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* feat(release): add release-manager feature flag (default off) * feat(release): change classification + semver-bump derivation * feat(release): readiness audit (changelog/version-ref/docs/migration/gate) * feat(release): release-manager engine proposes a gated release * feat(release): fail-closed release executor (bump, gate, publish) * feat(release): CEO approve/reject release-proposal surface * docs(release): document the gated release manager * feat(memory): add org-memory feature flags (default off) * feat(memory): add playbooks table + status enum + migration * feat(memory): playbook service with auditor curation transitions * feat(memory): playbooks RAG index plugin * feat(memory): index a playbook into RAG on approval * feat(memory): distill a high-signal lesson at task completion * feat(memory): keep private journal reflections out of the shared RAG corpus * feat(memory): draft_playbook verb + auditor curation verbs * fix(ci): resolve mypy tests/ errors blocking the gate (UUID casts, annotations) * feat(memory): auto-inject similar lessons/playbooks into the briefing * feat(memory): auditor playbook review queue (api + panel) * docs(memory): document the org-memory loop + playbook verbs * fix(provisioning): idempotent pitch provisioning (reuse product/project by slug on re-approval) * fix(memory): add chunks_playbooks to the chunk schema + isolate release route tests - Migration 030's CHUNK_TABLES was missing chunks_playbooks, breaking the IndexType<->migration parity guard once the PLAYBOOKS index landed. The upgrade is ALTER ... IF EXISTS so adding it is safe on any DB shape. - The release-route fixture's approve/reject paths call db.commit() (real behavior), so a held proposal outlived the per-test rollback and leaked into engine tests that read the global list_open_release_proposals(). Tear down source=release_manager rows after each test. - Make the gather_snapshot real-repo smoke version-agnostic (semver match) so it stops pinning the literal repo version. * chore(release): 0.13.0 * ++ --------- Co-authored-by: Renn F <rennf93@users.noreply.github.com>
338 lines
17 KiB
Markdown
338 lines
17 KiB
Markdown
# RoboCo
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AI Agents Company - A virtual organization of 25 AI agents + 1 human CEO, designed to operate as a complete software development workforce.
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<table align="center">
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<tr>
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<td width="50%" align="center">
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<a href="https://www.youtube.com/watch?v=t1QNqJgBmkM">
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<img src="https://img.youtube.com/vi/t1QNqJgBmkM/maxresdefault.jpg" alt="Watch the 26-minute RoboCo intro on YouTube — what it is, a walkthrough, and how to use it" width="100%">
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</a>
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<br>
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<sub>▶ <b><a href="https://www.youtube.com/watch?v=t1QNqJgBmkM">Watch the 26-min intro</a></b><br>what it is, a walkthrough, and how to use it</sub>
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</td>
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<td width="50%" align="center">
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<a href="https://www.youtube.com/watch?v=xige_EUIjIA">
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<img src="https://img.youtube.com/vi/xige_EUIjIA/maxresdefault.jpg" alt="Watch the 2.5-hour Working with RoboCo build session on YouTube — taking a conversation all the way to a shipped feature" width="100%">
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</a>
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<br>
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<sub>▶ <b><a href="https://www.youtube.com/watch?v=xige_EUIjIA">Watch the 2.5-hour build session</a></b><br>a conversation → a shipped feature</sub>
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</td>
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</tr>
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</table>
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<p align="center">
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<img src="docs/videos/panel-teaser.gif" alt="Twelve-second looping preview of the RoboCo control panel — the org tree, a task in progress, and an approval queue." width="80%">
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<br>
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<sub><a href="docs/videos/panel-full-walkthrough.mp4">Watch the full 2:33 walkthrough (.mp4) →</a></sub>
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</p>
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> [!WARNING]
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> **RoboCo is early-stage, work-in-progress software (v0).** It's under active development, runs in a homelab, and *will* have rough edges, breaking changes, and bugs. It is **not production-ready** and the API/database schema are not stable yet. Treat it as a working prototype to explore and build on — please don't expose it to the public internet as-is. Issues and PRs very welcome.
