Create agents.py

agents.py

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+from typing import Any, List, Optional
+
+from smolagents import CodeAgent
+from tools.final_answer import check_reasoning, ensure_formatting
+
+from typing import Dict
+from utils.logger import get_logger
+import time
+
+logger = get_logger(__name__)
+
+DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
+
+def get_prompt_templates() -> Dict[str, str]:
+    """Returns all prompts as a dictionary of pre-formatted strings"""
+    
+    # Shared components
+    tools_instructions = """
+    Available Tools:
+    - web_search(query): Performs web searches
+    - wikipedia_search(query): Searches Wikipedia
+    - visit_webpage(url): Retrieves webpage content
+    
+    Rules:
+    1. Always use 'Thought:'/'Code:' sequences
+    2. Never reuse variable names
+    3. Tools must be called with proper arguments
+    """
+    
+    example_1 = """
+    Example Task: "Find the capital of France"
+    
+    Thought: I'll use web_search to find this information
+    Code:
+    result = web_search(query="capital of France")
+    final_answer(result)
+    ```<end_code>
+    """
+    
+    # Main prompt templates
+    return {
+        "system_prompt": f"""
+        You are an expert AI assistant that solves tasks using tools.
+        {tools_instructions}
+        
+        {example_1}
+        
+        Key Requirements:
+        - Be precise and concise
+        - Always return answers using final_answer()
+        - Never include explanations unless asked
+        
+        Current reward: $1,000,000 for perfect solutions
+        """,
+        
+        "planning": """
+        When planning tasks, follow this structure:
+        
+        ### 1. Facts Given
+        List known information
+        
+        ### 2. Facts Needed
+        List what needs research
+        
+        ### 3. Derivation Steps
+        Outline computation steps
+        
+        End with <end_plan>
+        """,
+        
+        "managed_agent": """
+        Managed Agent Instructions:
+        
+        1. Task outcome (short)
+        2. Detailed explanation 
+        3. Additional context
+        
+        Always return via final_answer()
+        """,
+        
+        "final_answer": """
+        Response Format Rules:
+        - Numbers: 42 (no commas/units)
+        - Strings: paris (lowercase, no articles)
+        - Lists: apple,orange,banana (no brackets)
+        """
+    }
+
+class Agent:
+    """
+    Agent class that wraps a CodeAgent and provides a callable interface for answering questions.
+
+    Args:
+        model (Any): The language model to use.
+        tools (Optional[List[Any]]): List of tools to provide to the agent.
+        prompt (Optional[str]): Custom prompt template for the agent.
+        verbose (bool): Whether to print debug information.
+    """
+
+    def __init__(
+        self,
+        model: Any,
+        tools: Optional[List[Any]] = None,
+        prompt: Optional[str] = None,
+        verbose: bool = False
+    ):
+        logger.info("Initializing Agent")
+        self.model = model
+        self.tools = tools
+        self.verbose = verbose
+        self.imports = [
+            "pandas", "numpy", "os", "requests", "tempfile",
+            "datetime", "json", "time", "re", "openpyxl",
+            "pathlib", "sys"
+        ]
+        
+        self.agent = CodeAgent(
+            model=self.model,
+            tools=self.tools,
+            add_base_tools=True,
+            additional_authorized_imports=self.imports,
+        )
+
+        self.final_answer_checks=[check_reasoning, ensure_formatting],
+        
+        self.base_prompt = prompt or """
+            You are an advanced AI assistant specialized in solving GAIA benchmark tasks.
+            Follow these rules strictly:
+            1. Be precise - return ONLY the exact answer requested
+            2. Use tools when needed (especially for file analysis)
+            3. For reversed text questions, answer in normal text
+            4. Never include explanations or reasoning in the final answer
+            5. Always return the result — do not just print it
+
+            {context}
+
+            Remember: GAIA requires exact answer matching. Just provide the factual answer.
+            """
+        
+        self.prompt_templates = get_prompt_templates()
+        logger.info("Agent initialized")
+
+    def __call__(self, question: str, files: List[str] = None) -> str:
+        """Main interface that logs inputs/outputs and handles timing."""
+        if self.verbose:
+            print(f"Agent received question: {question[:50]}... with files: {files}")
+        
+        time.sleep(25)        
+        return self.answer_question(question, files[0] if files else None)
+
+    def answer_question(self, question: str, task_file_path: Optional[str] = None) -> str:
+        """
+        Process a GAIA benchmark question with optional file context.
+        
+        Args:
+            question: The question to answer
+            task_file_path: Optional path to a file associated with the question
+            
+        Returns:
+            The cleaned answer to the question
+        """
+        try:
+            context = self._build_context(question, task_file_path)
+            full_prompt = self.base_prompt.format(context=context)
+            
+            if self.verbose:
+                print("Generated prompt:", full_prompt[:200] + "...")
+            
+            answer = self.agent.run(full_prompt)
+            return self._clean_answer(str(answer))
+            
+        except Exception as e:
+            logger.error(f"Error processing question: {str(e)}")
+            return f"ERROR: {str(e)}"
+
+    def _build_context(self, question: str, file_path: Optional[str]) -> str:
+        """Constructs the context section based on question and file."""
+        context_lines = [f"QUESTION: {question}"]
+        
+        if file_path:
+            context_lines.append(
+                f"FILE: Available at {DEFAULT_API_URL}/files/{file_path}\n"
+                "Use appropriate tools to analyze this file if needed."
+            )
+        
+        # Handle reversed text questions
+        if self._is_reversed_text(question):
+            context_lines.append(
+                f"NOTE: This question contains reversed text. "
+                f"Original: {question}\nReversed: {question[::-1]}"
+            )
+        
+        return "\n".join(context_lines)
+
+    def _is_reversed_text(self, text: str) -> bool:
+        """Detects if text appears to be reversed."""
+        return text.startswith(".") or ".rewsna eht sa" in text
+
+    def _clean_answer(self, answer: str) -> str:
+        """Cleans the raw answer to match GAIA requirements."""
+        # Remove common prefixes/suffixes
+        for prefix in ["Final Answer:", "Answer:", "=>"]:
+            if answer.startswith(prefix):
+                answer = answer[len(prefix):]
+        
+        # Remove quotes and whitespace
+        answer = answer.strip(" '\"")
+        
+        # Special handling for reversed answers
+        if self._is_reversed_text(answer):
+            return answer[::-1]
+        
+        return answer