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Begin work on Runpod docker config

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Aaron Po
2026-05-03 23:32:08 -04:00
parent 26635ace84
commit 97b2ffeae4
16 changed files with 402 additions and 90 deletions
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docs/pipeline/README.md
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@@ -18,6 +18,7 @@ descriptions via a local GGUF model or a deterministic mock.
- [Build](#build)
- [Model](#model)
- [Run](#run)
- [Docker / RunPod](#docker--runpod)
- [Architecture](#architecture)
- [Pipeline Stages](#pipeline-stages)
- [Key Components](#key-components)
@@ -51,7 +52,7 @@ step.
### Build
Requirements: C++20 compiler, CMake 3.24+, libcurl, Boost (JSON and
Requirements: C++20 compiler, CMake 3.31+, OpenSSL, Boost (JSON and
ProgramOptions). SQLite is fetched from the upstream amalgamation, so no system
SQLite package is required.
@@ -60,6 +61,16 @@ cmake -S . -B build
cmake --build build
```
CMake automatically detects whether a compatible llama.cpp installation is
present on the system (`libllama`, `libggml`, `libggml-base`, and `llama.h`
visible on the default search paths). If found, it links against those
libraries and skips the FetchContent build. If not found, it fetches and builds
llama.cpp from source at tag `b9012`. No additional flags are required in
either case.
Metal is enabled automatically on Apple Silicon. CUDA or HIP/ROCm is detected
automatically on Linux when the relevant toolkit is present.
### Model
> Skip this step if you only need `--mocked`.
@@ -74,33 +85,124 @@ curl -L \
### Run
Run from `build/` so the copied `locations.json` and `prompts/` are available.
Each run also writes a fresh dated SQLite file such as
Each run writes a fresh dated SQLite file such as
`biergarten_seed_2026-04-19T15-30-45.123456Z.sqlite` into the working directory.
```bash
./biergarten-pipeline --mocked
./biergarten-pipeline --model models/google_gemma-4-E4B-it-Q6_K.gguf --temperature 1.0 --top-p 0.95 --top-k 64 --n-ctx 8192 --seed -1
./biergarten-pipeline \
--model ../models/google_gemma-4-E4B-it-Q6_K.gguf \
--prompt-dir prompts \
--temperature 1.0 --top-p 0.95 --top-k 64 --n-ctx 8192 --seed -1
```
#### CLI Flags
| Flag | Purpose |
| --------------- | ------------------------------------------------------- |
| `--mocked` | Deterministic mock generator, no model required. |
| `--model, -m` | Path to a GGUF file. Required unless `--mocked` is set. |
| `--temperature` | Sampling temperature. Default: `1.0`. |
| `--top-p` | Nucleus sampling. Default: `0.95`. |
| `--top-k` | Top-k sampling. Default: `64`. |
| `--n-ctx` | Context window size. Default: `8192`. |
| `--seed` | Random seed. Default: `-1` (random at runtime). |
| `--help, -h` | Print usage and exit. |
| Flag | Purpose |
| --------------- | ---------------------------------------------------------------------------------------------------- |
| `--mocked` | Deterministic mock generator, no model required. |
| `--model, -m` | Path to a GGUF file. Required unless `--mocked` is set. |
| `--prompt-dir` | Directory containing prompt files (e.g. `BREWERY_GENERATION.md`). Required unless `--mocked` is set. |
| `--output, -o` | Directory for generated SQLite artifacts. Default: `output`. |
| `--log-path` | Path for application logs. Default: `pipeline.log`. |
| `--temperature` | Sampling temperature. Default: `1.0`. |
| `--top-p` | Nucleus sampling. Default: `0.95`. |
| `--top-k` | Top-k sampling. Default: `64`. |
| `--n-ctx` | Context window size. Default: `8192`. |
| `--seed` | Random seed. Default: `-1` (random at runtime). |
| `--help, -h` | Print usage and exit. |
`--mocked` and `--model` are mutually exclusive. Omitting both exits with an
error before the pipeline starts. Sampling flags are ignored when `--mocked` is
set.
The post-build step copies `prompts/` into `build/prompts/`. Rebuild after
editing `prompts/system.md`.
editing any prompt file.
---
## Docker / RunPod
The `tooling/pipeline/runpod/` directory contains a GPU-ready container
configuration for running the pipeline on RunPod or any Docker host with an
NVIDIA GPU.
### How it works
The container uses a two-stage build. The first stage pulls prebuilt
`libllama`, `libggml`, and backend plugin libraries (including `libggml-cuda.so`
and the CPU variant plugins) from `ghcr.io/ggml-org/llama.cpp:full-cuda`. The
second stage copies those libraries into `/usr/local/lib` and runs `ldconfig` so
the dynamic linker and `dlopen` calls from `ggml_backend_load_all()` can resolve
the CUDA backend plugin at runtime. llama.cpp headers are cloned at the matching
tag and installed into `/usr/local/include`. CMake auto-detects both and skips
the FetchContent source build entirely, keeping image build times short.
