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| # Changelog | |
| All notable changes to ACE Framework will be documented in this file. | |
| The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/), | |
| and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html). | |
| ## [Unreleased] | |
| ## [0.12.0] - 2026-05-06 | |
| ### Added | |
| - **Cross-trace generalization gate** for the SkillManager — four-criterion check | |
| (≥3 instances across ≥2 domains, named slot, no API-specific params in the | |
| action, verifiable runtime trigger) that constrains when SM may write a broad | |
| skill subsuming existing narrow ones. Backed by [skill_generalization.md](ace-eval/research/skill_generalization.md) | |
| (14 cited sources). | |
| - **Action-equivalence rule** for within-run skill writing — splits on action, | |
| not on trigger surface. Prevents over-decomposition of structurally identical | |
| rules. | |
| - **Atomicity rule** in `insight` formatting — one trigger + one action per | |
| skill, with explicit good/bad shape examples in the prompt. | |
| - **Insight format guidance** in the SM prompt sourced from the in-context- | |
| learning research doc ([icl_skill_formatting.md](ace-eval/research/icl_skill_formatting.md)) — 15-50 word cap, imperative | |
| voice, positive framing default, examples only for format/shape rules. | |
| - **Evidence-only tagging** — SM tags only skills the reflection actually | |
| implicates, instead of iterating over every injected_skill_id. | |
| - **Broaden-via-comparison rule** for UPDATE — when two skills target the same | |
| root cause in different niches, broaden `issue` rather than adding a duplicate. | |
| - **Prompt caching for SM** via `CachePoint(ttl="5m")` mirroring RR's caching; | |
| cache_read/write tokens forwarded in run metadata. | |
| - **SM behavior spec + harness** — `ace-eval/scripts/sm_behavior_check.py`, | |
| `sm_iterative_check.py`, `sm_stability_check.py` and matching scenario | |
| fixtures cover replay stability, convergence, scope expansion, and the | |
| below-threshold gate boundary. | |
| ### Changed | |
| - **`update_skills` signature** — `source` is now optional; `SkillbookView` | |
| was dropped from the parameter list (callers pass the real `Skillbook` | |
| directly). | |
| - **Hard removal cap removed** — SM no longer auto-removes skills whose | |
| `harmful_count >= 3`. Heavily-used skills can legitimately accumulate | |
| harmful tags without being net-negative; REMOVE now requires explicit | |
| reflection evidence. | |
| - **TauBench evaluator** — `evaluation_type=ALL_WITH_NL_ASSERTIONS` on both | |
| `run_task` and `run_tasks` call sites in | |
| `ace-eval/src/ace_eval/e2e/benchmarks/tau_bench.py`. Retail (and any future | |
| benchmark with `NL_ASSERTION` in `reward_basis`) now produces real reward | |
| numbers instead of crashing on every task during reward computation. | |
| ### Removed | |
| - **Skillbook v1 legacy aliases** on `Skill` and `UpdateOperation` — v2 schema | |
| is now the only schema. | |
| ## [0.11.0] - 2026-04-29 | |
| ### Added | |
| - **`RecursiveAgent` core abstraction** — extracted from RR into `ace/core/recursive_agent.py`; provides a generic recursive PydanticAI agent with sandbox, microcompaction, default tool set, and depth-aware sub-agent registration. Reusable across roles beyond the Reflector. | |
| - **Skillbook v2 schema** — full rewrite of `ace/core/skillbook.py` with section-grouped storage, richer `InsightSource` provenance, and BM25-backed retrieval (`rank-bm25` runtime dependency). | |
| - **Agentic SkillManager** — `SkillManager` rewritten as a tool-calling loop (`ace/implementations/sm_tools.py`). Provenance is now populated by the SkillManager agent directly rather than a dedicated step. | |
| - **RR skillbook tools for the Reflector** — Reflector can introspect and propose updates to the skillbook from inside the recursive loop. | |
