Phase 5: Agent grouping and selection after Step 2
Backend: - Add /api/agent-group/categorize endpoint — AI groups agents by role - Add /api/agent-group/filter endpoint — filter by selected groups - Groups with default_enabled=false (advertiser, brand) are unchecked Frontend: - Add agent groups section in Step2EnvSetup.vue - 'Auto-categorize' button triggers AI grouping - Show groups with checkboxes (enabled groups checked, disabled unchecked) - Auto-remove unchecked agents when proceeding to Step 3 - Show selected count summary
This commit is contained in:
Kunthawat Greethong
@@ -65,10 +65,12 @@ def create_app(config_class=Config):
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# 注册蓝图
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from .api import graph_bp, simulation_bp, report_bp
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from .api.template import template_bp
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from .api.agent_group import agent_group_bp
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app.register_blueprint(graph_bp, url_prefix='/api/graph')
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app.register_blueprint(simulation_bp, url_prefix='/api/simulation')
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app.register_blueprint(report_bp, url_prefix='/api/report')
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app.register_blueprint(template_bp, url_prefix='/api/template')
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app.register_blueprint(agent_group_bp, url_prefix='/api/agent-group')
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# 健康检查
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@app.route('/health')
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173
backend/app/api/agent_group.py
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173
backend/app/api/agent_group.py
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@@ -0,0 +1,173 @@
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"""
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Agent Grouping API
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Groups simulation agents into categories and filters them
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"""
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import json
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import os
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from flask import Blueprint, request, jsonify
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from ..utils.llm_client import LLMClient
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from ..utils.locale import t, get_language_instruction
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from ..utils.logger import get_logger
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logger = get_logger('crowdsight.agent_group')
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agent_group_bp = Blueprint('agent_group', __name__)
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@agent_group_bp.route('/categorize', methods=['POST'])
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def categorize_agents():
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"""
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Categorize agents into groups based on their profiles.
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Request JSON:
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{
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"agents": [
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{
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"agent_id": 0,
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"name": "...",
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"profession": "...",
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"bio": "...",
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"persona": "...",
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"interested_topics": [...]
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}
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],
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"simulation_requirement": "..."
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}
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Response JSON:
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{
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"success": true,
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"groups": [
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{
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"group_id": "target_audience",
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"group_name": "กลุ่มเป้าหมาย",
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"default_enabled": true,
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"agents": [0, 2, 5]
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},
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{
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"group_id": "advertiser",
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"group_name": "ผู้โฆษณา/แบรนด์",
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"default_enabled": false,
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"agents": [1, 3]
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}
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]
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}
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"""
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try:
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data = request.get_json() or {}
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agents = data.get('agents', [])
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simulation_requirement = data.get('simulation_requirement', '')
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if not agents:
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return jsonify({'success': False, 'error': 'No agents provided'}), 400
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# Build agent summary for LLM
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agent_summaries = []
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for i, agent in enumerate(agents):
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summary = f"[{i}] {agent.get('name', 'Unknown')} - {agent.get('profession', 'N/A')} - {agent.get('bio', '')[:100]}"
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agent_summaries.append(summary)
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agents_text = '\n'.join(agent_summaries)
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lang_instruction = get_language_instruction()
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system_prompt = f"""You are an expert at analyzing social simulation agents. Your task is to categorize agents into groups and determine which groups are useful for the simulation.
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{lang_instruction}
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Return JSON format:
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{{
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"groups": [
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{{
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"group_id": "unique_english_id",
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"group_name": "group name in user's language",
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"description": "brief description",
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"default_enabled": true/false,
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"agent_indices": [0, 1, 2]
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}}
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]
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}}
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Guidelines:
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- Group agents by their ROLE in the simulation context
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- Groups that represent the TARGET AUDIENCE, INFLUENCERS, MEDIA, COMPETITORS should be default_enabled=true
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- Groups that represent THE ADVERTISER/BRAND ITSELF, ABSTRACT CONCEPTS, MARKETING METADATA should be default_enabled=false
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- If the simulation is about an ad/campaign, the company that made the ad should be in a disabled group
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- Each agent should be in exactly one group
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- Agent indices must match the input indices"""
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user_prompt = f"""Simulation requirement: {simulation_requirement}
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Agents to categorize:
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{agents_text}
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Categorize these agents into groups. Mark groups as default_enabled=false if they represent the entity that created the content being simulated (e.g., the advertiser in an ad scenario)."""
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llm = LLMClient()
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result = llm.chat_json(
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messages=[
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{"role": "system", "content": system_prompt},
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{"role": "user", "content": user_prompt}
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],
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temperature=0.3
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)
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# Validate and clean up
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groups = result.get('groups', [])
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if not groups:
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# Fallback: put all agents in one enabled group
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groups = [{
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'group_id': 'all',
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'group_name': 'All Agents',
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'description': 'All agents',
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'default_enabled': True,
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'agent_indices': list(range(len(agents)))
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}]
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return jsonify({
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'success': True,
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'groups': groups
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})
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except Exception as e:
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logger.error(f"Agent categorization failed: {e}")
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return jsonify({'success': False, 'error': str(e)}), 500
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@agent_group_bp.route('/filter', methods=['POST'])
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def filter_agents():
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"""
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Filter agents based on selected groups.
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Request JSON:
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{
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"agents": [...], // full agent list
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"selected_groups": [0, 2] // indices of enabled groups
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}
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Response JSON:
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{
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"success": true,
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"selected_agent_ids": [0, 2, 5]
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}
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"""
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try:
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data = request.get_json() or {}
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agents = data.get('agents', [])
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groups = data.get('groups', [])
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selected_group_ids = data.get('selected_group_ids', [])
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# Collect agent indices from selected groups
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selected_indices = set()
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for group in groups:
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if group.get('group_id') in selected_group_ids:
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selected_indices.update(group.get('agent_indices', []))
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return jsonify({
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'success': True,
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'selected_agent_ids': sorted(selected_indices)
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})
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except Exception as e:
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logger.error(f"Agent filtering failed: {e}")
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return jsonify({'success': False, 'error': str(e)}), 500
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