Create instructor.py

instructor.py

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+"""Instructor module for generating storytelling briefs from trending topics."""
+import os
+import json
+import logging
+from typing import Any, Dict, List, Optional
+from base_agent import BaseAgent
+from config import settings
+
+logger = logging.getLogger(__name__)
+
+class Instructor(BaseAgent):
+    """Instructor Agent: Fuses trending topics into storytelling briefs.
+    
+    This agent uses Instructor.md as a persistent pre-prompt and calls the 
+    DashScope API using the Qwen model specified in the environment.
+    """
+
+    def __init__(self):
+        """Initialize the Instructor agent with guidelines from Instructor.md."""
+        # Load guidelines from the root folder
+        content = self._load_instructor_md()
+        
+        # Construct the full system prompt (pre-prompt)
+        system_prompt = f"""You are the Instructor Agent, a master of viral storytelling and audience psychology.
+Your primary role is to take trending topics and fuse them into compelling, viral-ready storytelling briefs.
+
+### YOUR CORE PRINCIPLES (from Instructor.md):
+{content}
+
+### YOUR OBJECTIVE:
+1. Analyze the trending topics provided by the user.
+2. Synthesize these trends into a single, cohesive storytelling concept.
+3. Ensure the concept leverages human psychology (relatability, conflict, transformation).
+4. Output a structured JSON brief that will drive the multi-agent writing pipeline.
+
+### OUTPUT JSON STRUCTURE:
+{{
+    "user_brief": "The main story prompt/premise based on the trends.",
+    "hook_brief": "A specific 3-second hook to grab attention.",
+    "style_guide": "The visual and tonal style (e.g., 'TikTok relatable comedy').",
+    "character_bible": "Brief description of the key characters.",
+    "world_building_document": "The setting and world rules.",
+    "season_arc_document": "How this episode fits into a larger context.",
+    "character_voice_guide": "How characters should speak.",
+    "continuity_log": "The starting state of the world."
+}}
+"""
+        super().__init__(
+            agent_id="instructor",
+            agent_name="Instructor",
+            system_prompt=system_prompt
+        )
+
+    def _load_instructor_md(self) -> str:
+        """Load the Instructor.md file from the root directory."""
+        try:
+            # Look for Instructor.md in the current working directory (root)
+            path = "Instructor.md"
+            if not os.path.exists(path):
+                # Fallback to the directory of this file
+                path = os.path.join(os.path.dirname(__file__), "Instructor.md")
+            
+            with open(path, "r") as f:
+                return f.read()
+        except Exception as e:
+            logger.error(f"Failed to load Instructor.md: {str(e)}")
+            return "Master viral storytelling and audience psychology."
+
+    def generate_brief(self, trending_topics: List[str]) -> Dict[str, Any]:
+        """Generate a storytelling brief from trending topics using the LLM.
+
+        Args:
+            trending_topics: List of topics to fuse.
+
+        Returns:
+            Dictionary containing the brief fields.
+        """
+        inputs = {
+            "trending_topics": trending_topics,
+            "instruction": "Fuse these trending topics into a viral storytelling brief following your core principles."
+        }
+        
+        logger.info(f"[INSTRUCTOR] Calling DashScope API (Model: {settings.model_name}) to generate brief...")
+        
+        # Use the BaseAgent's process method which calls the LLM (DashScope/Qwen)
+        brief = self.process(inputs)
+        
+        # Validation and defaults for the pipeline
+        required = [
+            "user_brief", "hook_brief", "style_guide", "character_bible",
+            "world_building_document", "season_arc_document", 
+            "character_voice_guide", "continuity_log"
+        ]
+        
+        for field in required:
+            if field not in brief:
+                brief[field] = f"Auto-generated {field.replace('_', ' ')}."
+                
+        return brief