| - **Anthropic prompt caching enabled by default** for RR agents; `cache_read_tokens` and `cache_write_tokens` are forwarded in run metadata for cost accounting. | |
| - **Logfire spans around recursive agent sessions** for end-to-end observability of nested RR runs. | |
| - **Online / offline mode** in the ACE runner. | |
| - **`nest-asyncio`** added to the dev extra to support nested loops in notebooks and live test scripts. | |
| ### Changed | |
| - **RR collapsed into a single `RRStep`** — the orchestrator/worker split, batch machinery, and `AttachInsightSourcesStep` have been removed. RR now runs as a true recursive loop with depth-bounded sub-agent delegation and microcompaction of stale tool results. | |
| - **Reflector prompts** simplified, deduplicated, and made input-agnostic; added early-skillbook-skim and parallel-tool guidance. | |
| - **`record_observation` tool renamed to `think`** to clarify it is a scratch reasoning channel, not persistent storage. | |
| - **Native evidence summaries** are produced inside RR before final synthesis. | |
| - **Skillbook prompt format is now markdown** — `Skillbook.as_prompt()` returns a section-grouped markdown list instead of TOON. The `python-toon` dependency has been dropped. | |
| - **`metered_model` and `sandbox`** moved from `ace/rr/` into `ace/core/` to reflect their cross-role use. | |
| - **Pytest defaults** — `uv run pytest` now excludes `integration` and `requires_api` markers by default; coverage flags removed from `addopts` (run with `--cov` explicitly when needed). | |
| - **Observability** — `tool_arguments` and `tool_response` are no longer scrubbed by the Logfire callback so tool I/O remains inspectable. | |
| ### Removed | |
| - `ace/rr/` legacy package layout (`agent.py`, `runner.py`, `trace_context.py`, `message_trimming.py`, batch helpers). Functionality is now in `ace/core/recursive_agent.py` and `ace/implementations/rr/`. | |
| - `AttachInsightSourcesStep` and its pipeline wiring — provenance is attached by the SkillManager agent. | |
| - `python-toon` runtime dependency. | |
| - TAG handling from the SkillManager. | |
| - Citation scanning from the Reflector. | |
| ## [0.10.0] - 2026-04-13 | |
| ### Added | |
| - **Usage metering hook** — `RecursiveConfig.usage_callback: (RequestUsage, model_id) -> None` fires once per pydantic-ai model request (orchestrator turns, sub-agent runs, tool-call follow-ups). Implemented via `ace.rr.MeteredModel`, a `pydantic_ai.models.wrapper.WrapperModel` subclass, so metering lives at the framework's own model boundary — no per-call-site plumbing. Callback exceptions are caught and logged so metering never crashes the pipeline. | |
| - **Pre-built model instance support** — `RRStep`, `create_rr_agent`, `create_sub_agent`, and `RecursiveConfig.subagent_model` now accept either a model-id string or a pre-built `pydantic_ai.models.Model` instance. Enables callers that need a custom provider (e.g. cross-account Bedrock with STS-assumed credentials) to inject a fully-configured model rather than resolving from a string. | |
| - **Sub-agent `model_settings`** — `create_sub_agent` now threads an explicit `ModelSettings` parameter into its `PydanticAgent` constructor. | |
| ### Notes | |
| - Back-compat: existing `RRStep(model="...")` callers continue to work unchanged. The widened type signature is additive. | |
| ## [0.9.4] - 2026-04-11 | |
| ### Added | |
| - **Kayba tracing SDK** — `ace.tracing` module wraps MLflow tracing with Kayba-native configuration, folder organization, and input sanitization (`pip install ace-framework[tracing]`) | |
| ## [0.9.3] - 2026-04-01 | |
| ### Added | |
| - **Structured design docs** — split ACE_DESIGN.md into architecture, reference, and decisions docs under docs/design/ | |
| - **Simplified Skill model** — removed unused tag counters (helpful/harmful/neutral) and TagStep from the pipeline | |
