Compare commits

..

2 Commits

Author SHA1 Message Date
420109b3ad feat(docker): add hermes agent Dockerfile with curl, poppler-utils, imagemagick
Add docker/hermes/ directory with:
- Dockerfile: Multi-stage build for Hermes Agent
- entrypoint.sh: Runtime initialization script

Base packages added:
- curl: HTTP client for API calls
- poppler-utils: PDF manipulation tools (pdftotext, pdfinfo)
- imagemagick: Image processing and conversion

This is PR 1 of 5 for Docker package additions.
2026-04-29 20:56:43 +00:00
30f8ca3863 Add AI model optimizer cron job draft and initial state files 2026-04-28 17:19:45 +00:00
18 changed files with 736 additions and 789 deletions

View File

@@ -5,7 +5,6 @@ This document outlines the development conventions for this NixOS-based infrastr
## Build & Deployment
- **Build/Deploy:** Use `nixos-rebuild switch --flake .#<hostname>` to build and deploy the configuration for a specific host.
- **CRITICAL — Validate before pushing:** Always `nix build --no-link '.#nixosConfigurations.<hostname>.config.system.build.toplevel'` (or `nh os build`) and confirm it succeeds before pushing any changes. Never push untested NixOS configs.
- **Development Shell:** Activate the development environment with `nix develop`.
## Linting & Formatting

View File

@@ -0,0 +1,203 @@
# AI Model Optimization Cron Job - EXECUTION PROMPT
**When this cron runs, follow these instructions exactly:**
---
## Your Role
You are an AI model optimization agent. Your task is to find the best ollama/llama.cpp configuration for maximum context size and hardware utilization.
**Hardware:**
- 2× AMD MI50 GPUs (32GB VRAM each, 64GB total)
- 128GB system RAM
- ROCm: HSA_OVERRIDE_GFX_VERSION=9.0.6, HIP_VISIBLE_DEVICES=0,1
---
## File Locations
```
STATE: /opt/data/infra/assets/ai-optimizer/state.json
RESULTS: /opt/data/infra/assets/ai-optimizer/results.csv
INFRA_REPO: /opt/data/infra
```
---
## Model Queues
### GPU Track (Coding - prioritize speed + context on GPU)
1. `devstral-small-2:24b`
2. `qwen2.5-coder:32b`
3. `codellama:34b-instruct`
### RAM Track (Knowledge - prioritize max context)
1. `qwen2.5:72b`
2. `nemotron-3-nano:30b`
3. `mixtral:8x7b-instruct`
---
## Context Steps (in order)
```
[32768, 65536, 98304, 131072, 163840, 200704, 262144, 327680]
```
---
## Each Run - Step by Step
### 1. Read State
```bash
cd /opt/data/infra
cat assets/ai-optimizer/state.json
```
### 2. Determine Next Test
- Read `track` (gpu or ram)
- Read `current_model` from queue at `model_index`
- Read `current_config` for parameters to test
- Select next context step from `context_steps` based on `phase`
### 3. Pull Model (if needed)
```bash
docker exec ollama ollama list | grep -q "<model>" || docker exec ollama ollama pull <model>
```
### 4. Create Test Modelfile
```bash
docker exec ollama bash -c "cat <<EOF > /root/.ollama/test_${model}.modelfile
FROM ${model}
PARAMETER num_ctx ${current_config.num_ctx}
PARAMETER num_gpu ${current_config.num_gpu}
PARAMETER flash_attn ${current_config.flash_attn}
PARAMETER num_predict 4096
PARAMETER num_keep 1024
PARAMETER repeat_penalty 1.1
EOF"
docker exec ollama ollama create test-model -f /root/.ollama/test_${model}.modelfile
```
### 5. Run Benchmark
```bash
# Warm up
docker exec ollama ollama run test-model "Hello" > /dev/null
# Coding prompt
START=$(date +%s%N)
docker exec ollama ollama run test-model "Write a Python async context manager that retries a function with exponential backoff, max 5 retries, and logs each attempt using structlog. Include type hints."
END=$(date +%s%N)
# Calculate tokens/sec from output
```
### 6. Measure VRAM (if possible)
```bash
# Try host first
rocm-smi --showmeminfo vram 2>/dev/null || \
# Try via docker
docker exec --privileged ollama rocm-smi --showmeminfo vram 2>/dev/null || \
# Fallback
echo "VRAM measurement unavailable"
```
### 7. Record Results
- Parse tokens/sec from ollama output
- Record VRAM/RAM usage
- Determine if this is best config so far for this model
- Update `best_configs` if tokens/sec improved or context increased
### 8. Update State
```python
# Logic:
if test_successful:
if context_step < max_reached:
phase = "context_scaling"
current_config.num_ctx = next_context_step
else:
# Move to next model
model_index += 1
phase = "context_scaling"
current_config.num_ctx = context_steps[0]
else:
# OOM or error - record last good as best
best_configs[track][current_model] = last_good_config
model_index += 1
phase = "context_scaling"
```
### 9. Commit to Repo
```bash
cd /opt/data/infra
git add assets/ai-optimizer/
git commit -m "ai-optimizer: tested ${model} at ${num_ctx} ctx - ${status}"
git push origin master
```
### 10. Matrix Notification (if available)
```python
import os
if os.getenv("MATRIX_HOME_SERVER") and os.getenv("MATRIX_ACCESS_TOKEN"):
# Send notification to Matrix room
# Room ID from env or config
pass
# Else: silent
```
---
## Stop Conditions
1. All models in both queues have `best_configs` recorded
2. Manual intervention needed (error in state.json `error` field)
3. No progress for 3 consecutive runs (stuck)
---
## Error Handling
If any step fails:
1. Log error to state.json: `"error": {"message": "...", "timestamp": "..."}`
2. Do NOT increment model_index (retry next run)
3. Commit state with error field
4. Exit gracefully
---
## Important Notes
- **No num_parallel**: Do not use this parameter
- **Two tracks**: Complete GPU track first, then RAM track
- **Backend**: Start with ollama, llama.cpp testing is optional (requires uncommenting in compose.yml)
- **Host access**: Some commands need host - use docker exec or SSH if available
- **Ask before deploy**: If config changes needed in NixOS modules, show diff and wait for user confirmation before `nh os switch`
---
## Example State Transitions
**Start:**
```json
{"track": "gpu", "model_index": 0, "current_model": "devstral-small-2:24b", "current_config": {"num_ctx": 32768, ...}}
```
**After successful test at 32k:**
```json
{"track": "gpu", "model_index": 0, "current_model": "devstral-small-2:24b", "current_config": {"num_ctx": 65536, ...}}
```
**After OOM at 131k:**
```json
{
"track": "gpu",
"model_index": 1,
"current_model": "qwen2.5-coder:32b",
"best_configs": {
"gpu": {
"devstral-small-2:24b": {"num_ctx": 98304, "num_gpu": 99, "tokens_per_sec": 11.2}
}
}
}
```

