpoint CRUD operations via Web UI (add/edit/delete)
- ✅ Vision and image_generation model configuration
- ✅ Config file backup before writes
- ✅ Automatic role reassignment on endpoint deletion
Configuration Improvements:
- Visual settings modal (no code editing required)
- Dropdown selection for models and endpoints
- Provider-specific endpoint forms (HF: URL+Model, OpenAI/Anthropic: Model+MaxTokens)
- Secure API key handling (masking, show/hide toggle)
- Config validation and error handling
API Enhancements:
/api/settings/config- Read/write configuration/api/settings/models- List available models (all providers)/api/settings/endpoints- List endpoints (all providers)/api/settings/endpoint- Add/edit endpoint (provider-aware)/api/settings/endpoint/<key>- Delete endpoint (checks all providers)
Version 2.0.0 - Deep Research Release
Release Date: Previous
Major Features:
- ✅ Deep research engine with 6-phase workflow (MVP)
- ✅ Modular tool registry (
tools/research/,tools/registry.py) - ✅ SQLite + JSON storage layer (
engine/storage.py) - ✅ Web UI with Flask (
ui/web/app.py) - ✅ Credibility scoring system
- ✅ Parallel source aggregation (academic + web + newsroom)
- ✅ Research synthesis with citations
Architecture Changes:
- Refactored tool registry into modular structure
- Created
engine/module for research engine - Created
workflows/deep_research/for workflow components - Added Flask-based Web UI
Breaking Changes:
tool_registry.pyis now a backward-compatibility shim- Use
from tools.registry import ...for new code - Web UI requires Flask (added to requirements)
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See Also
- Getting Started - Installation and setup
- Guides - Usage guides
- API Reference - API documentation