Spaces:
Sleeping
Sleeping
File size: 5,354 Bytes
9b5b26a c19d193 6aae614 8fe992b 9b5b26a 5df72d6 d98032e 1fcde86 d98032e 9b5b26a 8c01ffb 7bee429 6aae614 ae7a494 e121372 bf6d34c 9019707 fe328e0 13d500a 703a7a1 9b5b26a 76673ae 1e3640f 861422e 9b5b26a 8c01ffb 8fe992b 76673ae 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 |
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
# 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 enhanced_translate(
text: str,
target_language: str,
source_language: str = "auto",
domain: str = "general",
preserve_formatting: bool = True
) -> str:
"""Translate text with advanced options.
Args:
text: Text to translate
target_language: Target language code (e.g., 'fr' for French)
source_language: Source language or 'auto' for detection
domain: Specialized domain ('general', 'medical', 'legal', 'technical')
preserve_formatting: Whether to maintain text formatting
"""
try:
# Could use different backends based on domain
# This example uses deep_translator but could be extended
from deep_translator import GoogleTranslator, DeepL
# Select appropriate service based on domain and languages
if domain == "general":
translator = GoogleTranslator(source=source_language, target=target_language)
elif domain in ["legal", "medical"] and target_language in ["en", "de", "fr"]:
# DeepL might be better for certain domain/language combinations
translator = DeepL(source=source_language, target=target_language, domain=domain)
else:
translator = GoogleTranslator(source=source_language, target=target_language)
# Handle formatting preservation
if preserve_formatting and "<" in text and ">" in text:
# Simple HTML handling (a more robust solution would use proper HTML parsing)
import re
# Extract tags and replace with placeholders
tags = re.findall(r'<[^>]+>', text)
for i, tag in enumerate(tags):
text = text.replace(tag, f"__TAG_{i}__")
# Translate the text without tags
translated = translator.translate(text)
# Restore tags
for i, tag in enumerate(tags):
translated = translated.replace(f"__TAG_{i}__", tag)
else:
translated = translator.translate(text)
return f"Translation ({domain} domain): {translated}"
except Exception as e:
return f"Translation failed: {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)}"
@tool
def generate_image(prompt: str) -> str:
"""
A tool that generates an image from a text prompt using Replicate's Stable Diffusion API.
Args:
prompt: A detailed text description of the image to generate.
Returns:
A URL of the generated image.
"""
try:
api_url = "https://replicate.com/api/models/stability-ai/stable-diffusion"
response = requests.post(api_url, json={"input": {"prompt": prompt}})
if response.status_code == 200:
return response.json().get("output", ["Image generation failed."])[0]
else:
return f"Error: {response.status_code} - {response.text}"
except Exception as e:
return f"Failed to generate image: {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='https://pflgm2locj2t89co.us-east-1.aws.endpoints.huggingface.cloud',# it is possible that this model may be overloaded
custom_role_conversions=None,
)
# Import tool from Hub
image_generation_tool = load_tool("m-ric/text-to-image", trust_remote_code=True)
search_tool = DuckDuckGoSearchTool()
with open("prompts.yaml", 'r') as stream:
prompt_templates = yaml.safe_load(stream)
agent = CodeAgent(
model=model,
tools=[final_answer,enhanced_translate,image_generation_tool,search_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() |