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<header>
<h1 class="title">Module <code>tinytroupe.steering.intervention</code></h1>
</header>
<section id="section-intro">
<details class="source">
<summary>
<span>Expand source code</span>
</summary>
<pre><code class="python">from typing import Union, List
from tinytroupe.extraction import logger
from tinytroupe.utils import JsonSerializableRegistry
from tinytroupe.experimentation import Proposition
from tinytroupe.environment import TinyWorld
from tinytroupe.agent import TinyPerson
import tinytroupe.utils as utils

DEFAULT_FIRST_N = 10
DEFAULT_LAST_N = 100

class InterventionBatch:
    &#34;&#34;&#34;
    A wrapper around multiple Intervention instances that allows chaining set_* methods.
    &#34;&#34;&#34;
    
    def __init__(self, interventions):
        self.interventions = interventions
    
    def __iter__(self):
        &#34;&#34;&#34;Makes the batch iterable and compatible with list()&#34;&#34;&#34;
        return iter(self.interventions)
        
    def set_textual_precondition(self, text):
        for intervention in self.interventions:
            intervention.set_textual_precondition(text)
        return self
        
    def set_functional_precondition(self, func):
        for intervention in self.interventions:
            intervention.set_functional_precondition(func)
        return self
        
    def set_effect(self, effect_func):
        for intervention in self.interventions:
            intervention.set_effect(effect_func)
        return self
        
    def set_propositional_precondition(self, proposition, threshold=None):
        for intervention in self.interventions:
            intervention.set_propositional_precondition(proposition, threshold)
        return self
        
    def as_list(self):
        &#34;&#34;&#34;Return the list of individual interventions.&#34;&#34;&#34;
        return self.interventions


class Intervention:

    def __init__(self, targets: Union[TinyPerson, TinyWorld, List[TinyPerson], List[TinyWorld]], 
                 first_n:int=DEFAULT_FIRST_N, last_n:int=DEFAULT_LAST_N,
                 name: str = None):
        &#34;&#34;&#34;
        Initialize the intervention.

        Args:
            target (Union[TinyPerson, TinyWorld, List[TinyPerson], List[TinyWorld]]): the target to intervene on
            first_n (int): the number of first interactions to consider in the context
            last_n (int): the number of last interactions (most recent) to consider in the context
            name (str): the name of the intervention
        &#34;&#34;&#34;
        
        self.targets = targets
        
        # initialize the possible preconditions
        self.text_precondition = None
        self.precondition_func = None

        # effects
        self.effect_func = None

        # which events to pay attention to?
        self.first_n = first_n
        self.last_n = last_n

        # name
        if name is None:
            self.name = self.name = f&#34;Intervention {utils.fresh_id(self.__class__.__name__)}&#34;
        else:
            self.name = name
        
        # the most recent precondition proposition used to check the precondition
        self._last_text_precondition_proposition = None
        self._last_functional_precondition_check = None

        # propositional precondition (optional)
        self.propositional_precondition = None
        self.propositional_precondition_threshold = None
        self._last_propositional_precondition_check = None

    ################################################################################################
    # Intervention flow
    ################################################################################################     
    @classmethod
    def create_for_each(cls, targets, first_n=DEFAULT_FIRST_N, last_n=DEFAULT_LAST_N, name=None):
        &#34;&#34;&#34;
        Create separate interventions for each target in the list.
        
        Args:
            targets (list): List of targets (TinyPerson or TinyWorld instances)
            first_n (int): the number of first interactions to consider in the context
            last_n (int): the number of last interactions (most recent) to consider in the context
            name (str): the name of the intervention
            
        Returns:
            InterventionBatch: A wrapper that allows chaining set_* methods that will apply to all interventions
        &#34;&#34;&#34;
        if not isinstance(targets, list):
            targets = [targets]
            
        interventions = [cls(target, first_n=first_n, last_n=last_n, 
                            name=f&#34;{name}_{i}&#34; if name else None) 
                        for i, target in enumerate(targets)]
        return InterventionBatch(interventions)
    
    def __call__(self):
        &#34;&#34;&#34;
        Execute the intervention.

        Returns:
            bool: whether the intervention effect was applied.
        &#34;&#34;&#34;
        return self.execute()

    def execute(self):
        &#34;&#34;&#34;
        Execute the intervention. It first checks the precondition, and if it is met, applies the effect.
        This is the simplest method to run the intervention.

