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Update app.py
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from smolagents import CodeAgent, DuckDuckGoSearchTool, HfApiModel, load_tool, tool
import datetime
import requests
import pytz
import yaml
import os
from tools.final_answer import FinalAnswerTool
from Gradio_UI import GradioUI
@tool
def my_cutom_tool(arg1: str, arg2: int) -> str:
"""A tool that does nothing yet.
Args:
arg1: the first argument.
arg2: the second argument.
Returns:
A placeholder string.
"""
return "What magic will you build ?"
@tool
def get_current_time_in_timezone(timezone: str) -> str:
"""Fetches the current local time in a specified timezone.
Args:
timezone: A string representing a valid timezone (e.g., 'America/New_York').
Returns:
A string stating the current local time in the specified timezone.
"""
try:
tz = pytz.timezone(timezone)
local_time = datetime.datetime.now(tz).strftime("%Y-%m-%d %H:%M:%S")
return f"The current local time in {timezone} is: {local_time}"
except Exception as e:
return f"Error fetching time for timezone '{timezone}': {str(e)}"
# --- Helper function to fetch Spotify access token ---
def fetch_spotify_access_token() -> str:
"""
Retrieves an access token from Spotify using the Client Credentials Flow.
Returns:
A string containing the access token, or None if the request fails.
"""
url = "https://accounts.spotify.com/api/token"
headers = {"Content-Type": "application/x-www-form-urlencoded"}
data = {
"grant_type": "client_credentials",
"client_id": os.getenv("SPOTIFY_CLIENT_ID"),
"client_secret": os.getenv("SPOTIFY_CLIENT_SECRET")
}
response = requests.post(url, headers=headers, data=data)
if response.status_code == 200:
return response.json().get("access_token")
return None
# --- Mood Mapping Dictionary ---
# This dictionary maps mood words to Spotify recommendation parameters.
MOOD_MAPPING = {
"happy": {"target_valence": 0.9, "target_energy": 0.8, "seed_genres": ["pop"]},
"sad": {"target_valence": 0.2, "target_energy": 0.3, "seed_genres": ["acoustic"]},
"energetic": {"target_valence": 0.7, "target_energy": 0.9, "seed_genres": ["work-out"]},
"chill": {"target_valence": 0.6, "target_energy": 0.4, "seed_genres": ["chill"]}
}
@tool
def get_songs_by_mood(mood: str) -> str:
"""Fetches a playlist of songs based on a given mood using Spotify's Recommendations API.
Args:
mood: A string representing the desired mood (e.g., "happy", "sad", "energetic", "chill").
Returns:
A string containing a list of recommended songs, each on a new line in the format:
'Track Name - Artist Name'.
The function uses an internal mapping to convert the mood word into target parameters
(valence, energy) and a seed genre, then calls the Spotify Recommendations endpoint.
"""
# Retrieve Spotify access token
access_token = fetch_spotify_access_token()
if not access_token:
return "Error: Unable to retrieve Spotify access token."
# Get mapping for the specified mood; use default if not found
mapping = MOOD_MAPPING.get(mood.lower(), {"target_valence": 0.5, "target_energy": 0.5, "seed_genres": ["pop"]})
# Build parameters for the Spotify Recommendations API request
params = {
"seed_genres": ",".join(mapping["seed_genres"]),
"target_valence": mapping["target_valence"],
"target_energy": mapping["target_energy"],
"limit": 10
}
url = "https://api.spotify.com/v1/recommendations"
headers = {"Authorization": f"Bearer {access_token}"}
response = requests.get(url, headers=headers, params=params)
if response.status_code == 200:
tracks = response.json().get("tracks", [])
if not tracks:
return "No tracks found for the specified mood."
playlist = []
for track in tracks:
track_name = track.get("name")
artist_name = track.get("artists", [{}])[0].get("name", "Unknown")
playlist.append(f"{track_name} - {artist_name}")
return "\n".join(playlist)
else:
return f"Error: {response.json()}"
final_answer = FinalAnswerTool()
model = HfApiModel(
max_tokens=2096,
temperature=0.5,
model_id='https://wxknx1kg971u7k1n.us-east-1.aws.endpoints.huggingface.cloud',
custom_role_conversions=None,
)
# Import tool from Hub
image_generation_tool = load_tool("agents-course/text-to-image", trust_remote_code=True)
with open("prompts.yaml", 'r') as stream:
prompt_templates = yaml.safe_load(stream)
agent = CodeAgent(
model=model,
tools=[
final_answer,
my_cutom_tool,
get_current_time_in_timezone,
get_songs_by_mood
],
max_steps=6,
verbosity_level=1,
grammar=None,
planning_interval=None,
name=None,
description=None,
prompt_templates=prompt_templates
)
GradioUI(agent).launch()