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> [!TIP]
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> 📚 **Full documentation:** **[rennf93.github.io/roboco](https://rennf93.github.io/roboco/)** — install & first run, the company model, a page-by-page panel reference, model providers, the optional subsystems, deployment, and the API.
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## Overview
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RoboCo implements a structured organizational hierarchy with formal communication protocols, task management, and quality controls. The system enables a single human (CEO) to orchestrate complex multi-project development at scale.
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```
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CEO (You, the human)
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│
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├── Intake (on-demand interviewer: chats only with you to draft a task)
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├── Secretary (on-demand chief-of-staff: reads company state, runs gated directives)
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├── PR Reviewer (read-only main reviewer: inbound external/fork + internal PRs, and the root→master in-path gate)
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│
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└── Board (3 agents)
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├── Product Owner
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├── Head of Marketing
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└── Auditor (silent observer, reports to you)
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│
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└── Main PM (coordinates all cells)
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│
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├── Backend Cell (6 agents: 2 Devs, 1 QA, 1 PM, 1 Documenter, 1 PR Reviewer)
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├── Frontend Cell (6 agents: 2 Devs, 1 QA, 1 PM, 1 Documenter, 1 PR Reviewer)
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└── UX/UI Cell (6 agents: 2 Devs, 1 QA, 1 PM, 1 Documenter, 1 PR Reviewer)
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```
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The 25 agents = Intake + Secretary + PR Reviewer + the Board (3) + Main PM + the three 6-agent cells (18). Agents run on Anthropic Claude by default, or on xAI Grok (the official `grok` CLI on a SuperGrok subscription) — see the provider note under Configuration.
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## How it works
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You hand a task to the company; it runs through a real *build → review → document → merge* pipeline and comes back to you to approve.
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One full loop, put simply:
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1. **You give the Board a task — they review it.** The Product Owner and Head of Marketing turn your ask into requirements and acceptance criteria.
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2. **You approve — the Main PM starts the work.** A notification asks for your *Approve & Start* decision; approve, and the Main PM breaks it into per-cell subtasks.
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3. **Each cell's PM delegates, supports, and triages** its developers (UX/UI, Frontend, Backend).
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4. **Developers build it, QA verifies and gates it, Documenters keep the books.**
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5. **Cell PMs merge their PRs into the Main PM's branch.**
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6. **The Main PM opens the final PR and notifies you "It's done!"** — you approve and merge, or send it back for rework. *(Only you ever merge to `master`.)*
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**— Full circle —**
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**[See the full walkthrough, with screenshots →](docs/how-to/README.md)**
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**[Or watch the full panel walkthrough (video) →](docs/videos/panel-full-walkthrough.mp4)**
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## Project Structure
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```
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roboco/
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├── roboco/ # Main Python package
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│ ├── api/ # FastAPI routes & schemas
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│ │ ├── routes/ # API endpoints (tasks, git, agents, etc.)
