Spaces:
Sleeping
Sleeping
File size: 4,404 Bytes
3629f64 f67e05d 3629f64 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 |
from smolagents import CodeAgent,DuckDuckGoSearchTool, HfApiModel,load_tool,tool
import datetime
import requests
import pytz
import yaml
import random
from tools.final_answer import FinalAnswerTool
from Gradio_UI import GradioUI
@tool
def get_word_prompt(die_roll: str) -> str:
"""A tool that generates a random word prompt based on a 3d6 roll.
Args:
die_roll: A string representing the result of the roll (e.g. "111", "222", "333", ..., "666").
"""
# read the word_prompts.csv
dict_word_prompts = {}
with open("word_prompts.csv", "r") as f:
lines = f.readlines()
dict_word_prompts = {line.split(",")[0]: line.split(",")[1].strip() for line in lines}
# get the word prompt based on the die roll
word_prompt = dict_word_prompts.get(die_roll)
if word_prompt:
return f"Your word prompt is: \"{word_prompt}\""
else:
return f"Invalid die roll '{die_roll}'. Please provide a valid 3d6 roll (e.g., '111', '222', '333', ..., '666')."
@tool
def get_oracle_result(likelihood_of_favorable_outcome: str) -> str:
"""A tool that provides a yes/no answer based on a likelihood of a favorable outcome.
Args:
likelihood_of_favorable_outcome: A string representing the likelihood of a favorable outcome. Choose only: "low", "medium", or "high".
"""
# critical is 2 6s
is_critical = False
if likelihood_of_favorable_outcome == "low":
# roll 1d6
roll = str(random.randint(1, 6))
elif likelihood_of_favorable_outcome == "medium":
# roll 2d6
rolls = [random.randint(1, 6), random.randint(1, 6)]
roll = max(rolls)
if rolls == [6, 6]:
is_critical = True
elif likelihood_of_favorable_outcome == "high":
# roll 3d6
rolls = [str(random.randint(1, 6), random.randint(1, 6), random.randint(1, 6))]
roll = max(rolls)
if rolls.count(6) >= 2:
is_critical = True
# now we have the roll, let's return the result
if roll == "6":
if is_critical:
return "Yes, and it's a critical success! You did it, plus another favorable outcome."
else:
return "Yes, and it's a success! You did it without any negative consequences."
elif roll >= 4:
return "Yes, but it's a partial success. You did it, but there are some minor negative consequences"
elif roll == 3:
return "No, because... Work with the GM to find out why."
elif roll == 2:
return "No, it failed. There are negative consequences."
else:
return "No. That's a critical failure. There are negative consequences, plus something else goes wrong."
@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_oracle_result, get_word_prompt],
max_steps=6,
verbosity_level=1,
grammar=None,
planning_interval=None,
name=None,
description=None,
prompt_templates=prompt_templates
)
GradioUI(agent).launch() |