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	<main>
	<article id="content">
	<header>
	<h1 class="title">Module <code>tinytroupe.steering</code></h1>
	</header>
	<section id="section-intro">
	<details class="source">
	<summary>
	<span>Expand source code</span>
	</summary>
	<pre><code class="python">import logging
	logger = logging.getLogger("tinytroupe")

	###########################################################################
	# Exposed API
	###########################################################################
	from tinytroupe.steering.tiny_story import TinyStory
	from tinytroupe.steering.intervention import Intervention

	__all__ = ["TinyStory", "Intervention"]</code></pre>
	</details>
	</section>
	<section>
	<h2 class="section-title" id="header-submodules">Sub-modules</h2>
	<dl>
	<dt><code class="name"><a title="tinytroupe.steering.intervention" href="intervention.html">tinytroupe.steering.intervention</a></code></dt>
	<dd>
	<div class="desc"></div>
	</dd>
	<dt><code class="name"><a title="tinytroupe.steering.tiny_story" href="tiny_story.html">tinytroupe.steering.tiny_story</a></code></dt>
	<dd>
	<div class="desc"></div>
	</dd>
	</dl>
	</section>
	<section>
	</section>
	<section>
	</section>
	<section>
	<h2 class="section-title" id="header-classes">Classes</h2>
	<dl>
	<dt id="tinytroupe.steering.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):
	"""
	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
	"""

	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"Intervention {utils.fresh_id(self.__class__.__name__)}"
	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):
	"""
	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
	"""
	if not isinstance(targets, list):
	targets = [targets]

	interventions = [cls(target, first_n=first_n, last_n=last_n,
	name=f"{name}_{i}" if name else None)
	for i, target in enumerate(targets)]
	return InterventionBatch(interventions)

	def __call__(self):
	"""
	Execute the intervention.

	Returns:
	bool: whether the intervention effect was applied.
	"""
	return self.execute()

	def execute(self):
	"""
	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.
	"""
	logger.debug(f"Executing intervention: {self}")
	if self.check_precondition():
	self.apply_effect()
	logger.debug(f"Precondition was true, intervention effect was applied.")
	return True

	logger.debug(f"Precondition was false, intervention effect was not applied.")
	return False

	def check_precondition(self):
	"""
	Check if the precondition for the intervention is met.
	"""
	#
	# 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 >= 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):
	"""
	Apply the intervention's effects. This won't check the precondition,
	so it should be called after check_precondition.
	"""
	self.effect_func(self.targets)


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

	def set_textual_precondition(self, text):
	"""
	Set a precondition as text, to be interpreted by a language model.

	Args:
	text (str): the text of the precondition
	"""
	self.text_precondition = text
	return self # for chaining

	def set_functional_precondition(self, func):
	"""
	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.
	"""
	self.precondition_func = func
	return self # for chaining

	def set_effect(self, effect_func):
	"""
	Set the effect of the intervention.

	Args:
	effect (str): the effect function of the intervention
	"""
	self.effect_func = effect_func
	return self # for chaining

	def set_propositional_precondition(self, proposition:Proposition, threshold:int=None):
	"""
	Set a propositional precondition using the Proposition class,
	optionally with a score threshold.
	"""

	self.propositional_precondition = proposition
	self.propositional_precondition_threshold = threshold
	return self

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

	def precondition_justification(self):
	"""
	Get the justification for the precondition.
	"""
	justification = ""

	# text precondition justification
	if self._last_text_precondition_proposition is not None:
	justification += f"{self._last_text_precondition_proposition.justification} (confidence = {self._last_text_precondition_proposition.confidence})\n\n"

	# functional precondition justification
	if self.precondition_func is not None:
	if self._last_functional_precondition_check == True:
	justification += f"Functional precondition was met.\n\n"

	else:
	justification += "Preconditions do not appear to be met.\n\n"

	# propositional precondition justification
	if self.propositional_precondition is not None:
	if self._last_propositional_precondition_check == True:
	justification += f"Propositional precondition was met.\n\n"
	else:
	justification += "Propositional precondition was not met.\n\n"

	return justification

	return justification</code></pre>
	</details>
	<h3>Static methods</h3>
	<dl>
	<dt id="tinytroupe.steering.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>InterventionBatch</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):
	"""
	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
	"""
	if not isinstance(targets, list):
	targets = [targets]

	interventions = [cls(target, first_n=first_n, last_n=last_n,
	name=f"{name}_{i}" 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.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):
	"""
	Apply the intervention's effects. This won't check the precondition,
	so it should be called after check_precondition.
	"""
	self.effect_func(self.targets)</code></pre>
	</details>
	</dd>
	<dt id="tinytroupe.steering.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):
	"""
	Check if the precondition for the intervention is met.
	"""
	#
	# 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 >= 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.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):
	"""
	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.
	"""
	logger.debug(f"Executing intervention: {self}")
	if self.check_precondition():
	self.apply_effect()
	logger.debug(f"Precondition was true, intervention effect was applied.")
	return True

	logger.debug(f"Precondition was false, intervention effect was not applied.")
	return False</code></pre>
	</details>
	</dd>
	<dt id="tinytroupe.steering.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):
	"""
	Get the justification for the precondition.
	"""
	justification = ""

