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multiqlti

A self-hosted platform that runs software development tasks through a pipeline of specialized AI agents. You describe what you want — the pipeline plans, architects, codes, tests, reviews, and deploys it.

Works with cloud AI (Claude, Gemini, Grok) or fully local (Ollama, vLLM). Your data, your infrastructure.

Architecture

┌─────────────────────────────────────────────────────────────────────┐
│                         User / API / Webhook                        │
└──────────────────────────────┬──────────────────────────────────────┘
                               │
                        ┌──────▼──────┐
                        │    Caddy    │  TLS termination, reverse proxy
                        └──────┬──────┘
                               │
┌──────────────────────────────▼──────────────────────────────────────┐
│                      multiqlti (Node.js)                            │
│                                                                     │
│  ┌─────────────┐  ┌──────────────┐  ┌───────────────────────────┐  │
│  │  Auth/RBAC  │  │  Pipeline    │  │  Execution Strategies     │  │
│  │  JWT + roles│  │  Controller  │  │  ┌───────┐ ┌──────────┐  │  │
│  └─────────────┘  │  ┌────────┐ │  │  │Single │ │Debate    │  │  │
│                    │  │ Linear │ │  │  │ pass  │ │3 models  │  │  │
│  ┌─────────────┐  │  │ DAG    │ │  │  │       │ │argue +   │  │  │
│  │  Skills     │  │  │ Swarm  │ │  │  └───────┘ │judge     │  │  │
│  │  Marketplace│  │  │ Manager│ │  │  ┌───────┐ └──────────┘  │  │
│  └─────────────┘  │  └────────┘ │  │  │MoA    │ ┌──────────┐  │  │
│                    └──────┬─────┘  │  │N prop +│ │Voting    │  │  │
│  ┌─────────────┐         │        │  │1 merge │ │K models  │  │  │
│  │  Workspace  │   ┌─────▼─────┐  │  └───────┘ │consensus │  │  │
│  │  Git, Index │   │  Gateway  │  │            └──────────┘  │  │
│  │  Code Chat  │   │  Router   │  └───────────────────────────┘  │
│  └─────────────┘   └─────┬─────┘                                 │
│                          │                                        │
│  ┌─────────────┐   ┌─────▼─────────────────────────────────────┐ │
│  │  Guardrails │   │              AI Providers                  │ │
│  │  Privacy    │   │  ┌────────┐ ┌──────┐ ┌────┐ ┌───────────┐│ │
│  │  Sandbox    │   │  │Claude  │ │Gemini│ │Grok│ │LM Studio  ││ │
│  └─────────────┘   │  │(cloud) │ │(cloud│ │(cl)│ │(local)    ││ │
│                     │  └────────┘ └──────┘ └────┘ └───────────┘│ │
│  ┌─────────────┐   │  ┌────────┐ ┌──────────────┐             │ │
│  │  Memory     │   │  │Ollama  │ │vLLM (GPU)    │             │ │
│  │  Triggers   │   │  │(local) │ │(self-hosted)  │             │ │
│  │  Federation │   │  └────────┘ └──────────────┘             │ │
│  └─────────────┘   └───────────────────────────────────────────┘ │
└──────────────────────────────┬──────────────────────────────────────┘
                               │
                ┌──────────────▼──────────────┐
                │  PostgreSQL    Redis         │
                │  (data store)  (queue/cache) │
                └─────────────────────────────┘

The Pipeline

Each stage uses a specialized AI agent with its own model and role:

You: "Build a REST API for user management"
 │
 ├─ Planning Agent ──────→ tasks, acceptance criteria, risks
 ├─ Architecture Agent ──→ components, tech stack, API contracts
 ├─ Development Agent ───→ source code files
 ├─ Testing Agent ───────→ test suites, coverage targets
 ├─ Code Review Agent ───→ security audit, quality score, approve/reject
 ├─ Deployment Agent ────→ Dockerfile, CI/CD, K8s manifests
 ├─ Monitoring Agent ────→ dashboards, alerts, health checks
 └─ Fact Check Agent ────→ verify libraries exist, flag hallucinations

Stages can run in sequence, as a DAG (parallel + conditional), or as a swarm (clone task across N agents, merge results).


Quick Start

cp .env.example .env
# Set POSTGRES_PASSWORD, JWT_SECRET, CADDY_DOMAIN in .env

docker compose --profile dev up -d    # Local (Ollama, no GPU)

Open https://localhost. Migrations run automatically.

