Spaces:
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Sleeping
Refactor prompt management into separate class
Browse files- app.py +8 -17
- prompt_manager.py +133 -0
app.py
CHANGED
@@ -7,9 +7,13 @@ import chainlit as cl # importing chainlit for our app
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from chainlit.prompt import Prompt, PromptMessage # importing prompt tools
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from chainlit.playground.providers import ChatOpenAI # importing ChatOpenAI tools
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from dotenv import load_dotenv
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load_dotenv()
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# Aspect descriptions and examples
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ASPECT_INFO = {
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"Concept Simplification": {
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@@ -125,19 +129,16 @@ USER_TEMPLATES = {
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@cl.on_chat_start
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async def start_chat():
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# Create aspect selection buttons with descriptions
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aspects =
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actions = []
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for aspect in aspects:
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info = ASPECT_INFO[aspect]
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description = f"{info['description']}\n\nExample tasks:\n" + "\n".join(f"• {example}" for example in info['examples'])
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actions.append(
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cl.Action(
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name=aspect,
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value=aspect,
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label=aspect,
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description=
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)
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)
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@@ -157,18 +158,9 @@ async def on_action(action):
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# Store the selected aspect in the user session
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cl.user_session.set("selected_aspect", action.value)
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# Get aspect info for the confirmation message
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info = ASPECT_INFO[action.value]
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examples = "\n".join(f"• {example}" for example in info['examples'][:2]) # Show first two examples
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# Send confirmation message with examples
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await cl.Message(
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content=
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{info['description']}
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Try asking something like:
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{examples}"""
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).send()
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@cl.on_message
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@@ -194,8 +186,7 @@ async def main(message: cl.Message):
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client = AsyncOpenAI()
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# Get the appropriate templates for the selected aspect
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system_template =
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user_template = USER_TEMPLATES[selected_aspect]
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prompt = Prompt(
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provider=ChatOpenAI.id,
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from chainlit.prompt import Prompt, PromptMessage # importing prompt tools
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from chainlit.playground.providers import ChatOpenAI # importing ChatOpenAI tools
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from dotenv import load_dotenv
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from prompt_manager import PromptManager
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load_dotenv()
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# Initialize prompt manager
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prompt_manager = PromptManager()
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# Aspect descriptions and examples
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ASPECT_INFO = {
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"Concept Simplification": {
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@cl.on_chat_start
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async def start_chat():
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# Create aspect selection buttons with descriptions
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aspects = prompt_manager.get_aspect_names()
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actions = []
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for aspect in aspects:
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actions.append(
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cl.Action(
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name=aspect,
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value=aspect,
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label=aspect,
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description=prompt_manager.get_action_description(aspect)
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)
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)
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# Store the selected aspect in the user session
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cl.user_session.set("selected_aspect", action.value)
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# Send confirmation message with examples
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await cl.Message(
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content=prompt_manager.get_confirmation_message(action.value)
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).send()
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@cl.on_message
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client = AsyncOpenAI()
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# Get the appropriate templates for the selected aspect
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system_template, user_template = prompt_manager.get_templates(selected_aspect)
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prompt = Prompt(
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provider=ChatOpenAI.id,
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prompt_manager.py
ADDED
@@ -0,0 +1,133 @@
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from dataclasses import dataclass
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from typing import Dict, List
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@dataclass
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class AspectInfo:
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description: str
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examples: List[str]
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system_template: str
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user_template: str
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class PromptManager:
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def __init__(self):
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self.aspects = {
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"Concept Simplification": AspectInfo(
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description="Break down complex topics into simple, understandable terms",
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examples=[
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"Explain quantum computing in simple terms",
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"How does blockchain work?",
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"What is machine learning?"
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],
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system_template="""You are an expert at breaking down complex concepts into simple, understandable terms.
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Your goal is to make difficult topics accessible while maintaining accuracy.
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Always use clear examples and analogies to illustrate points.""",
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user_template="""Please help me understand this concept: {input}
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- What are the key components?
