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Update smolagents_agent.py
Browse files- smolagents_agent.py +172 -270
smolagents_agent.py
CHANGED
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@@ -1,339 +1,240 @@
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import os
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import re
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-
import math
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import pandas as pd
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from typing import Optional
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from dotenv import load_dotenv
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from smolagents import
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from smolagents import DuckDuckGoSearchTool, VisitWebpageTool, InferenceClientModel
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# Load environment variables
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load_dotenv()
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# -------------------------
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#
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# -------------------------
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class RobustCalculatorTool(Tool):
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name = "robust_calculator"
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description = "Perform mathematical calculations with error handling"
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inputs = {"expression": {"type": "string", "description": "Math expression"}}
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output_type = "string"
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def forward(self, expression: str) -> str:
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try:
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# Clean expression
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expr = expression.strip()
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expr = re.sub(r'\s+', '', expr) # Remove all whitespace
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# Safe replacements only
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replacements = {
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'sin': 'math.sin', 'cos': 'math.cos', 'tan': 'math.tan',
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'log': 'math.log', 'sqrt': 'math.sqrt', 'pi': 'math.pi', 'e': 'math.e',
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'^': '**', 'ln': 'math.log'
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}
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for old, new in replacements.items():
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expr = expr.replace(old, new)
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# Very restrictive evaluation
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allowed_names = {
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'math': math, 'abs': abs, 'min': min, 'max': max,
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'round': round, 'sum': sum, 'pow': pow
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}
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result = eval(expr, {"__builtins__": {}}, allowed_names)
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return str(result)
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except Exception as e:
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return f"Calculation error: {str(e)}"
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class SafeWebSearchTool(Tool):
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name = "safe_web_search"
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description = "Safe web search with error handling"
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inputs = {"query": {"type": "string", "description": "Search query"}}
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output_type = "string"
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def forward(self, query: str) -> str:
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try:
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search_tool = DuckDuckGoSearchTool()
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result = search_tool.forward(query)
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if isinstance(result, str):
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# Limit result length
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if len(result) > 500:
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result = result[:500] + "..."
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return result
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return "Search completed"
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except Exception as e:
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return f"Search error: {str(e)}"
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class SafeWikipediaTool(Tool):
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name = "safe_wikipedia"
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description = "Safe Wikipedia search with error handling"
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inputs = {"query": {"type": "string", "description": "Search query"}}
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output_type = "string"
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def forward(self, query: str) -> str:
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try:
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import wikipedia
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summary = wikipedia.summary(query, sentences=2)
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if len(summary) > 300:
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summary = summary[:300] + "..."
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return summary
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except Exception as e:
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return f"Wikipedia error: {str(e)}"
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class SafeVisitWebpageTool(Tool):
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name = "safe_visit_webpage"
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description = "Safe webpage visit with error handling"
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inputs = {"url": {"type": "string", "description": "URL to visit"}}
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output_type = "string"
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def forward(self, url: str) -> str:
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try:
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visit_tool = VisitWebpageTool()
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result = visit_tool.forward(url)
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if isinstance(result, str) and len(result) > 500:
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return result[:500] + "..."
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return str(result) if result else "Page content not available"
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except Exception as e:
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return f"Visit error: {str(e)}"
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class SafeImageProcessorTool(Tool):
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name = "safe_image_processor"
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description = "Safe image processing with error handling"
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inputs = {
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"image_path": {"type": "string", "description": "Image path or URL"},
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"operation": {"type": "string", "description": "Operation type", "default": "analyze"}
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}
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output_type = "string"
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def forward(self, image_path: str, operation: str = "analyze") -> str:
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try:
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if operation == "analyze":
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return f"Image analysis: {image_path} - Processing image content for task completion"
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else:
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return f"Image {operation}: {image_path} - Operation completed"
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except Exception as e:
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return f"Image processing error: {str(e)}"
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# -------------------------
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# Comprehensive Error Handling Agent
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# -------------------------
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class OptimizedSmolagentsGAIAgent:
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def __init__(self):
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# Initialize
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self.calculator = RobustCalculatorTool()
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self.web_search = SafeWebSearchTool()
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self.wikipedia = SafeWikipediaTool()
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self.visit_webpage = SafeVisitWebpageTool()
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self.image_processor = SafeImageProcessorTool()
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self.tools = [
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self.calculator,
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self.web_search,
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self.wikipedia,
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self.visit_webpage,
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self.image_processor
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]
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# Initialize Hugging Face model with multiple fallbacks
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self.model = self._initialize_model()
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#
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self.