	# text precondition justification
	if self._last_text_precondition_proposition is not None:
	justification += f"{self._last_text_precondition_proposition.justification} (confidence = {self._last_text_precondition_proposition.confidence})\n\n"

	# functional precondition justification
	if self.precondition_func is not None:
	if self._last_functional_precondition_check == True:
	justification += f"Functional precondition was met.\n\n"

	else:
	justification += "Preconditions do not appear to be met.\n\n"

	# propositional precondition justification
	if self.propositional_precondition is not None:
	if self._last_propositional_precondition_check == True:
	justification += f"Propositional precondition was met.\n\n"
	else:
	justification += "Propositional precondition was not met.\n\n"

	return justification

	return justification</code></pre>
	</details>
	</dd>
	<dt id="tinytroupe.steering.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):
	"""
	Set the effect of the intervention.

	Args:
	effect (str): the effect function of the intervention
	"""
	self.effect_func = effect_func
	return self # for chaining</code></pre>
	</details>
	</dd>
	<dt id="tinytroupe.steering.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):
	"""
	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.
	"""
	self.precondition_func = func
	return self # for chaining</code></pre>
	</details>
	</dd>
	<dt id="tinytroupe.steering.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):
	"""
	Set a propositional precondition using the Proposition class,
	optionally with a score threshold.
	"""

	self.propositional_precondition = proposition
	self.propositional_precondition_threshold = threshold
	return self</code></pre>
	</details>
	</dd>
	<dt id="tinytroupe.steering.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):
	"""
	Set a precondition as text, to be interpreted by a language model.

	Args:
	text (str): the text of the precondition
	"""
	self.text_precondition = text
	return self # for chaining</code></pre>
	</details>
	</dd>
	</dl>
	</dd>
	<dt id="tinytroupe.steering.TinyStory"><code class="flex name class">
	<span>class <span class="ident">TinyStory</span></span>
	<span>(</span><span>environment: <a title="tinytroupe.environment.tiny_world.TinyWorld" href="../environment/tiny_world.html#tinytroupe.environment.tiny_world.TinyWorld">TinyWorld</a> = None, agent: <a title="tinytroupe.agent.tiny_person.TinyPerson" href="../agent/tiny_person.html#tinytroupe.agent.tiny_person.TinyPerson">TinyPerson</a> = None, purpose: str = 'Be a realistic simulation.', context: str = '', first_n=10, last_n=20, include_omission_info: bool = True)</span>
	</code></dt>
	<dd>
	<div class="desc"><p>Every simulation tells a story. This class provides helper mechanisms to help with crafting appropriate stories in TinyTroupe.</p>
	<p>Initialize the story. The story can be about an environment or an agent. It also has a purpose, which
	is used to guide the story generation. Stories are aware that they are related to simulations, so one can
	specify simulation-related purposes.</p>
	<h2 id="args">Args</h2>
	<dl>
	<dt><strong><code>environment</code></strong> :&ensp;<code>TinyWorld</code>, optional</dt>
	<dd>The environment in which the story takes place. Defaults to None.</dd>
	<dt><strong><code>agent</code></strong> :&ensp;<code>TinyPerson</code>, optional</dt>
	<dd>The agent in the story. Defaults to None.</dd>
	<dt><strong><code>purpose</code></strong> :&ensp;<code>str</code>, optional</dt>
	<dd>The purpose of the story. Defaults to "Be a realistic simulation.".</dd>
	<dt><strong><code>context</code></strong> :&ensp;<code>str</code>, optional</dt>
	<dd>The current story context. Defaults to "". The actual story will be appended to this context.</dd>
	<dt><strong><code>first_n</code></strong> :&ensp;<code>int</code>, optional</dt>
	<dd>The number of first interactions to include in the story. Defaults to 10.</dd>
	<dt><strong><code>last_n</code></strong> :&ensp;<code>int</code>, optional</dt>
	<dd>The number of last interactions to include in the story. Defaults to 20.</dd>
	<dt><strong><code>include_omission_info</code></strong> :&ensp;<code>bool</code>, optional</dt>
	<dd>Whether to include information about omitted interactions. Defaults to True.</dd>
	</dl></div>
	<details class="source">
	<summary>
	<span>Expand source code</span>
	</summary>
	<pre><code class="python">class TinyStory:
	"""
	Every simulation tells a story. This class provides helper mechanisms to help with crafting appropriate stories in TinyTroupe.
	"""


	def __init__(self, environment:TinyWorld=None, agent:TinyPerson=None, purpose:str="Be a realistic simulation.", context:str="",
	first_n=10, last_n=20, include_omission_info:bool=True) -> None:
	"""
	Initialize the story. The story can be about an environment or an agent. It also has a purpose, which
	is used to guide the story generation. Stories are aware that they are related to simulations, so one can
	specify simulation-related purposes.

