File size: 4,227 Bytes
9b5b26a
 
 
 
c19d193
6aae614
9a97e3e
8fe992b
9b5b26a
 
45236a5
 
 
4bcc31b
45236a5
 
 
 
 
 
 
 
 
 
 
 
 
 
4bcc31b
45236a5
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
2dfb143
45236a5
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
9b5b26a
45236a5
 
 
 
 
 
 
 
 
 
 
 
8fe992b
d81ee83
9b5b26a
d81ee83
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
from smolagents import CodeAgent,DuckDuckGoSearchTool, HfApiModel,load_tool,tool
import datetime
import requests
import pytz
import yaml
from tools.final_answer import FinalAnswerTool
import random

from Gradio_UI import GradioUI

# @tool
# def futuristic_profession_predictor(name: str) -> str:
#     """Predicts the person's profession in the year 2050 based on their name.
    
#     Args:
#         name: The name of the person.
#     """
#     professions = [
#         "Quantum Data Alchemist", 
#         "Neural Interface Designer", 
#         "AI-Powered Philosopher", 
#         "Martian Agriculture Specialist", 
#         "Virtual Reality Psychologist", 
#         "Holographic Content Creator", 
#         "Synthetic Biology Engineer",
#         "Time Travel Consultant",
#         "Cybersecurity Shaman"
#     ]
    
#     prediction = random.choice(professions)
#     return f"In the year 2050, {name} will be a {prediction}!"

# # 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 findLoveOfTwoNumbers(arg1:int, arg2:int)-> int:
#     """ A tool that returns Love of two numbers
#     Args:
#         arg1: the first argument
#         arg2: the second argument    
#     """
#     return arg1+arg2 - 20

# # Below is an example of a tool that does nothing. Amaze us with your creativity !
# @tool
# def personIdentifier(arg1:str)-> int: #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 identifies the person. For example, 
#     Task: Who is Ajit Kumar?
#     Answer: He is a professor at Shiv Nadar University.
    
#     Args:
#         arg1: the first argument
#     """
#     return "He is a professor at Shiv Nadar University"

# @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)
    
# agent = CodeAgent(
#     model=model,
#     #tools=[final_answer, image_generation_tool, DuckDuckGoSearchTool()], ## add your tools here (don't remove final answer)
#     tools = [final_answer, futuristic_profession_predictor, personIdentifier, findLoveOfTwoNumbers],
#     max_steps=20,
#     verbosity_level=1,
#     grammar=None,
#     planning_interval=None,
#     name=None,
#     description=None,
#     prompt_templates=prompt_templates
# )

from smolagents import CodeAgent, DuckDuckGoSearchTool, HfApiModel

agent2 = CodeAgent(tools=[DuckDuckGoSearchTool()], model=HfApiModel())

#agent.run("Search for the best music recommendations for a party at the Wayne's mansion.")


GradioUI(agent2).launch()