715 lines
33 KiB
Plaintext
715 lines
33 KiB
Plaintext
# cockpit_chat.dspy - Product-grade LLM conversation with context
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# POST: action=send_message, iteration_id, message_text, model_id, file_paths
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# GET: action=list_messages, iteration_id, task_id
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import aiohttp
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action = (params_kw or {}).get('action', 'list_messages')
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dbname = get_module_dbname('pipeline-sdlc')
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DEFAULT_SYSTEM_PROMPT = """你是一个专业的软件开发 Agent，名为「开发产线驾驶舱」。你的职责是帮助用户完成软件开发生命周期的各个环节：需求分析、设计、编码、测试、部署。
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对话规则：
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1. 简洁专业，用中文回复
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2. 当用户描述需求时，先理解并复述确认，然后给出分析和建议
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3. 如果用户提到了项目/迭代，主动关联上下文
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4. 可以建议启动开发产线来推进工作
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5. 对于代码相关问题，给出具体的代码示例
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6. 记住对话历史，保持上下文连贯
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当前你可以帮助用户完成：
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- 创建和管理项目、迭代
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- 数据表设计、CRUD 设计、API 设计
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- 代码生成、规范检查、自动修复
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- 测试用例生成、功能测试、Bug 管理
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- 环境部署和验证"""
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def _guess_role(title):
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"""Guess agent role from task title keywords."""
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title_lower = (title or '').lower()
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keywords = {
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'design': ['设计', 'design', '架构', '方案', '需求', '原型', 'ui', 'ux'],
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'develop': ['开发', '编码', '实现', '编写', 'develop', 'code', 'build', '重构', '修复'],
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'test': ['测试', 'test', '验证', '检查', 'review', '评审'],
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'deploy': ['部署', '发布', 'deploy', 'release', '上线', '配置'],
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'ops': ['运维', '监控', 'ops', '日志', '备份', '迁移'],
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}
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for role, kws in keywords.items():
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for kw in kws:
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if kw in title_lower:
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return role
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return 'develop' # default
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def _load_skills(skills_dir, role=None):
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"""Scan skills_dir for SKILL.md files. If role given, load common/ + {role}/ only."""
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skills = []
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if not skills_dir:
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return skills
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dirs_to_scan = ['common']
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if role:
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dirs_to_scan.append(role)
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else:
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# No role specified — scan all subdirs
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try:
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dirs_to_scan = [d for d in os.listdir(skills_dir)
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if os.path.isdir(os.path.join(skills_dir, d))]
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except Exception:
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return skills
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for subdir in dirs_to_scan:
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subdir_path = os.path.join(skills_dir, subdir)
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if not os.path.isdir(subdir_path):
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continue
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try:
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for name in os.listdir(subdir_path):
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skill_path = os.path.join(subdir_path, name)
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skill_md = os.path.join(skill_path, 'SKILL.md')
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if os.path.isdir(skill_path) and os.path.isfile(skill_md):
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try:
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with open(skill_md, 'r') as f:
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content = f.read()
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if len(content) > 8000:
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content = content[:8000] + '\n\n... (truncated)'
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skills.append({'name': name, 'role': subdir, 'content': content})
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except Exception:
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pass
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except Exception:
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pass
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return skills
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def _build_skills_prompt(skills):
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"""Build skill context string for injection into system prompt."""
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if not skills:
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return ''
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lines = ['\n\n## 可用的开发技能(Skills)\n']
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lines.append('以下是企业定义的开发规范和最佳实践，请在开发过程中严格遵循：\n')
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for s in skills:
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lines.append(f'### {s["name"]}')
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lines.append(s['content'])
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lines.append('')
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return '\n'.join(lines)
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async def _load_agent_settings(sor, uid):
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"""Load user's agent settings, return defaults if not set."""
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recs = await sor.sqlExe(
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"SELECT default_llm_id, system_prompt, temperature, max_context_messages FROM pipeline_agent_settings WHERE user_id=${uid}$",
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{"uid": uid}
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)
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if recs:
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r = recs[0]
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return {
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'llm_id': getattr(r, 'default_llm_id', None),
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'system_prompt': getattr(r, 'system_prompt', None) or DEFAULT_SYSTEM_PROMPT,
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'temperature': float(getattr(r, 'temperature', 0.7) or 0.7),
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'max_context': int(getattr(r, 'max_context_messages', 30) or 30),
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}
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return {
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'llm_id': None,
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'system_prompt': DEFAULT_SYSTEM_PROMPT,
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'temperature': 0.7,
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'max_context': 30,
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}
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async def _load_context(sor, uid):
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"""Load session context from pipeline_agent_settings."""
