organize project

agents.py

@@ -1,10 +1,9 @@
-import os
-import pandas as pd
-import requests
 from smolagents import OpenAIServerModel, CodeAgent, InferenceClientModel, DuckDuckGoSearchTool, VisitWebpageTool
-from smolagents.tools import tool
 import markdownify
 
+import tools
+import prompts
+
 MANAGER_MODEL = "deepseek-ai/DeepSeek-R1"
 AGENT_MODEL = "Qwen/Qwen2.5-Coder-32B-Instruct"
 FINAL_ANSWER_MODEL = "deepseek-ai/DeepSeek-R1" # OpenAIServerModel
@@ -18,123 +17,31 @@ ARITHMETIC_MODEL        = "Qwen/Qwen2.5-Coder-32B-Instruct"
 CODE_GENERATION_MODEL   = "Qwen/Qwen2.5-Coder-32B-Instruct"
 CODE_EXECUTION_MODEL    = "Qwen/Qwen2.5-Coder-32B-Instruct"
 
-def orchestrate(message, file_path):
-
-    # Tools
-
-    simple_web_search_tool = DuckDuckGoSearchTool()
-    visit_web_page_tool = VisitWebpageTool()
-
-    @tool
-    def web_search_tool(query: str) -> str:
-        """
-        Given a question, search the web and return a summary answer.
-
-        Args:
-            query (str): The search query to look up.
-
-        Returns:
-            str: A relevant summary or result from DuckDuckGo.
-        """
-        try:
-            url = "https://api.duckduckgo.com/"
-            params = {"q": query, "format": "json", "no_html": 1}
-            response = requests.get(url, params=params)
-            data = response.json()
-
-            if abstract := data.get("AbstractText"):
-                return abstract
-            elif related := data.get("RelatedTopics"):
-                return related[0]["Text"] if related else "No result found."
-            else:
-                return "No relevant information found via DuckDuckGo."
-        except Exception as e:
-            raise RuntimeError(f"DuckDuckGo search failed: {str(e)}")
-
-    # Promts
-
-    def get_manager_prompt(message, file_path=None):
-        prompt = f"""Your job is to answer the following question. 
-            Answer the following question. If needed, delegate to one of your coworkers:\n
-
-            - Web Search Agent: Use when the question requires current information. Web Search Agent requires a question only.\n
-            Format the prompt like:
-            "You are an expert web search assistant. Your task is to search the web and provide accurate answers to the following question: [INSERT QUESTION]"
-
-            ...
-
-            In case you cannot answer the question and there is not a good coworker, delegate to the Code Generation Agent.\n.
+# Agents
 
-            Question: {message}
-            """
-
-        return prompt
-
-    def run_manager_workflow(message, file_path=None):
-        final_prompt = get_manager_prompt(message, file_path)
-        initial_answer = manager_agent.run(message)
-
-        final_answer = get_final_answer(final_answer_agent, message, str(initial_answer))
-
-        print(f"=> Initial question: {message}")
-        print(f"=> Final prompt: {final_prompt}")
-        print(f"=> Initial answer: {initial_answer}")
-        print(f"=> Final answer: {final_answer}")
-
-        return final_answer
-
-    def get_final_answer(agent, question: str, initial_answer: str) -> str:
-        prompt = f"""
-            You are an expert question answering assistant. Given a question and an initial answer, your task is to provide the final answer.
-        Your final answer must be a number and/or string OR as few words as possible OR a comma-separated list of numbers and/or strings.
-        If you are asked for a number, don't use comma to write your number neither use units such as USD, $, percent, or % unless specified otherwise.
-        If you are asked for a string, don't use articles, neither abbreviations (for example cities), and write the digits in plain text unless specified otherwise.
-        If you are asked for a comma-separated list, apply the above rules depending of whether the element to be put in the list is a number or a string.
-        If the final answer is a number, use a number not a word.
-        If the final answer is a string, start with an uppercase character.
-        If the final answer is a comma-separated list of numbers, use a space character after each comma.
-        If the final answer is a comma-separated list of strings, use a space character after each comma and start with a lowercase character.
-        Do not add any content to the final answer that is not in the initial answer.
-        
-        **Question:** """ + question + """
-        
-        **Initial answer:** """ + initial_answer + """
-        
-        **Example 1:** What is the biggest city in California? Los Angeles
-        **Example 2:** How many 'r's are in strawberry? 3
-        **Example 3:** What is the opposite of black? White
-        **Example 4:** What are the first 5 numbers in the Fibonacci sequence? 0, 1, 1, 2, 3
-        **Example 5:** What is the opposite of bad, worse, worst? good, better, best
-        
-        **Final answer:**
-        """
-
-        return agent.run(prompt)
-
-    # Agents
-
-    web_search_agent = CodeAgent(
-        name="web_search_agent",
-        description="As an expert web search assistant, you search the web to answer the question. Your task is to search the web and provide accurate answers to the question: {message}",
+def create_custom_web_search_agent(message):
+    return CodeAgent(
+        name="custom_web_search_agent",
+        description=prompts.get_web_search_prompt(message),
         model=InferenceClientModel(WEB_SEARCH_MODEL),
         max_steps=2,
-        tools=[web_search_tool],
+        tools=[tools.simple_web_search_tool, tools.visit_web_page_tool],
     )
 
