File size: 5,530 Bytes
9b5b26a
 
 
 
c19d193
6aae614
8fe992b
9b5b26a
 
8a10c10
 
 
d2943b1
089099f
5df72d6
9b5b26a
3d1237b
9b5b26a
 
 
 
 
 
 
 
8a10c10
 
 
 
dbfe74a
8a10c10
 
 
dbfe74a
 
 
8a10c10
 
 
6da24fc
dbfe74a
 
 
8a10c10
6da24fc
 
 
 
 
 
 
 
 
 
 
 
 
 
 
dbfe74a
 
 
13a73d4
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
ce140c3
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
9b5b26a
 
 
 
 
 
 
 
 
 
 
 
 
 
8c01ffb
 
6aae614
ae7a494
 
 
 
e121372
bf6d34c
 
29ec968
fe328e0
13d500a
8c01ffb
 
9b5b26a
 
8c01ffb
861422e
 
9b5b26a
8c01ffb
8fe992b
dbfe74a
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
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
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
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 kokoro import KPipeline
import soundfile as sf
import os
import numpy as np

# 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 ?"


# Initialize the Kokoro pipeline
pipeline = KPipeline(lang_code='a')  # 'a' stands for American English

@tool
def text_to_speech_kokoro(text: str, voice: str = 'af_heart', speed: float = 1.0) -> str:
    """Convert text to speech using the Kokoro-82M model.
    
    Args:
        text: The text to be converted to speech.
        voice: The voice to use for speech synthesis (default is 'af_heart').
        speed: The speed of the speech (default is 1.0).
    
    Returns:
        An AgentAudio object with the relative URL to the generated audio file.
    """
    try:
        # Generate speech audio
        generator = pipeline(text, voice=voice, speed=speed, split_pattern=r'\n+')
        audio_segments = []
        for _, _, audio in generator:
            audio_segments.append(audio)
        if not audio_segments:
            raise ValueError("No audio generated.")
        # Concatenate segments into one audio array
        full_audio = np.concatenate(audio_segments)
        sample_rate = 24000  # Kokoro outputs at 24 kHz
        # Ensure the static folder exists and save the file there
        os.makedirs("static", exist_ok=True)
        filename = os.path.join("static", "output.wav")
        sf.write(filename, full_audio, sample_rate)
        # Return an AgentAudio object pointing to the relative URL of the audio file
        from smolagents.agent_types import AgentAudio
        return AgentAudio(f"/static/output.wav")
    except Exception as e:
        return f"Error generating speech: {str(e)}"

@tool
def search_dad_jokes(term: str) -> str:
    """A tool that searches for dad jokes containing a specific term.
    Args:
        term: The keyword to search for in dad jokes.
    """
    try:
        headers = {
            "Accept": "application/json",
            "User-Agent": "YourAppName (https://yourappurl.com)"
        }
        response = requests.get(f"https://icanhazdadjoke.com/search?term={term}", headers=headers)
        data = response.json()
        if data['results']:
            jokes = [joke['joke'] for joke in data['results']]
            return f"Found {len(jokes)} jokes:\n" + "\n\n".join(jokes)
        else:
            return f"No jokes found for the term '{term}'."
    except Exception as e:
        return f"Error searching for jokes: {str(e)}"



@tool
def get_random_cocktail() -> str:
    """A tool that fetches a random cocktail recipe.
    """
    try:
        response = requests.get('https://www.thecocktaildb.com/api/json/v1/1/random.php')
        data = response.json()
        if data and 'drinks' in data:
            drink = data['drinks'][0]
            cocktail_name = drink['strDrink']
            ingredients = [drink[f'strIngredient{i}'] for i in range(1, 16) if drink[f'strIngredient{i}']]
            instructions = drink['strInstructions']
            return f"Cocktail: {cocktail_name}\nIngredients: {', '.join(ingredients)}\nInstructions: {instructions}"
        else:
            return "No cocktail found. Please try again."
    except Exception as e:
        return f"Error fetching random cocktail: {str(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()

# 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, get_current_time_in_timezone, get_random_cocktail, search_dad_jokes, text_to_speech_kokoro], ## 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()