`GGML_BACKEND_PATH` is set to `/usr/local/lib` so llama.cpp knows where to scan
for backend plugins.
### Build the image
Run from the `tooling/pipeline/` directory (the CMake project root), not from
inside `runpod/`, so the `COPY . .` step picks up the full project context.
```bash
docker build -t biergarten-pipeline:latest -f runpod/Dockerfile .
```
To monitor the full build output and confirm CMake selects the system llama.cpp:
```bash
docker build \
--progress=plain \
--no-cache \
-t biergarten-pipeline:latest \
-f runpod/Dockerfile \
. 2>&1 | tee build.log
```
Look for `[biergarten] Found system llama.cpp — skipping FetchContent` in the
output to confirm the fast path was taken.
### Run in mocked mode
No model or GPU required. Useful for validating the pipeline logic and SQLite
export path.
```bash
docker run --rm \
-e BIERGARTEN_MODE=mocked \
-v "$PWD/output:/workspace/output" \
-v "$PWD/logs:/workspace/logs" \
biergarten-pipeline:latest
```
### Run in live mode
Mount your GGUF model before starting. The container validates the model path
before launching the binary.
```bash
docker run --rm \
--runtime=nvidia \
-e BIERGARTEN_MODE=live \
-e GGML_BACKEND_PATH="/usr/local/lib/libggml-cuda.so" \
-v "$PWD/models:/workspace/models" \
-v "$PWD/output:/workspace/output" \
-v "$PWD/logs:/workspace/logs" \
biergarten-pipeline:latest
```
The model must be present at `./models/google_gemma-4-E4B-it-Q6_K.gguf` on the
host. See [Model](#model) above for the download command.
### RunPod deployment
Use a GPU pod template. Mount persistent storage for `/workspace/models`,
`/workspace/output`, and `/workspace/logs`. Set `BIERGARTEN_MODE=live` in the
template environment. See `tooling/pipeline/runpod/pod-template.yaml` for a
starter template.
---
@@ -197,16 +299,18 @@ code, latitude, and longitude for each entry.
## Tech Stack
- C++20
- CMake 3.24+
- CMake 3.31+
- Boost.JSON, Boost.ProgramOptions, Boost.DI
- spdlog
- libcurl
- cpp-httplib (with OpenSSL)
- SQLite amalgamation fetched and compiled via CMake FetchContent
- llama.cpp
- llama.cpp (auto-detected from system install or fetched via FetchContent)
- Docker with NVIDIA CUDA 12.6 base image for GPU container builds
- RunPod for cloud GPU inference
The build fetches Boost.DI, spdlog, llama.cpp, and SQLite via CMake. Metal is
enabled on Apple Silicon; CUDA or HIP/ROCm is detected on Linux when the toolkit
is present.
The build fetches Boost.DI, spdlog, and SQLite via CMake. llama.cpp is fetched
only when a system installation is not detected. Metal is enabled on Apple
Silicon; CUDA or HIP/ROCm is detected on Linux when the toolkit is present.
> **Code Style:** Modern C++20 throughout — RAII for ownership,
> `std::unique_ptr` for injected dependencies, `std::optional` for parse
@@ -218,7 +322,7 @@ is present.
## Tested Hardware
### ARM macOS - M1 Pro
### ARM macOS — M1 Pro
| | |
| --------- | --------------------------------- |
@@ -229,7 +333,7 @@ is present.
| Model | Gemma 4 E4B |
| Inference | llama.cpp with Metal |
### x86_64 Linux - NVIDIA RTX 2000
### x86_64 Linux — NVIDIA RTX 2000
| | |
| --------- | ------------------------------ |
@@ -240,6 +344,15 @@ is present.
| Model | Gemma 4 E4B |
| Inference | llama.cpp with CUDA 12.x |
### x86_64 Linux — Docker / RunPod (NVIDIA CUDA)
| | |
| --------- | ------------------------------------------- |
| Host | RunPod GPU pod |
| Base | nvidia/cuda:12.6.3-devel-ubuntu24.04 |
| Model | Gemma 4 E4B Q6_K |
| Inference | llama.cpp prebuilt CUDA backends via dlopen |
---
## Fixture Strategy
@@ -260,8 +373,9 @@ is present.
| `includes/` | Public headers and shared models. |
| `src/` | Implementation files. |
| `locations.json` | Curated city input copied into the build tree. |
| `prompts/` | System prompt used by the model-backed path. |
| `prompts/` | System prompts used by the model-backed path. |
| `diagrams/` | Architecture and pipeline diagrams. |
| `tooling/pipeline/runpod/` | Dockerfile, launcher, and RunPod pod template. |
| `ETHICS-AND-KNOWN-ISSUES.md` | Ethics, bias, hallucination analysis, mitigations. |
---
@@ -276,6 +390,7 @@ is present.
- `src/data_generation/llama/` — local inference, prompt loading, output
validation.
- `src/data_generation/mock/` — deterministic fallback.
- `tooling/pipeline/runpod/` — container build and runtime launcher.
---