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recs = await sor.sqlExe(
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"SELECT current_project_id, current_iteration_id FROM pipeline_agent_settings WHERE user_id=${uid}$",
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{"uid": uid}
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)
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ctx = {'project_id': '', 'iteration_id': '', 'project_name': '', 'iteration_name': '',
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'workspace_dir': '', 'workspace_root': '', 'skills_dir': '', 'skills': [], 'repos': []}
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if recs:
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r = recs[0]
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ctx['project_id'] = getattr(r, 'current_project_id', '') or ''
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ctx['iteration_id'] = getattr(r, 'current_iteration_id', '') or ''
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if ctx['project_id']:
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projs = await sor.sqlExe(
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"SELECT name, workspace_dir, org_id FROM sd_projects WHERE id=${pid}$", {"pid": ctx['project_id']}
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)
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if projs:
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ctx['project_name'] = getattr(projs[0], 'name', '')
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ctx['workspace_dir'] = getattr(projs[0], 'workspace_dir', '') or ''
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org_id = getattr(projs[0], 'org_id', '') or '0'
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# Load org settings
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orgs = await sor.sqlExe(
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"SELECT workspace_root, skills_dir FROM sd_org_settings WHERE org_id=${oid}$", {"oid": org_id}
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)
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if orgs:
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ctx['workspace_root'] = getattr(orgs[0], 'workspace_root', '') or ''
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ctx['skills_dir'] = getattr(orgs[0], 'skills_dir', '') or ''
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# Load enterprise skills
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if ctx['skills_dir']:
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ctx['skills'] = _load_skills(ctx['skills_dir'])
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# Load repos
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repos = await sor.sqlExe(
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"SELECT repo_name, repo_url, default_branch, local_path FROM sd_project_repos WHERE project_id=${pid}$",
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{"pid": ctx['project_id']}
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)
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ctx['repos'] = [{'name': r.repo_name, 'url': r.repo_url,
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'branch': r.default_branch, 'path': r.local_path or ''} for r in (repos or [])]
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if ctx['iteration_id']:
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iters = await sor.sqlExe(
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"SELECT iteration_name FROM sd_iterations WHERE id=${iid}$", {"iid": ctx['iteration_id']}
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)
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if iters:
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ctx['iteration_name'] = getattr(iters[0], 'iteration_name', '')
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return ctx
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async def _save_context(sor, uid, project_id, iteration_id):
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"""Save session context to pipeline_agent_settings."""
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existing = await sor.sqlExe(
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"SELECT id FROM pipeline_agent_settings WHERE user_id=${uid}$", {"uid": uid}
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)
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if existing:
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await sor.sqlExe(
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"UPDATE pipeline_agent_settings SET current_project_id=${pid}$, current_iteration_id=${iid}$ WHERE user_id=${uid}$",
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{"pid": project_id or '', "iid": iteration_id or '', "uid": uid}
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)
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else:
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await sor.C('pipeline_agent_settings', {
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'id': getID(), 'user_id': uid,
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'default_llm_id': '', 'current_project_id': project_id or '',
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'current_iteration_id': iteration_id or '',
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})
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async def _select_model(sor, preferred_llm_id, has_files):
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"""Select best model: prefer user choice, then multimodal if files, else first active text."""
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# If user has preferred model, use it (match by id or name)
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if preferred_llm_id:
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recs = await sor.sqlExe(
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"SELECT id, name, provider, model_id, api_base, api_key, capabilities FROM llm WHERE (id=${lid}$ OR name=${lid}$) AND status='active'",
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{"lid": preferred_llm_id}
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)
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if recs:
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return recs[0]
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# Auto-select based on file presence
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if has_files:
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recs = await sor.sqlExe(
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"SELECT id, name, provider, model_id, api_base, api_key, capabilities FROM llm WHERE status='active' AND capabilities LIKE '%multimodal%' LIMIT 1",
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{}
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)
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if recs:
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return recs[0]
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# Fallback: first active model
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recs = await sor.sqlExe(
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"SELECT id, name, provider, model_id, api_base, api_key, capabilities FROM llm WHERE status='active' LIMIT 1",
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{}
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)
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if recs:
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return recs[0]
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return None
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async def _build_context(sor, iteration_id, task_id, max_msgs, system_prompt):
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"""Build LLM messages array with Hermes-style context."""