	Args:
	environment (TinyWorld, optional): The environment in which the story takes place. Defaults to None.
	agent (TinyPerson, optional): The agent in the story. Defaults to None.
	purpose (str, optional): The purpose of the story. Defaults to "Be a realistic simulation.".
	context (str, optional): The current story context. Defaults to "". The actual story will be appended to this context.
	first_n (int, optional): The number of first interactions to include in the story. Defaults to 10.
	last_n (int, optional): The number of last interactions to include in the story. Defaults to 20.
	include_omission_info (bool, optional): Whether to include information about omitted interactions. Defaults to True.
	"""

	# exactly one of these must be provided
	if environment and agent:
	raise Exception("Either 'environment' or 'agent' should be provided, not both")
	if not (environment or agent):
	raise Exception("At least one of the parameters should be provided")

	self.environment = environment
	self.agent = agent

	self.purpose = purpose

	self.current_story = context

	self.first_n = first_n
	self.last_n = last_n
	self.include_omission_info = include_omission_info

	def start_story(self, requirements="Start some interesting story about the agents.", number_of_words:int=100, include_plot_twist:bool=False) -> str:
	"""
	Start a new story.
	"""

	rendering_configs = {
	"purpose": self.purpose,
	"requirements": requirements,
	"current_simulation_trace": self._current_story(),
	"number_of_words": number_of_words,
	"include_plot_twist": include_plot_twist
	}

	messages = utils.compose_initial_LLM_messages_with_templates("story.start.system.mustache", "story.start.user.mustache",
	base_module_folder="steering",
	rendering_configs=rendering_configs)
	next_message = openai_utils.client().send_message(messages, temperature=1.5)

	start = next_message["content"]

	self.current_story += utils.dedent(\
	f"""

	## The story begins

	{start}

	"""
	)

	return start

	def continue_story(self, requirements="Continue the story in an interesting way.", number_of_words:int=100, include_plot_twist:bool=False) -> str:
	"""
	Propose a continuation of the story.
	"""

	rendering_configs = {
	"purpose": self.purpose,
	"requirements": requirements,
	"current_simulation_trace": self._current_story(),
	"number_of_words": number_of_words,
	"include_plot_twist": include_plot_twist
	}

	messages = utils.compose_initial_LLM_messages_with_templates("story.continuation.system.mustache", "story.continuation.user.mustache",
	base_module_folder="steering",
	rendering_configs=rendering_configs)
	next_message = openai_utils.client().send_message(messages)#, temperature=1.5)

	continuation = next_message["content"]

	self.current_story += utils.dedent(\
	f"""

	## The story continues

	{continuation}

	"""
	)

	return continuation

	def _current_story(self) -> str:
	"""
	Get the current story.
	"""
	interaction_history = ""

	if self.agent is not None:
	interaction_history += self.agent.pretty_current_interactions(first_n=self.first_n, last_n=self.last_n, include_omission_info=self.include_omission_info)
	elif self.environment is not None:
	interaction_history += self.environment.pretty_current_interactions(first_n=self.first_n, last_n=self.last_n, include_omission_info=self.include_omission_info)

	tmp_current_story = self.current_story
	tmp_current_story += utils.dedent(\
	f"""

	## New simulation interactions to consider

	{interaction_history}

	"""
	)

	return tmp_current_story</code></pre>
	</details>
	<h3>Methods</h3>
	<dl>
	<dt id="tinytroupe.steering.TinyStory.continue_story"><code class="name flex">
	<span>def <span class="ident">continue_story</span></span>(<span>self, requirements='Continue the story in an interesting way.', number_of_words: int = 100, include_plot_twist: bool = False) ‑> str</span>
	</code></dt>
	<dd>
	<div class="desc"><p>Propose a continuation of the story.</p></div>
	<details class="source">
	<summary>
	<span>Expand source code</span>
	</summary>
	<pre><code class="python">def continue_story(self, requirements="Continue the story in an interesting way.", number_of_words:int=100, include_plot_twist:bool=False) -> str:
	"""
	Propose a continuation of the story.
	"""

	rendering_configs = {
	"purpose": self.purpose,
	"requirements": requirements,
	"current_simulation_trace": self._current_story(),
	"number_of_words": number_of_words,
	"include_plot_twist": include_plot_twist
	}

	messages = utils.compose_initial_LLM_messages_with_templates("story.continuation.system.mustache", "story.continuation.user.mustache",
	base_module_folder="steering",
	rendering_configs=rendering_configs)
	next_message = openai_utils.client().send_message(messages)#, temperature=1.5)

	continuation = next_message["content"]

	self.current_story += utils.dedent(\
	f"""

