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| import os | |
| import re | |
| from datetime import datetime, timedelta | |
| from typing import TypedDict, Annotated | |
| import sympy as sp | |
| import math | |
| from langchain_openai import ChatOpenAI | |
| from langchain_community.tools.tavily_search import TavilySearchResults | |
| from langchain_core.messages import HumanMessage, SystemMessage | |
| # Load environment variables | |
| from dotenv import load_dotenv | |
| load_dotenv() | |
| def read_system_prompt(): | |
| """Read the system prompt from file""" | |
| try: | |
| with open('system_prompt.txt', 'r') as f: | |
| return f.read().strip() | |
| except FileNotFoundError: | |
| return """You are a helpful assistant tasked with answering questions using a set of tools. | |
| Now, I will ask you a question. Report your thoughts, and finish your answer with the following template: | |
| FINAL ANSWER: [YOUR FINAL ANSWER]. | |
| YOUR FINAL ANSWER should be a number 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 $ or percent sign unless specified otherwise. If you are asked for a string, don't use articles, neither abbreviations (e.g. for 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. | |
| Your answer should only start with "FINAL ANSWER: ", then follows with the answer.""" | |
| def math_calculator(expression: str) -> str: | |
| """ | |
| Advanced mathematical calculator that can handle complex expressions, | |
| equations, symbolic math, calculus, and more using SymPy. | |
| """ | |
| try: | |
| # Clean the expression | |
| expression = expression.strip() | |
| # Handle common mathematical operations and functions | |
| expression = expression.replace('^', '**') # Convert ^ to ** | |
| expression = expression.replace('ln', 'log') # Natural log | |
| # Try to evaluate as a symbolic expression first | |
| try: | |
| result = sp.sympify(expression) | |
| # If it's a symbolic expression that can be simplified | |
| simplified = sp.simplify(result) | |
| # Try to get numerical value | |
| try: | |
| numerical = float(simplified.evalf()) | |
| return str(numerical) | |
| except: | |
| return str(simplified) | |
| except: | |
| # Fall back to basic evaluation | |
| # Replace common math functions | |
| safe_expression = expression | |
| for func in ['sin', 'cos', 'tan', 'sqrt', 'log', 'exp', 'abs']: | |
| safe_expression = safe_expression.replace(func, f'math.{func}') | |
| # Evaluate safely | |
| result = eval(safe_expression, {"__builtins__": {}}, { | |
| "math": math, | |
| "pi": math.pi, | |
| "e": math.e | |
| }) | |
| return str(result) | |
| except Exception as e: | |
| return f"Error calculating '{expression}': {str(e)}" | |
| def date_time_processor(query: str) -> str: | |
| """ | |
| Process date and time related queries, calculations, and conversions. | |
| """ | |
| try: | |
| current_time = datetime.now() | |
| query_lower = query.lower() | |
| # Current date/time queries | |
| if 'current' in query_lower or 'today' in query_lower or 'now' in query_lower: | |
| if 'date' in query_lower: | |
| return current_time.strftime('%Y-%m-%d') | |
| elif 'time' in query_lower: | |
| return current_time.strftime('%H:%M:%S') | |
| else: | |
| return current_time.strftime('%Y-%m-%d %H:%M:%S') | |
| # Day of week queries | |
| if 'day of week' in query_lower or 'what day' in query_lower: | |
| return current_time.strftime('%A') | |
| # Year queries | |
| if 'year' in query_lower and 'current' in query_lower: | |
| return str(current_time.year) | |
| # Month queries | |
| if 'month' in query_lower and 'current' in query_lower: | |
| return current_time.strftime('%B') | |
| # Date arithmetic (simple cases) | |
| if 'days ago' in query_lower: | |
| days_match = re.search(r'(\d+)\s+days?\s+ago', query_lower) | |
| if days_match: | |
| days = int(days_match.group(1)) | |
| past_date = current_time - timedelta(days=days) | |
