tools.py

from langchain.tools import Tool
from langchain_community.tools import DuckDuckGoSearchRun
from langgraph.store.memory import InMemoryStore
import random
from huggingface_hub import list_models


# Initialize the DuckDuckGo search tool
search_tool = DuckDuckGoSearchRun()

# Initialize the memory store
store = InMemoryStore(index={"embed": "openai:text-embedding-3-small"})

# Define the weather information tool
def get_weather_info(location: str) -> str:
    """Fetches dummy weather information for a given location."""
    weather_conditions = [
        {"condition": "Rainy", "temp_c": 15},
        {"condition": "Clear", "temp_c": 25},
        {"condition": "Windy", "temp_c": 20}
    ]
    data = random.choice(weather_conditions)
    return f"Weather in {location}: {data['condition']}, {data['temp_c']}°C"

weather_info_tool = Tool(
    name="get_weather_info",
    func=get_weather_info,
    description="Fetches dummy weather information for a given location."
)

# Define the Hub stats tool
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",
    func=get_hub_stats,
    description="Fetches the most downloaded model from a specific author on the Hugging Face Hub."
)

# Define the memory management tool
def memory_management(query: str) -> str:
    """Manages and queries conversation memory."""
    results = store.retrieve(query)
    if results:
        return "\n\n".join(results)
    else:
        return "No relevant memory found."

memory_management_tool = Tool(
    name="memory_management",
    func=memory_management,
    description="Manages and queries conversation memory."
)


def duckduckgo_search(query: str) -> str:
    """Searches the web for information."""
    return search_tool.run(query)

duckduckgo_search_tool = Tool(
    name="duckduckgo_search",
    func=duckduckgo_search,
    description="Searches the web for information."
)

# manage_memory_tool = create_manage_memory_tool(namespace=("memories",))
# search_memory_tool = create_search_memory_tool(namespace=("memories",))