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│ │ └── schemas/ # Pydantic request/response models
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│ ├── services/ # Business logic services
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│ │ ├── task.py # Task lifecycle management
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│ │ ├── workspace.py # Multi-agent workspace management
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│ │ ├── messaging.py # Agent communication
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│ │ └── optimal.py # RAG/Knowledge base (in-house pgvector)
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│ ├── models/ # Pydantic domain models
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│ ├── db/ # SQLAlchemy ORM & session
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│ ├── enforcement/ # Task lifecycle state machine
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│ ├── runtime/ # Orchestrator for agent spawning
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│ ├── agents/ # Agent base classes
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│ ├── mcp/ # MCP server implementations
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│ └── config.py # Application configuration
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├── agents/
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│ └── prompts/ # Agent system prompts (roles, teams, identities)
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├── docs/
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│ ├── how-to/ # Visual walkthrough — 5-chapter guide (start at README.md)
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│ └── rag/ # Agent knowledge base (indexed into RAG)
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├── alembic/ # Database migrations
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├── CLAUDE.md # Claude Code guidance
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├── docker-compose.yml # Full stack, built from source
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└── docker-compose.registry.yml # Full stack, pulled from the image registry
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```
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## Running RoboCo
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You need **Docker** + **Docker Compose** and a Claude Code auth directory on the host (`~/.claude`, mounted into the orchestrator so agents can reach the model). Copy `.env.example` to `.env` and set at least `ROBOCO_ENCRYPTION_KEY` and `ROBOCO_AGENT_AUTH_SECRET` (that file shows how to generate each). However you start it, the whole company is reachable at one origin: **http://localhost:3000**.
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**Optional — run agents on xAI Grok instead of Claude.** RoboCo can spawn agents on xAI's official `grok` CLI authenticated by a SuperGrok subscription (no metered API key). Run `grok login` once on the host and point `ROBOCO_HOST_GROK_DIR` at the resulting `~/.grok` so it mounts into Grok agents; the orchestrator keeps the ~6h token refreshed for you. See the Grok block in `.env.example` (`ROBOCO_HOST_GROK_DIR`, `ROBOCO_GROK_AGENT_IMAGE`, `ROBOCO_GROK_CLI_MODEL`, `ROBOCO_GROK_REASONING_EFFORT`).
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### Option 1 — Run the pre-built images (quickest)
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Every release publishes all RoboCo images to both the GitHub Container Registry and Docker Hub, so you can run the full stack without building anything. Use the registry compose:
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```bash
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git clone https://github.com/rennf93/roboco.git && cd roboco
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cp .env.example .env # then edit in your secrets
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docker compose -f docker-compose.registry.yml pull
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docker compose -f docker-compose.registry.yml up -d
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```
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Choose the registry and version with two env vars (defaults shown):
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```bash
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ROBOCO_REGISTRY=ghcr.io/rennf93 # or docker.io/renzof93
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ROBOCO_VERSION=latest # or a pinned release, e.g. 0.13.0
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```
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The orchestrator spawns the matching pre-built agent images on demand — no build toolchain or source compile on your host.
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### Option 2 — Build from source
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The same full stack, built locally from the Dockerfiles instead of pulled:
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```bash
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git clone https://github.com/rennf93/roboco.git && cd roboco
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cp .env.example .env # then edit in your secrets
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docker compose up -d # builds images on first run, then starts everything
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```
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### Option 3 — Local development (no full stack)
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For hacking on the code itself, run only the backing services in Docker and the API on your host. RoboCo's own code requires **Python 3.13+** (`uv` will fetch it if needed):
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```bash
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uv sync
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docker compose up -d postgres redis ollama # backing services only
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uv run alembic upgrade head # migrate the database
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uv run python -m roboco.cli # API + orchestrator
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# Or just the API without the orchestrator:
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uv run uvicorn roboco.api.app:app --reload --host 0.0.0.0 --port 8000
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```
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## Configuration
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Key environment variables (see `roboco/config.py` for all options):
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```bash
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# API Server
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ROBOCO_HOST=0.0.0.0
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ROBOCO_PORT=8000
