import json
import ai_client
import mma_prompts
import re

def generate_tickets(track_brief: str, module_skeletons: str) -> list[dict]:
 """
    Tier 2 (Tech Lead) call.
    Breaks down a Track Brief and module skeletons into discrete Tier 3 Tickets.
    """
 # 1. Set Tier 2 Model (Tech Lead - Flash)
 # 2. Construct Prompt
 system_prompt = mma_prompts.PROMPTS.get("tier2_sprint_planning")
 user_message = (
  f"### TRACK BRIEF:\n{track_brief}\n\n"
  f"### MODULE SKELETONS:\n{module_skeletons}\n\n"
  "Please generate the implementation tickets for this track."
 )
 # Set custom system prompt for this call
 old_system_prompt = ai_client._custom_system_prompt
 ai_client.set_custom_system_prompt(system_prompt)
 try:
 # 3. Call Tier 2 Model
  response = ai_client.send(
   md_content="", 
   user_message=user_message
  )
  # 4. Parse JSON Output
  # Extract JSON array from markdown code blocks if present
  json_match = response.strip()
  if "```json" in json_match:
   json_match = json_match.split("```json")[1].split("```")[0].strip()
  elif "```" in json_match:
   json_match = json_match.split("```")[1].split("```")[0].strip()
   # If it's still not valid JSON, try to find a [ ... ] block
  if not (json_match.startswith('[') and json_match.endswith(']')):
   match = re.search(r'\[\s*\{.*\}\s*\]', json_match, re.DOTALL)
   if match:
    json_match = match.group(0)
  tickets = json.loads(json_match)
  return tickets
 except Exception as e:
  print(f"Error parsing Tier 2 response: {e}")
  # print(f"Raw response: {response}")
  return []
 finally:
 # Restore old system prompt
  ai_client.set_custom_system_prompt(old_system_prompt)

from dag_engine import TrackDAG
from models import Ticket

def topological_sort(tickets: list[dict]) -> list[dict]:
 """
    Sorts a list of tickets based on their 'depends_on' field.
    Raises ValueError if a circular dependency or missing internal dependency is detected.
    """
 # 1. Convert to Ticket objects for TrackDAG
 ticket_objs = []
 for t_data in tickets:
  ticket_objs.append(Ticket.from_dict(t_data))
  # 2. Use TrackDAG for validation and sorting
 dag = TrackDAG(ticket_objs)
 try:
  sorted_ids = dag.topological_sort()
 except ValueError as e:
  raise ValueError(f"DAG Validation Error: {e}")
  # 3. Return sorted dictionaries
 ticket_map = {t['id']: t for t in tickets}
 return [ticket_map[tid] for tid in sorted_ids]

if __name__ == "__main__":
# Quick test if run directly
 test_brief = "Implement a new feature."
 test_skeletons = "class NewFeature: pass"
 tickets = generate_tickets(test_brief, test_skeletons)
 print(json.dumps(tickets, indent=2))