Spaces:
Running
Running
new tools
Browse files
app.py
CHANGED
@@ -13,6 +13,8 @@ import datasets
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from langchain.docstore.document import Document
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from langgraph.graph import START, StateGraph
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from langchain_community.retrievers import BM25Retriever
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HUGGINGFACEHUB_API_TOKEN = os.environ["HUGGINGFACEHUB_API_TOKEN"]
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login(token=HUGGINGFACEHUB_API_TOKEN, add_to_git_credential=True)
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@@ -99,7 +101,50 @@ guest_info_tool = Tool(
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description="Retrieves detailed information about gala guests based on their name or relation."
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)
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chat_with_tools = model.bind_tools(tools)
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# Generate the AgentState and Agent graph
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from langchain.docstore.document import Document
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from langgraph.graph import START, StateGraph
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from langchain_community.retrievers import BM25Retriever
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from langchain_community.tools import DuckDuckGoSearchRun
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HUGGINGFACEHUB_API_TOKEN = os.environ["HUGGINGFACEHUB_API_TOKEN"]
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login(token=HUGGINGFACEHUB_API_TOKEN, add_to_git_credential=True)
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description="Retrieves detailed information about gala guests based on their name or relation."
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)
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search_tool = DuckDuckGoSearchRun()
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def get_weather_info(location: str) -> str:
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"""Fetches dummy weather information for a given location."""
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# Dummy weather data
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weather_conditions = [
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{"condition": "Rainy", "temp_c": 15},
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{"condition": "Clear", "temp_c": 25},
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{"condition": "Windy", "temp_c": 20}
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]
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# Randomly select a weather condition
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data = random.choice(weather_conditions)
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return f"Weather in {location}: {data['condition']}, {data['temp_c']}°C"
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# Initialize the tool
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weather_info_tool = Tool(
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name="get_weather_info",
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func=get_weather_info,
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description="Fetches dummy weather information for a given location."
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)
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def get_hub_stats(author: str) -> str:
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"""Fetches the most downloaded model from a specific author on the Hugging Face Hub."""
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try:
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# List models from the specified author, sorted by downloads
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models = list(list_models(author=author, sort="downloads", direction=-1, limit=1))
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if models:
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model = models[0]
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return f"The most downloaded model by {author} is {model.id} with {model.downloads:,} downloads."
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else:
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return f"No models found for author {author}."
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except Exception as e:
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return f"Error fetching models for {author}: {str(e)}"
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# Initialize the tool
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hub_stats_tool = Tool(
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name="get_hub_stats",
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func=get_hub_stats,
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description="Fetches the most downloaded model from a specific author on the Hugging Face Hub."
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)
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tools = [guest_info_tool, search_tool, weather_info_tool, hub_stats_tool]
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chat_with_tools = model.bind_tools(tools)
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# Generate the AgentState and Agent graph
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