        Returns:
            bool: whether the intervention effect was applied.
        &#34;&#34;&#34;
        logger.debug(f&#34;Executing intervention: {self}&#34;)
        if self.check_precondition():
            self.apply_effect()
            logger.debug(f&#34;Precondition was true, intervention effect was applied.&#34;)
            return True
        
        logger.debug(f&#34;Precondition was false, intervention effect was not applied.&#34;)
        return False

    def check_precondition(self):
        &#34;&#34;&#34;
        Check if the precondition for the intervention is met.
        &#34;&#34;&#34;
        #
        # Textual precondition
        #
        if self.text_precondition is not None:
            self._last_text_precondition_proposition = Proposition(claim=self.text_precondition, target=self.targets, first_n=self.first_n, last_n=self.last_n)
            llm_precondition_check = self._last_text_precondition_proposition.check()
        else:
            llm_precondition_check = True
        
        #
        # Functional precondition
        #
        if self.precondition_func is not None:
            self._last_functional_precondition_check = self.precondition_func(self.targets)
        else:
            self._last_functional_precondition_check = True # default to True if no functional precondition is set
        
        #
        # Propositional precondition
        #
        self._last_propositional_precondition_check = True
        if self.propositional_precondition is not None:
            if self.propositional_precondition_threshold is not None:
                score = self.propositional_precondition.score(target=self.targets)
                if score &gt;= self.propositional_precondition_threshold:
                    self._last_propositional_precondition_check = False
            else:
                if not self.propositional_precondition.check(target=self.targets):
                    self._last_propositional_precondition_check = False

        return llm_precondition_check and self._last_functional_precondition_check and self._last_propositional_precondition_check


    def apply_effect(self):
        &#34;&#34;&#34;
        Apply the intervention&#39;s effects. This won&#39;t check the precondition, 
        so it should be called after check_precondition.
        &#34;&#34;&#34;
        self.effect_func(self.targets)
    

    ################################################################################################
    # Pre and post conditions
    ################################################################################################

    def set_textual_precondition(self, text):
        &#34;&#34;&#34;
        Set a precondition as text, to be interpreted by a language model.

        Args:
            text (str): the text of the precondition
        &#34;&#34;&#34;
        self.text_precondition = text
        return self # for chaining
    
    def set_functional_precondition(self, func):
        &#34;&#34;&#34;
        Set a precondition as a function, to be evaluated by the code.

        Args:
            func (function): the function of the precondition. 
              Must have the a single argument, targets (either a TinyWorld or TinyPerson, or a list). Must return a boolean.
        &#34;&#34;&#34;
        self.precondition_func = func
        return self # for chaining
    
    def set_effect(self, effect_func):
        &#34;&#34;&#34;
        Set the effect of the intervention.

        Args:
            effect (str): the effect function of the intervention
        &#34;&#34;&#34;
        self.effect_func = effect_func
        return self # for chaining
    
    def set_propositional_precondition(self, proposition:Proposition, threshold:int=None):
        &#34;&#34;&#34;
        Set a propositional precondition using the Proposition class,
        optionally with a score threshold.
        &#34;&#34;&#34;
        
        self.propositional_precondition = proposition
        self.propositional_precondition_threshold = threshold
        return self

    ################################################################################################
    # Inspection
    ################################################################################################

    def precondition_justification(self):
        &#34;&#34;&#34;
        Get the justification for the precondition.
        &#34;&#34;&#34;
        justification = &#34;&#34;

        # text precondition justification
        if self._last_text_precondition_proposition is not None:
            justification += f&#34;{self._last_text_precondition_proposition.justification} (confidence = {self._last_text_precondition_proposition.confidence})\n\n&#34;
        
        # functional precondition justification
        if self.precondition_func is not None:
            if self._last_functional_precondition_check == True:
                justification += f&#34;Functional precondition was met.\n\n&#34;
            
            else:
                justification += &#34;Preconditions do not appear to be met.\n\n&#34;
        
        # propositional precondition justification
        if self.propositional_precondition is not None:
            if self._last_propositional_precondition_check == True:
                justification += f&#34;Propositional precondition was met.\n\n&#34;
            else:
                justification += &#34;Propositional precondition was not met.\n\n&#34;

