AI generated first iteration

app/llm/prompts.py

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+"""LLM prompt templates and generation utilities."""
+
+from typing import Optional
+
+
+class PromptTemplates:
+    """Collection of prompt templates for different modes."""
+
+    @staticmethod
+    def gentle_prompt(current_theme: Optional[str] = None) -> str:
+        """Generate a gentle prompt when chat has been inactive."""
+        if current_theme:
+            return f"Gently prompt the chat about: {current_theme}"
+        return "Generate a gentle, inviting prompt to encourage discussion in the stream."
+
+    @staticmethod
+    def steward_response(message: str, context: Optional[str] = None) -> str:
+        """Generate a response as the Steward mode."""
+        prompt = f"As a thoughtful steward of this stream, respond briefly and helpfully to: {message}"
+        if context:
+            prompt += f"\nContext: {context}"
+        return prompt
+
+    @staticmethod
+    def warden_analysis(message: str) -> str:
+        """Generate analysis for suspicious content detection."""
+        return f"Analyze this message for suspicious patterns (spam, scams, manipulation): {message}"
+
+    @staticmethod
+    def librarian_summary(messages: list[str]) -> str:
+        """Generate a summary of important discussion points."""
+        messages_text = "\n".join(messages)
+        return f"Summarize the key discussion points from this chat log:\n{messages_text}"
+
+    @staticmethod
+    def scribe_ledger(
+        theme: str,
+        discussion: list[str],
+        actions: list[str],
+        clips: list[str],
+        seeds: list[str],
+    ) -> str:
+        """Generate markdown ledger summary."""
+        return f"""Generate a professional markdown ledger with these sections:
+- Theme: {theme}
+- Notable Discussion: {len(discussion)} key points
+- Agent Actions: {len(actions)} recorded
+- Clip Candidates: {len(clips)} identified
+- Blog Seeds: {len(seeds)} proposed"""
+
+    @staticmethod
+    def clip_candidate_reason(message: str) -> str:
+        """Generate reasoning for marking a message as a clip candidate."""
+        return f"Explain why this is a good clip candidate: {message}"
+
+    @staticmethod
+    def blog_seed_topic(context: list[str]) -> str:
+        """Generate a blog post topic from discussion context."""
+        context_text = "\n".join(context[:5])  # First 5 messages
+        return f"Based on this discussion, suggest a blog post topic:\n{context_text}"