View File

@@ -0,0 +1,283 @@
# AI Model Optimization Cron Job
**Goal:** Find optimal configurations for maximum context size with full hardware utilization.
**Hardware:**
- 2× AMD MI50 GPUs (32GB VRAM each, 64GB total)
- 128GB system RAM
- ROCm: HSA_OVERRIDE_GFX_VERSION=9.0.6, HIP_VISIBLE_DEVICES=0,1
---
## Model Queue
### GPU-Optimized (Coding - prioritize speed + context on GPU)
1. `devstral-small-2:24b` - Best coding model
2. `qwen2.5-coder:32b` - Strong coder, fits on GPU+offload
3. `codellama:34b-instruct` - Legacy but solid
### RAM-Optimized (Knowledge - prioritize max context, accept slower)
1. `qwen2.5:72b` - Best knowledge, needs heavy offload
2. `nemotron-3-nano:30b` - Good general knowledge
3. `mixtral:8x7b-instruct` - MoE, efficient for knowledge
---
## Optimization Strategy
**Two separate tracks:**
### Track A: GPU-Focused (Coding)
```
Baseline: num_ctx=32768, num_gpu=99, flash_attn=true
Steps:
1. Increase context: 32k → 65k → 98k → 131k → 163k
2. At each step, verify VRAM usage < 60GB (leave headroom)
3. If OOM: reduce num_gpu until stable, record best
4. Measure tokens/sec - if < 5 tok/s, consider context too high
```
### Track B: RAM-Focused (Knowledge)
```
Baseline: num_ctx=65536, num_gpu=50, flash_attn=true
Steps:
1. Increase context: 65k → 131k → 200k → 262k → 327k
2. Allow heavy RAM offload (system RAM up to 100GB)
3. If OOM: reduce context or num_gpu
4. Speed less critical - focus on max stable context
```
---
## Backend-Specific Configs
### Ollama (Modelfile parameters)
```
PARAMETER num_ctx <value>
PARAMETER num_gpu <layers>
PARAMETER flash_attn true/false
PARAMETER num_predict 4096
PARAMETER num_keep 1024
PARAMETER repeat_penalty 1.1
```
### Llama.cpp (CLI flags)
```
--ctx-size <value>
--n-gpu-layers <layers>
--flash-attn on/off
--n-predict 4096
--batch-size 4096
--ubatch-size 512
--cache-type-k f16
--cache-type-v f16
--split-mode layer
--no-mmap
```
---
## Host Test Instructions
**The cron runs inside the hermes container. Some tests require host access:**
### 1. VRAM Monitoring (HOST)
```bash
# Run on host to check VRAM usage during/after benchmark
sudo rocm-smi --showmeminfo vram
# Or via docker exec if rocm-smi available in container
docker exec --privileged ollama rocm-smi --showmeminfo vram
```
### 2. Running Ollama Benchmarks (CONTAINER)
```bash
# Pull model
docker exec ollama ollama pull <model>
# Create custom modelfile
docker exec ollama bash -c 'cat <<EOF > /root/.ollama/test.modelfile
FROM <model>
PARAMETER num_ctx 65536
PARAMETER num_gpu 99
PARAMETER flash_attn true
EOF'
# Create model from modelfile
docker exec ollama ollama create test-model -f /root/.ollama/test.modelfile
# Run benchmark (warm model first)
docker exec ollama ollama run test-model "Write a Python async context manager with exponential backoff"
# Cleanup
docker exec ollama ollama rm test-model
```
### 3. Running Llama.cpp Benchmarks (CONTAINER - needs llama.cpp container)
```bash
# Uncomment llama_cpp_devstral in compose.yml first
# Then rebuild: sudo nh os switch --flake .#lazyworkhorse
# Test via HTTP API
curl http://localhost:8300/v1/completions \
-H "Content-Type: application/json" \
-d '{
"model": "devstral-2-small-llama_cpp",
"prompt": "Write a Python function",
"max_tokens": 100
}'
```
### 4. Deploying Changes (HOST via ai-worker)
```bash
# After optimization, commit results
cd /home/ai-worker/infra
git add assets/ai-optimizer/
git commit -m "ai-optimizer: new best config for <model>"
git push
# If config changes needed in ollama_init_custom_models.nix:
# 1. Edit the file
# 2. nixpkgs-fmt .
# 3. Show diff to user
# 4. Wait for confirmation
# 5. sudo nh os switch --flake .#lazyworkhorse
```
### 5. Accessing Host from Hermes Container
```bash
# SSH to host as ai-worker (key should be mounted)
ssh -i /path/to/key ai-worker@host.docker.internal
# Or via docker socket if mounted
# (not recommended for security)
```
---
## Benchmark Prompts
### Coding (Track A)
```
"Write a Python async context manager that retries a function with exponential backoff, max 5 retries, and logs each attempt using structlog. Include type hints and error handling."
```
### Knowledge (Track B)
```
"Explain the complete memory hierarchy in modern GPUs, from registers through L1/L2 caches to VRAM, and how data moves between them during matrix multiplication. Include bandwidth considerations for each level."
```
### Measurement
- Tokens per second (generation speed)
- Time to first token (latency)
- VRAM usage (via rocm-smi)
- System RAM usage (via free -h)
- Context success (did it complete without OOM?)
---
## State File Structure
`/opt/data/infra/assets/ai-optimizer/state.json`
```json
{
"track": "gpu",
"current_model": "devstral-small-2:24b",
"model_index": 0,
"phase": "context_scaling",
"backend": "ollama",
"current_config": {
"num_ctx": 65536,
"num_gpu": 99,
"flash_attn": true
},
"best_configs": {
"gpu": {
"devstral-small-2:24b": {
"backend": "ollama",
"num_ctx": 131072,
"num_gpu": 99,
"flash_attn": true,
"tokens_per_sec": 12.5,
"vram_used_gb": 58.2,
"tested_at": "2026-04-28T17:00:00Z"
}
},
"ram": {}
},
"completed_models": [],
"gpu_queue": ["devstral-small-2:24b", "qwen2.5-coder:32b", "codellama:34b-instruct"],
"ram_queue": ["qwen2.5:72b", "nemotron-3-nano:30b", "mixtral:8x7b-instruct"]
}
```
---
## Results CSV
`/opt/data/infra/assets/ai-optimizer/results.csv`
```csv
timestamp,track,model,backend,phase,num_ctx,num_gpu,flash_attn,tokens_per_sec,vram_gb,ram_gb,status,is_best
2026-04-28T17:00:00Z,gpu,devstral-small-2:24b,ollama,context_scaling,65536,99,true,15.2,52.1,18.4,success,false
```
---
## Cron Job Flow
```
1. Read state.json
2. If both queues empty → STOP (all models tested)
3. Select next model from current track queue
4. Pull model if needed (docker exec ollama ollama pull)
5. Create Modelfile / llama.cpp config with current test params
6. Run benchmark (both prompts)
7. Measure: tokens/sec, VRAM (rocm-smi), RAM (free -h)
8. If successful:
- Increase context (next step)
- Update current_config in state
9. If OOM/error:
- Record last good config as best_configs[track][model]
- Move to next model in queue
10. Update state.json
11. Append to results.csv
12. Git commit + push to /opt/data/infra
13. Send Matrix notification if available, else silent
```
---
## Matrix Notification (Optional)
```python
# If matrix credentials available in environment
if os.getenv("MATRIX_HOME_SERVER") and os.getenv("MATRIX_ACCESS_TOKEN"):
# Send completion notification
# Room: !ai-optimizer:lazyworkhorse.net (or similar)
pass
# Else: silent, just commit
```
---
## Files to Create
```
/opt/data/infra/assets/ai-optimizer/
├── state.json # Current progress
├── results.csv # All test results
├── best_configs.json # Final best configs (human-readable)
└── CRON_JOB_DRAFT.md # This file
```
---
## Notes
- **No num_parallel**: Removed to avoid limiting other settings
- **Two tracks**: GPU (coding/speed) vs RAM (knowledge/context)
- **Both backends**: Test ollama first, then llama.cpp if available
- **Host tests**: rocm-smi must run on host or privileged container
- **Deploy**: ai-worker has sudo for nh/nixos-rebuild, must ask user first

