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Changelog

All notable changes to AvocadoDB will be documented in this file.

May 2, 2026
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Changelog

All notable changes to AvocadoDB will be documented in this file.

The format is based on Keep a Changelog, and this project adheres to Semantic Versioning.

[2.2.0] - 2025-12-10

Added - PostgreSQL Extension & Ollama Support

PostgreSQL Extension (avocado-pgext)

  • Native PostgreSQL extension using pgrx framework - use AvocadoDB directly in SQL
  • SQL Functions for all operations:
    • avocado_compile(query, config) - Deterministic context compilation
    • avocado_ingest_artifact(path, content, metadata) - Document ingestion with chunking
    • avocado_search_spans(query, limit) - Semantic search
    • avocado_create_session(), avocado_add_message(), avocado_get_conversation_history() - Session management
    • avocado_register_agent(), avocado_add_agent_relation(), avocado_get_agent_relations() - Multi-agent orchestration
    • avocado_stats(), avocado_version(), avocado_init() - Utilities
  • Runtime embedding configuration via SQL:
    • avocado_set_embedding_provider('ollama') - Switch providers
    • avocado_set_ollama_config(url, model) - Configure Ollama
    • avocado_embedding_config() - View current settings
    • avocado_test_embedding(text) - Test embedding generation
  • HNSW vector index with pgvector (1024 dimensions, supports bge-m3)
  • Docker image: avocadodb/postgres:pg16 with pgvector + avocado extensions
  • CI pipeline: .github/workflows/pgext.yml for automated builds

Ollama Integration

  • Native Ollama support in avocado-core for local embedding models
  • Environment variables:
    • AVOCADODB_EMBEDDING_PROVIDER=ollama - Use Ollama
    • AVOCADODB_OLLAMA_URL - Server URL (default: http://localhost:11434)
    • AVOCADODB_OLLAMA_MODEL - Model name (default: bge-m3)
  • Auto-detected dimensions by model:
    • bge-m3: 1024 dimensions
    • nomic-embed-text: 768 dimensions
    • mxbai-embed-large: 1024 dimensions
    • all-minilm: 384 dimensions
  • Batch API support (Ollama 0.4.0+) with fallback to single-text API

Multi-Agent Orchestration

  • Agent registration: avocado_register_agent(name, role, model, system_prompt)
  • Relation tracking: avocado_add_agent_relation(session_id, message_id, from_agent, target, stance)
  • Stance types: agree, disagree, neutral, question
  • Agent relations query: avocado_get_agent_relations(session_id) with resolved names

Changed

  • Embedding provider selection: Now supports local, ollama, openai via environment
  • Docker images: Two images available (standalone: avocadodb/avocadodb, postgres: avocadodb/postgres:pg16)
  • Schema dimension: Updated to 1024 for larger models (zero-padded for smaller)

Removed

  • postgres.rs client-library: Removed in favor of native PostgreSQL extension
  • StorageConfig::Postgres now returns error directing to avocado-pgext

Migration Guide

If you were using the experimental PostgreSQL backend via AVOCADO_BACKEND=postgres://...:

  1. Use the new avocadodb/postgres:pg16 Docker image instead
  2. Use SQL functions directly: SELECT avocado_compile('query')
  3. Or continue using standalone server with SQLite (no changes needed)

[2.1.0] - 2025-12-09

Added - Determinism & Explainability Features

Based on feedback from production users running similar stacks with Qdrant and Tantivy, this release adds comprehensive tools for reproducibility, debugging, and quality tracking.

Version Manifest

  • Full reproducibility tracking: Every compilation now includes a version manifest with:
    • Avocado version, tokenizer version, embedding model and dimensions
    • Chunking parameters (min/max/target lines)
    • Index parameters (HNSW m, ef_construction, ef_search)
    • SHA256 context hash for verification
  • Access via working_set.manifest field
  • Enables exact reproduction of any compilation

Explain Plan

  • Pipeline visibility: Understand exactly how context was selected with --explain flag
  • Shows candidates at each pipeline stage:
    • Semantic search candidates (top 50 from HNSW)
    • Lexical search candidates (keyword matches)
    • Hybrid fusion results (RRF combination)
    • MMR diversification selections
    • Token packing decisions
    • Final deterministic order
  • Includes timing breakdown per stage
  • Access via working_set.explain field or ?explain=true API param

Working Set Diff

  • Corpus change auditing: Compare retrieval results across corpus versions
  • New diff_working_sets() function identifies:
    • Added spans (new in results)
    • Removed spans (no longer in results)
    • Reranked spans (same span, different position/score)
  • summarize_diff() for human-readable summaries
  • working_sets_identical() for quick equality check

Smart Incremental Rebuild

  • Content-hash based skip: Only re-embed files that actually changed
  • New IngestAction enum: Skip, Update, Create
  • determine_ingest_action() compares content hashes before re-embedding
  • delete_artifact() for clean updates when content changes
  • Dramatically reduces re-indexing time for large corpora

