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# multiagent.py — GAIA-compliant multi-agent system using Groq (patched)
import os
import dotenv
from smolagents import CodeAgent, PythonInterpreterTool
from smolagents.models.openai_server_model import OpenAIServerModel as BaseOpenAIServerModel
from tools.fetch import fetch_webpage, search_web
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
# ✅ Load .env
dotenv.load_dotenv()
# ✅ Monkeypatch: Ensure message['content'] is always a string
class PatchedOpenAIServerModel(BaseOpenAIServerModel):
def complete_chat(self, messages, **kwargs):
for msg in messages:
if not isinstance(msg.get("content", ""), str):
msg["content"] = str(msg["content"])
return super().complete_chat(messages, **kwargs)
# ✅ Groq model (OpenAI-compatible)
groq_model = PatchedOpenAIServerModel(
model_id="llama3-70b-8192",
api_key=os.environ["GROQ_API_KEY"],
api_base="https://api.groq.com/openai/v1",
)
# ✅ Final answer checker
def check_final_answer(final_answer, agent_memory) -> bool:
mylog("check_final_answer", final_answer)
return len(str(final_answer)) <= 200
# ✅ Sub-agents
web_agent = CodeAgent(
model=groq_model,
tools=[search_web, fetch_webpage],
name="web_agent",
description="Uses search engine and scrapes webpages for content.",
additional_authorized_imports=["pandas", "numpy", "bs4"],
verbosity_level=1,
max_steps=7,
)
audiovideo_agent = CodeAgent(
model=groq_model,
tools=[
get_youtube_transcript,
get_youtube_title_description,
get_text_transcript_from_audio_file,
analyze_image
],
name="audiovideo_agent",
description="Extracts data from audio, video, or images.",
additional_authorized_imports=["pandas", "numpy", "bs4", "requests"],
verbosity_level=1,
max_steps=7,
)
# ✅ Manager agent
manager_agent = CodeAgent(
model=groq_model,
tools=[PythonInterpreterTool()],
managed_agents=[web_agent, audiovideo_agent],
name="manager_agent",
description="Coordinates other agents and returns a final answer.",
additional_authorized_imports=["pandas", "numpy", "bs4"],
planning_interval=5,
verbosity_level=2,
final_answer_checks=[check_final_answer],
max_steps=15,
)
# ✅ Multi-agent interface
class MultiAgent:
def __init__(self):
print("MultiAgent initialized.")
def __call__(self, question: str) -> str:
mylog(self.__class__.__name__, question)
try:
prefix = """
You are the top agent of a multi-agent system that can answer questions by coordinating the work of other agents.
You can use the web_agent to search the web, or the audiovideo_agent to extract info from audio/video/images.
You must reason step by step and respect the required output format.
Only return the final answer in the correct format.
"""
prompt = prefix.strip() + "\nTHE QUESTION:\n" + question.strip() + "\n" + myprompts.output_format.strip()
answer = manager_agent.run(prompt)
return answer
except Exception as e:
error = f"An error occurred while processing the question: {e}"
print(error)
return error
# ✅ Local test
if __name__ == "__main__":
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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