Other profiles
docker compose --profile cloud-only up -d   # Cloud AI only (Anthropic/Google/XAI)
docker compose --profile full up -d         # GPU inference (vLLM + Ollama)
docker compose --profile full --profile monitoring up -d  # + Prometheus/Grafana
Profile Services Use case
dev app + postgres + ollama + caddy Local, no GPU
cloud-only app + postgres + caddy Cloud providers only
full app + postgres + vllm + ollama + caddy On-premise GPU
monitoring + prometheus + loki + grafana Add to any profile

Usage Patterns

AI Code Factory — describe a feature, get full implementation

Create a pipeline with stages: Planning → Architecture → Development → Testing → Code Review. Assign different models per stage (e.g. Claude for planning, DeepSeek for coding). Run it with a feature description as input.

Output: planned tasks, API design, implementation files, test suite, review report — all structured JSON.

Multi-Model Code Review — 3 models debate your code

Connect a GitHub workspace, select files, run a Code Review + Security Analysis pipeline in Debate mode. Three models independently analyze the code, then argue over findings with a judge model making the final call.

Architecture Decision Engine — models argue for different approaches

Use the Debate execution strategy on the Architecture stage. Configure roles:

  • Proposer argues for microservices
  • Critic argues for monolith
  • Devil's advocate argues for serverless
  • Judge evaluates on scalability, cost, maintainability

Get a structured, reasoned architecture decision with tradeoffs documented.

Automated PR Quality Gate — webhook-triggered review on every PR

Set up a Trigger (webhook type) that fires on GitHub PR events. The trigger runs a pipeline: Code Review → Security Analysis → Fact Check. Results post back as a PR comment. Every PR gets multi-model review automatically.

Research & Analysis — fan-out to multiple models, aggregate

Create a Task Group with parallel tasks:

  • Task 1: Research option A (model: Claude)
  • Task 2: Research option B (model: Gemini)
  • Task 3: Research option C (model: Grok)
  • Task 4: Compare all → recommendation (depends on 1,2,3)

Multiple models research in parallel. A final task synthesizes findings.

Multi-Model Consensus — 5 models vote, only agreement passes

Use the Voting execution strategy with 5 candidate models and a 60% threshold. Use this for high-stakes decisions where hallucination is costly (e.g. "Is this contract vulnerable to reentrancy?").

Air-Gapped / Local-Only — no data leaves your network

Deploy with --profile dev (Ollama only). Enable Privacy anonymization patterns to strip PII before model calls. Code execution runs in sandboxed Docker containers. No external API calls.

Workspace Code Chat — talk to your codebase

Connect a workspace (local path or GitHub URL). The platform indexes your code (AST parsing), builds a dependency graph, and lets you chat with an AI model that has full context of your codebase. Ask questions, request reviews, generate docs.


Environment Variables

Copy .env.example to .env. Required:

Variable Required Description
POSTGRES_PASSWORD Yes openssl rand -hex 16
JWT_SECRET Yes openssl rand -hex 32
CADDY_DOMAIN No Domain for HTTPS (default: localhost)
All variables
Variable Required Description
POSTGRES_USER No DB username (default: multiqlti)
POSTGRES_DB No DB name (default: multiqlti)
DATABASE_URL No Override for external DB
SANDBOX_ENABLED No Code sandbox (default: true)
VLLM_MODEL No vLLM model (default: Llama-3-70B)
ANTHROPIC_API_KEY No Claude provider
GOOGLE_API_KEY No Gemini provider
XAI_API_KEY No Grok provider

Health Check

curl https://localhost/api/health

Data Persistence

Volume Contents
pgdata PostgreSQL database
pgbackups Daily pg_dump backups (last 7)
workspace_data Cloned workspace repositories
ollama_data Downloaded Ollama models
vllm_cache Hugging Face model cache
caddy_data TLS certificates
Backup & restore
# Manual backup
docker compose exec postgres pg_dump -U multiqlti multiqlti > backup.sql

# Restore
cat backup.sql | docker compose exec -T postgres psql -U multiqlti multiqlti

Custom Configuration

cp docker-compose.override.yml.example docker-compose.override.yml
# Edit as needed — never committed to git

Stopping

docker compose --profile dev down      # Stop (data preserved)
docker compose --profile dev down -v   # Stop + delete all data

Production

See docs/DEPLOYMENT_DOCKER.md for cold start, upgrades, monitoring, security checklist.

Kubernetes: Helm charts in helm/multiqlti/ with dev/staging/prod value overrides.


Troubleshooting

Common issues

"JWT_SECRET must be set" — Set it in .env: openssl rand -hex 32

DB connection fails — Check docker compose ps, verify POSTGRES_PASSWORD matches in both services.

vLLM fails — Run nvidia-smi to confirm GPU. Install nvidia-container-toolkit. Or use --profile dev.

Caddy TLS fails — Open ports 80+443, verify CADDY_DOMAIN DNS resolves to this server.

Ollama unhealthy — The healthcheck uses ollama list. Check docker compose logs ollama.

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