Update multiagents.py

multiagents.py

@@ -1,11 +1,9 @@
+# multiagent.py — GAIA-compliant smolagents setup using Groq
 
-# a multi agent proposal to solve HF agent course final assignment
 import os
 import dotenv
-from smolagents import CodeAgent
-from smolagents import OpenAIServerModel
+from smolagents import CodeAgent, OpenAIServerModel, PythonInterpreterTool
 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
@@ -14,60 +12,32 @@ 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(
+# ✅ Use Groq’s LLaMA3 (OpenAI-compatible and fast)
+groq_model = OpenAIServerModel(
     model_id="llama3-70b-8192",
     api_key=os.environ["GROQ_API_KEY"],
-    api_base="https://api.groq.com/openai/v1"
+    api_base="https://api.groq.com/openai/v1",
 )
 
-openai_41mini_model = OpenAIServerModel(
-    model_id="llama3-70b-8192",
-    api_key=os.environ["GROQ_API_KEY"],
-    api_base="https://api.groq.com/openai/v1"
-)
-
-
-def check_final_answer(final_answer, agent_memory)  -> bool:
-    """
-    Check if the final answer is correct.
-    basic check on the length of the answer.
-    """
+# ✅ Final answer validation
+def check_final_answer(final_answer, agent_memory) -> bool:
     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
-
+    return len(str(final_answer)) <= 200
 
+# ✅ Web agent for search and scraping
 web_agent = CodeAgent(
-    model=openai_41nano_model,
-    tools=[
-        search_web,
-        fetch_webpage,                
-    ],
+    model=groq_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,    
+    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,
 )
 
+# ✅ Audio/Video/Image processing agent
 audiovideo_agent = CodeAgent(
-    model=openai_41nano_model,
+    model=groq_model,
     tools=[
         get_youtube_transcript,
         get_youtube_title_description,
@@ -75,19 +45,18 @@ audiovideo_agent = CodeAgent(
         analyze_image
     ],
     name="audiovideo_agent",
-    description="Extracts information from image, video or audio files from the web",
-    additional_authorized_imports=["pandas", "numpy","bs4", "requests"],
+    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 (planner/coordinator)
 manager_agent = CodeAgent(
-    model=openai_41mini_model,
-    tools=[ PythonInterpreterTool()],
-    managed_agents=[web_agent, audiovideo_agent],    
-    additional_authorized_imports=["pandas", "numpy","bs4"],
+    model=groq_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],
@@ -96,42 +65,32 @@ manager_agent = CodeAgent(
     description="A manager agent that coordinates the work of other agents to answer questions.",
 )
 
+# ✅ Multi-agent system wrapper class
 class MultiAgent:
     def __init__(self):
-        print("BasicAgent initialized.")
+        print("MultiAgent system initialized.")
 
     def __call__(self, question: str) -> str:
-        mylog(self.__class__.__name__, question)        
+        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 will receive a question and you will decide which agent to use to answer it.
-            You can use the web_agent to search the web for information and for fetching the content of a web page, or the audiovideo_agent to extract information from video or audio files.
-            You can also use your own knowledge to answer the question.
-            You need to respect the output format that is given to you.
-            Finding the correct answer to the question need reasoning and plannig, read the question carrefully, think step by step and do not skip any steps.
-            """
-
-            question = prefix + "\nTHE QUESTION:\n" + question + '\n' + myprompts.output_format
-
-            fixed_answer = ""
-
-            fixed_answer = manager_agent.run(question)
-            
-            return fixed_answer
+            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.
+"""
+            full_prompt = prefix.strip() + "\nTHE QUESTION:\n" + question.strip() + "\n" + myprompts.output_format.strip()
+            answer = manager_agent.run(full_prompt)
+            return answer
         except Exception as e:
             error = f"An error occurred while processing the question: {e}"
             print(error)
             return error
 
-
+# ✅ Manual test (can be triggered from HF Space too)
 if __name__ == "__main__":
-    # Example usage
-   
-    question = """
-What was the actual enrollment of the Malko competition in 2023?
-"""
+    question = "What was the actual enrollment of the Malko competition in 2023?"
     agent = MultiAgent()
     answer = agent(question)
     print(f"Answer: {answer}")
-