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def _initialize_model(self):
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"""Initialize model with multiple
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hf_token = os.getenv("HF_TOKEN")
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if not hf_token:
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print("HF_TOKEN not found. Using fallback mode.")
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return None
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#
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model_options = [
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{"timeout": 30} # Fallback without specific model
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]
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for
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try:
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model = InferenceClientModel(
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token=hf_token,
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)
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print(f"Using model: {
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return model
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except Exception as e:
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print(f"Failed to initialize {
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continue
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print("All model initialization attempts failed")
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return None
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def
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"""
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try:
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self.agent = CodeAgent(
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tools=self.tools,
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model=self.model,
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max_steps=5, # Reduced steps to prevent errors
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verbosity_level=0 # Minimal verbosity
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)
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print("Agent initialized successfully")
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except Exception as e:
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print(f"Agent initialization failed: {e}")
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self.agent = None
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def _generate_safe_prompt(self, question: str) -> str:
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"""Generate a safe, structured prompt to prevent code generation errors"""
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#
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elif any(word in question_lower for word in ['search', 'find', 'web', 'google']):
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prompt = f"""Search for information using safe web search tools.
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Question: {question}
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Instructions:
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- Use safe_web_search tool for web searches
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- Use safe_wikipedia tool for Wikipedia information
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- Provide a concise, factual answer"""
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elif any(word in question_lower for word in ['who is', 'what is', 'when', 'where']):
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prompt = f"""Find factual information about this topic.
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Question: {question}
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Instructions:
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- Use safe_wikipedia tool for reliable information
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- Use safe_web_search tool if additional info is needed
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- Provide a clear, factual response"""
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elif 'http' in question or 'www.' in question:
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- Provide a summary of findings"""
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elif any(word in question_lower for word in ['image', 'picture', 'visual']):
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prompt = f"""Analyze image content if provided.
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Question: {question}
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Instructions:
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- Use safe_image_processor tool for image analysis
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- Describe what you can determine from the image
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- Provide a focused answer"""
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else:
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prompt = f"""Answer this question using available tools safely.
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def
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"""
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# If no code blocks, return as-is
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if "```" not in result:
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return result
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# Only wrap actual markdown code blocks, never natural language
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try:
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import
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code_pattern = r'```(?:python)?\n(.*?)\n```'
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matches = re.findall(code_pattern, result, re.DOTALL)
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code_content = match.strip()
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if code_content and not any(phrase in code_content.lower() for phrase in [
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'the', 'and', 'or', 'but', 'then', 'now', 'here', 'there'
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]):
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# Only wrap if it looks like actual code
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wrapped_code = f"<code>{code_content}</code>"
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formatted_result = formatted_result.replace(f"```{code_content}```", wrapped_code)
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return formatted_result
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def process_question(self, question: str) -> str:
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"""Process question
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# Handle no model case
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if not self.model:
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return "No language model available. Please set HF_TOKEN in environment variables."
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# Handle no agent case
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if not self.agent:
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return "Agent not properly initialized. Please check configuration."
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try:
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#
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#
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result_str = str(result)
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formatted_result = self._safe_response_formatting(result_str)
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return formatted_result
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except Exception as e:
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error_msg = str(e)
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# Specific error handling
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if "timeout" in error_msg.lower()
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return "Request timed out. The question may be too complex. Please try a simpler question."
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elif "500" in error_msg
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return "Server error occurred. This may be a temporary issue. Please try again later."
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elif "syntax" in error_msg.lower() or "parsing" in error_msg.lower():
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return "Unable to process this question format. Please try rephrasing the question."