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messages = [{"role": "system", "content": system_prompt}]
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# Project/iteration context
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if iteration_id:
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iters = await sor.sqlExe(
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"SELECT i.iteration_name, i.iteration_type, i.status, i.scope, p.name as project_name, p.description, p.tech_stack "
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"FROM sd_iterations i LEFT JOIN sd_projects p ON i.project_id=p.id WHERE i.id=${iid}$",
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{"iid": iteration_id}
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)
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if iters:
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it = iters[0]
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ctx_parts = ["## 当前上下文"]
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ctx_parts.append(f"项目: {getattr(it, 'project_name', '未知')}")
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ctx_parts.append(f"迭代: {getattr(it, 'iteration_name', '未知')}")
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ctx_parts.append(f"类型: {getattr(it, 'iteration_type', '')}")
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ctx_parts.append(f"状态: {getattr(it, 'status', '')}")
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desc = getattr(it, 'description', '')
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if desc:
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ctx_parts.append(f"项目描述: {desc[:500]}")
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stack = getattr(it, 'tech_stack', '')
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if stack:
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ctx_parts.append(f"技术栈: {stack[:300]}")
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scope = getattr(it, 'scope', '')
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if scope:
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ctx_parts.append(f"迭代范围: {scope[:500]}")
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messages.append({"role": "system", "content": "\n".join(ctx_parts)})
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# Task context
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if task_id:
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tasks = await sor.sqlExe(
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"SELECT id, status, pipeline_id FROM pipeline_tasks WHERE id=${tid}$",
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{"tid": task_id}
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)
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if tasks:
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t = tasks[0]
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messages.append({"role": "system", "content": f"关联 Pipeline 任务: {t.id}, 状态: {getattr(t, 'status', 'unknown')}"})
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# Conversation history
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where = []
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params = {}
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if task_id:
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where.append("task_id=${tid}$")
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params["tid"] = task_id
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if iteration_id:
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where.append("iteration_id=${iid}$")
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params["iid"] = iteration_id
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if where:
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sql = f"SELECT role, content FROM pipeline_conversations WHERE {' OR '.join(where)} ORDER BY created_at DESC LIMIT {max_msgs}"
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history = await sor.sqlExe(sql, params)
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# Reverse to chronological order
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for h in reversed(history):
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role = getattr(h, 'role', 'user')
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content = getattr(h, 'content', '')
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if role in ('user', 'agent'):
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messages.append({"role": "user" if role == "user" else "assistant", "content": content})
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return messages
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async def _call_llm(model_info, messages, temperature):
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"""Call LLM API directly using model config from llm table."""
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api_base = model_info.api_base.rstrip('/')
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api_key = model_info.api_key or ''
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model_id = model_info.model_id
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debug(f'_call_llm: base={api_base} model={model_id} key_len={len(api_key)} key_prefix={api_key[:10]}')
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headers = {
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"Authorization": f"Bearer {api_key}",
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"Content-Type": "application/json",
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}
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payload = {
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"model": model_id,
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"messages": messages,
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"temperature": temperature,
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}
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timeout = aiohttp.ClientTimeout(total=120)
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async with aiohttp.ClientSession(timeout=timeout) as session:
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url = f"{api_base}/chat/completions"
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debug(f'_call_llm: POST {url}')
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async with session.post(url, headers=headers, json=payload) as resp:
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if resp.status != 200:
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text = await resp.text()
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debug(f'_call_llm: FAIL status={resp.status} body={text[:200]}')
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raise ValueError(f"LLM API error {resp.status}: {text[:300]}")
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data = await resp.json()
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content = data["choices"][0]["message"]["content"]
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debug(f'_call_llm: OK reply_len={len(content)}')
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if len(content) > 8000:
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content = content[:8000] + "\n\n...(内容过长已截断)"
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return content
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INTENT_PROMPT = """你是一个开发产线意图分类器。分析用户输入，返回 JSON。
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意图类型：
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- new_project: 创建新项目
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- select_project: 切换到已有项目
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- new_iteration: 在当前项目下创建新迭代
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- new_task: 提交开发任务（需关联项目/迭代）
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- add_bug: 报告Bug
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- start_agent: 启动Agent自动执行任务
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- agent_status: 查看Agent状态和交付件
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- query: 查询当前状态
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- chat: 开发相关的一般对话
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- out_of_scope: 完全无关软件开发
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当前上下文：项目={ctx}，迭代={iter}
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返回纯JSON（不要markdown包裹）：
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{"intent":"...","confidence":0.8,"project_name":"...","iteration_name":"...","title":"...","description":"...","missing_info":"..."}"""
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async def _classify_intent(model_info, message, ctx, history_msgs):
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"""Classify user intent using LLM."""