| return past_date.strftime('%Y-%m-%d') | |
| if 'days from now' in query_lower or 'days later' in query_lower: | |
| days_match = re.search(r'(\d+)\s+days?\s+(?:from now|later)', query_lower) | |
| if days_match: | |
| days = int(days_match.group(1)) | |
| future_date = current_time + timedelta(days=days) | |
| return future_date.strftime('%Y-%m-%d') | |
| # If no specific pattern matched, return current datetime | |
| return f"Current date and time: {current_time.strftime('%Y-%m-%d %H:%M:%S')}" | |
| except Exception as e: | |
| return f"Error processing date/time query: {str(e)}" | |
| # Removed LangGraph dependencies - using simpler approach | |
| class GAIAAgent: | |
| def __init__(self): | |
| # Check for required API keys | |
| openai_key = os.getenv("OPENAI_API_KEY") | |
| tavily_key = os.getenv("TAVILY_API_KEY") | |
| if not openai_key: | |
| raise ValueError("OPENAI_API_KEY environment variable is required") | |
| if not tavily_key: | |
| print("⚠️ TAVILY_API_KEY not found - web search will be disabled") | |
| self.has_search = False | |
| else: | |
| self.has_search = True | |
| print("✅ Initializing GAIA agent...") | |
| # Initialize LLM (using OpenAI GPT-4) | |
| self.llm = ChatOpenAI( | |
| model="gpt-4o-mini", | |
| temperature=0, | |
| openai_api_key=openai_key | |
| ) | |
| # Initialize search tool if available | |
| if self.has_search: | |
| self.search_tool = TavilySearchResults( | |
| max_results=5, | |
| tavily_api_key=tavily_key | |
| ) | |
| else: | |
| self.search_tool = None | |
| self.system_prompt = read_system_prompt() | |
| def _search_web(self, query: str) -> str: | |
| """Perform web search if available""" | |
| if not self.search_tool: | |
| return "Web search not available (no Tavily API key)" | |
| try: | |
| results = self.search_tool.invoke({"query": query}) | |
| if results and len(results) > 0: | |
| # Format the results nicely | |
| formatted_results = [] | |
| for i, result in enumerate(results[:3], 1): # Top 3 results | |
| if isinstance(result, dict): | |
| title = result.get('title', 'No title') | |
| content = result.get('content', 'No content') | |
| url = result.get('url', 'No URL') | |
| formatted_results.append(f"{i}. {title}\n {content}\n Source: {url}") | |
| else: | |
| formatted_results.append(f"{i}. {str(result)}") | |
| return "\n\n".join(formatted_results) | |
| else: | |
| return "No search results found" | |
| except Exception as e: | |
| return f"Search error: {str(e)}" | |
| def _is_math_problem(self, text: str) -> bool: | |
| """Check if the text contains mathematical expressions""" | |
| math_indicators = [ | |
| '+', '-', '*', '/', '^', '=', 'calculate', 'compute', | |
| 'solve', 'equation', 'integral', 'derivative', 'sum', | |
| 'sqrt', 'log', 'sin', 'cos', 'tan', 'exp' | |
| ] | |
| text_lower = text.lower() | |
| return any(indicator in text_lower for indicator in math_indicators) or \ | |
| re.search(r'\d+[\+\-\*/\^]\d+', text) is not None | |
| def _is_datetime_problem(self, text: str) -> bool: | |
| """Check if the text contains date/time related queries""" | |
| datetime_indicators = [ | |
| 'date', 'time', 'day', 'month', 'year', 'today', 'yesterday', | |
| 'tomorrow', 'current', 'now', 'ago', 'later', 'when' | |
| ] | |
| text_lower = text.lower() | |
| return any(indicator in text_lower for indicator in datetime_indicators) | |
| def __call__(self, question: str) -> str: | |
| """Process a question and return the answer""" | |
| try: | |
| print(f"Processing question: {question[:100]}...") | |
| # Check for file/media requirements that we can't handle | |
| if any(indicator in question.lower() for indicator in [ | |
| 'attached', 'audio', 'video', 'image', 'file', 'mp3', 'pdf', | |
| 'excel', 'spreadsheet', 'listen to', 'watch', 'download' | |
| ]): | |
| return "Unable to process files or media attachments" | |
| # Build the prompt based on question type | |
