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# a multi agent proposal to solve HF agent course final assignment
import os
import dotenv
from smolagents import CodeAgent
from smolagents import OpenAIServerModel
from tools.fetch import fetch_webpage, search_web
from smolagents import PythonInterpreterTool
from tools.yttranscript import get_youtube_transcript, get_youtube_title_description
from tools.stt import get_text_transcript_from_audio_file
from tools.image import analyze_image
from common.mylogger import mylog
import myprompts
dotenv.load_dotenv()
gemini_model = OpenAIServerModel(
model_id="gemini-2.0-flash",
api_key=os.environ["GEMINI_API_KEY"],
# Google Gemini OpenAI-compatible API base URL
api_base="https://generativelanguage.googleapis.com/v1beta/openai/",
)
vllm_model = OpenAIServerModel(
model_id="Qwen/Qwen2.5-1.5B-Instruct",
api_base="http://192.168.1.39:18000/v1",
api_key="token-abc123",
)
openai_41nano_model = OpenAIServerModel(
model_id="llama3-70b-8192",
api_base="https://api.groq.com/openai/v1",
api_key=os.environ["GROQ_API_KEY"],
)
openai_41mini_model = OpenAIServerModel(
model_id="llama3-70b-8192",
api_base="https://api.groq.com/openai/v1",
api_key=os.environ["GROQ_API_KEY"],
)
def check_final_answer(final_answer, agent_memory) -> bool:
"""
Check if the final answer is correct.
basic check on the length of the answer.
"""
mylog("check_final_answer", final_answer)
# if return answer is more than 200 characters, we will assume it is not correct
if len(str(final_answer)) > 200:
return False
else:
return True
web_agent = CodeAgent(
model=openai_41nano_model,
tools=[
search_web,
fetch_webpage,
],
name="web_agent",
description="Use search engine to find webpages related to a subject and get the page content",
additional_authorized_imports=["pandas", "numpy","bs4"],
verbosity_level=1,
max_steps=7,
)
audiovideo_agent = CodeAgent(
model=openai_41nano_model,
tools=[
get_youtube_transcript,
get_youtube_title_description,
get_text_transcript_from_audio_file,
analyze_image
],
name="audiovideo_agent",
description="Extracts information from image, video or audio files from the web",
additional_authorized_imports=["pandas", "numpy","bs4", "requests"],
verbosity_level=1,
max_steps=7,
)
manager_agent = CodeAgent(
model=openai_41mini_model,
tools=[ PythonInterpreterTool()],
managed_agents=[web_agent, audiovideo_agent],
additional_authorized_imports=["pandas", "numpy","bs4"],
planning_interval=5,
verbosity_level=2,
final_answer_checks=[check_final_answer],
max_steps=15,
name="manager_agent",
description="A manager agent that coordinates the work of other agents to answer questions.",
)
class MultiAgent:
def __init__(self):
print("BasicAgent initialized.")
def __call__(self, question: str) -> str:
from myprompts import output_format
try:
prefix = (
"You are the top agent of a multi-agent system that can answer questions by coordinating the work of other agents. "
"Use the `web_agent` to search the web and retrieve content. Use the `audiovideo_agent` for extracting transcripts and analyzing media. "
"Use your own knowledge when no tool is needed. Always follow the required output format."
)
full_prompt = f"""{prefix.strip()}
THE QUESTION:
{question.strip()}
{output_format.strip()}"""
# ✅ Validate before sending to model
assert isinstance(full_prompt, str), "Prompt must be a string."
print("Sending prompt to manager_agent:")
print(full_prompt)
result = manager_agent.run(full_prompt)
return result if isinstance(result, str) else str(result)
except Exception as e:
return f"❌ Agent Error: {str(e)}"
if __name__ == "__main__":
# Example usage
question = """
What was the actual enrollment of the Malko competition in 2023?
"""
agent = MultiAgent()
answer = agent(question)
print(f"Answer: {answer}")
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