File size: 2,672 Bytes
9b5b26a
012ad49
9b5b26a
 
 
c19d193
6aae614
8fe992b
9b5b26a
 
 
 
012ad49
 
 
9b5b26a
012ad49
 
 
 
 
 
 
 
 
9b5b26a
012ad49
 
 
 
 
 
 
 
 
 
 
 
 
 
 
8c01ffb
 
6aae614
012ad49
ae7a494
 
 
 
e121372
bf6d34c
 
29ec968
fe328e0
13d500a
8c01ffb
 
9b5b26a
 
8c01ffb
861422e
 
9b5b26a
8c01ffb
8fe992b
012ad49
8c01ffb
 
 
 
 
 
861422e
8fe992b
 
9b5b26a
8c01ffb
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
from smolagents import CodeAgent,DuckDuckGoSearchTool, HfApiModel,load_tool,tool
from typing import Dict
import datetime
import requests
import pytz
import yaml
from tools.final_answer import FinalAnswerTool

from Gradio_UI import GradioUI


@tool
def calculate_bandwidth(users: int, usage: Dict[str, int]) -> float:
    """Calculate the recommended internet speed based on user inputs.
    
    Args:
        users: The total number of users requiring internet access.
        usage: A dictionary with usage categories as keys and the number of users per category as values.
               Expected keys are:
                   - "browsing": Number of users browsing the web.
                   - "video_call": Number of users on video calls.
                   - "hd_streaming": Number of users streaming in HD.
                   - "4k_streaming": Number of users streaming in 4K.
                   - "gaming": Number of users gaming online.
                   - "remote_work": Number of users working remotely.
    """
    usage_requirements = {
        "browsing": 1,        # Mbps per user
        "video_call": 2,      # Mbps per user
        "hd_streaming": 5,    # Mbps per user
        "4k_streaming": 25,   # Mbps per user
        "gaming": 10,         # Mbps per user
        "remote_work": 3      # Mbps per user
    }
    
    total_bandwidth = sum(usage_requirements[activity] * usage.get(activity, 0) for activity in usage_requirements)
    overhead = 1.2  # 20% overhead for seamless experience
    # Apply overhead of 1.2
    total_bandwidth_with_overhead = total_bandwidth * overhead

    return round(total_bandwidth_with_overhead, 2)


final_answer = FinalAnswerTool()
#duck_duck_go_search = DuckDuckGoSearchTool()

# 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,calculate_bandwidth], ## Internet bandwidth Calculator Tool
    max_steps=6,
    verbosity_level=1,
    grammar=None,
    planning_interval=None,
    name=None,
    description=None,
    prompt_templates=prompt_templates
)


GradioUI(agent).launch()