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docs/pipeline/README.md
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@@ -1,9 +1,9 @@
# Biergarten Pipeline
A C++20 command-line pipeline that samples city records from local JSON,
enriches each with Wikipedia context, and generates bilingual brewery names
and descriptions plus locale-grounded user profiles via a local GGUF model or
a deterministic mock.
enriches each with Wikipedia context, and generates bilingual brewery names and
descriptions plus locale-grounded user profiles via a local GGUF model or a
deterministic mock.
> **This pipeline produces AI-generated data.** It is not a source of truth for
> brewing techniques, cultural representation, or local-language accuracy. See
@@ -40,12 +40,12 @@ The pipeline is a data ingestion layer. It sits outside the web app runtime and
produces seed records the app imports at startup or during a dedicated seed
step.
| Planned app area | Pipeline contribution |
| -------------------------------- | ------------------------------------------------------------------ |
| Brewery discovery and management | Sampled city records, localized names, long-form descriptions |
| Beer reviews and ratings | Stable brewery fixtures with enough context to anchor review pages |
| Social follow relationships | Repeatable brewery entities for feeds, follows, and saved lists |
| Geospatial brewery experiences | Latitude, longitude, and country-level metadata |
| Planned app area | Pipeline contribution |
| -------------------------------- | ------------------------------------------------------------------------------------------------- |
| Brewery discovery and management | Sampled city records, localized names, long-form descriptions |
| Beer reviews and ratings | Stable brewery fixtures with enough context to anchor review pages |
| Social follow relationships | Repeatable brewery entities for feeds, follows, and saved lists |
| Geospatial brewery experiences | Latitude, longitude, and country-level metadata |
| User accounts and profiles | Locale-grounded names, bios, and an auth-ready email/date-of-birth pair for seeding real accounts |
---
@@ -65,10 +65,9 @@ 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.
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.
@@ -138,17 +137,18 @@ NVIDIA GPU.
The container uses a two-stage build. The builder stage installs CMake/Ninja,
clones the matching llama.cpp release tag for its headers only (installed into
`/usr/local/include`), and copies prebuilt shared libraries (`libllama`,
`libggml`, and CUDA/CPU backend plugins) from `ghcr.io/ggml-org/llama.cpp:full-cuda`
into `/usr/local/lib`. With both headers and libraries present, CMake's
system-library detection (see [Build](#build) above) finds them and skips the
FetchContent source build, keeping image build times short.
`libggml`, and CUDA/CPU backend plugins) from
`ghcr.io/ggml-org/llama.cpp:full-cuda` into `/usr/local/lib`. With both headers
and libraries present, CMake's system-library detection (see [Build](#build)
above) finds them and skips the FetchContent source build, keeping image build
times short.
The runtime stage copies the compiled binary, the same prebuilt shared
libraries, and config/prompt assets into a slim CUDA runtime image. It sets
`LD_LIBRARY_PATH=/usr/local/lib:$LD_LIBRARY_PATH` so the dynamic linker
resolves `libllama`/`libggml` at startup, and also co-locates
`libggml-cuda.so` and the CPU backend plugins next to the binary for
`ggml_backend_load_all()`'s `dlopen` scan.
`LD_LIBRARY_PATH=/usr/local/lib:$LD_LIBRARY_PATH` so the dynamic linker resolves
`libllama`/`libggml` at startup, and also co-locates `libggml-cuda.so` and the
CPU backend plugins next to the binary for `ggml_backend_load_all()`'s `dlopen`
scan.
### Build the image
@@ -177,8 +177,8 @@ output to confirm the fast path was taken.
The container always runs the model-backed path; there is no `--mocked`
container mode (use a native build for that — see [Quick Start](#quick-start)).
The entrypoint, `runpod/start.sh`, downloads the GGUF model automatically if
it is not already present at the configured path.
The entrypoint, `runpod/start.sh`, downloads the GGUF model automatically if it
is not already present at the configured path.
```bash
docker run --rm \
@@ -189,20 +189,20 @@ docker run --rm \
biergarten-pipeline:latest
```
By default this downloads `google_gemma-4-E4B-it-Q6_K.gguf` to
`./models/` on first run if it isn't already there. To use a pre-downloaded
model, place it at that path first — see [Model](#model) above.