| - **Cleaner InsightSource provenance** — restored error_identification and learning_text fields | |
| ## [0.9.2] - 2026-03-31 | |
| ### Added | |
| - **Insight source provenance** — `InsightSource` typed model captures the origin of each skillbook update (trace ID, sample question, epoch/step, reflection summary, integration metadata); provenance is now populated by the SkillManager agent directly | |
| - **Claude SDK step** — `ClaudeSDKStep` integration for running Claude Code sub-agents from within ACE pipelines | |
| - **RR sub-agent code execution** — Recursive Reflector can now delegate to code-execution sub-agents at runtime | |
| - **RR raw trace batch helpers** — `build_raw_trace_batches` and related runtime utilities for feeding raw traces directly into the RR pipeline | |
| ### Fixed | |
| - **Logfire scrubbing** — added scrubbing callback to stop Logfire over-redacting trace content (reasoning, answers, messages now visible in Logfire UI) | |
| - **RR combined-batch normalization** — fixed ordering/deduplication of combined task batches in multi-sample runs | |
| ### Docs | |
| - Logfire query API guide clarifications | |
| - MCP client setup guide and compatibility tests | |
| - Design docs updated to reflect insight source provenance model | |
| ## [0.9.1] - 2026-03-26 | |
| ### Fixed | |
| - **CLI packaging** — include .md data files in wheel so `kayba setup` and skill install work on pip/uv-installed packages | |
| ## [0.9.0] - 2026-03-26 | |
| ### Added | |
| - **PydanticAI migration** — ACE roles (Agent, Reflector, SkillManager) rebuilt on PydanticAI agents with structured output, replacing the legacy role system | |
| - **Recursive Reflector** — PydanticAI-powered trace analysis agent with sandboxed code execution, sub-agent delegation, and working memory (`save_notes` tool) | |
| - **Kayba CLI** — full hosted API client with trace upload/management, interactive run, insights, prompts, batch processing, materialization, and integration commands (`kayba` entry point) | |
| ## [0.8.8] - 2026-03-17 | |
| ### Added | |
| - **Pipeline hooks & cancellation** — `PipelineHook` protocol and `CancellationToken` for observing and controlling pipeline execution | |
| - **Kayba pipeline skills for Claude Code** — 7-stage dynamic evaluation pipeline that generates custom benchmarks tailored to your agent's domain. Instead of static test suites, the skills analyze your API, build domain-aware metrics and rubrics, create action plans, and run human-in-the-loop validation — all as composable Claude Code skills | |
| - **`kayba setup` command** — one command to install the full evaluation skill pipeline into your `.claude/skills/` directory, ready to use inside Claude Code out of the box | |
| ### Docs | |
| - Documented `kayba setup` skills installation | |
| ### Try it free | |
| **7-day free trial** — Try the full Kayba evaluation pipeline on our hosted solution with zero setup. Sign up at [kayba.ai](https://kayba.ai) and run `kayba setup` to start building dynamic evals for your agents today. | |
| ## [0.8.7] - 2026-03-17 | |
| ### Added | |
| - **Improved Opik trace naming** — traces now display the question text (first 80 chars) instead of generic names like "ace_pipeline" or "rr_reflect" | |
| - **Thread ID support for Opik** — `OpikStep` and `RROpikStep` accept an optional `thread_id` parameter for grouping related traces | |
| ## [0.8.5] - 2026-03-04 | |
| ### Added | |
| - **Self-contained RR module** (`ace/rr/`) — sandbox, subagent, trace_context, config, code_extraction, message_trimming extracted from `ace/reflector/` into a standalone package | |
| - **v5.6 prompt promoted as default** — new prompt evolution (v4 → v5.1–v5.6) for the `ace` RR pipeline | |
| - **`build_steps()` API** — all runners gain a `build_steps()` classmethod for pipeline customization | |
| - **Shared `CallBudget`** — single budget instance shared across RR pipeline steps | |