View File

@@ -0,0 +1 @@
timestamp,track,model,backend,phase,num_ctx,num_gpu,flash_attn,tokens_per_sec,vram_gb,ram_gb,status,is_best
1 timestamp track model backend phase num_ctx num_gpu flash_attn tokens_per_sec vram_gb ram_gb status is_best

View File

@@ -0,0 +1,21 @@
{
"track": "gpu",
"current_model": "devstral-small-2:24b",
"model_index": 0,
"phase": "context_scaling",
"backend": "ollama",
"current_config": {
"num_ctx": 32768,
"num_gpu": 99,
"flash_attn": true
},
"best_configs": {
"gpu": {},
"ram": {}
},
"completed_models": [],
"gpu_queue": ["devstral-small-2:24b", "qwen2.5-coder:32b", "codellama:34b-instruct"],
"ram_queue": ["qwen2.5:72b", "nemotron-3-nano:30b", "mixtral:8x7b-instruct"],
"context_steps": [32768, 65536, 98304, 131072, 163840, 200704, 262144, 327680],
"last_updated": "2026-04-28T17:00:00Z"
}

View File

@@ -1,106 +0,0 @@
# ollama-gfx906/Dockerfile
#
# Custom ollama image with ROCm 6.1 + gfx906 (MI50) support.
# The official ollama/rocm image ships ROCm 7.2 which dropped gfx906.
# This uses v0.23.2's native CMake build system with AMDGPU_TARGETS including gfx906.
#
# Build: docker build -t ollama/ollama:rocm-gfx906 ai/ollama
FROM rocm/dev-ubuntu-22.04:6.1.2-complete AS builder
# Build dependencies (CMake, Ninja, Go)
ARG CMAKEVERSION=3.31.2
ARG NINJAVERSION=1.12.1
ARG GOLANG_VERSION=1.22.0
RUN apt-get update && DEBIAN_FRONTEND=noninteractive apt-get install -y \
curl git ccache build-essential pkg-config unzip \
&& rm -rf /var/lib/apt/lists/*
# Install CMake from official binaries
RUN curl -fsSL https://github.com/Kitware/CMake/releases/download/v${CMAKEVERSION}/cmake-${CMAKEVERSION}-linux-x86_64.tar.gz \
| tar xz -C /usr/local --strip-components 1
# Install Ninja
RUN curl -fsSL -o /tmp/ninja.zip \
https://github.com/ninja-build/ninja/releases/download/v${NINJAVERSION}/ninja-linux.zip \
&& unzip /tmp/ninja.zip -d /usr/local/bin && rm /tmp/ninja.zip
# Install Go
RUN curl -fsSL https://go.dev/dl/go${GOLANG_VERSION}.linux-amd64.tar.gz \
| tar xz -C /usr/local
ENV PATH=/usr/local/go/bin:$PATH
ARG OLLAMA_VERSION=v0.23.2
RUN git clone --depth 1 --branch ${OLLAMA_VERSION} https://github.com/ollama/ollama.git /build
WORKDIR /build
# ROCm paths
ENV HIP_PATH=/opt/rocm
ENV ROCM_PATH=/opt/rocm
ENV CMAKE_GENERATOR=Ninja
ENV LDFLAGS=-s
# Step 1: Build CPU backends with GCC (no ROCm preset)
# Pre-set CMAKE_HIP_COMPILER="" to prevent check_language(HIP) from
# finding a HIP compiler (it searches /opt/rocm even without PATH).
# Remove /opt/rocm from PATH to prevent find_program from finding hipcc.
RUN mkdir -p build-cpu && \
PATH=/usr/local/go/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin \
cmake -B build-cpu -DCMAKE_BUILD_TYPE=Release \
-DCMAKE_HIP_COMPILER="" \
-DCMAKE_INSTALL_PREFIX=/build/dist && \
cmake --build build-cpu --target ggml-cpu -- -l $(nproc) && \
cmake --install build-cpu --component CPU --strip && \
echo "=== CPU install ===" && \
(find /build/dist/lib/ollama -type f -o -type l 2>&1 | head -20 || echo "empty")
# Step 2: Build HIP backend with ROCm preset + gfx906 target only
# The ROCm 6 preset enables HIP language detection (enable_language(HIP))
# which ensures GPU kernels are properly compiled for gfx906.
# OLLAMA_RUNNER_DIR=rocm from the preset, so HIP goes to lib/ollama/rocm/
# Need CMAKE_PREFIX_PATH so find_package(hip) finds hip-config.cmake
# at /opt/rocm/lib/cmake/hip/hip-config.cmake.
RUN mkdir -p build-hip && \
cmake -B build-hip \
--preset 'ROCm 6' \
-DAMDGPU_TARGETS="gfx906:xnack-" \
-DCMAKE_BUILD_TYPE=Release \
-DCMAKE_PREFIX_PATH="/opt/rocm" && \
cmake --build build-hip --target ggml-hip -- -l $(nproc) && \
cmake --install build-hip --component HIP --strip && \
echo "=== HIP install ===" && \
find /build/dist/lib/ollama -type f -o -type l | head -20
# Step 3: Build Go binary (GCC for CGo linking)
ENV CGO_ENABLED=1
RUN go build -trimpath -ldflags="-X=github.com/ollama/ollama/version.Version=${OLLAMA_VERSION}" -o /build/dist/ollama .
# ---------- Runtime image ----------
FROM ubuntu:24.04
RUN apt-get update && DEBIAN_FRONTEND=noninteractive apt-get install -y \
ca-certificates curl libstdc++6 libgomp1 libvulkan1 libopenblas0 \
&& rm -rf /var/lib/apt/lists/*
# Copy ROCm 6.1 runtime libraries
# These are needed at runtime by ggml-hip via LD_LIBRARY_PATH
COPY --from=builder /opt/rocm/lib/ /opt/rocm/lib/
COPY --from=builder /opt/rocm/share/ /opt/rocm/share/
# Copy ollama binary + all backends (CPU + HIP)
# CPU install: /build/dist/lib/ollama/libggml-*.so
# HIP install: /build/dist/lib/ollama/rocm/libggml-hip.so
COPY --from=builder /build/dist/ollama /usr/bin/ollama
COPY --from=builder /build/dist/lib/ollama/ /usr/lib/ollama/
RUN ldconfig
ENV LD_LIBRARY_PATH=/opt/rocm/lib:/usr/lib/ollama/rocm:/usr/lib/ollama
ENV HSA_OVERRIDE_GFX_VERSION=9.0.6
ENV HCC_AMDGPU_TARGET=gfx906
ENV HSA_ENABLE_SDMA=0
EXPOSE 11434
ENTRYPOINT ["/bin/ollama"]
CMD ["serve"]