By default this downloads `google_gemma-4-E4B-it-Q6_K.gguf` to `./models/` on
first run if it isn't already there. To use a pre-downloaded model, place it at
that path first — see [Model](#model) above.
#### Environment variables
| Variable | Purpose |
| ------------------------- | ----------------------------------------------------------------- |
| `BIERGARTEN_MODEL_PATH` | GGUF model path. Default: `/workspace/models/google_gemma-4-E4B-it-Q6_K.gguf`. |
| `BIERGARTEN_OUTPUT_DIR` | SQLite output directory. Default: `/workspace/output`. |
| `BIERGARTEN_LOG_PATH` | Log file path. Default: `/workspace/logs/pipeline.log`. |
| `BIERGARTEN_GL_LAYERS` | GPU layers to offload (`--n-gpu-layers`). Default: `40`. |
| `BIERGARTEN_TEMPERATURE`, `BIERGARTEN_TOP_P`, `BIERGARTEN_TOP_K`, `BIERGARTEN_N_CTX`, `BIERGARTEN_SEED` | Optional sampling overrides, unset by default (binary defaults apply). |
| `BIERGARTEN_EXTRA_ARGS` | Additional raw CLI args appended verbatim. |
| Variable | Purpose |
| ------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------ |
| `BIERGARTEN_MODEL_PATH` | GGUF model path. Default: `/workspace/models/google_gemma-4-E4B-it-Q6_K.gguf`. |
| `BIERGARTEN_OUTPUT_DIR` | SQLite output directory. Default: `/workspace/output`. |
| `BIERGARTEN_LOG_PATH` | Log file path. Default: `/workspace/logs/pipeline.log`. |
| `BIERGARTEN_GL_LAYERS` | GPU layers to offload (`--n-gpu-layers`). Default: `40`. |
| `BIERGARTEN_TEMPERATURE`, `BIERGARTEN_TOP_P`, `BIERGARTEN_TOP_K`, `BIERGARTEN_N_CTX`, `BIERGARTEN_SEED` | Optional sampling overrides, unset by default (binary defaults apply). |
| `BIERGARTEN_EXTRA_ARGS` | Additional raw CLI args appended verbatim. |
`--prompt-dir` is hardcoded to `/app/prompts` inside the container and is not
configurable via environment variable.
@@ -220,15 +220,15 @@ environment variables listed above to match your run.
### Pipeline Stages
| Stage | Implementation |
| --------------- | ----------------------------------------------------------------------------------------------------------------------------------------- |
| Load | `ICuratedDataService` (`CuratedJsonDataService`) reads `locations.json`, `personas.json`, `forenames-by-country.json`, and `surnames-by-country.json` (paths supplied via a `CuratedDataFilePaths` DTO at construction) into typed records, caching each after its first load. `--mocked` runs use `MockCuratedDataService`'s fixed in-memory dataset instead. |
| Sample | `BiergartenPipelineOrchestrator::QueryCitiesWithCountries()` samples `--location-count` locations per run (default `10`). |
| Enrich | `WikipediaEnrichmentService` fetches brewing and beer-related context. Keeps going when a lookup fails. `--mocked` runs use `MockEnrichmentService` instead and skip Wikipedia entirely. |
| Generate Users | `GenerateUsers()` samples a persona and a forename/surname pair per enriched city (skipping countries with no name data), then `MockGenerator` or `LlamaGenerator` produces a username, bio, and activity weight around the sampled name. |
| Generate Breweries | `MockGenerator` or `LlamaGenerator` produces brewery names and descriptions in English and the local language. |
| Store | `SqliteExportService` writes each successful user and brewery into a fresh dated `.sqlite` database with normalized `locations`, `users`, and `breweries` tables. |
| Log | `spdlog` writes results and warnings to the console. |
| Stage | Implementation |
| ------------------ | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| Load | `ICuratedDataService` (`CuratedJsonDataService`) reads `locations.json`, `personas.json`, `forenames-by-country.json`, and `surnames-by-country.json` (paths supplied via a `CuratedDataFilePaths` DTO at construction) into typed records, caching each after its first load. `--mocked` runs use `MockCuratedDataService`'s fixed in-memory dataset instead. |
| Sample | `BiergartenPipelineOrchestrator::QueryCitiesWithCountries()` samples `--location-count` locations per run (default `10`). |
