feat: project-scoped conversation history via iteration_id=project_id
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@ -475,17 +475,21 @@ if action == 'send_message':
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env_text = f"【当前项目: {ctx['pname'] or '未选择'}】— 所有操作在当前项目内完成\n工作空间: {ctx['ws'] or '未设置'} | 仓库: {repos_str}"
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system = AGENT_PROMPT.replace('__TOOLS__',TOOLS_TEXT).replace('__ENV__',env_text)
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msgs = [{"role":"system","content":system}]
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for h in (await sor.sqlExe("SELECT role,content FROM pipeline_conversations WHERE created_by=${u}$ ORDER BY created_at ASC LIMIT 20",{"u":uid}) or []):
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# Load history scoped to current project (via iteration_id = project_id)
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sql = "SELECT role,content FROM pipeline_conversations WHERE created_by=${u}$ ORDER BY created_at ASC LIMIT 20"
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params = {"u":uid}
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if ctx['pid']:
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sql = "SELECT role,content FROM pipeline_conversations WHERE created_by=${u}$ AND iteration_id=${p}$ ORDER BY created_at ASC LIMIT 20"
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params = {"u":uid,"p":ctx['pid']}
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for h in (await sor.sqlExe(sql, params) or []):
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c = getattr(h,'content','') or ''
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r = getattr(h,'role','') or ''
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# Skip raw tool_call JSON and contaminated old messages
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# Skip raw tool_call JSON — prevents LLM from mimicking old tool calls
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if c.startswith('{"action":"tool_call"') or c.startswith('{"action": "tool_call"'):
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continue
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if 'tetris' in c.lower() or '俄罗斯方块' in c:
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continue
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msgs.append({"role":'user' if r=='user' else 'assistant',"content":c})
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msgs.append({"role":"user","content":message_text})
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await sor.C('pipeline_conversations',{'id':getID(),'role':'user','content':message_text,'msg_type':'text','org_id':org_id,'created_by':uid})
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await sor.C('pipeline_conversations',{'id':getID(),'role':'user','content':message_text,'msg_type':'text','org_id':org_id,'created_by':uid,'iteration_id':ctx['pid'] or ''})
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agent_reply = ''
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for turn in range(10):
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@ -521,7 +525,7 @@ if action == 'send_message':
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d = json.dumps(_w_text(agent_reply), ensure_ascii=False)+'\n'
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debug(f"YIELD final: {d[:60]}")
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yield d
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await sor.C('pipeline_conversations',{'id':getID(),'role':'agent','content':agent_reply,'msg_type':'text','org_id':org_id,'created_by':'system'})
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await sor.C('pipeline_conversations',{'id':getID(),'role':'agent','content':agent_reply,'msg_type':'text','org_id':org_id,'created_by':'system','iteration_id':ctx['pid'] or ''})
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return await stream_response(request, agent_stream, 'text/plain; charset=utf-8')
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