| - **ACE MCP server (optional)** — stdio MCP server in `ace.integrations.mcp` with tools: `ace.ask`, `ace.learn.sample`, `ace.learn.feedback`, `ace.skillbook.get`, `ace.skillbook.save`, `ace.skillbook.load` | |
| - **Session-scoped state management** — in-memory `session_id` registry with TTL cleanup and per-session async locking | |
| - **MCP packaging + CLI** — optional `mcp` extra and `ace-mcp` entrypoint | |
| - **MCP docs and demo client** — integration guide and stdio client example | |
| - **Composing pipelines guide** — new `docs/guides/composing-pipelines.md` | |
| - **RR examples** — `rr_demo.py`, `rr_opik_demo.py`, `compose_custom_pipeline.py` | |
| ### Changed | |
| - **RR backward-compat shims** — original `ace/reflector/` files now re-export from `ace.rr` (no duplication) | |
| - **`RRStep` dual protocol** — implements both `StepProtocol` and `ReflectorLike` | |
| - **Sandbox hardening** — hardened `getattr` in sandbox execution environment | |
| - **Opik made opt-in** — moved `opik` from hard dependency to `observability` extra | |
| - **Safety controls** — runtime request limits (`max_prompt_chars`, `max_samples_per_call`) and optional root-bound path enforcement for save/load via `ACE_MCP_SKILLBOOK_ROOT` | |
| - **Schema-driven validation** — MCP request/response models aligned to `specs/002-ace-mcp-server/contracts/tool-schemas.md` | |
| - **`learn_from_feedback` routed through pipeline** — feedback learning now uses the pipeline engine | |
| ### Testing | |
| - Added MCP test suite: models, registry, handlers, and server registration/startup smoke tests | |
| - Added optional-dependency boundary checks for the MCP integration | |
| - RR steps at 94%, sandbox at 92%, runner at 74%, MCP models at 100% | |
| ## [0.8.4] - 2026-02-27 | |
| ### Added | |
| - **OpenClaw integration** — learn from OpenClaw session transcripts (JSONL) via new `OpenClawToTraceStep` and `LoadTracesStep` pipeline steps (#86) | |
| - **ExportSkillbookMarkdownStep** — export skillbook to markdown file | |
| - OpenClaw example script and integration docs | |
| ## [0.8.3] - 2026-02-21 | |
| ### Added | |
| - **Pipeline engine** — generic pipeline framework with branching, async boundaries, and parallel execution (#78) | |
| - **Trace passthrough** — `_build_traces()` helper and raw trace data passed to RecursiveReflector sandbox | |
| ## [0.8.2] - 2026-02-18 | |
| ### Added | |
| - **RecursiveReflector None-response guard** — gracefully handles empty/None LLM responses (e.g. from Gemini) with retry prompt instead of crashing | |
| - **`LiteLLMClient.complete_messages()`** — native multi-turn completion that preserves structured message lists | |
| ## [0.8.1] - 2026-02-18 | |
| ### Added | |
| - **Insight source tracing** — `InsightSource` dataclass tracks skill provenance (epoch, sample, trace refs, error identification, learning text) | |
| - **Sample.id** promoted to first-class field with UUID auto-generation | |
| - **Skillbook query API** — `source_map()`, `source_summary()`, `source_filter()` for skill lineage | |
| - Insight sources wired through `OfflineACE`, `OnlineACE`, and async learning pipelines | |
| - `UpdateOperation.learning_index` for linking operations to reflector learnings | |
| - Bedrock e2e example (`examples/litellm/bedrock_insight_source_test.py`) | |
| - `docs/INSIGHT_SOURCES.md` guide | |
| ## [0.8.0] - 2026-02-17 | |
| ### Added | |
| - **Recursive reflector** with sandboxed code execution for validation | |
| - **TAU-bench integration** with config-driven YAML profiles, prompt sweep, capture/replay, and label support | |
| - **v3 prompt templates** for agent, reflector, and skill manager roles | |
| - **Trace context module** exposing agent system prompt and execution context to reflector | |
| ### Fixed | |
| - Opik cloud mode support when `OPIK_API_KEY` is set | |