| Enrich | `WikipediaEnrichmentService` fetches brewing and beer-related context. Keeps going when a lookup fails. `--mocked` runs use `MockEnrichmentService` instead and skip Wikipedia entirely. |
| Generate Users | `GenerateUsers()` samples a persona and a forename/surname pair per enriched city (skipping countries with no name data), then `MockGenerator` or `LlamaGenerator` produces a username, bio, and activity weight around the sampled name. |
| Generate Breweries | `MockGenerator` or `LlamaGenerator` produces brewery names and descriptions in English and the local language. |
| Store | `SqliteExportService` writes each successful user and brewery into a fresh dated `.sqlite` database with normalized `locations`, `users`, and `breweries` tables. |
| Log | `spdlog` writes results and warnings to the console. |
If name sampling, enrichment, or generation fails for a city, that city is
skipped and the pipeline continues. `GenerateUsers()` runs before
@@ -240,33 +240,32 @@ skipped and the pipeline continues. `GenerateUsers()` runs before
- `CuratedJsonDataService` — implements `ICuratedDataService`; takes a
`CuratedDataFilePaths` DTO (locations/personas/forenames/surnames paths) in
its constructor, then parses and validates curated location, persona, and
forename/surname JSON, memoizing each result after its first load on a
given instance. `MockCuratedDataService` is the in-memory substitute (4
fixed locations, 3 personas, and name data for `US`/`DE`/`FR`/`BE`) used in
forename/surname JSON, memoizing each result after its first load on a given
instance. `MockCuratedDataService` is the in-memory substitute (4 fixed
locations, 3 personas, and name data for `US`/`DE`/`FR`/`BE`) used in
`--mocked` runs.
- `WikipediaEnrichmentService` — queries Wikipedia extracts, caches results,
returns empty context on failure. `MockEnrichmentService` is the no-op
substitute used in `--mocked` runs.
- `LlamaGenerator` — formats prompts for Gemma 4, validates JSON output for
both `GenerateBrewery` and `GenerateUser`, retries malformed responses up
to three times with corrective feedback in the retry prompt. The token
budget is fixed across attempts; it is not raised automatically on
truncation.
- `MockGenerator` — stable hash-based output so the same city/persona/name
input always produces the same brewery or user.
- `SqliteExportService` — creates a dated SQLite file per run and persists
each successful user and brewery into normalized tables.
- `LlamaGenerator` — formats prompts for Gemma 4, validates JSON output for both
`GenerateBrewery` and `GenerateUser`, retries malformed responses up to three
times with corrective feedback in the retry prompt. The token budget is fixed
across attempts; it is not raised automatically on truncation.
- `MockGenerator` — stable hash-based output so the same city/persona/name input
always produces the same brewery or user.
- `SqliteExportService` — creates a dated SQLite file per run and persists each
successful user and brewery into normalized tables.
- Brewery payloads include English and local-language name and description
fields. User payloads carry a sampled first/last name and gender, an
LLM-generated username/bio/activity weight, and a programmatically
generated (not LLM-authored) unique email and date of birth.
LLM-generated username/bio/activity weight, and a programmatically generated
(not LLM-authored) unique email and date of birth.
### Runtime Behaviour
`WikipediaEnrichmentService` fetches two Wikipedia extracts per city: a
generic "brewing" extract and a "beer in `{country}`" extract. It does not
currently query a city- or region-specific page. Each query string is cached
after its first successful (or empty) lookup.
`WikipediaEnrichmentService` fetches two Wikipedia extracts per city: a generic
"brewing" extract and a "beer in `{country}`" extract. It does not currently
query a city- or region-specific page. Each query string is cached after its
first successful (or empty) lookup.
`GetLocationContext()` returns an empty string when the web client is
unavailable or when lookup/parsing fails.
