| from langchain_community.retrievers import BM25Retriever
|
| from langchain.tools import Tool
|
| from langchain_community.tools import DuckDuckGoSearchRun
|
| from huggingface_hub import list_models
|
| import random
|
| from retriever import docs
|
| import requests
|
|
|
|
|
| bm25_retriever = BM25Retriever.from_documents(docs)
|
|
|
| def extract_text(query: str) -> str:
|
| """Retrieves detailed information about gala guests based on their name or relation."""
|
| results = bm25_retriever.invoke(query)
|
| if results:
|
| return "\n\n".join([doc.page_content for doc in results[:3]])
|
| else:
|
| return "No matching guest information found."
|
|
|
| guest_info_tool = Tool(
|
| name="guest_info_retriever",
|
| func=extract_text,
|
| description="Retrieves detailed information about gala guests based on their name or relation."
|
| )
|
|
|
|
|
|
|
| search_tool = DuckDuckGoSearchRun()
|
|
|
|
|
| def get_weather_info(location: str) -> str:
|
| """Fetches weather information from wttr.in for a given location."""
|
| url = f"https://wttr.in/{location}?format=3"
|
| try:
|
| response = requests.get(url, timeout=10)
|
| return response.text
|
| except Exception as e:
|
| return f"Error fetching weather: {str(e)}"
|
|
|
|
|
| weather_info_tool = Tool(
|
| name="get_weather_info",
|
| func=get_weather_info,
|
| description="Fetches dummy weather information for a given location."
|
| )
|
|
|
|
|
|
|
| def get_hub_stats(author: str) -> str:
|
| """Fetches the most downloaded model from a specific author on the Hugging Face Hub."""
|
| try:
|
|
|
| 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)}"
|
|
|
|
|
| hub_stats_tool = Tool(
|
| name="get_hub_stats",
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| func=get_hub_stats,
|
| description="Fetches the most downloaded model from a specific author on the Hugging Face Hub."
|
| ) |