| - Bedrock/SageMaker API key lookup skipped for managed providers | |
| - Reflector trace quality improvements (user messages, turn separators) | |
| ### Changed | |
| - v3 prompts set as default prompt version | |
| - Reflector now includes agent system prompt in trace context | |
| ## [0.7.3] - 2026-02-04 | |
| ### Added | |
| - ACE learning for Claude Code via `/ace-learn` (transcript-based learning and skillbook updates). | |
| - CLI patching to minimize Claude Code system prompt overhead for learning runs. | |
| ### Fixed | |
| - Claude Code transcript parsing for feedback and last-prompt extraction edge cases. | |
| ### Changed | |
| - Unified agent guidance into `AGENTS.md` with `CLAUDE.md` symlink. | |
| ## [0.7.0] - 2025-12-04 | |
| ### ⚠️ Breaking Changes | |
| - **Complete terminology rename** - Playbook → Skillbook, Bullet → Skill | |
| - `Playbook` → `Skillbook` | |
| - `Bullet` → `Skill` | |
| - `Generator` → `Agent` | |
| - `Curator` → `SkillManager` | |
| - `OfflineAdapter` → `OfflineACE` | |
| - `OnlineAdapter` → `OnlineACE` | |
| - `DeltaOperation` → `UpdateOperation` | |
| - `DeltaBatch` → `UpdateBatch` | |
| - **Migration**: Update imports and method calls to use new names | |
| - **JSON files**: Change `"bullets"` key to `"skills"` in saved skillbooks | |
| ### Added | |
| - **Deduplication consolidation_operations field** - SkillManagerOutput now properly captures consolidation operations from LLM responses | |
| ### Fixed | |
| - **Deduplication not working** - Added `consolidation_operations` field to SkillManagerOutput Pydantic model. Previously, Instructor was silently dropping these operations. | |
| ## [0.5.0] - 2025-11-20 | |
| ### ⚠️ Breaking Changes | |
| - **Playbook format changed to TOON (Token-Oriented Object Notation)** | |
| - `Playbook.as_prompt()` now returns TOON format instead of markdown | |
| - **Reason**: 16-62% token savings for improved scalability and reduced inference costs | |
| - **Migration**: No action needed if using playbook with Generator/Curator/Reflector | |
| - **Debugging**: Use `playbook._as_markdown_debug()` or `str(playbook)` for human-readable output | |
| - **Details**: Uses tab delimiters and excludes internal metadata (created_at, updated_at) | |
| ### Added | |
| - **ACELiteLLM integration** - Simple conversational agent with automatic learning | |
| - **ACELangChain integration** - Wrap LangChain Runnables with ACE learning | |
| - **Custom integration pattern** - Wrap ANY agentic system with ACE learning | |
| - Base utilities in `ace/integrations/base.py` with `wrap_playbook_context()` helper | |
| - Complete working example in `examples/custom_integration_example.py` | |
| - Integration Pattern: Inject playbook → Execute agent → Learn from results | |
| - **Integration exports** - Import ACEAgent, ACELiteLLM, ACELangChain from `ace` package root | |
| - **TOON compression for playbooks** - 16-62% token reduction vs markdown | |
| - **Citation-based tracking** - Strategies cited inline as `[section-00001]`, auto-extracted from reasoning | |
| - **Enhanced browser traces** - Full execution logs (2200+ chars) passed to Reflector | |
| - **Test coverage** - Improved from 28% to 70% (241 tests total) | |
| ### Changed | |
| - **Renamed SimpleAgent → ACELiteLLM** - Clearer naming for conversational agent integration | |
| - `Playbook.__str__()` returns markdown (TOON reserved for LLM consumption via `as_prompt()`) | |
| ### Fixed | |
| - **Browser-use trace integration** - Reflector now receives complete execution traces | |
| - Fixed initial query duplication (task appeared in both question and reasoning) | |
| - Fixed missing trace data (reasoning field now contains 2200+ chars vs 154 chars) | |
| - Fixed screenshot attribute bug causing AttributeError on step.state.screenshot | |
| - Fixed invalid bullet ID filtering - hallucinated/malformed citations now filtered out | |
