Unit_3_Agentic_RAG / tools.py
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from smolagents import DuckDuckGoSearchTool
from smolagents import Tool
import random
from huggingface_hub import list_models
import requests
# Initialize the DuckDuckGo search tool
#search_tool = DuckDuckGoSearchTool()
class WeatherInfoTool(Tool):
name = "weather_info"
description = "Fetches dummy weather information for a given location."
inputs = {
"location": {
"type": "string",
"description": "The location to get weather information for."
}
}
output_type = "string"
def forward(self, location: str):
# Dummy weather data
weather_conditions = [
{"condition": "Rainy", "temp_c": 15},
{"condition": "Clear", "temp_c": 25},
{"condition": "Windy", "temp_c": 20}
]
# Randomly select a weather condition
data = random.choice(weather_conditions)
return f"Weather in {location}: {data['condition']}, {data['temp_c']}°C"
class HubStatsTool(Tool):
name = "hub_stats"
description = "Fetches the most downloaded model from a specific author on the Hugging Face Hub."
inputs = {
"author": {
"type": "string",
"description": "The username of the model author/organization to find models from."
}
}
output_type = "string"
def forward(self, author: str):
try:
# List models from the specified author, sorted by downloads
models = list(list_models(author=author, sort="downloads", direction=-1, limit=1))
if models:
model = models[0]
return f"The most downloaded model by {author} is {model.id} with {model.downloads:,} downloads."
else:
return f"No models found for author {author}."
except Exception as e:
return f"Error fetching models for {author}: {str(e)}"
class NewsTool(Tool):
name = "get_latest_news"
description = "Fetches the latest news headlines about a given topic."
inputs = {
"topic": {
"type": "string",
"description": "The topic to search news for."
}
}
def forward(self, topic: str):
url = f"https://newsapi.org/v2/everything?q={topic}&apiKey=15768396aec7461d927ed37dfffa2f84"
response = requests.get(url)
data = response.json()
if "articles" in data and len(data["articles"]) > 0:
headlines = [a["title"] for a in data["articles"][:5]]
return "\n".join(headlines)
return "No recent news found."