cpal#
Causal program-aided language (CPAL) is a concept implemented in LangChain as a chain for causal modeling and narrative decomposition.
CPAL improves upon the program-aided language (PAL) by incorporating causal structure to prevent hallucination in language models, particularly when dealing with complex narratives and math problems with nested dependencies.
CPAL involves translating causal narratives into a stack of operations, setting hypothetical conditions for causal models, and decomposing narratives into story elements.
It allows for the creation of causal chains that define the relationships between different elements in a narrative, enabling the modeling and analysis of causal relationships within a given context.
Classes
Causal program-aided language (CPAL) chain implementation. |
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Translate the causal narrative into a stack of operations. |
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Set the hypothetical conditions for the causal model. |
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Decompose the narrative into its story elements. |
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Query the outcome table using SQL. |
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Enum for constants used in the CPAL. |
Casual data. |
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Entity in the story. |
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Entity initial conditions. |
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Intervention data of the story aka initial conditions. |
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Narrative input as three story elements. |
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Query data of the story. |
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Result of the story query. |
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Story data. |
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System initial conditions. |