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from smolagents.tools import Tool
from anthropic import Anthropic, HUMAN_PROMPT, AI_PROMPT
import os
from dotenv import load_dotenv
load_dotenv() # Loads variables from .env into environment
class MoodToNeedTool(Tool):
"""
A tool that converts user mood descriptions into vacation needs using an LLM.
Attributes:
model: A callable language model used to generate the output.
"""
name = "MoodToNeed"
inputs = {
"mood": {"type": "string", "description": "User's mood as text"},
}
output_type = "string"
description = "Converts user mood into a travel-related need."
def __init__(self, model: callable) -> None:
"""
Args:
model: A callable language model with a __call__(str) -> str interface.
"""
super().__init__()
self.model = model
def forward(self, mood: str) -> str:
"""
Generates a vacation need from a user mood string.
Args:
mood: A string describing the user's emotional state.
Returns:
A short string describing the travel-related need.
"""
prompt = (
f"Given the user's mood, suggest a travel need.\n"
f'Mood: "{mood}"\n'
f'Return only the need, no explanation.\n'
f'Example:\n'
f'Mood: "I am exhausted" → Need: "A calm wellness retreat"\n'
f'Mood: "{mood}"\n'
f'Need:'
)
response = self.model(prompt)
return response.strip()
client = Anthropic(api_key=os.getenv("ANTROPIC_KEY"))
def claude_mood_to_need_model(prompt: str) -> str:
message = client.messages.create(
model="claude-3-opus-20240229",
max_tokens=1024,
temperature=0.7,
messages=[
{"role": "user", "content": prompt}
]
)
return message.content[0].text |