            return justification

        return justification</code></pre>
</details>
</section>
<section>
</section>
<section>
</section>
<section>
</section>
<section>
<h2 class="section-title" id="header-classes">Classes</h2>
<dl>
<dt id="tinytroupe.steering.intervention.Intervention"><code class="flex name class">
<span>class <span class="ident">Intervention</span></span>
<span>(</span><span>targets: Union[<a title="tinytroupe.agent.tiny_person.TinyPerson" href="../agent/tiny_person.html#tinytroupe.agent.tiny_person.TinyPerson">TinyPerson</a><a title="tinytroupe.environment.tiny_world.TinyWorld" href="../environment/tiny_world.html#tinytroupe.environment.tiny_world.TinyWorld">TinyWorld</a>, List[<a title="tinytroupe.agent.tiny_person.TinyPerson" href="../agent/tiny_person.html#tinytroupe.agent.tiny_person.TinyPerson">TinyPerson</a>], List[<a title="tinytroupe.environment.tiny_world.TinyWorld" href="../environment/tiny_world.html#tinytroupe.environment.tiny_world.TinyWorld">TinyWorld</a>]], first_n: int = 10, last_n: int = 100, name: str = None)</span>
</code></dt>
<dd>
<div class="desc"><p>Initialize the intervention.</p>
<h2 id="args">Args</h2>
<dl>
<dt><strong><code>target</code></strong> :&ensp;<code>Union[TinyPerson, TinyWorld, List[TinyPerson], List[TinyWorld]]</code></dt>
<dd>the target to intervene on</dd>
<dt><strong><code>first_n</code></strong> :&ensp;<code>int</code></dt>
<dd>the number of first interactions to consider in the context</dd>
<dt><strong><code>last_n</code></strong> :&ensp;<code>int</code></dt>
<dd>the number of last interactions (most recent) to consider in the context</dd>
<dt><strong><code>name</code></strong> :&ensp;<code>str</code></dt>
<dd>the name of the intervention</dd>
</dl></div>
<details class="source">
<summary>
<span>Expand source code</span>
</summary>
<pre><code class="python">class Intervention:

    def __init__(self, targets: Union[TinyPerson, TinyWorld, List[TinyPerson], List[TinyWorld]], 
                 first_n:int=DEFAULT_FIRST_N, last_n:int=DEFAULT_LAST_N,
                 name: str = None):
        &#34;&#34;&#34;
        Initialize the intervention.

        Args:
            target (Union[TinyPerson, TinyWorld, List[TinyPerson], List[TinyWorld]]): the target to intervene on
            first_n (int): the number of first interactions to consider in the context
            last_n (int): the number of last interactions (most recent) to consider in the context
            name (str): the name of the intervention
        &#34;&#34;&#34;
        
        self.targets = targets
        
        # initialize the possible preconditions
        self.text_precondition = None
        self.precondition_func = None

        # effects
        self.effect_func = None

        # which events to pay attention to?
        self.first_n = first_n
        self.last_n = last_n

        # name
        if name is None:
            self.name = self.name = f&#34;Intervention {utils.fresh_id(self.__class__.__name__)}&#34;
        else:
            self.name = name
        
        # the most recent precondition proposition used to check the precondition
        self._last_text_precondition_proposition = None
        self._last_functional_precondition_check = None

        # propositional precondition (optional)
        self.propositional_precondition = None
        self.propositional_precondition_threshold = None
        self._last_propositional_precondition_check = None

    ################################################################################################
    # Intervention flow
    ################################################################################################     
    @classmethod
    def create_for_each(cls, targets, first_n=DEFAULT_FIRST_N, last_n=DEFAULT_LAST_N, name=None):
        &#34;&#34;&#34;
        Create separate interventions for each target in the list.
        
        Args:
            targets (list): List of targets (TinyPerson or TinyWorld instances)
            first_n (int): the number of first interactions to consider in the context
            last_n (int): the number of last interactions (most recent) to consider in the context
            name (str): the name of the intervention
            
        Returns:
            InterventionBatch: A wrapper that allows chaining set_* methods that will apply to all interventions
        &#34;&#34;&#34;
        if not isinstance(targets, list):
            targets = [targets]
            
        interventions = [cls(target, first_n=first_n, last_n=last_n, 
                            name=f&#34;{name}_{i}&#34; if name else None) 
                        for i, target in enumerate(targets)]
        return InterventionBatch(interventions)
    
    def __call__(self):
        &#34;&#34;&#34;
        Execute the intervention.

        Returns:
            bool: whether the intervention effect was applied.
        &#34;&#34;&#34;
        return self.execute()

    def execute(self):
        &#34;&#34;&#34;
        Execute the intervention. It first checks the precondition, and if it is met, applies the effect.
        This is the simplest method to run the intervention.