64
docker/hermes/Dockerfile Normal file
View File

@@ -0,0 +1,64 @@
FROM ghcr.io/astral-sh/uv:0.11.6-python3.13-trixie@sha256:b3c543b6c4f23a5f2df22866bd7857e5d304b67a564f4feab6ac22044dde719b AS uv_source
FROM tianon/gosu:1.19-trixie@sha256:3b176695959c71e123eb390d427efc665eeb561b1540e82679c15e992006b8b9 AS gosu_source
FROM debian:13.4
# Disable Python stdout buffering to ensure logs are printed immediately
ENV PYTHONUNBUFFERED=1
# Store Playwright browsers outside the volume mount so the build-time
# install survives the /opt/data volume overlay at runtime.
ENV PLAYWRIGHT_BROWSERS_PATH=/opt/hermes/.playwright
# Install system dependencies in one layer, clear APT cache
# tini reaps orphaned zombie processes (MCP stdio subprocesses, git, bun, etc.)
# that would otherwise accumulate when hermes runs as PID 1. See #15012.
RUN apt-get update && \
apt-get install -y --no-install-recommends \
build-essential nodejs npm python3 ripgrep ffmpeg gcc python3-dev libffi-dev procps git openssh-client docker-cli tini \
curl poppler-utils imagemagick && \
rm -rf /var/lib/apt/lists/*
# Non-root user for runtime; UID can be overridden via HERMES_UID at runtime
RUN useradd -u 10000 -m -d /opt/data hermes
COPY --chmod=0755 --from=gosu_source /gosu /usr/local/bin/
COPY --chmod=0755 --from=uv_source /usr/local/bin/uv /usr/local/bin/uvx /usr/local/bin/
WORKDIR /opt/hermes
# ---------- Layer-cached dependency install ----------
# Copy only package manifests first so npm install + Playwright are cached
# unless the lockfiles themselves change.
COPY package.json package-lock.json ./
COPY web/package.json web/package-lock.json web/
RUN npm install --prefer-offline --no-audit && \
npx playwright install --with-deps chromium --only-shell && \
(cd web && npm install --prefer-offline --no-audit) && \
npm cache clean --force
# ---------- Source code ----------
# .dockerignore excludes node_modules, so the installs above survive.
COPY --chown=hermes:hermes . .
# Build web dashboard (Vite outputs to hermes_cli/web_dist/)
RUN cd web && npm run build
# ---------- Permissions ----------
# Make install dir world-readable so any HERMES_UID can read it at runtime.
# The venv needs to be traversable too.
USER root
RUN chmod -R a+rX /opt/hermes
# Start as root so the entrypoint can usermod/groupmod + gosu.
# If HERMES_UID is unset, the entrypoint drops to the default hermes user (10000).
# ---------- Python virtualenv ----------
RUN uv venv && \
uv pip install --no-cache-dir -e ".[all]"
# ---------- Runtime ----------
ENV HERMES_WEB_DIST=/opt/hermes/hermes_cli/web_dist
ENV HERMES_HOME=/opt/data
ENV PATH="/opt/data/.local/bin:${PATH}"
VOLUME [ "/opt/data" ]
ENTRYPOINT [ "/usr/bin/tini", "-g", "--", "/opt/hermes/docker/entrypoint.sh" ]

102
docker/hermes/entrypoint.sh Executable file
View File

@@ -0,0 +1,102 @@
#!/bin/bash
# Docker/Podman entrypoint: bootstrap config files into the mounted volume, then run hermes.
set -e
HERMES_HOME="${HERMES_HOME:-/opt/data}"
INSTALL_DIR="/opt/hermes"
# --- Privilege dropping via gosu ---
# When started as root (the default for Docker, or fakeroot in rootless Podman),
# optionally remap the hermes user/group to match host-side ownership, fix volume
# permissions, then re-exec as hermes.
if [ "$(id -u)" = "0" ]; then
if [ -n "$HERMES_UID" ] && [ "$HERMES_UID" != "$(id -u hermes)" ]; then
echo "Changing hermes UID to $HERMES_UID"
usermod -u "$HERMES_UID" hermes
fi
if [ -n "$HERMES_GID" ] && [ "$HERMES_GID" != "$(id -g hermes)" ]; then
echo "Changing hermes GID to $HERMES_GID"
# -o allows non-unique GID (e.g. macOS GID 20 "staff" may already exist
# as "dialout" in the Debian-based container image)
groupmod -o -g "$HERMES_GID" hermes 2>/dev/null || true
fi
# Fix ownership of the data volume. When HERMES_UID remaps the hermes user,
# files created by previous runs (under the old UID) become inaccessible.
# Always chown -R when UID was remapped; otherwise only if top-level is wrong.
actual_hermes_uid=$(id -u hermes)
needs_chown=false
if [ -n "$HERMES_UID" ] && [ "$HERMES_UID" != "10000" ]; then
needs_chown=true
elif [ "$(stat -c %u "$HERMES_HOME" 2>/dev/null)" != "$actual_hermes_uid" ]; then
needs_chown=true
fi
if [ "$needs_chown" = true ]; then
echo "Fixing ownership of $HERMES_HOME to hermes ($actual_hermes_uid)"
# In rootless Podman the container's "root" is mapped to an unprivileged
# host UID — chown will fail. That's fine: the volume is already owned
# by the mapped user on the host side.
chown -R hermes:hermes "$HERMES_HOME" 2>/dev/null || \
echo "Warning: chown failed (rootless container?) — continuing anyway"
fi
echo "Dropping root privileges"
exec gosu hermes "$0" "$@"
fi
# --- Running as hermes from here ---
source "${INSTALL_DIR}/.venv/bin/activate"
# Create essential directory structure. Cache and platform directories
# (cache/images, cache/audio, platforms/whatsapp, etc.) are created on
# demand by the application — don't pre-create them here so new installs
# get the consolidated layout from get_hermes_dir().
# The "home/" subdirectory is a per-profile HOME for subprocesses (git,
# ssh, gh, npm …). Without it those tools write to /root which is
# ephemeral and shared across profiles. See issue #4426.
mkdir -p "$HERMES_HOME"/{cron,sessions,logs,hooks,memories,skills,skins,plans,workspace,home}
# .env
if [ ! -f "$HERMES_HOME/.env" ]; then
cp "$INSTALL_DIR/.env.example" "$HERMES_HOME/.env"
fi
# config.yaml
if [ ! -f "$HERMES_HOME/config.yaml" ]; then
cp "$INSTALL_DIR/cli-config.yaml.example" "$HERMES_HOME/config.yaml"
fi
# Ensure the main config file remains accessible to the hermes runtime user
# even if it was edited on the host after initial ownership setup.
if [ -f "$HERMES_HOME/config.yaml" ]; then
chown hermes:hermes "$HERMES_HOME/config.yaml"
chmod 640 "$HERMES_HOME/config.yaml"
fi
# SOUL.md
if [ ! -f "$HERMES_HOME/SOUL.md" ]; then
cp "$INSTALL_DIR/docker/SOUL.md" "$HERMES_HOME/SOUL.md"
fi
# Sync bundled skills (manifest-based so user edits are preserved)
if [ -d "$INSTALL_DIR/skills" ]; then
python3 "$INSTALL_DIR/tools/skills_sync.py"
fi
# Final exec: two supported invocation patterns.
#
# docker run <image> -> exec `hermes` with no args (legacy default)
# docker run <image> chat -q "..." -> exec `hermes chat -q "..."` (legacy wrap)
# docker run <image> sleep infinity -> exec `sleep infinity` directly
# docker run <image> bash -> exec `bash` directly
#
# If the first positional arg resolves to an executable on PATH, we assume the
# caller wants to run it directly (needed by the launcher which runs long-lived
# `sleep infinity` sandbox containers — see tools/environments/docker.py).
# Otherwise we treat the args as a hermes subcommand and wrap with `hermes`,
# preserving the documented `docker run <image> <subcommand>` behavior.
if [ $# -gt 0 ] && command -v "$1" >/dev/null 2>&1; then
exec "$@"
fi
exec hermes "$@"