@@ -281,15 +280,15 @@ runs.
`CuratedJsonDataService` memoizes each of `LoadLocations()`, `LoadPersonas()`,
`LoadForenamesByCountry()`, and `LoadSurnamesByCountry()` independently the
first time each is called, since `BiergartenPipelineOrchestrator` owns a
single `ICuratedDataService` instance for the whole run — later calls return
the cached result instead of re-parsing.
first time each is called, since `BiergartenPipelineOrchestrator` owns a single
`ICuratedDataService` instance for the whole run — later calls return the cached
result instead of re-parsing.
`GenerateUsers()` samples a forename/surname pair per city via `SampleName()`,
keyed by the city's ISO 3166-1 code. Countries present in `locations.json`
but absent from either name fixture (currently `KE`, `SE`, `SG`, `TH`, `VN`,
`ZA`) are skipped, the same way a failed enrichment or generation call skips
a city — see ETHICS-AND-KNOWN-ISSUES.md's Names-by-Country Dataset section.
keyed by the city's ISO 3166-1 code. Countries present in `locations.json` but
absent from either name fixture (currently `KE`, `SE`, `SG`, `TH`, `VN`, `ZA`)
are skipped, the same way a failed enrichment or generation call skips a city —
see ETHICS-AND-KNOWN-ISSUES.md's Names-by-Country Dataset section.
### Process Flow - Activity Diagram
@@ -303,10 +302,10 @@ a city — see ETHICS-AND-KNOWN-ISSUES.md's Names-by-Country Dataset section.
## Generated Output
Each successful run stores a `BreweryRecord` pair with the source location
and a `BreweryResult` payload, and a `UserRecord` pair with the source
location and a `UserResult` payload. The same generated records are also
written to a fresh SQLite export file named with the current UTC timestamp.
Each successful run stores a `BreweryRecord` pair with the source location and a
`BreweryResult` payload, and a `UserRecord` pair with the source location and a
`UserResult` payload. The same generated records are also written to a fresh
SQLite export file named with the current UTC timestamp.
| Field | Meaning |
| ------------------- | ------------------------------------------ |
@@ -315,16 +314,16 @@ written to a fresh SQLite export file named with the current UTC timestamp.
| `name_local` | Brewery name in the local language. |
| `description_local` | Brewery description in the local language. |
| Field | Meaning |
| ----------------- | ----------------------------------------------------------------- |
| `first_name` | Sampled forename, copied from the curated name data (not LLM-invented). |
| `last_name` | Sampled surname, copied from the curated name data (not LLM-invented). |
| `gender` | Gender associated with the sampled forename in the source dataset. |
| `username` | LLM-generated handle. |
| `bio` | LLM-generated short biography. |
| `activity_weight` | Relative check-in/activity weight, reserved for a future J-curve activity profile. |
| Field | Meaning |
| ----------------- | -------------------------------------------------------------------------------------- |
| `first_name` | Sampled forename, copied from the curated name data (not LLM-invented). |
| `last_name` | Sampled surname, copied from the curated name data (not LLM-invented). |
| `gender` | Gender associated with the sampled forename in the source dataset. |
| `username` | LLM-generated handle. |
| `bio` | LLM-generated short biography. |
| `activity_weight` | Relative check-in/activity weight, reserved for a future J-curve activity profile. |
| `email` | Unique `@thebiergarten.app` address, generated programmatically from the sampled name. |
| `date_of_birth` | Randomized date of birth (age 19-48), generated programmatically. |
| `date_of_birth` | Randomized date of birth (age 19-48), generated programmatically. |
The log dump also includes city, country, state or province, ISO subdivision
code, latitude, and longitude for each entry.
@@ -358,11 +357,9 @@ 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
> outcomes, `std::span` for read-only views over generated city data, structured
> bindings in pipeline loops. Formatting follows the Google C++ Style Guide via
> `.clang-format` with a narrow column limit and two-space indentation.
> **Code Style:** Code style generally follows the Google Style Guide and
> features modern C++20 throughout. Formatting follows the Google C++ Style
> Guide, with the exception of indentation width (3 spaces vs. Google's 2).
