Ed_
8d9f25d0ce
- ai_client: add current_tier module var; stamp source_tier on every _append_comms entry - multi_agent_conductor: set current_tier='Tier 3' around send(), clear in finally - conductor_tech_lead: set current_tier='Tier 2' around send(), clear in finally - gui_2: _on_tool_log captures current_tier; _append_tool_log stores dict with source_tier - tests: 8 new tests covering current_tier, source_tier in comms, tool log dict format
80 lines
2.6 KiB
Python
80 lines
2.6 KiB
Python
import json
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import ai_client
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import mma_prompts
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import re
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def generate_tickets(track_brief: str, module_skeletons: str) -> list[dict]:
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"""
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Tier 2 (Tech Lead) call.
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Breaks down a Track Brief and module skeletons into discrete Tier 3 Tickets.
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"""
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# 1. Set Tier 2 Model (Tech Lead - Flash)
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# 2. Construct Prompt
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system_prompt = mma_prompts.PROMPTS.get("tier2_sprint_planning")
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user_message = (
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f"### TRACK BRIEF:\n{track_brief}\n\n"
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f"### MODULE SKELETONS:\n{module_skeletons}\n\n"
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"Please generate the implementation tickets for this track."
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)
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# Set custom system prompt for this call
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old_system_prompt = ai_client._custom_system_prompt
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ai_client.set_custom_system_prompt(system_prompt)
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ai_client.current_tier = "Tier 2"
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try:
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# 3. Call Tier 2 Model
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response = ai_client.send(
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md_content="",
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user_message=user_message
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)
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# 4. Parse JSON Output
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# Extract JSON array from markdown code blocks if present
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json_match = response.strip()
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if "```json" in json_match:
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json_match = json_match.split("```json")[1].split("```")[0].strip()
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elif "```" in json_match:
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json_match = json_match.split("```")[1].split("```")[0].strip()
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# If it's still not valid JSON, try to find a [ ... ] block
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if not (json_match.startswith('[') and json_match.endswith(']')):
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match = re.search(r'\[\s*\{.*\}\s*\]', json_match, re.DOTALL)
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if match:
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json_match = match.group(0)
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tickets = json.loads(json_match)
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return tickets
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except Exception as e:
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print(f"Error parsing Tier 2 response: {e}")
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return []
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finally:
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# Restore old system prompt and clear tier tag
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ai_client.set_custom_system_prompt(old_system_prompt)
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ai_client.current_tier = None
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from dag_engine import TrackDAG
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from models import Ticket
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def topological_sort(tickets: list[dict]) -> list[dict]:
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"""
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Sorts a list of tickets based on their 'depends_on' field.
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Raises ValueError if a circular dependency or missing internal dependency is detected.
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"""
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# 1. Convert to Ticket objects for TrackDAG
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ticket_objs = []
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for t_data in tickets:
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ticket_objs.append(Ticket.from_dict(t_data))
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# 2. Use TrackDAG for validation and sorting
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dag = TrackDAG(ticket_objs)
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try:
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sorted_ids = dag.topological_sort()
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except ValueError as e:
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raise ValueError(f"DAG Validation Error: {e}")
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# 3. Return sorted dictionaries
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ticket_map = {t['id']: t for t in tickets}
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return [ticket_map[tid] for tid in sorted_ids]
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if __name__ == "__main__":
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# Quick test if run directly
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test_brief = "Implement a new feature."
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test_skeletons = "class NewFeature: pass"
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tickets = generate_tickets(test_brief, test_skeletons)
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print(json.dumps(tickets, indent=2))
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