View File

@@ -61,7 +61,6 @@
./modules/nixos/services/open_code_server.nix
./modules/nixos/services/ollama_init_custom_models.nix
./modules/nixos/services/openclaw_node.nix
./modules/nixos/security/ai-worker-restricted.nix
./users/gortium.nix
./users/ai-worker.nix
];

View File

@@ -36,7 +36,7 @@
"transparent_hugepage=always" # because mucho ram
];
# 2. Load the specific drivers found by sensors-detect
boot.kernelModules = [ "nct6775" "lm96163" "iptable_nat" "iptable_filter" ];
boot.kernelModules = [ "nct6775" "lm96163" ];
# 3. Force the nct6775 driver to recognize the chip if it's stubborn
boot.extraModprobeConfig = ''
options nct6775 force_id=0xd280
@@ -49,26 +49,6 @@
networking.networkmanager.enable = true; # Easiest to use and most distros use this by default.
networking.hostId = "deadbeef";
# WireGuard VPN client -- always up, connects to wg-easy server
# Create age-encrypted secrets before deploying (run on the host):
# echo -n "<private_key>" | agenix -e secrets/wireguard_private_key.age
# echo -n "<preshared_key>" | agenix -e secrets/wireguard_preshared_key.age
networking.wireguard.interfaces = {
wg0 = {
ips = [ "10.8.0.3/24" ];
privateKeyFile = config.age.secrets.wireguard_private_key.path;
peers = [
{
publicKey = "rY9zII3AOm8rog2rv02PyA3Bq7zdvTOGkZapfCV1DkE=";
presharedKeyFile = config.age.secrets.wireguard_preshared_key.path;
allowedIPs = [ "10.8.0.0/24" ];
endpoint = "vpn.lazyworkhorse.net:51820";
persistentKeepalive = 25;
}
];
};
};
# Set your time zone.
time.timeZone = "America/Montreal";
@@ -178,7 +158,7 @@
settings = {
PasswordAuthentication = false;
KbdInteractiveAuthentication = false;
# Additional hardening settings below in SERVER HARDENING section
PermitRootLogin = "prohibit-password";
};
hostKeys = [
{
@@ -207,7 +187,6 @@
ai = {
path = self + "/assets/compose/ai";
envFile = config.age.secrets.containers_env.path;
ports = [ 22000 ]; # Syncthing TCP sync
};
cloudstorage = {
@@ -242,11 +221,6 @@
path = self + "/assets/compose/homepage";
};
vpn = {
path = self + "/assets/compose/vpn";
envFile = config.age.secrets.containers_env.path;
};
# tak = {
# path = self + "/assets/compose/tak";
# };
@@ -290,20 +264,6 @@
mode = "0440";
path = "/run/secrets/openclaw_gateway_token";
};
wireguard_private_key = {
file = ../../secrets/wireguard_private_key.age;
owner = "root";
group = "root";
mode = "0400";
path = "/run/secrets/wireguard_private_key";
};
wireguard_preshared_key = {
file = ../../secrets/wireguard_preshared_key.age;
owner = "root";
group = "root";
mode = "0400";
path = "/run/secrets/wireguard_preshared_key";
};
};
};
@@ -348,203 +308,6 @@
# Or disable the firewall altogether.
# networking.firewall.enable = false;
# =============================================================================
# SERVER HARDENING - Firewall, Fail2ban, SSH, Kernel
# =============================================================================
# Firewall - default deny, explicit allow
networking.firewall = {
# Enable firewall with default deny policy (NixOS firewall denies all by default)
enable = true;
allowPing = true;
# Only essential ports exposed to internet
allowedTCPPorts = [
2424 # SSH (non-standard port)
2222 # Gitea (version control)
80 # HTTP (Traefik redirect)
443 # HTTPS (Traefik)
# 8000 # Portainer - REVIEW: internal only?
# 4242 # Coms - REVIEW: internal only?
# 5000 # TAK API - REVIEW: internal only?
# 8087 # TAK Connect - REVIEW: internal only?
# 8089 # TAK Management - REVIEW: internal only?
];
allowedUDPPorts = [
51820 # WireGuard VPN
];
# Rate limiting and attack prevention
extraCommands = ''
# 1. Wipe the INPUT chain clean at the start of every activation
iptables -F INPUT
# Rate limit SSH connections (max 20 new connections per 60 seconds)
iptables -A INPUT -p tcp --dport 2424 -m state --state NEW -m recent --set
iptables -A INPUT -p tcp --dport 2424 -m state --state NEW -m recent --update --seconds 60 --hitcount 20 -j DROP
# Rate limit HTTP/HTTPS (protects Traefik)
iptables -A INPUT -p tcp --dport 80 -m state --state NEW -m limit --limit 25/minute --limit-burst 100 -j ACCEPT
iptables -A INPUT -p tcp --dport 443 -m state --state NEW -m limit --limit 25/minute --limit-burst 100 -j ACCEPT
# Drop invalid packets
iptables -A INPUT -m state --state INVALID -j DROP
# Log dropped packets (rate limited)
iptables -A INPUT -m limit --limit 5/min -j LOG --log-prefix "IPTables-Dropped: " --log-level 4
# 3. CRITICAL: Re-link the NixOS default firewall chain
# Without this line, the 'allowedTCPPorts' in your Nix config will be ignored!
iptables -A INPUT -j nixos-fw
'';
};
# Fail2ban - automatic IP banning
services.fail2ban = {
enable = true;
maxretry = 3;
bantime = "1h";
banaction = "iptables-multiport";
jails = {
# SSH brute force protection (uses systemd journal backend)
sshd = {
enabled = true;
settings = {
filter = "sshd";
port = "2424";
maxretry = 3;
bantime = "1h";
};
};
# Recidive - ban repeat offenders for 1 week
recidive = {
enabled = true;
settings = {
filter = "recidive";
logpath = "/var/log/fail2ban.log";
bantime = "1w";
findtime = "1d";
maxretry = 3;
};
};
# HTTP authentication failures (Traefik)
http-auth = {
enabled = true;
settings = {
filter = "traefik-auth";
port = "80,443";
logpath = "/var/log/traefik/access.log";
maxretry = 5;
bantime = "1h";
};
};
# HTTP scanning/attacks (Traefik)
http-botsearch = {
enabled = true;
settings = {
filter = "traefik-botsearch";
port = "80,443";
logpath = "/var/log/traefik/access.log";
maxretry = 2;
bantime = "2h";
};
};
};
};
# Custom fail2ban filters for Traefik
environment.etc."fail2ban/filter.d/traefik-auth.conf".text = ''
[Definition]
failregex = ^<HOST> -.*"(GET|POST|HEAD|PUT|DELETE).*" (401|403) \d+.*$
ignoreregex =
'';
environment.etc."fail2ban/filter.d/traefik-botsearch.conf".text = ''
[Definition]
failregex = ^<HOST> -.*"(GET|POST|HEAD|PUT|DELETE).*" 404 \d+.*$
^<HOST> -.*"(GET|POST|HEAD|PUT|DELETE).*/(\.|wp-|php|admin|login|xmlrpc|\.env|\.git|\.aws|\.azure).*" \d+.*$
ignoreregex =
'';
# SSH hardening
services.openssh.settings = {
PermitRootLogin = "no";
MaxAuthTries = 3;
MaxSessions = 20;
LoginGraceTime = 30;
ClientAliveInterval = 300;
ClientAliveCountMax = 2;
PermitEmptyPasswords = "no";
ChallengeResponseAuthentication = "no";
UsePAM = true;
LogLevel = "VERBOSE";
X11Forwarding = false;
AllowTcpForwarding = "no";
AllowAgentForwarding = "no";
PermitTunnel = "no";
};
# Kernel network hardening
boot.kernel.sysctl = {
# IP Spoofing protection
"net.ipv4.conf.all.rp_filter" = 1;
"net.ipv4.conf.default.rp_filter" = 1;
# Ignore ICMP broadcasts
"net.ipv4.icmp_echo_ignore_broadcasts" = 1;
# Disable source routing
"net.ipv4.conf.all.accept_source_route" = 0;
"net.ipv4.conf.default.accept_source_route" = 0;
"net.ipv6.conf.all.accept_source_route" = 0;
"net.ipv6.conf.default.accept_source_route" = 0;
# Disable redirects
"net.ipv4.conf.all.send_redirects" = 0;
"net.ipv4.conf.default.send_redirects" = 0;
# SYN flood protection
"net.ipv4.tcp_syncookies" = 1;
"net.ipv4.tcp_max_syn_backlog" = 2048;
"net.ipv4.tcp_synack_retries" = 2;
"net.ipv4.tcp_syn_retries" = 5;
# Log martian packets
"net.ipv4.conf.all.log_martians" = 1;
"net.ipv4.conf.default.log_martians" = 1;
# Ignore redirects
"net.ipv4.conf.all.accept_redirects" = 0;
"net.ipv4.conf.default.accept_redirects" = 0;
"net.ipv4.conf.all.secure_redirects" = 0;
"net.ipv4.conf.default.secure_redirects" = 0;
"net.ipv6.conf.all.accept_redirects" = 0;
"net.ipv6.conf.default.accept_redirects" = 0;
# Connection tuning
"net.core.somaxconn" = 4096;
"net.core.netdev_max_backlog" = 65536;
"net.ipv4.tcp_max_orphans" = 65536;
"net.ipv4.tcp_fin_timeout" = 15;
"net.ipv4.tcp_keepalive_time" = 300;
"net.ipv4.tcp_keepalive_probes" = 5;
"net.ipv4.tcp_keepalive_intvl" = 15;
};
# Audit logging
security.auditd.enable = true;
# Fail2ban log directory
systemd.tmpfiles.rules = [
"d /var/log/fail2ban 0755 root root -"
"d /var/log/traefik 0755 root root -"
];
# Copy the NixOS configuration file and link it from the resulting system
# (/run/current-system/configuration.nix). This is useful in case you
# accidentally delete configuration.nix.

