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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 requests import Request, Session
from requests.exceptions import ConnectionError, Timeout, TooManyRedirects
import json
from Gradio_UI import GradioUI
verbose = True
if verbose: print("Running app.py")
# Below is an example of a tool that does nothing. Amaze us with your creativity !
@tool
def my_custom_tool(arg1:str, arg2:int)-> str: #it's important to specify the return type
#Keep this format for the description / args / args description but feel free to modify the tool
"""A tool that does nothing yet
Args:
arg1: the first argument
arg2: the second argument
"""
return "What magic will you build ?"
@tool
def fetch_active_crypto()-> str: #it's important to specify the return type
#Keep this format for the description / args / args description but feel free to modify the tool
"""A tool that fetches all active crypto by market cap in USD
"""
url = 'https://sandbox-api.coinmarketcap.com/v1/cryptocurrency/listings/latest'
parameters = {
'start':'1',
'limit':'5000',
'convert':'USD'
}
headers = {
'Accepts': 'application/json',
'X-CMC_PRO_API_KEY': 'b54bcf4d-1bca-4e8e-9a24-22ff2c3d462c',
}
session = requests.Session()
session.headers.update(headers)
try:
response = session.get(url, params=parameters)
data = json.loads(response.text)
return data
except (ConnectionError, Timeout, TooManyRedirects) as e:
return e
@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()
############# MODEL SELECTION ################################################
# 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='https://pflgm2locj2t89co.us-east-1.aws.endpoints.huggingface.cloud',# it is possible that this model may be overloaded
# custom_role_conversions=None,
# )
MODEL_IDS = [
#'https://wxknx1kg971u7k1n.us-east-1.aws.endpoints.huggingface.cloud/',
#'https://jc26mwg228mkj8dw.us-east-1.aws.endpoints.huggingface.cloud/',
# 'https://pflgm2locj2t89co.us-east-1.aws.endpoints.huggingface.cloud'
#'meta-llama/Llama-3.2-1B-Instruct', ## Does a poor job of interpreting my questions and matching them to the tools
'Qwen/Qwen2.5-Coder-32B-Instruct',
'Qwen/Qwen2.5-Coder-14B-Instruct',
'Qwen/Qwen2.5-Coder-7B-Instruct',
'Qwen/Qwen2.5-Coder-3B-Instruct',
'Qwen/Qwen2.5-Coder-1.5B-Instruct'
# Add here wherever model is working for you
]
def is_model_overloaded(model_url):
"""Verify if the model is overloaded doing a test call."""
try:
response = requests.post(model_url, json={"inputs": "Test"})
if verbose:
print(response.status_code)
if response.status_code == 503: # 503 Service Unavailable = Overloaded
return True
if response.status_code == 404: # 404 Client Error: Not Found
return True
if response.status_code == 424: # 424 Client Error: Failed Dependency for url:
return True
return False
except requests.RequestException:
return True # if there are an error is overloaded
def get_available_model():
"""Select the first model available from the list."""
for model_url in MODEL_IDS:
print("trying",model_url)
if not is_model_overloaded(model_url):
return model_url
return MODEL_IDS[0] # if all are failing, use the first model by dfault
if verbose: print("Checking available models.")
selected_model_id = get_available_model()
model = HfApiModel(
max_tokens=104800000,
temperature=0.5,
#model_id='meta-llama/Llama-3.2-1B-Instruct',
#model_id='Qwen/Qwen2.5-Coder-32B-Instruct',
#model_id = 'Qwen/Qwen2.5-Coder-1.5B-Instruct',
model_id = selected_model_id, # model available selected from the list automatically
custom_role_conversions=None,
)
############# END: MODEL SELECTION ################################################
# 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, image_generation_tool, get_current_time_in_timezone, fetch_active_crypto], ## 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() |