AI Context Serializer #

The to_context function converts Kerykeion data models into precise, well-formed XML optimized for Large Language Models (LLMs). Optional fields are omitted when None, and all values are properly escaped.

Usage #

The primary function is to_context(). It takes a Kerykeion model and returns an XML string.

from kerykeion import AstrologicalSubjectFactory, to_context

# 1. Create Model
subject = AstrologicalSubjectFactory.from_birth_data("Alice", 1990, 1, 1, 12, 0, "London", "GB")

# 2. Serialize for AI
ai_context = to_context(subject)
print(ai_context)

Output Preview:

<chart name="Alice">
  <birth_data date="1990-01-01" time="12:00" city="London" nation="GB" ... />
  <config zodiac="Tropical" house_system="Placidus" perspective="Apparent Geocentric" />
  <planets>
    <point name="Sun" position="10.81" sign="Capricorn" element="Earth" quality="Cardinal" house="Tenth House" motion="direct" speed="1.02" />
    ...
  </planets>
  <houses>...</houses>
  <lunar_phase name="Waning Gibbous" phase="20" degrees_between="254.32" emoji="🌖" />
</chart>

Supported Models #

You can pass almost any Kerykeion object to to_context:

AstrologicalSubjectModel (Basic chart)
SingleChartDataModel (Chart with calculated aspects)
DualChartDataModel (Synastry/Transits with inter-aspects)
CompositeSubjectModel
PlanetReturnModel
MoonPhaseOverviewModel
KerykeionPointModel, LunarPhaseModel, AspectModel
ElementDistributionModel, QualityDistributionModel
PointInHouseModel, HouseComparisonModel
TransitMomentModel, TransitsTimeRangeModel

AI Integration Example #

Inject the serialized context directly into your LLM system prompt:

prompt = f"""
You are an expert astrologer. Analyze the following chart data:

{to_context(subject)}

Focus on career potential.
"""

Helper Functions #

For finer control, use these individual converters:

Function	Input Model	Description
`kerykeion_point_to_context`	`KerykeionPointModel`	Single planet/point as `<point />`.
`lunar_phase_to_context`	`LunarPhaseModel`	Lunar phase as `<lunar_phase />`.
`aspect_to_context`	`AspectModel`	Aspect as `<aspect />`.
`point_in_house_to_context`	`PointInHouseModel`	Point in house as `<point_in_house />`.
`astrological_subject_to_context`	`AstrologicalSubjectModel`	Full subject as `<chart>...</chart>`.
`single_chart_data_to_context`	`SingleChartDataModel`	Natal chart as `<chart_analysis>`.
`dual_chart_data_to_context`	`DualChartDataModel`	Synastry/Transit as `<chart_analysis>`.
`element_distribution_to_context`	`ElementDistributionModel`	Element breakdown as `<element_distribution />`.
`quality_distribution_to_context`	`QualityDistributionModel`	Quality breakdown as `<quality_distribution />`.
`house_comparison_to_context`	`HouseComparisonModel`	House overlay as `<house_overlay>`.
`transit_moment_to_context`	`TransitMomentModel`	Transit snapshot as `<transit_moment>`.
`transits_time_range_to_context`	`TransitsTimeRangeModel`	Time-range transits as `<transit_analysis>`.
`moon_phase_overview_to_context`	`MoonPhaseOverviewModel`	Moon phase overview as `<moon_phase_overview>`.

from kerykeion.context_serializer import kerykeion_point_to_context

sun_context = kerykeion_point_to_context(subject.sun)
print(sun_context)
# <point name="Sun" position="10.81" sign="Capricorn" abs_pos="280.81"
#   quality="Cardinal" element="Earth" house="Tenth House" motion="direct" speed="1.02" />

XML Format Details #

Self-closing tags for atomic data: <point ... />, <aspect ... />, <lunar_phase ... />
Nested tags for structured data: <chart>, <chart_analysis>, <moon_phase_overview>
Optional fields omitted when None — tags/attributes are not rendered at all
Non-qualitative — no interpretive words like “good”, “bad”, “strong”, “weak”
Properly escaped via xml.sax.saxutils — safe for any input data

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