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<article id="content">
<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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