        Returns:
            bool: whether the intervention effect was applied.
        &#34;&#34;&#34;
        logger.debug(f&#34;Executing intervention: {self}&#34;)
        if self.check_precondition():
            self.apply_effect()
            logger.debug(f&#34;Precondition was true, intervention effect was applied.&#34;)
            return True
        
        logger.debug(f&#34;Precondition was false, intervention effect was not applied.&#34;)
        return False

    def check_precondition(self):
        &#34;&#34;&#34;
        Check if the precondition for the intervention is met.
        &#34;&#34;&#34;
        #
        # Textual precondition
        #
        if self.text_precondition is not None:
            self._last_text_precondition_proposition = Proposition(claim=self.text_precondition, target=self.targets, first_n=self.first_n, last_n=self.last_n)
            llm_precondition_check = self._last_text_precondition_proposition.check()
        else:
            llm_precondition_check = True
        
        #
        # Functional precondition
        #
        if self.precondition_func is not None:
            self._last_functional_precondition_check = self.precondition_func(self.targets)
        else:
            self._last_functional_precondition_check = True # default to True if no functional precondition is set
        
        #
        # Propositional precondition
        #
        self._last_propositional_precondition_check = True
        if self.propositional_precondition is not None:
            if self.propositional_precondition_threshold is not None:
                score = self.propositional_precondition.score(target=self.targets)
                if score &gt;= self.propositional_precondition_threshold:
                    self._last_propositional_precondition_check = False
            else:
                if not self.propositional_precondition.check(target=self.targets):
                    self._last_propositional_precondition_check = False

        return llm_precondition_check and self._last_functional_precondition_check and self._last_propositional_precondition_check


    def apply_effect(self):
        &#34;&#34;&#34;
        Apply the intervention&#39;s effects. This won&#39;t check the precondition, 
        so it should be called after check_precondition.
        &#34;&#34;&#34;
        self.effect_func(self.targets)
    

    ################################################################################################
    # Pre and post conditions
    ################################################################################################

    def set_textual_precondition(self, text):
        &#34;&#34;&#34;
        Set a precondition as text, to be interpreted by a language model.

        Args:
            text (str): the text of the precondition
        &#34;&#34;&#34;
        self.text_precondition = text
        return self # for chaining
    
    def set_functional_precondition(self, func):
        &#34;&#34;&#34;
        Set a precondition as a function, to be evaluated by the code.

        Args:
            func (function): the function of the precondition. 
              Must have the a single argument, targets (either a TinyWorld or TinyPerson, or a list). Must return a boolean.
        &#34;&#34;&#34;
        self.precondition_func = func
        return self # for chaining
    
    def set_effect(self, effect_func):
        &#34;&#34;&#34;
        Set the effect of the intervention.

        Args:
            effect (str): the effect function of the intervention
        &#34;&#34;&#34;
        self.effect_func = effect_func
        return self # for chaining
    
    def set_propositional_precondition(self, proposition:Proposition, threshold:int=None):
        &#34;&#34;&#34;
        Set a propositional precondition using the Proposition class,
        optionally with a score threshold.
        &#34;&#34;&#34;
        
        self.propositional_precondition = proposition
        self.propositional_precondition_threshold = threshold
        return self

    ################################################################################################
    # Inspection
    ################################################################################################

    def precondition_justification(self):
        &#34;&#34;&#34;
        Get the justification for the precondition.
        &#34;&#34;&#34;
        justification = &#34;&#34;

        # text precondition justification
        if self._last_text_precondition_proposition is not None:
            justification += f&#34;{self._last_text_precondition_proposition.justification} (confidence = {self._last_text_precondition_proposition.confidence})\n\n&#34;
        
        # functional precondition justification
        if self.precondition_func is not None:
            if self._last_functional_precondition_check == True:
                justification += f&#34;Functional precondition was met.\n\n&#34;
            
            else:
                justification += &#34;Preconditions do not appear to be met.\n\n&#34;
        
        # propositional precondition justification
        if self.propositional_precondition is not None:
            if self._last_propositional_precondition_check == True:
                justification += f&#34;Propositional precondition was met.\n\n&#34;
            else:
                justification += &#34;Propositional precondition was not met.\n\n&#34;

