This page lists every hard requirement before you start the quickstart. Skipping any of these will cause the deployment to fail at a specific step.
Node.js
The backend requires Node.js exactly 22.18.0. The @exulu/backend package includes a preinstall script that checks process.version and exits with a non-zero code if the version does not match:
Use nvm to pin the version. The example repo ships an .nvmrc. The Docker images (Dockerfile.backend, Dockerfile.worker) use node:22.18.0-slim explicitly.
Container base image
Both the backend and worker Dockerfiles use node:22.18.0-slim (Debian-based). Alpine Linux is not supported. The ONNX runtime binaries that the knowledge-processing stack depends on are not published for Alpine. Switching to an Alpine base image will cause runtime errors during Python environment setup.
Postgres with pgvector
IMP requires Postgres 13 or later with the pgvector extension. The example compose file uses the official pgvector/pgvector:pg17 image, which ships with the extension pre-installed. On managed Postgres (AWS RDS, Azure, Google Cloud SQL), enable the pgvector extension yourself before first boot.
A second Postgres database for LiteLLM
The LiteLLM proxy needs its own Postgres database for key management and spend tracking. Set LITELLM_DATABASE_URL to a connection string pointing to this separate database. It can be on the same Postgres server but must be a different database name.
Never set LITELLM_DATABASE_URL to the same database as the IMP application. The proxy runs schema migrations on startup and will attempt to drop tables that belong to the IMP schema.
Redis 7
Redis is required when you run workers. Without Redis, BullMQ cannot enqueue or dequeue background jobs (knowledge ingestion, evals, routines). The example compose file uses redis:7.
If you deploy without workers (backend only), Redis is optional.
S3-compatible storage
File uploads require an S3-compatible bucket. Supported targets include MinIO (local) and AWS S3 (production). The bucket must be created before you start the backend — IMP does not create buckets automatically.
Supply the bucket details via the COMPANION_S3_* environment variables.
Version pins
The following component versions are tested and pinned. Do not upgrade these without testing — the pins exist because upstream releases have broken compatibility.
Notes on the Python pins
litellm[proxy]==1.85.1 — the tested version for the embedded proxy. LiteLLM’s API surface changes frequently; upgrade deliberately.prisma==0.15.0 — not included in litellm[proxy] at this version; pinned separately so the LiteLLM database integration works.torch==2.5.1 — pinned because pyannote.audio (used for speaker diarization in transcription) imports torchaudio.AudioMetaData, which was removed in torch 2.6+.transformers>=4.48,<5 — the 5.x line removed a kwarg that pyannote.audio 3.x still passes to hf_hub_download().
GPU (optional — Whisper transcription only)
The Whisper transcription server uses WhisperX with CUDA acceleration. Required only if you use the meeting transcription feature.
- CUDA
12.4
- NVIDIA driver
≥ 550
- At least 8 GB VRAM recommended for the default model size
Hardware guidance
