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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 smolagents import GradioUI
from smolagents import LiteLLMModel
import os
import litellm
litellm._turn_on_debug()
# 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 import 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 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)}"
@tool
def crypto_analysis(crypto_name: str) -> str:
"""
Fetches current cryptocurrency data for a given crypto currency name use the data extracted to perform crypto analysis.
Args:
crypto_name: The crypto currency id (e.g., 'bitcoin')
Returns:
A JSON-formatted string containing the crypto analysis if successful,
otherwise an error message
"""
url = f"https://rest.coincap.io/v3/assets/{crypto_name}?apiKey={os.getenv(key='coincap_api')}"
search_tool = DuckDuckGoSearchTool()
output = ""
try:
response = requests.get(url)
response.raise_for_status() # Raise exception for bad status codes
data = response.json()
crypto_info = data["data"]
return crypto_info
except Exception as e:
raise f"Error: {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='meta-llama/Llama-3.1-8B-Instruct',# it is possible that this model may be overloaded
# custom_role_conversions=None,
# )
model = LiteLLMModel(model_id="gemini/gemini-2.0-flash-lite", api_key=os.getenv(key="gemini_api"))
# model = LiteLLMModel(
# model_id="ollama_chat/qwen2:7b", # Or try other Ollama-supported models
# api_base=os.getenv(key='ollama_server_ip'), # Default Ollama local server
# num_ctx=8192,
# )
# 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,crypto_analysis,image_generation_tool], ## 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()