Update multiagents.py

multiagents.py

@@ -1,73 +1,34 @@
-
-# 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
 from common.mylogger import mylog
-import myprompts
+from myprompts import output_format
+import dotenv
 
 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"],
+# --- Models ---
+openai_model = OpenAIServerModel(
+    model_id="gpt-3.5-turbo",
+    api_key=os.environ["OPENAI_API_KEY"],
+    api_base="https://api.openai.com/v1",
 )
 
-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
-
-
+# --- Tool Agents ---
 web_agent = CodeAgent(
-    model=openai_41nano_model,
-    tools=[
-        search_web,
-        fetch_webpage,                
-    ],
+    model=openai_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,
+    description="Searches the web and fetches content from webpages.",
+    max_steps=6,
+    verbosity_level=1,
 )
 
 audiovideo_agent = CodeAgent(
-    model=openai_41nano_model,
+    model=openai_model,
     tools=[
         get_youtube_transcript,
         get_youtube_title_description,
@@ -75,69 +36,57 @@ 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="Processes audio, video, and image content.",
+    max_steps=6,
     verbosity_level=1,
-    max_steps=7,
 )
 
+# --- Answer Checker ---
+def check_final_answer(answer: str, _) -> bool:
+    return isinstance(answer, str) and len(answer.strip()) <= 200
 
-
+# --- Manager Agent ---
 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,
+    model=openai_model,
+    tools=[PythonInterpreterTool()],
+    managed_agents=[web_agent, audiovideo_agent],
     name="manager_agent",
-    description="A manager agent that coordinates the work of other agents to answer questions.",
+    description="Manages sub-agents to answer complex queries.",
+    final_answer_checks=[check_final_answer],
+    verbosity_level=2,
+    max_steps=12,
 )
 
+# --- Entry Class ---
 class MultiAgent:
     def __init__(self):
-        print("BasicAgent initialized.")
+        print("✅ MultiAgent initialized")
 
     def __call__(self, question: str) -> str:
-        from myprompts import output_format
-
+        mylog("MultiAgent", question)
         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."
+            system_instruction = (
+                "You are the lead agent in a multi-agent AI system. Use the sub-agents wisely."
+                " Answer using reasoning, planning, and tools where needed."
+                " Stay concise and always format the answer exactly as required."
             )
 
-            full_prompt = f"""{prefix.strip()}
+            prompt = f"""
+{system_instruction}
 
 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)
-
+{output_format.strip()}
+"""
+            return str(manager_agent.run(prompt))
         except Exception as e:
-            return f"❌ Agent Error: {str(e)}"
+            error_msg = f"An error occurred while processing the question: {e}"
+            print(error_msg)
+            return error_msg
 
 
 if __name__ == "__main__":
-    # Example usage
-   
-    question = """
-What was the actual enrollment of the Malko competition in 2023?
-"""
+    example_question = "What was the actual enrollment of the Malko competition in 2023?"
     agent = MultiAgent()
-    answer = agent(question)
-    print(f"Answer: {answer}")
-    
+    print(agent(example_question))