| - Added comprehensive regression tests to catch these issues | |
| - Impact: Reflector can now properly analyze browser agent's thought process | |
| - Test coverage improved: 69% → 79% for browser_use.py | |
| - Prompt v2.1 test assertions updated to match current format | |
| - All 206 tests now pass (was 189) | |
| ## [0.4.0] - 2025-10-26 | |
| ### Added | |
| - **Production Observability** with Opik integration | |
| - Enterprise-grade monitoring and tracing | |
| - Automatic token usage and cost tracking for all LLM calls | |
| - Real-time cost monitoring via Opik dashboard | |
| - Graceful degradation when Opik is not installed | |
| - **Browser Automation Demos** showing ACE vs baseline performance | |
| - Domain checker demo with learning capabilities | |
| - Form filler demo with adaptive strategies | |
| - Side-by-side comparison of baseline vs ACE-enhanced automation | |
| - Support for UV package manager (10-100x faster than pip) | |
| - Added uv.lock for reproducible builds | |
| - UV-specific installation and development instructions | |
| - Improved documentation structure with multiple guides | |
| - QUICK_START.md for 5-minute quickstart | |
| - API_REFERENCE.md for complete API documentation | |
| - PROMPT_ENGINEERING.md for advanced techniques | |
| - SETUP_GUIDE.md for development setup | |
| - TESTING_GUIDE.md for testing procedures | |
| - Optional dependency groups for modular installation | |
| - `observability` for Opik integration | |
| - `demos` for browser automation examples | |
| - `langchain` for LangChain support | |
| - `transformers` for local model support | |
| - `dev` for development tools | |
| - `all` for all features combined | |
| ### Changed | |
| - **Replaced explainability module with observability** | |
| - Removed empty ace/explainability directory | |
| - Migrated to production-grade Opik monitoring | |
| - Updated all documentation to reflect this change | |
| - Improved Python version requirements consistency (3.12 everywhere) | |
| - Enhanced README with clearer examples and installation options | |
| - Reorganized examples directory for better discoverability | |
| - Updated CLAUDE.md with comprehensive codebase guidance | |
| ### Fixed | |
| - Package configuration in pyproject.toml | |
| - Documentation references to non-existent explainability module | |
| - Python version inconsistencies across documentation files | |
| ### Removed | |
| - Empty ace/explainability module (replaced by observability) | |
| - Outdated references to explainability features in documentation | |
| ## [0.3.0] - 2025-10-16 | |
| ### Added | |
| - **Experimental v2 Prompts** with state-of-the-art prompt engineering | |
| - Confidence scoring at bullet and answer levels | |
| - Domain-specific variants for math and code generation | |
| - Hierarchical structure with identity headers and metadata | |
| - Concrete examples and anti-patterns for better guidance | |
| - PromptManager for version control and A/B testing | |
| - Comprehensive prompt engineering documentation (`docs/PROMPT_ENGINEERING.md`) | |
| - Advanced examples demonstrating v2 prompts (`examples/advanced_prompts_v2.py`) | |
| - Comparison script for v1 vs v2 prompts (`examples/compare_v1_v2_prompts.py`) | |
| - Playbook persistence with `save_to_file()` and `load_from_file()` methods | |
| - Example demonstrating playbook save/load functionality (`examples/playbook_persistence.py`) | |
| - py.typed file for PEP 561 type hint support | |
| - Mermaid flowchart visualization in README showing ACE learning loop | |
| ### Changed | |
| - Enhanced docstrings with comprehensive examples throughout codebase | |
| - Improved README with v2 prompts section and visual diagrams | |
| - Updated formatting to comply with Black code style | |
| ### Fixed | |
| - README incorrectly referenced non-existent docs/ directory | |
| - Test badge URL in README (test.yml → tests.yml) | |