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# Database
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ROBOCO_DATABASE_HOST=localhost
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ROBOCO_DATABASE_PORT=5432
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ROBOCO_DATABASE_NAME=roboco
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# Workspaces (Multi-Agent Git)
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ROBOCO_WORKSPACES_ROOT=/data/workspaces
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ROBOCO_WORKSPACE_AUTO_CLONE=true
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# RAG/LLM
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ROBOCO_LOCAL_LLM_BASE_URL=http://roboco-ollama:11434/v1
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ROBOCO_LOCAL_LLM_MODEL=glm-5:cloud
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# Feature flags (default-off unless noted; toggle from Settings → Feature Flags)
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ROBOCO_CONVENTIONS_ENABLED=false # per-project architectural conventions standard
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ROBOCO_TOOLCHAIN_MATCH_ENABLED=false # build each target project under its own Python
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ROBOCO_OVERLOAD_BREAK_ENABLED=true # park a provider on a persistent model-API overload
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```
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## Multi-Agent Workspace Structure
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Each agent gets their own git clone for parallel development:
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```
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{ROBOCO_WORKSPACES_ROOT}/
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└── {project-slug}/
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└── {team}/
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└── {agent-slug}/
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└── [git repository]
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Example:
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/data/workspaces/roboco/backend/be-dev-1/
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/data/workspaces/roboco/backend/be-dev-2/
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```
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## Task Lifecycle
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```
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backlog → pending → claimed → in_progress → verifying → awaiting_qa
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↓ ↓ ↓ ↓
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cancelled blocked needs_revision awaiting_documentation
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paused ↓
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awaiting_pm_review
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↓
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awaiting_ceo_approval
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↓
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completed
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```
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Assembled, PR-bearing tasks pass through one extra stage — the in-path PR-review gate — before the PM merges:
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```
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in_progress → awaiting_pr_review → awaiting_pm_review
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(submit_up / (pr_pass)
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submit_root) (pr_fail → needs_revision)
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```
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The cell PM's `submit_up` (cell→root PR) and the Main PM's `submit_root` (root→master PR) open the assembled PR and enter the gate; a PR reviewer `pr_pass`es it on to the PM merge or `pr_fail`s it back. Leaf dev tasks (reviewed by QA) and branchless coordination roots skip the gate.
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## API Endpoints
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Domain routes are mounted under `/api`:
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| Route Group | Description |
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|-------------|-------------|
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| `/api/tasks` | Task CRUD, lifecycle, claiming |
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| `/api/agents` | Agent management |
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| `/api/git` | Git operations (status, commit, push, PR) |
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| `/api/sessions` | Communication sessions |
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| `/api/messages` | Agent messages |
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| `/api/projects` | Project (repo) management |
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| `/api/work-sessions` | Git work session tracking |
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| `/api/optimal` | RAG/Knowledge base queries |
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| `/api/journals` | Agent journals/reflections |
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| `/api/orchestrator/status` | Orchestrator / dispatcher status |
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The agent **gateway** verbs are served separately under `/api/v1/flow/{role}/{verb}` (intent verbs) and `/api/v1/do` (content tools) — see the [Agent Gateway](CLAUDE.md#agent-gateway).
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## Development
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```bash
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# Install dev dependencies
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uv sync --all-extras
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# Run tests
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uv run pytest
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# Format and lint
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uv run ruff format .
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uv run ruff check .
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uv run mypy roboco/
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# Type checking
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uv run mypy roboco/
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```
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## Core Principles
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1. **Everything is a task** - All work is tracked and documented
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2. **No work without a task** - Create task record first
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3. **No task without acceptance criteria** - How do we know it's done?