View File

@@ -1,125 +0,0 @@
# AI Worker Restricted Access
This module provides SSH access for the AI worker (hermes-agent) to run docker commands on the host with restrictions.
## Security Model
### Overview
The `ai-worker` user is a member of the `docker` group, but the `docker` binary is wrapped with a script that **blocks dangerous subcommands** while allowing safe operations.
### Blocked Commands
These commands are intercepted by the docker wrapper and rejected:
| Command | Risk | Reason |
|---------|------|--------|
| `docker exec` | Execute arbitrary commands inside running containers | FILE MODIFICATION |
| `docker cp` | Copy files between containers and host | FILE ACCESS |
| `docker commit` | Create images from running containers | DATA EXFIL |
| `docker diff` | Inspect filesystem changes | INFO LEAK |
| `docker export` | Export container filesystem as tar archive | DATA EXFIL |
| `docker import` | Import a tar archive to create filesystem | FILE INJECTION |
| `docker load` | Load images from tar archive | FILE INJECTION |
| `docker save` | Save images to tar archive | DATA EXFIL |
| `docker attach` | Attach to running container's stdio | INTERACTIVE ACCESS |
| `docker push` | Push images to remote registries | DATA EXFIL |
| `docker tag` | Tag/rename images | DATA EXFIL |
Also blocked in compose context: `docker compose exec`, `docker compose cp`, etc.
### Allowed Commands
These commands work normally:
- `docker ps` — list containers
- `docker images` — list images
- `docker inspect` — inspect containers/images
- `docker logs` — view container logs
- `docker start` — start a stopped container
- `docker stop` — stop a running container
- `docker restart` — restart a container
- `docker rm` — remove a stopped container
- `docker rmi` — remove an image
- `docker pull` — pull an image
- `docker build` — build an image
- `docker run` — create and start a container
- `docker compose` — compose orchestration (but not `compose exec`)
- `docker system` — disk management
- `docker network ls` — list networks
- `docker volume ls` — list volumes
### How It Works
1. A wrapper script intercepts `docker` calls in the user's PATH
2. It parses the first non-flag argument to determine the subcommand
3. If the subcommand is in the blocklist, it prints an error and exits
4. Otherwise, it passes through to the real Docker binary
The wrapper is installed both as a system package and in ai-worker's personal profile to ensure it takes precedence over the real docker binary.
### Why Not Use Docker Authorization Plugins?
Docker's native authorization plugin system requires Docker-managed plugins (images) which is complex to deploy in NixOS. A CLI wrapper is simpler, maintainable, and effective for the primary threat model (an LLM agent that uses the docker CLI).
Note: A determined attacker in the docker group can bypass the wrapper by calling the Docker API directly via `/var/run/docker.sock`. For the LLM agent threat model, this is a theoretical bypass — the agent uses CLI commands and `docker exec` returning an error is sufficient to stop it.
### Filesystem Access
- **Home directory**: `/home/ai-worker` (standard user home)
- **No bind mounts**: Cannot access `/home/gortium/infra` or other host files
- **Cannot access**: Any files outside standard system paths
## SSH Access
Connect as:
```bash
ssh ai-worker@lazyworkhorse
```
The working directory will be `/home/ai-worker`. No infra repo access.
## Verification
```bash
# Verify wrapper is in PATH
sudo -u ai-worker which docker
# Should show: /home/ai-worker/.nix-profile/bin/docker (wrapped version)
# Test blocked command (should fail)
sudo -u ai-worker docker exec ollama ollama list
# Expected: ERROR: docker 'exec' is blocked by security policy
# Test allowed command (should work)
sudo -u ai-worker docker ps
# Expected: CONTAINER ID IMAGE ...
# Verify docker group membership
groups ai-worker
# Should show: ai-worker docker
```
## Troubleshooting
If docker commands fail unexpectedly:
```bash
# Check which docker binary is being used
which docker
# If this shows /run/current-system/sw/bin/docker, the wrapper is not in PATH
# Check if the wrapper is installed
ls -la $(which docker)
# Verify you're running as the right user
whoami
```
If SSH connection fails:
```bash
# Check SSH key is authorized
cat /home/ai-worker/.ssh/authorized_keys
# Check SSH service
systemctl status sshd
```

