feat: v2 plan — remove autogen/crewai, add tasks and wiki

- Remove autogen and crewai backends (focus on custom only)
- Simplify CLI: remove --backend flag
- Remove optional deps from pyproject.toml
- Add .tasks/ with 7 tasks for Phase 1 refactor
- Add .wiki/concepts/meeting-room-v2.md with architecture plan
- Update .wiki/index.md and .tasks/STATUS.md

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>

meeting_room/backends/autogen/run.py

@@ -1,60 +0,0 @@
-"""AutoGen backend — uses microsoft/autogen for multi-agent conversation."""
-
-
-def check_installed():
-    try:
-        import autogen  # noqa
-        return True
-    except ImportError:
-        return False
-
-
-def run(scenario_path: str, config: dict):
-    if not check_installed():
-        print("AutoGen is not installed. Run:\n  pip install meeting-room[autogen]")
-        return []
-
-    import yaml
-    import autogen
-    from meeting_room.api_client import init_providers
-    from meeting_room.scenario_loader import load_scenario
-
-    scenario = load_scenario(scenario_path)
-    init_providers(config)
-    roles = config["roles"]
-    participants = scenario.get("participants", list(roles.keys()))
-
-    llm_configs = {}
-    for prov_name, prov_cfg in config["providers"].items():
-        llm_configs[prov_name] = {
-            "base_url": prov_cfg["base_url"],
-            "api_key": prov_cfg["api_key"],
-        }
-
-    agents = []
-    for role_id in participants:
-        role = roles[role_id]
-        prov = role["provider"]
-        llm_cfg = dict(llm_configs[prov])
-        llm_cfg["model"] = role["model"]
-
-        agent = autogen.ConversableAgent(
-            name=role["name"],
-            system_message=role["system_prompt"].strip(),
-            llm_config={"config_list": [llm_cfg], "temperature": role.get("temperature", 0.7)},
-            human_input_mode="NEVER",
-        )
-        agents.append(agent)
-
-    groupchat = autogen.GroupChat(
-        agents=agents,
-        messages=[],
-        max_round=scenario.get("max_rounds", config["defaults"]["max_rounds"]),
-    )
-    manager = autogen.GroupChatManager(
-        groupchat=groupchat,
-        llm_config={"config_list": [llm_configs[participants[0]]]},
-    )
-
-    agents[0].initiate_chat(manager, message=scenario["problem"])
-    return groupchat.messages

meeting_room/backends/crewai/run.py

@@ -1,53 +0,0 @@
-"""CrewAI backend — uses crewai for task-oriented multi-agent discussion."""
-
-
-def check_installed():
-    try:
-        import crewai  # noqa
-        return True
-    except ImportError:
-        return False
-
-
-def run(scenario_path: str, config: dict):
-    if not check_installed():
-        print("CrewAI is not installed. Run:\n  pip install meeting-room[crewai]")
-        return []
-
-    import yaml
-    from crewai import Agent, Task, Crew, Process
-    from meeting_room.scenario_loader import load_scenario
-
-    scenario = load_scenario(scenario_path)
-    roles = config["roles"]
-    participants = scenario.get("participants", list(roles.keys()))
-
-    agents = []
-    for role_id in participants:
-        role = roles[role_id]
-        agent = Agent(
-            role=role["name"],
-            goal=role["system_prompt"].split(".")[0] + ".",
-            backstory=role["system_prompt"].strip(),
-            llm=f"{role['provider']}/{role['model']}",
-            verbose=True,
-        )
-        agents.append(agent)
-
-    discuss_task = Task(
-        description=f"Discuss this problem as a group:\n\n{scenario['problem']}",
-        agent=agents[0],
-        expected_output="Final solution with arguments from each participant",
-    )
-
-    crew = Crew(
-        agents=agents,
-        tasks=[discuss_task],
-        process=Process.sequential,
-        verbose=True,
-    )
-
-    result = crew.kickoff()
-    print(f"\n{'='*60}\nCREWAI RESULT:\n{'='*60}\n")
-    print(result)
-    return str(result)