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4. **No closure without documentation** - Future agents need context
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5. **Communication is constant** - Stream reasoning, log everything
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6. **The Auditor sees all** - Quality monitored silently
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7. **CEO approves major changes** - Human-in-the-loop for critical decisions
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## Technology Stack
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| Layer | Technology |
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|-------|------------|
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| API Framework | FastAPI |
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| Database | PostgreSQL + SQLAlchemy (async) |
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| Vector Store | PostgreSQL + pgvector (in-house engine) |
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| Cache/Queue | Redis |
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| RAG Engine | in-house (asyncpg + pgvector, hybrid retrieval) |
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| Embeddings | qwen3-embedding:0.6b (Ollama) |
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| Local LLM | Ollama (glm-5:cloud) |
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| Cloud LLM | Claude API (Anthropic) + xAI Grok (official `grok` CLI, SuperGrok subscription) |
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| Package Manager | uv |
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## Status
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**Core Infrastructure** (Complete)
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- [x] Data models (Pydantic)
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- [x] Database ORM (SQLAlchemy async)
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- [x] Task lifecycle state machine
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- [x] Multi-agent workspace management
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- [x] Agent prompts (25 agents)
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- [x] Messaging API
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- [x] Task API with full lifecycle
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- [x] Git operations API
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- [x] RAG/Knowledge base (in-house pgvector engine)
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- [x] Agent orchestrator
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- [x] CEO approval workflow
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- [x] Pluggable agent providers (Claude Code + xAI Grok on the official `grok` CLI)
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- [x] Inbound PR review (read-only PR-reviewer + CEO supersede/dismiss queue)
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- [x] Self-healing CI loop for RoboCo's own repo (default-off, CEO-gated)
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- [x] Business Goals tab with a live Company Scorecard (delivery, spend-vs-budget, lead time)
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**In Progress**
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- [x] Frontend panel (vendored under `panel/`, served through nginx on :3000)
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- [ ] Full agent autonomy testing
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## Security
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> [!IMPORTANT]
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> **Do not expose RoboCo to the public internet as-is.** It is designed to run on a trusted private network (homelab / LAN).
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**Agent authentication.** Requests identify the caller with `X-Agent-Id` / `X-Agent-Role` headers. The orchestrator issues each spawned agent an HMAC token (`X-Agent-Token`, signed with `ROBOCO_AGENT_AUTH_SECRET`) that binds its id, role and team. Token enforcement is gated by `ROBOCO_AGENT_AUTH_REQUIRED`:
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- **`ROBOCO_AGENT_AUTH_REQUIRED` unset/false (default):** *header-trust mode* — the role headers are accepted without a token, so any client that can reach the API may claim any role (including `ceo`). The API logs a warning at startup in this mode. Acceptable only on a trusted network.
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- **`ROBOCO_AGENT_AUTH_REQUIRED=true`:** every request must carry a valid token; an agent cannot spoof another agent's role. The control panel keeps working because **nginx** — the only trusted hop between the browser and the API — injects the CEO token (`X-Agent-Token`) on `/api` and `/ws`, so the browser never holds the signing secret. Generate that token with `make panel-token` and set it as `ROBOCO_PANEL_AGENT_TOKEN` in `.env` before enabling secure mode.
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**WebSocket streams.** Token enforcement is currently REST-only. The `/ws/*` endpoints authenticate by `agent_id` query param at most and do not yet validate `X-Agent-Token`, even in secure mode — nginx injects the token so the panel works, but a direct WebSocket connection that bypasses nginx is not rejected. In particular the operator stream `/ws/system` (rate-limit lifecycle + token-usage snapshots for the dashboard) is unauthenticated. These streams are read-only — no control surface, secrets, or task content — but treat the orchestrator port as trusted-network-only until WebSocket auth lands.
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**Secrets** (the Fernet `ROBOCO_ENCRYPTION_KEY`, GitHub PATs) live encrypted in the database and in gitignored env files — never in the repo. Per-project git tokens are Fernet-encrypted at rest and never returned by the API.
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## License
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Copyright (c) 2026 Renzo Franceschini
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RoboCo is licensed under the **GNU Affero General Public License v3.0** (AGPL-3.0). See [`LICENSE`](./LICENSE) for the full text.
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The AGPL's network-use clause (section 13) means that if you run a modified version of RoboCo as a network service, you must make your modified source available to its users. This keeps the project open while preventing closed, hosted re-distributions.
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## Contributing
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Contributions are welcome. All contributors must sign the Contributor License Agreement ([`CLA.md`](./CLA.md)) — this is automated on your first pull request. See [`CONTRIBUTING.md`](./CONTRIBUTING.md) for the workflow and why the CLA exists.
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