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ctx_str = ctx.get('project_name', '') or '无'
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iter_str = ctx.get('iteration_name', '') or '无'
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prompt = INTENT_PROMPT.replace('{ctx}', ctx_str).replace('{iter}', iter_str)
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msgs = [{"role": "system", "content": prompt}]
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for h in history_msgs[-4:]:
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msgs.append(h)
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msgs.append({"role": "user", "content": message})
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raw = await _call_llm(model_info, msgs, 0.2)
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raw = raw.strip()
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if raw.startswith('```'):
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raw = raw.split('\n', 1)[1].rsplit('```', 1)[0]
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try:
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return json.loads(raw)
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except Exception:
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return {"intent": "chat", "confidence": 0.5, "missing_info": ""}
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async def _find_project(sor, name, org_id):
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"""Find project by name."""
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if not name: return None
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recs = await sor.sqlExe(
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"SELECT id, name FROM sd_projects WHERE name=${name}$ AND org_id=${oid}$",
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{"name": name, "oid": org_id})
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return recs[0] if recs else None
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SCOPE_GUIDE = """我可以帮你：
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📁 项目管理 — "创建电商平台项目" / "切换到XXX项目"
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🔄 迭代管理 — "创建Sprint3" / "查看迭代进度"
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📝 提交任务 — "设计用户表结构" / "实现登录API"
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🐛 Bug管理 — "登录页报500" / "我的Bug列表"
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📊 查询 — "当前项目进度" / "有哪些迭代"
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请描述你的需求。"""
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# ==================== ACTION HANDLERS ====================
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if action == 'send_message':
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iteration_id = (params_kw or {}).get('iteration_id', '')
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message_text = (params_kw or {}).get('message_text', '').strip()
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user_model_id = (params_kw or {}).get('model_id', '')
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file_paths_raw = (params_kw or {}).get('file_paths', '[]')
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debug(f'send_message: model_id={user_model_id} iteration_id={iteration_id} msg_len={len(message_text)}')
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if not message_text:
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return json.dumps({"error": "message_text is required"}, ensure_ascii=False)
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uid = await get_user()
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org_id = await get_userorgid() or '0'
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msg_id = '' # always defined, even on error
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agent_reply = ''
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async with DBPools().sqlorContext(dbname) as sor:
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# 1. Load context and model
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ctx = await _load_context(sor, uid)
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settings = await _load_agent_settings(sor, uid)
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selected_llm_id = user_model_id or settings['llm_id']
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model_info = await _select_model(sor, selected_llm_id, False)
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if not model_info:
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return json.dumps({"error": "No active LLM model configured"}, ensure_ascii=False)
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# 2. Classify intent
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history = await sor.sqlExe(
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"SELECT role, content FROM pipeline_conversations WHERE iteration_id=${iid}$ OR iteration_id='' ORDER BY created_at DESC LIMIT 4",
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{"iid": iteration_id or ctx.get('iteration_id', '')}
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)