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elif "tool" in error_msg.lower() and "not found" in error_msg.lower():
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return "Required tools are not available for this question type."
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else:
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# General error handling
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return f"Unable to process question: {error_msg[:200]}"
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# -------------------------
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# Test the
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# -------------------------
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if __name__ == "__main__":
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@@ -341,12 +242,13 @@ if __name__ == "__main__":
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test_questions = [
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"What is the capital of France?",
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"Calculate 15 + 27 * 3",
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"
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"
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]
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print("===
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for question in test_questions:
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print(f"Q: {question}")
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import os
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import re
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from typing import Optional
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from dotenv import load_dotenv
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from smolagents import InferenceClientModel
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# Load environment variables
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load_dotenv()
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# -------------------------
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# Direct Tool-Based Agent (No Code Generation)
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# -------------------------
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class OptimizedSmolagentsGAIAgent:
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"""
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A direct agent that uses tools without code generation.
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This avoids all the syntax and runtime errors from generated code.
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"""
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+
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def __init__(self):
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# Initialize model
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self.model = self._initialize_model()
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# Available tools
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self.tools = {
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'calculator': self._safe_calculate,
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'web_search': self._safe_web_search,
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'wikipedia': self._safe_wikipedia_search,
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'visit_webpage': self._safe_visit_webpage,
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'image_analysis': self._safe_image_analysis
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}
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def _initialize_model(self):
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"""Initialize model with multiple fallbacks"""
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hf_token = os.getenv("HF_TOKEN")
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if not hf_token:
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print("HF_TOKEN not found. Using fallback mode.")
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return None
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# Try multiple models for reliability
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model_options = [
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"allenai/Olmo-3-7B-Instruct",
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"allenai/Olmo-3-7B-Think"
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]
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for model in model_options:
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try:
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model = InferenceClientModel(
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model_id=model,
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token=hf_token,
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timeout=30
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)
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print(f"Using model: {model}")
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return model
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except Exception as e:
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print(f"Failed to initialize {model}: {e}")
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continue
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return None
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+
def _classify_question(self, question: str) -> str:
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"""Classify question type for appropriate tool selection"""
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q_lower = question.lower()
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# Mathematical questions
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if any(word in q_lower for word in ['calculate', 'compute', 'solve', '+', '-', '*', '/', '=']):
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return 'math'
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| 69 |
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# Web search questions
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elif any(word in q_lower for word in ['search', 'find', 'recent', 'current', 'today']):
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| 71 |
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return 'search'
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| 72 |
+
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| 73 |
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# Factual/Wikipedia questions
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| 74 |
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elif any(word in q_lower for word in ['who is', 'what is', 'when', 'where', 'history', 'biography']):
|
| 75 |
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return 'wikipedia'
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| 76 |
+
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| 77 |
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# Webpage questions
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| 78 |
elif 'http' in question or 'www.' in question:
|
| 79 |
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return 'webpage'
|
| 80 |
+
|
| 81 |
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# Image questions
|
| 82 |
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elif any(word in q_lower for word in ['image', 'picture', 'photo', 'visual', 'chess']):
|
| 83 |
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return 'image'
|
| 84 |
+
|
| 85 |
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# Default to search for general questions
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|
| 86 |
else:
|
| 87 |
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return 'search'
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|
| 88 |
|
| 89 |
+
def _safe_calculate(self, question: str) -> str:
|
| 90 |
+
"""Safe calculation using basic math"""
|
| 91 |
+
try:
|
| 92 |
+
# Extract math expressions
|
| 93 |
+
math_pattern = r'[\d\+\-\*\/\.\(\)\s]+'
|
| 94 |
+
match = re.search(math_pattern, question)
|
| 95 |
+
if match:
|
| 96 |
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expr = match.group().strip()
|
| 97 |
+
# Only allow basic arithmetic
|
| 98 |
+
if re.match(r'^[\d\+\-\*\/\.\(\)\s]+$', expr):
|
| 99 |
+
result = eval(expr)
|
| 100 |
+
return f"The calculation result is: {result}"
|
| 101 |
+
return "No clear mathematical expression found in the question."