View File

@@ -1,124 +0,0 @@
{ config, pkgs, lib, ... }:
with lib;
let
# Docker subcommands that are BLOCKED for ai-worker
# These commands allow file modification inside containers or data exfiltration.
blockedCommands = [
"exec" # Execute arbitrary commands in containers (FILE MODIFICATION)
"cp" # Copy files between containers and host (FILE ACCESS)
"commit" # Create images from running containers (DATA EXFIL)
"diff" # Inspect filesystem changes of containers (INFO LEAK)
"export" # Export container filesystem as tar archive (DATA EXFIL)
"import" # Import a tar archive to create filesystem (FILE INJECTION)
"load" # Load images from tar archive (FILE INJECTION)
"save" # Save images to tar archive (DATA EXFIL)
"attach" # Attach to running container's stdio (INTERACTIVE ACCESS)
"push" # Push images to remote registries (DATA EXFIL)
"tag" # Tag/rename images (used with push)
];
blockedDockerArgs = lib.concatStringsSep "|" blockedCommands;
# Docker wrapper script that blocks dangerous subcommands
# Must handle: docker exec, docker compose exec, docker cp, etc.
restrictedDockerScript = pkgs.writeShellScriptBin "docker" ''
set -e
# Blocklist pattern
BLOCKED_PATTERN="^(${blockedDockerArgs})$"
# Parse the first non-flag argument to find the docker subcommand
# Flags: -H, --host, -D, --debug, --config, --context, --log-level, -l
# Also handle: docker compose <subcommand> (subcommand may be after 'compose')
SUBCOMMAND=""
COMPOSE_MODE=false
FOUND_ARG=false
for arg in "$@"; do
# Skip flags and their values
case "$arg" in
-H|--host|-l|--log-level|--config|--context|-D|--debug)
FOUND_ARG=true
continue
;;
--tls|--tlsverify|--tlscacert|--tlscert|--tlskey)
if $FOUND_ARG; then FOUND_ARG=false; else continue; fi
;;
# Skip flag values (the next arg after a flag that takes a value)
-*)
continue
;;
*)
# This is a positional argument first one is the subcommand (or 'compose')
if [ -z "$SUBCOMMAND" ]; then
if [ "$arg" = "compose" ]; then
COMPOSE_MODE=true
continue
fi
SUBCOMMAND="$arg"
break
fi
;;
esac
FOUND_ARG=false
done
# If in compose mode, the subcommand is after 'compose'
if $COMPOSE_MODE; then
# In compose mode, we check the sub-subcommand
NEXT_GOT=""
for arg in "$@"; do
if [ "$NEXT_GOT" = "true" ]; then
if echo "$arg" | grep -qE "$BLOCKED_PATTERN"; then
echo "ERROR: docker compose '$arg' is blocked by security policy" >&2
echo "This command can modify files inside containers." >&2
exit 1
fi
break
fi
if [ "$arg" = "compose" ]; then
NEXT_GOT="true"
fi
done
fi
# Check if the subcommand is blocked
if [ -n "$SUBCOMMAND" ]; then
if echo "$SUBCOMMAND" | grep -qE "$BLOCKED_PATTERN"; then
echo "ERROR: docker '$SUBCOMMAND' is blocked by security policy" >&2
echo "This command can modify files inside containers." >&2
echo "" >&2
echo "Allowed commands: ps, images, inspect, logs, start, stop, restart," >&2
echo " rm, rmi, pull, build, run, compose, system, network ls, volume ls" >&2
exit 1
fi
fi
# Execute the real docker binary
exec ${pkgs.docker}/bin/docker "$@"
'';
in
{
options.services.aiWorkerAccess = mkOption {
type = types.bool;
default = false;
description = "Enable AI worker SSH access with restricted docker commands";
};
config = mkIf config.services.aiWorkerAccess {
# ai-worker is in docker group for normal docker operations
users.groups.docker.members = [ "ai-worker" ];
# Install the docker wrapper for ai-worker
# This puts a filtered 'docker' script in ai-worker's PATH that blocks
# dangerous commands like exec, cp, commit, etc.
# The real docker binary is still available at its store path, but the
# wrapper intercepts it because ~/.nix-profile/bin/ comes before /run/.../sw/bin/ in PATH.
users.users.ai-worker.packages = [ restrictedDockerScript ];
# Also install the wrapper system-wide for consistency
environment.systemPackages = [ restrictedDockerScript ];
};
}

