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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
from tools.final_answer import FinalAnswerTool
from Gradio_UI import GradioUI
from googleapiclient.discovery import build
import os
from dotenv import load_dotenv
import uuid
# Google Books API setup
os.environ["GOOGLE_APPLICATION_CREDENTIALS"] = "/home/user/app/audiobookagent-aaf910cd6329.json"
google_api_key = os.getenv("AIzaSyDOxfDDznu39CSWR3wlGK-eEV2XH2zoGf4")
books_service = build("books", "v1", developerKey=google_api_key)
# I want to try connect to a google API to get some recommendation of audiobooks!
@tool
def search_audiobooks(topic: str, limit: int = 3)-> list[dict[str, any]]: #it's import to specify the return type
#Keep this format for the description / args / args description but feel free to modify the tool
"""The tool is designed to connect to the google API platform and retrieve some audiobooks recommendations
Args:
topic: the topic that I would like to use to retieve some audiobooks
limit: it is a constant as I want to recommend only three audiobooks
"""
request = books_service.volumes().list(
q=f"subject:{topic}+audiobook",
maxResults=limit,
printType="books",
gl="us"
)
response = request.execute()
audiobooks = []
for item in response.get("items", []):
volume_info = item.get("volumeInfo", {})
# Check if audiobook (based on categories or accessInfo)
if "Audiobook" in volume_info.get("categories", []) or volume_info.get("accessInfo", {}).get("epub", {}).get("isAvailable", False):
audiobooks.append({
"title": volume_info.get("title", "Unknown"),
"author": ", ".join(volume_info.get("authors", ["Unknown"])),
"categories": ", ".join(volume_info.get("categories", ["Unknown"])),
"url": volume_info.get("canonicalVolumeLink", "#"),
"estimated_minutes": volume_info.get("pageCount", 180) # Estimate: 1 page ≈ 1 minute
})
return audiobooks
@tool
# Function to estimate if audiobook fits time constraint
def filter_by_time(audiobooks: list[dict[str, any]], free_time: str) -> list[dict[str, any]]:
"""The tool is designed to match the time in terms of duration of the audiobook which is called estimated_minutes and the free time that the person have
Args:
audiobooks: the list of the audiobooks
free_time: The free time the person inform
"""
try:
if "hour" in free_time.lower():
hours = float(free_time.split()[0])
max_minutes = hours * 60
else:
max_minutes = float(free_time.split()[0])
except:
max_minutes = 180 # Default to 3 hours
return [book for book in audiobooks if book["estimated_minutes"] <= max_minutes]
@tool
def get_current_time_in_timezone(timezone: str) -> str:
"""A tool that fetches the current local time in a specified timezone.
Args:
timezone: A string representing a valid timezone (e.g., 'America/New_York').
"""
try:
# Create timezone object
tz = pytz.timezone(timezone)
# Get current time in that 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)}"
final_answer = FinalAnswerTool()
# If the agent does not answer, the model is overloaded, please use another model or the following Hugging Face Endpoint that also contains qwen2.5 coder:
# model_id='https://pflgm2locj2t89co.us-east-1.aws.endpoints.huggingface.cloud'
model = HfApiModel(
max_tokens=2096,
temperature=0.5,
model_id='Qwen/Qwen2.5-Coder-32B-Instruct',# it is possible that this model may be overloaded
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)
prompt_templates["final_answer"] = "Final answer: {answer}"
agent = CodeAgent(
model=model,
tools=[final_answer,search_audiobooks,get_current_time_in_timezone,filter_by_time], ## add your tools here (don't remove final answer)
max_steps=6,
verbosity_level=1,
grammar=None,
planning_interval=None,
name=None,
description=None,
prompt_templates=prompt_templates
)
GradioUI(agent).launch()