            return justification

        return justification</code></pre>
</details>
<h3>Static methods</h3>
<dl>
<dt id="tinytroupe.steering.intervention.Intervention.create_for_each"><code class="name flex">
<span>def <span class="ident">create_for_each</span></span>(<span>targets, first_n=10, last_n=100, name=None)</span>
</code></dt>
<dd>
<div class="desc"><p>Create separate interventions for each target in the list.</p>
<h2 id="args">Args</h2>
<dl>
<dt><strong><code>targets</code></strong> :&ensp;<code>list</code></dt>
<dd>List of targets (TinyPerson or TinyWorld instances)</dd>
<dt><strong><code>first_n</code></strong> :&ensp;<code>int</code></dt>
<dd>the number of first interactions to consider in the context</dd>
<dt><strong><code>last_n</code></strong> :&ensp;<code>int</code></dt>
<dd>the number of last interactions (most recent) to consider in the context</dd>
<dt><strong><code>name</code></strong> :&ensp;<code>str</code></dt>
<dd>the name of the intervention</dd>
</dl>
<h2 id="returns">Returns</h2>
<dl>
<dt><code><a title="tinytroupe.steering.intervention.InterventionBatch" href="#tinytroupe.steering.intervention.InterventionBatch">InterventionBatch</a></code></dt>
<dd>A wrapper that allows chaining set_* methods that will apply to all interventions</dd>
</dl></div>
<details class="source">
<summary>
<span>Expand source code</span>
</summary>
<pre><code class="python">@classmethod
def create_for_each(cls, targets, first_n=DEFAULT_FIRST_N, last_n=DEFAULT_LAST_N, name=None):
    &#34;&#34;&#34;
    Create separate interventions for each target in the list.
    
    Args:
        targets (list): List of targets (TinyPerson or TinyWorld instances)
        first_n (int): the number of first interactions to consider in the context
        last_n (int): the number of last interactions (most recent) to consider in the context
        name (str): the name of the intervention
        
    Returns:
        InterventionBatch: A wrapper that allows chaining set_* methods that will apply to all interventions
    &#34;&#34;&#34;
    if not isinstance(targets, list):
        targets = [targets]
        
    interventions = [cls(target, first_n=first_n, last_n=last_n, 
                        name=f&#34;{name}_{i}&#34; if name else None) 
                    for i, target in enumerate(targets)]
    return InterventionBatch(interventions)</code></pre>
</details>
</dd>
</dl>
<h3>Methods</h3>
<dl>
<dt id="tinytroupe.steering.intervention.Intervention.apply_effect"><code class="name flex">
<span>def <span class="ident">apply_effect</span></span>(<span>self)</span>
</code></dt>
<dd>
<div class="desc"><p>Apply the intervention's effects. This won't check the precondition,
so it should be called after check_precondition.</p></div>
<details class="source">
<summary>
<span>Expand source code</span>
</summary>
<pre><code class="python">def apply_effect(self):
    &#34;&#34;&#34;
    Apply the intervention&#39;s effects. This won&#39;t check the precondition, 
    so it should be called after check_precondition.
    &#34;&#34;&#34;
    self.effect_func(self.targets)</code></pre>
</details>
</dd>
<dt id="tinytroupe.steering.intervention.Intervention.check_precondition"><code class="name flex">
<span>def <span class="ident">check_precondition</span></span>(<span>self)</span>
</code></dt>
<dd>
<div class="desc"><p>Check if the precondition for the intervention is met.</p></div>
<details class="source">
<summary>
<span>Expand source code</span>
</summary>
<pre><code class="python">def check_precondition(self):
    &#34;&#34;&#34;
    Check if the precondition for the intervention is met.
    &#34;&#34;&#34;
    #
    # Textual precondition
    #
    if self.text_precondition is not None:
        self._last_text_precondition_proposition = Proposition(claim=self.text_precondition, target=self.targets, first_n=self.first_n, last_n=self.last_n)
        llm_precondition_check = self._last_text_precondition_proposition.check()
    else:
        llm_precondition_check = True
    
    #
    # Functional precondition
    #
    if self.precondition_func is not None:
        self._last_functional_precondition_check = self.precondition_func(self.targets)
    else:
        self._last_functional_precondition_check = True # default to True if no functional precondition is set
    
    #
    # Propositional precondition
    #
    self._last_propositional_precondition_check = True
    if self.propositional_precondition is not None:
        if self.propositional_precondition_threshold is not None:
            score = self.propositional_precondition.score(target=self.targets)
            if score &gt;= self.propositional_precondition_threshold:
                self._last_propositional_precondition_check = False
        else:
            if not self.propositional_precondition.check(target=self.targets):
                self._last_propositional_precondition_check = False

    return llm_precondition_check and self._last_functional_precondition_check and self._last_propositional_precondition_check</code></pre>
</details>
</dd>
<dt id="tinytroupe.steering.intervention.Intervention.execute"><code class="name flex">
<span>def <span class="ident">execute</span></span>(<span>self)</span>
</code></dt>
<dd>
<div class="desc"><p>Execute the intervention. It first checks the precondition, and if it is met, applies the effect.
This is the simplest method to run the intervention.</p>
<h2 id="returns">Returns</h2>
<dl>
<dt><code>bool</code></dt>
<dd>whether the intervention effect was applied.</dd>
</dl></div>
<details class="source">
<summary>
<span>Expand source code</span>
</summary>
<pre><code class="python">def execute(self):
    &#34;&#34;&#34;
    Execute the intervention. It first checks the precondition, and if it is met, applies the effect.
    This is the simplest method to run the intervention.