-    simple_web_search_agent = CodeAgent(
+def create_simple_web_search_agent(message):
+    return CodeAgent(
         name="simple_web_search_agent",
-        description="As an expert web search assistant, you search the web to answer the question. Your task is to search the web and provide accurate answers to the question: {message}",
-        # system_message="As an expert web search assistant, you search the web to answer the question. Your task is to search the web and provide accurate answers to the question: {message}",
+        description=prompts.get_web_search_prompt(message),
         model=InferenceClientModel(WEB_SEARCH_MODEL),
         max_steps=2,
-        tools=[simple_web_search_tool, visit_web_page_tool],
+        tools=[tools.simple_web_search_tool, tools.visit_web_page_tool],
     )
 
-    manager_prompt = get_manager_prompt(message)
-    manager_agent = CodeAgent(
+def create_manager_agent(message):
+    return CodeAgent(
         name="manager_agent",
         model=InferenceClientModel(MANAGER_MODEL, provider="together", max_tokens=8096),
-        description=manager_prompt,
+        description=prompts.get_manager_prompt(message),
         tools=[],
         planning_interval=4,
         verbosity_level=2,
@@ -168,15 +75,11 @@ def orchestrate(message, file_path):
         ],
     )
 
-    final_answer_agent = CodeAgent(
+def create_final_answer_agent(message):
+    return CodeAgent(
         name="final_answer_agent",
         description="Given a question and an initial answer, return the final refined answer following strict formatting rules.",
         model=InferenceClientModel(FINAL_ANSWER_MODEL),
         max_steps=1,
         tools=[],
     )
-
-    final_answer =  run_manager_workflow(message)
-
-    # final_answer =  manager_agent.run(message)
-    return final_answer

app.py

@@ -6,7 +6,7 @@ import pandas as pd
 from huggingface_hub import login
 from dotenv import load_dotenv
 
-from agents import orchestrate
+from multi_agent import orchestrate
 
 # (Keep Constants as is)
 # --- Constants ---
@@ -152,8 +152,6 @@ def test_init_agent_for_chat(text_input, history, file_name = ""):
 
     submitted_answer = orchestrate(text_input, file_name)
 
-    print(submitted_answer)
-
     return submitted_answer
 
 # --- Build Gradio Interface using Blocks ---
@@ -163,15 +161,8 @@ with gr.Blocks() as demo:
         """
         **Instructions:**
 
-        1.  Please clone this space, then modify the code to define your agent's logic, the tools, the necessary packages, etc ...
-        2.  Log in to your Hugging Face account using the button below. This uses your HF username for submission.
-        3.  Click 'Run Evaluation & Submit All Answers' to fetch questions, run your agent, submit answers, and see the score.
         4.  who is in the final of champions league this year?
 
