Update utils/optimizer.py

utils/optimizer.py

@@ -6,7 +6,7 @@ Enhances content for better AI/LLM performance and GEO scores
 import json
 import re
 from typing import Dict, Any, List, Optional
-from langchain.prompts import ChatPromptTemplate
+from langchain.prompts import ChatPromptTemplate, SystemMessagePromptTemplate, HumanMessagePromptTemplate
 
 
 class ContentOptimizer:
@@ -18,7 +18,7 @@ class ContentOptimizer:
     
     def setup_prompts(self):
         """Initialize optimization prompts"""
-        
+
         # Main content enhancement prompt
         self.enhancement_prompt = (
             "You are an AI Content Enhancement Specialist. Your purpose is to optimize user-provided text to maximize its effectiveness for large language models (LLMs) in search, question-answering, and conversational AI systems."
@@ -44,49 +44,62 @@ class ContentOptimizer:
             "}}"
             "```"
         )
-        
-      self.seo_style_prompt = ("You are an AI-first SEO specialist. Optimize this content for AI search engines and LLM systems."
-                                "Focus on:"
-                                "1. Semantic keyword optimization"
-                                "2. Question-answer format enhancement"
-                                "3. Factual accuracy and authority signals"
-                                "4. Conversational readiness"
-                                "5. Citation-worthy structure"
-                               " Provide analysis and optimization in JSON:"
-                                "```json"
-                                "{"
-                                "seo_analysis: {"
-                                "keyword_density: analysis of current keywords,"
-                                "semantic_gaps: [missing semantic terms],"
-                                "readability_score: 8.5,"
-                                "authority_signals : [credentials,  citations]"
-                                "},"
-                                "optimized_content: {"
-                                "title_suggestions: [optimized title 1, optimized title 2],"
-                                "meta_description: AI-optimized meta description,"
-                                "enhanced_content: full optimized content...,"
-                                "structured_data_suggestions: [schema markup recommendations]"
-                                "},"
-                                "improvement_summary: {"
-                                "changes_made: [change 1, change 2],"
-                                "expected_impact: description of expected improvements"
-                                "}"
-                                "}"
-                                "```"
-                            )
+
+        # SEO-style optimization prompt
+        self.seo_style_prompt = (
+            "You are an AI-first SEO specialist. Optimize this content for AI search engines and LLM systems. "
+            "Focus on:\n"
+            "1. Semantic keyword optimization\n"
+            "2. Question-answer format enhancement\n"
+            "3. Factual accuracy and authority signals\n"
+            "4. Conversational readiness\n"
+            "5. Citation-worthy structure\n"
+            "Provide analysis and optimization in JSON:\n"
+            "```json\n"
+            "{{\n"
+            "  \"seo_analysis\": {{\n"
+            "    \"keyword_density\": \"analysis of current keywords\",\n"
+            "    \"semantic_gaps\": [\"missing semantic terms\"],\n"
+            "    \"readability_score\": 8.5,\n"
+            "    \"authority_signals\": [\"credentials\", \"citations\"]\n"
+            "  }},\n"
+            "  \"optimized_content\": {{\n"
+            "    \"title_suggestions\": [\"optimized title 1\", \"optimized title 2\"],\n"
+            "    \"meta_description\": \"AI-optimized meta description\",\n"
+            "    \"enhanced_content\": \"full optimized content...\",\n"
+            "    \"structured_data_suggestions\": [\"schema markup recommendations\"]\n"
+            "  }},\n"
+            "  \"improvement_summary\": {{\n"
+            "    \"changes_made\": [\"change 1\", \"change 2\"],\n"
+            "    \"expected_impact\": \"description of expected improvements\"\n"
+            "  }}\n"
+            "}}\n"
+            "```"
+        )
+
+        # Competitive content analysis prompt
+        self.competitive_analysis_prompt = (
+            "Compare this content against best practices for AI search optimization. Identify gaps and opportunities.\n"
+            "Original Content: {content}\n"
+            "Analyze against these AI search factors:\n"
+            "- Entity recognition and linking\n"
+            "- Question coverage completeness\n"
+            "- Factual statement clarity\n"
+            "- Conversational flow\n"
+            "- Semantic relationship mapping\n\n"
+            "Provide competitive analysis in JSON format with specific recommendations:\n"
+            "{{\n"
+            "  \"competitive_analysis\": {{\n"
+            "    \"entity_gaps\": [\"gap1\", \"gap2\"],\n"
+            "    \"question_coverage\": \"summary of coverage\",\n"
+            "    \"factual_clarity\": \"assessment\",\n"
+            "    \"conversational_flow\": \"assessment\",\n"
+            "    \"semantic_relationships\": [\"relationship1\", \"relationship2\"]\n"
+            "  }},\n"
+            "  \"recommendations\": [\"recommendation 1\", \"recommendation 2\"]\n"
+            "}}\n"
+        )
     
-    # Competitive content analysis prompt
-    self.competitive_analysis_prompt =( "Compare this content against best practices for AI search optimization. Identify gaps and opportunities."
-                                        "Original Content: {content}"
-                                        "Analyze against these AI search factors:"
-                                        "- Entity recognition and linking"
-                                        "- Question coverage completeness"
-                                        "- Factual statement clarity"
-                                        "- Conversational flow"
-                                        "- Semantic relationship mapping"
-                                        
-                                        "Provide competitive analysis in JSON format with specific recommendations."
-                                    )
     def optimize_content(self, content: str, analyze_only: bool = False, 
                         include_keywords: bool = True, optimization_type: str = "standard") -> Dict[str, Any]:
         """
@@ -134,9 +147,11 @@ class ContentOptimizer:
             
             # Create and run chain
             prompt_template = ChatPromptTemplate.from_messages([
-                ("system", prompt_text),
-                ("user", content[:6000])  # Limit content length
+                 SystemMessagePromptTemplate.from_template(prompt_text),
+                HumanMessagePromptTemplate.from_template(content[:6000])  # Limit content length
             ])
+                # ("system", prompt_text),
+                # ("user", content[:6000])  # Limit content length
             
             chain = prompt_template | self.llm
             result = chain.invoke({})