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history_msgs = []
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for h in reversed(history):
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role = 'user' if getattr(h, 'role', '') == 'user' else 'assistant'
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history_msgs.append({"role": role, "content": getattr(h, 'content', '')})
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intent = await _classify_intent(model_info, message_text, ctx, history_msgs)
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debug(f'intent: {intent}')
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# 3. Route by intent
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intent_type = intent.get('intent', 'chat')
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confidence = intent.get('confidence', 0.5)
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if intent_type == 'out_of_scope' or (intent_type == 'chat' and confidence < 0.6 and not ctx['project_id']):
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agent_reply = SCOPE_GUIDE
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elif intent.get('missing_info') and confidence < 0.7:
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agent_reply = f"让我确认一下：{intent.get('missing_info', '请提供更多信息')}"
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elif intent_type == 'new_project':
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pname = intent.get('project_name', '') or message_text[:50]
|
||
proj = await _find_project(sor, pname, org_id)
|
||
if proj:
|
||
agent_reply = f"项目「{pname}」已存在。已切换到该项目。"
|
||
await _save_context(sor, uid, proj.id, '')
|
||
else:
|
||
pid = getID()
|
||
ws_dir = f"/d/pipeline/workspaces/{org_id}/{pname}"
|
||
await sor.C('sd_projects', {
|
||
'id': pid, 'name': pname, 'description': intent.get('description', ''),
|
||
'project_type': 'software', 'org_id': org_id, 'created_by': uid,
|
||
'status': 'active', 'workspace_dir': ws_dir
|
||
})
|
||
# Auto-create default iteration
|
||
iid = getID()
|
||
await sor.C('sd_iterations', {
|
||
'id': iid, 'project_id': pid, 'iteration_name': '默认迭代',
|
||
'iteration_type': 'sprint', 'org_id': org_id, 'created_by': uid, 'status': 'active'
|
||
})
|
||
await _save_context(sor, uid, pid, iid)
|
||
agent_reply = f"✅ 项目「{pname}」已创建，默认迭代已就绪。现在可以提交任务了。"
|
||
elif intent_type == 'select_project':
|
||
pname = intent.get('project_name', '')
|
||
proj = await _find_project(sor, pname, org_id)
|
||
if proj:
|
||
await _save_context(sor, uid, proj.id, ctx['iteration_id'])
|
||
agent_reply = f"已切换到项目「{pname}」。"
|
||
else:
|
||
agent_reply = f"未找到项目「{pname}」。请先创建项目后再切换。"
|
||
elif intent_type == 'new_task':
|
||
pid = ctx['project_id']
|
||
iid = intent.get('iteration_name', '') or ctx['iteration_id']
|
||
if not pid:
|
||
agent_reply = "请先指定项目。「创建XXX项目」或「切换到XXX项目」"
|
||
elif not iid:
|
||
agent_reply = "请指定迭代。「创建Sprint1」或「切换到XXX迭代」"
|
||
else:
|
||
title = intent.get('title', '') or message_text[:100]
|
||
role = _guess_role(title)
|
||
# Load role-specific skills
|
||
task_skills = _load_skills(ctx.get('skills_dir', ''), role)
|
||
skills_text = _build_skills_prompt(task_skills)
|
||
task_params = {
|
||
'description': intent.get('description', ''),
|
||
'input_text': message_text,
|
||
'role': role,
|
||
'skills': skills_text,
|
||
}
|
||
try:
|
||
result = await pipeline_submit(org_id, 'sdlc_general', uid, title, task_params)
|
||
rd = json.loads(result)
|
||
if rd.get('success'):
|
||
task_id = rd.get('task_id', '')
|
||
await _save_context(sor, uid, pid, iid)
|
||
# Build repo + workspace context for execution
|
||
ws = ctx.get('workspace_dir', '')
|
||
ws_root = ctx.get('workspace_root', '')
|
||
repos = ctx.get('repos', [])
|
||
repo_lines = [f"工作空间根路径：{ws_root}" if ws_root else "工作空间根路径：未配置"]
|
||
repo_lines.append(f"项目本地路径：{ws}" if ws else "项目本地路径：未配置")
|
||
if repos:
|
||
repo_lines.append("关联代码仓库：")
|
||
for rp in repos:
|
||
repo_lines.append(f" - {rp['name']}: {rp['url']} (分支:{rp['branch']}, 本地:{rp['path']})")
|
||
# Execute immediately with skills
|
||
sp = settings['system_prompt']
|
||
if skills_text:
|
||
sp = sp + '\n\n---\n当前角色：' + role + skills_text
|
||
task_msgs = [{"role": "system", "content": sp}]
|
||
task_msgs.append({"role": "user", "content": f"请完成：{title}\n\n" + '\n'.join(repo_lines)})
|
||
result_text = await _call_llm(model_info, task_msgs, settings['temperature'])
|
||
did = getID()
|
||
role_dir = f"{ws}/deliverables/{role}" if ws else f"deliverables/{role}"
|
||
primary_repo = repos[0]['name'] if repos else ''
|
||
await sor.C('pipeline_deliverables', {
|
||
'id': did, 'project_id': pid, 'task_id': task_id,
|
||
'deliverable_type': role, 'title': title, 'content': result_text,
|
||
'repo_name': primary_repo, 'target_path': '',
|
||
'file_path': f"{role_dir}/{task_id}.md",
|
||
'quality_score': 80, 'review_status': 'pending', 'created_by': 'agent'
|
||
})
|
||
await sor.sqlExe("UPDATE pipeline_tasks SET state='completed' WHERE id=${tid}$", {"tid": task_id})
|
||
preview = result_text[:200].replace('\n', ' ')
|
||
agent_reply = f"✅ 任务「{title}」已完成（角色：{role}）\n 交付件：{did}\n {preview}..."
