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Running on Zero
Running on Zero
File size: 3,871 Bytes
b74e950 9b5b26a c19d193 8729146 6aae614 b74e950 8fe992b 9b5b26a 267acbc 9b5b26a 8c01ffb 6aae614 b74e950 ae7a494 32e31aa ae7a494 e121372 32e31aa 13d500a 8c01ffb 861422e 7ff6e0c 32e31aa 90ec736 32e31aa 90ec736 7ff6e0c 9b5b26a 8c01ffb 8fe992b b74e950 32e31aa b74e950 8c01ffb b74e950 32e31aa 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 | from smolagents import CodeAgent, HfApiModel,load_tool,tool
import datetime
import requests
import pytz
import yaml
import spaces
# Add dummy function to satisfy ZeroGPU startup check
@spaces.GPU(duration=1)
def dummy_gpu():
return None
from tools.final_answer import FinalAnswerTool
from tools.web_search import DuckDuckGoSearchTool
from tools.visit_webpage import VisitWebpageTool
from tools.markdown_movie_release_sorter import MarkdownMovieReleaseSorterTool
from Gradio_UI import GradioUI
@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()
search_tool = DuckDuckGoSearchTool()
visit_tool = VisitWebpageTool()
sorter_tool = MarkdownMovieReleaseSorterTool()
# Import tool from Hub
image_generation_tool = load_tool("agents-course/text-to-image", trust_remote_code=True)
# 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=0.2,
model_id="Qwen/Qwen2.5-Coder-32B-Instruct",
custom_role_conversions=None,
)
with open("prompts.yaml", 'r') as stream:
prompt_templates = yaml.safe_load(stream)
# Cinema radar instructions
custom_instructions = """
You are 'Cinema Radar', an automated assistant that finds upcoming theatrical movie releases.
STRICT OPERATIONAL RULES:
- NEVER run python's `input()` function. Use details directly from the user prompt.
- If no country is specified, default to Spain.
- NEVER put URL paths or slashes inside `site:`. Only use root domains (e.g., `site:sensacine.com`).
- Maximum 2 searches allowed. If search does not return release dates, directly call `visit_webpage` on:
- Spain: 'https://www.sensacine.com/peliculas/estrenos/'
- Global/US: 'https://www.rottentomatoes.com/browse/movies_coming_soon/'
- YOU MUST call `sorter_tool` on the collected dates before calling `final_answer`. Sorting dates manually in code or thought is forbidden.
STEP-BY-STEP WORKFLOW:
1. Identify the genre and country from the user request.
2. Run `web_search`:
- Spain example: `web_search(query="site:sensacine.com estrenos [genre] 2026")`
- Global example: `web_search(query="upcoming [genre] movies release dates 2026")`
3. Call `visit_webpage(url=...)` on the best calendar/aggregator link found.
4. Format the found movies into markdown bullet lines:
raw_text = \"\"\"
- Movie Title 1: 2026-10-24 - Notes
- Movie Title 2: 2026-11-15 - Notes
\"\"\"
5. Run: `sorted_releases = sorter_tool(markdown_text=raw_text)`
6. Pass `sorted_releases` with concise summaries into `final_answer`.
"""
# Append the custom instructions to the existing system_prompt template
prompt_templates["system_prompt"] += f"\n\n{custom_instructions}"
agent = CodeAgent(
model=model,
tools=[
get_current_time_in_timezone,
search_tool,
visit_tool,
sorter_tool,
final_answer
],
max_steps=10,
verbosity_level=1,
grammar=None,
planning_interval=None,
name=None,
description=None,
prompt_templates=prompt_templates,
additional_authorized_imports=["re", "json", "datetime", "math"]
)
GradioUI(agent).launch() |