---
@@ -404,34 +401,33 @@ Silicon; CUDA or HIP/ROCm is detected on Linux when the toolkit is present.
## Fixture Strategy
- `--mocked` for stable fixtures, repeatable screenshots, and Storybook runs.
`MockCuratedDataService` swaps in for `CuratedJsonDataService`, so no
fixture files need to be present on disk.
`MockCuratedDataService` swaps in for `CuratedJsonDataService`, so no fixture
files need to be present on disk.
- `--model` when geographically grounded content matters for demos.
- Keep `locations.json` structured enough to support discovery and future
filtering.
- `personas.json`, `forenames-by-country.json`, and
`surnames-by-country.json` are curated/vendored fixture data, not
LLM-generated — see ETHICS-AND-KNOWN-ISSUES.md's Names-by-Country Dataset
section for provenance.
- Treat SQLite output as seed material for the app's brewery and user
domains, not production data.
- `personas.json`, `forenames-by-country.json`, and `surnames-by-country.json`
are curated/vendored fixture data, not LLM-generated — see
ETHICS-AND-KNOWN-ISSUES.md's Names-by-Country Dataset section for provenance.
- Treat SQLite output as seed material for the app's brewery and user domains,
not production data.
---
## Repo Layout
| Path | Purpose |
| -------------------------------------- | -------------------------------------------------- |
| `tooling/pipeline/includes/` | Public headers and shared models. |
| `tooling/pipeline/src/` | Implementation files. |
| `tooling/pipeline/locations.json` | Curated city input copied into the build tree. |
| `tooling/pipeline/personas.json` | Curated user persona archetypes copied into the build tree. |
| `tooling/pipeline/forenames-by-country.json` | Vendored (CC0) forename data by ISO 3166-1 country code. |
| `tooling/pipeline/surnames-by-country.json` | Vendored (CC0) surname data by ISO 3166-1 country code. |
| `tooling/pipeline/prompts/` | System prompts used by the model-backed path. |
| `tooling/pipeline/runpod/` | Dockerfile, launcher, and RunPod pod template. |
| `docs/pipeline/diagrams/` | Architecture and pipeline diagrams. |
| `docs/pipeline/ETHICS-AND-KNOWN-ISSUES.md` | Ethics, bias, hallucination analysis, mitigations. |
| Path | Purpose |
| -------------------------------------------- | ----------------------------------------------------------- |
| `tooling/pipeline/includes/` | Public headers and shared models. |
| `tooling/pipeline/src/` | Implementation files. |
| `tooling/pipeline/locations.json` | Curated city input copied into the build tree. |
| `tooling/pipeline/personas.json` | Curated user persona archetypes copied into the build tree. |
| `tooling/pipeline/forenames-by-country.json` | Vendored (CC0) forename data by ISO 3166-1 country code. |
| `tooling/pipeline/surnames-by-country.json` | Vendored (CC0) surname data by ISO 3166-1 country code. |
| `tooling/pipeline/prompts/` | System prompts used by the model-backed path. |
| `tooling/pipeline/runpod/` | Dockerfile, launcher, and RunPod pod template. |
| `docs/pipeline/diagrams/` | Architecture and pipeline diagrams. |
| `docs/pipeline/ETHICS-AND-KNOWN-ISSUES.md` | Ethics, bias, hallucination analysis, mitigations. |
---
@@ -456,12 +452,11 @@ Paths below are relative to `tooling/pipeline/`.
## Next Steps
The pipeline currently produces city-aware brewery and user records and
dated SQLite exports. The next passes add additional fixture types so the
app can exercise the full brewery and social domains without live data. For
the detailed engineering breakdown of what's needed to reach the
architecture in [`diagrams/planned/`](./diagrams/planned/), see
[ROADMAP.md](./ROADMAP.md).
The pipeline currently produces city-aware brewery and user records and dated
SQLite exports. The next passes add additional fixture types so the app can
exercise the full brewery and social domains without live data. For the detailed
engineering breakdown of what's needed to reach the architecture in
[`diagrams/planned/`](./diagrams/planned/), see [ROADMAP.md](./ROADMAP.md).
### Testing — Very High Priority