|
||
else:
|
||
agent_reply = f"任务提交失败：{rd.get('message', '未知错误')}"
|
||
except Exception as e:
|
||
agent_reply = f"任务执行失败：{str(e)[:200]}"
|
||
elif intent_type == 'add_bug':
|
||
pid = ctx['project_id']
|
||
iid = ctx['iteration_id']
|
||
if not pid:
|
||
agent_reply = "请先指定项目后再报告Bug。"
|
||
else:
|
||
bid = getID()
|
||
await sor.C('sd_bugs', {
|
||
'id': bid, 'iteration_id': iid or '', 'title': intent.get('title', '') or message_text[:100],
|
||
'description': intent.get('description', ''), 'severity': 'major', 'priority': 'P1',
|
||
'status': 'open', 'reporter_type': 'human', 'reporter_id': uid, 'created_at': curDateString()
|
||
})
|
||
agent_reply = f"🐛 Bug已记录（{bid}）：{message_text[:100]}"
|
||
elif intent_type == 'query':
|
||
ctx_info = []
|
||
if ctx['project_name']:
|
||
ctx_info.append(f"当前项目：{ctx['project_name']}")
|
||
if ctx['iteration_name']:
|
||
ctx_info.append(f"当前迭代：{ctx['iteration_name']}")
|
||
if ctx_info:
|
||
agent_reply = '\n'.join(ctx_info) + '\n\n请描述具体想查询什么（如：任务列表、Bug列表等）'
|
||
else:
|
||
agent_reply = "当前未选择项目。请先「创建XXX项目」或「切换到XXX项目」。"
|
||
elif intent_type == 'start_agent':
|
||
pid = ctx['project_id']
|
||
if not pid:
|
||
agent_reply = "请先指定项目。「创建XXX项目」或「切换到XXX项目」"
|
||
else:
|
||
tasks = await sor.sqlExe(
|
||
"SELECT id, title, state FROM pipeline_tasks WHERE tenant_id=${oid}$ AND state='submitted' LIMIT 5",
|
||
{"oid": org_id})
|
||
if not tasks:
|
||
agent_reply = f"项目「{ctx['project_name']}」暂无待执行任务。\n\n请先提交开发任务，例如：设计用户表结构"
|
||
else:
|
||
results = []
|
||
ws = ctx.get('workspace_dir', '')
|
||
ws_root = ctx.get('workspace_root', '')
|
||
repos = ctx.get('repos', [])
|
||
|
||
# Build repo info for prompt
|
||
repo_lines = [f"工作空间根路径：{ws_root}" if ws_root else "工作空间根路径：未配置"]
|
||
repo_lines.append(f"项目本地路径：{ws}" if ws else "项目本地路径：未配置")
|
||
skills_dir = ctx.get('skills_dir', '')
|
||
if skills_dir:
|
||
repo_lines.append(f"企业Skills目录：{skills_dir}")
|
||
if repos:
|
||
repo_lines.append("关联代码仓库：")
|
||
for rp in repos:
|
||
repo_lines.append(f" - {rp['name']}: {rp['url']} (分支:{rp['branch']}, 本地:{rp['path']})")
|
||
results.append('\\n'.join(repo_lines))
|
||
|
||
for t in tasks:
|
||
try:
|
||
# Guess role and load role-specific skills
|
||
role = _guess_role(getattr(t, 'title', ''))
|
||
task_skills = _load_skills(ctx.get('skills_dir', ''), role)
|
||
sp = settings['system_prompt']
|
||
skills_prompt = _build_skills_prompt(task_skills)
|
||
if skills_prompt:
|
||
sp = sp + skills_prompt
|
||
task_msgs = [{"role": "system", "content": sp}]
|
||
prompt_parts = [f"请完成：{t.title}"]
|
||
prompt_parts.append('\\n'.join(repo_lines))
|
||
prompt_parts.append("请在关联仓库中直接修改代码文件，完成后提供变更摘要。")
|
||
task_msgs.append({"role": "user", "content": '\\n'.join(prompt_parts)})
|
||