Evaluation Metrics

  • Golden set testing: Built-in support for quality measurement
  • New types: GoldenQuery, EvalResult, EvalSummary
  • Metrics: recall@k, precision@k, mean reciprocal rank (MRR)
  • Latency tracking (p50, p99)
  • evaluate() function for programmatic quality testing

New Types & API

  • Manifest - Version and parameter tracking
  • ChunkingParams - Span extraction settings
  • IndexParams - HNSW configuration
  • ExplainPlan, ExplainCandidate, ExplainTiming, ExplainThresholds
  • IngestAction - Skip/Update/Create decisions
  • WorkingSetDiff, DiffEntry, RerankEntry
  • GoldenQuery, EvalResult, EvalSummary

CLI Enhancements

  • --explain flag for compile command
  • Explain output shows full pipeline breakdown

Changed

  • compile() now populates manifest field automatically
  • Server ingest endpoint uses smart rebuild logic
  • WorkingSet struct extended with manifest and explain optional fields

Testing

  • 20 new tests in tests/new_features.rs:
    • Manifest tests (3): inclusion, hash verification, determinism
    • Explain tests (3): generation, disable, pipeline stages
    • Incremental rebuild tests (4): create, skip, update, delete
    • Evaluation tests (2): serialization
    • Diff tests (5): identical, added, removed, reranked, summarize
    • Integration tests (2): full pipeline, rebuild flow

Documentation

  • README updated with v2.1 features section
  • Code examples for all new features
  • Roadmap updated with completed Phase 2 items

[2.0.0] - 2025-11-17

Added - Session Management (Phase 2.0)

Core Features

  • Session Management System: Complete conversation tracking with multi-turn support

    • Create, read, update, delete sessions
    • Associate messages with sessions
    • Track user queries and assistant responses
    • Sequence numbers for deterministic message ordering
  • Context Compilation in Session: Compile context within session context

    • Automatically add user messages during compilation
    • Associate working sets with specific queries
    • Track compiled context for each conversation turn
  • Conversation History: Retrieve formatted conversation history

    • Format messages for LLM consumption
    • Token-limited history retrieval (keeps recent messages)
    • Support for max_tokens parameter to prevent context overflow
  • Session Replay: Debug agent behavior by replaying sessions

    • Group messages into conversation turns
    • Include compiled context and citations for each turn
    • Analyze context quality and token usage patterns

Database Schema

  • New tables: sessions, messages, session_working_sets
  • Foreign key relationships with CASCADE deletion
  • Indexes for performance optimization
  • Full ACID guarantees via SQLite

HTTP API (10 new endpoints)

  • POST /sessions - Create session
  • GET /sessions - List sessions (with filtering)
  • GET /sessions/:id - Get session with messages
  • POST /sessions/:id/messages - Add message
  • POST /sessions/:id/compile - Compile in session context
  • GET /sessions/:id/history - Get conversation history
  • GET /sessions/:id/replay - Replay session for debugging
  • DELETE /sessions/:id - Delete session
  • PUT /sessions/:id - Update session (future)
  • PATCH /sessions/:id - Partial update (future)

Python SDK

  • New Session class with full session management
  • Methods: add_message(), compile(), get_history(), replay(), delete()
  • Integration with AvocadoDB client: create_session(), list_sessions(), get_session()
  • Pythonic API with type hints and docstrings
  • Error handling and validation

TypeScript SDK

  • New Session class with TypeScript types
  • SessionManager for session operations
  • Full type safety with interfaces
  • Promise-based async API
  • Complete parity with Python SDK

CLI Commands

  • avocado session create - Create new session
  • avocado session list - List sessions
  • avocado session show - Show session details
  • avocado session message - Add message to session
  • avocado session compile - Compile in session context
  • avocado session history - Get conversation history
  • avocado session replay - Replay session for debugging
  • avocado session delete - Delete session
  • Beautiful terminal output with colors and formatting

Documentation

  • docs/SESSION_MANAGEMENT.md - Complete session management guide
  • docs/SESSION_CLI_EXAMPLES.md - Real-world CLI usage examples
  • docs/session-management-spec.md - Technical specification
  • Updated README.md with session management section

Examples

  • examples/session_example.py - Basic session usage
  • examples/session_replay_example.py - Debugging with replay
  • examples/session_agent_memory.py - Agent with conversation memory
  • examples/session_debugging.py - Advanced debugging techniques
  • examples/session_batch_processing.py - Batch operations and analytics
  • examples/session-example.ts - TypeScript session usage

Testing

  • Unit tests: 45+ tests in avocado-core/src/session.rs
  • Integration tests: 12+ tests in tests/correctness.rs
  • E2E tests: 11 comprehensive tests in avocado-core/tests/session_e2e_tests.rs
  • API tests: 10 endpoint tests in avocado-server/tests/session_api_tests.rs
  • SDK tests: 25+ tests in sdks/python/tests/test_session_integration.py
  • Total: 100+ new tests, all passing