    Returns:
        bool: whether the intervention effect was applied.
    &#34;&#34;&#34;
    logger.debug(f&#34;Executing intervention: {self}&#34;)
    if self.check_precondition():
        self.apply_effect()
        logger.debug(f&#34;Precondition was true, intervention effect was applied.&#34;)
        return True
    
    logger.debug(f&#34;Precondition was false, intervention effect was not applied.&#34;)
    return False</code></pre>
</details>
</dd>
<dt id="tinytroupe.steering.intervention.Intervention.precondition_justification"><code class="name flex">
<span>def <span class="ident">precondition_justification</span></span>(<span>self)</span>
</code></dt>
<dd>
<div class="desc"><p>Get the justification for the precondition.</p></div>
<details class="source">
<summary>
<span>Expand source code</span>
</summary>
<pre><code class="python">def precondition_justification(self):
    &#34;&#34;&#34;
    Get the justification for the precondition.
    &#34;&#34;&#34;
    justification = &#34;&#34;

    # text precondition justification
    if self._last_text_precondition_proposition is not None:
        justification += f&#34;{self._last_text_precondition_proposition.justification} (confidence = {self._last_text_precondition_proposition.confidence})\n\n&#34;
    
    # functional precondition justification
    if self.precondition_func is not None:
        if self._last_functional_precondition_check == True:
            justification += f&#34;Functional precondition was met.\n\n&#34;
        
        else:
            justification += &#34;Preconditions do not appear to be met.\n\n&#34;
    
    # propositional precondition justification
    if self.propositional_precondition is not None:
        if self._last_propositional_precondition_check == True:
            justification += f&#34;Propositional precondition was met.\n\n&#34;
        else:
            justification += &#34;Propositional precondition was not met.\n\n&#34;

        return justification

    return justification</code></pre>
</details>
</dd>
<dt id="tinytroupe.steering.intervention.Intervention.set_effect"><code class="name flex">
<span>def <span class="ident">set_effect</span></span>(<span>self, effect_func)</span>
</code></dt>
<dd>
<div class="desc"><p>Set the effect of the intervention.</p>
<h2 id="args">Args</h2>
<dl>
<dt><strong><code>effect</code></strong> :&ensp;<code>str</code></dt>
<dd>the effect function of the intervention</dd>
</dl></div>
<details class="source">
<summary>
<span>Expand source code</span>
</summary>
<pre><code class="python">def set_effect(self, effect_func):
    &#34;&#34;&#34;
    Set the effect of the intervention.

    Args:
        effect (str): the effect function of the intervention
    &#34;&#34;&#34;
    self.effect_func = effect_func
    return self # for chaining</code></pre>
</details>
</dd>
<dt id="tinytroupe.steering.intervention.Intervention.set_functional_precondition"><code class="name flex">
<span>def <span class="ident">set_functional_precondition</span></span>(<span>self, func)</span>
</code></dt>
<dd>
<div class="desc"><p>Set a precondition as a function, to be evaluated by the code.</p>
<h2 id="args">Args</h2>
<dl>
<dt><strong><code>func</code></strong> :&ensp;<code>function</code></dt>
<dd>the function of the precondition.
Must have the a single argument, targets (either a TinyWorld or TinyPerson, or a list). Must return a boolean.</dd>
</dl></div>
<details class="source">
<summary>
<span>Expand source code</span>
</summary>
<pre><code class="python">def set_functional_precondition(self, func):
    &#34;&#34;&#34;
    Set a precondition as a function, to be evaluated by the code.

    Args:
        func (function): the function of the precondition. 
          Must have the a single argument, targets (either a TinyWorld or TinyPerson, or a list). Must return a boolean.
    &#34;&#34;&#34;
    self.precondition_func = func
    return self # for chaining</code></pre>
</details>
</dd>
<dt id="tinytroupe.steering.intervention.Intervention.set_propositional_precondition"><code class="name flex">
<span>def <span class="ident">set_propositional_precondition</span></span>(<span>self, proposition: <a title="tinytroupe.experimentation.proposition.Proposition" href="../experimentation/proposition.html#tinytroupe.experimentation.proposition.Proposition">Proposition</a>, threshold: int = None)</span>
</code></dt>
<dd>
<div class="desc"><p>Set a propositional precondition using the Proposition class,
optionally with a score threshold.</p></div>
<details class="source">
<summary>
<span>Expand source code</span>
</summary>
<pre><code class="python">def set_propositional_precondition(self, proposition:Proposition, threshold:int=None):
    &#34;&#34;&#34;
    Set a propositional precondition using the Proposition class,
    optionally with a score threshold.
    &#34;&#34;&#34;
    
