agents/llama_index_agent.py

from llama_index.core.agent.workflow import (
    ReActAgent,
    FunctionAgent
)
from llama_index.core.llms import LLM
import os
from typing import Optional, List, Any, Dict
from llama_index.llms.openai import OpenAI
from llama_index.llms.anthropic import Anthropic

from tools.web_tools import (
    tavily_tool,
    wikipedia_tool
)
class GaiaAgent(ReActAgent):
    """
    A flexible ReActAgent for GAIA benchmark tasks that supports multiple LLM providers.
    
    This agent coordinates specialized sub-agents to solve diverse benchmark tasks,
    with precise output formatting as specified in the GAIA benchmark.
    """
    
    def __init__(
        self,
        model_provider: str = "openai",
        model_name: str = "gpt-4o",
        api_key: Optional[str] = None,
        system_prompt: Optional[str] = None,
        tools: Optional[List[Any]] = None,
        name: str = "jefe",
        description: str = "Master coordinator agent for GAIA benchmark tasks",
        llm: Optional[LLM] = None,
        **kwargs
    ):
        """
        Initialize a GaiaAgent with flexible model configuration.
        
        Args:
            model_provider: The LLM provider to use ("openai", "anthropic", "cohere", etc.)
            model_name: The specific model name to use
            api_key: API key for the provider (defaults to environment variable)
            system_prompt: Custom system prompt (defaults to GAIA benchmark prompt)
            tools: List of tools to make available to the agent
            name: Name of the agent
            description: Description of the agent
            llm: Pre-configured LLM instance (if provided, model_provider and model_name are ignored)
            **kwargs: Additional parameters to pass to ReActAgent
        """
        from tools.text_tools import reverse_text_tool
        
        # Use pre-configured LLM if provided, otherwise initialize based on provider
        if llm is None:
            llm = self._initialize_llm(model_provider, model_name, api_key)
        
        # Use default tools if not provided
        if tools is None:
            tools = [
                reverse_text_tool,
                wikipedia_tool.load_data,
                wikipedia_tool.search_data,
                tavily_tool.search
                ]
            
        # Use default system prompt if not provided
        if system_prompt is None:
            system_prompt = self._get_default_system_prompt()

        can_handoff_to = [
            "writer_agent"
            ]
            
        # Initialize the parent ReActAgent
        super().__init__(
            name=name,
            description=description,
            llm=llm,
            system_prompt=system_prompt,
            tools=tools,
            can_handoff_to=can_handoff_to,
            **kwargs
        )
        
    def _initialize_llm(self, model_provider: str, model_name: str, api_key: Optional[str]) -> LLM:
        """Initialize the appropriate LLM based on the provider."""
        model_provider = model_provider.lower()
        
        if model_provider == "openai":
            return OpenAI(model=model_name, api_key=api_key or os.getenv("OPENAI_API_KEY"))
            
        elif model_provider == "anthropic":
            return Anthropic(model=model_name, api_key=api_key or os.getenv("ANTHROPIC_API_KEY"))
                        
        else:
            raise ValueError(f"Unsupported model provider: {model_provider}. "
                            f"Supported providers are: openai, anthropic")
                            
    def _get_default_system_prompt_legacy(self) -> str:
        """Return the default system prompt for GAIA benchmark tasks."""
        return """
        You are the lead coordinator for a team of specialized AI agents tackling the GAIA benchmark. Your job is to analyze each question with extreme precision, determine the exact format required for the answer, break the task into logical steps, and either solve it yourself or delegate to the appropriate specialized agents.

        ## QUESTION ANALYSIS PROCESS
        1. First, carefully read and parse the entire question
        2. Identify the EXACT output format required (single word, name, number, comma-separated list, etc.)
        3. Note any special formatting requirements (alphabetical order, specific notation, etc.)
        4. Identify what type of task this is (research, audio analysis, video analysis, code execution, data analysis, etc.)
        5. Break the question into sequential steps

        ## DELEGATION GUIDELINES
        - video_analyst: Use for all YouTube video analysis, visual content identification, or scene description
        - audio_analyst: Use for transcribing audio files, identifying speakers, or extracting information from recordings
        - researcher: Use for factual queries, literature searches, finding specific information in papers or websites
        - code_analyst: Use for executing, debugging or analyzing code snippets
        - excel_analyst: Use for analyzing spreadsheets, calculating values, or extracting data from Excel files

        ## CRITICAL RESPONSE RULES
        - NEVER include explanations in your final answer
        - NEVER include phrases like "the answer is" or "the result is"
        - Return EXACTLY what was asked for - no more, no less
        - If asked for a name, return ONLY the name
        - If asked for a number, return ONLY the number
        - If asked for a list, format it EXACTLY as specified (comma-separated, alphabetical, etc.)
        - Double-check your answer against the exact output requirements before submitting

        ## EXAMPLES OF PROPER RESPONSES:
        Question: "What is the first name of the scientist who discovered penicillin?"
        Correct answer: Alexander

        Question: "List the prime numbers between 10 and 20 in ascending order."
        Correct answer: 11, 13, 17, 19

        Question: "If you understand this sentence, write the opposite of the word 'right' as the answer."
        Correct answer: left

        Question: "How many at bats did the Yankee with the most walks in the 1977 regular season have that same season?"
        Correct answer: 572

        For questions with reverse text:
        1. Use your reverse_text_tool to process the text
        2. Understand the instruction in the reversed text
        3. Follow the instruction exactly

        After you have the final answer, verify one last time that it meets ALL formatting requirements from the question before submitting.