|
| 102 |
+
except Exception as e:
|
| 103 |
+
return f"Unable to calculate: {str(e)}"
|
| 104 |
|
| 105 |
+
def _safe_web_search(self, question: str) -> str:
|
| 106 |
+
"""Safe web search with error handling"""
|
| 107 |
+
try:
|
| 108 |
+
from smolagents import DuckDuckGoSearchTool
|
| 109 |
+
search_tool = DuckDuckGoSearchTool()
|
| 110 |
+
|
| 111 |
+
# Clean the query for search
|
| 112 |
+
query = re.sub(r'[^a-zA-Z0-9\s]', '', question)
|
| 113 |
+
if len(query) > 100:
|
| 114 |
+
query = query[:100]
|
| 115 |
+
|
| 116 |
+
result = search_tool.forward(query)
|
| 117 |
+
if isinstance(result, str):
|
| 118 |
+
if len(result) > 300:
|
| 119 |
+
result = result[:300] + "..."
|
| 120 |
+
return f"Search results for '{query}': {result}"
|
| 121 |
+
return "Search completed successfully."
|
| 122 |
+
except Exception as e:
|
| 123 |
+
return f"Web search error: {str(e)}"
|
| 124 |
|
| 125 |
+
def _safe_wikipedia_search(self, question: str) -> str:
|
| 126 |
+
"""Safe Wikipedia search with error handling"""
|
| 127 |
+
try:
|
| 128 |
+
import wikipedia
|
| 129 |
+
|
| 130 |
+
# Extract search terms
|
| 131 |
+
if 'who is' in question.lower():
|
| 132 |
+
query = question.lower().replace('who is', '').strip()
|
| 133 |
+
elif 'what is' in question.lower():
|
| 134 |
+
query = question.lower().replace('what is', '').strip()
|
| 135 |
+
else:
|
| 136 |
+
query = question.strip()
|
| 137 |
+
|
| 138 |
+
if query:
|
| 139 |
+
summary = wikipedia.summary(query, sentences=2)
|
| 140 |
+
if len(summary) > 200:
|
| 141 |
+
summary = summary[:200] + "..."
|
| 142 |
+
return f"Information about '{query}': {summary}"
|
| 143 |
+
return "Unable to extract search terms from question."
|
| 144 |
+
except Exception as e:
|
| 145 |
+
return f"Wikipedia search error: {str(e)}"
|
| 146 |
|
| 147 |
+
def _safe_visit_webpage(self, question: str) -> str:
|
| 148 |
+
"""Safe webpage visiting with error handling"""
|
|
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|
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|
|
|
|
|
| 149 |
try:
|
| 150 |
+
from smolagents import VisitWebpageTool
|
| 151 |
+
visit_tool = VisitWebpageTool()
|
|
|
|
|
|
|
| 152 |
|
| 153 |
+
# Extract URL from question
|
| 154 |
+
url_pattern = r'https?://[^\s\)]+'
|
| 155 |
+
urls = re.findall(url_pattern, question)
|
|
|
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|
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|
|
| 156 |
|
| 157 |
+
if urls:
|
| 158 |
+
url = urls[0]
|
| 159 |
+
result = visit_tool.forward(url)
|
| 160 |
+
if isinstance(result, str):
|
| 161 |
+
if len(result) > 200:
|
| 162 |
+
result = result[:200] + "..."
|
| 163 |
+
return f"Content from {url}: {result}"
|
| 164 |
+
return f"Successfully visited {url}"
|
| 165 |
+
return "No URL found in the question."
|
| 166 |
+
except Exception as e:
|
| 167 |
+
return f"Webpage visit error: {str(e)}"
|
| 168 |
+
|
| 169 |
+
def _safe_image_analysis(self, question: str) -> str:
|
| 170 |
+
"""Safe image analysis with error handling"""
|
| 171 |
+
try:
|
| 172 |
+
# For chess questions
|
| 173 |
+
if 'chess' in question.lower():
|
| 174 |
+
return "Chess position analysis: This appears to be a chess-related question. Black's turn means black pieces need to make the next move. Without the actual board image, I cannot provide the specific move, but typical strategic considerations include developing pieces, controlling center, or_castling."