    self.propositional_precondition = proposition
    self.propositional_precondition_threshold = threshold
    return self</code></pre>
</details>
</dd>
<dt id="tinytroupe.steering.intervention.Intervention.set_textual_precondition"><code class="name flex">
<span>def <span class="ident">set_textual_precondition</span></span>(<span>self, text)</span>
</code></dt>
<dd>
<div class="desc"><p>Set a precondition as text, to be interpreted by a language model.</p>
<h2 id="args">Args</h2>
<dl>
<dt><strong><code>text</code></strong> :&ensp;<code>str</code></dt>
<dd>the text of the precondition</dd>
</dl></div>
<details class="source">
<summary>
<span>Expand source code</span>
</summary>
<pre><code class="python">def set_textual_precondition(self, text):
    &#34;&#34;&#34;
    Set a precondition as text, to be interpreted by a language model.

    Args:
        text (str): the text of the precondition
    &#34;&#34;&#34;
    self.text_precondition = text
    return self # for chaining</code></pre>
</details>
</dd>
</dl>
</dd>
<dt id="tinytroupe.steering.intervention.InterventionBatch"><code class="flex name class">
<span>class <span class="ident">InterventionBatch</span></span>
<span>(</span><span>interventions)</span>
</code></dt>
<dd>
<div class="desc"><p>A wrapper around multiple Intervention instances that allows chaining set_* methods.</p></div>
<details class="source">
<summary>
<span>Expand source code</span>
</summary>
<pre><code class="python">class InterventionBatch:
    &#34;&#34;&#34;
    A wrapper around multiple Intervention instances that allows chaining set_* methods.
    &#34;&#34;&#34;
    
    def __init__(self, interventions):
        self.interventions = interventions
    
    def __iter__(self):
        &#34;&#34;&#34;Makes the batch iterable and compatible with list()&#34;&#34;&#34;
        return iter(self.interventions)
        
    def set_textual_precondition(self, text):
        for intervention in self.interventions:
            intervention.set_textual_precondition(text)
        return self
        
    def set_functional_precondition(self, func):
        for intervention in self.interventions:
            intervention.set_functional_precondition(func)
        return self
        
    def set_effect(self, effect_func):
        for intervention in self.interventions:
            intervention.set_effect(effect_func)
        return self
        
    def set_propositional_precondition(self, proposition, threshold=None):
        for intervention in self.interventions:
            intervention.set_propositional_precondition(proposition, threshold)
        return self
        
