feat: Implement Pinecone vector store integration

- Update config.py with Pinecone settings and model configurations
- Implement VectorStore class with Pinecone backend
- Add comprehensive vector operations (add, search, delete)
- Set up proper error handling and metadata management
- Add .gitignore for Python project

backend/copywriter.py

@@ -0,0 +1,98 @@
+from transformers import pipeline
+from typing import List, Optional
+import torch
+from finetuned_model import finetuned_model
+
+class MarketingCopywriter:
+    def __init__(self):
+        # Use the finetuned model instead of the default GPT-2
+        self.model = finetuned_model
+        
+    def generate(
+        self,
+        prompt: str,
+        content_type: str,
+        similar_content: List[str],
+        tone: Optional[str] = None,
+    ) -> str:
+        # Generate the marketing copy using the finetuned model
+        generated_texts = self.model.generate_with_context(
+            prompt=prompt,
+            content_type=content_type,
+            similar_content=similar_content,
+            tone=tone,
+            max_length=500,
+            num_return_sequences=1,
+            temperature=0.7,
+            top_p=0.9
+        )
+        
+        # Return the first generated text
+        return generated_texts[0] if generated_texts else ""
+    
+    def _build_context(
+        self,
+        prompt: str,
+        content_type: str,
+        similar_content: List[str],
+        tone: Optional[str],
+        target_audience: Optional[str]
+    ) -> str:
+        context = f"Content Type: {content_type}\n"
+        if tone:
+            context += f"Tone: {tone}\n"
+        if target_audience:
+            context += f"Target Audience: {target_audience}\n"
+        
+        context += "\nSimilar Content Examples:\n"
+        for content in similar_content[:3]:  # Use top 3 similar content pieces
+            context += f"- {content}\n"
+        
+        context += f"\nGenerate marketing copy for: {prompt}\n"
+        return context
+    
+    def _post_process(self, text: str) -> str:
+        # Clean up the generated text
+        text = text.strip()
+        # Add any additional post-processing steps here
+        return text
+
+# Initialize the copywriter
+copywriter = MarketingCopywriter()
+
+def generate_marketing_copy(
+    prompt: str,
+    content_type: str,
+    similar_content: List[str],
+    tone: Optional[str] = None,
+    target_audience: Optional[str] = None
+) -> str:
+    """
+    Generate marketing copy based on the given parameters.
+    
+    Args:
+        prompt: The main prompt for content generation
+        content_type: Type of content (email, social media, etc.)
+        similar_content: List of similar content for context
+        tone: Optional tone specification
+        target_audience: Optional target audience specification
+    
+    Returns:
+        Generated marketing copy
+    """
+    return copywriter.generate(
+        prompt=prompt,
+        content_type=content_type,
+        similar_content=similar_content,
+        tone=tone,
+        target_audience=target_audience
+    ) 
+
+
+generate_marketing_copy(
+    prompt="Help me write a blog post about the benefits of using our product",
+    content_type="blog post",
+    similar_content=[],
+    tone="",
+    target_audience=""
+)