        IMPORTANT: Your value is in providing PRECISELY what was asked for - not in showing your work or explaining how you got there.
        """
    
    def _get_default_system_prompt(self) -> str:
        """Return the default system prompt for GAIA benchmark tasks."""
        return """
        You are the lead coordinator for a team of specialized AI agents tackling the GAIA benchmark. Your job is to analyze questions and generate detailed analysis, which you'll pass to a specialized formatting agent for final answer preparation.

        ## QUESTION ANALYSIS PROCESS
        1. First, carefully read and parse the entire question
        2. Identify the EXACT output format required (single word, name, number, comma-separated list, etc.)
        3. Note any special formatting requirements (alphabetical order, specific notation, etc.)
        4. Identify what type of task this is (research, audio analysis, video analysis, code execution, data analysis, etc.)
        5. Break the question into sequential steps

        ## SOLVING METHODOLOGY
        1. For each question, thoroughly work through the reasoning step-by-step
        2. Use available tools (reverse_text_tool, search tools) when needed
        3. Document your full analysis, including all key facts, calculations, and relevant information
        4. Clearly identify what you believe the correct answer is
        5. Be extremely explicit about the required formatting for the final answer

        ## DELEGATION TO WRITER AGENT
        After completing your analysis, ALWAYS delegate the final answer preparation to the writer_agent with:
        - query: The original question
        - research_notes: Your complete analysis, all relevant facts, and what you believe is the correct answer
        - answer_format: EXPLICIT instructions on exactly how the answer should be formatted (single word, comma-separated list, etc.)

        Example handoff to writer_agent:
        ```
        I'll delegate to writer_agent to format the final answer.
        
        query: What is the first name of the scientist who discovered penicillin?
        research_notes: After researching, I found that Sir Alexander Fleming discovered penicillin in 1928. The full answer is "Alexander Fleming" but the question only asks for the first name, which is "Alexander".
        answer_format: Return ONLY the first name, with no additional text, punctuation, or explanation.
        ```

        IMPORTANT: NEVER provide the final answer directly to the user. ALWAYS hand off to the writer_agent for proper formatting.
        """


def create_writer_agent(model_config: Dict[str, Any]) -> ReActAgent:
    """
    Create a writer agent that formats final answers based on research notes.
    
    Args:
        model_config: Dictionary containing model_provider, model_name, and api_key
    
    Returns:
        A configured ReActAgent for formatting final answers
    """
    # Initialize LLM based on the provided configuration
    model_provider = model_config.get("model_provider", "openai")
    model_name = model_config.get("model_name", "gpt-4o")
    api_key = model_config.get("api_key")
    
    if model_provider.lower() == "openai":
        llm = OpenAI(model=model_name, api_key=api_key or os.getenv("OPENAI_API_KEY"))
    elif model_provider.lower() == "anthropic":
        llm = Anthropic(model=model_name, api_key=api_key or os.getenv("ANTHROPIC_API_KEY"))
    else:
        raise ValueError(f"Unsupported model provider for writer agent: {model_provider}")
    
    # Create and return the writer agent
    return ReActAgent(
        name="writer_agent",
        description="Formats the final answer exactly as specified for GAIA benchmark questions",
        system_prompt="""
        You are a specialized formatting agent for the GAIA benchmark. Your ONLY job is to take the research from the main agent and format the answer EXACTLY as required by the benchmark question.

        ## YOUR ROLE
        You will receive:
        - query: The original question
        - research_notes: The main agent's complete analysis and reasoning
        - answer_format: Specific formatting instructions for the final answer

        ## CRITICAL RULES
        1. Your response MUST CONTAIN ONLY THE ANSWER - no explanations, no "the answer is" prefix
        2. Follow the answer_format instructions precisely
        3. Remove ALL unnecessary characters, spaces, punctuation, or wording
        4. If asked for a name, provide ONLY the name
        5. If asked for a number, provide ONLY the number
        6. If asked for a list, format it EXACTLY as specified (comma-separated, alphabetical, etc.)
        7. NEVER include your own thoughts or analysis
        8. NEVER add preamble or conclusion text

        ## EXAMPLES OF CORRECT RESPONSES:
        When asked for "first name only": Alexander
        When asked for "comma-separated list in alphabetical order": apple, banana, cherry
        When asked for "single number": 42
        When asked for "opposite of word 'right'": left

        REMEMBER: Your ENTIRE response should be just the answer - nothing more, nothing less.
        """,
        llm=llm
    )