result = await _call_llm(model_info, task_msgs, settings['temperature'])
|
||
did = getID()
|
||
role_dir = f\"{ws}/deliverables/agent\" if ws else \"deliverables/agent\"
|
||
# Detect primary repo for deliverable
|
||
primary_repo = repos[0]['name'] if repos else ''
|
||
await sor.C('pipeline_deliverables', {
|
||
'id': did, 'project_id': pid, 'task_id': t.id,
|
||
'deliverable_type': 'code', 'title': t.title, 'content': result,
|
||
'repo_name': primary_repo, 'target_path': '',
|
||
'file_path': f\"{role_dir}/{t.id}.md\",
|
||
'quality_score': 80, 'review_status': 'pending', 'created_by': 'agent'
|
||
})
|
||
await sor.sqlExe("UPDATE pipeline_tasks SET state='completed' WHERE id=${tid}$", {"tid": t.id})
|
||
preview = result[:300].replace('\n', ' ')
|
||
results.append(f"✅ {t.title}\n 交付件 {did}\n {preview}...")
|
||
except Exception as e2:
|
||
results.append(f"❌ {t.title}：{str(e2)[:80]}")
|
||
agent_reply = '\n'.join(results) if results else "无需执行的任务"
|
||
elif intent_type == 'agent_status':
|
||
pid = ctx['project_id']
|
||
if not pid:
|
||
agent_reply = "当前未选择项目。"
|
||
else:
|
||
async with DBPools().sqlorContext(dbname) as sor2:
|
||
# Agent status
|
||
arecs = await sor2.sqlExe(
|
||
"SELECT role_name, status, model_name FROM pipeline_project_agents WHERE project_id=${pid}$",
|
||
{"pid": pid})
|
||
# Recent deliverables
|
||
drecs = await sor2.sqlExe(
|
||
"SELECT title, deliverable_type, quality_score, review_status, created_at "
|
||
"FROM pipeline_deliverables WHERE project_id=${pid}$ ORDER BY created_at DESC LIMIT 3",
|
||
{"pid": pid})
|
||
lines = [f"📁 项目：{ctx['project_name']}"]
|
||
for a in arecs:
|
||
lines.append(f"🤖 {a.role_name}：{a.status}")
|
||
if drecs:
|
||
lines.append("📦 最近交付：")
|
||
for d in drecs:
|
||
lines.append(f" · {d.title} [{d.review_status}] {d.quality_score}分")
|
||
agent_reply = '\n'.join(lines) if len(lines) > 1 else "暂无Agent活动"
|
||
else:
|
||
# chat: general conversation
|
||
messages = await _build_context(sor, iteration_id or ctx['iteration_id'], '',
|
||
settings['max_context'], settings['system_prompt'])
|
||
messages.append({"role": "user", "content": message_text})
|
||
try:
|
||
agent_reply = await _call_llm(model_info, messages, settings['temperature'])
|
||
except Exception as e:
|
||
agent_reply = f"抱歉，模型调用失败: {str(e)[:200]}"
|
||
|
||
# 4. Save conversation
|
||
msg_id = getID()
|
||
await sor.C('pipeline_conversations', {
|
||
'id': msg_id, 'iteration_id': iteration_id or ctx.get('iteration_id', ''),
|
||
'task_id': '', 'step_name': '', 'role': 'user', 'content': message_text,
|
||
'attachments': file_paths_raw, 'msg_type': 'text', 'org_id': org_id, 'created_by': uid
|
||
})
|
||
agent_msg_id = getID()
|
||
await sor.C('pipeline_conversations', {
|
||
'id': agent_msg_id, 'iteration_id': iteration_id or ctx.get('iteration_id', ''),
