feat: Add SmoLAgents-based multi-agent party planning system

agents/smolagent/.python-version

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+3.13

agents/smolagent/main.py

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+import os
+import dotenv
+
+dotenv.load_dotenv(dotenv_path=".env.secure")
+
+from huggingface_hub import login
+from langfuse import get_client
+from openinference.instrumentation.smolagents import SmolagentsInstrumentor
+from smolagents import (
+    CodeAgent,
+    DuckDuckGoSearchTool,
+    InferenceClientModel,
+    ToolCallingAgent,
+    tool,
+)
+
+
+HUGGING_FACE_TOKEN = os.getenv("HUGGING_FACE_TOKEN")
+
+login(token=HUGGING_FACE_TOKEN)
+
+langfuse_client = get_client()
+
+
+if langfuse_client.auth_check():
+    print("Langfuse client authenticated")
+else:
+    print("Langfuse client not authenticated")
+
+SmolagentsInstrumentor().instrument()
+
+
+@tool
+def suggest_menu(occasion: str) -> str:
+    """
+    Suggests a menu based on the occasion.
+    Args:
+        occasion (str): The type of occasion for the party. Allowed values are:
+                        - "casual": Menu for casual party.
+                        - "formal": Menu for formal party.
+                        - "superhero": Menu for superhero party.
+                        - "custom": Custom menu.
+    """
+    if occasion == "casual":
+        return "The best menu for casual party is pizza."
+    elif occasion == "formal":
+        return "The best menu for formal party is steak."
+    elif occasion == "superhero":
+        return "The best menu for superhero party is superhero pizza."
+    else:
+        return "The best menu for custom party is custom menu."
+
+
+def music_agent():
+    prompt = """
+    Search for the best music recommendations for a Bruce Wayne's party.
+    """
+    return ToolCallingAgent(
+        model=InferenceClientModel(),
+        tools=[DuckDuckGoSearchTool()],
+    ).run(prompt)
+
+
+def menu_agent():
+    prompt = """
+    Suggest a menu for a Bruce Wayne's party.
+    """
+    return CodeAgent(
+        model=InferenceClientModel(),
+        tools=[suggest_menu],
+    ).run(prompt)
+
+
+def schedule_agent():
+    prompt = """
+    Alfred needs to prepare for the party. Here are the tasks:
+    1. Prepare the drinks - 30 minutes
+    2. Decorate the mansion - 60 minutes
+    3. Set up the menu - 45 minutes
+    4. Prepare the music and playlist - 45 minutes
+
+    If we start right now, at what time will the party be ready?
+    """
+    return CodeAgent(
+        model=InferenceClientModel(),
+        tools=[],
+        additional_authorized_imports=["datetime"],
+    ).run(prompt)
+
+
+def response_agent(music: str, menu: str, schedule: str):
+    prompt = """
+    Describe Bruce Wayne's party in a way that is engaging and interesting. 
+    Ensure to list out the menu items in the response.
+    For music, please provide the name of the song and the artist.
+    For schedule, please provide the time in the format of HH:MM:SS.
+    Music: {music}, Menu: {menu}, Schedule: {schedule}
+    """
+    return CodeAgent(
+        model=InferenceClientModel(),
+        tools=[],
+    ).run(prompt.format(music=music, menu=menu, schedule=schedule))
+
+
+def main():
+    # First, we need to get the results from the music and menu agents.
+    music_result = music_agent()
+    menu_result = menu_agent()
+
+    # Then, we schedule the party.
+    schedule_result = schedule_agent()
+
+    # Then, we synthesize the results into a response.
+    response_result = response_agent(music_result, menu_result, schedule_result)
+    print(response_result)
+
+
+if __name__ == "__main__":
+    main()

agents/smolagent/pyproject.toml

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+[project]
+name = "smolagent"
+version = "0.1.0"
+description = "Add your description here"
+readme = "README.md"
+requires-python = ">=3.13"
+dependencies = [
+    "ddgs>=9.5.5",
+    "huggingface-hub>=0.34.4",
+    "langchain>=0.3.27",
+    "langchain-community>=0.3.29",
+    "langfuse>=3.3.4",
+    "openinference-instrumentation-smolagents>=0.1.16",
+    "opentelemetry-exporter-otlp>=1.36.0",
+    "opentelemetry-sdk>=1.36.0",
+    "smolagents>=1.21.3",
+]