| - Code formatting issues detected by GitHub Actions | |
| ## [0.2.0] - 2025-10-15 | |
| ### Added | |
| - LangChain integration via `LangChainLiteLLMClient` for advanced workflows | |
| - Router support for load balancing across multiple model deployments | |
| - Comprehensive example for LangChain usage (`examples/langchain_example.py`) | |
| - Optional installation group: `pip install ace-framework[langchain]` | |
| - PyPI badges and Quick Links section in README | |
| - CHANGELOG.md for version tracking | |
| ### Fixed | |
| - Parameter filtering in LiteLLM and LangChain clients (refinement_round, max_refinement_rounds) | |
| - GitHub Actions workflow using deprecated artifact actions v3 → v4 | |
| ### Changed | |
| - Improved README with better structure and badges | |
| - Updated .gitignore to exclude build artifacts and development files | |
| ### Removed | |
| - Unnecessary development files from repository | |
| ## [0.1.1] - 2025-10-15 | |
| ### Fixed | |
| - GitHub Actions workflow for PyPI publishing | |
| - Updated artifact upload/download actions from v3 to v4 | |
| ## [0.1.0] - 2025-10-15 | |
| ### Added | |
| - Initial release of ACE Framework | |
| - Core ACE implementation based on paper (arXiv:2510.04618) | |
| - Three-role architecture: Generator, Reflector, and Curator | |
| - Playbook system for storing and evolving strategies | |
| - LiteLLM integration supporting 100+ LLM providers | |
| - Offline and Online adaptation modes | |
| - Async and streaming support | |
| - Example scripts for quick start | |
| - Comprehensive test suite | |
| - PyPI packaging and GitHub Actions CI/CD | |
| ### Features | |
| - Self-improving agents that learn from experience | |
| - Delta operations for incremental playbook updates | |
| - Support for OpenAI, Anthropic, Google, and more via LiteLLM | |
| - Type hints and modern Python practices | |
| - MIT licensed for open source use | |
| [0.9.4]: https://github.com/Kayba-ai/agentic-context-engine/compare/v0.9.3...v0.9.4 | |
| [0.9.3]: https://github.com/Kayba-ai/agentic-context-engine/compare/v0.9.2...v0.9.3 | |
| [0.9.2]: https://github.com/Kayba-ai/agentic-context-engine/compare/v0.9.1...v0.9.2 | |
| [0.9.1]: https://github.com/Kayba-ai/agentic-context-engine/compare/v0.9.0...v0.9.1 | |
| [0.9.0]: https://github.com/Kayba-ai/agentic-context-engine/compare/v0.8.9...v0.9.0 | |
| [0.8.8]: https://github.com/Kayba-ai/agentic-context-engine/compare/v0.8.7...v0.8.8 | |
| [0.8.7]: https://github.com/Kayba-ai/agentic-context-engine/compare/v0.8.6...v0.8.7 | |
| [0.8.5]: https://github.com/Kayba-ai/agentic-context-engine/compare/v0.8.4...v0.8.5 | |
| [0.8.4]: https://github.com/Kayba-ai/agentic-context-engine/compare/v0.8.3...v0.8.4 | |
| [0.8.3]: https://github.com/Kayba-ai/agentic-context-engine/compare/v0.8.2...v0.8.3 | |
| [0.8.2]: https://github.com/Kayba-ai/agentic-context-engine/compare/v0.8.1...v0.8.2 | |
| [0.8.1]: https://github.com/Kayba-ai/agentic-context-engine/compare/v0.8.0...v0.8.1 | |
| [0.8.0]: https://github.com/Kayba-ai/agentic-context-engine/compare/v0.7.3...v0.8.0 | |
| [0.7.3]: https://github.com/Kayba-ai/agentic-context-engine/compare/v0.7.0...v0.7.3 | |
| [0.7.0]: https://github.com/Kayba-ai/agentic-context-engine/compare/v0.6.0...v0.7.0 | |
| [0.6.0]: https://github.com/Kayba-ai/agentic-context-engine/compare/v0.5.0...v0.6.0 | |
| [0.5.0]: https://github.com/Kayba-ai/agentic-context-engine/compare/v0.4.0...v0.5.0 | |
| [0.4.0]: https://github.com/Kayba-ai/agentic-context-engine/compare/v0.3.0...v0.4.0 | |
| [0.3.0]: https://github.com/Kayba-ai/agentic-context-engine/compare/v0.2.0...v0.3.0 | |
| [0.2.0]: https://github.com/Kayba-ai/agentic-context-engine/compare/v0.1.1...v0.2.0 | |
| [0.1.1]: https://github.com/Kayba-ai/agentic-context-engine/compare/v0.1.0...v0.1.1 | |
| [0.1.0]: https://github.com/Kayba-ai/agentic-context-engine/releases/tag/v0.1.0 | |