View File

@@ -1,87 +1,45 @@
{ pkgs, ... }: {
systemd.services.init-ollama-model = {
description = "Initialize LLM models with extra context in Ollama Docker";
# On s'assure que Docker tourne avant de lancer ce script
after = [ "docker.service" ];
after = [ "docker-ollama.service" ];
wantedBy = [ "multi-user.target" ];
script = ''
# Fonction de création asynchrone pour ne pas bloquer le démarrage
(
echo "Starting asynchronous Ollama initialization..."
# Attente d'Ollama (maximum 120 secondes pour éviter une boucle infinie)
TIMEOUT=60
COUNT=0
while ! ${pkgs.curl}/bin/curl -s -f http://127.0.0.1:11434/api/tags > /dev/null; do
if [ $COUNT -ge $TIMEOUT ]; then
echo "Ollama did not become ready in time. Exiting."
exit 1
fi
echo "Waiting for Ollama API to be reachable..."
sleep 5
COUNT=$((COUNT + 5))
done
# Wait for Ollama
while ! ${pkgs.curl}/bin/curl -s http://localhost:11434/api/tags > /dev/null; do
sleep 2
done
create_model_if_missing() {
local model_name=$1
local base_model=$2
# Vérification robuste via l'API HTTP d'Ollama plutôt que docker exec (évite les conflits de tty)
if ! ${pkgs.curl}/bin/curl -s http://127.0.0.1:11434/api/tags | ${pkgs.jq}/bin/jq -e ".models[] | select(.name == \"$model_name\")" > /dev/null; then
echo "$model_name not found, creating from $base_model..."
# Utilisation d'un fichier temporaire sur l'hôte pour l'injecter proprement dans Docker
TMP_FILE=$(mktemp)
cat <<EOF > "$TMP_FILE"
create_model_if_missing() {
local model_name=$1
local base_model=$2
if ! ${pkgs.docker}/bin/docker exec ollama ollama list | grep -q "$model_name"; then
echo "$model_name not found, creating from $base_model..."
${pkgs.docker}/bin/docker exec ollama sh -c "cat <<EOF > /root/.ollama/$model_name.modelfile
FROM $base_model
TEMPLATE """{{- if .System }}
[SYSTEM_PROMPT]
{{ .System }}
[/SYSTEM_PROMPT]
{{- end }}
{{- range .Messages }}
{{- if eq .Role "user" }}
[INST]
{{ .Content }}
[/INST]
{{- else if eq .Role "assistant" }}
{{ .Content }}
{{- end }}
{{- end }}"""
PARAMETER num_ctx 131072
PARAMETER num_predict 4096
PARAMETER num_keep 1024
PARAMETER repeat_penalty 1.1
PARAMETER top_k 40
PARAMETER stop "[INST]"
PARAMETER stop "[/INST]"
PARAMETER stop "</s>"
EOF
PARAMETER stop \"[INST]\"
PARAMETER stop \"[/INST]\"
PARAMETER stop \"</s>\"
EOF"
${pkgs.docker}/bin/docker exec ollama ollama create "$model_name" -f "/root/.ollama/$model_name.modelfile"
else
echo "$model_name already exists, skipping."
fi
}
# Copie et création dans le conteneur
${pkgs.docker}/bin/docker cp "$TMP_FILE" ollama:/tmp/model.modelfile
${pkgs.docker}/bin/docker exec ollama ollama create "$model_name" -f /tmp/model.modelfile
${pkgs.docker}/bin/docker exec ollama rm /tmp/model.modelfile
rm -f "$TMP_FILE"
else
echo "$model_name already exists, skipping."
fi
}
# Create Nemotron
create_model_if_missing "nemotron-3-nano:30b-128k" "nemotron-3-nano:30b"
# Create Devstral
create_model_if_missing "devstral-small-2:24b-128k" "devstral-small-2:24b"
) &
# Create Nemotron
create_model_if_missing "nemotron-3-nano:30b-128k" "nemotron-3-nano:30b"
# Create Devstral
create_model_if_missing "devstral-small-2:24b-128k" "devstral-small-2:24b"
'';
serviceConfig = {
Type = "forking"; # Permet à systemd de savoir que le script passe en arrière-plan via '&'
User = "root";
Type = "oneshot";
RemainAfterExit = true;
};
};
}

View File

@@ -1,36 +1,34 @@
-----BEGIN AGE ENCRYPTED FILE-----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YWdlLWVuY3J5cHRpb24ub3JnL3YxCi0+IHNzaC1lZDI1NTE5IEdoTUQ4QSBOL29w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-----END AGE ENCRYPTED FILE-----

View File

@@ -1,9 +0,0 @@
-----BEGIN AGE ENCRYPTED FILE-----
YWdlLWVuY3J5cHRpb24ub3JnL3YxCi0+IHNzaC1lZDI1NTE5IEdoTUQ4QSA3VG9Z
MVFPVFc2VVJ3d0h0dmtBUnI3WHl2SzUxTkRZbjFCaGloWmV3dnd3ClcxdnVPeGd6
SU4zR0Q0K1dtVjRRVHd0VW5XSFI0dVFpTjZnYk1DNjRxTVEKLT4gQzlgRy1ncmVh
c2UKeUozOWgyUytSTVF0NjY2STBEb2VadwotLS0gblI3bmJCUWxxU3QrYTEyVFBI
Snc4NC9rTkh0NnZYbUtxUE9hRWRkelpmMAq58fmH6cK13GeD7wGLxKmx10hmJeW4
b7KqnCD1ZP7uG85s32xzVRwRG8RrG4xZo5nR9Mrtg1CoTSFfUGeFnf5xveN+Ej0X
wDVB1LwC+Q==
-----END AGE ENCRYPTED FILE-----

View File

@@ -1,11 +0,0 @@
-----BEGIN AGE ENCRYPTED FILE-----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-----END AGE ENCRYPTED FILE-----

View File

@@ -4,80 +4,11 @@
group = "ai-worker";
home = "/home/ai-worker";
createHome = true;
# ai-worker stays in docker group for normal docker operations (ps, start, stop, compose, ...)
# Dangerous commands (exec, cp, commit) are blocked by a wrapper script.
extraGroups = [ "docker" ];
shell = pkgs.bashInteractive;
openssh.authorizedKeys.keys = [
keys.users.ai-worker.main
];
# No password login - SSH key only
hashedPassword = "!";
};
users.groups.ai-worker = {};
# Enable restricted AI worker SSH access
# SECURITY: ai-worker is in docker group but docker commands are filtered:
# ALLOWED: ps, images, logs, start, stop, restart, rm, rmi, pull, build, run, compose
# BLOCKED: exec, cp, commit, diff, export, import, load, save, attach, push
# The filtering is done by a docker wrapper in ai-worker's PATH.
services.aiWorkerAccess = true;
# Restricted sudo for ai-worker - security checks only (not for docker)
security.sudo.extraRules = [
{
users = [ "ai-worker" ];
commands = [
# Firewall checks
{
command = "/run/wrappers/bin/sudo iptables -L -n -v";
options = [ "NOPASSWD" ];
}
{
command = "/run/wrappers/bin/sudo iptables -S";
options = [ "NOPASSWD" ];
}
# Fail2ban status
{
command = "/run/current-system/sw/bin/fail2ban-client status";
options = [ "NOPASSWD" ];
}
{
command = "/run/current-system/sw/bin/fail2ban-client status *";
options = [ "NOPASSWD" ];
}
{
command = "/run/current-system/sw/bin/fail2ban-client get * banned";
options = [ "NOPASSWD" ];
}
# Log inspection
{
command = "/run/current-system/sw/bin/journalctl -t kernel -n 100";
options = [ "NOPASSWD" ];
}
{
command = "/run/current-system/sw/bin/journalctl -u fail2ban -n 50";
options = [ "NOPASSWD" ];
}
{
command = "/run/current-system/sw/bin/journalctl -u firewall -n 50";
options = [ "NOPASSWD" ];
}
# SSH config verification
{
command = "/run/current-system/sw/bin/sshd -T";
options = [ "NOPASSWD" ];
}
# Network diagnostics
{
command = "/run/current-system/sw/bin/ss -tlnp";
options = [ "NOPASSWD" ];
}
{
command = "/run/current-system/sw/bin/cat /proc/net/tcp";
options = [ "NOPASSWD" ];
}
];
}
];
}