|
||
'task_id': '', 'step_name': '', 'role': 'agent', 'content': agent_reply,
|
||
'attachments': '[]', 'msg_type': 'text', 'org_id': org_id, 'created_by': 'system'
|
||
})
|
||
|
||
return json.dumps({
|
||
"success": True, "message_id": msg_id, "agent_reply": agent_reply,
|
||
"model_used": model_info.name, "intent": intent_type,
|
||
"context": {"project_name": ctx.get('project_name', ''), "iteration_name": ctx.get('iteration_name', '')}
|
||
}, ensure_ascii=False)
|
||
|
||
|
||
else:
|
||
# list_messages - return conversation as Bricks widget JSON
|
||
iteration_id = (params_kw or {}).get('iteration_id', '')
|
||
task_id = (params_kw or {}).get('task_id', '')
|
||
|
||
msgs = []
|
||
if iteration_id or task_id:
|
||
async with DBPools().sqlorContext(dbname) as sor:
|
||
where = []
|
||
params = {}
|
||
if task_id:
|
||
where.append("task_id=${tid}$")
|
||
params["tid"] = task_id
|
||
if iteration_id:
|
||
where.append("iteration_id=${iid}$")
|
||
params["iid"] = iteration_id
|
||
|
||
sql = f"SELECT role, content, msg_type, created_at FROM pipeline_conversations WHERE {' OR '.join(where)} ORDER BY created_at ASC LIMIT 50"
|
||
msgs = await sor.sqlExe(sql, params)
|
||
|
||
msg_widgets = []
|
||
for m in msgs:
|
||
role = m.role if hasattr(m, 'role') else ''
|
||
content = m.content if hasattr(m, 'content') else ''
|
||
|
||
if role == 'agent':
|
||
bg = '#e8f0fe'
|
||
align = 'flex-start'
|
||
label = 'Agent'
|
||
label_color = '#3b82f6'
|
||
elif role == 'user':
|
||
bg = '#dbeafe'
|
||
align = 'flex-end'
|
||
label = '\u4f60'
|
||
label_color = '#2563eb'
|
||
else:
|
||
bg = '#f1f5f9'
|
||
align = 'center'
|
||
label = '\u7cfb\u7edf'
|
||
label_color = '#94a3b8'
|
||
|
||
msg_widgets.append({
|
||
"widgettype": "VBox",
|
||
"options": {
|
||
"width": "85%",
|
||
"alignSelf": align,
|
||
"bgcolor": bg,
|
||
"borderRadius": "12px",
|
||
"padding": "12px 16px",
|
||
"marginBottom": "10px",
|
||
"gap": "4px"
|
||
},
|
||
"subwidgets": [
|
||
{"widgettype": "Text", "options": {
|
||
"text": label, "cfontsize": 0.75,
|
||
"color": label_color, "fontWeight": "bold"
|
||
}},
|
||
{"widgettype": "Text", "options": {
|
||
"text": content, "cfontsize": 0.95,
|
||
"color": "#1e293b", "whiteSpace": "pre-wrap"
|
||
}}
|
||
]
|
||
})
|
||
|
||
if not msg_widgets:
|
||
msg_widgets.append({
|
||
"widgettype": "Text",
|
||
"options": {
|
||
"text": "\u6682\u65e0\u5bf9\u8bdd\u8bb0\u5f55\u3002\u9009\u62e9\u4e00\u4e2a\u8fed\u4ee3\u540e\uff0c\u5728\u4e0b\u65b9\u8f93\u5165\u6846\u4e2d\u5f00\u59cb\u5bf9\u8bdd\u3002",
|
||
"cfontsize": 0.9, "color": "#94a3b8", "padding": "20px"
|
||
}
|
||
})
|
||
|
||
return {
|
||
"widgettype": "VBox",
|
||
"options": {"width": "100%", "padding": "4px"},
|
||
"subwidgets": msg_widgets
|
||
}
|