-        ---
-        **Disclaimers:**
-        Once clicking on the "submit button, it can take quite some time ( this is the time for the agent to go through all the questions).
-        This space provides a basic setup and is intentionally sub-optimal to encourage you to develop your own, more robust solution. For instance for the delay process of the submit button, a solution could be to cache the answers and submit in a seperate action or even to answer the questions in async.
         """
     )
 

multi_agent.py

@@ -0,0 +1,29 @@
+import os
+import pandas as pd
+import requests
+from smolagents import OpenAIServerModel, CodeAgent, InferenceClientModel
+from smolagents.tools import tool
+import markdownify
+
+import prompts
+import agents
+
+
+def orchestrate(message, file_path):
+    final_prompt = prompts.get_manager_prompt(message, file_path)
+    initial_answer = agents.create_simple_web_search_agent(message).run(message)
+
+    final_answer = agents.create_final_answer_agent(message).run(prompts.get_final_answer_prompt(message, initial_answer))
+
+    return final_answer
+    # def run_manager_workflow(message, file_path=None):
+    #     final_prompt = prompts.get_manager_prompt(message, file_path)
+    #     initial_answer = agents.create_simple_web_search_agent(message).run(message)
+
+    #     final_answer = agents.create_final_answer_agent(message).run(prompts.get_final_answer_prompt(message, initial_answer))
+
+    #     return final_answer
+
+    # final_answer =  run_manager_workflow(message)
+
+    # return final_answer

prompts.py

@@ -0,0 +1,53 @@
+ # Promts
+
+def get_web_search_prompt(message, file_path=None):
+    prompt = f"""
+    As an expert web search assistant, you search the web to answer the question. Your task is to search the web and provide accurate answers to the question: {message}
+        """
+
+    return prompt
+
+def get_manager_prompt(message, file_path=None):
+    prompt = f"""Your job is to answer the following question. 
+        Answer the following question. If needed, delegate to one of your coworkers:\n
+
+        - Web Search Agent: Use when the question requires current information. Web Search Agent requires a question only.\n
+        Format the prompt like:
+        "You are an expert web search assistant. Your task is to search the web and provide accurate answers to the following question: [INSERT QUESTION]"
+
+        ...
+
+        In case you cannot answer the question and there is not a good coworker, delegate to the Code Generation Agent.\n.
+
+        Question: {message}
+        """
+
+    return prompt
+
+def get_final_answer_prompt(message: str, initial_answer: str):
+    prompt = f"""
+            You are an expert question answering assistant. Given a question and an initial answer, your task is to provide the final answer.
+        Your final answer must be a number and/or string OR as few words as possible OR a comma-separated list of numbers and/or strings.
+        If you are asked for a number, don't use comma to write your number neither use units such as USD, $, percent, or % unless specified otherwise.
+        If you are asked for a string, don't use articles, neither abbreviations (for example cities), and write the digits in plain text unless specified otherwise.
+        If you are asked for a comma-separated list, apply the above rules depending of whether the element to be put in the list is a number or a string.
+        If the final answer is a number, use a number not a word.
+        If the final answer is a string, start with an uppercase character.
+        If the final answer is a comma-separated list of numbers, use a space character after each comma.
+        If the final answer is a comma-separated list of strings, use a space character after each comma and start with a lowercase character.
+        Do not add any content to the final answer that is not in the initial answer.
+        
+        **Question:** """ + message + """
+        
+        **Initial answer:** """ + initial_answer + """
+        
+        **Example 1:** What is the biggest city in California? Los Angeles
+        **Example 2:** How many 'r's are in strawberry? 3
+        **Example 3:** What is the opposite of black? White
+        **Example 4:** What are the first 5 numbers in the Fibonacci sequence? 0, 1, 1, 2, 3
+        **Example 5:** What is the opposite of bad, worse, worst? good, better, best
+        
+        **Final answer:**
+        """
+
+    return prompt

tools.py

@@ -0,0 +1,34 @@
+
+from smolagents import DuckDuckGoSearchTool, VisitWebpageTool
+from smolagents.tools import tool
+
+# Tools
+
+simple_web_search_tool = DuckDuckGoSearchTool()
+visit_web_page_tool = VisitWebpageTool()
+
+@tool
+def web_search_tool(query: str) -> str:
+    """
+    Given a question, search the web and return a summary answer.
+
+    Args:
+        query (str): The search query to look up.
+
+    Returns:
+        str: A relevant summary or result from DuckDuckGo.
+    """
+    try:
+        url = "https://api.duckduckgo.com/"
+        params = {"q": query, "format": "json", "no_html": 1}
+        response = requests.get(url, params=params)
+        data = response.json()
+
+        if abstract := data.get("AbstractText"):
+            return abstract
+        elif related := data.get("RelatedTopics"):
+            return related[0]["Text"] if related else "No result found."
+        else:
+            return "No relevant information found via DuckDuckGo."
+    except Exception as e:
+        raise RuntimeError(f"DuckDuckGo search failed: {str(e)}")