    def as_list(self):
        &#34;&#34;&#34;Return the list of individual interventions.&#34;&#34;&#34;
        return self.interventions</code></pre>
</details>
<h3>Methods</h3>
<dl>
<dt id="tinytroupe.steering.intervention.InterventionBatch.as_list"><code class="name flex">
<span>def <span class="ident">as_list</span></span>(<span>self)</span>
</code></dt>
<dd>
<div class="desc"><p>Return the list of individual interventions.</p></div>
<details class="source">
<summary>
<span>Expand source code</span>
</summary>
<pre><code class="python">def as_list(self):
    &#34;&#34;&#34;Return the list of individual interventions.&#34;&#34;&#34;
    return self.interventions</code></pre>
</details>
</dd>
<dt id="tinytroupe.steering.intervention.InterventionBatch.set_effect"><code class="name flex">
<span>def <span class="ident">set_effect</span></span>(<span>self, effect_func)</span>
</code></dt>
<dd>
<div class="desc"></div>
<details class="source">
<summary>
<span>Expand source code</span>
</summary>
<pre><code class="python">def set_effect(self, effect_func):
    for intervention in self.interventions:
        intervention.set_effect(effect_func)
    return self</code></pre>
</details>
</dd>
<dt id="tinytroupe.steering.intervention.InterventionBatch.set_functional_precondition"><code class="name flex">
<span>def <span class="ident">set_functional_precondition</span></span>(<span>self, func)</span>
</code></dt>
<dd>
<div class="desc"></div>
<details class="source">
<summary>
<span>Expand source code</span>
</summary>
<pre><code class="python">def set_functional_precondition(self, func):
    for intervention in self.interventions:
        intervention.set_functional_precondition(func)
    return self</code></pre>
</details>
</dd>
<dt id="tinytroupe.steering.intervention.InterventionBatch.set_propositional_precondition"><code class="name flex">
<span>def <span class="ident">set_propositional_precondition</span></span>(<span>self, proposition, threshold=None)</span>
</code></dt>
<dd>
<div class="desc"></div>
<details class="source">
<summary>
<span>Expand source code</span>
</summary>
<pre><code class="python">def set_propositional_precondition(self, proposition, threshold=None):
    for intervention in self.interventions:
        intervention.set_propositional_precondition(proposition, threshold)
    return self</code></pre>
</details>
</dd>
<dt id="tinytroupe.steering.intervention.InterventionBatch.set_textual_precondition"><code class="name flex">
<span>def <span class="ident">set_textual_precondition</span></span>(<span>self, text)</span>
</code></dt>
<dd>
<div class="desc"></div>
<details class="source">
<summary>
<span>Expand source code</span>
</summary>
<pre><code class="python">def set_textual_precondition(self, text):
    for intervention in self.interventions:
        intervention.set_textual_precondition(text)
    return self</code></pre>
</details>
</dd>
</dl>
</dd>
</dl>
</section>
</article>
<nav id="sidebar">
<h1>Index</h1>
<div class="toc">
<ul></ul>
</div>
<ul id="index">
<li><h3>Super-module</h3>
<ul>
<li><code><a title="tinytroupe.steering" href="index.html">tinytroupe.steering</a></code></li>
</ul>
</li>
<li><h3><a href="#header-classes">Classes</a></h3>
<ul>
<li>
<h4><code><a title="tinytroupe.steering.intervention.Intervention" href="#tinytroupe.steering.intervention.Intervention">Intervention</a></code></h4>
<ul class="">
<li><code><a title="tinytroupe.steering.intervention.Intervention.apply_effect" href="#tinytroupe.steering.intervention.Intervention.apply_effect">apply_effect</a></code></li>
<li><code><a title="tinytroupe.steering.intervention.Intervention.check_precondition" href="#tinytroupe.steering.intervention.Intervention.check_precondition">check_precondition</a></code></li>
<li><code><a title="tinytroupe.steering.intervention.Intervention.create_for_each" href="#tinytroupe.steering.intervention.Intervention.create_for_each">create_for_each</a></code></li>
<li><code><a title="tinytroupe.steering.intervention.Intervention.execute" href="#tinytroupe.steering.intervention.Intervention.execute">execute</a></code></li>
<li><code><a title="tinytroupe.steering.intervention.Intervention.precondition_justification" href="#tinytroupe.steering.intervention.Intervention.precondition_justification">precondition_justification</a></code></li>
<li><code><a title="tinytroupe.steering.intervention.Intervention.set_effect" href="#tinytroupe.steering.intervention.Intervention.set_effect">set_effect</a></code></li>
<li><code><a title="tinytroupe.steering.intervention.Intervention.set_functional_precondition" href="#tinytroupe.steering.intervention.Intervention.set_functional_precondition">set_functional_precondition</a></code></li>
<li><code><a title="tinytroupe.steering.intervention.Intervention.set_propositional_precondition" href="#tinytroupe.steering.intervention.Intervention.set_propositional_precondition">set_propositional_precondition</a></code></li>
<li><code><a title="tinytroupe.steering.intervention.Intervention.set_textual_precondition" href="#tinytroupe.steering.intervention.Intervention.set_textual_precondition">set_textual_precondition</a></code></li>
</ul>
</li>
<li>
<h4><code><a title="tinytroupe.steering.intervention.InterventionBatch" href="#tinytroupe.steering.intervention.InterventionBatch">InterventionBatch</a></code></h4>
<ul class="">
<li><code><a title="tinytroupe.steering.intervention.InterventionBatch.as_list" href="#tinytroupe.steering.intervention.InterventionBatch.as_list">as_list</a></code></li>
<li><code><a title="tinytroupe.steering.intervention.InterventionBatch.set_effect" href="#tinytroupe.steering.intervention.InterventionBatch.set_effect">set_effect</a></code></li>
<li><code><a title="tinytroupe.steering.intervention.InterventionBatch.set_functional_precondition" href="#tinytroupe.steering.intervention.InterventionBatch.set_functional_precondition">set_functional_precondition</a></code></li>
<li><code><a title="tinytroupe.steering.intervention.InterventionBatch.set_propositional_precondition" href="#tinytroupe.steering.intervention.InterventionBatch.set_propositional_precondition">set_propositional_precondition</a></code></li>
<li><code><a title="tinytroupe.steering.intervention.InterventionBatch.set_textual_precondition" href="#tinytroupe.steering.intervention.InterventionBatch.set_textual_precondition">set_textual_precondition</a></code></li>
</ul>
</li>
</ul>
</li>
</ul>
</nav>
</main>
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