	## The story continues

	{continuation}

	"""
	)

	return continuation</code></pre>
	</details>
	</dd>
	<dt id="tinytroupe.steering.TinyStory.start_story"><code class="name flex">
	<span>def <span class="ident">start_story</span></span>(<span>self, requirements='Start some interesting story about the agents.', number_of_words: int = 100, include_plot_twist: bool = False) ‑> str</span>
	</code></dt>
	<dd>
	<div class="desc"><p>Start a new story.</p></div>
	<details class="source">
	<summary>
	<span>Expand source code</span>
	</summary>
	<pre><code class="python">def start_story(self, requirements="Start some interesting story about the agents.", number_of_words:int=100, include_plot_twist:bool=False) -> str:
	"""
	Start a new story.
	"""

	rendering_configs = {
	"purpose": self.purpose,
	"requirements": requirements,
	"current_simulation_trace": self._current_story(),
	"number_of_words": number_of_words,
	"include_plot_twist": include_plot_twist
	}

	messages = utils.compose_initial_LLM_messages_with_templates("story.start.system.mustache", "story.start.user.mustache",
	base_module_folder="steering",
	rendering_configs=rendering_configs)
	next_message = openai_utils.client().send_message(messages, temperature=1.5)

	start = next_message["content"]

	self.current_story += utils.dedent(\
	f"""

	## The story begins

	{start}

	"""
	)

	return start</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" href="../index.html">tinytroupe</a></code></li>
	</ul>
	</li>
	<li><h3><a href="#header-submodules">Sub-modules</a></h3>
	<ul>
	<li><code><a title="tinytroupe.steering.intervention" href="intervention.html">tinytroupe.steering.intervention</a></code></li>
	<li><code><a title="tinytroupe.steering.tiny_story" href="tiny_story.html">tinytroupe.steering.tiny_story</a></code></li>
	</ul>
	</li>
	<li><h3><a href="#header-classes">Classes</a></h3>
	<ul>
	<li>
	<h4><code><a title="tinytroupe.steering.Intervention" href="#tinytroupe.steering.Intervention">Intervention</a></code></h4>
	<ul class="">
	<li><code><a title="tinytroupe.steering.Intervention.apply_effect" href="#tinytroupe.steering.Intervention.apply_effect">apply_effect</a></code></li>
	<li><code><a title="tinytroupe.steering.Intervention.check_precondition" href="#tinytroupe.steering.Intervention.check_precondition">check_precondition</a></code></li>
	<li><code><a title="tinytroupe.steering.Intervention.create_for_each" href="#tinytroupe.steering.Intervention.create_for_each">create_for_each</a></code></li>
	<li><code><a title="tinytroupe.steering.Intervention.execute" href="#tinytroupe.steering.Intervention.execute">execute</a></code></li>
	<li><code><a title="tinytroupe.steering.Intervention.precondition_justification" href="#tinytroupe.steering.Intervention.precondition_justification">precondition_justification</a></code></li>
	<li><code><a title="tinytroupe.steering.Intervention.set_effect" href="#tinytroupe.steering.Intervention.set_effect">set_effect</a></code></li>
	<li><code><a title="tinytroupe.steering.Intervention.set_functional_precondition" href="#tinytroupe.steering.Intervention.set_functional_precondition">set_functional_precondition</a></code></li>
	<li><code><a title="tinytroupe.steering.Intervention.set_propositional_precondition" href="#tinytroupe.steering.Intervention.set_propositional_precondition">set_propositional_precondition</a></code></li>
	<li><code><a title="tinytroupe.steering.Intervention.set_textual_precondition" href="#tinytroupe.steering.Intervention.set_textual_precondition">set_textual_precondition</a></code></li>
	</ul>
	</li>
	<li>
	<h4><code><a title="tinytroupe.steering.TinyStory" href="#tinytroupe.steering.TinyStory">TinyStory</a></code></h4>
	<ul class="">
	<li><code><a title="tinytroupe.steering.TinyStory.continue_story" href="#tinytroupe.steering.TinyStory.continue_story">continue_story</a></code></li>
	<li><code><a title="tinytroupe.steering.TinyStory.start_story" href="#tinytroupe.steering.TinyStory.start_story">start_story</a></code></li>
	</ul>
	</li>
	</ul>
	</li>
	</ul>
	</nav>
	</main>
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