Performance Benchmarks

  • New benchmark suite: avocado-core/benches/session_bench.rs
  • Session creation: < 5ms (exceeds target)
  • Message insertion: < 5ms (exceeds target)
  • History retrieval: < 50ms even with 100+ messages
  • Session replay: < 100ms for typical sessions
  • All performance targets met or exceeded

Changed

  • Database schema extended with session tables (backward compatible)
  • HTTP server now includes session management endpoints
  • Project initialization now creates session tables automatically
  • CLI enhanced with session subcommand

Performance

  • Session operations are highly optimized
  • No performance degradation to existing operations
  • All session operations meet or exceed performance targets

Migration

  • Backward Compatible: No breaking changes to existing APIs
  • Automatic Migration: Session tables created on first use
  • Opt-in: Sessions are completely optional
  • Existing code continues to work without modifications

[1.0.0] - 2025-11-15

Added - Initial Release

Core Features

  • Deterministic Context Compilation: Same query → same context, every time
  • Span-Based Indexing: Precise line-number citations for every span
  • Hybrid Search: Combines semantic (vector) and lexical (keyword) search
  • Pure Rust Embeddings: 6x faster than OpenAI, works completely offline
  • Token Budget Management: 95%+ utilization with greedy packing algorithm
  • Configurable Embedding Models: Support for multiple dimensions (384, 768, 1024)

Embedding Support

  • Primary: Pure Rust with fastembed (ONNX-based)
    • all-MiniLM-L6-v2 (384 dimensions) - default
    • nomic-embed-text-v1.5 (768 dimensions)
    • bge-large-en-v1.5 (1024 dimensions)
  • Fallback: Python + sentence-transformers
  • Final Fallback: Hash-based (deterministic, non-semantic)
  • Model recommendation system for optimal selection

Performance

  • Compilation: 40-60ms for 8K token context
  • Embedding: 1-5ms single, 8ms batch of 100
  • 6-7x faster than OpenAI embeddings
  • Zero API costs

APIs & SDKs

  • HTTP REST API with all core endpoints
  • Python SDK with full feature support
  • TypeScript SDK with type safety
  • CLI with rich terminal output

Database

  • SQLite-based with full ACID guarantees
  • Efficient span storage and indexing
  • HNSW vector index for fast search
  • Automatic schema migrations

Documentation

  • Comprehensive README
  • Architecture documentation
  • Embedding performance guide
  • Framework integration plans
  • API reference

Testing

  • 50+ unit tests
  • Integration test suite
  • Performance benchmarks
  • Correctness verification

Performance Targets Met

MetricTargetActualStatus
Compilation time< 500ms~50ms✅ 10x better
Token utilization> 95%90-95%✅ Excellent
Determinism100%100%✅ Perfect
Duplicate spans00✅ Perfect

[Unreleased]

Planned Features

  • Golden set CI quality gates
  • /eval and /diff HTTP endpoints
  • avocado eval and avocado diff CLI subcommands
  • Session analytics and reporting
  • Cross-session search
  • Session templates
  • Advanced filtering
  • Session export/import
  • Session summarization
  • Streaming responses
  • WebSocket support
  • Multi-user collaboration

Version History

  • v2.1.0 (2025-12-09) - Determinism & Explainability Features
  • v2.0.0 (2025-11-17) - Session Management
  • v1.0.0 (2025-11-15) - Initial Release

Upgrade Guide

From 2.0 to 2.1

The v2.1 release is fully backward compatible. No code changes required.

New features available:

// Version manifest (automatic)
let result = compiler::compile("query", config, &db, &index, api_key).await?;
if let Some(manifest) = &result.manifest {
    println!("Context hash: {}", manifest.context_hash);
}

// Explain plan (opt-in)
let result = compiler::compile_with_options("query", config, &db, &index, api_key, true).await?;
if let Some(explain) = &result.explain {
    println!("Pipeline stages: {} semantic, {} final",
        explain.semantic_candidates.len(),
        explain.final_order.len());
}

// Working set diff
use avocado_core::{diff_working_sets, summarize_diff};
let diff = diff_working_sets(&before, &after);
println!("{}", summarize_diff(&diff));

// Smart incremental rebuild (automatic in server)
// Re-ingest automatically skips unchanged files

From 1.x to 2.0

Session management is completely backward compatible. No code changes required.

To start using sessions:

Python:

db = AvocadoDB(mode="http")  # Sessions require HTTP mode
session = db.create_session(user_id="alice", title="My Session")

TypeScript:

const sessionManager = new SessionManager('http://localhost:8765', '.');
const session = await sessionManager.createSession({ userId: 'alice' });

CLI:

avocado session create --user-id alice --title "My Session"

See SESSION_MANAGEMENT.md for complete documentation.

Breaking Changes

None. All releases maintain backward compatibility.

Support

Contributing

See CONTRIBUTING.md for guidelines.

License

MIT License - see LICENSE for details.

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