|
| 175 |
|
| 176 |
+
# For general image questions
|
| 177 |
+
elif any(word in question.lower() for word in ['image', 'picture', 'photo']):
|
| 178 |
+
return "Image analysis: The question references image content that I cannot directly access. For visual analysis tasks, please describe what you can see in the image or provide specific details about the visual elements."
|
| 179 |
+
|
| 180 |
+
else:
|
| 181 |
+
return "Image processing: Unable to analyze image content directly. Please provide more details about what visual information you need."
|
| 182 |
+
except Exception as e:
|
| 183 |
+
return f"Image analysis error: {str(e)}"
|
| 184 |
+
|
| 185 |
+
def _generate_direct_answer(self, question: str, question_type: str) -> str:
|
| 186 |
+
"""Generate direct answers without code generation"""
|
| 187 |
+
|
| 188 |
+
if question_type == 'math':
|
| 189 |
+
return self._safe_calculate(question)
|
| 190 |
+
|
| 191 |
+
elif question_type == 'search':
|
| 192 |
+
return self._safe_web_search(question)
|
| 193 |
+
|
| 194 |
+
elif question_type == 'wikipedia':
|
| 195 |
+
return self._safe_wikipedia_search(question)
|
| 196 |
+
|
| 197 |
+
elif question_type == 'webpage':
|
| 198 |
+
return self._safe_visit_webpage(question)
|
| 199 |
+
|
| 200 |
+
elif question_type == 'image':
|
| 201 |
+
return self._safe_image_analysis(question)
|
| 202 |
+
|
| 203 |
+
else:
|
| 204 |
+
# Default fallback
|
| 205 |
+
return self._safe_web_search(question)
|
| 206 |
|
| 207 |
def process_question(self, question: str) -> str:
|
| 208 |
+
"""Process question using direct tool approach (no code generation)"""
|
| 209 |
|
| 210 |
# Handle no model case
|
| 211 |
if not self.model:
|
| 212 |
return "No language model available. Please set HF_TOKEN in environment variables."
|
| 213 |
|
|
|
|
|
|
|
|
|
|
|
|
|
| 214 |
try:
|
| 215 |
+
# Classify question type
|
| 216 |
+
question_type = self._classify_question(question)
|
| 217 |
|
| 218 |
+
# Generate direct answer using appropriate tool
|
| 219 |
+
answer = self._generate_direct_answer(question, question_type)
|
|
|
|
| 220 |
|
| 221 |
+
return answer
|
|
|
|
|
|
|
|
|
|
| 222 |
|
| 223 |
except Exception as e:
|
| 224 |
error_msg = str(e)
|
| 225 |
|
| 226 |
# Specific error handling
|
| 227 |
+
if "timeout" in error_msg.lower():
|
| 228 |
return "Request timed out. The question may be too complex. Please try a simpler question."
|
| 229 |
|
| 230 |
+
elif "500" in error_msg:
|
| 231 |
return "Server error occurred. This may be a temporary issue. Please try again later."
|
| 232 |
|
|
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|
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|
| 233 |
else:
|
|
|
|
| 234 |
return f"Unable to process question: {error_msg[:200]}"
|
| 235 |
|
| 236 |
# -------------------------
|
| 237 |
+
# Test the direct tool agent
|
| 238 |
# -------------------------
|
| 239 |
|
| 240 |
if __name__ == "__main__":
|
|
|
|
| 242 |
|
| 243 |
test_questions = [
|
| 244 |
"What is the capital of France?",
|
| 245 |
+
"Calculate 15 + 27 * 3",
|
| 246 |
+
"Who is Mercedes Sosa?",
|
| 247 |
+
"Review the chess position in the image",
|
| 248 |
+
"What does this webpage say: https://example.com"
|
| 249 |
]
|
| 250 |
|
| 251 |
+
print("=== DIRECT TOOL AGENT TEST ===\n")
|
| 252 |
|
| 253 |
for question in test_questions:
|
| 254 |
print(f"Q: {question}")
|