This repository is the Ambience Suites Renderer rendering and animation component of the Ambience Suites GUI Library ecosystem — a broadcast-grade production platform for rendering technical and fundamental analysis visualisations powered by 1970ai.
Ambience Suites Renderer data is packaged and distributed via Content Data Serial Boxes (Python-native format). See Content_Data_Serial_Boxes.md for the full specification.
+-------------------------+ +-------------------------+
| HOST NODE | | CLIENT NODE |
| | | |
| +------------------+ | | +-----------------+ |
| | Ambience Suites | | | | Display Layer | |
| | Renderer |<------->| | (consume boxes) | |
| +--------+---------+ | | +--------+--------+ |
| | | | | |
| +--------v--------+ | | +--------v--------+ |
| | Broadcast Engine| | | | Analysis Client | |
| | (frame pipeline)| | | | (tech + fund.) | |
| +--------+--------+ | | +--------+--------+ |
| | | | | |
| +--------v--------+ | | +--------v--------+ |
| | 1 9 7 0 a i | | | | Portfolio Layer | |
| | (AI / signals) | | | | (state tracking)| |
| +-----------------+ | | +-----------------+ |
+----------+--------------+ +------------+------------+
| |
+-----------------+---------------+
|
+-----------------v-----------------+
| Content Data Serial Boxes |
| +--------+ +--------+ +--------+ |
| | content| | config | | state | |
| +--------+ +--------+ +--------+ |
+-----------------------------------+
ambience_suites/ Python package — host/client/AI components
host/ Host business machine (renderer + broadcast)
config.py Python dataclass configuration
broadcast.py Frame pipeline and Serial Box delivery
client/ Client business machine (display + analysis)
config.py Python dataclass configuration
broadcast.py Serial Box consumer and dispatch
ai/ 1970ai — official AI component
engine.py Signal engine and emission bus
analysis.py Technical (RSI, MACD, BB, VWAP, EMA) and
fundamental (P/E, EPS, revenue, D/E) analysis
tools/
serial_boxes/ Python-native Serial Box pipeline
schema.py Dataclass schema (replaces JSON schema)
generator.py Generator CLI
validator.py Validator CLI
tvev/ TV/EV performance grading
scorer.py Scorer (per TV-EV Specification.md)
test_scorer.py Unit tests
animations/ Animation cycle definitions (YAML → content boxes)
fade_in.yaml
fade_out.yaml
render_config.py Render config expressed in Python (not JSON)
CMakePresets.json Modern CMake build presets
Ambience Suites Renderer assets map to Content Data Serial Boxes as follows:
| Source | Box Type | Content Type |
|---|---|---|
animations/*.yaml |
content |
animation |
render_config.py |
config |
style |
| Frame state snapshots | state |
ui_component |
Generate boxes:
python -m tools.serial_boxes.generator \
--animations-dir ./animations \
--render-config ./render_config.py \
--output-dir ./serial_boxesValidate boxes:
python -m tools.serial_boxes.validator --boxes-dir ./serial_boxes --strict +-------------------------------+
| 1 9 7 0 a i + AI Engine |
| * Technical Analysis |
| * Fundamental Analysis |
| * Broadcast Signal Engine |
+-------------------------------+
1970ai is the official AI component of Ambience Suites. It drives broadcast-grade rendering decisions through real-time market signals:
Technical indicators: RSI · MACD · Bollinger Bands · VWAP · EMA crossover
Fundamental factors: P/E ratio · EPS growth · Revenue growth · Debt-to-equity
Prompt feature stack (UI/UX LLM/SLM):
- Primary: Billfold Technologies Ambience Suites
- Additional 1970ai feature:
Demonstock-Cinematic/Datos-Novelas-Technologies
from ambience_suites.ai.engine import AI1970Engine
from ambience_suites.ai.analysis import TechnicalAnalysis, FundamentalAnalysis
engine = AI1970Engine()
engine.on_signal(lambda s: print(s.symbol, s.direction, s.strength))
ta = TechnicalAnalysis(engine)
for price in [440, 442, 441, 445, 448]:
ta.push_price("SPY", price, volume=1_000_000)
signals = ta.compute("SPY")
fa = FundamentalAnalysis(engine)
fa.evaluate("AAPL", pe_ratio=28.5, eps_growth=0.12, revenue_growth=0.08)For trade engine performance grading and Beamology dashboard plotting guidance, see TV-EV Specification.
TV/EV Grade Table
-------------------------------------------------
A+ 97-100 Elite Exceeds TV and EV
A 93-97 Excellent Very strong overall
A- 90-93 High Institutional-grade
B+ 87-90 Strong Solid production
B 83-87 Good Meets standard
-------------------------------------------------
Run the scorer:
from tools.tvev.scorer import TVEVScorer, ScorerConfig, LatencyObservation
scorer = TVEVScorer(ScorerConfig(tv_target=10_000.0, ev_target_ms=5.0))
result = scorer.score(
tv_observed=9_200.0,
latency=LatencyObservation(p50=2.5, p95=4.8, p99=6.2),
error_rate=0.00005,
)
print(result.report())Serial Box payloads now support a permission_ruleset that gates allowed
content_type values at schema-validation time.
Available rulesets:
default(all standard content types)billfold_primary_uiux_llm_slmdatos_novelas_prompt_extension
| Dependency | Type | Source |
|---|---|---|
| OpenImageIO | Required | BUILDING.md |
| TBB | Required | BUILDING.md |
| Alembic | Optional | BUILDING.md |
| Embree | Optional | BUILDING.md |
| OpenColorIO | Optional | BUILDING.md |
| OpenVDB / NanoVDB | Optional | BUILDING.md |
| OpenShadingLanguage | Optional | BUILDING.md |
| OpenImageDenoise | Optional | BUILDING.md |
| USD | Optional | BUILDING.md |
| Dependency | Type | Source |
|---|---|---|
| OpenGL | GUI | BUILDING.md |
| GLEW | GUI | BUILDING.md |
| SDL | GUI | BUILDING.md |
| CUDA Toolkit 11+ | GPU (NVIDIA) | BUILDING.md |
| OptiX 7.3+ SDK | GPU (NVIDIA) | BUILDING.md |
| Dependency | Used For | Source |
|---|---|---|
| PyYAML | Serial box generator | .github/workflows/ci.yaml |
| pyflakes | Python linting | .github/workflows/ci.yaml |
| pytest | TV/EV unit tests | .github/workflows/ci.yaml |
Ambience Suites Renderer can be built as a standalone application or a Hydra render delegate. See BUILDING.md for instructions.
CMake presets are available for common configurations:
cmake --preset release # optimised standalone
cmake --preset debug # debug + NaN detection
cmake --preset hydra # Hydra render delegate
cmake --preset tests # release + GTest suite
cmake --preset native # native CPU only (development)The repository contains example XML scenes which can be used for testing.
./install/ambience-suites-renderer examples/scene_monkey.xml
./install/ambience-suites-renderer --samples 100 --output ./image.png examples/scene_monkey.xml
./install/ambience-suites-renderer --shadingsys osl examples/scene_osl_stripes.xmlFor help building or running Ambience Suites Renderer, see BUILDING.md and the repository issue tracker.