Open Census MCP Server

# quick_retest.py """ Quick retest of the 3 failed concepts with improved candidate selection """ import os from llm_mapper import LLMConceptMapper def quick_retest(): """Test the 3 concepts that failed in Step 3""" api_key = os.getenv('OPENAI_API_KEY') if not api_key: print("❌ Need OPENAI_API_KEY to test LLM mapping") return mapper = LLMConceptMapper(api_key=api_key) failed_concepts = [ { "name": "MedianHouseholdIncome", "definition": "The median income of all households in a geographic area" }, { "name": "PovertyRate", "definition": "Percentage of population below the federal poverty line" }, { "name": "EducationalAttainment", "definition": "Highest level of education completed by individuals" } ] print("🔄 Quick Retest of Failed Concepts") print("=" * 50) successful = 0 for i, concept_info in enumerate(failed_concepts, 1): concept = concept_info["name"] definition = concept_info["definition"] print(f"\n📊 [{i}/3] Testing: {concept}") try: result = mapper.map_concept_to_variables(concept, definition) if result.confidence > 0: successful += 1 print(f" ✅ SUCCESS! Confidence: {result.confidence:.2f}") print(f" 📋 Variables: {result.census_variables}") print(f" 💭 Reasoning: {result.reasoning[:80]}...") else: print(f" ❌ Still failing: {result.reasoning[:80]}...") except Exception as e: print(f" ❌ Error: {e}") print(f"\n" + "=" * 50) print(f"📊 RETEST SUMMARY: {successful}/3 concepts now working") if successful == 3: print("🎉 EXCELLENT! All problem concepts fixed") print(" Ready to rerun full Step 3 proof of concept") elif successful >= 2: print("⚡ GOOD progress! Most concepts working") print(" Consider rerunning Step 3 or proceeding") else: print("🔧 Still needs work on LLM prompting") if __name__ == "__main__": quick_retest()