| enhanced_question = self._enhance_question(question) | |
| # Create messages | |
| messages = [ | |
| SystemMessage(content=self.system_prompt), | |
| HumanMessage(content=enhanced_question) | |
| ] | |
| # Get response from LLM | |
| response = self.llm.invoke(messages) | |
| response_content = response.content if hasattr(response, 'content') else str(response) | |
| # Extract the final answer | |
| final_answer = self._extract_final_answer(response_content) | |
| print(f"Final answer: {final_answer}") | |
| return final_answer | |
| except Exception as e: | |
| print(f"Error processing question: {e}") | |
| # Try to provide a meaningful fallback | |
| if "api" in str(e).lower() or "key" in str(e).lower(): | |
| return "Error: API key configuration issue" | |
| elif "tool" in str(e).lower(): | |
| return "Error: Tool execution issue" | |
| else: | |
| return f"Unable to process question due to technical error" | |
| def _enhance_question(self, question: str) -> str: | |
| """Enhance the question with relevant context and tools""" | |
| try: | |
| # Check if this is a math problem | |
| if self._is_math_problem(question): | |
| try: | |
| math_result = math_calculator(question) | |
| return f"Question: {question}\n\nMath calculation result: {math_result}\n\nBased on this calculation, provide your final answer using the format: FINAL ANSWER: [your answer]" | |
| except Exception as e: | |
| print(f"Math calculation error: {e}") | |
| # Check if this is a date/time problem | |
| elif self._is_datetime_problem(question): | |
| try: | |
| datetime_result = date_time_processor(question) | |
| return f"Question: {question}\n\nDate/time processing result: {datetime_result}\n\nBased on this information, provide your final answer using the format: FINAL ANSWER: [your answer]" | |
| except Exception as e: | |
| print(f"DateTime processing error: {e}") | |
| # Check if this needs web search | |
| elif self._needs_web_search(question): | |
| try: | |
| search_result = self._search_web(question) | |
| return f"Question: {question}\n\nWeb search results:\n{search_result}\n\nBased on this information, provide your final answer using the format: FINAL ANSWER: [your answer]" | |
| except Exception as e: | |
| print(f"Web search error: {e}") | |
| # For other questions, just add the format instruction | |
| return f"Question: {question}\n\nProvide your final answer using the format: FINAL ANSWER: [your answer]" | |
| except Exception as e: | |
| print(f"Question enhancement error: {e}") | |
| return f"Question: {question}\n\nProvide your final answer using the format: FINAL ANSWER: [your answer]" | |
| def _needs_web_search(self, text: str) -> bool: | |
| """Check if the question likely needs web search""" | |
| search_indicators = [ | |
| 'who', 'what', 'when', 'where', 'which', 'published', 'article', | |
| 'wikipedia', 'latest', 'recent', 'current', 'news', 'website', | |
| 'url', 'http', 'www', 'competition', 'olympics', 'award', | |
| 'winner', 'recipient', 'author', 'published in', 'paper', | |
| 'study', 'research', 'species', 'city', 'country' | |
| ] | |
| text_lower = text.lower() | |
| return any(indicator in text_lower for indicator in search_indicators) | |
| def _extract_final_answer(self, response: str) -> str: | |
| """Extract the final answer from the response""" | |
| if "FINAL ANSWER:" in response: | |
| # Find the final answer part | |
| parts = response.split("FINAL ANSWER:") | |
| if len(parts) > 1: | |
| answer = parts[-1].strip() | |
| # Remove any trailing punctuation or explanations | |
| answer = answer.split('\n')[0].strip() | |
| return answer | |
| # If no FINAL ANSWER format found, return the whole response | |
| return response.strip() | |
| # Create a function to get the agent (for use in app.py) | |
| def create_agent(): | |
| """Factory function to create the GAIA agent""" | |
| return GAIAAgent() |