Delete crew.py

crew.py

@@ -1,225 +0,0 @@
-# References:
-
-# https://docs.crewai.com/introduction
-# https://ai.google.dev/gemini-api/docs
-
-import os
-from crewai import Agent, Crew, Task
-from crewai.agents.agent_builder.base_agent import BaseAgent
-from crewai.project import CrewBase, agent, crew, task
-from google import genai
-from tools.ai_tools import AITools
-from tools.arithmetic_tools import ArithmeticTools
-from typing import List
-from utils import read_file_json, is_ext
-
-# LLMs
-
-MANAGER_MODEL      = "gpt-4.1"
-AGENT_MODEL        = "gpt-4.1-mini"
-
-FINAL_ANSWER_MODEL = "gemini-2.5-pro"
-
-@CrewBase
-class GAIACrew():
-    agents: List[BaseAgent]
-    tasks: List[Task]
-    
-    @agent
-    def web_search_agent(self) -> Agent:
-        return Agent(
-            config=self.agents_config["web_search_agent"],
-            allow_delegation=False,
-            llm=AGENT_MODEL,
-            max_iter=2,
-            tools=[AITools.web_search_tool],
-            verbose=True
-        )
-
-    @agent
-    def web_browser_agent(self) -> Agent:
-        return Agent(
-            config=self.agents_config["web_browser_agent"],
-            allow_delegation=False,
-            llm=AGENT_MODEL,
-            max_iter=3,
-            tools=[AITools.web_browser_tool],
-            verbose=True
-        )
-
-    @agent
-    def chess_analysis_agent(self) -> Agent:
-        return Agent(
-            config=self.agents_config["chess_analysis_agent"],
-            allow_delegation=False,
-            llm=AGENT_MODEL,
-            max_iter=2,
-            tools=[AITools.chess_analysis_tool],
-            verbose=True
-        )
-
-    @agent
-    def image_analysis_agent(self) -> Agent:
-        return Agent(
-            config=self.agents_config["image_analysis_agent"],
-            allow_delegation=False,
-            llm=AGENT_MODEL,
-            max_iter=2,
-            tools=[AITools.image_analysis_tool],
-            verbose=True
-        )
-
-    @agent
-    def audio_analysis_agent(self) -> Agent:
-        return Agent(
-            config=self.agents_config["audio_analysis_agent"],
-            allow_delegation=False,
-            llm=AGENT_MODEL,
-            max_iter=2,
-            tools=[AITools.audio_analysis_tool],
-            verbose=True
-        )
-
-    @agent
-    def video_analysis_agent(self) -> Agent:
-        return Agent(
-            config=self.agents_config["video_analysis_agent"],
-            allow_delegation=False,
-            llm=AGENT_MODEL,
-            max_iter=2,
-            tools=[AITools.video_analysis_tool],
-            verbose=True
-        )
-
-    @agent
-    def youtube_analysis_agent(self) -> Agent:
-        return Agent(
-            config=self.agents_config["youtube_analysis_agent"],
-            allow_delegation=False,
-            llm=AGENT_MODEL,
-            max_iter=2,
-            tools=[AITools.youtube_analysis_tool],
-            verbose=True
-        )
-
-    @agent
-    def document_analysis_agent(self) -> Agent:
-        return Agent(
-            config=self.agents_config["document_analysis_agent"],
-            allow_delegation=False,
-            llm=AGENT_MODEL,
-            max_iter=2,
-            tools=[AITools.document_analysis_tool],
-            verbose=True
-        )
-
-    @agent
-    def arithmetic_agent(self) -> Agent:
-        return Agent(
-            config=self.agents_config["document_analysis_agent"],
-            allow_delegation=False,
-            llm=AGENT_MODEL,
-            max_iter=2,
-            tools=[ArithmeticTools.add, ArithmeticTools.subtract, ArithmeticTools.multiply, ArithmeticTools.divide, ArithmeticTools.modulus],
-            verbose=True
-        )
-
-    @agent
-    def code_generation_agent(self) -> Agent:
-        return Agent(
-            config=self.agents_config["code_generation_agent"],
-            allow_delegation=False,
-            llm=AGENT_MODEL,
-            max_iter=3,
-            tools=[AITools.code_generation_tool],
-            verbose=True
-        )
-
-    @agent
-    def code_execution_agent(self) -> Agent:
-        return Agent(
-            config=self.agents_config["code_execution_agent"],
-            allow_delegation=False,
-            llm=AGENT_MODEL,
-            max_iter=3,
-            tools=[AITools.code_execution_tool],
-            verbose=True
-        )
-
-    @agent
-    def manager_agent(self) -> Agent:
-        return Agent(
-            config=self.agents_config["manager_agent"],
-            allow_delegation=True,
-            llm=MANAGER_MODEL,
-            max_iter=5,
-            verbose=True
-        )
-
-    @task
-    def manager_task(self) -> Task:
-        return Task(
-            config=self.tasks_config["manager_task"]
-        )
-
-    @crew
-    def crew(self) -> Crew:
-        return Crew(
-            agents=self.agents,
-            tasks=self.tasks,
-            verbose=True
-        )
-
-def run_crew(question, file_path):
-    final_question = question
-    
-    if file_path:
-        if is_ext(file_path, ".csv") or is_ext(file_path, ".xls") or is_ext(file_path, ".xlsx") or is_ext(file_path, ".json") or is_ext(file_path, ".jsonl"):
-            json_data = read_file_json(file_path)
-            final_question = f"{question} JSON data:\n{json_data}."
-        else:
-            final_question = f"{question} File path: {file_path}."
-
-    answer = GAIACrew().crew().kickoff(inputs={"question": final_question})   
-    final_answer = get_final_answer(FINAL_ANSWER_MODEL, question, str(answer))
-
-    print(f"=> Initial question: {question}")
-    print(f"=> Final question: {final_question}")
-    print(f"=> Initial answer: {answer}")
-    print(f"=> Final answer: {final_answer}")
-    
-    return final_answer
-
-def get_final_answer(model, question, answer):
-    prompt_template = """
-        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:** """ + 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:** 
-        """
-
-    client = genai.Client(api_key=os.environ["GEMINI_API_KEY"])
-
-    response = client.models.generate_content(
-        model=model, 
-        contents=[prompt_template]
-    )
-    
-    return response.text