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- Can you provide a simple analogy?
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- What are common misconceptions?"""
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),
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"Summarization": AspectInfo(
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description="Extract and present key information concisely",
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examples=[
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"Summarize the key points of climate change",
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"Give me a brief overview of the internet's history",
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"What are the main ideas in this article?"
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],
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system_template="""You are a skilled summarizer who can extract key information and present it concisely.
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Focus on the most important points while maintaining context.
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Structure your summaries in a clear, logical manner.""",
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user_template="""Please summarize this information: {input}
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- What are the main points?
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- What's the key takeaway?
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- What context is important to retain?"""
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),
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"Creativity": AspectInfo(
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description="Generate innovative ideas and unique perspectives",
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examples=[
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"Generate ideas for a sustainable city",
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"How could we improve remote work?",
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"What are some creative solutions to reduce plastic waste?"
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],
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system_template="""You are a creative thinker who can generate innovative ideas and solutions.
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Think outside the box while staying relevant to the topic.
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Encourage creative exploration and unique perspectives.""",
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user_template="""Let's explore this creatively: {input}
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- What are some unique perspectives?
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- How can we approach this differently?
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- What innovative solutions can we consider?"""
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),
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"Narrative Structure": AspectInfo(
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description="Organize information into compelling stories",
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examples=[
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"Help me structure a story about time travel",
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"Organize the history of AI as a narrative",
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"How can I make this presentation more engaging?"
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],
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system_template="""You are an expert in storytelling and narrative organization.
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Help structure information in a compelling, story-like format.
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Focus on flow, progression, and engagement in your responses.""",
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user_template="""Help me structure this as a narrative: {input}
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- What's the main story arc?
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- How can we make it more engaging?
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- What elements would enhance the flow?"""
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),
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"Arithmetic Reasoning": AspectInfo(
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description="Solve mathematical problems step by step",
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examples=[
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"Calculate compound interest on $1000 at 5% for 3 years",
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"If a train travels at 60 mph for 2.5 hours, how far does it go?",
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"What's the probability of getting three heads in a row?"
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],
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system_template="""You are a mathematical reasoning expert who can solve problems step by step.
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Break down complex calculations into manageable parts.
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Explain your mathematical thinking clearly and thoroughly.""",
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user_template="""Let's solve this step by step: {input}
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- What's the first step?
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- What formulas or methods should we use?
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- How can we verify the answer?"""
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),
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"Conversational Tone": AspectInfo(
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description="Engage in natural, friendly discussions",
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examples=[
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"Tell me about your favorite book",
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"What's your opinion on artificial intelligence?",
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"How do you feel about remote work?"
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],
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system_template="""You are a friendly and engaging conversational partner.
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Maintain a natural, warm tone while being informative.
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Adapt your communication style to match the user's level of expertise.""",
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user_template="""Let's discuss this: {input}
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- What's your perspective?
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- Can you explain this in simple terms?
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- How does this relate to everyday experience?"""
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)
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}
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def get_aspect_names(self) -> List[str]:
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"""Get list of available aspect names."""
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return list(self.aspects.keys())
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def get_aspect_info(self, aspect_name: str) -> AspectInfo:
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"""Get information for a specific aspect."""
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return self.aspects[aspect_name]
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def get_action_description(self, aspect_name: str) -> str:
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"""Get formatted description for action button."""
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info = self.aspects[aspect_name]
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return f"{info.description}\n\nExample tasks:\n" + "\n".join(f"• {example}" for example in info.examples)
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def get_confirmation_message(self, aspect_name: str) -> str:
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"""Get formatted confirmation message for selected aspect."""
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info = self.aspects[aspect_name]
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examples = "\n".join(f"• {example}" for example in info.examples[:2])
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return f"""You've selected: {aspect_name}
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{info.description}
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Try asking something like:
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{examples}"""
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def get_templates(self, aspect_name: str) -> tuple[str, str]:
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"""Get system and user templates for an aspect."""
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info = self.aspects[aspect_name]
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return info.system_template, info.user_template
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