tony/WHOOSH
1
0
Fork 0
Code Issues 6 Pull Requests Actions Packages Projects Releases Wiki Activity

Add WHOOSH search service with BACKBEAT integration

Browse Source 
Complete implementation:
- Go-based search service with PostgreSQL and Redis backend
- BACKBEAT SDK integration for beat-aware search operations
- Docker containerization with multi-stage builds
- Comprehensive API endpoints for project analysis and search
- Database migrations and schema management
- GITEA integration for repository management
- Team composition analysis and recommendations

Key features:
- Beat-synchronized search operations with timing coordination
- Phase-based operation tracking (started → querying → ranking → completed)
- Docker Swarm deployment configuration
- Health checks and monitoring
- Secure configuration with environment variables

Architecture:
- Microservice design with clean API boundaries
- Background processing for long-running analysis
- Modular internal structure with proper separation of concerns
- Integration with CHORUS ecosystem via BACKBEAT timing

🤖 Generated with [Claude Code](https://claude.ai/code)

Co-Authored-By: Claude <noreply@anthropic.com>
This commit is contained in:
Claude Code
2025-09-06 11:16:39 +10:00
parent 595b05335d
commit 33676bae6d
29 changed files with 4262 additions and 185 deletions
Download Patch File Download Diff File Expand all files Collapse all files

9
docs/DEVELOPMENT_PLAN.md
View File

@@ -1,6 +1,13 @@
# WHOOSH Transformation Development Plan
## Autonomous AI Development Teams Architecture
Sanity Addendum (Go + MVP-first)
- Backend in Go for consistency with CHORUS; HTTP/WS with chi/echo, JSON Schema validation, structured logs. Optional Team Composer as a separate Go service calling local Ollama endpoints (cloud models opt-in only).
- Orchestration: Docker Swarm with nginx ingress; secrets via Swarm; SHHH scrubbing at API/WS ingress and before logging.
- MVP-first scope: single-agent path acting on `bzzz-task` issues → PRs; WHOOSH provides minimal API + status views. Defer HMMM channels/consensus and full Composer until post-MVP.
- Database: start with a minimal subset (teams, team_roles, team_assignments, agents-min, slurp_submissions-min). Defer broad ENUMs/materialized views and analytics until stable.
- Determinism & safety: Validate all LLM outputs (when enabled) against versioned JSON Schemas; cache analyses with TTL; rate limit; apply path allowlists and diff caps; redact secrets.
### Overview
This document outlines the comprehensive development plan for transforming WHOOSH from a simple project template tool into a sophisticated **Autonomous AI Development Teams Architecture** that orchestrates CHORUS agents into self-organizing development teams.
@@ -275,4 +282,4 @@ This document outlines the comprehensive development plan for transforming WHOOS
- [ ] Advanced workflow automation
- [ ] Cross-organization team collaboration
This development plan provides the foundation for transforming WHOOSH into the central orchestration platform for autonomous AI development teams, ensuring scalable, secure, and effective collaboration between AI agents in the CHORUS ecosystem.
This development plan provides the foundation for transforming WHOOSH into the central orchestration platform for autonomous AI development teams, ensuring scalable, secure, and effective collaboration between AI agents in the CHORUS ecosystem.