Update utils/optimizer.py

utils/optimizer.py

@@ -78,8 +78,48 @@ class ContentOptimizer:
         )
 
         # Competitive content analysis prompt
-        self.competitive_analysis_prompt = ("Analyze the following content for AI search optimization gaps in entities, questions, clarity, flow, and semantic links. Return JSON with gaps and actionable recommendations.\nContent: {content}")
-
+        # self.competitive_analysis_prompt = ("Analyze the following content for AI search optimization gaps in entities, questions, clarity, flow, and semantic links. Return JSON with gaps and actionable recommendations.\nContent: {content}")
+        self.competitive_analysis_prompt = (
+            "Analyze the following content for AI search optimization gaps in entities, questions, clarity, flow, and semantic links. "
+            "Return JSON with gaps and actionable recommendations.\n"
+            "Content: {content}\n"
+            "Provide competitive analysis in JSON format:\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"
+        )
+        self.voice_prompt = (
+            """
+                Optimize this content for voice search and conversational AI systems.
+                Focus on:
+                1. Natural language patterns
+                2. Question-based structure
+                3. Conversational tone
+                4. Clear, direct answers
+                5. Featured snippet optimization
+                Original content: {content}
+                Provide optimization in JSON:
+                ```json
+                    {{
+                    "voice_optimized_content": "conversational version...",
+                    "question_answer_pairs": [
+                        {{"question": "What is...", "answer": "Direct answer..."}},
+                        {{"question": "How does...", "answer": "Step by step..."}}
+                    ],
+                    "featured_snippet_candidates": ["snippet 1", "snippet 2"],
+                    "natural_language_improvements": ["improvement 1", "improvement 2"],
+                    "conversational_score": 8.5
+                    }}
+                ```
+            """
+        )
 
     
         # Dedicated prompt for rewriting/optimizing content
@@ -108,9 +148,9 @@ class ContentOptimizer:
         """
         try:
             # Choose optimization approach
-            if optimization_type == "seo":
+            if optimization_type == "seo" and not analyze_only:
                 return self._seo_style_optimization(content, analyze_only)
-            elif optimization_type == "competitive":
+            elif optimization_type == "competitive" and not analyze_only:
                 return self._competitive_optimization(content)
             else:
                 return self._standard_optimization(content, analyze_only, include_keywords)
@@ -121,7 +161,8 @@ class ContentOptimizer:
     def _standard_optimization(self, content: str, analyze_only: bool, include_keywords: bool) -> Dict[str, Any]:
         """Standard content optimization using enhancement prompt"""
         try:
-            if analyze_only:
+            # Always assign prompt_text
+            if analyze_only is True:
                 prompt_text = self.enhancement_prompt
                 prompt_text = prompt_text.replace(
                     "Rewrite the text to improve:",
@@ -130,38 +171,37 @@ class ContentOptimizer:
                     '"optimized_text": "..."',
                     '"optimization_suggestions": ["suggestion 1", "suggestion 2"]'
                 )
-            # else:
-            #     # Use dedicated rewrite prompt for optimization
-            #     prompt_text = self.optimization_rewrite_prompt
-                
-            if not include_keywords:
-                prompt_text = prompt_text.replace(
-                    '"keywords": ["example", "installation", "setup"],',
-                    ''
-                )
+                if not include_keywords:
+                    prompt_text = prompt_text.replace(
+                        '"keywords": ["example", "installation", "setup"],',
+                        ''
+                    )
+            else:
+                # Use dedicated rewrite prompt for optimization
+                prompt_text = self.optimization_rewrite_prompt
 
-            prompt_template = ChatPromptTemplate.from_messages([
-                SystemMessagePromptTemplate.from_template(prompt_text),
-                HumanMessagePromptTemplate.from_template(content[:6000])
-            ])
+        prompt_template = ChatPromptTemplate.from_messages([
+            SystemMessagePromptTemplate.from_template(prompt_text),
+            HumanMessagePromptTemplate.from_template(content[:6000])
+        ])
 
-            chain = prompt_template | self.llm
-            result = chain.invoke({})
+        chain = prompt_template | self.llm
+        result = chain.invoke({})
 
-            result_content = result.content if hasattr(result, 'content') else str(result)
-            parsed_result = self._parse_optimization_result(result_content)
+        result_content = result.content if hasattr(result, 'content') else str(result)
+        parsed_result = self._parse_optimization_result(result_content)
 
-            parsed_result.update({
-                'optimization_type': 'standard',
-                'analyze_only': analyze_only,
-                'original_length': len(content),
-                'original_word_count': len(content.split())
-            })
+        parsed_result.update({
+            'optimization_type': 'standard',
+            'analyze_only': analyze_only,
+            'original_length': len(content),
+            'original_word_count': len(content.split())
+        })
 
-            return parsed_result
+        return parsed_result
 
-        except Exception as e:
-            return {'error': f"Standard optimization failed: {str(e)}"}
+    except Exception as e:
+        return {'error': f"Standard optimization failed: {str(e)}"}
     def _seo_style_optimization(self, content: str, analyze_only: bool) -> Dict[str, Any]:
         """SEO-focused optimization for AI search engines"""
         try:
@@ -432,7 +472,9 @@ class ContentOptimizer:
             Dict: Voice search optimization results
         """
         try:
-            self.voice_prompt = ("Optimize the following content for voice search and conversational AI by improving natural language flow, question-based structure, tone, and featured snippet potential. Return JSON with improved content, Q&A pairs, snippet candidates, and a conversational score.\nContent: {content}")
+            # self.voice_prompt = ("Optimize the following content for voice search and conversational AI by improving natural language flow, question-based structure, tone, and featured snippet potential. Return JSON with improved content, Q&A pairs, snippet candidates, and a conversational score.\nContent: {content}")
+            
+
             prompt_template = ChatPromptTemplate.from_messages([
                 SystemMessagePromptTemplate.from_template(voice_prompt.format(content=content[:4000])),
                 HumanMessagePromptTemplate.from_template("Optimize for voice search.")