From 4c5b3104cfcf0d7e68577864ca101b07d38b7008 Mon Sep 17 00:00:00 2001
From: ymq <ymq@opencomputing.net>
Date: Sat, 8 Aug 2026 15:19:18 +0800
Subject: [PATCH] agent-way: LLM resolves project aliases via project list in
 INTENT_PROMPT

---
 wwwroot/api/cockpit_chat.dspy | 32 ++++++++++++++------------------
 1 file changed, 14 insertions(+), 18 deletions(-)

diff --git a/wwwroot/api/cockpit_chat.dspy b/wwwroot/api/cockpit_chat.dspy
index 96db287..74b53a1 100644
--- a/wwwroot/api/cockpit_chat.dspy
+++ b/wwwroot/api/cockpit_chat.dspy
@@ -412,6 +412,7 @@ INTENT_PROMPT = """你是一个开发产线意图分类器。分析用户输入
 - show_repos: 查看当前项目关联的仓库（如"有哪些仓库""显示仓库"）
 
 当前上下文：项目={ctx}，迭代={iter}
+可选项目列表（select_project时project_name必须从列表中选择）：{projects}
 待客户回答的问题（角色Agent执行任务中提出）：{questions}
 若用户消息是在回答上述问题之一，intent应为answer_question，并把回答内容填入description。
 
@@ -419,11 +420,18 @@ INTENT_PROMPT = """你是一个开发产线意图分类器。分析用户输入
 {"intent":"...","confidence":0.8,"project_name":"...","iteration_name":"...","title":"...","description":"...","source_path":"...","role":"...","missing_info":"...","question_id":"...","repo_url":"...","repo_name":"..."}"""
 
 
-async def _classify_intent(model_info, message, ctx, history_msgs, questions_text='无'):
-    """Classify user intent using LLM."""
+async def _classify_intent(model_info, message, ctx, history_msgs, sor, questions_text='无'):
+    """Classify user intent using LLM. sor is needed to load project list."""
     ctx_str = ctx.get('project_name', '') or '无'
     iter_str = ctx.get('iteration_name', '') or '无'
-    prompt = INTENT_PROMPT.replace('{ctx}', ctx_str).replace('{iter}', iter_str).replace('{questions}', questions_text)
+    # 加载项目列表供LLM匹配
+    proj_recs = await sor.sqlExe("SELECT name FROM sd_projects ORDER BY created_at DESC LIMIT 20", {})
+    proj_names = ', '.join([getattr(r, 'name', '') for r in (proj_recs or [])]) or '无'
+    prompt = (INTENT_PROMPT
+              .replace('{ctx}', ctx_str)
+              .replace('{iter}', iter_str)
+              .replace('{projects}', proj_names)
+              .replace('{questions}', questions_text))
     msgs = [{"role": "system", "content": prompt}]
     for h in history_msgs[-4:]:
         msgs.append(h)
@@ -439,24 +447,12 @@ async def _classify_intent(model_info, message, ctx, history_msgs, questions_tex
 
 
 async def _find_project(sor, name, org_id):
-    """Find project by name (supports partial match)."""
+    """Find project by exact name (LLM should resolve aliases)."""
     if not name: return None
-    # Try exact match first
     recs = await sor.sqlExe(
         "SELECT id, name FROM sd_projects WHERE name=${name}$ AND org_id=${oid}$",
         {"name": name, "oid": org_id})
-    if recs:
-        return recs[0]
-    # Fuzzy: load all projects for this org and match in Python
-    all_recs = await sor.sqlExe(
-        "SELECT id, name FROM sd_projects WHERE org_id=${oid}$",
-        {"oid": org_id})
-    kw = name.lower()
-    for rec in (all_recs or []):
-        rname = (getattr(rec, 'name', '') or '').lower()
-        if kw in rname:
-            return rec
-    return None
+    return recs[0] if recs else None
 
 
 # ==================== 问题路由 ====================
@@ -656,7 +652,7 @@ if action == 'send_message':
                     qlines.append(f"- [id={getattr(fq, 'id', '')}] [{getattr(fq, 'from_role', '')}] {getattr(fq, 'question', '')}")
                 questions_text = '\n'.join(qlines)
 
-        intent = await _classify_intent(model_info, message_text, ctx, history_msgs, questions_text)
+        intent = await _classify_intent(model_info, message_text, ctx, history_msgs, sor, questions_text)
         debug(f'intent: {intent}')
 
         # 3. Route by intent